Abstract
The literature shows that the failure rate of startups is around 90%. Therefore, it is crucial for investors and financial advisors to be able to spot the 10% which eventually will generate higher return rates and bring in greater revenues. The absence of a general conceptual framework which could assist large corporations and investors in the selection and evaluation of startups is quite visible in the literature. In this research, critical success factors for strategic alliance making between startups and large sized companies are identified and possible selection methods are discussed. Second, based on our findings a conceptual framework is presented for the selection of successful startups. Semi-structured interviews are conducted at a large scale financial tech company to evaluate our proposed framework. The results of our expert interviews indicate that all the managers who were involved in the selection process of startups agree on the fact that the team experience and the startup’s position within its network are highly related to the success of the startup in the future. Furthermore, characteristics of the lead entrepreneur, competitive advantage of the firm’s products and the valuable resources the startup has are also ranked among the criteria which managers look into and have strong influence on their decision making.
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References
Barney, J.: Firm resources and sustained competitive advantage. J. Manage. 17(1), 99–120 (1991)
Baum, J.A., Silverman, B.S.: Picking winners or building them? Alliance, intellectual, and human capital as selection criteria in venture financing and performance of biotechnology startups. J. Bus. Ventur. 19(3), 411–436 (2004)
Baxter, P., Jack, S.: Qualitative case study methodology: study design and implementation for novice researchers. e Qual. Rep. 13(4), 544–559 (2008). http://nsuworks.nova.edu/tqr/vol13/iss4/2
Brouthers, K.D., Brouthers, L.E., Wilkinson, T.J.: Strategic alliances: choose your partners. Long Range Plann. 28(3), 2–25 (1995)
Chang, S.J.: Venture capital financing, strategic alliances, and the initial public offerings of Internet startups. J. Bus. Ventur. 19(5), 721–741 (2004)
Csaszar, F., Nussbaum, M., Sepulveda, M.: Strategic and cognitive criteria for the selection of startups. Technovation 26(2), 151–161 (2006)
Comi, A., Eppler, M.J.: Building and managing strategic alliances in technology-driven start-ups. Università della Svizzera italiana (2009)
Das, T., Teng, B.: A resource-based theory of strategic alliances. J. Manage. 26(1), 31–61 (2000)
Duchesneau, D.A., Gartner, W.B.: A profile of new venture success and failure in an emerging industry. J. Bus. Ventur. 5(5), 297–312 (1990)
Galloway, S.: The Four: The Hidden DNA of Amazon, Apple, Facebook, and Google. Bantam Press, London (2017)
Gulati, R.: Social structure and alliance formation patterns: a longitudinal analysis. Adm. Sci. Q. 40(4), 619 (1995)
Gulati, R.: Network location and learning: the influence of network resources and firm capabilities on alliance formation. Strateg. Manage. J. 20(5), 397–420 (1999)
Gelderen, M.V., Thurik, R., Bosma, N.: Success and risk factors in the pre-startup phase. Small Bus. Econ. 24(4), 365–380 (2005)
Hoffmann, W.H., Schlosser, R.: Success factors of strategic alliances in small and medium sized enterprises- an empirical survey. Long Range Plann. 34(3), 357–381 (2001)
Kinyenje, M.: Factors That Influence Success of Strategic Alliances Between Mobile Service Providers and Commercial Banks in the Money Transfer Services. University of Nairobi (2016)
Kioko Muthoka, R., Kilika, J.: Towards a theoretical model for strategic alliance, and partner selection among small medium enterprises (SMES): a research agenda. Sci. J. Bus. Manage. 4(1), 1 (2016)
Krishna, A., Agrawal, A., Choudhary, A.: Predicting the outcome of startups: less failure, more success. In: 2016 IEEE 16th International Conference on Data Mining Workshops (ICDMW) (2016)
Koohborfardhaghighi, S., Altmann, J.: A network formation model for social object networks. In: Zhang, Z., Shen, Z.M., Zhang, J., Zhang, R. (eds.) LISS 2014, pp. 615–625. Springer, Heidelberg (2015). https://doi.org/10.1007/978-3-662-43871-8_89
Koohborfardhaghighi, S., Altmann, J.: How strategic networking impacts the networking outcome: a complex adaptive system approach. In: Proceedings of the 18th Annual International Conference on Electronic Commerce: e-Commerce in Smart connected World, p. 30. ACM (2016)
Koohborfardhaghighi, S., Lee, D.B., Kim, J.: How different connectivity patterns of individuals within an organization can speed up organizational learning. Multimedia Tools Appl. 76(17), 17923–17936 (2017)
Schmidt, S.M., Kochan, T.A.: Interorganizational relationships: patterns and motivations. Adm. Sci. Q. 22(2), 220 (1977). https://doi.org/10.2307/2391957
Zinecker, M., Bolf, D.: Venture capitalists’ investment selection criteria in CEE countries and Russia. Verslas: Teorija ir Praktika 16(1), 94–103 (2015)
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Erdogan, E., Koohborfardhaghighi, S. (2019). Delivering a Systematic Framework for the Selection and Evaluation of Startups. In: Coppola, M., Carlini, E., D’Agostino, D., Altmann, J., Bañares, J. (eds) Economics of Grids, Clouds, Systems, and Services. GECON 2018. Lecture Notes in Computer Science(), vol 11113. Springer, Cham. https://doi.org/10.1007/978-3-030-13342-9_13
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