Behaviour and Information Technology

In the burgeoning landscape of metaverse gaming, understanding player behaviour and preferences is crucial for both academic and practical applications. This study delves into the dynamic realm of metaverse gaming, exploring the influence of various factors on user satisfaction and continuance intention. The primary purpose was to examine the roles of self-expression, challenge and achievement, social interaction, violence catharsis, and game difficulty in shaping player experiences in the metaverse. Employing Partial Least Squares Structural Equation Modeling (PLS-SEM) as the analytical method, the study analysed responses from 171 metaverse game users. The findings revealed intriguing patterns: while self-expression significantly impacts continuance intention, it does not affect immediate satisfaction. Challenge and achievement enhance satisfaction but not continuance intention, emphasizing the complex relationship between these constructs. Social interaction emerged as a critical factor positively influencing both satisfaction and continuance intention. Contrary to popular belief, violence catharsis did not significantly affect either satisfaction or continuance intention. Additionally, increased game difficulty was found to negatively impact both satisfaction and continuance intention. Satisfaction was shown to drive continuance intention. These insights bear significant implications for game developers and marketers, highlighting the need for nuanced game design strategies that emphasize social interaction and balanced challenges.

Hyeon Jo

Sun Park

Jiwoo Jeong

Juwon Yeon

Jae Kwang Lee

Metaverse gaming: analyzing the impact of self-expression, achievement, social interaction, violence, and difficulty

元宇宙游戏：分析自我表达、成就、社交互动、暴力和难度带来的影响

Gabbiadini Alessandro

Ognibene Dimitri

Baldissarri Cristina

Manfredi Anna

Behaviour &amp; Information Technology

The emotional impact of generative AI: negative emotions and perception of threat

生成式人工智能的情感影响：负面情绪与威胁感知

The demographic shift marks the beginning of a social transformation with far reaching implications, and differences in aging processes across individuals render one-size fits-all policies ineffective. An area of increasing importance is assistive technology, including physical and Social Assistance Robots (SARs) for elderly support. In order to increase the effectiveness of such technologies, their design, functionality, and acceptance by target users must be evaluated. This paper presents a study that examines SAR technology acceptance among the future elderly (aged 20–60) in a German-speaking population (N=188). In doing this, we investigated the relationships between personality, resilience, technology experience, expectations for technology, fulfilment of expectations for technology, and technology acceptance. The study found significant correlations between age, gender, education, personality, resilience, experience, expectations, and technology acceptance and its subdimensions. Of the personality dimensions, agreeableness and neuroticism were found most relevant. Small effects were found between resilience and acceptance, and highly significant ones between technology acceptance, technology experience, expectations for SARs, and fulfilment of expectations for SARs. In keeping with previous research, the findings suggest that personality plays a significant role in the acceptance of SAR technologies. This study may be one of the first that considers and evaluates resilience as a factor in technology acceptance.

A. S. Gessl

S. Schlögl

N. Mevenkamp

On the perceptions and acceptance of artificially intelligent robotics and the psychology of the future elderly

关于人工智能机器人感知与接受度及未来老年人心理

Recommender systems use machine-learning techniques to make predictions about resources. The medical field is one where much research is currently being conducted on recommender system utility. In the last few years, the amount of information available online that relates to healthcare has increased tremendously. Patients nowadays are more aware and look for answers to healthcare problems online. This has resulted in a dire need of an effective reliable online system to recommend the physician that is best suited to a particular patient in a limited time. In this article, a hybrid doctor-recommender system is proposed, by combining different recommendation approaches: content base, collaborative and demographic filtering to effectively tackle the issue of doctor recommendation. The proposed system addresses the issue of personalization through analysing patient's interest towards selecting a doctor. It uses a novel adoptive algorithm to construct a doctor's ranking function. Moreover, this ranking function is used to translate patients’ criteria for selecting a doctor into a numerical base rating, which will eventually be used in the recommendation of doctors. The system has been evaluated thoroughly, and result show that recommendations are reasonable and can fulfil patient's demand for reliable doctor's selection effectively.

Muhammad Waqar

Nadeem Majeed

Hassan Dawood

Ali Daud

Naif Radi Aljohani

An adaptive doctor-recommender system

一个自适应的医生推荐系统

Augmented Reality (AR) technology has been increasingly utilised in mobile shopping apps to enhance consumers' mobile shopping experiences, thereby affecting consumers' impulse buying behaviour. Drawing upon the Spatial Presence Theory and the Elaboration Likelihood Model, the current study aims to empirically investigate AR-related factors (vividness, spatial accuracy, local presence) and their impacts on impulse buying behaviour related factors (arousal, perceived diagnosticity, and urge to buy impulsively) in the context of AR mobile shopping apps. In this study, an experiment employing a full 2X2 factorial between-subject experimental design was carried out. There were a total of 137 participants actively involved in this experiment. The data analysis results and findings, along with the implications of this study, are provided in the paper.

Jengchung Victor Chen

Sirapattra Ruangsri

Quang-An Ha

Andree E. Widjaja

An experimental study of consumers’ impulse buying behaviour in augmented reality mobile shopping apps

增强现实移动购物应用中消费者冲动购买行为的实验研究

Shirley S. Ho

Sherry R. Xiong

Benjamin J. Li

Wenqi Tan

Mengxue Ou

Grzegorz Lisak

Encouraging pro-environmental behaviour in a virtual reality serious game: the interplay between competition and prior knowledge

鼓励虚拟现实严肃游戏中的亲环境行为：竞争与先验知识的相互作用

Educational and instructional research has provided contrasting results regarding the best representation of numerical information, with the two most common being tabular and graphical representations. This motivated us to examine the issue using a novel approach. We employed electroencephalography (EEG) with event-related synchronisation and desynchronisation (ERS/ERD) to model cognitive load, and alpha and beta band powers to model engagement. We conducted an experiment to measure the cognitive load and engagement of 48 Oregon State University students and compared their performances with respect to these two representations. Structural equation models (SEMs) were constructed to investigate the potential mediation of learning performance by engagement and cognitive load. The results indicate that learning performance was fully mediated by cognitive load and engagement. Relative to graphs, tables produced a higher cognitive load and engagement, and subsequently, greater overall learning performance. Current results showed that different representations could yield significant differences in learning performance, and that an understanding of representation-elicited affective behaviours has considerable potential for future online learning instructional design.

Yuzhi Sun

David A. Nembhard

Knowledge representation learning with EEG-based engagement and cognitive load as mediators of performance

基于脑电图的参与度和认知负荷作为绩效中介的知识表示学习

Problematic gaming (PG) refers to a dysfunctional pattern of online gaming behaviour that negatively affects individual functioning. The present study adopted a network analysis approach to investigate the patterns of reciprocal associations between PG, defense mechanisms, and psychopathological symptoms. Participants were 1,036 adult Italian online video game players (Mage = 29.94, SD = 8.85; females = 388) who completed self-report questionnaires. We used a regularised partial correlation network analysis (EBICglasso) to investigate the network structure of the relationships among PG, defense mechanisms, and psychopathological symptoms. Centrality measures were computed. The highly influential nodes in the network concerned both psychological symptoms (anxiety and obsessive-compulsive symptoms) and defense mechanisms (projection and autistic fantasy). Furthermore, the escapism feature of PG was detected as a prominent bridge symptom in the network. Our findings suggest that negative affect and immature defense mechanisms might play a pivotal role in PG, and that withdrawal in the virtual world may also exacerbate psychological symptoms. Therefore, better understanding the role of escapism and related immature defenses in PG might have important implications for theory and clinical practice.

Annarosa Cipriano

Stefania Cella

Adriano Schimmenti

Alessandro Musetti

A network analysis approach to understand the relationship between online problematic gaming, defense mechanisms, and psychopathological symptoms

网络分析方法在理解在线问题性游戏、防御机制与精神病理症状间关系中的应用

Helma Torkamaan

Steffen Steinert

Maria Soledad Pera

Olya Kudina

Samuel Kernan Freire

Himanshu Verma

Sage Kelly

Marie-Therese Sekwenz

Jie Yang

Karolien van Nunen

Martijn Warnier

Frances Brazier

Oscar Oviedo-Trespalacios

Challenges and future directions for integration of large language models into socio-technical systems

大型语言模型融入社会技术系统的挑战与未来方向

Beatriz Severes

Mary Barreto

Augusto Esteves

Designing for mental health in higher education: a collaborative approach to digital interventions

高等教育中的心理健康设计：数字干预的协作方法

Abbreviation	Behav. Inf. Technol.
Journal Impact	3.04
Quartiles(Global)	ERGONOMICS(Q2)

ISSN	0144-929X, 1362-3001
h-index	95

Publication Information	Publisher: Taylor and Francis Ltd.，Publishing cycle: Bimonthly，Journal Type: journal，Open Access Journals: No
Basic data	Year of publication: 1982，Proportion of original research papers: 95.63%，Self Citation Rate:10.30%， Gold OA Rate: 17.12%
Average review cycle	网友分享经验：平均6.0个月
Average recruitment ratio	网友分享经验：容易

Behaviour and Information Technology

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