Tracing Relationship between Cluster’s Performance and Transition to the Circular Economy

The Importance of Individual Actor Characteristics and Contextual Aspects for Promoting Industrial Symbiosis Networks

Factors that affect and influence industrial symbiosis (IS) collaborations have been researched extensively in the literature, where they are mostly reported at a network level or for IS in general, and lack the individual actor’s perspective. This review article contributes to and expands knowledge of influencing factors and their effect on the individual actor. In a systematic review, guided by the PRISMA 2020 guidelines, this study reviews 53 scientific papers examining planned or existing IS networks. It examines literature from 1 January 2000 to 28 March 2022, and it identifies drivers, barriers, and enablers influencing actors to participate in IS. It explores whether and how the perception and impact of these factors differs depending on the characteristics of individual actors and their specific context. The main findings of this study reveal that an actor’s specific characteristics and the network’s context have a significant impact on decision making and how actors both perceive and are affected by factors influencing collaboration. Furthermore, an additional novel contribution to this field of research is that the study identifies three underlying and recurring considerations that actors appear to find critical, namely, perceived business opportunities/risks, regulatory and political setting, and potential inequalities in the network. The results show that an actor’s take on these critical considerations determines whether the actor is willing to engage in IS.

Threats and Opportunities in Digital Transformation in SMEs from the Perspective of Sustainability: A Case Study in the Czech Republic

Digital technologies represent an important factor in the achievement of the sustainability goals of the European Green Deal. Whether the digitalisation trend will contribute to the sustainable development of societies in the long term depends on how we shape and understand it. The aim of this paper is to create a concept for the management of the threats and opportunities in the digital transformation of SMEs. As part of a broader research project, a complex tool was developed to assess the digital maturity of SMEs, and our paper focuses on one aspect of this tool, which is related to the identification and management of the opportunities and threats that are associated with digital transformation trends. The methodology that was used to develop this paper is based on a pilot survey that involved 154 SMEs in the Czech Republic, 74 of which were used for the follow-up survey on the opportunities and threats. Sixteen key trends were identified, which were then reduced to five latent factors, with their names forming five dimensions. In the cluster analysis, the companies were divided into three clusters, which served as the basis for determining the final cluster centres. The result is a concept for the management of the threats and opportunities in the digital transformation of SMEs. Digital transformation is the broad topic. Therefore, the theoretical overlap of this study can be seen in the narrower focus on the identification and management of the opportunities and threats in digital transformation. In addition, this study focuses on SMEs because there are more than one million small and medium-sized enterprises in the Czech Republic, and they create 54% of the innovative solutions. The practical impact of this study can be understood in the fact that the proposed concept may enable SMEs to more easily manage threats and opportunities in their digital transformation.

Application of Social Network Analysis to Visualization and Description of Industrial Clusters: A Case of the Textile Industry

This paper discusses the issues of industrial cluster analysis. Initially, the authors explore theoretical approaches to understanding the clusters phenomenon and their identification and analysis. Looking at industrial clusters as network structures connected by various forms of interaction between members, such as ownership linkages, transactions, the presence of common counterparts, and participation in arbitration processes, the authors propose visualizing clusters using social network analysis metrics. This approach helps to address one of the main difficulties when contacting the members of industrial clusters for a subsequent survey or in-depth interviewing. The analysis concludes with a discussion of the proposed method as a way to identify cluster members and determine the most significant ones that are the primary nodes of the network. These key members usually possess enough relevant information about the structure, coordination mechanisms, general strategy, and cluster management system. Therefore, it is possible to limit the list of interviewed respondents without a substantial loss in empirical data quality. The case of the textile industry cluster presented in this paper confirms the applicability of social network analysis to the visualization and description of industrial clusters.