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The lean inventory strategy can be a promising sustainable practice in the fashion retail industry. However, whether this strategy always has a positive impact on a firm’s financial performance has not been clarified in previous research. Thus, managers may hesitate to invest in implementing the lean inventory strategy. The present study investigates the boundary conditions of this strategy, i.e. the conditions under which it can improve firm performance.

Secondary longitudinal data were collected from 2005 to 2019 based on a survey of Japanese Business Structures and Activities conducted by the Ministry of Economy, Trade and Industry in Japan. The sample comprised 807 observations from 57 fashion retailers operating in the country. The research hypotheses were tested using a fixed-effect method.

This study found that IT intensity is the boundary condition of the strategy. Specifically, the lean inventory strategy has a positive effect on fashion retail companies’ profitability only when IT intensity is not zero. Moreover, this positive performance effect is strengthened by IT intensity.

This study considered the potential sustainability benefits of the lean inventory strategy in the fashion retail industry. The findings revealed that the strategy can serve as a sustainable practice for improving firm financial and environmental performance when IT intensity is present. This study provides valuable insights for fashion retail managers who handle both financial and environmental performance.

High levels of stress among students can adversely affect their wellbeing and academic performance. Effective stress management is crucial, yet traditional relaxation methods often pose challenges in implementation. Virtual reality (VR) relaxation, delivered through head-mounted displays (HMDs), offers an innovative approach to stress relief, promoting relaxation and restoring wellbeing. This study aims to review the feasibility, acceptability and effectiveness of VR relaxation for enhancing student wellbeing.

A comprehensive search of Embase, MEDLINE, PsychINFO and Web of Science databases was conducted. Studies using immersive, interactive, three-dimensional virtual environments via HMDs to measure or improve wellbeing, stress, relaxation or mood-related outcomes in post-secondary students were included. The methodological quality of studies was assessed using the Effective Public Health Practice Project (EPHPP) tool (PROSPERO: CRD42023396672).

This review included 24 studies (n = 1,811) published between 2007 and 2023. A majority of participants were university students across various disciplines. Virtual environments often featured natural audio-visual elements, showing that VR relaxation is feasible, acceptable and yields short-term improvements in wellbeing. Thirteen studies received “strong” EPHPP ratings, eight were rated “moderate” and four “weak.”

The limited number of randomised controlled trials and lack of long-term data necessitate cautious interpretation of results. Further rigorous research is recommended.

VR relaxation presents a promising intervention to reduce stress, enhance relaxation and improve mood among students.

This review highlights VR relaxation as a novel, practical solution for student wellbeing, contributing valuable insights to the field of mental health innovation.

The current study aims to explore the three dimensions of paternalistic leadership (i.e. moral leadership, benevolent leadership and authoritarian leadership) and their dual pathways of positive and negative influences on employees’ organizational citizenship behavior through the two aspects of trust (i.e. cognitive and affective trust).

Given that trust is pertinent in any human relationship, especially in Asian countries where bonding plays an important role, the current study investigated the relationship of each leadership style within paternalistic leadership on employees’ cognitive and affective trust in their leaders, employees’ organizational citizenship behavior and the processes involved. The current study employed a cross-sectional multilevel approach with 435 employees from 85 workgroups participating in the study.

As hypothesized, benevolent and moral leadership styles (but not the authoritarian leadership style) had a positive effect on employees’ cognitive and affective trust in their leaders and on employees’ organizational citizenship behavior. Cognitive and affective trust also mediated the relationships of benevolent and moral leadership styles with organizational citizenship behavior.

The study’s findings urge practitioners and human resources personnel to be aware of the dual effects that a paternalistic leader has on employees. To be specific, benevolent and moral leadership styles are conducive to employees’ work outcomes, whereas the authoritarian leadership style has a non-significant role in employees’ work outcomes.

Using the theoretical framework of social comparison theory (SCT), this study investigates the effects of employee envy on service sabotage behaviors in the hospitality industry. It further examines the complex dynamics of self-performance and job dissatisfaction in this context. Notably, this paper seeks to determine the potential moderating role of perceived employability in the interactions between service sabotage, employee envy, job dissatisfaction and self-performance.

Our research structure was divided into four distinct models. The findings of Model 1 highlight the significant impact of employee envy on service sabotage. The analysis in Model 2a shows that job dissatisfaction acts as a partial mediator in the employee envy and service sabotage linkage. On the other hand, Model 2b reveals self-performance as yet another partial mediator between envy-service sabotage relationships. In turn, Model 3 demonstrates that job dissatisfaction and self-performance play a serial mediation role in the envy-service sabotage relationship. In addition, our research shows that perceived employability effectively moderates the three proposed paths within these relationships.

Our research structure was divided into four distinct models. The findings of Model 1 highlight the significant impact of employee envy on service sabotage. The analysis in Model 2a shows that job dissatisfaction acts as a partial mediator in the employee envy and service sabotage linkage. On the other hand, Model 2b reveals self-performance as yet another partial mediator between envy-service sabotage relationships. In turn, Model 3 demonstrates that job dissatisfaction and self-performance play a serial mediation role in the envy-service sabotage relationship. In addition, our research shows that perceived employability effectively moderates the three proposed paths within these relationships.

Hotel managers must keep a close eye on their front-of-house staff to avoid any unintentional or direct interactions with customers. Equally important is the consistent and impartial treatment of all employees, which is an important consideration for managers to consider because it can help mitigate employee envy and job dissatisfaction.

This study seeks to enhance understanding of SCT by emphasizing perceived employability as a boundary influencing the relationships between these factors and desired outcomes in the hotel industry, such as job dissatisfaction, self-performance and service sabotage. This paper is an initial attempt to investigate the underlying mechanisms in the relationship between envy and service sabotage.

This study aims to apply deep convolutional neural network Mask-R-CNN algorithm based on transfer learning to realize the segmentation of online wear fragments.

Wear debris analysis is considered to be one of the most effective methods to maintain the condition of mechanical equipment. In this paper, the friction and wear testing machine was used to design pin-disk rotation, pin-disk reciprocation and four-ball test to produce cutting, sliding, laminar and fatigue debris. A semi-online sampling system was designed to collect ferrographic images containing various fragments. The images were rotated and flipped to augment the data and enhance the generalization ability of the model. The data set required for data analysis is established. Using COCO pre-trained Mask R-CNN data set as a benchmark, the region proposal network (RPN) is trained with labeled wear debris images to enhance the ability of RPN to recognize background and wear debris. Two transfer learning scenarios are tested in the network head of the Mask R-CNN.

The results show that the deep convolutional neural network is suitable for the automatic classification and detection of wear fragments. Through transfer learning and proper training configuration, the ferrographic image recognition based on Mask R-CNN achieves high accuracy.

The results show that the deep convolutional neural network is suitable for the automatic classification and detection of wear fragments. Through transfer learning and proper training configuration, the ferrographic image recognition based on Mask R-CNN achieves high accuracy.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-05-2024-0182/

This study aims to explore customer reactions to using chatbots in the airline industry and to understand the psychological factors influencing their preferences.

Study 1 assesses attitudes toward human versus chatbot service agents in customer service interactions with social presence theory as the theoretical foundation to corroborate prior research, whereas Study 2 applies motivated action theory to analyze the impact of an individual’s goal orientation traits (process and outcome) related to chatbot acceptance.

Results indicate that individuals with outcome-focused personality traits show a preference for human agents when addressing customer service issues, suggesting that psychological factors significantly impact technology acceptance.

This research contributes new insights into the understudied area of psychological predispositions affecting chatbot acceptance in service scenarios within the airline industry.

探讨消费者在航空行业使用聊天机器人的反应, 并分析影响其偏好的心理因素。

研究1以社会临场感理论为基础, 评估消费者对人工客服与聊天机器人的态度, 以验证现有研究。研究2运用动机行动理论, 分析个体目标导向特质（过程导向与结果导向）对聊天机器人接受度的影响。

研究发现, 具有结果导向特质的个体在处理客服问题时更倾向于选择人工客服, 表明心理因素对技术接受度有显著影响。

本研究为航空行业服务场景中聊天机器人接受度的研究提供了新视角, 填补了心理特质对技术采纳影响的研究空白。

Examining the impacts and specific paths of the green credit policy on the ESG peer effect of brown firms from the behavioral economics perspective.

We selected A-share listed companies from 2009 to 2022 as the research sample and constructed a difference-in-differences (DID) estimation model based on the issuance of the “Green Credit Guidelines” in 2012 as a natural experiment. From the perspective of behavioral economics, we examined the impact of green credit policies on the peer effect of ESG responsibility fulfillment of brown enterprises and the specific paths.

We find that the green credit policy significantly enhances the ESG peer effect of brown firms, which is asymmetric under a multilevel contextual reference.

We construct a peer ESG normative objective model under the new LIM framework, prove the existence of Nash equilibrium under any peer preference parameter ß and consider the peer ESG utility maximization function under green finance shocks.

The purpose of this study to brought new dimensions by inserting market conditions and investor sentiments as independent variable measure their impact on government policy formulation and sustainable development. This research also measures the moderating effective stakeholder engagement. Previous research has focused on demystifying the relationship between green bonds and sustainable development.

The analysis part of the research is initiated by factor analysis on the sample size of 100. After the construction of appropriate statements matching the research objective, it was circulated to the respondents of northern region of India. The sampling technique was random in nature through which data analysis on 700 respondents was done. For meeting research objectives present research applies PLS algorithm on the conceptual model framed through review of literature.

Out of all independent variables green bond issuance is having statistically significant impact on government policy formulation and investors’ sentiment is having statistically significant impact on sustainable development. Rest all other pairs are statistically insignificant. For an investor, it is necessary to understand that how its sentiments impacts government policy formulation and the health of ecology.

The research produced results with management implications for practitioners and policy makers that are very significant to the fields of sustainability, green finance and environmental policy. Green bonds also influence government policy, illustrating how green financing may revolutionize environmental laws and regulations.

The social implications of this revelation are considerable. The research enhances knowledge about sustainable development by emphasizing the importance of green bonds in supporting environmentally friendly activities. It allows for transparent reporting, increasing social accountability and reputation while attracting environmentally conscious consumers and fostering community trust. According to the survey, investor sentiment and their enthusiasm for eco-friendly investments may push more money to efforts that are good for society and the environment. This study enhances consciousness about sustainable finance, which has the potential to inspire beneficial social shifts towards a more environmentally and socially equitable future.

These social ramifications manifest themselves in various socioeconomic and environmental issues of the society in addition to credit and public policy. Second, it is evident that green bond emissions are influencing government policy, demonstrating the power of financial instruments to encourage environmentally beneficial social outcomes by providing officials with an incentive to modify environmental regulations.

In today’s digital age, where information spreads faster than ever, viral marketing has emerged as a powerful strategy for businesses to reach their target audience and achieve exponential growth. Despite the growing importance of viral marketing among academicians and practitioners, the existing research in this area remains fragmented, with various approaches and factors scattered throughout the literature. This fragmentation raises concerns as a lack of alignment may lead to misinterpretation and limit future research. To address this gap, the present study aims to systematically review the literature published on viral marketing.

The study utilizes a systematic literature review (SLR) methodology. About 671 studies were initially identified, and 105 were included in the literature review after screening for eligibility.

The applied approach sheds light on the publication patterns, geographical scope, industrial context, theoretical context, publication sources and research methods employed in studies. Based on the analysis of the literature, the study identifies five major themes: antecedents influencing customer viral decisions, consequences of viral marketing, disseminating channel features, mutation and replication and viral measurement. A theoretical framework is proposed to explain the viral marketing process.

The study’s implications are relevant for practitioners looking to utilize viral marketing strategies and researchers seeking a deeper understanding of the phenomenon. Furthermore, identifying research gaps and proposing future research questions provide opportunities for further investigation in this evolving field.

The paper offers an up-to-date and comprehensive synthesis of existing literature on viral marketing up to January 2025, providing a valuable resource for researchers, marketers and practitioners seeking to understand the latest developments and trends in this dynamic field.

With the advent of Industry 5.0, digital transformation (DT) has received much attention in the tourism industry. Therefore, this research aims to provide a thematic map of the DT of tourism in Industry 5.0 and then provide a model for tourists’ acceptance of Industry 5.0 digital technologies.

First, a systematic literature review was done to provide the thematic map of this field, and the data were analyzed using the R-Tool. In the second step, a meta-analysis of all available studies on technology acceptance by tourists in Industry 5.0 was conducted, and the data were analyzed using CMA3 software.

The findings are divided into four main themes: motor themes (acceptance of technology by tourists); basic themes (smart tourism through digital technologies); niche themes (digital transformation of tourism in small and medium-sized enterprises) and essential or declining themes (digital transformation in destination marketing). The second part showed that performance expectancy (PE), effort expectancy (EE), social influence (SI), facilitating conditions (FC), hedonic motivation (HM), price value (PV) and habit (HB) positively affect behavioral intention (BI). FC, HB and BI have a positive effect on use behavior (UB). Age variable moderates the impact of FC, HM and HB on BI but does not moderate the impact of PV on BI. Age variable moderates the effect of HB on UB. Gender variable moderates the impact of HB on UB but does not moderate the effect of FC, HM, PV and HB on BI. The experience variable moderates the effect of FC on BI, HB on UB and BI on UB but does not moderate the impact of HM and HB on BI.

This research is the first to present a thematic map of DT in the tourism industry in Industry 5.0. It is also the first research demonstrating the digital technology acceptance model by tourists in Industry 5.0.