ERP uygulama öncesi için süreç odaklı bir model önerisi ve testi

Bu araştırmada, Yazılım Geliştirme Yaşam Döngüsü (SDLC) yaklaşımı ile ERP projelerinin uygulama öncesi aşaması için süreç odaklı bir model önerilmektedir. SDLC yaklaşımı Planlama, Analiz, Tasarım, Gerçekleştirme, Test & Entegrasyon ve Bakım gibi sıralı ve doğrusal süreçler içermektedir. Araştırmanın amacı ERP uygulama öncesi aşamada SDLC’deki bir sürecin diğer bir süreci nasıl etkilediğini incelemek ve bu süreçler arasındaki ilişkileri test etmektir. Araştırmada, bir PLS-SEM (kısmi en küçük kareler yapısal eşitlik modellemesi) modeli önerilmiştir. Bu modelin geçerliliği ve güvenirliliği test edilmiştir. Model, SDLC’nin her süreci (değişkenler) için ayrı ayrı incelenmiş ve değişkenlerin birbirlerini ne ölçüde açıkladığı, değişkenler arasında kurulan ilişkilerin model tarafından desteklenip desteklenmediği değerlendirilmiştir. Elde edilen bulgulara göre, Planlama süreci, Analiz sürecinde 0.74, Gerçekleştirme sürecinde 0.25, Test ve Entegrasyon sürecinde 0.35 birimlik pozitif yönde bir etkiye neden olmaktadır. Benzer şekilde Analiz süreci, Tasarım sürecinde 0.68 birimlik pozitif yönde bir etkiye neden olmaktadır. Tasarım süreci ise, Gerçekleştirme sürecinde 0.48, Test & Entegrasyon sürecinde 0.43, Bakım sürecinde 0.53 birimlik pozitif yönde bir etkiye neden olmaktadır. Sonuç olarak ERP'nin uygulama öncesi aşamasındaki planlama süreci, sonraki süreçler açısından kritik öneme sahiptir. Benzer şekilde, analiz ve tasarım sürecindeki en iyi iş uygulamaları, kendilerinden sonra gelen gerçekleştirme, test & entegrasyon ve bakım süreçlerini olumlu yönde etkilemektedir.

A proposal and testing of a process-oriented model for ERP preimplementation

In this research, a process-oriented model for the pre-implementation phase of ERP projects was proposed with the Software Development Life Cycle (SDLC). SDLC approach includes sequential and linear processes such as Planning, Analysis, Design, Implementation, Test & Integration, and Maintenance. The purpose of the research is to examine how a process in SDLC affects what came after another process during the pre-implementation phase of ERP and then test the relationships between them. In the study, a PLS-SEM (partial least squares structural equation modelling) model was proposed. The validity and reliability of the model were tested. The model was examined separately for each process (variables) of the SDLC and evaluated in such issues; to what extent the variables explained each other, the model supported the relationships between variables. According to the findings, the "Planning" process has a positive effect of 0.74 on the "Analysis" process as well as 0.25 on the "Implementation" process and 0.35 on the "Test & Integration" process. Similarly, the "Analysis" process has a positive effect of 0.68 on the "Design" process. The "Design" process has a positive effect of 0.48 on the "Implementation" process as well as 0.43 in the "Test & Integration" process and 0.53 in the "Maintenance" process. As a result, the "Planning" process in the preimplementation phase of ERP is critical in subsequent processes. Similarly, best business practices in the "Analysis" process as well as "Design" process positively affect the other processes such as "Implementation", "Test & Integration", and "Maintenance".

___

  • Abdinnour, S., & Saeed, K. (2015). User perceptions towards an ERP system. Journal of Enterprise Information Management, 28(2), 243-259.
  • Afthanorhan, W. M. A. B. W. (2014). Hierarchical component using reflective-formative measurement model in partial least square structural equation modeling (PLS-SEM). International Journal of Mathematics, 2(2), 33-49.
  • Ahmad, R. M. T. R. L., Othman, Z., & Mukhtar, M. (2011). Campus ERP implementation framework for private institution of higher learning environment in Malaysia. WSEAS Transactions on advances in engineering education, 1(8), 1-12.
  • Balaji, S., & Murugaiyan, M. S. (2012). Waterfall vs. V-Model vs. Agile: A comparative study on SDLC. International Journal of Information Technology and Business Management, 2(1), 26-30.
  • Bento, F., & Costa, C. J. (2013). ERP measure success model; a new perspective. In Proceedings of the 2013 International Conference on Information Systems and Design of Communication (pp. 16-26).
  • Brunner, M., & SÜβ, H. M. (2005). Analyzing the reliability of multidimensional measures: An example from intelligence research. Educational and Psychological Measurement, 65(2), 227-240.
  • Chadhar, M. A., & Daneshgar, F. (2018). Organizational Learning and ERP Post-implementation Phase: A Situated Learning Perspective. Journal of Information Technology Theory and App., 19(2), 139-156.
  • Capaldo, G., & Rippa, P. (2009). A planned‐oriented approach for EPR implementation strategy selection. Journal of Enterprise Information Management, 22(6), 642-659.
  • Çakır, F. S. (2019). Kısmi En Küçük Kareler Yapısal Eşitlik Modellemesi (PLS-SEM) ve Bir Uygulama. Sosyal Araştırmalar ve Davranış Bilimleri, 5(9), 111-128.
  • Dearing, J. W., & Cox, J. G. (2018). Diffusion of innovations theory, principles, and practice. Health Affairs, 37(2), 183-190.
  • Davenport, T. H., & Short, J. E. (1990). The new industrial engineering: information technology and business process re-design. Sloan Management Review, 31(4), 11-27.
  • Ehie, I. C., & Madsen, M. (2005). Identifying critical issues in enterprise resource planning (ERP) implementation. Computers in industry, 56(6), 545-557.
  • Fink, A., & Litwin, M. S. (1995). How to measure survey reliability and validity (Vol. 7). Sage. Fornell, C., Larcker, D. F. (1981). Evaluating Structural Equation Models with Unobservable Variables and Measurement Error. Journal of Marketing Research, 18(1), 39-50.
  • Geisser, S. (1974). A predictive approach to the random effect model. Biometrika, 61(1), 101-107.
  • Grenci, R. T., & Hull, B. Z. (2020). New dog, old tricks: ERP and the systems development life cycle. Journal of Information Systems Education, 15(3), 7.
  • Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011). PLS-SEM: Indeed a silver bullet. Journal of Marketing theory and Practice, 19(2), 139-152.
  • Hair, J. F., Ringle, C. M., & Sarstedt, M. (2013). Partial least squares structural equation modeling: Rigorous applications, better results and higher acceptance. Long range planning, 46(1-2), 1-12.
  • Hair Jr, J. F., Hult, G. T. M., Ringle, C., & Sarstedt, M. (2016). A primer on partial least squares structural equation modeling (PLS-SEM). Sage publications.
  • Hair, J. F., Matthews, L. M., Matthews, R. L., & Sarstedt, M. (2017). PLS-SEM or CB-SEM: updated guidelines on which method to use. International Journal of Multivariate Data Analysis, 1(2), 107-123.
  • Hasibuan, Z. A., & Dantes, G. R. (2012). Priority of key success factors on enterprise resource planning (ERP) system implementation life cycle. Journal of Enterprise Resource Planning Studies. https://ibimapublishing.com/articles/JERPS/2012/122627/
  • Handcock, M. S., & Gile, K. J. (2011). Comment: On the concept of snowball sampling. Sociological Methodology, 41(1), 367-371.
  • Henseler, J., Ringle, C.M., & Sinkovics, R.R. (2009). The use of partial least squares path modeling in international marketing. In Sinkovics, R.R. and Ghauri, P.N. (Ed.) New Challenges to International Marketing (Advances in International Marketing, Vol. 20), Emerald Group Publishing Limited, Bingley, pp. 277-319.
  • Huang, T. (2016). Peeking at the ERP Decline stage: Japanese empirical evidence. Computers in Industry, 82, 224-232.
  • Huang, T., & Yasuda, K. (2014). ERP life cycle models: an annotated bibliographic review. In Proceedings of the 15th Asia Pacific Industrial Engineering and Management Systems Conference (pp. 70-77).
  • Huang, T., & Yasuda, K. (2016). Reinventing the ERP life cycle model: from go-Live to withdrawal. Journal of Enterprise Resource Planning Studies, 2016, 1-21.
  • Hustad, E., & Olsen, D. H. (2011). Exploring the ERP pre-implementation process in a small-andmedium-sized enterprise: a case study of a Norwegian retail company. ECIS 2011 Proceedings. 8. http://aisel.aisnet.org/ecis2011/8
  • Kanellou, A., & Spathis, C. (2013). Accounting benefits and satisfaction in an ERP environment. International Journal of Accounting Information Systems, 14(3), 209-234.
  • Kline, R. B. (2015). Principles and practice of structural equation modeling. Guilford publications.
  • Kwon, T. H., & Zmud, R. W. (1987). Unifying the fragmented models of information systems implementation. In Critical issues in information systems research (pp. 227-251).
  • Mahmud, I., Ramayah, T., & Kurnia, S. (2017). To use or not to use: Modelling end user grumbling as user resistance in pre-implementation stage of enterprise resource planning system. Information Systems, 69, 164-179.
  • Marnewick, C., & Labuschagne, L. (2005). A conceptual model for enterprise resource planning (ERP). Information management & computer security, 13(2), 144-155.
  • Meissonier, R., & Houzé, E. (2010). Toward an 'IT Conflict-Resistance Theory': action research during IT pre-implementation. European Journal of Information Systems, 19(5), 540-561.
  • Mudiraj, A. R. (2014). BPR: The First Step for ERP Implementation. Int. Res. J. Commerce, Business Social Sciences (IRJCBSS), 2(13), 1-2.
  • Mudiraj, A. R. (2017). Study on Critical Factors affecting on ERP implementation process. International Journal of Recent Trends in Engineering and Research, 3(6), 177-181.
  • Nizam, A. (2015). Yazılım Proje Yönetimi. İstanbul: Papatya Yayıncılık.
  • Panorama Consulting (2020). The 2020 ERP Report.https://www.panorama-consulting.com/resourcecenter/2020-erp-report/(Erişim Tarihi: 22.12.2020).
  • Peng, G. C., & Nunes, M. B. (2009). Identification and assessment of risks associated with ERP post‐ implementation in China. Journal of Enterprise Information Management, 22(5), 587-614.
  • Preacher, K. J. & Leonardelli, G.J. (2010). Calculation for the Sobel test: An interactive calculation tool for mediation tests. http://quantpsy.org/sobel/sobel.htm (Erişim Tarihi:23.12.2020).
  • Preacher, K. J., & Hayes, A. F. (2008). Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models. Behavior research methods, 40(3), 879-891.
  • Ringle, C. M., Wende, S., and Becker, J. M. (2015). "SmartPLS 3." Boenningstedt: SmartPLS GmbH, http://www.smartpls.com
  • Rogers, E. M. (2004). A prospective and retrospective look at the diffusion model. Journal of health communication, 9(S1), 13-19.
  • Ruivo, P., Oliveira, T., & Neto, M. (2014). Examine ERP post-implementation stages of use and value: Empirical evidence from Portuguese SMEs. International Journal of Accounting Information Systems, 15(2), 166-184.
  • Sobel, M. E. (1982). Asymptotic confidence intervals for indirect effects in structural equation models. Sociological methodology, 13, 290-312.
  • Stone, M. (1974). Cross‐validatory choice and assessment of statistical predictions. Journal of the Royal Statistical Society: Series B (Methodological), 36(2), 111-133.
  • Yılmaz, V., Yasemin, C. A. N., & Nil, A. R. A. S. (2019). Kısmi En Küçük Kareler Yapısal Eşitlik Modellemesiyle (PLS-YEM) Nükleer ve Yenilenebilir Enerjiye İlişkin Tutumların Araştırılması. Alphanumeric Journal, 7(1), 87-102.
  • Wong, K. K. K. (2013). Partial least squares structural equation modeling (PLS-SEM) techniques using SmartPLS. Marketing Bulletin, 24(1), 1-32.