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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.

A survey was given to 545 college students.

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.

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.

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.

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.

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.

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.

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.

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.

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.

This research applies ALBERT, which is based on the latest Natural Language Processing (NLP) architecture Transformer, to library book purchase task.

This study aims to offer a bibliometric analysis of the already substantial and growing literature on global virtual teams (GVTs).

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.

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.

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.

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.

The purpose of this study is to identify the barriers that hinder the implementation of age-friendly initiatives in smart cities.

A systematic review of the literature was conducted using Scopus search engine. Relevant keywords were used to discover 81 publications in academic journals. The titles, abstracts, keywords and full texts of the publications were examined to select 39 publications that were relevant for identifying the barriers that hinder the implementation of age-friendly initiatives in smart cities. The contents of the 39 relevant publications were analysed to ascertain the key barriers. A system thinking approach was adopted to understand the interaction among the barriers.

The study identified five key groups of barriers – namely physical barriers and environmental characteristics, technological barriers, social barriers, financial barriers and political barriers – that smart cities encountered or are likely to encounter in implementing age-friendly initiatives. Moreover, practical examples of good age-friendly implementation practices were highlighted.

A limitation of this study is in the number of publications reviewed. Despite the comprehensive review, the number of publications reviewed may not be exhaustive. This is justified by the inapplicability of considering all possible keywords in one review study.

The systemic perspective of the barriers that hinder the implementation of age-friendly initiatives in smart cities would support policymakers in formulating policy recommendations to improve age-friendliness in cities.

This study underscores the variable and dynamic nature of developing age-friendly smart cities and forms novel basis for gaining insights into the multiple factors that can promote the integration of age-friendly initiatives within smart cities.

The purpose of this paper is threefold. First, it aims to clarify the moderating role of self-esteem (SE) and susceptibility to normative influence (SNI) in the relationship between brand love and brand loyalty. Second, the study proposes modeling the mediation role of brand love and outlining how SE and SNI affect the consumer-brand relationship. Finally, the study explores the impact of brand love on brand loyalty: the moderating role of self-esteem and social influences, as the literature regarding this is still lacking.

Data were collected via an online survey, which yielded 218 responses. Structural equation modeling was used to predict the research model.

The findings indicate that both SE and SNI mediate the relationship between brand love and brand loyalty. Additionally, consumers love the focal brands positively relates to SE and SNI. In return, SE and SNI lead to brand loyalty. The tight relationship of SE and SNI affects the connection between brand love and brand loyalty.

The data has been collected in Vietnam, which creates a limitation regarding the study’s cross-cultural nature and the economic context. Thus, the study should be conducted in different cultures and economies (both developing and developed countries) to enhance the generalizability in consumer-brand relationships.

Brand managers should conduct more advertising in brand communities to enhance the influence of SNI and emphasize unique features of the brands, to attract consumers through the overlap of SE.

The findings can contribute to enhancing unique brand identity and self-motivation will increase consumer loyalty, increasing the revenue of a specific brand. Moreover, as acceptable peers contribute to making purchase decisions, boosting the brand community will maintain current consumers and attract additional potential consumers from the current consumer relationships.

This study contributes to consumer psychology by indicating both SNI and SE as the mediators in the relationship between brand love and brand loyalty and how the consumer-brand relationship can be enabled.

El propósito de este trabajo es triple. En primer lugar, pretende aclarar el papel moderador de la autoestima (SE) y la susceptibilidad a la influencia normativa (SNI) en la relación entre el amor y la lealtad a la marca. En segundo lugar, el estudio propone modelar el papel mediador del amor a la marca y esbozar cómo la autoestima y la SNI afectan a la relación consumidor-marca. Por último, el estudio explora los factores que afectan a la relación entre el amor a la marca y la lealtad a la misma, ya que aún no existe literatura al respecto.

Los datos se recogieron mediante una encuesta en línea, que arrojó 218 respuestas. Se utilizó el modelo de ecuaciones estructurales (SEM) para predecir el modelo de investigación.

Los hallazgos indican que tanto la autoestima como la SNI median la relación entre el amor y la lealtad a la marca. Además, el amor de los consumidores por las marcas focales se relaciona positivamente con la autoestima y la SNI. En cambio, la autoestima y la SNI conducen a la lealtad a la marca. La estrecha relación de la autoestima y la SNI afecta la conexión entre el amor a la marca y la lealtad a la misma.

Los datos se han recogido en Vietnam, lo que crea una limitación en cuanto a la naturaleza transcultural del estudio y el contexto económico. Así pues, el estudio debería realizarse en diferentes culturas y economías (tanto de países en desarrollo como desarrollados) para aumentar la posibilidad de generalización en las relaciones entre consumidores y marcas.

Los gerentes de marca deberían hacer más publicidad en las comunidades de marcas para aumentar la influencia de la SNI y hacer hincapié en las características singulares de las marcas, a fin de atraer a los consumidores mediante la superposición de la autoestima.

Las conclusiones pueden contribuir a mejorar la identidad de una marca única, y la automotivación aumentará la lealtad de los consumidores, incrementando los ingresos de una marca específica. Además, como los pares aceptables contribuyen a la toma de decisiones de compra, el impulso de la comunidad de marcas mantendrá a los consumidores actuales y atraerá a otros consumidores potenciales de las relaciones de consumo actuales.

Este estudio contribuye a la psicología del consumidor al indicar que tanto la SNI como la autoestima son los mediadores en la relación entre el amor y la lealtad a la marca y la forma en que se puede habilitar la relación consumidor-marca.

摘要

本文有三方面的研究目的。第一，明确自尊（SE）和易受规范影响（SNI）在品牌喜爱与品牌忠诚关系中的调节作用。第二，建立品牌喜爱的中介作用模型，并概述SE和SNI如何影响消费者与品牌的关系。最后，探讨品牌喜爱对品牌忠诚度的影响：自尊和社会影响因素的调节作用，目前有关这方面的文献还比较缺乏。

通过在线调查收集数据，共收到218份答复。采用结构方程模型进行预测研究模型。

研究结果表明，自尊和易受规范影响都对品牌喜爱和品牌忠诚度之间的关系起到了调节作用。此外，消费者对焦点品牌的喜爱与自尊和易受规范影响具有正相关关系。反过来，自尊和易受规范影响又会导致品牌忠诚。自尊和易受规范影响的紧密关系影响了品牌喜爱和品牌忠诚之间的联系。

由于本次研究数据是在越南收集的，造成了研究的跨文化性质和经济背景的局限性。因此，未来的研究可以在不同的文化和经济体（包括发展中国家和发达国家）进行，以提高关于消费者与品牌关系结论的普遍性。

品牌管理者可以在品牌社区中增强广告宣传，提高易受规范影响的影响力，同时强调品牌的独特性，与自尊因素相结合来吸引消费者。

本文研究结果有助于增强独特的品牌识别和自我激励，提高消费者的忠诚度，增加特定品牌的收入。此外，由于合适的同伴有助于消费者做出购买决策，提升品牌社区可以维持现有消费者，并通过现有消费者关系吸引更多的潜在消费者。

本研究提出了自尊和易受规范影响是品牌喜爱和品牌忠诚关系的调节变量，并且进一步阐释了它们如何促成消费者与品牌的关系，从而为消费者心理学做出了贡献。

This study aims to propose a conceptual framework for transition of brand trust to brand love in an uncertain market situation, from the perspective of cognitive-emotion theory (CET).

Since brand anthropomorphism is successfully established in branding research, this study takes cognitive characteristics of brand trust and emotional characteristic of brand love from extant literature to develop a conceptual framework for transformation of brand trust (cognition) into brand love (emotion). This study situates the relationship in the context of market uncertainty due to the COVID-19 pandemic. It focuses in the development of the conceptual framework by taking cognitive components of brand trust and brand behavioural characteristics as moderator, in uncertain market situation.

Findings suggest that transition of brand trust (cognition) to brand love (emotion) is possible in uncertain situation, and brand behavioural characteristics moderate this relationship. Brand behavioural characteristics are brand innovativeness, brand ethicality, brand empathy, brand expertise and brand agility, which have the potential to further strengthen the relationship in the given situation.

This research proposes a conceptual model and propositions that add a rich understanding to the relationship of brand trust and brand love, which requires empirical testing in any brand category context. Through a richer understanding of conditions and the underlying psychological mechanism, researchers and marketers, brand managers, policymakers and so forth can gain insights that aid strategic decision-making. Trusted brands can leverage on the situation by highlighting unique behavioural characteristics to establish a strong and sustainable long-term relationship.

The current research is an attempt to provide deeper insights from the perspective of CET, into the relationship of brand trust (cognition) and brand love (emotion) by introducing conditions under which a trusted brand becomes a lovable brand in uncertain market situation, thereby adding new knowledge to branding, customer-brand relationship sustainability, in uncertainty literature. The new perspective, that is CET, puts forward a novice view on the advantage of brand love over brand trust that could help in formulating strategic decisions in managing brands in crisis situation.

Human resource managers are adopting AI technology for conducting various tasks of human resource management, starting from manpower planning till employee exit. AI technology is prominently used for talent acquisition in organizations. This research investigates the adoption of AI technology for talent acquisition.

This study employs Technology-Organization-Environment (TOE) and Task-Technology-Fit (TTF) framework and proposes a model to explore the adoption of AI technology for talent acquisition. The survey was conducted among the 562 human resource managers and talent acquisition managers with a structured questionnaire. The analysis of data was completed using PLS-SEM.

This research reveals that cost-effectiveness, relative advantage, top management support, HR readiness, competitive pressure and support from AI vendors positively affect AI technology adoption for talent acquisition. Security and privacy issues negatively influence the adoption of AI technology. It is found that task and technology characteristics influence the task technology fit of AI technology for talent acquisition. Adoption and task technology fit of AI technology influence the actual usage of AI technology for talent acquisition. It is revealed that stickiness to traditional talent acquisition methods negatively moderates the association between adoption and actual usage of AI technology for talent acquisition. The proposed model was empirically validated and revealed the predictors of adoption and actual usage of AI technology for talent acquisition.

This paper provides the predictors of the adoption of AI technology for talent acquisition, which is emerging extensively in the human resource domain. It provides vital insights to the human resource managers to benchmark AI technology required for talent acquisition. Marketers can develop their marketing plan considering the factors of adoption. It would help designers to understand the factors of adoption and design the AI technology algorithms and applications for talent acquisition. It contributes to advance the literature of technology adoption by interweaving it with the human resource domain literature on talent acquisition.

This research uniquely validates the model for the adoption of AI technology for talent acquisition using the TOE and TTF framework. It reveals the factors influencing the adoption and actual usage of AI technology for talent acquisition.

This study aims to systematically review the current academic literature on the role of technologies in low-carbon supply chain management (SCM), identify and analyse critical themes and propose an integrated conceptual model.

A systematic literature review of 48 papers published between 2010 and 2022 was conducted. A conceptual model was advanced.

Based on the analysis and synthesis of the reviewed papers, this review provides an initial attempt to integrate technology adoption and low-carbon SCM by developing a diffusion of innovation model of technology-enabled low-carbon SCM within the technology–organisation–environment (TOE) framework, in which drivers, enablers and barriers to technology adoption practices are identified. The environmental, economic and social outcomes of adoption practices are also identified.

This study provides a novel and comprehensive roadmap for future research on technology-enabled low-carbon SCM. Furthermore, policy, as well as managerial implications, is presented for policymakers and managers.

The purpose of this paper is to explore the evolvement of investors’ behavior in stock market dynamically on the basis of non-cooperative strategy applied by investors in complex networks.

Using modeling and simulation research method, this study designs and conducts a mathematical modeling and its simulation experiment of financial market behavior according to research’s basic norms of complex system theory and methods. Thus the authors acquire needed and credible experimental data.

The conclusions drawn in this paper are as follows. The dynamical evolution of investors’ trading behavior is not only affected by the stock market network structure, but also by the risk dominance degree of certain behavior. The dynamics equilibrium of trading behavior’s evolvement is directly influenced by the risk dominance degree of certain behavior, connectivity degree and the heterogeneity of the stock market networks.

This paper focuses on the dynamical evolvement of investors’ behavior on the basis of the hypothesis that common investors prefer to mimic their network neighbors’ behavior through different analysis by the strategy of anti-coordination game in complex network. While the investors’ preference and the beliefs among them are not easy to quantify, that is deterministic or stochastic as the environment changes, and is heterogeneous definitely. Thus, these limitations should be broken through in the future research.

This paper aims to address the dynamical evolvement of investors’ behavior in stock market networks on the principle of non-cooperative represented by anti-coordination game in networks for the first time, considering that investors prefer to mimic their network neighbors’ behavior through different analysis by the strategy of differential choosing in every time step. The methodology designed and used in this study is a pioneering and exploratory experiment.