Technology in Society最新文献

{"title":"The more human-like the better? Effect of anthropomorphic level on customer intention to participate in AI service recovery","authors":"Mengmeng Song ,&nbsp;Wenjing Jiang ,&nbsp;Xinyu Xing ,&nbsp;Jian Mou ,&nbsp;Yucong Duan","doi":"10.1016/j.techsoc.2025.103065","DOIUrl":"10.1016/j.techsoc.2025.103065","url":null,"abstract":"<div><div>The increasing application of artificial intelligence (AI) technology in the service industry has required more studies on service failures caused by intelligent customer service and its repair. In this study, the influence of anthropomorphism on customers’ intention to participate in service recovery cooperation is examined by effectively controlling the appearance, expression, and language style of intelligent customer service anthropomorphism. Through three experiments, the role of the intelligent customer service anthropomorphic level on customers intention to participate in service recovery cooperation is revealed, as well as two mediating pathways (shifting emotion and aversion) and the boundary (time pressure) of the anthropomorphic level. These findings contribute toward the understanding of AI-assisted services, and they provide insights into the application of anthropomorphic design in the service industry.</div></div>","PeriodicalId":47979,"journal":{"name":"Technology in Society","volume":"84 ","pages":"Article 103065"},"PeriodicalIF":12.5,"publicationDate":"2025-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145160197","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The use of ChatGPT in service recovery: Compensating customers","authors":"Ahu Yazici Ayyildiz (Associate Professor of Marketing) ,&nbsp;Tugrul Ayyildiz (Associate Professor of Marketing) ,&nbsp;Erdogan Koc (Professor of Services Marketing and Management)","doi":"10.1016/j.techsoc.2025.103058","DOIUrl":"10.1016/j.techsoc.2025.103058","url":null,"abstract":"<div><div>Determining the appropriate compensation for customers is a crucial decision, as it may result in the wasting of resources and further exacerbating customer frustration. Making the right compensation decision requires a great deal of knowledge and expertise about the customers and their service encounters, as well as taking both the customers' and the service business's interests into account. This study investigates the usability of ChatGPT, as a generative AI tool, in identifying the severity of service failures for customers and producing an effective and efficient compensation suggestion accordingly. The two surveys in the study, carried out in two stages with 298 hotel customers and 54 managers from 5-star hotels, established that no single compensation strategy developed by ChatGPT can satisfy most of the customers, and a combination of compensation strategies needs to be used. The study has important theoretical and practical implications both regarding the field of generative AI, in terms of developing business solutions, and for the service recovery and compensation literature.</div></div>","PeriodicalId":47979,"journal":{"name":"Technology in Society","volume":"84 ","pages":"Article 103058"},"PeriodicalIF":12.5,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145107926","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development and validation of Generative AI Competence Scale (GenAIComp) among university students","authors":"Seul Chan Lee ,&nbsp;Tiju Baby ,&nbsp;Rattawut Vongvit ,&nbsp;Jieun Lee ,&nbsp;Young Woo Kim ,&nbsp;Min Chul Cha ,&nbsp;Sol Hee Yoon","doi":"10.1016/j.techsoc.2025.103059","DOIUrl":"10.1016/j.techsoc.2025.103059","url":null,"abstract":"<div><div>The rapid development of Generative Artificial Intelligence (Generative AI) across several sectors underscores the need for a systematic tool to evaluate AI competence. Current digital literacy frameworks lack AI-specific competencies, resulting in inconsistencies in the assessment of AI competence. This study aims to establish a standardized assessment framework for Generative AI competence by identifying key skill factors and empirically validating a structured evaluation tool called the Generative AI Competence Scale (GenAIComp). The proposed GenAIComp has five essential factors: Information and Data Literacy, Communication and Collaboration, Digital Content Creation, Safety and Ethics, and Problem-Solving. A quantitative approach was employed, incorporating expert validation, pilot testing, and extensive empirical evaluation involving 1000 participants, principally university students. The factor analysis confirmed a robust 5-factor structure with strong psychometric properties. The final model demonstrated excellent fit indices, confirming its reliability and validity in assessing Generative AI competence across the five key factors. Research demonstrates that educational background considerably impacts AI competence, with individuals from technical disciplines showing a greater aptitude for problem-solving and content generation. Gender-based disparities were noted, with males achieving marginally higher scores in several factors, but with minimal effect sizes. Correlation analysis indicated that perceived AI expertise and frequency of AI utilization significantly influenced competence, especially in data literacy and problem-solving, and exhibited less correlation with ethical awareness. GenAIComp provides a reliable tool for assessing AI competence, helping educators, industry experts, and policymakers to design AI training programs and integrate AI literacy into curricula and thereby AI technology advancement in society. Future research should explore its applicability across cultures and include performance-based assessments to enhance AI competence.</div></div>","PeriodicalId":47979,"journal":{"name":"Technology in Society","volume":"84 ","pages":"Article 103059"},"PeriodicalIF":12.5,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145119951","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Personalizing AI art boosts credit, not beauty","authors":"Maryam Ali Khan ,&nbsp;Elzė Sigutė Mikalonytė ,&nbsp;Sebastian Porsdam Mann ,&nbsp;Peng Liu ,&nbsp;Yueying Chu ,&nbsp;Mario Attie-Picker ,&nbsp;Mey Bahar Buyukbabani ,&nbsp;Julian Savulescu ,&nbsp;Ivar R. Hannikainen ,&nbsp;Brian D. Earp","doi":"10.1016/j.techsoc.2025.103055","DOIUrl":"10.1016/j.techsoc.2025.103055","url":null,"abstract":"<div><div>While image-generating artificial intelligence (AI) increasingly democratises art creation, people tend to devalue AI-generated content. Recent work suggests that human use of personalized AI models, trained on a user's past work, can increase credit attributions to the human user for achieving beneficial text-based outputs. We investigated whether this effect extends to visual artistic outputs and further examined the relationship between credit attribution and aesthetic appreciation. Across two studies (N = 774), UK participants evaluated identical paintings that were described as being created either by hand, with a standard text-to-image generative AI system, or with an AI system personalized to the artist. Personalization significantly improved both achievement credit and authorship attribution towards the human user compared to standard AI use. However, it failed to enhance either aesthetic appreciation of the image itself or willingness to categorize the output as \"true art\"—revealing a striking disconnect between judgments of artistic contribution and artistic value. Our findings suggest that although personalized AI may help bridge the \"achievement gap\" in credit attribution not only for written works, as demonstrated previously, but also for artistic visual images, it cannot overcome fundamental barriers to aesthetic appreciation of AI art. This challenges assumptions about the relationship between artistic input and aesthetic value, with implications for understanding art categorization and human-AI cooperation in creative pursuits.</div></div>","PeriodicalId":47979,"journal":{"name":"Technology in Society","volume":"84 ","pages":"Article 103055"},"PeriodicalIF":12.5,"publicationDate":"2025-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145325442","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Motivation or resistance: A multidimensional analysis of quantile network spillovers between smart grids and carbon markets from a digital technology perspective","authors":"Sen Qiao ,&nbsp;Yuan Chang ,&nbsp;Meng Yang ,&nbsp;Yi Jing Dang","doi":"10.1016/j.techsoc.2025.103053","DOIUrl":"10.1016/j.techsoc.2025.103053","url":null,"abstract":"<div><div>The impact of digital technologies on risk contagion mechanisms in energy systems has emerged as a critical area of research. This study explores how digital technologies reshape risk contagion pathways between smart grids and carbon markets by integrating the time-varying parameter quantile vector autoregression model and network topology analysis. The findings indicate that: (1) Digital technologies amplify the short-term extreme risk linkages between smart grids and carbon markets, with the risk distribution exhibiting an asymmetric U-shaped pattern featuring a fatter left tail. (2) Risks propagate along this pathway: smart grid and ultra-high voltage → grid equipment → the carbon market. As the quantiles increase, the risks transmitted from the smart grid weaken, while the risks absorbed by the carbon market strengthen. (3) Driven by digital technologies, the risk network structure under extreme upward markets is more complex, characterized by dynamic shifts in the risk roles of ultra-high voltage and grid equipment over both short and long terms. However, the smart grid maintains the risk transmitter. (4) Under extreme downward markets, big data and cloud computing exacerbate risk contagion, whereas the mobile internet mitigates such contagion. Under extreme upward markets, artificial intelligence reinforces risk contagion, while big data and mobile internet alleviate such contagion. The results provide a reference for preventing cross-market risk contagion.</div></div>","PeriodicalId":47979,"journal":{"name":"Technology in Society","volume":"83 ","pages":"Article 103053"},"PeriodicalIF":12.5,"publicationDate":"2025-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145095203","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Towards precision dentistry through artificial intelligence and blockchain-based digital Twins: Investigating challenges and solution strategies","authors":"Ismail Erol ,&nbsp;Iskender Peker ,&nbsp;Ihsan Tolga Medeni ,&nbsp;Fatma Yuce","doi":"10.1016/j.techsoc.2025.103051","DOIUrl":"10.1016/j.techsoc.2025.103051","url":null,"abstract":"<div><div>The integration of artificial intelligence (AI), blockchain, and digital twins (DT) in dentistry is essential to meet evolving patient expectations and global healthcare challenges. However, realizing their full potential requires addressing significant adoption barriers. While conceptual studies have explored challenges to implementing AI, blockchain, and DT in dentistry, no prior research has systematically analyzed the interrelationships among these obstacles using a structured decision framework. This study employs pentagonal fuzzy (PF) DEMATEL to investigate the connections among challenges to effectively implementing AI and blockchain-based DT in dentistry. Expert opinions highlight ethical considerations and bias and fairness in AI-based DT as the most critical causal challenges. We propose an AI and blockchain-based DT architecture that enables human doctors to leverage DT-based decision support, while AI-driven systems execute high-precision procedures with blockchain-verified workflows. This framework enhances treatment accuracy and personalization in dentistry and offers a scalable model for addressing societal concerns, such as privacy, fairness, and labor dynamics, in technology-driven ecosystems. A pilot study framework is proposed to validate diagnostic accuracy, data security, and treatment customization. Accompanied by stakeholder guidelines, this research bridges dentistry with broader discussions on technology's societal impact, emphasizing the need for interdisciplinary strategies to ensure equitable and trustworthy innovation.</div></div>","PeriodicalId":47979,"journal":{"name":"Technology in Society","volume":"83 ","pages":"Article 103051"},"PeriodicalIF":12.5,"publicationDate":"2025-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145046090","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"How network characteristics drive multi-layer innovation networks to achieve boundary-spanning convergence","authors":"Yonghong Ma,&nbsp;Enjia Zhu","doi":"10.1016/j.techsoc.2025.103048","DOIUrl":"10.1016/j.techsoc.2025.103048","url":null,"abstract":"<div><div>Cross-domain knowledge integration and boundary-spanning collaboration among firms are increasingly recognized as key characteristics of vigorous development within the renewable energy sector. This paper, utilizing cooperative patent data from the new energy industry, employs Social Network Analysis (SNA) to analyze the evolutionary characteristics of multi-layer innovation networks and applies the Multilayer Exponential Random Graph Model (MERGM) to examine the driving effects of network characteristics on the boundary-spanning convergence of these innovation networks. The study's results indicate that closed triadic structures promote boundary-spanning convergence within innovation networks. Furthermore, knowledge diversity and heterogeneity facilitate boundary-spanning convergence in collaboration networks. The breadth of inter-firm cooperation also enhances boundary-spanning convergence in knowledge networks; however, the intensity of inter-firm cooperation does not necessarily promote boundary-spanning convergence in knowledge networks. This research broadens the perspective on multi-layer innovation networks and provides practical insights for fostering technological innovation and collaboration in the new energy industry.</div></div>","PeriodicalId":47979,"journal":{"name":"Technology in Society","volume":"83 ","pages":"Article 103048"},"PeriodicalIF":12.5,"publicationDate":"2025-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145060075","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A systematic review of research on just, equitable, responsible, and inclusive smart cities","authors":"Md. Nazmul Haque ,&nbsp;Dominik Beckers ,&nbsp;Emilio Costales ,&nbsp;Samar Aad ,&nbsp;Ayyoob Sharifi ,&nbsp;Luca Mora","doi":"10.1016/j.techsoc.2025.103050","DOIUrl":"10.1016/j.techsoc.2025.103050","url":null,"abstract":"<div><div>Digital technologies and infrastructure are essential to the development of smart cities. Yet, vulnerable populations often lack equitable access to such resources. In this context, integrating justice into smart city development serves as a crucial foundation for developing just and equitable cities. To explore this issue, we examined 3067 articles and synthesized findings from 67 studies on justice in smart cities. Using deductive content analysis, we categorize justice issues into two distinct groups: types and dimensions. Among the various types of justice, infrastructural justice emerges as the most frequently discussed, appearing in 23 studies and highlighting significant disparities in access to basic urban infrastructure for marginalized communities. In terms of justice dimensions, procedural justice is the most prominent. Discussed in 27 studies, it emphasizes the importance of inclusive decision-making and the challenges posed by limited public awareness and tokenistic participation. The findings reveal that marginalized communities, particularly low-income groups, women, and individuals with disabilities, bear the brunt of exclusion, inequity, and marginalization in smart city developments. These communities are particularly vulnerable to gentrification, displacement, and reduced economic opportunities, further deepening existing inequalities. By positioning justice as a central element in smart city development, this study calls for a fundamental shift in the mindset of practitioners, advocating for policies and governance approaches that promote a just, equitable, responsible, and inclusive smart city ecosystem.</div></div>","PeriodicalId":47979,"journal":{"name":"Technology in Society","volume":"83 ","pages":"Article 103050"},"PeriodicalIF":12.5,"publicationDate":"2025-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145046125","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cooperative supervision of livestreaming e-commerce based on stochastic evolutionary game and overconfidence","authors":"Xiaochao Wei ,&nbsp;Qiping She","doi":"10.1016/j.techsoc.2025.103049","DOIUrl":"10.1016/j.techsoc.2025.103049","url":null,"abstract":"<div><div>The rapid development of livestreaming e-commerce has been accompanied by an increasing number of misleading marketing behaviors (MIBs) that require adequate regulations. To reveal the impact of irrational behavior (overconfidence) and to explore effective supervision strategies tailored to different types of streamers. We have classified streamers into brand-affiliated streamers and professional streamers (including internet celebrity streamers and ordinary streamers), then four types overconfidence are identified and integrated into a stochastic evolutionary game framework to investigate the regulatory effectiveness. The findings indicate that platform overconfidence positively affects supervision, while overconfidence among streamers and consumers has the opposite effect. For brand-affiliate streamers, the reputation mechanism exerts the most significant regulatory influence and should be heightened; additionally, enhancing platform penalties proves effective in cases of streamer overconfidence, whereas reducing supervision costs works better in other scenarios. Regarding professional streamers, a combination of platform penalties and incentive mechanisms leads to more stable and effective regulatory outcomes, especially in cases of streamer or consumer overconfidence. Furthermore, for internet celebrity streamers, the reputation mechanism serves as a beneficial supplement; for ordinary streamers, reducing regulatory costs proves to be more effective. Therefore, this study provides insights for classified and tiered regulation policy formulation regarding livestreaming e-commerce and provides a new perspective for supervision research by integrating overconfidence and evolutionary games.</div></div>","PeriodicalId":47979,"journal":{"name":"Technology in Society","volume":"84 ","pages":"Article 103049"},"PeriodicalIF":12.5,"publicationDate":"2025-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145107928","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"AI FoMO (fear of missing out) in the workplace","authors":"Mariano Méndez-Suárez ,&nbsp;Maja Ćukušić ,&nbsp;Ivana Ninčević-Pašalić","doi":"10.1016/j.techsoc.2025.103052","DOIUrl":"10.1016/j.techsoc.2025.103052","url":null,"abstract":"<div><div>While AI is credited with improving productivity, automating repetitive tasks, and fostering safer work environments, it also raises employee concerns about job security, reduced autonomy, and the perceived obsolescence of their skills. This study focuses on the fear of being left behind, or fear of missing out (FoMO), to understand employees' perceptions of AI adoption. Using data from the latest OECD study on AI in the workplace, specifically focusing on workers who had been using AI over an extended period of time, this article applies Fuzzy Set Qualitative Comparative Analysis (fsQCA) to examine the relationships between employee control over decision making, mental health impacts, concerns about AI oversight (“robo-boss”), and skill devaluation. Results reveal multiple causal pathways to FoMO, where combinations of perceived skill devaluation, lost autonomy, and concerns over AI supervision are key drivers of this anxiety. As the study reveals, employees who perceive AI to reduce their decision-making autonomy are significantly more likely to experience FoMO, amplifying the psychological impact of automation on job anxiety. Conversely, positive perceptions of AI's role in supporting well-being and maintaining decision-making authority mitigate FoMO. The study highlights the importance of promoting transparent communication, ongoing training, and inclusive AI implementation strategies to address emotional responses and improve workforce adaptability. To ensure a balanced transition to AI-enabled workplaces, organizations must integrate AI in a way that empowers employees, rather than exacerbating fears of obsolescence.</div></div>","PeriodicalId":47979,"journal":{"name":"Technology in Society","volume":"84 ","pages":"Article 103052"},"PeriodicalIF":12.5,"publicationDate":"2025-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145107925","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}