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The China-plus-one strategy is an increasingly attractive supply chain risk management strategy and has been adopted by many multinational enterprises. However, relevant research remains limited and warrants empirical validation. This paper addresses this research gap by investigating the determinants of emerging multinational enterprises’ adoption of a China-plus-one strategy.

The China-plus-one adoption decision of 1,527 firms was predicted using a logistic model based on Taiwan’s official data – Investigation of Foreign Sales and Manufacturing, for the years 2020–2022. This database is administered by the Department of Statistics of the Ministry of Economic Affairs (DSMEA) in Taiwan. Analysis was conducted using SPSS 25.0.

It is suggested that customer pressure and supplier relocation, functioning as push forces, lead to the China-plus-one strategy adopted by Taiwanese firms. Regarding pull forces, lower production cost has a positive association with China-plus-one adoption, whereas sufficient local workforce supply does not have a significant effect. Finally, in terms of the mooring forces, local sales performance is negatively related to the strategy adoption, whereas local access to components shows a positive association with such strategy.

This research uniquely adopts the push–pull–mooring framework to examine factors affecting supply chain restructuring in international business, representing a novel domain for this framework.

The rise of the mobile Internet has accumulated much text information in various online financial forums. Such information often contains the emotional attitudes of investors toward financial technology (fintech) platforms, so extracting the sentimental tendency information has great practical value for the development of fintech platforms. Based on the investor sentiment theory, the paper aims to analyze the relevant social media data and test the influence path of online news evaluation on the stock price fluctuation of fintech platforms.

Taking Oriental Fortune as the research object, this paper selects multiple variables such as stock bar popularity, snowball popularity, news popularity and news sentiment scores collected by UQER and combines the sentiment scores of single daily news into a daily sentiment score. Based on the period from November 1, 2019 to March 31, 2020, during the emergence of the coronavirus disease 2019 (COVID-19) pandemic as the background, the authors conduct the Granger causality test based on the vector autoregressive (VAR) model and analyze the relevant evaluation of Oriental Fortune through the empirical model.

The authors' results show that different online evaluations impact the rise and fall of stock prices differently, while news popularity has the most significant impact. Besides, news sentiment scores on share price fluctuation have a relatively substantial influence. These findings indicate that the authoritative news evaluation can strongly guide investors to make relevant investment behavior operations in the information dissemination process, significantly affecting stock prices.

The research findings of this paper have good inspiration and reference values for investors and financial regulators.

With its continuous development and application in the hotel industry, artificial intelligence (AI) is gradually replacing many jobs traditionally performed by humans. This research aims to understand how this threat and opportunity of substitution affects hotel employees’ behavioral decision-making.

This study uses a structural equation model, ordinary least squares and bootstrapping method to analyze the data collected with a field study and a scenario experiment from star-hotels in Shanghai, Paris and Seoul.

The results discovered that employees’ AI awareness has a positive relationship with their work engagement and AI boycott through two paths. The promoting path involves recovery level, while the hindering path includes job insecurity. In addition, the estimates showed that AI awareness has a great indirect effect on work engagement or AI boycott when innovativeness as a job requirement is high.

The findings offer insights to help hotels optimize the relationship between AI and hotel human workers while providing valuable implications for addressing behavioral dilemmas faced by hotel employees in the era of AI.

By integrating the behavioral decision-making literature with the conservation of resources theory, the study focuses on the dual mechanisms – challenging and hindering – through which AI awareness influences hotel employees’ coping strategies.

As more hotels adopt artificial intelligence (AI), it becomes inevitable for employees to rely on abilities enhanced by the use of AI to complete tasks. However, our understanding of how employees adapt to this shift in work design remains limited. Therefore, the purpose of this study is to explore hotel employees’ approach and avoidance behavioral reactions to dependence on AI.

A three-wave field study was conducted, collecting data from 303 hotel employees and analyzed using Mplus 8.3.

Dependence on AI can be construed as a positive stimulus, augmenting employees’ harmonious work passion and subsequently promoting approach job crafting. The promotion focus of employees positively moderates this process. On the other hand, dependence on AI also can be perceived as a negative stimulus, heightening employees’ feelings of AI threat and, consequently, fostering avoidance job crafting. In this case, the prevention focus of employees positively moderates the process.

This study provides theoretical foundations and decision-making references for management practice. Managers should implement measures to guide employees in developing a proper understanding of AI and provide them with emotional support and institutional safeguards.

This study unveils the consequences of dependence on AI for employees, offering new perspectives for AI research in the hotel industry. By differentiating job crafting, this study theorizes and tests a dual-path model of how dependence on AI may influence hotel employees’ approach and avoidance job crafting, thereby enriching the AI–job crafting literature.

This study aims to systematically review the literature on how various factors influence investor sentiment and affect financial markets. This study also sought to present an overview of explored contexts and research foci, identifying gaps in the literature and setting an agenda for future research.

The systematic literature investigation yielded 555 journal articles, with few other exceptional inclusions. The data have been extracted from the two databases, i.e. Scopus and Web of Science. For bibliometric analysis, VOSviewer and Biblioshiny by R have been used. The period of investigation is from 1985 to July 2023.

This systematic literature review helped us identify factors influencing investor sentiment and financial markets. This study has broadly classified these factors into two categories: rational and irrational. Rational factors include – economics and monetary policy, exchange rate, interest rates, inflation, government mandatory regulations, earning announcements, stock-split, dividend decisions, audit quality, environmental, social and governance aspects and ratings. Irrational factors include – behavioural and psychological factors, social media and online talk, news and entertainment, geopolitical and war events, calendar anomalies, environmental, natural disasters, religious events and festivals, irrationality caused due to government/supervisory body regulations, and corporate events. Using these factors, this study has developed an investor sentiment model. In addition, this review identified research trends, methodology, data and techniques used by researchers.

This review comprehensively explains how various factors affect investor sentiment and the stock market using the investor sentiment model. It further proposes an extensive future research agenda. This study has implications for stock market participants.

The emergence of social media platforms has revolutionized how brands develop partnerships with social media influencers (SMIs). However, users are seeking more meaningful engagement with SMIs, and little is known about how brands can shift their focus from transient engagements to continued engagement that builds long-term brand–consumer relationships. Extant research has provided inconsistent findings regarding consumer engagement behavior. To address this knowledge deficit, we contribute to the consumer engagement literature by developing and testing a conceptual model that explores and explains the relationships between the factors that influence continued engagement intention (CEI), a form of behavioral intention.

A literature review was conducted to identify gaps and develop a theoretically informed conceptual model and hypotheses. Survey data from 604 Instagram SMI followers were analyzed using partial least squares structural equation modeling using SmartPLS 3.3.3 to assess the structural model relationships and conduct post hoc analysis.

The findings suggest that it is important to positively influence consumer responses to elicit CEI. Furthermore, homophily attitudes toward SMIs moderate the relationship between SMI experience and CEI.

Brands must work with SMIs to create positive SMI experiences and develop CEI. Furthermore, SMIs should focus on brands that fit their lifestyles to enhance homophily attitudes and forge CEI.

This study contributes to the literature by combining social exchange and flow theories to develop and test a holistic framework for examining CEIs regarding SMIs and brands. The findings show that creating positive SMI experiences benefits brands seeking CEI.

This study aims to examine the effect of investor sentiment on stock market crash risk in the Asia–Pacific region and the moderating role of uncertainty factors.

This research uses principal component analysis to construct an investor sentiment index of 17 Asia–Pacific stock markets before analyzing the data through hierarchical regression with the feasible generalized least squares method.

The empirical results show that investor sentiment has a positive impact on crash risk in the Asia–Pacific stock markets. This impact is more significant in advanced economies compared to emerging markets and developing economies. The nexus between investor sentiment and stock market crash risk is increased by economic policy uncertainty but decreased by uncertainty from pandemics.

This study only investigates the moderating roles of global uncertainty factors but not local uncertainty factors. In addition, the sentiment of different investor groups has not been examined yet.

The findings of this study are relevant for global investors, portfolio managers and policymakers. Investors and portfolio managers can use sentiment indicators to predict downturns and adjust strategies, whereas policymakers can leverage these insights to design regulations that mitigate systemic risks during global uncertainties.

This study expands the literature on the relationship between investor sentiment and stock market crash risk, providing updated insights into sentimental bias in behavioral finance.

This study aims to examine the effects of economic uncertainty on Shariah stock returns (SR) in Asia-Pacific Economic Cooperation countries. This study also compares the impacts of uncertainty on Shariah and conventional stocks.

A panel vector autoregressive model was used to capture the dynamic relationships between variables. Granger tests, impulse response functions and forecast error variance decomposition are applied to obtain a comprehensive interpretation.

The empirical results indicated that temporary economic uncertainty has a significant adverse impact on Shariah SR. The stability was also observed over time. This study also revealed that Shariah stocks were affected by economic uncertainty, although they were designed to mitigate such effects. In addition, Shariah stocks show lower sensitivity to uncertainty. However, their recovery was slower than that of conventional stocks.

Short-term investors are advised to diversify their portfolios. In the long term, the stability of Shariah SR enables investors to pursue their financial goals. Policymakers are encouraged to improve investor confidence and develop policies to accelerate the recovery of the Sharia stock prices.

This study proves the existence of uncertainty in the Shariah stock market and explores the comparative impact of uncertainty on Shariah and conventional stocks. Furthermore, by incorporating uncertainty as a variable, this study contributes to expanding the efficient market hypothesis, offering a deeper understanding of market behaviour under uncertain conditions.

Digital well-being (DWB) has become a preoccupation of society, businesses and consumers because of the proliferation of technology and the pandemic. This study aims to understand the four main problems of DWB in hospitality (DWBH): epistemology, scope, aggregation and specification by adopting integrative literature review.

The systematic analysis process develops a dynamic DWBH framework, which connects individuals and society, based on the doughnut model. A critical method is used to conceptualize the DWBH and digital behavior change interventions (DBCIs) by combining psychology and sociology.

This study provides a definition of DWBH. It identifies three antecedents (digital design, awareness and utilization advancement), three decision factors (individual psychology, category differences and external environment) and four outcomes. The doughnut model visualizes dynamic sustainability of subjective well-being, master, engagement, autonomy, relationship and mastery. DBCIs provide a comprehensive strategy: effective design is essential, personalized implementation is standard, and strategy and structure ensure success.

This study theoretically addresses issues of epistemology, scope and aggregation, expanding the existing knowledge base of DWBH and fostering theoretical integration across different disciplines. Practically, it provides actionable guidelines for stakeholders in hospitality to enhance community DWB, thereby promoting both individual and societal well-being.

This study makes a pioneering effort by extending the knowledge of DWBH with epistemology, scope, aggregation and specification. Furthermore, this study helps clarify the academic research process of DWBH, formulating management and practical strategies and improving individuals’ well-being.

This study aims to investigate the effect of top management team (TMT) stability on outward foreign direct investment (OFDI) of Chinese firms and the moderating effects of state ownership and managerial ownership on this relationship.

An empirical analysis based on the ordinary least square regression model is conducted using Chinese A-share listed firms that engaged in OFDI from 2008 to 2021.

TMT stability has a positive effect on firms’ OFDI. Moreover, state ownership significantly strengthens the positive relationship between TMT stability and OFDI, while managerial ownership weakens this positive relationship.

The findings help firms to effectively retain TMT talents and promote the smooth internationalization of firms, thereby enhancing their long-term development capabilities and competitive advantages.

This study expands the investigation of the factors influencing OFDI at the micro level of the TMT, providing valuable decision-making insights for firms.