Jonas Soluk

Organizational change is crucial for family firms to survive and prosper in today’s complex business environment. However, organizational change is often impeded by the difficult trade-off between change and continuity. By providing insights into new ways of working during innovation collaborations, start-ups can help introduce change in family firms. Despite increasing scholarly attention, previous research has failed to explain the role of start-ups in organizational change in family firms and their interaction with internal actors. Based on data from six cases of family firms collaborating with start-ups (including 40 qualitative interviews), we distill the mechanisms that start-ups developed to interact with internal change agents and owning families to uncover opportunities for change, initiate new practices, and facilitate their implementation and dissemination within the family firm.

We use a sequential mixed methods approach to explore the relationship between long-term orientation (LTO), learning capabilities, and digital product innovation in firms with varying degrees of family influence. Although extant research has emphasized the relevance of digital innovation for long-term success, little is known about how firms can draw on LTO as a prevalent dominant logic and learning capabilities to create business value. More specifically, we find empirical evidence for a mediation effect with a positive association between LTO and learning capabilities on the one hand and learning capabilities and digital product innovation on the other. Surprisingly, and in contrast to our hypothesis, we find a negative moderating effect of family influence on the relationship between LTO and learning capabilities. To complement the large-scale statistical analysis and to explain the underlying mechanisms of this counterintuitive empirical result, we build on a qualitative investigation of family-influenced firms. Our qualitative findings suggest that the role of LTO and learning capabilities in the digital economy is more nuanced than previous literature suggests. Specifically, we reveal six impeding mechanisms that are associated with family influence. With these insights, we extend previous knowledge on digital product innovation, family influence, and learning as a crucial dynamic capability.

Trust plays a crucial role in interorganizational collaborations. However, barriers such as information asymmetry between prospective partners impede trust building, especially in asymmetric collaborations. Although trust and information asymmetry have been extensively studied, previous research has failed to provide insight into the mechanisms of trust transference and the circumstances under which information asymmetry is accepted and considered legitimate. This paper addresses these research gaps by drawing on data from 113 semi-structured interviews in a multiple-case study of eight intermediary-mediated innovation collaborations between incumbent firms and start-ups. Based on the results of an inductive cross-case analysis, we propose that intermediaries orchestrate the trust transference by building trust with the prospective parties and mitigating information asymmetry. Furthermore, the involvement of intermediaries leads to the acceptance of information asymmetry through its legitimation. Finally, we shed light on trust nurturing and trust repairing practices developed by intermediaries during innovation collaborations.

Organizations can accumulate knowledge through social relationships and thereby attain competitive advantages. Especially for family firms, these social relationships are relevant to bridging resource constraints and developing entrepreneurial opportunities through complementary knowledge. We approach this research gap by building on rich data taken from 92 interviews and further data sources from seven case firms. All case firms were family firms from Switzerland in which the owning families had significant influence on the management of the company. Building on within-case and cross-case pattern analysis, we show how family influence affects family social capital in family firms. This capital, in turn, affects levels of trust and control, which have stimulating and inhibiting influences, respectively, on openness and resistance to strengthening and expanding social relationships. As a result, multiple forms of social capital emerge at different levels of analysis, namely, organizational social capital and external social capital.

Artificial intelligence (AI) technologies have gained in significance for all types of firms, including family-influenced firms. However, despite their idiosyncratic motives, little is known about the issues family-influenced firms face in adopting complex and knowledge intensive technologies, such as AI. Peculiar characteristics of AI technologies—specifically, autonomy, learning, and inscrutability— present both opportunities and challenges to family-influenced firms. To explore how family-influenced firms approach AI technologies, we adopt a social capital perspective and combine inductive qualitative and deductive quantitative research into a mixed methods design. In the first step, we conducted a multiple case study of eight case firms consisting of rich data from 112 interviews and additional archival documents. Building on within-case and cross-case pattern analysis, we reveal opposing implications of external social capital and (internal) family social capital on the adoption of AI. While external network ties with suppliers, customers, and competitors help overcome the challenges due to the unique aspects of AI technologies, family influence exacerbate those challenges. In the second step, we sought to test the conceptual framework that we developed with our multiple case study. Based on large-scale data from 1,444 firms, we find empirical support that increasing levels of external social capital with regard to suppliers, customers, and competitors drive AI adoption. Moreover, we find that family influence has a negative moderating effect on the relationships between supplier, customer, and competitor ties on the one hand and AI adoption on the other hand. Our study contributes toward a nuanced understanding of the idiosyncratic challenges of AI adoption faced by family-influenced firms, the role of both external and family social capital in this regard, and how and why AI-related characteristics cause owning families to exacerbate the AI adoption-related challenges.

Few external shocks have had as severe an impact on organisations as COVID-19. To date, research on how management can respond to such a far-reaching trigger event is lacking. Due to their economic relevance, family firms, which are typically resource-constrained and rely on idiosyncratic resource allocation behaviour, are of particular interest in this regard. Based on an inductive, multicase study of German family firms and building on rich longitudinal insights from more than 100 semistructured interviews and secondary data, we develop a novel framework explaining how an external shock such as the COVID-19 pandemic can trigger a change in family firms’ motives. Linking certain adapted motives of family firms (i.e., survival, utilisation, and opportunism) with their resource allocation behaviour during the crisis (in terms of resource preservation, resource recombination, and reliance on social boundary resources), we reveal how digital innovation (digital process innovation, digital product innovation, and digital business model innovation) originates as a result of a process of entrepreneurial action.