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The purpose of this paper is to develop a research model that explains team performance based on social cognitive theory and social exchange theory. In the model, team performance indirectly relates to three kinds of leadership (i.e., charismatic, autocratic and considerate) via the full mediation of collective efficacy. At the same time, team justice as a focus in this study is examined as a moderator in the model.

The research hypotheses of this study were empirically tested using two-wave data collection across insurance sales teams from a leading bank holding company which is the largest bank holding company in Taiwan. In the first-wave data collection, researchers of this study surveyed six people anonymously from each sales team, including a team leader and five team members. Three months later, the researchers conducted the second-wave data collection by obtaining team performance data from the department of human resource management, which was an independent rater for each team’s performance. Two-wave data collection from 59 teams was achieved for verifying the hypothesized effects.

The team-level test results show that collective efficacy fully mediates the relationship between charismatic leadership and team performance and between considerate leadership and team performance. Justice moderates the relationship between collective efficacy and team performance and between charismatic leadership and collective efficacy.

This study has two major theoretical implications. First, this study conceptualized three distinct kinds of leadership as major determinants of team performance from a social exchange perspective. Such a theoretical conceptualization of leadership not only broadens the boundary of leadership beyond traditional one such as transactional leadership based on the theory of contingent reward but also closely reflects the practical status quo of leadership of teams. Second, this research incorporated social exchange theory into the framework of team performance in social cognitive theory. Specifically, this study theorized and validated justice as a moderator in the development of team performance.

With the growing global emphasis on environmental, social and governance (ESG) criteria, it is crucial to investigate the factors that influence individuals' intentions to invest in ESG and to understand the underlying mechanisms at play. This study constructs a theoretical model, grounded in the Fogg behavioral model (FBM), and explores the mediating role of ESG investment attitudes in shaping individuals' ESG investment behaviors.

A survey was conducted among ESG investors and potential ESG investors in China, resulting in 613 valid responses regarding ESG investment. The partial least squares structural equation modeling (PLS-SEM) approach was utilized to evaluate the proposed model and test the hypotheses.

The results reveal that future orientation, ESG investment bias and perceived ESG investment performance are significant determinants of ESG investment intentions, with attitude playing a partially mediating role. Furthermore, government support moderates the relationship between perceived ESG investment performance and investment intention.

This study expands the application of the FBM to the context of ESG investment and introduces a novel conceptual framework for understanding ESG investment behavior. The findings provide valuable insights for enterprises and institutions involved in ESG investment, aiding them in identifying and targeting potential investors more effectively. Additionally, the study offers a foundation for policymakers to devise strategies that promote sustainable development.

The theoretical background bases on the big data analytics-artificial intelligence (BDA-AI) technologies and supply chain ambidexterity (SCAX) in the firms to assess their sustainability endeavors such as green supply chain management (GSCM) to improve their green communication and corporate image.

Around 220 participants in the manufacturing firms are participants' industry expertise, diverse roles, and representation as key stakeholders.

The results show BDA-AI and SCAX affected on GSCM and found the significant relationships with green communication and corporate image. Green communication was discovered to impact corporate image significantly.

Prior studies are neglected to address the relationship among the AI, powered by rapid computational and BDA breakthroughs, redefines cognitive tasks, achieving feats previously deemed impossible-making implicit judgments, simulating emotions, and driving operations. This study selects manufacturing firms as respondents due to their forefront of BDA-AI and supply chain ambidexterity adoption to benefit the operational efficiency and competitiveness. The firms intricate supply chains, diverse stakeholders, and strategic emphasis on corporate image make it an ideal context to examine the nuanced impact of these technologies.

This research proposes and examines a theoretical model grounded in anthropomorphism theory considering the curvilinear and linear relationships between service robot anthropomorphism and consumer usage intention and explores the mediating effect of perceived risk.

To examine the developed model, two complementary studies are designed. In Study 1, multi-time data of 511 participants show that service robot anthropomorphism inverts U-shaped (curvilinear) relationship on consumer usage intention and perceived risk mediates this curvilinear relationship. In Study 2, multi-source data of 460 volunteers are used to confirm the findings of Study 1 and examine that consumer empathy moderates the complex nonlinear effect of service robot anthropomorphism on perceived risk, and the indirect curvilinear effect of service robot anthropomorphism on consumer usage intention through perceived risk.

This research provides preliminary and yet important findings on how service robot anthropomorphism most likely is positively associated with consumer usage intention, i.e. the positively influence mechanism of service robot anthropomorphism on consumer usage intention.

This research provides preliminary and yet important findings on how service robot anthropomorphism most likely is positively associated with consumer usage intention, i.e. the positively influence mechanism of service robot anthropomorphism on consumer usage intention.

This study aims to measure the integrated impact of big data analytics and artificial intelligence (BDA-AI) adoption by using the ChatGPT generative AI online platform as a BDA-AI tool on the operational and environmental performance.

This study considers Taiwanese professionals who engage with ChatGPT; the sample consists of 388 online users.

This study’s main finding is that the considered antecedents – including technological, organizational and environmental contexts, tangible resources and workforce skills – are significantly associated with BDA-AI adoption. Notably, BDA-AI adoption exhibits a significant relationship with operational performance, environmental performance and environmental process integration. Moreover, environmental process integration is significantly correlated with environmental performance. Lastly, operational performance is significantly correlated with environmental performance.

This study contributes to the heavily lacking but developing literature on the antecedents and consequences of BDA-AI adoption. Its theoretical foundation consists of the technological-organizational-environmental model, Roger’s diffusion of innovation theory and resource-based view theory.

As a high-reward strategy to differentiate social platforms, value co-creation is increasingly becoming a tool to enhance customers' social attachment. However, there is still a lack of academic understanding of the value co-creation that enables users to build social attachment with social platforms. To address this challenge, we develop and then examine a theoretical model grounded in value co-creation theory considering the relationship between value co-creation and social attachment, and also explore the mediating effect of user experience and the moderating effect of self-disclosure.

This study takes representative social platform users as the research object, chooses Questionnaire Star as the platform for questionnaire distribution and collection and collects 531 eligible data through the snowball sampling questionnaire method. And then, MPLUS7.4 is used to analyze the data and thus examine our proposed theoretical model.

The results of structural equation modeling analysis suggest that two dimensions of value co-creation (i.e. initiated value co-creation and spontaneous value co-creation) affect social attachment not only directly but also indirectly (i.e. the mediating role of user experience) and that self-disclosure moderates the impact of value co-creation affecting social attachment.

This study verifies the impact of different dimensions of value co-creation toward social platforms on social attachment, showing that value co-creation plays an important role in developing users' social attachment and provides practical implications for promoting the sustainable development of social platforms and building users' psychological well-being.

This study aims to empirically analyse the influence mechanism of perceived interactivity in real estate APP which affects consumers' psychological well-being. With the growing application of human–machine interaction in real estate APP, it is crucial to utilize human–machine interaction to stimulate perceived interactivity between humans and machines to positively impact consumers' psychological well-being and sustainable development of real estate APP. However, it is unclear whether perceived interactivity improves consumers' psychological well-being.

This study proposes and examines a theoretical model grounded in the perceived interactivity theory, considers the relationship between perceived interactivity and consumers' psychological well-being and explores the mediating effect of perceived value and the moderating role of privacy concerns. It takes real estate APP as the research object, analyses the data of 568 consumer samples collected through questionnaires and then employs structural equation modelling to explore and examine the proposed theoretical model of this study.

The findings are that perceived interactivity (i.e. human–human interaction and human–information interaction) positively influences perceived value, which in turn affects psychological well-being, and that perceived value partially mediates the effect of perceived interaction on psychological well-being. More important findings are that privacy concerns not only negatively moderate human–information interaction on perceived value, but also negatively moderate the indirect effects of human–information interaction on users' psychological well-being through perceived value.

This study expands the context on perceived interaction and psychological well-being in the field of real estate APP, validating the mediating role and boundary conditions of perceived interactivity created by human–machine interaction on consumers' psychological well-being, and suggesting positive implications for practitioners exploring human–machine interaction technologies to improve the perceived interaction between humans and machines and thus enhance consumer psychological well-being and span sustainable development of real estate APP.

In this era of smartphone applications, brands are actively developing applications to occupy the consumer’s mobile phone space, adding many practical functions to their applications to increase brand exposure or consumer interest in the brand. Augmented reality (AR) has evolved rapidly in the past decade because of technological breakthroughs, making AR no longer an untouchable technology, but one that can be easily used on almost every phone. Therefore, this study aims to combine extended customer experience with AR marketing activities to explain and predict usage and purchase intention.

The eight key factors integrated into the extended customer experience are used as environmental stimulation factors, and Wanna Kicks and FitGlasses are used as experimental environments. A total of 193 valid samples were collected from users with AR experience. The empirical data is processed and verified by partial least squares in this study.

Customer experience has received increasing attention in the field of marketing research. This study developed a model to evaluate the antecedents and consequences of AR marketing activities by systematically adding customer experience, continuance intention, purchase intention and customer engagement, and then linking them to the AR application environment. This study presents the academic and practical implications, which can provide future research directions and references for brand marketing strategies and AR applications.

This study adds interactivity, vividness, perceived usefulness and novelty to the extended concept of customer experience. Therefore, the authors proposed that the extended customer experience can be used to measure the perceptions related to AR applications. This study is expected to provide scholars and practitioners in AR fields with a better understanding of the causes and consequences of customer experience with innovative technologies and to suggest effective marketing recommendations.

在这个智能手机应用时代, 品牌积极发展能占据消费者的手机空间的应用软件, 在已有的应用软件上增加了许多实用性功能来增加品牌曝光或消费者对品牌的兴趣。增强现实 (AR) 在过去十年中由于技术突破从而发展迅速, 让AR不再触不可及, 而是几乎可以在每部手机上轻松使用的技术。因此, 本研究通过结合 AR 营销活动以及延展顾客体验, 来以解释和预测用户使用和购买意向。

本研究用延展顾客体验模型中的八项关键因素来作为环境刺激因素, Wanna Kicks 和 FitGlasses 用作实验环境。 本研究从具有 AR 经验的用户那里收集193个有效样本。数据通过偏最小二乘法来进行处理和验证。

客户体验在营销领域受到越来越多的关注。本研究通过系统地添加客户的 体验、持续意向、购买意向和客户参与度, 然后将它们链接到 AR 应用环境来评估AR 营销活动的前因和后果来建立了一项模型。本研究提出了学术和实践意义, 可以提供未来的研究方向品牌营销策略和AR应用提供参考。

这项研究对客户体验扩展概念增加了交互性、生动性、感知有用性、以及新颖性。因此, 我们建议延展客户体验模型可运用于衡量与 AR 应用相关的用户感知。本研究旨在为学者和AR领域的从业者关于创新技术的客户体验的因果提供更进一步的认知, 并提出有效的营销建议。

Self‐service technologies (SSTs) allow customers to offer their own service encounters via the interaction of electronic service interfaces or machines rather than by interacting with a firm's service personnel. This paper aims to develop an integrated model designed to predict and explain an individual's continuous use of SSTs based on the concepts of technology readiness (TR), technology acceptance model (TAM), and theory of planned behavior (TPB).

The participants are from 481 SST users as the sample finally. Structural equation modeling is applied to demonstrate the stability of the proposed model and the results of hypotheses testing.

This paper finds that consumers' satisfaction significantly influences continuance intention, while the perceived usefulness, perceived ease of use, subjective norm (SN), and perceived behavioral control (PBC) simultaneously influence satisfaction. Optimism and innovativeness are also the significant motivators of satisfaction. However, TR's inhibitors (discomfort and insecurity) have no significantly negative influence on continuance intention towards adopting SST services.

Different from previous SSTs studies, this paper suggests that SN and PBC play critical factors in users' adoption at SSTs encounters. However, additionally empirical evidences should be discussed why the inhibitors (discomfort and insecurity) of TR have no effect.

This paper proposes a comprehensive model to synthesize the essence of TR, TAM, and TPB for explaining customers' continuous intention of SSTs.