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Open innovation in software engineering: a systematic mapping study

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Abstract

Open innovation (OI) means that innovation is fostered by using both external and internal influences in the innovation process. In software engineering (SE), OI has existed for decades, while we currently see a faster and broader move towards OI in SE. We therefore survey research on how OI takes place and contributes to innovation in SE. This study aims to synthesize the research knowledge on OI in the SE domain. We launched a systematic mapping study and conducted a thematic analysis of the results. Moreover, we analyzed the strength of the evidence in the light of a rigor and relevance assessment of the research. We identified 33 publications, divided into 9 themes related to OI. 17/33 studies fall in the high–rigor/high–relevance category, suggesting the results are highly industry relevant. The research indicates that start-ups have higher tendency to opt for OI compared to incumbents. The evidence also suggests that firms assimilating knowledge into their internal R&D activities, have higher likelihood of gaining financial advantages. We concluded that OI should be adopted as a complementary approach to facilitate internal innovation and not to substitute it. Further research is advised on situated OI strategies and the interplay between OI and agile practices.

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References

  • Allen RC (1983) Collective invention. J Econ Behav Organ 4(1):1–24

    Article  Google Scholar 

  • Balka K (2010) Christina Raasch, and Cornelius Herstatt. How open is open source? - software and beyond. Creat Innov Manag 19(3):248–256

    Article  Google Scholar 

  • Beyer F, Wright K (2011) Comprehensive searching for systematic reviews: a comparison of database performance. Technical report, Centre for Reviews and Dissemination. The University of York

  • Brad S, Fulea M (2008) Bogdan Mocan, Adina Duca, and Emilia Brad. Software platform for supporting open innovation. In: 2008 IEEE International Conference on Automation, Quality and Testing, Robotics (AQTR 2008), vol 3, NJ, USA, pp 224–229

  • Chesbrough HW (2003) Open innovation: the new imperative for creating and profiting from technology. Harvard Business School Press, Boston, Mass

    Google Scholar 

  • Chulani S, Williams C, Yaeli A (2008) Software development governance and its concerns. In: Proceedings of the 1st International Workshop on Software Development Governance, SDG 08. ACM, NY, USA, pp 3–6

    Chapter  Google Scholar 

  • Colombo MG, Piva E, Rossi-Lamastra C (2013) Open innovation and within-industry diversification in small and medium enterprises: The case of open source software firms. Research Policy

  • Conboy K, Morgan L (2011) Beyond the customer: Opening the agile systems development process. Inf Softw Technol 53(5):535–542

    Article  Google Scholar 

  • Daniela SC, Dybå T (2011) Research synthesis in software engineering: A tertiary study. Inf Softw Technol 53(5):440–455

    Article  Google Scholar 

  • Cruzes DS, Dybå T, Runeson P, Höst M (2014) Case studies synthesis: A thematic, cross-case, and narrative synthesis worked example a thematic, cross-case, and narrative synthesis worked example. Empirical Software Engineering, Accepted for publication

  • Dahlander L, Magnusson M (2008) How do firms make use of open source communities? Long Range Plann 41(6):629–649

    Article  Google Scholar 

  • Dahlander L, Wallin MW (2006) A man on the inside: Unlocking communities as complementary assets. Res Policy 35(8):1243–1259

    Article  Google Scholar 

  • De Almeida Biolchini JC, Mian PG, Cruz Natali AC, Uchôa Conte T, Travassos GH (2007) Scientific research ontology to support systematic review in software engineering. Adv Eng Inf 21(2):133–151. Ontology of Systems and Software Engineering; Techniques to Support Collaborative Engineering Environments

    Article  Google Scholar 

  • Di Gangi PM, Wasko M (2009) Steal my idea organizational adoption of user innovations from a user innovation community: A case study of dell ideastorm. Decision Support Syst 48:303–312

    Article  Google Scholar 

  • Dittrich K, Duysters G (2007) Networking as a means to strategy change: The case of open innovation in mobile telephony. J Prod Innov Manag 24(6):510–521

    Article  Google Scholar 

  • Ebner W, Leimeister JM, Krcmar H (2009) Community engineering for innovations: the ideas competition as a method to nurture a virtual community for innovations. R&D Manag 39(4):342–56

    Article  Google Scholar 

  • Edison H, Ali NB, Torkar R (2013) Towards innovation measurement in the software industry. J Syst Softw 86(5):1390–1407

    Article  Google Scholar 

  • Enkel E, Gassmann O, Chesbrough H (2009) Open r&d and open innovation: exploring the phenomenon. R&D Manag 39(4):311–316

    Article  Google Scholar 

  • Oliver G (2006) Opening up the innovation process: towards an agenda. R&D Manag 36(3):223–228

    Article  Google Scholar 

  • Gassmann O, Enkel E (2004) Towards a theory of open innovation: three core process archetypes. In: R&D Management Conference (RADMA), Lisabon, Portugal, pp 1–18

  • Oliver G (2010) Ellen Enkel, and Henry Chesbrough. The future of open innovation. R&D Manag 40 (3):213–221

    Article  MathSciNet  Google Scholar 

  • Greenhalgh T, Peacock R (2005) Effectiveness and efficiency of search methods in systematic reviews of complex evidence: audit of primary sources. BMJ 331(7524):1064–1065

    Article  Google Scholar 

  • Grøtnes E (2009) Standardization as open innovation: two cases from the mobile industry. Inf Technol People 22(4):367–381

    Article  Google Scholar 

  • Harison E, Koski H (2010) Applying open innovation in business strategies: Evidence from finnish software firms. Res Policy 39(3):351–359

    Article  Google Scholar 

  • Henkel J (2006) Selective revealing in open innovation processes: The case of embedded linux. Res Policy 35(7):953–969

    Article  Google Scholar 

  • Henkel J (2008) Champions of revealing–the role of open source developers in commercial firms. Ind Corp Chang 18(3):435–471

    Article  Google Scholar 

  • Henkel J, Schöberl S, Alexy O (2013) The emergence of openness: How and why firms adopt selective revealing in open innovation. Research Policy

  • Höst M, Stol K-J, Orucevic-Alagic A (2014) Software Project Management in a Changing World. In: Ruhe G, Wohlin C (eds) Inner Source Project Management. Springer

  • Huizingh E K R E (2011) Open innovation: State of the art and future perspectives. Technovation 31(1):2–9

    Article  Google Scholar 

  • Husig S, Kohn S (2011) Open cai 2.0 - computer aided innovation in the era of open innovation and web 2.0. Comput Ind 62(4):407–413

    Article  Google Scholar 

  • Ivarsson M, Gorschek T (2011) A method for evaluating rigor and industrial relevance of technology evaluations. Empir Softw Eng 16(3):365–395

    Article  Google Scholar 

  • Jalali S, Wohlin C (2012) Systematic literature studies: database searches vs. backward snowballing. In: 2012 ACM-IEEE International Symposium on Empirical Software Engineering and Measurement, (ESEM 2012), pp 29–38

  • Jansen S, Brinkkemper S, Souer J, Luinenburg L (2012) Shades of gray: Opening up a software producing organization with the open software enterprise model. J Syst Softw 85(7):1495–1510

    Article  Google Scholar 

  • Jonsson A, Svingby G (2007) The use of scoring rubrics: Reliability, validity and educational consequences. Educ Res Rev 2(2):130–144

    Article  Google Scholar 

  • Kitchenham B, Brereton P, Budgen D (2012) Mapping study completeness and reliability - a case study. In: Proceedings of the 16th International Conference on Evaluation & Assessment in Software Engineering (EASE 2012), pp 126–135

  • Kitchenham BA, Budgen D, Pearl Brereton O (2011) Using mapping studies as the basis for further research - a participant-observer case study. Inf Softw Technol 53(6):638–651

    Article  Google Scholar 

  • Kundel HL, Polansky M (2003) Measurement of observer agreement. Radiology 228(2):303

    Article  Google Scholar 

  • Laine MOJ (2012) Using knowledge from end-users online for innovations: Effects of software firm types. In: Lecture Notes in Business Information Processing, volume 114 LNBIP, MA, US, pp 70–78

  • Morgan L, Feller J, Finnegan P (2011) Exploring inner source as a form of intra-organisational open innovation. In: 19th European Conference on Information Systems, Helsinki, Finland

  • Morgan L, Finnegan P (2010) Open innovation in secondary software firms: An exploration of managers perceptions of open source software. Data Base Adv Inf Syst 41(1):76–95

    Article  Google Scholar 

  • Moskal B, Miller K, King LA (2002) Grading essays in computer ethics: rubrics considered helpful. ACM SIGCSE Bull 34(1):101–105

    Article  Google Scholar 

  • Mowery DC (2009) Plus ca change: Industrial R&D in the third industrial revolution. Indus Corp Chang 18(1):1–50

    Article  Google Scholar 

  • Parida V, Westerberg M, Frishammar J (2011) Effect of open innovation practices on smes innovative performance: An empirical study. In: Annual ICSB World Conference, Stockholm, Sweden

  • Petersen K, Ali NB (2011) Identifying strategies for study selection in systematic reviews and maps. In: Proceedings of the 5th International Symposium on Empirical Software Engineering and Measurement, ESEM 2011, Banff, AB, Canada, September 22-23, vol 2011, pp 351–354

  • Petersen K, Feldt R, Mujtaba S, Mattsson M (2008) Systematic mapping studies in software engineering. In: 12th International Conference on Evaluation and Assessment in Software Engineering, vol 17, p 1

  • Rayna T, Striukova L (2010) Large-scale open innovation: open source vs. patent pools. International Journal of Technology Management 52(3-4):477–496

    Article  Google Scholar 

  • Rohrbeck R, Hölzle K, Gemünden HG (2009) Opening up for competitive advantage - how deutsche telekom creates an open innovation ecosystem. R&D Manag 39(4):420–430

    Article  Google Scholar 

  • Runeson P, Höst M, Rainer A, Regnell B (2012) Case Study Research in Software Engineering - Guidelines and Examples. Wiley

  • Runeson P, Skoglund M (2009) Reference-based search strategies in systematic reviews. In: Proceedings 13th International Conference on Empirical Assessment & Evaluation in Software Engineering (EASE). British Computer Society. Durham University, UK

  • Singer L, Seyff N, Fricker SA (2011) Online social networks as a catalyst for software and IT innovation. In: SSE’11, September 5 - Proceedings of the 4th International Workshop on Social Software Engineering, pp 1–5

  • Sjøberg D I K, Dybå T, Jørgensen M (2007) The future of empirical methods in software engineering research. In: Workshop on the Future of Software Engineering (FOSE 2007), pp 358–378

  • Sjøberg D I K, Hannay J E, Hansen O, Kampenes V B, Karahasanovic A, Liborg N-K, Rekdal A C (2005) A survey of controlled experiments in software engineering. IEEE Trans Softw Eng 31(9):733–753

    Article  Google Scholar 

  • Stam W (2009) When does community participation enhance the performance of open source software companies? Res Policy 38(8):1288–1299

    Article  Google Scholar 

  • Stuermer M, Spaeth S, Krogh GV (2009) Extending private-collective innovation: a case study. R&D Manag 39(2):170–191

    Article  Google Scholar 

  • Der Meer HV (2007) Open innovation? the dutch treat: Challenges in thinking in business models. Creat Innov Manag 16(2):192–202

    Article  Google Scholar 

  • Krogh GV, Spaeth S (2007) The open source software phenomenon: characteristics that promote research. J Strat Inf Syst 16(3):236–253

    Article  Google Scholar 

  • Krogh GV, Spaeth S, Lakhani KR (2003) Community, joining, and specialization in open source software innovation: A case study. Res Policy 32(7):1217–1241

    Article  Google Scholar 

  • Wang Y, Tong R, Yao S (2009) An empirical study on external influencing factors of user innovation performance. In: Management and Service Science, 2009. MASS ’09. International Conference on, pp 1–4

  • West J (2003) How open is open enough?: Melding proprietary and open source platform strategies. Res Policy 32(7):1259–1285

    Article  Google Scholar 

  • West J, Bogers M (2013) Leveraging external sources of innovation: A review of research on open innovation. Journal of Product Innovation Management

  • West J, Gallagher S (2006) Challenges of open innovation: the paradox of firm investment in open-source software. R&D Manag 36(3):319–331

    Article  Google Scholar 

  • West J, Wood D (2008) Creating and evolving an open innovation ecosystem: Lessons from symbian ltd. Available at SSRN 1532926

  • Wieringa R, Maiden N, Mead N, Rolland C (2006) Requirements engineering paper classification and evaluation criteria: a proposal and a discussion. Requir Eng 11 (1):102–107

    Article  Google Scholar 

  • Wnuk K, Pfahl D, Callele D, Karlsson EA (2012) How can open source software development help requirements management gain the potential of open innovation: an exploratory study. In: Proceedings of the ACM-IEEE international symposium on Empirical software engineering and measurement, NJ, USA, pp 271–279

  • Wnuk K, Runeson P (2013) Engineering open innovation–towards a framework for fostering open innovation. In: Herzwurm G, Margaria T (eds) Software Business. From Physical Products to Software Services and Solutions, volume 150 of Lecture Notes in Business Information Processing. Springer, pp 48–59

  • Wohlin C, Prikladnicki R (2013) Systematic literature reviews in software engineering. Inf & Softw Technol 55(6):919–920

    Article  Google Scholar 

  • Zelkowitz MV, Wallace DR, Binkley D (1998) Culture conflicts in software engineering technology transfer. In: NASA Goddard Softw Eng Workshop, p 52

Download references

Acknowledgments

This work is funded by the Swedish National Science Foundation Framework Grant for Strategic Research in Information and Communication Technology, project Synergies (Synthesis of a Software Engineering Framework for Open Innovation through Empirical Research), grant 621-2012-5354.

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Authors and Affiliations

  1. Department of Computer Science, Lund University, Lund, Sweden

    Hussan Munir, Krzysztof Wnuk & Per Runeson

Authors
  1. Hussan Munir
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  2. Krzysztof Wnuk
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  3. Per Runeson
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Corresponding author

Correspondence to Hussan Munir.

Additional information

Communicated by: Natalia Juristo

Appendices

Appendix A: Rigor and Relevance Criteria

1.1 A.1 Rigor

Context(C)

  1. 1.

    Strong description: The context is described to the extent where it becomes comparable to other settings (Ivarsson and Gorschek 2011). In particular, we emphasized subject type (graduate, undergraduate, professionals, researcher), development experience, development methodology, duration of the observation. If all these aforementioned factors are highlighted, then C is evaluated to 1.

  2. 2.

    Medium description: If any of the above mentioned factors is missing in the study, then C is evaluated to 0.5.

  3. 3.

    Weak description: If no description of context is provided in the study, then C is evaluated to 0.

Design (D)

  1. 1.

    Strong description: The research design is described to the extent where it becomes transparent and detailed enough for the reader to understand the design (Ivarsson and Gorschek 2011). To be specific, if the study underlined the outcome variables, measurement criteria, treatments, number of subjects , and sampling, then D is evaluated to 1.

  2. 2.

    Medium description: If a study is missing out on any of the factors related to design and data collection is missing (see above), then D evaluates to 0.5.

  3. 3.

    Weak description: If no design description is provided at all then, D is evaluated to 0.

Validity threats (V)

  1. 1.

    Strong description: If different types of validity (i.e. internal, external, conclusion and construct validity) are evaluated and reflected upon then, V is evaluated to 1.

  2. 2.

    Medium description: If a study only highlights the subset of the relevant threat categories then, V is evaluated to 0.5

  3. 3.

    Weak description: If a study is missing out on validity discussion completely, then V is evaluated to 0.

1.2 A.2 Relevance

Users/Subjects (U)

  1. 1.

    Contribute to relevance: If the subjects used in the study are from industry (professionals) then, U is evaluated to 1 for industry.

  2. 2.

    Partially contribute to relevance: The subjects are partially representative, i.e. they are master(Msc.) or graduated students then, U is evaluated to 0.5

  3. 3.

    Does not contribute to relevance: If the subjects are bachelor/undergrad students or the information is missing then, U is evaluated to 0

Scale (S)

  1. 1.

    Contribute to relevance: If an industrial size application is used in the study then, S is evaluated to 1.

  2. 2.

    Does not contribute to relevance: The application is down-scaled or a toy example hence, S is evaluated to 0.

Research Methodology (RM)

  1. 1.

    Contribute to relevance: The chosen research methodology is suitable to scrutinize real world contexts and situations with relevance for practitioners (action research, case study, industry interviews, experiment investigating a real situation, and surveys/interviews). If study belongs to any of the aforementioned research methodologies then, RM is evaluated to 1

  2. 2.

    Does not contribute to relevance: If a Study is using Lab experiment (human subjects/software) or missing information then, RM is evaluated to 0.

Context (C)

  1. 1.

    Contribute to relevance: If a study is executed in a setting that matches real industrial usage (industrial setting) then, C is evaluated to 1.

  2. 2.

    Does not contribute to relevance: If a study is investigated under under artificial setting (e.g. lab) or others that do not represent a context matching real world situations, or not reported then, C is evaluated to 0.

Appendix B: Database Search Strings

Search string used for the Compendex and Inspect database (years 1969 to 2013)

(((((Open Innovation WN KY OR Open-Innovation OR OI WN KY OR innovation WN KY OR innovation management WN KY) AND (software WN KY OR software ecosystem WN KY OR product line WN KY OR requirement* engineer* WN KY OR requirement* management WN KY OR open source WN KY) AND (exploratory study WN KY OR lesson* learn* WN KY OR challenge* WN KY OR guideline* WN KY OR Empirical investigation WN KY OR case study WN KY OR survey WN KY OR literature study WN KY OR literature review WN KY OR interview* WN KY OR experiment* WN KY OR questionnaire WN KY OR observation* WN KY OR quantitative study WN KY OR factor* WN KY) AND (ENGLISH) WN LA))))

Search string used for the ACM Digital Library database (years 1969 to 2013)

(((((((((((((((((((“Title”:“Open Innovation” OR “Title”:“Open-innovation” OR “Title”:OI OR “Title”:innovation OR “Title”:innovation management) AND (“Abstract”: software OR “Abstract”: software ecosystem OR “Abstract”: requirement* engineer* OR “Abstract”: open source OR “Abstract”: product line) AND (“Abstract”:exploratory study OR “Abstract”: challenge* OR “Abstract”: guideline* OR “Abstract”: Empirical investigation OR “Abstract”: case study OR “Abstract”: survey OR “Abstract”: literature study OR “Abstract”: literature review OR “Abstract”: interview* OR “Abstract”: experiment* OR “Abstract”: questionnaire OR “Abstract”:observation* OR “Abstract”:quantitative study OR “Abstract”:factor*)) ))) and (FtFlag:yes))) and (FtFlag:yes)) and (PublishedAs:journal OR PublishedAs:proceeding OR PublishedAs:transaction) and (FtFlag:yes)))) and (PublishedAs:journal OR PublishedAs:proceeding OR PublishedAs:transaction) and (FtFlag:yes)))))))))

Search string used for the IEEE Explore database (years 1969 to 2013)

(((“Index Terms”:“Open Innovation” OR “Index Terms”: “Open-Innovation” OR “Index Terms”:OI OR “Index Terms”: innovation management OR “Index Terms”: innovation) AND (Search_Index_Terms: software OR “Index Terms”: ecosystem OR “Index Terms”: product line OR “Index Terms”:requirement* engineer* OR “Index Terms”: requirement* management* OR “Index Terms”: open source) AND (p_Abstract:case study OR “Abstract”: exploratory study OR “Abstract”: lessons learn* OR “Abstract”: survey OR “Abstract”: Empirical investigation OR “Abstract”: guidelines “Abstract”: literature study OR “Abstract”: interview OR “Abstract”: experiment OR “Abstract”: factors OR “Abstract”: questionnaire)))

Search string used for the ISI Web of Science database (years 1969 to 2013)

(((TI=(“Open Innovation” OR “Open-Innovation” OR OI OR innovation OR innovation management) AND TS=(software OR software ecosystem OR product line OR requirement* engineer* OR requirement* management OR open source) AND TS=(exploratory study OR lesson* learn* OR challenge* OR guideline* OR Empirical investigation OR case study OR survey OR literature study OR literature review OR interview* OR experiment* OR questionnaire OR observation* OR quantitative study OR factor*)))) AND Language=(English) Refined by: Web of Science Categories=(COMPUTER SCIENCE INFORMATION SYSTEMS) Timespan=1969-2013. Databases=SCI-EXPANDED, SSCI, A&HCI, CPCI-S, CPCI-SSH

Search string used for the Science Direct database (years 1969 to 2013)

(open innovation OR open-innovation OR OI OR innovation OR innovation management) AND (software OR software ecosystem OR product line OR requirement* engineer* OR requirement* management OR open source) AND (exploratory study OR lesson* learn* OR challenge* OR guideline* OR Empirical investigation OR case study OR literature study OR literature review OR interview* OR experiment* OR case study OR questionnaire OR observation* OR quantitative study OR factor*)[All Sources(Computer Science)]

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Munir, H., Wnuk, K. & Runeson, P. Open innovation in software engineering: a systematic mapping study. Empir Software Eng 21, 684–723 (2016). https://doi.org/10.1007/s10664-015-9380-x

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