Patients' Intentions to Use Telemedicine for Ophthalmic Medical Care During the COVID-19 Pandemic

Background This study aimed to examine the factors predicting participants' intention to use telemedicine during the COVID-19 pandemic. Interest in health information technologies (HITs) has increased due to COVID-19. Most studies have focused on the acceptance of HIT by physicians and nurses, while there is a lack of studies on patients' perception and acceptance of such systems in ophthalmology. Methodology In the first year of the COVID-19 pandemic, a survey comprising 19 items was conducted at an ophthalmic center in Greece. The participants included 77 patients diagnosed with various eye diseases. The survey aimed to evaluate variables related to the Technology Acceptance Model (TAM), such as perceived usefulness, perceived ease of use, facilitating conditions, and intention to use telemedicine. The statistical analyses included intercorrelations, internal consistency reliability tests, and multiple linear regression analysis to examine the predictors of intention to use telemedicine. Results The multiple linear regression analysis revealed that perceived usefulness and facilitating conditions emerged as significant predictors of eye patients' intentions to use HIT. Interestingly, while perceived ease of use did not exhibit a significant predictive relationship with use intentions, the influence of perceived usefulness and facilitating conditions within the healthcare context underscores the pivotal role of perceived utility and external support in shaping patients' willingness to engage with HIT for eye care. Conclusions Empirical data on patient acceptance offer a better understanding of the limiting factors and the variables that facilitate intentions to use services that may improve medical diagnoses, patient communication, and treatment adherence processes. Related interventions and communication efforts should highlight the benefits of HIT in ophthalmology and provide the appropriate support and means to facilitate its use during and after the pandemic.

Acceptance and User Experiences of a Wearable Device for the Management of Hospitalized Patients in COVID-19-Designated Wards in Ho Chi Minh City, Vietnam: Action Learning Project

BACKGROUND

Wearable devices have been used extensively both inside and outside of the hospital setting. During the COVID-19 pandemic, in some contexts, there was an increased need to remotely monitor pulse and saturated oxygen for patients due to the lack of staff and bedside monitors.

OBJECTIVE

A prototype of a remote monitoring system using wearable pulse oximeter devices was implemented at the Hospital for Tropical Diseases in Ho Chi Minh City, Vietnam, from August to December 2021. The aim of this work was to support the ongoing implementation of the remote monitoring system.

METHODS

We used an action learning approach with rapid pragmatic methods, including informal discussions and observations as well as a feedback survey form designed based on the technology acceptance model to assess the use and acceptability of the system. Based on these results, we facilitated a meeting using user-centered design principles to explore user needs and ideas about its development in more detail.

RESULTS

In total, 21 users filled in the feedback form. The mean technology acceptance model scores ranged from 3.5 (for perceived ease of use) to 4.4 (for attitude) with behavioral intention (3.8) and perceived usefulness (4.2) scoring in between. Those working as nurses scored higher on perceived usefulness, attitude, and behavioral intention than did physicians. Based on informal discussions, we realized there was a mismatch between how we (ie, the research team) and the ward teams perceived the use and wider purpose of the technology.

CONCLUSIONS

Designing and implementing the devices to be more nurse-centric from their introduction could have helped to increase their efficiency and use during the complex pandemic period.

Internet-Enabled Behaviors in Older Adults During the Pandemic: Patterns of Use, Psychosocial Impacts, and Plans for Continued Utilization

In response to social distancing measures during the COVID-19 pandemic, there was a need to increase the frequency of internet enabled behaviors (IEBs). To date, little is known about how the pandemic impacted IEBs in older adults, a population that has historically been linked to lower digital literacy and utilization. We administered an online survey between April and July 2021 to 298 adults who were over age 50 (mean age = 73 years; 93.5% non-Hispanic white; 94% smart phone owners; 83.5% retired). Older adults self-reported IEBs for social, shopping, medical, and leisure activities during the pandemic, plans for continued use of these behaviors, and completed measures of psychosocial functioning. 66.8% of respondents reported an overall increase in IEBs during the pandemic, most notably for online meeting attendance. More frequent online meeting use was associated with less depression (r = -0.12, p = .04) and less loneliness (r = -0.14, p = .02). With regard to plans for continued use, 82.5% of the sample reported at least one IEB (M = 2.18, SD = 1.65) that they increased during the pandemic and planned to maintain over time (e.g., online shopping for household goods). Plans for continued use were more likely in participants who used IEBs more overall during the pandemic (r = 0.56, p < .001), and who frequently sought technical support on search engines (r = 0.22, p < .001), or online video sites (r = 0.16, p = .006). In summary, IEBs during the pandemic were associated with favorable psychosocial functioning and expectations for continued use in this sample of predominantly white older adults who had some baseline technological familiarity.

Analysis of the mediating effect of resistance to change, perceived ease of use, and behavioral intention to use technology-based learning among younger and older nursing students

BACKGROUND

To date, research has not examined the mediating mechanism of ease of use and emotional reaction on the short-term focus of resistance to change and behavior intention to participate in technology-based course activities.

OBJECTIVES

The study compares resistance to tech-based learning changes in younger and older nursing students and examines how ease of use and emotional reaction mediate between a short-term focus of resistance to change and intentional behavior to participate in technology-based course activities.

METHODS

The researcher recruited 218 nursing students from the School of Health Sciences for a cross-sectional survey. Participants voluntarily completed the online survey, consisting of four sections: perceived ease of use, behavioral intention to use technology, resistance to change scale, and background characteristics. The survey was analyzed using Model 6 via Process software, and ethical considerations such as informed consent and confidentiality were maintained.

RESULTS

The study found that younger nursing students had a more robust emotional response to changes in technology-enhanced learning, and older students were more cognitively rigid. The study also found statistically significant serial multiple mediations of emotional response and perceived ease of use in the relationship between short-term focus and intended behavior.

CONCLUSIONS

The study highlights the importance of considering learner diversity, including age, in designing technology-based learning programs and the role of ease of use and emotional reaction as mediating factors in determining students'' behavioral intention to participate. The findings contribute to the literature on inclusive education and the relationship between resistance to change, ease of use, and intention behaviors in technology-based learning.

Exploring the antecedents of AI adoption for effective HRM practices in the Indian pharmaceutical sector

Purpose: The aim of this research is to investigate the factors that facilitate the adoption of artificial intelligence (AI) in order to establish effective human resource management (HRM) practices within the Indian pharmaceutical sector. Design/methodology/approach: A model explaining the antecedents of AI adoption for building effective HRM practices in the Indian pharmaceutical sector is proposed in this study. The proposed model is based on task-technology fit theory. To test the model, a two-step procedure, known as partial least squares structural equational modeling (PLS-SEM), was used. To collect data, 160 HRM employees from pharmacy firms from pan India were approached. Only senior and specialized HRM positions were sought. Findings: An examination of the relevant literature reveals factors such as how prepared an organization is, how people perceive the benefits, and how technological readiness influences AI adoption. As a result, HR systems may become more efficient. The PLS-SEM data support all the mediation hypothesized by proving both full and partial mediation, demonstrating the accuracy of the proposed model. Originality: There has been little prior research on the topic; this study adds a great deal to our understanding of what motivates human resource departments to adopt AI in the pharmaceutical companies of India. Furthermore, AI-related recommendations are made available to HRM based on the results of a statistical analysis.

A contextual ICT model to explain adoption of mobile applications in developing countries: A case study of Tunisia

In Tunisia, agriculture is the main source of livelihood for more than 75% of small and subsistence farmers with minimal use of technology. The use of information and communication technology (ICT),such as mobile applications, represents a pertinent opportunity for these smallholders to access agricultural innovation and market information and improve their farming technologies and farm management. Thus, ICT can act as a replacement to foster access to innovation for this category of farmers. Unfortunately, the underuse of mobile applications has contributed to low and slow adoption of agricultural innovation and consequently the benefits of this technology have not been attained. The purpose of this study is to identify the factors affecting the adoption of Short Message Service (SMS) through a contextual ICT model for livestock, olive crop, and beekeeping. Data were collected from 200 small-scale beekeepers, 225 olive growers, and 140 livestock breeders selected in Jendouba, Kairouan, and Zaghouan in Tunisia. The objective of this paper is to examine the factors that influence mobile applications using the partial least squares structural equation modelling technique, for livestock, olive crop, and beekeeping agricultural activities. The results showed that the final ICT-induced structural models were highly predictive of the use of SMS and its increased adoption. Factors affecting the use of SMS differed according to the farming system. The major perceived factor affecting the use of SMS was 'observability' for livestock farmers, 'compatibility' for olive growers, and 'information quality' for beekeepers. Understanding these factors by taking into account the specificity of the agricultural activity leads to a better understanding of the adoption of ICT tools by smallholder farmers in Tunisia.

Assessing Health Students' Attitudes and Usage of ChatGPT in Jordan: Validation Study

BACKGROUND

ChatGPT is a conversational large language model that has the potential to revolutionize knowledge acquisition. However, the impact of this technology on the quality of education is still unknown considering the risks and concerns surrounding ChatGPT use. Therefore, it is necessary to assess the usability and acceptability of this promising tool. As an innovative technology, the intention to use ChatGPT can be studied in the context of the technology acceptance model (TAM).

OBJECTIVE

This study aimed to develop and validate a TAM-based survey instrument called TAME-ChatGPT (Technology Acceptance Model Edited to Assess ChatGPT Adoption) that could be employed to examine the successful integration and use of ChatGPT in health care education.

METHODS

The survey tool was created based on the TAM framework. It comprised 13 items for participants who heard of ChatGPT but did not use it and 23 items for participants who used ChatGPT. Using a convenient sampling approach, the survey link was circulated electronically among university students between February and March 2023. Exploratory factor analysis (EFA) was used to assess the construct validity of the survey instrument.

RESULTS

The final sample comprised 458 respondents, the majority among them undergraduate students (n=442, 96.5%). Only 109 (23.8%) respondents had heard of ChatGPT prior to participation and only 55 (11.3%) self-reported ChatGPT use before the study. EFA analysis on the attitude and usage scales showed significant Bartlett tests of sphericity scores (P<.001) and adequate Kaiser-Meyer-Olkin measures (0.823 for the attitude scale and 0.702 for the usage scale), confirming the factorability of the correlation matrices. The EFA showed that 3 constructs explained a cumulative total of 69.3% variance in the attitude scale, and these subscales represented perceived risks, attitude to technology/social influence, and anxiety. For the ChatGPT usage scale, EFA showed that 4 constructs explained a cumulative total of 72% variance in the data and comprised the perceived usefulness, perceived risks, perceived ease of use, and behavior/cognitive factors. All the ChatGPT attitude and usage subscales showed good reliability with Cronbach α values >.78 for all the deduced subscales.

CONCLUSIONS

The TAME-ChatGPT demonstrated good reliability, validity, and usefulness in assessing health care students' attitudes toward ChatGPT. The findings highlighted the importance of considering risk perceptions, usefulness, ease of use, attitudes toward technology, and behavioral factors when adopting ChatGPT as a tool in health care education. This information can aid the stakeholders in creating strategies to support the optimal and ethical use of ChatGPT and to identify the potential challenges hindering its successful implementation. Future research is recommended to guide the effective adoption of ChatGPT in health care education.

Fortifying Health Care Intellectual Property Transactions With Blockchain

BACKGROUND

Intellectual property (IP) is a substantial competitive advantage in the health care industry. However, the COVID-19 pandemic highlighted the need for open innovation and collaboration for the greater good. Despite this, the industry faces challenges with innovation owing to organizational and departmental barriers. A secure platform is necessary to facilitate IP sharing without compromising the rights of IP owners.

OBJECTIVE

This study proposes a blockchain-based framework to secure IP transactions in health care and bring social impact.

METHODS

This study reviews existing researches, publications, practical cases, firm and organization websites, and conferences related to blockchain technology, blockchain in health care, blockchain in IP management, IP pledge research, and practice of IP management blockchain. The platform architecture has 7 components: pledgers, advanced research technology (ART), IP pledge platforms, IP databases, health care research, seeking ART, and transaction condition setting. These components work together seamlessly to support the sharing and pledging of ART and knowledge, while ensuring the platform's transparency, security, and trust.

RESULTS

The open IP pledge framework can promote technology dissemination and use, reduce research and development costs, foster collaboration, and serve the public interest. Medical organizations' leadership and support and active participation from stakeholders are necessary for success. By leveraging blockchain technology, the platform ensures tamper-proof and transparent transactions and protects the rights of IP owners. In addition, the platform offers incentive mechanisms through pledge tokens that encourage stakeholders to share their ART and contribute to the platform.

CONCLUSIONS

Overall, the proposed framework can facilitate technological innovation, tackle various challenges, and secure IP transactions. It provides a secure platform for stakeholders to share their IP without compromising their rights, promoting collaboration and progress in the health care industry. The implementation of the framework has the potential to revolutionize the industry's approach to innovation, allowing a more open and collaborative environment driven by the greater good.

Older Adults and New Technology: Mapping Review of the Factors Associated With Older Adults' Intention to Adopt Digital Technologies

BACKGROUND

Ongoing advancements in digital solutions support older adults' healthy aging and well-being. However, a unified synthesis of sociodemographic, cognitive, attitudinal, emotional, and environmental factors that influence older adults' intention to use these new digital technologies is still lacking. Understanding the salient factors that influence older adults' intention to use digital technologies will help to ensure that technology is developed appropriately and contextually. This understanding is also likely to contribute to developing technology acceptance models specifically for the aging generation, by reorganizing principles and constructing objectivity criteria for future research studies.

OBJECTIVE

This review aims to identify the key factors associated with older adults' intention to use digital technologies and to provide a comprehensive conceptual framework to describe the relationships between these key factors and older adults' intention to use digital technologies.

METHODS

A mapping review was conducted using 9 databases from inception to November 2022. Articles were selected for review if they had an evaluative component of older adults' intention to use digital technologies. Three researchers independently reviewed the articles and extracted the data. Data synthesis was performed via narrative review and quality appraisal was measured using 3 different tools based on each article's study design.

RESULTS

We identified a total of 59 articles investigating older adults' intention to use digital technologies. The majority (40/59, 68%) of articles did not use an existing framework or model for technology acceptance. Studies mostly adopted a quantitative research design (27/59, 46%). We found 119 unique factors reported to influence older adults' intention to use digital technologies. These were categorized into 6 distinct themes: Demographics and Health Status, Emotional Awareness and Needs, Knowledge and Perception, Motivation, Social Influencers, and Technology Functional Features.

CONCLUSIONS

Given the importance of global demographic change toward an aging society, there is surprisingly limited research on the factors that influence older adults' intention to use digital technologies. Our identification of the key factors across different types of digital technology and models supports the future integration of a comprehensive perspective encompassing environmental, psychological, and social determinants for older adults' intention to use digital technologies.

Fluorescence-guided surgery: National trends in adoption and application in pediatric surgery

BACKGROUND

Fluorescence-guided surgery (FGS) with indocyanine green (ICG) is a rapidly diffusing surgical innovation, but its utilization in pediatrics remains unknown. We present a cross-sectional descriptive analysis of trends from a national database.

METHODS

The Pediatric Health Information System (PHIS) database was queried for patient encounters between January 2016 and July 2021 with an associated ICG administration within 3 days prior to surgery. All procedure codes from each encounter were reviewed by two surgeons to determine the most likely associated FGS procedure and assign an operative category.

RESULTS

1270 encounters were identified from 38 participating hospitals. The mean patient age (SD) was 8.3 (6.4) years, 54.5% were male, 63.8% were white, and 30.1% were Hispanic. The most common categories for ICG use were neurosurgery (21.3%), biliary (18.3%), perfusion (14.8%), urology (12.5%), gastrointestinal (10.8%), ophthalmology (8.8%), and thoracic (5.6%). Utilization over time increased for some categories (thoracic, visceral perfusion, and neurological procedures) or remained stable for other categories. Overall ICG utilization has increased in 2020 (n = 314) compared to 2016 (N = 83). The number of centers utilizing ICG has also increased from 14 hospitals in 2016 to 29 hospitals in 2020 though adoption remains unevenly distributed, with 5 high-utilization hospitals accounting for 56.8% of all ICG FGS cases.

CONCLUSION

ICG is being used across a wide variety of pediatric surgical disciplines. Trends over time show increasingly frequent adoption across the country, with a few high-volume centers driving the innovation. Fluorescence-guided surgery is commercially available and is becoming more commonplace for pediatric surgeons. Dedicated efforts will now be needed to assess outcomes using this promising technology.

LEVEL OF EVIDENCE

Level IV.

STUDY TYPE

Retrospective study.

Persuading Patients Using Rhetoric to Improve Artificial Intelligence Adoption: Experimental Study

BACKGROUND

Artificial intelligence (AI) can transform health care processes with its increasing ability to translate complex structured and unstructured data into actionable clinical decisions. Although it has been established that AI is much more efficient than a clinician, the adoption rate has been slower in health care. Prior studies have pointed out that the lack of trust in AI, privacy concerns, degrees of customer innovativeness, and perceived novelty value influence AI adoption. With the promotion of AI products to patients, the role of rhetoric in influencing these factors has received scant attention.

OBJECTIVE

The main objective of this study was to examine whether communication strategies (ethos, pathos, and logos) are more successful in overcoming factors that hinder AI product adoption among patients.

METHODS

We conducted experiments in which we manipulated the communication strategy (ethos, pathos, and logos) in promotional ads for an AI product. We collected responses from 150 participants using Amazon Mechanical Turk. Participants were randomly exposed to a specific rhetoric-based advertisement during the experiments.

RESULTS

Our results indicate that using communication strategies to promote an AI product affects users' trust, customer innovativeness, and perceived novelty value, leading to improved product adoption. Pathos-laden promotions improve AI product adoption by nudging users' trust (n=52; β=.532; P<.001) and perceived novelty value of the product (n=52; β=.517; P=.001). Similarly, ethos-laden promotions improve AI product adoption by nudging customer innovativeness (n=50; β=.465; P<.001). In addition, logos-laden promotions improve AI product adoption by alleviating trust issues (n=48; β=.657; P<.001).

CONCLUSIONS

Promoting AI products to patients using rhetoric-based advertisements can help overcome factors that hinder AI adoption by assuaging user concerns about using a new AI agent in their care process.

Digital literacy, technological literacy, and internet literacy as predictors of attitude toward applying computer-supported education

Even though there is an abundance of research on computer supported education (CSE), digital literacy (DL), technological literacy (TL), and internet literacy (IL), the correlation between them and their effect on each other have not been analyzed in the literature. However, no study has been conducted on the correlation between and effect of CSE, DL, TL, and IL and which additionally explains their relationship to each other. This study aims to analyze the effect levels among the latent variables of DL, TL, and IL, and the attitude toward applying CSE and these latent variables' ratios to each other. For this purpose, eight hypotheses were developed after reviewing the literature. A relational descriptive model is used to detect the presence and extent of covariance. The participants of this study were 510 prospective teachers. Exploratory and confirmatory factor analysis of the scales were performed. The hypotheses of the research were tested with the structural equation model. As a result, it was revealed that DL, TL, and IL together significantly affect and explain the attitude towards CSE. Different suggestions have been developed based on the results of the research.

Reliability Components of Online Teaching and Learning Tools in Lesotho Higher Education Institutions: A Systematic Review

Electronic learning is a techno approach that brings new opportunities for teaching and learning in many fields of education compared to the traditional classroom environment. However, there is a dearth of research on its effectiveness in practicality and whether it is dependable enough during teaching and learning. Thus, this systematic review aims to provide evidence from numerous findings on the reliability components (such as functionality, probability of success, environment, and duration) of online teaching and learning (OTL) tools in Lesotho higher education institutions (HEIs), focusing on functionality and probability of success only. A review of online learning tools includes Thuto, Google Meet, Google Classroom, Zoom, Moodle, and Microsoft Teams. Technology adoption models and Siemens’ theory of connectivism underpin this review. The review covered 18 articles between 2015 and 2021. Scopus, Google Scholar, ProQuest, and EBSCO were used for data search. In addition, selected studies were reviewed by experts in Educational Technology at the National University of Lesotho. Some factors were found to hinder the functionality and success of OTL tools, including lack of internet connectivity, electricity, and gadgets. As a result of this review, OTL tools are effective to some extent in terms of functionality and likelihood of success. However, the weaknesses of the e-learning tools outweigh the strengths of Lesotho HEIs. Consequently, only using OTL tools could hamper the quality of higher education in Lesotho. In HEIs, blended learning and continuous training on e-learning tools should be introduced for effective teaching and learning.

Theories and Models of Technology Adoption in Agricultural Sector

Agriculture is crucial in catering to the increasing demand for food and employment. Thus, adoption of novel technologies is important. Many scientists have developed different theories and models explaining the process of behavioral change relevant to adoption. They are either completely different, similar, or improvements of previously developed models. Therefore, compilation and summarization of these theories and models will support future studies and researchers. Thus, an analysis of literature on technology adoption was conducted. The review was prepared based on literature from various sources spanning around 50 years. The theories and models identified by different studies were compiled and analyzed in this review paper. Many theories and models in agricultural technology adoption such as transtheoretical model, theory of reasoned action, theory of interpersonal behavior, model for innovation-decision process, different versions of technology acceptance model, theory of planned behavior, theory of diffusion of innovation, task-technology fit, technology readiness, unified theory of acceptance and use of technology, expectancy livelihood model, social cognitive theory, and perceived characteristics of innovating theory were compiled. Each theory and model has its own uniqueness, which had explained different aspects of technology adoption process and factors determining the behavioral change. These theories and models included affecting factors such as technological, personal, social, and economical factors. In conclusion, it can be stated that, rather than having a single theory or a model, an integrated and amalgamated form will be more explanatory for technology adoption.

What Determines the Acceptance and Use of eHealth by Older Adults in Poland?

An aging population is considered a major challenge for governments and healthcare planners. eHealth is perceived as a tool with the potential to ensure efficient healthcare. Moreover, eHealth services may help older adults to maintain longer life in good health. However, there are still several challenges to the large-scale implementation of these solutions among older adults. Therefore, the aim of this study was to explore determinants of the acceptance and use of eHealth by older adults in Poland. Data was collected by the questionnaire, and the UTAUT model was employed. This research covered older adults aged 60 to 69. The analysis of the results using nested regression analysis showed that performance expectancy has a strong significance on the older adults' acceptance and use of eHealth, followed by effort expectancy and social influence. In contrast, facilitating conditions do not have a significant influence on the acceptance and use of eHealth. These findings may also be beneficial for the government to provide relative policies to support the development and usage of eHealth services as well as for the healthcare devices industry to design more older adult-oriented products.

Intention to use business intelligence tools in decision making processes: applying a UTAUT 2 model

The pressure on the speed of information processing ranks business intelligence technologies among the fastest growing decision support tools. The main goal of this article is, applying the UTAUT 2 (the unified theory of acceptance and use of technology), to verify the factors determining the implementation of business intelligence tools in business processes, especially decision-making, and their subsequent optimal use in business practice. The researched scheme was modified according to the specifics of business intelligence tools and was supplemented by user behaviour in decision-making. The verification was performed using a questionnaire survey based on UTAUT 2 theory and 152 respondents were included in the analysis. According to the results, the most important variable of influence on both the behavioural intention and the users' behaviour itself in decision-making was the factor of habit. And surprisingly, some previously recognised links were not confirmed, especially the factors influencing the intention of behaviour (effort expectancy, social influence, facilitating conditions). So, there is room after almost 10 years and experience gained during the Covid-19 pandemic to modify the latest version of a model.

The Use of Artificial Intelligence in Medical Imaging: A Nationwide Pilot Survey of Trainees in Saudi Arabia

Artificial intelligence is dramatically transforming medical imaging. In Saudi Arabia, there are a lack of studies assessing the level of artificial intelligence use and reliably determining the perceived impact of artificial intelligence on the radiology workflow and the profession. We assessed the levels of artificial intelligence use among radiology trainees and correlated the perceived impact of artificial intelligence on the workflow and profession with the behavioral intention to use artificial intelligence. This cross-sectional study enrolled radiology trainees from Saudi Arabia, and a 5-part-structured questionnaire was disseminated. The items concerning the perceived impact of artificial intelligence on the radiology workflow conformed to the six-step standard workflow in radiology, which includes ordering and scheduling, protocoling and acquisition, image interpretation, reporting, communication, and billing. We included 98 participants. Few used artificial intelligence in routine practice (7%). The perceived impact of artificial intelligence on the radiology workflow was at a considerable level in all radiology workflow steps (range, 3.64−3.97 out of 5). Behavioral intention to use artificial intelligence was linearly correlated with the perceptions of its impact on the radiology workflow and on the profession (p < 0.001). Artificial intelligence is used at a low level in radiology. The perceived impact of artificial intelligence on radiology workflow and the profession is correlated to an increase in behavioral intention to use artificial intelligence. Thus, increasing awareness about the positive impact of artificial intelligence can improve its adoption.

A study of safety acceptance and behavioral interventions for autonomous driving technologies

Explaining the phenomenon of declining acceptance of automated driving technology (ADT) and predicting trends in acceptance has become an important area of research. To explore the reasons for the decline in acceptance of automated vehicles and how to improve user acceptance, we studied mechanisms of the influence process from the relationship between safety riskiness of ADT and user acceptance, and examined the mediating and moderating effects of the proposed intervention behaviors on the influence relationship between these two. First, an improved acceptance model incorporating safety risk factors was developed. Subsequently, the psychological change process of user acceptance was analyzed based on people's response to accident information. Ultimately, the results show that safety cognition risk regarding ADT has a significant negative impact on user acceptance. Next, the mediating model where user experience was introduced as a moderating variable was designed. From the test results of this model, it is found that the proposed behavioral intervention strategy is effective in attenuating the degree of impact of the safety riskiness of ADT on acceptance. The risk-based acceptance explanation model and intervention method designed in this study provide a scientific basis and practical approach to develop the market for automated vehicles.

Accept it or forget it: mandatory digital learning and technology acceptance in higher education

In early 2020, the COVID-19 pandemic led to a rapid shift to emergency remote teaching and mandatory digital learning in higher education. This study tested an extended causal model built on the Unified Theory of Acceptance and Use of Technology (UTAUT) under the restrictions on higher education stemming from the pandemic. Data collected from a survey among 485 students were analyzed using structural equation modeling. Confirmatory factor analyses were performed to examine the construct validity of the measurement model using polychoric correlations. Path analysis was used to test the causal model. The results indicate a psychologically sound baseline model with nine latent variables that affect students’ behavioral intention to accept and continue using technology for learning. However, the model is only partially in line with the proposed causal model based on UTAUT. The implications of these results are discussed in terms of technology acceptance and use in higher education, both under the restrictions leading to mandatory digital learning and in future.

The Critical Success Factors for Sustainability Financial Technology in Vietnam: A Partial Least Squares Approach

This paper helps in determining the critical success factors (CSFs) for sustainability financial technology business. An attempt is made to study the influence of were found CSFs to be key aspects of a business that must go well to ensure the success of an organization. These CSFs include issues that are vital to a company’s operating activities and its future success. The study collected data from 253 respondents through a structured questionnaire. Partial Least Square Structural Equation Modelling has been adopted to analyze the data through SmartPLSv3. For better understanding, we emphasize that companies within the same industry may exhibit different CSFs due to anomalies in their environmental situation or strategic situations, which might pose as a challenge for this study and the future exploration towards a general set of CSFs for sustainability fintech companies. The research concluded the presented seven CSFs with the following customer centricity, low profit margin, agility, scalability, security management, innovation, and compliance easy. The findings of the paper are beneficial for fintech enterprises and marketers to enhance the awareness and advantages of financial technology according to the needs of consumers and add value to the existing literature on the future sustainable financial technology businesses.

Use of Telemedicine Technology among General Practitioners during COVID-19: A Modified Technology Acceptance Model Study in Poland

During the COVID-19 pandemic, telehealth became a popular solution for the remote provision of primary care by General Practitioners (GPs) in Poland. This study aimed to assess the GPs' acceptance of telehealth during the COVID-19 pandemic in Poland and to explain the factors that drive GPs' need to implement a telehealth system in primary care using the modified Technology Acceptance Model (TAM). In Poland, 361 GPs from a representative sample of 361 clinics drawn from 21,500 outpatient institutions in Poland participated in the empirical study. Structural equation modelling (SEM) was used to evaluate the causal relationships that were formulated in the proposed model. Research has shown that Polish GPs reported a positive perception and high acceptance of the telehealth system during the COVID-19 pandemic. Overall, the results show that the social factors (image, decision autonomy, perception of patient interaction) significantly positively influence the technological factors (perceived ease of use and perceived usefulness) that influence the need to implement a telehealth system. The proposed socio-technological model can serve as a theoretical basis for future research and offer empirical predictions for practitioners and researchers in health departments, governments, and primary care settings.

An Evaluation of Key Adoption Factors towards Using the Fog Technology

Fog technology is one of the recent improvements in cloud technology that is designed to reduce some of its drawbacks. Fog technology architecture is often widely distributed to minimize the time required for data processing and enable Internet of Things (IoT) innovations. The purpose of this paper is to evaluate the main factors that might influence the adoption of fog technology. This paper offers a combined framework that addresses fog technology adoption based on the technology adoption perspective, which has been comprehensively researched in the information systems discipline. The proposed integrated framework combines the technology acceptance model (TAM) and diffusion of innovation (DOI) theory to develop a holistic perspective on the adoption of fog technology. The factors that might affect the adoption of fog technology are analyzed from the results of an online survey in 43 different organizations across a wide range of industries. These factors are observed based on data collected from 216 participants, including professional IT staff and senior business executives. This analysis was conducted by using structural equation modeling (SEM). The research results identified nine factors with a statistically significant impact on the adoption of fog technology, and these factors included relative advantage, compatibility, awareness, cost-effectiveness, security, infrastructure, ease of use, usefulness, and location. The findings from this research offer insight to organizations looking to implement fog technology to enable IoT and tap into the digital transformation opportunities presented by this new digital economy.

IoT Adoption and Application for Smart Healthcare: A Systematic Review

In general, the adoption of IoT applications among end users in healthcare is very low. Healthcare professionals present major challenges to the successful implementation of IoT for providing healthcare services. Many studies have offered important insights into IoT adoption in healthcare. Nevertheless, there is still a need to thoroughly review the effective factors of IoT adoption in a systematic manner. The purpose of this study is to accumulate existing knowledge about the factors that influence medical professionals to adopt IoT applications in the healthcare sector. This study reviews, compiles, analyzes, and systematically synthesizes the relevant data. This review employs both automatic and manual search methods to collect relevant studies from 2015 to 2021. A systematic search of the articles was carried out on nine major scientific databases: Google Scholar, Science Direct, Emerald, Wiley, PubMed, Springer, MDPI, IEEE, and Scopus. A total of 22 articles were selected as per the inclusion criteria. The findings show that TAM, TPB, TRA, and UTAUT theories are the most widely used adoption theories in these studies. Furthermore, the main perceived adoption factors of IoT applications in healthcare at the individual level are: social influence, attitude, and personal inattentiveness. The IoT adoption factors at the technology level are perceived usefulness, perceived ease of use, performance expectancy, and effort expectations. In addition, the main factor at the security level is perceived privacy risk. Furthermore, at the health level, the main factors are perceived severity and perceived health risk, respectively. Moreover, financial cost, and facilitating conditions are considered as the main factors at the environmental level. Physicians, patients, and health workers were among the participants who were involved in the included publications. Various types of IoT applications in existing studies are as follows: a wearable device, monitoring devices, rehabilitation devices, telehealth, behavior modification, smart city, and smart home. Most of the studies about IoT adoption were conducted in France and Pakistan in the year 2020. This systematic review identifies the essential factors that enable an understanding of the barriers and possibilities for healthcare providers to implement IoT applications. Finally, the expected influence of COVID-19 on IoT adoption in healthcare was evaluated in this study.

Sustaining Consumer E-Commerce Adoption in Sub-Saharan Africa: Do Trust and Payment Method Matter?

The long-term sustainability of e-commerce usage for improving quality of life is dependent on several factors. Presently, trust and payment methods have emerged as critical factors influencing e-commerce adoption. Consequently, this study investigates the UTAUT determinants of consumer e-commerce adoption in Ghana by focusing on the mediating and moderating roles of trust and payment method. The study employs the Partial Least Square Structural Equation Model (PLS-SEM) to estimate the survey response of 535 purposively selected respondents from six regions in Ghana. The results corroborate a direct relationship between the UTAUT variables and e-commerce adoption. However, the payment method suggests no moderating effect on trust and e-commerce adoption connection. Nevertheless, trust significantly mediates the UTAUT variables and e-commerce adoption. Finally, the mediation was highest between social influence and trust but lowest between effort expectancy and trust. This challenges practitioners and managers of e-commerce platforms to consider the mediating role of trust to improve adoption and the sustainable usage of e-commerce.

Predictors for E-Government Adoption of SANAD App Services Integrating UTAUT, TPB, TAM, Trust, and Perceived Risk

Using mobile applications in e-government for the purpose of health protection is a new idea during COVID-19 epidemic. Hence, the goal of this study is to examine the various factors that influence the use of SANAD App As a health protection tool. The factors were adopted from well-established models like UTAUT, TAM, and extended PBT. Using survey data from 442 SANAD App from Jordan, the model was empirically validated using AMOS 20 confirmatory factor analysis, structural equation modeling (SEM) and machine learning (ML) methods were performed to assess the study hypotheses. The ML methods used are ANN, SMO, the bagging reduced error pruning tree (RepTree), and random forest. The results suggested several key findings: the respondents’ performance expectancy, effort expectancy, social influence, facilitating conditions, perceived risk, trust, and perceived service quality of this digital technology were significant antecedents for their attitude to using it. The strength of these relationships is affected by the moderating variables, including age, gender, educational level, and internet experience on behavioral intention. Yet, perceived risk did not have a significant effect on attitude towards SANAD App The study adds to literature by empirically testing and theorizing the effects of SANAD App on public health protection.

Roadmapping 5.0 Technologies in Agriculture: A Technological Proposal for Developing the Coffee Plant Centered on Indigenous Producers' Requirements from Mexico, via Knowledge Management

The coffee plant, with more than 40 billion shrubs, 9 million tons of grains produced, and 80% of its production accounted for by small-scale producers, has been severely damaged since the emergence of Hemileia vastatrix and Hypothenemus hampei. Despite technological support, these pests have caused 20% to 40% production losses, a 50% to 60% deficit in performance, and a cost of between USD 70 million and USD 220 million to the world economies, which forces us to rethink actions centered on people as the key elements to develop appropriate solutions. For this, the present study presents a technological proposal centered on small indigenous coffee producer requirements for introducing Industry 5.0 technologies, considering roadmapping, knowledge management, statistical analysis, and the social, productive, and digital contexts of five localities in Mexico. The results show a correlation between monitoring and control, soil analysis, the creation of organic fertilizers, accompaniment, and coffee experimentation, as the actions to be implemented, proposing the introduction of a mobile application; sensors, virtual platforms, dome-shaped greenhouses, and spectrophotometric technology as relevant technologies centered on indigenous coffee producers' requirements. This study is important for policymakers, academics, and producers who wish to develop strategies centered on people in Mexico and the world.

The Critical Factors Impacting Artificial Intelligence Applications Adoption in Vietnam: A Structural Equation Modeling Analysis

The concept of artificial intelligence (AI) is the transformation of inanimate objects into intelligent beings that can reason similarly to humans. Computer systems are capable of imitating a number of human intelligence functions, such as learning, reasoning, problem solving, speech recognition, and planning. In this regard, artificial intelligence applications have been developed to assist corporations and entrepreneurs in making business decisions. Hence, the aim of the study is to investigate the adoption of AI applications at the Vietnamese organizational level. Using the core structures of the technology–organization–environment (TOE), the theoretical model was constructed based on how technical and environmental elements influence companies’ technological innovation adoption decisions. Ten critical factors related to AI adoption are identified. To test the model, data were obtained from 193 senior managers who are directly in charge of information systems in both private and public companies in Vietnam. Subsequently, the Structural Equation Modeling (SEM) approach was used to analyze the data. The findings indicate that technical compatibility, relative advantage, technical complexity, technical capability, managerial capability, organizational readiness, government involvement, market uncertainty, and vendor partnership are significantly related to AI application adoption. Interestingly, the study results indicated that the relationship between organization size and AI adoption was not statistically significant. Therefore, the suggested adoption of the AI application could contribute to the existing research on the adoption of AI through the TOE. Finally, the significant government law implications and future research directions are further addressed.

Fate of AI for Smart City Services in India

With the rollout of the smart city initiative in India, this study explores potential risks and opportunities in adopting artificial intelligence (AI) for citizen services. The study deploys expert interview technique and the data collected from various sources are analyzed using qualitative analysis. It was found that AI implementation needs a critical examination of various socio-technological factors to avoid any undesirable impacts on citizens. Fairness, accountability, transparency, and ethics (FATE) play an important role during the design and execution of AI-based systems. This study provides vital insights into AI implications to smart city managers, citizen groups, and policymakers while delivering promised smart city experience. The study has social implications in terms of ensuring that proper guidelines are developed for using AI technology for citizen services, thereby bridging the ever-critical trust gap between citizens and city administration.

Factors Influencing the Behavioural Intention to Use Cryptocurrency in Emerging Economies During the COVID-19 Pandemic: Based on Technology Acceptance Model 3, Perceived Risk, and Financial Literacy

Cryptocurrency could redefine the interplay of Internet-connected world markets by eliminating constraints set by traditional local currencies and exchange rates. It has the potential to revolutionise digital markets through the use of duty-free trading. This study investigates the factors which influence the behavioural intention to use cryptocurrency based on the Technology Acceptance Model 3 (TAM 3) during the COVID-19 (SARS-COV-2) pandemic. Data were collected through a cross-sectional questionnaire from 357 Pakistani business-educated adults, including investors who had a rudimentary understanding of the technology and financial instruments. Partial least square (PLS)-based structural equation modeling (SEM) was used to test the developed theoretical framework based on the Technology acceptance model 3. The PLS model has explained 72.1% of what constitutes the behavioural intention to use cryptocurrency. Surprisingly, risk was not a major consideration. This might be due to the fact that the majority of respondents thought working with cryptocurrency was hazardous. Willingness to handle cryptocurrency risk, on the other hand, might be a stumbling block to acceptance. The most essential aspect of a cryptocurrency's success was the perceived usefulness. Moreover, the moderating role of experience was not substantiated in this study. However, perceived usefulness was identified as a partial mediator of subjective norm and the perceived ease to use. This study contributed to the literature through the application of TAM 3 (an extension of the technology acceptance models) to investigate the fundamental qualities a cryptocurrency should have in order to influence investor's behavioural intention to use it. These findings provide revolutionary insights for the present and future market players for investment planning and for improved cryptocurrencies development.

Use of daily posture and activity tracking to assess sedentary behavior, toss-and-turns, and sleep duration of independently living Thai seniors

This study examines the postures and activities of elders using activity-monitoring device or diary booklet. The research focuses on using the tracked data to assess sedentary behaviors, toss-and-turns, and sleep duration. Fifty seniors participated in the study for 14 days to obtain anecdotal evidence: half of them wore Sookjai, a motion-tracking device; the other half recorded their activities manually via a diary. The results show that they spent most of their time in the sit/stand posture; they tossed and turned during naps and sleep. Both groups showed a similar pattern of activities: the higher level of sedentary behavior is related to a longer sleep duration. Sedentary behavior and naps increased the number of toss-and-turns at night; toss-and-turns did not affect sleep duration. These independent living adults rated themselves healthy regardless of the extent of their sedentary behaviors or tossing and turning. Although the device did not meet all expectations, the seniors did indicate a positive intention to use wearables.

An Exploratory Research on Blockchain in Aviation: The Case of Maintenance, Repair and Overhaul (MRO) Organizations

The aircraft maintenance sector has high complexity with many intermediaries, multiple actors sharing data and needs to ensure high data security. The implementation of Blockchain technology can significantly contribute to the aforementioned characteristics. This research explores the implementation of Blockchain technology in Maintenance, Repair and Overhaul (MRO). For this research, a mixed-method approach was followed to obtain a holistic view of the adoption of Blockchain technology in an aircraft maintenance facility. Semi-structured interviews and a case study were used. The interview findings related to the current status of maintenance records management. The findings also highlighted the value of data storage within MRO’s and the benefits of Blockchain. The paper also discusses the readiness/willingness of aircraft maintenance facilities to implement Blockchain and the barriers to implementation. Recommendations and areas for further research are identified.

Processors' Experience in the Use of Flash Dryer for Cassava-derived Products in Nigeria

This study was designed and carried out to ascertain the situation and perceptions of end users of cassava flash drying equipment in Nigeria with the aim of giving suggestions to policies and approaches for improved technology. Forty-one processing firms were selected and interviewed. Descriptive analyses were used and a logistic regression model was estimated. The results revealed that 49% of the firms stopped using their flash dryers due to the low demand for high-quality cassava flour (HQCF) resulting from the high cost of processing occasioned by an inefficient heat-generating component. The estimated model provides evidence that cost effectiveness (p &lt; 0.05) and energy cost (p &lt; 0.10) are the two major determinants of the continuous usage of flash dryers in the study area. Forty-one percent of the firms indicated willingness to pay for any technical adjustment of their flash dryers, supposing such adjustment would improve on drying and the energy efficiency of the equipment up to 40%. The study recommends that machine fabricators in Nigeria and other African countries should be trained on the production of energy- and cost-efficient small-scale flash dryers. Again, the design and commercialization of flash dryers that can be mounted on mobile trucks for farm-gate processing should be encouraged to facilitate farm-gate processing, thereby reducing postharvest losses resulting from transporting perishable and bulky roots over a long distance.

Patient Perspectives on the Development of a Novel Mobile Health (mHealth) Application for Dietary Supplement Tracking and Reconciliation – A Qualitative Focus Group Study

Background: More than 170 million adults use dietary supplements (DS) in the United States, which can have both benefit and harm to patient health. DS use is often poorly documented in the medical record and can pose health risks if not properly communicated with providers. Reasons for poor DS documentation include low disclosure rates, time constraints of clinical encounters, and providers’ failure to inquire about DS use. This study was conducted to assess patients’ views on the facilitators and barriers to using a mobile health (mHealth) application (app) to collect and share DS information with their healthcare providers. Methods: Utilizing a theory-based conceptual model, we conducted seven patient focus groups (FGs) to assess opinions on DS safety, provider communication, comfort with technology use, and our proposed mHealth app. Participants were recruited from the general public and through patient advisory groups. Patient views will inform the creation of an mHealth app to improve DS patient-provider communication and tracking and reconciliation in the electronic medical record (EMR). Results: Overall, participants believe their DS information is inaccurately represented in the EMR leading to safety concerns and negatively impacting overall quality-of-care. Participants desired an app designed with: 1) Health Insurance Portability and Accountability Act (HIPAA)-compliance; 2) ease of use for a variety of technical efficacy levels; 3) access to reliable DS information, including a DS-drug interaction checker; 4) integration with the EMR. Conclusion: An app to simplify and improve DS entry and reconciliation was of interest to patients, as long as it maintained health autonomy and privacy and possessed key valuable features.

Acceptance of GIS within ERP System: Research Study in Higher Education

GIS is often used in companies where employees already use enterprise information systems/enterprise resource planning (ERP) systems and where both systems are used simultaneously. This article is a research study of GIS acceptance by users using GIS, not as a stand-alone tool, but as an integrated tool into the ERP system. The research was conducted using the Technology Acceptance Model (TAM), one of the most often used research models for researching behavioral intention and actual use of information systems. For this research study, TAM has been modified and extended with external factors. The main research objective is to identify determinants of GIS acceptance and the attitude of individuals toward using GIS integrated with ERP systems. The structural equation model with partial least squares (PLS) method was used to analyze collected survey data. The study researched 12 external factors in the TAM model, out of which 10 were found significant. The most important factors that impact behavioral intention to use ERP-GIS systems are perceived usefulness of ERP-GIS systems and attitude toward using GIS, followed by education and training about ERP-GIS systems and perceived enjoyment using ERP-GIS systems.

Dynamics of Contextual Factors, Technology Paradox, and Job Performance in Smartphone Usage

The purpose of this paper is to explore the theories pertaining to the dynamics of contextual factors, technology paradox, and job performance of employees so as to answer specific questions related to the theories’ progressive advancement, and to evaluate the relationships among them in the context of mobile phones, using the evidence-based systematic review methodology. The term technology paradox has evolved over past decades, and theories have been postulated to explain its nature and relationships with its antecedents and outcomes; however, there is a dearth in the integrative models. Thus, the theory of paradox has been combined with other theoretical lenses to conceptualize tensions and responses to enrich extant theories on technology paradox and job performance. The finding of the study identifies seven research gaps in the available literature, which need to be plugged so that a holistic model is developed to address the interrelationships among the aforementioned research constructs.

Use and Reuse of Collaboration and Communication Technologies in Projects

Use of technology and more recently reuse of technology have received a great deal of attention in Information Technology research. However, students’ use and reuse of technology have received little attention. The purpose of this research is to examine if students working in a team will use the same technology with which they have experience and reuse it again. Also, the purpose of this research is to examine the reasons for reusing technology. The Technology Continuance Theory (Liao et al., 2009) is used in this research as an explanatory theory for the reuse of collaboration and communication technologies in teamwork. The findings support experience with a technology as the main driver of reuse of the same technology. The findings also suggest perception of technology usefulness as the main reasons for reuse.

Mobile payment adoption process: a serial of multiple mediation and moderation analysis

Purpose

Global digital payment transactions increase continuously. Due to the inconsistencies that occurred across the research findings, past researchers have called for further investigation to verify and empirically test the mobile payment acceptance model. The purpose of this paper is to develop an integrative model that is derived from the multiple technology acceptance models (TAM)’s a theoretical framework and past literature to understand how consumers decided to adopt mobile payment. By simultaneously testing mechanisms, namely, ease of use, usefulness and risk, the current study will be able to advance scholarly knowledge of the underlying consumer’s attitude and behavior that link social influence to intention to use.

Design/methodology/approach

A total of 370 valid responses were collected using self-administered questionnaires distributed via online platforms, a representative for Thai consumers. An ordinary least square regression and bootstrap analyzes were conducted through PROCESS Macro to analyze the moderated serial-multiple mediation model in the consecutive inducing of social influence, perceived ease of use, perceived usefulness and perceived risk toward the consumer’s intention to use mobile payment.

Findings

Within the context of consumers evaluating a mobile payment, statistics significant were found for the hypothesized direct and indirect effects of perceived ease of use and perceived usefulness on an intention to use. The results showed that Thai consumers’ intention to use mobile payment was significantly affected by their attitudes in terms of usefulness and the less complication in using the applications. It is confirmed that social influence indirectly affects intention to use via the increase of perceived ease of use and perceived usefulness. The study also found a significant interaction between perceived risk and perceived usefulness toward intention to use.

Practical implications

It is recommended to service providers to continue improving the user-friendliness, navigation, integrity and furnish the system with more value-added activities within the mobile payment application. It is also essential for the company to deliver tutorials and clear and easy-to-follow instructions to customers. At the same time, the marketer should develop marketing strategies to promote the usefulness and simplicity of using the applications to the consumers. When consumers experienced the easiness and usefulness of the applications, these could overcome the resistance feeling to use due to the concern on any potential risk.

Originality/value

The study contributes to the existing body of knowledge on consumer usage behavior and TAM by integrating all important variables and developed a parsimony framework to explain consumers’ usage adoption on mobile payment. Moreover, the current study was the very first that proposed and tested a serial of multiple mediations of perceived ease of use and perceived usefulness, moderated by perceived risk, in the relationship between social influence and consumers’ intention to use mobile payment and discovered a moderating role of perceived risk toward the relationship between perceived usefulness and mobile payment usage intention.

Modifying the Unified Theory of Acceptance and Use of Technology (UTAUT) Model for the Digital Transformation of the Construction Industry from the User Perspective

Inefficient and ineffective practices in the construction industry have hindered productivity even though it is considered as one of the largest sectors in any county. One best solution to overcome these inherent problems in the construction industry is to move forward with digital technologies. For that, organizational structure, technical aspects, and, most importantly, human factors need to be considered. The aim of this research is to find out human behaviors that affect the digital transformation of the construction industry based on the well-accepted model Unified Theory of Acceptance and Use of Technology (UTAUT). An in-depth literature review was carried out using fifty-five journal papers to develop a conceptual model for the acceptance of digital transformation, and it was validated and further reviewed using ten expert interviews. The model consists of seven constraints: Personal Benefits, Perceived Usefulness, Perceived Risk, Facility Conditions, Attitudes, and Subjective Norms. The analytical hierarchy process (AHP) was carried out to rank these seven factors according to individual priorities in the construction industry. Further, the model was extended and modified using factors derived from literature review and expert feedback. It is proved that “Perceived Personal Benefits” is the major consideration of an individual who is willing to move towards digital transformation. This research fulfills the lack of knowledge in the digitalization of the construction industry as per a human perspective, and it provides a prerequisite to finding the solutions for the issues which emerged within the industry towards digitalization. Further, the framework developed in the research can be used to systematically adopt the human factor for the digital transformation of the construction industry. In addition, this enables the analysis of changing demands for humans in digitally transformed environments, such as Industry 4.0 environments, and contributes towards a successful digital transformation that avoids the pitfalls of innovation performed without attention to human factors. The paper concludes by highlighting future research directions on the human factor in digital transformation as well as managerial implications for successful application in practice.

Digital Entrepreneurship: Public Perception of Barriers, Drivers, and Future

The widespread access to the Internet has undoubtedly changed the way businesses handle their processes and interact with their customers. With the surge of new devices, business models, technologies, and platforms, alongside social media growth and innovative advertising, it became easier to transition from employment to entrepreneurship. The paper aims to assess the public perception of digital entrepreneurship, with a focus on its barriers, drivers, and expectations for the future. The results show that there is a slight agreement with a digital business being easier to establish compared with a traditional one. The driving forces behind starting a digital business are recognized, and the digital environment is considered essential for business growth in the following years. With some exceptions, there are no significant differences between age groups, genders, relationship statuses, levels of education, and/or occupations when rating the barriers, drivers, and expectations for the future of digital entrepreneurship.

Benefits or Risks: What Influences Novice Drivers Regarding Adopting Smart Cars?

Level 4 autonomous vehicles (AVs) are smart vehicles that can move between two different points without any human interference. In 2018, the Saudi Arabian ban on female drivers was finally lifted, resulting in a large number of novice women drivers of different ages. The Kingdom might therefore be considered a risky place to drive, but AVs would help novices to reduce their fear of driving and reduce accidents. Previous studies focused narrowly on those who already had sufficient driving experience and held a valid driving license, but there were no studies on the adoption of smart cars by novice drivers. Based on a literature search, no studies had used a net valence model (NVM) for the adoption of AVs to understand their benefits/risks. Therefore, this study proposed an adoption model for AVs using an NVM to identify the benefit and risk factors that have an impact on beginner drivers’ adoption of autonomous vehicles. A survey method was applied using the purposive sampling technique. Data were collected from 1400 female Saudi novice drivers who had experience with driving AVs. Data analysis was performed using Smart PLS Version 3. The results showed that individuals tended to ignore potential risks and focus instead on the potential benefits of using AVs. Performance expectancy, enjoyment, and effort expectancy were found to be positively related to the perceived advantages. On the other hand, the perceived risk as a construct did not have an impact on beginner drivers’ adoption of autonomous vehicles. Therefore, the major theoretical contribution of this study was the formation of a new NVM model by incorporating three more constructs, which were social influence, personal innovativeness, and alternatives. Finally, the enhanced NVM model could assist AV developers in identifying the expected benefits and drawbacks of AV adoption.

Identifying the Characteristics of Virtual Reality Gamification for Complex Educational Topics

Multidisciplinary topics in education pose a major challenge for traditional learning and teaching methods. Such topics can deter students from selecting particular courses or hinder their study progress. This study focused on the subject of medicinal chemistry, which is a discipline combining medicine and chemistry. This combination of applied and basic science creates a complex field of education that is challenging to both teach and learn. Chemical and pharmacological principles are typically presented in 2D molecular structures and, recently, 3D molecular models have been utilized to improve the visualization of chemical compounds and their chemical interactions. Contemporary studies have presented Virtual Reality (VR) as an alternative method for improving the learning and teaching of multidisciplinary specialties such as this. However, current educational efforts employing VR offer limited interactivity and a traditional teaching method previously presented in 2D. This reduces students’ interest and concentration in the taught subjects. This paper presents the development rationale of a novel VR educational application based on the evaluation of the user requirements by 405 pharmacy undergraduate students. The results informed the development and preliminary evaluation of a proposed VR serious game application, which was deployed in a real-life class environment and evaluated in contrast to traditional teaching methods by 15 students. The derived results confirmed the advantages of VR technology as a learning and teaching tool, in addition to the end-users’ willingness to adopt VR systems as a learning aid.

Smarter Open Government Data for Society 5.0: Are Your Open Data Smart Enough?

Nowadays, governments launch open government data (OGD) portals that provide data that can be accessed and used by everyone for their own needs. Although the potential economic value of open (government) data is assessed in millions and billions, not all open data are reused. Moreover, the open (government) data initiative as well as users' intent for open (government) data are changing continuously and today, in line with IoT and smart city trends, real-time data and sensor-generated data have higher interest for users. These "smarter" open (government) data are also considered to be one of the crucial drivers for the sustainable economy, and might have an impact on information and communication technology (ICT) innovation and become a creativity bridge in developing a new ecosystem in Industry 4.0 and Society 5.0. The paper inspects OGD portals of 60 countries in order to understand the correspondence of their content to the Society 5.0 expectations. The paper provides a report on how much countries provide these data, focusing on some open (government) data success facilitating factors for both the portal in general and data sets of interest in particular. The presence of "smarter" data, their level of accessibility, availability, currency and timeliness, as well as support for users, are analyzed. The list of most competitive countries by data category are provided. This makes it possible to understand which OGD portals react to users' needs, Industry 4.0 and Society 5.0 request the opening and updating of data for their further potential reuse, which is essential in the digital data-driven world.

Adoption of mobile technology for mobile learning by university students during COVID-19

Purpose

Due to the eruption of the COVID-19 pandemic, many universities were forced to shift from the traditional learning practices to digital learning. Hence, the purpose of this study is to evaluate the factors that affect the university student's adoption of mobile technologies for mobile learning (m-learning) in their learning process.

Design/methodology/approach

Technology acceptance model (TAM) is incorporated to study the adoption of mobile learning by university students. Quantitative research technique is used as core research approach in this study. Structural equation modelling (SEM), which is a part of quantitative research method, was employed on the congregated data via a set of questionnaire from 268 University students. SEM is used to explore the relationships among the hypothesized constructs. SPSS and AMOS software were used for the analysis of data.

Findings

This study validated the updated TAM model and assessed the students' adoption of mobile technologies for m-learning during COVID-19. All the constructs of proposed model were found to be significant with more than 50% average variance extracted. It was found that two external constructs mobile system efficacy and mobile service efficacy appended in technology acceptance model show the direct positive effect on perceived usefulness and perceived ease of use constructs. However, hypothesized relationships were found to be unsupported among perceived usefulness and perceived ease of use. Furthermore, perceived usefulness and ease of use during m-learning impact the students' usage attitude which consequently impact the students' adoption behaviour towards adoption of mobile technology.

Research limitations/implications

Six constructs were considered for this study; however, mobile information quality for mobile learning was not included which could affect students' adoption criteria. Additionally, this study is limited to a country where future study needs validation of propose constructs in different demographic settings.

Originality/value

No study allied to the students' adoption of mobile technology for m-learning has accomplished in the context of India during COVID-19. Furthermore, TAM model has been updated with regard to the students' adoption of mobile learning during COVID-19 in Indian higher education setting.

Unpacking smart education's soft smartness variables: Leadership and human resources capacities as key participatory actors

The education system has been radically transformed by technological impetuses owed to the Fourth Industrial Revolution (4.0). Most recently, developing nations expedited smart education implementation to combat the negative effects COVID-19 has on education; thus, presenting managerial issues. A review of the literature on smart education shows that past studies focused primarily on the smart learning environment, substantially ignoring the importance of leadership and human resources capacity in the management of smart education. This study addresses the deficiency observed in the literature as it relates to the key factors that enable success in the management of smart education. The study applied a quantitative approach that derived data from a structured survey of probability simple random sampled Grenadian employees belonging to tertiary education. The Hayes multiple moderated mediation, Model 23, supported by SPSS-PROCESS Macro software was used to examine the study's model. Results showed that human resources capacity has a conditional indirect effect on smart education through the mediating variable of leadership capacity. Additionally, the moderating variables of additional investment in the 'ɑ' path and student demographics in the 'ɓ' path both displayed significant moderating effects. The findings of the study have provided several valuable insights into the theoretical and practical implications of the influence of leadership and human resources capacity in the implementation of smart education. Therefore, it is recommended, that the soft variables assessed in this paper need to be harnessed accordingly to achieve smart education.

What virtual laboratory usage tells us about laboratory skill education pre- and post-COVID-19: Focus on usage, behavior, intention and adoption

COVID-19 pandemic has brought uncertainty in educational response, skilling methods, and training practices among teachers and institutions. Even before the pandemic shutdowns, the incorporation of virtual laboratories within classroom education had brought transformations in teaching laboratory courses. Virtual laboratories were integrated as training platforms for complementing learning objectives in laboratory education especially during this pandemic imposed shutdown. In context of suspended face-to-face teaching, this study explores the role of virtual laboratories as Massive Open Online Courses (MOOCs) in ensuring the continuity of teaching-learning, providing alternative ways for skill training from home. As an innovative approach, the study presents push-pull mooring theory to analyze switching intention of users from offline conventional education to online education. The study explores the complements of physical experiments brought in with animations, simulations, and remote laboratory set-ups for providing skill trainings to learners. To test whether virtualization techniques have global impact in education sector, the study included a comparative analysis of student users during the academic year 2019 (before-COVID) who had a blended approach of learning and those of the year 2020 (post-COVID), with remote learning. Initial before-COVID behavioral analysis on university students (n = 1059) indicated the substantial popularity of virtual laboratories in education for skill training and instructor dependency. Usage adoption of virtual laboratories increased during the pandemic-imposed lockdowns and learners were being less instructor dependent. 24% of students accessed more 10 times a week without the instructor being present and overall, 90% contributed to a minimum of 5 usages a week. In terms of Kolb's learning styles, most of the virtual laboratory learners were assimilators. The results suggest virtual laboratories may have a prominent role in inquiry based and self-guided education with minimum instructor dependency, which may be crucial for complementing practice skills and planning online tools to add to this post-COVID-19 teaching and learning scenarios.

Measuring User Experience, Usability and Interactivity of a Personalized Mobile Augmented Reality Training System

Innovative technology has been an important part of firefighting, as it advances firefighters' safety and effectiveness. Prior research has examined the implementation of training systems using augmented reality (AR) in other domains, such as welding, aviation, army, and mathematics, offering significant pedagogical affordances. Nevertheless, firefighting training systems using AR are still an under-researched area. The increasing penetration of AR for training is the driving force behind this study, and the scope is to analyze the main aspects affecting the acceptance of AR by firefighters. The current research uses a technology acceptance model, extended by the external constructs of perceived interactivity and personalization, to consider both the system and individual level. The proposed model was evaluated by a sample of 200 users, and the results show that both the external variables of perceived interactivity and perceived personalization are prerequisite factors in extending the TAM model. The findings reveal that the usability is the strongest predictor of firefighters' behavioral intentions to use the AR system, followed by the ease of use with smaller, yet meaningful, direct and indirect effects on firefighters' intentions. The identified acceptance factors help AR developers enhance the firefighters' experience in training operations.

Study of awareness, adoption and experience of telemedicine technology services; perspectives during coronavirus (COVID-19) pandemic crisis and associated economic lockdown in India

Purpose

The purpose of this paper is to study the phenomenon of abrupt shift by both doctors and patients to telemedicine during the coronavirus (COVID-19) pandemic and associated economic lockdown in India. The study explored various drivers of telemedicine technology awareness, adoption and usage. These drives were studied from both the doctors and the patients’ perspectives using the Push–Pull–Mooring (PPM) theoretical model.

Design/methodology/approach

An exploratory qualitative research was carried out with 24 doctors and 32 patients. This research was conducted in major urban cities of India. It was carried out during the economic lockdown due to the COVID-19 pandemic. The data was collected based upon a semi-structured open-ended questionnaire using telephonic interviews. Once thematic saturation was achieved, thematic content analysis was conducted. Finally, the themes were classified and analyzed using the PPM theoretical model

Findings

The data analysis indicated that there was the presence of all three factors, namely, push, pull and mooring. For the doctors, pull and push factors were more substantive than mooring factors. Although for the patients push and mooring factors were more important and pressing than pull factors.

Research limitations/implications

This study was conducted during the COVID-19 pandemic and associated economic lockdown in India. The interview respondents were located only in urban India. Future studies could be conducted to explore similarities and differences in telemedicine adoption patterns during non-crisis times vis-a-vis crisis times in urban and rural settings.

Practical implications

The insights from this study could be used by medical service providers to leverage telemedicine technology to improve the business model, service delivery, pricing strategy, value proposition and behavioral characteristics. Patients on the other hand could gather perspectives regarding how best to use telemedicine technological services.

Originality/value

The authors provided an integrated perspective regarding telemedicine technology awareness, adoption and usage in an emerging economy of India during the critical times of the COVID-19 pandemic crisis and the associated prolonged economic lockdown. This was one of the first studies that applied PPM theory for telemedicine adoption