Text me when it becomes dangerous: Exploring the determinants of college students’ adoption of mobile-based text alerts short message service

Guided by Davis’ (1986) technology acceptance model (TAM) and Brehm’s (1989) reactance theory, this study sought to explore the determinants of college students’ adoption of mobile-based text alert short message service (SMS). The findings of the study supported the primary argument of the model that individuals’ adoption of text alert SMS for emergency preparedness and response should be largely determined by social psychological factors, such as attitude toward, subjective norm associated with, and perceived intrusiveness of the SMS. In addition, the findings demonstrated that subjective norm of and attitude toward the service prompted individuals’ actual adoption whereas intrusiveness of the service served as a distinctive barrier to the actual adoption behavior. Finally, the findings also showed that the probability of adopting the text alert SMS was not directly increased by perceived ease of use and perceived usefulness of the service, but was indirectly affected by the two antecedents through ones’ attitude toward the use of the SMS. Theoretical and practical implications of the findings are discussed.     

Service Quality and Perceived Value's Impact on Satisfaction, Intention and Usage of Short Message Service (SMS)

SMS, being an almost instantaneous communication medium that connects people, is now a phenomenon that has grown and spread around the globe at an amazing speed. Given the current trend of SMS usage and its potential growth, this paper will provide an insight of the extent to which how service quality and the value perceived by the SMS users have an impact on their extent of the SMS usage in the post SMS adoption phase. Specifically, this article will examine how service quality of the service providers and perceived value affect customer satisfaction and how customer satisfaction will affect their behavioural intention to continue to use SMS which in turn affects the extent of SMS usage in the local context. Using partial-least-squares, an analysis was conducted based on the 150 surveys collected to test for the proposed relationships. The results showed that the tangibles, empathy and assurance dimensions of service quality are antecedents of customer satisfaction and a positive relationship exists between customer satisfaction and customers' behavioural intentions to continue to use SMS. Additionally, the positive relationship between customers' behavioural intentions to continue to use SMS and the extent of SMS usage is also significant. These results were similar to the results shown by Cronin and Taylor (1992) studies. The perceived value/customer satisfaction relationship investigated in this research was in line with Fornell et al.(1996) and Cronin et al.(2000) where perceived value was one of the determinants of customer satisfaction. Specially, the results revealed that perceived value, together with tangibles, empathy and assurance aspects of the service quality, played an important role in determining customer satisfaction for SMS. Implications of the above results for research and practice are discussed.     

A two-staged SEM-neural network approach for understanding and predicting the determinants of m-commerce adoption

The advancement in wireless and mobile technologies has presented tremendous business opportunity for mobile-commerce (m-commerce). This research aims to examine the factors that influence consumers’ m-commerce adoption intention. Variables such as perceived usefulness, perceived ease of use, perceived enjoyment, trust, cost, network influence, and variety of services were used to examine the adoption intentions of consumers. Data was collected from 376 m-commerce users. A multi-analytic approach was proposed whereby the research model was tested using structural equation modeling (SEM), and the results from SEM were used as inputs for a neural network model to predict m-commerce adoption. The result showed that perceived usefulness, perceived enjoyment, trust, cost, network influence, and trust have significant influence on consumers’ m-commerce adoption intentions. However, the neural network model developed in this research showed that the best predictors of m-commerce adoption are network influence, trust, perceived usefulness, variety of service, and perceived enjoyment. This research proposed an innovative new approach to understand m-commerce adoption, and the result for this study will be useful for telecommunication and m-commerce companies in formulating strategies to attract more consumers.     

An empirical analysis of the determinants of 3G adoption in China

The main aim of this study is to examine the factors that affect Chinese consumers’ intention to adopt 3G. This study has extended the Technology Acceptance Model (TAM) by incorporating the determinants of perceived usefulness, cost, trust, and demographic profiles of Chinese consumers. Data is collected from Chinese consumers via self-administered questionnaire. Structural equation modeling was applied to examine the research model proposed. Our result showed that social influence, service quality and perceived ease of use have a direct and significant relationship with perceived usefulness of 3G, and this in turn affects the consumers’ decision to adopt 3G. Contrary to existing TAM research, perceived ease of use was not found to have a direct and significant influence with Chinese consumers’ intention to adopt 3G. Our study also revealed that those with higher educational level are more likely to adopt 3G. Based on the findings, this research is able to propose several practical recommendations to 3G providers in China, such as enhancing the variety of services provided through collaborations with mobile software and content developers. Furthermore, 3G providers can focus on promoting 3G through services such as “Friends and Family” packages as Chinese consumers’ 3G adoption decisions is influenced by their social network. In terms of theoretical contributions, this study has answered many calls from past researchers to investigate the determinants of perceived usefulness. This research was also conducted in China, which is one of the largest telecommunication markets in the world.     

Factors driving the adoption of m-learning: An empirical study

Even if m-learning is spreading rapidly in many regions of the world, research addressing the driving factors of m-learning adoption is in short supply. Built on the Technology Acceptance Model, this paper proposes a hypothesized model of m-learning adoption. Employing structural equation modeling technology, the model was assessed based on the data collected from 230 participants using a survey questionnaire. Results indicate that perceived near-term/long-term usefulness and personal innovativeness have significant influence on m-learning adoption intention, while perceived long-term usefulness significantly affects the perceived near-term usefulness. Personal innovativeness is a predictor of both the perceived ease of use and perceived long-term usefulness as well. Of all variables, the perceived long-term usefulness contributes to the most influential predictor of m-learning adoption. The model accounts for approximately 60.8% of the variance of behavioural intention. The results indicted that offing high-quality contents complying with students’ future targets is key to the success of m-learning in China. Both theoretical and practical implications are discussed.     

Predicting motivators of cloud computing adoption: A developing country perspective

Cloud computing is a recent and significant development in the domain of network applications with a new information technology perspective. This study attempts to develop a hybrid model to predict motivators influencing the adoption of cloud computing services by information technology (IT) professionals. The research proposes a new model by extending the Technology Acceptance Model (TAM) with three external constructs namely computer self-efficacy, trust, and job opportunity. One of the main contributions of this research is the introduction of a new construct, Job Opportunity (JO), for the first time in a technology adoption study. Data were collected from 101 IT professional and analyzed using multiple linear regression (MLR) and neural network (NN) modeling. Based on the RMSE values from the results of these models NN models were found to outperform the MLR model. The results obtained from MLR showed that computer self-efficacy, perceived usefulness, trust, perceived ease of use, and job opportunity. However, the NN models result showed that the best predictor of cloud computing adoption are job opportunity, trust, perceived usefulness, self-efficacy, and perceived ease of use. The findings of this study confirm the need to extend the fundamental TAM when studying a recent technology like cloud computing. This study will provide insights to IT service providers, government agencies, academicians, researchers and IT professionals.     

An empirical examination of users' post-adoption behaviour of mobile services

Extant research has focused on the initial adoption and usage of mobile services and paid little attention to the post-adoption and continuance usage. However, unless users continue using mobile services, service providers cannot achieve success. Drawing upon the expectation confirmation theory, this research develops a mobile post-adoption model. The post-adoption behaviour includes three variables: continuance intention, recommendation and complaint. We conducted data analysis with partial least squares. The results indicated that expectation confirmation, perceived ease of use, perceived usefulness and usage cost significantly affect users' satisfaction, further determining their post-adoption behaviour. In addition, perceived usefulness has a direct effect on the continuance intention.     

User continuance intention to use cloud storage service

Cloud computing is a huge and important change in the field of network application in recent years to provide users with a completely different IT service and delivery mode. Among various cloud services, cloud storage is a service most closely related to web users’ need because it involves the storage of users’ all important data and backup files. In this study, a sample survey was conducted in Taiwan, and key factors influencing individual users’ adoption of the cloud storage service were analyzed and discussed based on Task-Technology Fit theory. The research results indicate that “cloud storage service”, “unstructured task”, “cloud storage self-efficacy” and “opinion of reference groups” all have significant positive influences on the “perceived usefulness”, which further has influence on users’ continuance intention to use the cloud storage service. The findings also support that the privacy protection risk and the lack of privacy-policy risk in the cloud storage service produce negative moderating effects on the perceived usefulness and the continuance intention.     

Understanding driver adoption of car navigation systems using the extended technology acceptance model

This study proposes an integrated research model for investigating driver adoption of car navigation systems. We consider the potential causal connections between core cognitive and psychological factors and driver intention to use these systems. We extracted possible factors that may significantly affect the perceived usability of car navigation systems from in-depth interviews with two groups of individuals: an expert group and a driver group. Data collected from N?=?1045 drivers via an online survey were analysed by structural equation modelling. The results showed that the service & display quality components of the systems were the most significant determinants of driver attitude and intention to use car navigation systems. Two other factors, namely attitude and perceived usefulness, also had impacts on driver intention. Moreover, both satisfaction and service & display quality were affected by perceived system reliability, while usefulness was affected by both perceived locational accuracy and satisfaction. Satisfaction also significantly affected perceived ease of use. In addition, we introduced new external variables to the technology acceptance model (TAM) and validated the causal connections proposed by the original TAM. The present study provides valuable insights into the core factors that significantly affect driver perspectives of and intention to use car navigation systems.     

The dark side of elderly acceptance of preventive mobile health services in China

Mobile health services have become increasingly important for people, especially for the elderly. Despite the potential benefits, there are challenges and barriers for the elderly in adopting mobile health services. Drawing upon the dual factor model, we investigate the enablers and the inhibitors of the elderly mobile health service adoption behaviour. We also address two typical characteristics of elderly users—technology anxiety and dispositional resistance to change—to understand the antecedents of the enablers and the inhibitors. The hypothesized model is empirically tested using data collected from a field survey of 204 customers of a large elderly service providing company in China. The key findings include: (1) resistance to change influences perceived usefulness but does not influence perceived ease of use and adoption intention; (2) technology anxiety is negatively associated with perceived ease of use but positively associated with resistance to change; (3) dispositional resistance to change is negatively associated with perceived ease of use but positively associated with resistance to change. Implications for research and practice are discussed.     

Exploring Factors Affecting the Adoption of Internet of Things Services

The Internet of things (IoT) is seen as a potentially effective means of integrating multiple technologies to improve the quality of life. However, little attention has been paid to factors that may have a significant effect on a user’s intention to use the IoT services. This study applies the value-based adoption model to examine the influences of benefits (i.e. perceived usefulness and perceived enjoyment) and sacrifices (i.e. perceived privacy risk and perceived costs) on the user’s perceived value of and intention to use the IoT services. A structural equation modeling approach is applied to a survey of 489 IoT users, with results indicating that perceived usefulness and perceived enjoyment significantly affect behavioral intention through perceived value. Moreover, perceived privacy risk also plays a key factor in determining IoT adoption. The implications of this study are discussed.     

Factors affecting e-training adoption: an examination of perceived cost,computer self-efficacy and the technology acceptance model

The objective of this paper is to highlight the role that perceived cost, computer self-efficacy and the technology acceptance model (TAM) constructs have in e-training adoption in the Nigerian civil service. With the use of the SmartPLS 2.0 M3 software, a framework that included perceived cost, computer self-efficacy and TAM constructs (perceived usefulness (PU) and perceived ease of use (PEOU)) was tested on 450 heads of departments. Scales on perceived cost, computer self-efficacy, PU and PEOU developed by previous studies were modified accordingly and used. This paper found perceived cost to have a significant effect on e-training adoption. Computer self-efficacy was statistically insignificant through PEOU. In addition, PEOU had an indirect effect through PU. Therefore, only PU of the TAM constructs indicated strong predictive strength in e-training adoption. This paper showed that with e-training adoption, facilities such as computers can be put in place, which can improve the outlook of the civil service. In addition, the cost that is usually associated with traditional training can be reduced, increasing the opportunity to invest in other aspects of the civil service which can help in adding to the overall performance. Relationships were examined in this paper, which were shown to be favourable to e-training adoption in the Nigerian civil service.     

E-banking in Jordan

The reasons why some customers use e-banking systems whereas others do not is the problem that motivated this study. This study examines the factors underlying customers' technology adoption based on the technology acceptance model (TAM). E-banking adoption is studied from the information systems acceptance point of view; banking customers use the information system to make financial transactions and hence more knowledge of the factors that affect information technology adoption is useful to better understand and facilitate their acceptance. Perceived ease of use, perceived usefulness, subjective norms, security and trust, Internet experience and enjoyment are the important factors that affect customers' adoption of e-banking in Jordan.     

Does Context Matter? The Impact of Use Context on Mobile Internet Adoption

Consumers' perceived value plays a dominant role in determining the adoption of mobile technologies. However, behavior literature suggests that consumer value is context dependent. The current study attempts to understand the effects of use context on consumers' perceived value and adoption of mobile Internet. An adoption model that reflects the unique use context and the utilitarian values (perceived usefulness and perceived mobility) and hedonic values (perceived enjoyment and concentration) of mobile Internet was developed and empirically tested against data collected from 507 mobile Internet users in China. Structural equation analysis results indicate that consumers' values perceptions and adoption decisions are context dependent. The use context fully mediates the effects of utilitarian values and partially mediates the relationship between hedonic values and intention to use mobile Internet. Theoretical and practical implications of the findings are discussed.     

Predicting Drivers of Mobile Entertainment Adoption: A Two-Stage SEM-Artificial-Neural-Network Analysis

This study aims to understand users’ motivations to adopt mobile entertainment (m-entertainment). Extending the Technology Acceptance Model (TAM), this study examined the effects of trust, perceived financial cost (PFC), and quality of the service on consumers’ decision in adopting the m-entertainment. Survey data were collected from 524 mobile users and analyzed using both structural equation modeling (SEM) and neural network (NN) . The result showed that perceived usefulness (PU), perceived ease of use (PEOU), and quality of service (QS) are important predictors of m-entertainment adoption. The study contributes to the existing literature by extending the TAM model as well as examining m-entertainment, an important and emerging business model in mobile commerce. A new analytical approach using both SEM and NN was also employed in this study.     

Determinants of users’ intention to adopt m-commerce: an empirical analysis

The fast-growing penetration of mobile devices and recent advances in mobile technologies have led to the development of increasingly sophisticated services such as m-shopping for goods or services and m-payment. However, although the number of mobile subscribers is increasing, levels of actual m-commerce activities in many cases remain low. Determining what influences users’ intention to use m-commerce is therefore of growing importance. The purpose of this study was to investigate possible factors. To this aim, we developed a conceptual user adoption model based on technology acceptance model variables and on specific factors such as social influence, personal innovativeness, customization, and individual mobility. The empirical results show that social influence and customization significantly affect perceived usefulness; mobility, customization, and personal innovativeness significantly affect perceived ease of use; and perceived usefulness and perceived ease of use have a direct positive effect on behavioral intention.     

Convergence adoption model (CAM) in the context of a smart car service

This study proposes the convergence adoption model (CAM) in the context of a smart car service. The unique characteristics of convergence technology demand the incorporation of compatibility judgment, task-technology-fit (TTF) and the effect of visual design to fully understand users' adoption intention. The results of our study indicate that the compatibility with past experiences with existing and comparable technologies is indeed a critical factor affecting perceived ease-of-use, usefulness, and enjoyment of convergence technology. TTF is found to directly influence the adoption intention and mediate the effect of perceived usefulness and enjoyment on the adoption intention. Finally, the results show that visual attractiveness of the interface design enhances the evaluation of the key constructs of our model, such as compatibility judgment, perceived enjoyment, and adoption intention of convergence technology.     

Determinants of accepting wireless mobile data services in China

Data services via wireless networks and mobile devices have experienced rapid growth worldwide. We investigated the factors influencing adoption of wireless mobile data services (WMDS) in China and tested our model for explaining adoption intentions there. We argued that individuals form their intention to adopt WMDS under the influence of wireless mobile technology, the social environment, personal innovativeness of IT, trust awareness, and the facilitating conditions. We examined the simultaneous effects of these five influences on beliefs in the context of wireless Internet data services via mobile phones. Survey data were collected from 1432 participants in several metro cities across China. The findings suggest that WMDS adoption intention in China is determined by consumers’ perceived usefulness and perceived ease of use of WMDS. Theoretical and practical implications are included in our paper.     

Examining mobile instant messaging user loyalty from the perspectives of network externalities and flow experience

Due to the intense competition and low switching cost, building user loyalty is critical for mobile instant messaging (IM) service providers. Integrating both perspectives of network externalities and flow experience, this research identified the factors affecting mobile IM user loyalty. Network externalities include referent network size and perceived complementarity. Flow experience includes perceived enjoyment and attention focus. We conducted data analysis with structural equation modeling (SEM). The results show that both network externalities and flow experience significantly affect perceived usefulness and satisfaction, further determining user loyalty. Thus mobile service providers need to improve their IM platforms, and deliver positive network externalities and good usage experience to users. Then they can facilitate users’ loyalty.