A Digital Capabilities Dataset From Small- and Medium-Sized Enterprises in the Basque Country (Spain)

Abstract

Sustainable competitiveness and growth of small- and medium-sized enterprises (SMEs) are increasingly determined by their capability to make use of digital technologies [EU (European Commission), 2018b] and tie into a digital ecosystem (Pelletier and Cloutier, 2019). Surveys (Tarutea and Gatautis, 2014; Bouwman et al., 2019; Shettima and Sharma, 2020) prove that the digitalization has a positive effect on the performance of SMEs. This includes dimensions such as growth, market value, and profitability as well as social and environmental performance and satisfaction; 46% of firms that participated in a survey of the European Digital Transformation Scoreboard report a medium-to-large increase in their annual turnover over the last 3 years following the adoption of technology [EU (European Commission), 2018a]. Many SMEs, however, are lagging behind in digital transition (OECD, 2017). According to a report by the Digital Innovation Hubs Working Group (2018), only 17% of SMEs have successfully integrated digital technologies into their businesses, compared with 54% of large companies. They lack resources and capabilities or suffer from inertia, which hampers opportunities (Cenamora et al., 2019). In the emerging highly interconnected and collaborative forms of value creation, the capacity to connect better to an integrated business network will be important to stay competitive (Rehm and Goel, 2017; EU (European Commission), 2014). SMEs comprise three different categories of enterprises, namely, micro-enterprises, small enterprises, and medium-sized enterprises (see Table 1). To classify firms, the official European definition of SMEs considers three different factors: level of employment, level of turnover, and size of balance sheet. Table 1. Definition of SMEs. According to the EU (European Commission) (2018b) overall, in 2017, SMEs in the EU accounted for 99.8% of all EU-28 nonfinancial business sector enterprises, two–thirds of total EU-28 employment (66.4%), and slightly less than three–fifths (56.8%) of the value added generated by the nonfinancial business sector. Micro-SMEs are by far the most common type of SME, accounting for 93.1% of all enterprises. SMEs are a highly diverse group of enterprises that also condition how they approach digitalization (OECD/UN ECLAC, 2012; Neirotti et al., 2018). For example, approaches differ in case of Industry 4.0 adoption (Matt and Rauch, 2020) or the integration in platform ecologies (Gierlich-Joas et al., 2019). A common denominator, however, is the need to integrate, build, and reconfigure internal and external resources in order to adapt to rapidly changing environments (North and Varvakis, 2016). These dynamic capabilities take the form of skills, processes, procedures, organizational structures, and decisions that motivate and promote the detection (sensing) and capture (seizing) of opportunities in order to reconfigure (transform) their capabilities (Teece, 2007). As several studies show, the development of dynamic capabilities impacts SME performance and growth (He and Wong, 2004; Lubatkin et al., 2006; Macpherson and Holt, 2007; Protogerou et al., 2008; Sunday and Vera, 2018) and is vital for implementing Industry 4.0 approaches (Garbellano and Da Veiga, 2019) and digitalization (Matarazzo et al., 2021). However, currently, there is a limited understanding of how SMEs are approaching digitalization from a dynamic capabilities perspective. Garzoni et al. (2020) introduce a four-level approach of engagement of SMEs in the adoption of digital technologies, namely, digital awareness, digital enquirement, digital collaboration, and digital transformation, hence the need to map adoption and learning paths of these firms. For this mapping, digital maturity models or frameworks can provide guidance (Valdez de Leon, 2016, Williams et al., 2019). The DIGROW digital maturity framework (North et al., 2020) is grounded on the microfoundations of dynamic capabilities (Teece, 2007) and therefore allows to link digitalization to organizational capabilities. Based on this framework, a questionnaire has been built and applied to a sample of 380 SMEs from the Basque region (Spain). In the following section, we describe the framework, the structure of the questionnaire, the data collection process, and the content of the database built as a result of this process. The DIGROW framework of digital maturity (North et al., 2020) aims at companies to assess their digital maturity level, and the capabilities associated with each level of maturity, which could support their digitally enabled growth. The framework is grounded in dynamic capabilities theory. In the explanation of microfoundations of dynamic capabilities, Teece (2007) described his constituent capacities: “For analytical purposes, dynamic capabilities can be disaggregated into the capacity (1) to sense and shape opportunities and threats, (2) to seize opportunities, and (3) to maintain competitiveness through enhancing, combining, protecting and, when necessary, reconfiguring the business enterprise's intangible and tangible assets” (Teece, 2007: 1319). Pavlou and El Sawy (2011), based on their empirical research, proposed four steps of dynamic capabilities development—sensing, learning, integration, and coordination—thus highlighting the importance of managing knowledge and learning to cope with turbulent and disruptive environments (North and Varvakis, 2016). A particular shortcoming in SMEs is that owners and managers are aware of growth potentials; however, they tend to lack an explicit strategy, and if they have one, they do not communicate that strategy to employees (North et al., 2016). Therefore, in the DIGROW framework, an intermediate step is inserted between Teece's “sensing” and “seizing,” the step of strategy development and communication, which is related to Pavlou and El Sawy's (2011) learning and integration. Thus, the...