The Impact of Self‐Checkout Technology on Shopping Behavior in B2B Retail: Evidence From Point‐Of‐Sale Transaction Data
Jindřich Špička & Michaela Dvořáková
Abstract
This study examines the impact of self‐checkout technology implementation on B2B customer shopping behavior using a novel methodological approach that combines propensity score matching with difference‐in‐differences analysis on actual point‐of‐sale transaction data. Drawing on transaction cost economics and service marketing research, we developed four hypotheses to examine how self‐checkout adoption influences purchase quantity, shopping frequency, average price per item, and total sales among B2B customers in a Czech retail chain. Our methodological contribution lies in employing actual transaction data rather than self‐reported measures, addressing a critical gap in retail technology research. The propensity score matching‐based difference‐in‐differences design enables causal inference, controlling for selection bias and unobserved heterogeneity. Data spanning January 2021 (pre‐implementation) and June–August 2021 (post‐implementation) encompass over 1500 matched customer pairs across multiple behavioral dimensions. Results reveal that implementing self‐checkout technology substantially increased shopping frequency and monthly sales per customer, with no significant impact on purchase quantities per transaction or average item prices. This asymmetric pattern provides empirical evidence for the disciplined nature of B2B purchasing behavior, in which organizational constraints limit technology's influence on transaction costs rather than purchasing decisions. We refer to this as a “frequency‐dominance effect,” in which transaction cost reductions primarily manifest through increased visit frequency rather than through altered transaction composition. The study advances service marketing research by empirically demonstrating that technology‐mediated convenience improvements disproportionately affect visit behavior over purchasing decisions. Our methodological framework provides a replicable template for evaluating retail technology interventions.
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.50 × 0.4 = 0.20 |
| M · momentum | 0.50 × 0.15 = 0.07 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.