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Behavioral Sciences
Special Issues
The Impact of Technology on Human Behavior
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The Impact of Technology on Human Behavior

A special issue of Behavioral Sciences (ISSN 2076-328X). This special issue belongs to the section "Cognition".

Deadline for manuscript submissions: 28 February 2026 | Viewed by 24902

Special Issue Editors

Dr. Ekta Sinha

E-Mail Website
Guest Editor
Business School for the Creative Industries, University for the Creative Arts, Epsom KT18 5BE, UK
Interests: human-centered technology; sustainability and technology; human-centered Innovation
Dr. Jalal Sarabadani

E-Mail Website
Guest Editor
School of Information Systems and Technology, Lucas College and Graduate School of Business, San Jose State University, San Jose, CA 95192, USA
Interests: dark side of IT; technostress; generative AI; AI in education

Special Issue Information

Dear Colleagues,

Technological advancements have profoundly shaped human behavior and influenced the way individuals think, feel, and act across diverse contexts. From the proliferation of artificial intelligence (AI) and wearable devices to the widespread adoption of virtual reality and social media, technology has found its way into our personal, professional, and social lives. Such advancements have introduced significant opportunities and challenges related to their adoption, use, reactions, and effectiveness.

This Special Issue aims to explore the multifaceted impact of technology on human behavior, bridging theoretical frameworks with empirical studies. Contributions are encouraged from interdisciplinary perspectives, including, but not limited to, psychology, sociology, organizational behavior, information systems, human–computer interaction, and behavioral economics. This Special Issue sets out to provide a platform for cutting-edge research that examines the complex relationship between technology and behavior, offering insights for academics, practitioners, and policymakers.

Dr. Ekta Sinha
Dr. Jalal Sarabadani
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Behavioral Sciences is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2200 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • technology and behavior
  • digital dependency
  • human-computer interaction
  • artificial intelligence
  • social and emotional impacts
  • workplace behavior
  • virtual reality
  • ethics in technology

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (6 papers)

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Research

20 pages, 392 KB  
Article
Impact of Artificial Intelligence on Spectator Viewing Behavior in Sports Events: Mediating Role of Viewing Motivation and Moderating Role of Player Identification
by Jie Min, Qing Xie and Yongjian Liu
Behav. Sci. 2025, 15(12), 1702; https://doi.org/10.3390/bs15121702 - 8 Dec 2025
Viewed by 131
Abstract
With the widespread application of artificial intelligence (AI) technology in the sports industry, the spectator’s experience is increasingly shaped by AI-driven features. To explore the mechanism through which the perceived AI-enabled spectating experience affects viewing behavior, and to validate the mediating role of [...] Read more.
With the widespread application of artificial intelligence (AI) technology in the sports industry, the spectator’s experience is increasingly shaped by AI-driven features. To explore the mechanism through which the perceived AI-enabled spectating experience affects viewing behavior, and to validate the mediating role of viewing motivation (SDT Needs Satisfaction) in the relationship between AI and viewing behavior as well as the moderating role of player identification in this mediating pathway, we adopted literature review, survey, and empirical analysis methods. A sample of 272 Chinese tennis enthusiasts was surveyed, and both the measurement model and the structural model were evaluated. The results indicate that the measurement model has good internal consistency, reliability, convergent validity, and discriminant validity. The perceived AI-enabled spectating experience has a significant positive effect on viewing motivation, viewing intention, and recommendation intention. The data show that the indirect effect of the perceived AI-enabled spectating experience on the viewing intention through the viewing motivation is 0.0479, and the indirect effect of the perceived AI-enabled spectating experience on the recommendation intention through the viewing motivation is 0.0548. Both reached a significant level, and the direct effect of the perceived AI-enabled spectating experience has also reached statistical significance. Therefore, viewing motivation plays a partial mediating role between AI and viewing intention and between AI and recommendation intention. Player identification plays a significant positive moderating role (β = 0.2809 on viewing intention, β = 0.1621 on recommendation intention) in the relationship between viewing motivation and viewing behavior; however, it does not moderate the relationship between AI and viewing motivation. In other words, for spectators with higher player identification, viewing motivation drives more strongly both their viewing intention and recommendation intention. We suggest that sports event organizers and media use AI technologies to design differentiated marketing to enhance user engagement and optimize spectators’ experience. For spectators with lower player identification, improving service quality can enhance their satisfaction; for those with higher player identification, efforts should focus on strengthening their connection with the players. Full article
(This article belongs to the Special Issue The Impact of Technology on Human Behavior)
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24 pages, 662 KB  
Article
Research on the Impact of AI Introduction on Employee Creativity: The Moderating Role of Technology Overload
by Dexia Zang and Manyu Li
Behav. Sci. 2025, 15(10), 1389; https://doi.org/10.3390/bs15101389 - 14 Oct 2025
Viewed by 1898
Abstract
The introduction and application of AI are profoundly affecting the working modes and psychological states of employees. For many organisations, AI is not only a tool to improve productivity, but also an important driving force for organisational change. In the context of the [...] Read more.
The introduction and application of AI are profoundly affecting the working modes and psychological states of employees. For many organisations, AI is not only a tool to improve productivity, but also an important driving force for organisational change. In the context of the rapid development of AI, it is particularly important to explore the impact mechanism of its introduction on employee creativity. This study uses the theory of technological affordances and job characteristics theory to explore the impact of AI introduction on employee creativity. Through an analysis of the questionnaire data of 309 employees, it is found that the introduction of AI has a significant positive impact on employee creativity, and perceived job autonomy and perceived job feedback play a mediating role between the introduction of AI and employee creativity. Technology overload not only negatively moderates the relationship between AI introduction and perceived job autonomy, but also negatively moderates the relationship between AI introduction and perceived job feedback; that is, the higher the technology overload is, the weaker the positive relationship between AI introduction and perceived job autonomy and perceived job feedback is. This study not only provides a new perspective for understanding the opportunities and challenges brought by the application of AI in the workplace, but also provides an empirical basis for enterprises to formulate effective human resource management strategies in the process of digital transformation. Full article
(This article belongs to the Special Issue The Impact of Technology on Human Behavior)
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25 pages, 325 KB  
Article
AI Personalization and Its Influence on Online Gamblers’ Behavior
by Florin Mihai, Ofelia Ema Aleca and Daniel-Marius Iordache
Behav. Sci. 2025, 15(6), 779; https://doi.org/10.3390/bs15060779 - 4 Jun 2025
Viewed by 3172
Abstract
Technological advancements in algorithmic personalization are widely believed to influence user behavior on online gambling platforms. This study explores how such developments, potentially including AI-driven mechanisms, may affect cognitive and motivational processes, especially in relation to risk perception, decision-making, and betting persistence. Using [...] Read more.
Technological advancements in algorithmic personalization are widely believed to influence user behavior on online gambling platforms. This study explores how such developments, potentially including AI-driven mechanisms, may affect cognitive and motivational processes, especially in relation to risk perception, decision-making, and betting persistence. Using ordinary least squares (OLS) and panel regression models applied to behavioral data from a gambling platform, we examine patterns that are consistent with increased personalization between two distinct time periods, 2016 and 2021. The datasets do not contain any direct metadata regarding AI interventions. However, we interpret changes in user behavior over time as indicative of evolving personalization dynamics within a broader technological and contextual landscape. Accordingly, our conclusions about algorithmic personalization are inferential and exploratory, drawn from temporal comparisons between 2016 and 2021. Our findings show that users receiving personalized bonuses or making early cash-out decisions tend to adjust their stake sizes and betting frequency in systematic ways, which may reflect indirect effects of technological reinforcement strategies. These behavioral patterns raise important ethical and regulatory questions, particularly regarding user autonomy, algorithmic transparency, and the protection of at-risk users. This research contributes to the literature on digital behavior influencing gambling by framing the analysis as observational and quasi-experimental and suggests that further studies use experimental and log-level data to more specifically analyze the algorithmic effects. However, no causal claims can be made about AI influence as the temporal contradictions are interpreted as broad phenomena of technological developments, since they are not measured as algorithmic interventions. Further studies should also investigate the development of predictive models aimed at countering gambling addiction; evaluate the long-term ethical implications of algorithmic personalization; and discuss potential solutions codeveloped to foster a responsible gambling climate. Full article
(This article belongs to the Special Issue The Impact of Technology on Human Behavior)
23 pages, 3824 KB  
Article
Phubbing Behaviour: A Bibliometric Analysis of Scientific Production
by Ana Cebollero-Salinas, Begoña Gutiérrez-Nieto and Jacobo Cano-Escoriaza
Behav. Sci. 2025, 15(6), 745; https://doi.org/10.3390/bs15060745 - 28 May 2025
Viewed by 1398
Abstract
Phubbing refers to the act of ignoring someone in a face-to-face conversation by paying more attention to a mobile phone. This practice, although common, has been identified as harmful and deserves to be considered a problem. As a result, it has captured the [...] Read more.
Phubbing refers to the act of ignoring someone in a face-to-face conversation by paying more attention to a mobile phone. This practice, although common, has been identified as harmful and deserves to be considered a problem. As a result, it has captured the attention of the scientific community, with a significant increase in studies in recent years. However, there is a lack of bibliometric analyses examining existing research on this topic, which would be useful in guiding future studies. This article seeks to fill that gap by providing a detailed bibliometric analysis of phubbing. It analyses the entire production in the Web of Science database between 1985 and 2022 (199 articles and 82 keywords). The study employs citation, co-occurrence, and co-citation analysis techniques using scientific maps created with VOSviewer software. The results indicate that most research has focused on how phubbing affects romantic relationships, with less emphasis on other types of relationships such as family, work, or friends. Areas that require further research are identified, such as motivations for internet use, the tendency to compare oneself on social networks, impulsivity, and the influence of executive functions on phubbing. Further exploration of the relationship between phubbing and other disorders is also suggested. This analysis will serve as a guide and stimulus for future research, offering valuable resources for professionals in psychology, health, and education. Full article
(This article belongs to the Special Issue The Impact of Technology on Human Behavior)
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21 pages, 554 KB  
Article
The Role of Artificial Intelligence in Personalizing Social Media Marketing Strategies for Enhanced Customer Experience
by Hasan Beyari and Tareq Hashem
Behav. Sci. 2025, 15(5), 700; https://doi.org/10.3390/bs15050700 - 19 May 2025
Cited by 6 | Viewed by 13186
Abstract
This paper explores the role of artificial intelligence (AI) in personalizing social media marketing strategies and its impact on customer experience, with a focus on consumers within the MENA region. Using data collected from an online questionnaire completed by 893 individuals, the study [...] Read more.
This paper explores the role of artificial intelligence (AI) in personalizing social media marketing strategies and its impact on customer experience, with a focus on consumers within the MENA region. Using data collected from an online questionnaire completed by 893 individuals, the study confirms that AI significantly enhances social media marketing by offering personalized content, optimizing influencer selection, and enabling real-time consumer interaction. These capabilities not only increase customer awareness but also improve user experience and purchase intentions. Key AI tools such as influencer marketing, content optimization, and customization are effective in capturing consumer attention, although further research is necessary to deepen understanding. By examining AI’s ability to analyze vast datasets and support targeted marketing efforts, the study contributes to both academic and practical discourse, offering insights that businesses can use to refine their AI-driven social media strategies. Ultimately, the research aims to guide marketers through the complexities of AI deployment, ensuring its benefits are fully realized for consumers. Full article
(This article belongs to the Special Issue The Impact of Technology on Human Behavior)
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28 pages, 1263 KB  
Article
The Influence of UI Design Attributes and Users’ Uncertainty Avoidance on Stickiness of the Young Elderly Toward mHealth Applications
by Zibin Chen and Jaehwan Lee
Behav. Sci. 2025, 15(5), 581; https://doi.org/10.3390/bs15050581 - 25 Apr 2025
Viewed by 2700
Abstract
The advantages of mHealth applications have been widely recognized. However, the existing literature rarely explores how user interface (UI) design and individual cultural values influence elderly users’ mHealth application stickiness, particularly among the young elderly. This study examines how two UI design attributes [...] Read more.
The advantages of mHealth applications have been widely recognized. However, the existing literature rarely explores how user interface (UI) design and individual cultural values influence elderly users’ mHealth application stickiness, particularly among the young elderly. This study examines how two UI design attributes (usability and aesthetics) and individual uncertainty avoidance (from Hofstede’s cultural dimensions) influence elderly users’ stickiness to mHealth applications. The study used PLS-SEM to analyze survey data from 492 elderly people in China. The research results indicate that uncertainty avoidance cultural values are negatively correlated with psychological engagement. The UI design attributes (aesthetic and usability) are positively correlated with psychological engagement, with learnability (usability sub-attributes) having the most significant impact. Furthermore, the study also reveals the serial mediation role of psychological engagement and user internal experiences (satisfaction and attachment). Notably, this study enriches the current literature on user behavior regarding mHealth applications by elucidating the process of user stickiness, incorporating UI design attributes and individual uncertainty avoidance cultural values. These findings offer valuable theoretical and practical insights. Full article
(This article belongs to the Special Issue The Impact of Technology on Human Behavior)
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