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1 – 10 of over 1000Xiao-Yu Xu, Syed Muhammad Usman Tayyab, Qingdan Jia and Albert H. Huang
Video game streaming (VGS) is emerging as an extremely popular, highly interactive, inordinately subscribed and very dynamic form of digital media. Incorporated environmental…
Abstract
Purpose
Video game streaming (VGS) is emerging as an extremely popular, highly interactive, inordinately subscribed and very dynamic form of digital media. Incorporated environmental elements, gratifications and user pre-existing attitudes in VGS, this paper presents the development of an extended model of uses and gratification theory (EUGT) for predicting users' behavior in novel technological context.
Design/methodology/approach
The proposed model was empirically tested in VGS context due to its popularity, interactivity and relevance. Data collected from 308 VGS users and structural equation modeling (SEM) was employed to assess the hypotheses. Multi-model comparison technique was used to assess the explanatory power of EUGT.
Findings
The findings confirmed three significant types elements in determining VGS viewers' engagement, including gratifications (e.g. involvement), environmental cues (e.g. medium appeal) and user predispositions (e.g. pre-existing attitudes). The results revealed that emerging technologies provide potential opportunities for new motives and gratifications, and highlighted the significant of pre-existing attitudes as a mediator in the gratification-uses link.
Originality/value
This study is one of its kind in tackling the criticism on UGT of considering media users too rational or active. The study achieved this objective by considering environmental impacts on user behavior which is largely ignored in recent UGT studies. Also, by incorporating users pre-existing attitudes into UGT framework, this study conceptualized and empirically verified the higher explanatory power of EUGT through a novel multi-modal approach in VGS. Compared to other rival models, EUGS provides a more robust explanation of users' behavior. The findings contribute to the literature of UGT, VGS and users' engagement.
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Sean Lancaster, David C. Yen, Albert H. Huang and Shin‐Yuan Hung
Instant messaging and e‐mail are popular communication methods on college campuses. However, students' perceptions of the two technologies vary greatly. This study seeks to…
Abstract
Purpose
Instant messaging and e‐mail are popular communication methods on college campuses. However, students' perceptions of the two technologies vary greatly. This study seeks to investigate the differences between instant messaging and e‐mail.
Design/methodology/approach
A survey was given to 545 college students.
Findings
Instant messaging is perceived as offering many advantages over e‐mail including conveying emotions, building relationships and ease of use (EU). Users are more likely to use symbols with their instant messages to help communicate. College students find both technologies to be easy to use, but show a preference for the EU of instant messaging. However, despite its perceived functional benefits, instant messaging is only the favored form of communication for personal and social relationships.
Originality/value
This paper builds on existing research by discussing information richness, EU, the use of emotions, multimedia, playfulness, flow, cognitive fit theory, bounded rationality, perceived commitment, and user satisfaction in the course of the study.
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I-Cheng Chang, Chuang-Chun Liu and Kuanchin Chen
The focus in this study is a model that predicts continuance intention of online multi-player games. In this integrated model, the social cognitive theory (SCT) lays out the…
Abstract
Purpose
The focus in this study is a model that predicts continuance intention of online multi-player games. In this integrated model, the social cognitive theory (SCT) lays out the foundation of two types of pre-use (pre-play) expectations, the flow theory captures the affective feeling with the game as a moderator for the effect from the two pre-use expectations, and subjective norm together with its associated antecedents cover a wide spectrum of social influences.
Design/methodology/approach
A questionnaire was designed and pre-tested before distributing to target respondents. The reliability and validity of the instrument both met the commonly accepted guidelines. The integrated model was assessed first by examining its measurement model and then the structural model.
Findings
The integration of cognitive, affective and social influence in this model explains a larger amount of variance compared to the competing models and existing studies.
Originality/value
Unlike a popular trend that studies predictors of online games from either cognitive or affect angle, the work looks at both together to study how their joint effect is related to continuance intention. This marks an important improvement as cognitive expectations derived from SCT captures the pre-use experience that may be influenced or swayed by sources including those that are inflated or incorrect. By studying flow as a moderator in conjunction with other sources of influence, the authors are able to further the understanding of how the pre-use expectations may be shaped by one's own experience.
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Yejun Wu, Xiaxian Wang, Peilin Yu and YongKai Huang
The purpose of this research is to achieve automatic and accurate book purchase forecasts for the university libraries and improve efficiency of manual book purchase.
Abstract
Purpose
The purpose of this research is to achieve automatic and accurate book purchase forecasts for the university libraries and improve efficiency of manual book purchase.
Design/methodology/approach
The authors presented a Book Purchase Forecast model with A Lite BERT(ALBERT-BPF) to achieve their goals. First, the authors process all the book data to unify format of books' features, such as ISBN, title, authors, brief introduction and so on. Second, they exploit the book order data to label all books supplied by booksellers with “purchased” or “non-purchased”. The labelled data will be used for model training. Last, the authors regard the book purchase task as a text classification problem and present a model named ALBERT-BPF, which applies ALBERT to extract text features of books and BPF classification layer to forecast purchased books, to solve the problem.
Findings
The application of deep learning in book purchase task is effective. The data the authors exploited are the historical book purchase data from their university library. The authors’ experiments on the data show that ALBERT-BPF can seek out the books that need to be purchased with an accuracy of over 82%. And the highest accuracy reached is 88.06%. These indicate that the deep learning model is sufficient to assist the traditional manual book purchase way.
Originality/value
This research applies ALBERT, which is based on the latest Natural Language Processing (NLP) architecture Transformer, to library book purchase task.
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Sheng-Qun Chen, Ting You and Jing-Lin Zhang
This study aims to enhance the classification and processing of online appeals by employing a deep-learning-based method. This method is designed to meet the requirements for…
Abstract
Purpose
This study aims to enhance the classification and processing of online appeals by employing a deep-learning-based method. This method is designed to meet the requirements for precise information categorization and decision support across various management departments.
Design/methodology/approach
This study leverages the ALBERT–TextCNN algorithm to determine the appropriate department for managing online appeals. ALBERT is selected for its advanced dynamic word representation capabilities, rooted in a multi-layer bidirectional transformer architecture and enriched text vector representation. TextCNN is integrated to facilitate the development of multi-label classification models.
Findings
Comparative experiments demonstrate the effectiveness of the proposed approach and its significant superiority over traditional classification methods in terms of accuracy.
Originality/value
The original contribution of this study lies in its utilization of the ALBERT–TextCNN algorithm for the classification of online appeals, resulting in a substantial improvement in accuracy. This research offers valuable insights for management departments, enabling enhanced understanding of public appeals and fostering more scientifically grounded and effective decision-making processes.
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Ernesto Tavoletti and Vas Taras
This study aims to offer a bibliometric analysis of the already substantial and growing literature on global virtual teams (GVTs).
Abstract
Purpose
This study aims to offer a bibliometric analysis of the already substantial and growing literature on global virtual teams (GVTs).
Design/methodology/approach
Using a systematic literature review approach, it identifies all articles in the Web of Science from 1999 to 2021 that include the term GVTs (in the title, the abstract or keywords) and finds 175 articles. The VOSviewer software was applied to analyze the bibliometric data.
Findings
The analysis revealed three dialogizing research clusters in the GVTs literature: a pioneering management information systems and organizational cluster, a general management cluster and a growing international management and behavioural studies cluster. Furthermore, it highlights the most cited articles, authors, journals and nations, and the network of strong and weak links regarding co-authorships and co-citations. Additionally, this study shows a change in research patterns regarding topics, journals and disciplinary approaches from 1999 to 2021. Finally, the analysis illustrates the position and centrality in the network of the most relevant actors.
Practical implications
The findings can guide management practitioners, educators and researchers to the most meaningful clusters of publications on GVTs, and help navigate and make sense of the vast body of the available literature. The importance of GVTs has been growing in the past two decades, and Covid-19 has accelerated the trend.
Originality/value
This study provides an updated and comprehensive systematic literature review on GVTs. To the best of the authors’ knowledge, it is also the first systematic literature review and bibliometry on GVTs. It concludes by suggesting future research paths.
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Michael G H Bell, Jan-Dirk Schmoecker, Yasunori Iida and William H K Lam
Pamala J. Dillon and Charles C. Manz
We develop a multilevel model of emotional processes grounded in social identity theory to explore the role of emotion in transformational leadership.
Abstract
Purpose
We develop a multilevel model of emotional processes grounded in social identity theory to explore the role of emotion in transformational leadership.
Methodology/approach
This work is conceptual in nature and develops theory surrounding emotion in organizations by integrating theories on transformational leadership, emotion management, and organizational identity.
Findings
Transformational leaders utilize interpersonal emotion management strategies to influence and respond to emotions arising from the self-evaluative processes of organizational members during times of organizational identity change.
Research limitations/implications
The conceptual model detailed provides insight on the intersubjective emotional processes grounded in social identity that influence transformational leadership. Future research into transformational leadership behaviors will benefit from a multilevel perspective which includes both interpersonal emotion management and intrapersonal emotion generation related to social identity at both the within-person and between-person levels.
Originality/value
The proposed model expands on the role of emotions in transformational leadership by theoretically linking the specific transformational behaviors to discrete emotions displayed by followers. While previous empirical research has indicated the positive outcomes of transformational leadership and the role of emotion recognition, work has yet to be presented which explicates the role of discrete emotions in the transformational leadership process.
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