User Adoption Behavior Research Articles

Investigating the determinants of user adoption behavior in the context of conflicting health information: a DEMATEL-ISM model approach

PurposeThe purpose of this paper is to investigate the factors influencing user adoption behavior in the context of conflicting health information, thereby contributing to the understanding of users' information decision-making and adoption processes within intricate information environments. Furthermore, this research endeavors to offer guidance for mitigating the adverse effects of contradictory health information on users' cognitive perceptions.Design/methodology/approachFirst, this study used literature coding to identify factors that influence user adoption behavior in the context of conflicting health information. Secondly, we utilized the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method to unveil the key influencing factors based on centrality and causality. Lastly, utilizing the Interpretive Structural Model (ISM), we constructed the multilevel hierarchical structure model of influencing factors to delineate the relationships among factors across different levels.FindingsThe key causal factors influencing user adoption behavior in the context of conflicting health information include user basic characteristics, experience accumulation, and information type. The key result factors consist of psychological emotion, perceived trade-offs, and the source credibility. The significant elements include users' psychological emotions, perceived trade-offs, emotional support, source credibility, and informational support. Furthermore, user adoption behavior in the context of conflicting health information is a manifestation of the interplay among surface-level, mid-level, and deep-level factors.Research limitations/implicationsTheoretically, this paper enriches the existing relevant theoretical framework and offers a novel perspective for further investigation into user adoption behavior concerning conflicting health information. Practically, this study extracts factors that can influence user adoption behavior in the context of conflicting health information which is an essential reference value for guiding and optimizing user adoption behavior.Originality/valueThis paper expands the system of factors influencing user adoption behavior in the context of conflicting health information from individual, information and social perspectives. Utilizing DEMATEL quantitative analysis and ISM multilevel hierarchical models, this research examines and illustrates the significance of the influencing factors and their interrelationships.

The Vinyasa Tool for mHealth solutions: supporting human-centered design in nascent digital health ecosystems.

mHealth systems have been deployed widely in Lower- and Middle-Income countries (LMICs) for health system strengthening, requiring considerable resource allocation. However, most solutions have not achieved scale or sustainability. Poor usability and failure to address perceived needs are among the principal reasons mHealth systems fail to achieve acceptance and adoption by healthcare workers. A human-centered design approach to improve mHealth system use requires an exploration of users' perceptions of mHealth systems including the environmental, user-related, and technological aspects of a system. At present, there is a dearth of contextually intelligent tools available to mHealth developers that can guide such exploration prior to full-scale development and deployment. To develop a tool to aid optimization of mHealth solutions in LMICs to facilitate human-centered design, and consequently, successful adoption. We collated findings and themes from key qualitative studies on mHealth deployment in LMICs. We then used the Informatics Stack framework by Lehmann (2017) to label, sort and collate findings and themes into a list of questions which explore the environment, users, artifacts, information governance, and interoperability of mHealth systems deployed in LMICs. We developed the Vinyasa Tool - to aid qualitative research about the need and usability of mHealth solutions in LMICs. The tool is a guide for focus group discussions and key informant interviews with community-based healthcare workers and primary care medical personnel who use or are expected to use proposed mHealth solutions. The tool consists of 71 questions organized in 11 sections which unpack and explore multiple aspects of mHealth systems from the perspectives of its users. These include the wider world and organization in which an mHealth solution is deployed; the roles, functions, workflow and adoption behavior of a system's users; the security, privacy and interoperability afforded by a system; and the artifacts of an information system - the data, information, knowledge, algorithms and technology which constitute the system. The tool can be deployed in whole or in part, depending on the context of study. The Vinyasa Tool is the first such comprehensive qualitative research instrument incorporating questions contextualized to the LMIC setting. We expect it will find wide application among mHealth developers, health system administrators and researchers developing and deploying mHealth tools for use by patients, providers, and administrators. The tool is expected to guide users toward human centered design with the goal of improving relevance and usability, and therefore, adoption.

Evaluating the Effectiveness of Mobile Health in Breast Cancer Care: A Systematic Review.

Breast cancer is affecting millions of people worldwide. If not appropriately handled, the side effects of different modalities of cancer treatment can negatively impact patients' quality of life and cause treatment interruptions. In recent years, mobile health (mHealth) interventions have shown promising opportunities to support breast cancer care. Numerous studies implemented mobile health interventions aiming to support patients with breast cancer, for example, through physical activity promotion or educational content. Nonetheless, current literature reveals that real-world evidence for the actual benefits remains unclear. In this systematic review, we focus on analyzing the methodology used in recent studies to determine the effects of mHealth applications and wearable devices on the outcome of patients with breast cancer. We followed the PRISMA guideline for the selection, analysis, and reporting of relevant studies found in the databases of Medline, Scopus, Web of Science, and Cochrane Library. A total of 276 unique records were identified, and 20 studies met the inclusion criteria. Study quality was assessed with the Effective Public Health Practice Project (EPHPP) Quality Assessment Tool for Quantitative Studies. While many of the studies used standardized questionnaires as patient-reported outcome measures, there was minimal use of objective measurements, such as activity sensors. Adoption, drop-out rates, and usage behavior of users of the mobile health intervention were often not reported. Future work should clearly define the focus and desired outcome of mHealth interventions and select outcome measures accordingly. Greater transparency facilitates the interpretation of results and conclusions about the real-world evidence of mobile health in breast cancer care.

Exploring the adoption decisions of mobile health service users: a behavioral reasoning theory perspective

PurposeTo improve the frequency of adoption of mobile health services (MHSs) by users (consumers), it is critical to understand users' MHS adoption behaviors. However, the literature primarily focuses on MHS adoption-related factors and lacks consideration of the joint impacts of reasons for (RF) and reasons against (RA) on users' attitudes and adoption behaviors regarding MHSs. To fill this gap, this study integrates behavioral reasoning theory (BRT) and protective motivation theory (PMT) to develop a research model by uncovering the reasoning process of personal values, RF and RA, adoption attitudes and behavior toward MHSs. In particular, health consciousness (HC) is selected as the value. Comparative advantage, compatibility and perceived threat severity are considered the RF subconstructs; value barriers, risk barriers and tradition and norm barriers are deemed the RA subconstructs.Design/methodology/approachA total of 281 responses were collected to examine the model with the partial least squares structural equation modeling (PLS-SEM) method.FindingsThe results show that HC positively affects attitude through RA and RF. Additionally, RF partially mediates the relationship between HC and adoption behavior. This study contributes to a deeper understanding of user adoption behavior in MHS and provides practical guidance for the health services industry.Originality/valueThis study contributes to the existing MHS literature by understanding the joint influences of personal values, RF and RA on user attitude, which eventually determines users' adoption decisions regarding MHSs.

An Investigation into the Adoption Behavior of mHealth Users: From the Perspective of the Push-Pull-Mooring Framework

As an important branch of the modern electronic health care services, mobile health applications (mHealth APP) have been widely accepted as a novel health care-providing platform. Based on mobile communications, mHealth is operated on smart terminals such as smart phones, tablet computers, wireless devices or wearable devices, providing multi-channel, multi-terminal and multi-network services. Because mHealth is not restricted by time and space, it serves as a more effective disease management tool for communications between patients and medical workers. In the background of “Internet+”, this study aims to explore the internal adoption behavior of mHealth users to improve the efficiency of medical services, reduce medical costs, and enrich the “Internet + medical health” research. Guided by the push-pull-mooring framework (PPM), this study proposes a conceptual model of mHealth users’ adoption behavior. A specially designed survey was used to collect data on users’ adoption behavior (n = 183). SPSS 25.0 (Guiyang, China) and AMOS 21.0 are used for data analysis. The results show that users’ adoption attitude partially mediates the relationship between the adoption intentions and three key factors (inconvenience, APP attractiveness, and high risk). The adoption intention also partially mediates the relationship between adoption attitude and adoption behavior. Peer influence does not have a direct effect on adoption intention, but it shows a statistically significant indirect effect on adoption intention and adoption behavior through adoption attitude. The negative effect of high switching cost is not significant for both adoption attitude and adoption intention. This study elucidates the internal mechanisms underlying mHealth users’ adoption behavior. The findings can help mHealth providers to arouse more users’ adoption behavior, improve the quality of medical services, and reduce medical costs.

Research on Adoption Behavior and Influencing Factors of Intelligent Pension Services for Elderly in Shanghai.

With the rapid development of artificial intelligence and Internet-of-Things technology, the traditional pension service mode has changed, and intelligent pension services have become a new direction of development. Descriptive statistical analysis is conducted on the supply status and demand of intelligent pension services. It is believed that the current intelligent pension services are still in the initial stage of development, and the contradiction between supply and demand is prominent. The demand for intelligent pension of the elderly is high, but the user acceptance and satisfaction are not high. On this basis, variables were selected from individual characteristics, family situation, economic status, education level, living conditions, and other indicators for multivariate unconditional logistic regression analysis. It was found that the adoption behavior of intelligent pension service users was most significantly affected by age, number of children, living conditions, service cost, service docking channel, and equipment operation difficulty. Based on the conclusion, this article puts forward some suggestions such as taking the government as the center to realize the multi-governance of intelligent pension services, improving the supply of intelligent pension service-related facilities guided by demand, optimizing the service mode based on the platform to realize dynamic combination, and taking talents as the core to promote the high-quality development of intelligent pension services.

Factors Affecting the Intention to Use Virtual Stores: Perspectives of Consumers in Saudi Arabia

Companies have explored various forms of virtual reality (VR) shopping, yet what is known about the user adoption behavior of VR apps is minimal and research into VR shopping from a user acceptance perspective is limited. This study investigates the factors that affect the intention to use VR for online shopping through undergoing a virtual shopping experience in the VR app. This is an exploratory study using a quantitative methodology. The findings indicate that telepresence, attitude, perceived control (PC), satisfaction, hedonic motivation (HM), and perceived usefulness (PU) are direct determinants of intention to use, whereas perceived security risk has no effect. Moreover, PEOU, PU, PC, and telepresence are indirect determinants of intention to use. This research is valuable for its identification of the determinants that can affect the adoption of VR in online shopping. This study helps store owners to understand what features will enable a successful implementation of virtual stores (VSs). This study has several limitations. First, the study was conducted using a convenience sample, making it difficult to generalize the results to the whole population. In terms of method, the study was entirely quantitative, using a questionnaire entirely consisting of close-ended questions, so participants were limited in their response options. The final limitation is in the scope of the research, which covered the perceptions of consumers only, while employees’ and ICT experts’ perspectives were not considered. In light of these limitations, this study allows some suggestions for future research directions to be made. (a) The perspectives of employees and ICT experts could be included so that more factors will be generated. (b) Future research could use different methodologies such as mixed methods to gain a deeper understanding of the responses. (c) A longitudinal study could be designed to address any developments occurring in VS features, as e-commerce is continually being developed.

Adoption behavior of water efficiency labeling: origin, research progress and theoretical framework – evidence from China

Abstract Research on the adoption behavior of water efficiency labeling is of great significance for improving citizens' water-saving consciousness and promoting water-saving techniques and standards. This study sorted out 559 papers about adoption behavior and then systematically analyzed the origin and research progress of water efficiency labeling in different fields. Finally, related theories and empirical analysis are integrated, and a research framework of ‘gold ingot’ that focuses on adoption behavior is constructed. The study found that the research mainly involves three contents in the current: adoption behavior of corporate users, adoption behavior of rural households and adoption behavior of individual users. Based on the above literature analysis, this study proposes a theoretical framework for research on the adoption behavior of water efficiency labeling.

Environmental air pollution management system: Predicting user adoption behavior of big data analytics

This study has a dual purpose: to explore the novel phenomenon of a big data analytics-environmental air pollution (BDA-EAP) management system, and to propose a research model of factors influencing adoption of such a system. The research model is based on task-technology fit (TTF) and unified theory of acceptance and use of technology (UTAUT) concepts. A comprehensive BDA-EAP management system is proposed and the potential adoption speed of such a system evaluated by sending structured questionnaires to the employees of relevant environmental agencies, yielding 412 valid responses, using the structural equation modeling approach. The results of the study predict that factors of TTF including task characteristics and technology characteristics are strong influencers of TTF, and TTF is a strong predictor of the behavioral intention of users to adopt a BDA-EAP management system. The results demonstrated that the combination of TTF and UTAUT is a stronger predictor of behavioral intention than either TTF or UTAUT alone. Furthermore, resistance to change negatively moderates and extrinsic motivation positively moderates the significant positive relationship between behavioral intention and adoption of a BDA-EAP management system. Meanwhile, behavioral intention, resistance to change, and extrinsic motivation have a significant three-way interaction impact on adoption of a BDA-EAP management system such that an increase in users’ extrinsic motivation will decrease the negative impact of resistance to change during the process of adoption. The study findings contribute to the literature regarding the use of BDA to manage EAP, and provide a basis for future research in this area.

Antecedent Effects of Info Content on User Attitudes Toward Radical Technology-Brand-Extension

Novel technologies can extend a brand and usher in a new age of digital confluence. The study extends TAM by examining information content as an antecedent to PEOU and PU and the moderating influences of prior knowledge and parent brand memory in early adoption decisions. Potential user attitudes towards novel technological-brand-extensions are captive to the information content that novel technological brand-extensions offer. While information content triggers user awareness, the path from awareness to adoption intention has not received much scrutiny. In surfacing the adoption intention process triggered by information content, we also investigate the roles of prior knowledge of similar products and parent brand memory as moderating influences that guide how information content (as persuasive appeal) is subsequently translated into user adoption behavior.

Research on the Adoption Behavior of Domestic Mobile Health Users: Present Situation and Direction

In recent years, the government has vigorously promoted mobile health services, and the related fields of mobile health are also developing rapidly. The research on mobile health at home and abroad mainly focuses on the present situation, problems and prospects. Users are the experience and consumers of mobile health. As an important part of Internet + Mobile Health, the adoption behavior research of mobile health users is still relatively lacking, most of the research is stuck in qualitative research, and theoretical innovation is also less. By combing the theoretical and practical research on the adoption behavior of mobile health users, this paper looks forward to the future research direction of the adoption behavior of mobile health users, in order to provide reference for future research and industry development.

An Examination of User Adoption Behavior of Autonomous Vehicles and Urban Sustainability Implications

An Examination of User Adoption Behavior of Autonomous Vehicles and Urban Sustainability Implications

The adoption of virtual reality devices: The technology acceptance model integrating enjoyment, social interaction, and strength of the social ties

Recently, the development of virtual reality technology in the entertainment industry has applied social network capability. This study empirically analyzes how the introduction of social network characteristics as a diffusion strategy for virtual reality devices affects consumers’ intention to use. This survey was conducted with 350 people from South Korea, and TAM was used to analyze the acceptability of virtual reality. User adoption behaviors were analyzed rigorously, adding perceived enjoyment, social interactions, and strength of the social ties to the basic TAM. The results of this study indicate that social interactions and strength of the social ties increase perceived enjoyment, and perceived enjoyment has a more significant effect on intention to use than perceived usefulness, which is the main element of TAM. These results have theoretical implications for consumer adoption behavior and empirical implications for the best marketing strategies for virtual reality devices.

Individual-level social influence identification in social media: A learning-simulation coordinated method

This study develops a learning-simulation coordinated method to perform individual-level causal inference and social influence identification in social media. This method uses machine learning models to predict user adoption behavior, uses simulation to infer unobservable potential outcomes, and uses a counterfactual framework to identify individual-level social influence. The method also uses an adjusting strategy to reduce the effect of homophily and correlated unobservables. Empirical results obtained on a synthetic dataset and a semi-synthetic dataset show that the proposed method performs better on causal inference at the individual and aggregate levels than competitive methods. The computational experiment using a real-world database considers three applications, i.e., new product adoption, repeated purchase and cross selling. The empirical results show that the proposed method performs well on identifying influential members. The results reveal that the global hubs and local central nodes of the versatile friend circles have similar influences on the adoption behavior of the followers.

Modeling Students' Perceptions of Simulation-Based Learning Using the Technology Acceptance Model

BackgroundTechnology acceptance research seeks to account for user adoption behaviors, to predict behavioral intentions and use of technologies. MethodsThis mixed-methods study tested a model of technology acceptance in the context of simulation-based learning, and reports on student perceptions of the learning environment in three cases from a Northeastern North American college nursing program using an extended technology acceptance survey instrument and simulation feedback form. ResultsThe model reproduced core and extended factors of perceived usefulness, perceived ease of use, attitude, behavioral intention, subjective norm, fidelity, and self-efficacy but not facilitating conditions. ConclusionsThe findings suggest that in a classroom environment meant to reproduce clinical situations as accurately as possible, students perceive fidelity as influencing their acceptance of SBL but not facilitating conditions. Thus, the extended model explained an important amount of variance in attitudes (R2 = 62.7%) as well as behavioral intentions (R2 = 68.3%) toward a clinically-oriented learning environment for practicing clinical skills, deepening conceptual understanding, applying knowledge, and learning teamwork and communication skills.

Moderating factors influencing adoption of a mobile chronic disease management system in China

ABSTRACTMobile chronic disease management systems (MCDMS) have become increasingly important in recent years, but in China, challenges remain for their adoption. Existing empirical studies have not completely explored the adoption behavior of potential MCDMS users. This article presents a study in which we investigated factors that influence chronically ill patients in China and their families to adopt or decline to use MCDMS. We applied a research model based on the technology acceptance model (TAM) as well as four contextual constructs (perceived disease threat, perceived risk, initial trust, and technology anxiety) to a survey of 279 potential MCDMS service participants in China. Our key findings include: (1) as consistent with current research, both perceived usefulness and perceived ease of use have positive impact on potential users’ MCDMS adoption intention; (2) both perceived disease threat and initial trust have positive impact on MCDMS adoption intention; (3) the impact of perceived risk is negative, and technology anxiety has negative impact on perceived ease of use of MCDMS; (4) young people place more importance on their perceptions of usefulness, ease of operation, and disease threat than middle-aged and older users; (5) family members are more influenced by their perception of ease of use and disease threat than chronically ill patients, while chronically ill patients place more importance on perceived usefulness than family members. This article concludes by discussing the implications of our study for research and practice, as well as limitations and future research directions.

Offering Supplementary Network Technologies: Adoption Behavior and Offloading Benefits

To alleviate the congestion caused by rapid growth in demand for mobile data, wireless service providers (WSPs) have begun encouraging users to offload some of their traffic onto supplementary network technologies, e.g., offloading from 3G or 4G to WiFi or femtocells. With the growing popularity of such offerings, a deeper understanding of the underlying economic principles and their impact on technology adoption is necessary. To this end, we develop a model for user adoption of a base technology (e.g., 3G) and a bundle of the base plus a supplementary technology (e.g., 3G + WiFi). Users individually make their adoption decisions based on several factors, including the technologies' intrinsic qualities, negative congestion externalities from other subscribers, and the flat access rates that a WSP charges. We then show how these user-level decisions translate into aggregate adoption dynamics and prove that these converge to a unique equilibrium for a given set of exogenously determined system parameters. We fully characterize these equilibria and study adoption behaviors of interest to a WSP. We then derive analytical expressions for the revenue-maximizing prices and optimal coverage factor for the supplementary technology and examine some resulting nonintuitive user adoption behaviors. Finally, we develop a mobile app to collect empirical 3G/WiFi usage data and numerically investigate the profit-maximizing adoption levels when a WSP accounts for its cost of deploying the supplemental technology and savings from offloading traffic onto this technology.

An Empirical Study of Smartphone User Behavior

This study investigates determinants of the adoption behavior of smartphone users. Despite the increasing number of smartphone users, the literature on information technology usage has paid little attention to the motivation behind smartphone adoption. This study identifies three determinants of smartphone adoption behavior: innovative characteristics, brand equity and social influences. Data were collected from 293 smartphone users. The analytical results have indicated that users choose to use smartphone not only for its usefulness, enjoyment and compatibility to their lifestyle (i.e. innovative characteristics), but also for its cost effectiveness (i.e. brand equity). Additionally, users will search for related information for the suitability of their adoption decisions (i.e. social influence). Together, the above factors account for over 60 percent of adoption behaviors. Moreover, the findings also indicate that perceptions of use varied over the innovation diffusion stage. Implications and suggestions for practitioners are also discussed.

Broadband Adoption in Regional and Urban Households

Broadband offers key advantages as a communication infrastructure, including efficiency and cost savings which can stimulate productivity, innovation, and ultimately economic growth and social well-being. This paper presents a comparative study on the adoption of broadband in urban and regional areas. It proposes a model concerning broadband adoption which we validate with data collected using a computer-aided telephone survey. We find that relative advantage, utility outcomes, and facilitating conditions play a crucial role in explaining the broadband adoption behavior of both urban and regional household users. In a dynamic environment where technologies are changing quickly, our findings about broadband adoption drivers are useful to stakeholders such as internet service providers, regulators, broadband application developers for encouraging further broadband and application adoption and developments in communication space in both regional and urban areas.

Application of Behavioral Theory in Predicting Consumers Adoption Behavior

A society produces some values, ideas, intentions, and speculations about the human personality. These perceived psychological phenomena depend on rules, regulations, relationships, culture, tradition, etc. Depending on cultural factors, the behavioral intention to adopt online system operated through information and communication technology (ICT) can be affected vividly. Since adoption of ICT potentially depends on citizens’ beliefs and attitude toward technology, adoption behavior of users should be revealed considering citizens behavioral differences. Technology Acceptance Model (TAM) by Davis et al. (1989) is a strong information system theory that models how users come to accept and use a technology. However, the foundation of TAM including many other ICT adoption models has been developed from the deep insight of two popular and widely used behavioral theories named Theory of Reasoned Action (TRA) and the Theory of Planned Behavior (TPB). To understand ICT adoption behavior, these two theories can provide generalized concept of human behavioral attitude and different beliefs which ultimately lead to behavioral intention to adopt ICT. This study has set its first objective to explore TRA and TPB as the theoretical foundation of behavioral attitude toward ICT-based online adoption. Then, based on that theoretical paradigm, our second objective focuses on developing a theoretical framework of revealing generalized ICT adoption and diffusion behavior.