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This study investigates the key factors that influence customer satisfaction when interacting with augmented reality shopping assistance applications (ARSAPs). ARSAPs grant consumers the capability to experience products in a virtually simulated user environment before product acquisition. With the development of mobile e-commerce due to breakthroughs in smartphone and augmented reality (AR) technologies, there is an increasing potential for these emergent AR mobile services, yet there is a need for further improvement.

This study initially explored the key satisfaction factors for ARSAPs by utilizing topic modeling of a collection of actual user reviews. These factors are subsequently revisited and complemented by existing literature, and finally verified through logistic regression analysis supported by sentiment analysis.

This study identified the key factors that influence customer satisfaction with ARSAPs, including visuality, sense of reality, credibility, format, completeness, understandability, relevance, flexibility, response time, reliability, availability, ease of use and privacy. In particular, two additional factors (i.e. visuality and sense of reality) were newly identified as important in the context of AR, despite their previous omissions in existing literature.

This study is the first to investigate the key factors that influence customer satisfaction with ARSAPs from users' perspectives, utilizing topic modeling of a large amount of real-world data on actual user feedback. By identifying new factors (i.e. visuality and sense of reality) that were not identified in previous literature, this study provides important academic implications for a broader understanding of AR and related technologies that are essential elements of the metaverse. This study also provides valuable insights for developers and companies in the e-commerce industry on how to optimize AR applications and develop more targeted and effective marketing strategies in this field.

This study investigates the individual and binary (i.e. combined) effects of institutional dimensions of open government data (which include instructional, structural and accessible rules) on scientific research innovation, as well as the mediating roles that researchers' perceived data usefulness and data capability play in between.

Based on a sample of 1,092 respondents, this study uses partial least squares structural equation modeling (PLS-SEM) and polynomial regression with response surface analysis to evaluate the direct and indirect effects of individual and binary institutional dimensions on scientific research innovation.

The findings demonstrate that instructional, structural and restricted access data have a positive effect on scientific research innovation in the individual effect. While the binary effect of institutional dimensions produces varying degrees of scientific research innovation. Furthermore, this study discovers that the perceived usefulness and data capability of researchers differ in the mediating effect of institutional dimensions on scientific research innovation.

Theoretically, this study contributes new knowledge on the causal links between data publication institutions and innovation. Practically, the research findings offer government data managers timely suggestions on how to build up institutions to foster greater data usage.

Numerous attempts at installing six sigma (SS) have faced challenges and fallen short of the desired success. Thus, it becomes vital to identify the critical factors and characteristics that play a pivotal role in achieving successful adoption. In this study the research has aimed to highlight that a considerable number of corporate SS initiatives, around 60%, fail primarily due to the improper incorporation of essential elements and flawed assumptions.

To validate the influence of critical success factors (CSFs) on SS accomplishment, the study employed a research design combining exploratory and mixed-methods approaches. A Likert-scale questionnaire was utilized, and a simple random sampling method was employed to gather data. Out of the 2,325 potential participants approached, 573 responses were received, primarily from Germany, the United Kingdom and Sweden. The analysis focused on 260 completed questionnaires and statistical methods including structural equation modeling (SEM), exploratory factor analysis (EFA) and Confirmatory Factor Analysis (CFA) were utilized for data analysis.

The study acknowledged four essential components of CSFs that are imperative for sustaining the success of SS: (1) Competence of belt System employees; (2) Project management skills; (3) Organizational economic capability and (4) Leadership commitment and engagement. These factors were identified as significant contributors to the maintenance of SS’s success.

The practical implications of this research imply that institutions, practitioners, and researchers can utilize the four identified factors to foster the sustainable deployment of SS initiatives. By incorporating these factors, organizations can enhance the effectiveness and longevity of their SS practices.

The investigation's originality lies in its contribution to assessing CSFs in SS deployment within the European automobile industry, utilizing a mixed-methods research design supplemented by descriptive statistics.

The present study examined the psychometric properties of the EGame- flow scale in a Mexican sample, presenting evidence of construct validity (exploratory factor analysis and confirmatory factor analysis), reliability (Cronbach’s alpha and McDonald’s omega) and discriminant validity (mean variance extracted).

Participants: Of the 255 Mexican participants in the non-probabilistic sample who had previously interacted with the LOST logistics simulator, 166 (65%) were men and 89 (35%) were women; their ages ranged from 22 to 45. The statistical packages SPSS 25, JASP 0.16 and AMOS 23 facilitated the corresponding analyses. First, we calculated the means and standard deviations of the scale items. Next, we performed an exploratory factor analysis to examine the measurement model’s internal structure and a confirmatory factor analysis to confirm the structure proposed in the exploratory factor analysis. To analyze the internal structure of the measurement model so that the estimates were not affected by multivariate normality problems, we utilized the AMOS bootstrap method (with 500 repetitions, 95% CI), the maximum likelihood (MV) estimation method, and the fit indices: X2, p (chi-square and associated likelihood), Tucker–Lewis index (TLI), standardized statistical mean square residual (SRMR), comparative fit index (CFI) and root mean Square error approximation (RMSEA) with its confidence interval, the values of X2 with p < 0.001; TLI, CFI, AGFI = 0.95; RMSEA and SRMR = 0.08 (Byrne, 2016). Finally, we estimated the reliability of the measurement model with Cronbach’s alpha (a), McDonald’s omega (ω) coefficient and the mean variance extracted (VME).

An exploratory factor analysis with the MV method and obliminal rotation showed a good fit of the data to the model, which aligns with the significance of the Barlette sphericity test (X2 = 8443.2, p < 0.000) and the Kaiser–Meyer-Olkin (KMO) value of 0.94. The indices confirmed the fit of the data to the six-dimensional model for measuring the users' level of enjoyment of online games (X2 = 678.2 gl = 411, p = 0.000; SRMR = 0.05; TLI = 0.95, CFI = 0.95 and RMSEA = 0.05, IC 90% [0.04, 0.05]).

The self-reporting format of the scale increases the social desirability of the responses, but the sample only collects information from a specific geographic location, so these findings cannot extrapolate to populations with very marked cultural differences. Finally, the study did not measure other validity evidence, such as predictive and concurrent validity, which should be considered in future studies.

From a practical perspective, the study offers a measurement scale with fewer items and robust psychometric evidence that ensures the fit of the data to the EGame-flow measurement scale. Further research must continue to learn about the behavior of the EGame-flow scale in different samples that new evidence of psychometric properties continues to appear and that other factors associated with the users' gaming enjoyment experience are analyzed.

The value and originality of the study lie in the type of evidence of psychometric properties that the instrument has and particularly in the style of sample in which the study is carried out, in this case, in the context of Mexico, where there are not enough instruments that measure the flow experience of users.

This study aims to apply the predictive processing theory to examine the influence of artificial intelligence (AI)-driven robotic performers on audience emotions and the audience’s resulting electronic word-of-mouth (eWOM) behaviors during tourism service encounters.

Using a quantitative research methodology, survey responses from 339 regular customers of performing arts in tourism destinations were analyzed. The respondents were recruited through Prolific, a professional data collection platform. SPSS 23.0 was used for the preliminary analysis, from which a research model to achieve the aim was proposed. SmartPLS 3 was used for partial least squares structural equation modeling to test the model.

Interactive and novel robotic performances significantly encouraged the consumers to share their experiences online, thereby enhancing eWOM. However, melodic resonance had no significant impact on eWOM intentions. The consumers’ emotional responses fully mediated the relationship of the novelty and interactivity of the performances to the consumers’ eWOM intentions but did not mediate the relationship of the musical elements to their eWOM intentions.

This study enriches the understanding of how AI-driven performances impact consumers’ emotional engagement and sharing behaviors. It extends the application of the predictive processing theory to the domain of consumer behavior, offering valuable insights for enhancing audience engagement in performances through technological innovation.

本研究旨在运用预测处理理论, 考察人工智能（AI）驱动的机器人表演对观众情感及其在旅游服务接触中的电子口碑（eWOM）行为的影响。。

采用定量研究方法, 分析了339名经常观看旅游景点表演艺术的常客的调查问卷。受访者通过专业数据收集平台Prolific招募。初步分析使用SPSS 23.0进行, 从中提出了实现研究目标的研究模型。使用SmartPLS 3进行偏最小二乘结构方程模型测试该模型。

互动性和新颖性的机器人表演显著鼓励消费者在线分享他们的体验, 从而增强电子口碑。然而, 旋律共鸣对电子口碑意图没有显著影响。消费者的情感反应完全中介了表演的新颖性和互动性与消费者电子口碑意图之间的关系, 但没有中介音乐元素与电子口碑意图之间的关系。

本研究丰富了对AI驱动表演如何影响消费者情感参与和分享行为的理解。将预测处理理论的应用扩展到消费者行为领域, 为通过技术创新增强观众参与度提供了宝贵的见解。

This paper aimed to explore the presence of altmetric data across the sub-categories of the medical science discipline and also explore whether the openness of articles results in (dis)advantage for altmetrics mentions.

The research implies data carpentry methods for gathering bibliographic data related to narrow fields of medical science discipline from the Scopus database with at least one Indian author affiliation during 2012–2021. The corresponding data were also collected from three different sources: Altmetric.com, Mendeley.com and Unpaywall.org, using OpenRefine and REST/API calls. Further, the authors observed open access altmetric advantages (OAAA) and categorical OAAA (COAAA) across seven altmetric platforms for all articles as well as discipline-wise.

The result shows that the overall coverage of altmetric events is still low, but it shows an increasing trend from the past. Mendeley has the largest coverage; almost 97.12% of publications are covered. The health policy discipline has extensive coverage across altmetric platforms (nearly 57.40% of publications in altmetrics and 99.23% in Mendeley), whereas the drug guides has the lowest (almost 0.92% in Altmetrics and 77.05% in Mendeley). Moreover, the OA articles have been highly covered in altmetrics than those of non-OA articles, and bronze OA articles covered mostly compared to others. News registered with the significant OA altmetric advantages across disciplines. Categorically, bronze and hybrid OA have the largest altmetric advantages.

This research is a unique attempt to apply OAAA and COAAA to explore OA altmetric advantages of narrow subject categories of medical science disciplines.

This study aims to explore factors that influence tourists’ visiting behaviors towards smart tourism destinations (STDs) by extending the theory of planned behavior.

Partial least squares structural equation modeling (PLS-SEM) technique is used to test the proposed hypotheses by analyzing 413 usable responses that are collected through personal interviews. Moreover, data are collected using structured interviews and analyzed by SmartPLS, 3.3.3.

This study results reveal that STD visit intentions significantly influence STD visiting behaviors among international and domestic tourists in Bangladesh. Moreover, the results show that e-attitude, resource efficiency norms and perceived environmental sustainability have significant impacts on STD visit intentions.

The study findings indicate that destinations’ electronic flowcharts of places, usage of low impact and biodegradable materials and history and culture presented in the forms of games and stories increase travelers’ motivation to visit STDs.

The study provides empirical evidence to support the importance of factors enhancing travelers’ STD visiting behaviors by integrating e-attitude, resource efficiency norms, perceived environmental sustainability and STD visit intentions.

研究人員藉著把計劃行為理論伸延開去,去探索是哪些因素影響著到訪智慧旅遊目的地的旅遊行為。

研究人員以偏最小平方法的結構方程模型 (PLS-SEM) 技術去測試其提出之假設,方法是透過分析取自個人訪談413個可用的回應。這些數據均以結構化訪談方式收集,繼而以 SmartPLS 3.3.3 來進行分析。

研究結果顯示,就於孟加拉的國際和國內旅客而言,到訪智慧旅遊目的地的目的,顯著地影響著智慧旅遊目的地的旅遊行為。研究結果亦顯示,到訪智慧旅遊目的地的目的和意願,會顯著地受電子態度、資源效率規範和感知環境可持續性所影響。

研究結果表明了目的地的處所電子流程圖、低影響和能進行生物降解材料的使用,以及以遊戲和故事形式展示的歷史和文化,均會提昇旅客到訪智慧旅遊目的地的動機。

研究人員透過結合電子態度、資源效率規範、感知環境可持續性和到訪智慧旅遊目的地的目的,給我們提供了經驗性證據,以確認增強及完善影響著旅客到訪智慧旅遊目的地的旅遊行為的因素至為重要。

The purpose of this study is to test the hypotheses proposed by Konadu et al. (2023) for the first time and provide empirical insight on the subject. Corruption concerns affect all economies, but those attempting to avoid foreign grants are especially vulnerable. Stakeholders in these economies have pushed for more honest public sector (PS) workers and better oversight of public funds in an effort to build a more trustworthy and efficient government to improve PS performance. Just as the mechanisms through which employee integrity (EI) influences work performance (WP) have not been proven empirically, neither has the effect of EI on WP in African economies. Also, how purposeful leadership (PL) interacts with EI to boost WP is yet to be empirically examined in the integrity literature.

This paper surveyed and analysed the responses of 875 workers across the three most corrupt large PS organisations in Ghana using Smart PLS 4. Perceived organisational support and contract fulfilment functioned as control factors influencing job satisfaction (JS, a mediator). Psychological need satisfaction and perceived procedural justice serve as control factors for organisational identification (OI, an additional mediator). Education, tenure, job position, sex and age were used as control variables in WP. Product indicator and variance accounted for (VAF) methods were used to estimate the impacts of moderation and mediation, respectively. A 5% level of significance was determined.

As hypothesised, this study found that EI and WP had a significantly positive connection (ß = 0.119, p = 0.026), and both JS (VAF = 25.16%) and OI (VAF = 39.59%) partially mediated this connection. Moreover, PL positively moderated the EI–JS (ß = 0.155, p = 0.000) and EI–OI (ß = 0.095, p = 0.000) connections.

This paper affords empirical insight on the EI–WP relationship, how this relationship is mediated and how the EI–JS and EI–OI relationships are amplified. In this context, it sheds light on new ways in which EI and WP in the PS are improved. In addition, this paper provides a roadmap for forthcoming academics to test the hypotheses in diverse PS contexts globally to triangulate the results.

Leadership in PS organisations must maintain a “values-grounded approach” to all parts of human resource (HR) practices, including hiring, performance reviews, leadership enhancement programmes, training and promotions, if they are to attract, develop and retain employees who stand for the sector’s ethics and beliefs.

This research gives African nations proof that enhancing EI in the PS is important, and it lays out the many ways in which EI transforms into WP. It also draws attention to the challenges that purposeful leaders may help alleviate and the opportunities that they may present.

To the best of the authors’ knowledge, the hypotheses put forward in the conceptual research by Konadu et al. (2023) are tested empirically for the first time in this study. It also adds to the empirical literature that already exists on EI, JS, OI, WP and PL in the PS. This contributes to the disciplines of integrity, performance and leadership by enhancing theoretical frameworks and expanding upon existing knowledge.

The importance of sustainable development has become increasingly significant in today’s fast-paced world. The 17 sustainable development goals (SDGs) aim to solve a range of environmental, economic and social challenges, which requires global collaboration among governments and private organisations. In light of this, social entrepreneurship has garnered significant attention as it combines the social purpose of non-profits with the market-driven approach of for-profits to address SDG goals. Yet the cognitive processes underpinning the career decisions of social entrepreneurs remain underexplored. This study aims to develop and validate a scale to measure social entrepreneurial career decisions based on the appraisal of perceived challenges.

The study followed the steps of tool development and was carried out in three phases: item analysis, exploratory factor analysis (EFA) and confirmatory factor analysis (CFA).

The final 20-item scale focuses on the appraisal components in pre-entry social entrepreneurial career decision-making and has four factors, which are relevance, coping potential, knowledge and resources and normative significance.

The study contributes to the literature on entrepreneurial cognition, specifically focusing on social entrepreneurship. The scale could guide model testing and quantitative research in social entrepreneurial cognition. The four-dimensional structure identified in the study may also have implications for researchers interested in the antecedents and effects of social entrepreneurial decision-making.

Accurate measurement of cognitive appraisal is necessary to understand the perceived challenges and thought processes of potential social entrepreneurs. The scale could be used to examine the cognitive appraisal patterns among students. Social entrepreneurship educators and policymakers can use the scale to design and assess educational programs.

Distinct from existing studies, this scale offers a multidimensional approach that captures the stages of career decision-making, providing a robust tool to enhance our understanding of the decision-making dynamics in social entrepreneurship.

We respond to the existing gaps regarding the drivers and outcomes of customer experience quality in the context of bank marketing by examining the interrelationships between distinct dimensions of VTM service quality, customer experience quality and customer loyalty.

This research follows the Stimulus-Organism-Response theory to examine the antecedents and behavioural outcomes of customer experience quality during their journeys with video teller machine (VTM) services in the banking industry (also known as LiveBank or SmartBank). First, we conducted in-depth interviews with 34 bank customers to develop distinct measurement scales for customer experience quality and VTM service quality. A structural equation model linking six dimensions of VTM service quality, including tangibles, interaction quality, empathy, reliability, user’s friendliness and efficiency with the affective-sensory and intellectual values of customer experience quality and customer loyalty to VTM service is tested using data obtained from 405 individual customers.

The findings reveal that tangibles, interaction quality, reliability, user-friendliness and efficiency contribute to customer experience quality, which, in turn, drives customers’ intention to use VTM again. This research provides crucial theoretical background and practical implications to accelerate the penetration of VTM among bank customers and hence, foster financial inclusion among societies.

This paper presents the first research that empirically employs the value-based approach to measure customer experience quality in the banking service industry and examine its linkages to service quality and customer loyalty. Moreover, given the emergence of VTM, this is also among the pioneering studies which validate measurement scales for VTM service quality. This could be either reused or revisited for further research about VTM. Overall, our study contributes to the literature about customer retention in the banking service industry from not only the customers’ backwards-looking evaluations of service performance (i.e. service quality) but also their forward-looking evaluations (i.e. their own experience).