The Acceleration of Digitalization and its Influence on Business Model Innovation : A qualitative study of Swedish SMEs from the perspective of a business developer

The Acceleration of Digitalization

and its Influence on Business Model

Innovation

A qualitative study of Swedish SMEs from the perspective of a business developer

BACHELOR’S DEGREE PROJECT THESIS WITHIN: Business Administration NUMBER OF CREDITS: 15 hp

PROGRAMME OF STUDY: International Management AUTHORS: Pim de Flon & Lovisa Lindgren

Acknowledgment

We want to acknowledge our thankfulness to all of the people who have contributed to this thesis. First and foremost, we would like to show our appreciation to the business developers

who dedicated their time and participated in the interviews. Your expertise, knowledge, and experience provided this thesis with highly valuable insights from which we could draw our conclusion. Without your contributions, this thesis would not have been possible. Secondly, we would like to thank our seminar group, who have helped develop this thesis, but also each

other for the dedication and effort put into this thesis. Although it has been a rollercoaster, there is no other person we would have wanted to do this with than each other. Lastly, we wish

to express our biggest thanks to our tutor, Hossain Shahriar, who has invested enormous time and effort into this process. His guidance, insights, and ability to make us reflect to a greater

extent, have highly contributed to the quality and results of this thesis.

_________________________________ _________________________________

Bachelor Thesis in Business Administration

Title: The Acceleration of Digitalization and its Influence on Business Model Innovation

Authors: Pim de Flon & Lovisa Lindgren

Tutor: Hossain Shahriar

Date: May 2021

Key terms: Business Model Innovation; Acceleration of Digitalization; Small- and

Medium-sized Enterprises; Covid-19; Theory of Organizational Change

Abstract

Background: Covid-19 has accelerated digitalization and pressured companies across multiple sectors to digitally transform their operations. Such adaptation requires businesses to rethink and change their existing business models, thus, business model innovation (BMI). Small- and Medium-sized Enterprises (SMEs), whose success is highly dependent on their experimentation and development of new technologies, are struggling with this adaptation. Problem: SMEs, the heart and backbone of economic growth, struggle with implementing digitalization due to their lack of awareness, evaluation, knowledge, and resources. Regardless of their struggle, they are now forced to change their structures and business models. While there is an abundance of research on the impact of digitalization on BMI those studies rarely focus on how the acceleration of digitalization has influenced SMEs BMI.

Purpose: The purpose of this research is to explore how the acceleration of digitalization has impacted BMI of Swedish SMEs. The findings from this research are expected to contribute with academic value to the theoretical fields under investigation, Swedish policymakers, and business authorities, along with providing guidance for individual SMEs.

Method: This study has an exploratory approach, an inductive design within the interpretive philosophy. To collect the primary data, ten qualitative semi-structured interviews were conducted with business developers who possessed strong expertise and knowledge within the investigated fields. The data analysis followed Charmaz’s (2006) constructivist grounded theory, which emphasized a coding process including initial and focused coding.

Conclusion: The empirical findings shed light on important attributes and actions for a successful BMI which set the basis for the proposed model. The 6-step model explains the process of how an SME can successfully adapt and change under external pressure, such as the acceleration of digitalization and a crisis like Covid-19. The 6 steps include Create Awareness,

Develop a Clear Strategy, Acquire Knowledge, Develop an Organizational Culture, Pursue Experimentation, and Implement the New Business Model. This process is not only crucial for

Table of Content

2.1 Construction of the Literature Review 11

2.2 Theoretical Framework 12

2.2.1 The Theory of Change 12

2.2.2 The Theory of Organizational Change 12

2.3 Digitalization 13

2.3.1 Business Digitalization 14

2.3.3 SMEs and Digitalization 15

2.4. Business Model Innovation 16

2.4.3 Business Model Innovation and SMEs 16

2.5 Theoretical Summary 17

3. Methodology and Method 19

3.1 Methodology 19

3.1.1 Research Philosophy 19

3.1.2 Research Approach 19

3.1.2 Research Strategy 20

3.2 Method 21

3.2.1 Primary Data Collection 21

3.2.3 Primary Data Selection Process 21

3.2.2 Interview Construction 22

3.2.4 Data Analysis 23

3.2.4.1 Initial Coding 24

3.2.4.2 Focused Coding 24

3.3 Research Quality and Trustworthiness 25

3.3.1 Credibility 25

3.3.2 Transferability 25

3.3.4 Confirmability 26

3.3.5 Ethical Considerations 26

4. Empirical findings & Analysis 28

4.1 Construction of Findings & Analysis 28

4.2 Background 29

4.3 The Acceleration of Digitalization 31

4.3.1 Digital Maturity 33

4.3.2 Successful Adaptation to Digitalization 35

4.4 Covid-19s Impact on SMEs 36

4.4.1 Changes in SMEs Operations 37

4.4.2 Attributes for Managing Covid-19 39

4.5 The Importance of Business Model Innovation 41

4.5.1 SMEs’ Innovation Strategies 42

4.5.2 Covid-19’s impact on Business Model Innovation 44

4.5.3 Digitalization and Innovation 45

4.6 Proposed Model: 6 Steps to Succeed with BMI for SMEs 47

5. Conclusion 52 6. Discussion 54 6.1 Limitations 54 6.2 Theoretical contributions 55 6.3 Practical implications 55 6.4 Future research 56 References 58 Appendix 65 Appendix A 65 Appendix B 66 Appendix C 67 Appendix D 69

1. Introduction

This section begins with a background that introduces the reader to the broader context of the research. In the subsequent section, the problem is formulated, which leads to the purpose and the formulation of the research question, followed by the delimitations of the study. Lastly, the authors present a definitions section with the most important definitions.

1.1 Background

In March 2020, the World Health Organization (2020) revealed that the disease, Covid-19, had spread as a global pandemic and global health crisis. Covid-19 outburst into a global economic recession (Nurunnabi, 2020; Klein & Todesco, 2021), which generated significant economic effects, increased uncertainties, and a collapse in consumption and confidence (OECD, 2020). The pandemic resulted in an increase in digital transformation, a change in customer behavior, and a realization that businesses lack technological knowledge (Klein & Todesco, 2021). Nevertheless, before Covid-19, one could notice a digital shift and increase in digitalization in global industries (Valenduc & Vendramin, 2017). This is described as an organization’s adaptation or increase in the usage of digital technologies (Brennareen & Kreiss, 2016), such as creating connections between organizational processes and customers (Ardito, Petruzzelli, Paniello, & Caravelli, 2019). The development of digital technologies has put pressure on companies to transform their operations digitally, but it also improves business performances and the scope of the business (Van Tonder, Schachtebeck, Nieuwenhuize, & Bossink, 2020). Adapting digital transformation is, however, not necessarily about optimizing internal processes or incorporating new technologies, rather it requires businesses to rethink and change their existing business models (BMs) (Bouwman, Nikou, & de Reuver, 2019; North, Aramburu, & Lorenzo, 2019). Hence, it puts pressure on firms to work with Business Model Innovation (BMI) (Rachinger et al., 2019).

As realized by European Commission (2019), 99.8 percent in the European Union and 99.9 percent in Sweden are Small- and Medium-Sized Enterprises (SMEs) (Appendix A). The U.S. Chamber of Commerce (2020) presented that SMEs’ transformation and transition to remote work have increased by 22.0 percent since the pandemic. Moreover, Klein and Todesco (2021)

stated that 74.8 percent of SMEs have started some digital action as a response to the pandemic. McKinsey & Company (2021) complemented the above and highlighted that the pandemic has led to an acceleration of the digital transformation, which resulted in significant pressure on companies to adapt to the digital environment. As SMEs success and survival highly depend on their ability to engage in the discovery, experimentation, and development of new technologies (Dabić et al., 2021), and adapting to change (Klein & Todesco, 2021), it is vitally important that they succeed with this implementation (Chonsawat & Sopadang, 2020). Furthermore, Hussain et al. (2018) highlighted within the Theory of Change how important organizational change is for companies’ survival, competition, and growth, which can further be connected to Ibarra et al.’s (2020) example of how BMI is a tool to manage these changes. However, Müller (2019) described how implementing the new embedded technology is more challenging for SMEs than Multinational Corporations (MNCs). In the long run, the disruption SMEs face today due to the pandemic might result in greater difficulties compared to larger firms in rebuilding their connections and networks (OECD, 2021). Firstly, due to their struggle with business evolution, awareness, and adapting to the acceleration of digitalization (Chonsawat & Sopadang, 2020). Secondly, their attributes make them more vulnerable to the challenges the pandemic brings upon, including financial scarcity, the gap of knowledge, and lack of resources (Klein & Todesco, 2021).

1.2 Problem formulation

As evident from previous literature, digitalization has put pressure on companies to transform and adapt their business models (Bouwman et al., 2019; North et al., 2019), and Covid-19 has increased this pressure by accelerating digitalization (Klein & Todesco, 2021). While most businesses globally face this pressure, SMEs, in particular, are struggling with the challenges it implies (Chonsawat & Sopadang, 2020), partly due to their unsuitable business models (Müller, 2019). Organizational change and businesses’ effectiveness to modify strategies, processes, and structures (Hussain et al., 2018) is strongly related to innovation of business models (Foss & Saebi, 2016), where business model innovation is one of the key activities that businesses need to continuously undertake to sustain competitiveness (Pucihar et al., 2019). As this is argued for companies in general, it is especially true for SMEs (Garzella, Fiorentino, Caputo, & Lardo, 2020), who do not have any other alternative than to adapt to the digital

The existing literature within the fields of Business Model Innovation, Digitalization and SMEs, shed light on the potential of digitalization and digital technologies to enable BMI (Parida, Sjödin, & Reim, 2021) and SMEs digital transformation (Klein & Todesco, 2021). It also highlighted SMEs BMI (Müller, 2019), how digitalization has affected SMEs BMI (Ibarra et al., 2020), and the importance for companies to adapt to the new digital technologies (Petruzzelli, 2020). While there is an abundance of research on the impact of digitalization on business model innovation (Langley et al., 2021; Bouwman et al., 2019; North et al., 2019; Parida et al., 2021; Rachinger et al., 2019; ), those studies rarely focus on how the acceleration of digitalization has influenced SMEs BMI. Furthermore, how SMEs pursue BMI as a response to the challenges the acceleration of digitalization has brought upon was also less explored. Thus, creating a theoretical gap which this research seeks to address.

Additionally, as several scholars stress the importance SMEs play in national economies as they generate added value and employment (Chonsawat & Sopadang, 2020; North et al., 2019; OECD, 2017; Sawaean & Ali, 2020), one can argue for their importance for the Swedish economy, as they represent 99.9 percent of all companies in Sweden (European Commission, 2019). When reviewing existing literature, research on how Swedish SMEs have been affected by the acceleration of digitalization was found to be limited, which provides a reason for studying the Swedish context.

1.3 Purpose

The purpose of this research is to explore how the acceleration of digitalization has impacted BMI of Swedish SMEs. By examining the major external and internal challenges SMEs have faced due to the acceleration of digitalization, along with opportunities and challenges it has resulted in to pursue a successful BMI, new insights will emerge. Through these understandings, this study aims to draw a conclusion of how SMEs can pursue BMI to adapt to the acceleration of digitalization successfully. Additionally, the Theory of Change, specifically, the Theory of Organizational Change, will be used for sense-making and interpretation of the empirical findings. This, due to its relevance for the fields this study aims to contribute to.

The findings of this research are expected to contribute with empirical insights and provide academic value to the theoretical fields under investigation, BMI, Digitalization, and SMEs. By addressing the research gap, how the acceleration of digitalization has influenced SMEs’ BMI, this research also seeks to extend the theoretical fields. Moreover, this research might be of value for individual SMEs who seek guidance in their process of innovating their business models. Considering the importance of SMEs in the Swedish economy (European Commission, 2019), these findings can also be valuable for Swedish policymakers and business authorities.

1.4 Research question

The research question for this study is the following:

“How has the acceleration of digitalization due to Covid-19 been experienced to have influenced SMEs business model innovation?

1.5 Delimitations

The delimitations of this study concern three areas, the chosen problem to investigate, the participants in this study, and the geographical location. Firstly, this study was delimited to investigate the acceleration of digitalization and its influence on SMEs’ BMI based on the theoretical gap of these fields found in the existing literature. Thus, other factors than the acceleration of digitalization that might affect SMEs’ BMI have not been included and analyzed in this research. Secondly, the participants in this study have been delimited to business developers, who were chosen based on their expertise and knowledge within the fields under investigation, BMI, Digitalization, and SMEs. While this delimitation excluded the perspectives of individual SMEs, it allowed the researchers to develop an understanding of a larger variety of industries which facilitated the ability to answer the research purpose. Thirdly, the geographical location of Sweden was applied due to the importance SMEs have for the Swedish economy (European Commission, 2019) and the realized gap in the current literature where SMEs are less explored within the fields under investigation. To further narrow the scope within Sweden, this study was delimited to business developers who originated from Småland and Västra Götaland. This sample was based on the criteria of the business developers’ expertise, in addition to practical reasons such as the researchers’ networks.

1.6 Definitions

Digitalization

Digitalization is defined as any changes in an organization's business model, or business, due to the increased usage of digital technologies to improve business performance and the scope of the business (van Tonder et al., 2020; Rachinger et al., 2019). Brennen and Kreiss (2016) further described digitalization as an organization’s adaptation or increase in digital or computer technology usage and as the main characteristic of contemporary social life.

Digital Technologies

Digital technologies are important in the transformation of a business, since their ability to use that technology and apply it to their business provides value. Digital technologies have changed traditional business structures, although it has also created “a more volatile, complex and uncertain business environment”. An example of digital technology is the Internet of Things (van Tonder et al., 2020).

Digital Transformation

Digital transformation can be referred to as the process to restructure economies, institutions, and society on a system level. This can be internal, for example, using big data for customer relationship management, or external to engage with customers in new channels such as social media channels (Bouwman et al., 2019).

Small-and-Medium sized enterprises

Companies are referred to as Small- and Medium-sized Enterprises (SMEs) if they meet the following criteria: staff headcount at fewer than 250 employees, an annual turnover of less than, or equal to, EUR 50 million, and balance sheet total or less than EUR 43 million. SMEs can further be divided into three subcategories, based on the size of the companies: micro-enterprises (0-9 employees), small micro-enterprises (10-49 employees), and medium-sized enterprises (50-249 employees) (European Commission, 2015).

Fourth Industrial Revolution

The fourth industrial revolution, Industry 4.0, is a new industrial transformation that aims to connect people and things “anytime, anyplace, with anything and anyone, ideally using any path/network and any service” (Calabrese, Dora, Levialdi Ghiron, & Tiburzi, 2020, p.1). It is also described as “the growing use of technology, cloud computing, Internet of Things (IoT)

and artificial intelligence” (Umar, Rizci, & Naqvi, 2021, p.1), which can be helpful in the development of future technological strategies (Su, Qin, Tao, & Umar, 2020).

Business Model Innovation

Business models describe the architecture of how firms create, deliver and capture value, both internally and externally. Business model innovation focuses on the changes in a firm’s business model and is viewed as a process that changes the business logic or core elements (Tykkyläinen & Ritala, 2021; Foss & Saebi, 2016).

Covid-19

In December 2019, Wuhan Municipal Health Commission, China, reported a disease outbreak, which started spreading worldwide. In March 2020, the World Health Organization (WHO) characterized Covid-19 as a pandemic (World Health Organization, 2020). The pandemic started as a health crisis and moved towards an economic crisis that generated significant economic effects (OECD, 2021).

2. Literature Review

In this section, the current literature within the context of this research is reviewed. Firstly, the construction and delimitations of the literature review are described. Thereafter, the theoretical framework the Theory of Change and Organizational Change is presented. In the subsequent sections, the pre-existing literature in the fields of Business Model Innovation, Digitalization and SMEs are analyzed. Lastly, a theoretical summary is provided in which the most important findings are presented.

2.1 Construction of the Literature Review

In most academic disciplines, peer-reviewed journals and articles are considered the most important source of information because, through the peer-review process the quality and relevance of the research can be judged (Easterby-Smith, Thorpe, Jackson, & Jaspersen, 2018). Consequently, the literature in this research has been retrieved from journals, articles, and publications accessed by Google Scholar and Jönköpings University library; Primo, and Web of Science. According to Collis and Hussey (2014), other secondary literature can be used if it provides important insights for a study’s purpose. Therefore, the Organization for Economic Co-operation and Development (OECD) and the Government Offices of Sweden (SOU) has been used due to its high relevance for this research. Delimitations and research boundaries of this study’s literature review have been used to better define the scope of this research (Collis & Hussey, 2014). Only English peer-reviewed sources have been used, and some keywords during the search process for relevant literature was: “Digitalization AND SMEs”, “Digitalization”, “Business models”, “Business model innovation AND SMEs”, “Business model innovation and Digitalization”, “Theory of Organizational Change”, “Theory of Organizational Change AND business model innovation”.

The most recently published literature should be emphasized to increase the relevance and trustworthiness of the information (Xiao & Watson, 2017), which this study has considered by limiting the years of publications to 2016-2021. Moreover, additional references and studies have been collected throughout the review of some articles and journals to reach the original publisher of the specific content and information. A critical evaluation received by the literature review provided the study with the support of its located and analyzed data (Collis & Hussey,

2014). This process involved the use of triangulation of the collected information to support the findings of this study, as well as accounting for the quality and trustworthiness. Triangulation is defined as using several sources of data that are not correlated to analyze and study the same topic and phenomena (Collis & Hussey, 2014). A systematic screening of both abstract and summaries of articles found by the specific keywords and delimitations was conducted, which enabled the researchers to collect literature that was relevant to this study’s purpose.

2.2 Theoretical Framework

2.2.1 The Theory of Change

According to Hussain et al. (2018), the Theory of Change is defined as “the effectiveness with which organizations can modify their strategies, processes, and structures” (p.1.). Due to the uncertain environment, businesses need to adapt to global changes in order to grow, compete, develop and survive in the market. The authors further argued that an organization’s life is dependent and affected by the global, technological, and economic features in today’s world. Burke (2018) agreed with the above but highlighted that changes in the external environment occur more rapidly than a change in organizations. The author described the changes as unplanned and gradual, along with being difficult to implement when the assumption within the organization is that nothing is broken.

2.2.2 The Theory of Organizational Change

Within the Theory of Change, the Theory of Organizational Change emphasizes the movement of an organization from its current and known state to its desired, future, and unknown state (Hussain et al., 2018). Guido and Hootegem (2019) supported the above but pointed out the vast complexity of organizational change. According to Hussain et al. (2018), organizational change can be practiced in two ways, proactive or reactive. Proactive change is the process when the organization itself decides to change to reach a desirable state, while reactive change is when the internal and/or external environment forces the business to persuade change (Hussain et al., 2018). This can be supported by Burke (2018), who argued for the changes to be unplanned and gradual. Nevertheless, the Theory of Organizational Change highlights different key factors for a successful change, including leadership (Hussain et al., 2018) and culture (Guido & Hootegem, 2019). These key factors are aligned with Burke’s (2018)

culture” (p.1). Singh and Ramdeo (2020) complemented the above and described that successful organizational change depends on employee commitment and that challenges in organizational change are connected to reputation, financial risks, time, and resources. Furthermore, the authors pointed out that actions that lead to a successful change in one business do not guarantee success in another business.

According to Foss and Seabi (2016), another challenge of organizational change is strongly related to innovation and innovation in business models. Guido and Hootegam (2019) defined BMI as a new organization through new designs of business models or a reconfiguration of business models that already exist. This, in turn, complements the definition by Burke (2018) that change is a modification or an entirely new entity. Furthermore, Hussain et al. (2018) argued for the importance of organizational change for survival, competition, and growth. This aligns with Ramdani, Binsaif, and Boukrami (2019), who stated that innovation of business models is essential for a business’s performance, competitive advantage, and survival on the market. Upon the above, Gronum, Steen, and Verreynne (2016) argued for the strong link between the width of innovation and new/changed business model designs. This complements Anderson (2016), who outlined the connection between business model change and organizational change. Moreover, the effect organizational change has on business model innovation should be at least as important as any other strategic choice (Anderson, 2016). New technologies and digitalization have disrupted the way businesses previously operated (Caputo, Pizzi, Pellegrini, & Dabić, 2021). SOU (2018:25) supported the above and shed light on digitalization as the strongest change factor of ‘our time’. Caputo et al. (2021) further argued that this change creates a demand for new business models to respond to the new market behavior, expanded time dimensions, and unprecedented ubiquity of information in a more effective manner.

2.3 Digitalization

Digitalization has disrupted previous ways businesses operate, therefore, organizations across the globe are continuously paying more attention to new technologies and their development, all to adapt their strategies to meet the new market’s needs (Caputo et al., 2021). Both Davidsson et al. (2016), and van Tonder et al. (2020), referred to the advancements of digital technologies during the past decades as different “waves” that have both transformed societies

and individual businesses. The authors held similar views on the first two waves, whereas the first wave introduced computers to society and the second wave introduced the internet, which allowed easier information sharing practices. Van Tonder et al. (2020) described that the third wave is currently realized, in which society and businesses are using power and communication through digitalization. On the contrary, Davidsson et al. (2016) argued that the third wave included the mobile internet and that society is currently experiencing the fourth wave, in which people not just use the internet to access and share information but to a broader extent. Calabrese et al. (2020) defined Industry 4.0 as a new industrial transformation that bridges the physical and virtual worlds. Spöttl and Windelband (2020) described how an organization’s work organization and work processes will change within the context of Industry 4.0. More specifically, how production will be automated, but also work contents and the interaction and communication between humans and technology. van Tonder et al. (2020) supported the above arguments by further arguing for digital technologies as the driver of the fourth industrial revolution.

2.3.1 Business Digitalization

The increasing digitalization of the economy has resulted in a digital and technological shift in global industries (Valenduc & Vendramin, 2017). This was acknowledged by van Tonder et al. (2020), who described that the digital transformation has put pressure on businesses to change their current operations. Along with their emphasis on identifying, understanding and adapting to the changing technologies (van Tonder et al., 2020). According to SOU (2018:25), digitalization is considered the strongest change factor of ‘our time’, as it enables the transition between the traditional flow of information to a digital flow. Although, opportunities related to the use of technology make digitalization a key challenge for managers, based on the need for managers to understand the most prioritized areas to apply digital technology (Ritter & Lund Pedersen, 2020).

Regardless of challenges, Rachinger et al. (2019) presented opportunities realized by digitalization, such as flexibility, optimization of resources, and competitive advantages. However, Lee and Falahat (2019) argued that digitalization is considered to have no direct effect on competitive advantages such as price, capabilities, product or service. Despite the above, SOU (2018:25) shed light on the benefits gained by digitalization in the form of

transformation creates competitive contexts within business processes, fewer boundaries, and dynamic expansion.

2.3.3 SMEs and Digitalization

Chonsawat and Sopadang (2020) argued that SMEs play an essential role in national economies since they generate employment and added value. The authors further referred to SMEs as the heart and backbone of development and economic growth. This was acknowledged by Yazdanfar and Öhman (2018) and North et al. (2019), who argued for SMEs’ importance for economic growth. However, North et al. (2019) also raised concerns regarding SMEs’ struggle with the implementation of technology and digitalization. As SMEs struggle with business evaluations, it, in turn, contributes to further challenges of adapting the digital and technological advancements (Chonsawat & Sopadang, 2020; OECD, 2017). Furthermore, North et al. (2019) described how SMEs do not have any alternatives than to adapt to the new requirements of the digital environment since their competitiveness is highly dependent on their connection with the business network. As stated by Müller (2019), SMEs face larger challenges with the adaptation to Industry 4.0 compared to larger businesses, challenges involving resource limitation, low bargaining power, and unsuitability to the digital change. This aligned with Amaral and Peças (2021), who argued that SMEs have had a more challenging time in the process of integrating to the fourth industrial revolution.

On the contrary, Garzella et al. (2020) emphasized some opportunities digitalization implies for SMEs rather than challenges. The authors argued that SMEs, in comparison to Multinational Corporations (MNCs), can both more easily and faster adapt to the digital environment, partly due to their ability to develop capabilities more quickly, which leads to business model innovation. This argument was supported by Eller, Alford, Kallmünzer, and Peters (2020), who outlined that SMEs possess other strengths which larger firms lack. These are connected to evolution, innovation, and involvement, due to SMEs’ flexibility and coherent culture. The authors further claimed that SMEs’ small size and flexibility increase the chances of a positive attitude towards digitalization. However, Eller et al. (2020) also mentioned that SMEs lag behind in digitalization compared to larger firms even though technologies are considered relevant for them, which further harms their performance. This complemented OECD (2021), which presented that the cost of changing work processes and transforming SMEs to remote work is higher than for larger firms due to their low level of digitalization, access, and the possibility of adapting to the digital technologies. Nevertheless, Eller et al.

(2020) outlined that digital technologies can extend value propositions and help SMEs reduce costs. The authors provided an example of how social media can be used to reduce marketing costs and improve customer relationships.

2.4. Business Model Innovation

Foss and Saebi (2016) described Business Model Innovation as an attempt to seize new opportunities by the advent of external elements and provided an example of such elements as digital technologies. Several scholars (Bouwman et al., 2019; North et al., 2019; Parida et al., 2021; Rachinger et al., 2019) argued that there is a clear link between BMI and digitalization and how digital transformation requires businesses to rethink and change their existing business models. Müller (2019) added to this argument by pointing out that the only way firms can extract value from new technologies is through suitable business models. As stated by Parida et al. (2021), digitalization and digital technologies enable business model innovation, Rachinger et al. (2019) agreed and outlined how digital technologies put pressure on companies to innovate their business models. Foss and Saebi (2016) further argued how some research refers to digital technologies as the antecedent to business model innovation.

Langley et al. (2021) explained how businesses that succeeded with adapting their BMs to the new technological advancements have considerable opportunities to innovate, referred to as increased competitiveness. Therefore, the authors claimed that it is important to understand the extent to which digitalization will transform business models. The statement is supported by Pucihar et al. (2019), who referred to BMI as one of the key activities that businesses need to continuously undertake to sustain competitiveness. Additionally, Ritter and Lund Pedersen (2020) argued that business model transformation to a digital approach enhances competitiveness since it meets the changing customer preferences and consumption, internal processes, and value propositions. However, Parida et al. (2021) argued that to profit from digitalization, only applying digital technology is not enough, companies also need to transition and innovate their business models to seize the opportunities that arise.

2.4.3 Business Model Innovation and SMEs

Garzella et al. (2020) stated how innovating business models has become a fundamental capability to survive competition and that this is particularly important for SMEs. The authors,

possibilities, offer potential to generate innovative business models, and enable unimaginary possibilities for business growth. Moreover, Anwar (2018) pointed out that BMI is considered the core driver for a business’s survival and that it has a significant positive effect on SMEs’ competitive advantages and performances. In addition, Ibarra et al. (2020) highlighted the need and relevance for SMEs to adapt BMI to stay competitive in the current fast-changing environment. The authors further presented five conclusions of how to achieve and develop a successful BMI. Firstly, sensing customer needs, this is particularly important for SMEs and includes identifying emerging market demands and anticipating customers with unmet needs. Secondly, sensing technological options, which refers to the ability to gain knowledge of new emerging technologies, which allows one to recognize both opportunities and threats. Thirdly,

conceptualizing and experimenting with new ideas, thinking outside the box, and developing

the competencies needed to transform these ideas into viable value propositions. Fourthly,

developing new collaborative approaches to co-design and co-produce new value propositions.

Lastly, developing a clear BMI strategy, which is considered the most critical step for BMI. This includes facilitating the diffusion of new BM concepts that are aligned with the company’s growth strategy, which will, in turn, allow the development of new competencies (Ibarra et al., 2020).

2.5 Theoretical Summary

The literature review aimed to present existing literature in the fields of Business Model Innovation, Digitalization, SMEs, and the Theory of Organizational Change. Firstly, the section on the Theory of Organizational Change and its connection to the mentioned fields under investigation was presented (Foss & Seabi, 2016). This section contributed to a deeper understanding of the importance of managing organizational change and guided the subsections of the literature review. Secondly, the chapter on Digitalization introduced a broad perspective of digitalization and Industry 4.0, its definitions, and impacts on businesses in general and on SMEs (Calabrese et al., 2020; Spöttl & Windelband, 2020; van Tonder et al., 2020). Furthermore, it provided the authors with knowledge that society is currently experiencing a new wave of digitalization (van Tonder et al., 2020; Davidsson et al., 2016) and emphasized the need for SMEs to implement digitalization (Chonsawat & Sopadang, 2020; OECD, 2017). Lastly, a deeper understanding of Business Model Innovation was attained as well as how it connects to SMEs adaptation to the digital environment and its effect on SMEs competitive

advantages and development (Langley et al., 2021; Pucihar et al., 2019; Ritter & Lund Pedersen, 2020; Garzella et al., 2020).

The literature review set the basis for this research, whereas the intention of using the Theory of Organizational Change was for interpretation and sense-making of the empirical findings. By gaining insights from collected literature in the fields of BMI, Digitalization, and SMEs, the purpose of the research could be further developed. As realized, the acceleration of digitalization and its connection to SMEs BMI was less explored, the researchers aimed to contribute to this theoretical gap by new empirical findings.

3. Methodology and Method

This section begins with presenting the methodology of this research, in which the research philosophy, approach, and strategy are discussed. Thereafter, the method is described, including the research design, and the techniques and processes of the data collection and data analysis. Finally, the criteria for research quality, trustworthiness, and ethical considerations are presented, which have been taken into consideration through the process of this research.

3.1 Methodology

3.1.1 Research Philosophy

The research philosophy explains the relationship between the observer and the unit of analysis (Duignan, 2016) and guides how the research should be conducted (Collis & Hussey, 2014). There are two major philosophies, positivism, and interpretivism. Positivism is based on the assumption that social reality is singular and objective. It has its roots in natural sciences and is widely used in quantitative studies (Collis & Hussey, 2014). Interpretivism, on the contrary, explores the complexity of social reality, constructionism, and phenomenon and aims to describe how people’s perceptions shape social reality. The epistemological assumption is that knowledge derives from subjective perspectives from the participants in the research and the authors of the research (Smith, 1983). The findings of this study were derived from qualitative methods of analysis, such as interviews, and on the interpretation of qualitative research data (Collis & Hussey, 2014). As this research aimed to develop an understanding of how the acceleration of digitalization has influenced SMEs BMI, interpretivism was seen as the most suitable research philosophy. It also allowed qualitative data collection methods, including a small sample, to gain a deeper knowledge and understanding of the topic through the participants’ thoughts and reflections. Thus, it provided their relative, subjective experiences.

3.1.2 Research Approach

A research approach gives the foundation for the research and can take two approaches, either inductive or deductive (Collis & Hussey, 2014). By following the theory, logic, and reasoning of this study, inductive reasoning was the most applicable. This, because the purpose of this study was to build theory from the conducted qualitative data by comparing similarities and

recurring patterns from the interview participants’ specific and individual perspectives (Saunders, Lewis, & Thornhill, 2016). The chosen theory follows the data that corresponded to this research's intention, rather than the opposite where data follows the theory as would have been the case in a deductive approach (Saunders et al., 2016). The inductive design further allowed the authors to make sense of the collected primary data, which led to the contribution to the fields under investigation, BMI, Digitalization, and SMEs. Following the inductive approach and the qualitative research, an exploratory approach was suitable considering the previous research within the fields under investigation, and as the acceleration of digitalization was found to be limited in the existing literature (Collis & Hussey, 2014).

3.1.2 Research Strategy

A research strategy can take many approaches. Following the interpretivism paradigm and the inductive reasoning of this study, the researchers decided to pursue certain elements from Kathy Charmaz Constructivist Grounded Theory (2006) as research strategy. Grounded theory was seen as a suitable strategy for the data collection and data analysis in this study, as it seeks to develop a theory through comparative methods, which means looking at the same event or process in different settings or situations (Collis & Hussey, 2014). Moreover, it is seen as a method that complements other approaches of qualitative data analysis instead of standing against them (Charmaz, 2006). The grounded theory further allowed the data to be collected, analyzed, and interpreted on a joint and collective base through a systematic procurement (Collis & Hussey, 2014).

Using the grounded theory starts with gathering data, linking sequences to the process at large, and ends by reviewing, reflecting, and analyzing the entire process (Charmaz, 2006). Applying Charmaz’s (2006) grounded theory to the data analysis (discussed more in section 3.2.4 Data Analysis) provided the possibility to write and analyze the process whenever ideas or themes occurred. It further enabled the researchers to gain a variety of constructions and definitions of the situation under study. The analysis from the grounded theory allowed generality to emerge, and not for the study, based on its conceptual analysis where one studies patterns of relationships (Charmaz, 2006). As Grounded Theory was emphasized in this research, the authors gained rich data, which was thereafter analyzed to understand the particularities and details of the context under investigation.

3.2 Method

3.2.1 Primary Data Collection

Primary data can be defined as the process where the researchers gather new data from primary sources of information such as interviews, observations, or focus groups (Collis & Hussey, 2014). Aligned with inductive reasoning, the empirical findings for this study were gathered through interviews with business developers since it allowed the generation of in-depth insights and understandings of exploratory data (Saunders et al., 2016). Conducting qualitative interviews further enabled a collection of information that captured meaning and interpretation of the phenomena in relation to the business developer’s world views (Easterby-Smith et al., 2018).

3.2.3 Primary Data Selection Process

The preparation for data collection through interviews is to develop a sampling strategy for the potential research participants and methods for data collection (Easterby-Smith et al., 2018). Snowball sampling was seen as the most suitable sampling method since it allowed to interview participants who had specific expertise and strong experience within the phenomena under study (Collis & Hussey, 2014), in this case, BMI, Digitalization and/or SMEs. Twelve interviews were scheduled with business developers who obtained the above-mentioned qualities, but only ten interviews were conducted as two were canceled due to the participants’ personal circumstances. To gain insights from a variety of industries, the business developers were currently working within different industries. Realized from the interviews, the range of SMEs the business developers worked with varied between 1-20 SMEs per month. To account for the ethical considerations concerning the participants’ anonymity and confidentiality, their gender, specific industries, and the number of SMEs they work with have not been presented (explained more in detail in section 3.3 Research Quality and Trustworthiness).

The researchers targeted both young and well-experienced business developers, as they contributed with diverse perspectives to the research. While a business developer who has spent many years in the profession provided the research with great insights due to his/her experience, it also hindered the ability to obtain novel insights. Therefore, business developers with fewer years of experience were also targeted as it enabled the obtainment of new perspectives. Interviewing business developers was also a result of the challenge of reaching

SMEs with the ability to provide valuable insights. Furthermore, the sampling method allowed the authors to ask the participants for recommendations of other business developers to interview (Collis & Hussey, 2014), which was favorable for this research as finding people with the right expertise was challenging. The interview length varied between the participants, thus, between 35:00-1:10:00 minutes with an average of 43 minutes. More specifics about the interviewees are presented in the table below.

3.2.2 Interview Construction

Interviews under an interpretive study will explore the understanding of opinions, experiences, and attitudes towards a topic (Saunders et al., 2016), in this research, SMEs’ business model innovation due to the acceleration of digitalization. The goal of the interviews was to gather rich data from the participants to, later on, be analyzed, contextualized and reported (Saunders et al., 2016). Therefore, semi-structured interviews with open-ended questions (Appendix C) were the most suitable for this research since it allowed the respondents to think and reflect in-depth, which led to longer and more developed answers (Collis & Hussey, 2014). It also allowed a discussion to take place that provided data relevance for the study that was not asked for (Saunders et al., 2016). Some of the interview questions were prepared in advance, and the

fields of BMI, Digitalization, and SMEs. The main idea with the prepared questions was to encourage the respondents to talk about the main topics and areas of interest for this study and later develop other questions during the interview. The order of the questions was flexible, which allowed the interviewee to choose the order that best fits each participant and their previous answers (Collis & Hussey, 2014).

To ensure that the interview questions were of good quality, formulated in a manner that was easily understood, and inspiring the respondents to answer them, pilot tests were conducted. The questions were tested on five persons that were not participating in the research nor had any connection with the research. According to Collis and Hussey (2014), rich communication channels are preferred when conducting interviews. These include face-to-face personal communication or using electronic communication, for example, through Skype. The latter was used as the communication tool in this research since the current pandemic did not allow for the interviews to occur face-to-face. However, communication through the internet or channels can affect the interpretation of the answers due to that the interviewee cannot see body language the same way one would have done in person. Although, this technique may provide flexibility concerning both time and geographical location (Collis & Hussey, 2014). Furthermore, the interviews were audio-recorded, and the researchers took additional notes to ensure that no important data was lost. Another consideration that was taken into account concerns the interview language. The interviews were conducted in Swedish, as this was the participant’s and the researcher’s native language. If speaking a second language, difficulties in expressing oneself can arise (Easterby-Smith et al., 2018), therefore, conducting the interviews in Swedish allowed the interviewees to speak without such restrictions or difficulties.

3.2.4 Data Analysis

Following Charmaz’s (2006) Grounded Theory, when analyzing the data, coding is the process of categorizing and defining the data along with naming the segment of the data piece. It further creates a link between the data collection, which aims to develop a theory that explains the empirical data, thus moving from the specific to the general. A researcher defines the data to try to understand its means. Aligned with Charmaz’s (2006) approach, the coding of this study took two forms, initial coding and focused coding. Compared to quantitative coding, qualitative coding through the grounded theory allowed for own created codes, defined from the collected

data. The codes, later on, emerged as one scrutinized and defined the meaning of the data in the researchers’ own words (Charmaz, 2006).

3.2.4.1 Initial Coding

Initial coding emphasized naming words, lines, and segments while keeping an open view when exploring the data to discover whatever theoretical opportunities the data might contain. This coding phase works closely with the data and tries to discover whatever theoretical opportunities the data might contain instead of finding pre-existing categories (Charmaz, 2006). Within this study, the initial codes were derived from the additional notes conducted during the interviews. Charmaz (2006) argued for this process as beneficial as it eliminates clusters and only advocates the most important codes. This process further accounted for objectivity, a wide view, and transparency of the participants' answers (Charmaz, 2006). Additionally, the initial coding allowed the researchers to realize lacking data and gaps throughout the coding process. By staying open, working close to the data, keeping it simple and precise, constructing short codes, and continually quickly comparing (Charmaz, 2006), the researchers were allowed to realize initial codes from the empirical data.

3.2.4.2 Focused Coding

From Charmaz’s (2006) grounded theory, the focused coding process acted upon the data rather than simply reading it. During the focused coding phase, codes were more selective and directed to synthesize and explain a large amount of data. Through these actions, new threads and patterns emerged where the researchers moved across interviews, actions, and experiences to compare the empirical data. The researchers derived the focused codes from the initial codes by coding the full transcript interviews, this provided a deeper understanding. As the grounded theory coding process is flexible, it allowed the authors to go forth and back when analyzing the empirical data (Charmaz, 2006). Furthermore, through the process of memo-writing the derived codes, categories were able to be created. Through memo-writing, one can stop and directly analyze codes whenever needed, as the categorizing and writing process allows to continuously analyze “data and data, data and codes, codes of data and other codes, codes and category, and category and concept” (Charmaz, 2006, p.72). Constructing the data analysis can be done in the manner that suits the specific research best. Therefore, the researchers constructed this study's findings and analysis section as one, as it allowed for advanced thinking and analyzing (Charmaz, 2006).

3.3 Research Quality and Trustworthiness

When conducting research, research quality should be considered to present the research as trustworthy. It can be achieved by presenting a systematic, rigorous, and clearly defined method, methodology, data collection, and data analysis (Collis & Hussey, 2014). Moreover, Lincoln and Guba (1985) presented four criteria that can be considered to account for research quality, these include Credibility, Transferability, Dependability, and Confirmability. These criteria have been taken into account in this research and are described in further detail in the following sections.

3.3.1 Credibility

Credibility “allows others to recognize the experiences contained within the study through the interpretation of the participants’ experience” (Thomas & Magilvy, 2011). Hence, describing the research topic in a correct manner (Saunders et al., 2016). To increase the credibility, the researchers should be present and involved, use triangulation of both sources and data collection (Collis & Hussey, 2014), and examine and review the participants’ individuals’ transcripts to search for similarities (Thomas & Magilvy, 2011). Thus, it improves the process of identifying and describing the participants' experiences in an accurate manner (Thomas & Magilvy, 2011). To improve the credibility of this study, the above-mentioned tools were applied, both authors were equally participating, and triangulation was emphasized throughout the entire process. Additionally, the use of transcripted interviews with direct quotes and words has been presented (Appendix D).

3.3.2 Transferability

Transferability is defined as the possibility to apply the results and findings of a study to other scenarios within the same topic, hence, creating a generalization (Collis & Hussey, 2014). As this is qualitative research with a relatively small sample frame, generalizing the results was not the ultimate goal, rather transferring the results (Shenton, 2004). Subsequently, this research is considered to have low generalization, but other means were emphasized to account for transferability. This study applied a complete and detailed description of the research question, method, sampling process, findings, and results (Saunders et al., 2016). Additionally, a clear description of the study's geographic and demographic boundaries and data collection (Thomas & Magilvy, 2011) increased this study’s transferability.

3.3.3 Dependability

Dependability is the process when one researcher can follow what another researcher has conducted (Thomas & Magilvy, 2011). Hence, how accurate and well documented the research process is (Collis & Hussey, 2014). To establish strong dependability, strategies including peer participants, describing the methods in detail (Thomas & Magilvy, 2011), coding, audio recordings, and triangulation (Collis & Hussey, 2014) can be applied. The researchers of this study have emphasized a detailed description of the entire construction and collection of both research and method, along with audio recording the interviews and taking notes during the interviews. This process reduced the risk of losing data that could be important. Lastly, transcriptions and coding of the interviews were conducted individually between the two authors, which was, later on, reviewed and compared to increase the dependability of this study.

3.3.4 Confirmability

Confirmability is defined as the degree of how well the research process is described and the possibility to assess how the findings flow from the data (Collis & Hussey, 2014). To increase confirmability, the researcher should “follow” rather than “lead” the interviews by asking for clarifications and documenting all feelings, biases, and insights through recordings. This provides a sense of trust for the reader and improves the quality (Thomas & Magilvy, 2011). In this research, confirmability was established by open-ended interview questions, audio recording, documenting the interviews with additional notes along a detailed coding process (described in section 4.1 Construction of Findings and Analysis). The documentations were reviewed and analyzed multiple times by both authors, which ensured confirmability and trust of the research and its empirical data. Moreover, by applying direct quotes and keywords from the interviews, the flow of the findings connected to the empirical data was shown, and conformability was increased. As the interviews were conducted in the participants’ native language (Swedish), the quotes used in this research are presented both in Swedish and English (Appendix D) to account for both trustworthiness and quality of its information.

3.3.5 Ethical Considerations

Collis and Hussey (2014) defined ethics as moral values or principles which set the basis for a code of conduct. Several guidelines can be applied to research to account for ethical considerations, including informed consent, privacy, confidentiality, anonymity, and voluntary

interviewees were contacted, the topic of the study and their role in the research was explained to present transparency and honesty of the research. When agreeing to participate, a document including the interview questions, the background of the study, and important definitions was sent to the participants. This further accounts for transparency and voluntary participation, two of the most important principles of research ethics (Collis & Hussey, 2014). Before the interviews, the participants’ consent was asked for along with sending a consent form after the finished interview (Appendix B). Anonymity (ensuring the participants not to be named in the study) and confidentiality (ensuring the participants that their provided information will not be traceable back to them) increases the process of gathering trustworthy empirical data and is of high importance in research to be ethical (Collis & Hussey, 2014). By naming the participants BD1-BD10 and not specifying gender or what specific industry they operate in, anonymity and confidentiality have been answered. Furthermore, the collected data was aligned with the European General Data Protection Regulation (REG. 2016/679), which was sent to the participants before the interviews took place and explained once again before the interview started. Among other things, this ensured anonymity and confidentiality, as the data was stored and protected on devices not accessible by other than the researchers or people with authorization.

4. Empirical findings & Analysis

In this section, the empirical findings and analysis are presented. Firstly, a brief description of the construction of the section and how the data analysis has been conducted is presented. In the following subsections, the empirical findings are presented, analyzed, and compared to the literature review. This is presented in categories following the themes retrieved by the coding process. The quotes are presented in italics where three dots in a parenthesis explain that repeating words or sentences irrelevant to the sentence’s overall meaning have been removed.

4.1 Construction of Findings & Analysis

As discussed under section 3.2.5 Data Analysis, this study has emphasized Charmaz’s (2006) constructivist grounded theory when coding the empirical findings and conducting the data analysis. Thus, initial coding and focused coding have been used to draw themes and categories from the empirical data to define the data and understand what it means (Charmaz, 2006).

Seen in the table below, 58 initial codes were found from the empirical data through an open perspective when searching for lines, words, and segments (Charmaz, 2006). Seven focused codes were derived from the initial codes through a more direct and selective approach (Charmaz, 2006). The focused codes led to the creation of three theoretical categories, which set the basis of the findings and analysis sections. The categories were identified and clustered based on the codes’ similarities as well as their relationships to each other through the process of writing memo notes. Since the interviews were conducted in the participants’ native language (Swedish), all quotes have been translated from Swedish to English. To show how the findings flow from the empirical data and account for the empirical findings' trustworthiness, quotes in both languages are presented in Appendix D.

4.2 Background

Realized from the literature review, SMEs are the backbone and heart of economic growth and development, along with their great importance for the national economy (Chonsawat & Sopadang, 2020) and society (North et al., 2019). This aligned with BD7’s statement below:

"The awareness that we must have SMEs with us in various ways has increased, which is a consequence of Covid-19, but an effect rather than a direct impact" (BD7)

Thus, one can argue that SMEs play a significant role in the Swedish economy and society but have become even more important due to Covid-19. However, this applies to the specific context investigated in this research and may not be generalizable to the entire SME industry. A business developer’s job is to guide, coach, and develop established and/or start-up firms in the development of their organizations (BD1-BD10). What is evident from all interview participants is that Covid-19 has had an impact on SMEs, however, the effect varies between

industries. This also holds true for SMEs’ relation to the acceleration of digitalization and business model innovation. Worth noticing is that while most participants have had great insights into SMEs in general, some have only provided insights into the specific industry they operate in.

“[...] they get in touch with us and for instance need help to survive tomorrow, while other industries are for example doing better than ever, and there are new businesses, and internationalization, it is innovations, and there are of course those industries and companies which have clearly been positively affected of the pandemic” (BD2)

BD2, BD4, and BD8-BD10 stated that an industry that has been tremendously vulnerable and realized more significant challenges to the effects of the pandemic is the restaurant, hotel, entertainment, and event industry (from this point onwards, the cluster of these specific industries will be referred to as the hospitality industry). One reason for this may be that these industries highly depend on social interactions and the experience itself rather than a physical product. On the other hand, examples of industries that have managed the pandemic better are the home-entertainment industry (BD5 & BD6), the software industry (BD9), and the production and industrial industry (BD8). As stated by BD5, BD6, BD8, and BD9, this is because the pandemic has not led to any significant changes in these industries’ work environment compared to the hospitality industry.

When asked if and how the pandemic had changed work practices, all business developers (BD1-BD10) stated that it has transformed from a physical environment to a digital environment.

"It has gone over to completely digital, from having previously run the business on-site, where everyone sat in premises in the offices, then there was a physical environment, now it does not exist at all" (BD6)

For instance, all meetings are now conducted through digital tools and with the use of digital technologies (BD1-BD10). BD3 and BD5-BD7 argued for the severe impact the pandemic has had on work assignments, and one is now forced to work on a digital platform. These findings support previous literature to some extent as it implies that the work environment and work

Windelband (2020) and Calabrese et al. (2020) argued that it is Industry 4.0 that drives this transformation and connects humans and technology within work content, the empirical findings rather suggest that this transformation is due to Covid-19. Nevertheless, Spöttl and Windelband (2020), Calabrese et al. (2020), and the empirical findings can all be connected to Davidsson et al. (2016), who defined the fourth wave of digitalization as a broader context than only digital communication.

4.3 The Acceleration of Digitalization

Garzella et al. (2020) pointed out that MNCs have an easier time adapting to digitalization than SMEs, however, this perspective was not presented during the interviews. A reason for this may be that the participants were specialized in SMEs and did not have good enough expertise in the field of MNCs to make this comparison. When discussing whether Covid-19 has led to an acceleration of digitalization for SMEs, participants BD1-BD4 and BD8-BD10 argued that it had. BD8 argued that one area that has been affected by the pandemic is that businesses' external approach has transformed to a more digital one, for instance, the use of digital technologies to communicate with customers. We believe that this can be aligned with the reasoning made by Klein and Todesco (2021), who described that the pandemic has brought an increase in digital transformation, and van Tonder et al. (2020), who explained the third wave of digitalization as the use of digital communication tools.

“Something that one can see on a broad front that all industries have, have really accelerated their digitalization, due to the pandemic” (BD2)

"I think it has definitely accelerated a lot” (BD9)

On the contrary, BD5, alongside BD6, had not realized any acceleration of digitalization within their specific industries, which was already well developed in using computers and digital technologies. However, the participants could not provide any insights on the general perspective of SMEs. Thus, one can conclude that Garzella et al.’s (2020) argument applies to those used to operating in a digital environment and using digital technologies have had an easier adaptation to the acceleration of digitalization due to the pandemic (BD4-BD6). The empirical findings extend Garzella et al.’s (2020) argument but also provide an industry-specific perspective.

Due to the acceleration of digitalization and Covid-19, several participants (BD2-BD5, BD9 & BD10) agreed that Covid-19 has created a new awareness and sense of the digital environment. Thus, SMEs are today more aware of both the need and requirement to change their operations. BD2 argued that one does not have to convince SMEs that they need to adapt to digitalization and to consider a digital customer journey, as was required before the pandemic. BD3 reasoned that many businesses have been forced to quickly change their work processes and increase or develop the use of technologies and tools to develop one’s products and services to become more digital. The interviewees’ presented the following views of how the acceleration of digitalization due to pandemic has affected SMEs:

“It is definitely the case that awareness of what digital tools are available is incredibly much higher now than a year ago" (BD9)

“[...] one will have an awareness for a long time to come as well, one will change its preparedness and the need to be innovative and quick-footed, rethink and to think new” (BD4)

“New things that have happened during the pandemic, it is just trends that were realized before, but in some way, has got anabolic steroids now during the pandemic and has forced them to really, to, one cannot hide from it anymore” [...] “Everyone has had to adapt to digital marketing, that has been really clear” (BD2)

Based on the statements above, we concluded that the pandemic has increased the awareness of digitalization and that this awareness may not be temporary and instead continue for a long time to come. Hence, it strengthens the argument of how important it is for companies to adapt to the digital environment. An insight presented by BD1, who was alone with this reasoning, concerned SMEs and the reason for their acceleration of using digital technologies. BD1 stated the following:

“[...] when we see that more tries, and when others implement something [...] there is a group behavior, more businesses dare to take this step [...] SMEs follow what other businesses do [...] those early adopters have disappeared” (BD1)

The statement by BD1 was, to some extent, aligned with BD3s’ reasoning, as BD3 pointed out that all SMEs have to be early adopters now. One can question if the choice of being an early adopter has disappeared since SMEs are now forced to adapt and change (North et al., 2019). Therefore, SMEs are currently in the position of being the first at something, hence, an early adopter.

4.3.1 Digital Maturity

BD2, BD3, BD7, and BD10 argued that SMEs generally have a low understanding and knowledge of digitalization. BD8 highlighted that the industrial industry has quite low digital maturity, and BD9 provided an example of subcontractors. BD2 stated that some SMEs had implemented digitalization in their operations prior to Covid-19, for example, internal operations such as working on digital platforms instead of using real papers but not to any further extent. BD10 stated that SMEs adaptation to digitalization depends on their maturity stage but highlighted the external side:

“[...] in general then I think that many companies are far too bad at being seen and marketing oneself and to take control of their brand digitally” (BD10)

The above reasonings are aligned with OECD (2020) and Eller et al. (2020), who argued for SMEs' low level of digitalization. However, BD5, BD6, BD8, and BD10 argued for this knowledge to be industry-specific, where some industries are better equipped than others to the adaptation of digitalization. However, this reasoning was not realized from the existing literature.

According to BD8 and BD10, SMEs specialized in the Business-to-Business (B2B) sector have a lower digital maturity and knowledge in digitalization compared to Business-to-Customer (B2C). One can argue for this to be aligned with the reasoning made by BD9, who mentioned that subcontracts to other businesses lack more digital knowledge than businesses who are working directly towards their customers. Furthermore, BD2 claimed that the B2C sector, including a digital customer relationship and digital business, was lagging more behind before the pandemic. BD9 further argued that the hospitality industry does not have the same digital knowledge as other industries since they have limited IT competencies and their value creation is based on creating experiences in reality. While these findings provide examples of the