Integrating inventory control and a price change in the presence of reference price effects: a two-period model

Taudes, Alfred; Rudloff, Christian

doi:10.1007/s00186-011-0374-1

Cited by 30 publications

(16 citation statements)

References 40 publications

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“…Kopalle and Lindsey-Mullikin [35] and Taudes and Rudloff [36] pointed out that the reference price would be affected by prior losses and gains, and people tend to adjust the current reference point according to the prior decision outcome. They believed that people would adjust their reference point as the following equation:…”

Section: Memory-adjusted Pricementioning

confidence: 99%

“…−1 is the stock price of last period, which means that people would adjust the current reference price with reference to the memory of the prior loss or gain on the basis of the last-period price. In view of the above, this paper takes the memory-adjusted price as investors' reference price, where the memory parameter is set to be 0.2 according to the study made by Taudes and Rudloff [36].…”

Section: Memory-adjusted Pricementioning

confidence: 99%

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Investors’ Risk Preference Characteristics Based on Different Reference Point

Wen

Gong

et al. 2014

Discrete Dynamics in Nature and Society

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Taking the stock market as a whole object, we assume that prior losses and gains are two different factors that can influence risk preference separately. The two factors are introduced as separate explanatory variables into the time-varying GARCH-M (TVRA-GARCH-M) model. Then, we redefine prior losses and gains by selecting different reference point to study investors' time-varying risk preference. The empirical evidence shows that investors' risk preference is time varying and is influenced by previous outcomes; the stock market as a whole exhibits house money effect; that is, prior gains can decrease investors' risk aversion while prior losses increase their risk aversion. Besides, different reference points selected by investors will cause different valuation of prior losses and gains, thus affecting investors' risk preference.

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Section: Memory-adjusted Pricementioning

confidence: 99%

Section: Memory-adjusted Pricementioning

confidence: 99%

Investors’ Risk Preference Characteristics Based on Different Reference Point

Wen

Gong

et al. 2014

Discrete Dynamics in Nature and Society

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show abstract

“…Building on this approach, and Fibich et al (2003) consider asymmetric reference effects. The joint study of reference effects with inventories is more recent, with Taudes and Rudloff (2012) proposing a two-period model. Stochastic demand and stochastic inventory are introduced in Cao et al (2012) and Li et al (2015), respectively.…”

Section: Introductionmentioning

confidence: 99%

Dynamic pricing for inventories with reference price effects

Chenavaz

Paraschiv

2018

Economics

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This article presents a dynamic pricing model of a retailer selling an inventory, accounting for consumer behavior. The authors propose an optimal control model, maximizing the intertemporal profit with consumers sensitive to the selling price and to a reference price. The optimal dynamic pricing policy is solved with Pontryagin's maximum principle with a structural (general) demand function. The authors obtain an original pricing rule, which explicitly accounts for the impact of price and inventory on future profits. The dynamics of price do not have to imitate the dynamics of the reference price. Instead, the dynamics of price are tied to opposing effects linked to this reference price. The authors also discuss managerial implications with regards to behavioral pricing policies. JEL C61 D03 D40 M21 M37

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“…[16]- [19] studied joint inventory and pricing problem with stochastic linear demand under reference effects with discrete time setting. [16] simulated the multi-period problem in case of linearity of the demand where the randomness is caused by an additional random term and showed that state-dependent order-up-to is optimal in the simulation.…”

Section: Introductionmentioning

confidence: 99%

“…[16] simulated the multi-period problem in case of linearity of the demand where the randomness is caused by an additional random term and showed that state-dependent order-up-to is optimal in the simulation. [19] studied problems with two periods and showed the optimality of a state-dependent order-up-to policy for two periods. In the state-dependent order-up-to policy, the order-up-to level depends on the state, particularly on the reference price.…”

Section: Introductionmentioning

confidence: 99%