Skip to main content

Advertisement

Springer Nature Link
Log in

Productivity paradoxes revisited

Assessing the relationship between quality maturity levels and labor productivity in brazilian software companies

  • Published:
Empirical Software Engineering Aims and scope Submit manuscript

Abstract

The adoption of quality assurance methods based on software process improvement models has been regarded as an important source of variability in software productivity. Some companies perceive that their implementation has prohibitive costs, whereas some authors identify in their use a way to comply with software development patterns and standards, produce economic value and lead to corporate performance improvement. In this paper, we investigate the relationship between quality maturity levels and labor productivity, using a data set containing 687 Brazilian software firms. We study here the relationship between labor productivity, as measured through the annual gross revenue per worker ratio, and quality levels, which were appraised from 2006 to 2012 according to two distinct software process improvement models: MPS.BR and CMMI. We perform independent statistical tests using appraisals carried out according to each of these models, consequently obtaining a data set with as many observations as possible, in order to seek strong support for our research. We first show that MPS.BR and CMMI appraised quality maturity levels are correlated, but we find no statistical evidence that they are related to higher labor productivity or productivity growth. On the contrary, we present evidence suggesting that average labor productivity is higher in software companies without appraised quality levels. Moreover, our analyses suggest that companies with appraised quality maturity levels are more or less productive depending on factors such as their business nature, main origin of capital and maintained quality level.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

Notes

  1. CVM is the Brazilian Securities and Exchanges Commission.

  2. We chose to adopt a smaller than usual significance level since the beginning of research because we consider the consequences of type I errors (rejecting the null hypothesis when it is true) more serious than type II errors (accepting the main hypothesis when it is false).

References

  • ABES (Unknown Month 2007) The Brazilian Software Market [Online]. Brazilian Association of Software Companies, volumes from 2006 to 2012 . https://www.abessoftware.com.br/dados-do-setor/anos-anteriores

  • Boehm BW (1981) Software Engineering Economics. Prentice Hall

  • Boehm BW (1987) Improving software productivity. IEEE Comput 20(9):43–57

    Article  Google Scholar 

  • Brynjolfsson E, Hitt LM (1998) Beyond the productivity paradox. Commun ACM 41(8):49–55

    Article  Google Scholar 

  • Chrissis MB, Konrad M, Shrum S (2006) CMMI: Guidelines For process integration and product improvement. Addison-Wesley, SEI Series in Software Engineering

    Google Scholar 

  • CMMI Institute (2013) Published Appraisal Results [Online]. https://sas.cmmiinstitute.com/pars/pars.aspx

  • Collofello JS, Woodfield SN, Gibbs NE (1983) Software productivity measurement. In: Proc. National Computer Conference (AFIPS’83), pp 757–762

  • Duarte CHC (1996) Moving software to a global platform. IEEE Spectr 33 (7):40–43

    Article  Google Scholar 

  • Duarte CHC (2002) Brazil: Cooperative Development of a software industry. IEEE Softw 19(3):84–87

    Article  Google Scholar 

  • Duarte CHC (2012) A decade of continued support to the information and communication technology sector in Brazil: The most relevant events and the role of BNDES. Revista do BNDES 19(37):91–126. in Portuguese

    Google Scholar 

  • Duarte CHC (2014) On the relationship between quality assurance and productivity in software companies. In: Proc. 2nd international workshop on conducting empirical studies in industry (CESI 2014). Hyderabad, India, pp 31–38

  • Duarte CHC, Branco CEC (2001) Social and economic impacts of the Brazilian policy for information technologies. Revista do BNDES 15:125–146. in Portuguese

    Google Scholar 

  • Exame Informática (Unknown Month 2007) The Bigger and Better Brazilian Companies. Volumes from 2006 to 2012. In Portuguese

  • Gorschek T, Davis A (2008) Requirements engineering: in search of the dependent variables. Inf Softw Technol 50(1-2):67–75

    Article  Google Scholar 

  • Griliches Z (1986) Productivity, R&D and basic research at the firm level in the 1970s. Am Econ Rev 76(1):141–154

    MathSciNet  Google Scholar 

  • Herbsleb JD, Goldenson DR (1996) A systematic survey of CMM experience and results. In: Proc. 18th International Conference on Software Engineering (ICSE 1996), pp 323–330

  • Herbsleb JD, Zubrow D, Goldenson DR, Hayes W, Paulk M (1997) Software quality and the capability maturity model. Commun ACM 40(6):30–40

    Article  Google Scholar 

  • Informática Hoje (Unknown Month 2007) Anuário [Online]. Volumes from 2006 to 2012. In Portuguese. http://www.forumeditorial.com.br/

  • ISO/IEC (1998) ISO/IEC 15504: Information Technology - Software Process Assessment. International Standards Organization

  • Jones C, Bonsignour O (2012) The Economics of Software Quality. Addison-Wesley

  • Kalinowski M, et al. (2011) From software engineering research to Brazilian software quality improvement. In: Proc. 15th Brazilian Software Engineering Symposium (SBES’2011), pp 120–125

  • Kamma D, Jalote P (2013) Effect of task processes on programmer productivity in model-based testing. In: Proc. 6th India Software Engineering Conference (ISEC 2013), pp 23–28

  • Konrad M, Shrum S (2011) CMMI For development: Version 1.3, 3rd edn. Addison-Wesley, SEI Series in Software Engineering

    Google Scholar 

  • Krishnan MS, Kriebel CH, Kekre S, Mukhopadhyay T (2000) An empirical analysis of productivity and quality in software products. Manag Sci 46(6):745–759

    Article  Google Scholar 

  • Levene DM, Berenson M, Stephan D, Krehbiel TC (2008) Statistics for Managers using Microsoft Excell, 5th edn. Prentice Hall

  • Maxwell K, Wassenhove LV, Dutta S (1996) Software development productivity of european space, military and industrial applications. IEEE Trans Softw Eng 22 (10):706–718

    Article  Google Scholar 

  • Montoni MA, Rocha AR, Weber KC (2009) MPS.BR: A successful program for software process improvement in Brazil. Softw Process: Improv Pract 14(5):289–300

    Article  Google Scholar 

  • Nguyen V, Huang LG, Boehm B (2011) An analysis of trends in productivity and cost drivers over years. In: Proc. 7th International Conference on Predictive Models in Software Engineering (PROMISE 2011), pp 1–10

  • OECD (2001) Measuring Productivity: Measurement of Aggregate and Industry-Level Productivity Growth. Organization for Economic Cooperation and Development

  • Paulk MC, Weber CV, Curtis B, Chrissis MB (1995) The Capability Maturity Model: Guidelines for Improving Software Processes. Addison-Wesley

    Google Scholar 

  • Petersen K (2011) Measuring and predicting software productivity. Inf Softw Technol 53(4):317–343

    Article  MathSciNet  Google Scholar 

  • Pilat D (2004) The ICT Productivity Paradox: Insights from Micro Data. OECD Economic Studies 38, Organization for Economic Cooperation and Development

  • Rosner B (2010) Fundamentals of Bioinformatics, 7th edn. Books and Coole

  • Rubin HA (1993) Software process maturity: Measuring its impact on productivity and quality. In: Proc. 15th International Conference on Software Engineering (ICSE 1993), pp 468–476

  • Siy HP, et al. (2001) Making the software factory work: Lessons from a decade of experience. In: Proc. 7th International Symposium on Software Metrics (METRICS 2001), pp 317–326

  • Softex Society (2013) MPS.BR Evaluations [Online]. http://www.softex.br/mpsbr

  • Staples M, et al. (2007) An exploratory study of why organizatons do not adopt CMMI. J Syst Softw 80(6):883–895

    Article  Google Scholar 

  • Trendowicz A, Ochs M, Wickenkamp A, Münch J, Ishigai Y, Kawaguchi T (2008) An integrated approach for identifying relevant factors influencing software development productivity. In: Balancing agility and forMalism in software engineering, Springer, lecture notes in computer science, vol 5082, pp 223–237

  • Tsunoda M, Monden A, Yadohisa H, Kikuchi N, Matsumoto K (2006) Productivity analysis of Japanese enterprise software development projects. In: Proc. 2006 International Workshop on Mining Software Repositories (MSR 2006), pp 14–17

  • Valor Econômico (Unknown Month 2007) Valor 1000. Volumes from 2006 to 2012. In Portuguese

  • Wang Y, Zhang C, Chen G, Shi Y (2012) Empirical research on the total factor productivity of Chinese software companies. In: Proc. 2012 international joint conferences on web intelligence and intelligent agent technology (WI-IAT 2012), vol 3, pp 25–29

Download references

Acknowledgments

The author wishes to thank the Softex Society administration, for providing a compilation of historical data concerning MPS.BR appraisals, as well as to Luiz Paulo Alves Franca and some anonymous reviewers, for their helpful comments and criticism on earlier versions of this paper.

Author information

Authors and Affiliations

  1. BNDES, Av. República do Chile 100, Rio de Janeiro, RJ, 20001-970, Brazil

    Carlos Henrique C. Duarte

Authors
  1. Carlos Henrique C. Duarte
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Carlos Henrique C. Duarte.

Additional information

Communicated by: Filippo Lanubile

This paper is an extended version of Duarte (2014). Although we adopt the same research methodology and report the same conclusions here, our data sets were revised and extended with data from financial statements and market research reports not available at the time of that publication. The assumptions, views and opinions in this paper are solely those of the author and do not necessarily reflect the official policy, strategy or position of any Brazilian government entity.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

C. Duarte, C.H. Productivity paradoxes revisited. Empir Software Eng 22, 818–847 (2017). https://doi.org/10.1007/s10664-016-9453-5

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10664-016-9453-5

Keywords

Search

Navigation