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We examined who is more likely to use flexible work arrangements (FWAs) to alleviate work-family conflict (WFC) and under what conditions the use of FWAs actually reduces WFC.

We tested the model using survey data collected at two time points from 217 employees.

Proactive employees are more likely to use flextime to alleviate WFC (b = −0.03; 95% biased-corrected CI: [−0.12, −0.01]) and this mediation relationship is not moderated by their level of low work-to-nonwork boundary permeability. In addition, only when proactive employees have a low work-to-nonwork boundary permeability does their use of flexplace alleviate WFC (b = −0.07, 95% bias-corrected CI: [−0.1613, −0.0093]).

We expand our understanding of who is more likely to utilize FWAs by identifying that employees with proactive personality are more likely to use flextime and flexplace. We also advance our understanding regarding the conditions whereby FWA use helps employees reduce WFC by identifying the moderating role of work-to-nonwork boundary permeability on the relationships between both flextime and flexplace use on WFC.

This study is based on the role congruity theory that examines the association between top management team (TMT) gender diversity and corporate social responsibility (CSR) performance.

This study uses data from the Taiwan Economic Journal database and the Market Observation Post System provided by the Taiwan Stock Exchange. The sample consists of 4,140 annual observations of Taiwanese-listed companies in the electronics industry from 2016–2020.

The results revealed that TMT gender diversity is positively associated with CSR performance, and TMT international experience strengthens the positive association between TMT gender diversity and CSR performance.

CSR is imperative. The TMT’s gender diversity aligns with current environmental trends and social expectations, driven for CSR implementation essential. This diverse configuration enables the TMTs to address corporate adaptability and maintain global competitiveness.

The findings contribute significantly to the literature on TMT gender diversity by extending the application of role congruity theory beyond individual to team-level contexts and across gender boundaries. By incorporating diverse capabilities such as international experience within TMTs, the authors identify key boundary conditions that foster CSR. This expansion not only aligns with practical realities but also opens new avenues for research into the dynamics of diverse management teams.

The use of digital channels to promote products and services is experimenting with an unprecedented boom in promotion and communication marketing campaigns; airports such as Los Angeles (IATA: LAX) in the United States, Orlando International (IATA: MCO) in the United States, Schiphol Amsterdam (IATA: AMS) in the Netherlands or Changi airport (IATA: SIN) in Singapore are pioneers and recognised experts in marketing communication and technical aspects of promotion campaigns. The brand image of airports is a great opportunity to universalise loyalty marketing and price promotion for airport business portfolios. For this reason, in this chapter, we speak about neuromarketing science, which is a marketing discipline that uses medical techniques to understand how our central nervous system reacts to marketing stimuli. This is helping companies and airports get more consumer insights through digital channels.

Microblogs are communication platforms for companies and consumers that challenge companies' brand marketing strategies. This paper provides a theoretical basis for expanding microblog applications and a practical basis for improving the effectiveness of brand marketing.

The authors use factor analysis to extract the factors of microblog user influence and construct a structural equation model to reveal the interaction mechanism of the influencing factors. Additionally, the authors clarify the promotion and enhancement effects of these factors.

Microblog user influence can be converted into richness, interaction and value factors. The richness factor significantly affects the latter two, whereas the interaction factor does not affect the value factor.

First, the sample used is limited to media industry practitioners. To increase generalizability, diverse groups should be included in future studies. Second, this model's theoretical explanatory ability can be further developed by adding other meaningful factors beyond the existing ones.

This study analyzes the factors of microblog user influence in China and validates the relevant elements. As a result, it improves the influence research on social media users and benefits the practice of information recommendation and microblog marketing.

The purpose of this study is to develop a framework for the perceived intelligence of VAs and explore the mechanisms of different dimensions of the perceived intelligence of VAs on users’ exploration intention (UEI) and how these antecedents can collectively result in the highest level of UEI.

An online survey on Amazon Mechanical Turk is employed. The model is tested utilizing the structural equation modeling (SEM) and fuzzy-set qualitative comparative analysis (fsQCA) approach from the collected data of VA users (N = 244).

According to the SEM outcomes, perceptual, cognitive, emotional and social intelligence have different mechanisms on UEI. Findings from the fsQCA reinforce the SEM results and provide the configurations that enhanced UEI.

This study extends the conceptual framework of perceived intelligence and enriches the literature on anthropomorphism and users’ exploration. These findings also provide insightful suggestions for practitioners regarding the design of VA products.

The purpose of this paper is to determine the most efficient hotels in the Indian hotel industry, the competitive positioning of these hotels, and the factors that affect their efficiency change.

This study conducts a two-stage analysis and uses data envelopment analysis (DEA) and Global Malmquist productivity index (MPI) approach in the first stage to calculate the managerial performance of a panel of 63 Indian hotels in 2019–2020 and their efficiency change from 2009–2010 to 2019–2020. Bootstrapped generalized least square (GLS) approach is applied in the second stage to evaluate the impact of contextual variables on efficiency change.

Using the results of the first stage analysis, the authors categorized the 63 Indian hotels into 7 distinct clusters. These clusters represent different levels of competitiveness and pace of growth. The GLS regression reveals a U-shaped relationship between hotel size and efficiency change and a negative relationship between pro social investments and efficiency.

This is the first study in the hotel industry that has used global MPI as a measure of efficiency change in the first stage and GLS in the second stage. In the Indian context, to the best of authors’ knowledge, no such study exists.

The purpose of this paper is to analyze research trends on “Wearable devices in textile filed” from 2010 to 2023 and determine the important keywords, nations and journals associated with this topic.

Utilizing journal literature on wearable devices from the 2010 to 2023 Web of Science (WoS) database, this study employs VOSviewer, biblioshiny of the R software package and the specialized software CiteSpace to generate knowledge graphs for measuring retrieval outcomes.

The research on wearable devices integrated into textiles between 2010 and 2023 can be divided into three stages: initial slow progress, subsequent rapid advancement and final slow progress, indicating a general rise in the quantity of published material. The terms “fabrication,” “wearable electronics” and “design” are closely linked in this field. China is the most globally networked country in this field, according to the World Collaboration Map. NANO ENERGY ranked first in the number of articles published in journals, with 18 articles and 1,151 citations.

The study identified the present state and research trends in the field of “Wearable devices in textile filed,” offering valuable information for researchers to enhance their understanding of the field’s progress.

This paper aims to explore the characteristics of lifting accidents and the significance of influencing factors and explain the causes from the perspective of human factors, thereby achieving a more accurate understanding of and prevention of lifting accidents.

A mixed simulation model for prefabricated component lifting is established by combining discrete event simulation (DES) with the system dynamics (SD) method. In addition, essential parameters and relationships within the system dynamics model are determined through survey questionnaires. Finally, the human factors analysis and classification system (HFACS) is used to analyze the cause of the accident.

The results show that workers falling from height and workers struck by objects are the most frequent types of lifting accidents. In 2072 experiments, these two types of accidents occurred three and five times, respectively. Besides, the links of “crane movement,” “component binding,” “component placement” and “component unhooking” are particularly prone to lifting accidents. In addition, the completeness of emergency plans, failure to observe the status of the tower crane and lack of safety education and training have emerged as primary influencing factors contributing to the occurrence of lifting accidents.

The findings of the study can serve as a reference basis for practitioners, enabling them to preemptively identify possible risk accidents and adopt corresponding measures to prevent them, ensuring the safety and property of practitioners. Additionally, targeted suggestions and innovative ideas are provided to enhance the safety guarantee of the lifting industry and promote its healthy and stable development through a more concrete theoretical foundation and practical guidance.

The expansion of online shopping aligned with challenging economic conditions has contributed to increasing fraudulent retail product returns. Retailers employ numerous interventions typically determined by embedded perspectives within the company (supply side) rather than consumer-based assessments of their effectiveness (demand side). This study aims to understand how customers evaluate counter-fraud measures on opportunistic returns fraud in the UK. Based on the fraud triangle and the theory of planned behaviour, we develop an empirically informed framework to assist retail practice.

We collected 485 valid survey responses about consumer attitudes regarding which interventions are effective against different types of returns fraud. First, a principal component section evaluates the policies' effectiveness to identify any policy grouping that could help prioritise specific sets of policies. Second, cluster analysis follows a two-stage approach, where cluster size is determined, and then survey respondents are partitioned into subgroups based on how similar their beliefs are regarding the effectiveness of anti-fraud policies.

We identify policies relating to perceived effectiveness of interventions and create customer profiles to assist retailers in conceptualising potential opportunistic fraudsters. Our product returns fraud framework adopts a consumer perspective to capture the perceived behavioural control of potential fraudsters. Results suggest effectiveness of different types of interventions vary between different types of consumers, which leads to the development of propositions to combat the fraud.

This study is unique in assessing the perceived effectiveness of a range of interventions based on data collection and advanced analytics to combat fraudulent product returns in omnichannel retail.

Although the importance and variety of emotions have been emphasized in existing literature, studies on discrete emotions remain limited. This study aims to propose a method for more precise recognition and calculation of emotions in massive amounts of online data on attraction visitor experiences and behaviour, by using discrete emotion theory.

Using HowNet’s word similarity calculation technique, this study integrated multiple generic dictionaries, including the sentiment vocabulary ontology database of the Dalian University of Technology, the National Taiwan University Sentiment Dictionary and the Boson Dictionary. Word2vec algorithm filters emotion words unique to hospitality and tourism in 1,596,398 texts from Sogou News, Wikipedia and Ctrip reviews about attractions, and 1,765,691 reviews about attractions in China.

The discrete sentiment dictionary developed in this study outperformed the original dictionary in identifying and calculating emotions, with a total vocabulary extension of 12.07%, demonstrating its applicability to tourism.

The developed new dictionary can be used by researchers and managers alike to quickly and accurately evaluate products and services based on online visitor reviews.

To the best of the authors’ knowledge, this study is the first to construct a sentiment dictionary based on discrete emotion theory applicable to hospitality and tourism in the Chinese context. This study extended the applicability of affective psychology to hospitality and tourism using discrete emotion theory. Moreover, the study offers a methodological framework for developing a domain-specific sentiment dictionary, potentially applicable to other domains in hospitality.