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The present work investigated the effect of corporate social responsibility and top management support on employee ecological behaviour (EEB) with the mediating role of green culture and green commitment. Social identity theory (SIT) was used to describe the association between green culture, green commitment and EEB. Further, a conceptual model that summarises the interaction between perceived corporate social responsibility, top management support, green commitment, green culture and the adoption of ecological behaviour was developed.

The paper opted for a quantitative design using convenience sampling by collecting the data through a structured questionnaire gathered from 308 academics working in five Malaysian higher education institutions.

Corporate social responsibility and top management support positively influence green culture and commitment. Moreover, green commitment positively influenced EEB and fully mediated the relationship between corporate social responsibility and EEB and between top management support and EEB.

The academic staff of universities was the target population of this research. Nevertheless, universities have a diverse population with complex activities that can affect the implementation of a sustainable workplace within the campus. Future research should also examine non-academic staff, including administrative, technical and operational staff, due to different employees' perceptions.

As far as the authors know, this is the first study to assign the mediator role to green culture in a relationship between top management support and EEB amongst academic staff in the Malaysian context. Future research should consider other intervening variables that influence adopting ecological behaviour.

The purpose of this study is the hydrothermal analysis of the natural convection phenomenon within the heat exchanger containing nanofluids using the lattice Boltzmann method (LBM).

The thermal conductivity as well as dynamic viscosity of the CuO–water nanofluid is estimated using the Koo-Kleinstreuer-Li model. The LBM has been used with unique modifications to make it flexible with the curved boundaries. The local as well as total entropy generation assessment, local Nusselt variation, as well as heatline visualization are used.

The solid volume percentage of the CuO–water nanofluid, a range of Rayleigh numbers (Ra) and thermal settings of internal operational fins and bodies are all factors that have been thoroughly researched to determine their effects on entropy production, heat transfer efficiency and nanofluid flow.

The originality of this work is using a novel numerical method (i.e. curved boundary LBM) as well as the local/volumetric second law analysis for the application of heat exchanger hydrothermal analysis.

Studies on developed economies showed that imposing taxes on animal-based foods could effectively reduce agricultural greenhouse gas emissions (AGHGEs), while this taxation may not be appropriate in developing countries due to the complex nutritional status across income classes. Hence, this study aims to explore optimal tax rate levels considering both emission reduction and nutrient intake, and examine the heterogenous effects of taxation across various income classes in urban and rural China.

The authors estimated the Quadratic Almost Ideal Demand System model to calculate the price elasticities for eight food groups, and performed three simulations to explore the relative optimal tax regions via the relationships between effective animal protein intake loss and AGHGE reduction by taxes.

The results showed that the optimal tax rate bands can be found, depending on the reference levels of animal protein intake. Designing taxes on beef, mutton and pork could be a preliminary option for reducing AGHGEs in China, but subsidy policy should be designed for low-income populations at the same time. Generally, urban residents have more potential to reduce AGHGEs than rural residents, and higher income classes reduce more AGHGEs than lower income classes.

This study fills the gap in the literature by developing the methods to design taxes on animal-based foods from the perspectives of both nutrient intake and emission reduction. This methodology can also be applied to analyze food taxes and GHGE issues in other developing countries.

Assistive technology has been developed to assist the visually impaired individuals in their social interactions. Specifically designed to enhance communication skills, facilitate social engagement and improve the overall quality of life, conversational assistive technologies include speech recognition APIs, text-to-speech APIs and various communication tools that are real. Enable real-time interaction. Using natural language processing (NLP) and machine learning algorithms, the technology analyzes spoken language and provides appropriate responses, offering an immersive experience through voice commands, audio feedback and vibration alerts.

These technologies have demonstrated their ability to promote self-confidence and self-reliance in visually impaired individuals during social interactions. Moreover, they promise to improve social competence and foster better relationships. In short, assistive technology in conversation stands as a promising tool that empowers the visually impaired individuals, elevating the quality of their social engagement.

The main benefit of assistive communication technology is that it will help visually impaired people overcome communication barriers in social contexts. This technology helps them communicate effectively with acquaintances, family, co-workers and even strangers in public places. By enabling smoother and more natural communication, it works to reduce feelings of isolation and increase overall quality of life.

Research findings include successful activity recognition, aligning with activities on which the VGG-16 model was trained, such as hugging, shaking hands, talking, walking, waving and more. The originality of this study lies in its approach to address the challenges faced by the visually impaired individuals in their social interactions through modern technology. Research adds to the body of knowledge in the area of assistive technologies, which contribute to the empowerment and social inclusion of the visually impaired individuals.

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 study examines the effect of occupational stress on turnover intention of employees working in the banking industry. The authors examine the mediating effects of service climate and emotional regulations of the employees in the relationship between occupational stress and intention to leave the organization.

This study followed stratified sampling technique for data collection from employees of ten commercial banks based on the banks' financial performance of top 5 and bottom 5 out of 27 banks. Data were collected at 2 stages, first from 465 employees for occupational stressors and second from 408 employees among the participants in the first stage for turnover intention, service climate and emotional regulation. Harman’s one-factor test was conducted to examine the common method bias. Confirmatory factor analysis (CFA), regression analysis and Preacher and Hayes Process Macro approach were used to examine mediation effect.

Three factors, namely workload (WL), role ambiguity and growth opportunity expectations were identified as the occupational stressors in the banking industry, predicting a positive relation of overall occupational stress to the intention to turnover. Service climate and the employees’ emotion regulation ability mediate the relationship between stress and turnover intention. Results also revealed no significant role of control variables in predicting occupational stress and turnover intention.

This study implies that the WL, role ambiguity and growth opportunity expectations of the employees cause stress in employees which may lead to have turnover intention. In order to get success in competitive environment, managers of banking industry can address stressors by enhancing service climate and formulating policies and programs to strengthen the emotion regulation which is evidence to strengthen the reciprocity approach of social exchange theory in employees’ commitment.

This study contributes to the social exchange theory and attempts to fulfill the gaps in empirical research on personnel psychology, human capital\ and organization management in developing countries.

Presently, 6 Degree of Freedom (6DOF) visual pose measurement methods enjoy popularity in the industrial sector. However, challenges persist in accurately measuring the visual pose of blank and rough metal casts. Therefore, this paper introduces a 6DOF pose measurement method utilizing stereo vision, and aims to the 6DOF pose measurement of blank and rough metal casts.

This paper studies the 6DOF pose measurement of metal casts from three aspects: sample enhancement of industrial objects, optimization of detector and attention mechanism. Virtual reality technology is used for sample enhancement of metal casts, which solves the problem of large-scale sample sampling in industrial application. The method also includes a novel deep learning detector that uses multiple key points on the object surface as regression objects to detect industrial objects with rotation characteristics. By introducing a mixed paths attention module, the detection accuracy of the detector and the convergence speed of the training are improved.

The experimental results show that the proposed method has a better detection effect for metal casts with smaller size scaling and rotation characteristics.

A method for 6DOF pose measurement of industrial objects is proposed, which realizes the pose measurement and grasping of metal blanks and rough machined casts by industrial robots.

The study seeks to analyze the influence of sensory experience on perceived environmental sustainability and word-of-mouth (WOM) of tourists and residents. The study also tests the moderation effect of satisfaction on the relationship between perceived environmental sustainability and WOM.

The study was conducted in Sikkim, a state in the northeastern part of India, which is regarded as the world's first organic state. The study was done in two phases. In the first phase, the data were collected from the tourists. And in the second phase, data were collected from the residents. A structured questionnaire was distributed to 700 tourists and residents in Sikkim. Out of these only 484 responses were considered for the study. Multivariate analyses were done using SPSS software and packages like Process Macro, and Amos to test the hypotheses.

The findings of the study indicated that sensory experience significantly influences perceived environmental sustainability and WOM. The study model fit with GFI = 0.955, CFI = 0.946 NFI = 0.929 and RMSEA = 0.07. The findings also indicate that satisfaction moderates the relation between sensory experience and word-of-mouth with a p value = 0.018.

The study was conducted in Sikkim and it used a convenience sampling method. Therefore, the study cannot be generalized.

An emphasis on building an organic brand image can positively impact the local community. A study of this kind will encourage the community to work toward sustainable development.

The study is unique as it explores the evaluation of destination environmental sustainability. And it is one of the first to test the impact of satisfaction in the relationship between the independent and dependent variables in the context of the tourism experience.

This research draws on drive reduction theory and mental accounting theory to understand how the prospect of reselling used items can influence consumer feelings of consumption guilt and impact their willingness to purchase new products.

We conducted two studies with between-subjects designs to explore this relationship. In Study 1, we examined the correlation between consumers' perceived guilt and their willingness to buy a new product, considering their awareness of the product’s resale potential. Study 2 delved into the aspect of reselling a similar old product already owned by the consumer.

The findings suggest three key insights. First, consumers' awareness of resale potential significantly affects their guilt perception and purchasing decisions. Second, the resale reference price (RRP) can decrease guilt perception but increase the intention to buy a new product. Lastly, when consumers are aware of the resale value of a previously owned product that is similar to the desired new product, the effect of the RRP on their purchasing intent is mediated by consumer guilt.

This research fills a theoretical gap by empirically exploring the emotional motivations behind consumer resale behavior. It presents a novel perspective on how resale activities can shape feelings of guilt and impact purchasing decisions. This offers important implications for understanding the dynamics of consumer behavior in the second-hand market.

The study seeks to evaluate the effect of capital adequacy and competition on the liquidity creation of Kenyan commercial banks.

Unbalanced panel data from 36 Kenyan commercial banks with licenses from 2001 to 2020 is used in the study. The generalized method of moments (GMM), a two-step system, is employed in the investigation. To increase the robustness and prevent erroneous findings, serial correlation tests and instrumental validity analyses are used. The methodology developed by Berger and Bouwman (2009) is used to estimate the commercial banks' levels of liquidity creation.

The study supports the financial fragility-crowding out hypothesis by finding a significant negative effect of capital adequacy on the liquidity creation of commercial banks. The research also identifies a significant inverse relationship between competition and liquidity creation, depicting competition's value-destroying effect.

A trade-off exists between capital adequacy and liquidity creation, which must be carefully evaluated as changes in capital requirements are considered. The value-destroying effect of competition on liquidity creation presents a case for policy geared toward consolidating banks' operations through possible mergers and acquisitions.

To the best of the authors' knowledge, this is the first study to empirically offer evidence concurrently on the effect of competition and capital adequacy on the liquidity creation of commercial banks in a developing economy such as Kenya. Additionally, the authors employ a novel measure of competition at the firm level.