Managing product variety with advance selling and capacity restrictions

Kuthambalayan, Thyagaraj S.; Mehta, Peeyush; Shanker, Kripa

doi:10.1016/j.ijpe.2015.10.006

Cited by 20 publications

(11 citation statements)

References 31 publications

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“…Minimization of food spoilage and retailer profit maximization can be done through pricing based on the shelf life of food (Wang & Li, 2012). The problem of a price reduction or discount on perishable products is studied in Wang and Li (2012), Muniappan et al (2016), Chung et al (2015), Kuthambalayan et al (2015), Chew et al (2014), Chakraborty et al (2013). In more complex cases, the optimal discount quantity for multi-item perishable products has been determined in Makkar et al (2012).…”

Section: Methodsmentioning

confidence: 99%

A Three-Phased Perishable Inventory Simulation Model with Quality Decrease Consideration

Ibrahim

Mardhiyyah

Rusdiansyah

et al. 2020

JITI

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In this article, focus on the simulation of a three-phase perishable product inventory system of a SMEs selling fresh and processed milkfish. This research was conducted to simulate a perishable product inventory system to understand and analyze the problems that occur then propose solutions to fix them. The simulation model was developed with ARENA software, simulation results of the existing condition show that there is 162 kg/month waste in fresh fish, 158 pcs/month in processed product A, and 86 pcs/month in processed product B. A model with a product renewal process mechanism was proposed to overcome this problem, and seven improvement scenarios were developed. The results obtained from the seventh improvement scenario revealed that there was a 100% reduction in fresh fish and processed product B and 94% in processed product A. Besides, there was a saving in need for fresh fish supply of 10 kg/day. In this article, we show how ARENA software can be adopted to simulate inventory system problems effectively. The method in this research can be applied to investigate various supply system scenarios and their consequences before implementing it in a real system.

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Section: Methodsmentioning

confidence: 99%

A Three-Phased Perishable Inventory Simulation Model with Quality Decrease Consideration

Ibrahim

Mardhiyyah

Rusdiansyah

et al. 2020

JITI

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“…In addition, some studies focus on eliminating the consumer risk of buying in advance at a higher presale price through price guarantees [20,28], buybacks [29,30] and refunds [30,31]. Many studies adopting various perspectives have examined why sellers use the presale strategy, including to determine market potential and forecast demand in advance [2,32,33], as a price discrimination tool [7,8,19,34], to increase sales volume [1,35,36] and for capacity planning [3,17,26].…”

Section: A Prsale Strategymentioning

confidence: 99%

Presale Strategy for a Dual-Channel Retailer Considering Sales Effort

Feng

Liu

2021

IEEE Access

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We study the presale strategy and decision-making problems for a retailer selling products. Based on the penetration and skimming pricing strategies, we consider the characteristics of consumer market segmentation and valuation heterogeneity, focus on the implementation conditions and optimal decision results of different pricing strategies before and after the introduction of an online presale channel, and conduct a multidimensional comparative study on the impact of the introduction of the online presale channel. We find that the introduction of an online presale channel can always improve the retailer's profitability, but its pricing strategy and sales effort should be adjusted to align with the consumer market segmentation. When the proportion of online consumers is high or their preference for the spot channel is high, the retailer should always adopt a penetration pricing strategy. If online consumers also show a high consumption preference for the presale channel, the retailer should reduce its sales effort to save costs after introducing the presale channel; otherwise, the retailer should increase its sales effort to increase demand in the offline spot channel. When the proportion of online consumers is low and their preference for the spot channel is low, the retailer should always adopt a skimming pricing strategy and keep sales effort unchanged. When the proportion of online consumers and their consumption preference for the spot channel are moderate, the retailer should adjust its pricing strategy from penetration to skimming after introducing the online presale channel and appropriately reduce the level of sales effort.

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“…Moe and Peter [9] measured the impact of the preselling of new product on the prediction of market demand, with the aid of models and empirical data. Kuthambalayan et al [17] evaluated the effect of preselling discount on seller profit in a production environment, featured by short cycle, multiple product categories, changing demand, and limited production capacity. Under the constraint of production capacity, Huang et al [18] constructed a two-stage pricing model for preselling, and deduced the optimal price decisions in the preselling period and the regular selling period.…”

Section: Literature Reviewmentioning

confidence: 99%