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Innovation characteristics and innovation adoption-implementation: A meta-analysis of findings
Abstract
A review and meta-analysis was performed of seventy-five articles concerned with innovation characteristics and their relationship to innovation adoption and implementation. One part of the analysis consisted of constructing a methodological profile of the existing studies, and contrasting this with a hypothetical optimal approach. A second part of the study employed meta-analytic statistical techniques to assess the generality and consistency of existing empirical findings. Three innovation characteristics (compatibility, relative advantage, and complexity) had the most consistent significant relationship to innovation adoption. Suggestions for future research in the area were made.
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Cited by
Perceived usefulness, perceived ease of use, and user acceptance of information technology
Davis, F. D. (1989) · MIS Quarterly · doi:10.2307/249008 · Cited by 68,483
User Acceptance of Information Technology: Toward A Unified View1
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003) · MIS Quarterly · doi:10.2307/30036540 · Cited by 45,035
Moore, G. C., & Benbasat, I. (1991) · Information Systems Research · doi:10.1287/isre.2.3.192 · Cited by 9,150
Understanding information technology usage: a test of competing models
Taylor, S., & Todd, P. A. (1995) · Information Systems Research · doi:10.1287/isre.6.2.144 · Cited by 8,815
Diffusion of Innovations in Service Organizations: Systematic Review and Recommendations
GREENHALGH, T., ROBERT, G., MACFARLANE, F., BATE, P., & KYRIAKIDOU, O. (2004) · The Milbank Quarterly · doi:10.1111/j.0887-378x.2004.00325.x · Cited by 7,448
Organizational innovation: A meta-analysis of effects of determinants and moderators
Damanpour, F. (1991) · Academy of Management Journal · doi:10.2307/256406 · Cited by 6,542
Task-Technology Fit and Individual Performance
Goodhue, D. L., & Thompson, R. L. (1995) · MIS Quarterly · doi:10.2307/249689 · Cited by 6,006
Agarwal, R., & Prasad, J. (1998) · Information Systems Research · doi:10.1287/isre.9.2.204 · Cited by 3,575
The utilization of e-government services: citizen trust, innovation and acceptance factors
Carter, L., & Bélanger, F. (2005) · Information Systems Journal · doi:10.1111/j.1365-2575.2005.00183.x · Cited by 2,207
Dwivedi, Y. K., Rana, N. P., Jeyaraj, A., Clement, M., & Williams, M. D. (2019) · Information Systems Frontiers · doi:10.1007/s10796-017-9774-y · Cited by 2,137
“Rooted in sociology, the innovation diffusion theory (IDT) (Rogers 1995) has been used to study a number of innovations ranging from agricultural tools to organizational innovation (Tornatzky and Klein 1982).”
MethodThe Challenge of Innovation Implementation
Klein, K. J., & Sorra, J. S. (1996) · The Academy of Management Review · doi:10.2307/259164 · Cited by 2,113
Self-citationCreativity syndrome: Integration, application, and innovation.
Mumford, M. D., & Gustafson, S. B. (1988) · Psychological Bulletin · doi:10.1037/0033-2909.103.1.27 · Cited by 1,766
An Integrated Model of Information Systems Adoption in Small Businesses
Thong, J. Y. L. (1999) · Journal of Management Information Systems · doi:10.1080/07421222.1999.11518227 · Cited by 1,727
Zhu, K., & Kraemer, K. L. (2005) · Information Systems Research · doi:10.1287/isre.1050.0045 · Cited by 1,723
Agarwal, R., & Prasad, J. (1997) · Decision Sciences · doi:10.1111/j.1540-5915.1997.tb01322.x · Cited by 1,669
Predicting Intention to Adopt Interorganizational Linkages: An Institutional Perspective1
Teo, H. H., Wei, K. K., & Benbasat, I. (2003) · MIS Quarterly · doi:10.2307/30036518 · Cited by 1,639
Zhu, K., Kraemer, K. L., & Xu, S. (2006) · Management Science · doi:10.1287/mnsc.1050.0487 · Cited by 1,440
Information technology acceptance by individual professionals: a model comparison approach
Chau, P. Y. K., & Hu, P. J. (2001) · Decision Sciences · doi:10.1111/j.1540-5915.2001.tb00978.x · Cited by 1,409
Kuan, K. K. Y., & Chau, P. Y. K. (2001) · Information & Management · doi:10.1016/s0378-7206(01)00073-8 · Cited by 1,335
Frambach, R. T., & Schillewaert, N. (2002) · Journal of Business Research · doi:10.1016/s0148-2963(00)00152-1 · Cited by 1,270
Adoption of new information technologies in rural small businesses
Premkumar, G., & Roberts, M. (1999) · Omega · doi:10.1016/s0305-0483(98)00071-1 · Cited by 1,108
Factors Affecting Technology Uses in Schools: An Ecological Perspective
Zhao, Y., & Frank, K. A. (2003) · American Educational Research Journal · doi:10.3102/00028312040004807 · Cited by 947
Chatterjee, D., Grewal, R., & Sambamurthy, V. (2002) · MIS Quarterly · doi:10.2307/4132321 · Cited by 945
Understanding the determinants of RFID adoption in the manufacturing industry
Wang, Y.-M., Wang, Y.-S., & Yang, Y.-F. (2010) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2010.03.006 · Cited by 912
Kleijnen, M., de Ruyter, K., & Wetzels, M. (2007) · Journal of Retailing · doi:10.1016/j.jretai.2006.10.004 · Cited by 898
How the use of big data analytics affects value creation in supply chain management
Chen, D. Q., Preston, D. S., & Swink, M. (2015) · Journal of Management Information Systems · doi:10.1080/07421222.2015.1138364 · Cited by 829
The Assimilation of Software Process Innovations: An Organizational Learning Perspective
Fichman, R. G., & Kemerer, C. F. (1997) · Management Science · doi:10.1287/mnsc.43.10.1345 · Cited by 811
An Empirically Derived Model for the Adoption of Customer‐based Interorganizational Systems*
Grover, V. (1993) · Decision Sciences · doi:10.1111/j.1540-5915.1993.tb01295.x · Cited by 757
Chau, P. Y. K., & Hu, P. J. (2002) · Journal of Management Information Systems · doi:10.1080/07421222.2002.11045699 · Cited by 707
Yang, S., Lu, Y., Gupta, S., Cao, Y., & Zhang, R. (2012) · Computers in Human Behavior · doi:10.1016/j.chb.2011.08.019 · Cited by 679
Hengstler, M., Enkel, E., & Duelli, S. (2016) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2015.12.014 · Cited by 661
An empirical validation of a unified model of electronic government adoption (UMEGA)
Dwivedi, Y. K., Rana, N. P., Janssen, M., Lal, B., Williams, M. D., & Clement, M. (2017) · Government Information Quarterly · doi:10.1016/j.giq.2017.03.001 · Cited by 622
Implementing computerized technology: An organizational analysis.
Klein, K. J., Conn, A. B., & Sorra, J. S. (2001) · Journal of Applied Psychology · doi:10.1037/0021-9010.86.5.811 · Cited by 615
Self-citationThakur, R., & Srivastava, M. (2014) · Internet Research · doi:10.1108/intr-12-2012-0244 · Cited by 606
e-Government Adoption Model (GAM): Differing service maturity levels
Shareef, M. A., Kumar, V., Kumar, U., & Dwivedi, Y. K. (2011) · Government Information Quarterly · doi:10.1016/j.giq.2010.05.006 · Cited by 581
Applying Diffusion of Innovation Theory to Intervention Development
Dearing, J. W. (2009) · Research on Social Work Practice · doi:10.1177/1049731509335569 · Cited by 567
Who will buy electric vehicles? Identifying early adopters in Germany
Plötz, P., Schneider, U., Globisch, J., & Dütschke, E. (2014) · Transportation Research Part A: Policy and Practice · doi:10.1016/j.tra.2014.06.006 · Cited by 517
Zhu, K., Kraemer, K. L., Gurbaxani, V., & Xu, S. X. (2006) · MIS Quarterly · doi:10.2307/25148771 · Cited by 500
A conceptual model for the process of IT innovation adoption in organizations
Hameed, M. A., Counsell, S., & Swift, S. (2012) · Journal of Engineering and Technology Management · doi:10.1016/j.jengtecman.2012.03.007 · Cited by 442
Atun, R., de Jongh, T., Secci, F., Ohiri, K., & Adeyi, O. (2010) · Health Policy and Planning · doi:10.1093/heapol/czp055 · Cited by 427
Building capacity and sustainable prevention innovations: a sustainability planning model
Johnson, K., Hays, C., Center, H., & Daley, C. (2004) · Evaluation and Program Planning · doi:10.1016/j.evalprogplan.2004.01.002 · Cited by 411
Kulviwat, S., Bruner, G. C., & Al-Shuridah, O. (2009) · Journal of Business Research · doi:10.1016/j.jbusres.2007.04.014 · Cited by 406
The adoption of information technology in the sales force
Schillewaert, N., Ahearne, M. J., Frambach, R. T., & Moenaert, R. K. (2005) · Industrial Marketing Management · doi:10.1016/j.indmarman.2004.09.013 · Cited by 362
Aboelmaged, M. G. (2014) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2014.05.002 · Cited by 355
Acceptance and Resistance of New Digital Technologies in Medicine: Qualitative Study
Safi, S., Thiessen, T., & Schmailzl, K. J. (2018) · JMIR Research Protocols · doi:10.2196/11072 · Cited by 346
Online banking adoption: an empirical analysis
Yee‐Loong Chong, A., Ooi, K., Lin, B., & Tan, B. (2010) · International Journal of Bank Marketing · doi:10.1108/02652321011054963 · Cited by 343
The effects of education compatibility and technological expectancy on e-learning acceptance
Chen, J.-L. (2011) · Computers & Education · doi:10.1016/j.compedu.2011.02.009 · Cited by 336
Determinants of E-Business Use in U.S. Firms
Hsu, P.-F., Kraemer, K. L., & Dunkle, D. (2006) · International Journal of Electronic Commerce · doi:10.2753/jec1086-4415100401 · Cited by 330
Technology Adaptation in E-commerce:
Chen, L.-D., & Tan, J. (2004) · European Management Journal · doi:10.1016/j.emj.2003.11.014 · Cited by 306
The fidelity‐adaptation debate: Implications for the implementation of public sector social programs
Blakely, C. H., Mayer, J. P., Gottschalk, R. G., Schmitt, N., Davidson, W. S., Roitman, D. B., & Emshoff, J. G. (1987) · American Journal of Community Psychology · doi:10.1007/bf00922697 · Cited by 297
Factors affecting adoption of online banking: A meta-analytic structural equation modeling study
Montazemi, A. R., & Qahri-Saremi, H. (2015) · Information & Management · doi:10.1016/j.im.2014.11.002 · Cited by 293
Review on IT adoption: insights from recent technologies
Gangwar, H., Date, H., & Raoot, A. D. (2014) · Journal of Enterprise Information Management · doi:10.1108/jeim-08-2012-0047 · Cited by 289
Sharma, R., & Yetton, P. (2007) · MIS Quarterly · doi:10.2307/25148789 · Cited by 285
Adoption of electronic government services among business organizations in Singapore
Tung, L. L., & Rieck, O. (2005) · The Journal of Strategic Information Systems · doi:10.1016/j.jsis.2005.06.001 · Cited by 278
Adoption of online public grievance redressal system in India: toward developing a unified view
Rana, N. P., Dwivedi, Y. K., Williams, M. D., & Weerakkody, V. (2016) · Computers in Human Behavior · doi:10.1016/j.chb.2016.02.019 · Cited by 274
Novins, D. K., Green, A. E., Legha, R. K., & Aarons, G. A. (2013) · Journal of the American Academy of Child & Adolescent Psychiatry · doi:10.1016/j.jaac.2013.07.012 · Cited by 270
A feedback model to understand information system usage
Bajaj, A., & Nidumolu, S. R. (1998) · Information & Management · doi:10.1016/s0378-7206(98)00026-3 · Cited by 266
Organizational context, climate and innovativeness: adoption of imaging technology
Nystrom, P. C., Ramamurthy, K., & Wilson, A. L. (2002) · Journal of Engineering and Technology Management · doi:10.1016/s0923-4748(02)00019-x · Cited by 263
Tsai, J.-M., Cheng, M.-J., Tsai, H.-H., Hung, S.-W., & Chen, Y.-L. (2019) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2019.03.003 · Cited by 257
Xu, S., Zhu, K., & Gibbs, J. (2004) · Electronic Markets · doi:10.1080/1019678042000175261 · Cited by 253
Forecasting Social CRM Adoption in SMEs: A Combined SEM-Neural Network Method
Ahani, A., Rahim, N. Z. A., & Nilashi, M. (2017) · Computers in Human Behavior · doi:10.1016/j.chb.2017.05.032 · Cited by 239
Exploring the public sector adoption of HRIS
Troshani, I., Jerram, C., & Rao Hill, S. (2011) · Industrial Management & Data Systems · doi:10.1108/02635571111118314 · Cited by 236
Michaelis, B., Stegmaier, R., & Sonntag, K. (2010) · Journal of Managerial Psychology · doi:10.1108/02683941011035304 · Cited by 219
Examining student decisions to adopt Web 2.0 technologies: theory and empirical tests
Hartshorne, R., & Ajjan, H. (2009) · Journal of Computing in Higher Education · doi:10.1007/s12528-009-9023-6 · Cited by 220
Navigating the Complexity of Generative AI Adoption in Software Engineering
Russo, D. (2024) · ACM Transactions on Software Engineering and Methodology · doi:10.1145/3652154 · Cited by 217
“In the case of LLMs, having a background in programming languages or NLP could facilitate their adoption in software engineering.”
BackgroundMichaelis, B., Stegmaier, R., & Sonntag, K. (2009) · Journal of Change Management · doi:10.1080/14697010903360608 · Cited by 216
Organizational intention to adopt big data in the B2B context: An integrated view
Sun, S., Hall, D. J., & Cegielski, C. G. (2020) · Industrial Marketing Management · doi:10.1016/j.indmarman.2019.09.003 · Cited by 212
Innovation Modification during Intraorganizational Adoption
Lewis, L. K., & Seibold, D. R. (1993) · The Academy of Management Review · doi:10.2307/258762 · Cited by 193
Differences between early adopters of disruptive and sustaining innovations
Reinhardt, R., & Gurtner, S. (2015) · Journal of Business Research · doi:10.1016/j.jbusres.2014.04.007 · Cited by 169
How to Institutionalize Health Promotion Programs
Steckler, A., & Goodman, R. M. (1989) · American Journal of Health Promotion · doi:10.4278/0890-1171-3.4.34 · Cited by 146
Implementation research: state of the art and future directions
Linton, J. D. (2002) · Technovation · doi:10.1016/s0166-4972(01)00075-x · Cited by 126
Supply chain innovation diffusion: Going beyond adoption
Hazen, B. T., Overstreet, R. E., & Cegielski, C. G. (2012) · The International Journal of Logistics Management · doi:10.1108/09574091211226957 · Cited by 117
Li, Y.-H. (2008) · 2008 International Conference on Management Science and Engineering 15th Annual Conference Proceedings · doi:10.1109/icmse.2008.4668890 · Cited by 112
The assimilation of RFID technology by Chinese companies: A technology diffusion perspective
Wei, J., Lowry, P. B., & Seedorf, S. (2015) · Information & Management · doi:10.1016/j.im.2015.05.001 · Cited by 112
Lin, T. T. C., & Bautista, J. R. (2017) · Journal of Health Communication · doi:10.1080/10810730.2017.1296508 · Cited by 89
Optimizing the language and format of guidelines to improve guideline uptake
Gupta, S., Rai, N., Bhattacharrya, O., Cheng, A. Y. Y., Connelly, K. A., Boulet, L.-P., Kaplan, A., Brouwers, M. C., & Kastner, M. (2016) · Canadian Medical Association Journal · doi:10.1503/cmaj.151102 · Cited by 82
Citizens as consumers: Profiling e-government services’ users in Egypt via data mining techniques
Mostafa, M. M., & El-Masry, A. A. (2013) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2013.03.007 · Cited by 60
Developing and validating a model explaining the assimilation process of RFID: An empirical study
Hossain, M. A., Quaddus, M., & Islam, N. (2016) · Information Systems Frontiers · doi:10.1007/s10796-014-9537-y · Cited by 57
Adoption of Internet and Web Technology for Hotel Marketing: A Study of Hotels in Thailand
Khemthong, S., & Roberts, L. M. (2006) · Journal of Business Systems, Governance and Ethics · doi:10.15209/jbsge.v1i2.74 · Cited by 53
Heidenreich, S., & Talke, K. (2020) · AMS Review · doi:10.1007/s13162-020-00164-x · Cited by 46
Exploring the diffusion of low-energy houses: An empirical study in the European Union
Olsthoorn, M., Schleich, J., & Faure, C. (2019) · Energy Policy · doi:10.1016/j.enpol.2019.03.043 · Cited by 32
Language teachers’ beliefs about using high-immersion virtual reality
Kaplan-Rakowski, R., Dhimolea, T. K., & Khukalenko, I. S. (2023) · Education and Information Technologies · doi:10.1007/s10639-023-11686-9 · Cited by 31
Moderating role of top management support in electronic procurement usage of Jordanian firms
Marei, A., Daoud, L., Ibrahim, M., & Al-Jabaly, S. M. (2021) · Management Science Letters · doi:10.5267/j.msl.2020.11.027 · Cited by 22
SUSTAINING INNOVATIONS IN COMMUNITY PREVENTION SYSTEMS: A DATA‐INFORMED SUSTAINABILITY STRATEGY
Johnson, K., Collins, D., & Wandersman, A. (2013) · Journal of Community Psychology · doi:10.1002/jcop.21540 · Cited by 20
A survey on adoption of e-procurement in Indian organisations
Gupta, M., & Narain, R. (2012) · International Journal of Indian Culture and Business Management · doi:10.1504/ijicbm.2012.044019 · Cited by 18
Metadata
- Authors
- Tornatzky, L. G., & Klein, K. J.
- Venue
- IEEE Transactions on Engineering Management
- Published
- 1982-02
- Volume
- EM-29
- Issue
- 1
- Pages
- 28-45
- ISSN
- 0018-9391 (ISSN-L)
- 1558-0040
- OpenAlex
- W1983629797
- Cited by
- 3,280
- References
- 0
- FWCI
- 5.54
- Type
- journal article
- Language
- en
- Open access
- closed
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