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This research aims to contribute to the literature on sustainable hospitality and tourism by applying social network analysis to identify sustainable tourism business networks and untangle the role of cognitive and geographical proximity in their formation.

Data mining and machine learning techniques were applied to data collected from the websites of tourism companies located in northeastern Italy, namely, the Veneto region. Specifically, the authors used Web scraping to extract relevant information from the internet.

The results support the existence of geographical clusters of tourist accommodation providers that are linked by strong cognitive proximity based on sustainability principles that are well communicated via their websites. This does not appear to be greenwashing because companies that have agreed on sustainability principles have also implemented concrete actions and tend to signal these actions through a variety of sustainability certifications.

The results may guide tourism managers and policymakers in developing tourism initiatives directed at the creation of fruitful collaborations between similarly oriented organizations and methods to support clusters of sustainable tourism accommodation. Identifying sustainable tourism networks may assist in the identification of potential actors of change, fueling a widespread transition toward sustainability.

In this study, the authors adopted an innovative methodology to detect sustainability-oriented tourism business networks. Additionally, to the best of the authors’ knowledge, this study is one of the first to simultaneously explore the cognitive and geographical connections between tourism businesses.

This paper explores how exaptive innovation process might be considered a useful innovation model in constraint-based environments. Through an in-depth case study, it illustrates clearly the antecedents of exaptation processes, which are particularly relevant in rapidly changing environments requiring new solutions under time and resource constraints.

The authors adopt a single case study approach that is particularly suitable in case of an inductive research design, which is required because of the novelty of the topic. The research is inspired by the use of the snorkeling mask EASYBREATH, commercialized by the giant Decathlon, as a medical device, a respirator to treat patients affected by coronavirus in Italy. The authors organized the evidence according to a novel taxonomy grounded in the literature.

The case study stimulates reflections on the existence of some antecedents to the exaptive innovation process in constraint-based environments: (1) the availability of specific actors in the innovation process; (2) the creation of platforms of interaction between people with different competences, nurtured by collective bottom-up financing systems; (3) the role of the community of makers, in particular, and of the 4th industrial revolution, in general, for creating enabling technologies; (4) multidisciplinary individual background of key actors in the innovation process is crucial to ensure the exaptive path to be in place.

This work has some limitations, due to the choice of limiting the analysis to a single case, nevertheless, it offers a first glance on a new technological trajectory available in constraint-based environments.

The case study results underline the importance of new digital collaboration platforms as knowledge multipliers, and illuminate on the potential of the fourth manufacturing revolution, which, through new technologies, creates opportunities for distributed forms of innovation that cross long distances.

This paper aims to explore if firms located in industrial districts (IDs) have different adoption paths concerning Industry 4.0 technologies and get different results with respect to other similar firms located outside IDs.

The study is based on a quantitative analysis related to an original data set of 206 Italian manufacturing firms specializing in made in Italy industries and adopting Industry 4.0 technologies. A case study of a district firm is also presented to explain the rationale of investment strategies and results obtained.

The analysis shows that there are differences between district and non-district firms when Industry 4.0 technology investments are concerned (higher investment rate in big data/cloud and augmented reality for district firms than non-district ones). In contrast to a breakthrough view of the fourth industrial revolution, the study suggests that 4.0 technologies emphasize the peculiarities and competitiveness factors typical of the district model in terms of customization and flexibility. There are differences in the motivations of adoption (product diversification for district firms vs productivity enhancement for non-district firms) and in the results achieved.

The paper is one of the first attempts to empirically explore the technological innovation paths related to Industry 4.0 within IDs, therefore, contributing to the debate on the possible evolution of the district model

We address the following research questions: (1) Is the innovation trajectory of the acquirer affected by previous acquisitions? (2) In which direction knowledge recombination from the acquisition is pushed further? (3) Is the technological acquisition more a means for knowledge exploration and radical innovation or, on the contrary, a way for consolidating previous technological specialization?

The nature of this study is exploratory; therefore, we opted for an inductive approach based on the L'Oréal case study analysis. Data were triangulated from different sources: (a) the L'Oréal website and press releases collected in the 2009–2015 period; (b) journal articles and books on the global cosmetics industry and the insightful work of Jones (2010); (c) the Questel Orbit database containing data on patents; and (d) the Zephyr – Bureau van Dijk database containing information on the acquisitions of firms.

Empirical evidence from a patent data analysis reveals a paradoxical path. On the one hand, acquisitions enable the company to explore new technological spaces; on the other hand, they allow it to reinforce a preexisting technological trajectory, even when the knowledge base of the target is distant from that of the acquirer. Thus, in our case study, the absorption and recombination of knowledge from a variety of domains support specialization more than diversification technology strategies.

We add to innovation management literature a new perspective, by offering a detailed analysis, through patent data, of the knowledge recombination process, led by technological acquisitions.

This paper aims to analyze how knowledge networks can be configured within a value chain and provide evidence of the coexistence of multiple knowledge networks in the same value chain.

The empirical setting is the Conegliano Valdobbiadene Prosecco Superiore DOCG wine cluster in the Veneto region of Northeast Italy. Data was collected through the administration by telephone of a semi-structured questionnaire to 37 oenologists, sales managers, production managers and owners of bottling companies in the district. The authors used social network analysis tools to map knowledge networks in the Prosecco cluster.

The results shed light on the importance of singling out knowledge networks in clusters at the value chain level to aid practitioners and researchers in this field. In fact, this research proves the existence of knowledge networks specificities related to the various phases of the production process.

This study has certain limitations. The most relevant is connected to the choice to limit the analysis to a specific cluster. Future research might extend this type of analysis to multiple clusters in different locations.

The authors explain that in the cluster they studied, internationalization, as a common objective, might be made easier if firms could establish a more developed sales knowledge network.

The relational approach to value chain enables disentangling specific roles of each actors. The social dimension of the value chain is taken in consideration.

The authors show that a firm operating in the wine industry can have different knowledge networks in the same value chain. This work adds to previous literature on knowledge networks in clusters by shedding light on an important, but still understudied aspect in the cluster functioning. Knowledge diffusion in clusters is not only uneven but is also value chain stage specific. By intersecting literature on knowledge networks, value chain and cluster research, the authors proposed a new perspective of analysis of the wine industry.