Digitalization and Resource Mobilization

Digitalization

The studies in Table 1 have exploited digitalization in at least five different ways, which we describe with specific examples in more detail below.

Resources

The concept of resources is central to various theories across different fields, each with a distinct perspective on what constitutes a resource. For example, probably most influential in the management and strategy literature is the resource-based view (RBV) of the firm. Resources, as a general term, are ‘all assets, capabilities, organizational processes, firm attributes, information, knowledge, etc. controlled by a firm that enable the firm to conceive of and implement strategies that improve its efficiency and effectiveness’ (Barney, 1991: 101; emphasis added). However, the RBV particularly emphasizes ‘strategic’ resources or valuable, rare, inimitable and non-substitutable (VRIN) resources that firms possess and enable them to achieve competitive advantage (Barney, 1991; Crook et al., 2008). Resources such as reputation, patents and unique knowledge have been identified in the literature as possible strategic resources (e.g. Barney and Arikan, 2005).

Alternatively, in social capital theory, the firm's external networks are expected to play a key role in its performance (e.g. Burt, 1992; Granovetter, 1985). Social capital represents ‘the set of resources, tangible or virtual, that accrue to a corporate player through the player's social relationships, facilitating the attainment of goals’ (Gabbay and Leenders, 1999: 3). Thus, social capital theory stresses the relational characteristics with external entities as the root for value creation (Lee, Lee and Pennings, 2001). The ability to mobilize resources, attract customers and identify entrepreneurial opportunities is conditional on external networks, as social relations mediate economic transactions and provide organizational legitimacy (Granovetter, 1985; Lee, Lee and Pennings, 2001). Relatedly, in agency theory, the third type of agency problem deals with the conflict of interests between shareholders and stakeholders. This conflict can influence resource allocations and give rise to agency problems with various stakeholders such as governments, employees or debtholders (Savio et al., 2024).

In HRM, resources are again conceptualized somewhat differently. The focus is on people here, also referred to as human resources, human capital or social capital, which are viewed as integral to an organization's capability and competitive advantage. HRM practices are seen as instrumental in deploying, developing and building these resources for organizational performance. Several theoretical models propose how HRM practices lead to organizational performance, arguing for an alignment between the business strategy and HRM systems in order to achieve organizational goals (e.g. Becker and Gerhat, 1996; Delery and Roumpi, 2017; Huselid, 1995). The RBV of an organization (Barney, 1991; Barney, Wright and Ketchen, 2001) has been particularly influential here, especially in the field of strategic HRM (e.g. Gerhart and Feng, 2021; Shaw, 2021), where approaches suggest that rather than focusing on individual best practices, HRM systems (i.e. combinations of HR practices) that are aligned with the business strategy are harder to imitate by competitors (Becker and Gerhat, 1996). At the heart of human capital are knowledge and skills (e.g. Crook et al., 2011), which also play a central role in digitalization in organizations as people adapt to new processes, products and operations. Empirical evidence supports the RBV, showing that human capital is a key predictor of firm performance (e.g. see the meta-analytic review of Crook et al., 2011).

In their review of the literature on how entrepreneurs mobilize resources, Clough et al. (2019: 243) noted that ‘disproportionate attention is paid to financial capital as an outcome variable compared with other forms of capital’. In Table 1, we see a somewhat broader focus in the literature on digitalization and resource mobilization. However, this broader focus is generally observed in conceptual articles only. We also observe that empirical studies generally conceptualize resources more narrowly, as financial resources or human resources, most likely driven by data considerations.

Crowdfunding research

Crowdfunding research has shown tremendous growth in fields such as management, entrepreneurship and, to a somewhat lesser degree, finance (Vismara, 2022). Crowdfunding is an umbrella term that captures different forms of crowdfunding (e.g. Ahlers et al., 2015; Mollick, 2014): donation crowdfunding, where the crowd simply donates funds; rewards-based crowdfunding, where the crowd provides funds in expectation of a reward such as an often personalized product or service; lending-based crowdfunding, where the crowd provides funds in return for the future repayment of the principal amount and interests; and equity-based crowdfunding, where the crowd provides funds in return for equity or equity-like claims.

Consistent with Approaches 1 and 2 to digitalization, extant crowdfunding research has primarily focused on the multitude of factors that relate to fundraising success on crowdfunding platforms (e.g. Ahlers et al., 2015; Allison et al., 2015, 2017, 2022; Kleinert, Volkmann and Grünhagen, 2020; Piva and Rossi-Lamastra, 2018; Rossi, Vanacker and Vismara, 2021; Vismara, 2016) and the funding dynamics as firms are listed on crowdfunding platforms (e.g. Burtch, Ghose and Wattal, 2016; Cong and Xiao, 2024; Cumming et al., 2022; Hornuf and Schwienbacher, 2018; Kuppuswamy and Bayus, 2017; Vismara, 2018). For example, Ahlers et al. examine how human capital, social capital and intellectual capital, uncertainty and equity retention influence fundraising success in equity crowdfunding. Another stream of crowdfunding work has also pointed out that raising money on crowdfunding platforms only represents the beginning (e.g. Mollick and Kuppuswamy, 2014; Signori and Vismara, 2018). Once the money is raised, entrepreneurs still need to develop viable firms that grow and perform. Research has made progress in understanding what happens to firms after successful crowdfunding campaigns in terms of follow-on fundraising, firm survival, performance and innovation (e.g. Blaseg, Cumming and Koetter, 2021; Coakley, Lazos and Liñares-Zegarra, 2022; Hornuf, Schmitt and Stenzhorn, 2018; Signori and Vismara, 2018; Walthoff-Borm, Vanacker and Collewaert, 2018a).

Our framework of the multiple ways in which digitalization has been employed by researchers suggests important avenues forward for crowdfunding research. More specifically, we highlight three key issues and examples.

First, it is relatively easy to observe the firms that raised crowdfunding, venture capital and, to a lesser degree, business angel funding – these firms are usually covered in large-scale commercial databases, such as CrunchBase (e.g. Rossi, Vanacker and Vismara, 2021) or ThomsonOne (e.g. Dutta and Folta, 2016). However, consistent with Approach 3 on digitalization, the crowdfunding context has made visible a set of firms that generally remained invisible. In particular, researchers can now observe entrepreneurs who tried to raise money on crowdfunding platforms but failed to do so. This set of entrepreneurs is generally not visible in private (non-digital) financing markets, such as the angel or venture capital markets (Block et al., 2021). Rather surprisingly then, only a limited set of studies have examined what happens to the entrepreneurs who were unsuccessful in raising funds (e.g. Piening et al., 2021; Rossi, Vanacker and Vismara, 2023; Stevenson, Allen and Wang, 2022). While much research in entrepreneurial finance has focused on the intersection between demand and supply for financing (the financing obtained), crowdfunding represents a unique opportunity for scholars to present novel insights into the demand for entrepreneurial finance (e.g. Walthoff-Borm, Schwienbacher and Vanacker, 2018b).

Second, by focusing on what happens to firms on crowdfunding platforms, much less attention has been paid to the impact of the digital aspect of crowdfunding on resource mobilization. To provide a specific example, research by Kleinert, Volkmann and Grünhagen (2020) focuses on how signalling theory can serve as a useful framework to understand why prior financing and related third-party signals positively affect campaign success on crowdfunding platforms. While this represents an important insight, third-party signals might equally influence other types of investors and have similar effects in non-digital contexts, such as venture capital markets, public markets and inter-organizational collaborations (e.g. Ozmel, Reuer and Gulati, 2013; Plummer, Allison and Connelly, 2016; Stuart, Hoang and Hybels, 1999). Thus, consistent with Approach 4 on digitalization, an important question remains of whether signals are more or less effective for fundraising in crowdfunding markets versus different (non-digital) markets. It provides an opportunity to examine how and what aspects of the digital context influence the boundary conditions of signalling theory.

Third, the fact that there are so few scams being found and funded on crowdfunding platforms represents an anomaly for many theories on informational asymmetry and governance in financial markets. Early on, practitioners also had very doubtful views: in the United States, state security regulators put the relatively new investment phenomenon of crowdfunding at the top of their annual investment scams list, arguing that the push of ‘crowdfunding … to a true investment model, … will make it even more of a lure for swindlers’.1 Consistent with Approach 5 on digitalization, such an anomaly presents a challenge to existing theoretical frameworks and suggests a need for novel frameworks adapted to the crowdfunding (and, more broadly, digital) context. Some studies have pointed towards ‘wisdom of crowd’ effects (Mollick and Nanda, 2016; Vismara, 2018). Others have presented conceptual ideas on how governance models might work differently in crowdfunding markets to reduce adverse selection and moral hazard issues (Cumming, Vanacker and Zahra, 2021b). Still others have argued that many past theories on information scarcity require adjustment in a new digital world with informational abundance (Dushnitsky and Matusik, 2019). However, there is still a dearth of research on these issues within the crowdfunding literature.

Moreover, our focus on the broad definition of what resources and resource mobilization constitute in different theories and fields also presents opportunities. We highlight two in particular.

First, much of crowdfunding research has focused on fundraising success, thereby focusing on financial resource mobilization. This focus is logical but also somewhat surprising, because some scholars have argued that fundraising in crowdfunding is accompanied by extra-financial resources, including market feedback, referrals, prospective customer lists and social promotions (e.g. Stevenson, Allen and Wang, 2022). For example, one could wonder how important these extra-financial resources are. Once controlling for selection and the money raised, do these extra-financial resources influence the strategies, growth or performance of crowdfunded firms? Moreover, while successful crowdfunding campaigns entail an inflow of money, can the quality of the extra-financial resources vary? What drives the quality of these extra-financial resources? Is it linked to the pre-existing social capital of entrepreneurs? If yes, this could have important ramifications for the democratization potential of crowdfunding (Butticè and Vismara, 2022; Cumming, Meoli and Vismara, 2021a; Fisch, Meoli and Vismara, 2022).

Second, much of crowdfunding research has focused on the ability of firms to access financial resources (and the amount of financial resources raised, often relative to a target amount). However, resource mobilization covers multiple dimensions next to resource access, such as search and governance (Clough et al., 2019). Much less research has focused on the question of why some entrepreneurs search for crowdfunding while others do not. Walthoff-Borm, Schwienbacher and Vanacker (2018b), for example, show that entrepreneurs with limited (or no) internal funds and additional debt capacity are more likely to search for equity crowdfunding. Why do entrepreneurs search for different types of crowdfunding? And, once they decide on the type of crowdfunding, how do they select a specific crowdfunding platform (e.g. Coakley and Lazos, 2021)? Moreover, not all crowdfunding is the same, and even within a category, there are important differences (e.g. equity crowdfunding can be very different on one platform vs. another). For example, Cumming, Meoli and Vismara (2019) have examined the value of dual-class equity crowdfunding as a digital governance model. Others have examined the impact of nominee versus direct shareholder structures on firm survival, innovation and performance (Walthoff-Borm, Vanacker and Collewaert, 2018a). While scholars have skimmed the surface of search and governance issues linked to crowdfunding, these issues have received much less attention than warranted.

Research in human resource management

Digitalization has several implications for resource mobilization in HRM, and research in this area is still emergent, as reflected in our literature review. Our framework of multiple ways in which digitalization has been considered by scholars also points to important areas for future research in HRM, which we highlight below.

First, digitalization affects the deployment, development and retention of resources (people) in organizations. These are core responsibilities of HRM and from the RBV (Barney, 1991; Barney et al., 2001), for organizations to achieve competitive advantage, their resources need to be valuable, rare and not easy to imitate and substitute. Digitalization processes in organizations typically require new knowledge and skills, which need to be continuously and often rapidly updated. The importance of knowledge and skills in organizations, as emphasized by the RBV (Barney, 1991), is of course not new, but has become more pressing in the context of digitalization. As specific knowledge dates quickly, transferrable skills and competencies, which are behaviours that are instrumental in the delivery of performance goals (Bartram, 2005; Bartram, Robertson and Callinan, 2002) – such as adapting to new tasks and responsibilities and being motivated and motivating others to learn continuously and be open to technological change – are of importance.

As a consequence, knowledge transfer has become a key goal for organizations and government initiatives, which now try out less ‘traditional’ methods to achieve this goal. Examples include reverse mentoring, where younger workers mentor older ones (e.g. Kaše, Saksida and Mihelič, 2019), and creating new roles such as those of digital champions, by nurturing and further developing existing knowledge and skills within their own organization. The case study by D'Angelo, Ghezzi and Cavallo (2024) examines the mechanisms whereby resources in the form of digital skills are mobilized in organizations in the context of digital transformation, by searching, accessing and transferring these skills internally via the newly created formal middle-management role of digital champions. From the RBV (Barney, 1991), this case study provides insight into how combining new practices to unearth, develop and transfer digital skills creates a competitive advantage by increasing human capabilities to stay ahead and respond to digital transformation.

Research in the area of HRM also includes questions on how learning/the acquisition of digital skills in organizations can be supported formally and informally through managers, who play a central role in encouraging and enabling the development of their employees (e.g. Solberg et al., 2022), and moving away from static models of knowledge and skills, requiring models that emphasize dynamic capabilities in organizations (e.g. Do et al., 2022). Another under-researched area pertains to questions around digital inclusion and equality (e.g. Pekkala, 2022): for example, to what extent do employees in an organization have equal opportunities to access and further develop digital skills? Most of the studies relevant for HRM that we identified in our literature review adopted Approach 2, by focusing on digitalization as a context within which questions such as the above are being examined. The context is shaping research questions here, and there is an opportunity for more research to examine how digitalization as a research context can help address questions in HRM beyond digitalization. For example, what are the implications for the acquisition and development of skills and knowledge in organizations more generally? What are the wider theoretical implications?

A second line of research concerns questions around the digitalization of HRM practices and processes, such as gamified HRM systems to increase employee engagement (e.g. Silic et al., 2020), the use of digital networking platforms in recruitment (e.g. Lucas, Bellavitis and Park, 2023) and using generative AI such as ChatGPT to increase efficiency and alleviate workload demands in HRM processes (e.g. Aguinis, Beltran and Cope, 2024). There are many open questions and research opportunities in this area, especially as digitalization provides access to unique data, for example, data obtained from digital network platforms (Lucas, Bellavitis and Park, 2023), recruitment processes and training and development. Avenues for research also include Approach 1, examining how the digitalization of HRM practices and processes is relevant for issues in HRM more generally, or challenging theoretical assumptions and models (Approaches 4 and 5). For example, clarifying conceptual issues such as the link between employee experience and employee engagement (Malik et al., 2023), or questioning theoretical propositions as suggested by the HR architecture model (Keegan and Meijerink, 2023). This research to date also demonstrates that resource mobilization in the context of digitalization changes labour dynamics (e.g. Lucas, Bellavitis and Park, 2023) and how organizational boundaries are viewed (i.e. becoming more permeable), as external labour resources are valued differently (e.g. Keegan and Meijerink, 2023). Especially with the use of generative AI, ethical questions (e.g. Malik et al., 2023) need to be addressed in this context (Approaches 1, 2 and 5).

A third avenue of research concerns work design, employee attitudes and employee well-being. For example, Weststar and Dubois (2023) draw attention to the ‘human side of the equation’ (p. 773) in the context of servitization, which refers to a service model (Vandermerwe and Rada, 1988) that prioritizes customer motives and needs in the development of, for example, products (here, games). The results of their qualitative study show that game developers who work in a servitization context in the gaming industry report work intensification as ‘new and continuously changing job demands related to the customer must be attended to in shorter time periods and with reduced worker autonomy’ (Weststar and Dubois, 2023: 973). This study falls within Approach 3, where servitization is studied in the specific context of the fast-moving gaming industry. Digitalization impacts work design in several ways: for example, skills requirements, digitalized HRM practices (e.g. gamification) and changing job demands as outlined above, but also automation and augmentation of job tasks (e.g. Parent-Rocheleau and Parker, 2022; Parker and Grote, 2022; Raisch and Krakowski, 2021). These have implications for how we design jobs, also at the task level (Parker and Knight, 2023), the consideration of boundaries between work and non-work, which have become more permeable with the use of information communication technologies (Farivar et al., 2023; Schlachter et al., 2018), employee engagement (e.g. Malik et al., 2023) and well-being (e.g. Weststar and Dubois, 2023). Avenues for research include questions that fall within Approaches 1 and 2: examining questions on work design, work attitudes and well-being in the context of digitalization and beyond to help us answer questions in HRM of how better jobs can be created, employees can be retained and their well-being enhanced. Digitalization provides a wealth of data now that can be used for examining questions in this area (Approach 3) via data collected through HRM platforms but also well-being-related data (e.g. Wenzel and Van Quaquebeke, 2018). Research in this area might lead us to challenge, review and revise existing theoretical models (Approaches 4 and 5).