scispace - formally typeset
Search or ask a question
Posted Content

Unified Theory of Acceptance and Use of Technology: A Synthesis and the Road Ahead

TL;DR: A multi-level framework that integrates the notion of research context and cross-context theorizing with the theory evaluation framework to synthesize the existing UTAUT extensions across both the dimensions and the levels of the research context is proposed.
Abstract: The unified theory of acceptance and use of technology (UTAUT) is a little over a decade old and has been used extensively in information systems (IS) and other fields, as the large number of citations to the original paper that introduced the theory evidences. In this paper, we review and synthesize the IS literature on UTAUT from September 2003 until December 2014, perform a theoretical analysis of UTAUT and its extensions, and chart an agenda for research going forward. Based on Weber’s (2012) framework of theory evaluation, we examined UTAUT and its extensions along two sets of quality dimensions; namely, the parts of a theory and the theory as a whole. While our review identifies many merits to UTAUT, we also found that the progress related to this theory has hampered further theoretical development in research into technology acceptance and use. To chart an agenda for research that will enable significant future work, we analyze the theoretical contributions of UTAUT using Whetten’s (2009) notion of cross-context theorizing. Our analysis reveals several limitations that lead us to propose a multi-level framework that can serve as the theoretical foundation for future research. Specifically, this framework integrates the notion of research context and cross-context theorizing with the theory evaluation framework to: (1) synthesize the existing UTAUT extensions across both the dimensions and the levels of the research context and (2) highlight promising research directions. We conclude with recommendations for future UTAUT-related research using the proposed framework.
Citations
More filters
Journal ArticleDOI
TL;DR: A first step toward an inclusive big data research agenda for IS is offered by focusing on the interplay between big data’s characteristics, the information value chain encompassing people-process-technology, and the three dominant IS research traditions (behavioral, design, and economics of IS).
Abstract: Big data has received considerable attention from the information systems (IS) discipline over the past few years, with several recent commentaries, editorials, and special issue introductions on the topic appearing in leading IS outlets. These papers present varying perspectives on promising big data research topics and highlight some of the challenges that big data poses. In this editorial, we synthesize and contribute further to this discourse. We offer a first step toward an inclusive big data research agenda for IS by focusing on the interplay between big data’s characteristics, the information value chain encompassing people-process-technology, and the three dominant IS research traditions (behavioral, design, and economics of IS). We view big data as a disruption to the value chain that has widespread impacts, which include but are not limited to changing the way academics conduct scholarly work. Importantly, we critically discuss the opportunities and challenges for behavioral, design science, and economics of IS research and the emerging implications for theory and methodology arising due to big data’s disruptive effects.

543 citations

Journal ArticleDOI
TL;DR: The practical contribution of this paper is the discussion of how blockchain can alleviate the issue of financial exclusion in rural India, thereby providing a basis for a solution that could connect rural Indians to global supply chain networks.

191 citations

Journal ArticleDOI
TL;DR: In this article, the authors studied the important factors which help explain consumer intention and use behavior in mobile banking (m-banking) adoption and found that most of the predictors of intention, including perceived value, performance expectancy, habit, social influence, effort expectancy, hedonic motivation (except for facilitating condition), perceived risk and trust, are significant.
Abstract: The purpose of this paper is to study the important factors which help explain consumer intention and use behavior in mobile banking (m-banking) adoption. All constructs of the unified theory of acceptance and use of technology 2 are studied. Non-monetary value is studied through perceived value. Trust and perceived risk are also included to predict intention.,A questionnaire was utilized to evaluate customer responses on a five-point Likert scale. A convenience sampling technique was used to collect data from a sample of 490 respondents in Pakistan. The data were analyzed using AMOS and SPSS for Cronbach’s α, CR, CMV, AVE, Harmon’s single factor test, correlation and structural equation modeling.,The results of the study show that most of the predictors of intention, including perceived value, performance expectancy, habit, social influence, effort expectancy, hedonic motivation (except for facilitating condition), perceived risk and trust, are significant. All predictors of usage behavior are significant.,A cross-sectional study was conducted due to time constraints.,Bank managers must focus on improving customers’ intentions to use m-banking as well as on providing facilitating conditions to increase its actual use. To boost mobile banking, banks’ management must consider the customers’ habits while designing their m-banking products.,The findings of this paper are not only interesting in terms of boosting m-banking diffusion rate, but also in terms of financial inclusion of the vast majority of mobile users. Further the impact of intention, facilitating condition and habit were checked on actual use behavior since people tend not always to act upon their intentions.

176 citations

Journal ArticleDOI
TL;DR: An objective of this study is to bring back much needed focus on motivation dichotomy from the consumer perspective by a systematic review and meta-analysis of hedonic motivation an affective construct in UTAUT2 studies.

174 citations


Cites methods from "Unified Theory of Acceptance and Us..."

  • ...This study deemed an integrated approach of “narrative review”, “citation reference search” and “meta-analysis” as appropriate to synthesise research findings from UTAUT2 based studies ( e.g., Dwivedi et al,, 2017; King & He, 2006; Venkatesh et al., 2016; Zhao et al., 2017)....

    [...]

Journal ArticleDOI
TL;DR: This project will develop and test a pharmacosurveillance blockchain system that will support information sharing along the official drug distribution network and test its functions in a simulated network.
Abstract: Background: Drug counterfeiting is a global problem with significant risks to consumers and the general public In the Philippines, 30% of inspected drug stores in 2003 were found with substandard/spurious/falsely-labeled/falsified/counterfeit drugs The economic burden on the population drug expenditures and on governments is high The Philippine Food and Drug Administration (FDA) encourages the public to check the certificates of product registration and report any instances of counterfeiting The National Police of Philippines responds to such reports through a special task force However, no literature on its impact on the distribution of such drugs were found Blockchain technology is a cryptographic ledger that is allegedly immutable through repeated sequential hashing and fault-tolerant through a consensus algorithm This project will develop and test a pharmacosurveillance blockchain system that will support information sharing along the official drug distribution network Objective: This study aims to develop a pharmacosurveillance blockchain system and test its functions in a simulated network Methods: We are developing a Distributed Application (DApp) that will run on smart contracts, employing Swarm as the Distributed File System (DFS) Two instances will be developed: one for Ethereum and another for Hyperledger Fabric The proof-of-work (PoW) consensus algorithm of Ethereum will be modified into a delegated proof-of-stake (DPoS) or practical Byzantine fault tolerance (PBFT) consensus algorithm as it is scalable and fits the drug supply chain environment The system will adopt the GS1 pedigree standard and will satisfy the data points in the data standardization guidelines from the US FDA Simulations will use the following 5 nodes: for FDA, manufacturer, wholesaler, retailer, and the consumer portal Results: Development is underway The design of the system will place FDA in a supervisory data verification role, with each pedigree type–specific data source serving a primary data verification role The supply chain process will be initiated by the manufacturer, with recursive verification for every transaction It will allow consumers to scan a code printed on the receipt of their purchases to review the drug distribution history Conclusions: Development and testing will be conducted in a simulated network, and thus, results may differ from actual practice The project being proposed is disruptive; once tested, the team intends to engage the Philippine FDA to discuss implementation plans and formulate policies to facilitate adoption and sustainability Registered Report Identifier: RR1-102196/10163

166 citations


Cites methods from "Unified Theory of Acceptance and Us..."

  • ...The assessment of adoption potential at the feature level using the unified theory of acceptance and use of technology (UTAUT) and its extensions [24] for each affected sector may be performed once the technology has been developed and tested....

    [...]

References
More filters
01 Jan 1989
TL;DR: Regression analyses suggest that perceived ease of use may actually be a causal antecdent to perceived usefulness, as opposed to a parallel, direct determinant of system usage.

40,975 citations


"Unified Theory of Acceptance and Us..." refers background in this paper

  • ...Note that we did not count studies that integrated TAM (Davis, 1989) and its updates (e.g., TAM3: Venkatesh & Bala, 2008) in this category but as general citations....

    [...]

  • ...Excludes studies that integrate with TAM/TAM2/TAM3....

    [...]

  • ...Summary of UTAUT Integrations Source Technology Dependent variable Theoretical foundation Role of UTAUT Other mechanisms Guo & Barnes (2011, 2012) Virtual world Purchase intention Motivation theory, transaction cost theory, and UTAUT Performance expectancy, effort expectancy, and social influences affect intention Perceived value, enjoyment, general achievement, and habit Hess et al. (2010) Online discussion forum Intention to use Equity-implementation model (Joshi, 1991) and UTAUT Main effects in UTAUT Perceived equity Hong et al. (2011) Agile IS User acceptance Tripartite model of attitude (e.g., Eagly & Chaiken, 1993), status quo bias, omission bias, and the availability heuristic Performance expectancy, effort expectancy, social influences, and facilitating conditions affect Intention Disconfirmation and satisfaction, comfort with change, habit, and personal innovativeness Kim et al. (2007) Portfolio of IT applications IT use IS success model (DeLone & McLean, 1992) and UTAUT Performance expectancy and social influences affect IT utilization User satisfaction affects IT use Lian & Yen (2014) Online shopping User acceptance Innovation resistance theory and UTAUT Main effects of UTAUT as the drivers of online shopping acceptance Usage, value, risk, image, and tradition as the barriers of online shopping acceptance Miltgen, Popovic, & Oliveira (2013) Biometrics User acceptance Technology acceptance model (TAM), diffusion of innovations (DOI), and UTAUT Social influences and facilitating conditions affect user acceptance Innovativeness and compatibility from DOI, perceived usefulness and perceived ease of use from TAM, trust, privacy concern, and perceived risks Oliveira, Faria, Thomas, & Popovic (2014) Mobile banking User adoption Task-technology fit theory (TTF), initial trust model, and UTAUT Main effects of UTAUT and the moderating effects of age and gender Task-technology fit affects performance expectancy and adoption intention, environmental factors and performance expectancy affect initial trust that in turn influences adoption intention Pramatari & Theotokis (2009) RFID-enabled services Consumer acceptance Theory of planned behavior (Fishbein & Ajzen, 1975) Performance expectancy and effort expectancy affect attitude Attitude, technology anxiety, and privacy concern Sun, Liu, Peng, Dong, & Barnes (2014) Social networking Continuance intention IS continuance, flow theory, social capital theory, and UTAUT Main effects of social influence and effort expectancy User satisfaction, perceived enjoyment, norms, trust, tie strength, and perceived usefulness Venkatesh et al. (2011) E-government technology Continuance intention IS continuance model (Bhattacherjee & Premkumar, 2004) and trust (e.g., McKnight, Choudhury, & Kacmar, 2002) Performance expectancy, effort expectancy, social influences, and facilitating conditions as pre-usage beliefs, disconfirmation, and post-usage beliefs Trust, satisfaction, and attitude Yoo et al. (2012) E-learning in the workplace Intention to use Motivation theory (e.g., Calder & Staw, 1975): extrinsic motivation and intrinsic motivation affect intention Performance expectancy, social influences, and facilitating conditions as components of extrinsic motivation; effort expectancy as a component of intrinsic motivation Attitude and anxiety as components of intrinsic motivation Zhou et al. (2010) Mobile banking User adoption Task-technology fit theory (Goodhue & Thompson, 1995) and UTAUT Performance expectancy, effort expectancy, social influences, and facilitating conditions affect user adoption Task-technology fit affects performance expectancy and user adoption; technology characteristics affects effort expectancy Volume 17 Issue 5 3.3 Review of UTAUT Extensions We found four main types of UTAUT extensions: new exogenous mechanisms, new endogenous mechanisms, new moderating mechanisms, and new outcome mechanisms....

    [...]

  • ...Note that we did not count studies that applied TAM (Davis, 1989) and its updates (e.g., TAM3: Venkatesh & Bala, 2008) in this category but as general citations....

    [...]

  • ...Excludes studies that applied TAM/TAM2/TAM3....

    [...]

Book
01 Jun 1975

36,032 citations


"Unified Theory of Acceptance and Us..." refers background in this paper

  • ...…trust that in turn influences adoption intention Pramatari & Theotokis (2009) RFID-enabled services Consumer acceptance Theory of planned behavior (Fishbein & Ajzen, 1975) Performance expectancy and effort expectancy affect attitude Attitude, technology anxiety, and privacy concern Sun, Liu,…...

    [...]

Journal ArticleDOI
TL;DR: The Unified Theory of Acceptance and Use of Technology (UTAUT) as mentioned in this paper is a unified model that integrates elements across the eight models, and empirically validate the unified model.
Abstract: Information technology (IT) acceptance research has yielded many competing models, each with different sets of acceptance determinants. In this paper, we (1) review user acceptance literature and discuss eight prominent models, (2) empirically compare the eight models and their extensions, (3) formulate a unified model that integrates elements across the eight models, and (4) empirically validate the unified model. The eight models reviewed are the theory of reasoned action, the technology acceptance model, the motivational model, the theory of planned behavior, a model combining the technology acceptance model and the theory of planned behavior, the model of PC utilization, the innovation diffusion theory, and the social cognitive theory. Using data from four organizations over a six-month period with three points of measurement, the eight models explained between 17 percent and 53 percent of the variance in user intentions to use information technology. Next, a unified model, called the Unified Theory of Acceptance and Use of Technology (UTAUT), was formulated, with four core determinants of intention and usage, and up to four moderators of key relationships. UTAUT was then tested using the original data and found to outperform the eight individual models (adjusted R2 of 69 percent). UTAUT was then confirmed with data from two new organizations with similar results (adjusted R2 of 70 percent). UTAUT thus provides a useful tool for managers needing to assess the likelihood of success for new technology introductions and helps them understand the drivers of acceptance in order to proactively design interventions (including training, marketing, etc.) targeted at populations of users that may be less inclined to adopt and use new systems. The paper also makes several recommendations for future research including developing a deeper understanding of the dynamic influences studied here, refining measurement of the core constructs used in UTAUT, and understanding the organizational outcomes associated with new technology use.

27,798 citations

Journal ArticleDOI
TL;DR: In this paper, the authors developed and tested a theoretical extension of the TAM model that explains perceived usefulness and usage intentions in terms of social influence and cognitive instrumental processes, which was tested using longitudinal data collected regarding four different systems at four organizations (N = 156), two involving voluntary usage and two involving mandatory usage.
Abstract: The present research develops and tests a theoretical extension of the Technology Acceptance Model (TAM) that explains perceived usefulness and usage intentions in terms of social influence and cognitive instrumental processes. The extended model, referred to as TAM2, was tested using longitudinal data collected regarding four different systems at four organizations ( N = 156), two involving voluntary usage and two involving mandatory usage. Model constructs were measured at three points in time at each organization: preimplementation, one month postimplementation, and three months postimplementation. The extended model was strongly supported for all four organizations at all three points of measurement, accounting for 40%--60% of the variance in usefulness perceptions and 34%--52% of the variance in usage intentions. Both social influence processes (subjective norm, voluntariness, and image) and cognitive instrumental processes (job relevance, output quality, result demonstrability, and perceived ease of use) significantly influenced user acceptance. These findings advance theory and contribute to the foundation for future research aimed at improving our understanding of user adoption behavior.

16,513 citations

Journal ArticleDOI
TL;DR: A large number of studies have been conducted during the last decade and a half attempting to identify those factors that contribute to information systems success, but the dependent variable in these studies-I/S success-has been an elusive one to define.
Abstract: A large number of studies have been conducted during the last decade and a half attempting to identify those factors that contribute to information systems success. However, the dependent variable in these studies-I/S success-has been an elusive one to define. Different researchers have addressed different aspects of success, making comparisons difficult and the prospect of building a cumulative tradition for I/S research similarly elusive. To organize this diverse research, as well as to present a more integrated view of the concept of I/S success, a comprehensive taxonomy is introduced. This taxonomy posits six major dimensions or categories of I/S success-SYSTEM QUALITY, INFORMATION QUALITY, USE, USER SATISFACTION, INDIVIDUAL IMPACT, and ORGANIZATIONAL IMPACT. Using these dimensions, both conceptual and empirical studies are then reviewed a total of 180 articles are cited and organized according to the dimensions of the taxonomy. Finally, the many aspects of I/S success are drawn together into a descriptive model and its implications for future I/S research are discussed.

10,023 citations


Additional excerpts

  • ...…and satisfaction, comfort with change, habit, and personal innovativeness Kim et al. (2007) Portfolio of IT applications IT use IS success model (DeLone & McLean, 1992) and UTAUT Performance expectancy and social influences affect IT utilization User satisfaction affects IT use Lian & Yen…...

    [...]