Product assortment and space allocation strategies to attract loyal and non-loyal customers

Timonina‐Farkas, Anna; Katsifou, Argyro; Seifert, Ralf W.

doi:10.1016/j.ejor.2020.02.019

Cited by 19 publications

(10 citation statements)

References 31 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The demand for the mass-produced product with characteristics can be written as , where is the maximal level of tolerance between the desired product and its closest available analog in . Thus, Note that the purchase happens if the individual customer’s utility is greater or equal to the price (see Timonina-Farkas, 2020 ) for an example with optimal purchase quantities). This goes in line with the well-known concept of customer’s surplus , which is greater than zero if the willingness-to-pay adjusted for the time and product misfit in our model (see Eq.…”

Section: Model Frameworkmentioning

confidence: 99%

Utilizing additive manufacturing and mass customization under capacity constraints

2022

Self Cite

View full text Add to dashboard Cite

Additive manufacturing (AM), originally used for prototyping, is increasingly adopted for custom final part production across different industries. However, printing speed and production volume are two barriers for the adoption of AM for product customization at large scale. Nevertheless, manufacturers could aim to combine the benefits of AM for product customization with traditional mass customization (MC) technologies over the product life cycle (PLC). This approach is showcased in our paper as a manufacturing opportunity and is addressed via a non convex-concave optimization model that considers a monopolist manufacturer producing horizontally differentiated products at scale. To satisfy individual customer preferences under capacity considerations, the firm jointly decides on the inventory, production quantity, product variety, optimal technology-switching times (between AM and MC) and pricing strategy. Our approach can be implemented by decision-makers to leverage customer-centricity and benefit from this novel hybrid manufacturing practice. By deriving a closed-form solution for the production quantity based on an adaptive inventory policy, the resulting optimization problem is solved using the Sample Average Approximation framework grounded by analytical results. Our results demonstrate that the new usage of AM with MC can benefit a manufacturer for customer-centric driven strategies. Significant profit improvements can be achieved with an AM–MC–AM technology-switching scenario under certain capacity conditions and with an increasing-decreasing pricing strategy. Our results also indicate that the benefits of pricing flexibility are highest when capacity is unlimited or when the firm does not hold inventory. Under capacity constraints, a simple decreasing pricing policy combined with inventory performs very well.

show abstract

Section: Model Frameworkmentioning

confidence: 99%

Utilizing additive manufacturing and mass customization under capacity constraints

2022

Self Cite

View full text Add to dashboard Cite

show abstract

“…If the demands are independent but not necessarily identically distributed, one can use independent convolution techniques to estimate their joint density. Furthermore, coupling methods can be employed to estimate the density of the sum of dependent random variables (Hochrainer‐Stigler et al., 2019; Timonina‐Farkas et al., 2020). Such methods should be used in the presence of seasonality issues or product life cycle patterns that imply that the independence condition should be relaxed.…”

Section: Mathematical Modelmentioning

confidence: 99%

“…From the retailer's perspective, the interdependence between demand and the optimal product assortment was studied in the work of Timonina‐Farkas et al. (2020). In our article, we develop a stochastic cost‐minimization problem with uncertain service‐level requirements extending the literature to the case where demand distributions depend on the realized disruption scenarios.…”

Section: Introduction and Literature Reviewmentioning

confidence: 99%

Limiting the impact of supply chain disruptions in the face of distributional uncertainty in demand

Timonina‐Farkas

Glogg

Seifert

2022

Production and Operations Management

Self Cite

View full text Add to dashboard Cite

Service‐level requirements play a crucial role in eliminating stock‐outs in a production pipeline. However, delivering a specific service level can become an unattainable goal given the various uncertainties influencing both the production pipeline and customer demand and causing the manufacturer to adapt the initial strategy in response to disruptions. Such deviations from optimality frequently result in unexpected (and potentially very high) costs and are complex to manage. On the one hand, the manufacturer can use a robust or distributionally robust approach to prepare for the worst‐case disruption, ensuring that the realized cost will be lower than the estimated cost with high probability. On the other hand, this solution may lead to overly conservative production schedules. In this article, we take a different approach and develop a bilevel stochastic optimization model with chance constraints, which allows us to make the production more predictable in the event of disruptions by driving costs and optimal schedules closer to the benchmark for each scenario considered. We introduce doubly probabilistic service‐level requirements to account for two interdependent layers of uncertainty, that is, production disruptions and distributional uncertainties in customer demand. This allows us to make high‐quality production decisions with only a limited understanding of the demand pattern. Approximating the problem for a numerical solution, we guarantee tight optimality gaps for high service levels and propose an efficient solution scheme, combining robust scenario reduction with a customized Benders decomposition procedure. In the managerial section, we use the Omega× Swatch MoonSwatches example to demonstrate that a desirable doubly probabilistic service level can be attained for disruptions with a drop in demand. In the case of disruptions followed by a peak in demand, one can tighten the optimality gaps if the service level is reduced.

show abstract

“…Despite the difficulties and the presence of a number of specific features, the presence of increased demand stimulates agricultural enterprises to develop in this area [1; 9]. The process of implementing measures for development and improving the assortment strategy is aimed at the creation and implementation of new business solutions and technologies [14].…”

Section: Introductionmentioning

confidence: 99%

Range of goods in framework of agricultural enterprise management

Bondarev

Бондарева

2022

BIO Web Conf.

View full text Add to dashboard Cite

The study of the product range of the enterprise, in particular, the agricultural ones, is one of the priority areas. Maintaining a stable demand for reduced goods is an obligatory condition for strategizing activities, a guarantee of development. The presented research reflects the theoretical foundations of enterprise management, in terms of building a strategy; the assortment features for both commodity and trade ones are disclosed; the authors highlighted the specifics of agricultural production through strategic management and its goal setting. In the main part of the work, there is a block focused on the study of the assortment within the framework of the agricultural enterprise management, based on the product range optimization. This is supported by the conclusions that this approach is a source of diversification of an agricultural enterprise production activity and takes into account both the existing market needs and the capabilities of the enterprise itself when creating the necessary conditions for its development, ensuring competitiveness not only in local markets, but also includes a possibility to expand its market zone. The assortment of goods was studied in a separate block on the example of a specific agricultural enterprise - the greenhouse complex JSC “Sukhovskiy”, a member of the Siberian agricultural complex of the brand “Em Rodnoe”. The assessment of the main economic indicators of the activities of JSC “Sukhovskiy” was carried out. For the purpose of practical testing of the developed directions of strategizing the product range of JSC “Sukhovskiy”, there was proposed a variant of its expansion by introducing roses into the “line” of production as the most popular and demanded flowers in high demand among the population. In addition, the agrotechnology of this production in the conditions of a greenhouse economy is shown, possible sales channels for finished products are proposed, the costs of the “rose” assortment line are structured and the predicted economic effect from the implementation of the proposed measures is calculated.

show abstract

Product assortment and space allocation strategies to attract loyal and non-loyal customers

Cited by 19 publications

References 31 publications

Utilizing additive manufacturing and mass customization under capacity constraints

Utilizing additive manufacturing and mass customization under capacity constraints

Limiting the impact of supply chain disruptions in the face of distributional uncertainty in demand

Range of goods in framework of agricultural enterprise management

Contact Info

Product

Resources

About