Technology in Society最新文献

The current study aimed to investigate the results of integrating the planned behavior model with the technology acceptance adoption model, and the differences between age groups in direct and indirect relationships. The empirical data of 203 online purchasing users from the Libyan city of Tripoli via Google surveys analyzed using Structural Equation Modelling. The questionnaire was employed and measured by TPB and TAM models. The most important findings reached are the presence of a significant direct effect of social influence and perceived behavior control impact on purchasing behavior because of the age group of 30–50 years. Likewise, perceived of use has a significant effect on purchasing behavior due to of the age group of 30–50 years and the age group of more than 50 years. Three out of four hypotheses were supported: purchase intention mediates the relationship between social influence and perceived behavior control, perceived usefulness, and ease of use on the one hand and purchasing behavior on the other hand. More, there are significant differences indirect effects of social influence and perceived behavior control and perceived usefulness on purchasing behavior due to the variable of age, more specifically in the age group of (30–50 years), while it was not significant in the other age groups. The research also discussed future directions for research in the field of technology use.

Artificial intelligence (AI) is increasingly prevalent in our daily lives, setting specific requirements for responsible development and deployment: The AI should be explainable and inclusive. Despite substantial research and development investment in explainable AI, there is a lack of effort into making AI explainable and inclusive to people with cognitive disabilities as well. In this paper, we present the first steps towards this research topic. We argue that three main questions guide this research, namely: 1) How explainable should a system be?; 2) What level of understanding can the user reach, and what is the right type of explanation to help them reach this level?; and 3) How can we implement an AI system that can generate the necessary explanations? We present the current state of the art in research on these three topics, the current open questions and the next steps. Finally, we present the challenges specific to bringing these three research topics together, in order to eventually be able to answer the question of how to make AI systems explainable also to people with cognitive disabilities.

While there is an interest in questions related to empathy and communication technologies (CTs) in various disciplines, conceptual and ethical ambiguities on what empathy exactly is and whether and how it can be shaped by technologies make it unclear how to approach such questions. This paper sets out to provide such a framework: a way to understand empathy and its relationship to CTs in a conceptually and ethically robust manner. A critical reconsideration of the concept is needed, especially if we want to use the concept to evaluate technologies and their impact in terms of desirability and guidance to shape our future. I argue we need to understand empathy explicitly as a moral concept that is contextually situated, relational, and diverse, and to do so, I argue to understand empathy as a virtue. Section 2 lays down the theoretical foundation to explore empathy as a virtue, technological mediation, and CTs. In section 3, I apply these concepts to identify different ways in which CTs can mediate empathy and change what it means to be empathetic on both individual and societal levels. This multi-layered understanding of “CT-mediated empathy” provides a lens through which questions on CTs and empathy can be approached, such that we can reflect on, evaluate and improve specific technologies, their implementation, and their use. In section 4, I summarize this in a list of seven questions that require reflection in the design and implementation of a (new) CT. The paper ends with some forward-looking implications and recommendations for design, research, education, and policy towards an empathetic sociotechnical future.

Transformative technologies are the key to leading future technology innovation and economic development. However, with the exchange of technological knowledge among countries and the explosive growth of patented technology, the uneven flow and application of technology across geographic regions has become increasingly apparent, making it more and more difficult to track and absorb potentially transformative technology (PTT). As a proxy, the wake-up trajectories of the sleeping beauty patent family (SBPF) reflect the unbalanced distribution and application of PTT but still lack in-depth discussion. Therefore, this study adopted the parameter-free criteria to identify SBPFs and revealed the globalized diffusion patterns of PTT behind SBPFs' wake-up time and pace trajectories by taking “Polymerase Chain Reaction” technology as an example. The findings show that SBPFs’ wake-up has five-time and four-spatial trajectories and presents a small-scale diffusion in local areas. Meanwhile, PTT shows five diffusion patterns, achieving an unbalanced and centralized diffusion worldwide. These provide theoretical support for predicting the global development of PTT, and practical guidance for choosing technical direction, grasping market opportunities, and optimizing the national innovation environment.

As content generated by artificial intelligence (AI) has become more accessible and higher quality, social debates have intensified. Therefore, this study investigates how people perceive and evaluate AI-generated content and accounts compared to human-created accounts and content. We created Instagram accounts representing AI, influencers, and the public and conducted a user study with 43 participants. The participants had difficulty distinguishing AI accounts from human ones. Moreover, there were significant differences in user perceptions concerning the three account types. Participants perceived the AI and influencer accounts as more attractive than the public account, and they rated the quality of AI-generated content as highly as that created by influencers. These findings suggest that the advancement of generative AI could alter the social media landscape and contribute to discussions on the characteristics and ethical problems of AI-generated content.

Recent technological advances have brought both anticipation and uncertainty. Entrepreneurs and external stakeholders in technology industries must distinguish between realistic and unrealistic prospects for new technologies. To address this issue, this study introduces the concept of near-lies defined as idealistic statements formally made by entrepreneurs, such as promises or predictions of a firm's future performance, that might exceed its capacity, potentially leading to future falsehoods. Near-lies differ from existing notions of corporate dishonesty because they are potential falsehoods or assume facts that are unknown at the moment, whereas existing notions represent exposed falsehoods. This concept offers practical implications in the era of advanced technology. To prevent dishonesty, entrepreneurs must engage in transparent communication when offering statements about their firm's future performance, prioritizing the long-term impression management toward external stakeholders. External stakeholders must rely on factual information to predict truths and effectively respond to entrepreneurs' near lies.

In the context of sustainable development, the energy crisis and the volatile carbon trading markets have made the integration of green technology increasingly essential. This study explores the spillover effects between green technology innovation (GTI), oil price, clean energy (CE), carbon emissions trading prices (CETP), and sustainable development (SD) using quantile connectedness. The static analysis reveals that the connectedness relationship in extreme quantiles is remarkably more related than the middle quantile. The dynamic results indicate that major events significantly strengthen the overall risk correlation, but spillover effects are asymmetric under different quantiles. Further analysis under extreme market conditions demonstrates that SD and CE have produced a continuous and steady risk spillover to GTI, while CETP increased the risk transmission to GTI following the COVID-19 pandemic. This research underscores the significance of coordinating the development of GTI, energy, carbon markets, and SD by investigating risk contagion mechanisms in various market scenarios. In terms of policy implications, the findings indicate that stable energy system and reasonable carbon prices can stimulate the advancement of GTI.

Small and medium-sized enterprises (SMEs) rely on a thriving distribution network and digital technologies, including the metaverse, to remain competitive. The retail industry is perceived as a portfolio-based and granular business. Hence, retail SMEs can be a key source of innovation and a major source of growth that need technical flexibility to react quickly to changing customer needs. Therefore, grounded in the TOE framework, this study is undertaken to explore the drivers of metaverse adoption for enhancing the marketing capabilities of retail SMEs. Online surveys were used to gather primary data from 300 marketing practitioners employed in retail SMEs. Subsequently, the data were analysed using quantitative research methodology. The finding reveals that the metaverse is gaining attention from retail SMEs due to its technological, organisational, and environmental drivers, as well as its ability to provide immersive experiences to customers. Thereafter, metaverse adoption enhances the marketing capabilities of SMEs with new sales channels, tailored marketing, and increased customer reach with an understanding of the marketplace focused on customer relations, market research, and cross-management capabilities.

This paper presents a decomposed self-efficacy-based value adoption model (SVAM) to explore user perceptions of partially autonomous vehicles (PAVs) and fully autonomous vehicles (FAVs) and their impacts on adoption intention. Data from 279 participants on Mechanical Turk were analyzed using structural equation modeling and multigroup analysis via SmartPLS4.0. Survey results revealed a preference among respondents for PAVs over FAVs. The analysis showed differential effects of perceived value and self-efficacy regarding PAVs and FAVs, shedding light on why users favored PAVs over more advanced FAVs. Perceived enjoyment was identified as a predominant factor in shaping value perceptions of autonomous vehicles, surpassing utilitarian usefulness. Self-efficacy played a varying driving force in preference for PAVs and FAVs, determined by perceived ease of use and familiarity. The proposed SVAM model offers enhanced insights compared to the technology acceptance model in discerning the adoption patterns between PAVs and FAVs. These findings provide valuable insights regarding factors influencing user perceptions and intentions toward PAVs and FAVs, highlighting the different emphases of technology development and marketing in this domain.

Coastal communities across the globe are prone to imminent disasters and emergencies due to their geographic placement, and their fishing occupations add to their exposure to ocean-related disasters more during their occupational voyage. The fishermen in the state of Kerala, India, lead a distinctive lifestyle compared to the mainstream community, primarily because of a significant digital divide. This divide hampers their access to livelihood support, such as live market information and impedes any potential improvement in their quality of life through digital services. The community's transformation is possible only through discrete and gradual steps of progression by bringing services to different areas such as education, connectivity, technology adoption, business, and livelihood. This study revealed prevalent gaps in the fishing community, including a lack of digital access and communication opportunities in the deep ocean, a deficiency in digital capacity preventing them from leveraging the benefits of Information and communications technology (ICT), leading to community isolation from digital inclusion and limiting economic opportunities. To address these issues, the study proposes an IoT-enabled digital ecosystem, transforming the community into a smart digital community. This ecosystem integrates a low-cost deep ocean communication solution, supportive software applications, a blockchain-based e-commerce platform, and a sustainable social change model for technology adoption. Proper adoption and utilisation of the digital ecosystem can strengthen the community's resilience to natural disasters, and climatic changes by providing relevant information and livelihood resilience by offering them an e-commerce platform to improve income and reduce their vulnerability. It will equip them to enhance their responsiveness to changing environmental and social factors and bounce back to build their innate resilience.