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Through the reconstruction of the events of some foreign entrepreneurs who worked in the territory of the Italian city of Bari in the first half of the 19th century, this paper aims to analyze the role of entrepreneurial migration in the economic development of Apulia land in this period.

This study adopts a theoretical framework that combines the concept of mixed embeddedness in a multifocal perspective, with the model of the diffusion of innovation focusing on the role of the so-called agency of actors, and of the network, in the dissemination of innovation. The theoretical framework is applied to multiple case studies to compare the evidence that emerged from the simultaneous analysis of several situations.

By analyzing how innovations have spread within the network of entrepreneurs of that time, it is possible to identify some relevant aspects related to the mechanisms of dissemination of innovations in the context of entrepreneurial migration. Specifically, the opportunity structure is intended in an even broader sense than indicated in the classic approach to mixed embeddedness: it is considered as the result of the joint interaction of the political, institutional and economic context of several places, and the behavioral dynamics of several groups.

Due to the specific method chosen, the outcomes of the research might apply to a narrow context. Therefore, the results need to be tested and confirmed in further empirical studies, and by applying multiple research methods.

Findings are useful and significant in the analysis of the link that exists between the diffusion of innovations and migrant entrepreneurship, and then the conclusions can be applied and extended to the current phenomenon of migration-related innovations, with specific reference to developing countries.

Findings can be applied and extended to the current phenomenon of migration-related innovations and highly skilled migration, with specific reference to developing countries.

This paper contributes to shed new light on the contextual and multifocal factors that influence the development of innovations in the networks of migrant entrepreneurship, in a specific historical period and a specific context. Combining social, human and financial capital with the wider opportunity structure, this study also provides a comprehensive understanding of the modalities through which migrant and high-skilled entrepreneurs could innovate.

This paper undertakes a structured literature review to analyse the literature on performance management and measurement (PMM) in universities over the last four decades. Over that time, PMM has emerged as an influential force in universities that impacts their operations and redefines their identity.

A structured literature review approach was used to analyse a sample of articles on PMM research from a broad range of disciplines over four decades. This was undertaken to understand the impacts of PMM practices on universities, highlight changes over time and point to avenues for future research.

The analysis highlights the fact that research on PMM in universities has grown significantly over the 40 years studied. We provide an overview of published articles over four decades regarding content, themes, theories, methods and impacts. We provide an empirical basis for discussing past, present and future university PMM research. The future research avenues offer multiple provocations for scholars and policymakers, for instance, PMM implementation strategies and relationships with various government programs and external evaluation and the role of different actors, particularly academics, in shaping PMM systems.

Unlike a traditional literature review, the structured literature review method can develop insights into how the field has changed over time and highlight possible future research. The sample for this literature review differs from previous reviews in covering a broad range of disciplines, including accounting.

The purpose of this paper is to present a conceptual framework that explores the determinants, mechanisms and consequences of reporting on the United Nations Sustainable Development Goals (UN SDGs) by universities. The framework considers the relationship between reporting on the SDGs and the three main activities of universities: research, teaching and service. As universities hold a unique position in society, understanding their experiences with SDG reporting offers insights into the promotion and integration of SDGs into reporting and practice more broadly.

The paper adopts a conceptual approach and draws on existing literature to develop a framework for understanding reporting on the UN SDGs by universities. The framework considers the challenges faced by universities in providing sustainability information and examines the motivations and outcomes associated with reporting. It also explores the coordination and collaboration necessary across departments within universities and discusses the risks associated with greenwashing.

The paper highlights that reporting on the UN SDGs can enhance university engagement with stakeholders, improve their reputation, and foster innovation and transdisciplinary research ideas. However, universities encounter challenges such as limited data availability, resource constraints, lack of coordination and competing priorities. The growing scepticism surrounding reporting motives has led to increased allegations of greenwashing within the sector.

This paper contributes to the accounting literature by presenting a comprehensive framework that explores the determinants, mechanisms and consequences of reporting on the UN SDGs by universities. The framework offers insights into how reporting on SDGs can lead to embedding the SDGs in research, teaching and service activities and can be adapted to other organisational contexts. The paper also emphasises the need for further research on the mechanisms of reporting, which play a crucial role in driving long-lasting change.

The purpose of this study is to examine the propagation of consumer and business confidence in the euro area with a particular focus on the global financial crisis (GFC), the European sovereign debt crisis (ESDC) and the COVID-19-induced Great Lockdown.

The authors apply Diebold and Yilmaz’s connectedness framework and the improved method based on the time-varying parameter vector autoregressive model.

The authors find that although the evolution of business confidence marked the GFC and the ESDC the role of consumer confidence (mainly in those countries with stricter containment and closure measures) increased in the COVID-19-induced crisis.

The findings are related to the different origins of the examined crisis periods, and the analysis of their interrelationship is a very relevant topic for future research.

This study aims to examine adolescents’ social media environment connected to unhealthy food marketing. As social media have become a ubiquitous part of young people’s everyday lives, marketers have also shifted their focus to these channels. Literature on this phenomenon is still scarce and often takes a quite narrow view of the role of marketing in social media. Furthermore, the experiences of the adolescents are seldom considered.

Using a sociocultural approach and netnographic methodology, this study presents findings from a research project conducted in Finland. The data consist of both social media material and focus group interviews with adolescents.

The findings elaborate on unhealthy food marketing to adolescents in social media from two perspectives: sociocultural representations of unhealthy foods in social media marketing and social media influencers connecting with adolescents.

The study broadens and deepens the current understanding of unhealthy food marketing to adolescents taking place in social media. The study introduces a novel perspective to the topic by looking at it as a sociocultural phenomenon.

Motivated by the wide application of procurement strategies in retailing, this paper aims to examine the effect of procurement strategies on decisions and profits and strategic inventory (SI) is considered.

The game-theoretic models are developed under a two-period fresh product supply chain (FSC), and consist of the mode of purchasing products only in the first period without SI (Scenario S), the mode of purchasing products in every period without SI (Scenario T) and the mode of purchasing products in every period with SI (Scenario TS).

Conducting the calculating and comparing, some major findings can be concluded. In general, two-period purchasing strategies (Scenarios T and TS) promote a higher freshness-keeping effort than the single buying strategy (Scenario S). Regarding the pricing strategy, SI and Scenario S can both contribute to obtaining a lower wholesale price, the retailer's pricing is relatively complicated and hinges on the consumer's sensitivity to freshness-keeping effort and the holding cost. Besides, comparing the sales quantity and the profit, the authors find that Scenario TS stimulates more demands and brings more profits for the manufacturer. However, Scenario TS is not the optimal selection for the reason that SI sometimes hurts the retailer and even the whole supply chain. Whereas, when the holding cost is in a certain range, Scenario TS will lead to a win-win situation.

The main findings of this study can give the enterprises some advice on the procurement strategies of fresh products and the decisions of pricing and the freshness-keeping effort.

To develop a fuzzy causal model of enterprise flexibility dimensions in a case study of Indian pharmaceutical industry.

The eight dimensions of enterprise flexibility were identified based on literature review. Fermatean fuzzy decision-making trail and evaluation laboratory (FF-DEMATEL) technique is applied to develop the cause-and-effect interrelationship model among various enterprise flexibility dimensions.

The information technology flexibility, supply chain flexibility, technical flexibility and marketing flexibility are found to be causing/influencing other flexibilities and contributing to overall enterprise flexibilities. Therefore, more attention needs to be paid to develop and sustain them for competitive advantage.

Fermatean fuzzy sets offer more flexibility and more accurate handling complex uncertain group decision making. FF-DEMATEL is a more accurate method to develop inter-dependencies and causal model than ISM, TISM. Ratings from the limited number of decision experts (DEs) from few pharmaceutical firms were done. Future study should take bigger sample of firms and more number of DEs to generalize the findings.

The model will help managers in pharmaceutical industry to prioritize the dimensions of enterprise flexibility to achieve agility, responsiveness, resilience and competitive advantage.

To the best knowledge of the authors, causal modeling enterprise flexibility dimensions using FF-DEMATEL has been studied for the first time in a developing economy context.

This study aims to test the market anomaly of herding behavior driven by the response to supply chain disruptions in extreme market conditions such as those observed during COVID-19. The authors empirically test the response of the capital market participants for B2B firms, resulting in herding behavior.

Using the event study approach based on the market model, the authors test the impact of supply chain disruptions and resultant herding behavior across six sectors and among different B2B firms. The authors used cumulative average abnormal returns (CAAR) and cross-sectional absolute deviation (CSAD) to examine the significance of herding behavior across sectors.

The event study results show a significant effect of COVID-19 due to supply chain disruptions across specific sectors. Herding was detected across the automotive and pharmaceutical sectors. The authors also provide evidence of sector-specific disruption impact and herding behavior based on the black swan event and social learning theory.

The authors examine the impact of COVID-19 on herding in the stock market of an emerging economy due to extreme market conditions. This is one of the first studies analyzing lockdown-driven supply chain disruptions and subsequent sector-specific herding behavior. Investors and regulators should take sector-specific responses that are sophisticated during extreme market conditions, such as a pandemic, and update their responses as the situation unfolds.

In this global digital era, health-care companies are increasing their presence on the internet through branded content that serves as a connecting link between customers and brands. However, there is a limited understanding of branded content’s impact on customers. Thus, this paper aims to empirically analyse customer engagement for branded content in the health-care sector.

The factors impacting customer engagement for branded content were identified and analysed using the Decision-Making Trial and Evaluation Laboratory approach to get their significance and the cause and effect relationship.

It emerged that co-creation is the most significant factor, having a substantial relationship with all other factors. It is substantiated that health-care companies can increase the intensity of customer engagement by delivering more authentic and relevant content and having an appealing look in a time-bound manner. This will increase the usefulness and entertaining value of the content.

The research findings contribute to the customer engagement dimension in the health-care sector and help the companies construct effective branded content leading towards higher customer engagement.

The crux of this paper is to unveil efficient features and practical tools that can predict credit default.

Annual data of non-financial listed companies were taken from 2000 to 2020, along with 71 financial ratios. The dataset was bifurcated into three panels with three default assumptions. Logistic regression (LR) and k-nearest neighbor (KNN) binary classification algorithms were used to estimate credit default in this research.

The study’s findings revealed that features used in Model 3 (Case 3) were the efficient and best features comparatively. Results also showcased that KNN exposed higher accuracy than LR, which proves the supremacy of KNN on LR.

Using only two classifiers limits this research for a comprehensive comparison of results; this research was based on only financial data, which exhibits a sizeable room for including non-financial parameters in default estimation. Both limitations may be a direction for future research in this domain.

This study introduces efficient features and tools for credit default prediction using financial data, demonstrating KNN’s superior accuracy over LR and suggesting future research directions.