Relationship between SDG-Orientation and total funding amount of European digital sustainable startups: A twin transition perspective

Abstract

Organizational research and practice evaluated the concept of "performance" primarily in economic terms, and ignored the environmental and social costs for a long period. In this respect, the fully economic perspective is widely criticized within the social, environmental, and economic dimensions. Today, in parallel to the growing orientation towards sustainability, both scholars, practitioners, and policy makers also increasingly adopt to a more value-driven approach rather than the conventional understanding of organizational performance. In this respect, long-term competitiveness is even linked to the strategic orientation towards sustainability. In this respect, the concept of innovation which is identified as a driving force for sustainability is also defined as critical factor for disrupting the markets towards sustainability. On the other hand, as a carrier of innovation, the startups are also identified as potential actors to disrupt the markets through sustainability. Drawing on the two main agendas for sustainability, this thesis specifically focuses on the direct and indirect relationships among SDG-orientation and economic performance of the digital sustainable startups (DSS). In this respect, the twin transition agenda (TT) of the European Union (EU), assesses the DSSs as small sized and innovative businesses, which employ digital technologies in providing sustainability-oriented value propositions, which positions at the forefront of this shift due to their innovating capacity. Adopting to a TT perspective, which suggests the employment of DTs and greening of the economy as interconnected processes, our research aims the shad a light on the integration of the green and digital dimensions, in explaining the variations within the economic performance of the European sustainability-oriented digital startups. Second, aiming to illuminate the factors which influence the economic performance of digital sustainable startups (DSSs) in the European context, this research also adopts to the Sustainable Development Goals (SDGs) of the United Nations (UN). In this context, the SDGs provide a globally recognized framework, which also enables academically established proposed keywords and search queries to be operationalized within textual data. Aiming to identify the integration of the green and the digital dimensions in explaining variations in total funding amount (TFA) of the European DSSs, this thesis tests the influence of SDGs-orientation as a strategic direction through the specific SDGs which shapes the organization and, in turn, affects TFA of the entrepreneurial action. Methodologically, this research adopts to a formative measurement model, based on secondary cross-sectional data, which is retrieved from Crunchbase database , which is considered as a robust repository of startup data, which enables operationalization of an economic dependent variable within the thesis research. In this context, the use of the secondary data is also expected to enable wide range of samples from the digital entrepreneurial which orients towards sustainability. Considering the "outcomes" definition of Cohen (2008), 17 results are retrieved for "pre-money valuation" data, 42 results are obtained for "money raised" data. Further, 101 results are collected from Crunchbase database for total funding amount (TFA) data, which also validates the sample of the study (n = 101). On the other hand, the SDGs which provide a globally recognized framework, also provides academically established search queries for each SDG, also enables SDG-oriented research capabilities within textual data. Borrowing these standardized search queries ensure that the identification of the SDG-orientation remains objective and replicable within the sampled DSSs. In this respect, SDG-orientations of the European DSSs are analyzed by conducting the conceptual content analysis on the organizational texts, which is collected from organizational websites and organizational business profile pages on Crunchbase website. Further, DT and IT adoption of the European DSSs are analyzed employing the same organizational texts by conducting manual analysis. Both the SDG-orientation, and the DT and IT preferences of the European DSSs are first binary coded. Data is also collected from multiple sources to enable NUTS2-level regional-GDP (GDP) variable, that is an economic variable, which is also assumed to reflect the entrepreneurial ecosystems effect on startup's access to funding. Further, TFA and GDP data are log-transformed within the data preparation process, to normalize the skewed data and stabilize the variance. Moreover, factor-cluster analysis is conducted on DT preferences and IT adoption data. Consequently, DT and IT data are operationalized as clustered latent constructs, which reflect the underlying concepts rather than the direct measurement of the variables as factor scores. The data analysis is conducted using Partial Least Squares Equation Modeling (PLS-SEM) in SmartPLS software. Selection of the research method based upon the requirement for analysis capabilities within (1) simultaneous analysis capability on direct, mediating and moderating influences, (2) analysis on complex formative and reflective relationships (3) with relatively smaller sample sizes (Elshaer et al. 2023), (4) which is also identified as accurate within the investigation of early levels of theory development (Elshaer et al. 2023). In this respect, a bootstrapping analysis is operationalized, as a powerful and significant non-parametric method, which is employed to estimate the precision of the statistical results, while ensuring the robustness and stabilization of the findings. In this respect, this research adopts to 90% CI and bootstrapping procedure with 50.000 subsamples to ensure the robustness of the results, and follows the guidelines of Hair et al. (2019). Our results indicate a positive and significant direct influence of the SDG-orientation on TFA within the European DSSs within the main model of this study (Model 1). Consequently, despite the insignificant formative indicator weights and loadings, the H1 hypothesis of this research is supported at the construct-level, which reflects the positive effect of SDG on TFA. Further, the results also point that the effect of SDG on TFA is also observed to be contingent to higher GDP levels. Reflecting low to medium effect sizes, the main research model also explains weak potion of variance in TFA, which indicates a limited overall explanatory power, despite significant contribution of SDG at the construct-level (Hair et al. 2019). In this respect, Model 1 also represents a good level of fit. Within this thesis study, four models are tested, and Model 3 is observed to represent the strongest overall statistical performance. In this respect, at the indicator-level, SUINRC (Sustainable Industries and Responsible Consumption) which covers SDG9 (Industry, Innovation and Infrastructure) and SDG12 (Responsible Consumption and Production), and HAREC which covers SDG3 (Good Health and Well-being) and SDG11 (Sustainable Cities and Communities), while SUINRC slightly outperforms HAREC as indicator of SDG construct. Further, at the construct-level, the direct influence of SDG on TFA is, also outperforms the direct influence of GDP on TFA in Model 3, which is also significant, and results in the acceptance of H1 hypothesis within the main research model (Model 1), with medium effect sizes, the findings demonstrate weak explanatory power, but structural stability and good model fit. In this respect, this thesis research contributes to the literature by conducting an organizational-level empirical analysis on the economic performance of DSSs, which are politically, theoretically, and practically examined as critical actors within the sustainability context. Further, our analysis points to a positive and significant relationship between SDG-orientation and TFA within the European DSSs, despite the respectively small samples size. On the other hand, the small sample size also resulted in the model to generally represent a weak explanatory power. Considering digital sustainable entrepreneurship (DSE) as niche area of the research on entrepreneurship, and our considerable effort within the comparison of potential data sources, in our definition the collected Crunchbase data which represents the sample of our research, also represents the available population for the collectable data within the field of research, considering the day of data retrieval.