Data-Driven Decision-Making in Digital Entrepreneurship
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 32870
Data-Driven Decision-Making in Digital Entrepreneurship

Authors: Abeba Nigussie Turi, Xiangming Samuel Li


Data-driven business models are more typical for established businesses than early-stage startups that strive to penetrate a market. This paper provided an extensive discussion on the principles of data analytics for early-stage digital entrepreneurial businesses. Here, we developed data-driven decision-making (DDDM) framework that applies to startups prone to multifaceted barriers in the form of poor data access, technical and financial constraints, to state some. The startup DDDM framework proposed in this paper is novel in its form encompassing startup data analytics enablers and metrics aligning with startups' business models ranging from customer-centric product development to servitization which is the future of modern digital entrepreneurship.

Keywords: Startup data analytics, data-driven decision-making, data acquisition, data generation, digital entrepreneurship.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 775


[1] Bean R. (2017) How Companies Say They’re Using Big Data in Harvard Business Review- Analytics And Data Science. Retrieved February 21, 2022, from
[2] Behl, A., Dutta, P., Lessmann, S., Dwivedi, Y. K., & Kar, S. (2019). A conceptual framework for the adoption of big data analytics by e-commerce startups: a case-based approach. Information Systems and e-Business Management, 17(2), 285-318.
[3] Berg, V., Birkeland, J., Pappas, I. O., & Jaccheri, L. (2018). The Role of Data Analytics in Startup Companies: Exploring Challenges and Barriers. In Conference on e-Business, e-Services and e-Society (pp. 205-216). Springer, Cham.
[4] Caulkins, J. P., Bao, Y., Davenport, S., Fahli, I., Guo, Y., Kinnard, K., ... & Kilmer, B. (2018). Big data on a big new market: Insights from Washington State's legal cannabis market. International Journal of Drug Policy, 57, 86-94.
[5] Giardino, C., Bajwa, S. S., Wang, X., & Abrahamsson, P. (2015, May). Key challenges in early-stage software startups. In International Conference on Agile Software Development (pp. 52-63). Springer, Cham.
[6] Hartmann, P. M., Zaki, M., Feldmann, N., & Neely, A. (2016). Capturing value from big data–a taxonomy of data-driven business models used by startup firms. International Journal of Operations & Production Management.
[7] Kandel, S., Paepcke, A., Hellerstein, J. M., & Heer, J. (2012). Enterprise data analysis and visualization: An interview study. IEEE Transactions on Visualization and Computer Graphics, 18(12), 2917-2926.
[8] Kemell, K. K., Wang, X., Nguyen-Duc, A., Grendus, J., Tuunanen, T., & Abrahamsson, P. (2020). Startup Metrics That Tech Entrepreneurs Need to Know. In Fundamentals of Software Startups (pp. 111-127). Springer, Cham.
[9] Li SX (2021), Short or Long Review? Text Analytics and Machine Learning Approaches to Online Reputation, International Journal of Business and Management Research (IJBMR), 9 (1), pp 28-40, e-ISSN: 2347-4696.
[10] McClure, D. (2007). Startup metrics for pirates: AARRR. Startup Metrics for Product Marketing & Product Management.
[11] NCES. (n.d.). Volume of data/information created, captured, copied, and consumed worldwide from 2010 to 2025(in zettabytes). In Statista - Telecommunications. Retrieved February 21, 2022, from
[12] Oliva, F. L., & Kotabe, M. (2019). Barriers, practices, methods and knowledge management tools in startups. Journal of knowledge management.
[13] Turi, A. N. Technologies for Modern Digital Entrepreneurship Understanding Emerging Tech at the Cutting-Edge of the Web 3.0 Economy.
[14] Mixpanel- service performance and efficiency available at, Retrieved Apri1 2, 2022