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Software code flexibility profitability in light of technology life cycle

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Abstract

This paper analyzes the crucial flexibility management facets of software code development, namely, reusable software code. Maximizing a reusable code level represents a normative engineering rationale of the highest adaptability for the code, which utterly generates future costs savings. However, given the finite life cycle of the technology, the optimal managerial financial-economic decision might not coincide with the pure engineering facet, which evolves from the reusable code’s tradeoff between initial investment and future project savings. The cost–benefit considerations of optimal software flexibility are converted into technology-based cyclical discounted cash flows. The study provides software development project managers with a powerful decision support tool to assess pro-engineering profitability of flexible code development. Numerical simulations on a set of literature-derived parameter values justify a pure reusable strategy in only 4.2% of the cases. Finally, the model illustrates the opportunity to adapt and optimize organizational structure as a substitute for software flexibility strategy.

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References

  • Agliardi E, Agliardi R (2011) Bond pricing under imprecise information. Oper Res Int J 11:299–309

    Article  Google Scholar 

  • Alexopoulos K, Papakostas N, Mourtzis D, Chryssolouris G (2011) A method for comparing flexibility performance for the lifecycle of manufacturing systems under capacity planning constraints. Int J Prod Res 49(11):3307–3317

    Article  Google Scholar 

  • Anand G, Ward PT (2004) Fit, flexibility and performance in manufacturing: coping with dynamic environments. Prod Oper Manag 13:369–385

    Article  Google Scholar 

  • Anderson SW (2001) Direct and Indirect Effects of Product Mix Characteristics on Capacity Management Decisions and Operating Performance. Int J Flex Manuf Syst 13:241–265

    Article  Google Scholar 

  • Baldwin CY, Clark KB (2000) Design rules: the power of modularity. The MIT Press, Cambridge

    Book  Google Scholar 

  • Baldwin CY, Clark KB (2006) The architecture of participation: does code architecture mitigate free riding in the open source development model? Manage Sci 52:1116–1127

    Article  Google Scholar 

  • Bruccoleri M, La Diega SN, Perrone G (2003) An Object-Oriented Approach for Flexible Manufacturing Control Systems Analysis and Design Using the Unified Modeling Language. Int J Flex Manuf Syst 15:195–216

    Article  Google Scholar 

  • Cai W, Abdel-Malek L, Hoseini B, Dehkordi SR (2015) Impact of flexible contracts on the performance of both retailer and supplier. Int J Prod Econ 170:429–444

    Article  Google Scholar 

  • Carr D, Kizior RJ (2003) Continued Relevance of COBOL in Business and Academia: current Situation and Comparison to the Year 2000 Study. Inf Syst Educ J 52(1):1–23

    Google Scholar 

  • Chakravarty S, Padakandla S, Bhatnagar S (2014) A simulation-based algorithm for optimal pricing policy under demand uncertainty. Int Trans Oper Res 21(5):737–760

    Article  Google Scholar 

  • Chryssolouris G, Efthymiou K, Papakostas N, Mourtzis D, Pagoropoulos A (2013) Flexibility and complexity: is it a trade-off? Int J Prod Res 51(23–24):6788–6802

    Article  Google Scholar 

  • Correa HL (1994) Linking flexibility, uncertainty and variability in manufacturing systems: managing unplanned change in the automotive industry. Aldershot, Avebury

    Google Scholar 

  • De Groote X (1994) Flexibility of production processes: a general framework. Manage Sci 40:933–945

    Article  Google Scholar 

  • Elkins DA, Huang N, Alden JM (2004) Agile manufacturing systems in the automotive industry. Int J Prod Econ 91(3):201–214

    Article  Google Scholar 

  • Favaro J (1996) A comparison of approaches to reuse investment analysis. In: Proceedings fourth international conference on software reuse, 1996, anonymous IEEE, pp 136–145

  • Favaro JM, Favaro KR, Favaro PF (1998) Value based software reuse investment. Ann Softw Eng 5:5–52

    Article  Google Scholar 

  • Fiorencio L, Oliveira F, Nunes P, Hamacher S (2015) Investment planning in the petroleum downstream infrastructure. Int Trans Oper Res 22(2):339–362

    Article  Google Scholar 

  • Fortune J, Valerdi R, Boehm BW, Settles FS (2009) Estimating systems engineering reuse. In: 7th annual conference on systems engineering research, CSER, Anonymous

  • Frakes WB, Isoda S (1994) Success factors of systematic reuse. IEEE Softw 11:15–19

    Article  Google Scholar 

  • Frakes WB, Kang K (2005) Software reuse research: status and future. IEEE Trans Software Eng 31(7):529–536

    Article  Google Scholar 

  • Frakes W, Terry C (1996) Software reuse: metrics and models. ACM Comput Surv 28:415–435

    Article  Google Scholar 

  • Gerwin D (1993) Manufacturing flexibility: a strategic perspective. Manage Sci 39(4):395–408

    Article  Google Scholar 

  • Gordon MJ (1959) Dividends, earnings, and stock prices. Rev Econ Stat 41:99–105

    Article  Google Scholar 

  • Gupta D (1993) On measurement and valuation of manufacturing flexibility. Int J Prod Res 31(12):2947–2958

    Article  Google Scholar 

  • Gupta D, Buzacott JA (1989) A framework for understanding flexibility of manufacturing systems. J Manuf Syst 8(2):89–97

    Article  Google Scholar 

  • Gupta YP, Goyal S (1989) Flexibility of manufacturing systems: concepts and measurement. Eur J Oper Res 43:119–135

    Article  Google Scholar 

  • Haefliger S, Von Krogh G, Spaeth S (2008) Code reuse in open source software. Manage Sci 54:180–193

    Article  Google Scholar 

  • Haruvy E, Sethi SP, Zhou J (2008) Open source development with a commercial complementary product or service. Prod Oper Manag 17(1):29–43

    Article  Google Scholar 

  • Hu F, Lim C, Lu Z (2013) Coordination of supply chains with a flexible ordering policy under yield and demand uncertainty. Int J Prod Econ 146(2):686–693

    Article  Google Scholar 

  • Hughes B, Cotterell M (2002) Software Project Management. McGraw-Hill, London

  • Jakubovskis A (2017) Flexible production resources and capacity utilization rates: a robust optimization perspective. Int J Prod Econ 189:77–85

    Article  Google Scholar 

  • Kalantonis P, Gaganis C, Zopounidis C (2014) The role of financial statements in the prediction of innovative firms: empirical evidence from Greece. Oper Res Int J 14:439–451

    Article  Google Scholar 

  • Kirk D, Roper M, Wood M (2007) Identifying and addressing problems in object-oriented framework reuse. Emp Softw Eng 12:243–274

    Article  Google Scholar 

  • Kogan K, El Ouardighi F, Herbon A (2017) Production with learning and forgetting in a competitive environment. Int J Prod Econ 189:52–62

    Article  Google Scholar 

  • Koste LL, Malhotra MK (1999) Theoretical framework for analyzing the dimensions of manufacturing flexibility. J Oper Manag 18:75–93

    Article  Google Scholar 

  • Krishnan V, Bhattacharya S (2002) Technology selection and commitment in new product development: the role of Uncertainty and Flexibility Design. Manage Sci 48(3):313–327

    Article  Google Scholar 

  • Krueger CW (1992) Software reuse. ACM Comput Surv 24:131–183

    Article  Google Scholar 

  • Kulatilaka N, Marks SG (1988) The strategic value of flexibility: reducing the ability to compromise. Am Econ Rev 78(3):574–580

    Google Scholar 

  • Lenz JE (1992) The need for both labor and machine flexibility in manufacturing. Ind Eng 24(10):22-23

    Google Scholar 

  • Maccormack A, Rusnak J, Baldwin CY (2006) Exploring the structure of complex software designs: an empirical study of open source and proprietary code. Manage Sci 52:1015–1030

    Article  Google Scholar 

  • McIlroy MD, Buxton J, Naur P, Randell B (1968) Mass-produced software components. In: Proceedings of the 1st international conference on software engineering, Garmisch Pattenkirchen, Germany, Anonymous sn, pp 88–98

  • Mellarkod V, Appan R, Jones DR, Sherif K (2007) A multi-level analysis of factors affecting software developers’ intention to reuse software assets: an empirical investigation. Inf Manag 44:613–625

    Article  Google Scholar 

  • Mernik M, Heering J, Sloane AM (2005) When and how to develop domain-specific languages. ACM Comput Surv 37:316–344

    Article  Google Scholar 

  • Mili H, Mili F, Mili A (1995) Reusing software: issues and research directions. IEEE Trans Softw Eng 21:528–562

    Article  Google Scholar 

  • Mishra R, Pundir AK, Ganapathy L (2014) Manufacturing flexibility research: a review of literature and agenda for future research. Global J Flex Syst Manag 15(2):101–112

    Article  Google Scholar 

  • Naab M, Stammel J (2012) Architectural flexibility in a software-system’s life-cycle: systematic construction and exploitation of flexibility. In: Proceedings of the 8th international ACM SIGSOFT conference on quality of software architectures. ACM, pp 13–22

  • Nagarur N (1992) Some performance measures of flexible manufacturing systems. Int J Prod Res 30(4):799–809

    Article  Google Scholar 

  • Narasimhan R, Das A (1999) An empirical examination of the contribution of strategic sourcing to manufacturing flexibilities and performance. Decis Sci 30(3):683–718

    Article  Google Scholar 

  • Naumann M, Suhl L (2013) How does fuel price uncertainty affect strategic airline planning? Oper Res Int J 13(3):343–362

    Article  Google Scholar 

  • Park PS, Bobrowski PM (1989) Job release and labor flexibility in a dual resource constrained job shop. J Oper Manag 8:230–249

    Article  Google Scholar 

  • Pendaraki K, Spanoudakis N (2015) Portfolio performance and risk-based assessment of the PORTRAIT tool. Oper Res 15(3):359-378

    Google Scholar 

  • Pressman RS (2005) Software engineering: a practitioner’s approach, 7th edn, McGraw-Hill

  • Prikladnicki R, Audy J, Damian D, De Oliveira TC (2007) Distributed software development: practices and challenges in different business strategies of offshoring and onshoring. Munich, 27–30 August 2007, Anonymous, pp 262–274

  • Ramasesh RV, Jayakumar MD (1991) Measurement of manufacturing flexibility: a value based approach. J Oper Manag 10:446–468

    Article  Google Scholar 

  • Ramasesh RV, Jayakumar MD (1997) Inclusion of flexibility benefits in discounted cash flow analyses for investment evaluation: a simulation/optimization model. Eur J Oper Res 102:124–141

    Article  Google Scholar 

  • Sethi AK, Sethi PS (1990) Flexibility in manufacturing: a survey. Int J Flex Manuf Syst 2:289–328

    Article  Google Scholar 

  • Shuiabi E, Thomson V, Bhuiyan N (2005) Entropy as a measure of operational flexibility. Eur J Oper Res 165:696–707

    Article  Google Scholar 

  • Siraj S, Mikhailov L, Keane JA (2015) PriEsT: an interactive decision support tool to estimate priorities from pairwise comparison judgments. Int Trans Oper Res 22(2):217–235

  • Slack N (2005) The changing nature of operations flexibility. Int J Oper Prod Manag 25(12):1201–1210

    Article  Google Scholar 

  • Sohel A, Schroeder R (2003) The Impact of Human Resource Management Practices on Operational Performance: recognizing Country and Industry Differences. J Oper Manag 21:19–43

    Article  Google Scholar 

  • Sommerville I (2007) Software engineering, 8th edn. Addison-Wesley, Boston

    Google Scholar 

  • Spinellis D (2007) Cracking software reuse. IEEE Softw 24:12–13

    Article  Google Scholar 

  • Upton DM (1994) The management of manufacturing flexibility. Calif Manag Rev 36(2):72–89

    Article  Google Scholar 

  • Wang X, Zhang J (2015) Process flexibility: a distribution-free bound on the performance of k-chain. Oper Res 63(3):555–571

    Article  Google Scholar 

  • Wang G, Valerdi R, Fortune J (2010) Reuse in systems engineering. IEEE Syst J 4:376–384

    Article  Google Scholar 

  • Yang D, Kim S, Nam C, Min J (2007) Developing a decision model for business process outsourcing. Comput Oper Res 34:3769–3778

    Article  Google Scholar 

  • Yu K, Cadeaux J, Luo BN (2015) Operational flexibility: review and meta-analysis. Int J Prod Econ 169:190

    Article  Google Scholar 

  • Zhang Q, Wu D, Fu C, Baron C, Peng Z (2017) A new method for measuring process flexibility of product design. Int Trans Oper Res 24(4):821–838

    Article  Google Scholar 

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Akron, S., Gelbard, R. Software code flexibility profitability in light of technology life cycle. Oper Res Int J 20, 723–746 (2020). https://doi.org/10.1007/s12351-017-0350-5

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