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The purpose of this study is to explore and conducts a critical literature review to answer a fundamental question in the industrial district literature: are clusters and industrial (clusters/IDs) driving sustainability innovation? By intersecting different yet related strands of literature, the authors take stock of what the authors know about sustainability innovation in clusters/IDs.

This paper reviews the literature for conceptualizing sustainability innovation in clusters/districts.

Insights point out that the sustainability innovation process (development and diffusion) in clusters/IDs and their firms couples into mainstream cluster/IDs framework; clusters/IDs enable sustainability innovation through usual mechanisms, fostering collective change toward sustainability innovation, vis-à-vis other settings and strengthening firm sustainability innovation and performance. Sustainability innovation in clusters/IDs requires coupling different multi-scalar institutional systems effectively, and the cooperation of local organizations and policymakers for co-designing dedicated policies. Collective actions are important and firm heterogeneity needs to be considered in the clusters/IDs framework.

This study is original because it provides state-of-the-art on sustainability innovation in clusters/districts, enabling the topic to advance in this direction.

Today, individuals use social media to express their opinions and feelings, which offers a living laboratory to researchers in various fields, such as management, innovation, technology development, environment and marketing. It is therefore necessary to understand how the language used in user-generated content and the emotions conveyed by the content affect responses from other social media users.

In this study, almost 700,000 posts from Twitter (as well as Facebook, Instagram and forums in the appendix) are used to test a conceptual model grounded in signaling theory to explain how the language of user-generated content on social media influences how other users respond to that communication.

Extending developments in linguistics, this study shows that users react negatively to content that uses self-inclusive language. This study also shows how emotional content characteristics moderate this relationship. The additional information provided indicates that while most of the findings are replicated, some results differ across social media platforms, which deserves users' attention.

This article extends research on Internet behavior and social media use by providing insights into how the relationship between self-inclusive language and emotions affects user responses to user-generated content. Furthermore, this study provides actionable guidance for researchers interested in capturing phenomena through the social media landscape.

The study explores Degree Apprenticeship Identity (DAI) conceptualisation to enrich understanding to enhance work-integrated learning (WIL). Lived experiences of degree apprentices (DAs) are examined, and a model of DAI developed to support teaching and learning interventions on this relatively new and significant programme.

It draws pragmatically upon qualitative data from semi-structured interviews with Chartered Manager Degree Apprenticeship from diverse backgrounds in a higher education institutes (HEI). Data were explored abductively, using thematic analysis to investigate common patterns that influence identity; investigating personal experiences, socio-economic and cultural background, educational context and social interactions.

Influential themes surfaced, including pride in work, supporting others, sharing experiences and belonging, facilitating DAI model formation. The model illustrates that DAI is composed of existing personal, necessary professional and power of learning transformation through social identity by interventions that encourage peer engagement, group reflection and group-actualisation.

As this is a small-scale exploratory study, it is not intended to be representative of wider populations, which results in generalisability of findings. Data were collected from a well-established closed cohort programme led by the researcher, previously programme director. Interviews generated a broad range of anecdotal evidence, surfacing valuable insights relating to DAI formation.

To enhance WIL, tutors can foster social interventions that encourage peer dialogue, heighten DAs sense of self as capable learners and increase confidence growth.

The research provides a DAI Model, a fresh approach to understanding ways to enhance WIL for DAs through a stronger focus on group identity through social interventions. This preliminary model presents an opportunity for further research; other apprenticeships, larger and/or open cohorts.

Vocational education and entrepreneurship are constantly increasing in research fields. However, what is the current state of vocational education and entrepreneurial research? Where will the area go next? These questions are still unanswered; thus, this study tries to map the research landscape of the study area to get insights and provide directions for future research.

This research collected extant literature on vocational education and entrepreneurship using Scopus scientific database. Bibliometric analysis has been performed to extract insights from 175 documents published in the study area. Content analysis on the extant literature has also been committed to getting contextual information and developing an integrated research framework for future researchers.

The bibliometric analysis revealed that training, career choice, curriculum, self-employment, student psychology, better job opportunity, learning environment and innovation are the most discussed in the vocational education and entrepreneurship literature. Developed nation’s strong presence, indicated by the number of publications in the field.

This study significantly contributes to entrepreneurship by disclosing advances in the literature and some of the most active research fronts in this sector, delivering insights that have yet to be wholly appreciated or appraised. The study also developed an integrated framework that could benefit various vocations, education and entrepreneurship stakeholders.

The purpose of this paper is to explore the prospect of using neurophenomenology to understand, design and test phygital consumer experiences. It aims to clarify interpretivist approaches to consumer neuroscience, wherein theoretical models of individual phenomenology can be combined with modern neuroimaging techniques to detect and interpret the first-person accounts of phygital experiences.

The argument is conceptual in nature, building its position through synthesizing insights from phenomenology, phygital marketing, theoretical neuroscience and other related fields.

Ultimately, the paper presents the argument that interpretivist neuroscience in general, and neurophenomenology specifically, provides a valuable new perspective on phygital marketing experiences. In particular, we argue that the approach to studying first-personal experiences within the phygital domain can be significantly refined by adopting this perspective.

One of the primary goals of this paper is to stimulate a novel approach to interpretivist phygital research, and in doing so, provide a foundation by which the impact of phygital interventions can be empirically tested through neuroscience, and through which future research into this topic can be developed. As such, the success of such an approach is yet untested.

Phygital marketing is distinguished by its focus on the quality of subjective first-personal consumer experiences, but few papers to date have explored how neuroscience can be used as a tool for exploring these inner landscapes. This paper addresses this lacuna by providing a novel perspective on “interpretivist neuroscience” and proposes ways that current neuroscientific models can be used as a practical methodology for addressing these questions.

The emergence of new generations of artificial intelligence (AI), such as ChatGPT or Copilot has brought about a wave of innovation in the service workplace. These robotic agents can serve as companions, helping employees cope with work-related stress. This research introduces the concept of “artificial companionship,” which explains how robotic agents can function as partners in assisting service employees to fulfill their job responsibilities and maintain their mental well-being.

This research uses a mixed methods approach grounded in social support theory from psychology and management to develop a conceptual framework for the stress-alleviating implications of artificial companionship. A qualitative employee survey is conducted to justify the relevance of the propositions.

This research delineates the concept of artificial companionship. It highlights four distinct roles that AI can play in companionship – instrumental, informative, caring, and intimate. Building on this foundation, the research presents a series of propositions that elucidate the potential of artificial companionship in mitigating stress among employees.

Firms should consider aligning the types of artificial companionship with the demands inherent in employees’ job responsibilities to better reinforce their resilience and sustainment in overcoming work-related challenges.

This research introduces a new perspective on artificial companionship through the lens of social support theory. It extends the current understanding of human-robot collaboration in service workspaces and derives a set of propositions to guide future investigations.

We develop a conceptual framework as a basis for thinking about the impact of extractive industries and emancipatory potential of alternative accounts. We then review selected alternative accounts literature on some contemporary issues surrounding the extractive industries and identify opportunities for accounting, auditing, and accountability research. We also provide an overview of the other contributions in this special issue.

Drawing on alternative accounts from the popular and social media as well as the alternative accounting literature, this primarily discursive paper provides a contemporary literature review of identified issues within the extractive industries highlighting potential areas for future research. The eight papers that make up the special issue are located within a conceptual framework is employed to illustrate each paper’s contribution to the field.

While accounting has a rich literature covering some of the issues detailed in this paper, this has not necessarily translated to the extractive industries. Few studies in accounting have got “down and dirty” so to speak and engaged directly with those impacted by companies operating in the extractive industries. Those that have, have focused on specific areas such as the Niger Delta. Although prior studies in the social governance literature have tended to focus on disclosure issues, it is questionable whether this work, while informative, has resulted in any meaningful environmental, social or governance (ESG) changes on the part of the extractive industries.

The extensive extractive industries literature both from within and outside the accounting discipline makes a comprehensive review impractical. Drawing on both the accounting literature and other disciplines, this paper identifies areas that warrant further investigation through alternative accounts.

This paper and other contributions to this special issue provide a basis and an agenda for accounting scholars seeking to undertake interdisciplinary research into the extractive industries.