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The purpose of this study is to propose and test an integrated model to explain how trust is built in sharing economy (SE) transactions.

Initially, prior literature was systematically selected and synthesized to develop a comprehensive framework applicable to multiple trust-building perspectives and categories of SE platforms. Then, a survey was conducted to validate the constructs and test the model with Airbnb guests. A sample of 351 responses was collected and analyzed using structural equation modeling.

The results indicate that the cues an individual assesses to infer their counterpart’s trustworthiness and the reasons the individual has for engaging in the SE transaction can explain a large variance in their trust in the counterpart. In addition, the individual’s propensity to trust moderates this relationship.

The proposed model can help identify the most effective trust-building mechanisms. It can be taken as a common knowledge base for scholars to compare the four trust-building perspectives and different categories of SE platforms, as well as to investigate the subject over time and across cultures.

This research can also help practitioners understand the complexity of building trust and design platform features to do so.

A unified model clarifies trust in the SE, aiding platform growth and community bonding. This insight guides platforms in feature enhancement and policymakers in drafting balanced regulations.

To the best of the authors’ knowledge, for the first time, there is a comprehensive and parsimonious model applicable to the four trust-building perspectives and different categories of SE platforms.

Existing research has predominantly concentrated on examining the factors that impact consumer decisions through the lens of potential consumer motivations, neglecting the sentiment mechanisms that propel guest behavioral intentions. This study endeavors to systematically analyze the underlying mechanisms governing how negative reviews exert an influence on potential consumer decisions.

This paper constructs an “Aspect-based sentiment accumulation” index, a negative or positive affect load, reflecting the degree of consumer sentiment based on affect infusion model and aspect-based sentiment analysis. Initially, it verifies the causal relationship between aspect-based negative load and consumer decisions using ordinary least squares regression. Then, it analyzes the threshold effects of negative affect load on positive affect load and the threshold effects of positive affect load on negative affect load using a panel threshold regression model.

Aspect-based negative reviews significantly impact consumers’ decisions. Negative affect load and positive affect load exhibit threshold effects on each other, with threshold values varying according to the overall volume of reviews. As the total number of reviews increases, the impact of negative affect load diminishes. The threshold effects for positive affect load showed a predominantly U-shaped course of change. Hosts respond promptly and enthusiastically with detailed, lengthy text, which can aid in mitigating the impact of negative reviews.

The study extends the application of the affect infusion model and enriches the conditions for its theoretical scope. It addresses the research gap by focusing on the threshold effects of negative or positive review sentiment on decision-making in sharing accommodations.

This study aims to examine the antecedents of tourist citizenship behavior (TCB). It also investigates the role of digital halal literacy (DHL) and religiosity in enhancing TCB.

This quantitative research used survey with questionnaire as the data collection methods. The samples of this study were 400 tourists who visited tourist destinations in five cities/municipals in West Sumatra Indonesia. This research used partial least square structural equation model as the data analysis tools.

This study found that satisfaction, trust and DHL are significant antecedents of TCB. In addition, satisfaction had a direct impact on TCB and influenced TCB through trust as a mediator. This study also found that religiosity had a direct influence on DHL, satisfaction and trust.

The findings will provide insights to tourist destination managers as well as the government on how to motivate tourists to participate in the development of Halal tourism in Indonesia. The tourists should gain sufficient knowledge or literacy about Halal, and especially in the digital context. Therefore, this will lead to their satisfaction, trust and willingness to participate in tourism development such as providing assistance to other tourists in the destinations.

This research has identified a new variable, DHL, which has not been addressed previously. This research has extended social exchange theory by establishing a relationship between TCB and DHL that has also not been previously explored. In addition, this study has investigated several relationships between DHL, satisfaction, trust and TCB and has shed new insights in the context of Halal tourism. This study has also provided a more comprehensive model of the relationship between DHL, satisfaction, trust and citizenship behavior specifically in Halal tourism research.

Ineffective management inventory of medical products such as blood and vaccines can create severe repercussions for hospitals, clinics or medical enterprises, such as surgery delays and postponements. Inventory sharing is a form of horizontal collaboration that can provide solutions to key actors of the healthcare supply chain (HSC), yet no prior study reviewed this topic.

This study conducts a systematic literature review of thirty-nine inventory-sharing studies in the context of HSCs published from 2012 until early 2022. The descriptive and thematic analyses include chronological distribution, geographical location, comparison between developed/developing regions, stakeholder and incident analysis.

Thematic analysis classified inventory sharing among five product supply chains (blood, medical supplies, medicines, vaccines and generic medical products). Benefits include shortage reduction, cost minimisation, and wastage mitigation. Barriers include (1) IT infrastructure, (2) social systems, (3) cost and (4) supply chain operations. Perishable inventory policies include Fresher-First (FF), Last-Expire-First-Out (LEFO), First-In-First-Out (FIFO) and First-Expire-First-Out (FEFO). The analysis also showed differences between developed and developing countries. The study identifies several future research opportunities that include (1) product utilisation rate, (2) cost reductions, (3) shortage mitigation and (4) waste reduction.

No prior study has systematically reviewed inventory sharing in HSCs to reveal benefits, barriers, patterns and gaps in the current literature. It makes five propositions and develops a research model to guide future research. The study concludes with theoretical and managerial implications.

This paper aims to highlight unconventional or underused theories that can be considered for the study of hospitality and tourism consumers. The authors discuss how these theories can be applied.

This research paper is conceptual and descriptive in nature. The authors address the proposed theories by applying the Delphi method.

Theories such as dramaturgical theory, persuasion theory, script theory, customer inspiration theory and segmented assimilation theory are underused but can be applied to studies of hospitality and tourism consumers’ behavior. They can be helpful for understanding various aspects of consumer behavior, such as their decision-making, motivations, attitudes and perceptions, in hospitality and tourism.

Consumer behavior is more diverse and complex in the post-pandemic era. The authors draw attention to theories that are underused but have explanatory power with regards to hospitality and tourism consumers’ behaviors. These non-conventional theories can provide new theoretical perspectives and offer new insights.

Based on stakeholder, agency and institutional theory, this study aims to examine the role of institutional ownership in the relationship between environmental, social and governance practices and CEO compensation.

Utilizing a fixed-effect panel regression analysis, this research utilized a panel data approach, analyzing data spanning from 2014 to 2021, focusing on US companies listed on the S&P500 stock market index. The dataset encompassed 219 companies, leading to a total of 1,533 observations.

The analysis identified that environmental scores significantly impact CEO equity-linked compensation, unlike social and governance scores. Additionally, it was found that institutional ownership acts as a moderating factor in the relationship between the environmental score and CEO equity-linked compensation, as well as the association between the social score and CEO equity-linked compensation. Interestingly, the direction of these moderating effects varied between the two relationships, suggesting a nuanced role of institutional ownership.

This research makes a unique contribution to the field of corporate governance by exploring the relatively understudied area of institutional ownership's influence on the ESG practices–CEO compensation nexus.

This paper presents a set of instrumental case studies for the context-based learning of BIM in the milieu of knowledge-based practice in the AEC industry. The study aimed to examine students' actions and perspectives in a simulated learning environment for real-world BIM processes. The core intent was to provide an in-depth understanding of strategic and functional BIM implementation by synthesizing a suggestive pedagogical framework based on context-based learning approaches.

Derived from context-based approaches and experiential learning methods such as role-play, problem-based and active learning, the study involved a set of doctoral-level case studies. In a qualitative research study, these cases were devised and organized around industry-focused simulations on various levels of BIM implementation strategies.

Results from the case studies and the student responses suggest that the comprehensive evaluation of real-world BIM implementation simulations facilitates a solid understanding of the value of BIM. The participation of industry professionals catalyzes the development of strategic and functional BIM competencies.

The study proposes a well-structured and replicable BIM learning framework based on context-based learning approaches. The novel framework is adaptive and flexible for BIM education. It can provide students with the necessary skills, strategic vision and professional competencies for innovative practices in the 21st-century AEC Industry. The simulative learning settings, including the evaluation rubrics and connected instructional methods, can be implemented and further developed for similar education efforts.

The purpose of this study is to examine the influence of corporate governance (CG) mechanisms on earnings management (EM) within the Gulf Co-operation Council (GCC) countries. In addition, the impact of firm’s political connections (PCs) on EM is investigated, as well as whether it moderates the relationship between CG and EM.

Fixed-effects model is used on a sample of non-financial firms across the GCC countries to test the hypotheses. Moreover, a two-stage least squares method and a propensity score matching procedure are used to mitigate potential reverse causality and sample selection bias.

This study reveals that CG mechanisms such as board size and board independence are negatively associated with EM, while CEO duality is positively association with EM. In addition, this study shows that institutional ownership and blockholders do not influence EM. Furthermore, PCs are shown to play a moderating role in the relationship between CG and EM. The results of this study are robust to endogeneity testing and to alternative measures of CG.

Because of a lack of data, the authors do not consider additional CG attributes such as tenure, education and age of board members. Future research could explore the impact of these attributes when data becomes available.

This study provides valuable insights for government officials, policymakers, standard-setters, regulators and corporations by presenting new evidence on the relationship among CG, PCs and EM. Moreover, this study underscores that, in the absence of a strong institutional infrastructure and investor protection, relying solely on strong CG and Islamic values and GCC culture may have a limited impact on effective monitoring of opportunistic managerial behaviors.

This study contributes to existing literature with a specific focus on the unique political, legal, institutional, social and cultural setting of the GCC region. Moreover, this study provides new insights that PCs serve as a governance mechanism in mitigating EM because relatively little attention has been given to the impact of PCs in improving accounting outcomes, especially in the context of the GCC region where Islamic ethical norms often shape business practices.

The purpose of this paper is to review the literature on Central Bank Digital Currencies (CBDCs) in light of the increasing demand for digital payments globally. It aims to assess the global research landscape, methodologies and data utilized in CBDC studies as their popularity grows.

The paper employs a systematic literature review (SLR) framework, utilizing the Scopus database to identify 323 studies related to Central Bank Digital Currency or CBDC. Through a thorough manual screening process, 169 studies were selected for inclusion. The research employs R, Biblioshiny and Excel for data evaluation, classifying the studies into three methodological categories: quantitative, qualitative and mixed approaches. This classification allows for a detailed assessment of the research techniques and data used in the literature on CBDCs.

The findings include a diverse range of research methodologies and data employed in CBDCs literature, highlighting the growing interest and depth of academic investigation into this area. By categorizing papers according to research technique, the study provides a comprehensive evaluation of the academic landscape regarding CBDC research. It offers valuable insights for researchers, policymakers and stakeholders, contributing to an enhanced understanding of the complexities and opportunities presented by the development and implementation of CBDCs.

This study’s originality lies in its rigorous and transparent methodology for data from CBDC studies, offering a solid framework for future research. By evaluating global research growth within an SLR framework and categorizing studies by research technique, it contributes uniquely to the academic discourse on digital currencies. The paper provides a critical resource for researchers, lawmakers and stakeholders, enriching the knowledge base on CBDCs and supporting informed decision-making in the context of digital financial innovation.

This study examines two distinct bearing stiffness calculation methods, both of which are based on the displacement-load function. Previous research typically incorporated one type of bearing stiffness into their system mechanics or vibration analysis. However, these two methods of calculating stiffness lead to different vibration models. This implies that the choice for vibration investigation is not merely about selecting one of the two types of stiffness, but also about how to appropriately implement that chosen stiffness within a model. The primary objective of this work is to compare these two methods of bearing calculation and to discuss the suitable applications of each method in both static and dynamic analyses.

This study compares two distinct methods for calculating bearing stiffness. It explores the relationships between varying bearing stiffnesses, their internal structures, and contact features. Furthermore, it examines the impact of external loads on the static properties and dynamic characteristics of different bearing stiffnesses. Finally, based on the outcomes observed under various operating conditions, the study discusses the suitability of each method for static and dynamic analysis.

Mean stiffness is more suitable for calculating load transmissibility in a static state or capturing the delivery performance at instantaneous equilibrium positions in a dynamic state. Since the variation of the equilibrium positions is ignored, the alternating stiffness model is better suited for capturing the fluctuating properties of the vibration behaviors, especially under variable external load conditions.

We compare the two bearing calculation methods and discuss the appropriate applications of each method for static and dynamic analysis.