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Digital transformation: a review, synthesis and opportunities for future research

• Open Access
• Published: 18 April 2020
• volume  71 ,  pages 233–341 ( 2021 )

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• Swen Nadkarni 1 &
• Reinhard Prügl 1  

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In the last years, scholarly attention was on a steady rise leading to a significant increase in the number of papers addressing different technological and organizational aspects of digital transformation. In this paper, we consolidate existing findings which mainly stem from the literature of information systems, map the territory by sharing important macro- and micro-level observations, and propose future research opportunities for this pervasive field. The paper systematically reviews 58 peer-reviewed studies published between 2001 and 2019, dealing with different aspects of digital transformation. Emerging from our review, we develop inductive thematic maps which identify technology and actor as the two aggregate dimensions of digital transformation. For each dimension, we derive further units of analysis (nine core themes in total) which help to disentangle the particularities of digital transformation processes and thereby emphasize the most influential and unique antecedents and consequences. In a second step, in order to assist in breaking down disciplinary silos and strengthen the management perspective, we supplement the resulting state-of-the-art of digital transformation by integrating cross-disciplinary contributions from reviewing 28 papers on technological disruption and 32 papers on corporate entrepreneurship. The review reveals that certain aspects, such as the pace of transformation, the culture and work environment, or the middle management perspective are significantly underdeveloped.

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1 introduction.

Digital transformation, defined as transformation ‘concerned with the changes digital technologies can bring about in a company’s business model, … products or organizational structures’ (Hess et al. 2016 , p. 124), is perhaps the most pervasive managerial challenge for incumbent firms of the last and coming decades. However, digital possibilities need to come together with skilled employees and executives in order to reveal its transformative power. Thus, digital transformation needs both technology and people. In the last years, scholarly attention, particularly in the information systems (IS) literature, was on a steady rise leading to a significant increase in the number of papers addressing different technological and organizational aspects of digital transformation. In the light of this development, we are convinced it is the right time to map the territory and reflect on the current state of knowledge. Therefore, in this paper we aim at providing a descriptive, thematic analysis of the field by critically assessing where, how and by whom research on digital transformation is conducted. Based on this analysis, we identify future research opportunities.

We approach this objective in two steps. First, we adopt an inductive approach and conduct a systematic literature review (following Tranfield et al. 2003 ; Webster and Watson 2002 ) of 58 peer-reviewed papers dealing with digital transformation. By applying elements of grounded theory and content analysis (Corley and Gioia 2004 ; Gioia et al. 1994 ) we identify important core themes in the literature that are particularly pronounced and/or unique in transformations enabled by digital technologies. In a second step, in order to assist in breaking down disciplinary silos (Jones and Gatrell 2014 ) and avoiding the building of an ivory tower (Bartunek et al. 2006 ; Fuetsch and Suess-Reyes 2017 ), we supplement the pre-dominantly IS-based digital transformation literature with a broader management perspective. Accordingly, we integrate cross-disciplinary contributions from reviewing 28 papers on technological disruption and 32 papers on corporate entrepreneurship.

We find these research fields particularly suitable for informing digital transformation research for two reasons. First, by reviewing the literature on technological disruption we hope to derive implications regarding technology adoption and integration. Burdened with the legacy of old technology, bureaucratic structures and core rigidities (Leonard-Barton 1992 ), incumbents may face major challenges in this respect during their digital transformation journey. Second, we expect corporate entrepreneurship to add a more holistic perspective on firm-internal aspects during the process of transformation, such as management influence or the impact of knowledge and organizational learning.

Our findings and related contributions are threefold: First, based on a systematic and structured analysis we develop digital transformation maps which inductively categorize and describe the existing body of research. These thematic maps identify technology and actor as the two aggregate dimensions of digital transformation. Within these dimensions, we reveal nine core themes which help to disentangle the particularities of digital transformation processes and thereby emphasize the most influential and unique antecedents and consequences of this specific type of transformation. Thus, it becomes possible to identify the predominant contextual factors for which research would create the strongest leverage for a better understanding of the challenges inherent in digital transformation. Second, we contribute to the advancement of this field by elaborating opportunities for future research on digital transformation which integrate the three perspectives mentioned above. In particular, informed by corporate entrepreneurship, we find that the important middle management perspective on digital transformation has thus far been largely neglected by researchers. Also, emerging from our review we call for more studies on the various options for integrating digital transformation within organizational architectures and existing processes. Third, in reviewing the adjacent literature on technological disruption and corporate entrepreneurship, we strengthen the valuable management perspective within the primarily IS-based discussion on digital transformation. This way we avoid the reinvention of the wheel while at the same time enable the identification of cross-disciplinary research opportunities. We hope to stimulate discussion between these different but strongly related disciplines and enable mutual learning and a fruitful exchange of ideas.

2 Conceptual foundations

Technology as a major determinant of organizational form and structure has been well acknowledged by academics for a long time (Thompson and Bates 1957 ; Woodward 1965 ; Scott 1992 ). Following a significant decline of interest in this relationship until the mid-1990s (Zammuto et al. 2007 ), innovations in information technologies (IT) and the rise of pre-internet technologies have revitalized its relevance in the context of organizational transformation. Thus, the literature on IT-enabled organizational transformation, a concept which originates from the field of information systems (IS) that has caught considerable academic attention starting back in the early 1990s (Ranganathan et al. 2004 ; Besson and Rowe 2012 ), may be seen as one of the scholarly roots of digital transformation research. In his seminal book, Morton ( 1991 ) argued that companies must experience fundamental transformations for effective IT implementation. In the course of the years a shift of attention occurred from technological to managerial and organizational issues (Markus and Benjamin 1997 ; Doherty and King 2005 ). Non-technological aspects such as leadership, culture, and employee training were found to be equally important for successful IT-enabled transformation (Markus 2004 ). This is supported by Orlikowski ( 1996 ) who found empirical evidence from a 2-year case study that organizational transformation was in fact enabled by technology, but not caused by it.

Today, information technologies have become ‘one of the threads from which the fabric of organization is now woven’ (Zammuto et al. 2007 , p. 750). Digital technologies are considered a major asset for leveraging organizational transformation, given their disruptive nature and cross-organizational and systemic effects (Besson and Rowe 2012 ). In order to achieve successful digital transformation, changes must occur at various levels within the organization, including an adaptation of the core business (Karimi and Walter 2015 ), the exchange of resources and capabilities (Cha et al. 2015 ; Yeow et al. 2018 ), the reconfiguration of processes and structures (Resca et al. 2013 ), adjustments in leadership (Hansen and Sia 2015 ; Singh and Hess 2017 ), and the implementation of a vivid digital culture (Llopis et al. 2004 ). Therefore, the scope of our review revolves around digital transformation at the organizational level only (in contrast to implications at the individual level).

In this study, we conceptualize digital transformation at the intercept of the adoption of disruptive digital technologies on the one side and actor-guided organizational transformation of capabilities, structures, processes and business model components on the other side. In other words, and in line with Hess et al. ( 2016 ), we define digital transformation as organizational change triggered by digital technologies. Hence, we argue that two perspectives of digital transformation within organizations must be captured: a technology-centric and an actor-centric perspective. To exploit the technology-centric perspective we include the literature on technological disruption (e.g. Tushman and Anderson 1986 ; Anderson and Tushman 1990 ) and merge it with research on digital transformation. For the actor-centric perspective, we derive essential implications from the field of corporate entrepreneurship (Guth and Ginsberg 1990 ), which we believe may add valuable insights regarding actor-driven innovation and renewal processes within firms. In the following, we offer a brief introduction to both concepts and their relationship with digital transformation.

Rice et al. ( 1998 ) define disruptive innovations as ‘game changers’ which have the potential ‘(1) for a 5–10 times improvement in performance compared to existing products; (2) to create the basis for a 30–50% reduction in costs; or (3) to have new-to-the world performance features’ (p. 52). Similarly, Utterback ( 1994 ) emphasizes this disruptiveness at the firm and industry level and provides a similar ‘game changer’ definition in terms of ‘change that sweeps away much of a firm’s existing investment in technical skills and knowledge, designs, production technique, plant and equipment’ (p. 200). Tushman and Anderson ( 1986 ) distinguish between product and process disruptiveness. Product disruptiveness encompasses new product classes, product substitutions, or fundamental product improvements. Process disruptiveness may take the form of process substitutions or process innovations which radically improve industry-specific dimensions of merit. Christensen and Raynor ( 2003 ) introduce a further form of disruptive innovations, namely disruptive business model innovations, which represent the implementation of fundamentally different business models in an existing business.

We argue that digital technologies may reflect in all of these definitions of disruptive innovation. They may represent new-to-the-world product innovations, dislocate existing processes, and open up entirely new business models. As resumed in a recent study by Li et al. ( 2017 ), e-commerce for instance is defined as a disruptive technology (Johnson 2010 ) which involves significant changes to an organization’s culture, business processes, capabilities, and markets (Zeng et al. 2008 ; Cui and Pan 2015 ).

Corporate entrepreneurship (CE) on the other side is a multi-dimensional concept at the intersection of entrepreneurship and strategic management in existing organizations (Zahra 1996 ; Hitt et al. 2001 ; Dess et al. 2003 ). We adopt the conceptualization proposed by Guth and Ginsberg ( 1990 , p. 5), who argue that corporate entrepreneurship deals with two phenomena ‘(1) the birth of new businesses within existing organizations, i.e. internal innovation or venturing, and (2) the transformation of organizations through renewal of the key ideas on which they are built, i.e. strategic renewal.’ Particularly the aspect of strategic renewal in corporate entrepreneurship, also labelled as strategic change, revival, transformation (Schendel 1990 ), reorganization, redefinition (Zahra 1993 ), or organizational renewal (Stopford and Baden-Fuller 1994 ), provides a promising interface to digital transformation. As stated by Covin and Miles ( 1999 , p. 50), corporate entrepreneurship ‘revitalizes, reinvigorates and reinvents’—processes also required for digital transformation. Various authors have stated that corporate entrepreneurship is a vehicle to improve competitive positioning and transform corporations (Schollhammer 1982 ; Miller 1983 ; Khandwalla 1987 ; Guth and Ginsberg 1990 ; Naman and Slevin 1993 ; Lumpkin and Dess 1996 ). Considering the disruptive nature of many current digital technologies, we believe that organizations need to fundamentally renew and redefine the key ideas of their business in order to fully exploit the potential of digitization and eventually achieve successful transformation. The literature places particular attention on the role of middle managers as the locus of corporate entrepreneurship (Burgelman 1983 , Floyd and Wooldridge 1999 ). Concluding, we will review the research on corporate entrepreneurship and identify those contributions which we believe may offer valuable knowledge regarding actor-driven internal renewal and change processes in the light of digital transformation.

Our review of the literature on digital transformation, technological disruption and corporate entrepreneurship is conducted in a two-step approach. First, we review, analyze and synthesize existing articles on digital transformation. Then, in a second step we supplement these findings be simultaneously reviewing the literature stream on technological disruption and corporate entrepreneurship. We believe a separate analysis and contrasting of the research streams is appropriate for two reasons: first, it provides the reader with more clarity on the status quo of digital transformation knowledge and prevents the confusion of concepts emerging from different literature fields. Second, white spots and opportunities for future research regarding digital transformation become much more visible in such a structured approach.

3 Research methodology

A systematic review is a type of literature review that applies an explicit algorithm and a multi-stage review strategy in order to collect and critically appraise a body of research studies (Mulrow 1994 ; Pittaway et al. 2004 ; Crossan and Apaydin 2010 ). This transparent and reproducible process is ideally suited for analyzing and structuring the vast and heterogeneous literature on digital transformation. In conducting our review, we followed the guidelines of Tranfield et al. ( 2003 ) and the recommendations of Denyer and Neely ( 2004 , p. 133) Footnote 1 as well as Fisch and Block ( 2018 ) in order to ensure a high quality of the review.

The nature of our review is both scoping and descriptive (Rowe 2014 ; Paré et al. 2015 ) as we aim to provide an initial indication of the potential size and nature of the available literature as well as to summarize and map existing findings from digital transformation research. By developing opportunities for future research, our review further contributes to the advancement of this field and stimulates theory development.

For the purpose of data collection, we exclusively limit our focus on peer-reviewed academic journals as recommended by McWilliams et al. ( 2005 ). Thus, we opted to exclude work in progress, conference papers, dissertations, or books. First, based on discussion among the authors and the reading of a few highly-cited papers, we designed our search criteria using combinations of keywords containing ‘ digital* AND transform*’ , ‘ digital* AND disrupt*’ , ‘ digitalization’ , and ‘ digitization ’. Then, we manually searched each issue of each volume of the leading journals in the management Footnote 2 and IS field (AIS Basket of eight). Footnote 3 In addition, we run our search query against five different electronic databases: Business Source Premier (EBSCO) , Scopus , Science Direct , Social Sciences Citation Index (SSCI) , and Google Scholar . We used all years available and only included articles referring to business, management, or economics in order to exclude irrelevant publications. We abstained from including digital innovation in our search (the only exception in our sample is a recent literature review by Kohli and Melville ( 2019 ), in order to capture consolidated insights). Although we realize that it is a hot topic in IS research at the moment (e.g. Fichman et al. 2014 ; Nambisan et al. 2017 ; Yoo et al. 2010 , 2012 ), we aim to concentrate our focus on papers dealing with digital transformation on a broader level (firm and industry), rather than with transitions within innovation management.

Our first search query was conducted mid 2017 and yielded an initial sample of 1722 publications. This very large sample was mainly due to the broad ambiguity of the terms ‘digital’ and ‘disrupt’. Given these broad search parameters, we anticipated that only a small fraction of this very large sample would prove to be of substantive relevance to us. To select these relevant articles for our final sample, we performed a predefined and structured multi-step selection process (similar to the approach of Siebels and Knyphausen-Aufseß 2012 ; Vom Brocke et al. 2015 ) and defined specific criteria for inclusion (Templier and Paré 2015 ). The filters during our selection process included (1) scanning the titles, (2) reading abstracts, (3) removing duplicates, (4) full reading and in-depth analysis of the remaining papers, and finally (5) cross-referencing and backward searching by looking through the bibliographies of the most important articles to find additional relevant work. The initial pool was split in half between two panelists who separately performed the scanning of titles, analysis of abstracts and removal of duplicates. After these early steps, the sample could be narrowed down to 155 articles. As we arrived at step 4 “full reading and in-depth analysis of the remaining papers”, both panelists read and independently classified each of the remaining 155 studies. During this process, papers qualified for the final sample if they satisfied three requirements: (1) articles were required to have their primary focus and contribution within digital transformation research or digitally-induced organizational transformation (e.g. a vast number of papers inadequately captured the topic of digital transformation as they primarily focused on business model innovation), (2) articles needed to be based on a sound theoretical foundation and therefore not primarily practitioner oriented (such as articles that offer popular recommendations to business leaders on how to survive digital transformation), (3) papers that were not addressing digital transformation at an organizational level (e.g. the rise of home-based online businesses by entrepreneurs) were dismissed. Whenever disagreements emerged regarding the inclusion or classification of an article, we engaged in discussion and tried to resolve the issue together to make our selection rules more reliable. We updated the review in the autumn of 2018 for any articles that had appeared between then. Following this approach, 58 studies passed all five selection steps and were included in our final sample.

Within this sample, conceptual articles (27) and case studies (20) are dominant. Roughly 60% of the articles stem from the IS literature, while 40% cover a broader management perspective of digital transformation. While the reviewed papers span a time frame from 2001 to 2018, approximately eighty-percent of articles were published within the past 5 years, indicating the relative novelty of digital transformation as a research discipline. The distribution of our sample according to journals is provided in Table  4 of “ Appendix ”.

Upon the recommendation of Webster and Watson ( 2002 ), our categorization and analysis of the literature was concept-centric. First, to facilitate analysis and build a basis for our initial coding, each selected paper was reviewed to determine the following database information.

(1) Article title, (2) outlet, (3) research methodology, (4) sample, (5) region, and (6) key findings (see full database in Table  5 of “ Appendix ”). Next, we started coding our sample, adopting elements of the approach introduced by Corley and Gioia ( 2004 ). We began by identifying initial concepts in the data and grouping them into provisional categories and first order concepts (open coding). Then, we engaged in axial coding (Locke 2001 ) and searched for relationships and common patterns between and among these provisional categories, which allowed us to assemble them into second order themes. Finally, we assigned these second order themes to aggregate dimensions, representing the highest level of abstraction in our coding. In sum, reviewing and analyzing the extant literature, 194 coded insights were generated within the field of digital transformation: 61 first order concepts, nine second order themes, and two aggregate dimensions. The nine second order themes represent core themes across the papers, which finally constitute two aggregate dimensions: technology and actor. In conclusion, we define digital transformation as actor-driven organizational transformation triggered by the adoption of technology-driven digital disruptions. The result of the coding process is a high-level inductive map of the core themes in digital transformation research (Fig.  1 ).

Digital transformation high-level thematic map emerging from the analysis of the literature

The reviewed studies from our sample provide a rich body of knowledge regarding the specific contextual factors of digital transformation. This may be beneficial to both researchers and practitioners enabling a more comprehensive understanding of the peculiarities of digital transformation (in comparison to previous technology-driven transformations).

4.1 Macro-level findings

On a macro level, the central observation emerging from our review is that both technology- and actor-centric aspects take center stage within this debate. This is also reflected in various definitions of digital transformation provided in the sample. For example, Lanzolla and Anderson ( 2008 ) represent the technology-centric side and emphasize the diffusion of digital technologies as an enabler for transformation. Such digital technologies may include big data, mobile, cloud computing or search-based applications (White 2012 ). Similarly, Hess et al. ( 2016 ) note that digital transformation is ‘concerned with the changes digital technologies can bring about in a company’s business model, which result in changed products or organizational structures or in the automation of processes’ (p. 124). However, Hess et al. ( 2016 ) also highlight the role of actors (e.g. managers) in promoting transformation processes, while facing the challenge of simultaneously balancing the exploration and exploitation of resources. Leaders must have trust in the value and benefits of new IT technologies and support their implementation (Chatterjee et al. 2002 ).

In total, we find an almost even distribution of papers studying the two dimensions of technology and actor: 33% are technology-centric, 34% are actor-centric, and 33% of papers cover both technology and actor. However, within these two dimensions we observe a rather uneven distribution of articles by second order themes. On the technology-centric side, we find that understanding the implications of digital technologies on the consumer interface and market environment are highly active research streams. In comparison, understanding the pace of change in times of digital transformation and its direct impact on incumbents is so far comparably understudied. On the actor-centric side, our review reveals a very dominant focus on leadership and capabilities in a digital context, while in contrast company culture and work environment thus far received less recognition. We also find that the status-quo of digital transformation literature is rather diverse, in a sense that papers discuss topics across various categories of our thematic map and are therefore not restricted nor focused to a specific unit of analysis. The vast majority of articles is related to adjacent topics of digital transformation underpinning its nature as a diverse and broad field of research while again indicating its emerging nature.

In addition, we observe some degree of diversity in the theoretical foundations drawn upon. Different theories are applied by several authors to capture the context of digital transformation, e.g. alignment view, configuration theory, resource-based view, dynamic capabilities, organizational learning theory, network view or business process reengineering. It would be interesting to use other theoretical angles, for example from the literature on corporate entrepreneurship and technological disruption, in order to increase theoretical diversity. Such an exchange with different fields of research would broaden the scope of the field and help bridging an ivory divide . Finally, from a methodological perspective, we observe that actor-centric papers primarily use case studies while technology-centric studies at this point are pre-eminently conceptual. In general, the literature is scarce regarding quantitative empirical evidence. We see this as a strong indicator for the early stage of digital transformation research.

4.2 Micro-level findings: the technology-centric side of the equation

In the following, we present and discuss the most important findings of the second order themes within the technology-centric dimension. In Fig.  2 we provide a thematic map for this dimension and in Table  1 a brief summary including illustrative quotes.

Thematic map for technology-driven themes in digital transformation literature

4.2.1 Pace of change and time to market

In times of digital transformation, the speed of technological change is disproportionally accelerating with new digital capabilities being rolled out every year. The technological capability of applications such as the Internet of Things (IoT), big data, cloud computing, and mobile technologies significantly increases the overall pace of change. For example, entire industries, like the newspaper business, have been transformed and digitized within a very short period of time (Karimi and Walter 2015 ). Further, the cloud and online platforms have revolutionized the process and pace of turning an innovative idea into a business (Vey et al. 2017 ). Today, innovative ideas can be realized within days and companies set-up literally ‘overnight’. In this sense, in the digital world striving for a ‘first-mover advantage’ due to a ‘winner takes it all’ environment has become more important for incumbent firms (Grover and Kohli 2013 ) as they have much less time to respond to such threats and should not give away first-mover advantages too easily.

Moreover, pure digital companies like Facebook, Google or Amazon have substantially raised the overall time to market and speed of product launches (Bharadwaj et al. 2013 ). With continuous improvements in hardware, software and connectivity, these companies set the pace for a tightly timed series of product launches. Thus, firms in the hybrid world (digital and physical) are being put under enormous pressure to also accelerate their product introductions. In a digitally transformed market, the control of speed of product development and launches is increasingly transferred to an ‘ecosystem of innovation’ in the sense of a network of actors with complementary products and services (Bharadwaj et al. 2013 ).

4.2.2 Technology capability and integration

The technological capability and power of digital transformation applications, such as for example the Internet of Things (IoT), big data, cloud computing, and mobile technologies, is in terms of computing power, data storage and information distribution in many cases significantly higher than in previous technology-driven transformations. Earlier business transformations were mostly concerned about introducing internal management information systems such as enterprise resource planning (ERP) or customer relationship management (CRM). These transformations were usually limited to improvements to business processes within firm boundaries (see Ash and Burn 2003 ; Kauffman and Walden 2001 in: Li et al. 2017 ). But today, cross-boundary digital technologies such as IoT devices (Ng and Wakenshaw 2017 ), 3D printing (Rayna and Striukova 2016 ), and big data analytics (Dremel et al. 2017 ), drive transformations that go far beyond internal process optimizations as they potentially induce drastic changes to business models (Rayna and Striukova 2016 ), organizational strategy (Bharadwaj et al. 2013 ), corporate culture (El Sawy et al. 2016 ; Dremel et al. 2017 ; Sia et al. 2016 ), and entire industry structures (Kohli and Johnson 2011 ).

Further, the review confirms that the role and significance of data itself is changing profoundly and that personal data has become one of the most powerful assets in the digital era (Ng and Wakenshaw 2017 ). In fact, we believe the impact of the massive increase in quantity and quality of data generated every day (Bharadwaj et al. 2013 ) and the game changing power of big data analytics (Günther et al. 2017 ) are yet to be fully experienced and understood by society, economy and academics.

With regards to the process of dematerialization of tangible products and objects (e.g. CDs, books, machinery etc.), triggered by the transformative capabilities of digital technologies, the most notable insight is that intriguingly, in many cases the digital substitutes, for example e-books, offer superior performance and higher customer benefits than their physical counterparts (Loebbecke and Picot 2015 ). This, for example, is in contrast to the assumptions provided by Christensen ( 1997 ) more than 20 years ago, arguing that new disruptive technologies usually provide different values from mainstream technologies and are often initially inferior to mainstream technologies, therefore only serving niche markets in the beginning.

Finally, regarding technology integration, the current state of research emphasizes the importance of flexible IT (Cha et al. 2015 ), new enterprise platforms (El Sawy et al. 2016 ), and a strong and scalable operational backbone (Sebastian et al. 2017 ) as part of an agile digital infrastructure. The old paradigms of technology integration are not effective any more. However, in a second step we need to reach a more comprehensive understanding of ‘how’ and ‘where’ the integration of technology and transformation activities should be embedded within the organizational architectures of incumbent firms.

4.2.3 Consumer and other stakeholder interface

With regards to the customer interface, which is currently receiving the highest levels of attention by scholars, we conclude that there is some solid research particularly on changes in consumer behavior (Berman 2012 ; El Sawy et al. 2016 ; Ives et al. 2016 ; Lanzolla and Anderson 2008 ), consumer preferences (Vey et al. 2017 ) and consumer knowledge (Berman 2012 ; Granados and Gupta 2013 ). Firstly, our review confirms that in the new digital marketplace, consumers behave differently than before, and traditional marketing techniques may not apply anymore. Today there are myriad choices to easily gather information about products and services far before the actual purchase. For instance, customer buying decisions are increasingly influenced by online customer-to-customer interaction via platforms and social media, where users share products feedbacks, upload home video clips, or publish blog entries (Berman 2012 ). In this sense, digital technologies are also transforming firms’ customer-side operations (Setia et al. 2013 ) and customer engagement strategies (Sebastian et al. 2017 ). For example, reaching out to customers in a digital environment requires digital omnichannel marketing, including e.g. social media, mobile apps, and augmented reality (El Sawy et al. 2016 ). Secondly, we may note that digital technologies increasingly reduce the information asymmetries between sellers and buyers (Granados and Gupta 2013 ). In this sense, information ubiquity (Vey et al. 2017 ) and instant access to data via mobile technologies (Berman 2012 ) profoundly change the long-established seller–customer relationship. And thirdly, the current literature raises awareness for the emergence of multi-sided business models. While in the ‘old’ world, intermediaries were matching sellers and buyers, in the digital market place, intermediation increasingly takes place through the establishment of multi-sided digital platforms and networks (Bharadwaj et al. 2013 ; Evens 2010 ; Pagani 2013 ).

4.2.4 Distributed value creation and value capture

The review of the literature reveals that the value chain has become far more distributed in times of digital transformation—particularly value creation and value capture. Two major changes can be observed here: (1) digital technologies offer opportunities to customers to co-create products with the manufacturer, e.g. via digital platforms (El Sawy et al. 2016 ; Ng and Wakenshaw 2017 ), and (2) on an inter-firm level value is increasingly co-created and captured in a series of partnerships in a value network (Evens 2010 ). As Bharadwaj et al. ( 2013 ) argue, network effects are the key differentiator and driver of value creation and capture in a digital world. The focus of value creation is therefore shifting from value chain to value networks. For this purpose, companies like Google are experimenting with multi-sided business models. In such a multilayered business model, a company gives away certain products or services in one layer to capture value at a different layer (Bharadwaj et al. 2013 ). Google is giving away its Android operating system for free and captures value via the ability to control advertising on every phone that uses Android.

In more general terms, we may conclude that control of value in the digital world is less and less determined by R&D capabilities, competitors, or industry boundaries. Instead the buyer, not the seller, determines the dimensions of value that matter (Keen and Williams 2013 ). Therefore, businesses need to engage with their customers at every point in the process of value creation (Berman 2012 ). Also, the strong impact of digital technologies on incumbent’s value chains imply some degree of deviation from the classical and often analog core business. For example, new product-related competencies, platform capabilities or value architectures will be required. And, incumbents must prepare for new forms of monetization in the digitized marketplace.

4.2.5 Market environment and rules of competition

This is a rather broad and diverse categorization in our review, as it comprises technology-driven changes in the market environment. After consumer-centric aspects this research stream received the most attention by scholars in the review (on the technology-centric side). In sum, the current state of literature recognizes three major developments. First, digital transformation redefines, blurs and even dissolves existing industry boundaries which may lead to cross-industry competition (Sia et al. 2016 ; Weill and Woerner 2015 ). Dominant industry logics (Sabatier et al. 2012 ) apparently do not work anymore in times of digital transformation. The ‘new kid on the block can come out of the blue’ (Vey et al. 2017 , p. 23) and even individuals can become competitors as 3D Printing is expected to lead to a sharp increase in competition from SMEs and individual entrepreneurs (Rayna and Striukova 2016 ). And with the emergence of multi-sided business models also incumbents are starting to disrupt new markets (Weill and Woerner 2015 ). For instance, Google is disrupting the mobility sector with its self-driving car subsidiary Waymo, while Amazon has introduced AmazonFresh as a grocery delivery service which is seen as a potentially tough competitor to supermarkets. Second, with the emergence of digital platforms, networks, and ecosystems the market infrastructure becomes increasingly interconnected (Grover and Kohli 2013 ; Majchrzak et al. 2016 ; Markus and Loebbecke 2013 ). In a broader sense, we see a shift from controlling or participating in a linear value chain to operating in an ecosystem or network (Weill and Woerner 2015 ). As different types of innovation networks with different cognitive and social translations regarding knowledge emerge, novel properties of digital infrastructure in support of each network are required. Digital technologies therefore increase innovation network knowledge heterogeneity (Lyytinen et al. 2016 ). Third, the free flow of digital goods precipitates an erosion of property rights and higher risks of imitation (Loebbecke and Picot 2015 ).

4.3 Micro-level findings: the actor-centric side of the equation

In the following, we present and discuss the most important findings of the second order themes within the actor-centric dimension. In Fig.  3 we provide a thematic map for this dimension and in Table  2 a brief summary including illustrative quotes.

Thematic map for actor-driven themes in digital transformation literature

4.3.1 Transformative leadership

Understanding the impact of digital transformation on leadership and management behavior is a very active and prioritized research focus. In total, 23 papers in our review explore this aspect. First and foremost, research calls for a shift in the traditional view of IT strategy as being subordinate to business strategy (El Sawy et al. 2016 ). In the course of the past two decades information technologies have surpassed their subordinate role as administrative ‘back office’ assets and evolved into an essential element of corporate strategy building. Thus, incumbents should align IT and business strategies on equal terms and fuse them into ‘digital business strategy’ (Bharadwaj et al. 2013 ).

Also, emphasis is placed on the changing nature of leadership itself, caused by digital transformation. Such changes may include rapid optimization of top management decision-making processes enabled by instant access to information and expansive data sets (Mazzei and Noble 2017 ), new communication principles (Bennis 2013 ; Granados and Gupta 2013 ), or changes in leadership education (Sia et al. 2016 ). Further, there is consensus that senior management requires a new digital mindset in order to captain their company’s digital transformation journey. Therefore, incumbents should also rethink their leadership education practices. In the past, leadership programs have been primarily about leadership and communication skills. But in times of digital transformation, executives must become ‘tech visionaries’ and develop their transformative powers. For example, Sia et al. ( 2016 ) have conducted a case study on an Asian bank that uses hackathons to educate their senior managers. Media transparency and exposure are further key challenges of digitization where top managers may require some additional education. Given the ubiquity of information and the speed of online data dissemination (via mobile phones, viral effects of social media etc.), leaders today are significantly more exposed publicly than their analog predecessors. Therefore, according to Bennis ( 2013 ) leadership in the digital era needs to be learned through embracing transparency and adaptive capacity (specifically resilience as the ability to rebound from problems and crisis).

Finally, the vast extent and complexity of digital transformation leads to the emergence of an additional position at the top management level—the Chief Digital Officer (Dremel et al. 2017 ; Tumbas et al. 2017 ). Given the immense challenges of digital transformation and the claim for a new mindset and different skills, CEOs or even CIOs are conceivably not the best match (Singh and Hess 2017 ). Particularly not if they are expected to drive digital transformation in addition to their original tasks.

4.3.2 Managerial and organizational capabilities

Our analysis suggests that in order to effectively drive digital transformation additional and refined capabilities are required—both managerial and organizational (Li et al. 2017 )—in comparison to the analogue world.

At the managerial level, for one thing, a much faster strategy and implementation cycle is needed to cope with the pace of digital transformation (Daniel and Wilson 2003 ). The turbulent and ever-changing digital environment is forcing managers to make decisions and implement strategies significantly faster than they had been previously required to. In order to study managerial capabilities in the context of digital transformation, some studies have adopted the theory of dynamic capabilities (Daniel and Wilson 2003 ; Li et al. 2017 ; Yeow et al. 2018 ) as introduced by Teece et al. ( 1997 ), Teece ( 2007 , 2014 ). In particular, results indicate that dynamic capabilities may support the refinement of digital strategy and are therefore not separate from alignment, but on the contrary have the potential to enact and guide the process of aligning.

At the organizational level, one of the most intriguing challenges for incumbents will be to manage the ambidexterity of capabilities in terms of analog and digital capabilities. Firms need to incorporate ‘old’ and ‘new’ capabilities into their organizational structure in a complementary and not impeding way. In addition, capabilities in two further areas are of particular importance to many firms. First, capabilities to implement and operate in networks (Bharadwaj et al. 2013 ), platforms (Li et al. 2017 ; Sebastian et al. 2017 ), and ecosystems (El Sawy et al. 2016 ; Weill and Woerner 2015 ). Depending on contextual factors like for example their industry or business model, companies must learn to take advantage of network effects in terms of complementary capabilities while also learn how to become more of an ecosystem rather than continue managing value chains. Second, in the digital era it is essential to develop sensing capabilities, such as entrepreneurial alertness and environmental scanning (Kohli and Melville 2019 ), in order to identify new ideas and critically evaluate, design, modify and eventually deliver new business models (Berman 2012 ; Daniel and Wilson 2003 ).

4.3.3 Company culture

Digital transformation is not exclusively a technology-driven challenge but requires deep cultural change. Everyone within the organization must be prepared with an adaptive skill set and digital know-how. Two major insights can be identified within the existing literature. First, digital transformation demands a data-sharing and data-driven corporate culture (Dremel et al. 2017 ). Data as such must be recognized much more as a valuable resource and an enabler to become a digital enterprise. This will require higher operational transparency in daily-business and work-routines and a data-sharing mindset among employees. In this sense, incumbents need to develop their informatic culture to an informational culture (Llopis et al. 2004 ). In comparison to an informatic culture, an informational culture values IT as a core element of strategic and tactical decisions and clearly understands the financial and transformative potential of digital technologies. Second, digital transformation may trigger cultural conflict between younger and comparably inexperienced digital employees and older but more experienced pre-digitization employees (Kohli and Johnson 2011 ). Management is well advised to prevent that two different cultures arise within the same organization—a group of employees who understand digital technologies and those who have a long-standing track record in the traditional business but are technologically lagging behind. Facilitating a learning friendly culture (Kohli and Melville 2019 ) and publicly affirming support and trust by the executive level may effectively mitigate such a potential cultural divide.

4.3.4 Work environment

Our review reveals that digital transformation is changing the daily work environment in incumbent firms in terms of work structures (Hansen and Sia 2015 ; Loebbecke and Picot 2015 ), job roles, and workplace requirements (White 2012 ). For example, digital interconnectivity enables the emergence of flexible and networked cross-location teams across the entire geographical company map. In this context, traditional hierarchical work structures dissolve and new opportunities emerge beyond company boundaries, such as the integration of external freelancers (Loebbecke and Picot 2015 ). Also, the implementation of a digital workplace becomes inevitable. Particularly for ‘born digital’ younger employees a digitally well-equipped workplace may represent a major criterion for their choice of employer (El Sawy et al. 2016 ). According to White ( 2012 ), a digital workplace must be adaptive, compliant, imaginative, predictive, and location-independent.

However, the most notable insight in this perspective is that—in addition to a potential cultural divide—digitization may effectively lead to a growing skills gap between pre-digitization workers and recently hired digitally savvy employees (Kohli and Johnson 2011 ). In fact, while digital technologies significantly help to optimize and accelerate many work processes and thereby increase productivity, incumbents must be aware that many employees might not keep pace with this digital high-speed train and feel left behind. It is unclear how such a tradeoff is considered and how firms could handle related conflicts.

5 Avoiding an ivory tower: drawing on existing knowledge from adjacent research fields

We assume that pre-existing knowledge on corporate transformation processes in general is partly already available and may provide implications for digital transformation. Therefore, at this point in our review, we aim to stimulate a theoretical discussion by identifying potential white spots abstracted from adjacent research fields. For this purpose, we additionally reviewed 28 studies from the literature on technological disruption (to gain technology-centric input) and 32 papers from corporate entrepreneurship (to expand the actor-centric view). By this, we supplement the pre-dominantly IS-based digital transformation literature with a broader management perspective. First, by reviewing the literature on disruptive innovations we hope to derive implications regarding technology adoption and integration. Burdened with the legacy of old technology, bureaucratic structures and core rigidities (Leonard-Barton 1992 ), incumbents may face major challenges in this respect during their digital transformation journey. Second, we expect corporate entrepreneurship to add a more holistic perspective on firm-internal aspects during the process of transformation, such as management contribution or the impact of knowledge and learning.

We rigorously conducted the same review and analysis process as for our digital transformation sample. A database and concept matrix (Webster and Watson 2002 ) for the sample on technological disruption and corporate entrepreneurship are provided in Tables  6 and 7 of “ Appendix ”. The data structures, which summarize the second order themes for both the actor-centric and technology-centric dimension of these additional research fields are illustrated in Figs.  5 and 6 of “ Appendix ”. Within the main body of this article, we only draw attention toward three key implications (Fig.  4 ). In the following, we provide a brief synthesis of these implications and their grounding in the respective literature. In a second step, we transfer and apply these implications to the context of digital transformation and integrate them into an agenda for future research opportunities.

Expanding the digital transformation high-level thematic map with insights from technological disruption and corporate entrepreneurship

5.1 Insights from technological disruption

Existing knowledge from the adoption of disruptive technologies suggests that in order to successfully integrate, commercialize or develop disruptive technologies incumbents need to create organizations that are independent from but interconnected in one way or another with the mainstream business (Bower and Christensen 1995 ). The reasons for this are manifold. For example, managers are encouraged to protect disruptive technologies from the processes and incentives that are targeted to serve established customers. Rather, disruptive innovations should be placed in separate new organizations that work with future customers for this technology (Bower and Christensen 1995 ; Gans 2016 ). Further, separation potentially helps to unravel the discord between viewing disruptive innovations as a threat or an opportunity. Exempted from obligations to a parent company, separate ventures are more likely to perceive a novel technology as an opportunity (Gilbert and Bower 2002 ). And lastly, a freestanding business also enables local adaptation and increased sensitivity to changes in the environment (Hill and Rothaermel 2003 ).

5.2 Insights from corporate entrepreneurship

Our review of the corporate entrepreneurship literature identifies two major implications that have not been (adequately) considered in digital transformation research yet.

First, the literature indicates that middle management plays a crucial role in redefining a firm’s strategic context and by this driving organizational transformation. A middle management perspective has thus far been completely neglected in digital transformation research. We see this as a major gap, since the middle layers of management are ‘where the action is’ (Floyd and Wooldridge 1999 , p. 124). Top management should control the level and the rate of change and ensure that entrepreneurial activities correspond to their strategic vision (Burgelman 1983 ), but middle managers at the implementation level are the driving force and key determinant behind organizational transformation. However, on the downside, middle managers may also represent a major barrier to organizational change (Thornberry 2001 ). Typically, managers have the task to minimize risks, make sure everything is compliant to the rules and perform their functional roles. Thus, middle managers usually have the most to lose from radical changes and are therefore often the least likely to be entrepreneurial or to support transformations (Thornberry 2001 ). In order to solve middle and operational manager’s risk-awareness and unleash their entrepreneurial spirit, research suggests encouraging autonomous behavior (Shimizu 2012 ). In sum, reviewing the literature on corporate entrepreneurship raises our awareness for the impact of hierarchy and management levels on organizational transformation (Hornsby et al. 2009 ).

Second, a closer cooperation and regular exchange between incumbents and start-ups in order to accelerate entrepreneurial transformation is proposed (Engel 2011 ; Kohler 2016 ). Incumbents should recognize start-up companies as a source of external innovation and develop suitable models for collaboration (e.g. corporate accelerators). In particular, incumbents are advised to implement three common best practices from successful start-ups in order to facilitate transformation: (1) working in small omni-functional teams, (2) goal-driven rapid development instead of bureaucratic processes, and (3) field-level exploration of market potential instead of complex and tedious quantitative models (Engel 2011 ). In addition, corporate entrepreneurship underlines the importance of organizational learning as a vehicle to drive and shape cultural transformation (Dess et al. 2003 ; Floyd and Wooldridge 1999 ; Zahra 2015 ). We come to understand that learning, and in fact also knowledge management, are intimately tied to the concept of organizational transformation. A culture of learning and knowledge drives experimentation, encourages the development of an adaptive skill set, reshapes competitive positioning, and opens the minds of employees to new realities (Zahra et al. 1999 ).

6 Opportunities for future research

Based on the cross-disciplinary perspectives from reviewing the literature on digital transformation, technological disruption and corporate entrepreneurship, we propose opportunities for future research on digital transformation. Using our thematic map as a lens to view future research opportunities, we focus on the two dimensions of technology and actor. For the technology-centric dimension we expand on the structural and operational integration of digital technologies and organizational transformation initiatives as well as gaining a deeper understanding of the pace of technological transformation. For the actor-centric dimension we address three topics: we start at the leadership level by emphasizing the relevance of middle management in digital transformation, after that we refer to the potential skills gap and threat of an employee divide in incumbent organizations induced by digital technologies, and finally we move beyond organizational boundaries to turn toward the potential benefits and drawbacks of cooperating with start-ups and pure digital companies to boost transformation. For each area, we propose a set of research questions. Altogether, the agenda is organized around five guiding topics (Table  3 ).

6.1 Integration of digital transformation within organizational structures and activities in incumbent firms

Our review of the literature on digital transformation reveals a knowledge gap regarding this topic. However, we do gain some interesting cross-disciplinary insights from technological disruption at this point. In fact, as already discussed, studies on technological disruption indicate that in order to successfully integrate, commercialize or develop disruptive technologies incumbents need to create organizations that are completely independent from but interconnected in one way or another with the mainstream business (Bower and Christensen 1995 ; Gans 2016 ; Gilbert and Bower 2002 ; Hill and Rothaermel 2003 ).

Thus, the question arises as to how incumbents should incorporate their digital transformation activities. Several options and interesting questions arise in this matter that future research may investigate on:

Which forms of organizational architecture are most suitable for digital transformation? Seamless integration of digital technologies requires building an agile and scalable digital infrastructure that enables continuous scalability of new initiatives (Sia et al. 2016 ). For example, Resca et al. ( 2013 ) suggest a platform-based organization. In addition, digital transformation demands a new kind of enterprise platform integration (El Sawy et al. 2016 ). Given the high intensity of interactive digital connectivity between the outside and inside of a company, traditional enterprise platforms (like ERP) and the ‘old’ supply chain management integration paradigm are in many cases not the most suitable solution anymore. Therefore, flexible IT is a key transformation resource in the digital world (Cha et al. 2015 ). Pursuing an open innovation approach might be another alternative for incumbents.

When and why is it an advantage/disadvantage to start digital transformation in a new organization which is completely independent from traditional business, as suggested by technological disruption research? Under what circumstances and why do spill - over - effects to the parent organization happen/not happen? ? For example, Ravensburger AG , a German toy and jigsaw puzzle company, founded Ravensburger Digital GmbH as a subsidiary in 2009. The purpose of the subsidiary was to become the firm’s digital competence center. In 2017, the digital subsidiary was reincorporated in the parent organization as a digital unit with the goal to apply their digital knowledge to transform the traditional business segments. We call for more qualitative case study research devoted to this question to develop our understanding in this topic.

How, when, and why do incumbents benefit from adopting a ‘let a hundred flowers bloom’ philosophy versus taking a ‘launch, learn, pivot’ approach? In the first scenario, a company would start its digital initiatives across all divisions simultaneously and locally to encourage broad experimentation. Such an approach was adopted by AmerisourceBergen Corp. , an American drug wholesale company. The company is convinced that digital transformation is a matter of culture that needs to be established across the entire organization. For this purpose, it implemented agile project teams throughout the entire enterprise, of which each focused on different aspects. On the downside, companies following such a broad approach may risk losing focus and at some point, the various initiatives may start competing against each other. Hence, we believe it is crucial to have a big picture in mind and accordingly allocate resources and attention very thoughtfully. Alternatively, incumbents may start with a pilot transformation project in a smaller market or subsidiary. Arguably, a major advantage is the opportunity to assure that customers are happy with the transformation results and everything is working out well before starting the large roll out in other markets. And it provides incumbents time to fine-tune their initiatives. For example, American medical company Alcon premiered their initial transformation efforts in Brazil before ramping up their rollout in 27 further countries.

6.2 Pace of digital transformation

The rapid pace of technological change is perhaps the most defining characteristic of digital transformation in distinction to previous IT-enabled transformations. Yet, as this topic is only addressed by four papers in our sample it is still to be studied in more depth. For example, there is consensus among the studies that the pace of change has accelerated significantly, however the parameters that define the pace of change remain yet to be defined. Further, we are informed that some industries like the newspaper business have been digitally transformed within a very short period of time (Karimi and Walter 2015 ), while other branches are still under transformation or are yet to be converted. We posit two exemplary research questions regarding the pace of digital transformation:

What are the parameters that define the pace of change? Our review reveals that the speed of product launches (Bharadwaj et al. 2013 ) and the time it takes to turn an idea into a business (Vey et al. 2017 ) are two potential indicators, but we certainly need to obtain a more comprehensive conceptualization at this point.

Why do industries adopt to digital transformation at a different speed? For example, consider front-runner industries like the media or publishing versus late-comers such as oil and gas. In this specific case, the easiness to dematerialize and digitize the product portfolio is certainly a main reason. However, other industries are less obvious, and we would like to invite future research to investigate upon these conditions. What are the parameters that define whether an industry is more or less transformative?

6.3 The role of middle management in digital transformation

We have learned from our review of the corporate entrepreneurship literature that middle managers are the locus of organizational transformation in incumbent firms (Floyd and Wooldridge 1999 ; Hornsby et al. 2002 , 2009 ; Shimizu 2012 ). While top management controls the level and rate of change, middle managers are in charge of execution (Burgelman 1983 ). Hence, one may conclude that middle managers are the kingpin of digital transformation. Yet, there is not a single paper in our sample that covers a middle management perspective in digital transformation. We believe that this subject has been highly neglected in research to this point and deserves far more attention in future. Several topics are particularly interesting:

How and why is digital transformation affecting the role, tasks and identity of middle managers? How and why do middle managers react to these changes? Based on our review, we expect a deep change in the nature of middle management’s role and influence in a ‘digitally transformed’ company ranging from administration to leadership aspects. Middle managers require a new attitude as they move from directing and controlling stable processes and people at the middle of hierarchy to managing resources and connecting people in the middle of networks. In addition, middle managers in the digital era must step up to their role of supporting, enabling, and coaching people to use the available digital tools. They are expected to facilitate the organization.

What kind of new responsibilities and functions in middle management hierarchy are required to accelerate digital transformation? The odds are that change fatigue might grow on employees and digital transformation may start faltering. For this purpose, horizontal functions such as business-process management layers or central administration platforms may be implemented (McKinsey & Company 2017 ). They could be shared across multiple initiatives within the organization and help to accelerate transformation.

Which mindset and digital literacy do middle managers need to be the driving force behind digital transformation? How, when, and why are middle managers motivated/not motivated to drive transformation? Research on corporate entrepreneurship emphasizes that middle managers are often the least likely to support change as they are inherently risk-averse, hardly entrepreneurial and very attached to their functional routines (Thornberry 2001 ). In addition, middle managers may easily get stressed about their ‘sandwich’ position in-between senior management and the operational level. So how can we expect middle managers to be the speedboat of digital transformation? Also, incumbents need to carefully evaluate the existing digital skills and literacy of their middle managers. How comfortable do they feel with digital tools, social media, the cloud and similar trends? They may not fulfill their coaching and leadership role if they heavily struggle with technology in the first place.

How and why is digital transformation affecting the interface of the top management team (TMT) and middle managers? The relationship between the TMT and middle managers is a very special and important relationship which significantly affects both strategy formulation and the quality of implementation. Middle managers are the organizational ‘linking pins’ between top and operational level and thus heavily rely on a good exchange with their superiors. To what extent and in which ways does digital transformation affect this special leader–follower relationship? How are digital technologies changing the speed and quality of information exchange? What is the impact on the inter-personal level?

What is the impact of digital transformation on the overall importance of the middle management layer? Since the 1950s, research indicates the decline of middle managers in terms of both numbers and influence (Dopson and Stewart 1993 ; Leavitt and Whisler 1958 ; Pinsonneault and Kraemer 1997 ). The shift in emphasis from planning and controlling to speed and flexibility is severely affecting the assumedly ‘slow’ middle. Are middle managers afraid that digital technologies will replace most of their traditional tasks and functions, e.g. communicating and monitoring strategy? Will digitalization naturally empower lower level operational managers at the bottom and consequently eliminate the middle layer?

6.4 A growing skills gap and threat of an employee divide

Given the complexity and explosive pace of digital technologies, there is a threat of a growing skills gap between pre-digitization workers and recently hired digitally savvy employees (Kohli and Johnsons 2011 ). A couple of topics are particularly interesting for future research:

How, when and why are incumbents able/unable to mitigate a growing skills gap and employee divide in the face of digital transformation? Given the increased complexity of digital technologies, traditional IT trainings may not be effective anymore. In a similar vein, how could different levels of knowledge and experience residing within different employees be integrated in the context of digital transformation? Future research might examine the mechanisms required for facilitating or hindering such an integration.

How and when are incumbents able/unable to incorporate ‘old’ and ‘new’ capabilities within their organization? On the one hand firms need to develop new capabilities to continuously transform their business, while on the other hand they must leverage their existing knowledge and skills in order to maintain their existing operations. Thus, for the time of transformation incumbents need to develop multiple, often inconsistent competencies simultaneously. In this context, how do firms ensure not to lose focus while mastering the challenge of ambidexterity in times of digital transformation?

Who in the company is managing the development and transformation of skills (e.g. HR, senior leadership, IT division, functional teams, employees etc .), and how and why does that impact outcomes of digital transformation ? This question is not addressed by current research at all. However, according to a survey (Capgemini Consulting 2013) this lack of alignment with digital strategy is rather worrisome. Responsibilities for skills transformation and development in times of digitization need to be clearly defined and allocated. Empirical academic research in this direction might be helpful to understand the status-quo in incumbent firms regarding this issue.

6.5 Cooperation with startups and pure tech companies to accelerate digital transformation

Corporate entrepreneurship proposes a closer cooperation and regular exchange between incumbents and start-ups in order to accelerate entrepreneurial transformation (Engel 2011 ; Kohler 2016 ). In fact, start-ups are often perceived as the forerunners of digital transformation. They are praised for faster innovation capabilities, higher levels of agility, a culture of risk-taking, and supremely digitized processes and workflows. In contrast, incumbents have more experience, access to capital, established brand trust and a huge customer base. Hence, a cooperation between start-ups and incumbents may be beneficial for both parties. In addition, non-tech incumbents may also consider cooperating with pure digital players which are beyond their start-up phase but are important knowledge carriers in digital matters. Two topics are particularly interesting:

Assuming that successful start - ups have a good digital culture — what are the constituent pillars of such a digital culture? And how could incumbents incorporate these “best practices” and “lessons learned”?

What are the benefits of employee exchange programs with technology companies or start - ups to scale - up digital skills? For example, in early 2008 consumer goods giant Procter and Gamble and Google have been swapping two dozen employees in an effort to foster creativity, exchange thoughts on online advertisement and strengthen their mutual relationship. This program worked very well for both sides.

7 Limitations and conclusion

Our review is not without limitations. First, the specific objectives and nature of our filtering process applied during the review naturally come with a certain selection bias. For example, data collection, analysis and interpretation remain influenced by the subjective assessments of the researchers. Also, despite being the common rule within systematic literature reviews, searching exclusively in peer-reviewed academic journals might have omitted some relevant research contained in books or dissertations. However, by means of a rigorous and transparent search process, an as complete as possible review sample was collected and analyzed subsequently. Second, using a high-level thematic map for such a complex multi-dimensional phenomenon like digital transformation highlights particular connections while it potentially fails to capture others. Specifically, critics may point to the lack of analytical depth within each second order theme. However, we believe that within the limited scope of a review our broad thematic description nevertheless adds value to the advancement of this field and should rather be seen as a holistic starting point for future research to dive deeper into the characteristics of sub-themes of digital transformation. Finally, we are aware that our focus on the organizational level of digital transformation within the private sector does not fully capture the implications of digital transformation for our society, as it also occurs at various other levels, such as the individual level or public sector. As such, future researchers may apply alternative approaches to review and synthesize the existing literature on digital transformation. For example, in contrast to our inductive method to code and analyze our sample, it may also be interesting to apply a more deductive and pre-structured method, in particular when focusing on a deeper understanding of the sub-themes emerging from our analysis. Accordingly, future research could benefit from adopting a phenomenon-based research strategy as proposed by von Krogh et al. ( 2012 ).

Concluding, our paper contributes to the extant discussion by consolidating, mapping and analyze the existing research on digital transformation, sharing important macro- and microlevel observations in the literature and proposing corresponding future research directions. Emerging from our review of 58 studies, we develop a thematic map which identifies technology and actor as the two aggregate dimensions of digital transformation and that elaborates on the predominant contextual concepts (second order themes) within these dimensions. From a macrolevel perspective, we observe that the status-quo of digital transformation literature is rather diverse, in a sense that papers discuss topics across various clusters and concepts. Further, we find some degree of diversity in the theoretical foundations drawn upon as well as confirm that the existing literature in general is scarce regarding quantitative empirical evidence. Another important contribution of our paper is bringing different lenses together by integrating knowledge from related disciplinary areas outside IS management, such as technological disruption and corporate entrepreneurship. With our review, we hope to provide a comprehensive and solid foundation for the on-going discussions on digital transformation and to stimulate future research on this exciting topic.

The development of clear and precise aims and objectives; pre-planned methods; a comprehensive search of all potentially relevant articles; the use of explicit, reproducible criteria in the selection of articles; an appraisal of the quality of the research and the strength of the findings; a synthesis of individual studies using an explicit analytic framework; and a balanced, impartial and comprehensible presentation of the results.

The search included Academy of Management Journal , Administrative Science Quarterly , Entrepreneurship Theory and Practice , Journal of Management Studies , Strategic Management Journal .

The search included European Journal of Information Systems , Information Systems Journal , Information Systems Research , Journal of the Association for Information Systems , Journal of Information Technology , Journal of Management Information Systems , Journal of Strategic Information Systems , MIS Quarterly , MISQ Executive .

Ahuja G, Morris Lampert C (2001) Entrepreneurship in the large corporation: a longitudinal study of how established firms create breakthrough inventions. Strateg Manag J 22:521–543

Google Scholar  

Alos-Simo L, Verdu-Jover AJ, Gomez-Gras JM (2017) How transformational leadership facilitates e-business adoption. Ind Manag Data Syst 117:382–397

Anderson P, Tushman ML (1990) Technological discontinuities and dominant designs: a cyclical model of technological change. Adm Sci Q 35:604–633

Ash CG, Burn JM (2003) Assessing the benefits from e-business transformation through effective enterprise management. Eur J Inf Syst 12:297–308

Bartunek JM, Rynes SL, Ireland RD (2006) What makes management research interesting, and why does it matter. Acad Manag J 49:9–15

Bennis W (2013) Leadership in a digital world: embracing transparency and adaptive capacity. MIS Q 37:635–636

Bergek A, Berggren C, Magnusson T, Hobday M (2013) Technological discontinuities and the challenge for incumbent firms: destruction, disruption or creative accumulation? Res Policy 42:1210–1224

Berman SJ (2012) Digital transformation: opportunities to create new business models. Strategy Leadersh 40:16–24

Berman SJ, Davidson S, Ikeda K, Korsten PJ, Marshall A (2016) How successful firms guide innovation: insights and strategies of leading CEOs. Strategy Leadersh 44:21–28

Besson P, Rowe F (2012) Strategizing information systems-enabled organizational transformation: a transdisciplinary review and new directions. J Strateg Inf Syst 21:103–124

Bharadwaj A, El Sawy O, Pavlou P, Venkatraman N (2013) Digital business strategy: toward a next generation of insights. MIS Q 37:471–482

Birkinshaw J (1997) Entrepreneurship in multinational corporations: the characteristics of subsidiary initiatives. Strateg Manag J 18:207–229

Bower JL, Christensen CM (1995) Disruptive technologies: catching the wave. Harv Bus Rev 73:43–53

Burgelman RA (1983) Corporate entrepreneurship and strategic management: insights from a process study. Manag Sci 29:1349–1364

Cha KJ, Hwang T, Gregor S (2015) An integrative model of IT-enabled organizational transformation: a multiple case study. Manag Decis 53:1755–1770

Chatterjee D, Grewal R, Sambamurthy V (2002) Shaping up for e-commerce: institutional enablers of the organizational assimilation of web technologies. MIS Q 26:65–89

Chen J, Nadkarni S (2017) It’s about time! CEOs’ temporal dispositions, temporal leadership, and corporate entrepreneurship. Adm Sci Q 62:31–66

Christensen CM (1997) The innovator’s dilemma. When new technologies cause great firms to fail. Harvard Business School Press, Boston

Christensen CM, Raynor ME (2003) Why hard-nosed executives should care about management theory. Harv Bus Rev 81:66–75

Corbett A, Covin JG, O’Connor GC, Tucci CL (2013) Corporate entrepreneurship: state-of-the-art research and a future research agenda. J Prod Innov Manag 30:812–820

Corley KG, Gioia DA (2004) Identity ambiguity and change in the wake of a corporate spin-off. Adm Sci Q 49:173–208

Covin JG, Miles MP (1999) Corporate entrepreneurship and the pursuit of competitive advantage. Entrepreneursh Theory Pract 23:47–63

Crossan MM, Apaydin M (2010) A multi-dimensional framework of organizational innovation: a systematic review of the literature. J Manag Stud 47:1154–1191

Cui M, Pan SL (2015) Developing focal capabilities for e-commerce adoption: a resource orchestration perspective. Inf Manag 52(2):200–209

Daniel EM, Wilson HN (2003) The role of dynamic capabilities in e-business transformation. Eur J Inf Syst 12:282–296

Danneels E (2004) Disruptive technology reconsidered: a critique and research agenda. J Prod Innov Manag 21:246–258

DaSilva CM, Trkman P, Desouza K, Lindič J (2013) Disruptive technologies: a business model perspective on cloud computing. Technol Anal Strateg Manag 25:1161–1173

Denyer D, Neely A (2004) Introduction to special issue: innovation and productivity performance in the UK. Int J Manag Rev 5:131–135

Dess GG, Ireland RD, Zahra SA, Floyd SW, Janney JJ, Lane PJ (2003) Emerging issues in corporate entrepreneurship. J Manag Stud 29:351–378

Dijkman RM, Sprenkels B, Peeters T, Janssen A (2015) Business models for the Internet of Things. Int J Inf Manag 35(6):672–678

Doherty NF, King M (2005) From technical to socio-technical change: tackling the human and organizational aspects of systems development projects. Eur J Inf Syst 14:1–5

Dopson S, Stewart R (1993) Information technology, organizational restructuring and the future of middle management. New Technol Work Employ 8(1):10–20

Downes L, Nunes P (2013) Big bang disruption. Harv Bus Rev 91:44–56

Dremel C, Wulf J, Herterich MM, Waizmann JC, Brenner W (2017) How AUDI AG established big data analytics in its digital transformation. MIS Q Exec 16(2):81–100

Dushnitsky G, Lenox MJ (2005) When do incumbents learn from entrepreneurial ventures? Corporate venture capital and investing firm innovation rates. Res Policy 34(5):615–639

El Sawy OA, Malhotra A, Park Y, Pavlou PA (2010) Research commentary-seeking the configurations of digital ecodynamics: it takes three to tango. Inf Syst Res 21(4):835–848

El Sawy OA, Kræmmergaard P, Amsinck H, Vinther AL (2016) How LEGO built the foundations and enterprise capabilities for digital leadership. MIS Q Exec 15(2):141–166

Engel JS (2011) Accelerating corporate innovation: lessons from the venture capital model. Res-Technol Manag 54(3):36–43

Evens T (2010) Value networks and changing business models for the digital television industry. J Media Bus Stud 7(4):41–58

Fichman RG, Dos Santos BL, Zheng Z (2014) Digital innovation as a fundamental and powerful concept in the information systems curriculum. MIS Q 38(2):329–A15

Fisch C, Block J (2018) Six tips for your (systematic) literature review in business and management research. Manag Rev Q 68:103–106

Floyd SW, Wooldridge B (1999) Knowledge creation and social networks in corporate entrepreneurship: the renewal of organizational capability. Entrepreneursh Theory Pract 23(3):123–144

Fuetsch E, Suess-Reyes J (2017) Research on innovation in family businesses: are we building an ivory tower? J Fam Bus Manag 7(1):44–92

Gans JS (2016) Keep calm and manage disruption. MIT Sloan Manag Rev 57(3):83–90

Gawer A, Cusumano MA (2014) Industry platforms and ecosystem innovation. J Prod Inov Manag 31(3):417–433

Gerstner WC, König A, Enders A, Hambrick DC (2013) CEO narcissism, audience engagement, and organizational adoption of technological discontinuities. Adm Sci Q 58(2):257–291

Gerth AB, Peppard J (2016) The dynamics of CIO derailment: how CIOs come undone and how to avoid it. Bus Horiz 59(1):61–70

Gilbert C, Bower JL (2002) Disruptive change. When trying harder is part of the problem. Harv Bus Rev 80(5):94–101

Gioia DA, Thomas JB, Clark SM, Chittipeddi K (1994) Symbolism and strategic change in academia: the dynamics of sensemaking and influence. Org Sci 5(3):363–383

Granados N, Gupta A (2013) Transparency strategy: competing with information in a digital world. MIS Q 37(2):637–641

Grover V, Kohli R (2013) Revealing your hand: caveats in implementing digital business strategy. MIS Q 37(2):655–662

Günther WA, Mehrizi MHR, Huysman M, Feldberg F (2017) Debating big data: a literature review on realizing value from big data. J Strateg Inf Syst 26:191–209

Günzel F, Holm AB (2013) One size does not fit all—understanding the front-end and back-end of business model innovation. Int J Innov Manag 17(1):1340002-1–1340002-34

Guth WD, Ginsberg A (1990) Guest editors’ introduction: corporate entrepreneurship. Strateg Manag J 11:5–15

Habtay SR, Holmén M (2014) Incumbents’ responses to disruptive business model innovation: the moderating role of technology vs. market-driven innovation. Int J Entrep Innov Manag 18(4):289–309

Hagberg J, Sundstrom M, Egels-Zandén N (2016) The digitalization of retailing: an exploratory framework. Int J Retail Distrib Manag 44(7):694–712

Hansen R, Sia SK (2015) Hummel’s digital transformation toward omnichannel retailing: key lessons learned. MIS Q Exec 14(2):51–66

Hess T, Matt C, Benlian A, Wiesböck F (2016) Options for formulating a digital transformation strategy. MIS Q Exec 15(2):123–139

Hill CW, Rothaermel FT (2003) The performance of incumbent firms in the face of radical technological innovation. Acad Manag Rev 28(2):257–274

Hitt M, Ireland R, Camp S, Sexton D (2001) Strategic entrepreneurship: entrepreneurial strategies for wealth creation. Strateg Manag J 22:479–491

Holm AB, Günzel F, Ulhøi JP (2013) Openness in innovation and business models: lessons from the newspaper industry. Int J Technol Manag 61(3/4):324–348

Hornsby JS, Kuratko DF, Zahra SA (2002) Middle managers’ perception of the internal environment for corporate entrepreneurship: assessing a measurement scale. J Bus Vent 17(3):253–273

Hornsby JS, Kuratko DF, Shepherd DA, Bott JP (2009) Managers’ corporate entrepreneurial actions: examining perception and position. J Bus Ventur 24(3):236–247

Hu H, Huang T, Zeng Q, Zhang S (2016) The role of institutional entrepreneurship in building digital ecosystem: a case study of Red Collar Group (RCG). Int J Inf Manag 36(3):496–499

Ireland RD, Covin JG, Kuratko DF (2009) Conceptualizing corporate entrepreneurship strategy. Entrepreneursh Theory Pract 33(1):19–46

Ives B, Palese B, Rodriguez JA (2016) Enhancing customer service through the internet of things and digital data streams. MIS Q Exec 15(4):279–297

Johnson M (2010) Barriers to innovation adoption: a study of e-markets. Ind Manag Data Syst 110(2):157–174

Johnson MW, Christensen CM, Kagermann H (2008) Reinventing your business model. Harv Bus Rev 86(12):50–59

Jones O, Gatrell C (2014) Editorial: the future of writing and reviewing for IJMR. Int J Manag Rev 16(3):249–264

Karimi J, Walter Z (2015) The role of dynamic capabilities in responding to digital disruption: a factor-based study of the newspaper industry. J Manag Inf Syst 32(1):39–81

Karimi J, Walter Z (2016) Corporate entrepreneurship, disruptive business model innovation adoption, and its performance: the case of the newspaper industry. Long Range Plan 49(3):342–360

Kauffman RJ, Walden EA (2001) Economics and electronic commerce: survey and directions for research. Int J Electric Commun 5(4):5–116

Keen P, Williams R (2013) Value architectures for digital business: beyond the business model. MIS Q 37(2):643–648

Khandwalla PN (1987) Generators of pioneering-innovative management: some Indian evidence. Org Stud 8(1):39–59

Koen PA, Bertels H, Elsum IR, Orroth M, Tollett BL (2010) Breakthrough innovation dilemmas. Res Technol Manag 53(6):48–51

Kohler T (2016) Corporate accelerators: building bridges between corporations and startups. Bus Horiz 59(3):347–357

Kohli R, Johnson S (2011) Digital transformation in latecomer industries: CIO and CEO Leadership Lessons from Encana Oil and Gas (USA) Inc. MIS Q Exec 10(4):141–156

Kohli R, Melville NP (2019) Digital innovation: a review and synthesis. Inf Syst J 29(1):200–223

Kuratko DF, Covin JG, Hornsby JS (2014) Why implementing corporate innovation is so difficult. Bus Horiz 57(5):647–655

Lant TK, Mezias SJ (1990) Managing discontinuous change: a simulation study of organizational learning and entrepreneurship. Strateg Manag J 11:147–179

Lanzolla G, Anderson J (2008) Digital transformation. Bus Strateg Rev 19(2):72–76

Lavie D (2006) Capability reconfiguration: an analysis of incumbent responses to technological change. Acad Manag Rev 31(1):153–174

Leavitt HJ, Whisler TL (1958) Management in the 1980’s. In: Technology, organizations and innovation. London and New York, pp 41–48

Leonard-Barton D (1992) Core capabilities and core rigidities: a paradox in managing new product development. Strateg Manag J 13(S1):111–125

Leong C, Tan B, Xiao X, Tan FTC, Sun Y (2017) Nurturing a FinTech ecosystem: the case of a youth microloan startup in China. Int J Inf Manag 37(2):92–97

Li L, Su F, Zhang W, Mao JY (2017) Digital transformation by SME entrepreneurs: a capability perspective. Inf Sys J 28(6):1129–1157

Ling YAN, Simsek Z, Lubatkin MH, Veiga JF (2008) Transformational leadership’s role in promoting corporate entrepreneurship: examining the CEO-TMT interface. Acad Manag J 51(3):557–576

Liu DY, Chen SW, Chou TC (2011) Resource fit in digital transformation: lessons learned from the CBC Bank global e-banking project. Manag Decis 49(10):1728–1742

Llopis J, Gonzalez MR, Gasco JL (2004) Transforming the firm for the digital era: an organizational effort towards an E-culture. Hum Syst Manag 23(4):213–225

Locke K (2001) Grounded theory in management research. Sage, London

Loebbecke C, Picot A (2015) Reflections on societal and business model transformation arising from digitization and big data analytics: a research agenda. J Strateg Inf Syst 24(3):149–157

Lucas HC Jr, Goh JM (2009) Disruptive technology: how Kodak missed the digital photography revolution. J Strateg Inf Syst 18(1):46–55

Lumpkin GT, Dess GG (1996) Clarifying the entrepreneurial orientation construct and linking it to performance. Acad Manag J 2(1):135–172

Lyytinen K, Yoo Y, Boland RJ Jr (2016) Digital product innovation within four classes of innovation networks. Inf Sys J 26(1):47–75

Majchrzak A, Markus ML, Wareham J (2016) Designing for digital transformation: lessons for information systems research from the study of ICT and societal challenges. MIS Q 40(2):267–277

Marion T, Dunlap D, Friar J (2012) Instilling the entrepreneurial spirit in your RandD team: what large firms can learn from successful start-ups. IEEE Trans Eng Manag 59(2):323–337

Markus ML (2004) Technochange management: using IT to drive organizational change. J Inf Technol 19(1):4–20

Markus ML, Benjamin RI (1997) The magic bullet theory in IT-enabled transformation. Sloan Manag Rev 38:55–68

Markus ML, Loebbecke C (2013) Commoditized digital processes and business community platforms: new opportunities and challenges for digital business strategies. MIS Q 37(2):649–654

Matt C, Hess T, Benlian A (2015) Digital transformation strategies. Bus Inf Syst Eng 57(5):339–343

Mazzei MJ, Noble D (2017) Big data dreams: a framework for corporate strategy. Bus Horiz 60(3):405–414

McKinsey & Company (2017) A CEO guide for avoiding the ten traps that derail digital transformations. Digital McKinsey. https://www.mckinsey.com/business-functions/digital-mckinsey/our-insights/a-ceo-guide-for-avoiding-the-ten-traps-that-derail-digital-transformations . Accessed 28 July 2018

McWilliams A, Siegel D, Van Fleet DD (2005) Scholarly journals as producers of knowledge: theory and empirical evidence based on data envelopment analysis. Organ Res Methods 8:185–201

Meyer AD, Brooks GR, Goes JB (1990) Environmental jolts and industry revolutions: organizational responses to discontinuous change. Strateg Manag J 11:93–110

Miller D (1983) The correlates of entrepreneurship in three types of firms. Manag Sci 29:770–791

Mithas S, Tafti A, Mitchell W (2013) How a firm’s competitive environment and digital strategic posture influence digital business strategy. MIS Q 37(2):511–536

Moreau F (2013) The disruptive nature of digitization: the case of the recorded music industry. Int J Arts Manag 15(2):18–31

Morton MS (1991) The corporation of the 1990s: information technology and organizational transformation. Oxford University Press, New York

Mulrow CD (1994) Systematic reviews: rationale for systematic reviews. Br Manag J 309:597–599

Naman JL, Slevin DP (1993) Entrepreneurship and the concept of fit: a model and empirical tests. Strateg Manag J 14:137–153

Nambisan S, Lyytinen K, Majchrzak A, Song M (2017) Digital innovation management: reinventing innovation management research in a digital world. MIS Q 41(1):223–238. https://doi.org/10.25300/MISQ/2017/41:1.03

Nason RS, McKelvie A, Lumpkin GT (2015) The role of organizational size in the heterogeneous nature of corporate entrepreneurship. Small Bus Econ 45(2):279–304

Ng IC, Wakenshaw SY (2017) The Internet-of-Things: review and research directions. Int J Res Market 34(1):3–21

Obal M (2013) Why do incumbents sometimes succeed? Investigating the role of interorganizational trust on the adoption of disruptive technology. Ind Market Manag 42(6):900–908

Orlikowski WJ (1996) Improvising organizational transformation over time: a situated change perspective. Inf Syst Res 7(1):63–92

Pagani M (2013) Digital business strategy and value creation: framing the dynamic cycle of control points. MIS Q 37(2):617–632

Paré G, Trudel MC, Jaana M, Kitsiou S (2015) Synthesizing information systems knowledge: a typology of literature reviews. Inf Manag 52(2):183–199

Peltola S (2012) Can an old firm learn new tricks? A corporate entrepreneurship approach to organizational renewal. Bus Horiz 55(1):43–51

Pinsonneault A, Kraemer KL (1997) Middle management downsizing: an empirical investigation of the impact of information technology. Manag Sci 43(5):659–679

Pittaway L, Robertson M, Munir K, Denyer D, Neely A (2004) Networking and innovation: a systematic review of the evidence. Int J Manag Rev 5:137–168

Ranganathan C, Watson-Manheim MB, Keeler J (2004) Bringing professionals on board: lessons on executing IT-enabled organizational transformation. MIS Q Exec 3(3):151–160

Rayna T, Striukova L (2016) From rapid prototyping to home fabrication: how 3D printing is changing business model innovation. Technol Forecast Soc Change 102:214–224

Resca A, Za S, Spagnoletti P (2013) Digital platforms as sources for organizational and strategic transformation: a case study of the Midblue project. J Theor Appl Electron Commer Res 8(2):71–84

Rice MP, O’Connor GC, Peters LS, Morone JG (1998) Managing discontinuous innovation. Res-Technol Manag 41(3):52–58

Rigby DK, Sutherland J, Takeuchi H (2016) Embracing agile. Harv Bus Rev 94(5):40–50

Rindova VP, Kotha S (2001) Continuous “morphing”: competing through dynamic capabilities, form, and function. Acad Manag J 44(6):1263–1280

Rowe F (2014) What literature review is not: diversity, boundaries and recommendations. Eur J Inf Syst 23(3):241–255

Roy R, Sarkar MB (2016) Knowledge, firm boundaries, and innovation: mitigating the incumbent’s curse during radical technological change. Strateg Manag J 37(5):835–854

Sabatier V, Craig-Kennard A, Mangematin V (2012) When technological discontinuities and disruptive business models challenge dominant industry logics: insights from the drugs industry. Technol Forecast Soc Change 79(5):949–962

Sambamurthy V, Bharadwaj A, Grover V (2003) Shaping agility through digital options: reconceptualizing the role of information technology in contemporary firms. MIS Q 27(2):237–263

Sandström CG (2016) The non-disruptive emergence of an ecosystem for 3D Printing—insights from the hearing aid industry’s transition 1989–2008. Technol Forecast Soc Change 102:160–168

Schendel D (1990) Introduction to the special issue on corporate entrepreneurship. Strateg Manag J 11:1–3

Schollhammer H (1982) Internal corporate entrepreneurship. In: Kent CA, Sexton DL, Vesper KH (eds) Encyclopedia of entrepreneurship. Prentice Hall, Englewood Cliffs, pp 209–229

Schuchmann D, Seufert S (2015) Corporate learning in times of digital transformation: a conceptual framework and service portfolio for the learning function in banking organisations. Int J Adv Corp Learn 8(1):31–39

Scott WR (1992) Organizations rational, natural, and open systems. Prentice Hall, Englewood Cliffs

Sebastian IM, Ross JW, Beath C, Mocker M, Moloney KG, Fonstad NO (2017) How big old companies navigate digital transformation. MIS Q Exec 16(3):197–213

Setia P, Venkatesh V, Joglekar S (2013) Leveraging digital technologies: How information quality leads to localized capabilities and customer service performance. MIS Q 37(2):565–590

Seufert S, Meier C (2016) From eLearning to digital transformation: a framework and implications for LandD. Int J Adv Corp Learn 9(2):27–33

Shaughnessy H (2016) Harnessing platform-based business models to power disruptive innovation. Strategy Leadersh 44(5):6–14

Shimizu K (2012) Risks of corporate entrepreneurship: autonomy and agency issues. Org Sci 23(1):194–206

Sia SK, Soh C, Weill P (2016) How DBS bank pursued a digital business strategy. MIS Q Exec 15(2):105–121

Siebels J, Knyphausen-Aufseß D (2012) A review of theory in family business research: the implications for corporate governance. Int J Manag Rev 14:280–304

Singh A, Hess T (2017) How chief digital officers promote the digital transformation of their companies. MIS Q Exec 16(1):1–17

Stopford JM, Baden-Fuller CW (1994) Creating corporate entrepreneurship. Strateg Manag J 15(7):521–536

Svahn F, Mathiassen L, Lindgren R (2017) Embracing digital innovation in incumbent firms: how Volvo cars managed competing concerns. MIS Q 41(1):239–253

Teece DJ (2007) Explicating dynamic capabilities: the nature and microfoundations of (sustainable) enterprise performance. Strateg Manag J 28(13):1319–1350

Teece DJ (2014) A dynamic capabilities-based entrepreneurial theory of the multinational enterprise. J Int Bus Stud 45(1):8–37

Teece DJ, Pisano G, Shuen A (1997) Dynamic capabilities and strategic management. Strateg Manag J 18(7):509–533

Templier M, Paré G (2015) A framework for guiding and evaluating literature reviews. Commun Assoc Inf Syst 37:112–137

Thompson JD, Bates FL (1957) Technology, organization, and administration. Adm Sci Q 2:325–342

Thornberry N (2001) Corporate entrepreneurship: antidote or oxymoron? Eur Manag J 19(5):526–533

Tongur S, Engwall M (2014) The business model dilemma of technology shifts. Technovation 34(9):525–535

Tranfield D, Denyer D, Smart P (2003) Towards a methodology for developing evidence-informed management knowledge by means of systematic review. Br J Manag 14(3):207–222

Tumbas S, Berente N, vom Brocke J (2017) Three types of chief digital officers and the reasons organizations adopt the role. MIS Q Exec 16(2):121–134

Turner T, Pennington WW (2015) Organizational networks and the process of corporate entrepreneurship: how the motivation, opportunity, and ability to act affect firm knowledge, learning, and innovation. Small Bus Econ 45(2):447–463

Turró A, Urbano D, Peris-Ortiz M (2014) Culture and innovation: the moderating effect of cultural values on corporate entrepreneurship. Technol Forecast Soc Change 88:360–369

Tushman ML, Anderson P (1986) Technological discontinuities and organizational environments. Adm Sci Q 31:439–465

Urbano D, Turró A (2013) Conditioning factors for corporate entrepreneurship: an in (ex)ternal approach. Int Entrep Manag J 9(3):379–396

Utterback JM (1994) Mastering the dynamics of innovation. Harvard Business School Press, Boston

Vecchiato R (2017) Disruptive innovation, managerial cognition, and technology competition outcomes. Technol Forecast Soc Change 116:116–128

Vey K, Fandel-Meyer T, Zipp JS, Schneider C (2017) Learning and development in times of digital transformation: facilitating a culture of change and innovation. Int J Adv Corp Learn 10(1):22–32

Vom Brocke J, Simons A, Riemer K, Niehaves B, Plattfaut R, Cleven A (2015) Standing on the shoulders of giants: challenges and recommendations of literature search in information systems research. Commun Assoc Inf Syst 37(1):9

von Krogh G, Rossi-Lamastra C, Haefliger S (2012) Phenomenon-based research in management and organisation science: when is it rigorous and does it matter? Long Range Plan 45(4):277–298

von Pechmann F, Midler C, Maniak R, Charue-Duboc F (2015) Managing systemic and disruptive innovation: lessons from the Renault Zero Emission Initiative. Ind Corp Change 24(3):677–695

Webster J, Watson RT (2002) Analyzing the past to prepare for the future: writing a literature review. MIS Q 26(2)::xiii–xxiii

Weill P, Woerner SL (2015) Thriving in an increasingly digital ecosystem. MIT Sloan Manag Rev 56(4):27–34

White M (2012) Digital workplaces: vision and reality. Bus Inf Rev 29(4):205–214

Woodward J (1965) Industrial organization theory and practice. Oxford University Press, New York

Yeow A, Soh C, Hansen R (2018) Aligning with new digital strategy: a dynamic capabilities approach. J Strateg Inf Syst 27(1):43–58

Yoo Y, Henfridsson O, Lyytinen K (2010) Research commentary—the new organizing logic of digital innovation: an agenda for information systems research. Inf Syst Res 21(4):724–735

Yoo Y, Boland RJ Jr, Lyytinen K, Majchrzak A (2012) Organizing for innovation in the digitized world. Organ Sci 23(5):1398–1408

Yu D, Hang CC (2010) A reflective review of disruptive innovation theory. Int J Manag Rev 12(4):435–452

Zahra SA (1993) A conceptual model of entrepreneurship as firm behavior: a critique and extension. Entrepreneursh Theory Pract 17(4):5–21

Zahra SA (1996) Goverance, ownership, and corporate entrepreneurship: the moderating impact of industry technological opportunities. Acad Manag J 39(6):1713–1735

Zahra SA (2015) Corporate entrepreneurship as knowledge creation and conversion: the role of entrepreneurial hubs. Small Bus Econ 44(4):727–735

Zahra SA, Covin JG (1995) Contextual influences on the corporate entrepreneurship–performance relationship: a longitudinal analysis. J Bus Ventur 10(1):43–58

Zahra SA, Nielsen AP, Bogner WC (1999) Corporate entrepreneurship, knowledge, and competence development. Entrepreneursh Theory Pract 23(3):169–189

Zammuto RF, Griffith TL, Majchrzak A, Dougherty DJ, Faraj S (2007) Information technology and the changing fabric of organization. Org Sci 18(5):749–762

Zeng Q, Chen W, Huang L (2008) E-business transformation: an analysis framework based on critical organizational dimensions. Tsinghua Sci Technol 13(3):408–413

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Data structure for the technology-centric dimension of technological disruption

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Nadkarni, S., Prügl, R. Digital transformation: a review, synthesis and opportunities for future research. Manag Rev Q 71 , 233–341 (2021). https://doi.org/10.1007/s11301-020-00185-7

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Original research article, teaching and learning in times of covid-19: uses of digital technologies during school lockdowns.

• Department of Basic Psychology, Faculty of Psychology, Autonomous University of Madrid, Madrid, Spain

The closure of schools as a result of COVID-19 has been a critical global incident from which to rethink how education works in all our countries. Among the many changes generated by this crisis, all teaching became mediated by digital technologies. This paper intends to analyze the activities carried out during this time through digital technologies and the conceptions of teaching and learning that they reflect. We designed a Likert-type online questionnaire to measure the frequency of teaching activities. It was answered by 1,403 teachers from Spain (734 primary and 669 secondary education teachers). The proposed activities varied depending on the learning promoted (reproductive or constructive), the learning outcomes (verbal, procedural, or attitudinal), the type of assessment to which the activities were directed, and the presence of cooperative activities. The major result of this study was that teachers used reproductive activities more frequently than constructive ones. We also found that most activities were those favoring verbal and attitudinal learning. The cooperative activities were the least frequent. Finally, through a cluster analysis, we identified four teaching profiles depending on the frequency and type of digital technologies use: Passive, Active, Reproductive, and Interpretative. The variable that produced the most consistent differences was previous digital technologies use These results show that Information and Communication Technologies (ICT) uses are reproductive rather than constructive, which impedes effective digital technologies integration into the curriculum so that students gain 21st-century competencies.

Introduction

When schools were closed in most countries in March 2020 because of the COVID-19 pandemic, teachers had no other option but to change their classrooms into online learning spaces. It was a critical global incident. In research on identity and teacher training ( Tripp, 1993 ; Butterfield et al., 2005 ; Monereo, 2010 ), a critical incident is an unexpected situation that hinders the development of the planned activity and that, by exceeding a certain emotional threshold, puts the identity in crisis and obliges that teachers review their concepts, strategies, and feelings. Thus, these incidents can become meaningful resources for training and changing teaching and learning practices because they allow us to review our deep beliefs ( Monereo et al., 2015 ).

The critical global incident generated by the pandemic forced most teachers to assume virtual teaching where they had to use digital technologies, sometimes for the first time, to facilitate their students’ learning. The closure of schools as a consequence of COVID-19 led to substantial changes in education with profound consequences. Today we know that educational inequalities have widened ( Dorn et al., 2020 ), while students have suffered greater social and emotional imbalances ( Colao et al., 2020 ). In this context, families have also been more involved in the school education of their children ( Bubb and Jones, 2020 ). Moreover, concerning the objectives of this study, it has been necessary to rethink the teaching strategies in the new virtual classrooms. In fact, this research focuses precisely on analyzing the uses that teachers made of the digital technologies or Information and Communication Technologies (ICT) (from now on, we will use this acronym) during the confinement to become familiar with their practices and use them to review their conceptions of teaching and learning.

For several decades, many authors have argued that ICT as educational devices facilitate the adaptation of teaching to each student. Some argue this is because they can promote collaboration, interactivity, the use of multimedia codes, and greater control of learning by the learner (e.g., Jaffee, 1997 ; Collins and Halverson, 2009 ). In this way, their integration in the curriculum would contribute to the acquisition of 21st-century competencies (autonomy, collaboration, critical thinking, and problem-solving) that the OECD ( Ananiadou and Claro, 2009 ) links to the so-called “global competence” that should define the current education ( Ertmer et al., 2015 ).

However, after decades of use of ICT in classrooms, they have not fully achieved their promise to transform teaching and learning processes. The results of a lot of international studies are, in fact, quite discouraging, like those claimed by the PISA studies ( OECD, 2015 ). In its report, the OECD(2015 , p. 3) concludes that “the results also show no appreciable improvements in student achievement in reading, mathematics or science in the countries that had invested heavily in ICT for education.” Thus, Biagi and Loi (2013) found that the more education ICT uses reported, the less learning in reading, mathematics, and science achieved. These data caused even Andreas Schleicher, head and coordinator of PISA studies, to claim that “the reality is that technology is doing more harm than good in our schools today” ( Bagshaw, 2016 ).

These conclusions contrast with the results obtained in most of the experimental research on the effects of ICT on learning. A decade ago, after conducting a second-order meta-analysis of 25 meta-analyses, Tamim et al.(2011 , p. 14) found “a significant positive small to moderate effect size favoring the utilization of technology in the experimental condition over more traditional instruction (i.e., technology-free) in the control group,” a conclusion that is still valid today. Various studies and meta-analyses reflect moderate but positive effects on learning, whether for example from the use of touch screens in preschools ( Xie et al., 2018 ), from cell phones ( Alrasheedi et al., 2015 ; Sung et al., 2015 ) or video games ( Clark et al., 2016 ; Mayer, 2019 ). It has also been found that they favor collaboration in secondary education ( Corcelles Seuba and Castelló, 2015 ) or learning mathematics ( Li and Ma, 2010 ; Genlott and Grönlund, 2016 ), science ( Hennessy et al., 2007 ) or second languages ( Farías et al., 2010 ).

What is the reason for this disagreement between research conducted in experimental laboratories and large-scale studies? Many factors could explain this distance ( de Aldama, 2020 ). But one difference is that the experimental studies have been carefully designed and controlled to promote these forms of learning mentioned above, while the usual work in the classroom is mediated by the activity of teachers who, in most cases, have little training using ICT ( Sigalés et al., 2008 ). Several authors ( Gorder, 2008 ; Comi et al., 2017 ; Tondeur et al., 2017 ) conclude that it is not the ICT themselves that can transform the classroom and learning, but rather the use that teachers make of them. While the experimental studies mostly promote activities that encourage autonomous learning ( Collins and Halverson, 2009 ), the most widespread uses of ICT, as reflected in these international studies with more diverse samples, report other kinds of use whose benefits are more doubtful.

Different classifications of teachers’ use of ICT in the classroom have been proposed in recent years (e.g., Gorder, 2008 ; Mama and Hennessy, 2013 ; Comi et al., 2017 ). Tondeur et al. (2008a) differentiate three types of educational computer use: (a) basic computer skills; (b) use of computers as an information tool, and (c) use of them as a learning tool. Laying aside the acquisition of basic skills related to digital devices, learning is promoted by the last two uses that lead to second-order digital skills related to information management and its conversion into knowledge ( Fulton, 1997 ; Gorder, 2008 ). Thus, the distinction is usually made between two types of use. The first use is aimed at traditional teaching, focused on the transmission and access to information, and usually called teacher-centered use (although perhaps it should be called content-centered use). The second one, called student-centered use, promotes diverse competencies (autonomy, collaboration, critical thinking, argumentation, and problem-solving) and is part of the Global Competence characteristic of 21st-century education ( Ananiadou and Claro, 2009 ; OECD, 2019 , 2020 ). According to Tondeur et al. (2017) , integration of ICT in education requires assuming a constructivist conception of learning and adopting a student-centered approach in which the students manage the information through the ICT instead of, as in the more traditional approach (content-centered), it being the teacher who uses the ICT.

The experimental studies mentioned above show that student-centered approaches improve verbal earning, producing a better understanding of the subjects studied, promoting self-regulation of the learning processes themselves, and generating critical and collaborative attitudes toward knowledge. Thus, Comi et al.(2017 , pp 36–37), after analyzing data from different standardized assessments, conclude: “computer-based teaching practices increase student performance if they are aimed at increasing students’ awareness of ICT use and at improving their navigation critical skills, developing students’ ability to distinguish between relevant and irrelevant material and to access, locate, extract, evaluate, and organize digital information.” Besides, they also found a slight negative correlation between using ICT to convey information and academic performance.

In spite of these better results of adopting student-centered uses, the studies support that the most frequent uses in classrooms are still centered on the teachers, who indeed use ICT as a substitute for other more traditional resources to transmit information ( Loveless and Dore, 2002 ; Sigalés et al., 2008 ; de Aldama and Pozo, 2016 ). Even if what Ertmer (1999) called type I barriers are overcome, related to the availability of these technological resources and the working conditions in the centers, several studies show that there are other types II barriers that limit the use of ICT ( Ertmer et al., 2015 ); in particular, the conceptions about learning and teaching to the extent that they mediate the use of ICT ( Hermans et al., 2008 ).

Different studies have shown that these teachers’ beliefs about learning and teaching are the best predictor of the use made of ICT in the classroom ( Ertmer, 2005 ; Ertmer et al., 2015 ). Most of the work on these beliefs ( Hofer and Pintrich, 1997 , 2002 ; Pozo et al., 2006 ; Fives and Gill, 2015 ) identifies two types of conceptions: some closer to a reproductive vision of learning, which would be related to the teacher or content-centered teaching uses, and others nearer to constructivist perspectives, which promote student-centered teaching uses. Studies show teachers who have constructivist beliefs tend to use more ICT than those with more traditional beliefs ( Judson, 2006 ; Law and Chow, 2008 ; Ertmer et al., 2015 ). They also employ them in a more student-centered way, and their uses are oriented toward the development of problem-solving skills ( Tondeur et al., 2017 ). On the other hand, teachers with more traditional beliefs use them primarily to present information ( Ertmer et al., 2012 ).

However, the relationship between conceptions and educational practices is not so clear and linear ( Liu, 2011 ; Fives and Buehl, 2012 ; Tsai and Chai, 2012 ; Mama and Hennessy, 2013 ; Ertmer et al., 2015 ; de Aldama and Pozo, 2016 ; de Aldama, 2020 ). Many studies show a mismatch between beliefs and practices, above all, when we refer to beliefs closer to constructivism that do not always correspond to constructive or student-centered practices. We can distinguish three types of arguments that explain the mismatches. First, the beliefs seem to be more complex and less dichotomous than what is assumed ( Ertmer et al., 2015 ). The studies comparing beliefs and practices tend to focus on the more extreme positions of the spectrum -reproductive vs. constructive beliefs-, despite research showing they are part of a continuum of intermediate beliefs between both aspects ( Hofer and Pintrich, 1997 , 2002 ; Pérez Echeverría et al., 2006 ). Thus, for example, the so-called interpretive beliefs maintain traditional reproductive epistemological positions. People who have these conceptions think that learning is an exact reflection of reality or the content which should be learned, whereas they also think teaching is mediated by cognitive processes of the learner which are based on his or her activity ( Pozo et al., 2006 ; López-Íñiguez and Pozo, 2014 ; Martín et al., 2014 ; Pérez Echeverría, in press ). Other examples of this belief can be found in the technological-reproductive conception described by Strauss and Shilony (1994) , which is close to a naïve information processing theory.

Second, we must acknowledge that neither teachers’ beliefs nor their educational practices remain stable but vary according to the teaching contexts. As Ertmer et al. (2015) claim, beliefs are not unidimensional, but teachers assume them in varying degrees and with different types of relationships. The teacher’s beliefs seem to be organized in profiles that gather aspects of the different theories about teaching and whose activation depends on the contextual demands ( Tondeur et al., 2008a ; Bautista et al., 2010 ; López-Íñiguez et al., 2014 ; Ertmer et al., 2015 ).

Third, we consider that this multidimensionality of beliefs makes them very difficult to measure or evaluate ( Pajares, 1992 ( Schraw and Olafson, 2015 ; see also Ertmer et al., 2015 ; Pérez Echeverría and Pozo, in press ), so perhaps different studies are measuring different components. For example, many studies focus on explicit beliefs, or “what teachers believe to be true” for learning, and therefore evaluate more the general ideas about what ICT-based education should be. Usually, these statements tend to be relatively more favorable to the advantages mentioned above. In this paper, we have chosen to analyze teachers’ stated practices as a means of addressing specific beliefs about teaching.

In addition to beliefs, other variables have been identified that influence the use of ICTs such as gender, age, educational level, or subject curriculum, with results that are usually inconclusive. Thus, while Mathews and Guarino (2000) found that men were more inclined toward the use of ICTs than women, in other studies no differences were found ( Gorder, 2008 ; Law and Chow, 2008 ). Similarly, other studies ( van Braak et al., 2004 ; Suárez et al., 2012 ) concluded that there was an inverse relationship between the age of the teachers and their interest in ICT, but other studies did not confirm this conclusion ( Gorder, 2008 ; Law and Chow, 2008 ; Inan and Lowther, 2010 ). Finally, the teaching experience gives equally ambiguous results; some papers report a negative relationship ( Mathews and Guarino, 2000 ; Baek et al., 2008 ; Inan and Lowther, 2010 ) while others find no relationship ( Gorder, 2008 ).

The influence of factors like educational level or curriculum subjects has also been analyzed. The data seem to be more conclusive regarding educational level: teachers in secondary education have more favorable attitudes toward ICT than teachers of earlier levels ( Gorder, 2008 ; Vanderlinde et al., 2010 ). However, the data are not so conclusive regarding the influence of curriculum subjects ( Williams et al., 2000 ; Gorder, 2008 ; Vanderlinde et al., 2010 ).

Although it will take time to understand what has happened in teaching during these months, many studies and proposals have analyzed the use of ICT in distance education. We can classify them into three types of research. The first type of analyses has measured the impact of classroom closures on the education of students, many of them focusing on their effects on inequality or the way different countries have dealt with this crisis ( Crawford et al., 2020 ; Reimers and Schleicher, 2020 ; Zhang et al., 2020 ). Second, studies have aimed at proposing principles that should guide the use of ICT in the classroom ( Ferdig et al., 2020 ; Rapanta et al., 2020 ; Sangrà et al., 2020 ). The last ones, which are close to the aims of this study, are focused on how teachers have used ICT for the COVID-19 crisis. Some of these studies have carried out qualitative case analyses in different contexts, institutions ( Koçoğlu and Tekdal, 2020 ; Rasmitadila et al., 2020 ), and even countries ( Hall et al., 2020 ; Iivari et al., 2020 ). However, others have resorted to the use of questionnaires applied to larger samples to inquire about the teaching experience for confined education ( Devitt et al., 2020 ; Luengo and Manso, 2020 ; Tartavulea et al., 2020 ; Trujillo-Sáez et al., 2020 ). These studies have concluded the most common use by teachers was to upload materials to a platform ( Tartavulea et al., 2020 ); the most activities were teacher-centered ( Koçoğlu and Tekdal, 2020 ); or the more constructivist the teachers are, the more ICT use is reported for confined education ( Luengo and Manso, 2020 ).

However, despite these indications, there has been no study that analyzes the activities and uses of ICT in school during confinement. What learning have teachers prioritized in this period? Has it been more oriented toward verbal, procedural, or attitudinal learning? ( Pozo, in press ). Through what activities, either more constructive or reproductive, have these learnings been promoted? Have the ICT been used to assess the accumulation of information or the global competencies in its management? What variables prompt carrying out one type of activity or another? These are some questions that have guided our research and are reflected in the following specific objectives.

1. Identifying the frequency with which Spanish teachers of primary, and compulsory and non-compulsory secondary education carried out activities using ICT during the pandemic, and how some variables influence this frequency (gender, teaching experience, previous ICT use, educational level, and curriculum subjects).

2. Analyzing the type of learning (reproductive or teacher-centered vs. constructive or student-centered) promoted most frequently by these teachers, as well as the influence of the variables mentioned.

3. Analyzing the types of outcomes (verbal learning, procedural learning, or attitudinal learning), assessment, and social organization promoted by the ICT and the possible influence of the mentioned variables.

4. Investigating if different teaching profiles can be identified in the use of ICT, as well as their relationship with the variables studied.

Regarding objective 1, as the contradictory results reviewed in the Introduction showed, it is difficult to sustain a concrete hypothesis. However, in the case of objective 2, as argued in the Introduction, we expect to find a higher frequency of reproductive activities (or teacher-centered) than constructive (student-centered). Along the same lines, concerning the third objective, we hope to find more activities oriented to verbal learning, reproductive assessment, and individual organization of tasks, with few activities based on cooperation between students. Finally, about objective 4, we hope to identify teacher profiles that differ in the frequency and type of activities proposed to their students and that these profiles are related to some of the demographic variables analyzed in the study.

Materials and Methods

Task and procedure.

To achieve these objectives, we designed a questionnaire on ICT through the Qualtrics software and sent telematically to various networks of teachers and primary and secondary education centers in Spain. For the construction of the questionnaire, we consulted different blogs where teachers shared the activities they were applying during the pandemic. The questionnaire was composed of two parts. In the first one, after participants gave informed consent, they were requested to provide personal and professional information (see Table 2 ). The second part comprised 36 items that described different types of teaching activities. Participants were asked to rate how often they carried them out on a Likert scale (1, Never; 2 Some days per month; 3, Some days per week; and 4, Every day). After the analysis of the methodologies carried out in the Introduction, we considered asking teachers what they were doing in their classrooms was the most accurate procedure to know the true practices they were carrying out. On the one hand, we wanted to avoid the bias of classic questionaries on conceptions that require teachers to express their agreement with some beliefs. On the other hand, the analysis of teachers’ actual practices in their classrooms would require a different, more qualitative work, with a smaller sample size.

As we show in Table 1 , these activities were directed toward reproductive and constructive learning and different types of learning outcomes (verbal, procedural, and attitudinal), assessment (usually called summative and formative assessment), and cooperative activities.

Table 1. Structure and examples of questionnaire items.

Table 2. Characteristics of the sample and variables.

Participants

The participants were primary and secondary education teachers who were working in Spain when they completed the questionnaire. In Spain, compulsory education is from 6 to 16 years. In primary education (6–12 years), a single generalist teacher imparts most of the subjects, while specialist teachers (music, physical education, foreign language, etc.) only attend class during the hours of their subjects. After compulsory secondary education, there is a non-compulsory secondary education (16–18 years old) that is taught in the same centers as compulsory secondary education and by the same teachers.

We used directories of emails from public, private schools, and high schools of Spain to get in contact with the participants. Besides, to encourage participation, we raffled 75 euros for the purchase of teaching materials among all participants. We collected 1,541 answers. We eliminated 52 of them because they belonged to people who were not teachers of primary or secondary education in Spain. Then, we removed 45 participants who completed the questionnaire in less than 5 min, insufficient time to read and complete it, and we excluded 41 participants who indicated the 3rd (“Some days per week”) or 4th option (“Every day”) in over 80% of the items. We argue this exclusion as it is unlikely that a teacher could carry out such a quantity of activities in the span of a week. The questionnaire has 36 activities, so doing over 80% of items with a frequency of a minimum some days per week implies carrying out almost 29 activities per week. We consider this is not possible in the pertaining virtual class context and noted several contradictions in the answers. Therefore, the final sample had 1,403 teachers (see Table 2 ). Note that the sum of all variables does not reach this total because some values were so unusual that they were not considered in the statistical analyses.

Data Analysis

To ensure the consistency of the questionnaire and the dimensions, a reliability analysis was carried out using Cronbach’s Alpha coefficient. The reliability of the scale was 0.90, the reproductive and constructive scales obtained alphas above 0.75, and the verbal, procedural, attitudinal, assessment, and cooperation dimensions got alphas above 0.65.

The 1, 2, and 3 objectives were analyzed with one and two-factor ANOVA. These factors can be both repeated measures and completely randomized, according to the characteristics of the variable. Besides, we carried out post hoc analysis in which the Tukey or Bonferroni correction was applied depending on whether the ANOVA was 1 or 2 factors, to see the differences between categories in the ANOVA analyses. However, post hoc analyses were only performed on the ANOVA of the two factors when the interaction effects were significant.

Finally, a cluster analysis was implemented to identify different teaching profiles (objective 4). Once identified, we created contingency tables and their corresponding Corrected Typified Residuals (CTR) to know which variables were related to each profile. Finally, we carried out ANOVA to analyze the differences between profiles according to each of the designed dimensions. All the statistical analyses were carried out using SPPS version 26.

The results are written referring to what the teachers were doing to facilitate reading. However, in all cases, we refer to declared activities.

Frequency of Activities Carried Out

Regarding the first objective, teachers performed the activities between Some days per week and Some days per month on average ( M = 2.44, SD = 0.50). However, this frequency varied according to teaching experience, educational level, curriculum subject, and previous ICT use. Gender did not produce differences (see Table 3 ). In the case of teaching experience, according to the post hoc tests, teachers with intermediate experience (from 16 to 25 years) carried out a lower number of activities than novice teachers (5 years or fewer) ( p < 0.05). In turn, teachers who taught children between 6 and 9 years old were also less active than the rest ( p < 0.01). Within primary education, the generalists, who spend more time with the same students, proposed more activities than the specialists ( p < 0.01). In secondary education, the teachers of Spanish language were more active than those of mathematics and physical education ( p < 0.01). Finally, there seems to be a positive linear relationship between previous ICT use and the amount of activity for confined education ( F = 61.66, p < 0.001).

Table 3. Influence of personal and professional variables on the frequency of activities.

Teaching Activities: Reproductive or Constructive?

Nevertheless, we were not so much interested in the total amount of activities carried out as in the type of learning they promoted (reproductive or constructive). For this, we proposed objective 2. The data was overwhelming. They showed much greater use of reproductive ( M = 2.79, SD = 0.50) than constructive ( M = 2.16, SD = 0.60) learning activities ( F = 2,217.91, p < 0.001, η p 2 = 0.61). This is the largest and most robust effect size in this study; it occurs in all groups and for all variables ( p < 0.001), although to a different degree, as shown in Table 4 .

Table 4. Influence of the different variables on the type of activity.

Post hoc results reveal that novice teachers (5 years or fewer), the most active group according to the previous analysis, performed more reproductive activities than teachers with experience from 16 to 25 years ( p < 0.01), the least active one. However, the most experienced teachers (more than 25 years) executed more constructive activities than those with intermediate experience (from 16 to 25 years) ( p < 0.05). The teachers of children between 6 and 9 years old did less reproductive and constructive activities ( p < 0.05) than the rest of the groups, with significant differences in all cases except in the case of the teachers of non-compulsory secondary education, who stated less reproductive activities than they did.

In secondary education, the mathematics teachers did less constructive activities than those of Spanish language and social sciences ( p < 0.05). In turn, physical education teachers performed less reproductive activities than the rest of their classmates ( p < 0.01).

Finally, the higher the previous ICT the teachers used, the higher the frequencies indicated by them in both reproductive ( F = 33.57, p < 0.001) and constructive activities ( F = 61.61, p < 0.001). Notwithstanding, the size of the observed effect shows greater differences in the case of constructive activities (reproductive, F = 13.94, p < 0.001, η p 2 = 0.29, vs. constructive, F = 25.60, p < 0.001, η p 2 = 0.95).

Learning Outcomes, Assessment, and Cooperation Dimensions

The third objective was to determine what kind of learning outcomes resulted from the activities. As we show in Figure 1 , the teachers focused more on verbal and attitudinal learning than on procedural ( F = 100.11, p < 0.001, η p 2 = 0.07). On the other hand, the mean responses of the assessment tasks were similar to those of verbal learning and attitudinal learning, but the cooperative activities were less frequent than the remainder ( p < 0.001), performed between never and some days per month ( M = 1.78; SD = 0.74). However, as we see in Table 5 , these results are mediated by the effect of some variables.

Figure 1. Average of the frequencies of each type of activity.

Table 5. Influence of different variables on the frequency of activities for each dimension.

Post hoc analyses show that men carried out more activities focused on procedural learning than women ( p < 0.05), who in turn promoted more activities related to attitudinal learning ( p < 0.001). Men also carried out more cooperation activities than women ( p < 0.01), but there were no differences among them in the Assessment activities. However, the only effect related to teaching experience shows that less experienced teachers (5 years or fewer) carried out more assessment activities than teachers with intermediate experience (from 16 to 25 years) ( p < 0.05).

The teachers of the youngest children (6–9 years old) carried out more activities aimed at attitudinal learning ( p < 0.05) and fewer at procedural learning ( p < 0.01) than the rest of the teachers. Interestingly, the activities aimed at attitudinal learning decreased progressively when the educational level increased, with differences between the upper level of primary education (9–12 years) and secondary education ( p < 0.001). At the same time, the older the students were, the more verbal learning activities they performed, with differences between the first years of primary education (6–9 years) and secondary education (12–18) ( p < 0.05). Besides, the assessment and cooperation activities became more frequent as the educational levels advanced, with differences in both cases between the teachers of the first years of primary education ( p < 0.01) and the last years of primary education and non-compulsory secondary education ( p < 0.05).

In secondary education, verbal learning predominates in almost every subject. However, the Spanish language and foreign language teachers also carried out many activities aimed at attitudinal learning. Only in technology were more activities aimed at procedural learning executed compared to the others ( p < 0.05). At the same time, the mathematics teachers stand out for their little use of cooperation activities. To sum up, the activities aimed at verbal learning increase their frequency when the educational level increases, while attitudinal learning decreases. Nevertheless, the characteristics of each subject have some influence on the increases among educational levels. The cooperation activities also increase, although their frequency is still small. Finally, again, the higher the previous ICT use, the higher the frequency of all activities during the pandemic ( p < 0.001).

But all these differences become more meaningful when we look at the type of learning (reproductive or constructive) that is promoted by these activities. Again, as we see in Figure 2 , there is a considerable difference between the reproductive and constructive activities regardless of the dimension involved (see Table 6 ), a trend also confirmed by the low frequency of cooperation activities that, by their nature, promote constructive learning. It is remarkable that the highest differences between both scales happen in attitudinal learning. In fact, the most frequent activities in the questionnaire involved attitudinal reproductive learning.

Figure 2. Average of the reproductive and constructive activities in each dimension.

Table 6. Differences between reproductive and constructive activities in the dimensions.

Profiles of Teachers in the Use of ICT

Our final objective was to identify possible profiles in the use of ICT during confined education. For this purpose, we proceeded with a cluster analysis that allowed us to identify different teaching profiles as we showed in Figure 3 . After testing clusters of three centers in which the groups only differed in the number of activities, we executed a four centers cluster, which showed differences in the amount of activity ( F = 2,220.33, p < 0.001, η p 2 = 0.83) and the mean differences between reproductive and constructive activities ( F = 310.39, p < 0.001, η p 2 = 0.40).

Figure 3. Frequency of use of reproductive and constructive activities for each teachers’ profile.

• The first profile (“Passive”) was composed of 327 teachers who were characterized by a very low activity (MD = 0.63, SD = 0.02, p < 0.001), essentially reproductive ( M = 2.15, SD = 0.35) and scarcely constructive ( M = 1.52, SD = 0.29).

• The second profile (“Active”) was composed of 424 teachers, was the most numerous. It had a very similar pattern to the previous one, focused mainly on reproductive activities ( M = 2.82, SD = 0.33) rather than constructive ( M = 2.41, SD = 0.21) but with a higher level of activity ( MD = 0.41, SD = 0.02, p < 0.001).

• The third profile (“Reproductive”) was composed of 263 teachers with a similar level of activity to the previous one. However, they have a relatively higher frequency of reproductive activities ( M = 2.93, SD = 0.29) with hardly any constructive activities ( M = 1.82, SD = 0.24).

• The fourth profile (“Interpretative”) which was composed of 389 teachers, was corresponded to the most active teachers. This profile had the smallest differences between reproductive ( M = 3.32, SD = 0.29) and constructive activities ( M = 3.04, SD = 0.31), ( MD = 0.29, SD = 0.02, p < 0.001). According to the terminology used in the introduction, we have called it Interpretative because it integrated both types of activities.

Among the different profiles, we found systematic differences in the dimensions and types of learning. In fact, all differences among profiles were significant ( p < 0.01) except between the Active and Reproductive profiles in verbal, procedural, and attitudinal reproductive learning. There were also no differences between the Passive and Reproductive profiles in cooperative activities because of their low frequency in both groups. On the other hand, teachers in the Interpretive profile carried out more activities in all dimensions than the rest of the groups; the teachers of the Passive profile did fewer tasks than the others (except in the cases already indicated) and finally, the other two profiles maintained an intermediate level of activity, with the difference that the teachers of the Reproductive profile focused almost exclusively on reproductive activities as we see in Figure 4 .

Figure 4. Use of each dimension for each teachers’ profile.

The distribution of teachers in each of the four profiles varied depending on educational level (χ 2 = 29.57, p < 0.001), primary curriculum subjects (χ 2 = 60.97, p < 0.001), secondary curriculum subjects (χ 2 = 60.97, p < 0.001), and previous ICT use (χ 2 = 77.46, p < 0.001). We did not find any relationship with gender or teaching experience, the variables with the least influence in the study.

As we see in Table 7 , the first profile or Passive was over-represented by teachers of children aged 6–9, and teachers of non-compulsory secondary education were under-represented. Between the primary education teachers, specialists predominated, and there were practically no generalist teachers. The only secondary education teachers that appeared in this profile were physical education ones. Finally, there is a significant number of teachers who had not used ICT with their students before the confinement, and there was hardly any representation of those who had most used them.

Table 7. Variables related to each of the profiles.

The second or Active profile is distributed homogeneously way among the different educational levels. It is predominantly formed by secondary education teachers of Spanish language and social sciences. In the third or Reproductive profile, secondary education teachers who taught mathematics, and those who had never used ITC in the classroom were over-represented.

The fourth or Interpretative profile, characterized by integrating reproductive and constructive activities, had hardly any teachers of children from 6 to 9 years old nor specialist teachers of primary education, unlike the first profile. However, this profile included a high number of generalist teachers of primary education and Spanish language teachers of secondary education. On the other hand, it had a few mathematics teachers from secondary education who were over-represented in the Reproductive profile. Finally, the teachers who used ICT more before confinement were also over-represented, and there were hardly any teachers who had not used them.

Discussion and Conclusion

In this study, taking advantage of the critical incident caused by the COVID-19 pandemic, we analyzed the type of activities with ICT that primary and secondary education teachers proposed to their students. Our purpose was to check if, in this context, ICT contributed to promoting more constructive ways of teaching. The most dominant effect of the results, related to the second aim of the study, showed that teachers carried out significantly more activities oriented to reproductive learning than constructive ones. In other words, they preferred teacher-centered activities to student-centered ones. This effect was very robust ( F = 2,217.91, p < 0.001, η p 2 = 0.61), and it was manifested in all dimensions of the questionnaire, was maintained when we introduced any of the variables studied and was presented in all profiles.

On the other hand, our work has revealed other variables that influence the frequency of ICT use. Thus, we have found that teachers who attend to young children use them less than teachers of older students. These data coincide with those found in other works ( Gorder, 2008 ; Vanderlinde et al., 2010 ) and are probably related to the characteristics of the teaching activity itself. It is undoubtedly more arduous to use ICT in class with young children than with adolescents or adults. We have also found a greater frequency of use by generalists than specialists because the former teach more hours in the same class and consequently have more responsibilities with their students. Both the specialists and the teachers of the youngest children were overrepresented in the Passive profile. Nevertheless, the influence of the subjects taught in compulsory and non-compulsory secondary education is not so clear. We found there was hardly any influence of gender on different results. Data from other studies show that the influence of this variable is quite unstable and varies among studies ( Mathews and Guarino, 2000 ; Gorder, 2008 ; Law and Chow, 2008 ). However, teaching experience seems to influence in another way: whereas less experienced teachers are more reproductive, the more experienced teachers present fewer differences between reproductive and constructive activities. It should be noted that in other studies this variable has also shown ambiguous results ( Mathews and Guarino, 2000 ; Baek et al., 2008 ; Gorder, 2008 ; Inan and Lowther, 2010 ).

The third objective analyzed the learning outcomes that the activities provided, the type of assessment used, and the cooperation that activities promoted. In general, we have seen that teachers performed more verbal and attitudinal learning than procedural. However, in these cases (as well as in the assessment), activities were aimed at reproductive instead of constructive learning. The least frequent activities were cooperative (between never and some days per month), which is consistent with the importance given to reproduction. The salience of verbal learning increased as the higher the educational level was and, in the same way, the attitudinal activities decreased, with hardly any change in the procedural ones.

Considering that these data were collected in Spain when there were strict confinement and social isolation, we would emphasize that the activities related to attitudes were directed at maintaining classroom control in all groups and profiles (but outside the classroom) whereas there was much less frequency of activities focused on getting the ability to managing student attitudes, behavior or self-control during that situation of confinement. This difference suggests that teachers were more concerned about controlling their students’ study habits.

Regarding our fourth objective, we find four profiles of teachers (Passive, Active, Reproductive, and Interpretative). The first two differed only in the amount of total activity performed, while the Reproductive one was characterized by almost exclusively executing reproductive learning activities. Although, as in the previous groups, the Interpretative teachers carried out many reproductive activities, they also carried out constructive activities with considerable frequency. Teachers of children from 3 to 6 years, for whom engaging in the virtual activity is more complicated, abounded in the Passive profile. However, in the Reproductive profile, teachers of mathematics of secondary education predominated. In contrast, in the Interpretative profile, in which there were fewer differences between reproductive and constructive activities, generalists of primary education and teachers of social and natural sciences and Spanish language of secondary education were over-represented. But principally, this profile was over-represented by teachers who had previously used ICT.

In conclusion, it seems the teachers in this study use ICT essentially for presenting different kinds of information ( Tondeur et al., 2008b ) and do not use them as learning tools that help students to build, manage, and develop their knowledge. On the other hand, this study seems to show that teachers’ beliefs are much closer to the reproductive pole than to the constructive one. In this study, beliefs have been inferred through the frequency with which the teachers stated they carried out predetermined activities. In our view, the description of the activities was much closer to the actual practices and theories of the teachers than the results that questionnaires on beliefs could provide us with. For this reason, we expect the mismatch between theories and practices ( Liu, 2011 ; Fives and Buehl, 2012 ; Tsai and Chai, 2012 ; Mama and Hennessy, 2013 ; Ertmer et al., 2015 ; de Aldama and Pozo, 2016 ) was smaller and helped us to discover the true beliefs of teachers when they teach.

We could therefore conclude that, despite all the educational possibilities and all the promises of change in teaching that ICT raise ( Jaffee, 1997 ; Collins and Halverson, 2009 ), teachers have only perceived these tools as informative support. It seems the critical incident caused by the pandemic has not been resolved in the short-term with a change in favor of student-centered activities and content-centered ones continue predominating. Therefore, our data are more consistent with the results of some international mass studies ( Biagi and Loi, 2013 ; OECD, 2015 ) than with the experimental works that analyze how teachers who are previously chosen use ICT ( Tamim et al., 2011 ; Alrasheedi et al., 2015 ; Sung et al., 2015 ; Clark et al., 2016 ; Xie et al., 2018 ; Mayer, 2019 ). However, there is no doubt that the pandemic has contributed to familiarizing teachers with ICT. In our results, previous use of ICT was the variable that produced the most systematic differences in both the frequency of proposed reproductive and constructive activities. In this sense, perhaps the pandemic may have contributed to an increase in teachers’ experience in two of the three educational computer uses described by Tondeur et al. (2008a) : basic computer skills and use of computers as an information tool. Maybe, this fact could contribute in the future to using the third one, the use of ICT as learning tools. However, there are undoubtedly other variables related to first-order and second-order barriers (beliefs) or teacher training with ICT that influence this possibility of change.

In summary, our work shows that activities carried out through ICT during confined schooling were more teacher-centered than student-centered and hardly promoted the 21st-century skills, that digital technologies should facilitate ( Ertmer et al., 2015 ). However, the data also show that the greater the stated previous use of ICT, the greater and more constructive its use was reported for the pandemic. Previous use of ICTs is related not only to beliefs about their usefulness but also to specific training to master these tools and to use them in a versatile manner, adapted to different purposes or objectives. It seems clear that teacher training should be promoted not only to encourage more frequent use of ICT but also to change conceptions toward them to promote constructive learning. In this sense, the forced use of ICT because of COVID-19 will only encourage this change if we support teachers with adequate resources and activities which facilitate reflection on their use.

However, we should consider that one limitation of this study is that the practices analyzed were those declared by the teachers. It would be necessary to complete this study with an analysis of the practices that the teachers really applied and to analyze their relationship with their conceptions of learning and teaching. In fact, we are currently analyzing the actual practices of a sub-sample of the teachers who filled out the questionnaire, taking the profiles found in this work as the independent variable. In future research, it would be necessary to analyze the relationship between student learning and these different teaching practices.

Data Availability Statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Ethics Statement

The studies involving human participants were reviewed and approved by the Ethics Committee of the Autonomous University of Madrid. The patients/participants provided their written informed consent to participate in this study.

Author Contributions

J-IP: funding acquisition, project administration, conceptualiza-tion, methodology, supervision, writing – original draft, and writing – review and editing. M-PE: funding acquisition, conceptualization, methodology, validation, writing – original draft, and writing – review and editing. BC: conceptualization, methodology, data curation, formal analysis, investigation, software, writing – original draft, writing – review and editing, and visualization. DLS: conceptualization, methodology, and writing – review and editing. All authors contributed to the article and approved the submitted version.

This work was supported by the Ministry of Innovation and Science of Spain (EDU2017-82243-C2-1-R).

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.

Acknowledgments

We would like to thank our colleagues from SEIACE for their participation in the item dimension task. We would also like to thank Ricardo Olmos for sharing his statistical knowledge with us. Finally, we would like to appreciate Krystyna Sleziaka her support with the translation of this paper.

Alrasheedi, M., Capretz, L. F., and Raza, A. (2015). A systematic review of the critical factors for success of mobile learning in higher education (University Students’ Perspective). J. Educ. Comput. Res. 52, 257–276. doi: 10.1177/0735633115571928

CrossRef Full Text | Google Scholar

Ananiadou, K., and Claro, M. (2009). 21st Century Skills and Competences for New Millennium Learners in OECD Countries. OECD Education Working Papers, 41. Paris: OECD Publishing. doi: 10.1787/218525261154

Bagshaw, E. (2016). The Reality is that Technology is Doing More Harm than Good in our Schools’ says Education Chief. North Sydney, NSW: Sydney Morning Herald.

Google Scholar

Baek, Y., Jung, J., and Kim, B. (2008). What makes teachers use technology in the classroom? Exploring the factors affecting facilitation of technology with a Korean sample. Comput. Educ. 50, 224–234. doi: 10.1016/j.compedu.2006.05.002

Biagi, F., and Loi, M. (2013). Measuring ICT use and learning outcomes: evidence from recent econometric studies. Eur. J. Educ. 48, 28–42. doi: 10.1111/ejed.12016

Bautista, A., Pérez Echeverría, M. P., and Pozo, J. I. (2010). Music performance teachers’ conceptions about learning and instruction: a descriptive study of Spanish piano teachers. Psychol. Music 38, 85–106. doi: 10.1177/0305735609336059

Bubb, S., and Jones, M. A. (2020). Learning from the COVID-19 home-schooling experience: listening to pupils, parents/carers and teachers. Improv. Sch. 23, 209–222. doi: 10.1177/1365480220958797

Butterfield, L. D., Borgen, W. A., Amundson, N. E., and Maglio, A.-S. T. (2005). Fifty years of the critical incident technique: 1954–2004 and beyond. Qual. Res. 5, 475–497. doi: 10.1177/1468794105056924

Clark, D. B., Tanner-Smith, E. E., and Killingsworth, S. S. (2016). Digital games, design, and learning: a systematic review and meta-analysis. Rev. Educ. Res. 86, 79–122. doi: 10.3102/0034654315582065

PubMed Abstract | CrossRef Full Text | Google Scholar

Colao, A., Piscitelli, P., Pulimeno, M., Colazzo, S., Miani, A., and Giannini, S. (2020). Rethinking the role of the school after COVID-19. Lancet Public Health 5:e370. doi: 10.1016/S2468-2667(20)30124-9

Collins, A., and Halverson, R. (2009). Rethinking Education in the Age of Digital Technology. New York, NY: Teacher’s College Press.

Comi, S. L., Argentin, G., Gui, M., Origo, F., and Pagani, L. (2017). Is it the way they use it? Teachers, ICT and student achievement. Econ. Educ. Rev. 56, 24–39. doi: 10.1016/j.econedurev.2016.11.007

Corcelles Seuba, M., and Castelló, M. (2015). Learning philosophical thinking through collaborative writing in secondary education. J. Writing Res. 7, 157–200. doi: 10.17239/jowr-2015.07.01.07

Crawford, J., Butler-Henderson, K., Rudolph, J., Malkawi, B., Glowatz, M., Burton, R., et al. (2020). COVID-19: 20 countries’ higher education intra-period digital pedagogy responses. J. Appl. Learn. Teach. 3, 9–28. doi: 10.37074/jalt.2020.3.1.7

de Aldama, C. (2020). Cognitive enhancement or cognitive diminishing? Digital technologies and challenges for education from a situated perspective. Límite Interdiscip. J. Philos. Psychol. 15:21.

de Aldama, C., and Pozo, J. I. (2016). How are ICT use in the classroom? A study of teachers’ beliefs and uses. Electron. J. Res. Educ. Psychol. 14, 253–286. doi: 10.14204/ejrep.39.15062

Devitt, A., Bray, A., Banks, J., and Ní Chorcora, E. (2020). Teaching and Learning During School Closures: Lessons Learned. Irish Second-Level Teacher Perspectives. Dublin: Trinity College Dublin

Dorn, E., Hancock, B., Sarakatsannis, J., and Viruleg, E. (2020). COVID-19 and Learning Loss—Disparities Grow and Students Need Help. Chicago, IL: McKinsey & Company.

Ertmer, P. A. (1999). Addressing first-and second-order barriers to change: strategies for technology integration. Educ. Technol. Res. Dev. 47, 47–61. doi: 10.1007/BF02299597

Ertmer, P. A. (2005). Teacher pedagogical beliefs: the final frontier in our quest for technology integration? Educ. Technol. Res. Dev. 53, 25–39. doi: 10.1007/BF02504683

Ertmer, P. A., Ottenbreit-Leftwich, A. T., Sadik, O., Sendurur, E., and Sendurur, P. (2012). Teacher beliefs and technology integration practices: a critical relationship. Comput. Educ. 59, 423–435. doi: 10.1016/j.compedu.2012.02.001

Ertmer, P. A., Ottenbreit-Leftwich, A. T., and Tondeur, J. (2015). “Teachers’ beliefs and uses of technology to support 21st-century teaching and learning,” in International Handbook of Research on Teachers’ Beliefs , eds H. Fives and M. G. Gill (New York, NY: Routledge), 403–418.

Farías, M., Obilinovic, K., and Orrego, R. (2010). Modelos de aprendizaje multimodal y enseñanza-aprendizaj e de lenguas extranjeras [Models of multimodal learning and foreign language teaching-learning]. Univ. Tarraconensis 1, 55–74. doi: 10.17345/ute.2010.2.631

Ferdig, R. E., Baumgartner, E., Hartshorne, R., Kaplan-Rakowski, R., and Mouza, C. (2020). Teaching, Technology, and Teacher Education During the COVID-19 Pandemic: Stories from the Field. Waynesville, NC: Association for the Advancement of Computing in Education (AACE).

Fives, H., and Buehl, M. M. (2012). “Spring cleaning for the “messy” construct of teachers’ beliefs: What are they? Which have been examined? What can they tell us?,” in APA Educational Psychology handbook: Individual Differences and Cultural and Contextual Factors , Vol. 2, eds K. R. Harris, S. Graham, T. Urdan, S. Graham, J. M. Royer, and M. Zeidner (Washington, DC: American Psychological Association), 471–499. doi: 10.1037/13274-019

Fives H. and (Eds.) Gill M. G. (2015). International Handbook of Research on Teachers’ Beliefs. New York, NY: Routledge.

Fulton, K. (1997). The Skills Students Need for Technological Fluency. Santa Monica, CA: Milken Exchange on Education Technology.

Genlott, A. A., and Grönlund, Å (2016). Closing the gaps - Improving literacy and mathematics by ICT-enhanced collaboration. Comput. Educ. 99, 68–80. doi: 10.1016/j.compedu.2016.04.004

Gorder, L. M. (2008). A study of teacher perceptions of instructional technology integration in the classroom. Delta Pi Epsilon J. 50, 63–76.

Hall, T., Connolly, C., Ó Grádaigh, S., Burden, K., Kearney, M., Schuck, S., et al. (2020). Education in precarious times: a comparative study across six countries to identify design priorities for mobile learning in a pandemic. Inform. Learn. Sci. 121, 433–442. doi: 10.1108/ILS-04-2020-0089

Hennessy, S., Deaney, R., Ruthven, K., and Winterbottom, M. (2007). Pedagogical strategies for using the interactive whiteboard to foster learner participation in school science. Learn. Media Technol. 32, 283–301. doi: 10.1080/17439880701511131

Hermans, R., Tondeur, J., van Braak, J., and Valcke, M. (2008). The impact of primary school teachers’ educational beliefs on the classroom use of computers. Comput. Educ. 51, 1499–1509. doi: 10.1016/j.compedu.2008.02.001

Hofer, B. K., and Pintrich, P. R. (1997). The development of epistemological theories: beliefs about knowledge and knowing and their relation to learning. Rev. Educ. Res. 67, 88–140. doi: 10.3102/00346543067001088

Hofer, B. K., and Pintrich, P. R. (eds) (2002). Personal Epistemology: The Psychology of Beliefs about Knowledge and Knowing. Mahwah, NJ: L. Erlbaum Associates.

Iivari, N., Sharma, S., and Ventä-Olkkonen, L. (2020). Digital transformation of everyday life – How COVID-19 pandemic transformed the basic education of the young generation and why information management research should care? Int. J. Inform. Manag. 55:102183. doi: 10.1016/j.ijinfomgt.2020.102183

Inan, F. A., and Lowther, D. L. (2010). Factors affecting technology integration in K-12 classrooms: a path model. Educ. Technol. Res. Dev. 58, 137–154. doi: 10.1007/s11423-009-9132-y

Jaffee, D. (1997). Asynchronous learning: technology and pedagogical strategy in a distance learning course. Teach. Sociol. 25, 262–277. doi: 10.2307/1319295

Judson, E. (2006). How teachers integrate technology and their beliefs about learning: is there a connection? J. Technol. Teacher Educ. 14, 581–597.

Koçoğlu, E., and Tekdal, D. (2020). Analysis of distance education activities conducted during COVID-19 pandemic. Educ. Res. Rev. 15, 536–543. doi: 10.5897/ERR2020.4033

Law, N., and Chow, A. (2008). “Teacher characteristics, contextual factors, and how these affect the pedagogical use of ICT,” in Pedagogy and ICT use in Schools Around the World. Findings From the IEA SITES 2006 Study , eds N. Law, W. J. Pelgrum, and T. Plomp (Hong Kong: Springer).

Li, Q., and Ma, X. (2010). A meta-analysis of the effects of computer technology on school students’ mathematics learning. Educ. Psychol. Rev. 22, 215–243. doi: 10.1007/s10648-010-9125-8

Liu, S.-H. (2011). Factors related to pedagogical beliefs of teachers and technology integration. Comput. Educ. 56, 1012–1022. doi: 10.1016/j.compedu.2010.12.001

López-Íñiguez, G., Pozo, J. I., and de Dios, M. J. (2014). The older, the wiser? Profiles of string instrument teachers with different experience according to their conceptions of teaching, learning, and evaluation. Psychol. Music 42, 157–176. doi: 10.1177/0305735612463772

López-Íñiguez, G., and Pozo, J. I. (2014). Like teacher, like student? Conceptions of children from traditional and constructive teaching models regarding the teaching and learning of string instruments. Cogn. Inst. 32, 219–252. doi: 10.1080/07370008.2014.918132

Loveless, A., and Dore, B. (2002). ICT in the Primary School. Buckingham: Open University Press.

Luengo, F., and Manso, J. (eds) (2020). Informe de Investigación COVID19. Voces de docentes y familias. [Report on COVID19 Investigation. Voices from Teachers and Families]. Madrid: Proyecto Atlántida.

Mama, M., and Hennessy, S. (2013). Developing a typology of teacher beliefs and practices concerning classroom use of ICT. Comput. Educ. 68, 380–387. doi: 10.1016/j.compedu.2013.05.022

Martín, E., Pozo, J. I., Mateos, M., Martín, A., and Pérez Echeverría, M. P. (2014). Infant, primary and secondary teachers’ conceptions of learning and teaching and their relation to educational variables. Rev. Latinoameric. Psicol. 46, 211–221. doi: 10.1016/S0120-0534(14)70024-X

Mathews, J. G., and Guarino, A. J. (2000). Predicting teacher computer use: a path analysis. Int. J. Inst. Media 27, 385–392.

Mayer, R. E. (2019). Computer games in education. Annu. Rev. Psychol. 70, 531–549. doi: 10.1146/annurev-psych-010418-102744

Monereo, C. (2010). La formación del profesorado: una pauta para el análisis e intervención a través de incidentes críticos. [Teacher education: a standard for analysis and intervention through critical incidents]. Rev. Iberoameric. Educ. 52, 149–178. doi: 10.35362/rie520615

Monereo, C., Monte, M., and Andreucci, P. (2015). La Gestión de Incidentes Críticos en la Universidad . [Management of critical incidents in university]. Madrid: Narcea.

OECD (2015). Students, Computers and Learning: Making the Connection. Paris: OECD Publishing. doi: 10.1787/9789264239555-en

OECD (2019). PISA 2018 results: What Students Know and Can do , Vol. I, Paris: OECD Publishing. doi: 10.1787/5f07c754-en

OECD (2020). How Prepared are Teachers and Schools to Face the Changes to Learning Caused by the Coronavirus Pandemic? Teaching in Focus 32 , Paris: OECD Publishing. doi: 10.1787/2fe27ad7-en

Pajares, M. F. (1992). Teachers’ beliefs and educational research: cleaning up a messy construct. Rev. Educ. Res. 62, 307–332. doi: 10.3102/00346543062003307

Pérez Echeverría, M. P. (in press). “How teachers and students conceive music education: towards changing mentalities,” in Learning and Teaching Music: A Student-Centered Approach , eds J. I. Pozo, M. P. Pérez-Echeverría, G. Torrado, and J. A. López-Íñiguez (Berlin: Springer).

Pérez Echeverría, M. P., Mateos, M., Scheuer, N., and Martín, E. (2006). “Enfoques en el estudio de las concepciones sobre el aprendizaje y la enseñanza. [Approaches for studying conceptions on learning and teaching],” in Nuevas formas de pensar la enseñanza y el aprendizaje: Las concepciones de profesores y alumnos , eds J. I. Pozo, N. Scheuer, M. P. Pérez Echeverría, M. Mateos, E. Martín, and M. de la Cruz (Barcelona: Graó), 55–94.

Pérez Echeverría, M. P., and Pozo, J. I. (in press). “How to know and analyse conceptions on learning and teaching,” in Learning and Teaching Music: A Student-Centered Approach , eds J. I. Pozo, M. P. Pérez Echeverría, G. López-Íñiguez, and J. A. Torrado (Berlin: Springer).

Pozo, J. I. (in press). “The psychology of music learning,” in Learning and Teaching Music: A Student-Centered Approach , eds J. I. Pozo, M. P. Pérez Echeverría, G. López-Íñiguez, and J. A. Torrado (Berlin: Springer).

Pozo, J. I., Scheuer, N., Pérez Echeverría, M. P., Mateos, M., Martín, E., and de la Cruz, M. (2006). Nuevas Formas de Pensar la Enseñanza y el Aprendizaje. Las Concepciones de Profesores y Alumnos. [New ways of Thinking about Teaching and Learning. Teachers’ and Student’s Conceptions]. Barcelona: Graó.

Rasmitadila, R., Aliyyah, R. R., Rachmadtullah, R., Samsudin, A., Syaodih, E., Nurtanto, M., et al. (2020). The perceptions of primary school teachers of online learning during the COVID-19 pandemic period: a case study in Indonesia. J. Ethnic Cult. Stud. 7, 90–109. doi: 10.29333/ejecs/388

Rapanta, C., Botturi, L., Goodyear, P., Guàrdia, L., and Koole, M. (2020). Online university teaching during and after the Covid-19 crisis: refocusing teacher presence and learning activity. Postdigital Sci. Educ. 2, 923–945. doi: 10.1007/s42438-020-00155-y

Reimers, F. M., and Schleicher, A. (2020). A Framework to Guide an Education Response to the COVID-19 Pandemic of 2020. Paris: OECD Publishing.

Sangrà A. (ed.), Badia, A., Cabrera, N., Espasa, A., Fernández-Ferrer, M., Guàrdia, L., et al. (2020). Decálogo Para la Mejora de la Docencia Online. Propuestas Para Educar en Contextos Presenciales Discontinuos. [Decalogue for the Improvement of Online Teaching. Suggestions for Teaching in Intermittent Face-to-Face Contexts]. Barcelona: Editorial UOC.

Schraw, G., and Olafson, L. (2015). “Assessing teachers’ beliefs,” in International Handbook of Research on Teachers’ Beliefs , eds H. Fives and M. G. Gill (New York, NY: Routledge), 87–105.

Sigalés, C., Monimó, J. M., Meneses, J., and Badia, A. (2008). La Integración de Internet en la educación Escolar Española: Situación Actual y Perspectivas de Futuro. [Internet inclusion in Spanish School Education: Present Condition and Future perspectives]. Madrid: Fundación Telefónica.

Strauss, S., and Shilony, T. (1994). “Teachers’ models of children’s minds and learning,” in Mapping the Mind: Domain Specificity in Cognition and Culture , eds L. A. Hirschfeld and S. A. Gelman (Cambridge: Cambridge University Press), 455–473.

Suárez, J. M., Almerich, G., Orellana, N., and Belloch, C. (2012). El uso de las TIC por el profesorado no universitario. Modelo básico e influencia de factores personales y contextuales. [ICT use by non-university teachers. Basic model and the influence of personal and contextual factors]. Rev. Iberoameric. Eval. Educ. 5, 249–265.

Sung, Y.-T., Chang, K.-E., and Liu, T.-C. (2015). The effects of integrating mobile devices with teaching and learning on students’ learning performance: a meta-analysis and research synthesis. Comput. Educ. 94, 252–275. doi: 10.1016/j.compedu.2015.11.008

Tamim, R. M., Bernard, R. M., Borokhovski, E., Abrami, P. C., and Schmid, R. F. (2011). What forty years of research says about the impact of technology on learning: a second-order meta-analysis and validation study. Rev. Educ. Res. 81, 4–28. doi: 10.3102/0034654310393361

Tartavulea, C. V., Albu, C. N., Albu, N., Dieaconescu, R. I., and Petre, S. (2020). Online teaching practices and the effectiveness of the educational process in the wake of the COVID-19 pandemic. Amfiteatru Econ. 22, 920–936. doi: 10.24818/EA/2020/55/920

Tondeur, J., Hermans, R., van Braak, J., and Valcke, M. (2008a). Exploring the link between teachers’ educational belief profiles and different types of computer use in the classroom. Comput. Hum. Behav. 24, 2541–2553. doi: 10.1016/j.chb.2008.02.020

Tondeur, J., Valcke, M., and van Braak, J. (2008b). A multidimensional approach to determinants of computer use in primary education: teacher and school characteristics. J. Comput. Assist. Learn. 24, 494–506. doi: 10.1111/j.1365-2729.2008.00285.x

Tondeur, J., van Braak, J., Ertmer, P. A., and Ottenbreit-Leftwich, A. T. (2017). Understanding the relationship between teachers’ pedagogical beliefs and technology use in education: a systematic review of qualitative evidence. Educ. Tech. Res. Dev. 65, 555–575. doi: 10.1007/s11423-016-9481-2

Tripp, D. (1993). Critical Incidents in Teaching: Developing Professional Judgement. New York, NY: Routledge.

Trujillo-Sáez, F., Fernández-Navas, M., Montes-Rodríguez, M., Segura-Robles, A., Alaminos-Romero, F. J., and Postigo-Fuentes, A. Y. (2020). Panorama de la Educación en España tras la pandemia de COVID-19: La Opinión de la Comunidad Educativa. [Outlook on Spanish Education After COVID-19 pandemic: The Opinion of the Educational Community]. Madrid: Fundación de Ayuda contra la Drogadicción (FAD). doi: 10.5281/zenodo-3878844

Tsai, C.-C., and Chai, C. S. (2012). The “third”-order barrier for technology-integration instruction: implications for teacher education. Aust. J. Educ. Technol. 28, 1057–1060. doi: 10.14742/ajet.810

van Braak, J., Tondeur, J., and Valcke, M. (2004). Explaining different types of computer use among primary school teachers. Eur. J. Psychol. Educ. 19:407. doi: 10.1007/BF03173218

Vanderlinde, R., van Braak, J., and Tondeur, J. (2010). Using an online tool to support school-based ICT policy planning in primary education. J. Comput. Assist. Learn. 26, 434–447. doi: 10.1111/j.1365-2729.2010.00358.x

Williams, D., Coles, L., Wilson, K., Richardson, A., and Tuson, J. (2000). Teachers and ICT: Current use and future needs. Br. J. Educ. Technol. 31, 307–320. doi: 10.1111/1467-8535.00164

Xie, H., Peng, J., Qin, M., Huang, X., Tian, F., and Zhou, Z. (2018). Can touchscreen devices be used to facilitate young children’s learning? A meta-analysis of touchscreen learning effect. Front. Psychol. 9:2580. doi: 10.3389/fpsyg.2018.02580

Zhang, W., Wang, Y., Yang, L., and Wang, C. (2020). Suspending classes without stopping learning: China’s education emergency management policy in the COVID-19 outbreak. J. Risk Finan. Manag. 13:55. doi: 10.3390/jrfm13030055

Keywords : digital technologies uses, constructive learning, reproductive learning, learning and teaching conceptions, learning outcomes, COVID-19

Citation: Pozo J-I, Pérez Echeverría M-P, Cabellos B and Sánchez DL (2021) Teaching and Learning in Times of COVID-19: Uses of Digital Technologies During School Lockdowns. Front. Psychol. 12:656776. doi: 10.3389/fpsyg.2021.656776

Received: 21 January 2021; Accepted: 07 April 2021; Published: 29 April 2021.

Reviewed by:

Copyright © 2021 Pozo, Pérez Echeverría, Cabellos and Sánchez. 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: Juan-Ignacio Pozo, [email protected]

† These authors have contributed equally to this work and share first authorship

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