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The main goal of our research is to analyze users' acceptance of mobile payment systems, considering the population's widespread use of mobile devices. In order to explain acceptance, we have added trust and perceived risk to the traditional variables. To this end, we have carried out a study through an online survey to a national panel of Internet users. The results of this survey check the implications considered on the basis of the Technological Acceptance Model, the Theory of Reasoned Action and the trust building principles for a given system. The conclusions and implications for management provide alternatives for companies to promote this new business by means of the new technical developments.

This study identifies the cultural influences on the adoption of mobile commerce based on the comparative cases of Taiwan and Malaysia, so as to give insights to mobile operators' global entries. Using Hofstede's five cultural orientations as moderators in conjunction to Davis' technology acceptance model (TAM), the combined model has been tested by the confirmatory factor analysis for measurement validity and the multiple regression approach for the moderation effect of cultural influences on the adoption of novel mobile services. This results show that uncertainty avoidance (UA), individualism (ID), and long-term (LT) orientation have significant influences on the influence of perceived usefulness (PU) and perceived ease-of-use (PEOU) regarding the adoption intentions of mobile commerce. However, the power distance (PD) and masculinity (MA) have different effects in Taiwan and Malaysia. These results not only supplement the explanation of the technology adoption, but also hold strategic implications for the global expansion of mobile operators by emphasizing on local preferences and their differentiation advantages.

The introduction of innovations in organizations with high professionalization seems to lead to mixed results in practice. It is widely known that innovation adoption success is largely dependent on user commitment and absorption of the innovation in work processes. However, the hardest task for any person interested in innovation implementation activities is how to achieve high levels of commitment and acceptance of those stakeholders that matter the most. In this article, we argue that much can be gained by having good insights in indicators of both influence and acceptance of stakeholders during innovation implementation and adoption phases; the so-called stakeholder dynamics. To gain insights in a stakeholder's potential influence and potential acceptance of the innovation during the innovation implementation project, we argue that stakeholder capacity and intentions are key characteristics. By reviewing relevant theoretical foundations relating to innovation implementation, technology acceptance and stakeholder theory, we argue that literature considering the combination of both capacity as well as intentions in an integrated evaluation model is scarce.

In this article, we are presenting a synthesized model and methodology for the iterative evaluation of stakeholder dynamics during innovation implementations; the stakeholder-based innovation acceptance web (SIAW). Insights in the combination of capacity and intentions dimensions can help in focussing and matching engagement strategies. The practical model, as part of the iterative methodology, aids in visualizing and classifying stakeholders in order to determine stakeholder engagement priorities during an innovation implementation project.

Artificial intelligence-based investment services (robo-advisors) are becoming increasingly commercialized. Robo-advisors are expected to expand further due to the enhancement of accessibility to investment for general investors through customized portfolio selection and automated transactions established upon the artificial intelligence-based algorithm. This study comprehensively investigates factors that influence acceptance intention of and resistance to robo-advisors using a combined model of technology acceptance model and innovation resistance model. The model was examined through conducting a choice-based conjoint analysis of 158 users with investment experience and age ranging from 20s to 60s. The independent variables of the research for robo-advisors are transparency, customization, social presence, and user control. The effects of the independent variables on acceptance intention and innovation resistance are analyzed, respectively, through mediator variables of perceived usefulness, perceived complexity, and perceived safety. This study indicates the fundamental factors for the promotion of the domestic robo-advisor market based on the analysis of further advanced overseas robo-advisor markets. The significance of this study derives from providing implications on the direction of development for companies or financial institutions in the sphere of robo-advisors.

Although technology acceptance and adoption have been intensively investigated using well-established theories called the Technology Acceptance Model (TAM) and Innovation Diffusion Theory (IDT), this paper claims that Emerging Technology (ET) has particular characteristics that differentiate it from the adoption of traditional technology that has been used for a long time. Therefore, it argues that TAM and IDT are not sufficient to investigate the adoption of ET. Investigating the adoption of ET requires additional, unique, non-traditional factors (constructs). Therefore, this paper aims first to conceptually develop a model of ETs adoption (META). To achieve this objective, TAM and IDT will be reviewed. Then, this paper will use the characteristics of ET as the basis for developing the factors that influence the adoption of ET. Secondly, to validate the model, a case study of an ET (i.e. Virtual Reality) will be analysed in-depth to reveal the factors that influence on its adoption by applying META. A discussion of META applications and implications for future research are also provided.

Although several previous studies have investigated the success factors and implementations of data warehouses, only few of them have explored the end-users' perceptions of data warehouses. Moreover, none of these previous studies were conducted in a company outside North America. Thus, this study was conducted to identify the data warehousing system characteristics affecting end-users' usage and perceived impact of using data warehouses in Korean financial companies. A research model for end-users' usage and perceived impact of using data warehouses was developed based on the Technology Acceptance Model and the IS Success Model. Then, a survey questionnaire was design to collect data from the data warehousing users in four leading Korean financial companies. We analyzed these data to test the proposed hypotheses by using Structural Equation Modeling. Results of this study suggest that Data Quality and End-user Support and Training are significant system characteristics affecting end-users' usage of data warehouses and perceived impact of data warehouses.

The study explores relationship between technological orientations and demographics of bottom of the pyramid (BOP) entrepreneurs in Ghana. The study reviewed literature on the BOP concept. Based on the reviewed literature, hypotheses were developed for testing. Data was collected from 287 micro-entrepreneurs using a structured questionnaire. The data collected was analyzed using the analysis of variance (ANOVA) and regression analysis. The study found some relationships between technology acceptance, connectivity to networks and entrepreneurial demographics. This provides the information necessary for information communications technology (ICT) and technology companies seeking to expand to these new markets as top of the pyramid markets saturate.

Drawing upon diffusion of innovation (DoI) theory, technology acceptance models (TAMs), social network perspective and resistance literature, the study developed and tested a model, named integrated resistance factor model (IRFM), which integrates four key elements i.e. resistance indicators, support network factors, experience and disposition factors and the integration and accessibility factors. The study investigated if the model applies in a selected technology, namely online project information management systems (OPIMS). The IRFM was tested with partial least square (PLS) techniques and results from the $R^2$ analysis of the whole PLS structural model were significant and the data were coherence with the proposed model $(R^2=0.484)$. These results indicated that user resistance to technology innovation can be predicted using the IRFM.

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.

The main purpose of this study is to develop and improve a framework utilising network externality and monetary factors in order to provide a theoretical framework for the motivation behind customers’ acceptance of self-driving cars from companies that would service self-driving cars. The survey was conducted after a concept of level 5 of self-driving cars by NHTSA (2016) was explained to respondents. This study examined the impact of network externalities and monetary issues on perceived benefit and sacrifice, including perceived value, trust and intention to use. The results indicated that indirect network externalities have a stronger effect than direct network externalities on the perceived benefit and intention to use. This study also revealed that concerns for safety and privacy were the main barriers to intention to use. Furthermore, the trust and value are considered important factors by consumers who choose self-driving cars; thus, self-driving car makers should consider how to increase these points. This study may offer a comprehensive model for the acceptance of self-driving cars and is expected to help expand and advance the Value-based Adoption Model. This study also provides practical implications for marketing related to customers’ technology acceptance.