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FQWCOS: A Flexible Model for Measuring Customer Satisfaction on Software Based Products and Service

Received: 10 November 2018     Accepted: 11 December 2018     Published: 28 December 2018
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Abstract

Many software products and services deployed in user environments at times fail to meet user needs satisfactorily. This may be due to the fact that the product or service failed to meet user requirements from the outset (inception) of the Information Systems (IS) project. This study proposes a Flexible Qualifier Weighted Customer Opinion with Safeguard Estimates (FQWCOS) model for measuring the satisfaction of users of software products and services. The FQWCOS model is a variant of the Qualifications Weighted Customer Opinion with Safeguard questions (QWCOS). The FQWCOS model was verified with empirical data using samples from 40 users of ASAS software product. Descriptive statistics were also used to obtain the frequencies, mean values, relative frequencies, standard error, and standard deviation. From these values, it was possible to compute the normalized score of customer opinion Oi and the external measures E for QWCOS and Ei (i=1-4) for FQWCOS were computed. Results from the study reveal that there was no difference between the external measures for QWCOS and FQWCOS. However, the result suggest that external measures were higher when standard error (SE) was used to obtain the measures at different levels 31.58, 19.79, 21.76, 35.69 and 31.06 than when external measure was computed using standard deviation (STD) which yielded the values 4.99, 3.13, 3.44, 5.64 and 4.07. We conclude that FQWCOS and QWCOS yield the same values probably due to small sample used. However, FQWCOS provides a flexible and simple approach, and reveals the need to use the standard error instead of standard deviation since this yields higher magnitude values appropriate for expressing external measures in percentages.

Published in Software Engineering (Volume 6, Issue 4)
DOI 10.11648/j.se.20180604.11
Page(s) 110-115
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2018. Published by Science Publishing Group

Keywords

Software Quality, External Measurement, Customer Satisfaction, Flexible Model

References
[1] D. A. Baker and J. L. Crompton, “Quality, satisfaction and behavioral intentions”, Annals of Tourism research, Vol. 27, no. 3, pp. 785-804, 2000.
[2] D. Dungan. “Enterprise Software Architecture and Design: Entities, Services, and Resources”. USA: Wiley, 2012, pp. xxiii+481.
[3] D. Stravrinoudis, and M. Xenos, “Comparing internal and external software quality measurements,” Proceedings of the 8th Joint Conference on Knowledge-Based Software Engineering, Piraeus Greece: IOS Press, August 25-28, pp. 115-124, 2008.
[4] E. J. Weyuker, “Evaluating software complexity measures,” IEEE Transactions on Software Engineering, vol. 14, no. 9, pp. 1357– 1365, 1988.
[5] E. U. Okike, “Measuring Class Cohesion in Object-Oriented Systems Using Chidamber and Kemerer Metrics and Java as Case study,” P.HD Thesis, Department of Computer Science, University of Ibadan, xvii+133 pp, 2007.
[6] E. U. Okike, and Merapelo Mogorosi, “Measuring the usability probability of learning management software using logistic regression model”, Computing conference, London, UK, 18-20 July, 2017.
[7] E. U. Okike, “A proposal of Normalized Lack of Cohesion in Method (LCOM) metric using field experiment”, International journal of Computer Science Issues, vol. 7, issue 4, no. 5, pp. 19-27, 2010.
[8] E. Okike and A. Osofisan, “A validation of Chidamber and Kemerer’s LCOM metric using measurement theory”, Journal of Applied Information Science and Technology, vol 1 issue 1, pp. 30-43, 2007.
[9] F. Beck, and S, Dichl, “On the congruence of modularity and code coupling”, Proceedings of the 19th ACM SIGSOFT symposium and the 13th European conference on Foundations of software engineering, ACM, NYUSA, 354-364, 2011
[10] ISO 25022-250240 Quality Measurement structure and revised models, 2015
[11] J. A. Dallal, “Measuring the discriminating power of Object-oriented class cohesion metrics”, IEEE transactions on software engineering, 37 (6), 788-804, 2011.
[12] J. M. Bieman and B. K. Kang, “Measuring design level cohesion”, IEEE transactions on Softwate Engineering, 20, 2: 111-124, 1998.
[13] J. Michura, M. Capretz and S. Wang, “Extension of Object-oriented metrics suite for software maintenance”, Hindawi Publishing Corporation ISRN Software Engineering Volume 2013, Article ID 276105, 14 pages, 2013 http://dx.doi.org/10.1155/2013/276105
[14] H Oh, “Service quality, customer satisfaction, and customer value: A holistic perspective”, Hospitality Management 18, 67-82, 1999.
[15] H. S. Chae, Y. R. Kwon, and D. H. Bae, “A cohesion measure for classes in object-oriented classes,” Software, vol. 30, no. 12, pp. 1405–1431, 2000.
[16] L. Badri, and M. Badri, “A proposal of a new class cohesion criterion: an empirical study”, Journal of object technology, 3, 4: 145-159, 2004.
[17] L. Etzkorn, J. Bansiya, and C. Davis, “Design and code complexity metrics for OO classes,” Journal of Object-Oriented Programming, vol. 12, no. 1, pp. 35–40, 1999.
[18] M. Asher. Measuring customer satisfaction, The TQM magazine. Vol. Iss. 2. Pp 93-97. 1989.
[19] M. Bundschuh and C. Dekkers, “Object-oriented metrics,” in The IT Measurement Compendium, M. Bundschuh and C. Dekkers, Eds., pp. 241–255, Springer, Berlin, Germany, 2008.
[20] M. H. Tang, M. H. Kao, and M. H. Chen, “An empirical study on object-oriented metrics,” in Proceedings of the 6th International Software Metrics Symposium, pp. 242–249, November 1999.
[21] N. E. Fenton, and S. L. Pfleedger, “ Software Metrics: A rigorous & Practical Approach,” 2nd ed., London: PWS, pp. xii+638, 1997.
[22] N. F. Schneidewind, “ Systems ans Software Engineering with Applications”, USA: Standards Information Network, IEEE press, xix+ 443pp, 2009.
[23] N. Gorla, and R. Ramakrishnan, “ The Effect of Software Structure attributes on Software Development Productivity,” Journal of Systems and Software, 36, 2: 191-199, 1997.
[24] P. D. Dacrcy; C. F. Kemerer; S. A. Slaughter, and J. E. Tomayko, “ The structural complexity of software: an experimental test”, IEEEtransactions on Software Engineering, 32. 1: 54-64, 2005.
[25] P. Ralph. “The illusion of Requirements in Software Development,” Requirements Engineering (2013) 18, pp. 293-296.
[26] S. M. Smith, “ Customer Satisfaction Survey Questions: 5 Sample Templates you can use right away,” www. Qualtric.com retrieved 26 July, 2018.
[27] S. Ian, “Software Engineering”, 9th ed., USA: Pearson, 2011, pp. xiii+773.
[28] S. Sarkar, A. C. Kak, and G. M. Rama, “Metrics for measuring the quality of modularization of large-scale object-oriented software,” IEEE Transactions on Software Engineering, vol. 34, no. 5, pp. 700–720, 2008.
[29] V. R. Basili, L. C. Briand, and W. L. Melo, “A validation of object-oriented design metrics as quality indicators,” IEEE Transactions on Software Engineering, vol. 22, no. 10, pp. 751– 761, 1996.
[30] Y. Zhou, B. Xu, and H. Leung, “On the ability of complexity metrics to predict fault-prone classes in object-oriented systems,” Journal of Systems and Software, vol. 83, no. 4, pp. 660–674, 2010.
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  • APA Style

    Ezekiel Uzor Okike. (2018). FQWCOS: A Flexible Model for Measuring Customer Satisfaction on Software Based Products and Service. Software Engineering, 6(4), 110-115. https://doi.org/10.11648/j.se.20180604.11

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    ACS Style

    Ezekiel Uzor Okike. FQWCOS: A Flexible Model for Measuring Customer Satisfaction on Software Based Products and Service. Softw. Eng. 2018, 6(4), 110-115. doi: 10.11648/j.se.20180604.11

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    AMA Style

    Ezekiel Uzor Okike. FQWCOS: A Flexible Model for Measuring Customer Satisfaction on Software Based Products and Service. Softw Eng. 2018;6(4):110-115. doi: 10.11648/j.se.20180604.11

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  • @article{10.11648/j.se.20180604.11,
      author = {Ezekiel Uzor Okike},
      title = {FQWCOS: A Flexible Model for Measuring Customer Satisfaction on Software Based Products and Service},
      journal = {Software Engineering},
      volume = {6},
      number = {4},
      pages = {110-115},
      doi = {10.11648/j.se.20180604.11},
      url = {https://doi.org/10.11648/j.se.20180604.11},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.se.20180604.11},
      abstract = {Many software products and services deployed in user environments at times fail to meet user needs satisfactorily. This may be due to the fact that the product or service failed to meet user requirements from the outset (inception) of the Information Systems (IS) project. This study proposes a Flexible Qualifier Weighted Customer Opinion with Safeguard Estimates (FQWCOS) model for measuring the satisfaction of users of software products and services. The FQWCOS model is a variant of the Qualifications Weighted Customer Opinion with Safeguard questions (QWCOS). The FQWCOS model was verified with empirical data using samples from 40 users of ASAS software product. Descriptive statistics were also used to obtain the frequencies, mean values, relative frequencies, standard error, and standard deviation. From these values, it was possible to compute the normalized score of customer opinion Oi and the external measures E for QWCOS and Ei (i=1-4) for FQWCOS were computed. Results from the study reveal that there was no difference between the external measures for QWCOS and FQWCOS. However, the result suggest that external measures were higher when standard error (SE) was used to obtain the measures at different levels 31.58, 19.79, 21.76, 35.69 and 31.06 than when external measure was computed using standard deviation (STD) which yielded the values 4.99, 3.13, 3.44, 5.64 and 4.07. We conclude that FQWCOS and QWCOS yield the same values probably due to small sample used. However, FQWCOS provides a flexible and simple approach, and reveals the need to use the standard error instead of standard deviation since this yields higher magnitude values appropriate for expressing external measures in percentages.},
     year = {2018}
    }
    

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  • TY  - JOUR
    T1  - FQWCOS: A Flexible Model for Measuring Customer Satisfaction on Software Based Products and Service
    AU  - Ezekiel Uzor Okike
    Y1  - 2018/12/28
    PY  - 2018
    N1  - https://doi.org/10.11648/j.se.20180604.11
    DO  - 10.11648/j.se.20180604.11
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    JF  - Software Engineering
    JO  - Software Engineering
    SP  - 110
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    PB  - Science Publishing Group
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    UR  - https://doi.org/10.11648/j.se.20180604.11
    AB  - Many software products and services deployed in user environments at times fail to meet user needs satisfactorily. This may be due to the fact that the product or service failed to meet user requirements from the outset (inception) of the Information Systems (IS) project. This study proposes a Flexible Qualifier Weighted Customer Opinion with Safeguard Estimates (FQWCOS) model for measuring the satisfaction of users of software products and services. The FQWCOS model is a variant of the Qualifications Weighted Customer Opinion with Safeguard questions (QWCOS). The FQWCOS model was verified with empirical data using samples from 40 users of ASAS software product. Descriptive statistics were also used to obtain the frequencies, mean values, relative frequencies, standard error, and standard deviation. From these values, it was possible to compute the normalized score of customer opinion Oi and the external measures E for QWCOS and Ei (i=1-4) for FQWCOS were computed. Results from the study reveal that there was no difference between the external measures for QWCOS and FQWCOS. However, the result suggest that external measures were higher when standard error (SE) was used to obtain the measures at different levels 31.58, 19.79, 21.76, 35.69 and 31.06 than when external measure was computed using standard deviation (STD) which yielded the values 4.99, 3.13, 3.44, 5.64 and 4.07. We conclude that FQWCOS and QWCOS yield the same values probably due to small sample used. However, FQWCOS provides a flexible and simple approach, and reveals the need to use the standard error instead of standard deviation since this yields higher magnitude values appropriate for expressing external measures in percentages.
    VL  - 6
    IS  - 4
    ER  - 

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Author Information
  • Department of Computer Science, University of Botswana, Gaborone, Botswana

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