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The use of augmented reality (AR) and experiential learning go hand in hand. Although AR learning opportunities have been well discussed, there is limited empirical research on the use of AR within higher education settings. Drawing from the uses and gratifications theory (U&GT), this study aims to explore the use of AR for learning satisfaction and student engagement, while also examining differences in learning styles.

This study used experiments with higher education students in the UK to explore the use of AR as part of the learning experience. Data from 173 students who experienced AR as part of their learning experience were analysed using partial least square analysis.

The authors found that hedonic, utilitarian, sensual and modality gratifications influence AR learning satisfaction and student engagement. Furthermore, the authors found differences between active and passive learners with regards to utilitarian (information seeking, personalisation) and sensual gratifications (immersion, presence) and effects on learning satisfaction.

This study developed and validated a U&GT framework incorporating different learning styles rooted in Kolb’s learning cycle. Findings provide important implications for the use of commercial AR applications as part of the learning experience within higher education settings.

The purpose of this study is to examine the impact of experience dimensions on the engagement in pro-environmental behaviour (PEB) within nature-based tourism in China. The focus was on sustainable/responsible consumer behaviour by the Chinese Gen Z (18–26 years).

Firstly, a conceptual model was suggested, drawn on experiential marketing approach. Secondly, an empirical study (online survey) with a sample of 580 young persons was conducted and data were analysed using structural equation modeling (SEM).

It was revealed that the act and feel dimensions significantly influence experiential value (EV), and EV positively affects satisfaction, significantly impacting arousal and memory. Positive outcomes of experience impact Gen Z members’ engagement in PEBs. Furthermore, arousal and memory play a similar and partial mediating role between satisfaction and engagement in PEB.

The insights gained give support and guidance to tourism destinations and suppliers to promote environmentally friendly behaviour among tourists. This understanding is valuable and useful to industry practitioners in elaborating and implementing the appropriate strategies to stimulate, motivate and promote tourists’ PEB.

This study elaborates an integrative framework, drawn on a marketing approach and establishing a relationship between experiential dimensions and engagement in PEB through the mediating factors of perceived EV, satisfaction, memory and arousal. It provides tourism researchers with new perspective and insights on tourism experience and consumption behaviour.

本研究证实了体验维度对于中国自然旅游地游客的亲环境旅游行为(PEB)的影响。研究对象聚焦于中国Z世代(18 至26 岁)游客的亲环境行为。

本研究基于体验营销, 提出了一个概念模型, 对580名Z世代游客进行了实证研究(在线调查), 并采用结构方程模型（SEM）对数据进行分析。

结果表明, 行动维度和情感维度显著影响体验价值, 体验价值正向影响满意度, 满意度显著影响唤醒度和记忆。体验后的积极结果会影响Z世代游客的亲环境行为的参与。此外, 唤醒度和记忆在满意度和亲环境行为参与之间起平行的部分中介作用。

研究结果可为旅游目的地的管理者和从业者提供借鉴和参考, 以促进游客的环保行为。这对于旅游业从业者制定和采取恰当的策略来促进和激励游客的亲环境行为也具有重要意义。

本研究基于营销方法, 构建了一个整合框架, 并通过体验价值、满意度, 记忆和唤醒度等中介, 建构了体验维度和参与亲环境行为之间的关系, 拓展了旅游体验及消费行为的研究视角。

El propósito de este estudio fue examinar el impacto de las dimensiones de la experiencia en el comportamiento turístico proambiental (CTP) en el turismo de naturaleza en China, centrándose en el comportamiento sostenible y responsable de la Generación Z china (entre 18 y 26 años).

Se propuso un modelo conceptual basado en el enfoque del marketing experiencial. Posteriormente, se llevó a cabo un estudio empírico mediante una encuesta en línea a 580 jóvenes, y los datos obtenidos se analizaron utilizando SEM (Modelado de Ecuaciones Estructurales).

Se encontró que las dimensiones “actuar” y “sentir” tienen una influencia significativa en el valor experiencial, y este último impacta positivamente en la satisfacción, lo cual a su vez influye en la excitación y la memoria. Los resultados positivos de la experiencia turística tienen un efecto en el compromiso de los miembros de la Generación Z con el comportamiento turístico proambiental. Además, tanto la excitación como la memoria desempeñan un papel parcialmente mediador entre la satisfacción y el compromiso en el CTP.

Los conocimientos obtenidos en este estudio brindan apoyo y orientación a los actores del sector turístico para fomentar un comportamiento respetuoso con el medio ambiente entre los turistas y visitantes. Esta comprensión es valiosa y útil para los profesionales del sector al diseñar e implementar estrategias adecuadas que estimulen, motiven y promuevan el comportamiento turístico proambiental.

Este estudio presenta un marco integrador basado en el enfoque del marketing experiencial, estableciendo una relación entre las dimensiones experienciales y el compromiso en el CTP a través de factores mediadores como el valor experiencial percibido, la satisfacción, la memoria y la excitación. Proporciona a los investigadores del turismo una nueva perspectiva y conocimientos sobre la experiencia turística y el comportamiento de consumo.

Healthcare workers’ (HCWs’) job-related high exposure to Covid-19 virus arouses fear of Covid-19 among them. Based on the Theory of Mind (ToM), the study predicts that fears will lead to negative psychological (psychological distress) and behavioral (withdrawal intentions) outcomes. ToM is also used to identify social intelligence as a means to counter fear of Covid-19 on heightened psychological distress and increased withdrawal intentions.

To investigate the study design, a sample of 262 HCWs, including doctors, nurses and technicians, were surveyed using standardized questionnaires.

As predicted, Covid-19 fear led to increased withdrawal intentions with heightened psychological distress partially mediating the relationship. The alleviating role of social intelligence on the effects of Covid-19 was supported as high social intelligence reduced HCWs’ turnover intentions, with decreased psychological distress partially mediating the relationship.

Given the universality of the Theory of Mind (ToM), the findings of this study are likely to be generalizable to all pandemics. The study results support the increased application of ToM in organizational settings and have both theoretical and practical implications for health administrators. Based on study results, health administrators are exhorted to develop ToM-based mental models to understand and deal with the fear of contagious diseases. Health administrators can also increase HCWs’ social intelligence to deal with the negative perceptual and behavioral outcomes arising from the emotions aroused by the nature of their work.

Road traffic emissions are generally believed to contribute immensely to air pollution, but the effect of road traffic data sets on air quality (AQ) predictions has not been fully investigated. This paper aims to investigate the effects traffic data set have on the performance of machine learning (ML) predictive models in AQ prediction.

To achieve this, the authors have set up an experiment with the control data set having only the AQ data set and meteorological (Met) data set, while the experimental data set is made up of the AQ data set, Met data set and traffic data set. Several ML models (such as extra trees regressor, eXtreme gradient boosting regressor, random forest regressor, K-neighbors regressor and two others) were trained, tested and compared on these individual combinations of data sets to predict the volume of PM_2.5, PM₁₀, NO₂ and O₃ in the atmosphere at various times of the day.

The result obtained showed that various ML algorithms react differently to the traffic data set despite generally contributing to the performance improvement of all the ML algorithms considered in this study by at least 20% and an error reduction of at least 18.97%.

This research is limited in terms of the study area, and the result cannot be generalized outside of the UK as some of the inherent conditions may not be similar elsewhere. Additionally, only the ML algorithms commonly used in literature are considered in this research, therefore, leaving out a few other ML algorithms.

This study reinforces the belief that the traffic data set has a significant effect on improving the performance of air pollution ML prediction models. Hence, there is an indication that ML algorithms behave differently when trained with a form of traffic data set in the development of an AQ prediction model. This implies that developers and researchers in AQ prediction need to identify the ML algorithms that behave in their best interest before implementation.

The result of this study will enable researchers to focus more on algorithms of benefit when using traffic data sets in AQ prediction.

The application of artificial intelligence chatbots is an emerging trend in educational technology studies for its multi-faceted advantages. However, the existing studies rarely take a perspective of educational technology application to evaluate the application of chatbots to educational contexts. This study aims to bridge the research gap by taking an educational perspective to review the existing literature on artificial intelligence chatbots.

This study combines bibliometric analysis and citation network analysis: a bibliometric analysis through visualization of keyword, authors, organizations and countries and a citation network analysis based on literature clustering.

Educational applications of chatbots are still rising in post-COVID-19 learning environments. Popular research issues on this topic include technological advancements, students’ perception of chatbots and effectiveness of chatbots in different educational contexts. Originating from similar technological and theoretical foundations, chatbots are primarily applied to language education, educational services (such as information counseling and automated grading), health-care education and medical training. Diversifying application contexts demonstrate specific purposes for using chatbots in education but are confronted with some common challenges. Multi-faceted factors can influence the effectiveness and acceptance of chatbots in education. This study provides an extended framework to facilitate extending artificial intelligence chatbot applications in education.

The authors have to acknowledge that this study is subjected to some limitations. First, the literature search was based on the core collection on Web of Science, which did not include some existing studies. Second, this bibliometric analysis only included studies published in English. Third, due to the limitation in technological expertise, the authors could not comprehensively interpret the implications of some studies reporting technological advancements. However, this study intended to establish its research significance by summarizing and evaluating the effectiveness of artificial intelligence chatbots from an educational perspective.

This study identifies the publication trends of artificial intelligence chatbots in educational contexts. It bridges the research gap caused by previous neglection of treating educational contexts as an interconnected whole which can demonstrate its characteristics. It identifies the major application contexts of artificial intelligence chatbots in education and encouraged further extending of applications. It also proposes an extended framework to consider that covers three critical components of technological integration in education when future researchers and instructors apply artificial intelligence chatbots to new educational contexts.

Demonstrate proof-of-concept for conducting NFL Draft trades on a blockchain network using smart contracts.

Using Ethereum smart contracts, the authors model several types of draft trades between teams. An example scenario is used to demonstrate contract interaction and draft results.

The authors show the feasibility of conducting draft-day trades using smart contracts. The entire negotiation process, including side deals, can be conducted digitally.

Further work is required to incorporate the full-scale depth required to integrate the draft trading process into a decentralized user platform and experience.

Cutting time for the trade negotiation process buys decision time for team decision-makers. Gains are also made with accuracy and cost.

Full-scale adoption may find resistance due to the level of fan involvement; the draft has evolved into an interactive experience for both fans and teams.

This research demonstrates the new application of smart contracts in the inter-section of sports management and blockchain technology.

This study aims to examine the effect of social reputation on the relationship between boards and foreign ownership on the quality of sustainability disclosure.

The sample of this study consists of publicly-traded primary and secondary sector companies in Indonesia for 12 years, from 2009 to 2020. This study uses panel model regression to generate its results. The disclosure data are hand-collected data sourced from annual financial and company sustainability reports.

Higher foreign board component companies report lower quality of sustainability disclosure, whereas companies that possess foreign ownership components report a higher quality of sustainability disclosure. This result is strengthened by obtaining consistent results tested with economic, social and environmental disclosure components. In addition, if the company has a good social reputation, it will strengthen the relationship of foreign ownership to the quality of sustainability disclosure.

These findings are relevant for policymakers, professional organizations and practitioners in Indonesia and other developing countries.

The moderating effect of social reputation on the relation of the foreign board and foreign ownership-quality of sustainability disclosure as this study does remain rare in developing countries. This study complements various research conducted in developing countries, such as Indonesia, by offering a new dimension. The results indicate that social reputation has a moderating role in determining the impact of foreign ownership on the quality of sustainability disclosure.

The purpose of this study is to investigate the key predictors and outcomes of task–technology fit (TTF) of facial recognition payment systems with the moderating role of cultural differences in the restaurant industry.

The survey responses were collected from 336 South Korean and 336 US restaurant customers.

The results revealed that function significantly affected TTF in both groups. Unique to the Korean sample, emotion was found to be a significant determinant of TTF, whereas convenience and social influence were key predictors of TTF only for the US sample. TTF had significant and positive effects on the three dimensions of behavioral intentions in both groups. The result of multi-group analysis showed that cultural differences moderated the effect of convenience on TTF and the effect of emotion on TTF.

The authors provided recommendations for restaurant operators and technology companies seeking to improve customer TTF and acceptance of facial recognition payment systems for the first time.

本研究旨在调查面部识别支付系统任务技术匹配（TTF）的关键前置因素和影响, 以文化差异为调节变量, 研究其在餐饮行业的应用。

我们收集了来自336名韩国和336名美国餐厅顾客的调查回答。

结果显示, 在两组中, 功能显著影响TTF。对于韩国样本来说, 情感被发现是TTF的重要决定因素, 而对于美国样本来说, 方便性和社会影响是TTF的关键预测因素。在两组中, TTF对行为意向的三个维度均产生了显著且积极的影响。多组分析结果显示, 文化差异在方便性对TTF的影响以及情感对TTF的影响中起到了调节作用。

我们首次为寻求改善顾客TTF和接受面部识别支付系统的餐厅经营者和技术公司提供了建议。

Exploratory search activities are ubiquitous in various information systems. Much potentially useful or even serendipitous information is discovered during the exploratory search process. Given its irreplaceable role in information systems, exploratory search has attracted growing attention from the information system community. Since few studies have methodically reviewed current publications, researchers and practitioners are unable to take full advantage of existing achievements, which, in turn, limits their progress in this field. Through a literature review, this study aims to recapitulate important research topics of exploratory search in information systems, providing a research landscape of exploratory search.

Automatic and manual searches were performed on seven reputable databases to collect relevant literature published between January 2005 and July 2023. The literature pool contains 146 primary studies on exploratory search in information system research.

This study recapitulated five important topics of exploratory search, namely, conceptual frameworks, theoretical frameworks, influencing factors, design features and evaluation metrics. Moreover, this review revealed research gaps in current studies and proposed a knowledge framework and a research agenda for future studies.

This study has important implications for beginners to quickly get a snapshot of exploratory search studies, for researchers to re-align current research or discover new interesting issues, and for practitioners to design information systems that support exploratory search.

The purpose of this study is to conduct a systematic literature review of the adoption of immersive marketing technology (IMT) in terms of strategic planning of its adoption, resource requirements and its implications and challenges.

This study categorizes and contextualizes qualitative approaches to evaluate the literature, with Scopus databases serving as the primary source of 90 selected articles in the areas of information technology, business and marketing strands. Theme analysis was carried out using thematic techniques and grounded approach principles to facilitate thematic coding and generate theme analysis.

The analysis was supported by the three concepts of business flexibility, agility and adaptability, which were drawn as a strategy for IMT adoption. The findings presented three main themes: proactive flexibility, responsive agility and reactive adaptability that enable business owner–managers to craft a strategy for IMT adoption.

The novel contribution of this study is the inclusion of key implications related to IMT as a starting point of the next level of innovative marketing for all academics, practitioners and business owner–managers.