Managing robust development process for high-tech startups through multi-project learning: The case of two European start-ups

Midler, Christophe; Silberzahn, Philippe

doi:10.1016/j.ijproman.2008.05.003

Cited by 42 publications

(34 citation statements)

References 12 publications

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“…To accommodate flexibility of managerial and organizational practices, the empowerment of team members represents the main viable strategy to enhance performance and chances of success [19,78]. The team needs to be able to absorb and learn from trial and error quickly enough to adapt to new emergent practices [74,3,78].…”

Section: Managerial and Organizational Practicesmentioning

confidence: 99%

Software development in startup companies: A systematic mapping study

Paternoster

Giardino

Unterkalmsteiner

et al. 2014

Information and Software Technology

304

350

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Context: Software startups are newly created companies with no operating history and fast in producing cutting-edge technologies. These companies develop software under highly uncertain conditions, tackling fast-growing markets under severe lack of resources. Therefore, software startups present an unique combination of characteristics which pose several challenges to software development activities. Objective: This study aims to structure and analyze the literature on software development in startup companies, determining thereby the potential for technology transfer and identifying software development work practices reported by practitioners and researchers. Method: We conducted a systematic mapping study, developing a classification schema, ranking the selected primary studies according their rigor and relevance, and analyzing reported software development work practices in startups. Results: A total of 43 primary studies were identified and mapped, synthesizing the available evidence on software development in startups. Only 16 studies are entirely dedicated to software development in startups, of which 10 result in a weak contribution (advice and implications (6); lesson learned (3); tool (1)). Nineteen studies focus on managerial and organizational factors. Moreover, only 9 studies exhibit high scientific rigor and relevance. From the reviewed primary studies, 213 software engineering work practices were extracted, categorized and analyzed. Conclusion: This mapping study provides the first systematic exploration of the state-of-art on software startup research. The existing body of knowledge is limited to a few high quality studies. Furthermore, the results indicate that software engineering work practices are chosen opportunistically, adapted and configured to provide value under the constrains imposed by the startup context.

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Section: Managerial and Organizational Practicesmentioning

confidence: 99%

Software development in startup companies: A systematic mapping study

Paternoster

Giardino

Unterkalmsteiner

et al. 2014

Information and Software Technology

304

350

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“…Midler and Silberzahn (2008) [46] develop a project-learning-based system to manage knowledge in startups. Specifically, this system allows startups to integrate three different bodies of knowledge: project management, organizational learning and entrepreneurship.…”

Section: Area 2 Knowledge Management Systems Adopted By Startupsmentioning

confidence: 99%

Knowledge Management in Startups: Systematic Literature Review and Future Research Agenda

2017

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This paper conducts a systematic literature review on knowledge management (KM) in the context of startups in order to analyze the state of the art, identify research gaps and define a future research agenda. The main findings highlight that, even though there is an increasing number of papers on the topic of KM in startups, several issues are still neglected. Specifically, the paper identifies four main gaps in the body of literature. The first gap deals with the environmental and socio-political factors influencing the adoption of KM in startups. The second gap regards the lack of a comprehensive taxonomy of knowledge management systems (KMSs) that may support the processes of knowledge creation, acquisition, storage, transfer, sharing and application. This second gap allows us to identify a third gap concerning the level of alignment between startup's strategies and technologies adopted. Finally, the fourth gap deals with the issue of the impact of KM on startup's performances with regard to economic, financial, market, technical, technological, organizational, human and relational performance. From these four gaps, six research questions (RQs) have been proposed. These RQs allow us to identify possible areas of analysis to define a future research agenda. Neglecting these issues means underestimating all the possible advantages of KM adoption for a startup to achieve efficiency, effectiveness and scalability goals.

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“…Startups face uncertain conditions, leading to a fast learning from trial and error, with a strong customer relationship, and avoiding wasting time in building unneeded functionality and preventing exhaustion of resources [48], [49], [6]. Customer involvement in software development has also been discussed by Yogendra [50] as an important factor to encourage an early alignment of business concerns to technology strategies.…”

Section: Software Development In Startupsmentioning

confidence: 99%

Software Development in Startup Companies: The Greenfield Startup Model

Giardino

Paternoster

Unterkalmsteiner

et al. 2016

IIEEE Trans. Software Eng.

130

122

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PostprintThis is the accepted version of a paper published in IEEE Transactions on Software Engineering. This paper has been peer-reviewed but does not include the final publisher proof-corrections or journal pagination.Citation for the original published paper (version of record):Giardino, C., Paternoster, N., Unterkalmsteiner, M., Gorschek, T., Abrahamsson, P. The Greenfield Startup Model Carmine Giardino, Nicolò Paternoster, Michael Unterkalmsteiner, Member, IEEE, Tony Gorschek, Member, IEEE, and Pekka Abrahamsson, Member, IEEE Abstract-Software startups are newly created companies with no operating history and oriented towards producing cutting-edge products. However, despite the increasing importance of startups in the economy, few scientific studies attempt to address software engineering issues, especially for early-stage startups. If anything, startups need engineering practices of the same level or better than those of larger companies, as their time and resources are more scarce, and one failed project can put them out of business. In this study we aim to improve understanding of the software development strategies employed by startups. We performed this stateof-practice investigation using a grounded theory approach. We packaged the results in the Greenfield Startup Model (GSM), which explains the priority of startups to release the product as quickly as possible. This strategy allows startups to verify product and market fit, and to adjust the product trajectory according to early collected user feedback. The need to shorten time-to-market, by speeding up the development through low-precision engineering activities, is counterbalanced by the need to restructure the product before targeting further growth. The resulting implications of the GSM outline challenges and gaps, pointing out opportunities for future research to develop and validate engineering practices in the startup context.

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Managing robust development process for high-tech startups through multi-project learning: The case of two European start-ups

Cited by 42 publications

References 12 publications

Software development in startup companies: A systematic mapping study

Software development in startup companies: A systematic mapping study

Knowledge Management in Startups: Systematic Literature Review and Future Research Agenda

Software Development in Startup Companies: The Greenfield Startup Model

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