Thesis (Ph.D.)--The Chinese University of Hong Kong, 2006. / Adviser: Xiaoqiang Cai. Includes bibliographical references.

Thesis (Ph.D.)--City University of Hong Kong, 2009. / "Submitted to Department of Management Sciences in partial fulfillment of the requirements for the degree of Doctor of Philosophy." Includes bibliographical references (leaves 80-86)

Thesis (Ph.D.)--Hong Kong University of Science and Technology, 2006. / Includes bibliographical references (leaves 82-88). Also available in electronic version.

Thesis (Ph. D.)--West Virginia University, 2006. / Title from document title page. Document formatted into pages; contains xii, 152 p. : ill. (some col.). Includes abstract. Includes bibliographical references (p. 127-129).

Thesis (Ph. D.)--Industrial and Systems Engineering, Georgia Institute of Technology, 2007. / Dr. Faiz Al-Khayyal, Committee Co-Chair ; Dr. Paul M. Griffin, Committee Co-Chair ; Dr. Earl Barnes, Committee Member ; Dr. Jye-Chyi Lu, Committee Member ; Dr. John Elton, Committee Member.

M.Com. (Business Economics) / Proper pricing should be done in three phases. Firstly, the determination of the market-price, namely that price which the consumers are prepared to pay for the amount of need-satisfaction they perceived from using the product. Secondly, the determination of the target-price, namely that price wrich will give a satisfactory rate of return on investment for the firm. Thirdly, the determination of the final price, by comparing the market-price with the target-price. The determination of the market-price is becoming more and more relevant and up to the present time no comprehensive research has been done on this subject in South Africa. In this dissertation an investigation was undertaken into the present technology concerning market-pricing and from this knowledge a method was developed which will be applicable to the determination of market prices in South Africa.

Thesis (Ph.D.)--Drexel University, 2009. / Includes abstract and vita. Includes bibliographical references (leaves 116-120).

Xu Xiaolin. / "August 2006." / Thesis (Ph.D.)--Chinese University of Hong Kong, 2006. / Includes bibliographical references (p. 149-156). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstracts in English and Chinese.

Pricing decision is the minority of all important decisions which can apparently influence a firm's profit-making within extremely short time. In an era of meagre profit, firms cannot stand any more injury caused of mistake at pricing. However, lots of managers still make pricing decision according to their experience or the action of other competitors without any mechanism of price-determining based on their firms' resource condition. The subject of this research is to probe the abiding price-reducing strategy for fashion appearing firms. Fashion apparel is a kind of commodities with seasonality and popularity, and is an example of all perishable goods. For all sorts of characteristic such as the need for long lead time before production, short time span for sale , and the low salvage value after season...etc., it makes firms reduce price to close out inventories by the end of seasons to evade value loss. When it comes to price-reducing, the fashion apparel is quite different from other commodities. It is a kind of commodity which has speciality of phased and monotonicity on price reduction. Therefore, it lacks two kinds of elasticity which are price-adjusting at any time and adjusting the price range at will. For the characteristic of close interdependence between product and time, and the normal demand on price-reducing, fashion apparel firms need some decision tools which are more fast, correct, and practical than any other ones. With two main parameters which are 'the levels of unsold inventory' and ' the length of season remaining ' along with two parameters which are 'discount factor' and ' the salvage value after season ', this research constructs out an stochastic dynamic programming model to maximize the expect profit and offer an program for calculating the optimal price-reduced range and time. After the analysis of generality and sensitivity with this model, it is found that the characteristics of this model are in conformity with theoretical research and real phenomenon of market. Besides, it is suitable for various kinds of price elastic demand. Hence, this model can be proved to be able to extend to other similar industries with the same nature.

The focuses of this dissertation are problems of batch production scheduling problems for perishable products with setup times, with the main applications in answering production planning problems faced by manufacturers of perishable products, such as beers, vaccines and yoghurts. The benefits of effective production plans can help companies reduce their total costs substantially to gain the competitive advantages without reduction of the service level in a globalize economy. We develop concepts and methodologies that are applied in two fundamental problems: (i) the batch production scheduling problem for perishable products with sequence-independent setup times (BPP-SI) and (ii) the batch production scheduling problem for perishable products with sequence-dependent setup times (BPP-SD). The problem is that given a set of forecast demand for perishables products to be produced by a set of parallel machines in the single stage of batch production, with each product having fixed shelf-life times and each machine requiring setup times before producing a batch of product, find the master production schedule which minimizes total cost over a specified time horizon. We present the new models for both problems by formulating them as a Mixed Integer Program (MIP) on the discrete time. Computational studies in BPP-SI and BPP-SD for industrial problems are presented. In order to efficiently solve the large BPP-SI problems in practice, we develop the five efficient heuristics. The extensive computational results show that the developed heuristics can obtain the good solution for the very large problem size and require very short amount of computational time.