Evaluation of Consultant Selection Criteria with Level Based Weight Assessment (LBWA) Method in Intelligent ERP (Enterprise Resource Planning) Perspective

Yıl 2025, Cilt: 23 Sayı: 1, 29 - 52, 26.03.2025

Hakan Aşan

https://doi.org/10.18026/cbayarsos.1514312

Öz

Businesses require computer software to manage their processes systematically and flawlessly. The most important of these software is Enterprise Resource Planning (ERP) software that allows many departments to work together. However, ERP software is difficult to install and manage for businesses. Various factors such as the innovations, expectations, user problems, and costs that ERP projects bring to businesses affect the success of ERP projects. At the same time, these difficulties also carry risks. Businesses need consultants to ensure the success of their projects at this point. The selection of consultants for ERP projects is crucial for project success. This is especially critical for ERP software, which is currently transforming. With the influence of new technologies, ERP software is transforming into a new dimension called intelligent ERP (i- ERP). In this transformation process, the selection of consultants has become more critical and strategic. Currently, consultants are required to possess different skills and experiences besides being familiar with ERP data structures and processes. With ERP software's innovations within itself and in the business, other approaches are needed in consultant selection.
In this study, the criteria that could be considered in the selection problem of ERP consultants were evaluated from the perspective of intelligent enterprise resource planning software. The criteria were determined based on the existing consultant selection literature and expert opinions. The LBWA (Level Based Weight Assessment) method, one of the multi-criteria decision-making (MCDM) methods, was used to determine the criteria weights. LBWA method was preferred in this study because it is more advantageous for decision-makers in decision-making compared to other methods. According to the results obtained with the LBWA method, the most critical criteria in selecting consultants were respectively determined as employee competence, references and support cost. Although there are studies in the literature on consultant selection, this study is considered unique because it focuses on consultant selection from the perspective of i-ERP projects. In this sense, it is expected to contribute to the literature.

Anahtar Kelimeler

Intelligent Enterprise Resource Planning, Intelligent ERP (i-ERP), Consultant Selection, LBWA

Akıllı ERP (Kurumsal Kaynak Planlama) Perspektifinde Düzey Temelli Ağırlık Değerlendirmesi (LBWA) Yöntemi ile Danışman Seçim Kriterlerinin Değerlendirilmesi

Öz

İşletmeler süreçlerini sistematik, hatasız yönetebilmek için bilgisayar yazılımlarına ihtiyaç duymaktadırlar. Bu yazılımlardan en önemlisi birçok departmanın bir arada çalışmasına olanak sağlayan Kurumsal Kaynak Planlama (ERP) yazılımlarıdır. ERP yazılımları işletmeler açısından kurulumu ve yönetilmesi zor projelerdir. ERP projelerinin işletmeye getirdiği yenilikler, beklentiler, kullanıcı sorunları, maliyet gibi birçok detay ERP projelerinin başarısını etkilemektedir. Aynı zamanda bu zorluklar riskleri de beraberinde getirmektedir. Bu noktada işletmeler projelerinin başarılı olması için danışmanlara ihtiyaç duymaktadır. ERP projelerinde danışman seçimi projenin başarısı için çok önemlidir. Özellikle günümüzde bir dönüşüm süreci yaşayan ERP yazılımları için bu süreç daha kritiktir. ERP yazılımları yeni teknolojilerin etkisiyle a-KKP (Akıllı ERP) ismi verilen yeni bir boyuta dönüşmektedir. Bu dönüşüm sürecinde danışman seçimi daha önemli ve stratejik bir hal almıştır. Artık sadece ERP veri yapısına ve süreçlerine hâkim olması yetmeyen farklı yetenekler ve tecrübeler aranan danışmanlara ihtiyaç duyulmaktadır. ERP yazılımlarının kendi içeriğinde ve işletmede yarattığı yeniliklerle beraber danışman seçiminde de farklı yaklaşımlara ihtiyaç duyulmaktadır.
Bu çalışmada ERP danışman seçimi probleminde dikkate alınabilecek kriterler akıllı kurumsal kaynak planlama yazılımları açısından değerlendirilmiştir. Kriterlerin belirlenmesinde mevcut danışman seçimi literatürü ve uzman görüşünden yararlanılmıştır. Kriterlerin ağırlıklarını belirlemek için ÇKKV (Çok Kriterli Karar Verme) yöntemlerinden birisi olan LBWA (Düzey Temelli Ağırlık Değerlendirmesi) kullanılmıştır. Çalışmada LBWA yöntemi karar vericiler için diğer yöntemlere göre karar vermede daha avantajlı olması nedeniyle tercih edilmiştir. LBWA yöntemiyle elde edilen sonuçlara göre danışman seçiminde en önemli kriterler sırasıyla çalışan yetkinliği, referans ve destek maliyeti olarak belirlenmiştir. Literatürde danışman seçimine yönelik çalışmalar bulunmakta olsa da çalışma a-KKP projeleri perspektifinde danışman seçimine yönelik olması nedeniyle özgündür. Bu anlamda literatüre katkı sunacağı düşünülmektedir.

Anahtar Kelimeler

Akıllı Kurumsal Kaynak Planlaması, Akıllı ERP (a-KKP), Danışman Seçimi, LBWA

Kaynakça

• Ali, T., Sunny, M. R., Aghaloo, K., & Wang, K. (2024). Planning Off-Grid Hybrid Energy System Using Techno-Economic Optimization and Wins in League Theory-Based Multi-Criteria Decision-Making Method in The Wetland Areas of Developing Countries. Energy Conversion and Management, 313, 118587.
• Andersson, B. (2022). An Assessment of The Effects of Enterprise Resource Planning Adoption in SMEs. Journal of Enterprise and Business Intelligence, 66-76. https://doi.org/10.53759/5181/jebi202202008.
• Atan, T. (2023). A Unified Multiplicative Group Best-Worst Method with A New Assessment Approach For Dissimilar Markets. Informatica, 465-489. https://doi.org/10.15388/23-infor528.
• Ayan, B., ABACIOĞLU, S., & Basílio, M. (2023). A Comprehensive Review of The Novel Weighting Methods for Multi-Criteria Decision-Making. Information, 14(5), 285. https://doi.org/10.3390/info14050285.
• Avikal, S., Nigam, M., & Ram, M. (2022). A Hybrid Multi Criteria Decision Making Approach for Consultant Selection Problem in ERP Project. International Journal of System Assurance Engineering and Management, 1-10.
• Ayçin, E. (2023). Çok Kriterli Karar Verme: Bilgisayar Uygulamalı Çözümler. Genişletilmiş ve Güncellenmiş 3. Basım, Nobel Akademik Yayıncılık, Ankara.
• Baker, R. and Haddara, M. (2019). Exploring Consultants' Role in ERP Systems Implementations. 12th IADIS International Conference Information Systems 2019, 163-170. https://doi.org/10.33965/is2019_201905l021.
• Barna, L., Ionescu, B., & Haralambie, M. (2021). Using ERP Systems for A Green Company. Proceedings of The International Conference on Business Excellence, 15(1), 280-291. https://doi.org/10.2478/picbe-2021-0027.
• Bawack, R. and Kamdjoug, J. (2022). Managing Client–Consultant Relationships to Derive Benefits from ERP Projects. Information Technology and People, 36(4), 1669-1702. https://doi.org/10.1108/itp-07-2021-0573.
• Biswas, S., and Pamucar, D. (2020). Facility Location Selection For B-Schools in Indian Context: A Multi-Criteria Group Decision-Based Analysis. Axioms, 9(77), 2-18.
• Božanić, D., Jurišić, D., & Erkić, D. (2020). LBWA–Z-MAIRCA Model Supporting Decision Making in The Army. Operational Research in Engineering Sciences: Theory and Applications, 3(2), 87-110.
• Božanić, D., Pamucar, D., Badi, I. et al. A decision support tool for oil spill response strategy selection: application of LBWA and Z MABAC methods. OPSEARCH 60, 24–58 (2023). https://doi.org/10.1007/s12597-022-00605-0.
• Çilek, A. (2022). Kripto Para Talebini Etkileyen Faktörlerin LBWA Tekniğiyle Değerlendirilmesi. 9. Uluslararası Muhasebe ve Finans Araştırmaları Kongresi. Tokat. Türkiye
• Chairunnisa, K. (2019). Effect of Implementation of Enterprise Resource Planning System on Quality Of Accounting Information. Russian Journal of Agricultural and Socio-Economic Sciences, 87(3), 15-20. https://doi.org/10.18551/rjoas.2019-03.03.
• Cheung F. K. T., Kuen J. L. F. and Skitmore M., (2002). Multi-Criteria Evaluation Model for The Selection of Architectural Consultants, Construction Management and Economics, 20 (7) (2002) 569-580.
• Ćurĉić, S., Titović, M., Koprivica, S. M., Vesković, M., & Turanjanin, D. (2020). Multicriteria Analysis of Production Alternatives of Raspberry and Blackberry Production Residues. Quaestus Multidiscip. Res. J, 3(3), 155-158.
• Demir, G., & Arslan, R., (2021). Analysis of The Performance of Non-Life Insurance Companies In Turkey with The LBWA-PIV MCDM Model. 3. International Baku Scientific Research Congress (pp.419-435). Baku, Azerbaijan.
• Deveci, M., Özcan, E., John, R., Covrig, C. F., & Pamucar, D. (2020). A Study on Offshore Wind Farm Siting Criteria Using A Novel Interval-Valued Fuzzy-Rough Based Delphi Method. Journal of Environmental Management, 270, 110916.
• Ecer, F. (2020). Çok Kriterli Karar Verme Geçmişten Günümüze Kapsamlı Bir Yaklaşım. Ankara: Seçkin Yayınları.
• Fouad, R. H., Samhouri, M. S., & Qamar, A. M. (2012). An Intelligent Preventive Maintenance Scheduling in ERP Systems: A Fuzzy Logic Approach. International Journal of Advancements in Computing Technology, 4(23), 651-661.
• Grandhi, R. (2021). The Role of It in Automating the Business Processes in Retail Sector with Reference to Enterprise Resource Planning. International Journal of Business and Management Research, 9(2), 190-193.
• Haddara, M. (2014). ERP Selection: The SMART Way. Procedia technology, 16, 394-403.
• Jenab, K., Staub, S., Moslehpour, S., & Wu, C. (2019). Company Performance Improvement by Quality Based Intelligent-ERP. Decision Science Letters, 151–162. https://doi.org/10.5267/j.dsl.2018.7.003.
• Kamdjoug, J., Bawack, R., & Tayou, A. (2020). An ERP Success Model Based on Agency Theory Is Success Model. Business Process Management Journal, 26(6), 1577-1597. https://doi.org/10.1108/bpmj-04-2018-0113.
• Khan, S., Kusi‐Sarpong, S., Naim, I., Ahmadi, H., & Oyedijo, A. (2021). A Best-Worst-Method-Based Performance Evaluation Framework for Manufacturing Industry. Kybernetes, 51(10), 2938-2963. https://doi.org/10.1108/k-03-2021-0202.
• Kirmizi, M. (2021). The Influencing Factors of Enterprise Resource Planning (ERP) Readiness Stage on Enterprise Resource Planning Project Success: A Project Manager’s Perspective. Kybernetes, 51(3), 1089-1113. https://doi.org/10.1108/k-11-2020-0812.
• Korucuk, S., Ayteki̇n, A., Ecer, F., Pamucar, D., & Karamaşa, Ç. (2022). Assessment of Ideal Smart Network Strategies for Logistics Companies Using an Integrated Picture Fuzzy LBWA–COCOSO framework. Management Decision, 61(5), 1434-1462. https://doi.org/10.1108/md-12-2021-1621.
• Kulikov, I., Semin, A., Skvortsov, E., Ziablitckaia, N., & Skvortsova, E. (2020). Challenges of Enterprise Resource Planning (ERP) Implementation in Agriculture. Journal of Entrepreneurship and Sustainability Issues, 7(3), 1847-1857. https://doi.org/10.9770/jesi.2020.7.3(27).
• Kumar V., Bharat M., & Kumar U. (2003). An Investigation of Critical Management Issues in ERP Implementation: Empirical Evidence from Canadian Organizations. Technovation 23:793–807.
• Lech, P. (2016). Causes and Remedies for The Dominant Risk Factors in Enterprise System Implementation Projects: The Consultants’ Perspective. Springer Plus, 5(1). https://doi.org/10.1186/s40064-016-1862-9.
• Lin, T. and Chen, S. (2007). Users' Service Quality Satisfaction and Performance Improvement of ERP Consultant Selections. International Journal of Business and Systems Research, 1(3), 280. https://doi.org/10.1504/ijbsr.2007.015830.
• Lunenburg, F. C. (2010). Managing Change: The Role of The Change Agent. International Journal of Management, Business and Administration, 13(1), 1-6.
• Lv, T., Zhang, J., & Chen, Y. (2018). Research of ERP Platform Based on Cloud Computing. In IOP Conference Series: Materials Science and Engineering (Vol. 394, No. 4, p. 042004). IOP Publishing.
• Maditinos, D., Chatzoudes, D., & Tsairidis, C. (2011). Factors Affecting ERP System Implementation Effectiveness. Journal of Enterprise Information Management, 25(1), 60-78. https://doi.org/10.1108/17410391211192161.
• Martinović, N. & Delibašić, B. (2014). Selection of The Best Consultant for SAP ERP Project Using Combined AHP-IBA Approach. Yugoslav Journal of Operation Research, 24, pp. 383-398.
• Morris, H. D., Mahowald, R. P., Jimenez, D. Z., Stratis, A., Rizza, M. N., Hayward, D., & Motai, Y. (2016). i-ERP (Intelligent ERP): The New Backbone for Digital Transformation. Industry Development and Models.
• Ogundoyin, S. O., & Kamil, I. A. (2023). An integrated Fuzzy-BWM, Fuzzy-LBWA and V-Fuzzy-CoCoSo-LD model for gateway selection in fog-bolstered Internet of Things. Applied Soft Computing, 143, 110393.
• Özekenci, E. K. (2024). Personnel Selection Based on the LBWA, TOPSIS and GRA Methods: A Case Study on Foreign Trade Company. Fiscaoeconomia, 8(2), 646-665. https://doi.org/10.25295/fsecon.1411468.
• Pamučar, D., Žižović, M., Marinković, D., Doljanica, D., Jovanović, S., & Brzaković, P. (2020). Development of A Multi-Criteria Model for Sustainable Reorganization of a Healthcare System in An Emergency Situation Caused By The Covid-19 Pandemic. Sustainability, 12(18), 7504. https://doi.org/10.3390/su12187504.
• Pamucar, D., Deveci, M., Canıtez, F., and Lukovac, V. (2020). Selecting an Airport Ground Access Mode Using Novel Fuzzy LBWA-WASPAS-H Decision Making Model. Engineering Applications of Artificial Intelligence, 93, 103703.
• Saremi M. and Mousavi SF, Sanayei A. (2009). TQM consultant selection in SMEs with TOPSIS under fuzzy environment, Expert System Application, 36 (2) 2742-2749.
• Saha, A. and Roy, R. (2021). An Integrated Approach to Identify Suitable Areas for Built-Up Development Using GIS-Based Multi-Criteria Analysis and AHP In Siliguri Planning Area, India. Sn Applied Sciences, 3(4). https://doi.org/10.1007/s42452-021-04354-5.
• Salur, M. N., & Kattar, W. K. (2021). Denetimde İş Zekâsı Uygulamalarının Artı ve Eksileri. Anemon Muş Alparslan Üniversitesi Sosyal Bilimler Dergisi, 9(2), 553–559. https://doi.org/10.18506/anemon.897711.
• Shimange, T. and Pillay, K. (2022). A South African Institution Perspective of a Framework for Enterprise Resource Planning Systems. Journal of Information Management, 24(1). https://doi.org/10.4102/sajim.v24i1.1578.
• Tatar, V., Ayvaz, B. (2024). Assessment of Environmental Performance of Ports Utilizing an Integrated LBWA- MARCOS Decision-Making Approach Based on Picture Fuzzy Sets.
• Tešić, D., Bozanic, D., Puška, A., Štilić, A., & Milić, A. (2023). Application of MCMD model rough dibr - fuzzy LBWA - Bonferroni and decision support system dexi for the improvement of earthquake risk level assessment. https://doi.org/10.21203/rs.3.rs-3248793/v1.
• Tsai, W. H., Lin, T. W., Chen, S. P., & Hung, S. J. (2007). Users' service quality satisfaction and performance improvement of ERP consultant selections. International Journal of Business and Systems Research, 1(3), 280-301.
• Uluskan, M., Topuz, D., & Çimen, C. (2022). AHP, Bulanık AHP, LBWA ve COPRAS Yöntemleri İle Tedarikçi Değerlendirme: Demiryolu Sektöründe Bir Uygulama. Eskişehir Osmangazi Üniversitesi Mühendislik ve Mimarlık Fakültesi Dergisi, 30(3), 412-430. https://doi.org/10.31796/ogummf.1068384.
• Vayvay, O., Ozcan, Y., & Cruz-Cunha, M. M. (2012). ERP Consultant Selection Problem Using AHP, Fuzzy AHP and ANP: A Case Study in Turkey. E3 Journal of Business Management and Economics, 3(3), 106-117.
• Verma, S., Sharma, R., Deb, S., & Maitra, D. (2021). Artificial Intelligence in Marketing: Systematic Review and Future Research Direction. International Journal of Information Management Data Insights, 1(1), 100002.
• Westrup, C., & Knight, F. (2000). Consultants and Enterprise Resource Planning (ERP) Systems. ECIS 2000 Proceedings, 178.
• Zizovic, M., & Pamucar, D. (2019). New Model for Determining Criteria Weights: Level Based Weight Assessment (LBWA) Model. Decision Making: Applications in Management and Engineering, 2(2), 126-137.