Decision support for build-to-order supply chain management through multiobjective optimization

This paper aims to identify the gaps in decision-making support based on multiobjective optimization for build-to-order supply chain management (BTOSCM). To this end, it reviews the literature available on modelling build-to-order supply chains (BTO-SC) with the focus on adopting multiobjective optimization (MOO) techniques as a decision support tool. The literature has been classified based on the nature of the decisions in different part of the supply chain, and the key decision areas across a typical BTO-SC are discussed in detail. Available software packages suitable for supporting decision making in BTO supply chains are also identified and their related solutions are outlined. The gap between the modelling and optimization techniques developed in the literature and the decision support needed in practice are highlighted and future research directions to better exploit the decision support capabilities of MOO are proposed

Decision support for build-to-order supply chain management through multiobjective optimization

This is the post-print version of the final paper published in International Journal of Production Economics. The published article is available from the link below. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. Copyright @ 2010 Elsevier B.V.This paper aims to identify the gaps in decision-making support based on multiobjective optimization (MOO) for build-to-order supply chain management (BTO-SCM). To this end, it reviews the literature available on modelling build-to-order supply chains (BTO-SC) with the focus on adopting MOO techniques as a decision support tool. The literature has been classified based on the nature of the decisions in different part of the supply chain, and the key decision areas across a typical BTO-SC are discussed in detail. Available software packages suitable for supporting decision making in BTO supply chains are also identified and their related solutions are outlined. The gap between the modelling and optimization techniques developed in the literature and the decision support needed in practice are highlighted. Future research directions to better exploit the decision support capabilities of MOO are proposed. These include: reformulation of the extant optimization models with a MOO perspective, development of decision supports for interfaces not involving manufacturers, development of scenarios around service-based objectives, development of efficient solution tools, considering the interests of each supply chain party as a separate objective to account for fair treatment of their requirements, and applying the existing methodologies on real-life data sets.Brunel Research Initiative and Enterprise Fund (BRIEF

Economic Perspective on Cloud Computing: Three Essays

Improvements in Information Technology (IT) infrastructure and standardization of interoperability standards among heterogeneous Information System (IS) applications have brought a paradigm shift in the way an IS application could be used and delivered. Not only an IS application can be built using standardized component but also parts of it can be hosted by different organizations in different locations provided it can be accessed using the Internet. This dissertation is an attempt to uncover unique aspects of this phenomenon known as Software as a Service (SaaS). The first essay examines design decision making by SaaS providers by analyzing effects of two non-functional attributes of an IS Application - modularity and architectural performance. We model the relationship of the two attributes with factors such as demand, price, and user\u27s preference. The model includes marginal cost and maintenance cost to recognize the service aspect of SaaS. Our results show the optimal values of various decision variables while taking into account user\u27s sensitivity to modularity, architectural performance and price. The service component in cloud computing necessitates that the service providers plan for requisite delivery capacity. The second essay addresses optimal infrastructure capacity planning while taking into account the opportunity cost of having low capacity and cost of unused capacity in the case of high capacity. We develop a model which provides insight to a SaaS provider on optimal capacity planning of IT infrastructure when faced with a variable demand and performance expectations. The third essay focuses on financial risks faced by SaaS providers in the context of provider\u27s risk tolerance. We analyze the financial risk of provider\u27s decision making on pricing, capacity and other factors that may lead to financial risk as they are based on incomplete information. We built a model using Mean Variance Analysis theory for investigating the effect of provider\u27s risk tolerance on infrastructure capacity planning while taking into account modularity in software architecture and operational performance. This dissertation extends our understanding of significant issues facing a SaaS provider. The models presented here can form the basis for an extensive exploration of the phenomenon of SaaS specifically and Cloud Computing in general

Service customization under capacity constraints: an auction-based model

In mass customization, companies strive to enhance customer value by providing products and services that are approximate to customers’ needs. A company’s strategy of allocating its limited capacity to meeting diverse customer requirements directly impact customer perceived value in terms of available options, cost, and schedule. Proposed in this paper is an auction-based mass customization model for solving the problem of service customization under capacity constraints (SCCC). The proposed model integrates customers’ customization decision making with the allocation of company’s capacity through multilateral negotiation between the company and its customers. The negotiation is conducted through a combinatorial iterative auction designed to maximize the overall customer value given limited capacity. The auction is incentive-compatible in the sense that customers will follow the prescribed myopic best-response bidding strategy. Experimental results indicate that customization solutions computed by the proposed model are very close to the optimal one. Revenue performance is also adequate when there is sufficient competition in the market

Responsive supply in fashion mass customisation systems with consumer returns

Mass customisation systems have been well-established in the fashion industry. Some fashion brands offer the mass customisation system for their selected seasonal products, and allow unconditional returns and full refund for any unsatisfied customers. Motivated by the above mentioned observed industrial practice and based on the growing importance of responsive supply, we explore in this paper the value of quick response supply in fashion mass customisation systems with consumer returns. We focus on investigating how the consumer returns rate affects (i) the optimal inventory decision of the fashion brand, (ii) the achievability of Pareto improvement in implementing quick response supply, (iii) the respective values of quick response for the fashion brand, the fashion supplier and also the fashion supply chain, and (iv) the impact of quick response supply on the environment. We interestingly find that consumer returns enhance the value of quick response supply to the fashion supplier. Quick response supply is also found to be helpful in reducing the environmental cost under the fashion mass customisation system with consumer returns

The Cost of Consent: Optimal Standardization in the Law of Contract

This article argues that informed consent to contract terms is not a good to be maximized, but is rather an information cost that courts should minimize. The goal of mass-market contract law ought to be to keep costs low by encouraging contract standardization. The article applies information cost theory to show that information-forcing rules are often inefficient at both the micro- and macroeconomic levels. Such rules also impose greater costs on third parties than the benefits they create for the contracting parties. When one consumer creates an idiosyncratic deal, the information-savings benefits of standardization are reduced for all other potential consumers. The article demonstrates that in some cases courts are already abandoning a rigid view of contractual consent where consent is too costly; but that under other doctrines courts insist on an inefficient level of informed contractual consent

The feasibility of adopting clothing mass customisation in South Africa

Abstract: Mass Customisation (MC) is increasingly seen as a strategy to survive in the competitive clothing fashion markets. This importance to retail sales necessitates its consideration in the South African context. There is a paucity of literature on adopting MC so exploring the feasibility of MC for South African clothing manufacturers was a step in understanding what is required from manufacturers. Three corporate clothing manufacturers were selected for qualitative interviews to determine whether they currently exhibit identified competencies from literature considered essential to undertake MC. Two manufacturers exhibited key competencies of communication, human capital, flexibility and technology needed for MC success