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Information Technology Implementation Research: A Technological Diffusion Approach
Abstract
Based on the innovation and technological diffusion literatures, promising research questions concerning the implementation of a production and inventory control information system (material requirements planning: MRP) are identified and empirically examined. These questions focus on the interaction of managerial tasks with the information technology and the resulting effect on the adoption and infusion of that technology. Using a random sample of manufacturing firms across the United States, we find that this interaction does indeed affect the adoption of MRP, though it does not seem to affect MRP infusion. These results support the notion that though rational decision models may be useful in explaining information technology adoption, political and learning models may be more useful when examining infusion.
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Citations
Cites
User Involvement and MIS Success: A Review of Research
Ives, B., & Olson, M. H. (1984) · Management Science · doi:10.1287/mnsc.30.5.586 · Cited by 1,318
Cited by
Understanding Information Systems Continuance: An Expectation-Confirmation Model1
Bhattacherjee, A. (2001) · MIS Quarterly · doi:10.2307/3250921 · Cited by 8,767
Technology Acceptance Model 3 and a Research Agenda on Interventions
Venkatesh, V., & Bala, H. (2008) · Decision Sciences · doi:10.1111/j.1540-5915.2008.00192.x · Cited by 8,159
Task-Technology Fit and Individual Performance
Goodhue, D. L., & Thompson, R. L. (1995) · MIS Quarterly · doi:10.2307/249689 · Cited by 6,006
Dwivedi, Y. K., Kshetri, N., Hughes, L., Slade, E. L., Jeyaraj, A., Kar, A. K., Baabdullah, A. M., Koohang, A., Raghavan, V., Ahuja, M., et al. (2023) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2023.102642 · Cited by 4,584
Personal Computing: Toward a Conceptual Model of Utilization1
Thompson, R. L., Higgins, C. A., & Howell, J. M. (1991) · MIS Quarterly · doi:10.2307/249443 · Cited by 3,814
Examining the technology acceptance model using physician acceptance of telemedicine technology
Hu, P. J., Chau, P. Y. K., Sheng, O. R. L., & Tam, K. Y. (1999) · Journal of Management Information Systems · doi:10.1080/07421222.1999.11518247 · Cited by 1,951
Proctor, E. K., Landsverk, J., Aarons, G., Chambers, D., Glisson, C., & Mittman, B. (2009) · Administration and Policy in Mental Health and Mental Health Services Research · doi:10.1007/s10488-008-0197-4 · Cited by 1,894
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
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
The Technology–Organization–Environment Framework
Baker, J. (2012) · Integrated Series in Information Systems · doi:10.1007/978-1-4419-6108-2_12 · Cited by 1,275
Understanding the determinants of cloud computing adoption
Low, C., Chen, Y., & Wu, M. (2011) · Industrial Management & Data Systems · doi:10.1108/02635571111161262 · Cited by 1,181
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 the Adoption of Open Systems: An Exploratory Study1
Chau, P. Y. K., & Tam, K. Y. (1997) · MIS Quarterly · doi:10.2307/249740 · Cited by 1,067
Zhu, K., Kraemer, K., & Xu, S. (2003) · European Journal of Information Systems · doi:10.1057/palgrave.ejis.3000475 · Cited by 1,043
Determining Uses and Gratifications for the Internet
Stafford, T. F., Stafford, M. R., & Schkade, L. L. (2004) · Decision Sciences · doi:10.1111/j.00117315.2004.02524.x · Cited by 1,010
Planning and Studying Improvement in Patient Care: The Use of Theoretical Perspectives
GROL, R. P. T. M., BOSCH, M. C., HULSCHER, M. E. J. L., ECCLES, M. P., & WENSING, M. (2007) · The Milbank Quarterly · doi:10.1111/j.1468-0009.2007.00478.x · Cited by 943
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
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
Digital Product Innovation Within Four Classes of Innovation Networks
Lyytinen, K., Yoo, Y., & Boland Jr., R. J. (2016) · Information Systems Journal · doi:10.1111/isj.12093 · Cited by 806
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
A taxonomy of players and activities across the ERP project life cycle
Somers, T. M., & Nelson, K. G. (2004) · Information & Management · doi:10.1016/s0378-7206(03)00023-5 · Cited by 694
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
The illusory diffusion of innovation: An examination of assimilation gaps
Fichman, R. G., & Kemerer, C. F. (1999) · Information Systems Research · doi:10.1287/isre.10.3.255 · Cited by 633
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
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
Morris, M. G., & Venkatesh, V. (2010) · MIS Quarterly · doi:10.2307/20721418 · Cited by 437
Determinants of e-business diffusion: A test of the technology diffusion perspective
Lin, H.-F., & Lin, S.-M. (2008) · Technovation · doi:10.1016/j.technovation.2007.10.003 · Cited by 447
Hong, W., & Zhu, K. (2006) · Information & Management · doi:10.1016/j.im.2005.06.003 · Cited by 390
Aboelmaged, M. G. (2014) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2014.05.002 · Cited by 355
Lee, Y., & Kwon, O. (2011) · Electronic Commerce Research and Applications · doi:10.1016/j.elerap.2010.11.005 · Cited by 343
Kim, S. S., & Son, J.-Y. (2009) · MIS Quarterly · doi:10.2307/20650278 · Cited by 339
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
Critical factors that influence e-procurement implementation success in the public sector
Vaidya, K., Sajeev, A. S. M., & Callender, G. (2006) · Journal of Public Procurement · doi:10.1108/jopp-06-01-02-2006-b004 · Cited by 293
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
What Is the True Value of a Lost Customer?
Hogan, J. E., Lemon, K. N., & Libai, B. (2003) · Journal of Service Research · doi:10.1177/1094670502238915 · Cited by 275
Beyond TAM and UTAUT: Future directions for HIT implementation research
Shachak, A., Kuziemsky, C., & Petersen, C. (2019) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2019.103315 · Cited by 263
A unified perspective on the factors influencing usage intention toward mobile financial services
Lee, Y.-K., Park, J.-H., Chung, N., & Blakeney, A. (2012) · Journal of Business Research · doi:10.1016/j.jbusres.2011.02.044 · Cited by 261
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
Rajan, C. A., & Baral, R. (2015) · IIMB Management Review · doi:10.1016/j.iimb.2015.04.008 · Cited by 234
Hwang, H.-G., Ku, C.-Y., Yen, D. C., & Cheng, C.-C. (2004) · Decision Support Systems · doi:10.1016/s0167-9236(02)00191-4 · Cited by 228
Impact of electronic medical record on physician practice in office settings: a systematic review
Lau, F., Price, M., Boyd, J., Partridge, C., Bell, H., & Raworth, R. (2012) · BMC Medical Informatics and Decision Making · doi:10.1186/1472-6947-12-10 · Cited by 199
“In this regard, the CA Framework should be expanded by incorporating post-adoption usage behaviours by physicians and their effects over time to reflect the different maturity stages of the EMRs involved [66,67].”
MethodE‐commerce usage and business performance in the Malaysian tourism sector: empirical analysis
Intan Salwani, M., Marthandan, G., Daud Norzaidi, M., & Choy Chong, S. (2009) · Information Management & Computer Security · doi:10.1108/09685220910964027 · Cited by 202
(2003) · Journal of the Association for Information Systems · Cited by 202
Thatcher, J. B., McKnight, D. H., Baker, E. W., Arsal, R. E., & Roberts, N. H. (2011) · IEEE Transactions on Engineering Management · doi:10.1109/tem.2009.2028320 · Cited by 196
Dimensions of national culture and corporate adoption of IT infrastructure
Png, I. P. L., Tan, B. C. Y., & Wee, K.-L. (2001) · IEEE Transactions on Engineering Management · doi:10.1109/17.913164 · Cited by 197
How does artificial intelligence create business agility? Evidence from chatbots
Wang, X., Lin, X., & Shao, B. (2022) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2022.102535 · Cited by 197
Liberating HR through technology
Shrivastava, S., & Shaw, J. B. (2003) · Human Resource Management · doi:10.1002/hrm.10081 · Cited by 152
Kim, T. (., Suh, Y. K., Lee, G., & Choi, B. G. (2010) · International Journal of Tourism Research · doi:10.1002/jtr.787 · Cited by 139
Service robots in hospitals: new perspectives on niche evolution and technology affordances
Mettler, T., Sprenger, M., & Winter, R. (2017) · European Journal of Information Systems · doi:10.1057/s41303-017-0046-1 · Cited by 134
Spencer, A. J., Buhalis, D., & Moital, M. (2012) · Tourism Management · doi:10.1016/j.tourman.2011.11.011 · Cited by 129
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
Cao, Q., Jones, D. R., & Sheng, H. (2014) · Information & Management · doi:10.1016/j.im.2013.11.007 · Cited by 126
What is the value of an IT e-procurement system?
Ronchi, S., Brun, A., Golini, R., & Fan, X. (2010) · Journal of Purchasing and Supply Management · doi:10.1016/j.pursup.2010.03.013 · Cited by 122
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
An attention-based view of AI assimilation in public sector organizations: The case of Saudi Arabia
Alshahrani, A., Dennehy, D., & Mäntymäki, M. (2022) · Government Information Quarterly · doi:10.1016/j.giq.2021.101617 · Cited by 106
Mishra, D., Luo, Z., Hazen, B., Hassini, E., & Foropon, C. (2019) · Management Decision · doi:10.1108/md-03-2018-0324 · Cited by 87
Barriers to the Implementation of AI in Organizations: Findings from a Delphi Study
Bérubé, M., Giannelia, T., & Vial, G. (2021) · Proceedings of the Annual Hawaii International Conference on System Sciences · doi:10.24251/hicss.2021.805 · Cited by 67
The effects of e-Government cloud assimilation on public value creation: An empirical study of China
Liang, Y., Qi, G., Zhang, X., & Li, G. (2019) · Government Information Quarterly · doi:10.1016/j.giq.2019.101397 · Cited by 65
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
Ramayah, T., Roy, M. H., Arokiasamy, S., Zbib, I., & Ahmed, Z. U. (2007) · International Journal of Business Information Systems · doi:10.1504/ijbis.2007.011980 · Cited by 53
Heidenreich, S., & Talke, K. (2020) · AMS Review · doi:10.1007/s13162-020-00164-x · Cited by 46
Reunis, M. R. B., van Raaij, E. M., & Santema, S. C. (2004) · Journal of Purchasing and Supply Management · doi:10.1016/j.pursup.2004.10.002 · Cited by 30
The role of formal controls in facilitating information system diffusion
Abubakre, M. A., Ravishankar, M. N., & Coombs, C. R. (2015) · Information & Management · doi:10.1016/j.im.2015.04.005 · Cited by 20
Metadata
- Authors
- Cooper, R. B., & Zmud, R. W.
- Venue
- Management Science
- Published
- 1990-02
- Volume
- 36
- Issue
- 2
- Pages
- 123-139
- ISSN
- 0025-1909 (ISSN-L)
- 1526-5501
- OpenAlex
- W2123438112
- Cited by
- 2,765
- References
- 1
- FWCI
- 17.23
- Type
- journal article
- Language
- en
- Open access
- closed
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