Technology Acceptance Behavior Research Articles

Wearable Technology for Health Monitoring and Diagnostics

Purpose: The general objective of this study was to investigate wearable technology for health monitoring and diagnostics. Methodology: The study adopted a desktop research methodology. Desk research refers to secondary data or that which can be collected without fieldwork. Desk research is basically involved in collecting data from existing resources hence it is often considered a low cost technique as compared to field research, as the main cost is involved in executive’s time, telephone charges and directories. Thus, the study relied on already published studies, reports and statistics. This secondary data was easily accessed through the online journals and library. Findings: The findings reveal that there exists a contextual and methodological gap relating to wearable technology for health monitoring and diagnostics. The advancement of wearable technology in health monitoring and diagnostics transformed the healthcare landscape by enabling continuous, real-time data collection and analysis, empowering individuals to manage their health proactively. Despite its benefits, challenges such as data privacy, device accuracy, and user adherence needed addressing. Ensuring robust data protection, validating device accuracy in diverse environments, and understanding barriers to sustained use were essential. Addressing the digital divide was also vital for equitable access. Overall, wearable technology held significant promise for preventive care and early diagnosis, but required ongoing research and collaboration to maximize its impact. Unique Contribution to Theory, Practice and Policy: The Technology Acceptance Model (TAM), Health Belief Model (HBM) and Unified Theory of Acceptance and Use of Technology (UTAUT) may be used to anchor future studies on wearable technology for health monitoring and diagnostics. The study recommended integrating technology acceptance and health behavior theories to provide a comprehensive understanding of adoption factors, emphasizing user-centered design for enhanced engagement, and advocating for stringent data privacy and security standards. It highlighted the importance of integrating wearable technology into healthcare systems for better clinical decisions, promoting equitable access, and using wearables in public health initiatives. The study also called for collaboration between technology developers, healthcare providers, and policymakers to address challenges and maximize the benefits of wearable health technology.

Asses the Behaviour of Consumers for Enhancing Claims Processing and Fraud Detection in Insurance Through Blockchain Technology

The rapid advancement of blockchain technology presents a transformative opportunity for the insurance industry, particularly in claims processing and fraud detection. This paper explores the impact of blockchain technology on consumer behavior and its potential to enhance the efficiency and security of insurance operations. We begin by providing a comprehensive overview of blockchain technology, outlining its decentralized nature, immutability, and transparency. We then delve into the current challenges faced by the insurance industry, including prolonged claims processes and prevalent fraudulent activities. Through a mixed-methods approach, incorporating both quantitative surveys and qualitative interviews, we analyze how consumers perceive and interact with blockchain-based insurance solutions. The findings suggest that while there is general awareness about blockchain, its understanding remains limited among consumers. However, our study indicates a positive correlation between blockchain adoption and increased trust in insurance processes, driven by the technology's inherent characteristics of security and data integrity. Furthermore, we discuss several blockchain implementations, such as smart contracts that automate claims adjudication, and decentralized applications that ensure transparency and reduce opportunities for fraud. Finally, we propose a framework for insurance companies to effectively integrate blockchain technology, emphasizing consumer education, stakeholder engagement, and regulatory compliance. This study not only highlights the transformative potential of blockchain in reshaping consumer behavior and operational processes in insurance but also provides strategic insights for stakeholders aiming to harness these innovations for improved service delivery and fraud mitigation. The study titled "Assess the behavior of consumers for enhancing claims processing and fraud detection in insurance through blockchain technology" aims to explore how blockchain can revolutionize the insurance sector by influencing consumer behavior, improving claims processing, and enhancing fraud detection mechanisms. The focus of this research involves several key areas. This study explores the behavior of consumers in the context of enhancing claims processing and fraud detection in the insurance sector through the adoption of blockchain technology. Blockchain, known for its decentralized and transparent nature, holds promise for revolutionizing traditional insurance processes by improving transparency, efficiency, and security. However, successful integration relies heavily on consumer acceptance and adoption. This research aims to investigate consumer attitudes, perceptions, and intentions towards blockchain-based insurance solutions. Drawing upon established theories of technology acceptance and consumer behavior, the study examines factors influencing consumer trust, privacy concerns, and perceived benefits of blockchain in insurance. Additionally, demographic variations in consumer behavior and the impact of cultural and regulatory factors are explored. Through a comprehensive literature review and empirical research methods such as surveys and interviews, this study seeks to provide insights into how insurers can effectively engage consumers, address concerns, and leverage blockchain technology to enhance claims processing efficiency and fraud detection capabilities. The findings aim to inform strategic decision-making for insurance companies, regulators, and policymakers, facilitating the successful adoption and implementation of blockchain solutions in the insurance industry.

The different impact of utilitarian and hedonic attributes on web-based retail shopping behaviour through the lens of extended technology acceptance model

PurposeAcknowledging previous scholarly focus on functional attributes in understanding technology acceptance behaviour, the current study aims to offer a novel perspective by integrating eight different dimensions of utilitarian and hedonic attributes to examine their influence in delivering a holistic web-based retail shopping experience.Design/methodology/approachThe research model was tested and validated through data collected from 370 online shoppers across both hedonic and utilitarian product ranges. Hypotheses were tested using covariance-based structural equation modelling with multi-group analysis to examine the moderation effect.FindingsThe findings strongly support the model confirming eight new utilitarian and hedonic dimensions that influence web-based retail shopping behaviour. The findings also confirm that hedonic attributes remain important even for utilitarian product purchasing.Practical implicationsThe key managerial implication is the demonstrated need to balance utilitarian and hedonic attributes in web-based retail platforms, where previously, there has been an overemphasis on functional features. Web-based retailers should consider the optimal blend of utilitarian (e.g. information quality) and hedonic (e.g. aesthetic) attributes in the design of a retail shopping site, irrespective of the product category.Originality/valueThis study integrates multiple dimensions of utilitarian and hedonic attributes into a single model and highlights the interplay of these attributes, thus extending the technology acceptance model. This paper also advances scholarship through its identification of attribute impact across different product categories.

The impact of construction stakeholder’s readiness and acceptance of technology on the success of Indonesian digital government transformation in construction sector

Despite its potential to significantly improve the efficiency, effectiveness, transparency, and accountability of construction sector services, the implementation of digital government transformation in many countries has often failed to achieve desired results due to low user adoption. This study introduces a factor model to predict technology readiness and acceptance behavior in the implementation of digital government transformation within construction business licensing and procurement services by integrating the Technology Readiness and Technology Acceptance Models. Survey data collected from construction companies, experts, project managers, and procurement committees in Indonesia were used to test the model through Structural Equation Modelling (SMART-PLS). The findings reveal that positive technological readiness has a significant impact on perceived usefulness and users' intention to use the system. Additionally, it was discovered that a one-point increase in the intention to use led to a 0.625 increase in achievement value. This research contributes to addressing the slow adoption of digital government transformation by exploring intention-to-use behavior in the construction sector.

App atmospherics, personality factors and technology acceptance behaviour towards the adoption of mobile banking apps – a systematic literature review

Mobile banking apps have become increasingly popular in recent years, providing customers with a convenient and secure way to manage their finances. These apps have transformed the way we conduct financial transactions and have revolutionized the banking industry. However, despite the widespread adoption of mobile banking apps, there is still a significant gap in our understanding of the factors that influence customers' acceptance of these apps. This systematic literature review aims to provide a comprehensive overview of the current state of research in this area based on app atmospherics, personality factors, and technology acceptance behaviour. The review analysed 40 papers published between 2019 to 2023 to synthesize the evidence and identify key factors that influence the adoption and intention to use mobile banking apps. One of the key findings of the review is that app atmospherics, including the visual design, functionality, and interactivity of mobile banking apps, significantly influence customers' technology acceptance behaviour. Customers are more likely to adopt mobile banking apps that are visually appealing, user-friendly, and interactive. Additionally, technology acceptance behaviour, such as perceived usefulness, perceived ease of use, and perceived trustworthiness, also plays a crucial role in shaping customers' attitudes towards mobile banking apps. The review also identified personality factors such as emotions and attitudes that significantly influence the adoption and intention to use mobile banking apps. Customers who are open to change, innovative, and willing to take risks are more likely to adopt mobile banking apps than those who are not. Additionally, customer demographics, cultural differences, and technological advancements were identified as key factors that affect the adoption of mobile banking apps. Banks and financial institutions must keep up with technological advancements to stay ahead of the competition and provide customers with the latest and most innovative technologies. This study has identified the key research gaps and suggest a theoretical framework for future research agenda.

Understanding Blockchain Technology Adoption in Operation and Supply Chain Management of Pakistan: Extending UTAUT Model With Technology Readiness, Technology Affinity and Trust

This paper aims to investigate the behavioral intention to adopt blockchain technology (BC) in Pakistan’s operation and supply chain management. A conceptual framework is developed by extending the unified theory of acceptance and use of technology (UTAUT) model, incorporating technology readiness, technology affinity, and trust. The model was empirically examined using 198 responses from an online survey directed by a Pakistan operation and supply chain professionals. The proposed model is tested using Smart PLS. The empirical results suggest that BC adoption is positively influenced by facilitating condition, social influence, effort expectancy, technology readiness, and technology affinity, while performance expectancy and trust negatively influence BC to adopt. This research contributes to the advancement and stimulation of blockchain technology acceptance behavior in supply chains and significant managerial implications that could be more meaningful for developing economies.

HUBUNGAN ANTARA FAKTOR DETERMINAN UTAUT DENGAN MINAT DOKTER GIGI TERHADAP PENGGUNAAN TELEDENTISTRY: STUDI PILOT

The development of Information and Communication Technology (ICT) in the health sector is growing with the existence of teledentistry. This revolution in fact has triggered problems in terms of acceptance of ICT adoption which is still low for both patients, health practitioners and health care providers. Approaches based on behavioral theories are widely used to assess ICT acceptance. The purpose of this article is to explain the concepts and determinants of Unified Theory of Acceptance and Use of Technology (UTAUT) model that can predict the behavioral intention in using teledentistry. This model is the combination of eight theories of technology acceptance behavior that have been widely used in various studies. The UTAUT concept model has four determinants that affect the individual's intention of technology: performance expectancy, effort expectancy, social influence and facilitating conditions. This model also has moderating factors that can affect the relationship between determinants and behavioral intention. This model is proven to provide variation of intention up to 70% when compared to the other theories.

Predicting intention to use QR code mobile payment among Malaysian Muslim millennials

Financial transactions in the digital age have shifted from traditional to digital systems. With the proliferation of smartphones and the internet, cashless payments via smartphone or mobile payment system are becoming more popular. Quick Response (QR) code mobile payment is one of the cashless payment options available today. Using the extended theory of Technology Acceptance Model (TAM), this study investigates the intention of Malaysian Muslim millennials to opt for QR code mobile payment. The study was conducted as a cross-sectional study with a convenience sample. Data was collected through a questionnaire distributed via Google forms on various social media applications. Multiple linear regression analysis was used to analyse the data. The results showed that perceived usefulness, perceived risk, hedonic motivation, and performance expectancy have a significant influence on the intention of Malaysian Muslim millennials to use QR code mobile payment as a payment method. Perceived ease of use and social influence, on the other hand, were not predictors of intention to use QR code mobile payment. This study contributes to filling the gap in the literature on technology acceptance, digital payments, and consumer behaviour. At the same time, this study can serve as a basis for QR code developers and retailers to better understand and serve their customers, and for the government to integrate more QR code applications into many government-provided services.

Online Single Submission (OSS) Izin Usaha pada DPMPTSP Kabupaten Nagan Raya

This article aims to discuss the Online Single Submission (OSS) for Business Permits at DPMPTSP Nagan Raya Regency. The research was conducted in Nagan Raya to see how acceptable Online Single Submission (OSS) as a solution for obtaining business permits was accepted by service users. OSS is then analyzed using the Technology Acceptance Model/TAM to see which constructs are most influential in the process of accepting this technology to replace conventional service processes. A total of 73 research respondents were involved in this study taken from entrepreneurs who use business license processing services at DPMPTSP Nagan Raya. All constructs of research variables were tested using the Partial Least Square (PLS) method and the results obtained showed that behavior intention occupies a position as the dominant construct affecting technology acceptance behavior.

Predicting the Blockchain Technology Acceptance in Supply Chains with Inter-Firm Perspective: An Integrated DEMATEL and PLS-SEM Approach

Predicting the Blockchain Technology Acceptance in Supply Chains with Inter-Firm Perspective: An Integrated DEMATEL and PLS-SEM Approach

Technology Acceptance of Neo-Broker Applications: An Empirical Investigation

Disruptive neo-broker applications (NBAs) enable users to access financial markets easily and have attracted millions of investors worldwide. As a gamified implementation for financial services, NBAs provide a unique research setting in which to examine the determinants of NBA acceptance among investors, some of whom are wholly inexperienced in financial products. We propose a research model specifically designed to explain the usage intention of NBAs by drawing on established factors from technology acceptance and financial behavior research. We validated the research model empirically with structural equation modeling (N = 653) and found significant drivers of NBA acceptance. Distinct from previous finance technologies, we confirmed consumption-oriented factors, including performance expectancy, hedonic motivation, price value, and habit as antecedents of NBA usage intention. From the financial perspective, initial trust and overconfidence were identified as further drivers, while overconfidence in turn is shaped by risk aversion and subjective financial knowledge, indicating a mediated effect on NBA acceptance. Thereby, we present the first NBA-tailored acceptance model that links technology characteristics and financial behavior. Correspondingly, we provide implications for theory and practice.

Employees' technology adoption in the context of smart tourism development: the role of technological acceptance and technological readiness

PurposeThe technology readiness and acceptance model were mostly employed as theoretical bases to analyze tourist behaviors of adoption of innovative technologies that are part of the smart tourism offer. This study attention now turns to the field of smart tourism human resource management and tries to establish a model to explain the relationship between general dimensions of personality with systematic specific dimensions toward ICT acceptance.Design/methodology/approachThe authors adopted the TRAM model as a way to better understand and evaluate the causal relationships between the personality dimensions, factors of perception, attitudes and behavior of users regarding the acceptance and use of innovative technologies. Based on the empirical data of 478 employees operating in tourist organizations, travel agencies and hotels, the authors employed regression analysis as the basic method for examining the research hypotheses and causal relationships between variables in the presented model.FindingsThe analysis revealed that employees in the tourism sector are inclined to adopt new technology, and that technological readiness has an impact on attitudes and intentions toward the use of technologies. Moreover, the results show that the path between the dimensions of technological readiness and intention to use technologies is to a certain extent mediated through perceived ease of use and perceived usefulness.Originality/valueThis research is among the first empirical studies that examine technology readiness and adoption in the context of smart tourism development. Besides the findings extend the literature on the mediating effect of perceived usefulness and perceived ease of use between technology readiness index and technology acceptance behavior.

On the Technology Acceptance Behavior of Romanian Preschool Teachers

300 participants were invited to participate in this research from 15 Romanian counties. 182 preschool teachers' questionnaires were utilized for data analysis after the return and screening of responses. A valid and accurate scale evaluating preschool teachers' behavior towards technology adoption was included in the questionnaire, along with self-reported demographic data, professional identification, and other information. Data was analyzed using SPSS V.16. (1) Intention to use, compatibility, perceived enjoyment, and actual use were positively associated. (2) The effect of compatibility and perceived enjoyment on the link between intention to use and actual technology use was carried out in the following way: Intention to use → Compatibility with technology → Perceived enjoyment → Actual use. We hypothesize that intention to use affects compatibility, compatibility affects perceived enjoyment, and, lastly, perceived enjoyment affects actual use. For a more robust validation of results, we have also modelled this relationship with the Radial Basis Function (RBF) neural network. Compatibility and perceived enjoyment partially mediate the relationship between intention to use and actual technology use in class by Romanian preschool teachers. According to the theory of planned behavior, this study brought to light the intricacy of the relationship between preschool teachers' intention to utilize technology in the classroom and their actual usage of it. Limitations and implications are discussed.

Employee Acceptance of E-Health and Its Implication for Performance in Specialist Hospitals in Ondo State, Nigeria

The study examined e-health (ICT) acceptance on employee performance in Ondo State specialist hospitals. The study investigated the challenges facing acceptance of e-health by employees of state specialist hospitals and also examined the effect of acceptance of e-health on the performance of employees in state specialist hospitals. The purpose was to access how ehealth can help improve service delivery in teaching hospitals in the study area. The work is anchored on the Technology Acceptance Model (TAM) which is an adoption model focusing on users’ acceptance of information systems or computer technologies. The aim of this theory is to describe factors that determine technology acceptance and information technology usage behavior. Primary data was used for the study. The questionnaire was used for the collection of data. The number of respondents for the study is 318. Descriptive and inferential statistics were used for data analysis. The research findings using descriptive analysis showed that a lot of challenges exist and affect the degree of acceptance of e-health by the employees in the study area. The result also showed that e-health (ICT) acceptance has a positive significant effect on employee performance in the state specialist hospitals in the study area. The hypothesis stated was tested at a 0.05 level of significance to determine the effect of e-health acceptance on employees’ performance using regression analysis and it was rejected because the pvalue was less than 0.05 (Beta=0.208, t=7.149, Sig=0.000, p<0.05). The study, therefore, concludes that there are challenges that affect the acceptance of ehealth (ICT) and that there is a significant positive effect of e-health acceptance and performance of employees in the state specialist hospitals in Ondo State, Nigeria.

디지털 파도 앞에 선 중고령자: 중고령자 집단 내 디지털 격차에 관한 질적연구

The purpose of this study is to explore how the within-group digital divide occurs among middle-aged and older adults. For this, the statements of twenty middle-aged and older adults aged 55 and above about their daily use of digital devices were qualitatively analyzed based on Creswell’s data analysis spiral. Applying the systematic process for coding data, the participants were divided into three groups; the ‘following’ group that diligently follows the changes for coexistence with the younger generation, the ‘lagging’ group that was reluctant to follow these changes due to the lack of meaning or necessity of using digital technology, and the ‘pushed’ group that had no choice but to be pushed by social currents to survive. The semantic units derived from each group were classified based on the micro-environment, awareness of the macro-environment, attitudes toward digital technology acceptance, and digital technology acceptance behaviors, through the categorization process. Based on the contents of the meaning of various sub-themes of each group, this study presented detailed discussions and suggestions for each group. This study is meaningful in empirically exploring the reality of digital technology acceptance experienced in daily life through the voice of middle-aged and older adults in the middle of ‘the digital wave’. Also, the findings from this study suggest more effective and customized intervention plans to minimize social exclusion and inequality of middle-aged and older adults living in the digital age.

Exploring students' learning management system acceptance patterns: Antecedents and consequences of profile membership

Although numerous studies have revealed various mechanisms involved in users' technology acceptance behaviors, the literature lacks insights about distinct profiles of teenagers' e-learning technology acceptance and how these profiles are associated with teenagers' contextual backgrounds and continued technology use. This study fills this gap by unpacking teenagers' learning management system (LMS) acceptance patterns through three-step latent profile analysis (LPA). The results of LPA on a survey of 1180 junior secondary students from 25 Hong Kong school identified three profiles, namely: Reluctant Pattern (8%), Embracing Pattern (61%), and Affirmative Pattern (31%), with ascending acceptance of LMS. A number of contextual factors were identified as antecedents of LMS acceptance, including school factors (i.e., school banding), family factors (i.e., family socio-economic status (SES), family environment, and both parents' parenting styles), and personal factors (i.e., gender, experience, conceptions of learning, and ICT literacy). All the antecedents were significantly associated with profile membership, except for family SES and experience. In addition, the three acceptance patterns also affected consequences of LMS acceptance, represented by LMS continued use and use satisfaction. Students from Affirmative Pattern had higher satisfaction and more intensive LMS use than other acceptance patterns. The findings of this study not only contribute to theory through the development of teenagers' different latent profiles of LMS acceptance and relating these profiles to teenagers' contextual characteristics and LMS continued use, but also provide strong implications for future research on teenagers’ e-learning technology use and for practitioners to improve LMS implementation and LMS use among teenagers.

A Radial Basis Function Neural Network Approach to Predict Preschool Teachers' Technology Acceptance Behavior.

With the continual development of artificial intelligence and smart computing in recent years, quantitative approaches have become increasingly popular as an efficient modeling tool as they do not necessitate complicated mathematical models. Many nations have taken steps, such as transitioning to online schooling, to decrease the harm caused by coronaviruses. Inspired by the demand for technology in early education, the present research uses a radial basis function (RBF) neural network (NN) modeling technique to predict preschool instructors’ technology usage in classes based on recognized determinant characteristics of technology acceptance. In this regard, this study utilized the RBFNN approach to predict preschool teachers’ technology acceptance behavior, based on the theory of planned behavior, which states that behavioral achievement, in our case the actual technology use in class, depends on motivation, intention and ability, and behavioral control. Thus, this research design is based on an adapted version of the technology acceptance model (TAM) with eight dimensions: D1. Perceived usefulness, D2. Perceived ease of use, D3. Perceived enjoyment, D4. Intention to use, D5. Actual use, D6. Compatibility, D7. Attitude, and D8. Self-efficacy. According to the TAM, actual usage is significantly predicted by the other seven dimensions used in this research. Instead of using the classical multiple linear regression statistical processing of data, we opted for a NN based on the RBF approach to predict the actual usage behavior. This study included 182 preschool teachers who were randomly chosen from a project-based national preschool teacher training program and who responded to our online questionnaire. After designing the RBF function with the actual usage as an output variable and the other seven dimensions as input variables, in the model summary, we obtained in the training sample a sum of squares error of 37.5 and a percent of incorrect predictions of 43.3%. In the testing sample, we obtained a sum of squares error of 14.88 and a percent of incorrect predictions of 37%. Thus, we can conclude that 63% of the classified data are correctly assigned to the models’ dependent variable, i.e., actual technology use, which is a significant rate of correct predictions in the testing sample. This high significant percentage of correct classification represents an important result, mainly because this is the first study to apply RBFNN’s prediction on psychological data, opening up a new interdisciplinary field of research.

Learning with desktop virtual reality: changes and interrelationship of self-efficacy, goal orientation, technology acceptance and learning behavior

AbstractWith advantages such as ease of use and low cost, desktop virtual reality (VR) technologies are increasingly being used in practical learning. This study aims to clarify the relationship among students' self-efficacy, goal orientation, technology acceptance [e.g., perceived usefulness (PU) and perceived ease of use (PEOU)] and learning behavior, and the changes of these variables as well as gender difference in the early and late stages of course study when desktop VR technology is applied to business simulation learning. A pretest–posttest group design with two repeated measures is employed for this study. During a 10-week period, students' self-efficacy, goal orientation, technology acceptance and learning behavior are measured among junior and senior students majoring in Business Administration from a four-year undergraduate university who used desktop VR technology for practical learning. Course scores for these students are also collected and used to measure whether desktop VR is helping to improve their learning outcomes. Findings indicate that there is a significant correlation between self-efficacy, PEOU, PU and goal orientation, which further affects learners' learning behavior and learning outcomes when desktop VR is used for practical learning. After learning with desktop VR, self-efficacy, perceived ease of use and usefulness, and surface learning behaviors increased, while mastery goal orientation decreased. Furthermore, self-efficacy, PEOU and PU are found to be significantly higher in males than in females.

기술수용모형을 통한 디지털 물류 플랫폼에서의 사용의도에 미치는 요인에 관한 연구

With the growth of the global economy, along with the rapid spread of mobile devices, e-commerce and COVID-19, transactions between shippers and logistics service companies and domestic import and export trades have shown a drastic increase. Platforms merging from the 4th industrial revolution have allowed Small and Medium Enterprises (SME) logistics service companies to participate as equal bidding service providers in Business-to-Business (B2B) logistics field. However, SME logistics services have experienced difficulties in accessing and utilizing the B2B logistics platforms because of the existing trading practices, such as information asymmetry and closures led by existing large corporations in the logistics industry. Therefore, it is necessary for the SME to study the factors that influence users’ decision to use the platform when securing its competitiveness in the logistics field. Since it is difficult to reflect a company’s relationship characteristics of B2B transactions with existing Technology Acceptance Models(TAMs), it is extended by adding fair trade and risk factors to study the technology acceptance behavior of users. The studies show that social influence, price efficiency and fair trade are the crucial variables for the users’ decision to use the platform. It also demonstrates that fair trade, in correlation to risk, has the significant impact on users’ acceptance of the platform. Based on the results of this study, it is beneficial if a company designs a platform structure from the perspective of fair trade and risks when developing a B2B platform in the future.

Reviewing the Components of Technology Acceptance Behavior in Transportation Sector

Technology integration in transportation enhances the efficiency towards urban mobility management. The effective implementation of such technologies requires exploration of vital factors of acceptance and use. This study synthesizes a review work on the road-transport technologies' literature from 2011 to 2021 by contemplating the adoption mechanism keywords such as "acceptance", "usability", "adoption" of technology in transportation, mobility and numerous transport technologies through Boolean operators. Total of 42 articles from 20 developed and developing countries are enlisted for analysis. Numerous Information System (IS) theories and behavioral dimensions are emanated from surveyed literature. Avoid-Shift-Improve (ASI) framework is also materialized to understand the inferences of reviewed articles. Study conclusions are debated for implications of transport technologies from citizens' perspective.