Measurement and structural model of agile software development critical success factors

  • Authors

    • Vinay Kukreja Chitkara University
    • Sachin Ahuja Chitkara University
    • Amitoj Singh Punjab Technical University
    2018-06-30
    https://doi.org/10.14419/ijet.v7i3.12776
  • Agile Software Development, Agile Methodologies, Measurement Model, Confirmatory Factor Analysis, Fitness Indexes, Structural Equation Modeling, Structural Model.

  • Purpose: Agile methodologies have emerged as an innovative and successful business changing way for software development companies since the success rate for completing the software projects on time and budget is better than conventional methodologies. This study proposes a theoretical framework of success factors for agile software development and validates the proposed framework using structural equation modeling.

    Design Methodology: A survey based random sampling was performed for data collection from 201 respondents identified from the pool of agile practitioners in software companies. Structural Equation Modeling performed on the collected data to validate measurement model as well as the structural model.

    Findings: The theoretical model was confirmed with modifications and the results showed that required level of fitness indexes have been achieved for the measurement model and structural model. The validation of the factors has also been done.

    Originality/Value: This study will guide the agile practitioners, academicians and project managers to focus more on the particular success factors which have high weight towards project success.

  • References

    1. [1] V. Kukreja and A. Singh, “Agile Enablers and Adoption Scenario in Industry Context,†in Achieving Enterprise Agility through Innovative Software Development., IGI Global, 2015, pp. 157–178.

      [2] “11th Annual State of Agile Report,†2017.

      [3] KPMG, “Driving business performance : Project Management Survey 2017,†2017.

      [4] S. Ahmad, N. N. A. Zulkurnain, and F. I. Khairushalimi, “Assessing the fitness of a measurement model using Confirmatory Factor Analysis (CFA),†Int. J. Innov. Appl. Stud., vol. 17, no. 1, pp. 159–168, 2016.

      [5] Z. Awang, A handbook on SEM : Structural equation modeling using AMOS. Malaysia, Universiti Technologi MARA Press, 2012.

      [6] Y. Baruch, “Response rate in academic studies - A comparative analysis,†Hum. Relations, vol. 52, no. 4, pp. 421–438, 1999. https://doi.org/10.1177/001872679905200401.

      [7] A. Singh, “Design of distributed agile development system for indian software industry,†Punjabi University, 2013.

      [8] R. L. Ackoff, “Redesigning the future,†Syst. Pract., vol. 3, no. 6, pp. 521–524, 1990.

      [9] J. B. Ullman, “Structural Equation Modeling: Reviewing the Basics and Moving Forward,†J. Pers. Assess., vol. 87, no. 1, pp. 35–50, 2006.

      [10] J. B. Schreiber, K. Stage. Frances, J. King, A. Nora, and E. A. Barlow, “Reporting Structural Equation Modeling and Confirmatory Factor Analysis Results : A Review,†vol. 99, no. 6, 2006.

      [11] M. Matsunaga, “How to Factor-Analyze Your Data Right: Do’s, Don’ts, and How-To’s,†Int. J. Psychol. Res., vol. 3, no. 1, pp. 97–110, 2010.

      [12] W. Mohamad, A. Bin, W. Afthanorhan, S. Ahmad, and I. Mamat, “Pooled Confirmatory Factor Using Structural Equation Modeling On Volunteerism Program : A Step By Step Approach Sabri Ahmad Ibrahim Mamat Contribution / Originality,†Int. J. Asian Soc. Sci., vol. 4, no. 5, pp. 642–653, 2014.

      [13] M. Igbaria and J. Iivari, “The effects of self-efficacy on computer usage,†Omega, Int. J. Mgmt Sci., vol. 23, no. 6, pp. 587–605, 1995.

      [14] C. Fornell and D. F. Larcker, “Structural Equation Models with Unobservable Variables and Measurement Error: Algebra and Statistics,†J. Mark. Res., vol. 18, no. 3, pp. 382–388, 1981. https://doi.org/10.2307/3150980

      [15] H. H. Chang and S.-S. Chuang, “Social capital and individual motivations on knowledge sharing: Participant involvement as a moderator,†Inf. Manag., vol. 48, no. 1, pp. 9–18, 2011. https://doi.org/10.1016/j.im.2010.11.001.

      [16] H.-F. Lin, “A stage model of knowledge management: an empirical investigation of process and effectiveness,†J. Inf. Sci., vol. 33, no. 6, pp. 643–659, 2007.

      [17] E. E. Chong, A. Nazim, and S. B. Ahmad, “A comparison between individual confirmatory factor analysis and pooled confirmatory factor analysis: An analysis of library service quality, a case study at a public university in Terengganu,†Int. J. Eng. Sci. Innov. Technol., vol. 3, no. 1, pp. 110–116, 2014.

      [18] J. F. Hair, W. C. Black, J. Babin, Barry, and R. E. Anderson, Multivariate data analysis, 7th ed., vol. 417, no. 1–2. 2010.

      [19] R. P. McDonald and M. R. Ho, “Principles and practice in reporting structural equation analyses,†Psychol. Methods, vol. 7, no. 1, pp. 64–82, 2002. https://doi.org/10.1037/1082-989X.7.1.64.

      [20] W. J. Doll and W. Xia, “Confirmatory Factor Analysis of the End – User Computing Satisfaction Instrument : A Replication,†J. Organ. End User Comput., vol. 9, no. 2, pp. 24–32, 1997. https://doi.org/10.4018/joeuc.1997040103.

      [21] A. H. Seyal, M. N. A. Rahman, and M. M. Rahim, “Determinants of academic use of the internet: A structural equation model,†Behav. Inf. Technol., vol. 21, no. 1, pp. 71–86, 2002. https://doi.org/10.1080/01449290210123354.

      [22] C. L. Hsu and J. C.-C. Lin, “Acceptance of blog usage: The roles of technology acceptance, social influence and knowledge sharing motivation,†Inf. Manag., vol. 45, no. 1, pp. 65–74, 2008. https://doi.org/10.1016/j.im.2007.11.001.

      [23] J. Etezadi-Amoli and A. F. Farhoomand, “A Structural Model of End Eser Computing Satisfaction and User Performance,†Inf. Manag., vol. 30, no. 2, pp. 65–73, 1996. https://doi.org/10.1016/0378-7206(95)00052-6.

      [24] H. Baumgartner and C. Homburg, “Applications of structural equation modeling in marketing and consumer research: A review,†Int. J. Res. Mark., vol. 13, no. 2, pp. 139-161, 1996. https://doi.org/10.1016/0167-8116(95)00038-0.

      [25] L. Hu and P. M. Bentler, “Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives,†Struct. Equ. Model. vol. 6, no. 1, pp. 1–55, 1999. https://doi.org/10.1080/10705519909540118.

      [26] P. M. Bentler and D. G. Bonett, “Significance tests and goodness of fit in the analysis of covariance structures,†Psychol. Bull., vol. 88, no. 3, pp. 588–606, 1980. https://doi.org/10.1037/0033-2909.88.3.588.

      [27] J.-H. Wu and Y.-M. Wang, “Measuring KMS success: A respecification of the DeLone and McLean’s model,†Inf. Manag., vol. 43, pp. 728–739, 2006.

      [28] R. B. Kline, Principles and practice of structural equation modeling, Second. New York, London: Guilford press, 2005.

      [29] J. E. Scott, “The Measurement of Information Systems Effectiveness: Evaluating a Measuring Instrument,†Data Base Adv., vol. 26, no. 1, pp. 43–61, 1995.

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    Kukreja, V., Ahuja, S., & Singh, A. (2018). Measurement and structural model of agile software development critical success factors. International Journal of Engineering & Technology, 7(3), 1236-1242. https://doi.org/10.14419/ijet.v7i3.12776