Search results

The increasing popularity of immersive activities (e.g. immersive performing art (IPA) at tourism destinations calls for the need to understand customers’ immersive experiences and its impact on their attitudes and behavioral intentions. This study aims to conceptualize customers’ interactive experience in IPA and systematically examine how interaction in IPA experience shapes customers’ word-of-mouth (WOM) intention and thus generates business values for destination managers.

A two-step mixed-methods approach was used. The qualitative study was adopted to identify the salient dimensions of interaction in IPA experience and develop a context-specific measurement scale. Structural equation modeling approach was applied to test the theoretical model using partial least squares 3.3.0.

The results indicated that the three dimensions of interaction in IPA experience (i.e. parasocial interaction, narrative interaction and environmental interaction) are positively related to customers’ experiences of narrative transportation and self-expansion related to the IPA, which further influence their WOM intention.

This study considers IPA as an emerging form of immersive tourism activities and conceptualizes its interactive nature, and contributes to the understanding of how customers’ interactive experience helps them construct meanings through narrative transportation, and offers valuable guidance for IPA designers and destination management organizations.

Leaders' behavior has a critical impact on workers' safety behavior. However, previous studies have shown contradictive views on the effect of different leadership styles on safety behavior. One reason may be that the effectiveness of leaders' behavior varies according to diverse contexts. This study examines the effect of transformational and transactional leadership (TsL) on the safety behavior of on-site workers under different levels of social capital in construction projects.

Safety behavior is divided into three types: safety compliance (SC), organizational-oriented safety participation and individual-oriented safety participation (ISP). Questionnaire survey data were collected from 302 construction workers in the Chinese construction industry.

The results indicate that the positive effect of transformational leadership (TfL) of frontline supervisors on the two types of construction workers' safety participation is enhanced when social capital is high, although TfL has no significant effect on SC behavior. In contrast, TsL can promote construction workers' SC behavior and organizational-oriented safety participation and social capital positively moderating these relationships. TsL has no significant effect on ISP, but its interaction with safety behavior is positively related to ISP.

This study explains the inconsistent findings of previous research related to the role of leadership in safety behavior by introducing the social capitaltheory and distinguishing safety participation into two typesThis study is confined to one specific country, future research may benefit from investigating whether the conclusions of this study will be different in other nations with diverse cultures.

The findings of the study provide frontline supervisors with new insights into improving workers' safety and the efficiency of leadership in safety management.

This study explains the inconsistent findings of previous research related to the role of leadership in safety behavior by introducing the social capital theory and distinguishing safety participation into two types.

Knowledge sharing in online health communities (OHCs) disrupts consumers' health information-seeking behavior patterns such as seeking health information and consulting. Based on social exchange theory, this study explores how the two dimensions of experts' free knowledge sharing (general and specific) affect customer transactional and nontransactional engagement behavior and how the quality of experts' free knowledge sharing moderates the above relationships.

We adopted negative binomial regression models using homepage data of 2,982 experts crawled from Haodf.com using Python.

The results show that experts' free general knowledge sharing and free specific knowledge sharing positively facilitate both transactional and nontransactional engagement of consumers. The results also demonstrate that experts' efforts in knowledge-sharing quality weaken the positive effect of their knowledge-sharing quantity on customer engagement.

This study provides new insights into the importance of experts' free knowledge sharing in OHCs. This study also revealed a “trade-off” between experts' knowledge-sharing quality and quantity. These findings could help OHCs managers optimize knowledge-sharing recommendation mechanisms to encourage experts to share more health knowledge voluntarily and improve the efficiency of healthcare information dissemination to promote customer engagement.

Free knowledge sharing in the online health community has been widely documented. However, whether free knowledge sharing can help physicians accumulate popularity and further the accumulated popularity can help physicians attract patients remain unclear. To unveil these gaps, this study aims to examine how physicians' popularity are affected by their free knowledge sharing, how the relationship between free knowledge sharing and popularity is moderated by professional capital, and how the popularity finally impacts patients' attraction.

The authors collect a panel dataset from Hepatitis B within an online health community platform with 10,888 observations from April 2020 to August 2020. The authors develop a model that integrates free knowledge sharing, popularity, professional capital, and patients' attraction. The hierarchical regression model is used to for examining the impact of free knowledge sharing on physicians' popularity and further investigating the impact of popularity on patients' attraction.

The authors find that the quantity of articles acted as the heuristic cue and the quality of articles acted as the systematic cue have positive effect on physicians' popularity, and this effect is strengthened by physicians' professional capital. Furthermore, physicians' popularity positively influences their patients' attraction.

This study reveals the aggregation of physicians' popularity and patients' attraction within online health communities and provides practical implications for managers in online health communities.

The purpose of this paper is to synthesize a polyacrylate-based dispersant with a determined target molecular weight for oily systems and to determine the optimal dispersant level and monomer ratio of the dispersant.

The dispersant was synthesized by conventional radical polymerization using methacrylic acid, butyl acrylate and dimethylamino ethyl methacrylate as the monomer. It was characterized by Fourier transform infrared spectroscopy, nuclear magnetic hydrogen spectroscopy, gel permeation chromatography and thermogravimetric analysis. The dispersant was used to disperse TiO₂, and the performance of the dispersant was evaluated by measuring the viscosity, particle size and dispersive force of the slurry.

The dispersant exhibited high thermal stability and was successfully anchored to the surface of the TiO₂ pigment. When used to disperse a TiO₂ slurry, it effectively made the TiO₂ slurry more fluid, indicating its strong viscosity-reducing properties. The viscosity, particle sizes and dispersion capabilities of the TiO₂ slurry were found to vary depending on the contents and monomer ratios of the dispersant.

P(MAA-BA-DM) dispersant increases the wettability of TiO₂ only in oily solvents but not in aqueous solvents.

P(MAA-BA-DM) dispersant makes it easier to disperse TiO₂ pigments in oily solvents, increasing the amount of pigment in the solvent and making the preparation of highly pigmented pastes easier.

A dispersant containing suitable carboxyl and tertiary amine groups was initially synthesized to disperse TiO₂ in an oily system. The findings are anticipated to be used in the formulation of pigment concentrates, industrial coatings and other solvent-based coatings.

The interaction between evaluators is underestimated in legitimacy literature. This study aims to examine the impact of CEO celebrity on initial public offerings (IPOs) underpricing in Strategic Emerging Industries (SEIs). Based on legitimacy and limited attention effect, this study introduces a new antecedent to the asset pricing literature under a particular sample.

This paper illustrates how CEO celebrity promotes IPO underpricing by enhancing the legitimacy and then explores how the CEO characteristics can moderate this relationship. Using 1,128 IPO companies in China SEIs from 2010 to 2019, cross-section data is used to build a multiple linear regression model to test the hypotheses.

The result indicates that CEO celebrity is positively related to IPO underpricing. Founder CEO and CEO duality amplify the relationship. Further analysis shows that the relationship between CEO celebrity and IPO underpricing is more pronounced in firms with high Baidu search and low market sentiment.

This study provides insights into how CEO celebrity as notable internal information shapes the formation of investors' preliminary impressions of firms. The evidence consists of legitimacy and limited attention perspective by showing how investors favor, follow and hype the stocks with celebrity CEOs. The results extend the knowledge about how CEO characteristics influence information frictions in asset pricing during IPO.

This study aims to investigate the influence of the reviewed establishment’s price level and the user’s social network size and reputation status on consumers’ tendency to post more visual imagery content. Furthermore, it explores the moderating effects of user experiences and geographic distance on these dynamics.

This study adopts a multi-method approach to explore both the determinants behind the sharing of user-generated photos in online reviews and their internal mechanisms. Using a comprehensive secondary data set from Yelp.com, the authors focused on restaurant reviews from a prominent tourist destination to construct econometric models incorporating time-fixed effects. To enhance the robustness of the authors’ findings, the authors complemented the big data analysis with a series of controlled experiments.

The reviewed establishments price level and the users reputation status and social network size incite corresponding motivations conspicuous display “reputation seeking” and social approval motivating users to incorporate more images in reviews. “User experiences can amplify the influence of these factors on image sharing.” An increase in the users geographical distance lessens the impact of the price level on image sharing, but it heightens the influence of the users reputation and social network size on the number of shared images.

As a result of this study, high-end establishments can increase their online visibility by leveraging user-generated visual content. A structured rewards program could significantly boost engagement by incentivizing photo sharing, particularly among users with elite status and extensive social networks. Additionally, online review platforms can enhance users’ experiences and foster more dynamic interactions by developing personalized features that encourage visual content production.

This research, anchored in trait activation theory, offers an innovative examination of the determinants of photo-posting behavior in online reviews by enriching the understanding of how the intricate interplay between users’ characteristics and situational cues can shape online review practices.

This research aims to evaluate the accuracy of several Value-at-Risk (VaR) approaches for determining the Minimum Capital Requirement (MCR) for Islamic stock markets during the pandemic health crisis.

This research evaluates the performance of numerous VaR models for computing the MCR for market risk in compliance with the Basel II and Basel II.5 guidelines for ten Islamic indices. Five models were applied—namely the RiskMetrics, Generalized Autoregressive Conditional Heteroskedasticity, denoted (GARCH), fractional integrated GARCH, denoted (FIGARCH), and SPLINE-GARCH approaches—under three innovations (normal (N), Student (St) and skewed-Student (Sk-t) and the extreme value theory (EVT).

The main findings of this empirical study reveal that (1) extreme value theory performs better for most indices during the market crisis and (2) VaR models under a normal distribution provide quite poor performance than models with fat-tailed innovations in terms of risk estimation.

Since the world is now undergoing the third wave of the COVID-19 pandemic, this study will not be able to assess performance of VaR models during the fourth wave of COVID-19.

The results suggest that the Islamic Financial Services Board (IFSB) should enhance market discipline mechanisms, while central banks and national authorities should harmonize their regulatory frameworks in line with Basel/IFSB reform agenda.

Previous studies focused on evaluating market risk models using non-Islamic indexes. However, this research uses the Islamic indexes to analyze the VaR forecasting models. Besides, they tested the accuracy of VaR models based on traditional GARCH models, whereas the authors introduce the Spline GARCH developed by Engle and Rangel (2008). Finally, most studies have focus on the period of 2007–2008 financial crisis, while the authors investigate the issue of market risk quantification for several Islamic market equity during the sanitary crisis of COVID-19.

The authors proposed a conceptual model by examining the influence of threats to their freedom on tourists’ psychological distance including social distance, spatial distance, and temporal distance, which effect psychological reactance and the consequent online Airbnb booking intentions. Furthermore, media intrusiveness as a moderator determines the boundary conditions between perceived threats to their freedom and social distance, spatial distance, and temporal distance.

Data was gathered from 491 Chinese travelers to provide empirical evidence. The authors performed data analysis in Amos 26.0 using structural equation modeling (SEM) and Hayes (2013) PROCESS macro.

The findings positively reinforced all the structural relationships of the study. Notably, media intrusiveness significantly moderates the association between perceived threats to their freedom and psychological distance (i.e. social distance, spatial distance, and temporal distance).

The findings contribute significantly to the field of social psychology, advertising, and consumer behavior derive prolific implications for policymakers and sharing economy platforms. Lastly, by identifying limitations, this research opens doors for future scholars.

Governments' acute precautionary measures in response to the COVID-19 outbreak have confined individual freedom across the globe. This study illuminates how tourists conceive these preventative measures as perceived threats to their freedom, and subsequently engage psychological reactance.

Knowledge adoption is the key to effective knowledge exchange in virtual question-and-answer (Q&A) communities. Although previous studies have examined the effects of knowledge content, knowledge source credibility and the personal characteristics of knowledge seekers on knowledge adoption in virtual Q&A communities from a static perspective, the impact of answer deviation on knowledge adoption has rarely been explored from a context-based perspective. The purpose of this study is to explore the impact of two-way deviation on knowledge adoption in virtual Q&A communities, with the aim of expanding the understanding of knowledge exchange and community management.

The same question and the same answerer often yield multiple answers. Knowledge seekers usually read multiple answers to make adoption decisions. The impact of deviations among answers on knowledge seekers' knowledge adoption is critical. From a context-based perspective, a research model of the impact of the deviation of horizontal and vertical answers on knowledge adoption is established based on the heuristic-systematic model (HSM) and empirically examined with 88,287 Q&A data points and answerer data collected from Zhihu. Additionally, the moderation effects of static factors such as answerer reputation and answer length are examined.

The negative binomial regression results show that the content and emotion deviation of horizontal answers negatively affect knowledge seekers' knowledge adoption. The content deviation of vertical answers is negatively associated with knowledge adoption, while the emotion deviation of vertical answers is positively related to knowledge adoption. Moreover, answerer reputation positively moderates the negative effect of the emotion deviation of horizontal answers on knowledge adoption. Answer length weakens the negative correlation between the content deviation of horizontal and vertical answers and knowledge adoption.

This study extends previous research on knowledge adoption from a static perspective to a context-based perspective. Moreover, information deviation is expanded from a one-way variable to a two-way variable. The combined effects of static and contextual factors on knowledge adoption are further uncovered. This study can not only help knowledge seekers identify the best answers but also help virtual Q&A community managers optimize community design and operation to reduce the cost of knowledge search and improve the efficiency of knowledge exchange.