Search Results (14)

Although digital hoarding behavior does not directly affect physical space, with the popularization of cloud storage services, its impact on energy consumption has become increasingly significant, posing a challenge to environmental sustainability. This study focuses on the factors influencing consumer digital hoarding behavior on e-commerce platforms, aiming to provide management decision-making references for e-commerce enterprises to deal with consumer digital hoarding phenomena and improve transaction effectiveness. Based on the Motivation–Opportunity–Ability (MOA) Theory and through the Adversarial Interpretive Structure Modeling Method (AISM), this study systematically identifies and analyzes the influencing factors. The findings reveal that emotional attachment, burnout, and fear of missing out are the main motivational factors directly affecting consumer digital hoarding behavior, with strong interconnections between these factors. Perceived usefulness and platform interaction design are significant opportunity factors, indirectly affecting digital hoarding behavior by improving user experience and satisfaction. E-commerce platform convenience, anticipated ownership, perceived economic value, emotional regulation ability, auxiliary shopping decision-making, perceived behavioral control, and information organization ability are the foundational and intermediate factors. The research results emphasize the importance of understanding consumer digital hoarding behavior in the context of sustainable development. This is not only conducive to optimizing the shopping cart function and data management strategy of e-commerce platforms and improving transaction conversion rates but also provides a reference for policymakers to formulate data management and privacy protection policies. Full article

Background: Hepatitis C virus (HCV) infection presents a significant public health challenge globally, particularly in high-burden countries like Nigeria, where an estimated 2.4 million individuals are living with HCV. HCV self-testing (HCVST) can potentially bridge the significant diagnosis gap and help individuals to determine their HCV status in the privacy of their homes. It offers a solution to overcome barriers related to stigma and limited access to healthcare. In Nigeria, Self-testing for hepatitis C has only been implemented in a pilot research context. This study aimed to assess stakeholder and community awareness and perceptions of HCVST in Nigeria. The findings will provide insights that could inform effective policies and future scale-up programs for HCV control. Methods: A cross-sectional descriptive study was conducted using an online social media survey administered through SurveyMonkey. The survey was disseminated across social media platforms and groups between October–November 2023. Participants included Nigerians (both health professionals and non-health professionals) aged 18 years or older residing in any of the 36 states and the Federal Capital Territory (FCT). Data collected include sociodemographic characteristics, awareness and perceptions of HCVST, and perceived benefits and barriers. Results: Of 321 respondents, 94% perceived HCVST as highly important. While 77% of respondents knew about HIVST, only 58% had prior knowledge of HCVST. The analysis also showed that healthcare workers had greater awareness of HIV self-testing (82.3%) compared to non-healthcare workers (50.0%). Most respondents (88%) were highly likely to recommend HCVST and perceived it as a cost-effective alternative to traditional testing. Key perceived benefits included increased disease detection and control (67%), improved access to testing (21%), and reduced stigma (11%). In the unadjusted model, geographical zone (Southern Nigeria: cOR = 0.49, 95% CI: 0.30–0.77, p = 0.002), work experience (more than 20 years: cOR = 2.79, 95% CI: 1.11–8.07, p = 0.039), and prior awareness of HIV self-testing (cOR = 5.24, 95% CI: 3.00–9.43, p < 0.001) were significant predictors of HCVST awareness. However, in the adjusted model, only prior awareness of HIV self-testing remained significant (aOR = 4.77, 95% CI: 2.62–8.94, p < 0.001). Conclusions: The strong support for HCVST among stakeholders in Nigeria highlights its potential to enhance HCV control, especially within the broader context of infectious diseases like STIs. The greater awareness of HIV self-testing among healthcare workers compared to non-healthcare workers indicates the need for targeted awareness campaigns for non-healthcare populations. Addressing these awareness gaps, leveraging lessons from HIVST, and using existing infrastructure will be crucial. Prioritizing public education, outreach, and effective linkage to care will drive the impact of HCVST in achieving HCV elimination goals and position it as a model for expanding similar STI interventions in Nigeria. Full article

The 21st century has marked the dawn of an aging population. China’s aging process ranks first worldwide. The country has recognized the gravity of this demographic shift and implemented strategies to address it at the national level. A vast majority of elderly Chinese individuals (approximately 90%) aspire to age in their own homes. Smart homes, endowed with cutting-edge digital technologies, such as AI, the Internet of Things, and big data, hold vast potential for enabling this vision. However, acceptance of smart home products and services among elderly individuals in China remains low. The main reason is that the related products and services fail to effectively alleviate the perceived risk of this population in the R&D process of related products and services, and there is a lack of effective measurement methods. To holistically assess the potential obstacles faced by elderly individuals using smart home products and services, this study targeted individuals aged 45–60 years in China. This study aimed to develop a comprehensive perceived risk scale specific to smart homes for this demographic. Initially, this study identified key risk dimensions and corresponding measurement items through a rigorous literature review, user interviews, and expert consultations. Subsequently, it ensured the reliability and validity of each dimension and its corresponding observation variables through preliminary research, exploratory factor analysis, and confirmatory factor analysis. This approach allowed for a comprehensive understanding of the challenges faced by future elderly individuals when utilizing smart home products and services, thus enabling the development of more effective solutions. The scale encompassed ten factors and seventy measurement items, including Privacy and Security Risk (seven items), Physical Risk (seven items), Technological Risk (nine items), Performance Risk (seven items), Service Risk (nine items), Financial Risk (five items), Psychological Risk (seven items), Industry and Market Risk (six items), Social Support Risk (six items), and Policy and Legal risk (seven items). The measurement scale developed in this study represents a groundbreaking first attempt to create a systematic scale for assessing the perceived risks associated with smart homes for the elderly in China. It not only enables professionals, businesses, and manufacturers to avoid or reduce barriers in the R&D process of related products and services, facilitating smart home industry growth and enhancing user adoption, but also serves as a universal reference for the potential obstacles that digital technology may encounter in addressing aging-related issues, which has significant theoretical value and practical importance. Full article

The purpose of this article is to identify what factors influence employees’ opinions on supervisors’ interference with their lifestyles in remote working conditions during COVID-19. Our sample included 1000 participants, both managers and non-managers. Outcomes variables included the following: managerial interference with the lifestyle of employees, acceptance of different lifestyles, and unequal treatment of employees in relation to their lifestyle. Explanatory variables related to employees’ characteristics included sex, age, education and seniority and the position in the company (managers/workers), size of the team of employees, size of the organization, characteristics of work (individual/teamwork), as well as the degree of formality in employees’ behaviors. Analysis was conducted using logistic regression in a multivariate analysis of individual (employee-side) and organizational determinants. Our research has shown that lifestyle acceptance, lifestyle interference when working remotely, and unequal treatment of employees based on lifestyle are determined as follows: the organization’s characteristics, the nature of the work, and the social characteristics of the employees. Our findings contribute to understanding how remote work is perceived in relation to employees’ lifestyles. These insights can help organizations develop effective policies and practices regarding, for example, health interventions to support and not unreasonably interfere with their privacy. Full article

Background: With a massive population of internet users, China has witnessed a shift in the behavior of social media users towards the COVID-19 pandemic, transitioning from reticence to frequent sharing of information in response to changing circumstances and policy adjustments of the disease. This study aims to explore how perceived benefits, perceived risks, subjective norms, and self-efficacy influence the intentions of Chinese COVID-19 patients to disclose their medical history on social media, and thus to examine their actual disclosure behaviors. Methods: Based on the Theory of Planned Behavior (TPB) and Privacy Calculus Theory (PCT), a structural equation model was constructed to analyze the influence paths among perceived benefits, perceived risks, subjective norms, self-efficacy, and behavioral intentions to disclose medical history on social media among Chinese COVID-19 patients. A total of 593 valid surveys were collected via a randomized internet-based survey, which constituted a representative sample. Firstly, we used SPSS 26.0 to conduct reliability and validity analyses of the questionnaire, as well as the tests of demographic differences and correlations between variables. Next, Amos 26.0 was employed to construct and test the model fit degree, identify the relationships among latent variables, and conduct path tests. Results: Our findings revealed the following: (1) There were significant gender differences in the self-disclosure behaviors of medical history on social media among Chinese COVID-19 patients. (2) Perceived benefits had a positive effect on self-disclosure behavioral intentions (β = 0.412, p < 0.001); perceived risks had a positive effect on self-disclosure behavioral intentions (β = 0.097, p < 0.05); subjective norms had a positive effect on self-disclosure behavioral intentions (β = 0.218, p < 0.001); self-efficacy had a positive effect on self-disclosure behavioral intentions (β = 0.136, p < 0.001). (3) Self-disclosure behavioral intentions had a positive effect on disclosure behaviors (β = 0.356, p < 0.001). Conclusions: Our study, by integrating TPB and PCT to examine the influencing factors of the self-disclosure behaviors among Chinese COVID-19 patients on social media, found that perceived risks, perceived benefits, subjective norms, and self-efficacy had a positive influence on the self-disclosure intentions of Chinese COVID-19 patients. We also found that self-disclosure intentions, in turn, positively influenced disclosure behaviors. However, we did not observe a direct influence of self-efficacy on disclosure behaviors. Our study provides a sample of the application of TPB in the context of social media self-disclosure behavior among patients. It also introduces a novel perspective and potential approach for individuals to address the feelings of fear and shame related to illness, particularly within the context of collectivist cultural values. Full article

The optimization of caching mechanisms has long been a crucial research focus in cloud–edge collaborative environments. Effective caching strategies can substantially enhance user experience quality in these settings. Deep reinforcement learning (DRL), with its ability to perceive the environment and develop intelligent policies online, has been widely employed for designing caching strategies. Recently, federated learning, when combined with DRL, has been in gaining popularity for optimizing caching strategies and protecting data training privacy from eavesdropping attacks. However, online federated deep reinforcement learning algorithms face high environmental dynamics, and real-time training can result in increased training energy consumption despite improving caching efficiency. To address this issue, we propose a low-energy federated deep reinforcement learning strategy for caching mechanisms (LFDC) that balances caching efficiency and training energy consumption. The LFDC strategy encompasses a novel energy efficiency model, a deep reinforcement learning mechanism, and a dynamic energy-saving federated policy. Our experimental results demonstrate that the proposed LFDC strategy significantly outperforms existing benchmarks in terms of energy efficiency. Full article

Technology advancements have paved the way for public access to shared autonomous vehicles (SAVs), but there is still no travel survey examining how SAVs with dynamic ride sharing (DRS) affect long-distance (LD) trips. Given the growth in these trips and the higher importance of travel time and cost on LD trips, assessing potential impacts of SAVs could be a vital tool in planning for a sustainable transportation system. This paper examines the impact of various attitudinal, sociodemographic, and travel-related characteristics on the usage intention of SAVs with DRS on LD trips. We have designed and conducted a web-based survey for this purpose and based on a representative sample of 723 individuals in 2021, a Generalized Ordered Logit model is estimated. Estimation results highlight the key importance of following psychological factors in a descending order: price evaluation, perceived usefulness, consumer innovativeness, sharing attitude, and privacy concern. Further, key factors among sociodemographic and travel-related characteristics are gender, education level, driving license, household car ownership, generational element, and crash history. These findings provide crucial insights into the likely effects of SAVs with DRS on LD trip behavior, based on which a number of practical implications are proposed for facilitating policy-making. Full article

The integration of automation and shared mobility services would significantly affect transportation demand, especially mode choice. However, little is known about how attitudes, travel attributes, and demographic factors affect the modal shift to shared autonomous vehicles (SAVs). A stated preference survey was designed to determine the preferences of car and transit users in relation to a modal shift to SAVs. The binary logit models’ results revealed distinct behavior patterns and systematic heterogeneity among transit and private car users based on a representative sample of 607 individuals in 2021. The shifting behavior of both users is positively affected by attitudinal factors, including consumer innovativeness, perceived usefulness, sharing intention, and ecological awareness, while negatively affected by privacy concerns. In terms of travel-related attributes of SAVs, car users are eight times more sensitive to waiting times compared to transit users, who are three times more concerned with travel costs. Further, privacy concerns, the number of passengers sharing a trip, and the ratio of waiting time to travel time of SAVs were the major barriers to shifting the likelihood of car users’ behavior. In light of these findings, based on the likely effects of SAVs on shifting behavior, a number of practical implications are suggested for more effective policy making. Full article

Along with the increasing popularity of autonomous vehicles (AVs), urban livability and public health will be enhanced due to ecofriendly issues: alleviated traffic congestion, lower car ownership, and reduced transport emissions. However, some emerging issues, including public safety, trust, privacy, reliability, underdeveloped legislation, and liability, may deter user intentions to adopt an AV. This study introduces an extensive factor, playfulness, into the technology acceptance model (TAM) to quantify the impacts of psychological factors (perceived usefulness, perceived ease of use, and perceived playfulness) on AV adoption intention. This study proposes four AV-related policy measures (financial incentivization, information dissemination, convenience, and legal normalization) and examines how policy measures motivate users to adopt an AV to facilitate public safety. Furthermore, this study investigated the moderating effects of demographic factors on the relationships between independent variables and AV adoption intention. Two models were proposed and estimated using a total of 1831 survey responses in China. The psychology-related and policy-related models explained 62.2% and 33.6% of the variance in AV adoption intention, respectively. The results suggest that perceived playfulness (β = 0.524, p < 0.001) and information dissemination (β = 0.348, p < 0.001) are the most important influencing factors of AV adoption intention. In addition, demographic factors (gender, education, income, the number of private cars owned by a family, and types of cities) can moderate the effects of psychological factors and policy measures on user intentions to adopt an AV. These insights can be employed to design more cost-effective policies and strategies for subgroups of the population to maximize the AV adoption intention. Full article

Interaction is the main feature of social media, while in recent years, frequent privacy disclosure events of the social media user affect users’ privacy disclosure behavior. In this paper, we explore the mechanism of interaction characteristics by social media apps on users’ privacy disclosure behavior. Using SOR theoretical models and the privacy calculus theory, the effects of privacy disclosures on TikTok are examined. Structural equation modeling is used to analyze the data from 326 questionnaires. We concluded that human–computer interaction (perceived personalization, perceived control) and interpersonal interaction (perceived similarity) positively and negatively affected perceived benefits and perceived risks, respectively, and had positive effects on intention to disclose privacy through perceived benefits and perceived risks, respectively, except that perceived personalization had no effect on perceived risk and intention to disclose privacy. In addition, perceived benefits and perceived risks played an intermediary role in interactivity and privacy disclosure intention. Finally, we provided countermeasures and suggestions for social media operators and policy makers. Full article

Taiwan has been a world leader in controlling the spread of SARS-CoV-2 during the COVID-19 pandemic. Recently, the Taiwan Government launched its COVID-19 tracing app, ‘Taiwan Social Distancing App’; however, the effectiveness of this tracing app depends on its acceptance and uptake among the general population. We measured the acceptance of three hypothetical tracing technologies (telecommunication network tracing, a government app, and the Apple and Google Bluetooth exposure notification system) in four nationally representative Taiwanese samples. Using Bayesian methods, we found a high acceptance of all three tracking technologies, with acceptance increasing with the inclusion of additional privacy measures. Modeling revealed that acceptance increased with the perceived technology benefits, trust in the providers’ intent, data security and privacy measures, the level of ongoing control, and one’s level of education. Acceptance decreased with data sensitivity perceptions and a perceived low policy compliance by others among the general public. We consider the policy implications of these results for Taiwan during the COVID-19 pandemic and in the future. Full article

Public officials are constantly facing decisions under risk, particularly in digitalization policies, the consequences of which are hard to predict given their multiple dimensional nature. Since scholarly research has not yet addressed this phenomenon, we do not know what influences the risk preferences of politicians in digitalization policies. Prospect theory—widely used to explain political decisions—can help us describe politicians’ potential risk references and the conditions affecting their decisions. Accordingly, this paper aims to answer the following question: what are the conditions affecting the risk preferences of politicians in digitalization policies? I address this question by employing two important assumptions of prospect theory: the value function and the probability weighting function. Particularly, I discuss the effects of loss/gain frames and probability weighting on the risk preferences of politicians in digitalization with outcomes in multiple dimensions (e.g., data privacy and economy). I argue that whether an outcome is perceived as a gain or as a loss depends on how the situation is framed and how the probabilities are weighted. I conclude with a brief discussion of how prospect theory can leverage our understanding of political decisions in highly complex policy environments. Full article

In recent decades cities have applied a number of policy measures aimed at reducing car use and increasing public transportation (PT) patronage. Persuasive strategies to change mobility behavior present notable limitations in economic and logistical terms and have only minor impacts. The smartphone has emerged as a promising tool to overcome these challenges, as it can host persuasion strategies through mobility apps. Simultaneously, Mobility-as-a-Service (MaaS) schemes could open up new possibilities for addressing both sustainability goals and the needs of urban travelers. This paper carries out a literature review to identify the key elements of mobility apps that foster more sustainable travelers’ choices. The findings show that some persuasive strategies such as eco-feedback, rewards or social challenges are effective because they are well received by users. From the users’ point of view, the perceived barriers (e.g., usability, privacy) relate negatively to app adoption, and it is considered useful to include functional needs such as real-time information (e.g., to avoid congestion), cost savings (e.g., customized multimodal packages), comfort (e.g., crowding on public transport) or health (e.g., calories burned). We have found that a proper design of multimodal travel packages based on (i) financial incentives and (ii) environmental awareness, could help increase public transport patronage and reduce private car use. Full article

Developing an approach to manage privacy risk is critical to the success of e-marketing. Understanding the antecedents of privacy risk is therefore essential for the success of e-business. Because governments, businesses, and consumers are economic agents, this study examined the effects of governmental (privacy legislations) and firm-related (online business brand image) factors on consumer perceptions of online privacy risk. This paper proposes a conceptual model for exploring the underlying mechanisms of privacy legislations and online business brand image on consumer perceptions of online privacy risk. To test the conceptual model, data were collected from 425 students on a university campus which provided real personal information to online businesses within the preceding 3 months. Structural equation modeling was employed to test all the hypotheses in the conceptual model. The results reveal that perceived effectiveness of privacy legislations and online business brand image positively affect trust in online businesses. In addition, trust in online businesses positively affects perceived effectiveness of business privacy policies and perceived benefits of information disclosure, which in turn negatively influences online privacy risk perception. Full article