TY - JOUR
T1 - Dynamic pricing for perishable goods: a data-driven digital transformation approach
AU - Syed, Tahir Abbas
AU - Aslam, Harris
AU - Bhatti, Zeeshan Ahmed
AU - Mehmood, Fahad
AU - Pahuja, Aseem
N1 - 18 month embargo - Elsevier - may be Gold OA via agreement
PY - 2024/9/9
Y1 - 2024/9/9
N2 - In supermarkets, rapid pricing adjustments are crucial due to the short shelf life of products. Adopting a multi-case study approach, this study examines the application of dynamic pricing strategies for perishable goods through the lens of a data-driven digital transformation (DD-DT) approach. We introduce a three-phase model of DD-DT for dynamic pricing: initiation, facilitation, and strategic adaptation. In the initiation phase, we identify essential frameworks for robust data collection and analytical processes, which form the backbone of informed pricing decisions. During the facilitation phase, the study integrates sophisticated algorithms and real-time analytics to process and interpret the collected data, facilitating its seamless integration into pricing strategies. The strategic adaptation phase is critical as it focuses on the ongoing refinement and enhancement of pricing strategies, enabling supermarkets to adapt swiftly to market fluctuations and consumer behaviour changes. By presenting a comprehensive DD-DT framework, this research significantly augments the existing literature on dynamic pricing and offers actionable insights for practitioners seeking to optimize pricing strategies in a digitally transforming marketplace.
AB - In supermarkets, rapid pricing adjustments are crucial due to the short shelf life of products. Adopting a multi-case study approach, this study examines the application of dynamic pricing strategies for perishable goods through the lens of a data-driven digital transformation (DD-DT) approach. We introduce a three-phase model of DD-DT for dynamic pricing: initiation, facilitation, and strategic adaptation. In the initiation phase, we identify essential frameworks for robust data collection and analytical processes, which form the backbone of informed pricing decisions. During the facilitation phase, the study integrates sophisticated algorithms and real-time analytics to process and interpret the collected data, facilitating its seamless integration into pricing strategies. The strategic adaptation phase is critical as it focuses on the ongoing refinement and enhancement of pricing strategies, enabling supermarkets to adapt swiftly to market fluctuations and consumer behaviour changes. By presenting a comprehensive DD-DT framework, this research significantly augments the existing literature on dynamic pricing and offers actionable insights for practitioners seeking to optimize pricing strategies in a digitally transforming marketplace.
KW - Data-driven digital transformation
KW - dynamic pricing
KW - perishable food
KW - supermarkets
M3 - Article
SN - 0925-5273
JO - International Journal of Production Economics
JF - International Journal of Production Economics
ER -