Causal paths to acceptance of technological innovations by individual employees

Despite much research on organizations’ adoption of innovation, little is currently known about individual employees have gone about it. The purpose of this paper is to empirically investigate the determinants that address individual employees’ decisions concerning innovation in the workplace.,Data were collected from 272 employees from a tertiary education institution in Australia using a structured instrument.,Results from the structural equation modeling analysis indicate that enjoyment and motivation impact significantly on attitudes to an innovation, which, in turn, affects how employees behave toward it.,Furthermore, organizational patronage, innovativeness and self-image have been found to influence the innovation adoption process. These findings have implications for the effective management and implementation of an innovation at the individual level.,Although innovation adoption has been studied extensively, drivers of adoption and research on individual innovation acceptance remain limited. Designing an effective approach for increasing end-user acceptance and subsequent use of innovation continues to be a fundamental challenge. The current literature indicates that we know relatively little about the ways in which individuals adopt and the factors that influence individual adoption of innovation. This study is designed to fill that gap. The identification of the factors is important to create a work environment that is conducive to individual adoption of innovation and thereby gain the expected benefits from the innovation.

[1]  Peter A. Todd,et al.  Understanding Information Technology Usage: A Test of Competing Models , 1995, Inf. Syst. Res..

[2]  Yi-Shun Wang,et al.  Factors affecting hotels' adoption of mobile reservation systems: A technology-organization-environment framework , 2016 .

[3]  D. Sappington Incentives in Principal-Agent Relationships , 1991 .

[4]  P. Attewell Technology Diffusion and Organizational Learning: The Case of Business Computing , 1992 .

[5]  Viswanath Venkatesh,et al.  A Longitudinal Investigation of Personal Computers in Homes: Adoption Determinants and Emerging Challenges , 2001, MIS Q..

[6]  Sang M. Lee,et al.  The role of exogenous factors in technology acceptance: The case of object-oriented technology , 2006, Inf. Manag..

[7]  H. Nguyen Critical factors in e-business adoption: Evidence from Australian transport and logistics companies , 2013 .

[8]  Vincent S. Lai,et al.  Prediction of Internet and World Wide Web usage at work: a test of an extended Triandis model , 2000, Decis. Support Syst..

[9]  Izak Benbasat,et al.  Integrating Diffusion of Innovations and Theory of Reasoned Action models to predict utilization of information technology by end-users , 1996 .

[10]  Gary Garrison,et al.  Investigating mobile wireless technology adoption: An extension of the technology acceptance model , 2009, Inf. Syst. Frontiers.

[11]  Pei-Fang Hsu,et al.  International Journal of Information Management , 2014 .

[12]  Milena M. Head,et al.  Understanding student attitudes of mobile phone features: Rethinking adoption through conjoint, cluster and SEM analyses , 2012, Comput. Hum. Behav..

[13]  Susan A. Brown,et al.  E-Learning and Individual Characteristics: The Role of Computer Anxiety and Communication Apprehension , 2006, J. Comput. Inf. Syst..

[14]  DongPing Tang,et al.  A review of the evolution of research on information Technology Acceptance Model , 2011, 2011 International Conference on Business Management and Electronic Information.

[15]  D. Walker,et al.  Exploratory factors influencing information and communication technology diffusion and adoption within Australian construction organizations: a micro analysis , 2005 .

[16]  Paul A. Pavlou,et al.  Understanding and Predicting Electronic Commerce Adoption: An Extension of the Theory of Planned Behavior , 2006, MIS Q..

[17]  James D. Westaby,et al.  Behavioral reasoning theory: Identifying new linkages underlying intentions and behavior , 2005 .

[18]  Eugenia Y. Huang,et al.  The Acceptance of Women-Centric Websites , 2005, J. Comput. Inf. Syst..

[19]  John Ingham,et al.  Why do people use information technology? A critical review of the technology acceptance model , 2003, Inf. Manag..

[20]  Sheng Gao,et al.  Attitude towards Knowledge Sharing Behavior , 2005, J. Comput. Inf. Syst..

[21]  Fred D. Davis,et al.  User Acceptance of Computer Technology: A Comparison of Two Theoretical Models , 1989 .

[22]  Ronald M. Lee,et al.  A logic programming framework for planning and simulation , 1986 .

[23]  Martin Wetzels,et al.  A meta-analysis of the technology acceptance model: Investigating subjective norm and moderation effects , 2007, Inf. Manag..

[24]  Stephen B. Johnson,et al.  Grounding a new information technology implementation framework in behavioral science: a systematic analysis of the literature on IT use , 2003, J. Biomed. Informatics.

[25]  Anol Bhattacherjee Managerial Influences on Intraorganizational Information Technology Use: A Principal-Agent Model , 1998 .

[26]  Vallabh Sambamurthy,et al.  Sources of Influence on Beliefs about Information Technolgoy Use: An Empirical Study of Knowledge Workers , 2003, MIS Q..

[27]  Zhan Wu,et al.  How Individual Differences Influence Technology Usage Behavior? Toward an Integrated Framework , 2005, J. Comput. Inf. Syst..

[28]  I. Ajzen The theory of planned behavior , 1991 .

[29]  Sumeet Gupta,et al.  Value-based Adoption of Mobile Internet: An empirical investigation , 2007, Decis. Support Syst..

[30]  Chang Liu,et al.  Facilitating Conditions, Wireless Trust and Adoption Intention , 2005, J. Comput. Inf. Syst..

[31]  Ángel Francisco Agudo-Peregrina,et al.  Behavioral intention, use behavior and the acceptance of electronic learning systems: Differences between higher education and lifelong learning , 2014, Comput. Hum. Behav..

[32]  S. Counsell,et al.  A conceptual model for the process of IT innovation adoption in organizations , 2012 .

[33]  Fred D. Davis,et al.  A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies , 2000, Management Science.

[34]  R. Vallerand Toward A Hierarchical Model of Intrinsic and Extrinsic Motivation , 1997 .

[35]  Jen-Her Wu,et al.  What drives mobile commerce?: An empirical evaluation of the revised technology acceptance model , 2005, Inf. Manag..

[36]  Gaby Haddow,et al.  The Mobile Library and Staff Preparedness: Exploring Staff Competencies Using the Unified Theory of Acceptance and Use of Technology Model , 2011 .

[37]  Wei-Tsong Wang,et al.  Examining the adoption of KMS in organizations from an integrated perspective of technology, individual, and organization , 2014, Comput. Hum. Behav..

[38]  Waiman Cheung,et al.  Determinants of the intention to use Internet/WWW at work: a confirmatory study , 2001, Inf. Manag..

[39]  Hsiu-Fen Lin Understanding the determinants of electronic supply chain management system adoption: Using the technology–organization–environment framework , 2014 .

[40]  Andrew Schwarz,et al.  Toward a deeper understanding of IT adoption: A multilevel analysis , 2014, Inf. Manag..

[41]  Juan Sánchez-Fernández,et al.  The moderating effect of experience in the adoption of mobile payment tools in Virtual Social Networks: The m-Payment Acceptance Model in Virtual Social Networks (MPAM-VSN) , 2014, Int. J. Inf. Manag..

[42]  Tuure Tuunanen,et al.  Consumers' adoption of information services , 2013, Inf. Manag..

[43]  Ziqi Liao,et al.  An empirical study on organizational acceptance of new information systems in a commercial bank environment , 2000, Proceedings of the 33rd Annual Hawaii International Conference on System Sciences.

[44]  Hans van der Heijden,et al.  User Acceptance of Hedonic Information Systems , 2004, MIS Q..

[45]  Juan Sánchez-Fernández,et al.  Antecedents of the adoption of the new mobile payment systems: The moderating effect of age , 2014, Comput. Hum. Behav..

[46]  G. Zaltman,et al.  Innovations and organizations , 2020, Organizational Innovation.

[47]  Alain Yee-Loong Chong,et al.  A SEM-neural network approach for understanding determinants of interorganizational system standard adoption and performances , 2012, Decis. Support Syst..

[48]  Viswanath Venkatesh,et al.  Technology Acceptance Model 3 and a Research Agenda on Interventions , 2008, Decis. Sci..

[49]  Adel M. Aladwani A Deeper Look at the Attitude-Behavior Consistency Assumption in Information Systems Satisfaction Research , 2003, J. Comput. Inf. Syst..

[50]  E. Rogers,et al.  Diffusion of Innovations , 1964 .

[51]  Russell K.H. Ching,et al.  A proposed framework for transitioning to an e-business model , 2001 .

[52]  Thomas Hill,et al.  Role of efficacy expectations in predicting the decision to use advanced technologies: The case of computers. , 1987 .

[53]  Alok Mishra,et al.  Theory of Reasoned Action application for Green Information Technology acceptance , 2014, Comput. Hum. Behav..

[54]  Diane Poremsky Sams Teach Yourself Microsoft Office Outlook 2003 in 24 Hours , 2003 .

[55]  Magid Igbaria,et al.  User acceptance of microcomputer technology: An empirical test , 1993 .

[56]  Berend Wierenga,et al.  Intra-firm Adoption Decisions:: Role of Inter-firm and Intra-firm Variables , 2002 .

[57]  Kamel Rouibah,et al.  Factors affecting camera mobile phone adoption before e-shopping in the Arab world , 2011 .

[58]  Said S. Al-Gahtani,et al.  Empirical investigation of e-learning acceptance and assimilation: A structural equation model , 2016 .

[59]  Tiago Oliveira,et al.  Mobile payment: Understanding the determinants of customer adoption and intention to recommend the technology , 2016, Comput. Hum. Behav..

[60]  Debra L. Nelson,et al.  Individual Adjustment to Information-Driven Technologies: A Critical Review , 1990, MIS Q..

[61]  Fred D. Davis Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology , 1989, MIS Q..

[62]  T. Lam,et al.  A study of hotel employee behavioral intentions towards adoption of information technology , 2007 .

[63]  K. Atuahene–Gima,et al.  Resolving the Capability–Rigidity Paradox in New Product Innovation , 2005 .

[64]  A. Bandura Social Foundations of Thought and Action: A Social Cognitive Theory , 1985 .

[65]  Kun-Huang Huarng,et al.  Viral effects of social network and media on consumers’ purchase intention , 2015 .

[66]  William R. Darden,et al.  Work and/or Fun: Measuring Hedonic and Utilitarian Shopping Value , 1994 .

[67]  Gordon B. Davis,et al.  Testing the Determinants of Microcomputer Usage via a Structural Equation Model , 1995, J. Manag. Inf. Syst..

[68]  Mun Y. Yi,et al.  Understanding information technology acceptance by individual professionals: Toward an integrative view , 2006, Inf. Manag..

[69]  Sung Youl Park,et al.  An Analysis of the Technology Acceptance Model in Understanding University Students' Behavioral Intention to Use e-Learning , 2009, J. Educ. Technol. Soc..

[70]  Gordon B. Davis,et al.  User Acceptance of Information Technology: Toward a Unified View , 2003, MIS Q..

[71]  Magid Igbaria,et al.  A Motivational Model of Microcomputer Usage , 1996, J. Manag. Inf. Syst..

[72]  Chang-Hyun Jin,et al.  The effects of individual innovativeness on users' adoption of Internet content filtering software and attitudes toward children's Internet use , 2013, Comput. Hum. Behav..

[73]  Linda G. Wallace,et al.  The adoption of software measures: A technology acceptance model (TAM) perspective , 2014, Inf. Manag..

[74]  Viswanath Venkatesh,et al.  Expectation Confirmation in Information Systems Research: A Test of Six Competing Models , 2014, MIS Q..

[75]  Chuang-Chun Liu,et al.  An empirical investigation of factors influencing the adoption of data mining tools , 2012, Int. J. Inf. Manag..

[76]  Katherine M. White,et al.  Predicting adolescents' use of social networking sites from an extended theory of planned behaviour perspective , 2010, Comput. Hum. Behav..

[77]  Daniel K. Maduku,et al.  Understanding mobile marketing adoption intention by South African SMEs: A multi-perspective framework , 2016, Int. J. Inf. Manag..

[78]  Janneke K. Oostrom,et al.  New technology in personnel selection: How recruiter characteristics affect the adoption of new selection technology , 2013, Comput. Hum. Behav..

[79]  Jatinder N. D. Gupta,et al.  Improving Workers' Productivity and Reducing Internet Abuse , 2004, J. Comput. Inf. Syst..

[80]  Son K. Lam,et al.  Exploring the dynamics of antecedents to consumer–brand identification with a new brand , 2013 .

[81]  Greg Preston,et al.  Web-based lecture technologies and learning and teaching: a study of change in four Australian universities , 2010 .

[82]  Jongsu Lee,et al.  Technology adoption: A conjoint analysis of consumers' preference on future online banking services , 2015, Inf. Syst..

[83]  Barney Dalgarno,et al.  Digital divides? Student and staff perceptions of information and communication technologies , 2010, Comput. Educ..

[84]  Timo Saari,et al.  Understanding the most influential user experiences in successful and unsuccessful technology adoptions , 2015, Comput. Hum. Behav..

[85]  William R. King,et al.  A meta-analysis of the technology acceptance model , 2006, Inf. Manag..

[86]  Magid Igbaria,et al.  Personal Computing Acceptance Factors in Small Firms: A Structural Equation Model , 1997, MIS Q..

[87]  Said S. Al-Gahtani,et al.  Attitudes, satisfaction and usage: Factors contributing to each in the acceptance of information technology , 1999, Behav. Inf. Technol..

[88]  Barney Dalgarno,et al.  An Australian and New Zealand scoping study on the use of 3D immersive virtual worlds in higher education , 2011 .

[89]  Jane M. Howell,et al.  Personal Computing: Toward a Conceptual Model of Utilization , 1991, MIS Q..

[90]  M. Conner,et al.  Extending the Theory of Planned Behavior: A Review and Avenues for Further Research , 1998 .

[91]  Zawiyah Mohammad Yusof,et al.  Data Mining Technology Adoption in Institutions of Higher Learning: A Conceptual Framework Incorporating Technology Readiness Index Model and Technology Acceptance Model 3 , 2014 .

[92]  N. Schillewaert,et al.  Organizational innovation adoption: a multi-level framework of determinants and opportunities for future research , 2002 .

[93]  Viswanath Venkatesh,et al.  Determinants of Perceived Ease of Use: Integrating Control, Intrinsic Motivation, and Emotion into the Technology Acceptance Model , 2000, Inf. Syst. Res..

[94]  Yong-Ki Lee,et al.  The intention to use computerized reservation systems: the moderating effects of organizational support and supplier incentive , 2005 .

[95]  Hayagreeva Rao,et al.  Agency Theory and Uncertainty in Organizations: An Evaluation , 1994 .

[96]  Bo-Christer Björk,et al.  A Longitudinal Study of the Adoption of IT Technology in the Swedish Building Sector , 2014 .