An Empirical Study on Impact of Project Management Constraints in Agile Software Development

Multigroup Analysis between Scrum and Kanban


  • Chaitanya Arun Sathe Symbiosis Institute of Bussiness Management (SIBM)-Pune, Symbiosis International (Deemed University), Maharastra, Índia.
  • Chetan Panse Symbiosis Institute of Bussiness Management (SIBM)-Pune, Symbiosis International (Deemed University), Maharastra, Índia.



Scrum, Agile Software Development, Theory of Constraints (TOC), Multi-group Analysis, Structural Equation Modelling


Goal: The Study aims to investigate the impact of project management constraints in fixed-cost and fixed-scheduled Agile software development contracts using multigroup analysis (MGA) to perform repeated comparisons of parameters across groups of Scrum or Kanban methodologies using structural equation modelling (SEM)

Design/Methodology/Approach: A web-based survey is used to collect responses to a questionnaire based on project management constraints for Kanban and Scrum method-based Agile software development projects from people working on projects fixed-cost and fixed-schedule contracts and then analyzed with the help of multi-group analysis using SmartPLS 4.0

Results: Risk management has a mediating effect between project scope, resources, and delivery quality. MGA implied that the Kanban method is better at managing resources and will have a higher impact on the quality of deliverables than the Scrum method. 

Limitations of the investigation:  Evaluating the suitability of various multi-group analysis approaches requires more than just our empirical example using satisfactory data and other project management constraints.

Practical implications: The findings of the study suggest that hypothesis testing should be carried out for a distinct model parameter between study groups, whenever they are comparing more than two group.

Originality/Value:  This study helps in contributing to exploring PLS route modelling by the introduction of the original non-parametric confidence set approach based on a comparison of parameter estimations and bootstrap confidence intervals. The study investigates the impact of several project management constraints on to fixed-cost Agile software development projects.



Download data is not yet available.


Aizaz, F., Khan, S.U.R., Khan, J.A. and Akhunzada, A. (2021), “An empirical investigation of factors causing scope creep in an agile global software development context: a conceptual model for project managers”, IEEE Access, Vol. 9, pp. 109166-109195.

Albadarneh, A., Albadarneh, I. and Qusef, A. (2015), “Risk management in Agile software development: A comparative study”, IEEE Jordan Conference on Applied Electrical Engineering and Computing Technologies (AEECT), pp. 1-6.

Alqudah, M. and Razali, R. (2017), “A comparison of scrum and Kanban for identifying their selection factors”, The IEEE 6th International Conference on Electrical Engineering and Informatics (ICEEI), pp. 1-6.

Al-Rubaiei, Q.H.S., Nifa, F.A.A. and Musa, S. (2018), “Project scope management through multiple perspectives: A critical review of concepts”, AIP Conference Proceedings, Vol. 2016, No.1, pp. 20-25.

Alves, J.L., Ferreira, E.A and Nadae, J. (2021), “Crisis and risks in engineering project management: a review”, Brazilian Journal of Operations & Production Management, Vol. 18, No. 4, e2021991.

Anderson, D.J., Concas, G., Lunesu, M.I., Marchesi, M. and Zhang, H. (2012), “A comparative study of Scrum and Kanban approaches on a real case study using simulation”, In International Conference on Agile Software Development, Springer, Berlin, Heidelberg, pp. 123-137.

Atencio, E., Mancini, M. & Bustos, G. (2022), "An Ontology for Project-Based Organization Design: The Star Model Case", In proceedings of the 5th IEOM European Conference on Industrial Engineering and Operations Management, pp. 1-11.

Bagozzi, R P. and Yi, Y. (1988), “On the evaluation of structural equation models”, Journal of the academy of marketing science, Vol. 16, No.1, pp.74-94.

Bannerman, P.L. (2008), “Risk and risk management in software projects: A reassessment”, Journal of systems and software, Vol. 81, No.12, pp.2118-2133.

Baquero, A. (2022), “Net Promoter Score (NPS) and Customer Satisfaction: Relationship and Efficient Management”, Sustainability, Vol. 14, No. 4, pp. 20-25.

Beck, K., Beedle, M., Van Bennekum, A., Cockburn, A., Cunningham, W., Fowler, M., and Thomas, D. (2001), “The agile manifesto”, The Agile Alliance, New York, NY, pp. 01-12.

Boehm, B.W. (1991), “Software risk management: principles and practices”, IEEE Software, Vol.8, No.1, pp.32-41.

Buganová, K. and Šimíčková, J. (2019), “Risk management in traditional and agile project management”, Transportation Research Procedia, Vol. 40, pp. 986-993.

Chowdhury, A.A.M. and Arefeen, S. (2011), “Software risk management: importance and practices”, International Journal of Computer and Information Technology, Vol. 10, pp. 2078-5828.

Cochran, W.G. (1977), Sampling techniques, John Wiley & Sons.

Cohen, J. (1988). “Statistical power analysis for the behavioural sciences”. Academic press.

Dingsøyr, T., Fægri, T.E., Dybå, T., Haugset, B. and Lindsjørn, Y. (2016), “Team performance in software development: research results versus agile principles”, IEEE Software, Vol. 33, No. 4, pp. 106-110.

Elmezain, M., Baduruzzaman, W.H.W. and Khoiry, M.A. (2021), “The impact of project manager’s skills and age on project success”, Brazilian Journal of Operations & Production Management, Vol. 18, No. 04, e2021950.

Falk, R.F. and Miller, N.B. (1992), “A primer for soft modelling”, University of Akron Press.

Ghane, K. (2017), “Quantitative planning and risk management of Agile Software Development”, IEEE Technology & Engineering Management Conference (TEMSCON), IEEE, pp. 109-112.

Gheorghe, A.M., Gheorghe, I.D. and Iatan, I.L. (2020), “Agile Software Development”, Informatica Economica, Vol.24, No. 2. pp. 25-29.

Goldratt, E.M. (1990), “Theory of Constraints”, Croton-on-Hudson: North River, pp. 1-159.

Grewal, R., Cote, J. A. and Baumgartner, H. (2004), “Multicollinearity and measurement error in structural equation models: Implications for theory testing”, Marketing Science, Vol. 23, No.4, pp.519-529.

Haenlein, M. and Kaplan, A.M. (2011), “The influence of observed heterogeneity on path coefficient significance: Technology acceptance within the marketing discipline”, Journal of Marketing Theory and Practice, Vol. 19, No.2, pp.153-168.

Haindl, P. and Plösch, R. (2022), “Value‐oriented quality metrics in software development: Practical relevance from a software engineering perspective”, IET Software, Vol. 16, No. 2, pp.167-184.

Hair, J.F., Ortinau, D.J. and Harrison, D.E. (2010), Essentials of marketing research, Vol. 2, 2nd ed., McGraw-Hill/Irwin, New York.

Hayat, F., Rehman, A.U., Arif, K.S., Wahab, K. and Abbas, M. (2019), “The influence of agile methodology (Scrum) on software project management”. IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Vol. 20, IEEE Networking and Parallel/Distributed Computing (SNPD), pp. 145-149.

Henseler, J., Ringle, C.M. and Sarstedt, M. (2016), “Testing measurement invariance of composites using partial least squares, International Marketing Review, Vol. 33 No. 3, pp.405-431.

Hijazi, H., Khdour, T. and Alarabeyyat, A. (2012), “A review of risk management in different software development methodologies”, International Journal of Computer Applications, Vol. 45, No.7, pp. 8-12.

Imran, R. and Soomro, T.R. (2022), “Mapping of Agile Processes into Project Management Knowledge Areas and Processes”, In 2022 International Conference on Business Analytics for Technology and Security (ICBATS), IEEE, pp. 1-12.

Kassab, M. (2014), “An empirical study on the requirements engineering practices for agile software development”, The 40th EUROMICRO Conference on Software Engineering and Advanced Applications, IEEE, pp. 254-261.

Keogh, L. (2011), “Scrum and Kanban are both the Same, Only Different”, available from:

Kerzner, H. (2022), Project management metrics, KPIs, and dashboards: a guide to measuring and monitoring project performance, 1ed., John Wiley & Sons, New York.

Kniberg, H. and Skarin, M. (2010), “Kanban and Scrum-making the most of both”, available from:

Lalsing, V., Kishnah, S. and Pudaruth, S. (2012), “People factors in agile software development and project management”, International Journal of Software Engineering & Applications, Vol. 3, No.1, pp. 116-117.

Leguina, A. (2015), A primer on partial least squares structural equation modeling (PLS-SEM), 1st ed., New Castle University, UK, pp. 220-221,

Lei, H., Ganjeizadeh, F., Jayachandran, P.K. and Ozcan, P. (2017), “A statistical analysis of the effects of Scrum and Kanban on software development projects”, Robotics and Computer-Integrated Manufacturing, Vol. 43, pp. 59-67.

Mamanovna, S. and Ligay, T., (2023), “Comparison of Kanban and Scrum methodologies. What is the best fit for your company?” Scientific Collection, Proceedings of the 8th International Scientific and Practical Conference, Vol. 142, pp. 58-61.

Marnada, P., Raharjo, T., Hardian, B. and Prasetyo, A. (2022), “Agile project management challenge in handling scope and change: A systematic literature review”, Procedia Computer Science, Vol. 197, pp. 290-300.

McManus, J. (2012), Risk management in software development projects, 1st ed., Routledge Publications, New York.

Noor, R. and Khan, M.F. (2014), “Defect management in agile software development”, International Journal of Modern Education and Computer Science, Vol. 6, No.3, pp. 53-55.

Nurdiani, I., Börstler, J. and Fricker, S.A. (2016), “ The impacts of agile and lean practices on project constraints: A tertiary study”, Journal of Systems and Software, Vol. 119, pp. 162-183,

Oliveira, E.R. et al. (2023), “Scrum method assessment in Federal Universities in Brazil: multiple case studies”, Brazilian Journal of Operations and Production Management, Vol. 20, No. 1, e20231496. Doi:

Özkan, D. and Mishra, A. (2019), “Agile Project Management Tools: A Brief Comparative View”, Cybernetics and Information Technologies, Vol.19, No.4, pp.17-25.

Ozkan, N., Bal, S., Erdogan, T.G. and Gök, M.Ş. (2022), “Scrum, Kanban or a Mix of Both? A Systematic Literature Review”, In 2022 17th Conference on Computer Science and Intelligence Systems (FedCSIS), IEEE, pp. 883-893. Doi: 0.15439/2022F143

Pai, A.R., Joshi, G. and Rane, S. (2021), “Quality and reliability studies in software defect management: a literature review”, International Journal of Quality & Reliability Management, Vol. 38, No. 10, pp 2007-2033, Doi: /10.1108/IJQRM-07-2019-0235

Powell, R. and Jandreau, T. (2022), “Establishing Quality Metrics for Systems Engineering Process”, INCOSE International Symposium, Vol. 32, No. 1, pp. 159-182.

Riaz, A. R. and Gilani, S. M. (2022)”, Risk assessment approach for software development using cause and effect analysis”, KIET Journal of Computing and Information Sciences, Vol. 5, No. 1, 48-61.

Rigdon, E.E., Ringle, C.M. and Sarstedt, M. (2010), “Structural modeling of heterogeneous data with partial least squares”, Review of Marketing Research, Vol. 7, Emerald Group Publishing Limited, Bingley, pp. 255-296,

Salin, H., Rybarczyk, Y., Han, M. and Nyberg, R. G. (2022), “Quality Metrics for Software Development Management and Decision Making: An Analysis of Attitudes and Decisions”, International Conference on Product-Focused Software Process Improvement, Springer, Cham.

Sirshar, M.; Khalid, M. (2019), “A Study Analysis on Effect of Software Scope Management and Scope creeping Factors in Software Project Management”, Preprints, pp. 2006-20191, Doi:

Sudhakar, G.P., Farooq, A. and Patnaik, S. (2011), “Soft factors affecting the performance of software development teams”, Team Performance Management, Vol. 17 No. 3-4, pp. 187-205, Doi:

Tabachnick, B.G., Fidell, L.S. and Ullman, J. B. (2007), Using multivariate statistics, 1st ed., Vol. 5, pp. 481-498, Pearson, Boston, MA.

Thakurta, R. (2013), “Impact of Scope Creep on Software Project Quality”, The XIMB Journal of Management, Vol. 10, No. 1, pp. 37-46.

Trendowicz, A. (2013), Software Cost Estimation, Benchmarking, and Risk Assessment: The Software Decision-Makers' Guide to Predictable Software Development. Heidelberg Springer, New York, NY. Doi:

Van Wyngaard, C.J., Pretorius, J.H.C. and Pretorius, L. (2012), “Theory of the triple constraint—A conceptual review”, IEEE International Conference on Industrial Engineering and Engineering Management, pp. 1991-1997.

Westland, C.J. (2010), “Lower bounds on sample size in structural equation modelling”, Electronic Commerce Research and Applications, Vol. 9, No. 6, pp. 476–487. Doi:

Wideman, R.M. (2022), Project and program risk management a guide to managing project risks and opportunities, Project Management Institute, Inc., SIBN: 1880410001, 9781880410004.

Wold, H. (1982), “Models for knowledge”, The making of Statisticians, 1st ed., Springer New York, NY, pp.189-212. DOI

Zanezi, A.C. and Carvalho, M.M. (2022), “How project management principles affect Lean Six Sigma program and projects: a systematic literature review”, Brazilian Journal of Operations and Production Management, Vol. 20, No. 1, e20231564. Doi:




How to Cite

Sathe, C. A., & Panse, C. (2023). An Empirical Study on Impact of Project Management Constraints in Agile Software Development: Multigroup Analysis between Scrum and Kanban. Brazilian Journal of Operations & Production Management, 20(3), 1796.



Research paper