Public defence with Nima Yahyapour

Nima Yahyapour defends his thesis “Data-centric Business Model Innovation. Evidence from Eastern European and Baltic Region Enterprises”.

Doctoral thesis: “Data-centric Business Model Innovation. Evidence from Eastern European and Baltic Region Enterprises External link, opens in new window.”
Subject: Business Studies
Research area: Politics, Economy and the Organisation of Society
Research school: The Baltic and East European Graduate School (BEEGS)
External reviewer: Cecilia Lindh, docent in business administration, Mälardalen University
Language: English

Abstract

This dissertation examines how data can move from being an operational resource to becoming a strategic and ecosystem-level enabler of business model innovation, creating opportunities for firm growth. Drawing on four interrelated studies and a cumulative multi-method research design, the dissertation develops an integrative data-centric framework that links digital readiness achieved through digital transformation, data strategy, and intra- and interorganizational business model innovation. The framework is dynamic, incorporating feedback loops that enable continuous interaction between business model innovation, digital readiness, and data strategy.

The findings show that data-centric business model innovation depends not only on technological adoption but also on organizational readiness, leadership capabilities, cultural change, and skill shifts as enabling mechanisms of data strategy. The dissertation argues that data strategy acts as a central bridge between digital readiness and business model innovation by defining how data is collected, integrated, modeled, governed, shared, and used for value creation and value capture.

With evidence from Article 5 and additional publicly available datasets, the dissertation further contextualizes some of these dynamics through a descriptive comparative analysis of digital readiness conditions in selected Eastern European and Baltic region economies. The results suggest that while larger economies tend to have greater ICT scale, digital sophistication, particularly cloud and AI adoption, should be understood as a qualitative capability dimension rather than simply a function of economic size. The regional analysis therefore provides contextual support for the framework, while not claiming causal evidence between country-level digital readiness factors and firm-level growth outcomes.

Overall, the dissertation contributes to business model innovation and ecosystem research by positioning data as a strategic resource, a mechanism for coordination, and an enabler of value creation at both the firm and ecosystem levels.

It also offers practical implications for managers, emphasizing the need to align digital transformation with clear data strategies while strengthening elements such as organizational digital capabilities, ecosystem alignment, digital infrastructure, human capital, and responsible data sharing practices.

For policymakers and decision-makers, it also highlights the importance of supporting digital infrastructure, human capital development, regulatory clarity, and facilitating data-sharing conditions.

The dissertation acknowledges that the proposed framework is a conceptual synthesis rather than a universal prescription and calls for future research across longer time horizons, broader geographical contexts, and more diverse industrial settings. Additionally, the country-level comparative analysis is constrained by limited temporal scope and available data coverage, which restricts the depth of insights.