Open access peer-reviewed chapter
Abstract
An imperative contemporary management dilemma in moments of rapidly evolving regarding the ongoing digital transformation of business and society in general is recognizing and trying to translate these adjustments into digital business model innovation (DBMI). Academia has plenty to show in exchange of assisting with this managerial problem, but studies in the field still seem to be hazy in terms of what DBMI is, the present, future, and vision. Therefore, this article aimed to review the present situation of DBMI, its future, and its vision in the general context. The secondary databases were used to collect the relevant articles, and the outcome of the study found that DBMI has attained prolonged growth in different businesses especially in COVID-19 period. This scenario would not be changed in future because of increasing digital impact on several businesses. Therefore, it is recommended for all types of businesses to adopt digital business model innovation to attain competitive advantage.
Keywords
- digital business model innovation
- innovation
- future of DBMI
- vision of DBMI
- managerial challenges
1. Introduction
Almost all industries are being impacted by digitalization, which is creating opportunities and challenges for established firms, large born digitals, and smaller start-ups [1, 2]. Through the proliferation of digital technologies, such as those related to the Internet of Things, and the acceptance and use of affordable mobile devices and personal computers, both industry players and consumers are becoming increasingly smart [3, 4, 5]. The competition has increased with the introduction of dynamic changes in the business environment. This is fueled by agile start-ups that leverage the low entry barriers in digital markets to enter industries that were once dominated by veterans [6, 7, 8].
With increasing penetration of digital technologies, the availability of data has increased in multiple folds. This scenario makes the data analytics and ML capabilities, crucial competitive advantages for business sustainability [9]. Such instances, when the impact of digitization in business has gained much attention, transform the functioning of businesses oriented to digital formats and not as a secondary support activity. Further, digital assets have gained much attention in organizations and businesses [10, 11]. In this crucial time, managers understood the importance of digital technology and prioritized the digital transformation of their business functions in their leadership agendas [12]. Despite this, a lot of such migrations fail since businesses fail to unleash the advantages of significant investments in digital technologies [13]. One of the primary reasons for this digital paradox is that investments in digital technologies alone, while potentially leading to technological superiority, do not guarantee success [2, 14].
Nonetheless, given its significance in firm digital transformation, DBMI research is still in its infancy, and the phenomenon is poorly understood [1, 4, 15, 16]. The primary issue to be addressed here is the absence of construct clarity in terms of DBMI concept [5] since DBMI was not defined earlier [17, 18]. Scholars have repeatedly identified a lack of coherent nomenclature [19, 20] or the continual uncertainty [21, 22], emphasizing that consternation about the DBMI concept is critical [17]. A high level of construct clarity for DBMI is thus required to advance the understanding of DBMI and allow further knowledge accumulation to assist managers and practitioners in their digital transformation endeavors [23, 24]. Scholars, on the other hand, have made few attempts to define the concept of DBMI [25]. Considering these facts, the present article aimed to fill the gap by reviewing the current and future trend of DBMI. Hence, the article conducts review collection from reputed journals. The article was structured into the following ways as the initial section will collect the relevant reviews, later section will follow methods, findings, and discussion, and the final section will conclude the article.
2. Literature
2.1 Business model innovation
During this financial change, managers, executives, and entrepreneurs are in the hunt for latest sources of competitive benefit, which is distinct from the previously explored product area and process innovation as stated by [26]. The term “business model innovation” is split into two kinds: business model design and business model reconfiguration [27]. Business model reconfiguration includes the alteration of the present company trade model, while the trade model design denotes the process of designing the novel trade model for newly developed companies [27].
The rationale to follow BMI is it’s holistic as well as systemic thinking. On having an observation of Figure 1 [29] rather than focusing on separated changes or hindering personal choice, the strategic leadership is to acquire the total design of activity system prior to optimizing the information.
Figure 1.
An illustration of business model innovation and its holistic perspective [
Utmost level of focus is kept on the business model innovation in the recent period of years, this report has opted to employ a definition from a recent report within the industry, and it was quite effective as well. The description is considered to be credible since the literature research encloses many study papers from effectively renowned authors simultaneously enclosing both contrary outlooks of disruptive trade model innovation and incremental innovation.
2.2 Relevance of business model innovation for a firm
A customer-centric trade model is mainly about serving its consumer in an efficient way. To do the same, the organization must understand the consumer and implement the model as per these knowledge and understandings. Consequently, business model management involves the changes of present model, modifying it to the changes in the industry along with the new insights regarding the consumers. The efforts are made, rearranged and renewed trade models are to be taken to consideration as trade model innovations while the market implementation turns new-to-the-organization. To elevate the consumer’s empathy, companies are using various tools, which are generally associated with the design thinking [30]. These kinds of tools involve the journey maps [31] and empathy maps [32] while the latter is mainly gused to catch the outlook and viewpoint of the consumer.
Collin et al. [33]; Jansson and Andervin [34]; Dufva and Dufva [35] examined that a vital transformative force, which tends to influence our society in an extensive way, is none other than digitalization; the societal impacts, which root from the application of digital technological developments. These waves of change not alone bring new products, services, or technology but as well change the basic human behavior.
As per the study of OECD [36], digitalization tends to affect in a virtual manner and the chances are wide and expanded, but simultaneously it is not completely imaginable. The opportunities that emerge from digitalization are promptly persuaded by several numbers of factors. The new radical business models are the outcome along with the optimizations in resource usage and production, automation, etc. [4].
2.3 Digital Business Model Innovation (DBMI)
Undoubtedly, digital transformation is more of a managerial issue than a technological one [37]. To prosper from digital technologies and stay competitive in this complicated digital business context, firms must design, develop, and implement digital business model innovation [38]. Digital business model innovation entails changes in a company’s value proposition, value delivery, and/or value capture [4]. The importance of treating digital business model innovation as a stand-alone treatment from prior kinds of business model innovation has been actually supported in the literature [2, 3, 39, 40].
Digital business model is an evolution of business continuity plan by itself in which companies innovate and improve themselves on a daily basis to ensure their product and service offerings attract, build, and sustain a loyal customer network. Business owners experience a prism of challenges such as dynamic customer demands, increasing physical and digital safety concerns, competitive markets, vibrant work environment, and the need for sustainability practices [41]. With Industry 5.0, Artificial Intelligence, Blockchain technology, Virtual Reality, and IoT round the corner, digital business models focus on enhancing value proposition and providing a competitive edge for the firms.
The current section will further discuss on advanced digital business models, evolution of digital business models in the aftermath of COVID-19 and its future.
2.4 Evolution of digital business models
In recent years, the phenomenon of digital transformation (DT) has grown in popularity [42, 43]. Digital transformation, also known as “digitalization,” is defined as “the incorporation of digital technologies into business processes” [44]. The use of digital technologies allows for the integration of products and services across functional, organizational, and geographic boundaries [45]. As a result, because they have the “power” to disrupt the status quo and drive technological change, digital technologies accelerate the pace of change and lead to significant transformation in a variety of industries [46, 47].
Digital technologies have transformed how industries operate [48], ushering in the concept of “Industry 4.0” or the “smart factory” [49]. Strategy researchers listed out the three essential features of digital technologies such as digital artifacts, digital platforms, and digital infrastructures [40]. These elements produce opportunities for layered modular architecture and empower firms with strategic choice of pursuing a digital innovation strategy [50]. As a result, digitalization blurs the boundaries between technology and management by introducing new digital tools and concepts that are dramatically altering how firms face new managerial challenges, innovate, develop relationships, and conduct business [51].
To remain competitive in the new digital environment, firms must use digital technologies and platforms for data collection, integration, and utilization in order to adapt to the platform economy [52]. Atluri et al. [53] confirmed that digital transformation and the resultant BM opportunities are still in nascent stage.
Both business model innovation and digital transformation are the ways for mature organizations in renewing their competitive benefit as per the concept of [26, 27, 28, 29, 30, 31, 32, 33, 34, 42]. Both activities are in the motive of helping the companies to grow in this dynamic world. A big variation relies in that kind of digital transformation, which is focused on the establishment of new technology into the trade model, irrespective of its make, that is, whether on operational level or strategic level. The intersection amid digital transformation and business model innovation, the tool to manage digitalization can be asserted to enclose: the strategic realignment of business activities to develop a new trade model with bigger value compared with the previous stuff, which is made certainly through the establishment of new digital technology as noted as follows. Figure 2 shows the intersection between digital transformation and the business model innovation.
Figure 2.
The intersection between digital transformation and business model innovation.
2.5 Advanced digital business models
Opportunities are provided to all the organizations in the field on two crucial dimensions: understanding and knowledge of business design and end customer, that is, breadth of provisions of goods and services. These sorts of dimensions integrate to create four trade models for value creation (seen in Figure 3): Multichannel Businesses, Ecosystem Drivers, Modular Producers, and Suppliers.
Figure 3.
Advanced digital business models.
Suppliers have a direct understanding and knowledge about the priorities of end consumers, perhaps or certainly have a direct association with one another. These organizations tend to sell their goods and services to the distributors side in terms of value chain. Because of the ease in digital search, they act vulnerable toward commoditization and pricing pressures since consumers are in the hunt for less costly alternatives.
If individuals are unaware of end customers and not intended to resolve their issues, organizations will be in the need of finding other possible ways of preventing commoditization.
Multichannel businesses possess in-depth knowledge and understanding about their customers as they get to experience direct association with one another.
Extensive understanding about the life-event requirements of consumers is quite important for developing the integrated experience, which will significantly retain the present customers and grab the new customers as well.
Further, the rivalry or competition is too powerful in case of Suppliers, it’s essential for the offerings to remain well priced as well as creative.
Ecosystem Drivers possess the best of broad supply base as well as deep end-customer knowledge. They tend to leverage these sorts of dimensions to offer seamless experience to the customers that sell not proprietary goods and services alone but as even from offerers all throughout the whole ecosystem. Hence they develop value while obtaining rent from one another. Since the study of Weil and Woerner exhibits the prospect for value creation, which is significant and predominant for the organizations that take part in ecosystems instead of value chains, thus Ecosystem Drivers contain biggest capability of creating value.
All the four paths are noted of being viable routes to promote success, if you remain precise about your generic plan and what is needed to execute the strategy. Even if you tend to lose consumers or having a gradual growth or development compared with your industry, it’s important to consider migrating toward various quadrant, either through extending your understanding of the end customers or through turning more of ecosystem.
2.6 Foundations of DBMI attributes
In the reviewed literature, five broad qualities surfaced besides being commonly in use by DBMI academics: intentional, nontrivial, vibrant, transition in crucial areas of business operations, and digitalization. These characteristics are the foundation of novel description and will be debated further below.
2.7 DBMI is purposeful and deliberate
The review of the literature shows a discussion as to whether DBMI is intentional and meaningful or occurs on an ad hoc and unexpected basis [21, 54]. As per Kotarba [55], adjustments in a company’s digital business model can either be optional, where the company took an assertive influence in forming its future digital business model, or reactionary, where unexpected and unforeseen adjustments have a negative impact on the business model and necessitate restructuring or emergency operations. The majority of scholars were motivated by a strategic decision made by an entrepreneur or manager [16, 56, 57, 58].
Considering (digital) business model innovation to be intentional or meaningful is consistent with a large community of strategic planning academics who regard business models (and their advancement) as distinguishable occurrences connected to strategy [59].
Cavalcante [54] wants to introduce a pre-stage to DBMI that is defined by conducting experiments and knowledge construction and can lead to real DBMI. Even when the method is more experimental, DBMIs do not appear out of nowhere; thereby, the characteristic of intentional could be used to introduce the meaning.
2.8 DBMI is novel and nontrivial
Various propositions have been constructed to measure novelty while the most established one is to distinguish new to the world and new to the firm. In literature, it is mentioned that DBMI should be new to the world so that it can be considered as novel strategy [60, 61]. Others, on the other hand, take a more nuanced approach to DBMI’s novelty [62]. Several make the argument, for example, that the new digital business model must be difficult to replicate [47], that a significant portion of the business must be converted to digital [63], or that digital refers to companies that rely heavily on the Internet [20].
Further evidence for this nuanced viewpoint comes from Warner and Wäger [12], who argue that the creation of truly new digital business models is unlikely for most incumbents. Indeed, Li [16] extensively discusses the question of what a new business model entails, concluding that truly novel (digital) business model innovations are difficult to come by, as precedents almost always exist. As a result, the authors of our reviewed literature frequently identify various levels of digitalization in terms of business model innovation [1, 63, 64]. Li [16] described a continuum of how firms can enhance, extend, transform, or redefine their value propositions through digitalization.
2.9 DBMI is dynamic
The advent of digitalization has resulted in a strong changing situation. Firms are frequently faced with security flaws and possibilities as a result of the pervasive explosion of smart technologies, customer adaptation to the digital culture, and competitive intensity in online markets due to reduced barriers of entry [5, 22, 65]. This dynamic environment has been dubbed VUCA (volatile, uncertain, complex, and ambiguous) [12, 38].
As a result, it is not surprising that many scholars have addressed the dynamics of DBMI [66]. According to researchers, digital business models evolve over time [16, 62, 67, 68, 69] and that developing a successful DBMI is a journey [65]. Being constantly on the move is especially important in digital business models because they are often transparent to all [65].
König et al. [69] concluded that digital ventures, as relative to specific ventures, advance their business models to achieve the required proper. Kohtamäki et al. [64] sometimes encourage supervisors to discover (digital) business model innovation on a constant basis because it is vital to living. As a result of these findings, DBMIs are highly dynamic, and this dynamic is a key characteristic of the notion.
2.10 DBMI requires changes in the key elements of the business model
According to the reviewed literature, a business model describes a firm’s overall logic, including the three key components of value proposition, value creation, and value capture. Changes in one or more of these components constitute business model innovation [47, 62, 70], for example, emphasize the importance of business model alignment by arguing that firms must evaluate and understand their shortcomings in each of these key components, and that any changes made to one of them must always take the other components into account.
As a result, DBMI scholars rely heavily on traditional business model thinking when it comes to changes in business model components. One reason for this is that there is currently no agreement on the essential components of digital business models.
2.11 DBMI entails transformation from analog to digital format
The involvement of digital technologies in facilitating DBMI is widely discussed in latest DBMI literary works [16, 60, 71, 72]. According to Aagaard [15], the use of digital technologies is central to DBMI. Firms can make such a transition using a variety of digital technologies. There it seems to be a starting to emerge agreement in the literature based on the classification of digital technologies, such as automated processes (e.g., robotic systems, additive manufacturing, artificial intelligence), interplay (e.g., wearable tech, internet Technology, apps, social media), facilitation (e.g., distributed ledgers, cryptocurrency), data (e.g., big data, predictive analysis, predictive algorithms), and interconnection (e.g., broadband, cloud computing, sensors).
However, this variety of options for digital technologies is at the heart of criticism about the operational definitions value of the definition of digital technologies for the DBMI construct [39]. Parida et al. [4], for instance, argue that the concept is difficult to apply due to the variety of technologies and their applications. To avoid this conceptual stumbling block in the definition of DBMI and to broaden the debate, we will refer to digitization in a very broad sense. Several academics in their sample agree that digitization is the transformation of processes, content, or objects that were previously mainly (or wholly) physical or analogue to primarily (or entirely) digital [3, 7, 17, 73]. Even though some make the argument that this perception of digital understates the construct’s far-reaching ramifications [55, 74], it is presumed that at this early stage in DBMI research, this broad understanding means allowing for even more inclusive, exploratory research, which is required to advance the field.
2.12 Future of DBMI
The workplace is expected to change dramatically over the next 10 years. First, digital technology can help and/or restrict the formation and seize of correct value. Firms can use mechanization, interplay, facilitation, data, or interconnection technologies to boost disruptive DBMI on the enablement side [45, 75]. Businesses can select from a stream of unparalleled technological advances and apply them to the realization of their DBMI. As a result, the empowering role provides an online asset bundle from which companies can choose, utilize, and/or develop.
Nevertheless, on the limiting side, the limited availability from certain mobile technology (e.g., a 5G network) and connecting directly to complementary technologies (e.g., advanced sensory technologies) may make such digital technologies less helpful for interruptive DBMI (e.g., technological barriers to making driverless vehicles), whereas the rapid speed of technology technological development may make a firm’s investing in digital technologies dangerous or more efficient [76]. Second, digital technologies can be direct enablers and/or constraints for DBMI while also generating a triggering context in which DBMI’s purpose-making may arise. The dual role of technologies will shape a new opportunity landscape for starting new businesses, this line of questioning will also be important for future entrepreneurship [77].
To summarize, the literature review shows that there is currently no agreement on the critical parts that characterize digital business models. Even so, in the particular instance of DBMI, the logical implication that changes in the critical parts of a business strategy is a key characteristic.
3. Research approach
The present article collects the multiple reviews through various secondary databases including EBSCO, Google scholar, OpenDOAR, etc. Specifically, the literature search was completely carried out by utilizing electronic databases include ACM Digital Library (https://dl.acm.org/); Science IEEE Xplore Digital Library (https://ieeexplore.ieee.org/Xplore/home.jsp); and direct (https://www.sciencedirect.com/). Only peer-reviewed English-language publications that discussed the concept of DBMI were considered. The importance of review articles in management science is well established [78, 79]. Wolfswinkel et al. [80] propose a five-stage approach to rigorously reviewing the literature, which includes (1) defining the scope of the review, (2) searching the literature, (3) selecting the final sample, (4) analyzing the corpus, and (5) presenting the findings. The collected articles were restricted to 2009–2021. This review did not include keynotes, opinion pieces, conference papers, or workshop notes. The Braun and Clarke [81] iterative approach to thematic analysis motivated the article analysis, which includes a few stages such as familiarizing oneself with the information, trying to generate coding categories, naming themes, and evaluating and trying to define themes. In the first step, the researcher carefully reads all of the chosen studies [82] before selecting the relevant articles.
4. Findings and discussion
The majority of the studies in this review were published within the last 5 years (from 2016 to 2020). This is encouraging because it shows a strong and growing interest in the field. However, it also encourages researchers to improve the clarity of the concept so that research efforts do not diverge in unrelated directions. But the articles included the papers from 2010 to give more clarity to the research. When considering the quantity and diversity of existing definitions, it is clear that the paper contribution is relevant and timely. Throughout the analysis, it was discovered that only a few studies in the sample explicitly provided information about the current DBMI trend, albeit with varying degrees of clarity and detail [16, 60, 71, 72].
The number of articles evaluated have a good base in typical business model research, either expressly discussing the concept or reliance on well-established discussion (e.g., [26, 29]). To elevate the consumer’s empathy, companies are using various tools, which are generally associated with the design thinking [30]. These kinds of tools involve the journey maps [31] and empathy maps [32] was noted. This showed the performance of organization in designing business model innovation.
It is further noted that the digitalization has impact the businesses, as a result, business firms adopt DBMI concept [4]. However, digital transformation is a management issue rather than a technical one [37]. Firms should layout, create, and be equipped to address business model innovation to benefit from digital technologies and remain competitive in this complex digital business context [38]. Furthermore, recent research indicates that firms use external venturing modes to develop dynamic capabilities (e.g., start-up programs and accelerator [83, 84]). As a result, digitalization is viewed as an entrepreneurial process [85, 86], in which firms pursuing digital transformation render formerly successful BMs obsolete [87, 88] through business model innovation (BMI), which is revolutionizing many industries. Firms adopting digital technologies, for example, regard data streams as critical and assign them a central role in supporting their digital transformation strategies [89], in contrast to traditional BM frameworks [90].
This is an important finding because it demonstrates that the impact of digital on business model innovation remains hazy [1] and that a digital conundrum prevails in the literature where key concepts lack construct clarity [17]. However, such a lack of focus on digital is problematic because simply adding a few digital features when discussing innovative business models leads to the horseless carriage fallacy [11]. In other words, the digital era offers a radically different context that is incomparable to previous environments where generic business model innovation has been studied [2, 40]. However, most researchers working at the intersection of digital and business model innovation fail to clearly define the DBMI concept.
5. Conclusion
This chapter has clearly showed the growth of digital business model innovation in recent years especially in COVID-19 period. During this period, majority of the businesses adopted digitalization as a result, their business models also innovative and digitalized. This scenario would not be changed in future because of increasing digital impact on several businesses. Therefore, it is recommended for all types of businesses to adopt digital business model innovation to attain competitive advantage.
References
- 1.
Rachinger M et al. Digitalization and its influence on business model innovation. Journal of Manufacturing Technology Management. 2019; 30 (8):1143-1160. DOI: 10.1108/JMTM-01-2018-0020 - 2.
Volberda HW et al. Strategizing in a digital world: Overcoming cognitive barriers, reconfiguring routines and introducing new organizational forms. Long Range Planning. 2021; 54 (5):102110. DOI: 10.1016/j.lrp.2021.102110 - 3.
Fichman RG, Dos Santos BL, Zheng Z(E). Digital innovation as a fundamental and powerful concept in the information systems curriculum. MIS Quarterly. 2014; 38 (2):329-343. DOI: 10.25300/MISQ/2014/38.2.01 - 4.
Parida V, Sjödin D, Reim W. Reviewing literature on digitalization, business model innovation, and sustainable industry: Past achievements and future promises. Sustainability. 2019; 11 (2):391. DOI: 10.3390/su11020391 - 5.
Venkatesh R, Mathew L, Singhal TK. Imperatives of business models and digital transformation for digital services providers. International Journal of Business Data Communications and Networking. 2019; 15 (1):105-124. DOI: 10.4018/IJBDCN.2019010107 - 6.
Ehret M, Wirtz J. Unlocking value from machines: Business models and the industrial internet of things. Journal of Marketing Management. 2017; 33 (1–2):111-130. DOI: 10.1080/0267257X.2016.1248041 - 7.
Loebbecke C, Picot A. Reflections on societal and business model transformation arising from digitization and big data analytics: A research agenda. The Journal of Strategic Information Systems. 2015; 24 (3):149-157. DOI: 10.1016/j.jsis.2015.08.002 - 8.
Teece DJ, Linden G. Business models, value capture, and the digital enterprise. Journal of Organization Design. 2017; 6 (1):8. DOI: 10.1186/s41469-017-0018-x - 9.
Hanelt A et al. A systematic review of the literature on digital transformation: Insights and implications for strategy and organizational change. Journal of Management Studies. 2021; 58 (5):1159-1197. DOI: 10.1111/joms.12639 - 10.
Matt C, Hess T, Benlian A. Digital transformation strategies. Business & Information Systems Engineering. 2015; 57 (5):339-343. DOI: 10.1007/s12599-015-0401-5 - 11.
El Sawy OA, Pereira F. Business Modelling in the Dynamic Digital Space. Berlin, Heidelberg: Springer Berlin Heidelberg (SpringerBriefs in Digital Spaces); 2013. DOI: 10.1007/978-3-642-31765-1 - 12.
Warner KSR, Wäger M. Building dynamic capabilities for digital transformation: An ongoing process of strategic renewal. Long Range Planning. 2019; 52 (3):326-349. DOI: 10.1016/j.lrp.2018.12.001 - 13.
Linde L et al. Evaluation of digital business model opportunities. Research-Technology Management. 2021; 64 (1):43-53. DOI: 10.1080/08956308.2021.1842664 - 14.
Vial G. Understanding digital transformation: A review and a research agenda. The Journal of Strategic Information Systems. 2019; 28 (2):118-144. DOI: 10.1016/j.jsis.2019.01.003 - 15.
Aagaard A, editor. Digital Business Models. Cham: Springer International Publishing; 2019. DOI: 10.1007/978-3-319-96902-2 - 16.
Li F. The digital transformation of business models in the creative industries: A holistic framework and emerging trends. Technovation. 2020; 92–93 :102012. DOI: 10.1016/j.technovation.2017.12.004 - 17.
Bican PM, Brem A. Digital business model, digital transformation, digital entrepreneurship: Is there a sustainable “digital”? Sustainability. 2020; 12 (13):5239. DOI: 10.3390/su12135239 - 18.
Schallmo DRA, Williams CA. Digital transformation of business models. In: Digital Transformation Now! New York City, New York, United States: Springer; 2018. pp. 9-13. DOI: 10.1007/978-3-319-72844-5_3 - 19.
Blaschke M et al. Designing business models for the digital economy. In: Shaping the Digital Enterprise. Cham, Switzerland: Springer International Publishing; 2017. pp. 121-136. DOI: 10.1007/978-3-319-40967-2_6 - 20.
Standing C, Mattsson J. “Fake it until you make it”: Business model conceptualization in digital entrepreneurship. Journal of Strategic Marketing. 2018; 26 (5):385-399. DOI: 10.1080/0965254X.2016.1240218 - 21.
Kohli R, Melville NP. Digital innovation: Areview and synthesis. Information Systems Journal. 2019; 29 (1):200-223. DOI: 10.1111/isj.12193 - 22.
Veit D et al. Business models. Business & Information Systems Engineering. 2014; 6 (1):45-53. DOI: 10.1007/s12599-013-0308-y - 23.
Foss NJ, Saebi T. Business models and business model innovation: Between wicked and paradigmatic problems. Long Range Planning. 2018; 51 (1):9-21. DOI: 10.1016/j.lrp.2017.07.006 - 24.
Gong C, Ribiere V. Developing a unified definition of digital transformation. Technovation. 2021; 102 :102217. DOI: 10.1016/j.technovation.2020.102217 - 25.
Trischler MFG, Li-Ying J. Digital business model innovation: Toward construct clarity and future research directions. Review of Managerial Science [Preprint]. 2022. Available from: https://link.springer.com/content/pdf/10.1007/s11846-021-00508-2.pdf . DOI: 10.1007/s11846-021-00508-2 - 26.
Sund KJ et al. Managing tensions between new and existing business models. MIT Sloan Management Review. 2016; 57 (4): 8-10 - 27.
García-Gutiérrez I, Martínez-Borreguero FJ. The innovation pivot framework: Fostering business model innovation in startups. Research-Technology Management. 2016; 59 (5):48-56. DOI: 10.1080/08956308.2016.1208043 - 28.
Eksell A, Härenstam A. Business Model Innovation for a Digital Future. Chalmers University of Technology; 2017. Accessed at https://publications.lib.chalmers.se/records/fulltext/250572/250572.pdf - 29.
Amit RH, Zott C. Business model innovation: Creating value in times of change. 2010. Working Paper WP-870. 2010. DOI: 10.2139/ssrn.1701660 Available from: https://media.iese.edu/research/pdfs/DI-0870-E.pdf - 30.
Carlgren L, Rauth I, Elmquist M. Framing design thinking: The concept in idea and enactment. Creativity and Innovation Management. 2016; 25 (1):38-57. DOI: 10.1111/caim.12153 - 31.
Rosenbaum MS, Otalora ML, Ramírez GC. How to create a realistic customer journey map. Business Horizons. 2017; 60 (1):143-150. DOI: 10.1016/j.bushor.2016.09.010 - 32.
Gibbons S. Empathy Mapping: The First Step in Design Thinking. Nielsen Norman Group; 2018. Accessed at https://www.nngroup.com/articles/empathy-mapping/ - 33.
Collin J et al. IT Leadership in Transition: The Impact of Digitalization on Finnish Organizations. Finland: Espoo; 2015 - 34.
Jansson J, Andervin M. Leading Digital Transformation. Flexband, Sweden: Adlibris; 2016 - 35.
Dufva T, Dufva M. Grasping the future of the digital society. Futures. 2019; 107 :17-28. DOI: 10.1016/j.futures.2018.11.001 - 36.
Organisation for Economic Co-operation and Development. Key Issues for Digital Transformation in the G20. Berlin, Germany; 2017 - 37.
Li L et al. Digital transformation by SME entrepreneurs: A capability perspective. Information Systems Journal. 2018; 28 (6):1129-1157. DOI: 10.1111/isj.12153 - 38.
Schoemaker PJH, Heaton S, Teece D. Innovation, dynamic capabilities, and leadership. California Management Review. 2018; 61 (1):15-42. DOI: 10.1177/0008125618790246 - 39.
Lanzolla G et al. Digital transformation: What is new if anything? Emerging patterns and management research. Academy of Management Discoveries. 2020; 6 (3):341-350. DOI: 10.5465/amd.2020.0144 - 40.
Nambisan S. Digital entrepreneurship: Toward a digital technology perspective of entrepreneurship. Entrepreneurship Theory and Practice. 2017; 41 (6):1029-1055. DOI: 10.1111/etap.12254 - 41.
Diebner R, Silliman E, Ungerman K, Vancauwenberghe M. Adapting customer experience in the time of coronavirus. 2020. Accessed at https://www.mckinsey.com/capabilities/growth-marketing-and-sales/our-insights/adapting-customer-experience-in-the-time-of-coronavirus - 42.
Fitzgerald M et al. Embracing digital technology: A new strategic imperative. MIT Sloan Management Review. 2014; 55 (2):1-12 - 43.
Kane GC et al. Strategy, Not Technology, Drives Digital Transformation: Becoming a Digitally Mature Enterprise. Cambridge: Massachusetts, United States; 2015 - 44.
Liu D, Chen S, Chou T. Resource fit in digital transformation. Management Decision. 2011; 49 (10):1728-1742. DOI: 10.1108/00251741111183852 - 45.
Sebastian IM et al. How big old companies navigate digital transformation. MIS Quarterly Executive. 2017; 16 (3):197-213 - 46.
Bharadwaj A et al. Digital business strategy: Toward a next generation of insights. MIS Quarterly. 2013; 37 (2):471-482. DOI: 10.25300/MISQ/2013/37:2.3 - 47.
Ghezzi A, Cavallo A. Agile business model innovation in digital entrepreneurship: Lean startup approaches. Journal of Business Research. 2020; 110 :519-537. DOI: 10.1016/j.jbusres.2018.06.013 - 48.
Dal Mas F et al. Strategy innovation, intellectual capital management, and the future of healthcare: The case of kiron by nucleode. In: Knowledge, People, and Digital Transformation. New York City, New York, United States: Springer; 2020. pp. 119-131. DOI: 10.1007/978-3-030-40390-4_9 - 49.
Lasi H et al. Industry 4.0. Business & Information Systems Engineering. 2014; 6 (4):239-242. DOI: 10.1007/s12599-014-0334-4 - 50.
Yoo Y, Henfridsson O, Lyytinen K. Research commentary —The new organizing logic of digital innovation: An agenda for information systems research. Information Systems Research. 2010; 21 (4):724-735. DOI: 10.1287/isre.1100.0322 - 51.
Bresciani S, Ferraris A, Del Giudice M. The management of organizational ambidexterity through alliances in a new context of analysis: Internet of Things (IoT) smart city projects. Technological Forecasting and Social Change. 2018; 136 :331-338. DOI: 10.1016/j.techfore.2017.03.002 - 52.
Petrakaki D, Hilberg E, Waring J. Between empowerment and self-discipline: Governing patients’ conduct through technological self-care. Social Science & Medicine. 2018; 213 :146-153. DOI: 10.1016/j.socscimed.2018.07.043 - 53.
Atluri V, Sahni S, Rao S. The Trillion-Dollar Opportunity for the Industrial Sector: How to Extract Full Value from Technology. London: United Kingdom; 2018 - 54.
Cavalcante SA. Preparing for business model change: The “pre-stage” finding. Journal of Management & Governance. 2014; 18 (2):449-469. DOI: 10.1007/s10997-012-9232-7 - 55.
Kotarba M. Digital transformation of business models. Foundations of Management. 2018; 10 (1):123-142. DOI: 10.2478/fman-2018-0011 - 56.
Aversa P et al. Customer complementarity in the digital space: Exploring Amazon’s business model diversification. Long Range Planning. 2021; 54 (5):101985. DOI: 10.1016/j.lrp.2020.101985 - 57.
Bouwman H, Nikou S, de Reuver M. Digitalization, business models, and SMEs: How do business model innovation practices improve performance of digitalizing SMEs? Telecommunications Policy. 2019; 43 (9):101828. DOI: 10.1016/j.telpol.2019.101828 - 58.
Priyono A, Moin A, Putri VNAO. Identifying digital transformation paths in the business model of SMEs during the COVID-19 pandemic. Journal of Open Innovation: Technology, Market, and Complexity. 2020; 6 (4):104. DOI: 10.3390/joitmc6040104 - 59.
Teece DJ. Business models, business strategy and innovation. Long Range Planning. 2010; 43 (2–3):172-194. DOI: 10.1016/j.lrp.2009.07.003 - 60.
Sahut J, Dana L, Laroche M. Digital innovations, impacts on marketing, value chain and business models: An introduction. Canadian Journal of Administrative Sciences/Revue Canadienne des Sciences de l’Administration. 2020; 37 (1):61-67. DOI: 10.1002/cjas.1558 - 61.
Zott C, Amit R. Business model innovation: How to create value in a digital world. NIM Marketing Intelligence Review. 2017; 9 (1):18-23. DOI: 10.1515/gfkmir-2017-0003 - 62.
Bouncken RB, Kraus S, Roig-Tierno N. Knowledge- and innovation-based business models for future growth: Digitalized business models and portfolio considerations. Review of Managerial Science. 2021; 15 (1):1-14. DOI: 10.1007/s11846-019-00366-z - 63.
Kraus S et al. Digital entrepreneurship. International Journal of Entrepreneurial Behavior & Research. 2019; 25 (2):353-375. DOI: 10.1108/IJEBR-06-2018-0425 - 64.
Kohtamäki M et al. Digital servitization business models in ecosystems: A theory of the firm. Journal of Business Research. 2019; 104 :380-392. DOI: 10.1016/j.jbusres.2019.06.027 - 65.
Weill P, Woerner S. Optimizing your digital business model. IEEE Engineering Management Review. 2015; 43 (1):123-131. DOI: 10.1109/EMR.2015.7059380 - 66.
Hoßbach N, Wiener M, Saunders CS. The unfolding of value sources during online business model transformation. Journal of Business Models. 2016; 4 (2):22-41. DOI: 10.5278/ojs.jbm.v4i2.1623 - 67.
Gauthier C, Bastianutti J, Haggège M. Managerial capabilities to address digital business models: The case of digital health. Strategic Change. 2018; 27 (2):173-180. DOI: 10.1002/jsc.2192 - 68.
Katsamakas E, Pavlov OV. AI and business model innovation: Leveraging the AI feedback loop. SSRN Electronic Journal. 2020; 8 (2):21-30. DOI: 10.2139/ssrn.3554286 - 69.
König M et al. Different patterns in the evolution of digital and non-digital ventures’ business models. Technological Forecasting and Social Change. 2019; 146 :844-852. DOI: 10.1016/j.techfore.2018.05.006 - 70.
Paiola M, Gebauer H. Internet of things technologies, digital servitization and business model innovation in BtoB manufacturing firms. Industrial Marketing Management. 2020; 89 :245-264. DOI: 10.1016/j.indmarman.2020.03.009 - 71.
Dellermann D, Fliaster A, Kolloch M. Innovation risk in digital business models: The German energy sector. Journal of Business Strategy. 2017; 38 (5):35-43. DOI: 10.1108/JBS-07-2016-0078 - 72.
Mihardjo LWW et al. Digital leadership role in developing business model innovation and customer experience orientation in industry 4.0. Management Science Letters. 2019;(9):1749-1762. DOI: 10.5267/j.msl.2019.6.015 - 73.
Bleicher J, Stanley H. Digitization as a catalyst for business model innovation a three-step approach to facilitating economic success. Journal of Business Management. 2019; 5 (2):62-71 - 74.
Laudien SM, Pesch R. Understanding the influence of digitalization on service firm business model design: A qualitative-empirical analysis. Review of Managerial Science. 2019; 13 (3):575-587. DOI: 10.1007/s11846-018-0320-1 - 75.
Karimi J, Walter Z. The role of dynamic capabilities in responding to digital disruption: A factor-based study of the newspaper industry. Journal of Management Information Systems. 2015; 32 (1):39-81. DOI: 10.1080/07421222.2015.1029380 - 76.
Kuk G, Janssen M. Assembling infrastructures and business models for service design and innovation. Information Systems Journal. 2013; 23 (5):445-469. DOI: 10.1111/j.1365-2575.2012.00418.x - 77.
Kraus S, Roig-Tierno N, Bouncken RB. Digital innovation and venturing: An introduction into the digitalization of entrepreneurship. Review of Managerial Science. 2019; 13 (3):519-528. DOI: 10.1007/s11846-019-00333-8 - 78.
Breslin D, Gatrell C, Bailey K. Developing insights through reviews: Reflecting on the 20th anniversary of the international journal of management reviews. International Journal of Management Reviews. 2020; 22 (1):3-9. DOI: 10.1111/ijmr.12219 - 79.
Kraus S, Breier M, Dasí-Rodríguez S. The art of crafting a systematic literature review in entrepreneurship research. International Entrepreneurship and Management Journal. 2020; 16 (3):1023-1042. DOI: 10.1007/s11365-020-00635-4 - 80.
Wolfswinkel JF, Furtmueller E, Wilderom CPM. Using grounded theory as a method for rigorously reviewing literature. European Journal of Information Systems. 2013; 22 (1):45-55. DOI: 10.1057/ejis.2011.51 - 81.
Braun V, Clarke V. Using thematic analysis in psychology. Qualitative Research in Psychology. 2006; 3 (2):77-101. DOI: 10.1191/1478088706qp063oa - 82.
Patton MQ. Qualitative Research & Evaluation Methods: Integrating Theory and Practice. 4th ed. Thousand Oaks, California, United States: SAGE Publications; 2015 - 83.
Bagnoli C et al. Business models for accelerators: A structured literature review. Journal of Business Models. 2020; 8 (2):1-21. DOI: 10.5278/ojs.jbm.v8i2.3032 - 84.
Enkel E, Sagmeister V. External corporate venturing modes as new way to develop dynamic capabilities. Technovation. 2020; 96–97 :102128. DOI: 10.1016/j.technovation.2020.102128 - 85.
Autio E et al. Digital affordances, spatial affordances, and the genesis of entrepreneurial ecosystems. Strategic Entrepreneurship Journal. 2018; 12 (1):72-95. DOI: 10.1002/sej.1266 - 86.
Henfridsson O, Yoo Y. The liminality of trajectory shifts in institutional entrepreneurship. Organization Science. 2014; 25 (3):932-950. DOI: 10.1287/orsc.2013.0883 - 87.
Kiel D, Arnold C, Voigt K-I. The influence of the Industrial Internet of Things on business models of established manufacturing companies—A business level perspective. Technovation. 2017; 68 :4-19. DOI: 10.1016/j.technovation.2017.09.003 - 88.
Tongur S, Engwall M. The business model dilemma of technology shifts. Technovation. 2014; 34 (9):525-535. DOI: 10.1016/j.technovation.2014.02.006 - 89.
Zott C, Amit R, Massa L. The business model: Recent developments and future research. Journal of Management. 2011; 37 (4):1019-1042. DOI: 10.1177/0149206311406265 - 90.
Pigni F, Piccoli G, Watson R. Digital data streams: Creating value from the real-time flow of big data. California Management Review. 2016; 58 (3):5-25. DOI: 10.1525/cmr.2016.58.3.5