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This study aims to investigate whether higher value creation leads to higher value appropriation and to identify the boundary conditions in a buyer–supplier relationship that can explain why a particular supplier can appropriate higher value than others.

The study uses questionnaire surveys. The sample of the survey has 150 publicly-listed supplier firms in Taiwan. The unit of analysis is the buyer–supplier relationship.

In the buyer–supplier relationship, suppliers’ bargaining power, partnership and a supplier’s original brand manufacturing (OBM) business can strengthen the positive relationship between value creation and value appropriation.

This study adopts the unilateral viewpoint of suppliers; however, some constructs might require dyadic evaluation. This study only explores the spillover effect of OBM business on the relationship between value creation and appropriation.

The spillover effect of a supplier’s OBM business in a buyer–supplier relationship allows the buyer to share more common benefits and the supplier to capture more private benefits as compensation. By broadening its customer base, a supplier can increase its bargaining power. A supplier can also maintain a strategic partnership with each essential buyer.

To avoid the dark-side effect of partnership, the model provides the contingency that a supplier can capture more value from a buyer–supplier relationship.

The purpose of this paper is to investigate what factors can affect individuals’ knowledge sharing on social media from the perspectives of personality traits and social capital.

A theoretical model was developed with reference to the personality traits theory and the social capital theory. Accordingly, a questionnaire was designed to collect the individuals’ ideas on knowledge sharing on social media and further test the model. The questionnaire was then distributed to two LINE groups. Finally, the collected data were analyzed using the partial least squares (PLS) approach.

Personality traits not only directly affect knowledge sharing, but also indirectly influence it via social capital. Of all personality traits, agreeableness, openness and extraversion directly and indirectly influence knowledge sharing.

Knowledge sharing is undertaken by individuals and social groups. It starts with individuals and then diffuses to other members of a group.

Group managers have to identify the members who are friendly, open-minded or extroverted and encourage them to act as the bellwethers for knowledge sharing under an effective regulatory regime, through which intra-group knowledge sharing can be promoted.

This study introduces a new model to explore knowledge sharing on social media from individual and social perspectives. It illustrates what will affect individuals’ knowledge sharing on social media.

Forecasting population movement trends is crucial for implementing effective policies to regulate labor force growth and understand demographic changes. Combining migration theory expertise and neural network technology can bring a fresh perspective to international migration forecasting research.

This study proposes a conditional generative adversarial neural network model incorporating the migration knowledge – conditional generative adversarial network (MK-CGAN). By using the migration knowledge to design the parameters, MK-CGAN can effectively address the limited data problem, thereby enhancing the accuracy of migration forecasts.

The model was tested by forecasting migration flows between different countries and had good generalizability and validity. The results are robust as the proposed solutions can achieve lesser mean absolute error, mean squared error, root mean square error, mean absolute percentage error and R² values, reaching 0.9855 compared to long short-term memory (LSTM), gated recurrent unit, generative adversarial network (GAN) and the traditional gravity model.

This study is significant because it demonstrates a highly effective technique for predicting international migration using conditional GANs. By incorporating migration knowledge into our models, we can achieve prediction accuracy, gaining valuable insights into the differences between various model characteristics. We used SHapley Additive exPlanations to enhance our understanding of these differences and provide clear and concise explanations for our model predictions. The results demonstrated the theoretical significance and practical value of the MK-CGAN model in predicting international migration.

This study presents a systematic literature review (SLR) of the interdisciplinary literature on drones in last-mile delivery (LMD) to extrapolate pertinent insights from and into the logistics management field.

Rooting their analytical categories in the LMD literature, the authors performed a deductive, theory refinement SLR on 307 interdisciplinary journal articles published during 2015–2022 to integrate this emergent phenomenon into the field.

The authors derived the potentials, challenges and solutions of drone deliveries in relation to 12 LMD criteria dispersed across four stakeholder groups: senders, receivers, regulators and societies. Relationships between these criteria were also identified.

This review contributes to logistics management by offering a current, nuanced and multifaceted discussion of drones' potential to improve the LMD process together with the challenges and solutions involved.

The authors provide logistics managers with a holistic roadmap to help them make informed decisions about adopting drones in their delivery systems. Regulators and society members also gain insights into the prospects, requirements and repercussions of drone deliveries.

This is one of the first SLRs on drone applications in LMD from a logistics management perspective.

This paper aims to provide researchers and practitioners with a consumer-focused alternative for considering the integration of artificial intelligence (AI) into services.

The paper reviews and critiques the most popular frameworks for addressing AI in service. It offers an alternative approach, one grounded in social psychology and leveraging influential concepts from management and human–computer interaction.

The frameworks that dominate discourse on this topic (e.g. Huang and Rust, 2018) are fixated on assessing technology-determined feasibility rather than consumer-granted permissibility (CGP). Proposed is an alternative framework consisting of three barriers to CGP (experiential, motivational and definitional) and three responses (communicate, motivate and recreate).

The implication of this research is that consistent with most modern marketing thought, researchers and practitioners should approach service design from the perspective of customer experience, and that the exercise of classifying service occupation tasks in terms of questionably conceived AI intelligences should be avoided.

Indicative of originality, this paper offers an approach to considering AI in services that is nearly the polar opposite of that widely advocated by e.g., Huang et al., (2019); Huang and Rust (2018, 2021a, 2021b, 2022b). Indicative of value is that their highly cited paradigm is optimized for predicting the rate at which AI will take over service tasks/occupations, a niche topic compared to the mainstream challenge of integrating AI into service offerings.

Recent advancements in the field of organizational psychology have transformed the employees’ perceptions related to the reactions of the employment relationship. The main aim of the study is to explore the consequences of psychological contracts among the nursing staff and how to provide better patient care and quality service in the health-care system as nurses play a pivotal role in the context of Pakistan. Significantly, this study attempts to bridge the research gap by exploring consequences of psychological contracts. Drawing on the social exchange theory, this study examined the psychological contracts of nurses and their reactions to the perceived violation.

This research adopted a qualitative method and was based on an exploratory approach. Data were collected through in-depth semi-structured interviews from 21 nurses working in public, private and charity hospitals in Karachi, Pakistan. The thematic content analysis is employed for the analysis of data by using NVivo software.

The study identified the relational and transactional elements related to the psychological contract of nurses who predominantly consisted of supervisor support, autonomy, tangible/intangible rewards and trust. The intrinsic motivation which relates to their devotion to work was found as an additional element to balance their psychological contract. This research also establishes that the psychological contract of nurses is being violated in their work settings.

By highlighting the importance of psychological contract breach, the findings demonstrate that health-care institutions should take measures to cope with psychological contract breach issues at the workplace.

This study contributes to the body of knowledge by exploring psychological contract breach. Substantially, there are rare studies conducted on psychological contract breach among nurses in developing country context (Pakistan). However, this study adds to the previous studies related to the psychological contract of nurses in the context of Pakistan by using social exchange theories. Finally, this study enables the management of healthcare to balance the psychological contract issues effectively.

This study attempts to fill the research gap by extending sustainability literature and providing empirical evidence that considers sustainability marketing commitment (SMC) as a fundamental attribute of effective marketing strategy that consequently improves tourism service quality, as represented by service attractiveness.

In the current study, data was collected from 313 tourism and hospitality firms. To test the model, this study applied structural equation modeling (SEM) to investigate the relationships among environmental strategy, SMC, supplier trust and service attractiveness in a mediation-moderation setting.

The results indicate that the multiple mediation effects of environmental strategy may indirectly influence tourist attractiveness through SMC and tourism services. The two-way moderating effects reveal that supplier trust and socialization strengthen the service attractiveness development process, while three-way interaction discovered that socialization and supplier trust positively moderate the relationships between tourism services and service attractiveness.

Sustainable strategy is a future trend for tourism business management; however, unknown to most is the role of marketing and environmental strategy in tourism business due to lack of integration with concepts in marketing strategy, with the multidimensionality of tourism services, and with the function of trust and socialization, critically undermining analyses of service attractiveness. This paper combines corporate sustainability and sustainability marketing methods to explore how an environmental strategy can improve tourism services and enhance a destination's attractiveness based on a mediation-moderation mechanism.

Technostress reduces employees' work performance and increases their turnover intentions, such that technostress harms organizations' success. This paper investigates how the digital mindset of employees, reflecting their cognitive filter while using digital technologies, influences reactions to techno-stressors.

In this quantitative study, the authors conducted a survey among 151 employees who regularly use digital technologies and encounter various techno-stressors in their daily work. To build this research model and evaluate the influence of employees’ digital mindset on technostress, the authors followed arguments from the transactional model of stress. The authors evaluated our research model using the covariance-based structural equation model.

The study findings reveal that employees’ digital mindset influences technostress. Employees with high levels of digital mindset react with less adverse effects on perceived techno-stressors. Further, the authors find that employees with high levels of digital mindset perform well and are satisfied with their job. The authors contribute to technostress research by revealing that digital mindset buffers the adverse effects of techno-stressors. The authors also contribute to research on digital mindset by showing that it influences psychological and behavioral reactions to techno-stressors.

This study develops and empirically tests an integrated model of technostress to explain how digital mindset mitigates technostress. The study findings outline relevant research avenues for studies investigating employees’ characteristics and technostress.

Recently, electric vehicles have been widely used in the cold chain logistics sector to reduce the effects of excessive energy consumption and to support environmental friendliness. Considering the limited battery capacity of electric vehicles, it is vital to optimize battery charging during the distribution process.

This study establishes an electric vehicle routing model for cold chain logistics with charging stations, which will integrate multiple distribution centers to achieve sustainable logistics. The suggested optimization model aimed at minimizing the overall cost of cold chain logistics, which incorporates fixed, damage, refrigeration, penalty, queuing, energy and carbon emission costs. In addition, the proposed model takes into accounts factors such as time-varying speed, time-varying electricity price, energy consumption and queuing at the charging station. In the proposed model, a hybrid crow search algorithm (CSA), which combines opposition-based learning (OBL) and taboo search (TS), is developed for optimization purposes. To evaluate the model, algorithms and model experiments are conducted based on a real case in Chongqing, China.

The result of algorithm experiments illustrate that hybrid CSA is effective in terms of both solution quality and speed compared to genetic algorithm (GA) and particle swarm optimization (PSO). In addition, the model experiments highlight the benefits of joint distribution over individual distribution in reducing costs and carbon emissions.

The optimization model of cold chain logistics routes based on electric vehicles provides a reference for managers to develop distribution plans, which contributes to the development of sustainable logistics.

In prior studies, many scholars have conducted related research on the subject of cold chain logistics vehicle routing problems and electric vehicle routing problems separately, but few have merged the above two subjects. In response, this study innovatively designs an electric vehicle routing model for cold chain logistics with consideration of time-varying speeds, time-varying electricity prices, energy consumption and queues at charging stations to make it consistent with the real world.

The present study assesses the impact resistance of the shear thickening fluids-filled (STFs-filled) foam through drop-hammer impact tests.

The maximum residual impact load and specific impact energy absorption rate of STF-filled foam are studied with varying thickness (4–14 mm), densities (0.35–0.6 g/cm3) and hardness (40–50 Rockwell Hardness C Scale (HRC)) under different ambient temperatures (−20−20 °C) and impact energies (25–75 J).

The following conclusions are obtained from this study: (1) the higher the impact energy, the greater the maximum residual impact force and energy absorption efficiency of the material; (2) the impact resistance of STF-filled foam can be improved with the decrease of ambient temperature, achieving the highest energy absorption rate at −10?. (3) STF-filled foam substrate has the highest impact resistance, the lowest maximum residual impact force and the highest energy absorption coefficient when the density is 0.35  g/cm3, the hardness is 45HC and the thickness is 10 mm.

This is the first paper to analyze the impact of both environmental factors and material properties on the impact resistance of STF-filled foam. The results show that the decrease in temperature and the increase in hardness can enhance the impact resistance of STF-filled foam.