Main article

Aulia Pratiwi Hasanah
Department of Management, Universitas Brawijaya, Malang, East Java 65145, Indonesia
Bagus Wijaya Kusuma
Department of Economics, Universitas Diponegoro, Semarang, Central Java 50275, Indonesia
Citra Dewi Lestari*
Department of Business and Information Systems, Universitas Hasanuddin, Makassar, South Sulawesi 90245, Indonesia
citra.lestari@unhas.ac.id

DOI: https://doi.org/10.63646/jbda.2023.010203

Abstract

Urban green technological innovation (GTI) is widely recognized as a strategic outcome that supports the simultaneous pursuit of decarbonization and high-quality economic growth. Existing empirical work has dissected the marginal effects of individual drivers — environmental regulation, green finance, FinTech, human capital, urbanization — but has rarely treated GTI as the joint product of several interacting conditions. This paper applies a configurational business-data-analytics design to the urban GTI problem. Drawing on panel-style observations from 283 prefecture-level cities matched with a two-year outcome lag, we combine Necessary Condition Analysis (NCA) with fuzzy-set Qualitative Comparative Analysis (fsQCA) under a unified Technology-Finance-Government-Talent-Structure framework comprising seven antecedents and one outcome. The NCA shows that no single antecedent acts as a strict prerequisite, but FinTech, economic development, and urbanization display medium-to-strong necessity bottlenecks that rise sharply at the mid-to-high GTI range. The fsQCA returns two equifinal sufficient configurations for high GTI — a Technology-Structure dual-driven pattern and a broader Technology-Finance-Talent-Structure synergistic pattern — both of which contain FinTech and economic development as core conditions. The configurations producing non-high GTI are markedly more heterogeneous, falling into four archetypes: regional-foundation deficit, compounded multi-factor deficit, industrial-structure–FinTech mismatch, and environmental-regulation–FinTech mismatch. The asymmetry between the success and failure pathways supports a configurational, rather than linear, view of urban green innovation. We discuss implications for business data analytics curricula, for cross-functional policy design, and for emerging-economy city governments that need to combine industrial modernization with credible decarbonization commitments.

Article details

How to Cite

Hasanah, A. P., Kusuma, B. W., & Lestari, C. D. . (2023). Business Data Analytics for Urban Green Innovation: Identifying Multi-Condition Pathways with NCA and fsQCA. Journal of Business and Data Analytics, 1(2), 45-65. https://doi.org/10.63646/jbda.2023.010203