Search results

The social media expands the scope of museum marketing. Through the social media marketing, visitors get a rich and colorful visual experience, and the museum can quickly and effectively convey various information to visitors. At present, the research on social media in the museum industry mainly focuses on the level of technology use, while the research on the marketing application of social media is relatively scarce, especially from the empirical perspective. This study constructs a conceptual model to identify the impact of SMMAs on visitor experience in the context of the museum industry through the empirical analysis.

A survey is conducted with a total of 538 visitors who follow the fan page of the Palace Museum Weibo. The collected data are analyzed via structural equation modeling.

The results show that SMMAs have significant effects on social presence and social support, which in turn significantly affect flow state. Moreover, the results demonstrate that social presence and social support partially mediates the relationships between SMMAs and flow state.

The contribution of this study is twofold. First, from a theoretical perspective, it offers new insights into the conceptualization of social media marketing. Second, from a pragmatic perspective, the results are helpful to guide museums how to carry out social media marketing activities.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-12-2020-0564

This study investigates how to motivate behavioral intentions toward green investment (BIGI) with the moderating effect of social media platforms usage (SMPU) among individual investors in Egypt.

The study used partial least squares structural equation modeling (PLS-SEM) to analyze the data and test hypotheses based on a sample of 550 individual investors with investment experience.

The results show that attitude, subjective norm (SN), and perceived behavioral control (PBC) have a significant relationship with investors' behavioral intention toward green investment. The moderating effect of (SMPU) supported the relationship between (SN), (PBC), and (BIGI), but (SMPU) does not support the relationship between attitude and (BIGI).

This study provides some implications for investment providers, service providers, and policymakers.

Despite the increasing global interest in climate change and its consequent opportunities and challenges for business, previous studies did not strongly emphasize green investment. So, based on the theory of planned behavior (TPB), this study sheds light on the motivational factors that may push investors' behavioral intentions toward green investment. With the increasing interest in digital transformation, the study also examined how digital platforms support (BIGI), especially in Egypt as a developing country.

The authors’ examination aims to offer a quantitative perspective on the interrelationships between tourist harassment, the destination image, emotions and destination revisit intent. Furthermore, it explores the moderating role of travelers' experiences and tolerance in the link between tourist harassment, the destination image and revisit intentions.

The authors’ examination seeks to fill this research gap by utilizing a combination of qualitative and quantitative methods to test eight hypotheses using AMOS 23 and PROCESS MARCO.

The findings showed that tourist harassment negatively impacts the destination image and revisit intentions. Moreover, it indicated that tourists' experiences and tolerance moderate the link between harassment, the destination image and revisit intentions for travelers with high levels of experience and tolerance compared to those with low levels.

This article contributes to travel research and service failure recovery research on tourist harassment and its consequences. To this end, it developed and validated a new tourist harassment scale. Moreover, it is the first study that examines the moderating role of visitors' experiences and tolerance on the link between tourist harassment, the destination image and revisit intentions. Finally, this article is the first to empirically offer destination harassment reduction techniques.

Artificial intelligence (AI) radically transforms organizations, yet ethical AI’s effect on employee innovation remains understudied. Therefore, this study aims to explore whether responsible artificial intelligence (RAI) enhances high-tech employees’ innovative work behavior (IWB) through creative self-efficacy (CSE) and employee mental health and well-being (EMHWB). The study further examines how leaders’ RAI symbolization (LRAIS) moderates RAI’s effect.

Through structural equation modeling, 441 responses of high-tech firms’ employees from Pakistan were utilized for hypotheses testing via SmartPLS-4.

The results revealed that second-order RAI enhances employees’ IWB. The effect was supported directly and indirectly through CSE and EMHWB. Findings also showed that LRAIS significantly moderates RAI’s influence on CSE, on the one hand, and EMHWB, on the other.

High-tech firms’ managers can fix AI-outlook issues that impair their employees’ IWB by prioritizing an ethical AI design involving actions like AI control mechanisms, bias checks and algorithmic audits. Similarly, these managers should facilitate RAI discussions and targeted trainings focusing on employees’ cognitive development and well-being. Likewise, RAI embracement programs and evaluations for leadership positions could be incorporated into high-tech firms.

This study advances the mainstream AI literature and addresses a notable gap concerning RAI’s influence on employees’ IWB while grounding in social cognitive theory. Moreover, this study unveils how CSE and EMHWB affect IWB within RAI milieus. Additionally, through signaling theory, it underscores the significance of LRAIS in amplifying the direct association between RAI, CSE, and EMHWB within high-tech firms in emerging markets.

This study aims to determine how cognitive diversity at the workplace influences team creativity. In this regard, the authors examined knowledge sharing and team-focused inclusion through which team members’ cognitive diversity was expected to elevate their positive work outcomes.

A quantitative method is used to accumulate the data. The authors surveyed workers and their respective managers at a single China-based food company. The supervisors rated the outcome variables (creativity and team effectiveness) regarding their employees, whereas employees were asked to rate the cognitive diversity, inclusion and knowledge sharing within the workgroup. The final valid sample size (n = 391) consisted of 137 workgroups with an adequate response rate (62.3%).

Cognitive diversity is related to team effectiveness but not creativity. The research found that cognitive diversity can increase creativity only through enhanced inclusion and knowledge sharing. Inclusion, likewise, explained the impact of cognitive diversity on effectiveness.

The originality of the current research lies in its contemporary exploration of inclusion and cognitive diversity and their pathways to team creativity and effectiveness. The social capital theory was applied to explain the proposed relationships.

This study aims to determine whether the stock holdings of equity mutual funds are informative for predicting future stock performance in the Chinese market. It is a puzzle that actively managed mutual funds underperform passive benchmarks, whereas retail investors still delegate investment decisions to the fund managers. The present study sheds light on whether mutual fund managers possess security selection skills in their top ten holdings.

By regression analysis and portfolio sorting, this study focuses on 830 Chinese A-share stocks in the industry research reports from the Guotai Junan Securities Company. It collects mutual fund's top ten holdings data from the Wind Financial Terminal between 2019Q1 and 2021Q1. As robustness checks, the result holds for the fixed-effect model, an additional measure of ranks in the top ten holdings, the predictability test based on the confusion matrix and two stage least square (2SLS) regression.

The authors find that the top ten holdings by equity mutual funds are informative for predicting stock performance and can provide valuable information for investors to support their decision-making.

The findings of this study provide insightful guidance for retail investors in making investment decisions and support the hypothesis that active fund management adds value.

Firstly, the authors find that the top ten holdings of Chinese mutual funds show significantly positive signals for future stock excess returns, indicating the selection skills of fund managers. Secondly, the above positive relationship exhibits a diminishing marginal effect with more funds holding this stock. Thirdly, the authors find that the predictability horizon of the number of overweighing funds is up to three quarters and then diminishes in the fourth quarter. Finally, investors have a 59% prediction accuracy for the whole stock sample and an 85% precision conditional on the predicted positive subsample to outperform the market. The authors also address the endogeneity and reverse causality issues.

Entrepreneurial passion has important implications for entrepreneurial success and psychological well-being. But their connections are complicated by the fact that three entrepreneurial passions (passion for inventing, passion for founding and passion for developing) can be combined differently according to their level and shape difference. A variable-centered approach cannot explain their relationship very well, by only focusing on the level difference and ignoring the different combination of entrepreneurial passion in subpopulations. The purpose of this study is to explore the function of entrepreneurial passion on entrepreneurial success and psychological well-being from a person-cantered approach.

In this study, the authors conducted latent profile analyses to identify different configurations of different entrepreneurial passions (passion for inventing, passion for founding, passion for developing) on two samples of Chinese students and entrepreneurs. Then in the sample of Chinese entrepreneurs, the authors utilized the DCON command in Mplus to provide comparisons among the profiles on entrepreneurial success and psychological well-being.

Based on identity theory, the authors found four entrepreneurial passion profiles across two samples—fully passionate, action-driven, interest-driven and dispassionate. Furthermore, the authors found that fully passionate entrepreneurs showed the highest level of entrepreneurial success, followed by action-driven, and then by interest-driven and dispassionate showed the lowest level. Action-driven entrepreneurs experienced the highest level of psychological well-being, followed by fully passionate entrepreneurs, then by interest-driven and dispassionate.

The results provide new insights into the nature and influence of entrepreneurial passion on entrepreneurial success and psychological well-being from a person-centered perspective.

The research aims to explore the influence mechanism of peer feedback and users' knowledge contribution behavior. This study draws on the social identity theory and considers social identity as a mediating factor into the research framework.

This paper collected users' activity data of 142,191 ideas submitted by 76,647 users from the MIUI community between October 2010 and May 2018 via Python software, and data were processed using Stata 16.0.

The results indicate that knowledge feedback and social feedback positively influence users' knowledge contribution (quantity and quality), respectively. User's cognitive identity positively mediates the relationship between peer feedback and knowledge contribution behavior, affective identity positively mediates the relationship between peer feedback and knowledge contribution behavior, while evaluative identity positively mediates the relationship between peer feedback and knowledge contribution quality, but there is no mediating effect between peer feedback and knowledge contribution quantity.

This study advances knowledge management by highlighting peer feedback on online innovation communities. By demonstrating the significant mediating effect of social identity, this study empirically clarifies the relationships of peer feedback (knowledge feedback and social feedback) to specific dimensions of knowledge contribution, thereby providing managerial guidance to the online innovation community on incentivizing and managing user interaction to foster the innovation development of firms.

This paper aims to investigate the impact of green human capital (GHC) on green supply chain management (GSCM) practices (environmental education and internal environmental management) and sustainable supply chain performance.

This study used a survey method to collect data from 350 randomly selected manufacturing firms in China, including supply chain and human resource professionals from the period of December 2021 to June 2022.

The partial least squares-structural equation modeling version 4 is applied to assess the data and test the hypotheses. Under the notion of resource-based view theory, the findings demonstrate that GHC has a positive and significant relationship with GSCM practices (environmental education and internal environmental management) and that GSCM practices are positively associated with the sustainable supply chain performance.

This study offers implications for Chinese manufacturing firms to use GHC on dimensions of GSCM implementations for achieving environmental, financial and social performance.

This study finds that GHC as a critical enabler for implementing GSCM practices, resulting in more robust and better sustainable supply chain performance (environmental, financial and social performance).

This research proposes a novel risk assessment model to elucidate the risk propagation process of industrial safety accidents triggered by natural disasters (Natech), identifies key factors influencing urban carrying capacity and mitigates uncertainties and subjectivity due to data scarcity in Natech risk assessment.

Utilizing disaster chain theory and Bayesian network (BN), we describe the cascading effects of Natechs, identifying critical nodes of urban system failure. Then we propose an urban carrying capacity assessment method using the coefficient of variation and cloud BN, constructing an indicator system for infrastructure, population and environmental carrying capacity. The model determines interval values of assessment indicators and weights missing data nodes using the coefficient of variation and the cloud model. A case study using data from the Pearl River Delta region validates the model.

(1) Urban development in the Pearl River Delta relies heavily on population carrying capacity. (2) The region’s social development model struggles to cope with rapid industrial growth. (3) There is a significant disparity in carrying capacity among cities, with some trends contrary to urban development. (4) The Cloud BN outperforms the classical Takagi-Sugeno (T-S) gate fuzzy method in describing real-world fuzzy and random situations.

The present research proposes a novel framework for evaluating the urban carrying capacity of industrial areas in the face of Natechs. By developing a BN risk assessment model that integrates cloud models, the research addresses the issue of scarce objective data and reduces the subjectivity inherent in previous studies that heavily relied on expert opinions. The results demonstrate that the proposed method outperforms the classical fuzzy BNs.