No abstract

We examine whether the probability of innovating a company’s business model towards the Industry 4.0 paradigm is affected by external institutional support and family leadership. Industry 4.0 is the information-intensive transformation of global manufacturing enabled by Internet technologies aimed at reinventing products and services from design and engineering to manufacturing. Using a sample of 3000 firms from a corporate survey on the manufacturing industry in Italy, our results showed that family leadership has a significant positive influence on the adoption of Industry 4.0 business models, but only in terms of family ownership. By contrast, family management has a negative influence on the probability of adopting a new business model. However, this negative influence is almost totally offset by the presence of the Triple Helix, i.e. the external support by public institutions and universities, which counterbalances the lower propensity of family managers to adopt Industry 4.0 business models. This supporting role only occurs when institutions and universities act together.

This study aims to use a quantitative analysis to explore the effects of openness to Industry 4.0 on the perceived production recovery post the COVID-19 pandemic, mediated by digital and classical reorganization. Openness to Industry 4.0 is measured by the breadth of the number of technologies adopted. The production recovery is measured by the perception of firms that a return to pre-COVID-19 production levels will happen within either 2021, 2022, or 2023. The study takes a representative sample of 2622 manufacturing small and medium enterprises across Italy (surveyed between October and November 2020) through a mediation analysis based on nonlinear probability models (KHB method). The results of the models show the following. First, openness to Industry 4.0 has a positive and significant direct effect on a perceived production recovery in the short term (within 2021) and medium term (within 2022 and 2023). Further, this effect is accelerated in the short term by digital reorganization and in the medium term by the addition of a classical reorganization. The research provides relevant managerial implications based on a large sample of current empirical data, showing that Industry 4.0 technologies, when adopted in tandem with the digital reorganization of production activity, can accelerate production recovery to pre-COVID-19 levels.

Sustainable behavior should necessarily benefit both the environment and society. However, we cannot take for granted that socially responsible firms are also environmentally responsible—e.g., a firm might benefit its stakeholders while degrading the environment—and the reverse applies too—e.g., an environmentally responsible firm might disrespect its employees. Consequently, our purpose is checking whether social responsibility and green investments—proxying for a firm’s environmental responsibility—are complements, substitutes, or unrelated choices. Using a representative sample of Italian manufacturing firms, our econometric estimates uncover the empirical relationship between social responsibility and green investments at firm level. We find evidence of complementarity, since socially responsible firms: (i) Are systematically more likely to make green investments; (ii) identify green investments as a voluntary choice promoting business competitiveness much more than other firms. Finding complementarity between social and environmental responsibility has important implications. Policies favoring the transition to sustainable development should adopt a systemic approach considering the positive spillovers of Corporate Social Responsibility (CSR) on environmental responsibility. Our evidence also suggests that firms indeed tend to behave in ways consistent with the holistic approach of the 2030 UN Agenda for sustainable development. Additional research should study how governance affects the CSR–environmental responsibility nexus.

This paper tests the impact of different types of management within family businesses on digital innovation related to Industry 4.0 investments, from a geographical perspective. The data set consists of 3,000 Italian manufacturing small-and medium-sized enterprises. Using probit models, the results show that while in the more advanced area (center-north) external management affects the propensity for innovation significantly, in the less developed area (Southern Italy) external management requires an additional and simultaneous investment in R&D to drive a firm's innovation. This suggests that innovation policy should define incentives that also help enhance new management business models and take into account behavioral features of different firms in relation to the level of the development of the geographical areas in which they operate. This is an open access article under the CC BY license (https://creativecommons.org/licenses/by/4.0/legalcode). 74 / Family management and Industry 4.0: Different effects in different geographical areas? An analysis of the less developed regions in Italy Entrepreneurship, Technological Upgrading and Innovation Policy in Less Developed and Peripheral Regions Ivano Dileo, Manuel González-López (Eds.)