Impact of Pricing Analytics Capability on Competitive Pricing Effectiveness Among Third-Party Sellers of Consumer Electronics on Amazon and Flipkart in India

Abstract

The explosive growth of Indian e-commerce has created an intensely algorithmic competitive environment in which pricing is the primary determinant of marketplace visibility and sales conversion. This study empirically examines the impact of Pricing Analytics Capability (PAC) — operationalised across three dimensions: technology infrastructure (PAC-TECH), human analytical skill (PAC-HUMAN), and management process (PAC-MGMT) — on Competitive Pricing Effectiveness (CPE) among third-party sellers on major Indian e-commerce platforms. Anchored in Dynamic Capabilities Theory (Teece et al., 1997), the Resource-Based View (Barney, 1991), and the Technology Acceptance Model (Davis, 1989), a quantitative cross-sectional survey yielded N = 121 valid responses from active sellers across nine product categories and seven platforms. Statistical analyses including descriptive statistics, Pearson correlation, simple and multiple OLS regression were conducted using SPSS. Results reveal that PAC significantly and positively predicts CPE (β = 0.550, R² = 0.404, p < .001). At the sub-dimension level, PAC-HUMAN emerges as the strongest driver (β = 0.393, p < .001), followed by PAC-TECH (β = 0.184, p = .050), while PAC-MGMT does not achieve independent significance when controlling for the other dimensions. The findings provide the first empirically validated evidence of the PAC-CPE relationship in the Indian marketplace context, extending the BDAC framework to individual MSME seller pricing behaviour.

Keywords: pricing analytics capability, competitive pricing effectiveness, Indian e-commerce, dynamic capabilities, third-party sellers, MSME, Buy Box