Risk tolerance and a retailer's pricing and ordering policies within a newsvendor framework

This paper evaluates the pricing and ordering policies of a retailer, facing a price-dependent stochastic demand, within a newsvendor framework, under different degrees of risk tolerance and under a variety of optimizing objectives. These are (i) maximizing expected profit, for a retailer who may be risk-seeker, risk-averse or risk neutral; (ii) deriving a maximin strategy of maximizing a minimum guaranteed profit and (iii) modeling the probability of exceeding a target profit, as a constraint or as an objective. Some analytical properties and numerical examples illustrate the main features of the models and provide some comparative policy analysis across the model.     

Evaluating manufacturer's buyback policies in a single-period two-echelon framework under price-dependent stochastic demand

This paper attempts to model the profitability of a secondary market, in a newsvendor setting, to a profit-maximizing manufacturer, who is offering to the retailer a buyback policy for the unsold merchandise left at the end of the selling season. With a buyback agreement, the manufacturer shares the risks of demand uncertainty, thus inducing the buyer to place larger orders. The manufacturer's risk is mitigated to some extent by the availability of an extra market to dispose off the unsold merchandise. Both parties are risk-neutral profit-maximizers and both have the same information about the final demand for the product and its uncertainty. The manufacturer's decision is to arrive at an optimal wholesale price and the buyback price. Based on this offer, the retailer in turn sets the optimal amount of merchandise to purchase, as well as the unit selling price to meet a price-dependent uncertain demand for the merchandise in question. Due to the difficulty of obtaining analytical results, we have undertaken a numerical analysis to (i) compare the optimal policies across demand functions and error structures for three situations namely the no-incentive case and the buyback policies with and without a secondary market; (ii) indicate the conditions whereby the trade incentive is beneficial to both parties; (iii) assess the efficacy of the policies using two other performance indices (probability of achieving a target profit, and pass-through ratios) alternate to profit maximization; and (iv) conjecture the conditions for successful buyback policies and the nature of the benefits from the secondary market.     

Retailer's Response to Alternate Manufacturer's Incentives Under a Single‐Period,Price‐Dependent,Stochastic‐Demand Framework*

This article considers the joint development of the optimal pricing and ordering policies of a profit‐maximizing retailer, faced with (i) a manufacturer trade incentive in the form of a price discount for itself or a rebate directly to the end customer; (ii) a stochastic consumer demand dependent upon the magnitude of the selling price and of the trade incentive, that is contrasted with a riskless demand, which is the expected value of the stochastic demand; and (iii) a single‐period newsvendor‐type framework. Additional analysis includes the development of equal profit policies in either form of trade incentive, an assessment of the conditions under which a one‐dollar discount is more profitable than a one‐dollar rebate, and an evaluation of the impact upon the retailer‐expected profits of changes in either incentive or in the degree of demand uncertainty. A numerical example highlights the main features of the model. The analytical and numerical results clearly show that, as compared to the results for the riskless demand, dealing with uncertainty through a stochastic demand leads to (i) (lower) higher retail prices if additive (multiplicative) error, (ii) lower (higher) pass throughs if additive (multiplicative) error, (iii) higher claw backs in both error structures wherever applicable, and (iv) higher rebates to achieve equivalent profits in both error structures.     

An Assessment of the Measurement Properties of the Human Development Index

One of the more important determinants of the competitiveness of a nation is the quality of its human capital. The Human Development Index (HDI) is the most widely used yardstick of human development. It measures human development for all the countries of the world, through the use of three factors – longevity, knowledge and GDP measured in purchasing power. This paper evaluates HDI's contribution towards measuring the quality of the human capital component of a nation's competitiveness. Two primary issues under study are the HDI's information properties vis-a-vis its components and its measurement properties as an index. The primary conclusion of the study is that the HDI carries useful information about a country's current development, but not about the future level of development. Hence, further refinements in its construction as well as additional theoretical support as a quantitative measure are needed.     

Generalizing the Announced Price Increase Problem*

This paper generalizes the announced price increase problem to consider a variety of practical concerns arising out of applications ranging from foreign exchange fluctuations to upper limits on the purchase of discounted supermarket items. These include limitations on the amount that can be purchased at the old price and/or on the length of the grace period, within which buyers may take advantage of this lower price. These constraints give rise to 16 possible situations. For each situation purchasing and inventory decision rules are developed. A numerical example is discussed to highlight the main features of the models.     

A Purchasing Framework for B2B Pricing Decisions and Risk‐sharing in Supply Chains*

This paper presents a common modelling structure for (i) the implementation of operational policies by individual purchasing managers of risk‐sharing agreements among supply‐chain partners, and (ii) the integration of brick and click purchasing policies in a B2B. The problem of price uncertainty created within these two environments is modelled as a stochastic repetitive‐sales problem, applicable to any probability distribution. The model identifies sufficient conditions for regenerative ordering cycles, which allows for the use of the renewal reward theorem. The end result is a two‐price purchasing policy, which may substantially ease implementation problems across a global corporation's purchasing managers world‐wide and across B2B markets.