Technology in Society最新文献

Given their novelty and ethical complexity, this study delves into the public acceptance of artificial intelligence-based resurrection technologies (AI-RTs), an emerging area in the AI domain that proposes to digitally “resurrect” individuals who have passed away. Employing a survey-based experimental design, the study explores various cognitive, affective, normative, and ethical predictors of acceptance, as outlined in the Technology Acceptance Model and its extensions. A nationally representative sample of U.S. adults (N = 1115) was randomly exposed to the description of an AI-RT application — virtual reality, chatbot, or deepfake — to gauge variations in public attitude and behavioral intention. The findings reveal a nuanced understanding of public sentiment towards AI-RTs. Factors such as perceived usefulness, perceived ease of use, perceived benefit, positive emotions, and negative emotions emerged as significant influencers of both attitude towards and intention to use AI-RTs. This study contributes to the understanding of public acceptance of controversial and ethically charged technologies, offering insights for developers, marketers, media, and regulators.

With the advancement of technology, digitalization has attracted increasing attention in recent years. Previous studies have linked firm digitalization to innovation performance; however, less attention has been given to ambidextrous innovation and small and medium-sized enterprises (SMEs), which play a vital role in economic development. Based on a knowledge-based view (KBV), this research investigates the relationship between digitalization and ambidextrous innovation in Chinese publicly listed SMEs. We found that digitalization promotes radical innovation more significantly than incremental innovation of listed SMEs. We further observed that firm digitalization and highly educated employees with a master's degree or above have a complementary effect on radical innovation, and the financial background of firms' top management team (TMT) members strengthens strengthens this complementary effect. This study not only enriches the digitalization–innovation performance relationship literature, but also contributes to the KBV by tying together three vital elements (technology, people, and relational networks) in the KBV and examining their relationships with ambidextrous innovation. It also has implications for managers of SMEs related to increasing the innovation returns from digitalization endeavors.

OpenAI's ChatGPT is a widely used artificial intelligence tool that has recently experienced rapid growth and widespread adoption. ChatGPT enhances digital accessibility, performance in communication, and supports the creation of digital content, which can be a powerful assistive technology for the education industry. However, the role of ChatGPT for higher education students remains a topic of contention. Therefore, this study is undertaken to investigate how ChatGPT usage can enhance information and communication technology (ICT) accessibility and performance by influencing life satisfaction among higher education students by proposing a unique conceptual model. The primary data were collected from 305 respondents, and quantitative methodology was used to analyse the data. The results indicate that interaction with ChatGPT increases freedom and productivity by producing understandable and relevant responses that meet emotional needs, which are positively correlated with happiness. ChatGPT usage provides unique experiences to students that evoke their feelings to strengthen academic engagement, and such feelings positively influence their perceptions and behaviour towards academic buoyancy. However, the concerns about the biased response, limited knowledge, and lack of emotional intelligence of ChatGPT limit trustworthiness and cause disengagement, which have been deemed the most significant weaknesses in improving quality of life.

Social platforms contribute to various hedonic and informational needs of their users. However, the unregulated, ubiquitous, and unhindered nature of the platforms is intricately linked to the exponential rise of online misinformation. The complexities in governing misinformation, coupled with the growing distrust of users, have diminished its value proposition for all stakeholders. Hence, it is crucial for all stakeholders to examine the state of research in this domain. We aim to examine the core value-adding governance mechanisms through a systematic scoping literature review. We propose an overarching conceptual framework that integrates the drivers of governance mechanisms with the outcomes of effective misinformation governance. Additionally, the framework illustrates the moderation role of platform monitoring efficiency for effective governance. This study will be especially useful for platform designers and practitioners to identify avenues for introducing strategic interventions on their platform and for scholars to develop a holistic understanding of the overall knowledge base in this domain and thus identify existing gaps in the literature which are rich for future examination.

The rapid development of generative AI represented by ChatGPT has attracted a large number of users, but also brings problems such as user addiction, which may undermine its sustainable development. Drawing on a cognition-affect-conation (C-A-C) perspective, this research examined generative AI user addiction. We used a mixed method of structural equation modeling (SEM) and fuzzy-set qualitative comparative analysis (fsQCA) to conduct data analysis. The results show that perceived anthropomorphism, perceived interactivity, perceived intelligence, and perceived personalization influence flow experience and attachment, both of which further affect user addiction. The fsQCA revealed three configurations triggering user addiction, among which flow experience and attachment are the common core conditions. The results imply that generative AI companies need to prevent user addiction and ensure a sustainable development.

Cognitive-Affective Mapping is a novel mind-map like technique enabling to visually represent existing belief systems or any declarative knowledge and can therefore be used in empirical social research. It can be applied broadly, for example to assess technology acceptance, and the obtained data can be analyzed with quantitative and/or qualitative approaches. Here, we aimed for the first time to assess the data quality of Cognitive-Affective Maps (CAMs). To assess whether the findings of CAM studies are due to measurement errors or due to a real effect, we aimed for a quantitative as well as qualitative test-retest reliability approach. Participants (62 in total) drew a CAM online on their cognitions, emotions and experiences regarding the topic "Universal Basic Income" twice with delays of the two measurement time points ranging from 7 to 24 days. Assuming that the evaluation of this topic is driven by values, a stable psychological measurement construct, we presume a high test-retest reliability. Pearson's Product-Moment-Correlations and Spearman's Rank Correlations of CAM parameters show quantitative test-retest reliabilities up to 0.78. Furthermore, two raters identified on average 52 % of repeated or at least semantically similar concepts drawn by the participants between the two measurement time points. Taken together, these findings are promising for a method with this amount of degrees of freedom.

This study employs microdata from the China Labor-force Dynamics Survey to investigate the influence of foreign language proficiency on the adoption of Internet technology within households. The results indicate that householders who are proficient in foreign languages are more likely to adopt Internet technology at home than those who lack such knowledge. The greater the foreign language proficiency of the householder, the greater the likelihood of Internet technology adoption. Further analyses indicate that the positive effect of foreign language proficiency on the Internet technology adoption of the household in China is more pronounced in male-headed households, in urban areas, and in eastern and central regions. This study also identifies three potential mechanisms by which foreign language proficiency influences household Internet technology adoption: the information effect, the trust effect, and the income effect. These findings contribute to the understanding of the role of language proficiency in technology adoption at the household level, offer new insights into the positive outcomes of foreign language education in China, and encourage measures to reduce digital inequality among households through language learning.

Grounded in a socio-technical systems governance framework, we explore the perceptions and strategies of SME managers and cybersecurity providers within the cybersecurity landscape. Addressing the gap in understanding of how cybersecurity governance takes place in the Canadian SME landscape, Interviews were conducted with 35 SME representatives and 11 cybersecurity providers and analyzed using discourse analysis. The results highlight four critical themes in this socio-technical transition: initial conditions, SME business model discourse, cybersecurity provider business model discourse, and transition outcomes. The transition underpins a mode of governance, blending elements of oligopoly and self-regulation, characterized by the dominance of key cybersecurity firms and a more facilitative role of state actors. A novel conceptual model emerges from the study, explicating the transition in SME institutional logics from a traditional ‘legacy logic’ towards an integrated cybersecurity approach. This transition is shaped by the principal-agent disconnect and moderated by SME and cybersecurity provider business model discourses.

Digital transition to Industry 5.0 (I5.0) has finally arrived after Industry 4.0 (I4.0) was offered ten years ago to help address industry flaws in manufacturing. I5.0 is necessary in contemporary business to achieve competitive advantages for a sustainable future. However, despite the importance of I5.0, the critical success factors (CSFs) for the transition from I4.0 to I5.0 have not been explored extensively in the literature. This study develops a model to investigate potential CSFs for the smooth transition from I4.0 to I5.0. The study ensures systems flexibility, then ranks the identified CSFs based on their influential weights and explores their interrelationships. The study adopts the Bayesian best-worst method (B-BWM) to assess the perceptions of several decision-makers from a probabilistic perspective for reducing information loss. The results from this study reflect that CSFs, such as adoption of advanced technology to create value in I5.0 paradigm, high-powered analytical ability for smart manufacturing, cost and funding in transition from I4.0 to I5.0, aligned organizational strategy in transition to I5.0, and security and privacy to ensure effective digital transformation, contribute significantly towards the digital transformation from I4.0 to I.50 in smart manufacturing in the context of steel manufacturing business environment considering the developing countries. The successful implementation of CSFs can help achieve flexibility in the supply chain, contribute to flexible systems and support managers in framing strategies that help them prioritize for an easy transition towards a sustainable future.

Recent papers assume that whereas the value of ‘traditional’ communications networks follows Metcalfe's law – that is, grows with the square of the number of users – the value of group-forming network platforms should increase faster. The papers see evidence in the fact that the advertising revenues of platforms such as Facebook and Tencent follow a cube law or stronger. We argue that such tests do not make much sense, as they lack a theoretical justification. Growth laws such as Metcalfe's and Reed's were conceived with purely one-sided networks in mind, reason in terms of utility for users, and have little to say about the monetisation of the value created. The results of the very papers that we discuss show that the laws have no generality. We also provide a counterexample of our own and proffer an alternative explanation.