consumer behavior changes in critical times research paper

Click through the PLOS taxonomy to find articles in your field.

For more information about PLOS Subject Areas, click here .

Loading metrics

Open Access

Peer-reviewed

Research Article

Psychological factors and consumer behavior during the COVID-19 pandemic

Contributed equally to this work with: Adolfo Di Crosta, Irene Ceccato

Roles Data curation, Formal analysis, Investigation, Methodology, Writing – original draft, Writing – review & editing

Affiliation Department of Neuroscience, Imaging and Clinical Sciences, G. d’Annunzio University of Chieti-Pescara, Chieti, Italy

Roles Conceptualization, Formal analysis, Methodology, Writing – original draft, Writing – review & editing

Roles Conceptualization, Formal analysis, Methodology

Affiliation Department of Psychological, Health and Territorial Sciences, G. d’Annunzio University of Chieti-Pescara, Chieti, Italy

Roles Investigation, Writing – review & editing

Roles Writing – original draft, Writing – review & editing

Affiliations Department of Neuroscience, Imaging and Clinical Sciences, G. d’Annunzio University of Chieti-Pescara, Chieti, Italy, Center for Advanced Studies and Technology (CAST), G. d’Annunzio University of Chieti-Pescara, Chieti, Italy

Affiliation Department of Business Studies, Grenon School of Business, Assumption University, Worcester, MA, United States of America

Roles Conceptualization, Writing – review & editing

Roles Conceptualization, Methodology, Writing – review & editing

* E-mail: [email protected]

Roles Conceptualization, Writing – original draft, Writing – review & editing

• Adolfo Di Crosta, 
• Irene Ceccato, 
• Daniela Marchetti, 
• Pasquale La Malva, 
• Roberta Maiella, 
• Loreta Cannito, 
• Mario Cipi, 
• Nicola Mammarella, 
• Riccardo Palumbo, 

• Published: August 16, 2021
• https://doi.org/10.1371/journal.pone.0256095
• Reader Comments

The COVID-19 pandemic is far more than a health crisis: it has unpredictably changed our whole way of life. As suggested by the analysis of economic data on sales, this dramatic scenario has also heavily impacted individuals’ spending levels. To better understand these changes, the present study focused on consumer behavior and its psychological antecedents. Previous studies found that crises differently affect people’s willingness to buy necessities products (i.e., utilitarian shopping) and non-necessities products (i.e., hedonic shopping). Therefore, in examining whether changes in spending levels were associated with changes in consumer behavior, we adopted a fine-grained approach disentangling between necessities and non-necessities. We administered an online survey to 3833 participants (age range 18–64) during the first peak period of the contagion in Italy. Consumer behavior toward necessities was predicted by anxiety and COVID-related fear, whereas consumer behavior toward non-necessities was predicted by depression. Furthermore, consumer behavior toward necessities and non-necessities was predicted by personality traits, perceived economic stability, and self-justifications for purchasing. The present study extended our understanding of consumer behavior changes during the COVID-19 pandemic. Results could be helpful to develop marketing strategies that consider psychological factors to meet actual consumers’ needs and feelings.

Citation: Di Crosta A, Ceccato I, Marchetti D, La Malva P, Maiella R, Cannito L, et al. (2021) Psychological factors and consumer behavior during the COVID-19 pandemic. PLoS ONE 16(8): e0256095. https://doi.org/10.1371/journal.pone.0256095

Editor: Marcel Pikhart, University of Hradec Kralove: Univerzita Hradec Kralove, CZECH REPUBLIC

Received: March 8, 2021; Accepted: July 31, 2021; Published: August 16, 2021

Copyright: © 2021 Di Crosta et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All data are available from the figshare database (accession number(s) DOI: 10.6084/m9.figshare.14865663.v2 , URL: https://figshare.com/articles/dataset/RawData_PO_sav/14865663 ).

Funding: The authors received no specific funding for this work.

Competing interests: The authors have declared that no competing interests exist.

Introduction

Coronavirus disease 2019 (COVID-19) refers to an infection (SARS-CoV-2) of the lower respiratory tract [ 1 , 2 ], which was first detected in Wuhan (China) in late December 2019. Since then, the number of contagions by COVID-19 has been increasing globally each day [ 3 ]. In March 2020, the World Health Organization (WHO) declared the COVID-19 outbreak a global pandemic [ 4 ]. Subsequently, several national governments implemented long-term full or partial lockdown measures to reduce the spread of the virus. Although these strict measures have proven to be quite effective in containing the further spread of the virus, they have severely impacted the global economic system and caused an unprecedented shock on economies and labor markets [ 5 ]. As a matter of fact, the COVID-19 pandemic can be defined as far more than just a health crisis since it has heavily affected societies and economies. COVID-19 outbreak has unpredictably changed how we work, communicate, and shop, more than any other disruption in this decade [ 6 ]. As reflected by the analysis of economic data on sales, this dramatic situation has greatly influenced consumer attitudes and behaviors. According to a study conducted by the Nielsen Company, the spread of the COVID-19 pandemic led to a globally manifested change in spending levels related to consumer behavior [ 7 ]. Specifically, a growing tendency in the sales of necessities has been observed: consumer priorities have become centered on the most basic needs, including food, hygiene, and cleaning products. In Italy, consumer shopping preferences have changed throughout the pandemic. Initially, when Italy was the first country in Europe to experience the spreading of COVID-19 (between March and April 2020). Consumer behavior tended to compulsively focus on purchasing essential goods, especially connected with preventing the virus, such as protective devices and sanitizing gel [ 8 ]. The pandemic changed the consumption patterns, for instance reducing sales for some product categories (e.g., clothes), and improving sales for other categories (e.g., entertainment products) [ 9 ]. Also, research indicated that job insecurity and life uncertainty experienced during the pandemic negatively impacted on consumer behavior of Italian workers [ 10 ].

It comes as no surprise that in such a situation of emergency, the need for buying necessities takes precedence [ 11 ]. However, the investigation of antecedent psychological factors, including attitudes, feelings, and behaviors underlying changes in consumer behavior during the COVID-19 pandemic, have received less attention. Nevertheless, understanding the psychological factors which drive consumer behavior and products choices can represent a crucial element for two main reasons. First, such investigation can extend our understanding of the underpinnings of the changes in consumer behavior in the unprecedented context of COVID-19. Second, obtained results could be helpful in the development of new marketing strategies that consider psychological factors to meet actual consumers’ needs and feelings [ 12 ]. On the one side, companies could benefit from this knowledge to increase sales during the COVID-19 pandemic [ 13 ]. Moreover, understanding these needs and feelings could be fundamental to improve the market’s preparedness to face future pandemics and emergencies [ 14 , 15 ]. On the other hand, consumers could take advantage of this new market’s preparedness to respond to their actual needs and feelings. As a result, in case of future emergency, factors such as anxiety and a perceived shortage of essential goods could be reduced [ 16 ], whereas well-being and the positive sense of self of the consumers could be supported [ 17 ]. Furthermore, the novelty of the present study lies in two main aspects. First, based on previous studies highlighting that crises differently affect people’s willingness to buy necessities and non-necessities products [ 11 , 18 ], we adopted a fine-grained approach and disentangled between necessities and non-necessities. Second, considering the unprecedented context of the COVID-19 pandemic, we adopted an integrative approach to investigate the role of different psychological factors such as fear, anxiety, stress, depression, self-justifications, personality traits, and perceived economic stability in influencing consumer behavior. Noteworthy, all these factors have been implicated in consumer behavior in previous research, but, to our knowledge, no study has considered all of them at once. Therefore, considering both the lack of studies that have focused on these factors at once and the unique opportunity to study them in the context of such an unprecedented global pandemic, we adopted an integrative approach to get one of the first overviews of the role of the several psychological factors influencing consumer behavior.

Previous studies in consumer psychology and behavioral economics have highlighted that several psychological factors impact consumer behavior differently [ 18 – 20 ]. Consumer behavior refers to the study of individuals or groups who are in the process of searching to purchase, use, evaluate, and dispose of products and services to satisfy their needs [ 12 ]. Importantly, it also includes studying the consumer’s emotional, mental, and behavioral responses that precede or follow these processes [ 21 ]. Changes in consumer behavior can occur for different reasons, including personal, economic, psychological, contextual, and social factors. However, in dramatic contexts such as a disease outbreak or a natural disaster, some factors, more than others, have a more significant impact on consumer behavior. Indeed, situations that potentially disrupt social lives, or threaten individuals’ health, have been proven to lead to strong behavioral changes [ 22 ]. An example is panic buying, a phenomenon occurring when fear and panic influence behavior, leading people to buy more things than usual [ 23 ]. Specifically, panic buying has been defined as a herd behavior that occurs when consumers buy a considerable amount of products in anticipation of, during, or after a disaster [ 24 ]. A recent review on the psychological causes of panic buying highlighted that similar changes in consumer behavior occur when purchase decisions are impaired by negative emotions such as fear and anxiety [ 25 ]. Noteworthy, in the context of the COVID-19 pandemic, Lins and Aquino [ 23 ] showed that panic buying was positively correlated with impulse buying, which has been defined as a complex buying behavior in which the rapidity of the decision process precludes thoughtful and deliberate consideration of alternative information and choice [ 25 ]. The analysis of the different psychological factors involved in consumer behavior and changes in purchase decisions still represents an area that is scarcely explored. Arguably, during an uncertain threatening situation, such as a health crisis or a pandemic, the primitive part of our brain usually becomes more prominent, pushing individuals to engage in behaviors that are (perceived as) necessary for survival [ 26 – 29 ]. Importantly, these primitive instinctual behaviors can override the rational decision-making process, having an immense impact on usual consumer behavior. Therefore, the basic primitive response of humans represents the core factor responsible for changes in consumer behavior during a health crisis [ 16 ]. Specifically, fear and anxiety originated from perceived feelings of insecurity and instability, are the factors driving these behavioral changes [ 30 ]. In line with the terror management theory [ 31 ], previous studies have shown that external events, which threaten the safety of individuals, motivate compensatory response processes to alleviate fear and anxiety [ 32 , 33 ]. These response processes can prompt individuals to make purchases to gain a sense of security, comfort, and momentarily escape, which can also serve as a compensatory mechanism to alleviate stress. However, as such buying motivation represents an attempt to regulate the individuals’ negative emotions, the actual need for the purchased products is often irrelevant [ 34 ].

Pandemics and natural disasters are highly stressful situations, which can easily induce negative emotions and adverse mental health states [ 35 – 37 ] such as perceived lack of control and instability, which are core aspects of emergency situations, contribute directly to stress. In turn, research has highlighted that stress is a crucial factor in influencing consumer behavior. For example, past studies have shown that individuals may withdraw and become passive in response to stress, and this inaction response can lead to a decrease in purchasing [ 38 , 39 ]. However, some studies point out that stress can lead to an active response, increasing impulsive spending behaviors [ 40 , 41 ]. Moreover, event-induced stress can lead to depressive mood. In some cases, the depressive mood may translate into the development of dysfunctional consumer behavior, such as impulsive (the sudden desire to buy something accompanied by excessive emotional response) and/or compulsive buying (repetitive purchasing due to the impossibility to control the urge) [ 41 , 42 ]. In this context, Sneath and colleagues [ 37 ] highlighted that changes in consumer behavior often represent self-protective strategies aimed at managing depressive states and negative emotions by restoring a positive sense of self. Importantly, a recent study conducted during the COVID-19 pandemic showed that depression predicted the phenomenon of the over-purchasing, which was framed as the degree to which people had increased their purchases of some necessities goods (e.g. food, water, sanitary products, pharmacy products, etc.) because of the pandemic [ 43 ].

A recent study recommended a differentiation between necessity and non-necessity products to better understand consumer behavior in response to stressful situations [ 18 ]. According to the authors, contrasting findings on the link between stress and consumer behavior may be due to the fact that stress affects certain purchasing behaviors negatively, but others positively, depending on the type of product under investigation. On one side, it has been argued that consumers may be more willing to spend money on necessities (vs. non-necessities) by making daily survival products readily available. Accordingly, recent research documented an increase in buying necessities products (i.e., utilitarian shopping) during and after a traumatic event [ 11 ]. However, other findings showed that impulsive non-necessities purchasing (i.e., hedonic shopping) could also increase as an attempt to escape or minimize the pain for the situation. That is, non-necessities buying is used as an emotional coping strategy to manage stress and negative emotional states [ 44 ]. To reconcile these findings, Durante and Laran [ 18 ] proposed that people adopt strategic consumer behavior to restore their sense of control in stressful situations. Hence, high stress levels generally lead consumers to save money and spend strategically on products perceived as necessities. Importantly, regarding the impact of perceived stress due to the COVID-19 pandemic on consumer behavior, a recent study showed that the likelihood of purchasing quantities of food larger than usual increased with higher levels of perceived stress [ 45 ].

Another psychological factor implicated in consumer behavior that deserves special attention is self-justification strategies [ 46 ]. Self-justification refers to the cognitive reappraisal process by which people try to reduce the cognitive dissonance stemming from a contradiction between beliefs, values, and behaviors. People often try to justify their decisions to avoid the feeling of being wrong to maintain a positive sense of self [ 17 ]. In consumer behavior research, it is widely acknowledged that consumers enhance positive arguments that support their choices and downplay counterarguments that put their behavior in question [ 47 ]. Based on previous research, it is plausible that, within the context of the COVID-19 pandemic, self-justifications for buying non-necessities products may also include pursuing freedom and defying boredom [ 11 , 48 ]. Further, the hedonistic attitude of “I could die tomorrow” or “You only live once” could certainly see a resurgence during the COVID-19 emergency [ 48 ], and become a crucial mechanism accounting for individual differences in consumer behavior. Based on these considerations, in the context of the COVID-19 pandemic, self-justifications strategies could be relevant for non-necessities, since products for fun or entertainment could be more suited to the pursuit of freedom and to defy boredom. Conversely, self-justifications strategies related to necessities could be implemented to a lesser degree, due to the very nature of the products. The unprecedented context of the pandemic could already justify the purchase of those essential goods by itself, and additional justifications may not be necessary.

Furthermore, several studies have shown that household income has a significant impact in determining people’s expenses [ 49 – 51 ]. Not surprisingly, the research highlighted a positive relationship between income and spending levels [ 52 ]. Income is defined as money received regularly from work or investments. Interestingly, a different line of research pointed out that self-perceived economic stability is a more appropriate determinant of consumer behavior than actual income [ 53 , 54 ]. Usually, people tend to report subjective feelings of income inadequacy, even when their objective financial situation might not support such attitude [ 55 ]. An interesting explanation for this bias draws on the social comparison process. Indeed, the study of Karlsson et colleagues [ 53 ] showed that, compared to families who considered themselves to have a good financial situation, households which considered themselves to be worse off economically than others reported fewer purchases of goods, perceived the impact of their latest purchase on their finance to be greater, and planned purchases more carefully. Furthermore, a recent study in the context of the COVID-19 emergency showed that people who believed to have limited financial resources were the most worried about the future [ 56 , 57 ]. Therefore, in the present study, we measured both the income and the perceived economic situation of the respondents to respectively consider the objective economic information and the subjective perception of respondents. However, considering the state of uncertainty experienced by many households during the COVID-19 pandemic [ 58 ], we changed the comparison from other families to participants’ economic situation in different time frames. We asked respondents to report perceived economic stability before, during, and after the emergency.

Finally, besides situational factors related to the specific emergency, the individuals’ personality traits are likely to have a role in determining consumer behavior as well. Past research has highlighted that the Big Five personality traits [ 59 ] can differently predict consumer behavior [ 60 ]. Specifically, conscientiousness, openness, and emotional stability (alias neuroticism) were related to compulsive buying, impulsive buying, and utilitarian shopping. Nevertheless, how different personality traits are related to consumer behavior is still an open question [ 61 ].

We conducted a nationwide survey in the Italian population to examine consumer behavior during the lockdown phase due to the COVID-19 pandemic. Since the COVID-19 emergency has emphasized the usefulness of essential goods (e.g. food, medications, etc.) compared to non-essential products (e.g. luxury items such as clothes and accessories) [ 62 ], in our study, we categorized products in necessities and non-necessities. Furthermore, changes in spending levels (necessities vs. non-necessities) were examined to confirm the effect that COVID-19 had on people’s expenses. Moreover, we tried to clarify the relationship between changes in spending levels and changes in consumer behavior. Finally, we focused on the psychological factors underlying changes in consumer behavior toward the target products. Based on the literature, we expected to find an increase in purchases with a more noticeable rise in necessity products. Specifically, we explored potential underpinnings of consumer behavior by examining mood states and affective response to the emergency, perceived economic stability, self-justification for purchasing, and personality traits. All these factors have been implicated in consumer behavior in previous research, but, to our knowledge, no study has considered all of them at once. Therefore, in this study, we adopted an integrative approach to study the contribution of different psychological factors by considering their mutual influence (see Fig 1 ). Specifically, based on the empirical findings and theoretical accounts presented above, we hypothesized that during the COVID-19 pandemic:

• Higher levels of anxiety and COVID-related fear would explain changes in consumer behavior, increasing the need for buying necessities.
• Higher levels of stress would lead consumers to save money or, in alternative, would increase the need to spend money on necessities (i.e., utilitarian shopping).
• Higher levels of depressive state would be associated with an increase in the need for buying, both necessities and non-necessities.
• Higher implementation of self-justification strategies would be associated with a higher need for buying, especially for non-necessities.
• Higher perceived economic stability would be associated with an increase in the need for both necessities and non-necessities.

• PPT PowerPoint slide
• PNG larger image
• TIFF original image

https://doi.org/10.1371/journal.pone.0256095.g001

The construct involved in the study is placed in the center of the figure. Arrows depart from these constructs to show the hypothesized relationship between the constructs and the outcomes of the present study (Necessities and Non-necessities). The symbol “±” was used to take into consideration two possible opposite directions.

Materials and methods

Data were collected through a series of questionnaires, using a web-based survey implemented on the Qualtrics software. The survey was active in the period starting from April 1st, 2020, to April 20th, 2020, during the first peak of the contagion in Italy. We used a convenience sample due to the exceptional situation of the COVID-19 pandemic and the time constraints to conduct our investigation. Therefore, participants were recruited through word-of-mouth and social media. Inclusion criteria were the age over 18 and be resident in Italy. First, socio-demographic information was collected, including gender, age, annual income, and education. Then, questions on spending levels and consumer behavior, both before the COVID-19 pandemic and during the first week of lockdown in Italy, were presented, separating necessities and non-necessities. Finally, a series of specifically created questionnaires and standardized measures were administered to investigate psychological and economic variables.

Participants

A total of 4121 participants were initially recruited. For the present study, we adopted a rigorous approach, excluding 104 participants over the age of 64, since they relied on retirement benefits and -from an economic point of view- were considered a specific population, not comparable to the rest of the sample [ 63 ]. Furthermore, we excluded 184 participants who did not report spending any money before the COVID-19 pandemic on buying necessities and/or non-necessities. Therefore, 3833 Italian participants (69.3% women, age M = 34.2, SD = 12.5) were included in this study. All participants provided their written informed consent before completing the survey. The study was conducted following the ethical standards of the Declaration of Helsinki and was approved by the Institutional Review Board of Psychology (IRBP) of the Department of Psychological, Health and Territorial Sciences at G. d’Annunzio University of Chieti-Pescara (protocol number: 20004). Participants did not receive monetary or any other forms of compensation for their participation.

Demographic variables

A demographic questionnaire was administered to collect background information. The questions considered age, gender, annual income, and education. The annual income was then categorized into five levels, based on the income brackets established by the Italian National Statistical Institute [ 64 ]. Education was categorized into five levels, from elementary to school to postgraduate degree.

Consumer behavior during COVID-19

We created this questionnaire from scratch to get a comprehensive overview of people’s economic attitudes and behaviors during the COVID-19 emergency. The idea of this new questionnaire was developed based on a series of previous studies on consumer behavior [ 43 , 65 – 67 ]. However, specific items were developed from scratch adapting them to the specific unprecedented context of the COVID-19 pandemic. Specifically, these items were created following a series of group discussions between all co-authors of the present study. To directly measure changes in consumer behavior due to the COVID-19 pandemic, participants were requested to compare their actual behavior to their normal behavior before the COVID-19 outbreak. Therefore, the initial statement in the questionnaire underlined that answers had to be given by referring to the COVID-19 emergency period compared to everyday life before the outbreak.

The factor structure and reliability were evaluated in the larger sample ( n = 4121), using principal component analysis (PCA) and Cronbach’s alpha. The results revealed a six-factor structure and satisfactory reliability values (see S1 Table for more details). Note that the PCA and reliability analyses were also conducted on the current subsample, and the pattern of results did not change.

For the present study’s aims, we focused on three scales: “Necessities”, “Non-necessities”, and “Self-justifications”. Items are shown in Table 1 . The first two scales investigated consumer behavior toward the different framed products. Specifically, items addressed the individual’s attitudes, feelings, and behaviors toward necessities and non-necessities. Thus, higher scores reflected greater value (e.g., need, utility) placed on the target products.

https://doi.org/10.1371/journal.pone.0256095.t001

The self-justifications scale referred to consumers’ thoughts to justify their purchases, with no distinction between necessity and non-necessity products. Higher scores reflected a frequent use of self-justifications in purchasing items.

For all these scales, responses were given on a Likert scale ranging from 0 ( not at all ), to 100, ( extremely ). Total scores on each scale were obtained by averaging all items.

Change in spending levels due to COVID-19

A fourth scale, i.e. “Spending Habits,” was extracted from the questionnaire mentioned above. As we aimed at measuring changes in the spending levels due to the COVID-19 emergency, we decided to use single items instead of the total scale score (items are presented in Table 1 ). Specifically, we created three percentage scores: “Changes in General Spending”, “Changes in Necessities spending”, and “Changes in Non-necessities spending” considering the difference between the money spent during the first week of lockdown, and the money spent on average in a week before the emergency (see Table 1 notes). Scores reflect the change in the amount (in Euro) that people devolved in purchasing the target products (hypothetical range from -1999 to +1999).

Big Five Inventory 10-item (BFI-10)

Big Five Inventory 10-item (BFI-10) is a short scale designed to briefly assess the five personality traits with two items for each trait. Specifically, these traits are: Agreeableness (example item: “I see myself as someone who is generally trusting”), Conscientiousness (example item: “I see myself as someone who does a thorough job”), Emotional stability (example item: “I see myself as someone who is relaxed, handles stress well”), Extraversion (example item: “I see myself as someone who is outgoing, sociable”), and Openness (example item: “I see myself as someone who has an active imagination”) [ 68 ]. In addition, respondents are asked to indicate whether they agree or disagree with each statement on a 5-point Likert-type scale, ranging from 1 ( not agree at all ) to 5 ( totally agree ). A previously validated Italian version was used in the present study [ 69 ].

Generalized anxiety disorder (GAD-7)

The GAD-7 [ 70 ] is a 7-item self-reported measure designed to screen for generalized anxiety disorder and to measure the severity of symptoms, based on the DSM-IV criteria. This measure is often used in both clinical practice and research. Specifically, respondents are asked the frequency they have experienced anxiety symptoms in the past two weeks (e.g., “Not being able to stop or control worrying”) on a 4-point Likert scale, ranging from 0 ( not at all ) to 3 ( nearly every day ). The total score ranges from 0 to 21, with higher scores indicating worse anxiety symptomatology.

Patient health questionnaire (PHQ-9)

The patient health questionnaire (PHQ-9) is a 9-item self-reported brief diagnostic measure for depression [ 71 ]. Specifically, respondents are asked of the frequency they felt bothered by several depressive symptoms during the past two weeks (e.g., “Little interest or pleasure in doing things”) on a 4-point Likert scale, ranging from 0 ( not at all ) to 3 ( nearly every day ). Total score ranges from 0 to 27, with higher scores indicating higher depressive symptoms.

Perceived Stress Scale (PSS)

The Perceived Stress Scale (PSS) is a 14-item self-report measure designed to assess the degree to which situations are appraised as stressful [ 72 ]. Each item (e.g., “In the last month, how often have you been upset because of something that happened unexpectedly?”) is rated on a 5-point Likert scale ranging from 0 ( never ) to 4 ( very often ). Thus, the total score ranges from 0 to 56, with a higher score indicating a higher level of perceived stress during the COVID-19 emergency.

Fear for COVID-19

We administered the Fear for COVID-19 questionnaire to measure fear and concerning beliefs related to the COVID-19 pandemic [ 35 , 36 , 73 ]. This questionnaire was created from the assumption that, during a health crisis, the individual’s fear is determined by both the hypothesized susceptibility (i.e., probability of contracting a disease) and the expected severity of the event (i.e., perceived consequences of being infected) [ 25 ]. Therefore, the 8 items dealt with the perceived probability of being infected by COVID-19 (Belief of contagion) and the possible consequences of the contagion (Consequences of contagion). See Table 1 for the complete list of the items. Previous studies have reported the PCA and reliability of the questionnaire [ 36 ]. Responses were given on a Likert scale ranging from 0 ( not at all ), to 100, ( extremely ). A total score was obtained by averaging the items (range 0–100).

Perceived economic stability

This questionnaire was developed to assess the subjective perception of an individual’s economic situation. The PCA in the larger sample revealed a unidimensional structure (see S2 Table for more details). The scale assessed perceived economic stability in three different timepoints: before, during, and after (in terms of expectation) the COVID-19 pandemic. Responses were given on a Likert scale ranging from 0 ( not at all ), to 100, ( extremely ). The total score was calculated by averaging these three items (range 0–100).

Statistical analysis

We preliminary investigated changes in spending levels due to the COVID-19 pandemic, comparing expenses before the emergency to expenses during the COVID-19 pandemic. First, we analyzed changes in the average general spending level. Then, we performed dependent (paired) sample t -tests between “Changes in necessities spending” and “Changes in non-necessities spending” to examine differences between products framed as necessities and non-necessities.

Afterward, we checked whether changes in spending levels were associated with changes in consumer behavior by conducting Pearson’s correlation analyses, respectively between “Changes in necessities spending” and “Necessities”, and “Changes in non-necessities spending” and “Non-necessities” scores.

Finally, to investigate the psychological underpinnings of consumer behavior, we performed two hierarchical multiple regressions, respectively, with “Necessities” (Model 1) and “Non-necessities” (Model 2) as outcomes. The same predictors were entered in Model 1 and Model 2. Specifically, the order of the steps was designed to include at first the socio-demographic information as control variables. Hence, we entered the age, gender, annual income brackets, and education in the first step. In Step 2, we included the personality measures (i.e., Big-Five personality traits) since these traits are stable and are not affected by the specific situation. In Step 3, Anxiety, Depression, and Stress were entered, to analyze the impact of emotional antecedents of consumer. Further, we decided to include Fear for the COVID-19 in a separate fourth step to evaluate the effect of this specific aspect. We included perceived economic stability at Step 5 after the psychological variables. This choice allowed to analyze the impact of the perceived economic stability after controlling for the role of emotional antecedents on consumer behavior. Finally, following the same logic, we included self-justifications strategies.

Considering “Changes in General spending”, our results showed that our sample reported, on average, an increase of 60.48% in the general spending level during the first week of lockdown. Furthermore, significant differences between “Changes in Necessities spending” and “Changes in Non-necessities spending”, t (3832) = 11.99, p < .001, were detected. Indeed, the spending level for necessities products showed an increase of 90.69%, while for non-necessities products, the average increase was only 36.11%. Means and standard deviations are presented in Table 2 .

https://doi.org/10.1371/journal.pone.0256095.t002

The results of the correlation analyses indicated that there was a significant positive association between “Changes in necessities spending” and “Necessities”, r (3831) = .22, p < .001. Furthermore, a significant positive association was highlighted between “Changes in non-necessities spending” and “Non-necessities”, r (3831) = .23, p < .001. Therefore, people’s changes in spending levels were related to their attitudes and feelings toward specific products. This finding supported our choice to investigate the psychological underpinnings of people’s consumer behavior.

Hierarchical multiple regression analyses were performed on the two consumer behavior scores. In addition, control variables, psychological factors, and economic variables were entered as predictors as detailed above.

Regarding Model 1 (Necessities), results showed that all the steps explained a significant amount of additional variance (see Table 3 for detailed results). When personality traits were entered in the model (Step 2), only agreeableness, openness, and emotional stability negatively predicted the outcome. However, when anxiety, depression, and stress were entered in the model (Step 3), only openness remained statistically significant. The variables entered in Step 3 contributed to explaining 7% of the variance, with anxiety and stress positively predicting the outcome. Adding fear for COVID-19 in the following step increased the explained variance by 6%, reduced the impact of anxiety, and completely overrode the effect of stress, which became non-significant. In the following steps, perceived economic stability offered a small but significant contribution (1%), and Self-justifications explained even further variance (4%). Overall, in the final step, the final model explained 23% of the variance in Necessities. Inspecting coefficients, we found that, after accounting for control variables, openness ( p < .001), anxiety ( p < .001), fear for COVID-19 ( p < .001), perceived economic stability ( p < .001), and self-justifications ( p < .001) emerged as significant predictors.

https://doi.org/10.1371/journal.pone.0256095.t003

In Model 2 (Non-necessities), results indicated that each step significantly contributed to explaining the outcome (see Table 4 ). In Step 2, personality traits explained 2% of the outcome variance, with consciousness and openness emerging as significant predictors and remaining significant until the final step. Notably, consciousness was negatively associated with non-necessities behavior, while high scores in openness were associated with higher scores on the Non-necessities scale. In Step 3, only depression was significantly and positively related to the outcome and remained so in subsequent models. Both fear for COVID-19 and perceived economic stability further significantly explained the outcome, albeit weakly (about 1% of variance each one). Higher levels of fear and perceived economic stability were associated with higher scores on the Non-necessities scale. Noteworthy, adding Self-justifications in the final step explained a substantial share of variance, equal to 12%. Specifically, higher scores on self-justifications were associated with higher scores on the Non-necessities scale. Furthermore, self-justifications also had a greater impact on non-necessities compared to those had on necessities, t (7664) = -10.60, p < .05. Total variance explained in the final step was 22%, with conscientiousness ( p < .001), openness ( p = .001), depression ( p = .002), perceived economic stability ( p = .009), and self-justifications ( p < .001) being significant predictors.

https://doi.org/10.1371/journal.pone.0256095.t004

The present study aimed to examine changes in consumer behavior and their psychological antecedents during the lockdown period due to the COVID-19 pandemic. We were specifically interested in separating necessity and non-necessity products since previous studies suggested that such a distinction is helpful to better understand consumer behavior[ 18 , 74 ]. First, our results indicated a 61% increase in spending levels during the first week of the lockdown, compared to the average expenses before the health crisis. Furthermore, spending levels were differently increased for buying products framed as necessities (91%) and non-necessities (36%). Second, we examined consumer behavior through Necessities and Non-necessities scales, which included measures related to the psychological need of buying, the specific aspects of the purchase experience (e.g., impulsiveness, perceived utility, satisfaction), and the number of products purchased. Our results highlighted that changes in consumer behavior were positively associated with changes in spending levels during the COVID-19 emergency.

Finally, we focused on psychological factors that can explain these changes in consumer behavior. In this context, our hypothesis about the role of the identified psychological factors in predicting consumer behavior during COVID-19 was supported. Also, our findings confirmed the importance of separating necessities from non-necessities products, as we found that they had different psychological antecedents. Regarding the investigation on spending levels, our findings are in line with sales data reporting that, during the COVID-19 pandemic, consumer priorities have become more centered on necessities, including food, hygiene, and cleaning products[ 7 , 62 ]. Therefore, the present study confirmed the greater tendency to buy necessities products during the COVID-19 pandemic. It is noteworthy to mention that our sample also reported an increase in spending levels related to non-necessities products. These data can be explained by referring to previous research that considered increases in non-necessities spending levels to respond to the hedonistic pursuit of freedom, defying boredom, restoring the sense of self, and compensatory mechanism, to alleviate negative psychological states[ 16 , 32 , 34 , 37 , 44 , 75 ]. However, as highlighted in the study by Forbes and colleagues[ 76 ] these hedonic needs and compensatory mechanisms can have a different impact during or in the aftermath of a crisis. In addition, the authors highlighted that the consumption of non-necessities products increased, as a way of coping to alleviate negative psychological states, particularly in the short term after a natural disaster. According to these results, a recent study conducted during the COVID-19 pandemic suggested that some factors, such as the degree of perceived threat, may vary during the COVID-19 pandemic, thus, having a different impact on consumer behavior[ 77 ]. Therefore, future research could delve into the analysis of changes in consumer behavior over time in relation to the different phases of the COVID-19 pandemic.

Regarding our investigation of consumer behavior’s antecedent psychological factors, we found partly different antecedents for necessities and non-necessities. Regarding demographic effects, in the present study, we found that men were more oriented in terms of needs and feelings toward non-necessities than women. A possible explanation could consider the context of the COVID-19, whereas the lockdown has imposed the closure of physical stores. In this context, it could be appropriate to refer to those studies that found several gender differences between consumer e-commerce adoption and purchase decision making. Specifically, research has shown that men and women have different psychological pre-disposition of web-based purchases, with men having more positive attitudes toward online shopping[ 78 , 79 ]. Furthermore, a study conducted during COVID-19 showed that women spent more time on necessities such as childcare and chores compared to men[ 80 ]. Regarding age differences, we found that younger people were more oriented toward non-necessities products. A study conducted in Italy during the COVID-19 pandemic highlighted that older adults showed lower negative emotions than younger adults[ 73 , 81 , 82 ]. In this view, it is possible that lower emotional antecedents, such as depressive states, lowered the need to buy non-necessities for more aged people. Another study conducted during the COVID-19 pandemic showed that older adults, aged 56 to 75, had significantly reduced the purchase of non-necessities goods compared to younger people[ 83 ]. Furthermore, considering the closure of physical stores, it is possible that younger people were more able and got used to buy a broader range of non-necessities products by e-commerce. However, it is important to note that we excluded in the present study people aged over 65. We also found a positive effect of income on necessities. A possible explanation is that people more stable from an economic point of view were more oriented to feel the need to buy products. However, surprisingly we did not find this effect for non-necessities. Finally, we found a positive effect of education on non-necessities. This data is congruent with another study conducted during the COVID-19 pandemic, showing that people with higher education (e.g., bachelor’s degrees and graduate or professional degrees) tended to buy an unusual amount of goods than people with lower education[ 84 ].Furthermore, another study highlighted that during COVID-19 pandemic entertainment and outdoor expenses significantly varied across different education groups[ 85 ]. Considering the present results, further studies should better investigate the impact of socio-demographic factors on the need to purchase necessities and non-necessities during health emergency and natural disaster.

Furthermore, after accounting for control variables (gender, age, income brackets, and education), consumer behavior toward necessities was explained by personality traits (openness), negative emotions (anxiety and COVID- related fear), perception of economic stability, and self-justifications. On the other side, consumer behavior toward non-necessities was explained by conscientiousness, openness, depression, perceived economic stability, and self-justifications.

Present findings showed that negative feelings have a considerable role in predicting changes in consumer behavior related to necessities products. This result is consistent with previous literature showing that, during a health crisis, fear and anxiety are developed from perceived feelings of insecurity and instability[ 30 ]. To reduce these negative feelings, people tend to focus on aspects and behaviors that can help them regain control and certainty, such as buying[ 86 ]. Therefore, changes in consumer behavior could be explained as a remedial response to reduce fear and anxiety related to the COVID-19 emergency. According to our hypothesis, present findings indicated that fear and anxiety play an important role in predicting changes in consumer behavior related to necessities. In contrast, no significant effects were found on non-necessities. A possible explanation for this remarkable difference can be provided by research in survival psychology, which highlighted that individuals might undergo behavioral changes during events such as natural disasters or health crises, including herd behavior, panic buying, changes in purchasing habits, and decision making[ 8 , 76 ]. Following these changes, individuals can be more engaged in behaviors that are necessary for survival[ 26 , 87 ]. In this view, COVID-related fear and anxiety could lead individuals to feel the need to buy necessities products useful for daily survival.

Stress is another factor suggested to differently affect changes in consumer behavior toward necessities and non-necessities[ 18 ]. It is noticeable that consumers experiencing stressful situations may show increased spending behavior, explicitly directed toward products that the consumer perceives to be necessities and that allow for control in an otherwise uncontrollable environment[ 18 ]. Our results partly support this position, showing that stress has a specific role in predicting changes in consumer behavior related to necessities but not to non-necessities. However, the role of stress was no longer significant when fear was entered in the regression model. Noteworthy, we focused on fear for COVID-19, therefore, it is possible that in such an exceptionally unprecedented situation, fear had a prominent role compared to stress. Moreover, previous literature shows that the relationship between fear and consumer behavior increases as the type of fear measured becomes more specific[ 88 ]. In this sense, further studies could delve into the relationship between fear and stress in relation to consumer behavior.

Notably, past studies had found a relationship between depressive states and consumer behavior, suggesting that changes in consumer behavior can represent self-protective behaviors to manage negative affective states[ 37 ]. The role of depression was highlighted by our results in respect to consumer behavior only related to non-necessities. Therefore, conversely to the study conducted in the UK and Ireland during the COVID-19 pandemic by Bentall et colleagues (2021), we did not find a relationship between depression and buying necessities. It is important to note that we described non-necessities products as “products for fun or entertainment”. In our opinion, people with higher levels of depressive symptoms may feel a greater need for this kind of product. Thus, people were drawn more toward this category of purchases because it was better suited to satisfy compensatory strategies to improve their negative emotional states. However, future studies are required to investigate this possibility and deepen the relationship between depressive states and the need to buy necessities and non-necessities. Furthermore, considering that depressive mood can be related to severe dysfunctional aspects of consumer behavior, such as impulsivity and compulsivity, future clinical studies should further investigate this relationship.

Furthermore, based on the limited and contrasting literature on this topic, we considered the role of personality traits. As suggested by previous studies, conscientiousness and openness were found to be associated with consumer behavior[ 89 – 91 ]. Interestingly, we found that personality traits were more relevant in consumer behavior toward non-necessities than necessities products. Only openness had a role in (negatively) predicting consumer behavior toward necessities, whereas conscientiousness (negatively) and openness (positively) predicted consumer behavior toward non-necessities. Unexpectedly, we found that people with a high level of openness showed high scores in consumer behavior toward non-necessities but low scores in necessities products. We speculated that individuals with higher levels of openness, which are more inclined to develop interests and hobbies[ 92 ], might have experienced a higher need to purchase non-necessities products during the lockdown. On the other hand, individuals with lower scores of openness, which tend to prefer familiar routines to new experiences and have a narrower range of interests, might have been more focused on purchasing necessity products. However, further studies should investigate the different roles of openness on necessities vs non-necessities consumer behavior. Globally, we acknowledge that the specific role and directions of these different personality traits on consumer behavior toward necessities and non-necessities is still an unexplored question, fully deserving of further investigations.

Finally, in both regression models, perceived economic stability and self-justifications predicted changes in consumer behavior. It comes as no surprise that individuals who perceived themselves and their family as more economically stable were prone to spend more in both products categories, necessities and non-necessities [ 52 , 53 ]. More intriguing, we found that the self-justifications that consumers adopted to motivate their purchases were a strong predictor of consumer behavior, especially in relation to non-necessities, where it explained the largest amount of variance (12%). Therefore, our hypothesis on the greater impact of self-justifications strategies on non-necessities compared to necessities was confirmed. Non-necessities, framed as products for fun or entertainment, seem more suited to satisfy that pursuit of freedom and the need to defy boredom that people increasingly experienced during the COVID-19 pandemic[ 48 ]. Therefore, we confirmed that the hedonistic attitude is an important predictor of consumer behavior during the COVID-19 pandemic. This result supported and extended previous literature showing that, during a crisis, changes in consumer behavior are related to self-justifications and rationalizations that people formulate to feel right in making their purchases, including the pursuit of freedom and the reduction of boredom[ 11 , 48 ]. Companies and markets can acknowledge this process and use it to develop new marketing strategies to meet consumers’ actual needs, feelings, and motivation to purchase during the COVID-19 emergency[ 12 ]. On the one hand, satisfying these needs could support and favor well-being and the positive sense of self, which are essentially sought by the consumer developing such self-justification strategies[ 17 ]. On the other hand, focusing on strategies that consider these psychological self-justifications could be a winning marketing strategy for increasing sales, contributing to the economic recovery after the COVID-19 outbreak[ 13 ].

The results of the present study highlighted that the COVID-19 pandemic had a considerable impact on consumer behavior. In our sample, this impact resulted in increased spending levels accompanied by an increase in the psychological need to purchase both necessities and non-necessities products. Furthermore, our findings demonstrated that several psychological factors predicted these changes in consumer behavior. Notably, consumer behavior respectively toward necessities and non-necessities differed on some psychological predictors.

Some limits of the current study need to be acknowledged. First, we studied consumer behavior from a broad perspective on a non-clinical sample, therefore we did not include dysfunctional aspects related to consumer behavior, such as impulsivity and compulsivity buying and hoarding behavior, which the emergency may elicit. Hence, in relation to the COVID-19 pandemic, it would be interesting to integrate our results with investigations of dysfunctional aspects of consumer behavior. Furthermore, since the unique opportunity to study psychological factors and consumer behavior during this unprecedented period, we adopted an integrative approach to consider the impact of several psychological factors at once, obtaining one of the first overviews of consumer behavior during the COVID-19 pandemic. However, combining all these psychological factors could have led to an aggregation bias[ 93 ], which could have masked the specific roles of each of the individual factors influencing consumer behavior. Therefore, future studies could adopt a more fine-grained approach to disentangle the role of each factor. Another limit is that we collected data during the initial stage of the COVID-19 outbreak in Italy. Notably, we reasoned that focusing on the very first period of the lockdown would likely allow us to capture the greater shift in consumer behavior, thus offering compelling evidence on the first impact of the pandemic on consumers. Nevertheless, it is likely that consumer behavior will undergo further changes in the longer term. Hence, future studies should investigate the evolution of consumer behaviors in relation to the development of the pandemic. Indeed, it is likely that when the “sense of urgency” and the negative affective reaction to the emergency will decrease, also the need for buying and purchases preferences would change. Furthermore, since we asked participants to estimate their weekly expenditures before and during the COVID-19 pandemic, it is important to keep in mind that our study focused on the people’s perception of changes in expenses. We did not know how much reliable these estimations were, and it is possible that objective assessment of change in the amount of money spent before and during the pandemic diverge from subjective views. In the present study, we focused on individual internal factors that could influence consumer behavior. However, other external factors, including the lockdown restrictions as the closure of physical stores, had certainly had a further impact on consumer behavior. Notwithstanding these limitations, this study represents one of the first attempts to examine changes in consumer behavior during the COVID-19 pandemic from a behavioral economic perspective, providing a thorough analysis of the psychological factors driving changes in consumer behavior, with a direct link to previous psychological research in consumer behavior. Furthermore, our results provided new evidence on the role of psychological factors influencing necessities and non-necessities spending and extended our knowledge of the antecedents of consumer behavior changes during the unprecedented health crisis we are experiencing.

In conclusion, the present study, by shedding new light on changes in people’s behavior due to the pandemic, fits into the growing body of research which helps increase economic and psychological preparedness in the face of future health emergencies.

Supporting information

S1 table. pattern matrix of the pca for the questionnaire on consumer behavior during the covid-19 pandemic..

https://doi.org/10.1371/journal.pone.0256095.s001

S2 Table. PCA for the “Perceived economic stability” questionnaire.

https://doi.org/10.1371/journal.pone.0256095.s002

• View Article
• PubMed/NCBI
• Google Scholar
• 3. John Hopkins University. Coronavirus COVID-19 Global Cases by the Center for System Science and Engineering (CSSE). In: Johns Hopkins Coronavirus Resource Center [Internet]. 2020 [cited 20 Jul 2020]. Available: https://coronavirus.jhu.edu/map.html
• 6. Despin T. Knock-on Effects Of COVID-19 On Consumer Behavior And How Businesses Can Prepare For Them. In: Entrepreneur [Internet]. 11 May 2020 [cited 12 Jun 2020]. Available: https://www.entrepreneur.com/article/350457
• 7. Nielsen. Key Consumer Behavior Thresholds Identified as the Coronavirus Outbreak Evolves–Nielsen. 2020 [cited 20 Jul 2020]. Available: https://www.nielsen.com/us/en/insights/article/2020/key-consumer-behavior-thresholds-identified-as-the-coronavirus-outbreak-evolves/?utm_source=sfmc&utm_medium=email&utm_campaign=newswire&utm_content=3-18-2020
• 12. Rajagopal . Development of Consumer Behavior. In: Rajagopal , editor. Transgenerational Marketing: Evolution, Expansion, and Experience. Cham: Springer International Publishing; 2020. pp. 163–194. https://doi.org/10.1007/978-3-030-33926-5_6
• 13. Diebner R, Silliman E, Ungerman K, Vancauwenberghe M. Adapting customer experience in the time of coronavirus. McKinsey & Company. 2020 [cited 10 Sep 2020]. Available: available at https://www. mckinsey. com/business-func tions/marketing-and-sales/our-insights/adapting-customer-experi ence-in-the-time-of-coronavirus
• 20. Foxall G. Consumer Psychology in Behavioral Perspective. Beard Books; 2004.
• 22. Leach J. Survival psychology. New York, NY, US: New York University Press; 1994. pp. xii, 220. https://doi.org/10.1057/9780230372719
• 24. Steven D, O’Brien E, Jones BD. The New Politics of Strategic Resources: Energy and Food Security Challenges in the 21st Century. Brookings Institution Press; 2014. Available: https://muse.jhu.edu/book/35813
• 26. Dodgson L. A human behavior expert explains 4 psychological reasons why people are panic buying items in bulk during the coronavirus pandemic. In: Insider [Internet]. 2020 [cited 22 Jul 2020]. Available: https://www.insider.com/why-people-are-panic-bulk-buying-during-the-coronavirus-pandemic-2020-3
• 31. Greenberg J, Solomon S, Pyszczynski T. Terror Management Theory of Self-Esteem and Cultural Worldviews: Empirical Assessments and Conceptual Refinements. In: Zanna MP, editor. Advances in Experimental Social Psychology. Academic Press; 1997. pp. 61–139. https://doi.org/10.1016/S0065-2601(08)60016-7
• 55. Streib GF, 1918-, Schneider CJ. Retirement in American society. 1971 [cited 11 Sep 2020]. Available: https://agris.fao.org/agris-search/search.do?recordID=US201300475317
• 60. Maison D. The Psychological Perspective in Financial Behaviour. In: Maison D, editor. The Psychology of Financial Consumer Behavior. Cham: Springer International Publishing; 2019. pp. 1–49. https://doi.org/10.1007/978-3-030-10570-9_1
• 64. Istat. Statistiche Istat. 2020 [cited 28 Jul 2020]. Available: http://dati.istat.it/
• 86. Wilkens J. Why we hoard: Fear at root of panic-buying, psychologists say. In: San Diego Union-Tribune [Internet]. 22 Mar 2020 [cited 3 Aug 2020]. Available: https://www.sandiegouniontribune.com/news/health/story/2020-03-22/hoard-fear-panic-buying-psychology
• 92. McCrae RR, Costa PT. Conceptions and Correlates of Openness to Experience. In: Hogan R, Johnson J, Briggs S, editors. Handbook of Personality Psychology. San Diego: Academic Press; 1997. pp. 825–847. https://doi.org/10.1016/B978-012134645-4/50032-9

To read this content please select one of the options below:

Please note you do not have access to teaching notes, how pandemic crisis times affects consumer behaviour.

Retail in a New World

ISBN : 978-1-80117-847-1 , eISBN : 978-1-80117-846-4

Publication date: 24 January 2022

Crisis can bring out the true nature of people. Also in terms of consumers, this can be for better or for worse. On the one hand, irresponsible consumer behaviours rose, with for example people starting to hoard bulk quantities of toilet paper, rice and flour, which in turn increased scarcity perceptions and induced fear in others. Besides panic buying, impulse purchasing also rose, as a means to alleviate negative feelings and to treat oneself (particularly once the stores reopened again). For some consumers, this increased buying can become compulsive, leading to shopping addiction and financial problems. On the other hand, the crisis also forced a pause in the rat race we live, allowing people to reconsider their consumption behaviour and evolve towards more sustainable choices. This chapter provides insights on both directions, allowing retail managers to incorporate this new reality in further strategic decisions. In what follows, three consecutive stages in notable changes in consumer behaviour in the pandemic crisis are discussed: from reacting (e.g. hoarding), over coping (e.g. do-it-yourself behaviours), to longer-term adapting (e.g. potentially transformative changes in consumption).

• Consumer behaviour
• Panic buying
• Impulsive buying
• Coping mechanism
• Psychological reactance theory
• Sustainable consumption

Pantano, E. and Willems, K. (2022), "How Pandemic Crisis Times Affects Consumer Behaviour", Retail in a New World , Emerald Publishing Limited, Leeds, pp. 13-28. https://doi.org/10.1108/978-1-80117-846-420221004

Emerald Publishing Limited

Copyright © 2022 Eleonora Pantano and Kim Willems. Published under exclusive licence by Emerald Publishing Limited

We’re listening — tell us what you think

Something didn’t work….

Report bugs here

All feedback is valuable

Please share your general feedback

Join us on our journey

Platform update page.

Visit emeraldpublishing.com/platformupdate to discover the latest news and updates

Questions & More Information

Answers to the most commonly asked questions here

Changes in the post-covid-19 consumers’ behaviors and lifestyle in italy. A disaster management perspective

• Original Article
• Published: 07 December 2021
• Volume 2022 , pages 87–106, ( 2022 )

Cite this article

• Annarita Sorrentino   ORCID: orcid.org/0000-0002-5245-1407 1 ,
• Daniele Leone 1 &
• Andrea Caporuscio 1  

7624 Accesses

6 Citations

Explore all metrics

The changes in consumption habits brought about from the covid-19 pandemic is completely reshaping the consumer profiles examined by different organizations. The purpose of this paper is to contribute to the consumer behavior studies by analyzing changes post-disasters. Our paper aims at understanding Italians’ lifestyle and behaviours during and post crisis in order to explore what behaviours people would keep after the disaster and to identify possible megatrends. Through a mixed method approach, we propose a trendy avatar which summarizes in its representation the four categories emerged from our explorative study: (1) digital, (2) homescape lovers, (3) responsible and (4) self-care oriented. Drawing on the new behavioural consumer profile proposed, some research avenues and managerial implications are advanced.

Similar content being viewed by others

The Relationship of Historical Redlining with Present-Day Neighborhood Environmental and Health Outcomes: A Scoping Review and Conceptual Model

Person-Centred Approaches to Social Work Practice

The Ethics of Digital Well-Being: A Thematic Review

Avoid common mistakes on your manuscript.

1 Introduction

The COVID-19 pandemic has emerged as a global catastrophe by affecting every feature of our lives. While the capacity to provide forecasting is restricted, it seems likely that the impact of COVID-19 is bound to be abrupt and profound in relation to marketing strategies and principles (Hoekstra & Leeflang, 2020 ). The wide-ranging upheaval of the COVID-19 outbreak is reconfiguring the discipline of marketing in a variety of directions. Notwithstanding the human catastrophe of the sudden rise in deaths and dramatic social effects the pandemic-driven lockdown might represent an opportunity to study the singular and unprecedented changes in consumer behavior (Sheth, 2020 ).

Right from the beginning of the pandemic, a large number of empirical studies have been published, for instance the study by Naeem ( 2020 ) has argued that during the COVID-19 pandemic the use of social media has affected customer psychology by improving its capacity to take optimal consumption decisions. In the same vein, the study by Mason et al. ( 2020 ) analyzes the alteration of consumer needs in the USA during the lockdown. The authors illustrated that the changes have affected both purchasing behavior and post-purchase satisfaction.

Unfortunately, the changes in marketing habits and procedures were provoked by such a very rare and unpredictable event as a COVID-19 pandemic. Therefore, the traditional marketing frameworks, much more focused on the symbolic value of products and hedonistic consumption experiences, seem to partially support the analysis by failing to capture some external determinants (Holbrook & Hirschman, 1982 ; Kim et al., 2019 ). To address this absence and align the actor-based marketing analysis to such an enormous and tragic external event as the COVID-19 pandemic, we have drawn from another block of managerial literature that is focused on coping with crisis, catastrophe, and disaster. In fact, disaster management is able to provide some frameworks and lenses for analysis to reveal the effects of huge, rare, and unpredictable negative events. Accordingly, the COVID-19 outbreak acts as a Black Swan (Taleb, 2007 ) and it cannot be studied using ordinary theoretical approaches. Therefore, we decided to examine disaster management to conceptualize the main crisis drivers (Taleb et al., 2009 ). Disaster management studies (Grossi, 2005 ; Park et al., 2015 ; Pearson & Clair, 1998 ; Taleb et al., 2009 ) suggest analyzing the consequences of a catastrophe, adopting an event timeline, and splitting a disaster into phases. From the very beginning, marketing scholars have addressed the topic of behavioral changes in consumption habits, although what seems to be lacking is a deep understanding of the correlation between behavioral consumption frameworks and disaster management determinants. Our study tries to exploit the stage of the catastrophe recovery scheme, drawing from the disaster management field to investigate the real changes in consumption habits. Indeed, our work seeks to pursue three objectives: first, investigating consumer lifestyle changes due to the lockdown; next, looking further into the behaviors that people are willing to make permanent; and last, profiling a new consumer behavioral pattern. Specifically, disaster studies provide a mitigation measure scheme that inspired our quantitative investigation. Indeed, scholars approached a negative event by listing several mitigating measures that, during the outbreak, in Italy just as all around the world, corresponded to social distancing and compulsory home life. At the same time, the literature on the crisis argues that the reaction of people and a recovery phase always follows that of mitigation. As part of the reaction phase, people started to change their habits and also consumer behavior, with some of the factors related to the mitigation phase affecting consumption paradigms and leading toward simpler lifestyles and to the utilitarian value of goods (Cozzolino, 2012 ). Such a kind of change might be understood as part of the reaction or recovery phase in terms of consumer attitudes and resilience. Accordingly, we harness such a chronological perspective with the aim of studying if people will keep the consumption changes after the lockdown and, consequently, if a new consumer behavioral profile will emerge. In other words, this study aims to identify various consumer response attitudes. Thus, the research question is: how does COVID-19 change consumers' lifestyle and behaviors and what habits will remain post-crisis?

To answer to this research question we chose the Italian situation, because Italy was one of the countries most affected by the pandemic; indeed, the official news was posted on the Italian Ministry of Health website on March 10, the decree stating a limitation of movement for Italian citizens to mitigate the outbreak of the virus. Such restrictions were without precedent in Italy. Meanwhile, due to the extraordinary impact on social life and peoples’ habits; citizens were obliged to respect social distancing measures; we decided to begin this article during the first phase of lockdown in Italy. We immediately thought about analyzing the disaster impact from a marketing perspective. We were witnessing a huge catastrophe that would provoke a disruptive transformation in social life. At the same time, consumer behavior was changing, so we started to gather data to capture the new direction of customer changes.

The phase of data analysis is based on a mixed method approach (Dunning et al., 2008 ) organized in two phases (quantitative and qualitative). In order to achieve a deep understanding, we set up a semi-structured questionnaire. We investigated the adaptation of consumers to new lifestyle habits by structuring the questions to achieve a full understanding of what the new consumption habits that the respondent has adopted are, and which of them the respondent perceives to be permanent, even after the lockdown. To expand comprehension of the phenomenon and for the sake of clarity, we arranged a qualitative phase of analysis by interviewing ten respondents belonging to the incumbent sample. This approach permits us have a deep insight into consumer changes and its latent categories of new habits that are strictly related to pandemic measures.

To accomplish our research project this paper is shaped as follows. In the first part we explain the theoretical background that supports our empirical work. Specifically, the first subsection concerns the exploration of the fundamentals of disaster management. The second part of the theoretical background section shows the crucial paradigm on consumer behavior and its evolution during the COVID-19 outbreak. The second section is dedicated to illustrating the methodology. Due to its mixed approach this creates both qualitative and quantitative investigations. The section relating to the findings, which replaces the methodical analysis pattern, illustrates both the qualitative and quantitative parts. At the end we debate our discussions and provide implications for scholars, practitioners, and policy makers

2 Literature background

2.1 disaster management: a lens of analysis for revealing new behavioral profiles.

Disaster management has a huge body of parallel fields of study that can sufficiently provide a consistent clarification on the main characteristics of the disaster management concept. Therefore, the literature has addressed the theme of negative, relevant, and unexpected events labelling the studies in different ways. As a consequence, catastrophe management, emergency management, crisis management, and Black Swan management are the strains of literature that contribute to powering the understanding of the study of disaster management (Grossi, 2005 ; Park et al., 2015 ; Pearson & Clair, 1998 ; Taleb et al., 2009 ). The fragmentation of the study about disaster management is not just a matter of semantic clarification; instead it is related to several facets of disaster events. In fact, a large realm of disaster definitions exists (Perry, 2007 ); this study exploits the definition of McFarlane and Norris ( 2006 , p. 4). The authors have argued that disasters are “ potentially traumatic events that are collectively experienced, have an acute onset, and are time-delimited ”. A pioneer of crisis management like Burnett ( 1998 ) described seven categories of changes during a catastrophe at business level: (1) heroes are born; (2) changes are accelerated; (3) latent problems are faced; (4) people can be changed; (5) new strategies evolve; (6) early warning systems develop; and (7) new competitive edges appear (Burnett, 1998 ). The outbreak is depicted by exploiting the study of Taleb ( 2007 ) as a Black Swan event. Accordingly, the COVID-19 pandemic has the main features of a Black Swan in that it has an unconstrained impact, with no room for forecasting. The study of Neal and Philipps ( 1995 ) argues that disaster events open the route to new collective behaviour. The study has been useful for unpacking the disaster response. It was even full of novelty in considering the focal role of a group or subgroup of people in moving as a crowd. Disaster management has taken into account the timeline of a tragic event, especially for assessing the impact and confronting it. Houston ( 2012 ) has divided the disaster into phases by splitting it into: a pre-event phase that is hard to predict, an event phase that concerns the disaster spread, and a post-event phase that corresponds to the negative impact of the event. Cozzolino ( 2012 ) has presented an interesting approach on the evolution of a disaster and its correlation with the recovery path. The author has analyzed catastrophic events by introducing the concept of a disaster management cycle (Marshall & Schrank, 2014 ). The author argues that disaster management is framed as a cycle and that it is essentially formed by four categories: mitigation, preparedness, response, and recovery.

The theoretical framework that supports our study is inspired most of all by Cozzolino’s ( 2012 ) study. Indeed, we adopt the disaster recovery path to investigate the changes in consumer behaviors. Our work exploits the disaster management cycle of Cozzolino ( 2012 ) to understand the evolution triggered by the COVID-19 outbreak. Furthermore, Huston's ( 2012 ) study argues that a disaster is characterized by a post event phase that impacts on habits and behaviors. Our theoretical framework takes this post-event phase into account to discover customers' behavioral changes that might become permanent. To the best of our knowledge there are no extant studies that try to bridge disaster management and customer behavior. The work of Burnett is not directly focused on customer behavior, it addresses the changes in organization when a disaster occurs. As suggested by Burnett, there are no systematic or widely accepted strategies for managing crises (Burnett, 1998 ). Each disaster concurs with the loss of traditional business guidelines; therefore, it is needed to establish steps to limit negative impacts on markets. Highlighting this kind of consequence of disaster has been a crucial element in anticipating the emergence of spontaneous behavioral norms. Guion and his co-authors (2007) have faced the issue of behavioral changes of people, but only during the disaster. The authors argue that a catastrophe has the capacity to profoundly modify behavior (Guion et al., 2007 ). As a consequence of the negative event, people adopt a new lifestyle to directly or indirectly overcome the emergence of the disaster.

2.2 Italians’ lifestyle and behaviors during the COVID-19 pandemic

In times of crisis, firms need to pay attention to consumer behaviors, reactions, and adaptation (Eger et al., 2021 ). The unexpected restrictions imposed during the COVID-19 outbreak (in early 2020), have made consumers deviate significantly from their usual shopping behavior (Eger et al., 2021 ). The more limited accessibility of store premises, the increase in digital shopping, the growth of self and home care orientation, and some other new habits, are reshaping the consumption paradigms (Eger et al., 2021 ). The need to investigate recent trends is crucial and useful to design new value propositions and consumer experiences (Dalli, 2004 ; East et al., 2016 ).

Postmodern consumption paradigms have long been characterized by demanding consumers oriented to the symbolic value of goods and services and hedonistic consumption experiences (Holbrook & Hirschman, 1982 ; Kim et al., 2019 ). After the COVID-19 crisis, some effects such as lockdown, social distancing, the shortage of available resources, home life, more time available, and the fear of contagion, have brought people back to simpler lifestyles and to the utilitarian value of goods (Sheth, 2020 ), such as buying food and basic goods, going out to the grocer’s, and using technology to feel close to loved ones.

New normal life derived from the consequence of the COVID-19 pandemic has pointed out the importance of time, space, and relations (Ferraresi, 2020 ), while increased digital adoption changed mobility patterns, changed purchasing behavior, increased awareness of health, and changed interpersonal behavior (SwisseRE institute, 2020 ).

With particular reference to purchasing and consumption behavior, before the COVID-19 pandemic, Italian consumers could mainly be identified as traditional shoppers, and only to a minor degree as online shoppers (called switch ) (Zhai et al., 2017 ; Eger et al., 2021 ). Traditional shoppers and online shoppers use a single channel to shop, meanwhile switch shoppers are shoppers who buy online but have previously explored the store in the pre-purchase stage. If, previously, these shopping behaviors depended on many reasons, such as: type of products to buy, motivation (task or leisure), age, culture, the exogenous event of the pandemic and its restrictions have totally removed these paradigms by changing lifestyles and behaviors and shaping new habits and new consumption models toward a massive use of digitalization, a healthy lifestyle, and a local shopping orientation (Eger et al., 2021 ).

On this point, some recent studies have investigated the possible impact on individual habits and social consumption trends after the pandemic. For example, Sheth ( 2020 ) has analyzed the immediate impact derived from the general lockdown on consumer behavior with eight elements: 1. Hoarding, 2. Improvisation, 3. Pent-up demand, 4. Embracing digital technology (e.g. online meetings, digital education), 5. Shops come to the home, 6. Blurring of work-life boundaries, 7. Reunions with friends and family and 8. Discovery of talent. In the same vein, Hoekstra and Leeflang ( 2020 ) discussed the impact of the pandemic on consumer behavioral changes and five possible new marketing megatrends. In particular, the authors observed that digital technology should be used to enhance the connection between consumers and firms in a more emotional way ( Connected Consumers ); shopping habits have been characterized by the use of digital platforms and the consumption of local goods ( shopping reinvented ); moreover, authors have observed a propensity to protect health and lifestyle as new priorities for consumers ( Healthy Living ). An additional megatrend derived from an observation of the economic consequences of the COVID-19 pandemic, and the particular condition of middle and lower economic classes, who are keen to maintain their economic position and lifestyles ( Middle Class and Lower Class Retreat ). Finally, the authors observe a possible depopulation of large cities, where green areas are likely to become saturated soon, as well as a switch of market frontiers due to the impact of COVID-19 measures (e.g. the conversion of tourist services into agriculture) ( Shifting Market Frontiers).

Against this backdrop, an interesting analysis may be carried out at a country level in the Italian context. Italy is well known all over the world for its food, art, fashion, and the Italian lifestyle, characterized by healthy consumption of food, healthy physical activity, and healthy prevention (Nomisma, 2020 ). Especially in some northern regions, this lifestyle was marked by fast work rhythms, well-defined roles within the family, and a lot of social activity (Nomisma, 2020 ). Italy was one of the countries most affected by the pandemic with over two million cases and over one hundred thousand dead (OMS, 2021 ). With the strict restrictions imposed by the Government, the COVID-19 pandemic has suddenly slowed down this lifestyle. On the one hand, it forced many cancellations (e.g. going to the restaurant, going to the gym, travelling), returning the country to the consumption of the 1980s. On the other hand, there was a speeding up of the dynamics of technological innovation, such as smart working, e-grocery, distance learning, and all public services, which were suddenly digitized (Deloitte, 2020 ). Furthermore, the need to stay at home has created a kind of comfort zone where Italians took refuge, especially to cook, unlike in previous years where there was almost an escape from the stove (Coop2020 Report). Thanks to the availability of time, the search for healthy food, and the need to reduce the family budget, people were made more aware and responsible, not only by cooking everything at home but also by purchasing from local suppliers (Cancello et al., 2020 ).

According to recent data (Nomisma, 2020 ), these trends also seem to have been confirmed in the months following the lockdown, in the so-called new normality , where people have shown a maintenance of respect for the hygiene and health regulations imposed by the pandemic, continuing to buy online and preferring sustainable products.

While the majority of the recent literature on consumer behavioral changes in Italy after the lockdown has been focused on food habits, this research aims to explore how the restrictions imposed by COVID-19 may influence long-term behavioral intentions, becoming new consumer trends. The present study contributes to the debate on behavioral changes and new trends of consumption and offers interesting insights for managers and policymakers.

3 Methodology

The purpose of this research is threefold. First, it analyzes the consumer lifestyle during the COVID-19 lockdown; second, it explores the behaviors that people would keep after the lockdown, and finally, it proposes to define the new consumer behavioral profile. Therefore, this study adopted a mixed-method approach (Dunning et al., 2008 ).

To achieve the research aims, we adopted an exploratory sequential strategy, first starting with a quantitative analysis and then using a qualitative assessment to gain more insights into the individuals’ perspectives toward identifying themselves under the categories revealed by the results of the quantitative study (Mikalef et al., 2019 ). More specifically, our research efforts comprise two phases. In phase 1, motivated by the aim of research, we used quantitative methods (explorative survey) and then, with the aim of analyzing if something changed five months after the end of the lockdown, in phase 2 we developed a qualitative analysis (short discussions) on previous respondents who have previously filled in the online survey in the first stage of the study (Mehta et al., 2020 ; Tashakkori & Creswell, 2007 ). This study was conducted in Italy because Italy was one of the countries most affected by the pandemic with 4,449,606 confirmed cases and 128,510 dead (OMS, August 2021). With the closure of all work activities (except for the primary goods supply chain), the forced transition to the use of digital technology to work and study, and the duty to stay at home, lifestyles have been profoundly reconfigured (Sheth, 2020 ).

3.1 Quantitative study

To examine the behavioral profile and lifestyles during the lockdown, a survey-based instrument was conducted on an Italian sample of people (n = 810) through a semi-structured questionnaire administrated via digital tools. The questionnaire was divided in five sections. Closed and open questions were included in the questionnaire. Given that the study was carried out during the COVID-19 pandemic, it did not precisely follow pre-existing measurement scales. Therefore, the mixed method study adopted is based on the sequential in-depth qualitative phase after the quantitative survey, which helps to confirm the results which emerged from the explorative study or reveals if something changed in the first section of the questionnaire related to the behavioral profile of the respondents during the lockdown. Individuals were asked to indicate their level of adjustment with each of the items related to ten questions (see Table 1 ) about opinions and adaptation to the COVID-19 conditions, using a 5-point Likert scale ranging from 1 (for nothing) to 5 (totally). To explore the behavioral intentions, people were invited to answer the following questions: “Are there any consumption habits that you will keep in the future after the pandemic crisis?” and “If yes, could you tell us what they are?”.

Data resulting from this open question were analyzed adapting the thematic analysis approach by Braun and Clarke ( 2006 ), where each author searched for meanings and patterns using an iterative and hermeneutical approach.

Thematic analysis is defined as “a method for identifying, analyzing, and reporting patterns or themes within the data” (Braun & Clarke, 2006 , p.79). Through this process, initial codes were produced from a frequency analysis. Then, based on an inductive-deductive approach to the thematic analysis, we have manually identified some codes as an expression of the ideas or feelings given in the text (e.g. “I will keep going to shop online” has been coded into “online shopping”; “I want to save money and shop once a week for food” has been coded into “weekly planning of food shopping”) which were organized into broader categories (themes). Afterwards, the categories were re-examined and checked against the codes and the original data. Then we manually look at the codes we have created, identify patterns among them, and start to come up with themes. With the aim to identify behavioral factors, several codes were combined into a single theme to highlight the essential meaning (see Table 2 and the Fig.  1 ).

Source : Authors’ elaboration

An example of thematic map.

As national lockdown in Italy lasted from 9th of March to 18th of May, to be sure of capturing feelings derived from a new lifestyle, our questionnaire was disseminated in May 2020, almost at the end of the two month lockdown. Non-probability snowball sampling was used for the online survey due to the lack of an appropriate sampling frame (Nguyen et al., 2020 ). The questionnaire was disseminated via email to different groups of people (different age and work groups and residing across different areas in Italy) to prevent the formation of a homogeneous sample (Del Chiappa et al., 2021 ). People were invited to fill in the Google form and requested to find additional respondents. After a week of dissemination, a total of 810 surveys were returned.

3.2 Qualitative study

Second, a qualitative approach was followed (Hesse-Biber & Leavy, 2010 ) by using short discussions. Since the primary purpose of qualitative studies is to acquire relatively more comprehensive, updated knowledge on a specific topic, a short discussion is a convenient method to match such purposes (Lamont & White, 2005 ). Due to the exceptionality of the event, we adopted a qualitative approach after the explorative survey to verify if something had changed five months after the end of lockdown.

Hence, ten random short discussions were conducted in October 2020 with previous respondents who had previously filled in the online survey in the first stage of the study.

The focus of the discussions was to gain more insights into the individuals’ perspectives toward identifying themselves under the latent categories revealed by the results of the quantitative study. Respondents received an introduction to the purpose of the study and an explanation of the four latent categories of new habits. The following are examples of questions asked during the discussion: “how do you feel after two months of lockdown?” “how much have you adapted yourself to the new lifestyle required by the pandemic?”, “Are there any consumption habits that you will keep in the future after the pandemic crisis?” and “If yes, could you tell us what they are?” It was noticed that after the 7 th discussion, the quality and quantity of information gained was almost repeated and no more ideas about the new lifestyle trends after COVID-19 were evolving, which is a signal of “data saturation” (Guest et al., 2006 ). To make sure that the data obtained was sufficient for the current study, three more discussions were added. Each discussion lasted between 15 and 22 min. A code containing letters to denote the first letter of the participant's name followed by a number (the age of the participant), and M/F to indicate their gender is assigned to each quote in the transcript to protect the anonymity of the participants. Transcripts were analyzed by using the coding process of dividing data into codes and themes related to the segments (Braun & Clarke, 2006 ). Interpretation of data collected helped in informing and further explaining the study results.

4.1 Quantitative findings

The socio-demographic profile of the sample is presented in Table 2 . The majority of the interviewees were female (63.2%). In terms of age, 58 per cent were between 21 and 30, 17 per cent were between 31 and 40, 15 per cent above 41, and 10 per cent were below 20. The majority of the sample were from southern Italy (59.4%), 26.5 per cent from northern Italy, and 14.1 per cent from central Italy. In terms of employment status, a large portion of the sample (46.7%) were students, while the rest of the sample was divided among employed (26.7%), workers (6.9%), self-employed (7.5%), entrepreneurs (1.9%), and unemployed (10.5%).

With the aim of verifying how much the lifestyle and habits of the Italians have changed during the lockdown, participants were asked if and how much their eating, study, and work habits have changed and how much they adapted themselves to these new dynamics of daily life (see Table 3 ). Before proceeding with the questions illustrated in the tables, respondents were asked if they had the opportunity to continue their work from home (70%).

Despite this extraordinary and forced change, respondents showed a satisfactory level of adjustment. Moreover, people also asserted that some of the new habits (e.g. home working, home studying) should be implemented even after the pandemic emergency. On the other hand, concerning leisure activities (e.g. eating out vs home delivery), people showed a propensity to go back to eating out in the post-COVID stage. In addition, regarding shopping behavior, people showed a change in their approach to shopping. However, during the lockdown, they felt they were not much influenced by advertising. Overall, in response to the last question, people showed a high propensity to return to pre-COVID life, even if they have appreciated some changes.

To understand the appreciated habits that people would keep after the pandemic, respondents were asked “Are there any habits you will keep in your post-COVID stage?” 65 per cent responded positively.

In a first step analysis, in order to obtain quick feedback from the question, a frequency analysis was performed. It revealed two relevant habits that people would keep in their new lifestyle: online shopping and home cooking. In addition, the table illustrated some interesting insights, with similar frequencies. To move from the list format to something that provides a better basis for the identification of new behavioral trends of information, in a second step we applied the identify-categories strategy (Braun & Clarke, 2006 ; Vaughn & Turner, 2016 ), which is discussed in the next paragraph.

4.2 Qualitative findings

After having verified similar topics in the manifest responses, we developed coding that makes connections between similar themes. Thus, we tried to combine the manifest definitions with similar meanings, similar values, similar goals and similar tools into themes. Four themes have been identified which help to shape the new profile of Italian consumers after the COVID-19 lockdown.

The first category is digital resulting from the unified items “online shopping” and “digital meetings”; the second category has been called homescape lovers , which is the manifestation of all the home-related items (home cooking, home delivery, food delivery, home working, spending more time at home); the third category has been named responsible to group all the items related to a more conscious behavior (saving money, doing proximity shopping, avoiding waste, more reasoned purchases, weekly planning of food shopping). Finally, the fourth category has been labelled as self-care oriented to indicate the items related to personal care (wearing a face mask, social distancing, personal and home care, eating healthy food, physical activities, and time for hobbies).

The data collected from the discussions revealed that all the participants interviewed in the second stage identified themselves in the four categories. In particular, regarding the category ‘digital’, a participant indicated “ During the lockdown I appreciated the time spent at home, despite the new reorganization of work, spaces and family ” and “ Even though my work has partially returned, I continue to spend a lot of time at home through digital tools ” (Y54, F). Another participant indicated “ I see myself in the habits indicated and for the future I’m trying to maintain a more balanced work-life lifestyle, take better care of myself and the environment for a better society ” (M55, M). On this point, another participant found himself in the categories responsible behavior and homescape lover and said “ I would definitely keep the habit of buying more stocks of basic goods and continue cooking at home, because I like it and it is certainly more hygienic and safe ”.

Two participants declared that they had completely changed their lifestyle and that the time spent at home also changed their consumption behavior, especially in terms of values. Accordingly, one participant said “ I saved money and I am currently not interested in buying non-primary goods” (G43, F). In addition, when we asked what changes you would bring with you in your post-COVID life, some of the participants declared “ Home life made me think about life priorities: caring for myself, the environment, and loved ones ” (M67, M). Additionally, an interesting comment came from a young participant who said “ Despite the fact that COVID robbed me of the pleasure of seeing my friends and colleagues, I appreciated the utility of following lessons from home and I would like this possibility to always remain after this” (H65, M).

Overall, discussions confirmed the categories that emerged from the coding by confirming that the main behaviors that people would like to maintain even beyond the pandemic emergency are related to a more responsible behavior, oriented toward taking care of oneself and others, especially the environment, and a new awareness of the use of technology and home spaces.

5 Discussion and conclusion

COVID-19 has revealed the unstable foundations upon which much of what we take for granted in the developed world is built, from the complex nature of globalized manufacturing chains and infrastructures to just-in-time supermarket deliveries, as well as stark contrasts between public health systems or those financed by private insurance. Furthermore, the results attested that this pandemic has produced many changes in the lifestyles of the individual and of society as a whole. Lockdown created resilience and improvisation behaviors, which influenced behavioral intentions in a post-crisis stage.

We derived a new behavioral consumer profile by presenting a trendy avatar (see Fig.  1 ) which summarizes in its representation the four categories that emerged from our explorative study: (1) digital, (2) homescape lovers, (3) responsible and (4) self-care oriented (Fig. 2 ).

A new behavioral consumer profile presented by a trendy avatar

The avatar summarized the main evidence, which helped us to shape and propose the new profile of Italian consumers to manage the disaster after the COVID-19 lockdown. Indeed, the results presented in the previous Tables 2 and 3 attest to the fact that consumption behaviors in the next few years will not only be related to well-known and consolidated trends, such as the growing attention to health and wellbeing and the greater connection and sharing of information through digital devices, but also new orientations that will change the styles of living and consumer shopping globally.

In particular, the results of Table 2 show customers switching habits in favour of online shopping and adopting the principle of proximity when in need of a “brick and mortar store”. Another piece of evidence referred to the rise in awareness about wellbeing and personal care (e.g. wearing a mask), and also that there is an increase in interest in environmental issues and new ideas of living together. For these reasons, the new behavioral consumer profile shows the adoption of more responsible consumption behavior, for instance waste reduction, frugality, and the remodulation of the shopping budget and homemade cooking. Furthermore, one of the main drivers toward these personal and family changes has been the activation of smart working for many workers, and for others, the temporary suspension of work as a result of the closure of businesses and workplaces (for example, shops and restaurants). Thus, the concept of the house is being expanded by adding the perspective of a workplace i.e. home working, and reinforcing the idea of the pivotal place of families.

As illustrated above in Table 3 , the respondents described that the lockdown period allowed exploration of hobbies and interests (e.g. home cooking) that we may never have had before. Many consumers want to keep these behaviors after the lockdown, are spending much more time cooking, and are paying more attention to food. Even if physically distant, digital technologies and social media have allowed us to enter the homes of others and to connect with them (Tables 4 and 5 ).

The knock-on effect of these behavioral changes can be the decline in the value of properties in large cities and the increase in the number of people who decide to move outside the metropolis, to the suburbs or to rural areas: a reversal of the trend compared to the beginning of the industrial revolution.

The economic impact was terrible, the effort and measures to neutralize the outbreak had a negative impact on different sectors. It occurred without any scope for predictions and it found the world completely unprepared to control and manage the outbreak and its consequences. As our very lives, companies, communities, and countries have been disrupted by this dramatic event, so too will be the philosophies, ideologies, and fundamental principles that theorize management studies, and more specifically the marketing field.

Furthermore, our results offer an interesting focus on utilitarian value (Overby & Lee, 2006 ; Li et al., 2018 ) as a need after the emergency period, contrary to the pre-COVID stage where consumers were more demanding and hedonistic in their consumption experience. For these reasons, grabbing and developing new paradigms (e.g. new lifestyle habits) to understand the impact of disasters on customer habits is relevant for the advancement of marketing studies because the situation we are likely to see continue after the pandemic will be that of many employees who continue to work from home.

Indeed, our research has shown that such a system worked during the lockdown, and this evidence will force many executives to no longer appeal to traditional arguments against requests for permission to work from home. This condition could in turn lead to a change in the expectations and culture of the workplace, where employees are evaluated based on their achievement in terms of the effectiveness and efficiency of the objectives assigned to them, and not on how many hours they sit behind their desk in the office. For these reasons, people who could continue to benefit from the extra time they have at home will be those whose working lifestyle has changed irreversibly. This situation is likely to favor employees over service industry workers, which means that not everyone will benefit equally from these changes in the future. Despite being enormously disruptive and painful, crisis management invariably also fuels the emergence of more reasoned purchases and proximity shopping by creating a more responsible profile. The difficulty in finding simple consumer products, or the inability to go shopping in stores, or perhaps just the fact that many of us had more time available, have developed online shopping skills by exploiting food delivery and resourcefulness in avoiding waste that have been largely shared online. Social media has opened small windows to share and compare with others regarding the different reaction mechanisms to the crisis through digital meetings. For these reasons, these conceptual limits related to these complex situations within disaster management have led to different lifestyles and behaviors. Other respondents have even affirmed the habit of dedicating themselves to physical activity around the house, or simply personal and home care in a small space on the windowsill of an urban window.

6 Implications

We used the COVID disaster event in order to see what is happening to consumer behavior during and after the event, especially regarding consumer behavior and lifestyle changes post-crisis. To answer this question, the study examined the Italian context to explore how Italians have already begun to make changes in their daily lives that allow the definition of a new consumer behavioral profile.

Our theoretical contribution refers to the consumer behavior literature (Mason et al., 2020 ; Naeem et al., 2020 ; Shet, 2020 ; Eger et al., 2021 ) by offering some megatrends that may affect future marketing trajectories. Indeed, the results provide a new behavioral profile based on four categories, which could be interesting insights for future research. Second, our study seeks to exploit the disaster management perspective (Grossi, 2005 ; Park et al., 2015 ; Pearson & Clair, 1998 ; Taleb et al., 2009 ) in order to understand what post-crisis changes in consumers' lifestyle and behavior (Shet, 2020 ; Eger et al., 2021 ) will have a definitive impact and what will not persist for a long time.

We attempt to develop some interesting implications for scholars and practitioners through this proposal of a new behavioral consumer profile.

Starting from the observation of the effects of the pandemic as a disastrous event on health, economy, and society, we analyzed the changes in the lifestyle and behavior of Italians, strongly affected by the pandemic, with the final purpose to identify possible future trajectories in purchase and consumption models. The four categories identify trends that were unimaginable until a year ago and which instead are characterizing these months, and perhaps they will enter into future behaviors, at least for a while, effectively reconfiguring the transaction models of sales, communication, etc.

Referring to the managerial implications, firms can consider the deployment of new business models to face the rise in online purchasing and behavioral consumer changes, which affect the logistics chain. On the other hand, the reconfiguration of the customer timeframe is changing from daily purchasing to weekly planning. This is because daily habits are changing in favor of the pleasure of cooking for oneself, which has been rediscovered, avoiding take-away dinners when returning from the office, carefully choosing a recipe, chopping and mixing ingredients, enjoying, in short, the process of preparing a meal. For these reasons, large scale distribution should take account of this significant evolution by updating its discount plan. Finally, organizations have to rethink their product and services proposals by considering the redesign of homespace as a new opportunity. Indeed, the respondents affirmed that they have been involved in a large number of creative projects during the lockdown at home with their family. Additionally, personal care organizations such as beauty companies have to consider that many Italians have rediscovered activities and habits that were lost due to a hectic modern life: making things exclusively for themselves and realizing how deeply satisfying and fulfilling this can be.

Referring to the theoretical implications, scholars interested in consumer behavior studies and disaster management literature (Grossi, 2005 ; Park et al., 2015 ; Pearson & Clair, 1998 ; Taleb et al., 2009 ) can exploit this research by considering the lens of this study on Italian consumers during the COVID pandemic, which shows interesting insights on new habits and consumption experiences post-crisis. In line with the study by Shet ( 2020 ), we contribute to this field of literature of consumer behavior by examining the consumer lifestyle during the COVID-19 lockdown in order to explore post-disaster behaviors that people would keep after the lockdown, and finally, we propose a new consumer behavioral profile (see Fig.  1 ).

7 Limitations and future research

Our analysis has some limitations. First, it is closely connected to the COVID-19 disaster in Italy; therefore, we invite future researchers to study these behaviors in different contexts to understand if the model is replicable. Furthermore, we aimed to raise awareness of the necessity to examine these behavioral issues in depth in complex environments and situations, trying to conceptually classify them into homogeneous elements that shape the four main categories of the new consumer profile proposed in this study.

Future research could be carried out by profiling the sample to identify possible latent clusters; moreover, the consumer perspective and the highlighted consumer behavioral changes provide the opportunity to investigate the firm’s response to the new needs and attitudes.

Basu, A. J., & van Zyl, D. J. (2006). Industrial ecology framework for achieving cleaner production in the mining and minerals industry. Journal of Cleaner Production, 14 (3–4), 299–304.

Article   Google Scholar  

Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3 (2), 77–101.

Burnett, J. J. (1998). A strategic approach to managing crises. Public Relations Review, 24 (4), 475–488.

Burt, R. S. (1992). Structural holes: The structure of social capital competition . Harvard University Press.

Book   Google Scholar  

Cancello, R., Soranna, D., Zambra, G., Zambon, A., & Invitti, C. (2020). Determinants of the lifestyle changes during COVID-19 pandemic in the residents of Northern Italy. International Journal of Environmental Research and Public Health, 17 (17), 6287.

Chesbrough, H., Kim, S., & Agogino, A. (2014). Chez Panisse: Building an open innovation ecosystem. California Management Review, 56 (4), 144–171.

COOP Rapporto (2020) available at https://www.italiani.coop/wp-content/uploads/2020/09/PRESENTAZIONE-RAPCOOP2020-web-hd.pdf

Coleman, J. S. (1988). Social capital in the creation of human capital. American Journal of Sociology, 94 , S95–S120.

Coleman, J. (1990). Foundations of Social Theory . Belknap Press of Harvard University Press.

Google Scholar  

Coppola, D. P. (2006). Introduction to international disaster management . Elsevier.

Cozzolino, A. (2012). Cross-Sector Cooperation in Disaster Relief Management (pp. 5–16). Heidelberg: Humanitarian Logistics and Supply Chain Management, Berlin.

Dalli, D. (2004). La ricerca sul comportamento del consumatore: lo stato dell'arte in Italia e all'estero. Mercati e competitività.

Del Chiappa, G., Pung, J. M., Atzeni, M., & Sini, L. (2021). What prevents consumers that are aware of Airbnb from using the platform? A mixed methods approach. International Journal of Hospitality Management, 93 , 102775.

Deloitte (2020). Il consumatore e la new reality . https://assets.kpmg/content/dam/kpmg/it/pdf/2020/09/Consumer-Behavior-Survey-Report_GlobalFocusItaly.pdf?__hstc=160160738.ae551b36011bed93214e96de1ee2ffb4.1627291293576.1627291293576.1627291293576.1&__hssc=160160738.1.1627291293576&__hsfp=1360741907

Dunning, H., Williams, A., Abonyi, S., & Crooks, V. (2008). A mixed method approach to quality of life research: A case study approach. Social Indicators Research, 85 (1), 145–158.

East, R., Singh, J., Wright, M., & Vanhuele, M. (2016). Consumer behaviour: Applications in marketing. Sage.

Eger, L., Komárková, L., Egerová, D., & Mičík, M. (2021). The effect of COVID-19 on consumer shopping behaviour: Generational cohort perspective. Journal of Retailing and Consumer Services, 61 , 102542.

Ehrenfeld, J. R. (2000). Industrial ecology: Paradigm shift or normal science? American Behavioral Scientist, 44 (2), 229–244.

Feng, Y., Wu, J., & He, P. (2019). Global M&A and the development of the IC industry ecosystem in China: What can we learn from the case of Tsinghua Unigroup? Sustainability, 11 (1), 106.

Ferraresi, M. (2020) Interview available at https://www.huffingtonpost.it/entry/mauro-ferraresi-effetto-covid-prima-compravamo-tempo-ora spazio_it_5ec7ddbec5b6cc3a293443f8?ie=&utm_hp_ref=it-homepage&ncid=fcbklnkithpmg00000001&ref=fbph&fbclid=IwAR09FFRz78JsxZ2e0QOlORar-H6oLQH_s-QoAOiuTlvPpuSZ79XZ5afk7vM

Fritsch, M., & Kauffeld-Monz, M. (2010). The impact of network structure on knowledge transfer: An application of social network analysis in the context of regional innovation networks. The Annals of Regional Science, 44 (1), 21.

Frosch, R. A., & Gallopoulos, N. E. (1989). Strategies for manufacturing. Scientifi,c American, 261 (3), 144–152.

Grossi, P. (2005).  Catastrophe modeling: a new approach to managing risk  (Vol. 25). Springer Science & Business Media.

Guest, G., Bunce, A., & Johnson, L. (2006). How many interviews are enough? An experiment with data saturation and variability. Field Methods, 18 (1), 59–82.

Guion, D. T., Scammon, D. L., & Borders, A. L. (2007). Weathering the storm: A social marketing perspective on disaster preparedness and response with lessons from Hurricane Katrina. Journal of Public Policy & Marketing, 26 (1), 20–32.

Hesse-Biber, S. N., & Leavy, P. (2010). The practice of qualitative research . Sage.

Hoekstra, J. C., & Leeflang, P. S. (2020). Marketing in the era of COVID-19. Italian Journal of Marketing, 2020 (4), 249–260.

Holbrook, M. B., & Hirschman, E. C. (1982). The experiential aspects of consumption: Consumer fantasies, feelings, and fun. Journal of Consumer Research, 9 (2), 132–140.

Houston, J. B., Pfefferbaum, B., & Rosenholtz, C. E. (2012). Disaster news: Framing and frame changing in coverage of major US natural disasters, 2000–2010. Journalism & Mass Communication Quarterly, 89 (4), 606–623.

Iansiti, M., & Levien, R. (2004). The keystone advantage: what the new dynamics of business ecosystems mean for strategy, innovation, and sustainability. Harvard Business Press.

Kim, S., Ham, S., Moon, H., Chua, B. L., & Han, H. (2019). Experience, brand prestige, perceived value (functional, hedonic, social, and financial), and loyalty among GROCERANT customers. International Journal of Hospitality Management, 77 , 169–177.

Lamont, M., White, P. (2005),Workshop on Interdisciplinary Standards for Systematic Qualitative Research, in Cultural Anthropology, Law and Social Science, Political Science, and Sociology Programs, National Science Foundation, Available from: https://www.nsf.gov/sbe/ses/soc/ISSQR_rpt.pdf .

Lin, H. C., Bruning, P. F., & Swarna, H. (2018). Using online opinion leaders to promote the hedonic and utilitarian value of products and services. Business Horizons, 61 (3), 431–442.

Marshall, M. I., & Schrank, H. L. (2014). Small business disaster recovery: A research framework. Natural Hazards, 72 (2), 597–616.

Mason, A., Narcum, J., & Mason, K. (2020). Changes in consumer decision-making resulting from the COVID-19 pandemic. Journal of Customer Behaviour., 19 , 299–321.

McFarlane, A. C., & Norris, F. H. (2006). Definitions and concepts in disaster research. Methods for Disaster Mental Health Research, 2006 , 3–19.

Mehta, S., Saxena, T., & Purohit, N. (2020). The New consumer behaviour paradigm amid COVID-19: Permanent or Transient ? . Journal of Health Management, 22 (2), 291–301.

Mikalef, P., Boura, M., Lekakos, G., & Krogstie, J. (2019). Big data analytics and firm performance: findings from a mixed-method approach. Journal of Business Research, 98 , 261–276.

Morrish, S. C., & Jones, R. (2020). Post-disaster business recovery: An entrepreneurial marketing perspective. Journal of Business Research, 113 , 83–92.

Naeem, M. (2020). Understanding the customer psychology of impulse buying during COVID-19 pandemic: implications for retailers.  International Journal of Retail & Distribution Management .

Neal, D. M., & Phillips, B. D. (1995). Effective emergency management: Reconsidering the bureaucratic approach. Disasters, 19 (4), 327–337.

Nguyen, H. V., Tran, H. X., Van Huy, L., Nguyen, X. N., Do, M. T., & Nguyen, N. (2020). Online book shopping in Vietnam: The impact of the COVID-19 pandemic situation. Publishing Research Quarterly, 36 , 437–445.

Nomisma (2020). Un Italiano su tre preferisce uno stile di vita corretto. Available at https://www.nomisma.it/stili-di-vita-corretti/

OMS (2021) available at https://www.salute.gov.it/portale/nuovocoronavirus/dettaglioContenutiNuovoCoronavirus.jsp?lingua=italiano&id=5338&area=nuovoCoronavirus&menu=vuoto

Overby, J. W., & Lee, E. J. (2006). The effects of utilitarian and hedonic online shopping value on consumer preference and intentions. Journal of Business Research, 59 (10–11), 1160–1166.

Park, I., Sharman, R., & Rao, H. R. (2015). Disaster experience and hospital information systems: An examination of perceived information assurance, risk, resilience, and his usefulness. Mis Quarterly, 39 (2), 317–344.

Pearson, C. M., & Clair, J. A. (1998). Reframing crisis management. Academy of Management Review, 23 (1), 59–76.

Perry, M. (2007). Natural disaster management planning.  International Journal of Physical Distribution & Logistics Management .

Porter, M. E. (1991). Michael E . Harvard Business School Press.

Pullen, A., de Weerd-Nederhof, P. C., Groen, A. J., & Fisscher, O. A. (2012). SME network characteristics vs. product innovativeness: How to achieve high innovation performance. Creativity and Innovation Management, 21 (2), 130–146.

Sheth, J. (2020). Impact of Covid-19 on consumer behavior: will the old habits return or die? Journal of Business Research., 117 , 280–283.

SwissRe Institute (2020). Article available at https://www.swissre.com/institute/research/topics-and-risk-dialogues/health-and-longevity/covid-19-and-consumer-behaviour.html

Taleb, N. N. (2007).  The black swan: The impact of the highly improbable  (Vol. 2). Random house.

Taleb, N. N., Goldstein, D. G., & Spitznagel, M. W. (2009). The six mistakes executives make in risk management. Harvard Business Review, 87 (10), 78–81.

Tashakkori, A., & Creswell, J. W. (2007). The new era of mixed methods.

Vaughn, P., & Turner, C. (2016). Decoding via coding: Analyzing qualitative text data through thematic coding and survey methodologies. Journal of Library Administration, 56 (1), 41–51.

Wankmüller, C. (2021). European disaster management in response to the COVID-19 pandemic. Mind & Society, 20 (1), 165–170.

Wasserman, S., & Faust, K. (1994). Social network analysis: Methods and applications. Cambridge university press

Zhai, Q., Cao, X., Mokhtarian, P. L., & Zhen, F. (2017). The interactions between e-shopping and store shopping in the shopping process for search goods and experience goods. Transportation, 44 (5), 885–904.

Download references

Acknowledgements

The authors did not receive support from any organization for the submitted work.

Author information

Authors and affiliations.

Department of Management and Quantitative Studies, Parthenope University of Naples, Via Generale Parisi 13, 80131, Naples, Italy

Annarita Sorrentino, Daniele Leone & Andrea Caporuscio

You can also search for this author in PubMed   Google Scholar

Corresponding author

Correspondence to Annarita Sorrentino .

Ethics declarations

Conflict of interest.

The authors have no conflict of interest to declare that are relevant to the content of this article.

Additional information

Publisher's note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Sorrentino, A., Leone, D. & Caporuscio, A. Changes in the post-covid-19 consumers’ behaviors and lifestyle in italy. A disaster management perspective. Ital. J. Mark. 2022 , 87–106 (2022). https://doi.org/10.1007/s43039-021-00043-8

Download citation

Received : 15 January 2021

Accepted : 16 November 2021

Published : 07 December 2021

Issue Date : March 2022

DOI : https://doi.org/10.1007/s43039-021-00043-8

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Consumer behaviour
• Disaster management
• Italians lifestyle
• Covid-19 pandemic
• Find a journal
• Publish with us
• Track your research

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

• Publications
• Account settings

Preview improvements coming to the PMC website in October 2024. Learn More or Try it out now .

• Advanced Search
• Journal List
• Springer Nature - PMC COVID-19 Collection

The past, present, and future of consumer research

Maayan s. malter.

1 Columbia Business School, Columbia University, New York, NY USA

Morris B. Holbrook

Barbara e. kahn.

2 The Wharton School, University of Pennsylvania, Philadelphia, PA USA

Jeffrey R. Parker

3 Department of Marketing, University of Illinois at Chicago, Chicago, IL USA

Donald R. Lehmann

In this article, we document the evolution of research trends (concepts, methods, and aims) within the field of consumer behavior, from the time of its early development to the present day, as a multidisciplinary area of research within marketing. We describe current changes in retailing and real-world consumption and offer suggestions on how to use observations of consumption phenomena to generate new and interesting consumer behavior research questions. Consumption continues to change with technological advancements and shifts in consumers’ values and goals. We cannot know the exact shape of things to come, but we polled a sample of leading scholars and summarize their predictions on where the field may be headed in the next twenty years.

Introduction

Beginning in the late 1950s, business schools shifted from descriptive and practitioner-focused studies to more theoretically driven and academically rigorous research (Dahl et al. 1959 ). As the field expanded from an applied form of economics to embrace theories and methodologies from psychology, sociology, anthropology, and statistics, there was an increased emphasis on understanding the thoughts, desires, and experiences of individual consumers. For academic marketing, this meant that research not only focused on the decisions and strategies of marketing managers but also on the decisions and thought processes on the other side of the market—customers.

Since then, the academic study of consumer behavior has evolved and incorporated concepts and methods, not only from marketing at large but also from related social science disciplines, and from the ever-changing landscape of real-world consumption behavior. Its position as an area of study within a larger discipline that comprises researchers from diverse theoretical backgrounds and methodological training has stirred debates over its identity. One article describes consumer behavior as a multidisciplinary subdiscipline of marketing “characterized by the study of people operating in a consumer role involving acquisition, consumption, and disposition of marketplace products, services, and experiences” (MacInnis and Folkes 2009 , p. 900).

This article reviews the evolution of the field of consumer behavior over the past half century, describes its current status, and predicts how it may evolve over the next twenty years. Our review is by no means a comprehensive history of the field (see Schumann et al. 2008 ; Rapp and Hill 2015 ; Wang et al. 2015 ; Wilkie and Moore 2003 , to name a few) but rather focuses on a few key thematic developments. Though we observe many major shifts during this period, certain questions and debates have persisted: Does consumer behavior research need to be relevant to marketing managers or is there intrinsic value from studying the consumer as a project pursued for its own sake? What counts as consumption: only consumption from traditional marketplace transactions or also consumption in a broader sense of non-marketplace interactions? Which are the most appropriate theoretical traditions and methodological tools for addressing questions in consumer behavior research?

A brief history of consumer research over the past sixty years—1960 to 2020

In 1969, the Association for Consumer Research was founded and a yearly conference to share marketing research specifically from the consumer’s perspective was instituted. This event marked the culmination of the growing interest in the topic by formalizing it as an area of research within marketing (consumer psychology had become a formalized branch of psychology within the APA in 1960). So, what was consumer behavior before 1969? Scanning current consumer-behavior doctoral seminar syllabi reveals few works predating 1969, with most of those coming from psychology and economics, namely Herbert Simon’s A Behavioral Model of Rational Choice (1955), Abraham Maslow’s A Theory of Human Motivation (1943), and Ernest Dichter’s Handbook of Consumer Motivations (1964). In short, research that illuminated and informed our understanding of consumer behavior prior to 1969 rarely focused on marketing-specific topics, much less consumers or consumption (Dichter’s handbook being a notable exception). Yet, these works were crucial to the rise of consumer behavior research because, in the decades after 1969, there was a shift within academic marketing to thinking about research from a behavioral or decision science perspective (Wilkie and Moore 2003 ). The following section details some ways in which this shift occurred. We draw on a framework proposed by the philosopher Larry Laudan ( 1986 ), who distinguished among three inter-related aspects of scientific inquiry—namely, concepts (the relevant ideas, theories, hypotheses, and constructs); methods (the techniques employed to test and validate these concepts); and aims (the purposes or goals that motivate the investigation).

Key concepts in the late - 1960s

During the late-1960s, we tended to view the buyer as a computer-like machine for processing information according to various formal rules that embody economic rationality to form a preference for one or another option in order to arrive at a purchase decision. This view tended to manifest itself in a couple of conspicuous ways. The first was a model of buyer behavior introduced by John Howard in 1963 in the second edition of his marketing textbook and quickly adopted by virtually every theorist working in our field—including, Howard and Sheth (of course), Engel-Kollat-&-Blackwell, Franco Nicosia, Alan Andreasen, Jim Bettman, and Joel Cohen. Howard’s great innovation—which he based on a scheme that he had found in the work of Plato (namely, the linkages among Cognition, Affect, and Conation)—took the form of a boxes-and-arrows formulation heavily influenced by the approach to organizational behavior theory that Howard (University of Pittsburgh) had picked up from Herbert Simon (Carnegie Melon University). The model represented a chain of events

where I = inputs of information (from advertising, word-of-mouth, brand features, etc.); C = cognitions (beliefs or perceptions about a brand); A = Affect (liking or preference for the brand); B = behavior (purchase of the brand); and S = satisfaction (post-purchase evaluation of the brand that feeds back onto earlier stages of the sequence, according to a learning model in which reinforced behavior tends to be repeated). This formulation lay at the heart of Howard’s work, which he updated, elaborated on, and streamlined over the remainder of his career. Importantly, it informed virtually every buyer-behavior model that blossomed forth during the last half of the twentieth century.

To represent the link between cognitions and affect, buyer-behavior researchers used various forms of the multi-attribute attitude model (MAAM), originally proposed by psychologists such as Fishbein and Rosenberg as part of what Fishbein and Ajzen ( 1975 ) called the theory of reasoned action. Under MAAM, cognitions (beliefs about brand attributes) are weighted by their importance and summed to create an explanation or prediction of affect (liking for a brand or preference for one brand versus another), which in turn determines behavior (choice of a brand or intention to purchase a brand). This took the work of economist Kelvin Lancaster (with whom Howard interacted), which assumed attitude was based on objective attributes, and extended it to include subjective ones (Lancaster 1966 ; Ratchford 1975 ). Overall, the set of concepts that prevailed in the late-1960s assumed the buyer exhibited economic rationality and acted as a computer-like information-processing machine when making purchase decisions.

Favored methods in the late-1960s

The methods favored during the late-1960s tended to be almost exclusively neo-positivistic in nature. That is, buyer-behavior research adopted the kinds of methodological rigor that we associate with the physical sciences and the hypothetico-deductive approaches advocated by the neo-positivistic philosophers of science.

Thus, the accepted approaches tended to be either experimental or survey based. For example, numerous laboratory studies tested variations of the MAAM and focused on questions about how to measure beliefs, how to weight the beliefs, how to combine the weighted beliefs, and so forth (e.g., Beckwith and Lehmann 1973 ). Here again, these assumed a rational economic decision-maker who processed information something like a computer.

Seeking rigor, buyer-behavior studies tended to be quantitative in their analyses, employing multivariate statistics, structural equation models, multidimensional scaling, conjoint analysis, and other mathematically sophisticated techniques. For example, various attempts to test the ICABS formulation developed simultaneous (now called structural) equation models such as those deployed by Farley and Ring ( 1970 , 1974 ) to test the Howard and Sheth ( 1969 ) model and by Beckwith and Lehmann ( 1973 ) to measure halo effects.

Aims in the late-1960s

During this time period, buyer-behavior research was still considered a subdivision of marketing research, the purpose of which was to provide insights useful to marketing managers in making strategic decisions. Essentially, every paper concluded with a section on “Implications for Marketing Managers.” Authors who failed to conform to this expectation could generally count on having their work rejected by leading journals such as the Journal of Marketing Research ( JMR ) and the Journal of Marketing ( JM ).

Summary—the three R’s in the late-1960s

Starting in the late-1960s to the early-1980s, virtually every buyer-behavior researcher followed the traditional approach to concepts, methods, and aims, now encapsulated under what we might call the three R’s —namely, rationality , rigor , and relevance . However, as we transitioned into the 1980s and beyond, that changed as some (though by no means all) consumer researchers began to expand their approaches and to evolve different perspectives.

Concepts after 1980

In some circles, the traditional emphasis on the buyer’s rationality—that is, a view of the buyer as a rational-economic, decision-oriented, information-processing, computer-like machine for making choices—began to evolve in at least two primary ways.

First, behavioral economics (originally studied in marketing under the label Behavioral Decision Theory)—developed in psychology by Kahneman and Tversky, in economics by Thaler, and applied in marketing by a number of forward-thinking theorists (e.g., Eric Johnson, Jim Bettman, John Payne, Itamar Simonson, Jay Russo, Joel Huber, and more recently, Dan Ariely)—challenged the rationality of consumers as decision-makers. It was shown that numerous commonly used decision heuristics depart from rational choice and are exceptions to the traditional assumptions of economic rationality. This trend shed light on understanding consumer financial decision-making (Prelec and Loewenstein 1998 ; Gourville 1998 ; Lynch Jr 2011 ) and how to develop “nudges” to help consumers make better decisions for their personal finances (summarized in Johnson et al. 2012 ).

Second, the emerging experiential view (anticipated by Alderson, Levy, and others; developed by Holbrook and Hirschman, and embellished by Schmitt, Pine, and Gilmore, and countless followers) regarded consumers as flesh-and-blood human beings (rather than as information-processing computer-like machines), focused on hedonic aspects of consumption, and expanded the concepts embodied by ICABS (Table ​ (Table1 1 ).

Extended ICABS Framework after 1980

Methods after 1980

The two burgeoning areas of research—behavioral economics and experiential theories—differed in their methodological approaches. The former relied on controlled randomized experiments with a focus on decision strategies and behavioral outcomes. For example, experiments tested the process by which consumers evaluate options using information display boards and “Mouselab” matrices of aspects and attributes (Payne et al. 1988 ). This school of thought also focused on behavioral dependent measures, such as choice (Huber et al. 1982 ; Simonson 1989 ; Iyengar and Lepper 2000 ).

The latter was influenced by post-positivistic philosophers of science—such as Thomas Kuhn, Paul Feyerabend, and Richard Rorty—and approaches expanded to include various qualitative techniques (interpretive, ethnographic, humanistic, and even introspective methods) not previously prominent in the field of consumer research. These included:

• Interpretive approaches —such as those drawing on semiotics and hermeneutics—in an effort to gain a richer understanding of the symbolic meanings involved in consumption experiences;
• Ethnographic approaches — borrowed from cultural anthropology—such as those illustrated by the influential Consumer Behavior Odyssey (Belk et al. 1989 ) and its discoveries about phenomena related to sacred aspects of consumption or the deep meanings of collections and other possessions;
• Humanistic approaches —such as those borrowed from cultural studies or from literary criticism and more recently gathered together under the general heading of consumer culture theory ( CCT );
• Introspective or autoethnographic approaches —such as those associated with a method called subjective personal introspection ( SPI ) that various consumer researchers like Sidney Levy and Steve Gould have pursued to gain insights based on their own private lives.

These qualitative approaches tended not to appear in the more traditional journals such as the Journal of Marketing , Journal of Marketing Research , or Marketing Science . However, newer journals such as Consumption, Markets, & Culture and Marketing Theory began to publish papers that drew on the various interpretive, ethnographic, humanistic, or introspective methods.

Aims after 1980

In 1974, consumer research finally got its own journal with the launch of the Journal of Consumer Research ( JCR ). The early editors of JCR —especially Bob Ferber, Hal Kassarjian, and Jim Bettman—held a rather divergent attitude about the importance or even the desirability of managerial relevance as a key goal of consumer studies. Under their influence, some researchers began to believe that consumer behavior is a phenomenon worthy of study in its own right—purely for the purpose of understanding it better. The journal incorporated articles from an array of methodologies: quantitative (both secondary data analysis and experimental techniques) and qualitative. The “right” balance between theoretical insight and substantive relevance—which are not in inherent conflict—is a matter of debate to this day and will likely continue to be debated well into the future.

Summary—the three I’s after 1980

In sum, beginning in the early-1980s, consumer research branched out. Much of the work in consumer studies remained within the earlier tradition of the three R’s—that is, rationality (an information-processing decision-oriented buyer), rigor (neo-positivistic experimental designs and quantitative techniques), and relevance (usefulness to marketing managers). Nonetheless, many studies embraced enlarged views of the three major aspects that might be called the three I’s —that is, irrationality (broadened perspectives that incorporate illogical, heuristic, experiential, or hedonic aspects of consumption), interpretation (various qualitative or “postmodern” approaches), and intrinsic motivation (the joy of pursuing a managerially irrelevant consumer study purely for the sake of satisfying one’s own curiosity, without concern for whether it does or does not help a marketing practitioner make a bigger profit).

The present—the consumer behavior field today

Present concepts.

In recent years, technological changes have significantly influenced the nature of consumption as the customer journey has transitioned to include more interaction on digital platforms that complements interaction in physical stores. This shift poses a major conceptual challenge in understanding if and how these technological changes affect consumption. Does the medium through which consumption occurs fundamentally alter the psychological and social processes identified in earlier research? In addition, this shift allows us to collect more data at different stages of the customer journey, which further allows us to analyze behavior in ways that were not previously available.

Revisiting the ICABS framework, many of the previous concepts are still present, but we are now addressing them through a lens of technological change (Table ​ (Table2 2 ). In recent years, a number of concepts (e.g., identity, beliefs/lay theories, affect as information, self-control, time, psychological ownership, search for meaning and happiness, social belonging, creativity, and status) have emerged as integral factors that influence and are influenced by consumption. To better understand these concepts, a number of influential theories from social psychology have been adopted into consumer behavior research. Self-construal (Markus and Kitayama 1991 ), regulatory focus (Higgins 1998 ), construal level (Trope and Liberman 2010 ), and goal systems (Kruglanski et al. 2002 ) all provide social-cognition frameworks through which consumer behavior researchers study the psychological processes behind consumer behavior. This “adoption” of social psychological theories into consumer behavior is a symbiotic relationship that further enhances the theories. Tory Higgins happily stated that he learned more about his own theories from the work of marketing academics (he cited Angela Lee and Michel Pham) in further testing and extending them.

ICABS framework in the digital age

Present Methods

Not only have technological advancements changed the nature of consumption but they have also significantly influenced the methods used in consumer research by adding both new sources of data and improved analytical tools (Ding et al. 2020 ). Researchers continue to use traditional methods from psychology in empirical research (scale development, laboratory experiments, quantitative analyses, etc.) and interpretive approaches in qualitative research. Additionally, online experiments using participants from panels such as Amazon Mechanical Turk and Prolific have become commonplace in the last decade. While they raise concerns about the quality of the data and about the external validity of the results, these online experiments have greatly increased the speed and decreased the cost of collecting data, so researchers continue to use them, albeit with some caution. Reminiscent of the discussion in the 1970s and 1980s about the use of student subjects, the projectability of the online responses and of an increasingly conditioned “professional” group of online respondents (MTurkers) is a major concern.

Technology has also changed research methodology. Currently, there is a large increase in the use of secondary data thanks to the availability of Big Data about online and offline behavior. Methods in computer science have advanced our ability to analyze large corpuses of unstructured data (text, voice, visual images) in an efficient and rigorous way and, thus, to tap into a wealth of nuanced thoughts, feelings, and behaviors heretofore only accessible to qualitative researchers through laboriously conducted content analyses. There are also new neuro-marketing techniques like eye-tracking, fMRI’s, body arousal measures (e.g., heart rate, sweat), and emotion detectors that allow us to measure automatic responses. Lastly, there has been an increase in large-scale field experiments that can be run in online B2C marketplaces.

Present Aims

Along with a focus on real-world observations and data, there is a renewed emphasis on managerial relevance. Countless conference addresses and editorials in JCR , JCP , and other journals have emphasized the importance of making consumer research useful outside of academia—that is, to help companies, policy makers, and consumers. For instance, understanding how the “new” consumer interacts over time with other consumers and companies in the current marketplace is a key area for future research. As global and social concerns become more salient in all aspects of life, issues of long-term sustainability, social equality, and ethical business practices have also become more central research topics. Fortunately, despite this emphasis on relevance, theoretical contributions and novel ideas are still highly valued. An appropriate balance of theory and practice has become the holy grail of consumer research.

The effects of the current trends in real-world consumption will increase in magnitude with time as more consumers are digitally native. Therefore, a better understanding of current consumer behavior can give us insights and help predict how it will continue to evolve in the years to come.

The future—the consumer behavior field in 2040 1

Niels Bohr once said, “Prediction is very difficult, especially if it’s about the future.” Indeed, it would be a fool’s errand for a single person to hazard a guess about the state of the consumer behavior field twenty years from now. Therefore, predictions from 34 active consumer researchers were collected to address this task. Here, we briefly summarize those predictions.

Future Concepts

While few respondents proffered guesses regarding specific concepts that would be of interest twenty years from now, many suggested broad topics and trends they expected to see in the field. Expectations for topics could largely be grouped into three main areas. Many suspected that we will be examining essentially the same core topics, perhaps at a finer-grained level, from different perspectives or in ways that we currently cannot utilize due to methodological limitations (more on methods below). A second contingent predicted that much research would center on the impending crises the world faces today, most mentioning environmental and social issues (the COVID-19 pandemic had not yet begun when these predictions were collected and, unsurprisingly, was not anticipated by any of our respondents). The last group, citing the widely expected profound impact of AI on consumers’ lives, argued that AI and other technology-related topics will be dominant subjects in consumer research circa 2040.

While the topic of technology is likely to be focal in the field, our current expectations for the impact of technology on consumers’ lives are narrower than it should be. Rather than merely offering innumerable conveniences and experiences, it seems likely that technology will begin to be integrated into consumers’ thoughts, identities, and personal relationships—probably sooner than we collectively expect. The integration of machines into humans’ bodies and lives will present the field with an expanding list of research questions that do not exist today. For example, how will the concepts of the self, identity, privacy, and goal pursuit change when web-connected technology seamlessly integrates with human consciousness and cognition? Major questions will also need to be answered regarding philosophy of mind, ethics, and social inequality. We suspect that the impact of technology on consumers and consumer research will be far broader than most consumer-behavior researchers anticipate.

As for broader trends within consumer research, there were two camps: (1) those who expect (or hope) that dominant theories (both current and yet to be developed) will become more integrated and comprehensive and (2) those who expect theoretical contributions to become smaller and smaller, to the point of becoming trivial. Both groups felt that current researchers are filling smaller cracks than before, but disagreed on how this would ultimately be resolved.

Future Methods

As was the case with concepts, respondents’ expectations regarding consumer-research methodologies in 2030 can also be divided into three broad baskets. Unsurprisingly, many indicated that we would be using many technologies not currently available or in wide use. Perhaps more surprising was that most cited the use of technology such as AI, machine-learning algorithms, and robots in designing—as opposed to executing or analyzing—experiments. (Some did point to the use of technologies such as virtual reality in the actual execution of experiments.) The second camp indicated that a focus on reliable and replicable results (discussed further below) will encourage a greater tendency for pre-registering studies, more use of “Big Data,” and a demand for more studies per paper (versus more papers per topic, which some believe is a more fruitful direction). Finally, the third lot indicated that “real data” would be in high demand, thereby necessitating the use of incentive-compatible, consequential dependent variables and a greater prevalence of field studies in consumer research.

As a result, young scholars would benefit from developing a “toolkit” of methodologies for collecting and analyzing the abundant new data of interest to the field. This includes (but is not limited to) a deep understanding of designing and implementing field studies (Gerber and Green 2012 ), data analysis software (R, Python, etc.), text mining and analysis (Humphreys and Wang 2018 ), and analytical tools for other unstructured forms of data such as image and sound. The replication crisis in experimental research means that future scholars will also need to take a more critical approach to validity (internal, external, construct), statistical power, and significance in their work.

Future Aims

While there was an air of existential concern about the future of the field, most agreed that the trend will be toward increasing the relevance and reliability of consumer research. Specifically, echoing calls from journals and thought leaders, the respondents felt that papers will need to offer more actionable implications for consumers, managers, or policy makers. However, few thought that this increased focus would come at the expense of theoretical insights, suggesting a more demanding overall standard for consumer research in 2040. Likewise, most felt that methodological transparency, open access to data and materials, and study pre-registration will become the norm as the field seeks to allay concerns about the reliability and meaningfulness of its research findings.

Summary - Future research questions and directions

Despite some well-justified pessimism, the future of consumer research is as bright as ever. As we revised this paper amidst the COVID-19 pandemic, it was clear that many aspects of marketplace behavior, consumption, and life in general will change as a result of this unprecedented global crisis. Given this, and the radical technological, social, and environmental changes that loom on the horizon, consumer researchers will have a treasure trove of topics to tackle in the next ten years, many of which will carry profound substantive importance. While research approaches will evolve, the core goals will remain consistent—namely, to generate theoretically insightful, empirically supported, and substantively impactful research (Table ​ (Table3 3 ).

Future consumer behavior research questions

At any given moment in time, the focal concepts, methods, and aims of consumer-behavior scholarship reflect both the prior development of the field and trends in the larger scientific community. However, despite shifting trends, the core of the field has remained constant—namely, to understand the motivations, thought processes, and experiences of individuals as they consume goods, services, information, and other offerings, and to use these insights to develop interventions to improve both marketing strategy for firms and consumer welfare for individuals and groups. Amidst the excitement of new technologies, social trends, and consumption experiences, it is important to look back and remind ourselves of the insights the field has already generated. Effectively integrating these past findings with new observations and fresh research will help the field advance our understanding of consumer behavior.

1 The other papers use 2030 as a target year but we asked our survey respondents to make predictions for 2040 and thus we have a different future target year.

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

• Beckwith NE, Lehmann DR. The importance of differential weights in multiple attribute models of consumer attitude. Journal of Marketing Research. 1973; 10 (2):141–145. doi: 10.1177/002224377301000203. [ CrossRef ] [ Google Scholar ]
• Belk RW, Wallendorf M, Sherry JF., Jr The sacred and the profane in consumer behavior: theodicy on the odyssey. Journal of Consumer Research. 1989; 16 (1):1–38. doi: 10.1086/209191. [ CrossRef ] [ Google Scholar ]
• Dahl, R. A., Haire, M., & Lazarsfeld, P. F. (1959). Social science research on business: product and potential . New York: Columbia University Press.
• Ding, Y., DeSarbo, W. S., Hanssens, D. M., Jedidi, K., Lynch Jr., J. G., & Lehmann, D. R. (2020). The past, present, and future of measurements and methods in marketing analysis. Marketing Letters, 10.1007/s11002-020-09527-7.
• Farley JU, Ring LW. An empirical test of the Howard-Sheth model of buyer behavior. Journal of Marketing Research. 1970; 7 (4):427–438. doi: 10.1177/002224377000700401. [ CrossRef ] [ Google Scholar ]
• Farley JU, Ring LW. “Empirical” specification of a buyer behavior model. Journal of Marketing Research. 1974; 11 (1):89–96. [ Google Scholar ]
• Fishbein M, Ajzen I. Belief, attitude, intention, and behavior: an introduction to theory and research. Reading: Addison-Wesley; 1975. [ Google Scholar ]
• Gerber, A. S., & Green, D. P. (2012). Field experiments: design, analysis, and interpretation . New York: WW Norton.
• Gourville JT. Pennies-a-day: the effect of temporal reframing on transaction evaluation. Journal of Consumer Research. 1998; 24 (4):395–408. doi: 10.1086/209517. [ CrossRef ] [ Google Scholar ]
• Higgins ET. Promotion and prevention: regulatory focus as a motivational principle. Advances in Experimental Social Psychology. 1998; 30 :1–46. [ Google Scholar ]
• Howard JA, Sheth J. The theory of buyer behavior. New York: Wiley; 1969. [ Google Scholar ]
• Huber J, Payne JW, Puto C. Adding asymmetrically dominated alternatives: violations of regularity and the similarity hypothesis. Journal of Consumer Research. 1982; 9 (1):90–98. doi: 10.1086/208899. [ CrossRef ] [ Google Scholar ]
• Humphreys A, Wang RJH. Automated text analysis for consumer research. Journal of Consumer Research. 2018; 44 (6):1274–1306. doi: 10.1093/jcr/ucx104. [ CrossRef ] [ Google Scholar ]
• Iyengar, S. S., & Lepper, M. R. (2000). When choice is demotivating: can one desire too much of a good thing? Journal of Personality and Social Psychology, 79 (6), 995–1006. [ PubMed ]
• Johnson EJ, Shu SB, Dellaert BG, Fox C, Goldstein DG, Häubl G, et al. Beyond nudges: tools of a choice architecture. Marketing Letters. 2012; 23 (2):487–504. doi: 10.1007/s11002-012-9186-1. [ CrossRef ] [ Google Scholar ]
• Kruglanski AW, Shah JY, Fishbach A, Friedman R, Chun WY, Sleeth-Keppler D. A theory of goal systems. Advances in Experimental Social Psychology. 2002; 34 :311–378. [ Google Scholar ]
• Lancaster K. A new theory of consumer behavior. Journal of Political Economy. 1966; 74 :132–157. doi: 10.1086/259131. [ CrossRef ] [ Google Scholar ]
• Laudan L. Methodology’s prospects. In PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association. 1986; 1986 (2):347–354. [ Google Scholar ]
• Lynch Jr., J. G. (2011). Introduction to the journal of marketing research special interdisciplinary issue on consumer financial decision making. Journal of Marketing Research, 48 (SPL) Siv–Sviii.
• MacInnis DJ, Folkes VS. The disciplinary status of consumer behavior: a sociology of science perspective on key controversies. Journal of Consumer Research. 2009; 36 (6):899–914. doi: 10.1086/644610. [ CrossRef ] [ Google Scholar ]
• Markus HR, Kitayama S. Culture and the self: implications for cognition, emotion, and motivation. Psychological Review. 1991; 98 (2):224–253. doi: 10.1037/0033-295X.98.2.224. [ CrossRef ] [ Google Scholar ]
• Payne JW, Bettman JR, Johnson EJ. Adaptive strategy selection in decision making. Journal of Experimental Psychology: Learning, Memory, and Cognition. 1988; 14 (3):534–552. [ Google Scholar ]
• Prelec D, Loewenstein G. The red and the black: mental accounting of savings and debt. Marketing Science. 1998; 17 (1):4–28. doi: 10.1287/mksc.17.1.4. [ CrossRef ] [ Google Scholar ]
• Rapp JM, Hill RP. Lordy, Lordy, look who’s 40! The Journal of Consumer Research reaches a milestone. Journal of Consumer Research. 2015; 42 (1):19–29. doi: 10.1093/jcr/ucv011. [ CrossRef ] [ Google Scholar ]
• Ratchford BT. The new economic theory of consumer behavior: an interpretive essay. Journal of Consumer Research. 1975; 2 (2):65–75. doi: 10.1086/208617. [ CrossRef ] [ Google Scholar ]
• Schumann, D. W., Haugtvedt, C. P., & Davidson, E. (2008). History of consumer psychology. In Haugtvedt, C. P., Herr, P. M., & Kardes, F. R. eds.  Handbook of consumer psychology (pp. 3-28). New York: Erlbaum.
• Simonson, I. (1989). Choice based on reasons: the case of attraction and compromise effects. Journal of Consumer Research, 16 (2), 158–174.
• Trope Y, Liberman N. Construal-level theory of psychological distance. Psychological Review. 2010; 117 (2):440–463. doi: 10.1037/a0018963. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Wang X, Bendle NT, Mai F, Cotte J. The journal of consumer research at 40: a historical analysis. Journal of Consumer Research. 2015; 42 (1):5–18. doi: 10.1093/jcr/ucv009. [ CrossRef ] [ Google Scholar ]
• Wilkie WL, Moore ES. Scholarly research in marketing: exploring the “4 eras” of thought development. Journal of Public Policy & Marketing. 2003; 22 (2):116–146. doi: 10.1509/jppm.22.2.116.17639. [ CrossRef ] [ Google Scholar ]

OPINION article

Factors affecting impulse buying behavior of consumers.

• Instituto Superior de Gestão, Lisbon, Portugal

In recent years, the study of consumer behavior has been marked by significant changes, mainly in decision-making process and consequently in the influences of purchase intention ( Stankevich, 2017 ).

The markets are different and characterized by an increased competition, as well a constant innovation in products and services available and a greater number of companies in the same market. In this scenario it is essential to know the consumer well ( Varadarajan, 2020 ). It is through the analysis of the factors that have a direct impact on consumer behavior that it is possible to innovate and meet their expectations. This research is essential for marketers to be able to improve their campaigns and reach the target audience more effectively ( Ding et al., 2020 ).

Consumer behavior refers to the activities directly involved in obtaining products /services, so it includes the decision-making processes that precede and succeed these actions. Thus, it appears that the advertising message can cause a certain psychological influence that motivates individuals to desire and, consequently, buy a certain product/service ( Wertenbroch et al., 2020 ).

Studies developed by Meena (2018) show that from a young age one begins to have a preference for one product/service over another, as we are confronted with various commercial stimuli that shape our choices. The sales promotion has become one of the most powerful tools to change the perception of buyers and has a significant impact on their purchase decision ( Khan et al., 2019 ). Advertising has a great capacity to influence and persuade, and even the most innocuous, can cause changes in behavior that affect the consumer's purchase intention. Falebita et al. (2020) consider this influence predominantly positive, as shown by about 84.0% of the total number of articles reviewed in the study developed by these authors.

Kumar et al. (2020) add that psychological factors have a strong implication in the purchase decision, as we easily find people who, after having purchased a product/ service, wonder about the reason why they did it. It is essential to understand the mental triggers behind the purchase decision process, which is why consumer psychology is related to marketing strategies ( Ding et al., 2020 ). It is not uncommon for the two areas to use the same models to explain consumer behavior and the reasons that trigger impulse purchases. Consumers are attracted by advertising and the messages it conveys, which is reflected in their behavior and purchase intentions ( Varadarajan, 2020 ).

Impulse buying has been studied from several perspectives, namely: (i) rational processes; (ii) emotional resources; (iii) the cognitive currents arising from the theory of social judgment; (iv) persuasive communication; (v) and the effects of advertising on consumer behavior ( Malter et al., 2020 ).

The causes of impulsive behavior are triggered by an irresistible force to buy and an inability to evaluate its consequences. Despite being aware of the negative effects of buying, there is an enormous desire to immediately satisfy your most pressing needs ( Meena, 2018 ).

The importance of impulse buying in consumer behavior has been studied since the 1940's, since it represents between 40.0 and 80.0% of all purchases. This type of purchase obeys non-rational reasons that are characterized by the sudden appearance and the (in) satisfaction between the act of buying and the results obtained ( Reisch and Zhao, 2017 ). Aragoncillo and Orús (2018) also refer that a considerable percentage of sales comes from purchases that are not planned and do not correspond to the intended products before entering the store.

According to Burton et al. (2018) , impulse purchases occur when there is a sudden and strong emotional desire, which arises from a reactive behavior that is characterized by low cognitive control. This tendency to buy spontaneously and without reflection can be explained by the immediate gratification it provides to the buyer ( Pradhan et al., 2018 ).

Impulsive shopping in addition to having an emotional content can be triggered by several factors, including: the store environment, life satisfaction, self-esteem, and the emotional state of the consumer at that time ( Gogoi and Shillong, 2020 ). We believe that impulse purchases can be stimulated by an unexpected need, by a visual stimulus, a promotional campaign and/or by the decrease of the cognitive capacity to evaluate the advantages and disadvantages of that purchase.

The buying experience increasingly depends on the interaction between the person and the point of sale environment, but it is not just the atmosphere that stimulates the impulsive behavior of the consumer. The sensory and psychological factors associated with the type of products, the knowledge about them and brand loyalty, often end up overlapping the importance attributed to the physical environment ( Platania et al., 2016 ).

The impulse buying causes an emotional lack of control generated by the conflict between the immediate reward and the negative consequences that the purchase can originate, which can trigger compulsive behaviors that can become chronic and pathological ( Pandya and Pandya, 2020 ).

Sohn and Ko (2021) , argue that although all impulse purchases can be considered as unplanned, not all unplanned purchases can be considered impulsive. Unplanned purchases can occur, simply because the consumer needs to purchase a product, but for whatever reason has not been placed on the shopping list in advance. This suggests that unplanned purchases are not necessarily accompanied by the urgent desire that generally characterizes impulse purchases.

The impulse purchases arise from sensory experiences (e.g., store atmosphere, product layout), so purchases made in physical stores tend to be more impulsive than purchases made online. This type of shopping results from the stimulation of the five senses and the internet does not have this capacity, so that online shopping can be less encouraging of impulse purchases than shopping in physical stores ( Moreira et al., 2017 ).

Researches developed by Aragoncillo and Orús (2018) reveal that 40.0% of consumers spend more money than planned, in physical stores compared to 25.0% in online purchases. This situation can be explained by the fact that consumers must wait for the product to be delivered when they buy online and this time interval may make impulse purchases unfeasible.

Following the logic of Platania et al. (2017) we consider that impulse buying takes socially accepted behavior to the extreme, which makes it difficult to distinguish between normal consumption and pathological consumption. As such, we believe that compulsive buying behavior does not depend only on a single variable, but rather on a combination of sociodemographic, emotional, sensory, genetic, psychological, social, and cultural factors. Personality traits also have an important role in impulse buying. Impulsive buyers have low levels of self-esteem, high levels of anxiety, depression and negative mood and a strong tendency to develop obsessive-compulsive disorders. However, it appears that the degree of uncertainty derived from the pandemic that hit the world and the consequent economic crisis, seems to have changed people's behavior toward a more planned and informed consumption ( Sheth, 2020 ).

Author Contributions

All authors listed have made a substantial, direct and intellectual contribution to the work, and approved it for publication.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Aragoncillo, L., and Orús, C. (2018). Impulse buying behaviour: na online-offline comparative and the impact of social media. Spanish J. Market. 22, 42–62. doi: 10.1108/SJME-03-2018-007

CrossRef Full Text | Google Scholar

Burton, J., Gollins, J., McNeely, L., and Walls, D. (2018). Revisting the relationship between Ad frequency and purchase intentions. J. Advertising Res. 59, 27–39. doi: 10.2501/JAR-2018-031

Ding, Y., DeSarbo, W., Hanssens, D., Jedidi, K., Lynch, J., and Lehmann, D. (2020). The past, present, and future of measurements and methods in marketing analysis. Market. Lett. 31, 175–186. doi: 10.1007/s11002-020-09527-7

Falebita, O., Ogunlusi, C., and Adetunji, A. (2020). A review of advertising management and its impact on consumer behaviour. Int. J. Agri. Innov. Technol. Global. 1, 354–374. doi: 10.1504/IJAITG.2020.111885

Gogoi, B., and Shillong, I. (2020). Do impulsive buying influence compulsive buying? Acad. Market. Stud. J. 24, 1–15.

Google Scholar

Khan, M., Tanveer, A., and Zubair, S. (2019). Impact of sales promotion on consumer buying behavior: a case of modern trade, Pakistan. Govern. Manag. Rev. 4, 38–53. Available online at: https://ssrn.com/abstract=3441058

Kumar, A., Chaudhuri, S., Bhardwaj, A., and Mishra, P. (2020). Impulse buying and post-purchase regret: a study of shopping behavior for the purchase of grocery products. Int. J. Manag. 11, 614–624. Available online at: https://ssrn.com/abstract=3786039

Malter, M., Holbrook, M., Kahn, B., Parker, J., and Lehmann, D. (2020). The past, present, and future of consumer research. Market. Lett. 31, 137–149. doi: 10.1007/s11002-020-09526-8

PubMed Abstract | CrossRef Full Text | Google Scholar

Meena, S. (2018). Consumer psychology and marketing. Int. J. Res. Analyt. Rev. 5, 218–222.

Moreira, A., Fortes, N., and Santiago, R. (2017). Influence of sensory stimuli on brand experience, brand equity and purchase intention. J. Bus. Econ. Manag. 18, 68–83. doi: 10.3846/16111699.2016.1252793

Pandya, P., and Pandya, K. (2020). An empirical study of compulsive buying behaviour of consumers. Alochana Chakra J. 9, 4102–4114.

Platania, M., Platania, S., and Santisi, G. (2016). Entertainment marketing, experiential consumption and consumer behavior: the determinant of choice of wine in the store. Wine Econ. Policy 5, 87–95. doi: 10.1016/j.wep.2016.10.001

Platania, S., Castellano, S., Santisi, G., and Di Nuovo, S. (2017). Correlati di personalità della tendenza allo shopping compulsivo. Giornale Italiano di Psicologia 64, 137–158.

Pradhan, D., Israel, D., and Jena, A. (2018). Materialism and compulsive buying behaviour: the role of consumer credit card use and impulse buying. Asia Pacific J. Market. Logist. 30,1355–5855. doi: 10.1108/APJML-08-2017-0164

Reisch, L., and Zhao, M. (2017). Behavioural economics, consumer behaviour and consumer policy: state of the art. Behav. Public Policy 1, 190–206. doi: 10.1017/bpp.2017.1

Sheth, J. (2020). Impact of Covid-19 on consumer behavior: will the old habits return or die? J. Bus. Res. 117, 280–283. doi: 10.1016/j.jbusres.2020.05.059

Sohn, Y., and Ko, M. (2021). The impact of planned vs. unplanned purchases on subsequent purchase decision making in sequential buying situations. J. Retail. Consumer Servic. 59, 1–7. doi: 10.1016/j.jretconser.2020.102419

Stankevich, A. (2017). Explaining the consumer decision-making process: critical literature review. J. Int. Bus. Res. Market. 2, 7–14. doi: 10.18775/jibrm.1849-8558.2015.26.3001

Varadarajan, R. (2020). Customer information resources advantage, marketing strategy and business performance: a market resources based view. Indus. Market. Manag. 89, 89–97. doi: 10.1016/j.indmarman.2020.03.003

Wertenbroch, K., Schrift, R., Alba, J., Barasch, A., Bhattacharjee, A., Giesler, M., et al. (2020). Autonomy in consumer choice. Market. Lett. 31, 429–439. doi: 10.1007/s11002-020-09521-z

Keywords: consumer behavior, purchase intention, impulse purchase, emotional influences, marketing strategies

Citation: Rodrigues RI, Lopes P and Varela M (2021) Factors Affecting Impulse Buying Behavior of Consumers. Front. Psychol. 12:697080. doi: 10.3389/fpsyg.2021.697080

Received: 19 April 2021; Accepted: 10 May 2021; Published: 02 June 2021.

Reviewed by:

Copyright © 2021 Rodrigues, Lopes and Varela. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Rosa Isabel Rodrigues, rosa.rodrigues@isg.pt

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

Understanding the ever-evolving, always-surprising consumer

For many consumers around the world, a return to normalcy feels so close, yet so far away, in light of the alarming spread of COVID-19 variants. Although it’s unclear what the next 12 to 24 months will bring, what’s almost certain is that consumers won’t simply revert to doing exactly what they did in 2019. In this episode of the McKinsey on Consumer and Retail podcast, three consumer-behavior experts share their insights into how consumers’ spending patterns and purchasing behaviors are changing, and what companies should do given those changes. An edited transcript of the conversation with executive editor Monica Toriello follows. Subscribe to the podcast .

Monica Toriello: Over the past several weeks, people in some parts of the world have resumed their prepandemic habits. Maybe you’ve recently seen a movie at a theater, or flown on an airplane, or even just stopped for a cup of coffee on your way to the office for the first time in over a year. But a return to “normal” won’t look the same for everyone. Today, we’ll hear from three people who intensively study consumer behavior. They’ll share fascinating insights into how consumers are changing and what companies should do about it.

Kari Alldredge is a McKinsey partner based in Minneapolis. Kari has been advising consumer-goods companies for more than 20 years on a variety of topics, and she leads McKinsey’s work in consumer-goods growth transformation. She is an author of several articles, including a recent one on COVID-19’s impact on demand and costs in the consumer-packaged-goods [CPG] industry .

Anne Grimmelt is a senior knowledge expert in McKinsey’s Consumer Packaged Goods Practice. She is based in Stamford, Connecticut. Anne has been one of the driving forces behind McKinsey’s consumer-sentiment survey , which was launched in 2008 and during the pandemic has expanded to 45 countries. It provides a rich fact base for how consumers are feeling about their finances and how their buying behavior is changing.

And our third guest is Anjali Lai, a senior analyst at Forrester. Anjali, who is based in New York, helps chief marketing officers [CMOs] and other business leaders to understand the shifts in consumer behavior and consumer decision making and then to figure out what these changes mean for the future of brands and industries.

[To comply with Forrester’s Citation Policy, this transcript excludes Anjali Lai’s comments. Listen to the full episode on McKinsey.com or on Apple, Google, and other podcast platforms.]

A ‘reversal of fortune’ for big brands

Monica Toriello: Kari, Anne, Anjali, it’s great to have you here today. All three of you have been keeping your fingers on the pulse of consumers, both before and throughout the pandemic. Have there been any surprises? Are consumers doing things that you didn’t expect? Or is there anything that seemed to be going one way in, say, March or April 2020 but is going in a different direction today?

Kari Alldredge: In 2019 or early 2020, the topic on the minds of large branded consumer-packaged-goods manufacturers was portfolio shaping: how to reimagine their portfolios, how to move away from center-of-store food products and big brands and instead engage with consumers in very different, more targeted, niche-oriented ways. The degree to which the pandemic pushed people back toward big brands in the center of the store, and toward cooking at home, has been a complete turnaround, a reversal of fortune, for large CPG companies.

Some of those changes could have been anticipated, but others are quite shocking: the notion that bread baking would become a phenomenon among millennials, or that pet ownership would skyrocket to the extent that it has, and that those same millennials would be willing to spend more than they spend on their daily Starbucks to feed their new pets.

So, many of those companies that were desperately searching for growth 18 months ago now have the opposite problem: their supply chains can’t keep up . The big question for all of them is which of those consumer behaviors are truly going to persist  and be “sticky” coming out of this pandemic? Certainly, the dog that you adopted is likely to stay at your home. But when you go back to ordering your daily Starbucks and spending $7 a day on a coffee, are you going to spend the same amount to feed your pet? Those are the questions that are on many company leaders’ minds.

Anne Grimmelt: As Kari said, we saw a complete shift. Prepandemic, the growth was in smaller, niche brands, but early in the pandemic, it was large CPG players that really gained scale because their products were available on the shelf. They were also brands that were trusted by consumers, so consumers felt good buying them. If you look at point-of-sale data from IRI or Nielsen, you see that large companies—those with more than $2.5 billion in retail sales in the US market—picked up most of the share growth early in the pandemic, whereas smaller and midsize companies, as well as private label, were really not picking up growth.

In the second half of 2020 and in early 2021, small and midsize companies are regaining their sales growth. And we expect that private label is going to be powerful again , because if you dive into the why—why did consumers pick a new brand, and why did they pick the brands they chose?—it was about availability, it was about purpose, but it was also about value . It was about price points. Going forward, value is going to be even more important, and private label will gain strength in the future.

Trust as a strategic imperative

Monica Toriello: All three of you to some extent have written about customer loyalty: how to win it and how to retain it, particularly in an environment where people are willing to try new brands. Anne and Kari, you found that 39 percent of consumers tried new brands during the pandemic. And Anjali, in your research, you found that small brands are particularly good at earning consumers’ trust and consequently their loyalty. In a recent blog post, you wrote, “Now is the time for companies to embrace trust as a strategic imperative.” What does that mean? How should companies do that?

Even relatively mundane CPG companies are thinking about the end-to-end consumer journey, including consumer experience pre- and postpurchase. Kari Alldredge

Kari Alldredge: I’m seeing two interesting things in response to the trends you just talked about, Anjali. One is the degree to which even relatively mundane CPG companies are thinking about the end-to-end consumer journey, including consumer experience pre- and postpurchase, as they try to understand how to serve their existing consumers but also look for new ways to better meet consumer needs. The notion that there is a pre- and postpurchase experience related to a can of soda or a can of soup is a relatively novel idea, right? But, increasingly, the most forward-thinking companies are doing research across that entire journey to be able to understand the needs of consumers as they’re considering the range of options that are available to them—all the way through to satisfaction with usage and even disposal of the packaging of products.

Another interesting thing I’m seeing is a recognition that marketing is a dialogue, and a recognition of the degree to which consumers now “own” or shape the narratives of many brands. This, too, was happening before the pandemic but was vastly accelerated during the pandemic. The notion that a marketer positions the brand and delivers a message and a promise to consumers is really becoming quite an antiquated one, I think, as consumers themselves—through reviews, ratings , blogs, videos, and social-media posts—shape the identity of many of these brands. Recommendations from friends and family become part of the brand’s identity and are critical to shaping both loyalty and consumer trust.

We found in our research that about 33 percent of millennial and Gen Z consumers say they choose to buy a brand from a company that has their values, versus about 12 percent of baby boomers. Anne Grimmelt

Anne Grimmelt: Our research corroborates that. We found in our research that about 33 percent of millennial and Gen Z consumers  say they choose to buy a brand from a company that has their values, versus about 12 percent of baby boomers. But every demographic group is leaning toward that.

Another finding from our research is the reasons why consumers change to a new brand. It is definitely the younger generation that more often indicates that it’s because of purpose. It’s because of what the company stands for, how it treats its employees, et cetera.

Purpose: More than just a buzzword

Monica Toriello: We’ve been hearing a lot about purpose and values, but I also hear some skepticism in certain pockets of the corporate world as to whether an emphasis on corporate purpose  actually pays off. Because there is an attitude–behavior gap, right? What’s your response to a CEO who says, “Consumers like to say they care about purpose and values, but when they’re at the point of deciding to buy something, they truly only care about convenience or price or quality. Purpose is just a buzzword.”

Kari Alldredge: It’s necessary but not sufficient. I think there’s an increasing recognition that alignment with a consumer’s values may put you in the consideration set but won’t drive you over the line to purchase. You still have to have product superiority, whether that’s taste superiority, functional superiority, or a price-to-value equation that works for that particular consumer.

We talk a lot about the pandemic, which definitely shone a light on health in general, but there are other crises—like social justice  and climate change —that have come to light over the past year and a half and that have really shaken the corporate community. These crises have helped companies understand that some of these factors are fundamental in how consumers perceive themselves and the world around them, to the point where we now actually see some change happening.

One of the things that I was struck by was the speed and seriousness with which many of the household-cleaning companies responded to the pandemic and the heroic efforts to convert production capacity to manufacture things like wipes and sanitizer. Yes, some of that was for financial gain, but I think there really was an almost wartime mentality that I saw companies get new energy from.

I think about center-of-store food manufacturers who, prepandemic, maybe viewed themselves as being a bit sleepy and not exciting in terms of attracting the best talent. Now when you hear them talk about what they do, there’s real pride in the fact that they fed America, or they kept America safe. It really changed the way they think about the importance of what they do.

Subscribe to the McKinsey on Consumer and Retail podcast

Sources of insight.

Monica Toriello: All three of you are experts in consumer behavior. But consumers are changing fast and they’re changing constantly. Anjali, in another recent blog post, you wrote, “Rather than expect consumers to settle into a defined postpandemic normal, CMOs should prepare for a constant evolution of consumer needs and expectations over the next 12 to 24 months.” So beyond reading the latest consumer research and analysis, what are the best ways for CMOs and CEOs to understand where consumers are and where they’re headed?

Kari Alldredge: One of the best sources of insights is their online channel partners and their own D2C [direct to consumer] sites . Companies should mine online data to get a quick pulse on the way consumers are thinking or feeling. They should look at ratings and reviews using advanced analytics to understand and see trends and what’s selling on sites like Kroger.com, Walmart.com, or Amazon.com. They could even develop products that they can quickly test in an online environment and then change and adjust, as opposed to thinking about mass development of a product that gets pushed out to thousands and thousands of brick-and-mortar retail stores.

Consumers don’t always know what they want, and they can’t predict how their behavior will change. So traditional consumer research—which asks consumers how likely they are to purchase something—is becoming less relevant or reliable than actual data in market. That’s why data from e-commerce sites can be so valuable.

Anne Grimmelt: Another very powerful way to understand consumers  is by looking at what your peer companies do. You can go to industry conferences like the CAGNY [Consumer Analyst Group of New York] conference and hear a company like L’Oréal talk about how they use their D2C and their online-sales platform to see what type of color lipstick people try—not buy , but try —on their online platform. That information is critical for them to know where to innovate. What are the colors that people want and what are the products that people like to try out on the digital platform?

Similarly, I think it’s very important to keep an open mind beyond your own borders, to realize what’s happening elsewhere in the world. Going back to the topic of purpose, for instance, it is very much alive in the US but it’s also very much alive in Europe. Learning about the power of what consumers demand and how purpose is driving consumer decisions about CPG companies—and what companies in Europe are doing to meet consumer demand—can be valuable, wherever you are in the world.

Kari Alldredge: I think we also shouldn’t underestimate the resilience of consumers and the gravitational pull of life as we knew it before the pandemic. One thing that surprised me even in the past several weeks is the degree to which behaviors have bounced back. If there’s anything I’ve learned over the past 18 months it’s that I don’t have a crystal ball, or if I did, it is certainly broken—because there is no part of this last 18 months that I ever could have in a million years predicted.

At the beginning of the pandemic, one company I work with asked every board member, “When you look back, what’s the one thing that will be blazingly obvious that we either should always have done or never have been doing?” And one of the things that came up was shaking hands: “We’re never going to shake hands again.” But I attended a graduation ceremony in the beginning of June—so, early into the recovery—and what was striking to me is that the dean of that school shook the hand of, and physically embraced, every single one of the thousand students who crossed that stage. And this was at an institution that had been, like most educational institutions, incredibly thoughtful and conservative about their public-health response. Literally days after restrictions were lifted, the urge to connect was so strong that it looked as if the pandemic had never happened.

People are resilient. Hundreds of years of behavior certainly have been meaningfully changed by the past 18 months, but I think a lot of the old behaviors will bounce back pretty quickly.

Monica Toriello: So if you could gather all the CEOs and CMOs of consumer companies in one room and leave them with one message, what would it be? What is the one thing they need to do to position themselves for success in 2021 and 2022?

Anne Grimmelt: My one-liner would be, “Be open to change and be agile .”

Kari Alldredge: I would say, “Listen; don’t tell.”

Kari Alldredge is a partner in McKinsey’s Minneapolis office, and  Anne Grimmelt is a senior knowledge expert in the Stamford office.  Monica Toriello is an executive editor in the New York office.

Explore a career with us

Related articles.

McKinsey on Consumer and Retail Podcast: Insights from experts on business and management

Global surveys of consumer sentiment during the coronavirus crisis

COVID-19’s impact on demand and costs in the CPG industry