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This contribution responds to the call of various researchers for a shift in Responsible Management Education (RME) to adopt a more human-centered and less organizational-centered approach. Service learning (SL) is introduced as a possibility to offer didactical opportunities for participants to connect real-world experiences to system thinking in various ways. We suggest an approach called a “Prism of Reflections” to pique participants' hermeneutical, technical, and emancipatory interests so they can delve deeply into local social and environmental issues and be able to connect them to broader global issues as encapsulated in the Sustainable Development Goals (SDGs). We exemplify our method by demonstrating how students reflect on their experiences working at food banks, and how they relate to concerns of sustainability, poverty, and access to food. Our research suggests that this approach offers a way to situate organizational thinking and instrumental reasoning in a larger framework that considers the aims of hermeneutics, technical and emancipatory discourses. Our findings demonstrate that there are conflicts and dissonances when connecting intersubjective real-world perceptions to emancipatory interests and technical knowledge, particularly when it comes to challenges in the realm of food.

This chapter presents a genderwashing critique of UK historic universities. Taking an interdisciplinary approach, it conceptualizes genderwashing and gender-based violence (GBV). Underpinned by feminist subjectivity, raising consciousness to women's situated lived experiences, examples of public declarations of gender equality by UK historic universities are considered alongside women's experiences of GBV. Using Walter's (2022) genderwash varieties, university hypocrisy is illustrated by women academic handmaidens, abuse of women in Professional Services, and women standing up to GBV. This chapter contributes “Eradicating and Silencing Women’”and “Asking the Minority to Fix It” as genderwash processes, theorizing how genderwashing (or genderbleaching) in historic universities not only perpetuates the falsehood of practicing equality but also provides a veil to conceal GBV.

Managers and scholars alike claim that artificial intelligence (AI) represents a tool to enhance supply chain collaborations; however, existing research is limited in providing frameworks that categorise to what extent companies can apply AI capabilities and support existing collaborations. In response, this paper clarifies the various implications of AI applications on supply chain collaborations, focusing on the core elements of information sharing and trust. A five-stage AI collaboration framework for supply chains is presented, supporting managers to classify the supply chain collaboration stage in a company’s AI journey.

Using existing literature on AI technology and collaboration and its effects of information sharing and trust, we present two frameworks to clarify (a) the interrelationships between information sharing, trust and AI capabilities and (b) develop a model illustrating five AI application stages how AI can be used for supply chain collaborations.

We identify various levels of interdependency between trust and AI capabilities and subsequently divide AI collaboration into five stages, namely complementary AI applications, augmentative AI applications, collaborative AI applications, autonomous AI applications and AI applications replacing existing systems.

Similar to the five stages of autonomous driving, the categorisation of AI collaboration along the supply chain into five consecutive stages provides insight into collaborations practices and represents a practical management tool to better understand the utilisation of AI capabilities in a supply chain environment.

The purpose of this study is to investigate managers’ decision-making processes when evaluating suggestions provided by human collaborators or artificial intelligence (AI) systems. We employed the framework of Social Comparison Theory (SCT) in the business context to examine the influence of varying social comparison orientation levels on managers’ willingness to accept advice in their organization.

A survey was conducted on a sample of 192 US managers, in which we carried out an experiment manipulating the source type (human vs AI) and assessing the potential moderating role of social comparison orientation. Results were analyzed using a moderation model by Hayes (2013).

Despite the growing consideration gained by AI systems, results showed a discernible preference for human-generated advice over those originating from Artificial Intelligence (AI) sources. Moreover, the moderation analysis indicated how low levels of social comparison orientation may lead managers to be more willing to accept advice from AI.

This study contributes to the current understanding of the interplay between social comparison orientation and managerial decision-making. Based on the results of this preliminary study that used a scenario-based experiment, future research could try to expand these findings by examining managerial behavior in a natural context using field experiments, or multiple case studies.

This is among the first studies that examine AI adoption in the organizational context, showing how AI may be used by managers to evade comparison among peers or other experts, thereby illuminating the role of individual factors in affecting managers’ decision-making.

This study aims to argue that manufacturers with more exploration orientation (compared to exploitation orientation) have higher degrees of export marketing internalization (EMI) of branding and channels.

The authors use a multisource survey collecting data from 161 Taiwanese high-tech manufacturers in emerging markets.

The results show that manufacturers with more exploration orientation have higher degrees of EMI of both branding and channels. This work also reveals that relational ties with supply chain peers can strengthen this proposed positive effect on the EMI of channels while weakening the positive proposed effect on the EMI of branding.

Accordingly, this study enriches the resource-based view (RBV) literature by showing how firms’ unique resource portfolios affect their adopted EMI strategies in two ways: (1) firms design their EMI based on their value maximization of core competences (e.g. ambidexterity capability), and (2) firms face resource inconsistency when designing their EMI of different marketing activities.

This study investigates the factors influencing the intention to use Islamic Debt Financing (IDF) among owners-managers of Micro, Small, and Medium Enterprises (MSMEs) in Morocco.

We developed and validated a comprehensive model that examines the key behavioral elements affecting attitude towards IDF, entrepreneurial achievement motivation, and IDF usage intention. Entrepreneurial achievement motivation was assessed as a mediator in the relationship between attitude towards IDF and usage intention. Gender and Islamic religiosity were examined as moderators through Multi-Group analysis. Utilizing data from 266 Moroccan MSMEs, we applied structural equation modeling for empirical evaluation.

Results revealed direct relationships with financial literacy, risk perception, and cost perception negatively affecting attitude toward IDF. Financial suitability is inversely related to attitude toward IDF. Entrepreneurial self-efficacy and subjective norms positively influenced entrepreneurial achievement motivation. Attitude toward IDF positively impacted entrepreneurial achievement motivation, and both attitude toward IDF and entrepreneurial achievement motivation were linked to the intention to use IDF. Empirical findings indicated that entrepreneurial achievement motivation partially mediates the relationship between attitude towards IDF and usage intention. Multi-group analysis revealed a significant moderating effect of Islamic religiosity on three out of nine structural relationships.

This study is primarily limited by the absence of a longitudinal examination tracking real usage behavior. Moreover, data collection focused on analyzing the behavioral intention to use Islamic debt-based financing products, excluding equity-based financing instruments. Finally, our proposed model concentrates on establishing usage intention solely based on demand-side factors without explicitly integrating supply-side consideration.

Our findings contribute to a deeper understanding of IDF adoption behavior and have the potential to support the development of more effective public policies, targeted promotional campaigns, and impactful financial education programs for MSMEs in similar markets.

This paper represents the first attempt to address MSMEs’ apprehensions regarding Islamic debt-based financing products in the MENA region.

This study explored the influence of Dervin’s sensemaking methodology (SMM).

Citation context analysis was used to identify the most influential SMM concepts in 948 articles citing 34 SMM-related studies by Dervin that were published between 1983 and 2017. Moreover, the bibliometric method and content analysis were incorporated to examine the disciplines and research topics influenced by the SMM-related studies and the role of cited content in SMM-related studies.

The influence of SMM is concentrated in information behavior research in the field of library and information science (LIS). The 1992 book chapter From the mind’s eye of the user was most frequently cited, followed by the first SMM study from 1983; 14 of the 18 content categories were relevant to SMM. “Sensemaking,” at the core of SMM, was the most influential cited concept, primarily cited from the 1983 SMM-related study. Although the SMM was developed as a research method, it has not been primarily applied to design research methods in other studies.

This study explored the interdisciplinary influence of Dervin’s SMM from several aspects and demonstrated the complex information dynamics between SMM-related works and citing articles.

Most educational institutions worldwide have shifted to online teaching and learning approaches to mitigate risks imposed by the COVID-19 pandemic. This causes several issues, particularly in delivering the construction management (CM) courses which require site visits, interpreting technical drawings and developing 3D building models. This paper aims to identify the key strategies for online learning and teaching adopted during the COVID-19 pandemic and to investigate the implications for construction management education.

The research approach is twofold. First, the study presents a systematic literature review (SLR) through a synthesis of the existing literature to identify the key strategies and lessons learned about online education during the COVID-19 pandemic in tertiary programs. It also discusses their implications in the context of the construction management (CM) sector in particular. Secondly, the authors shared their hands-on experience as construction management course facilitators – using the autoethnography approach – during the COVID-19 crisis.

In addition to identifying the key strategies such as online course delivery and assessments, the paper critically discusses the barriers to online learning and teaching, including (1) the technological and infrastructure barriers; (2) required online teaching skills and competencies; (3) issues surrounding mental health and wellbeing; (4) lack of consistency in the online delivery of various courses in a given program (5) difficulties around students' engagement and (6) the course characteristics and requirements.

The study offers some implications and recommendations not only for educational institutions and staff but also for vendors of online course delivery software. To prepare educational institutions for future online course delivery, the paper proposes several strategies. These include developing a set of guidelines for online course delivery, incorporating online teaching training modules into the recruitment process for academic staff, applying agile and resilience teaching and learning methods, wellbeing and mental health support and continuously improving course features to adapt to the online environment.

Unlike well-documented market or behavioral uncertainty, patent uncertainty has been significantly under-explored in the field of international entrepreneurship. Drawing on an institution-based view of strategy, this study investigated Netac, a Chinese knowledge-based international new venture (KINV), which was facing uncertainty over patents in China and the US. The aim was to address two questions: (1) how does patent uncertainty emerge in the context of KINVs? And (2) how can KINVs navigate patent hazards by interacting with national patent institutions?

A longitudinal single-case study approach was adopted as the most appropriate method for exploring novel business phenomena and dynamic processes.

Results suggested that a KINV can adopt strategies to build a unique identity and so better conform to the expectations of institutions that ultimately decide on patent validity. Strategies may involve building institutional awareness, amplifying mass media effects, and strategically managing the intellectual property and socio-emotional tensions between China and the US.

This study introduced the notion of patent uncertainty into research around international new ventures, highlighting how this type of uncertainty in the advanced technology sector can affect the end-product and patent licensing opportunities of KINVs. It also explored the institution-based view of company strategy in the internationalization process by emphasizing interactive institutional mechanisms, and the role of an organization’s identity when interacting with institutions. The study enriches the literature on institutional theory and organizational identity, and also suggests solutions for firms dealing with efforts by competitors to invalidate patents.

The notion of using a generative artificial intelligence (AI) engine for text composition has gained excessive popularity among students, educators and researchers, following the introduction of ChatGPT. However, this has added another dimension to the daunting task of verifying originality in academic writing. Consequently, the market for detecting artificially generated content has seen a mushroom growth of tools that claim to be more than 90% accurate in sensing artificially written content.

This research evaluates the capabilities of some highly mentioned AI detection tools to separate reality from their hyperbolic claims. For this purpose, eight AI engines have been tested on four different types of data, which cover the different ways of using ChatGPT. These types are Original, Paraphrased by AI, 100% AI generated and 100% AI generated with Contextual Information. The AI index recorded by these tools against the datasets was evaluated as an indicator of their performance.

The resulting figures of cumulative mean validate that these tools excel at identifying human generated content (1.71% AI content) and perform reasonably well in labelling AI generated content (76.85% AI content). However, they are perplexed by the scenarios where the content is either paraphrased by the AI (39.42% AI content) or generated by giving a precise context for the output (60.1% AI content).

This paper evaluates different services for the detection of AI-generated content to verify academic integrity in research work and higher education and provides new insights into their performance.