Offshore outsourcing has been considered a low cost production site. There is rare studies that addressed the offshore outsourcing strategy as a growth strategy where offshoring focal firm can... Show More

Offshore outsourcing has been considered a low cost production site. There is rare studies that addressed the offshore outsourcing strategy as a growth strategy where offshoring focal firm can develop their capabilities for competitive advantage. This paper explores how SMEs enhance their dynamic capabilities by entering into offshore outsourcing relationships. The dynamic capabilities development process includes increasing focus on the Core competency, developing innovation capabilities, increasing market share in existing and/or new markets, and improving its flexibility to face the dynamic business ecosystem. This exploratory case study on ten manufacturing SMEs from Quebec (Canada) shows that offshore outsourcing contributes to developing dynamic capabilities with varying degrees of success. It shows an evolutionary path of the dynamic capability development process. Managers can enhance their understanding on how offshoring can enable firms to improve their dynamic capabilities to face challenging business eco-system and remain competitive in the high cost countries (HCC).

The purpose of this article is to study analysis the Decentralized Finance (DeFi) literature. By synthesizing the themes and theorical frameworks, we aim to identify knowledge gaps and potential... Show More

The purpose of this article is to study analysis the Decentralized Finance (DeFi) literature. By synthesizing the themes and theorical frameworks, we aim to identify knowledge gaps and potential areas for future research in the DeFi landscape. We conduct bibliometric and content analysis on a corpus of 275 articles extracted from the Web of Science and Scopus databases. We use the Bibliometrix package in R software to apply co-citation and bibliographic coupling. We find three research clusters (a) socioeconomic (b) technology and (c) financial with their conceptual structure, interactions and transformations. Applying both co-citation and bibliographic coupling network analysis yields a dynamic view of the field tracing thematic evolution from its inception to the present day, revealing a decline in academic interest in DeFi security vulnerabilities in contrast to the growing emphasis on social media's influence on DeFi prices.

Recent global events, notably the COVID-19 pandemic, have posed significant challenges to information systems (IS) companies, highlighting the critical importance of system resilience and its... Show More

Recent global events, notably the COVID-19 pandemic, have posed significant challenges to information systems (IS) companies, highlighting the critical importance of system resilience and its relationship with digital transformation (DT) during disruptive times. Despite this, there is a notable lack of literature examining the interactions between DT and resilience. To address this gap, this article presents a comprehensive review of the various types of interactions between these two concepts. Drawing on 73 articles published between 2010 and 2021 in leading IS research journals, our study identifies multiple dimensions of both DT and resilience. Mobilizing these dimensions, we explore their interactions to enhance our understanding of their causal dynamics. This review provides valuable insights for researchers and practitioners interested in the mutual interactions between DT and resilience, especially in the context of disruptive events.

Retransmitted messages online can have profound effects on disaster response; however, existing literature provides an incomplete account of why messages are retransmitted on social media in... Show More

Retransmitted messages online can have profound effects on disaster response; however, existing literature provides an incomplete account of why messages are retransmitted on social media in disasters. In particular, there is a need to theorize the capabilities of the communication tools used for sending messages, because nowadays people can send messages online via different tools. This paper aims to theorize and explain how the capabilities of communication tools affect message retransmission by affecting the generation of message characteristics. To test our account, we collected and coded Twitter data from three disasters, and employed five logistic regressions to test our hypotheses. Our results confirm our expectations that compared to messages sent from desktops, messages sent from mobile devices are less likely to be helpful and verifiable, but are more likely to have visual attachments and expressions of anxiety.

The study explores the relationship between an organization's survival and its digital knowledge management (DKM) in a rapidly changing digital world. It emphasizes the role of acquiring, sharing... Show More

The study explores the relationship between an organization's survival and its digital knowledge management (DKM) in a rapidly changing digital world. It emphasizes the role of acquiring, sharing, and applying knowledge digitally in organizational adaptation and competitiveness. The research utilizes current literature and theoretical frameworks to explore the importance of systems thinking and organization learning for sustainability purposes. Moreover, it examines how technological uncertainty influences these relationships. The study recruited 479 employees working in manufacturing firms in India and employed partial least squares for data analysis. The findings suggest that when companies seek to maximize resource efficiency while minimizing environmental impact, they must improve their digital knowledge processes. This work aims to provide insights for organizations seeking to benefit from digital technology without endangering global sustainability efforts, and to provide appropriate recommendations.

The reliability of a power distribution system reflects its ability to supply uninterrupted electricity. The installation of smart meters improves reliability by minimizing outages and expediting... Show More

The reliability of a power distribution system reflects its ability to supply uninterrupted electricity. The installation of smart meters improves reliability by minimizing outages and expediting restoration. Smart meters enhance efficient energy use, balance supply and demand, and strengthen system reliability. This study applies a simultaneous equations model and a modified Hyperlink Induced Topic Search algorithm to analyze the relationship between federal funding, smart meter adoption by electric utilities, and reliability, aiming to rank electric utility companies in the United States. Results show positive associations between federal funding and smart meter adoption rates, as well as between smart meter adoption rates and system reliability. The proposed network-based methodology ranks electric utility companies by ownership type. The research findings underscore the significance of smart meter adoption and provide valuable insights for policymakers and electric utility companies seeking to enhance power system reliability.

Capturing learners' attention in the classroom has become challenging. Learners have different learning styles influencing their attitude towards learning processes and contents. Serious Games (SG)... Show More

Capturing learners' attention in the classroom has become challenging. Learners have different learning styles influencing their attitude towards learning processes and contents. Serious Games (SG) are rich and promising learning tools that have been introduced to support a new form of gamified learning, mainly to enhance students' engagement and motivation. Such games facilitate learning because they generate enthusiasm and are part of a learning-by-doing experience. This study analyzes the role of learning styles and motivation on learner cognitive engagement and performance when using SG. Answers from 188 users of a serious game conducted in KEDGE Business School were analyzed. The findings show that learning goals have a strong positive effect on intrinsic and extrinsic motivation. The paper reveals that learning styles have a significant impact upon both intrinsic and extrinsic motivation. The latter is also influenced by learning styles as is cognitive engagement. Finally, the future research directions are presented.

This study investigates the drivers of customer engagement in e-commerce livestreaming, examining the roles of livestreamer attributes and of community support. With data from 532 Chinese... Show More

This study investigates the drivers of customer engagement in e-commerce livestreaming, examining the roles of livestreamer attributes and of community support. With data from 532 Chinese livestreaming customers, we examine the effects of livestreamer credibility and attractiveness, together with informational and emotional support from the community, on customer engagement. Findings reveal that livestreamer credibility is the only positive driver of customer engagement. Emotional support from the community reduces engagement. Livestreamer attractiveness and credibility enhance emotional and informational support within the community, respectively, but neither type of support positively influences customer engagement. These results challenge assumptions about the uniformly beneficial nature of community interactions and underscore the pivotal role of livestreamer credibility in driving engagement. The study contributes to theoretical frameworks on customer engagement and on source credibility models offering actionable insights for e-commerce livestreaming platforms.

This study investigates the impact of network capabilities and deep learning techniques on companies' financial performance within buyer-supplier networks. It broadens the scope by incorporating... Show More

This study investigates the impact of network capabilities and deep learning techniques on companies' financial performance within buyer-supplier networks. It broadens the scope by incorporating network measures such as closeness and network constraint, whereas previous studies have primarily focused on suitable buyer-supplier relationships. The analysis evaluates the effects of these network measures on companies' financial performance metrics, including asset growth rate, return on assets, and more. In addition, this study explores the impact of extended networks on company performance using deep learning techniques. The results show that companies' network capabilities are positively associated with their financial performance, highlighting the critical role of network positions in driving success. Furthermore, the findings suggest that extending the network through deep learning offers significant benefits for companies.

Physicians working in emergency departments (ED) face significant challenges due to inadequate clinical decision support and the fragmentation of hospital information systems (HIS). This study... Show More

Physicians working in emergency departments (ED) face significant challenges due to inadequate clinical decision support and the fragmentation of hospital information systems (HIS). This study develops a system integration architecture that facilitates the creation of a clinical decision support system (CDSS) based on machine learning to improve decision-making in the ED. Design science research methodology was employed to create and evaluate the designed architecture which provides integration of HIS systems within the ED setting. The research enables seamless accessing and processing of data from disparate HIS systems, allowing the implementation of machine learning techniques for enhanced clinical decision support. The designed system integration architecture enables the CDSS and allows physicians to address patients' data more effectively, leading to better-informed clinical decisions and significantly enhancing decision support capabilities in the ED, contributing to improved healthcare outcomes and hospital expenditure by leveraging machine learning techniques.

Personalized recommendation systems have become crucial for enhancing user experience and driving engagement in various online platforms. However, existing methods face challenges in accurately... Show More

Personalized recommendation systems have become crucial for enhancing user experience and driving engagement in various online platforms. However, existing methods face challenges in accurately modeling high-order user-item relationships, dynamically capturing user preferences, and effectively utilizing multi-modal data. These limitations hinder their ability to deliver relevant, diverse, and context-aware recommendations. To address these challenges, we propose the Graph Attention-based Dynamic Recommendation Framework (GADR). GADR incorporates a graph attention mechanism to prioritize high-order relationships dynamically, a dual-channel structure to simultaneously model long-term and short-term user preferences, and a unified pipeline for integrating textual, visual, and behavioral data. By combining these components, GADR ensures adaptability to dynamic user behavior, improves recommendation diversity, and enhances ranking quality.

In the digital landscape, online gaming has become an integral part of entertainment. This empirical research aims to examine the influence of AI-based emotional attachment-oriented anthropomorphic... Show More

In the digital landscape, online gaming has become an integral part of entertainment. This empirical research aims to examine the influence of AI-based emotional attachment-oriented anthropomorphic features and their impact on the online gaming experience. Under the paradigm of cognitive load theory (CLT) and Computers Are Social Actors (CASA) framework, a theoretical model was developed for an empirical investigation. To examine the model, the present study applied a partial least squares structural equation modeling process with 1802 respondents' data from India. The results show that AI-based emotional attachment anthropomorphic features enhance consumer's overall service experience. In addition, trust and engagement partially mediate the relationship between AI-based emotional attachment anthropomorphic features and consumer's overall service experience.

This paper explores the significance of temporality in the study of global information systems (IS) Research. It critiques the static cross-sectional focus of traditional IS research, advocating for... Show More

This paper explores the significance of temporality in the study of global information systems (IS) Research. It critiques the static cross-sectional focus of traditional IS research, advocating for longitudinal studies that capture the evolving dynamics of organizational processes and technological change, in the context of globalized and complex IS. We conduct a meta-analysis of 327 longitudinal IS studies between 2004 and 2023, categorizing them by methodological approach (ethnographic, quantitative) and time perception (social “Kairos” vs. mechanical “Chronos”). We propose a conceptual framework highlighting the need for future IS research to integrate both social and mechanical conceptions of time. This framework aids in understanding technological adoption, user behavior, and organizational transformation in a global context. The paper underscores the importance of considering temporal factors in IS research, offering insights that benefit both academic researchers and practitioners in managing long-term IS implementations involving complex and multicultural teams.

Coal plays an important role in China's economic and income growth. This paper uses provincial panel data from 2007 to 2022 in China and employs the panel ARDL model to explore the impact of coal... Show More

Coal plays an important role in China's economic and income growth. This paper uses provincial panel data from 2007 to 2022 in China and employs the panel ARDL model to explore the impact of coal prices on regional and urban-rural income inequality in China based on information of coal price shocks. Empirical results show that: (1) Coal price shocks have a significant long-term effect on income inequality in coal exporting provinces, but have no significant effect on importing provinces. (2) This impact is asymmetric, indicating that the decrease in coal prices has to a greater extent damaged income equality in coal exporting provinces. (3) Coal price shocks have a significant effect on urban-rural income inequality, supporting the energy ladder theory of urban-rural disparity in China. Overall, this research provides an energy perspective for China to improve income inequality issues. Stable coal prices and orderly energy transition have important practical significance for coal exporting provinces and rural areas in China.

With the rapid development of Generative AI technology, businesses need their marketers to adopt it to assist in completing their job tasks. However, marketers are not entirely optimistic and may... Show More

With the rapid development of Generative AI technology, businesses need their marketers to adopt it to assist in completing their job tasks. However, marketers are not entirely optimistic and may feel anxious and concerned about it. This research explores how AI anxiety affects marketers' AI-generated content intention. Based on social cognitive theory, this study empirically examines the impact of anxiety on marketers' intention to use AI-generated content, including the mediating role of AI trust and the moderating effect of AI self-efficacy. Using survey data from 495 marketers, we found that AI privacy, bias, and opacity anxiety negatively correlate with AI trust and weaken marketers' intention to use AI-generated content. Furthermore, this relationship is moderated by AI self-efficacy, where the negative relationship is significantly mitigated when marketers possess AI self-efficacy. These findings enrich the research on Generative AI in marketing and help organizations focus on marketers' anxious resistance to adopting Generative AI and reduce the adverse effects of AI anxiety.

This study examines the elements of matchmaking intention, highlighting a significant gap in matchmaking behaviors within Metaverse platforms. The study explores the socio-psychological and... Show More

This study examines the elements of matchmaking intention, highlighting a significant gap in matchmaking behaviors within Metaverse platforms. The study explores the socio-psychological and behavioral factors impacting matchmaking intention in this digital landscape. We developed a conceptual model integrating social presence theory and status quo bias with the technology acceptance model (TAM). Using survey data from 512 participants across various regions of India, we tested the proposed relationships through structural equation modeling. The results indicate that intimacy, interactivity, connectedness, and responsiveness contribute to increased agreeableness regarding matchmaking intention on Metaverse platforms. Furthermore, real, non-perceived usage significantly moderates the relationship between agreeableness and matchmaking intention. Our findings provide valuable insights for creating effective marketing strategies to enhance matchmaking user intentions and behaviors within the Metaverse. The study can be used to launch any new service through Metaverse.

This review examines the emerging field of service robot adoption in hospitality. It provides a comprehensive overview of their evolution, classification, and conceptualization. The review offers a... Show More

This review examines the emerging field of service robot adoption in hospitality. It provides a comprehensive overview of their evolution, classification, and conceptualization. The review offers a theoretically grounded analysis of customer intentions, identifying and evaluating salient models and frameworks. Through research synthesis, it pinpoints key gaps hindering holistic understanding of customer acceptance, particularly in hotels. The review highlights limitations of traditional acceptance models like TAM, advocating exploration of alternatives for a unified understanding. It underscores the need for robust methodologies to capture real-world interactions, as well as meta-analyses to establish consensus. The review also identifies critical gaps related to anthropomorphism, customer segmentation, and resistance, emphasizing the importance of contextual factors. By addressing these theoretical and methodological limitations, the review provides valuable insights to guide future research on enhancing service robot integration in hospitality.

Managing energy efficiency is essential for ensuring national energy security and facilitating a transition to a green economy. Outer circulation creates favorable external conditions. Using data... Show More

Managing energy efficiency is essential for ensuring national energy security and facilitating a transition to a green economy. Outer circulation creates favorable external conditions. Using data from listed firms information in China between 2007 and 2016, this paper examines the effect of cross-border mergers and acquisitions (M&A) on energy efficiency through a PSM-DID model. The research shows that: (1) M&A can effectively manage and improve energy efficiency of domestic enterprises, with the positive impact showing a clear trend of increasing annually. (2) The mechanism analysis suggests that the enhancement of energy efficiency is driven by technological and structural effects. (3) Furthermore, the rise in energy efficiency benefits more from M&A in regions along the Belt and Road Initiative and countries with stricter environmental regulations. The findings of this paper provide important insights into the management of international capital flows, energy efficiency improvement, and sustainable development.

This study utilized mapping knowledge domains to conduct scientometric analysis to better understand the current landscape of subculture research and development. The dataset comprises 2,647... Show More

This study utilized mapping knowledge domains to conduct scientometric analysis to better understand the current landscape of subculture research and development. The dataset comprises 2,647 articles from 1998 to 2023 sourced from the Web of Science (WOS). The data were visualized and analyzed using CiteSpace by co-citation analysis and keyword co-occurrence analysis. The results provide an overview of the concept of subculture and underscore key authors, affiliations and countries in this field. Additionally, the knowledge map of subculture studies can be summarized into four primary categories: adolescents, gender, identity group, and the Internet. The results indicate that current subculture research trends focus on developmental aspects, with particular attention to commercialization, social integration, and mental health issues. Moreover, interdisciplinary approaches are increasingly applied in this field. Finally, limitations and potential directions for future studies are discussed.

This research aims to develop and test a conceptual model to examine customer citizenship behaviour towards generative AI-enabled chatbots. This study also examines the crucial role of... Show More

This research aims to develop and test a conceptual model to examine customer citizenship behaviour towards generative AI-enabled chatbots. This study also examines the crucial role of customer-generative AI experiences in enhancing trust. This study also examines the moderating role of customer fatigue. The study utilized a self-administered questionnaire distributed on Prolific Academic to gather data from 282 eligible participants worldwide. The findings reveal that data capture experience and anthropomorphic experience are positively associated with trust. Moreover, the findings show that trust is significantly associated with customer citizenship behaviour. Also, customer fatigue was found to be a significant moderator. This study enriches the generative AI and phygital consumer literature. Further, this study contributes to the customer experience literature as this study investigates how user citizenship intentions towards generative AI-enabled chatbots are influenced by their customer experiences.

The aim of this study is to identify and empirically validate the factors that increase students' engagement in remote work-integrated learning (WIL). The technology interactivity model was... Show More

The aim of this study is to identify and empirically validate the factors that increase students' engagement in remote work-integrated learning (WIL). The technology interactivity model was considered an appropriate theoretical foundation for proposing the conceptual model in this study. Four factors i.e. interactivity, customisation, active control, and synchronicity were derived as key predictors of student's engagement. This was also extended by considering two factors from social identity theory: social identity and personal identity. The necessary data was collected using an online questionnaire with a purposive sample of students at different levels and from different educational backgrounds. Statistical findings largely approved the impact of social identity, interactivity, customisation, and active control on the students' engagement with remote WIL. Results supported the moderating effects of telepresence and social presence on the relationships between the key independent factors: interactivity, customisation, social identity and engagement.

This study examines the unexpected rise in electricity production in China amid economic pressures from 2022 to 2023, highlighting the role of information dynamics. Employing a Bayesian Structural... Show More

This study examines the unexpected rise in electricity production in China amid economic pressures from 2022 to 2023, highlighting the role of information dynamics. Employing a Bayesian Structural VAR model, the research delves into technology shocks derived from the semiconductor cycle to elucidate these anomalies within China's Coal-Electricity Market. We find: (1) A positive response of China's electricity production to technology and demand shocks, influenced by information transitions, lasting nearly a year. (2) Rapid absorption of reactions to coal supply and inherent electricity production shocks within one to two months. (3) The semiconductor cycle, though initially set as the primary variable in Cholesky identification, is determined to be endogenous in this information-intensive system. (4) Historical decomposition reveals increased electricity use from 2022 to 2023 is propelled by tech-driven growth and energy market speculative behaviors, paralleling the peak of the dot-com bubble in 1999-2000. Accordingly, we propose policy recommendations.

Live streaming e-commerce is a new mode of shopping that has been introduced over recent years. Understanding the factors affecting consumers' purchase intention is becoming increasingly critical.... Show More

Live streaming e-commerce is a new mode of shopping that has been introduced over recent years. Understanding the factors affecting consumers' purchase intention is becoming increasingly critical. The purpose of this paper is to present an empirical analysis of consumers' purchase intention in live streaming e-commerce. An inductive qualitative approach was followed. Using the research method of interview, twenty-eight consumers were selected as research samples to explore what factors affect consumers' purchase intention. The interview data was analyzed using a thematic analysis method. The results of this research contain a categorization of seven different key factors, namely streamer's credibility, product evaluation, platform design, price promotion, perceived value, live interactivity and service integrity, together with the interrelationships between them. This study contributes to the literature of live streaming e-commerce, consumer purchase intention and marketing by bridging three disciplines and provides a constructive insight into live streaming e-commerce merchants.

This research explores the benefits and challenges associated with Gen-AI tools for business improvement from the perspective of business players and academicians. Data comprises of interviews with... Show More

This research explores the benefits and challenges associated with Gen-AI tools for business improvement from the perspective of business players and academicians. Data comprises of interviews with 7 academicians and 10 European industry players. Several benefits were recognized from the use of Gen-AI in business context, mainly resolution of complex situations and operational improvement of processes. At the optimization level, industry players perceived Gen-AI with more potential than academicians. Advantages of Gen-AI were identified as strongly aligned with data quality. Both academicians and industry players highlight difficulty of identification, collection, and update of relevant data, together with the needed parsimony in decision-making about Gen-AI-produced results. This study corroborates the current awareness of scarcity in trained people to explore the full potential of Gen-AI and highlights the resistance towards its adoption by top management, especially in SMEs, which due to their scale may lack structured data and act more risk averse.

Using the Stimulus-Organism-Response (S-O-R) framework, this paper examines how review valence influences information adoption in e-commerce, highlighting the mediating role of the perceived... Show More

Using the Stimulus-Organism-Response (S-O-R) framework, this paper examines how review valence influences information adoption in e-commerce, highlighting the mediating role of the perceived usefulness of online reviews and the moderating effects of two distinct regulatory focuses. Empirical results from a survey of Chinese consumers reveal that the perceived usefulness of online review mediates the relationship between review valence and information adoption. Consumers with a promotion focus are more likely to adopt positive reviews, while those with a prevention focus are more inclined to adopt negative reviews. Furthermore, situational regulatory focus further also moderates this relationship, with consumers browsing promotion-focused products more likely to adopt positive reviews and those evaluating prevention-focused products more likely to adopt negative reviews. These findings provide valuable insights into online review adoption and offer practical implications for optimizing review strategies on e-commerce platforms.

The global ecological crisis is driving the beverage industry toward sustainable and personalized marketing to meet consumer demand. This study integrates the Big Five personality model and... Show More

The global ecological crisis is driving the beverage industry toward sustainable and personalized marketing to meet consumer demand. This study integrates the Big Five personality model and experiential marketing theory, constructing a chain mediation model linking personality traits, experiential dimensions, experiential value (functional and hedonic), and green purchase intention. Using PLS-SEM on data from 688 Chinese consumers, the results show that openness influences all five experiential dimensions; extraversion affects all except think; conscientiousness influences only think; agreeableness impacts sense and feel; and neuroticism negatively affects all dimensions. Mediation analysis reveals that act and relate do not mediate functional value, while sense and act do not mediate hedonic value. These findings highlight how personality traits shape experiential marketing outcomes, emphasizing the importance for multinational beverage companies to tailor their strategies to consumer personalities in order to enhance green purchase intention and strengthen global competitiveness.

Artificial intelligence (AI) technologies are rapidly being deployed to develop AI-powered applications, including AI fitness apps. These AI-enhanced fitness apps are more intelligent and human-like... Show More

Artificial intelligence (AI) technologies are rapidly being deployed to develop AI-powered applications, including AI fitness apps. These AI-enhanced fitness apps are more intelligent and human-like than their conventional counterparts, offering users a highly engaging and personalized experience. However, the underlying mechanisms driving these experiences require further exploration. This research focuses on two key attributes of AI—perceived intelligence (PI) and perceived anthropomorphism (PA)—and investigates their effects on user behavioral intentions through various gratifications in the context of AI fitness apps. Using survey data from 408 participants, our empirical findings reveal that PI and PA significantly influence users' intentions to use and purchase AI fitness apps, primarily by enhancing gratifications such as exercise enjoyment, social presence, and social interaction. These findings provide valuable insights and guidance for fitness app developers on leveraging AI technologies to optimize app functionalities and enhance user engagement.

As more and more organizations recognize the importance of data analytics, more and more academic departments and professional training programs engage in training future data analysts. However, not... Show More

As more and more organizations recognize the importance of data analytics, more and more academic departments and professional training programs engage in training future data analysts. However, not all geographical regions, states, or business industries have the same level of demand for data analysts. Based on over 2,500 data-analyst job advertisements posted on LinkedIn and utilizing Chi Square and Wilcoxon tests, this study examined which geographical regions, which states, and which business industries in the United States have the most or least demand for data analysts; it also explored the possible relationship between a state's demand for data analysts and its economic strength. Among many findings, the study discovered that the larger a state's economic strength or growth, the stronger its demand for data analysts.

This study investigates the impact of perceived organizational support (POS) on employees' intentions to continue using business analytics (BA) tools. By integrating Organizational Support Theory... Show More

This study investigates the impact of perceived organizational support (POS) on employees' intentions to continue using business analytics (BA) tools. By integrating Organizational Support Theory (OST) and technology adoption models, the research highlights the critical roles of technical and top management support in influencing perceived compatibility and usefulness, which drive BA continuance intentions. Data were collected between August and October 2021 from employees across various industries in Ireland, Finland, and Sweden who used BA tools in their work. Using Partial Least Squares Structural Equation Modeling (PLS-SEM) to analyze data, the findings reveal significant relationships between the organizational support types and continuance intentions, with technical support being particularly crucial for long-term use. This study extends OST by emphasizing the importance of technical support and confirms the relevance of perceived compatibility and usefulness in technology continuance.

The widespread influence of social media and online discourse has made enterprise public opinion monitoring essential, yet existing sentiment analysis models struggle with sarcasm detection... Show More

The widespread influence of social media and online discourse has made enterprise public opinion monitoring essential, yet existing sentiment analysis models struggle with sarcasm detection, multimodal sentiment integration, and high-risk user identification. Additionally, traditional text-based models face cross-domain generalization issues, limiting their effectiveness in real-world sentiment trend forecasting. To address these challenges, we propose HDLU-POMS (Hybrid Deep Learning and User Profiling-Enhanced Public Opinion Monitoring System), a novel framework that integrates Convolutional Neural Network-Long Short-Term Memory-Attention (CNN-LSTM-Attention) sentiment modeling, multimodal sarcasm detection, user profiling, and feature fusion. By incorporating audio-visual cues for sarcasm interpretation, behavioral metadata for user profiling, and feature fusion techniques for adaptability, HDLU-POMS enhances sentiment classification and trend forecasting.

As labour costs in China increase, labour-intensive industries are migrating to ASEAN countries, attracted by lower labour costs and market potential. This shift not only affects the economies of... Show More

As labour costs in China increase, labour-intensive industries are migrating to ASEAN countries, attracted by lower labour costs and market potential. This shift not only affects the economies of China and ASEAN but also reshapes the global manufacturing landscape. This paper investigates the correlation and spillover of supply chain risks using production exposure indicators derived from inter-country input-output data and the R-Vine Copula model. We assess the risk spillover of each country within the global supply chain. Our findings indicate that industrial relocation can significantly alter supply chain structures, thereby affecting the concentration and direction of risks. While China's role in the global textile supply chain has diminished, it remains significant, with notable increases in the roles of Vietnam and Thailand. This research reveals the supply chain risks between China and ASEAN in the context of industrial transfer, exploring the sustainable development of production linkages and sustainable economic cooperation among countries.

AI's expanding role in daily life offers data-driven decision-making but risks privacy breaches. This study, using the Communication Privacy Management theory, explores AI adoption's future privacy... Show More

AI's expanding role in daily life offers data-driven decision-making but risks privacy breaches. This study, using the Communication Privacy Management theory, explores AI adoption's future privacy implications. Through thematic analysis of 42 AI expert interviews, we identify six key themes: human agency, data use/abuse, AI transparency/opacity, information weaponization, cyberbullying, and privacy enforcement. These themes contextualize the evolving AI-privacy relationship. We argue that AI's advancement will challenge traditional privacy ownership concepts. This research provides insights into navigating the complex interplay between AI's growth and safeguarding information privacy

This study examines factors influencing continuous intention to use (CITU) e-learning systems in universities and professional organizations through a systematic literature review (SLR) of studies... Show More

This study examines factors influencing continuous intention to use (CITU) e-learning systems in universities and professional organizations through a systematic literature review (SLR) of studies from 2004 to 2022. Using a novel graphical synthesis method, we reconstruct the nomological network to map key constructs, revealing a predominant focus on utilitarian motivations like satisfaction and perceived usefulness. Key gaps include limited research on CITU outcomes, system characteristics, and intrinsic motivations. Most studies assume voluntary use, despite non-voluntary contexts in education and training. Additionally, longitudinal and mixed-methods studies remain scarce, with geographic coverage heavily skewed toward Asia. Our contributions include a novel graphical synthesis for visualizing research gaps and actionable recommendations for advancing CITU research in e-learning.