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The fresh food supply chain industry faces significant challenges in risk management because of the complexity, immature development and unpredictable external environment of imported fresh food supply chains (IFFSCs). This study aims to identify specific risk factors in IFFSCs, demonstrate how these risks are transmitted within the system and provide an analytical framework for managing these risks.

A total of 15 risk factors for IFFSCs through extensive literature review and expert consultation are identified and classified into seven levels using interpretive structural modeling (ISM) to demonstrate the risk transmission path. Fuzzy Matrice d’Impacts Croises-Multiplication Appliance Classement (MICMAC) analysis is then used to analyze the role of each factor.

The interactions of the 15 identified risk factors of IFFSCs, classified into seven levels, are visualized using ISM. The fuzzy MICMAC analysis classifies the factors into four groups, namely, dependent, independent, linkage and autonomous factors, and identifies the relatively critical risk factors in the system.

The findings of this research provide a clear framework for enterprises operating in IFFSCs to understand the specific risks they may face and how these risks interact within the system. The fuzzy MICMAC analysis also classifies and highlights critical risk factors in the system to facilitate the formulation of appropriate mitigation measures.

This study provides enterprises in IFFSCs with a comprehensive understanding of how the risks can be effectively managed and a basis for further exploration. The theoretical model constructed is also a new effort to address the issues of risk in IFFSCs. The ISM and the fuzzy MICMAC analysis offer clear insights for researchers and enterprises to grasp complex concepts.

This study aims to explore how green supply chain management (GSCM) strategies can be effectively implemented for business supply chain operations, relationship management and product design to gain green competitive advantages.

An exploratory in-depth case study was conducted with one of the largest Chinese electronics manufacturers that is considered a leading GSCM adopter in the industry, to understand how the company adopts green supply chain practices across its multiple product lines.

The findings show that businesses can build different green focuses across GSCM elements of green operation, green relationship management and green product design to form diverse hybrid strategic solutions. They include green control, lean, leagile, agile and clean innovation while taking consideration of supply chain type and product lifespan. A taxonomy of four key GSCM strategic combinations is proposed based on the findings. The strategies align with green demand and supply chain characteristics balancing a series of business competitive objectives in terms of reducing pollution and waste, improving green cost efficiency, enhancing green demand innovation and building green service effectiveness.

This study lends insight into the strategic alignment relationships between product supply chain types and approaches to GSCM.

The findings of this study can support industry practitioners in formulating aligned GSCM strategies based on product types to achieve optimal results.

Optimised green supply chain design, operations and relationship management incorporating product attributes can help further minimise negative impacts of business activities on the environment.

This research provides a systematic understanding of how product supply chain types can influence GSCM strategy formulation. It gives a holistic picture of how hybrid choices of strategies with green supply chain operations, relationship management and product design can be formulated based on product and supply chain characteristics.

This study investigates the behaviour of family firms, family management and family ownership regarding their socioemotional wealth (Corporate Social Responsibility (CSR)) during the COVID-19 pandemic and according to their slack resources availability.

This study employs a multiple regression analysis to analyse 245 firm-year observations from 2020 to 2021.

Family firms have a negative effect on CSR, as do family management and family ownership. Slack resources (both absorbed and unabsorbed) reduce the negative effect of family firms (and family ownership) on CSR. Unabsorbed slack resources reduce the negative effect of family management on CSR and absorbed slack resources increase the negative effect of family management on CSR. The results are robust with various measurements of slack resources. Extra analyses reveal that family commissioner has no effect on CSR.

To the best of the author’s knowledge, this is the first empirical study to analyse the impact of COVID-19 on the preservation of socioemotional wealth in family firms. This study proves the theoretical argument of prior studies that the preservation of socioemotional wealth in family firms during the COVID-19 pandemic depends on their financial condition. The study also proves that there are different attitudes among family ownership, family management and family firms concerning the use of slack resources for socioemotional wealth preservation that have not been analysed by previous research.

This study examines academic librarians' perceptions and attitudes toward Internet of Things (IoT) applications in Hong Kong academic libraries and the problems and possible improvements in using IoT technologies to strengthen library services.

This qualitative research used video conferencing software for semi-structured, one-on-one interviews. Participants were given introductory material about the IoT and asked to complete an interview. The data were analyzed using inductive theme clustering for this study.

The analysis identified three themes: perception about applying IoT technology to the library, problems and improvements in using IoT. Participants were generally optimistic about the potential benefits of IoT for improving library operations and providing personalized services. However, they also expressed concerns about privacy and security, errors and extra efforts for information literacy training. They suggested improvements such as incorporating facial recognition technology, advanced RFID technology and collections identification technology to enhance user experience.

Most studies examined users' views rather than librarians' on IoT applications, which few studies cover, especially in East Asia.

The COVID-19 outbreak reached a critical stage when it became imperative for public health systems to act decisively and design potential behavioral operational strategies aimed at containing the pandemic. Isolation through social distancing played a key role in achieving this objective. This research study examines the factors affecting the intention of individuals toward social distancing in India.

A correlation study was conducted on residents from across Indian states (N = 499). Online questionnaires were floated, consisting of health belief model and theory of planned behavior model, with respect to social distancing behavior initially. Finally, structural equation modeling was used to test the hypotheses.

The results show that perceived susceptibility (PS), facilitating conditions (FC) and subjective norms are the major predictors of attitude toward social distancing, with the effect size of 0.277, 0.132 and 0.551, respectively. The result also confirms that the attitude toward social distancing, perceived usefulness of social distancing and subjective norms significantly predict the Intention of individuals to use social distancing with the effect size of 0.355, 0.197 and 0.385, respectively. The nonsignificant association of PS with social distancing intention (IN) (H1b) is rendering the fact that attitude (AT) mediates the relationship between PS and IN; similarly, the nonsignificant association of FC with IN (H5) renders the fact that AT mediates the relationship between FC and IN.

The results of the study are helpful to policymakers to handle operations management of nudges like social distancing.

The research is one of its kind that explores the behavioral aspects of handling social nudges through FC.

Social presence (SP), which refers to individuals’ perception of others being engaged as “real people” in the same situation, is a crucial component in technology-rich learning environments (TREs). This study aims to identify major learning design, antecedents and outcomes of SP within TREs, and identify common findings from the past two decades.

Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses review principles and a qualitative analysis of selected articles, a final review of 72 studies that met inclusion criteria was obtained. Key information, including education level, discipline, sample size, study type and measurements, was extracted and studies were further analyzed and synthesized based on design features and learning modes.

The study identifies five crucial factors for instructional design to foster SP in TREs: technology affordances, multimedia features, social factors, instructional principles, learner characteristics and learning management systems. The authors compare two learning modes across three dimensions and identify popular technologies used in studies related to SP over the past two decades. Practical recommendations are provided for educators and educational technology developers to enhance SP within technology-rich learning environments.

This research contributes to the discourse on online learning and computer-supported communication, particularly in the post-COVID-19 era. By examining factors influencing SP and providing implications for instruction and educational technology development, this study offers evidence-based support to educators for engaging learners and fostering authentic learning experiences through adaptive selection of educational technologies.

The study hypothesized that the impact of board diversity on financial distress (FD) is not direct but rather mediated by the firm’s corporate social responsibility (CSR) activities. Consequently, the purpose of this study is to examine the impact of CSR as a mediator in the board diversity–FD relationship.

The study examined six board diversity dimensions – age, gender, nationality, education and tenure in 81 nonfinancial Pakistan Stock Exchange (PSX)-listed firms from 2010 to 2021. The CSR engagement of the sample firms is evaluated using a multidimensional financial approach and the likelihood of FD is computed using Altman’s Z-score. The system-generalized method of moments estimator is used to meet the study objectives. In addition, several tests are run to determine the robustness of the study’s findings.

Based on the procedure for mediation analysis outlined by Baron and Kenny (1986), the authors found that CSR is significantly inversely associated with the likelihood of FD. Second, board diversity variables age, gender and national diversity were positively associated with CSR. Third, board age, gender and national diversity are significantly inversely related to FD. Finally, it was found that there is partial mediation between board age diversity and FD, whereas full mediation is shown between board age diversity and FD and between board nationality diversity and FD.

This study provides practical insights into PSX’s board diversity for companies, regulators and policymakers.

This research studies the connection between board diversity and FD. In addition, the current study extended the analysis by testing for the first time the mediating role of CSR in the diversity–distress relationship, particularly in the context of an emerging economy.

Given the distinct and unique climates in these countries, research conducted in other parts of the world may not be directly applicable. Therefore, it is crucial to conduct research tailored to the specific climatic conditions of Australia and New Zealand to ensure accuracy and relevance.

Given population growth, urban expansions and predicted climate change, researchers should provide a deeper understanding of microclimatic conditions and outdoor thermal comfort in Australia and New Zealand. The study’s objectives can be classified into three categories: (1) to analyze previous research works on urban microclimate and outdoor thermal comfort in Australia and New Zealand; (2) to highlight the gaps in urban microclimate studies and (3) to provide a summary of recommendations for the neglected but critical aspects of urban microclimate.

The findings of this study indicate that, despite the various climate challenges in these countries, there has been limited investigation. According to the selected papers, Melbourne has the highest number of microclimatic studies among various cities. It is a significant area for past researchers to examine people’s thermal perceptions in residential areas during the summer through field measurements and surveys. An obvious gap in previous research is investigating the impacts of various urban contexts on microclimatic conditions through software simulations over the course of a year and considering the predicted future climate changes in these countries.

This paper aims to review existing studies in these countries, provide a foundation for future research, identify research gaps and highlight areas requiring further investigation.

This study analyses the literature on artificial intelligence (AI) and its implications for the agri-food sector. This research aims to identify the current research streams, main methodologies used, findings and results delivered, gaps and future research directions.

This study relies on 69 published contributions in the field of AI in the agri-food sector. It begins with a bibliographic coupling to map and identify the current research streams and proceeds with a systematic literature review to examine the main topics and examine the main contributions.

Six clusters were identified: (1) AI adoption and benefits, (2) AI for efficiency and productivity, (3) AI for logistics and supply chain management, (4) AI for supporting decision making process for firms and consumers, (5) AI for risk mitigation and (6) AI marketing aspects. Then, the authors propose an interpretive framework composed of three main dimensions: (1) the two sides of AI: the “hard” side concerns the technology development and application while the “soft” side regards stakeholders' acceptance of the latter; (2) level of analysis: firm and inter-firm; (3) the impact of AI on value chain activities in the agri-food sector.

This study provides interpretive insights into the extant literature on AI in the agri-food sector, paving the way for future research and inspiring practitioners of different AI approaches in a traditionally low-tech sector.