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The growing awareness of climate risks associated with food safety issues has drawn the attention of stakeholders urging the food industry to carry out a sustainable food safety management system (FSMS). This study aims to investigate whether the critical success factors (CSFs) of sustainable FSMS can contribute to achieving climate neutrality, and how the adoption of FSMS 4.0 supported by the Industry Revolution 4.0 (IR 4.0) technologies moderates the impact of the CSFs on achieving climate neutrality.

Survey data from 255 food production firms in China and Vietnam were utilised for the empirical analysis. The research hypotheses were examined using structural equations modelling (SEM) with route analysis and bootstrapping techniques.

The results show that top management support, human resource management, infrastructure and integration appear as the significant CSFs that directly impact food production firms in achieving climate neutrality. Moreover, the results demonstrate that the adoption of FSMS 4.0 integrated with the three components (ecosystems, quality standards and robustness) significantly moderates the impact of the CSFs on achieving climate neutrality with lower inputs in human resources, infrastructure investment, integration and external assistance, and higher inputs in strengthening food safety administration.

This study provides empirical findings that fill the research gap in understanding the relationship between climate neutrality and the CSFs of sustainable FSMS while considering the moderating effects of the FSMS 4.0 components. The results provide theoretical and practical insights into how the food production sector can utilise IR 4.0 to attain sustainable FSMS for achieving climate neutrality.

Managers play a crucial role in organizations. They make decisions that directly influence organizational success and significantly impact employees’ mental health, development and performance. They are responsible for ensuring the financial well-being and long-term sustainability of organizations. However, their mental health is often overlooked, which can negatively affect employees and organizations. This study aims to address managers’ mental health at work, by examining specifically the direct and indirect effects of identity verification on their psychological distress and depression through self-esteem at work. The study also aims to examine the moderating as well as moderated mediation effects of identity salience.

A sample of 314 Canadian managers working in 56 different companies was studied, using multilevel analyses.

The findings showed that the verification of managers’ identity vis-à-vis recognition is positively associated with psychological distress and depression. Self-esteem completely mediates the association between low identity verification vis-à-vis work control and psychological distress, and also the association between low identity verification vis-à-vis work control and superior support and depression, while it partially mediates the association between low identity verification vis-à-vis recognition and depression.

This study can also help both managers and human resource management practitioners in understanding the role of workplaces in the identity verification process and developing relevant interventions to prevent mental health issues among managers at work.

This study proposed a relatively unexplored approach to the study of managers’ mental health at work. Its integration of identity theory contributes to expanding research on management and workplace mental health issues.

Every day, small and big incidents happen all over the world, and given the human, financial and spiritual damage they cause, proper planning should be sought to deal with them so they can be appropriately managed in times of crisis. This study aims to examine humanitarian supply chain models.

A new model is developed to pursue the necessary relations in an optimal way that will minimize human, financial and moral losses. In this developed model, in order to optimize the problem and minimize the amount of human and financial losses, the following subjects have been applied: magnitude of the areas in which an accident may occur as obtained by multiple attribute decision-making methods, the distances between relief centers, the number of available rescuers, the number of rescuers required and the risk level of each patient which is determined using previous data and machine learning (ML) algorithms.

For this purpose, a case study in the east of Tehran has been conducted. According to the results obtained from the algorithms, problem modeling and case study, the accuracy of the proposed model is evaluated very well.

Obtaining each injured person's priority using ML techniques and each area's importance or risk level, besides developing a bi-objective mathematical model and using multiple attribute decision-making methods, make this study unique among very few studies that concern ML in the humanitarian supply chain. Moreover, the findings validate the results and the model's functionality very well.

This study aims to examine whether and why subsidiary-unit managers’ prior international work experiences across multinational enterprises’ (MNEs) home and host countries impact their subsidiary-unit performance, considering the mediating effect of their advice networks.

A survey on 222 subsidiary-unit managers (154 parent country nationals [PCNs] and 68 host country nationals [HCNs]) of a Korean MNE operating in China, Vietnam, Thailand, Singapore, Hungary and Slovakia was conducted. The authors analyzed the data using partial least square structural equation modeling, multigroup analysis and bootstrapping techniques.

PCN subsidiary managers with more prior international work experience manage better-performing units due to the strength of the manager’s advice networks across local parties. However, for HCN subsidiary managers, this study did not find such mediating roles of the size and strength of their advice networks in the MNE home country.

This study provides novel insights and empirical evidence about the effect of the length of prior international work experience of subsidiary managers on their advice-seeking networks and subsidiary-unit performance. In addition, it draws on and add to social capital theory about how international work experience impacts dealing with local businesses and the relationship with corporate headquarters.

The proposed model aims to consider the flying hours as a criterion to initiate maintenance operation. Based on this condition, aircraft must be checked before flying hours threshold is met. After receiving maintenance service, the model ignores previous flying hours and the aircraft can keep on flying until the threshold value is reached again. Moreover, the model considers aircraft age and efficiency to assign them to flights.

The aircraft maintenance routing problem (AMRP), as one of the most important problems in the aviation industry, determines the optimal route for each aircraft along with meeting maintenance requirements. This paper presents a bi-objective mixed-integer programming model for AMRP in which several criteria such as aircraft efficiency and ferrying flights are considered.

As the solution approaches, epsilon-constraint method and a non-dominated sorting genetic algorithm (NSGA-II), including a new initializing algorithm, are used. To verify the efficiency of NSGA-II, 31 test problems in different scales are solved using NSGA-II and GAMS. The results show that the optimality gap in NSGA-II is less than 0.06%. Finally, the model was solved based on real data of American Eagle Airlines extracted from Kaggle datasets.

The authors confirm that it is an original paper, has not been published elsewhere and is not currently under consideration of any other journal.

There is a growing body of literature discussing the green logistics practices (GLPs) that companies could introduce to reduce the logistics environmental impact. Current approaches also identify several influencing factors within firms that could serve as barriers to, or enablers of, GLPs. However, less is known about the role of extra-firm stakeholders, even though these are crucial to operationalizing green logistics effectively. This study merges current theoretical understanding with empirical evidence to provide a detailed stakeholder analysis of GLPs.

Using stakeholder theory as a theoretical lens, the authors aimed at offering a mid-range contribution by conducting multiple embedded case studies examining Italian logistics service providers and shippers. GLPs and the related influencing factors were examined as sub-units of analysis within broader companies' environmental sustainability strategies.

The authors identified cascading effects among factors influencing the adoption of GLPs (e.g. key economic factors are affected by external factors which also influence organizational and collaboration factors). These effects are moderated by interdependencies between primary and secondary stakeholders, and the study highlights the prominent involvement of secondary stakeholders, such as final consumers.

This paper contributes to better understanding how and why companies adopt GLPs, emphasizing the wide set of stakeholders involved and illustrating how different stakeholders impact on GLPs adoption by affecting a set of influencing factors. By combining insights from the available literature with contemporary empirical data, the authors emphasize how Logistics Service Providers (LSPs) and shippers can no longer address the adoption of GLPs as “focal companies”, but only as part of a “focal network of interconnected stakeholders”, all of them influencing GLPs adoption.

The work-from-home scheme (WFH) is increasingly being adopted in service firms. However, the blurred border between employees’ work and life can create work–life conflict (WLC) that negatively affects their well-being. Therefore, identifying factors that help employees overcome WLC and nurture their well-being is imperative. From a transformative service research (TSR) and personal psychology perspective, this study aims to explore the roles of service employee state of mindfulness and resilience in reducing WLC, alleviating its negative effects and ultimately nurturing their happiness.

A structural model was proposed. Data were collected from 339 WFH employees in various knowledge-based services such as professional services, information, education and training, financial consulting and marketing. Direct, indirect, mediating and moderating effects were estimated using the CB-SEM method.

Mindfulness is the overarching capability that helps reduce WLC and raise resilience. It nurtures WFH employee happiness not only directly but also via the mediation of resilience and WLC. Resilience, on the other hand, mediates the effect of mindfulness on happiness and moderates the negative impact of WLC on happiness.

Firms are recommended to organize mindfulness and resilience training programs, and encourage organizational- and job-related facilitators. WFH employees should actively participate in such programs and add them to their to-do-list practices.

To the best of the authors’ knowledge, this study is among the first empirical studies of employee mindfulness and resilience in the WFH context. It contributes to the TSR research stream and enriches the concepts of mindfulness and resilience by elucidating different mechanisms in which each of these personal qualities operates to help employees nurture happiness in this specific working condition.

The digitalization of schools has intensified in recent years. It is reflected in policy documents as well as in extensive investments in digital technology and professional development initiatives to promote digitalization. At the same time, attempts are being made to “tame” the same digitization sometimes by regulations banning smartphones in class. This study aims to examine how smartphones are interpreted by vocational teachers in Sweden using the theoretical lens of technological frames.

The data consist of ten semi-structured interviews with vocational teachers, representing eight vocational programs in Sweden.

The results show breadth in how teachers understand, interpret and relate to the smartphone in vocational education. The authors show how the smartphone often forms an integral part of professional work and is thus difficult to separate from vocational teaching and nurturing vocational competencies.

The authors’ contributions include using technological frames to explore how smartphones are interpreted and understood by vocational teachers by demonstrating how they relate to the nature of the smartphone, the strategy for the smartphone and the smartphone in use. The theoretical framework is used to interpret restrictions on technology use, in this case a smartphone, in education. The results could be of interest to researchers as well as to teachers, school leaders and policymakers.

The purpose of the study is to identify the soft skills and abilities that are crucial to success in the fields of operations management (OM) and supply chain management (SCM), using the O*NET database and the classification of a set of professional figures integrating values for task skills and abilities needed to operate successfully in these professions.

The study used the O*NET database to identify the soft skills and abilities required for success in OM and SCM industries. Correlation analysis was conducted to determine the tasks required for the job roles and their characteristics in terms of abilities and soft skills. ANOVA analysis was used to validate the findings. The study aims to help companies define specific assessments and tests for OM and SCM roles to measure individual attitudes and correlate them with the job position.

As a result of the work, a set of soft skills and abilities was defined that allow, through correlation analysis, to explain a large number of activities required to work in the operations and SCM (OSCM) environment.

The work is inherently affected by the database used for the professional figures mapped and the scores that are attributed within O*NET to the analyzed elements.

The information resulting from this study can help companies develop specific assessments and tests for the roles of OM and SCM to measure individual attitudes and correlate them with the requirements of the job position. The study aims to address the need to identify soft skills in the human sphere and determine which of them have the most significant impact on the OM and SCM professions.

The originality of this study lies in its approach to identify the set of soft skills and abilities that determine success in the OM and SCM industries. The study used the O*NET database to correlate the tasks required for specific job roles with their corresponding soft skills and abilities. Furthermore, the study used ANOVA analysis to validate the findings in other sectors mapped by the same database. The identified soft skills and abilities can help companies develop specific assessments and tests for OM and SCM roles to measure individual attitudes and correlate them with the requirements of the job position. In addressing the necessity for enhanced clarity in the domain of human factor, this study contributes to identifying key success factors. Subsequent research can further investigate their practical application within companies to formulate targeted growth strategies and make appropriate resource selections for vacant positions.

The rapid development of urban areas in Sleman District, Indonesia, has created new challenges for firefighting response services. One of the primary challenges is to identify the optimal locations for new fire stations, to improve service quality and maximize service coverage within the specified time.

This paper proposes a method for precisely calculating travel time that integrates delay time caused by traffic lights, intersections and congestion. The study highlights the importance of precise calculation of travel time in order to provide a more accurate understanding of the service area covered by the fire stations. The proposed method utilizes network analysis in ArcGIS, the analytical hierarchy process (AHP) and simple additive weighting (SAW) to accurately calculate travel time and to identify the best locations for new fire stations. The identification of new site was based on service safety, service quality, service costs and demographic factors and applied to the Sleman district in Indonesia.

The results showed that the total area covered by old and new fire stations decreased from 61% to 31.8% of the study area when the adjusted default speed scenario was implemented.

The results indicated that the default speed scenario could provide misleading information about the service area, while the adjusted default speed scenario improved service quality and maximized service coverage.

The proposed method provides decision-makers with an effective tool to make informed decisions on optimal locations for new fire stations and thus enhance emergency response and public safety.