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What Is a Business Model?

• Andrea Ovans

A history, from Drucker to Christensen.

A look through HBR’s archives shows that business thinkers use the concept of a “business model” in many different ways, potentially skewing the definition. Many people believe Peter Drucker defined the term in a 1994 article as “assumptions about what a company gets paid for,” but that article never mentions the term business model. Instead, Drucker’s theory of the business was a set of assumptions about what a business will and won’t do, closer to Michael Porter’s definition of strategy. Businesses make assumptions about who their customers and competitors are, as well as about technology and their own strengths and weaknesses. Joan Magretta carries the idea of assumptions into her focus on business modeling, which encompasses the activities associated with both making and selling something. Alex Osterwalder also builds on Drucker’s concept of assumptions in his “business model canvas,” a way of organizing assumptions so that you can compare business models. Introducing a better business model into an existing market is the definition of a disruptive innovation, as written about by Clay Christensen. Rita McGrath offers that your business model is failing when innovations yield smaller and smaller improvements. You can innovate a new model by altering the mix of products and services, postponing decisions, changing the people who make the decisions, or changing incentives in the value chain. Finally, Mark Johnson provides a list of 19 types of business models and the organizations that use them.

In The New, New Thing , Michael Lewis refers to the phrase business model as “a term of art.” And like art itself, it’s one of those things many people feel they can recognize when they see it (especially a particularly clever or terrible one) but can’t quite define.

• AO Andrea Ovans is a former senior editor at Harvard Business Review.

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Business model innovation: a review and research agenda

New England Journal of Entrepreneurship

ISSN : 2574-8904

Article publication date: 16 October 2019

Issue publication date: 13 November 2019

The aim of this paper is to review and synthesise the recent advancements in the business model literature and explore how firms approach business model innovation.

Design/methodology/approach

A systematic review of business model innovation literature was carried out by analysing 219 papers published between 2010 and 2016.

Evidence reviewed suggests that rather than taking either an evolutionary process of continuous revision, adaptation and fine-tuning of the existing business model or a revolutionary process of replacing the existing business model, firms can explore alternative business models through experimentation, open and disruptive innovations. It was also found that changing business models encompasses modifying a single element, altering multiple elements simultaneously and/or changing the interactions between elements in four areas of innovation: value proposition, operational value, human capital and financial value.

Research limitations/implications

Although this review highlights the different avenues to business model innovation, the mechanisms by which firms can change their business models and the external factors associated with such change remain unexplored.

Practical implications

The business model innovation framework can be used by practitioners as a “navigation map” to determine where and how to change their existing business models.

Originality/value

Because conflicting approaches exist in the literature on how firms change their business models, the review synthesises these approaches and provides a clear guidance as to the ways through which business model innovation can be undertaken.

• Business model
• Value proposition
• Value creation
• Value capture

Ramdani, B. , Binsaif, A. and Boukrami, E. (2019), "Business model innovation: a review and research agenda", New England Journal of Entrepreneurship , Vol. 22 No. 2, pp. 89-108. https://doi.org/10.1108/NEJE-06-2019-0030

Emerald Publishing Limited

Copyright © 2019, Boumediene Ramdani, Ahmed Binsaif and Elias Boukrami

Published in New England Journal of Entrepreneurship . Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode

1. Introduction

Firms pursue business model innovation by exploring new ways to define value proposition, create and capture value for customers, suppliers and partners ( Gambardella and McGahan, 2010 ; Teece, 2010 ; Bock et al. , 2012 ; Casadesus-Masanell and Zhu, 2013 ). An extensive body of the literature asserts that innovation in business models is of vital importance to firm survival, business performance and as a source of competitive advantage ( Demil and Lecocq, 2010 ; Chesbrough, 2010 ; Amit and Zott, 2012 ; Baden-Fuller and Haefliger, 2013 ; Casadesus-Masanell and Zhu, 2013 ). It is starting to attract a growing attention, given the increasing opportunities for new business models enabled by changing customer expectations, technological advances and deregulation ( Casadesus-Masanell and Llanes, 2011 ; Casadesus-Masanell and Zhu, 2013 ). This is evident from the recent scholarly outputs ( Figure 1 ). Thus, it is essential to comprehend this literature and uncover where alternative business models can be explored.

Conflicting approaches exist in the literature on how firms change their business models. One approach suggests that alternative business models can be explored through an evolutionary process of incremental changes to business model elements (e.g. Demil and Lecocq, 2010 ; Dunford et al. , 2010 ; Amit and Zott, 2012 ; Landau et al. , 2016 ; Velu, 2016 ). The other approach, mainly practice-oriented, advocates that innovative business models can be developed through a revolutionary process by replacing existing business models (e.g. Bock et al. , 2012 ; Iansiti and Lakhani, 2014 ). The fragmentation of prior research is due to the variety of disciplinary and theoretical foundations through which business model innovation is examined. Scholars have drawn on perspectives from entrepreneurship (e.g. George and Bock, 2011 ), information systems (e.g. Al-debei and Avison, 2010 ), innovation management (e.g. Dmitriev et al. , 2014 ), marketing (e.g. Sorescu et al. , 2011 ) and strategy (e.g. Demil and Lecocq, 2010 ). Also, this fragmentation is deepened by focusing on different types of business models in different industries. Studies have explored different types of business models such as digital business models (e.g. Weill and Woerner, 2013 ), service business models (e.g. Kastalli et al. , 2013 ), social business models (e.g. Hlady-Rispal and Servantie, 2016 ) and sustainability-driven business models ( Esslinger, 2011 ). Besides, studies have examined different industries such as airline ( Lange et al. , 2015 ), manufacturing ( Landau et al. , 2016 ), newspaper ( Karimi and Walter, 2016 ), retail ( Brea-Solís et al. , 2015 ) and telemedicine ( Peters et al. , 2015 ).

Since the first comprehensive review of business model literature was carried out by Zott et al. (2011) , several reviews were published recently (as highlighted in Table I ). Our review builds on and extends the extant literature in at least three ways. First, unlike previous reviews that mainly focused on the general construct of “Business Model” ( George and Bock, 2011 ; Zott et al. , 2011 ; Wirtz et al. , 2016 ), our review focuses on uncovering how firms change their existing business model(s) by including terms that reflect business model innovation, namely, value proposition, value creation and value capture. Second, previous reviews do not provide a clear answer as to how firms change their business models. Our review aims to provide a clear guidance on how firms carry out business model innovation by synthesising the different perspectives existing in the literature. Third, compared to recent reviews on business model innovation ( Schneider and Spieth, 2013 ; Spieth et al. , 2014 ), which have touched lightly on some innovation aspects such as streams and motivations of business model innovation research, our review will uncover the innovation areas where alternative business models can be explored. Taking Teece’s (2010) suggestion, “A helpful analytic approach for management is likely to involve systematic deconstruction/unpacking of existing business models, and an evaluation of each element with an idea toward refinement or replacement” (p. 188), this paper aims to develop a theoretical framework of business model innovation.

Our review first explains the scope and the process of the literature review. This is followed by a synthesis of the findings of the review into a theoretical framework of business model innovation. Finally, avenues for future research will be discussed in relation to the approaches, degree and mechanisms of business model innovation.

2. Scope and method of the literature review

Given the diverse body of business models literature, a systematic literature review was carried out to minimise research bias ( Transfield et al. , 2003 ). Compared to the previous business model literature, our review criteria are summarised in Table I . The journal papers considered were published between January 2010 and December 2016. As highlighted in Figure 1 , most contributions in this field have been issued within this period since previous developments in the literature were comprehensively reviewed up to the end of 2009 ( Zott et al. , 2011 ). Using four databases (EBSCO Business Complete, ABI/INFORM, JSTOR and ScienceDirect), we searched peer-reviewed papers with terms such as business model(s), innovation value proposition, value creation and value capture appearing in the title, abstract or subject terms. As a result, 8,642 peer-reviewed papers were obtained.

Studies were included in our review if they specifically address business models and were top-rated according to The UK Association of Business Schools list ( ABS, 2010 ). This rating has been used not only because it takes into account the journal “Impact Factor” as a measure for journal quality, but also uses in conjunction other measures making it one of the most comprehensive journal ratings. By applying these criteria, 1,682 entries were retrieved from 122 journals. By excluding duplications, 831 papers were identified. As Harvard Business Review is not listed among the peer-reviewed journals in any of the chosen databases and was included in the ABS list, we used the earlier criteria and found 112 additional entries. The reviewed papers and their subject fields are highlighted in Table II . Since the focus of this paper is on business model innovation, we selected studies that discuss value proposition, value creation and value capture as sub-themes. This is not only because the definition of business model innovation mentioned earlier spans all three sub-themes, but also because all three sub-themes have been included in recent studies (e.g. Landau et al. , 2016 ; Velu and Jacob, 2014 ). To confirm whether the papers addressed business model innovation, we examined the main body of the papers to ensure they were properly coded and classified. At the end of the process, 219 papers were included in this review. Table III lists the source of our sample.

The authors reviewed the 219 papers using a protocol that included areas of innovation (i.e. components, elements, and activities), theoretical perspectives and key findings. In order to identify the main themes of business model innovation research, all papers were coded in relation to our research focus as to where alternative business models can be explored (i.e. value proposition, value creation and value capture). Coding was cross checked among the authors on a random sample suggesting high accuracy between them. Having compared and discussed the results, the authors were able to identify the main themes.

3. Prior conceptualisations of business model innovation

Some scholars have articulated the need to build the business model innovation on a more solid theoretical ground ( Sosna et al. , 2010 ; George and Bock, 2011 ). Although many studies are not explicitly theory-based, some studies partially used well-established theories such as the resource-based view (e.g. Al-Debei and Avison, 2010 ) and transaction cost economics (e.g. DaSilva and Trkman, 2014 ) to conceptualise business model innovation. Other theories such as activity systems perspective, dynamic capabilities and practice theory have been used to help answer the question of how firms change their existing business models.

Using the activity systems perspective, Zott and Amit (2010) demonstrated how innovative business models can be developed through the design themes that describe the source of value creation (novelty, lock-in, complementarities and efficiency) and design elements that describe the architecture (content, structure and governance). This work, however, overlooks value capture which limits the explanation of the advocated system’s view (holistic). Moreover, Chatterjee (2013) used this perspective to reveal that firms can design innovative business models that translate value capture logic to core objectives, which can be delivered through the activity system.

Dynamic capability perspective frames business model innovation as an initial experiment followed by continuous revision, adaptation and fine-tuning based on trial-and-error learning ( Sosna et al. , 2010 ). Using this perspective, Demil and Lecocq (2010) showed that “dynamic consistency” is a capability that allows firms to sustain their performance while innovating their business models through voluntary and emergent changes. Also, Mezger (2014) conceptualised business model innovation as a distinct dynamic capability. He argued that this capability is the firm’s capacity to sense opportunities, seize them through the development of valuable and unique business models, and accordingly reconfigure the firms’ competences and resources. Using aspects of practice theory, Mason and Spring (2011) looked at business model innovation in the recorded sound industry and found that it can be achieved through various combinations of managerial practices.

Static and transformational approaches have been used to depict business models ( Demil and Lecocq, 2010 ). The former refers to viewing business models as constituting core elements that influence business performance at a particular point in time. This approach offers a snapshot of the business model elements and how they are assembled, which can help in understanding and communicating a business model (e.g. Eyring et al. , 2011 ; Mason and Spring, 2011 ; Yunus et al. , 2010). The latter, however, focuses on innovation and how to address the changes in business models over time (e.g. Sinfield et al. , 2012 ; Girotra and Netessine, 2014 ; Landau et al. , 2016 ). Some researchers have identified the core elements of business models ex ante (e.g. Demil and Lecocq, 2010 ; Wu et al. , 2010 ; Huarng, 2013 ; Dmitriev et al. , 2014 ), while others argued that considering a priori elements can be restrictive (e.g. Casadesus-Masanell and Ricart, 2010 ). Unsurprisingly, some researchers found a middle ground where elements are loosely defined allowing flexibility in depicting business models (e.g. Zott and Amit, 2010 ; Sinfield et al. , 2012 ; Kiron et al. , 2013 ).

Prior to 2010, conceptual frameworks focused on the business model concept in general (e.g. Chesbrough and Rosenbloom, 2002 ; Osterwalder et al. , 2005 ; Shafer et al. , 2005 ) apart from Johnson et al. ’s (2008 ), which is one of the early contributions to business model innovation. To determine whether a change in existing business model is necessary, Johnson et al. (2008) suggested three steps: “Identify an important unmet job a target customer needs done; blueprint a model that can accomplish that job profitably for a price the customer is willing to pay; and carefully implement and evolve the model by testing essential assumptions and adjusting as you learn” ( Eyring et al. , 2011 , p. 90). Although several frameworks have been developed since then, our understanding of business model innovation is still limited due to the static nature of the majority of these frameworks. Some representations ignore the elements and/or activities where alternative business models can be explored (e.g. Sinfield et al. , 2012 ; Chatterjee, 2013 ; Huarng, 2013 ; Morris et al. , 2013 ; Dmitriev et al. , 2014 ; Girotra and Netessine, 2014 ). Other frameworks ignore value proposition (e.g. Zott and Amit, 2010 ), ignore value creation (e.g. Dmitriev et al. , 2014 ; Michel, 2014 ) and/or ignore value capture (e.g. Mason and Spring, 2011 ; Sorescu et al. , 2011 ; Storbacka, 2011 ). Some conceptualisations do not identify who is responsible for the innovation (e.g. Casadesus-Masanell and Ricart, 2010 ; Sinfield et al. , 2012 ; Chatterjee, 2013 ; Kiron et al. , 2013 ). Synthesising the different contributions into a theoretical framework of business model innovation will enable a better understanding of how firms undertake business model innovation.

4. Business model innovation framework

Our framework ( Figure 2 ) integrates all the elements where alternative business models can be explored. This framework does not claim that the listed elements are definitive for high-performing business models, but is an attempt to outline the elements associated with business model innovation. This framework builds on the previous work of Johnson et al. (2008) and Zott and Amit (2010) by signifying the elements associated with business model innovation. Unlike previous frameworks that mainly consider the constituting elements of business models, this framework focuses on areas of innovation where alternative business models can be explored. Moreover, this is not a static view of the constituting elements of a business model, but rather a view enabling firms to explore alternative business models by continually refining these elements. Arrows in the framework indicate the continuous interaction of business model elements. This framework consists of 4 areas of innovation and 16 elements (more details are shown in Table IV ). Each will be discussed below.

4.1 Value proposition

The first area of innovation refers to elements associated with answering the “Why” questions. While most of the previously established models in the literature include at least one of the value proposition elements (e.g. Brea-Solís et al. , 2015 ; Christensen et al. , 2016 ), other frameworks included two elements (e.g. Dahan et al. , 2010 ; Cortimiglia et al. , 2016 ) and three elements (e.g. Eyring et al. , 2011 ; Sinfield et al. , 2012 ). These elements include rethinking what a company sells, exploring new customer needs, acquiring target customers and determining whether the benefits offered are perceived by customers. Modern organisations are highly concerned with innovation relating to value proposition in order to attract and retain a large portion of their customer base ( Al-Debei and Avison, 2010 ). Developing new business models usually starts with articulating a new customer value proposition ( Eyring et al. , 2011 ). According to Sinfield et al. (2012) , firms are encouraged to explore various alternatives of core offering in more depth by examining type of offering (product or service), its features (custom or off-the-shelf), offered benefits (tangible or intangible), brand (generic or branded) and lifetime of the offering (consumable or durable).

In order to exploit the “middle market” in emerging economies, Eyring et al. (2011) suggested that companies need to design new business models that aim to meet unsatisfied needs and evolve these models by continually testing assumptions and making adjustments. To uncover unmet needs, Eyring et al. (2011) suggested answering four questions: what are customers doing with the offering? What alternative offerings consumers buy? What jobs consumers are satisfying poorly? and what consumers are trying to accomplish with existing offerings? Furthermore, Baden-Fuller and Haefliger (2013) made a distinction between customers and users in two-sided platforms, where users search for products online, and customers (firms) place ads to attract users. They also made a distinction between “pre-designed (scale) based offerings” and “project based offerings”. While the former focuses on “one-size-fits-all”, the latter focuses on specific client solving specific problem.

Established firms entering emerging markets should identify unmet needs “the job to be done” rather than extending their geographical base for existing offerings ( Eyring et al. , 2011 ). Because customers in these markets cannot afford the cheapest of the high-end offerings, firms with innovative business models that meet these customers’ needs affordably will have opportunities for growth ( Eyring et al. , 2011 ). Moreover, secondary business model innovation has been advocated by Wu et al. (2010) as a way for latecomer firms to create and capture value from disruptive technologies in emerging markets. This can be achieved through tailoring the original business model to fit price-sensitive mass customers by articulating a value proposition that is attractive for local customers.

4.2 Operational value

The second area of innovation focuses on elements associated with answering the “What” questions. Many of the established frameworks included either one element (e.g. Sinfield et al. , 2012 ; Taran et al. , 2015 ), two elements (e.g. Mason and Spring, 2011 ; Dmitriev et al. , 2014 ). However, very few included three or more elements (e.g. Mehrizi and Lashkarbolouki, 2016 ; Cortimiglia et al. , 2016 ). These elements include configuring key assets and sequencing activities to deliver the value proposition, exposing the various means by which a company reaches out to customers, and establishing links with key partners and suppliers. Focusing on value creation, Zott and Amit (2010) argued that business model innovation can be achieved through reorganising activities to reduce transaction costs. However, Al-Debei and Avison (2010) argued that innovation relating to this dimension can be achieved through resource configuration, which demonstrates a firm’s ability to integrate various assets in a way that delivers its value proposition. Cavalcante et al. (2011) proposed four ways to change business models: business model creation, extension, revision and termination by creating or adding new processes, and changing or terminating existing processes.

Western firms have had difficulty competing in emerging markets due to importing their existing business models with unchanged operating model ( Eyring et al. , 2011 ). Alternative business models can be uncovered when firms explore the different roles they might play in the industry value chain ( Sinfield et al. , 2012 ). Al-Debei and Avison (2010) suggested achieving this through answering questions such as: what is the position of our firm in the value system? and what mode of collaboration (open or close) would we choose to reach out in a business network? Dahan et al. (2010) found cross-sector partnerships as a way to co-create new multi-organisational business models. They argued that multinational enterprises (MNEs) can collaborate with nongovernmental organisations (NGOs) to create products/or services that neither can create on their own. Collaboration allows access to resources that firms would otherwise need to solely develop or purchase ( Yunus et al. , 2010 ). According to Wu et al. (2010) , secondary business model innovation can be achieved when latecomer firms fully utilise strategic partners’ complementary assets to overcome their latecomer disadvantages and build a unique value network specific to emerging economies context.

4.3 Human capital

The third area of innovation refers to elements associated with answering the “Who” questions. Most of the established frameworks in this field tend to focus less on human capital and include one element at most (e.g. Wu et al. , 2010 ; Kohler, 2015 ). However, our framework highlights four elements, which include experimenting with new ways of doing business, tapping into the skills and competencies needed for the new business model through motivating and involving individuals in the innovation process. According to Belenzon and Schankerman (2015) , “the ability to tap into a pool of talent is strongly related to the specific business model chosen by managers” (p. 795). They claimed that managers can strategically influence individuals’ contributions and their impact on project performance.

Organisational learning can be maximised though continuous experimentation and making changes when actions result in failure ( Yunus et al. , 2010 ). Challenging and questioning the existing rules and assumptions and imagining new ways of doing business will help develop new business models. Another essential element of business model design is governance, which refers to who performs the activities ( Zott and Amit, 2010 ). According to Sorescu et al. (2011) , innovation in retail business models can occur as a result of changes in the level of participation by actors engaged in performing the activities. An essential element of retailing governance is the incentive structure or the mechanisms that motivate those involved in carrying out their roles to meet customer demands ( Sorescu et al. , 2011 ). For example, discount retailers tend to establish different compensation and incentive policies ( Brea-Solís et al. , 2015 ). Revising the incentive system can have a major impact on new ventures’ performance by aligning organisational goals at each stage of growth ( Roberge, 2015 ). Zott and Amit (2010) argued that alternative business models can be explored through adopting innovative governance or changing one or more parties that perform any activities. Sinfield et al. (2012) suggested that business model innovation only requires time from a small team over a short period of time to move a company beyond incremental improvements and generate new opportunities for growth. This is supported by Michel’s (2014) finding that cross-functional teams were able to quickly achieve business model innovation in workshops through deriving new ways to capture value.

4.4 Financial value

The final area of innovation focuses on elements associated with answering the “How” questions. Previously developed frameworks tend to prioritise this area of innovation by three elements (e.g. Eyring et al. , 2011 ; Huang et al. , 2013 ), and in one instance four elements (e.g. Yunus et al. , 2010 ). These elements include activities linked with how to capture value through revenue streams, changing the price-setting mechanisms, and assessing the financial viability and profitability of a business. According to Demil and Lecocq (2010) , changes in cost and/or revenue structures are the consequences of both continuous and radical changes. They also argued that costs relate to different activities run by organisations to acquire, integrate, combine or develop resources. Michel (2014) suggested that alternative business models can be explored through: changing the price-setting mechanism, changing the payer, and changing the price carrier. Different innovation forms are associated with each of these categories.

Business model innovation can be achieved through exploring new ways to generate cash flows ( Sorescu et al. , 2011 ), where the organisation has to consider (and potentially change) when the money is collected: prior to the sale, at the point of sale, or after the sale ( Baden-Fuller and Haefliger, 2013 ). Furthermore, Demil and Lecocq (2010) suggested that changes in business models affect margins. This is apparent in the retail business models, which generate more profit through business model innovation compared to other types of innovation ( Sorescu et al. , 2011 ).

5. Ways to change business models

From reviewing the recent developments in the business model literature, alternative business models can be explored through modifying a single business model element, altering multiple elements simultaneously and/or changing the interactions between elements of a business model.

Changing one of the business model elements (i.e. content, structure or governance) is enough to achieve business model innovation ( Amit and Zott, 2012 ). This means that firms can have a new activity system by performing only one new activity. However, Amit and Zott (2012) clearly outlined a systemic view of business models which entails a holistic change. This is evident from Demil and Lecocq’s (2010) work suggesting that the study of business model innovation should not focus on isolated activities since changing a core element will not only impact other elements but also the interactions between these elements.

Another way to change business models is through altering multiple business model elements simultaneously. Kiron et al. (2013) found that companies combining target customers with value chain innovations and changing one or two other elements of their business models tend to profit from their sustainability activities. They also found that firms changing three to four elements of their business models tend to profit more from their sustainability activities compared to those changing only one element. Moreover, Dahan et al. (2010) found that a new business model was developed as a result of MNEs and NGOs collaboration by redefining value proposition, target customers, governance of activities and distribution channels. Companies can explore multiple combinations by listing different business model options they could undertake (desirable, discussable and unthinkable) and evaluate new combinations that would not have been considered otherwise ( Sinfield et al. , 2012 ).

Changing business models is argued to be demanding as it requires a systemic and holistic view ( Amit and Zott, 2012 ) by considering the relationships between core business model elements ( Demil and Lecocq, 2010 ). As mentioned earlier, changing one element will not only impact other elements but also the interactions between these elements. A firm’s resources and competencies, value proposition and organisational system are continuously interacting and this will in turn impact business performance either positively or negatively ( Demil and Lecocq, 2010 ). According to Zott and Amit (2010) , innovative business models can be developed through linking activities in a novel way that generates more value. They argued that alternative business models can be explored by configuring business model design elements (e.g. governance) and connecting them to distinct themes (e.g. novelty). Supporting this, Eyring et al. (2011) suggested that core business model elements need to be integrated in order to create and capture value ( Eyring et al. , 2011 ).

6. Discussion and future research directions

From the above synthesis of the recent development in the literature, several gaps remain unfilled. To advance the literature, possible future research directions will be discussed in relation to approaches, degrees and mechanisms of business model innovation.

6.1 Approaches of business model innovation

Experimentation, open innovation and disruption have been advocated as approaches to business model innovation. Experimentation has been emphasised as a way to exploit opportunities and develop alternative business models before committing additional investments ( McGrath, 2010 ). Several approaches have been developed to assist in business model experimentation including mapping approach, discovery-driven planning and trail-and-error learning ( Chesbrough, 2010 ; McGrath, 2010 ; Sosna et al. , 2010 ; Andries and Debackere, 2013 ). Little is known about the effectiveness of these approaches. It will be worth investigating which elements of the business model innovation framework are more susceptible to experimentation and which elements should be held unchanged. Although business model innovation tends to be characterised with failure ( Christensen et al. , 2016 ), not much has been established on failing business models. It is interesting to explore how firms determine a failing business model and what organisational processes exist (if any) to evaluate and discard these failed business models. Empirical studies could examine which elements of business model innovation framework are associated with failing business models.

Another way to develop alternative business models is through open innovation. Although different categories of open business models have been identified by researchers (e.g. Frankenberger et al. , 2014 ; Taran et al. , 2015 ; Kortmann and Piller, 2016 ), their effectiveness is yet to be established. Further research is needed to examine when can a firm open and/or close element(s) of the business model innovation framework. Future studies could also examine the characteristics of open and/or close business models.

In responding to disruptive business models, how companies extend their existing business model, introduce additional business model(s) and/or replace their existing business model altogether remains underexplored. Future research is needed to unravel the strategies deployed by firms to extend their existing business models as a response to disruptive business models. In introducing additional business models, Markides (2013) suggested that a company will be presented with several options to manage the two businesses at the same time: create a completely separate business unit, integrate the two business models from the beginning or integrate the second business model after a certain period of time. Finding the balance between separation and integration is of vital importance. Further research could identify which of these choices are most common among successful firms introducing additional business models, how is the balance between integration and separation achieved, and which choice(s) prove more profitable. Moreover, very little is known on how firms replace their existing business model. Longitudinal studies could provide insights into how a firm adopts an alternative model and discard the old business model over time. It may also be worth examining the factors associated with the adoption of business model innovation as a response to disruptive business models. Moreover, new developments in digital technologies such as blockchain, Internet of Things and artificial intelligence are disrupting existing business models and providing firms with alternative avenues to create new business models. Thus far, very little is known on digital business models, the nature of their disruption, and how firms create digital business models and make them disruptive. Future research is needed to fill these important gaps in our knowledge.

6.2 Degrees of business model innovation

Business models can be developed through varying degrees of innovation from an evolutionary process of continuous fine-tuning to a revolutionary process of replacing existing business models. Recent research shows that survival of firms is dependent on the degree of their business model innovation ( Velu, 2015, 2016 ). This review classifies these degrees of innovation into modifying a single element, altering multiple elements simultaneously and/or changing the interactions between elements of the business model innovation framework.

In changing a single element, further research is needed to examine which business model element(s) is (are) associated with business model innovation. It is not clear whether firms intentionally make changes to a single element when carrying out business model innovation or stumble at it when experimenting with new ways of doing things. It may also be worth investigating the entry (or starting) points in the innovation process. There is no consensus in the literature on which element do companies start with when carrying out their business model innovation. While some studies suggest starting with the value proposition ( Eyring et al. , 2011 ; Landau et al. , 2016 ), others suggest starting the innovation process with identifying risks in the value chain ( Girotra and Netessine, 2011 ). Dmitriev et al. (2014) suggested two entry points, namely, value proposition and target customers. In commercialising innovations, the former refers to technology-push innovation while the latter refers to market-pull innovation. Also, it is not clear whether the entry point is the same as the single element associated with changing the business model. Further research can explore the different paths to business model innovation by identifying the entry point and subsequent changes needed to achieve business model innovation.

There is little guidance in the literature on how firms change multiple business model elements simultaneously. Landau et al. (2016) claimed that firms entering emerging markets tend to focus on adjusting specific business model components. It is unclear which elements need configuring, combining and/or integrating to achieve a company’s value proposition. Furthermore, the question of which elements can be “bought” on the market or internally “implemented” and their interplay remains unanswered ( DaSilva and Trkman, 2014 ). Casadesus-Masanell and Ricart (2010) argued that “[…] there is (as yet) no agreement as to the distinctive features of superior business models” (p. 196). Further research is needed to explore these distinctive elements of high-performing business models.

In changing the interactions between business model elements, further research is needed to explore how these elements are linked and what interactions’ changes are necessary to achieve business model innovation. Moreover, the question of how firms sequence these elements remains poorly understood. Future research can explore the synergies created over time between these elements. According to Dmitriev et al. (2014) , we need to improve our understanding of the connective mechanisms and dynamics involved in business model development. More work is needed to explore the different modalities of interdependencies among these elements and empirically testing such interdependencies and their effect on business performance ( Sorescu et al. , 2011 ).

It is surprising that the link between business model innovation and organisational performance has rarely been examined. Changing business models has been found to negatively influence business performance even if it is temporary ( McNamara et al. , 2013 ; Visnjic et al. , 2016 ). Contrary to this, evidence show that modifying business models is positively associated with organisational performance ( Cucculelli and Bettinelli, 2015 ). Empirical research is needed to operationalise the various degrees of innovation in business models and examine their link to organisational performance. Longitudinal studies can also be used to explore this association since it may be the case that business model innovation has a negative influence on performance in the short run and that may change subsequently. Moreover, it is not clear whether high-performing firms change their business models or innovation in business models is a result from superior performance ( Sorescu et al. , 2011 ). Further studies are needed to determine the direction of causality. Another link that is worth exploring is business model innovation and social value, which has only been explored in a few studies looking at social business models (e.g. Yunus et al. , 2010 ; Wilson and Post, 2013 ). Further research is needed to examine this link and possibly examine both financial and non-financial business performance.

6.3 Mechanisms of business model innovation

Although we know more about how firms define value proposition, create and capture value ( Landau et al. , 2016 ; Velu and Jacob, 2014 ), what remains as a blind spot is the mechanism of business model innovation. This is due to the fact that much of the literature seems to focus on value creation. To better understand the various mechanisms of business model innovation, future studies must integrate value proposition, value creation and value capture elements. Empirical studies could use the business model innovation framework to examine the various mechanisms of business model innovation. Also, the literature lacks the integration of internal and external perspectives of business model innovation. Very few studies look at the external drivers of business model innovation and the associated internal changes. The external drivers are referred to as “emerging changes”, which are usually beyond manager’s control ( Demil and Lecocq, 2010 ). Inconclusive findings exist as to how firms develop innovative business models in response to changes in the external environment. Future studies could examine the external factors associated with the changes in the business model innovation framework. Active and reactive responses need to be explored not only to understand the external influences, but also what business model changes are necessary for such responses. A better understanding of the mechanisms of business model innovation can be achieved by not only exploring the external drivers, but also linking them to specific internal changes. Although earlier contributions linking studies to established theories such as the resource-based view, transaction cost economics, activity systems perspective, dynamic capabilities and practice theory have proven to be vital in advancing the literature, developing a theory that elaborates on the antecedents, consequences and different facets of business model innovation is still needed ( Sorescu et al. , 2011 ). Theory can be advanced by depicting the mechanisms of business model innovation through the integration of both internal and external perspectives. Also, we call for more empirical work to uncover these mechanisms and provide managers with the necessary insights to carry out business model innovation.

7. Conclusions

The aim of this review was to explore how firms approach business model innovation. The current literature suggests that business model innovation approaches can either be evolutionary or revolutionary. However, the evidence reviewed points to a more complex picture beyond the simple binary approach, in that, firms can explore alternative business models through experimentation, open and disruptive innovations. Moreover, the evidence highlights further complexity to these approaches as we find that they are in fact a spectrum of various degrees of innovation ranging from modifying a single element, altering multiple elements simultaneously, to changing the interactions between elements of the business model innovation framework. This framework was developed as a navigation map for managers and researchers interested in how to change existing business models. It highlights the key areas of innovation, namely, value proposition, operational value, human capital and financial value. Researchers interested in this area can explore and examine the different paths firms can undertake to change their business models. Although this review pinpoints the different avenues for firm to undertake business model innovation, the mechanisms by which firms can change their business models and the external factors associated with such change remain underexplored.

The evolution of business model literature (pre-2000 to 2016)

Business model innovation framework

Previous reviews of business model literature

Reviewed papers and their subject fields

Source of our sample

Business model innovation areas and elements

ABS ( 2010 ), Academic Journal Quality Guide , Version 4 , The Association of Business Schools , London .

Al-Debei , M.M. and Avison , D. ( 2010 ), “ Developing a unified framework of the business model concept ”, European Journal of Information Systems , Vol. 19 No. 3 , pp. 359 - 376 .

Amit , R. and Zott , C. ( 2012 ), “ Creating value through business model innovation ”, MIT Sloan Management Review , Vol. 53 No. 3 , pp. 41 - 49 .

Andries , P. and Debackere , K. ( 2013 ), “ Business model innovation: Propositions on the appropriateness of different learning approaches ”, Creativity and Innovation Management , Vol. 22 No. 4 , pp. 337 - 358 .

Baden-Fuller , C. and Haefliger , S. ( 2013 ), “ Business models and technological innovation ”, Long Range Planning , Vol. 46 No. 6 , pp. 419 - 426 .

Belenzon , S. and Schankerman , M. ( 2015 ), “ Motivation and sorting of human capital in open innovation ”, Strategic Management Journal , Vol. 36 No. 6 , pp. 795 - 820 .

Bock , A.J. , Opsahl , T. , George , G. and Gann , D.M. ( 2012 ), “ The effects of culture and structure on strategic flexibility during business model innovation ”, Journal of Management Studies , Vol. 49 No. 2 , pp. 279 - 305 .

Brea-Solís , H. , Casadesus-Masanell , R. and Grifell-Tatjé , E. ( 2015 ), “ Business model evaluation: quantifying Walmart’s sources of advantage ”, Strategic Entrepreneurship Journal , Vol. 9 No. 1 , pp. 12 - 33 .

Casadesus-Masanell , R. and Llanes , G. ( 2011 ), “ Mixed source ”, Management Science , Vol. 57 No. 7 , pp. 1212 - 1230 .

Casadesus-Masanell , R. and Ricart , J.E. ( 2010 ), “ From strategy to business models and onto tactics ”, Long Range Planning , Vol. 43 Nos 2-3 , pp. 195 - 215 .

Casadesus-Masanell , R. and Zhu , F. ( 2013 ), “ Business model innovation and competitive imitation: the case of sponsor-based business models ”, Strategic Management Journal , Vol. 34 No. 4 , pp. 464 - 482 .

Chatterjee , S. ( 2013 ), “ Simple rules for designing business models ”, California Management Review , Vol. 55 No. 2 , pp. 97 - 124 .

Cavalcante , S. , Kesting , P. and Ulhøi , J. ( 2011 ), “ Business model dynamics and innovation: (re)establishing the missing linkages ”, Management Decision , Vol. 49 No. 8 , pp. 1327 - 1342 .

Chesbrough , H. ( 2010 ), “ Business model innovation: opportunities and barriers ”, Long Range Planning , Vol. 43 Nos. 2-3 , pp. 354 - 363 .

Chesbrough , H. and Rosenbloom , R.S. ( 2002 ), “ The role of the business model in capturing value from innovation: evidence from Xerox corporation’s technology spin off companies ”, Industrial & Corporate Change , Vol. 11 No. 3 , pp. 529 - 555 .

Christensen , C.M. , Bartman , T. and Van Bever , D. ( 2016 ), “ The hard truth about business model innovation ”, MIT Sloan Management Review , Vol. 58 No. 1 , pp. 31 - 40 .

Cortimiglia , M.N. , Ghezzi , A. and Frank , A.G. ( 2016 ), “ Business model innovation and strategy making nexus: evidence from a cross‐industry mixed‐methods study ”, R&D Management , Vol. 46 No. 3 , pp. 414 - 432 .

Cucculelli , M. and Bettinelli , C. ( 2015 ), “ Business models, intangibles and firm performance: evidence on corporate entrepreneurship from Italian manufacturing SMEs ”, Small Business Economics , Vol. 45 No. 2 , pp. 329 - 350 .

Dahan , N.M. , Doh , J.P. , Oetzel , J. and Yaziji , M. ( 2010 ), “ Corporate-NGO collaboration: Co-creating new business models for developing markets ”, Long Range Planning , Vol. 43 Nos 2-3 , pp. 326 - 342 .

DaSilva , C.M. and Trkman , P. ( 2014 ), “ Business model: what it is and what it is not ”, Long Range Planning , Vol. 47 No. 6 , pp. 379 - 389 .

Demil , B. and Lecocq , X. ( 2010 ), “ Business model evolution: in search of dynamic consistency ”, Long Range Planning , Vol. 43 Nos 2-3 , pp. 227 - 246 .

Dmitriev , V. , Simmons , G. , Truong , Y. , Palmer , M. and Schneckenberg , D. ( 2014 ), “ An exploration of business model development in the commercialization of technology innovations ”, R&D Management , Vol. 44 No. 3 , pp. 306 - 321 .

Dunford , R. , Palmer , I. and Benveniste , J. ( 2010 ), “ Business model replication for early and rapid internationalisation: the ING direct experience ”, Long Range Planning , Vol. 43 Nos 5-6 , pp. 655 - 674 .

Esslinger , H. ( 2011 ), “ Sustainable design: beyond the innovation-driven business model ”, The Journal of Product Innovation Management , Vol. 28 No. 3 , pp. 401 - 404 .

Eyring , M.J. , Johnson , M.W. and Nair , H. ( 2011 ), “ New business models in emerging markets ”, Harvard Business Review , Vol. 89 No. 1 , pp. 89 - 95 .

Frankenberger , K. , Weiblen , T. and Gassmann , O. ( 2014 ), “ The antecedents of open business models: an exploratory study of incumbent firms ”, R&D Management , Vol. 44 No. 2 , pp. 173 - 188 .

Gambardella , A. and McGahan , A.M. ( 2010 ), “ Business-model innovation: general purpose technologies and their implications for industry structure ”, Long Range Planning , Vol. 43 Nos 2-3 , pp. 262 - 271 .

George , G. and Bock , A.J. ( 2011 ), “ The business model in practice and its implications for entrepreneurship research ”, Entrepreneurship: Theory & Practice , Vol. 35 No. 1 , pp. 83 - 111 .

Girotra , K. and Netessine , S. ( 2011 ), “ How to build risk into your business model ”, Harvard Business Review , Vol. 89 No. 5 , pp. 100 - 105 .

Girotra , K. and Netessine , S. ( 2014 ), “ Four paths to business model innovation ”, Harvard Business Review , Vol. 92 No. 7 , pp. 96 - 103 .

Hartmann , P.M. , Hartmann , P.M. , Zaki , M. , Zaki , M. , Feldmann , N. and Neely , A. ( 2016 ), “ Capturing value from Big Data – a taxonomy of data-driven business models used by start-up firms ”, International Journal of Operations & Production Management , Vol. 36 No. 10 , pp. 1382 - 1406 .

Hlady-Rispal , M. and Servantie , V. ( 2016 ), “ Business models impacting social change in violent and poverty-stricken neighbourhoods: a case study in Colombia ”, International Small Business Journal , Vol. 35 No. 4 , pp. 1 - 22 .

Huang , H.C. , Lai , M.C. , Lin , L.H. and Chen , C.T. ( 2013 ), “ Overcoming organizational inertia to strengthen business model innovation: an open innovation perspective ”, Journal of Organizational Change Management , Vol. 26 No. 6 , pp. 977 - 1002 .

Huarng , K.-H. ( 2013 ), “ A two-tier business model and its realization for entrepreneurship ”, Journal of Business Research , Vol. 66 No. 10 , pp. 2102 - 2105 .

Iansiti , M. and Lakhani , K.R. ( 2014 ), “ Digital ubiquity: how connections, sensors, and data are revolutionizing business ”, Harvard Business Review , Vol. 92 No. 11 , pp. 91 - 99 .

Johnson , M.W. , Christensen , C.M. and Kagermann , H. ( 2008 ), “ Reinventing your business model ”, Harvard Business Review , Vol. 86 No. 12 , pp. 57 - 68 .

Karimi , J. and Walter , Z. ( 2016 ), “ Corporate entrepreneurship, disruptive business model innovation adoption, and its performance: the case of the newspaper industry ”, Long Range Planning , Vol. 49 No. 3 , pp. 342 - 360 .

Kastalli , I. , Van Looy , B. and Neely , A. ( 2013 ), “ Steering manufacturing firms towards service business model innovation ”, California Management Review , Vol. 56 No. 1 , pp. 100 - 123 .

Kohler , T. ( 2015 ), “ Crowdsourcing-based business models ”, California Management Review , Vol. 57 No. 4 , pp. 63 - 84 .

Kiron , D. , Kruschwitz , N. , Haanaes , K. , Reeves , M. and Goh , E. ( 2013 ), “ The innovation bottom line ”, MIT Sloan Management Review , Vol. 54 No. 2 , pp. 1 - 20 .

Klang , D. , Wallnöfer , M. and Hacklin , F. ( 2014 ), “ The business model paradox: a systematic review and exploration of antecedents ”, International Journal of Management Reviews , Vol. 16 No. 4 , pp. 454 - 478 .

Kortmann , S. and Piller , F. ( 2016 ), “ Open business models and closed-loop value chains ”, California Management Review , Vol. 58 No. 3 , pp. 88 - 108 .

Landau , C. , Karna , A. and Sailer , M. ( 2016 ), “ Business model adaptation for emerging markets: a case study of a German automobile manufacturer in India ”, R&D Management , Vol. 46 No. 3 , pp. 480 - 503 .

Lange , K. , Geppert , M. , Saka-Helmhout , A. and Becker-Ritterspach , F. ( 2015 ), “ Changing business models and employee representation in the airline industry: a comparison of British Airways and Deutsche Lufthansa ”, British Journal of Management , Vol. 26 No. 3 , pp. 388 - 407 .

McGrath , R.G. ( 2010 ), “ Business models: a discovery driven approach ”, Long Range Planning , Vol. 43 Nos. 2-3 , pp. 247 - 261 .

McNamara , P. , Peck , S.I. and Sasson , A. ( 2013 ), “ Competing business models, value creation and appropriation in English football ”, Long Range Planning , Vol. 46 No. 6 , pp. 475 - 487 .

Markides , C.C. ( 2013 ), “ Business model innovation: what can the ambidexterity literature teach us? ”, Academy of Management Perspectives , Vol. 27 No. 3 , pp. 313 - 323 .

Mason , K. and Spring , M. ( 2011 ), “ The sites and practices of business models ”, Industrial Marketing Management , Vol. 40 No. 6 , pp. 1032 - 1041 .

Mehrizi , M.H.R. and Lashkarbolouki , M. ( 2016 ), “ Unlearning troubled business models: from realization to marginalization ”, Long Range Planning , Vol. 49 No. 3 , pp. 298 - 323 .

Mezger , F. ( 2014 ), “ Toward a capability-based conceptualization of business model innovation: insights from an explorative study ”, R&D Management , Vol. 44 No. 5 , pp. 429 - 449 .

Michel , S. ( 2014 ), “ Capture more value ”, Harvard Business Review , Vol. 92 No. 4 , pp. 78 - 85 .

Morris , M.H. , Shirokova , G. and Shatalov , A. ( 2013 ), “ The business model and firm performance: the case of Russian food service ventures ”, Journal of Small Business Management , Vol. 51 No. 1 , pp. 46 - 65 .

Osterwalder , A. , Pigneur , Y. and Tucci , C.L. ( 2005 ), “ Clarifying business models: origins, present, and future of the concept ”, Communications of the Association for Information Systems , Vol. 16 No. 1 , pp. 1 - 25 .

Peters , C. , Blohm , I. and Leimeister , J.M. ( 2015 ), “ Anatomy of successful business models for complex services: insights from the telemedicine field ”, Journal of Management Information Systems , Vol. 32 No. 3 , pp. 75 - 104 .

Rajala , R. , Westerlund , M. and Möller , K. ( 2012 ), “ Strategic flexibility in open innovation – designing business models for open source software ”, European Journal of Marketing , Vol. 46 No. 10 , pp. 1368 - 1388 .

Roberge , M. ( 2015 ), “ The right way to use compensation: to shift strategy, change how you pay your team ”, Harvard Business Review , Vol. 93 No. 4 , pp. 70 - 75 .

Schneider , S. and Spieth , P. ( 2013 ), “ Business model innovation: towards an integrated future research agenda ”, International Journal of Innovation Management , Vol. 17 No. 1 , pp. 134 - 156 .

Shafer , S.M. , Smith , H.J. and Linder , J.C. ( 2005 ), “ The power of business models ”, Business Horizons , Vol. 48 No. 3 , pp. 199 - 207 .

Sinfield , J.V. , Calder , E. , McConnell , B. and Colson , S. ( 2012 ), “ How to identify new business models ”, MIT Sloan Management Review , Vol. 53 No. 2 , pp. 85 - 90 .

Sinkovics , N. , Sinkovics , R.R. and Yamin , M. ( 2014 ), “ The role of social value creation in business model formulation at the bottom of the pyramid – implications for MNEs? ”, International Business Review , Vol. 23 No. 4 , pp. 692 - 707 .

Spieth , P. , Schneckenberg , D. and Ricart , J.E. ( 2014 ), “ Business model innovation – state of the art and future challenges for the field ”, R&D Management , Vol. 44 No. 3 , pp. 237 - 247 .

Sorescu , A. , Frambach , R.T. , Singh , J. , Rangaswamy , A. and Bridges , C. ( 2011 ), “ Innovations in retail business models ”, Journal of Retailing , Vol. 87 No. 1 , pp. S3 - S16 .

Sosna , M. , Trevinyo-Rodríguez , R.N. and Velamuri , S.R. ( 2010 ), “ Business model innovation through trial-and-error learning: the naturhouse case ”, Long Range Planning , Vol. 43 Nos. 2-3 , pp. 383 - 407 .

Storbacka , K. ( 2011 ), “ A solution business model: capabilities and management practices for integrated solutions ”, Industrial Marketing Management , Vol. 40 No. 5 , pp. 699 - 711 .

Taran , Y. , Boer , H. and Lindgren , P. ( 2015 ), “ A business model innovation typology ”, Decision Sciences , Vol. 46 No. 2 , pp. 301 - 331 .

Transfield , D. , Denyer , D. and Smart , P. ( 2003 ), “ Towards a methodology for developing evidence-informed management knowledge by means of systematic review ”, British Journal of Management , Vol. 14 No. 3 , pp. 207 - 222 .

Teece , D.J. ( 2010 ), “ Business models, business strategy and innovation ”, Long Range Planning , Vol. 43 Nos 2-3 , pp. 172 - 194 .

Velu , C. ( 2015 ), “ Business model innovation and third-party alliance on the survival of new firms ”, Technovation , Vol. 35 No. 1 , pp. 1 - 11 .

Velu , C. ( 2016 ), “ Evolutionary or revolutionary business model innovation through coopetition? The role of dominance in network markets ”, Industrial Marketing Management , Vol. 53 No. 1 , pp. 124 - 135 .

Velu , C. and Jacob , A. ( 2014 ), “ Business model innovation and owner–managers: the moderating role of competition ”, R&D Management , Vol. 46 No. 3 , pp. 451 - 463 .

Visnjic , I. , Wiengarten , F. and Neely , A. ( 2016 ), “ Only the brave: product innovation, service business model innovation, and their impact on performance ”, Journal of Product Innovation Management , Vol. 33 No. 1 , pp. 36 - 52 .

Weill , P. and Woerner , S.L. ( 2013 ), “ Optimizing your digital business model ”, MIT Sloan Management Review , Vol. 54 No. 3 , pp. 71 - 78 .

Wilson , F. and Post , J.E. ( 2013 ), “ Business models for people, planet (& profits): exploring the phenomena of social business, a market-based approach to social value creation ”, Small Business Economics , Vol. 40 No. 3 , pp. 715 - 737 .

Wirtz , B.W. , Pistoia , A. , Ullrich , S. and Göttel , V. ( 2016 ), “ Business models: origin, development and future research perspectives ”, Long Range Planning , Vol. 49 No. 1 , pp. 36 - 54 .

Wu , X. , Ma , R. and Shi , Y. ( 2010 ), “ How do latecomer firms capture value from disruptive technologies? A secondary business-model innovation perspective ”, IEEE Transactions on Engineering Management , Vol. 57 No. 1 , pp. 51 - 62 .

Yunus , M. , Moingeon , B. and Lehmann-Ortega , L. ( 2010 ), “ Building social business models: lessons from the grameen experience ”, Long Range Planning , Vol. 43 Nos 2-3 , pp. 308 - 325 .

Zott , C. and Amit , R. ( 2010 ), “ Business model design: an activity system perspective ”, Long Range Planning , Vol. 43 Nos 2-3 , pp. 216 - 226 .

Zott , C. , Amit , R. and Massa , L. ( 2011 ), “ The business model: recent developments and future research ”, Journal of Management , Vol. 37 No. 4 , pp. 1019 - 1042 .

Further reading

Weill , P. , Malone , T.W. and Apel , T.G. ( 2011 ), “ The business models investors prefer ”, MIT Sloan Management Review , Vol. 52 No. 4 , pp. 17 - 19 .

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Conceptualising business models: Definitions, frameworks and classifications

Fielt, Erwin (2013) Conceptualising business models: Definitions, frameworks and classifications. Journal of Business Models , 1 (1), pp. 85-105.

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The business model concept is gaining traction in different disciplines but is still criticized for being fuzzy and vague and lacking consensus on its definition and compositional elements. In this paper we set out to advance our understanding of the business model concept by addressing three areas of foundational research: business model definitions, business model elements, and business model archetypes. We define a business model as a representation of the value logic of an organization in terms of how it creates and captures customer value. This abstract and generic definition is made more specific and operational by the compositional elements that need to address the customer, value proposition, organizational architecture (firm and network level) and economics dimensions. Business model archetypes complement the definition and elements by providing a more concrete and empirical understanding of the business model concept. The main contributions of this paper are (1) explicitly including the customer value concept in the business model definition and focussing on value creation, (2) presenting four core dimensions that business model elements need to cover, (3) arguing for flexibility by adapting and extending business model elements to cater for different purposes and contexts (e.g. technology, innovation, strategy),(4) stressing a more systematic approach to business model archetypes by using business model elements for their description, and (5) suggesting to use business model archetype research for the empirical exploration and testing of business model elements and their relationships.

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Impact of initial business model on the growth trajectory of new technology-based firms: a path dependency perspective

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• Hans Löfsten   ORCID: orcid.org/0000-0002-7958-0516 1 ,
• Anders Isaksson 1 ,
• Heikki Rannikko 2 ,
• Erno Tornikoski 3 &
• Mickaël Buffart 4  

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Our study explores links between the initial business model design and the post-founding development of new technology-based firms (NTBFs) through a selection of recently established NTBFs across Sweden, Finland, and France (481 firms). The trajectory of these firms’ performance has been observed and analyzed over the span of five years. The study examines the long-term effects of NTBFs’ initial business model design on their development and the path dependency of these designs on future firm performance. Our results indicate that high-growth and stable NTBFs have distinct initial designs, implying that new firms’ founders and their business design decisions have important consequences for subsequent NTBF development. Specifically, our study examines how business model characteristics impact the growth trajectory of NTBFs by empirically differentiating between the foundational characteristics of high-growth and stable NTBFs. We find that maintaining stable activity is linked to a low level of uniqueness, less demanding business objectives, and a lack of risk while high-growth is related to a larger early access to resources. We propose an explanation using path dependency literature, arguing how early business model choices predetermine long-term growth paths. Our research also provides valuable insights for stakeholders in designing targeted strategies for sustainable development.

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1 Introduction

The startup ecosystem traditionally prioritizes high-growth, disruptive companies with the potential to become the next “unicorn” startup (Atzmon et al., 2022 ; Kuratko & Audretsch, 2022 ). However, this narrow focus overlooks the significance of “stable” new firms in driving economic growth and job creation (Kuckertz et al., 2023 ). Entrepreneurship researchers have predominantly concentrated on high-impact “black swan” events in the entrepreneurial realm (Mahroum, 2016 ), despite initial public offerings and venture capital-backed high-growth firms comprising only a small percentage of new firms and job creation. This oversight disregards the crucial role that stable and sustainable small and medium-sized enterprises play in propelling economic growth (Aldrich & Ruef, 2018 ). Our study aims to redirect this focus by investigating factors supporting the stability and long-term success of new technology-based firms (NTBFs) as they navigate their post-founding phase.

From a conceptual point of view, path dependency theory, as proposed by Arthur ( 1994 ) and David ( 1985 ), posits that initial choices have lasting effects, influencing future outcomes (Bergek & Onufrey, 2014 ). Previous studies have explored how path dependency affects the founding process (e.g., Boxstael & Denoo, 2020 ; Snihur & Zott, 2020 ; Tornikoski & Renko, 2014 ) and post-founding growth (e.g., Bamford et al., 2000 ), but have not been very specific in specifying what impacts founding process and subsequent development. In this study, we introduce the notion of business model as one possible conduit through which path dependency works in NTBFs.

Indeed, while NTBFs’ post-founding development is marked by diverse trajectories, including high growth, stable path, or failure, this variation can be attributed to the business models adopted by these firms. Business models play a critical role in extracting value from innovation, enhancing firm performance, and building organizational capabilities (Aversa et al., 2015 ; Chesbrough & Rosenbloom, 2002 ; Jacobides, 2006 ). However, these business models often lack clarity and undergo multiple iterations before firm establishment (Loch et al., 2008 ; Kessler et al., 2012 ). Recent studies have explored scalable and non-scalable business models (Nair & Blomquist, 2019 ; Nielsen & Lund, 2018 ) and their link to resilience (Buliga et al., 2016 ) and financial risk (Patzelt et al., 2008 ). Analyzing NTBFs’ founding business models sheds light on their growth potential and long-term viability. The success of NTBFs hinges on their initial business models, which delineate how a startup intends to generate revenue from its products or services. A robust initial business model articulates the value proposition to customers, addresses market needs, and identifies avenues for scalability. Investors often scrutinize the initial business model to evaluate its viability and potential return on investment.

Applying path dependency theory in our context, we anticipate discovering differences in founding business models between stable and high-growth NTBFs. This investigation is crucial for technology transfer, as the stability and adaptability of NTBFs are central to the effective dissemination and application of new technologies. To this end, our study builds on previous research by investigating the influence of founding business model design on NTBFs’ sustained development. We consider NTBFs to be founded when they have initiated business activities and generate revenue, thus identifying their founding business models. Specifically, we aim to understand NTBFs’ post-founding trajectories by examining the developmental impact of founding business models. Guided by path dependency theory, our primary research question is: To what extent do founding business models and their different elements explain why some NTBFs witness stable post-founding development while others witness high growth?

To investigate our research question, we conduct a quantitative, exploratory study using a sample of 481 NTBFs established across Finland, France, and Sweden in 2013. Tracking their progress until 2018, corresponding to their first five years of operation, our findings suggest that certain elements of founding business models significantly influence subsequent NTBF development. Additionally, we observe distinct differences in founding business models between stable and high-growth NTBFs. Overall, our study provides some evidence supporting the utility of path dependency theory in comprehending the lasting effects of founders’ decisions on NTBFs’ post-founding development. By identifying the characteristics and strategies enabling NTBFs to maintain positive activity over time and contribute to economic growth, this study provides valuable insights for policymakers, entrepreneurs, and researchers in their efforts to support the development of stable, job-creating startups. As such, our findings have practical implications for entities interested in investing in NTBFs, such as venture capitalists, as they underscore the importance of understanding the conditions under which NTBFs are founded.

The paper is organized as follows. Section  2 outlines the theoretical framework. Section  3 details the dataset, data collection methods, and analyzed variables. Section  4 presents the findings, and Sect.  5 discusses their implications. Finally, Sect.  6 presents the conclusions.

2 Theoretical framework

2.1 growth and survival.

Policymakers and researchers recognize NTBFs’ significant impact on long-term economic growth (Spencer & Kirchhoff, 2006 ; Storey & Tether, 1998 ). High-growth NTBFs can spur job creation (Coad et al., 2014 ; Henrekson & Johansson, 2010 ), leading to policies favoring resource allocation for their support (Mason & Brown, 2013 ; Shane, 2009 ). However, critics highlight the potential unsustainability of high growth (Daunfeldt & Halvarsson, 2015 ) and difficulty in identifying high-growth firms early (Hölzl, 2009 ; Rannikko et al., 2019 ; Storey, 1994 ). Evolving firm growth theories include neoclassical, transaction cost, and Penrose’s theories. Modern economic theory, emphasizing competition and rapid technological change, aligns with contemporary growth and industrial understanding. This concurs with Schumpeter’s concept of capitalism as “creative destruction.” Alchian ( 1950 ) argues for the economic progress-driving mechanism of successful firm survival and growth, contrasting with the exit of less viable firms. However, new firms face challenges, with average survival rates around 50–55% (Dunne et al., 1989 ; Löfsten, 2016 ; van Praag, 2003 ). In 2005, the five-year survival rate for EU-founded enterprises was 46.4% (Eurostat, 2014 ), making survival and growth critical for economic development.

Policymakers acknowledge high-growth NTBFs’ role in driving economic growth through R&D investments and innovative products (Martínez-Ros & Labeaga, 2009 ; García-Manjón and Remero-Merino, 2012 ). Several studies focus on NTBFs and early processes and support (Davidsson & Klofsten, 2003 ) as well as on the human capital side of NTBFs (De Cleyn, et al., 2015 ). However, high-growth NTBFs remain uncommon (Autio & Rannikko, 2016 ). Typically, small firms exhibit tent-shaped growth rate distributions, implying limited high-growth instances (Coad & Hölzl, 2009 ). High-growth firms struggle to maintain growth over time (Coad, 2007 ; Coad & Hölzl, 2009 ), and are often labeled “temporarily unstable populations” (Delmar et al., 2003 ).

With this focus on high-growth firms, firms that maintain stability over time have received little attention, despite their economic importance. Although much is known regarding these firms’ survival rates, how and why they achieve stability is less understood. To address this knowledge gap, this study applies path dependency theory to investigate the characteristics of founding business models that may influence NTBF development over time. Specifically, we explore the relationship between NTBFs’ founding business models and subsequent development, focusing on both high-growth and stable firms.

2.2 Path dependency and initial conditions

We adopt path dependency theory to explore how new firms’ founding business models affect subsequent development, and whether these firms experience high growth or stability. The path dependency theory posits that past decisions and actions influence future ones, leading to a similar developmental pattern. This suggests that a system has a memory that shapes its future development. However, path dependency is not a clearly defined concept (Djelic & Quack, 2007 ; Morgan & Kubo, 2005 ; Pierson, 2000 ), and collecting acceptable empirical evidence for it can be challenging (Vergne & Durand, 2010 ).

Scholars such as David ( 1985 ), Arthur ( 1989 ), North ( 1990 ), Witt ( 1997 ), Rusko et al. ( 2019 ), Sydow et al. ( 2020 ), Cloutier and Messeghem ( 2021 ), Samuelsson et al. ( 2021 ), Ben-Hafaïedh and Hamelin ( 2022 ), and Hepp ( 2022 ) have been widely discussing this theory in the context of technological change. NTBFs are considered successful when they begin operations and generate sales revenue, at which point, past decisions regarding market access result in a founding business model. This model, validated by market success, continues to influence future decisions and determines a firm’s development path .

Stinchcombe ( 1965 ) presents supporting ideas when arguing that a new organization’s performance is significantly affected by the conditions and events surrounding its founding. Empirical evidence shows that founding conditions affect organizations over time (e.g., Boeker, 1988 , 1989 ; Kimberly, 1975 ; Pennings, 1980 ; Tucker et al., 1990 ). Consequently, founding conditions are important sources of path dependency and imprinting effects for new firms at their inception (Romanelli, 1989 ). Moreover, imprinting can be understood as a founder-driven process for new firms (Johnson, 2007 ; Simsek et al., 2015 ). Founders’ decisions when establishing a firm have long-term effects on firm development (Bamford et al., 2004 ). Thus, previous studies have proposed or discovered firm founders’ imprint routines (Phillips, 2002 ), structures (Phillips, 2005 ), strategies (Boeker, 1989 ), capabilities (Klepper, 2002 ), values (Leung et al., 2013 ), and networks (Marquis, 2003 ; McEvily et al., 2012 ; Milanov & Fernhaber, 2009 ).

Why a firm’s initial founding conditions and events shape its developmental trajectory is rooted in path dependency (Boeker, 1989 ). Once a firm establishes its initial strategies and configurations, the tendency to preserve these initial choices makes deviating from them difficult (Miller & Friesen, 1984 ; Quinn, 1980 ). This can be problematic for new firms if founders become overly optimistic and commit to decisions that ultimately hinder a firm’s ability to adapt and adjust during its development (Cooper et al., 1988 ). Once an NTBF initiates operations and generates sales revenue, choices made during its founding will shape its development path (Sydow et al., 2009 ).

Research on new firms commonly assumes that high-growth firms are successful and low-growth firms are failures. However, this ignores the importance of firms that maintain stability over time, which do not qualify as high-growth firms. Accordingly, policymakers and researchers have paid little attention to these stable firms’ economic importance and survival rates. Previous research has primarily focused on identifying high-growth firms’ characteristics or determinants (e.g., Siegel et al., 1993 ; Barringer et al., 2005 ; Moreno & Casillas, 2008 ; Audretsch, 2012 ; Bianchini et al., 2017 ; Moschella et al., 2019 ; Rydehell et al., 2019a ), which can be related to growth opportunities, ability, and motivation (Löfsten & Lindelöf, 2001 , 2002 ). However, growth orientation cannot sufficiently explain new firm growth, particularly in uncertain and unstable environments (Autio et al., 2000 ; Christensen & Raynor, 2013 ; Yli-Renko et al., 2002 ).

Some entrepreneurs refrain from pursuing certain growth strategies for non-economic reasons, such as employee well-being or the risk of losing control (Wiklund et al., 2003 ). Isaksson et al. ( 2021 ) analyze how initial business models in NTBFs influence their growth intentions and strategies. They underscore the significance of key partners, activities, resources, and value propositions in shaping the firm’s strategic orientation towards growth. Notably, while Isaksson et al. ( 2021 ) identify critical differences in the business model components between high-tech manufacturing and knowledge-intensive firms, they report minimal direct correlations between the specific design of the business model and actual early growth outcomes. This suggests that, although the choice of business model elements is strategic, it does not necessarily translate into a willingness or capability for growth. Thus, it aligns with the notion that not all founders aim to expand their new businesses rapidly or extensively (Napier et al., 2012 ; Storey, 1994 ), pointing to a nuanced understanding of growth strategies where the willingness to grow is as pivotal as the strategic choices made in the business model design. We push this study further by exploring longer term growth outcomes.

According to Kirchhoff ( 1994 ), a lack of motivation and resources can impede innovative small firms’ development. Research shows that founders’ attitudes toward growth play a significant role in entrepreneurial firms’ performance (Autio et al., 2000 ; Isaksson et al., 2013 ; Wiklund & Shepherd, 2003 ). Rydehell et al. ( 2019b ) highlights the relationship between founders’ growth orientation and actual growth. However, whether this relationship also applies to perceived performance (i.e., compared to the founders’ goals) remains unclear. A firm’s perceived performance can be influenced by unrealistic expectations at its inception (Rydehell et al., 2019b ); however, not all entrepreneurs aspire for high growth (Gartner & Liao, 2012 ; Wiklund et al., 2003 ). Research also shows that founders may differ in their attitudes toward growth (Gartner & Liao, 2012 ; Kirchhoff, 1994 ; Wiklund et al., 2003 ), which should be considered when examining high-growth firms’ characteristics and determinants (e.g., Siegel et al., 1993 ; Barringer et al., 2005 ; Moreno & Casillas, 2008 ; Audretsch, 2012 ; Bianchini et al., 2017 ; Moschella et al., 2019 ).

The discussion above highlights the crucial role that founders’ aspirations and motivations play in shaping a new firms’ developmental trajectory (Löfsten & Lindelöf, 2002 ; Yli-Renko et al., 2002 ). The decisions founders make at a new firm’s inception, such as the type of business model adopted, likely have lasting effects on firm development. This aligns with path dependency and imprinting mechanism theories, which suggest that the choices made during a firm’s early stages shape its future trajectory. However, while these theories provide insight into the potential impact of founders’ decisions, they offer little guidance on what specific elements of a founding business model may have the most significant effects on new firm development. To address this gap, our study explores what elements of founding business models, if any, have an imprinting effect on subsequent new firm development. Through an explorative examination of the types of decisions entrepreneurs can make regarding new firms’ founding business models, our study aims to provide a more nuanced understanding of the relationship between founding business models and new firm development.

Based on imprinting effects Snihur and Zott ( 2020 ) identify how founders achieve novelty imprinting, which they conceive as imprinting processes that result in and explain how cognitive imprints reinforce structural imprints in the context of business model innovation. Other researchers studying the connection between organizational models and high-tech firms found that the employment relations models firm founders adopt shape how human resource management evolves, with a strong path dependency in the development of employment systems. Baron et al. ( 2001 ) find that changes in organizational leaders’ accepted employment models increase turnover, thereby affecting subsequent organizational performance.

Our study demonstrates the utility of path dependency theory in understanding how founders’ decisions regarding founding business models have imprinting effects on NTFBs’ post-founding development. A business model delineates the manner in which a company generates, delivers, and enhances value (Amit & Zott, 2001 ; Osterwalder et al., 2005 ). In our study’s context, the founding business model pertains to the framework of a nascent firm concerning its surroundings (Chesbrough & Rosenbloom, 2002 ). We hypothesize that low-growth, stable activity is not on the same continuum as high firm growth, which is inherently prone to instability. Stable, low-growth firms could benefit from being embedded in an entrepreneurial ecosystem to face difficulties despite their weaknesses. This same ecosystem might hinder high-growth companies, giving them less control and flexibility over their activities; however, if they assume their risk, they might have more freedom to differentiate themselves from competitors.

3 Sample and method

To investigate the relationship between a new firm’s founding business model and its development, we mixed survey data (to collect information in the business model elements) with registry data (to gather annual financial records). We used logistic regression to analyze the connection between founding business models and subsequent development.

3.1 Definition of new technology-based firms

We used the NACE Rev. 2 classification to identify NTBFs, categorizing firms by R&D expenditure to value-added ratio. Our focus was on technology intensity, encompassing high-tech manufacturing, mid-tech manufacturing, and knowledge-intensive service industries. Notably, for knowledge-intensive services, we recognize that R&D expenditures are not the sole indicator of their intensity. Consistent with the Eurostat’s high-tech classification, knowledge-intensive services can also be characterized by the proportion of employees with higher education degrees, reflecting their reliance on intellectual capabilities and expertise (Eurostat, n.d.). This broader definition allows for a more inclusive identification of NTBFs across various sectors, aligning our approach with prior research (Butchart, 1987 ; Daunfeldt et al., 2015 ; Ejermo & Xiao, 2014 ).

We conducted telephone surveys with 589 NTBFs founded in 2013 across Finland, France, and Sweden to gather business model information. We obtained annual financial records from founding to 2018 via official registries. Employing logistic regression, we explored the connection between founding business models and long-term success factors. Further details are available in Appendix Table 6 .

3.2 Data collection

3.2.1 initial data collection about the founding business model.

Initially, we identified firms registered in 2013 within our target industries through business registries. Our second step involved conducting a telephone survey in early 2016. This timing was strategically chosen to ensure the firms had been operational long enough for their foundational business models to be established, typically a span of two to three years, which we considered an adequate period for meaningful data collection. In addition, surveying the firms in 2016 allowed targeting them in a phase where their business models were neither too nascent to reflect mere aspirations nor too matured to have significantly deviated from their original concepts. Business model configuration is often established through trial-and-error learning (Andries et al., 2013 ; Berends et al., 2016 ). Surveying firms after months of existence ensures that the founders provide insights about a business model on which they engaged enough time and energy to become path dependent while being, at the same time, very close to its initial implemented configuration. The survey yielded 589 responses, with 481 meeting our criteria for inclusion in the analysis.

Overall, selecting Sweden, Finland, and France allowed us to gather a diverse and representative sample of NTBFs, providing a strong foundation for our research and making our findings more generalizable to the broader European industrial sector. We selected firms from Sweden, Finland, and France to ensure the relevance of our results to the European industrial sector. These countries were chosen for several reasons. First, they have a strong history of innovation and entrepreneurship, with Sweden and Finland known for their high-tech industries (Autio et al., 2014 ; Balawi & Ayoub, 2022 ), and France having a thriving startup ecosystem (Davies, 2022 ), making them ideal for studying NTBF development. Second, they offer a diverse range of cultural and economic environments, providing a comprehensive understanding of the factors that influence NTBFs. Third, they have developed infrastructures for innovation and entrepreneurship, including access to funding, training, and mentoring programs, supporting NTBF growth and development. Finally, the availability and quality of data in these countries is excellent, allowing us to track the development of NTBFs over time. Selecting these countries enhances the validity and reliability of our findings. To study French NTBFs, we focused on the Rhône-Alpes region, known for its high business activity and concentration of cities and industrial centers, such as Lyon and Grenoble. Its business register provided a comprehensive sample, improving the robustness of our findings.

We chose our sample selection criteria carefully to ensure the data accurately represents the population of interest. We only included firms organized as limited companies, as this legal structure clearly separates the firm from the individual and eliminates hobby firms from our sample. Additionally, detailed annual report data is typically only available for limited companies, making this structure more suitable for our study. By limiting our sample in this way, ensured a more robust and representative dataset, ultimately strengthening the validity of our findings. To ensure the homogeneity of our sample, we took several measures to control for heterogeneity among new firms. As Wennberg ( 2005 ) and Davidsson ( 2007 ) note, the characteristics and origins of new firms can vary greatly. Thus, we focused on independent firms that started as “de novo” entities, rather than spin-offs from existing businesses or other types of startups. Furthermore, to ensure that the sample firms were operationally active, we only included those that were registered in a specific year (2013), active (i.e., not deregistered or liquidated), and liable for value added tax and tax prepayment. These measures allowed us to create a sample of firms that were truly independent, operationally active, and representative of the studied population.

This sample represented 18.8% of all NTBFs established in 2013 in the geographical areas of study. This response rate is consistent with previous mail surveys of small and medium-sized firms (Chandler & Hanks, 1994 ; McDougall et al., 1994 ; Yli-Renko et al., 2001 ). The non-respondents included firms that were inactive, could not be located, or chose not to participate without providing a specific reason. We found that the performance of non-respondents did not differ significantly from that of the firms in our sample, indicating that our results are generalizable to the population of NTBFs in the studied geographical areas. In the Appendix, Tables 7 and 8 respectively provide the response rates for each country and an analysis of the non-responses. Table 8 shows that firms decided not to report on their performance for reasons other than the characteristics of their founding business model.

3.2.2 Performance data and screening criteria

In 2020, we conducted a follow-up study to assess the growth and performance of our sample firms. Data were collected from reliable sources including the Retriever Business database (Sweden), Voitto + database (Finland), and Rhône-Alpes business register (France). These trusted sources maintained by organizations such as Asiakastieto Oy and French commercial courts ensured accurate, up-to-date, and comprehensive performance data.

We employed rigorous screening to ensure our sample represented genuine “de novo” firms. Firms reporting their business as “a purchase or takeover of an existing business” were excluded (44 firms). Additionally, 64 firms without established founding business models or initial sales were excluded. Data availability issues led to 75 firms being excluded, resulting in a final sample of 406 observations with performance and business model information. This meticulous screening process ensured that true independent startups were represented in our sample.

3.3 Questionnaire design and administration

To ensure reliable and valid data collection, we collaborated with TNS-Sifo, a leading research agency, to conduct telephone interviews in March 2016 across all three study countries. This approach enhanced data quality and control. Experienced professional callers, chosen randomly, were employed to further bolster data reliability. Telephone interviews yielded high response rates and minimized question misinterpretation risks. Interviewers were trained to guide respondents through the survey, reducing confusion.

Our survey development followed a two-step process. We initiated discussions with entrepreneurs to identify key resource dimensions for quantitative measurement. Thorough pre-testing and questionnaire modifications occurred through telephone discussions with firms to eliminate uncertainties. TNS-Sifo reviewed the questionnaire for language and clarity, enhancing result validity.

Interviews were monitored and recorded to ensure response consistency and quality. The master questionnaire was initially developed in English and later translated by proficient researchers into Swedish, Finnish, and French. Six NTBFs participated in a telephone pre-test to identify uncertainties and refine the survey. A pilot study with 26 NTBFs assessed questionnaire effectiveness. A pre-test in each country enhanced question clarity. Our research design prioritized reliability and validity in the data collection process.

3.4 Variables

3.4.1 dependent variables.

In the conceptual section of this paper, we suggest that firms witnessing stable and high-growth development are, by nature, different from inception. For this reason, we analyze the correlations between the business model characteristics and the firm trajectories in a different set of analyses, with two different dependent variables: a dichotomous measure for stable firms and one for high-growth firms.

Stable firms : We identified stable firms as those consistently reporting positive sales over at least three consecutive years: 2014–2016, 2015–2017, or 2016–2018 (294 firms in the sample). Stability was determined by consistent reporting, excluding firms with irregular activity reporting, failed firms, or those missing activity reports.

High-growth firms : Eurostat and OECD ( 2007 ) suggest defining high-growth firms as those with a minimum of ten employees in the founding year and an annualized employment growth surpassing 20% over three years (Hölzl, 2014 ). However, Coad et al. ( 2014 ) and Halabinsky et al. (2006) propose defining high-growth as those achieving at least 50% sales growth across three financial years. In our study, high-growth status was assigned to firms reporting sales for three consecutive years (meeting stability criteria) with an average annual growth rate exceeding 50% (103 firms in the sample). We calculated year-to-year growth (2014–2015, 2015–2016, 2016–2017, and 2017–2018), and the high-growth dummy was assigned if the four-period average exceeded 50%. Figure  1 a presents the average annual sales growth distribution, showing sparse values above 50%. Our sample comprised three groups: (1) Non-stable firms, (2) Stable firms, and (3) High-growth firms. Figure  1 b displays total sales distribution, accounting for new firms’ inherent small initial values. To avoid disproportionate effects of extreme values, we dichotomized high growth (above/below 50%). Median annual growth for NTBFs in the sample was 18%.

a Distribution of sales growth – Frequency and average sales growth. N = 406; the graph includes all the stable firms; the average sales growth is the average annual growth of sales between 2014 and 2018. If the first value is below 1 (no sales), the growth of that year is ignored, to avoid infinite value. A value of 1 means 100% sales increase per year, on average, over the study period. A negative value means that on average, the revenue decreased between the first and the last record of positive sales. b Distribution of sales (sum) over the study period. N = 406; 30 firms (not displayed) have a total revenue beyond 3 million euros over the study period

3.4.2 Independent variables

We focused on founders’ decisions regarding the design of their business, specifically the founding business model. This area of interest is particularly relevant, as new firms often encounter a high uncertainty in terms of markets and technologies (Andries et al., 2013 ), which poses challenges when deciding on a business model (Trimi & Berbegal-Mirabent, 2012 ). Furthermore, the technological uncertainties inherent in new firms’ products, services, and processes exacerbate these difficulties (Bollinger et al., 1983 ; Storey & Tether, 1998 ).

A business model is a description of how a firm creates, delivers, and adds value (Amit & Zott, 2001 ; Osterwalder et al., 2005 ). In the context of our study, the founding business model refers to the architecture of a new firm in relation to its environment (Chesbrough & Rosenbloom, 2002 ). Founding business models also reflect the market knowledge and resources that a firm can acquire and utilize (Andries & Debackere, 2007 , 2013 ).

A new firm’s architecture is commonly described in relation to its environment by dividing its business model into nine interconnected elements: value proposition, target customer segments, customer relationships, distribution channels, revenue streams, vital resources, key activities, strategic partners, and cost structure (Osterwalder et al., 2005 ). When designed effectively, these elements determine how a firm interacts with current and potential customers and organizes its internal operations and supply chain to meet customer needs (Sohl et al., 2020 ). The nine business model elements are represented by independent variables grouped into nine categories (Osterwalder & Pigneur, 2010 ):

Value proposition was measured using three five-point scales: differentiation from competitors, pricing relative to industry peers, and product quality.

Customer segment was assessed through three dummy variables: customer size, payers, and exporting.

Customer relationship was measured using a five-point scale reflecting the proximity of a firm’s relationship with primary customers.

Channel was represented as a dummy variable indicating direct customer interaction.

Revenue streams were denoted by a dummy variable for multiple revenue sources.

Key activities were a measure comprising three five-point scales evaluating the extent of internalization for expertise, technology, production, and sales-related functions.

Cost structure was a measure comprising two five-point scales reflecting the dominance of fixed costs and economies of scale in production.

Key partners were quantified by averaging the number of different partner types, such as suppliers, subcontractors, distributors, local authorities, and universities.

Key resources were assessed through two five-point scales gauging a firm’s advanced expertise and recognition, along with counting external funding sources, such as banks, venture capital, crowdfunding, or public sources.

In operationalizing the components of founding business models, our methodology employed a nuanced approach by distinguishing between reflective, formative, and single-item measures to capture the multifaceted nature of new firm development. Reflective measures were strategically applied to constructs such as the value proposition and customer relationships, where the underlying concept is believed to cause the observed indicators, ensuring coherence and inter-correlation among these indicators, reflective of the firm’s strategic emphasis (Jarvis et al., 2003 ). This approach underscores the reflective nature of these variables, where changes in the construct are expected to be mirrored by all indicators. Formative measures were utilized for constructs where indicators collectively contribute to the formation of the latent variable, as seen in key activities and cost structure. These components independently affect the business model, highlighting the formative nature of these variables where each aspect contributes uniquely to the construct, necessitating a composite measure to account for the diverse elements (Diamantopoulos & Winklhofer, 2001 ).

Lastly, single-item measures were applied to straightforward constructs, where a singular, well-defined indicator sufficiently captures the construct’s nature, such as channel and revenue streams. This decision, guided by the need for parsimony and the aim to reduce respondent burden, did not compromise the depth of insights into the founding business models’ influence on firm development (Edwards & Bagozzi, 2000 ).

Together, these methodological choices, reflective measures for strategic emphasis constructs, formative measures for composite business model elements, and single-item measures for straightforward constructs, ensure a robust and nuanced understanding of how foundational business model elements drive new firm growth and evolution.

3.4.3 Control variables

We included four control variables to isolate the effects of different settings (i.e., all chosen variables may be associated with NTBF sales growth, in addition to the chosen independent variables): (1) Type of goods for sales measured on a five-point scale whether firms were selling “only products” (1), “Mainly products” (2), “Products and services equally” (3), “Mainly services” (4) or “Only services” (5); (2) Growth satisfaction as a composite measure of how satisfied the founder was with the time required to commercialize the product or service, with an increase in sales, business profitability, and employment; (3) Startup experience ; and (4) Industry experience of the founders (dummies). We used dummies to assess whether founders had experience in startups (“true” if they had founded a prior business) or in the industry (“true” if the number of years of experience was greater than (5) To address the highly skewed distribution in our sample. We did not choose one year as the threshold, because 94% of the respondents had at least some prior industry experience.

4.1 Descriptive statistics

Table 1 presents the descriptive statistics for our initial sample of NTBFs (complete observations, minus respondents screened out; N  = 481), for the complete dataset after collecting performance measures in the follow-up study in 2020 ( n  = 406), and for the group of stable firms ( n  = 294). Overall, the values are very similar across groups, suggesting that a firm’s founding business model and its different elements, as measured in 2016, had little to no effect on subsequent firm development (follow-up and stable firms).

Table 2 shows the correlations between variables in our model. No major multicollinearity issues were found overall, although some business model elements were somewhat correlated. The highest correlation was 0.36, between the number of external sources of funding and number of key partners. To avoid spurious effects due to some collinearity between variables, we ran our two models with each business model element separately and all elements together.

4.2 Regression analysis

The next step was the regression analysis. Table 3 presents the results of the logistic regression to assess the correlations between the business model measurements and three-year positive sales reporting (at least) to identify stable NTBFs. Blocks 1–9 present the different business model elements individually. Model 10 aggregates all business models elements. The results were consistent across models. Product quality was strongly significantly correlated was a lower likelihood of reporting stable sales (β = -0.925; p -value < 0.001), as was customer size (many small clients, as opposed to a few big clients; β = -0.661; p -value < 0.05). Key activities (higher value means that more firm’s activities are done externally; β = 0.481; p -value < 0.05) and key resources (higher value means a firm’s expertise is more advance and their reputation is better; β = 0.498; p -value < 0.001) were associated with a higher likelihood of reporting stable sales. Thus, the NTBFs in our sample were more likely to achieve stable sales (as opposed to non-stable sales) when characterized by lower product quality, having few big clients, higher externalization of key activities, and better resources (more advanced expertise and a better reputation).

Table 4 focuses on the stable firms (reported positive sales for at least three consecutive years) and predicts which business model elements are correlated with a high-growth development path. The results were consistent across models. Two business model elements were correlated with high-growth. External funding (higher value means more funding sources) was associated was a higher likelihood of reporting high growth (β = 0.576; p -value < 0.01), as were revenue streams (higher value means higher diversity in revenue streams; β = 0.865; p -value < 0.01). Overall, the NTBFs in our sample were more likely to achieve an average annual growth above 50% (as opposed to stable sales) when they were characterized by more diverse revenue streams and funding sources.

4.3 Robustness checks

Most recently founded NTBFs are in the computer programming industry, which was also the case in our sample (60% of firms). To assess the extent to which our results are robust to industry differences, we computed multiple models with industry dummies and subsamples by industry (computer programming or others). The results are available in Table 9 in the Appendix. For the models that predicted sales stability, our results were robust to industry controls. Maintaining the same significance level is difficult when splitting a sample, likely because of a lack of power related to a much smaller sample size. For the models predicting high growth, although the direction remained the same and the model with industry controls was identical, the significance level varied by industry. Further studies could consider the industry-specific effects of business model characteristics with a larger sample of firms.

5 Discussion, limitations and future research directions

This study applied path dependency theory to investigate if variations in founding business models impact NTBFs’ development paths, distinguishing between stable growth and high growth. We analyzed a 2013 NTBF cohort in Sweden, Finland, and France, tracking their development from 2014 to 2018. Our findings reveal two key insights. First, NTBFs achieve sales stability by displaying traits such as lower product quality, fewer major clients, increased externalization of key activities, and superior resources (enhanced expertise and reputation). Second, NTBFs attain high growth through diverse revenue streams and funding sources. However, few founding business model elements overall influence NTBF development. Elements driving stable growth and high growth diverge, with no single element aligning with both trajectories. We explore the theoretical and practical implications of these findings further below.

5.1 Theoretical implications

While classical approaches to path dependency theory focus on external conditions surrounding new organizations, our study focuses on imprinting factors under founders’ volitional control: newly founded firms’ business models. Founders face several possibilities when considering whether to start a new firm; however, once they begin to make decisions and take action, these initial choices trigger further developments that determine a firm’s organizational path (Sydow et al., 2009 ). Our findings appear to support this, as they show differences in founding business models that apparently result in different development paths between stable and high-growth NTBFs. These observations provide support for path dependency theory in that choices made at a new firm’s inception have significant effects well beyond the founding phase (Aspelund et al., 2005 ; Geroski et al., 2010 ). Thus, our findings complement existing studies demonstrating the benefits of adopting path dependency theory to explain performance and success when founding new firms (e.g., Boxstael & Denoo, 2020 ; Snihur & Zott, 2020 ). Boxstael and Denoo ( 2020 ) analyzed business model design during new venture creation and provided a dynamic view on founder identity imprinting on business models, finding that novelty-centered business models are derived from cognitive work developed by founder identity construction and verification processes.

The founding business model elements explored in our study did not all exert significant path dependency effects on subsequent NTBF development. Specifically, the nine business model elements were not shown to be equally important for imprinting NTBFs’ development paths. Notably, some business model elements are related to stable development while others are associated with high-growth; however, the rationale behind these differences in path dependency effects deserves further exploration.

First, we observed that high-growth NTBFs’ founding business models are characterized by highly diverse funding sources and revenue streams. External funding has been consistently associated with high growth, as a requirement or enabler (Assenova & Sorenson, 2017 ; Delmar and Shane, 2003 ; Cavallo et al., 2019 ; Huergo et al., 2020 ). Thus, external financing can be used to acquire other resources (Katila et al., 2008 ) and enhance the development of the new offer to accelerate market development (Festel et al., 2013 ; Homburg et al., 2014 ; Katila et al., 2008 ). Firms with access to more resources can diversify their revenue sources early. Resource slack enables parallel development (as opposed to sequential) of different revenue logics. Although these observations are not particularly surprising, the underlying path dependency remains in question. We refer to this business model path dependency as “increasing resources” and posit that, when external funding brings in new powerful external stakeholders, this creates a moral and legal obligations for NTBFs to deliver on promises they made to secure financing (Table  5 ). Thus, the entry of external stakeholders in the form of new funding imprints NTBF development toward the sole goal of high growth. Acquiring other required resources through external funding can also cement an NTBF’s path toward high growth.

Second, stable NTBFs have a distinct path dependency. We observed that stable NTBFs’ founding business models are characterized by lower product quality , few big customers , externalizing key activities , and better resources (higher expertise and reputation). Adopting these elements in their founding business model will help NTBFs experience stable development. These elements provide an intriguing picture about stable NTBFs. To design firms that will experience stable development, founders should focus on lower-quality products, offer their products to few big clients, and maintain a lean organization (i.e., externalize key activities), while honing their expertise and reputation. We refer to this business model path dependency as “preserving resources,” (Table  5 ) and posit that, when founders aim to maintain sales, overextending their resources may not be sensible.

The assumption that founders focus on lower-quality products might be explained by their lack of funding to develop high-quality products. Stable growth might be result from an inability to incorporate venture capital or other investments, not a deliberate design choice, and externalizing key activities may not lead to lower quality, but rather a basic lack of funding to internalize activities. This could be a critical design issue related to a trade-off between product-related choices and financial arrangements. The selection of economies of scope versus scale and product quality may be evident design choices enabled by financial resources and risk.

Thus, NTBFs may face drawbacks in developing perfect products (which takes time), while missing potential revenue from offering less-finished products on the market (DeKinder & Kohli, 2008 ). Externalizing the maximum number of key activities might also make it harder for NTBFs to pursue high-quality products. Instead, keeping an organization lean, and focusing on honing its own internal expertise and reputation, might be the right decision if internal resources are used to target a few large clients and keep them satisfied with lower-quality products. Externalizing key activities might also allow NTBFs to remain flexible when facing potential market disturbances (Kim & Pennings, 2009 ) and adjust needed operations to maintain sales. When adopting path dependency theory to explain stable NTBF development, several initial decisions of founders should be considered: the organization of key activities (maximum number externalized), quality of firm resources, and less-than-perfect products initially offered to a few big clients. Compared with the other five, these four business model elements appear to result in more imprinting effects on NTBFs’ subsequent stable development.

Our study indicates that new firms’ founders and their business design decisions have important consequences for subsequent NTBF development. However, designing business models is complex, can require multiple iterations, and may be characterized by regression, which conflicts with path dependency theory. After a business model is implemented and exploited, path dependency might hinder changes, particularly in exploration phases where new high-tech startups have more freedom and entrepreneurs appear completely free to choose their path. Several trade-offs between technology, financial, product/service and financial dimensions in a business model are intently related and interdependent, and the most important issues can be related to customers, resources, and expertise or an entrepreneurial ecosystem. A founder’s decision itself might not imprint a certain business model, but rather the degree to which the founder succeeds in attracting external funding. Certain partners being included in an entrepreneurial ecosystem leads to access to capital. Including a venture capitalist’s relevant knowledge and partners including intellectual capital is often why startups grow quickly. However, receiving external funding may not be an intentional choice founders make, but dependent on selection mechanisms that venture capital funding agencies commonly use.

5.2 Practical implications

Our study has practical relevance for not only NTBFs but also individuals interested in investing in such firms, such as venture capitalists. To make informed investment decisions, potential investors should understand the conditions under which an NTBF is founded. The job-creation ability of high-growth firms implies that policymakers should allocate more resources to support these firms, rather than investing in startups that generally have no growth ambition. However, this suggestion has been criticized because high-growth does not appear to have long-term stability, and potential high-growth firms are difficult to identify early. However, stable firms can also benefit from being embedded in an entrepreneurial ecosystem, which can provide them with the support and resources necessary to face difficulties despite their weaknesses. Therefore, policymakers should consider allocating resources to support both high-growth and stable NTBFs to promote the overall development of technology-based industry.

While it’s true that stable firms can benefit from being embedded in an entrepreneurial ecosystem by gaining access to new ideas, talent, and potential collaboration opportunities, the practical implementation of this recommendation may encounter several challenges. Firstly, stable firms may have different organizational cultures and risk appetites compared to start-ups and other entrepreneurial ventures within the ecosystem, which could lead to difficulties in integrating and collaborating effectively. Secondly, the priorities and objectives of stable firms may not always align with those of the entrepreneurial ecosystem. These firms may prioritize efficiency, predictability, and risk mitigation over innovation and experimentation, making it challenging to navigate within the dynamic and uncertain environment of an entrepreneurial ecosystem.

The approach to allocate more resources to support high-growth NTBFs over start-ups with no growth ambition is a topic that warrants careful consideration and discussion. High-growth NTBFs have the potential to significantly impact economic growth, job creation, and innovation. By allocating resources to support these firms, policymakers can catalyze economic development and drive technological advancements that benefit society as a whole. NTBFs often pioneer disruptive technologies and business models that enhance competitiveness and drive industry innovation. By prioritizing support for high-growth NTBFs, policymakers can foster a culture of innovation and entrepreneurship that propels industries forward. High-growth NTBFs have the potential to scale rapidly and expand into international markets, bringing revenue and investment back to the home country. Allocating resources to support these firms can position the country as a leader in emerging industries and create opportunities for global market penetration. However, supporting start-ups with no growth ambition can contribute to job stability, community resilience, and the diversification of the business landscape. Policymakers must strike a balance between supporting high-growth NTBFs and start-ups with no growth ambition. Both types of firms play valuable roles in the economy, and a holistic approach that considers the diverse needs of entrepreneurs and businesses is essential. A balanced approach that considers the unique contributions and challenges of different types of firms is essential for fostering a dynamic and resilient entrepreneurial ecosystem.

In examining the influence of initial business models on the growth trajectories of NTBFs, it is pertinent to consider the broader context of governmental support mechanisms, such as the Small Business Innovation Research (SBIR) program in the United States. The SBIR program exemplifies a strategic government initiative aimed at fostering innovation and growth within small businesses, serving as a critical comparison point for our study. As highlighted by Link and Scott (2013), the SBIR program underscores the economic role of government in facilitating business innovation and development. This comparison elucidates the nuanced differences in governmental roles across different national contexts and their impact on NTBF growth. Furthermore, our analysis aligns with the concept of institutional path dependence, as discussed by Goel and Saunoris ( 2016 ), which emphasizes the enduring influence of initial conditions and institutional frameworks on firms’ international research intensity and growth patterns.

5.3 Limitations and future research directions

This study has limitations that can provide a foundation for future research. First, our study has limitations in terms of measuring business models. Although we used a comprehensive framework of nine business model elements, alternative, more effective measures may exist for some elements, particularly those we found to have no significant impact on NTBF development, such as customer relationships, key partnerships, and customer-centric value proposition. Also, conceptually, the role of critical design in business model innovation has received some attention (Clauss, 2017 ; Sánchez & Ricart, 2010 ; Schneckenberg & Velamuri, 2019 ) because the design aspect and how these nine business model elements of Osterwalder and Pigneur ( 2010 ) does not make the interdependencies (trade-offs) between design choices explicit. Trade-offs with respect to market access include customer segmentation and channels used to access customers and may be part of a business model’s design, but not the result of design choices. Additionally, we did not collect data on respondents’ growth mindset, which might provide insights into how it aligns with various imprinting elements. Thus, future research should explore these issues in greater depth and develop new methods for measuring business model elements in the context of NTBF development.

Second, we also acknowledge that relying on founders’ declarations about their business may lead to some biases in the answer, including desirability biases. This is a common risk of surveys. We tried to mitigate this risk by measuring the business model elements in a neutral way, giving no hint to the respondent on possible preference in answer. We also collected the performance measure independently of the survey, from registry. However, future studies may try to assess business characteristics using, for instance, archival data and observations rather than declaration, for increased objectivity of the measures.

Third, regarding the sampling frame, we chose NTBFs created (registered) in 2013 and surveyed them in 2016. This allowed us to analyze the founding business models of NTBFs that had generated sales revenue, which is an important indicator of a company’s progress and growth potential. Additionally, this sampling method allowed us to track NTBF development over time, which is crucial for understanding factors that influence firm development. However, this might have excluded some NTBFs created in 2013 that had not reported sales revenue at the time of our survey but might have succeeded in doing so after 2016. Future research can expand and improve our sampling method by incorporating a wider range of NTBFs.

Reflecting further on our methodological choices, particularly the exclusion of firms without established founding business models or those that did not report performance data, we acknowledge the potential for selection bias. This exclusion was predicated on the focus of our study on the tangible impacts of specific business model configurations on firm performance. Including firms at too nascent or undefined a stage could have compromised the clarity and relevance of our findings. However, this approach may limit the generalizability of our results across a broader spectrum of NTBFs. Recognizing this, future research could endeavor to include a wider range of NTBFs, perhaps those in earlier stages of development or with incomplete data sets, employing innovative methodologies to infer missing data points. Such studies could provide valuable insights into the early dynamics of business model formation and performance outcomes, enriching our understanding of NTBF development trajectories. This expansion of the research scope would not only address potential biases but also enhance the robustness and applicability of findings across different contexts and stages of firm development.

Fourth, we used a survey to collect information on founding business models, resulting in cross-sectional data. Thus, while we can provide a snapshot of the situation of NTBFs in 2016, we have limited means to identify founders’ intentions and development paths in firms’ early stages. However, our design was able to capture the state of a founding business model in 2016, and the subsequent development data collected through business registries provides valuable insights into these firms’ post-founding development. Although our design has its limitations, we have provided a detailed description of our methodological approach to allow future researchers to build upon and improve our measures and design. Due to the structure of our data and the type of analyses we conduct, correlational in nature, we make no causal claims, but we highlight significant differences in the initial business model characteristics of some NTBFs with stable development trajectories and with high-growth trajectories. We hope that further studies may overcome empirical limitations of ours, including an integrated measure and modeling of the new firm growth trajectories.

Fifth, the study’s claim that specific business model elements dominate path dependency effects on subsequent high-growth NTBFs overlooks the dynamic nature of entrepreneurial processes. While certain business model elements may indeed influence the trajectory of NTBFs, attributing dominance to specific factors oversimplifies the complex interplay of variables shaping entrepreneurial outcomes. Entrepreneurial ventures are inherently dynamic, influenced by various internal and external factors that evolve over time. Path dependency effects, while significant, are just one aspect of a multifaceted process that includes adaptation, learning, and response to changing market conditions, technological advancements, and competitive landscapes. Advocating for a more nuanced approach to understanding NTBF development involves recognizing the interactive nature of entrepreneurial processes. Rather than attributing outcomes solely to specific business model elements, it is crucial to consider how these elements interact with each other and with external factors to shape the growth trajectory of NTBFs.

Our investigation was guided by path dependency theory. We acknowledge that alternative perspectives exist to investigate the same phenomenon. In fact, we encourage future scholarly work to build on our insights and continue exploring the phenomenon of stable development among NTBFs by adopting alternative theoretical perspectives to complement and build on our results. However, rather than categorizing founding business model elements into distinct path dependency effects, another research approach is to study the complex interplay of factors that shape new firm development. This approach acknowledges that the process of founding and developing a new firm involves a dynamic interaction of various internal and external factors. These factors can include market conditions, technological advancements, regulatory environments, entrepreneurial skills and capabilities, industry dynamics, and socio-cultural influences, among others. By focusing on the interplay of these factors, researchers and practitioners can gain a deeper understanding of how new firms emerge and evolve over time. Hopefully, our findings will inspire further scholarly work and serve as a catalyst for further conceptual development in this field. Future research can also focus on different types of business models, industries, or countries to establish our findings’ generalizability. In addition to investigating the imprinting effects of founding business models on subsequent NTBF development, it would be valuable for future research to explore the origins of founding business models and extent to which they are shaped by path dependency and imprinting mechanisms. A further challenge for future scholars is also to develop improved methods for measuring business model elements (for example customer relationships and key partnerships) in the context of NTBFs to better guide decision making of investors and policy makers.

6 Conclusions

This study provides valuable insights into the role of path dependency of founding business models on NTBFs’ post-founding development. Given the crucial role NTBFs play in the economy, gaining a deeper understanding of their development paths is of great importance. This study’s findings provide support for path dependency theory, indicating that the choices made at the inception of a new organization have profound effects on its future development. The study reveals that differences in founding business models result in distinct development paths for NTBFs with stable compared with high growth. NTBFs with stable growth are typically characterized by lower-quality products, fewer big clients, higher externalization of key activities, and better resources, while high-growth NTBFs have more diverse revenue streams and funding sources. This study emphasizes the significance of considering theory-based logic to explain the post-founding development of NTBFs and has implications for both academia and practitioners. Furthermore, for policymakers the idea that founding conditions play a significant role in NTBF development should also be of importance. Understanding concerning this relationship would help to develop conditions under which desired types of NTBFs could be created. By enriching the ongoing discussion regarding the importance of founding business models and their imprinting role in NTBFs’ post-founding development, we aim to contribute to the field and provide useful insights for future research.

Differences in founding business models indeed dictate distinct development paths for NTBFs. However, oversimplification of these paths may hinder practical relevance by overlooking the nuanced entrepreneurial trajectories that exist. Each NTBF, depending on its unique business model, faces a set of challenges and opportunities that shape its development journey. For instance, a knowledge-intensive service startup may have a different growth trajectory compared to a manufacturing startup due to differences in market dynamics, customer acquisition strategies, and revenue models. By recognizing and understanding these differences, policymakers, investors, and entrepreneurs can tailor their support, funding, and strategies to better suit the specific needs of NTBFs. Failure to acknowledge the complexity of entrepreneurial trajectories may result in generic solutions that do not effectively address the diverse challenges faced by NTBFs.

Furthermore, whether an NTBF targets many small customers or a few big customers does not appear to matter; once they accept external funding, they need to pursue high growth no matter what type of customers they target. Similarly, regardless of whether key activities are mostly external or internal, or their own expertise is high quality, an NTBF that accepts external funding needs to pursue high growth. Almost all other business model elements are irrelevant (except the revenue model) from a path dependency perspective if an NTBF accepts external funding. Thus, when adopting path dependency to explain the development of NTBFs toward a high-growth path, only at two of the founders’ initial decisions need to be examined: whether they accepted external funding and if they decided to develop multiple revenue streams simultaneously with the firm’s founding. These two business model elements appear to override any path dependency effects the other seven might have on the subsequent high growth of NTBFs. We aimed to provide conceptual arguments, highlighting why certain business model elements appear to have a greater impact on NTBF development. Our study has limited ability to examine the factors that influence founding business model formation, particularly during the nascent entrepreneurial stage when founders are trying to establish their business and generate their first sales. This could include exploring the constraints and forces that shape the development of an entrepreneurial project, and how they may affect the creation of the desired founding business model. Understanding these underlying mechanisms could provide insight into how founding business models emerge and evolve over time.

Alchian, A. A. (1950). Uncertainty, evolution and economic theory. Journal of Political Economy, 58 , 211–222.

Article   Google Scholar  

Aldrich, H. E., & Ruef, M. (2018). Unicorns, gazelles, and other distractions on the way to understanding real entrepreneurship in the United States. Academy of Management Perspectives, 32 (4), 458–472.

Amit, R., & Zott, C. (2001). Value creation in e-business. Strategic Management Journal, 22 (6–7), 493–520.

Andries, P., & Debackere, K. (2007). Adaptation and performance in new businesses: Understanding the moderating effects of independence and industry. Small Business Economics., 29 (1–2), 81–99.

Andries, P., Debackere, K., & van Looy, B. (2013). Simultaneous experimentation as a learning strategy: Business model development under uncertainty. Strategic Entrepreneurship Journal, 7 (4), 288–310. https://doi.org/10.1002/sej.1170

Arthur, W. B. (1989). Competing technologies, increasing returns, and lock-in by historical events. Economic Journal, 99 (394), 116–131.

Arthur, W. B. (1994). Increasing returns and path dependence in the economy . University of Michigan Press.

Book   Google Scholar  

Aspelund, A., Berg-Utby, T., & Skjevdal, R. (2005). Initial resource´s influence on new venture survival: A longitudinal study of new technology-based firms. Technovation, 25 (11), 1337–1347.

Assenova, V. A., & Sorenson, O. (2017). Legitimacy and the benefits of firm formalization. Organization Science, 28 (5), 804–818.

Atzmon, M. B., Vanderstraeten, J., & Albers, S. (2022). Small-firm growth-enabling capabilities: A framework for young technology-based firms. Technovation, 117 , 102542.

Audretsch, D. (2012), Determinants of high-growth entrepreneurship. Report prepared for the OECD/DBA International Workshop on “High-Growth Firms: local policies and local determinants . Copenhagen, 28th of March, 2012.

Autio, E., Rannikko, H., Handelberg, J., and Kiuru, P. (2014). Analyses on the Finnish high-growth entrepreneurship ecosystem.

Autio, E., & Rannikko, H. (2016). Retaining winners: can policy boost high-growth entrepreneurship? Research Policy, 45 (1), 42–55.

Autio, E., Sapienza, H., & Almeida, J. (2000). Effects of time to internationalization, knowledge-intensity, and imitability on growth. Academy of Management Journal, 43 (5), 909–924.

Aversa, P., Furnari, S., & Haefliger, S. (2015). Business model configurations and performance: A qualitative comparative analysis in Formula One racing, 2005–2013. Industrial and Corporate Change, 24 (3), 655–676.

Balawi, A., & Ayoub, A. (2022). Assessing the entrepreneurial ecosystem of Sweden: A comparative study with Finland and Norway using Global Entrepreneurship Index. Journal of Business and Socio-Economic Development, 2 (2), 165–180.

Bamford, C. E., Dean, T. J., & Douglas, T. J. (2004). The temporal nature of growth determinants in new bank foundings: Implications for new venture research design. Journal of Business Venturing, 19 (6), 899–919.

Bamford, C. E., Dean, T. J., & McDougall, P. P. (2000). An examination of the impact of initial founding conditions and decisions upon the performance of new bank start-ups. Journal of Business Venturing, 15 (3), 253–277.

Baron, J. N., Hannan, M. T., & Burton, M. D. (2001). Labor pains: Change in organizational models and employee turnover in young, high-technology firms. The American Journal of Sociology, 106 (4), 960–1012.

Barringer, B. R., Jones, F. F., & Neubaum, D. O. (2005). A quantitative content analysis of the characteristics of rapid-growth firms and their founders. Journal of Business Venturing, 20 (5), 663–687.

Ben-Hafaïedh, C., & Hamelin, A. (2022). Questioning the growth dogma: A replication study. Entrepreneurship Theory and Practice, 47 , 10422587211059992.

Google Scholar  

Berends, H., Smits, A., Reymen, I., & Podoynitsyna, K. (2016). Learning while (re)configuring: Business model innovation processes in established firms. Strategic Organization, 14 (3), 181–219. https://doi.org/10.1177/1476127016632758

Bergek, A., & Onufrey, K. (2014). Is one path enough? Multiple paths and path interaction as an extension of path dependency theory. Industrial and Corporate Change, 23 (5), 1261–1297.

Bianchini, S., Bottazzi, G., & Tamagni, F. (2017). What does (not) characterize persistent corporate high-growth? Small Business Economics, 48 (3), 633–656.

Boeker, W. (1988). Organizational Origins: entrepreneurial and environmental imprinting of the time of founding. Ecological Models of Organizations, 1988 , 33–51.

Boeker, W. (1989). Strategic change: The effects of founding and history. Academy of Management Journal, 32 (3), 489–515.

Bollinger, L., Hope, K., & Utterback, J. M. (1983). A review of literature and hypotheses on new technology-based firms. Research Policy, 12 (1), 1–14.

Boxstael, A. V., & Denoo, L. (2020). Escaping the founder identity trap: A process view on business model design during new venture creation. In K. J. Sund, R. J. Galavan, & M. Bogers (Eds.), Business models and cognition (pp. 57–94). Emerald Publishing Limited.

Buliga, O., Scheiner, C. W., & Voigt, K. I. (2016). Business model innovation and organizational resilience: Towards an integrated conceptual framework. Journal of Business Economics, 86 (6), 647–670.

Butchart, R. L. (1987). A new UK definition of the high technology industries. Economic Trends, 400 , 82–88.

Cavallo, A., Ghezzi, A., Dell’Era, C., & Pellizzoni, E. (2019). Fostering digital entrepreneurship from startup to scaleup: The role of venture capital funds and angel groups. Technological Forecasting and Social Change, 145 , 24–35. https://doi.org/10.1016/j.techfore.2019.04.022

Chandler, G. N., & Hanks, S. H. (1994). Market attractiveness, resource-based capabilities, venture strategies, and venture performance. Journal of Business Venturing, 9 (4), 331–349.

Chesbrough, H., & Rosenbloom, R. S. (2002). The role of the business model in capturing value from innovation: Evidence from Xerox Corporation’s technology spin-off companies. Industrial and Corporate Change., 11 (3), 529–555.

Christensen, C. M., & Raynor, M. E. (2013). The Innovator´s Solution: Creating and Sustaining Successful Growth . Harvard Business Scholl Press.

Clauss, T. (2017). Measuring business model innovation: Conceptualization, scale development and proof of performance. R&D Management, 47 (3), 385–403.

Cloutier, L., & Messeghem, K. (2021). Whirlwind model of entrepreneurial ecosystem path dependence. Small Business Economics . https://doi.org/10.1007/s11187-021-00553-x

Coad, A. (2007). A closer look at serial growth rate correlation. Review of Industrial Organization, 31 (1), 69–82.

Coad, A., Daunfeldt, S.-O., Hölzl, W., Johansson, D., & Nightingale, D. (2014). High-growth firms: Introduction to the special section. Industrial and Corporate Change, 23 (1), 91–112.

Coad, A., & Hölzl, W. (2009). On the autocorrelation of growth rates. Journal of Industry, Competition and Trade, 9 (2), 139–166.

Cooper, A. C., Woo, C. Y., & Dunkelberg, W. C. (1988). Entrepreneurs’ perceived chances for success. Journal of Business Venturing, 3 (2), 97–108.

Daunfeldt, S. O., Elert, N., & Johansson, D. (2015). Are high-growth firms overrepresented in high-tech industries? Industrial and Corporate Change, 25 (1), 1–21.

Daunfeldt, S.-O., & Halvarsson, D. (2015). Are high-growth firms one-hit wonders? Evidence from Sweden. Small Business Economics, 44 (2), 361–383.

David, P. A. (1985). Clio and the economics QWERTY. The American Economic Review, 75 (2), 332–337.

Davidsson, P. (2007). Interpreting Performance in Research on Independent Entrepreneurship. In L. M. Gillin (Ed.), 4th AGSE International Entrepreneurship Research Exchange 2007. Brisbane.

Davidsson, P., & Klofsten, M. (2003). The business platform: Developing an instrument to gauge and to assist the development of young firms. Journal of Small Business Management, 41 (1), 1–26.

Davies , P., (2022), The future of French tech: why start-ups are optimistic despite economic gloom and cyber attacks. https://www.euronews.com/next/2022/09/20/the-future-of-french-tech-why-start-ups-are-optimistic-despite-economic-gloom-and-cyber-at

De Cleyn, S. H., Braet, J., & Klofsten, M. (2015). How human capital interacts with the early development of academic spin-offs. International Entrepreneurship and Management Journal, 11 (3), 599–621.

DeKinder, J. S., & Kohli, A. K. (2008). Flow signals: How patterns over time affect the acceptance of start-up firms. Journal of Marketing, 72 , 84–97.

Delmar, F., Davidsson, P., & Gartner, W. (2003). Arriving at the high-growth firm. Journal of Business Venturing, 18 (2), 189–216.

Delmar, F., & Shane, S. (2003). Does Business planning facilitate the development of new ventures? Strategic Management Journal, 24 (12), 1165–1185.

Diamantopoulos, A., & Winklhofer, H. M. (2001). Index construction with formative indicators: An alternative to scale development. Journal of Marketing Research, 38 (2), 269–277.

Djelic, M.-L., & Quack, S. (2007). Overcoming path dependency: Path generation in open systems. Theory and Society, 36 (2), 161–186.

Dunne, T., Roberts, M., & Samuelson, L. (1989). The growth and failure of US manufacturing plants. The Quarterly Journal of Economics., 104 (4), 671–698.

Edwards, J. R., & Bagozzi, R. P. (2000). On the nature and direction of relationships between constructs and measures. Psychological Methods, 5 (2), 155–174.

Ejermo, O., & Xiao, J. (2014). Entrepreneurship and survival over the business cycle: How do new technology-based firms differ? Small Business Economics, 43 (2), 411–426.

Eurostat., (2014), Eurostat indicators on high-tech industry and knowledge–intensive services (Annex 3 – High-tech aggregation by NACE Rev. 2).

Eurostat-OECD, (2007), Eurostat-OECD Manual on Business Demography Statistics. Luxembourg Office for Official Publications of the European Communities.

Festel, G., Wuermseher, M. & Cattaneo, G. (2013). Valuation of early stage high-tech start-up companies. Journal of Business Venturing , 8 (3), 216–231.

García-Manjón, J. V., & Romero-Merino, M. E. (2012). Research, development, and firm growth. Empirical evidence from European top R&D spending firms. Research Policy, 41 (6), 1084–1092.

Gartner, W., & Liao, J. (2012). The effects of perceptions of risk, environmental uncertainty, and growth aspirations on new venture creation success. Small Business Economics, 39 (3), 703–712.

Geroski, P. A., Mata, J., & Portugal, P. (2010). Founding conditions and the survival of new firms. Strategic Management Journal, 31 (5), 510–529.

Goel, R. K., & Saunoris, J. W. (2016). Institutional path dependence and international research intensity. Economic Modelling, 52 , 851–858.

Henrekson, M., & Johansson, D. (2010). Gazelles as job creators: A survey and interpretation of the evidence. Small Business Economics, 35 (2), 227–244.

Hepp, J. (2022). Being small at the right moment: Path dependence after a shift in the technological regime. Industrial and Corporate Change, 31 (2), 464–499.

Hölzl, W. (2009). Is the R&D behaviour of fast-growing SMEs different? Evidence from CIS III data for 16 countries. Small Business Economics, 33 (1), 59–75.

Hölzl, W. (2014). Persistence, survival and growth: A closer look at 20 years of fast-growing firms in Austria. Industrial and Corporate Change, 23 (1), 199–231.

Homburg, C., Hahn, A., Bornemann, T., & Sandner, P. (2014). The role of chief marketing officers for venture capital funding: endowing new ventures with marketing legitimacy. Journal of Marketing Research, 51 (5), 625–644.

http://ec.europa.eu/eurostat/cache/metadata/Annexes/htec_esms_an3.pdf [Accessed 2016–05–20]

Huergo, E., & López, A. (2020). Growth effects of economic conditions at birth: the role of public funding for technology-based start-ups. Economics of Innovation and New Technology, 30 (2), 511–538.

Isaksson, A., Löfsten, H., & Rannikko, H. (2021). The influence of initial business models on early business performance—a study of 589 new high-tech firms. International Journal of Innovation Management, 25 (5), 2150055. https://doi.org/10.1142/S1363919621500559

Isaksson, A., Vanyushyn, V., & Hultén, P. (2013). The impact of managers’ attitudes on SMEs’ growth in northern Sweden. International Journal of Entrepreneurship and Small Business, 18 (3), 298–312.

Jacobides, M. G. (2006). The architecture and design of organizational capabilities. Industrial and Corporate Change, 15 (1), 151–171.

Jarvis, C. B., MacKenzie, S. B., & Podsakoff, P. M. (2003). A critical review of construct indicators and measurement model misspecification in marketing and consumer research. Journal of Consumer Research, 30 (2), 199–218.

Johnson, V. (2007). What Is Organizational Imprinting? Cultural Entrepreneurship in the Founding of the Paris Opera. American Journal of Sociology , 113 (1). https://doi.org/10.1086/517899 .

Katila, R., Rosenberger, J. D., & Eisenhardt, K. M. (2008). Swimming with sharks: technology ventures, defense mechanisms and corporate relationships. Administrative Science Quarterly, 53 (2), 295–332.

Kessler, A., Korunka, C., Frank, H. & Lueger, M. (2012). Predicting founding success and new venture survival: A longitudinal nascent entrepreneurship approach. Journal of Enterprising Culture , 20 (1), 25–55. https://doi.org/10.1142/S021849581250002125 .

Kim, H. E., & Pennings, J. M. (2009). Innovation and strategic renewal in mature markets: A study of the tennis racket industry. Organization Science, 20 (2), 368–383.

Kimberly, J. R. (1975). Environmental constraints and organizational structure: A comparative analysis of rehabilitation organizations. Administrative Science Quarterly, 20 (1), 1–9.

Kirchhoff, B. (1994). Entrepreneurship and Dynamic Capitalism . Westport.

Klepper, S. (2002). The capabilities of new firms and the evolution of the US automobile industry. Industrial and Corporate Change, 11 (4), 645–666.

Kuckertz, A., Scheu, M., & Davidsson, P. (2023). Chasing mythical creatures–A (not-so-sympathetic) critique of entrepreneurship’s obsession with unicorn startups. Journal of Business Venturing Insights, 19 , e00365. https://doi.org/10.1016/j.jbvi.2022.e00365

Kuratko, D. F., & Audretsch, H. E. (2022). The future of entrepreneurship: The few or the many? Small Business Economics, 59 (1), 269–278.

Leung, A., Foo, M. D., & Chaturvedi, S. (2013). Imprinting effects of founding core teams on HR values in new ventures. Entrepreneurship Theory and Practice, 37 (1), 87–106.

Loch, C. H., Solt, M. E., & Bailey, E. M. (2008). Diagnosing unforeseeable uncertainty in a new venture. Journal of Product Innovation Management, 25 (1), 28–46.

Löfsten, H. (2016). Business and innovation resources: Determinants for the survival of new technology-based firms. Management Decision, 54 (1), 88–106.

Löfsten, H., & Lindelöf, P. (2001). Science parks in Sweden—Industrial renewal and development? R&D Management, 31 (3), 309–322.

Löfsten, H., & Lindelöf, P. (2002). Science parks and the growth of new technology based firms—Academic-industry links, innovation and markets. Research Policy, 31 (6), 859–876.

Mahroum, S. (2016). Black swan start-ups: Understanding the rise of successful technology business in unlikely places . Palgrave Macmillan, London.

Marquis, C. (2003). The pressure of the past: Network imprinting in intercorporate communities. Administrative Science Quarterly, 48 (4), 655–689.

Martínez-Ros, E., & Labeaga, J. M. (2009). Product and process innovation: Persistence and complementarities. Europan Management Review, 6 (1), 65–75.

Mason, C., & Brown, R. (2013). Creating good public policy to support high-growth firms. Small Business Economics, 40 (2), 211–225.

McDougall, P. P., Scott, S. & Oviatt, B. (1994). Explaining the formation of international new ventures: The limits of theories from international business research. Journal of Business Venturing 9 (6), 469–487.

McEvily, B., Jaffee, J., & Tortoriello, M. (2012). Not all bridging ties are equal: Network imprinting and firm growth in the nashville legal industry, 1933–1978. Organization Science, 23 (2), 547–563.

Milanov, H., & Fernhaber, S. A. (2009). The impact of early imprinting on the evolution of new venture networks. Journal of Business Venturing, 24 (1), 46–61.

Miller, D., & Friesen, P. H. (1984). Organizations: A Quantum View . Englewood Cliffs.

Moreno, A. M., & Casillas, J. C. (2008). Entrepreneurial orientation and growth of SMEs: A causal model. Entrepreneurship Theory and Practice, 32 (3), 507–528.

Morgan, G., & Kubo, I. (2005). Beyond path dependency? Constructing new models for institutional change: The case of capital markets in Japan. Socio-Economic Review., 3 (1), 55–82.

Moschella, D., Tamagni, F., & Xu, X. (2019). Persistent high-growth firms in China’s manufacturing. Small Busienss Economics, 52 (1), 573–594.

Nair, S., & Blomquist, T. (2019). Failure prevention and management in business incubation: Practices towards a scalable business model. Technology Analysis & Strategic Management, 31 (3), 266–278.

Napier, G., Rouvinen, P., Johansson, D., Finnbjörnsson, T., Solberg, E. and Pedersen, K. (2012), Nordic Growth Entrepreneurship Review 2012—Final report , Nordic Innovation Publication 2012:25, Nordic Innovation, Oslo

Nielsen, C., Lund, M., Montemari, M., Paolone, F., Massaro, M., & Dumay, J. (2018). Business Models: A Research Overview . Routledge. https://doi.org/10.4324/9781351232272

North, D. C. (1990). Institutions, institutional change and economic performance . Cambridge University Press.

Osterwalder, A., & Pigneur, Y. (2010). Business Model Generation . John Wiley and Sons.

Osterwalder, A., Pigneur, Y., & Tucci, C. L. (2005). Clarifying business models: Origins, present, and future of the concept. Communications of the Association for Information Systems, 16 , 1. https://doi.org/10.17705/1CAIS.01601

Patzelt, H., Zu Knyphausen-Aufseß, D., & Nikol, P. (2008). Top management teams, business models, and performance of biotechnology ventures: An upper echelon perspective. British Journal of Management, 19 (3), 205–221.

Pennings, J. M. (1980). Interlocking Directories: Origins and Consequences of Connections Among organization´s Board of Directors . Jossey-Bass.

Phillips, D. J. (2002). A genealogical approach to organizational life chances: The parent-progeny transfer among Silicon Valley law firms, 1946–1996. Administrative Science Quarterly, 47 (3), 474–506.

Phillips, D. J. (2005). Organizational genealogies and the persistence of gender inequality: The case of silicon valley law firms. Administrative Science Quarterly, 50 (3), 440–472.

Pierson, P. (2000). Increasing returns, path dependence, and the study of politics. American Political Science Review, 94 (2), 251–267.

Quinn, J. B. (1980). Strategies for change: Logical incrementalism . Richard D. Irwin.

Rannikko, H., Tornikoski, E., Isaksson, A., & Löfsten, H. (2019). Survival and growth patterns among new technology-based firms: Empirical study of cohort 2006 in Sweden. Journal of Small Business Management, 57 (2), 640–657.

Romanelli, E. (1989). Environments and strategies of organization start-up: Effects on early survival. Administrative Science Quarterly, 34 (3), 369–387.

Rusko, R., Hietanen, L., Kohtakangas, K., & Järvi, T. (2019). Roles of career anchors and path dependency in the entrepreneurial process: Case Finland. International Journal of Entrepreneurship and Small Business, 37 (3), 342–363.

Rydehell, H., Isaksson, A., & Löfsten, H. (2019a). Business networks and localization effects for new Swedish technology-based firms’ innovation performance. The Journal of Technology Transfer, 44 (5), 1547–1576.

Rydehell, H., Isaksson, A., & Löfsten, H. (2019b). Effects of internal and external resource dimensions on the business performance of new technology-based firms. International Journal of Innovation Management, 23 (1), 1950001.

Samuelsson, M., Söderblom, A., & McKelvie, A. (2021). Path dependence in new ventures’ capital structures. Entrepreneurship Theory and Practice, 45 (2), 319–349.

Sánchez, P., & Ricart, J. E. (2010). Business model innovation and sources of value creation in low-income markets. European Management Review, 7 (3), 138–154.

Schneckenberg, D., & Velamuri, V. (2019). The design logic of new business models: Unveiling cognitive foundations of managerial reasoning. European Management Review, 16 (2), 427–447.

Siegel, R., Siegel, E. & Macmillan, I. C. (1993). Characteristics distinguishing high-growth ventures. Journal of Business Venturing , 8 (2), 169–180.

Shane, S. (2009). Why encouraging more people to become entrepreneurs is bad public policy. Small Business Economics, 33 (2), 141–149.

Simsek, Z., Fox, B. C., & Heavey, C. (2015). “What’s Past Is Prologue” A framework, review, and future directions for organizational research on imprinting. Journal of Management, 41 (1), 288–317.

Snihur, Y., & Zott, C. (2020). The genesis and metamorphosis of novelty imprints: How business model innovation emerges in young ventures. Academy of Management Journal, 63 (2), 554–583.

Sohl, T., Vroom, G., & Fitza, M. A. (2020). How much does business model matter for firm performance? A variance decomposition analysis. Academy of Management Discoveries, 6 (1), 61–80. https://doi.org/10.5465/amd.2017.0136

Spencer, A., & Kirchhoff, B. (2006). Schumpeter and new technology based firms: Towards a framework for how NTBFs cause creative destruction. International Entrepreneurship and Management Journal, 2 (2), 145–156.

Stinchcombe, A. L. (1965). Social Structure and Organizations. In J. P. March (Ed.), Handbook of Organizations (pp. 142–193). Rand McNally.

Storey, D. J. (1994). Understanding the Small Business Sector . Routledge.

Storey, D. J., & Tether, B. S. (1998). New technology-based firms in the European Union: An introduction. Research Policy, 26 (9), 933–946.

Sydow, J., Schreyögg, G., & Koch, J. (2009). Organizational path dependency: Opening the black box. Academy of Management Review, 34 (4), 689–709.

Sydow, J., Schreyögg, G., & Koch, J. (2020). On the theory of organizational path dependence: Clarifications, replies to objections, and extensions. Academy of Management Review, 45 (4), 717–734.

Tornikoski, E., & Renko, M. (2014). Timely creation of new organizations: The imprinting effects of entrepreneurs’ initial founding decisions. Management, 17 (3), 193–213.

Trimi, S., & Berbegal-Mirabent, J. (2012). Business model innovation in entrepeneurship. International Entrepreneurship and Management Journal, 8 (4), 449–465.

Tucker, D. J., Singh, J. V., & Meinhard, A. G. (1990). Founding characteristics: imprinting, and organizational change. In J. V. Singh (Ed.), Organizational Evolution: New Directions (pp. 180–200). Newbury Park.

Van Praag, C. M. (2003). Business survival and success of young small business owners. Small Business Economics, 21 (1), 1–17.

Vergne, J.-P., & Durand, R. (2010). The missing link between the theory and empirics of path dependence: Conceptual clarification, testability issue, and methodological implications. Journal of Management Studies, 47 (4), 736–759.

Wennberg, K. (2005). Entrepreneurship research through longitudinal databases: Measurement and design issues. New England Journal of Entrepreneurship, 8 (2), 9–19.

Wiklund, J., Davidsson, P., & Delmar, F. (2003). What do they think and feel about growth? An expectancy–value approach to small business managers’ attitudes toward growth. Entrepreneurship Theory and Practice, 27 (3), 247–270.

Wiklund, J., & Shepherd, D. (2003). Aspiring for, and achieving growth: The moderating role of resources and opportunities. Journal of Management Studies, 40 (8), 1921–1941.

Witt, U. (1997). ‘Lock-In’ vs ‘critical masses’—industrial change under network externalities. International Journal of Industrial Organization, 15 (6), 753–773.

Yli-Renko, H., Autio, E., & Sapienza, H. J. (2001). Social capital, knowledge acquisition, and knowledge exploitation in young technology-based firms. Strategic Management Journal, 22 (6–7), 587–613.

Yli-Renko, H., Autio, E., & Tontti, V. (2002). Social capital, knowledge, and the international growth of technology-based new firms. International Business Review, 11 (3), 279–304.

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Acknowledgements

The authors hereby gratefully acknowledge financial support for this study from the Peter Wallenberg Foundation for Economics and Technology. We are grateful for the comments of the participants at the Virtual BCERC (Babson College Entrepreneurship Research Conference) in Munich, Germany, June 8-11, 2021.

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Löfsten, H., Isaksson, A., Rannikko, H. et al. Impact of initial business model on the growth trajectory of new technology-based firms: a path dependency perspective. J Technol Transf (2024). https://doi.org/10.1007/s10961-024-10086-6

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