E-learning adoption for sustainable higher education

Electronic learning (E-L) is a profound transition that is occurring in education as a new learning platform in countries across the globe. COVID-19 pandemic has forced all higher education institutions in Sri Lanka to adopt e-learning to maintain sustainable teaching. This study identified the relationships between the main influencing factors of e-learning usage behaviour and, in turn, sustainability in teaching. Theory of Planned Behaviour (TPB) was used to formulate the research framework and hypotheses. The population of the study was comprised of permanent academics attached to Sri Lankan public universities under the patronage of UGC. The sample size was 357 for the given population size of 5399, and a stratified sampling technique was used to select the sample. The study used a quantitative method under the philosophical assumption of positivism. The researchers have applied Structural Equation Modelling (SEM) to test the path association among factors. The result explores the path relationship between exogenous and mediating variables, mediating to an endogenous variable. The research outcome shows that attitude and perceived behavioural control influence e-learning usage but not the subjective norm. While behavioural intention mediates the relationship between attitude and perceived behavioural control and e-learning usage, the latter mediates the association between behavioural intention and sustainability in teaching. Gender, academic position and computer literacy level moderate the causal relationships of the factors influencing sustainability in teaching. Finally, this study concludes that Attitude, Perceived Behavioural Control, Behavioural Intention and E-learning Usage Behaviour are the factors influencing sustainability in teaching. This study recommends universities develop infrastructures, train staff members and establish an office for sustainability development. Furthermore, it recommends that future researchers do longitudinal studies and adopt decomposed TPB.

Modelling the significance of psychological, social, and situational factors on work efficiency and the preference for working from home in Southeast Asia

The shift in work paradigm owing to the implementation of new policies in the developing countries of Southeast Asia to reduce the spread of COVID-19 has created new challenges for both employers and employees. The study aimed to address the lack of extensive research on the effects of psychological, social, and situational factors on the work-from-home shift in Southeast Asia. This study incorporates the job characteristic theory, emphasizing how specific job characteristics influence motivation and performance. The study emphasizes the importance of creating an innovative and supportive work environment, improving digital capabilities, and promoting sustainable development through high-skill jobs to enhance remote employees' productivity. Valid responses from 288 full-time employees who have the option to work remotely were collected through online survey. The findings indicate that self-discipline, digital capability, and perceived organizational support significantly influence the preference for remote work. Managers should focus on motivating employees, providing support, and establishing a digital infrastructure to maximize productivity. Training and recruitment strategies should adapt to the changing work culture, while social support is crucial for encouraging innovative problem-solving. Trusting employees with autonomy and providing appropriate technologies fosters collaboration, efficiency, and creativity in different work settings.

Mapping the optimization of groundwater abstraction research: A bibliometric review in the context of South Asian region

Water scarcity has increased dramatically in many parts of the world and has become a major environmental problem globally in recent years. To address this challenge, researchers are continuously exploring and investigating different water sources and the relevant abstraction method. South Asian countries are not an exception in this regard. Specifically, how optimization has been done during the water abstraction process is becoming a key research agenda in South Asian region. This study attempts to systematically review the optimization of groundwater abstraction research in the South Asian region. First, bibliometric analysis has been performed to quantitatively assess the current research trends in the optimization of groundwater abstraction research. Second, a qualitative analysis has been done to get more insights into the different abstraction methods and simulation models used in groundwater abstraction research. This study has addressed the gap and explored research streams through scientific and conceptual mapping of the optimization of groundwater abstraction research. As revealed, the year 2020 is the most productive in groundwater abstraction research. Indian Institute of Technology and India were found to be the most impactful institution and countries in this field. The most studied area in groundwater abstraction research was found to be sustainable groundwater management, the geochemical process of controlling groundwater evolution, the Spatio-temporal variability of groundwater and the supply-demand of water during dry seasons. As revealed, statistical and mathematical modelling analysis is the most used approach in these studies. The findings of this study suggested that the water scarcity problem can be fixed by improving the design and operational techniques of the groundwater abstraction method and by using the different water sources collectively. This study further provides future directions and opportunities for research in the field of the groundwater abstraction process.

To Zoom or not: Diverging responses to privacy and security risks

During the onset of the COVID-19 pandemic and the subsequent lock-down, digital platforms like Zoom became essential for remote work. Yet at the same time, substantial security and privacy risks made the headlines. Using the lenses of Naturalistic Decision-making and the Theory of Multilevel Information Privacy, we find diverging responses to well-documented security risks of Zoom use in educational environments. We identify-three distinct response patterns, which we name the 'Agnostic', the 'Pragmatic' and the 'Sceptic', and show how the interplay of the salient social identity, personal privacy norms, and the privacy calculus guides the dynamic of privacy decision-making in light of experiential feedback, and the developing public discourse about security risks. We provide empirical evidence for multilevel decision-making and highlight the contextual and social nature of privacy decision-making about platform mode of use for remote work.

Examining the Acceptance of Blockchain by Real Estate Buyers and Sellers

Buying and selling real estate is time consuming and labor intensive, requires many intermediaries, and incurs high fees. Blockchain technology provides the real estate industry with a reliable means of tracking transactions and increases trust between the parties involved. Despite the benefits of blockchain, its adoption in the real estate industry is still in its infancy. Therefore, we investigate the factors that influence the acceptance of blockchain technology by buyers and sellers of real estate. A research model was designed based on the combined strengths of the unified theory of technology acceptance and use model and the technology readiness index model. Data were collected from 301 real estate buyers and sellers and analyzed using the partial least squares method. The study found that real estate stakeholders should focus on psychological factors rather than technological factors when adopting blockchain. This study adds to the existing body of knowledge and provides valuable insights to real estate stakeholders on how to implement blockchain technology.

Blockchain Technology Application Challenges in Renewable Energy Supply Chain Management

With the advent of new technologies and globalization of business, supply chains have turned into indispensable tools for gaining competitive advantage. The application of new technologies like blockchain can benefit sustainable energy supply chains by improving chain and logistics operations in the areas of trust, transparency and accountability, cooperation, information sharing, financial exchanges, and supply chain integration. However, the efforts to adopt such technologies in supply chains tend to face many challenges and challenges, which can seriously threaten their success. Therefore, it is crucial to carefully examine the challenges to blockchain technology application. This research focuses on identifying the criteria and challenges to the application of blockchain in renewable energy supply chains and also ranks the identified challenges in terms of their capacity to disrupt the process. The applicability of the suggested structure is examined in a case study of the renewable energy supply chain of Iran. In this study, the challenges are evaluated and ranked by the hybrid developed methods by the integration of the concept of gray numbers into the gray stepwise weight assessment ratio analysis (SWARA-Gray) and the gray evaluation based on distance from average solution (EDAS-Gray). Another group of hybrid methods including the gray weighted sum method (WSM-Gray), the gray complex proportional assessment (COPRAS-Gray), and the gray technique for order of preference by similarity to ideal solution (TOPSIS-Gray) is used to validate the results. The rankings obtained from all of these techniques show high degree of correlation. Among the identified challenges, "high investment cost" is found to be the most important challenge to the application of blockchain in sustainable energy supply chains.

An exploration of the role played by attachment factors in the formation of social media addiction from a cognition-affect-conation perspective

More and more users are overusing social media and the situation is getting worse, yet there is still a lack of research on social media addiction. Based on attachment theory and the Cognition-Affect-Conation (CAC) framework, this study combines the perception of intrinsic motivation and the technical features of social media as extrinsic motivators and explores the formative factors in social media addiction. The results show that social media addiction is determined by an individual's emotional and functional attachment to the platform, and that attachment is in turn influenced by intrinsic motivation (perceived enjoyment and perceived relatedness) and extrinsic motivation (functional support and information quality). The SEM-PLS technique was used to analyze the data collected from a questionnaire survey of 562 WeChat users. The results showed that social media addiction is determined by an individual's emotional and functional attachment to the platform. This attachment is, in turn, influenced by intrinsic motivation (perceived enjoyment and perceived relatedness) and extrinsic motivation (functional support and informational quality). The study first explains the latent antecedents of social media addiction. Second, it examines user attachment, particularly the role of emotional and functional attachment, and explores the platform technology system, which plays a key role in the development of addiction. Third, it extends attachment theory to the study of social media addiction.

Understanding the role of social media usage and health self-efficacy in the processing of COVID-19 rumors: A SOR perspective

Apart from the direct health and behavioral influence of the COVID-19 pandemic itself, COVID-19 rumors as an infodemic enormously amplified public anxiety and cause serious outcomes. Although factors influencing such rumors propagation have been widely studied by previous studies, the role of spatial factors (e.g., proximity to the pandemic) on individuals' response regarding COVID-19 rumors remain largely unexplored. Accordingly, this study, drawing on the stimulus-organism-response (SOR) framework, examined how proximity to the pandemic (stimulus) influences anxiety (organism), which in turn determines rumor beliefs and rumor outcomes (response). Further, the contingent role of social media usage and health self-efficacy were tested. The research model was tested using 1246 samples via an online survey during the COVID-19 pandemic in China. The results indicate that: (1)The proximity closer the public is to the pandemic, the higher their perceived anxiety; (2) Anxiety increases rumor beliefs, which is further positively associated rumor outcomes; (3) When the level of social media usage is high, the relationship between proximity to the pandemic and anxiety is strengthened; (4) When the level of health self-efficacy is high, the effect of anxiety on rumor beliefs is strengthened and the effect of rumor beliefs on rumor outcomes is also strengthened. This study provides a better understanding of the underlying mechanism of the propagation of COVID-19 rumors from a SOR perspective. Additionally, this paper is one of the first that proposes and empirically verifies the contingent role of social media usage and health self-efficacy on the SOR framework. The findings of study can assist the pandemic prevention department in to efficiently manage rumors with the aim of alleviating public anxiety and avoiding negative outcomes cause by rumors.

Possibilities, Patience, and Perseverance: A Preliminary Analysis of the Needs and Experiences of Ten Older Adults Regarding Their Use of Digital Health Technology

The COVID-19 pandemic created the need to use digital health resources (DR), as they sometimes were the only option to receive healthcare or social interaction. The aim of this research is to provide insight into the experiences during the lockdown of older people using DR for health in general and the points of improvement they see. A qualitative study was carried out using semi-structured interviews with older persons by telephone. A total of 10 older adults participated, with a median age of 78 years, the majority having a chronic disease. The most important themes for motivation to use health-related DR were 'urgency' and 'usefulness'. Experiences with DR were related to the themes 'human contact' and 'communication', which were experienced by respondents as facilitated by DR, and 'time and energy', which was two-sided. Additionally, most older persons worried about accessibility of DR by all older persons and the support needed. In conclusion, older persons are convinced of the urgency and the usefulness of digital technology for health and healthcare. Time and energy constraints can be alleviated by using DR on the one hand, but this can also be challenging if older persons are less digitally skilled or lack digital literacy. Good and sustained human support is therefore mandatory.

Problems and alternatives of testing significance using null hypothesis and P-value in food research

A testing method to identify statistically significant differences by comparing the significance level and the probability value based on the Null Hypothesis Significance Test (NHST) has been used in food research. However, problems with this testing method have been discussed. Several alternatives to the NHST and the P-value test methods have been proposed including lowering the P-value threshold and using confidence interval (CI), effect size, and Bayesian statistics. The CI estimates the extent of the effect or difference and determines the presence or absence of statistical significance. The effect size index determines the degree of effect difference and allows for the comparison of various statistical results. Bayesian statistics enable predictions to be made even when only a small amount of data is available. In conclusion, CI, effect size, and Bayesian statistics can complement or replace traditional statistical tests in food research by replacing the use of NHST and P-value.

Data security crisis in universities: identification of key factors affecting data breach incidents

The extremely complex and dynamic digital environments of universities make them highly vulnerable to the risk of data breaches. This study empirically investigated the factors influencing data breach risks in the context of higher education, according to crime opportunity theory and routine activity theory. The data consisted of university samples from China and were collected mainly from the Chinese Education Industry Vulnerability Reporting Platform. After applying Poisson regression for the estimation, increased public disclosure of vulnerabilities was found to escalate the frequency of data breaches, whereas cross-border data flow decreased the number of data breaches. Furthermore, the mechanism by which academic strength affects data breaches was examined through the two mediators of cross-border data flow and vulnerability disclosure. In addition, cloud adoption reduced data breaches, and public clouds were determined to be relatively more secure than private clouds. Cloud adoption also acted as a moderator between the negative impact of vulnerabilities and the positive impact of cross-border data flow on data breaches. The estimation and robustness findings revealed the underlying mechanisms that impacted university data security, clarifying the understanding of data breaches and suggesting practical implications for universities and other institutes to improve information security. The findings of this study provide insights and directions for future research.

Enablers and inhibitors of digital startup evolution: a multi-case study of Swedish business incubators

Global advances in digital technology are facilitating corresponding rises in digital entrepreneurship and its startup manifestation. There are many uncertainties on the road to digital startup evolution, some of which may be successfully navigated with the assistance of business incubators. While these organisations provide valuable guidance and support to the startup community, their efforts are at least partly constrained by the lack of a consistent, coherent roadmap to guide both them and their incubatees. T0 help efforts to develop such a map, this paper seeks to identify factors that influence digital startup evolution within an incubator setting through a multiple-case study focusing on digital startups under the umbrella of three business incubators in the Swedish city Umeå. Sets of enabling and inhibitory factors are identified through literature searches and the case studies. The latter may include inertia and possibly attitudes towards failure. In addition, present the Ideation Dynamics Model as a guide for both incubators and digital startups is proposed.

Impact of green technology innovation based on IoT and industrial supply chain on the promotion of enterprise digital economy

With the gradual deterioration of the natural environment, a green economy has become a competing goal for all countries. As a trend of green innovation development, the digital economy has become a research hotspot for scientists. In this article, we study the supply chain management of enterprises in green innovation and digital economy development and complete the identification and demand prediction of warehouse goods through the Internet of Things (IoT) and artificial intelligence (AI). As the stuff meets the goods detection and storage, we employ an intelligent method to detect and classify the goods. The demand prediction analysis is carried out based on historical data on goods demand in the enterprise. The absolute error between the prediction result and the actual demand within 1 week is less than 30 goods by the particle swarm optimization-support vector machine (PSO-SVM) method used in this article. First, the goods identification task is completed based on video surveillance data using YOLOv4, and the recognition rate is as high as 98.3%. This article realises enterprises' intelligent supply chain management through the intelligent identification of goods and the demand forecasting analysis of goods in the warehouse, which provides new ideas for green innovation and digital economy development.

Acceptability of fully guided virtual implant planning software among dental undergraduate students

BACKGROUND

Fully guided implant surgery as a technique is gaining popularity. It has been observed that use of surgical guides improves precision and predictability for dental implant placement. However, like any other newer technology, the acceptance of fully guided dental implant technology among users is based upon its perceived usability. This study aimed at evaluating the perception about using Virtual Implant Planning Software (VIPS) among undergraduate dental students at the university of Sharjah.

METHODS

Ninety-Six dental surgery students from the University of Sharjah were included in the study. One week after the Virtual Implant Planning Software (Planmeca Romexis version 6.2 procedure, students were asked to complete a Combined technology acceptance model and the theory of planned behaviour (C-TAM TPB) questionnaire. Sixty-six students responded to the questionnaire.

RESULTS

Cronbach's alpha surpassed 0.7 for perceived usefulness, perceived ease of use, perceived behavioral control, and subjective norm. Attitude and behavioural intention reported Cronbach's alpha values less than 0.7. Spearman's correlation coefficient was significant for all the constructs. Perceived ease of use explained 49%, 33%, and 42% of the variance of perceived usefulness (R² = 0.49), attitude (R² = 0.33), and perceived behavioral control (R² = 0.42) respectively. Perceived usefulness explained 25%, 18%, and 23% of the variance of attitude (R² = 0.25), behavioral intention (R² = 0.18), and perceived behavioral control (R² = 0.23) respectively. Attitude accounted for 25%, 33%, and 29% of the variance of behavioral intention (R² = 0.25), perceived behavioral control (R = 0.33), and subjective norm (R = 0.29) respectively.

CONCLUSION

The fully guided VIPS was acceptable by dental students specifically because of its usability. This makes VIPS a very effective tool for teaching implantology for dental students. VIPS also allows students to perform multiple repetitions of the implant planning procedure which enhances understanding and content retention.

Designing an E-learning Readiness Assessment Model for Iraqi Universities Employing Fuzzy Delphi Method

The assessment process of readiness for adoption an educational system considers the lifeblood of the e-learning system in a particular educational organization and the ability to assess the organization's readiness among the main factors which contributes to the success and progress. The readiness models are instruments that assist educational organizations in measuring their capability level and identifying the gaps to develop a strategy for implementing and adopting e-learning system. Due to the sudden chaos that Iraqi educational institutions have been exposed to the Covid-19 epidemic since the beginning of 2020, the e-learning system has been adopted as a quick alternative educational system for the continuation of the educational process without taking into consideration the readiness of the basic components of the educational process, which comprises the readiness of the infrastructure, human and educational organization to adopt such systems. Despite increased attention by stakeholders and the government with the readiness assessment process recently, there is no comprehensive model for assessing e-learning readiness in Iraqi higher education institutions, the purpose of this study is to design a model of an e-learning readiness assessment for Iraqi universities based on the comparative studies and the experts' views. It is worth to mention that the proposed model has objectively designed according to particular features and local characteristics country. The fuzzy delphi method was utilized for the validation process of the proposed model. The main dimensions and all factors of the proposed model reached the experts' agreement except a number of measures that did not achieve the assessment requirements. The final analysis result indicates that the e-learning readiness assessment model includes 3 main dimensions and 13 factors with 86 measures. Iraqi higher educational institutions can employ the designed model to assess their readiness and identify the areas that need improvement and reduce the gaps failures in e-learning adoption.

Effects of Time Pressure, Reward, and Information Involvement on User Management of Fake News on a Social Media Platform

This study examined the effects of time pressure, reward, and information involvement on individual fact-checking behavior within a social media platform. We used a four-factor mixed-design experiment to examine fact-checking performances of 144 participants for 36 ambiguous social platform statements, all of which were news statements of social events or of common-sense knowledge collected from the internet and selected through pre-test screening. We measured the participants' total number of fact-checked statements and their judgment accuracy of those statements. We also measured participants' decision time for making judgments, and their judgment confidence levels. Participants' social presence, time pressure, and information involvement were significantly related to the number of statements they fact-checked. Their perceived social presence on a social media platform reduced their fact-checking. Time pressure increased the frequency of fact-checking and weakened the impact of social presence. Participants were less likely to fact-check statements when they had high involvement with the information, due to overconfidence. Statements with high information involvement had longer decision-making times. These findings provide a basis for designing ways to display and push information to increase an individual's awareness of a need to fact-check ambiguous information in a new social media environment.

Unraveling the Influential Mechanisms of Social Commerce Overloads on User Disengagement: The Buffer Effect of Guanxi

Purpose

Although user engagement has been paid increasing attention, the work on user disengagement is scarce, and little is understood about how overloads elicited by excessive social commerce activities affect user disengagement. Based on the stimulus-organism-response (SOR) framework and psychological reactance theory (PRT), the authors aimed to investigate the effects of social commerce overloads (SCOs) on user disengagement, its influential mechanism, and the buffer effect of guanxi.

Participants and Methods

The authors conducted an online survey to collect the data and then examined our theoretical model and hypotheses. This study employed SPSS 20.0 software and Amos 24.0 software to examine the hypothesized relationships and the model.

Results

Social commerce overloads (ie, information overload (IO), social overload (SO), and communication overload (CO)) positively impact reactance via inferences of manipulative intent (IMI) and compulsive perception (CP); IMI and CP positively influence reactance; IMI, CP, and reactance positively affect user disengagement (ie, neglecting behavior and blocking behavior); guanxi has the buffer effect on the relationship between IMI (CP) and user disengagement, negatively moderates the impacts of IMI on user disengagement (ie, neglecting behavior and blocking behavior), and negatively moderates the effects of CP on blocking behavior but not neglecting behavior.

Conclusion

The findings of this study contribute to the literature on PRT and user disengagement by displaying the effects of excessive social commerce activities on user disengagement and uncovering the buffer effect of guanxi, which can help social e-commerce practitioners better reduce the negative effect of social commerce overloads.

Virtual Leadership and Nurses' Psychological Stress during COVID-19 in the Tertiary Hospitals of Pakistan: The Role of Emotional Intelligence

Although intelligence has been widely examined in the literature, the correlation of emotional intelligence (EI) has with virtual leadership, work stress, work burnout, and job performance in the nursing profession needs further consideration. Prior studies have confirmed that leadership style and emotional intelligence massively contribute to better outcomes in the nursing profession. Based on these confirmations, this research intended to explore the impact of virtual leadership and EI on work stress, work burnout, and job performance among nurses during the COVID-19 pandemic. A convenient sampling technique was adopted to select the data sample. To analyze our hypotheses, 274 self-reported surveys were distributed in five tertiary hospitals in Pakistan through a cross-sectional quantitative research design. The hypotheses were tested with SmartPLS-3.3.9. Our findings revealed that virtual leadership and EI have considerably influenced nurses' work stress, burnout level, and job performance. The study concludes that EI significantly moderates virtual leadership and psychological stress among nurses.

Use of locum doctors in NHS trusts in England: analysis of routinely collected workforce data 2019-2021

OBJECTIVES

Temporary doctors, known as locum doctors, play an important role in the delivery of care in the National Health Service (NHS); however, little is known about the extent of locum use in NHS trusts. This study aimed to quantify and describe locum use for all NHS trusts in England in 2019-2021.

SETTING

Descriptive analyses of data on locum shifts from all NHS trusts in England in 2019-2021. Weekly data were available for the number of shifts filled by agency and bank staff and the number of shifts requested by each trust. Negative binomial models were used to investigate the association between the proportion of medical staffing provided by locums and NHS trust characteristics.

RESULTS

In 2019, on average 4.4% of total medical staffing was provided by locums, but this varied substantially across trusts (25th-75th centile=2.2%-6.2%). Over time, on average two-thirds of locum shifts were filled by locum agencies and a third by trusts' staff banks. On average, 11.3% of shifts requested were left unfilled. In 2019-2021, the mean number of weekly shifts per trust increased by 19% (175.2-208.6) and the mean number of weekly unfilled shifts per trust increased by 54% (32.7 to 50.4). Trusts rated by the Care Quality Commission (CQC) as inadequate or requiring improvement (incidence rate ratio=1.495; 95% CI 1.191 to 1.877), and smaller trusts had a higher use of locums. Large variability was observed across regions for use of locums, proportion of shifts filled by locum agencies and unfilled shifts.

CONCLUSIONS

There were large variations in the demand for and use of locum doctors in NHS trusts. Trusts with poor CQC ratings and smaller trusts appear to use locum doctors more intensively compared with other trust types. Unfilled shifts were at a 3-year high at the end of 2021 suggesting increased demand which may result from growing workforce shortages in NHS trusts.

Does Preferred Information Format Affect Consumers' Willingness to Pay: A Case Study of Orange Juice Produced by Biotechnology

People who received a more personally relevant message were motivated to pay closer attention to the information and actively process it, which ultimately may stimulate behavioral changes. Therefore, preferred information content has been used in many disciplines to promote effective communication. However, no study has explored the impact of preferred information formats (e.g., word, infographic, and video) concerning food production. With the increasing application of biotechnology to food production, a complex topic to communicate, and evidence that consumers were willing to pay less for bioengineered foods, efficient communication was important to impact consumer preferences. The results of this study showed that consumers mostly preferred information format is writing. Providing information in video format did improve consumers' trust in information about food biotechnology. However, receiving information in consumers' preferred formats did not significantly change consumers' WTP for genetically engineered orange juice.

Chatbots and messaging platforms in the classroom: An analysis from the teacher's perspective

Messaging platforms are applications, generally mediated by an app, desktop program or the web, mainly used for synchronous communication among users. As such, they have been widely adopted officially by higher education establishments, after little or no study of their impact and perception by the teachers. We think that the introduction of these new tools and the opportunities and challenges they have needs to be studied carefully in order to adopt the model, as well as the tool, that is the most adequate for all parties involved. We already studied the perception of these tools by students, in this paper we examine the teachers' experiences and perceptions through a survey that we validated with peers, and what they think these tools should make or serve so that it enhances students learning and helps them achieve their learning objectives. The survey has been distributed among tertiary education teachers, both in universitary and other kind of tertiary establishments, based in Spain (mainly) and Spanish-speaking countries. We have focused on collecting teachers' preferences and opinions on the introduction of messaging platforms in their day-to-day work, as well as other services attached to them, such as chatbots. What we intend with this survey is to understand their needs and to gather information about the various educational use cases where these tools could be valuable. In addition, an analysis of how and when teachers' opinions towards the use of these tools varies across gender, experience, and their discipline of specialization is presented. The key findings of this study highlight the factors that can contribute to the advancement of the adoption of messaging platforms and chatbots in higher education institutions to achieve the desired learning outcomes.

Factors influencing loyalty to online health consultation platform: a cross-strait cultural perspective

BACKGROUND

The geographical, cultural, and linguistic proximity between Taiwan and Mainland China has facilitated rapid growth of cross-strait interactions. Both countries have developed online health consultation platforms on the Internet for the public to access healthcare related information. This study examines factors that influence loyalty to a specific online health consultation platform (OHCP) from a cross-strait perspective.

METHODS

Based on the Expectation Confirmation Theory and the combined Trust, Perceived Health Risks and Culture, we examine factors that influence loyalty to OHCPs among cross-strait users by investigating the roles of trust, perceived health risks, and culture. Data was collected through a questionnaire survey.

RESULTS

The research models used provide a high-power explanation of loyalty to OHCPs. Results generally align with those of previous studies, with the exception of the relationships between Perceived Health Risks and Perceived Usefulness, Perceived Usefulness and Loyalty, Confirmation and Satisfaction, and Trust and Loyalty. In other words, culture may have moderated these relationships.

CONCLUSIONS

Findings can help promote OHCPs among cross-strait users to make things easier for patients, and further reduce the load on the emergency department, especially in view of the still ongoing issues related to global outbreak of Coronavirus disease by facilitating early detection of potential cases.

Social informedness and investor sentiment in the GameStop short squeeze

We examine investor behavior on social media platforms related to the GameStop (GME) short squeeze in early 2021. Individual investors stimulated the stock market via Reddit social posts in the presence of institutional investors who bet against GME's success as short sellers. We analyzed r/WallStreetBets subreddit posts related to GME's trading patterns. We performed text-based sentiment analysis and compared the social informedness of posting users for GME trading on two social media platforms. The short squeeze occurred due to coordinated trading by individual investors, who discussed trading strategies on the platforms and drove collective social informedness-based trading behavior. Our findings suggest that the valence and number of submissions influenced GME's intraday transaction volumes and precursors for irrational trading behavior patterns to have emerged. We provide a theoretical interpretation of what occurred and call for tighter monitoring of social news platforms. We also encourage effort to create an in-depth understanding of the observed patterns and the linkages between them and the larger equity markets.

What drives the adoption of online health communities? An empirical study from patient-centric perspective

BACKGROUND

Online health communities (OHCs) provide platforms for patients to seek advice from physicians and receive professional suggestions online. It can improve the efficiency of patients' diagnosis of simple diseases and alleviate hospital congestion. However, few empirical studies have comprehensively explored the factors influencing patients' intention to use OHCs through objective data. This study aims to fill this gap by identifying key factors that influence patients' acceptance of OHCs and proposing effective ways to promote the applications of OHCs in China.

METHODS

Based on the Unified Theory of Acceptance and Usage of Technology (UTAUT), extended with additional constructs identified with patients' information demands in OHCs, this study developed a research model and proposed nine hypotheses. An online survey involving 783 valid responses was conducted in China to collect data to validate the proposed model. Confirmatory factor analysis and partial least squares (PLS) path model were conducted for instrument validation and hypothesis testing.

RESULTS

Price value, eHealth literacy, and performance expectancy are the most prominent constructs in the study context. Interestingly, relation quality was also found to have a significant positive relationship with behavioral intention.

CONCLUSIONS

Based on these findings, OHC operators need to create a user-friendly platform, improve information quality, set reasonable prices, and establish consummate security systems. Physicians and related organizations can raise awareness and assist patients in developing the skills to appropriately comprehend and utilize information in OHCs. This study contributes to both technology adoption theory and practice.

Exploring the Impact of Time Spent Reading Product Information on E-Commerce Websites: A Machine Learning Approach to Analyze Consumer Behavior

In this study, we aim to investigate the influence of the time spent reading product information on consumer behavior in e-commerce. Given the rapid growth of e-commerce and the increasing importance of understanding online consumer behavior, our research focuses on gaining a deeper understanding of customer navigation on e-commerce websites and its effects on purchasing decisions. Recognizing the multidimensional and dynamic nature of consumer behavior, we utilize machine learning techniques, which offer the capacity to handle complex data structures and reveal hidden patterns within the data, thereby augmenting our comprehension of underlying consumer behavior mechanisms. By analyzing clickstream data using Machine Learning (ML) algorithms, we provide new insights into the internal structure of customer clusters and propose a methodology for analyzing non-linear relationships in datasets. Our results reveal that the time spent reading product-related information, combined with other factors such as bounce rates, exit rates, and customer type, significantly influences a customer's purchasing decision. This study contributes to the existing literature on e-commerce research and offers practical implications for e-commerce website design and marketing strategies.

A Study of Reasons for Self-Disclosure on Social Media among Chinese COVID-19 Patients: Based on the Theory of Planned Behavior Model

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.

Examining retweeting behavior on social networking sites from the perspective of self-presentation

On social networking sites, people can express themselves in a variety of ways such as creating personalized profiles, commenting on some topics, sharing their experiences and thoughts. Among these technology-enabled features, retweeting other-sourced tweet is a powerful way for users to present themselves. We examine users' retweeting behavior from the perspective of online identity and self-presentation. The empirical results based on a panel dataset crawled from Twitter reveal that, people are prone to retweet topics they are interested in and familiar with, in order to convey a consistent and clear online identity. In addition, we also examine which user groups exhibit a stronger propensity for a clear online identity, considering the practical value of these users to both social media platforms and marketers. By integrating self-presentation theory with social influence theory and social cognitive theory, we propose and confirm that users with higher value in online self-presentation efficacy and users who are more involved with the social media platform have a stronger than average propensity to maintain a consistent online identity, and thus are more likely to retweet familiar topics. These users are characterized by (1) owning a larger number of followers, (2) authoring longer and more original tweets than average, (3) being active in retweeting other-sourced posts. This study contributes to our understanding of SNS users' retweeting behavior and adds to the emerging line of research on online identity. It also provides insights on how microblogging service providers and enterprises can promote people's retweeting behavior.

Scenario-feature identification from online reviews based on BERT

Scenario endows a product with meanings. It has become the key to win the competition to design a product according to specific usage scene. Traditional scenario identification and product feature association methods have disadvantages such as subjectivity, high cost, coarse granularity, and limited scenario can be identified. In this regard, we propose a BERT-based scenario-feature identification model to effectively extract the information about users' experience and usage scene from online reviews. First, the scenario-feature identification framework is proposed to depict the whole identification process. Then, the BERT-based scene-sentence recognition model is constructed. The Skip-gram and word vector similarity methods are used to construct the scene and feature lexicon. Finally, the triad is constructed through the analysis of scene-feature co-occurrence matrix, which realizes the association of scenario and product features. This proposed model is of great practical value for product developers to better understand customer's requirements in specific scenarios. The experiments of scenario-feature identification from the reviews of Pacific Auto verifies the effectiveness of this method.

Increasing clinical medical service satisfaction: An investigation into the impacts of Physicians' use of clinical decision-making support AI on patients' service satisfaction

BACKGROUND

The medical industry is one of the key industries for the application of artificial intelligence (AI). Although it is believed that the combination of CDSS and physicians could improve the medical service, there are still many concerns about the usage of CDSS. Based on these concerns, limited studies have answered the question that when a physician makes decision independently or with AI's help, will there be any differences in patients' satisfaction with the medical service?

METHODS

This study uses the service fairness theory as a theoretical lens and employs three vignette experiments to address this research gap. There are totally 740 subjects recruited to participate into the three experiments. Group comparison methods and structural equation model are used to verify the hypotheses.

RESULTS

The experimental results reveal that: (1) physicians using AI can reduce patients' service satisfaction (M_difference=0.404,p=0.004); (2) the negative relationship between AI usage and service satisfaction can partially be mediated through distributive fairness and procedural fairness; (3) physicians actively informing their patients about the usage of AI can help mitigate the reduction in service satisfaction (M_difference=0.400,p=0.003) and three types of fairness M_difference^distributive=0.307,p=0.042;M_difference^procedural=0.483,p<0.001;M_difference^{interactional}=0.253,p=0.027.

CONCLUSION

This study investigates the effect of physicians using decision-making support AI on their patients' service satisfaction. These results contribute to the existing literature pertaining to AI and fairness theory, and also help in formulating some practical suggestions for medical staff and AI development companies.

Exploring Factors and Impact of Blockchain Technology in the Food Supply Chains: An Exploratory Study

Blockchain technology (BCT) has been proven to have the potential to transform food supply chains (FSCs) based on its potential benefits. BCT promises to improve food supply chain processes. Despite its several benefits, little is known about the factors that drive blockchain adoption within the food supply chain and the impact of blockchain technology on the food supply chain, as empirical evidence is scarce. This study, therefore, explores factors, impacts and challenges of blockchain adoption in the FSC. The study adopts an exploratory qualitative interview approach. The data consist of Twenty-one interviews which were analyzed using thematic analysis techniques in NVivo (v12), resulting in identifying nine factors classified under three broad categories (Technology-complexity, compatibility, cost; Organization-organization size, knowledge; Environment-government support, competitive pressure, standardization, and compliance) as the most significant factors driving blockchain adoption in the FSC. In addition, five impacts were identified (visibility, performance, efficiency, trust, and value creation) to blockchain technology adoption. This study also identifies significant challenges of blockchain technology (interoperability, privacy, infrastructure conditions, and lack of knowledge). Based on the findings, the study developed a conceptual framework for blockchain adoption in food supply chains. The study adds to the corpus of knowledge by illuminating the adoption of blockchain technology and its effects on food supply chains and by giving the industry evidence-based guidance for developing its blockchain plans. The study provides full insights and awareness of blockchain adoption challenges among executives, supply chain organizations, and governmental agencies.

Measuring digital capital in Italy

Introduction

This paper aims to theoretically and empirically investigate the concept of digital capital in the Italian context. Digital Capital can be conceived as independent individual capital whose lack within a population can be a cause of digital inequality. Our paper draws from recent works that have measured the Digital Capital as a combination of digital access and digital competences, and have tested this operational definition through an online survey on a UK sample. The results of such research proved the construct validity of the operational definition, thus showing that Digital Capital could be empirically measured. However, a measurement model needs to be tested and validated over time and in different socio-cultural contexts in order to be refined and strengthened, and eventually disseminated on a large scale.

Method

This is the reason why this paper will show the results of a funded research project (named DigiCapItaly) carried out to test the validity of the Digital Capital measure in a different country, i.e., Italy. The data were collected with an online survey using a representative sample (by age, gender and geographical area) of individuals living in Italy aged 18 years or more. The creation of a composite index to measure Digital Capital followed a two-stage Principal Component Analysis approach.

Results

First, the paper provides a methodological framework for facing challenges and pitfalls in operationalizing and assessing a complex concept in social research. Secondly, results show that Digital Capital operational definition works in Italy as well as in the UK, thus legitimizing its recognition as an independent capital.

Knowledge transfer between physicians from different geographical regions in China's online health communities

Online Health Communities (OHCs) are a type of self-organizing platform that provide users with access to social support, information, and knowledge transfer opportunities. The medical expertise of registered physicians in OHCs plays a crucial role in maintaining the quality of online medical services. However, few studies have examined the effectiveness of OHCs in transferring knowledge between physicians and most do not distinguish between the explicit and tacit knowledge transferred between physicians. This study aims to demonstrate the cross-regional transfer characteristics of medical knowledge, especially tacit and explicit knowledge. Based on data collected from 4716 registered physicians on Lilac Garden (DXY.cn), a leading Chinese OHC, Exponential Random Graph Models are used to (1) examine the overall network and two subnets of tacit and explicit knowledge (i.e., clinical skills and medical information), and (2) identify patterns in the knowledge transferred between physicians, based on regional variations. Analysis of the network shows that physicians located in economically developed regions or regions with sufficient workforces are more likely to transfer medical knowledge to those from poorer regions. Analysis of the subnets demonstrate that only Gross Domestic Product (GDP) flows are supported in the clinical skill network since discussions around tacit knowledge are a direct manifestation of physicians' professional abilities. These findings extend current understanding about social value creation in OHCs by examining the medical knowledge flows generated by physicians between regions with different health resources. Moreover, this study demonstrates the cross-regional transfer characteristics of explicit and tacit knowledge to complement the literature on the effectiveness of OHCs to transfer different types of knowledge.

Formation mechanism of consumers' purchase intention in multimedia live platform: a case study of taobao live

The rapid development of live e-commerce in China in recent years has been accompanied by a change in consumer shopping behavior and a general upgrading of consumption in China. The rise and development of e-commerce live shopping mainly stem from the fact that the multimedia live stream provides consumers with a different shopping experience. Based on this, this paper outlines the meaning and application of multimedia, introduces the application of multimedia technology in live e-commerce platforms, constructs a model of the influence of visibility, authenticity, and interactivity of live platforms on consumers' purchase intention, and explores the role of trust in influencing both, using a questionnaire survey for empirical research. The results show that the characteristics of visibility, authenticity, and interactivity have significant positive effects on consumers' purchase intentions, and that trust partially mediates the relationship between the three characteristics of the live streaming platform and consumers' purchase intentions. In summary, the results of this study not only explore the formation mechanism of consumers' purchase intention from the perspective of the characteristics of multimedia e-commerce live streaming platforms, but also provide developers with further improvement ideas for the design of e-commerce live streaming platforms.

Antecedents of Compliance Intention and Its Impact on Waste Separation Behavior: Based on Rational Choice Theory and Deterrence Theory

With the rapid growth of the urban population, the development of production and consumption, and improved living standards, waste generation has increased over time. The first positive step to solve the problem of household waste is waste separation behavior. Studying the determinants that prompt individuals to comply with waste separation policy (WSP) is worthwhile. The author aims to offer an integrated view of individuals' compliance with waste separation policy based on rational choice and deterrence theories. Survey data collected from 306 households in South Korea are used to test the research model using partial least squares analysis. The study shows that WSP compliance intention is motivated by the perceived benefit and perceived effectiveness of WSP. Furthermore, the results show that perceived deterrent severity and perceived deterrent certainty positively influence WSP compliance intention. The implications for theory and policymakers are discussed to facilitate waste separation behavior.

Switching from offline to online health consultation in the post-pandemic era: the role of perceived pandemic risk

Introduction

Due to its effectiveness and various benefits, the use of online health consultation (OHC) has dramatically increased in recent years, especially since the outbreak of the COVID-19 pandemic. However, underlying mechanism whereby the pandemic impacted OHC usage is still unclear.

Methods

Via an online survey (N=318), the present paper measures the users' perceptions towards both offline and online services, their intention to switch to OHC, and the perceived pandemic risks. The relationships among these factors are conceptualized by the push-pull-mooring framework, and tested via structural equation modelling.

Results

Dissatisfaction with offline service (process inefficiency and consultation anxiety), the attractiveness of OHC (perceived benefits and perceived ease of use), and users' behavioral inertia (switching cost and habit) jointly influence the intention to switching to OHC. The significant role of the perceived pandemic risk of going to medical facilities is particularly addressed. On the one hand, the perceived pandemic risk is found with an indirect impact on the switching intention by enlarging the dissatisfaction with offline service and the attractiveness of OHC. On the other hand, a high perceived pandemic risk induces more actual switching behavior and also amplifies the transition from switching intention to behavior.

Discussion

The study provides novel insights into the understanding of OHC usage in the post-pandemic era, and also informs medical facilities, OHC platforms, and policymakers on managing and balancing the online and offline healthcare provision.

Exploring the Influential Factors of Personal Media Bloggers on Followers' Continuous Following Intention Based on Relationship Marketing Theory

The use of personal media has become increasingly popular in recent years. However, gaining and retaining followers has become increasingly challenging, given the fierce competition among bloggers and the constant changes in personal media. In this context, this study aims to explore the factors that influence followers' continued usage intentions toward personal media bloggers and strategies to improve their loyalty. Drawing upon the theory of relationship marketing, a structural model is constructed to examine the impacts and mechanisms of personal media bloggers' attributes and communication on social presence, fanship, intention to use, and word of mouth. This research focuses on two dimensions of personal media bloggers' attributes: expertise and attractiveness. A sample of 155 highly active personal media users in China was collected through a questionnaire for analysis and validation. The findings reveal that expertise and communication have positive impacts on followers' intentions to continue following a blogger, while attractiveness has a significant, positive, and direct impact on word of mouth. Furthermore, this study shows that social presence and fanship play mediating roles in the effects of expertise and communication on followers' usage intentions and word of mouth. The research results provide valuable insights for personal media operators and marketers seeking to improve followers' loyalty and encourage potential users to become more loyal fans.

Immersive and desktop virtual reality in virtual fashion stores: a comparison between shopping experiences

With the high growth and prosperity of e-commerce, the retail industry needs to explore new technologies that improve digital shopping experiences. In the current technological scenario, Virtual Reality (VR) emerges as a tool and an opportunity for enhancing shopping activities, especially for the fashion industry. This study explores whether using Immersive Virtual Reality (IVR) technologies enhances the shopping experience in the fashion industry compared to Desktop Virtual Reality (DVR). A within-subject experiment was carried out involving a sample of 60 participants who completed a simulated shopping experience. In the first mode (DVR), a desktop computer setup was used to test the shopping experience using a mouse and keyboard for navigation. The second mode (IVR) exploited a Head-Mounted Display (HMD), and controllers, that allowed navigation while seated on a workstation to avoid sickness. Participants had to find a bag in the virtual shop and explore its features until they were ready to purchase it. Post-hoc measures of time duration of the shopping experience, hedonic and utilitarian values, user experience, and cognitive load were compared. Results showed that participants experienced higher hedonism and utilitarianism in the IVR shop compared to DVR. The cognitive load was comparable in both modes, while user experience was higher in IVR. In addition, the time duration of the shopping experience was higher in IVR, where users stayed immersed and enjoyed it for longer. This study has implications for fashion industry research, as the use of IVR can potentially lead to novel shopping patterns by enhancing the shopping experience.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10055-023-00806-y.

Centre assessment grades in 2020: a natural experiment for investigating bias in teacher judgements

The COVID-19 pandemic meant that, in 2020, students in England were unable to sit their examinations and instead received predicted grades, or "centre assessment grades" (CAGs), from their teachers to allow them to progress. Using the Grading and Admissions Data for England (GRADE) dataset for students from 2018 to 2020, this study treats the use of CAGs as a natural experiment for causally understanding how teacher judgements of academic ability may be biased according to the demographic and socio-economic characteristics of their students. A variety of machine learning models were trained on the 2018-19 data and then used to generate predictions for what the 2020 students were likely to have received had their examinations taken place as usual. The differences between these predictions and the CAGs that students received were calculated and then averaged across students' different characteristics, revealing what the treatment effects of the use of CAGs were likely to have been for different types of students. No evidence of absolute negative bias against students of any demographic or socio-economic characteristic was found, with all groups of students having received higher CAGs than the grades they were likely to have received had they sat their examinations. Some evidence for relative bias was found, with consistent, but insubstantial differences being observed in the treatment effects of certain groups. However, when higher-order interactions of student characteristics were considered, these differences became more substantial. Intersectional perspectives which emphasise interactions and sub-group differences should be used more widely within quantitative educational equalities research.

Factors affecting students' online courses learning behaviors

Online course learning is an important part of higher education curriculum. However, the factors influencing college students' online course learning behavior are poorly understood. The purpose of this study is to analyze the factors affecting college students' online course learning behavior. This study integrated the Information System Success Model, the Technology Acceptance Model, and Self-efficacy Theory to construct an online course learning acceptance model. A total of 308 college students participated from China filled out the questionnaire, and 18 of them also participated in a semi-structured interview. The structural equation model was used to analyze the research data. The empirical analysis showed that self-efficacy has a positive impact on perceived usefulness and perceived ease-of-use; Perceived usefulness, attitude, system quality, and information quality affect users' behavioral intentions positively; Perceived ease of use has a positive effect on users' attitudes and perceived usefulness; and perceived usefulness has a direct effect on users' attitudes; Furthermore, behavioral intention can predict the actual use of online courses by college students. In addition, we will discuss these results and provide recommendations. This study provides a theoretical basis for the study of online course learning acceptance and extends the technology acceptance model. The research can provide inspiration for the design of online course learning and the decision-making of management institutions, and contribute to the sustainable development of education.

Toward the validation of VR-HMDs for medical education: a systematic literature review

The latest technological advancements in the domain of virtual reality (VR) have created new opportunities to use VR as a training platform for medical students and practitioners more broadly. Despite the growing interest in the use of VR as a training tool, a commonly identified gap in VR-training for medical education is the confidence in the long-term validity of the applications. A systematic literature review was undertaken to explore the extent of VR (in particular head-mounted displays) applications for medical training with an additional focus on validation measures. The papers included in this review discussed empirical case studies of specific applications; however, these were mostly concerned with human-computer interaction and were polarized between demonstrating that a conceptual technology solution was feasible for simulation or looked at specific areas of VR usability with little discussion on validation measures for long-term training effectiveness and outcomes. The review uncovered a wide range of ad hoc applications and studies in terms of technology vendors, environments, tasks, envisaged users and effectiveness of learning outcomes. This presents decision-making challenges for those seeking to adopt, implement and embed such systems in teaching practice. The authors of this paper then take a wider socio-technical systems perspective to understand how the holistic training system can be engineered and validated effectively as fit for purpose, through distillation of a generic set of requirements from the literature review to aid design specification and implementation, and to drive more informed and traceable validation of these types of systems. In this review, we have identified 92 requirement statements in 11 key areas against which a VR-HMD training system could be validated; these were grouped into design considerations, learning mechanisms and implementation considerations.

Adopting AI: how familiarity breeds both trust and contempt

Despite pronouncements about the inevitable diffusion of artificial intelligence and autonomous technologies, in practice, it is human behavior, not technology in a vacuum, that dictates how technology seeps into-and changes-societies. To better understand how human preferences shape technological adoption and the spread of AI-enabled autonomous technologies, we look at representative adult samples of US public opinion in 2018 and 2020 on the use of four types of autonomous technologies: vehicles, surgery, weapons, and cyber defense. By focusing on these four diverse uses of AI-enabled autonomy that span transportation, medicine, and national security, we exploit the inherent variation between these AI-enabled autonomous use cases. We find that those with familiarity and expertise with AI and similar technologies were more likely to support all of the autonomous applications we tested (except weapons) than those with a limited understanding of the technology. Individuals that had already delegated the act of driving using ride-share apps were also more positive about autonomous vehicles. However, familiarity cut both ways; individuals are also less likely to support AI-enabled technologies when applied directly to their life, especially if technology automates tasks they are already familiar with operating. Finally, we find that familiarity plays little role in support for AI-enabled military applications, for which opposition has slightly increased over time.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00146-023-01666-5.

Curbing vehicular urban pollution in China: Investigating the usage intentionof public electric buses

Public electric bus (PEB) usage remains critical in reducing carbon emissions, traffic congestion, energy consumption, resource exhaustion, and environmental pollution. PEB usage revolves around consumer acceptance, and assessing the psychological factors accounting for using PEBs is essential in mitigating these challenges for a sustainable environment. The study extends the reasoned action theory (TRA) with environmental awareness, convenience, and personal norms in investigating residents' intention to use electric buses in Nanjing, China. 405 responses were gathered through an online survey and evaluated using Structural Equation Modeling (SEM). Statistical analysis showed that the structural model (66.4%) explained public electric bus use better than the original TRA model (20.7%). Attitude, subjective norms, personal norms, environmental awareness, and convenience directly influenced the intention to use PEBs. Personal norms related to attitude positively. Environmental awareness related to personal norms in PEB use. Subjective norms partially mediated the impact of personal norms on the intention to use PEBs. Convenience moderated the interaction between personal norms and intention to use PEBs. Respondents differed in income level, educational level, and employment but not gender in their inclinations to use PEBs. The current study recommends potent policy implications to enhance and ensure the maximum use of PEBs.

Messaging strategies for communicating health-related information in social media-a content and effectiveness analysis of organ donation posts on Instagram in Germany

BACKGROUND

Although organ transplantation is a very effective clinical solution to save the lives of patients suffering from organ failure, the supply of donated organs still cannot meet its growing demand. Educating the society about organ donation is a critical success factor in increasing donation rates, especially in countries that require potential donors to proactively register and opt-in (e.g., Germany). While social media has emerged as an effective tool for disseminating health information, recent evidence suggests that published organ donation content (both online and offline), aimed at raising awareness, still lacks effectiveness. To develop recommendations for optimizing organ donation messaging via social media, this study not only examines the current state of organ donation communication on Instagram, but also identifies factors that contribute to message effectiveness.

METHODS

We conducted a retrospective content analysis to in-depth assess organ donation-related content published on Instagram in Germany between January and March 2022. Systematic coding allowed to identify common themes, sentiments, and communication strategies, which were analyzed for their effectiveness using linear regression analyses.

RESULTS

Of the 500 organ donation posts, 57% were published by institutional authors while the remainder was shared by private accounts. Most content was aimed at the general population and shared neutral (80%) or positive sentiments (17%). Transformative messages, positive emotions, posts published by the transplant recipient and the image of a human served as predictors for post effectiveness measured in terms of likes (p < 0.001) and comments (p < 0.01). Sharing personal experiences (p < 0.01) and highlighting the meaning of organ donations (p < 0.05) resulted in significantly higher audience engagement than any other topic discussed.

CONCLUSION

Our findings highlight the need for health officials to work closely with organ transplant recipients to publicly advocate for organ donations by sharing personal and transformative messages. The high share of posts published by transplant recipients indicates a certain openness to share personal experiences with broad audiences. Different message characteristics served as predictors for message effectiveness (i.e., increased audience engagement) which can likely be extrapolated to other health-related use cases (e.g., cancer screening).

Teaching after the pandemic: The role of technostress and organizational support on intentions to adopt remote teaching technologies

The ongoing COVID-19 pandemic has led to several changes in academic teaching practices. Although educational digital technologies have been crucial during the initial phases of the pandemic, their forced adoption has led to negative consequences. In the present study, we aimed to integrate the Technology Acceptance Model theoretical framework (Davis, 1989) by exploring the effects of some possible factors that influence the willingness to adopt digital learning tools in the future when the pandemic is over. Among them, technostress was considered one of the external factors that could have adversely affected digital teaching technology adoption in the future. In contrast, the perception of technical support offered by the university was considered a potential protective factor. A total of 463 Italian university faculty completed an online questionnaire at the end of the first semester (a.y. 2020-21). The frequency of distance teaching technologies usage behavior was measured objectively by extracting teachers' activities from the University's e-learning databases. Key findings indicated that distance teaching technologies' frequency of use increased technostress, which in turn negatively impacted the perception of ease of use. The latter influences - both directly and indirectly through perceived usefulness - the intentions to adopt distance learning tools after the pandemic. Organizational support negatively predicted technostress. Implications to help public institutions develop functional strategies to cope with the technological changes brought by the pandemic are discussed.

A review on individual and multistakeholder fairness in tourism recommender systems

The growing use of Recommender Systems (RS) across various industries, including e-commerce, social media, news, travel, and tourism, has prompted researchers to examine these systems for any biases or fairness concerns. Fairness in RS is a multi-faceted concept ensuring fair outcomes for all stakeholders involved in the recommendation process, and its definition can vary based on the context and domain. This paper highlights the importance of evaluating RS from multiple stakeholders' perspectives, specifically focusing on Tourism Recommender Systems (TRS). Stakeholders in TRS are categorized based on their main fairness criteria, and the paper reviews state-of-the-art research on TRS fairness from various viewpoints. It also outlines the challenges, potential solutions, and research gaps in developing fair TRS. The paper concludes that designing fair TRS is a multi-dimensional process that requires consideration not only of the other stakeholders but also of the environmental impact and effects of overtourism and undertourism.

Associations of technostressors at work with burnout symptoms and chronic low-grade inflammation: a cross-sectional analysis in hospital employees

OBJECTIVE

Despite the increasing scholarly interest in the phenomenon technostress, associated biological effects on employee health are under-researched. Chronic low-grade inflammation is suggested as a central pathway linking stress experience to disease development. The aim of this study was to assess associations of technology-related work stressors (technostressors) with low-grade inflammation and burnout symptoms.

METHODS

N = 173 (74.6% women, M_age = 31.0 years) university hospital employees participated in a cross-sectional study. Self-report questionnaires were used for the assessment of general psychosocial working conditions (work overload, job control, social climate), a range of different technostressors, burnout symptoms, and relevant confounders. Participants provided capillary blood samples, and high-sensitivity C-reactive protein (hs-CRP) as an inflammatory biomarker was analyzed from dried blood spots.

RESULTS

Based on a factor analysis, we identified four underlying dimensions of technostressors: techno- and information overload, techno-complexity, interruptions and multitasking as well as usability and technical support. In multivariate linear regressions, techno-/information overload and techno-complexity were associated with core (exhaustion, mental distance) and secondary (psychosomatic complaints) symptoms of burnout. Techno-/information overload was a significant predictor of burnout core symptoms, even when general work overload was controlled for. The technostressors were not associated with hs-CRP.

CONCLUSION

This is the first study on technology-related stress at work and chronic low-grade inflammation. The results suggest that (information) overload caused by digital technology use is a distinct work stressor with genuine consequences for psychological health. To what extent these effects also manifest on a physiological level needs to be subjected to future studies, ideally with prospective designs.

The Role of Platform Quality on Consumer Purchase Intention in the Context of Cross-Border E-Commerce: The Evidence from Africa

Africa, as one of the rapidly growing markets, presents a significant opportunity for cross-border e-commerce companies to penetrate their consumer market, which is in dire need of development. This study utilizes the Information System Success model to investigate the impact of cross-border e-commerce platform quality on consumers' purchase intentions. Additionally, the study identifies the role of perceived value and trust in the purchase process. Moreover, the moderating effect of consumer acculturation on the relationship between cross-border platform quality and perceived value is examined. A total of 446 valid responses were obtained through a questionnaire survey and analyzed using structural equations. The findings reveal that platform information quality, system quality, and service quality significantly enhance consumers' perceived value, thereby positively influencing their purchase intention. Furthermore, the results highlight the joint effect of perceived value and trust on purchase intention, and trust plays a mediating role in this relationship. The moderating effect of acculturation is also confirmed, indicating that it negatively moderates the impact of system and information quality on perceived value, while positively moderating the impact of service quality on perceived value. These findings complement and extend existing cross-border e-commerce research and provide valuable insights into the buying behavior of African consumers.