A numerical optimization approach for pricing components in customer defined bundles in a B2B market

Raj, Ritwik; Karwan, Mark H.; Murray, Chase; Sun, Lei

doi:10.1016/j.cor.2023.106215

Cited by 1 publication

(1 citation statement)

References 32 publications

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“…Previous studies (Flores et al, 2019;Raj et al, 2023;Zhang et al, 2023) developed and formulated optimisation algorithms using simulated data. In this study, as a contribution, we EJMBE apply the same algorithm to empirical (field) data collected through a consumer survey.…”

Section: Introductionmentioning

confidence: 99%

Simultaneous consideration of consumer preferences and seller revenue as a smart retail sales and management strategy

Ahmadi Kaliji,

Mojaverian,

Amirnejad

et al. 2024

EJMBE

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PurposeThe authors propose a dairy bundle, integrating strategies to jointly maximise producer revenue and consumer utility according to the latter's preferences.Design/methodology/approachAn algorithm based on a nested logit model identifies the bundle maximising producer revenue based on factors affecting consumer purchase behaviour. The data are drawn from a mall-intercept survey administered in Iran, with consumers stating a hypothetical choice among a comprehensive set of dairy products.FindingsDemographic characteristics and marketing mix elements significantly affect consumers' preferences. An algorithm based on the estimated dissimilarity parameter determines the best bundle of dairy products, simultaneously obtaining the highest utility and the highest expected revenue.Originality/valueConsumer preference and maximum producer or retail seller income are considered simultaneously. The bundling promotion strategy is widely used for food offerings and fresh foods and can be extended to other products.

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Section: Introductionmentioning

confidence: 99%