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

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

Efficient Order and Resource Coordination in Mass Customization

Mass customization manufacturing systems require a high level of adaptability and flexibility in production – especially in production planning and control. In particular, the Coordination of orders and resources is critical, because of the high volatility and the make to order principle. Multi-agent systems theoretically provide the required features to handle that complexity, but a lack of informational integration and organizational incompatibilities lead to low applicability. The application of Internet Technology provides the necessary interoperability and organizational alignment to support an overall application of multi-agent systems in mass customization.Mass Customization; Internet Technologies; Multi Agent Systems; Production Planning and Control

SERVICE-PROCESS CONFIGURATIONS IN ELECTRONIC RETAILING: A TAXONOMIC ANALYSIS OF ELECTRONIC FOOD RETAILERS

Service-processes of electronic retailers are founded on electronic technologies that provide flexibility to sense and respond online to the dynamic and complex needs of customers. In this paper, we develop a taxonomy of service-processes in electronic retailing and demonstrate their linkage to customer satisfaction and customer loyalty. The taxonomy is grounded in a conceptual classification scheme that differentiates service-process stages on a continuum of flexibility. Using data on electronic service-processes collected from 255 electronic food retailers, we identified eight configurations for the taxonomy. We also collected and analyzed publicly reported customer satisfaction survey data that were available for 52 electronic food retailers in the study sample. The results of this analysis indicate positive and significant correlation of the ordering of the taxonomy configurations with (i) customer satisfaction with product information, product selection, web site aesthetics, web site navigation, customer support, and ease of return, and (ii) customer loyalty. Taken together, the results of our empirical analyses demonstrate that the taxonomy captures information and variety within and across the electronic service-process configurations in ways that can be related to customer satisfaction and customer loyalty.Marketing, Research and Development/Tech Change/Emerging Technologies,

A Framework for Understanding the Interdependencies between Mass Customization and Complexity

Mass customization is a business strategy that aims at satisfying individual customer needs, nearly with mass production efficiency. It induces a high complexity level because of various customer requirements and a steadily changing environment. However, mass customization has some potential to reduce complexity. The interdependencies between mass customization and complexity are discussed in order to demonstrate that mass customization is not just an oxymoron linking two opposite production concepts, but a business strategy that contributes towards reaching a competitive advantage. On the one hand, mass customization increases the production program, manufacturing and configuration complexities. On the other hand, it contributes to reduce complexity at the levels of order taking process, product and inventories. The main results attained through the analysis are integrated in a comprehensive framework that shows the complexity increasing and complexity decreasing aspects due to mass customization.Mass Customization; Complexity Management; Product Variety

Mass Customization vs. Complexity: A Gordian Knot?

Mass customization is a business strategy that aims at satisfying individual customer needs, nearly with mass production efficiency. It induces a high complexity level because of various customer requirements and a steadily changing environment. However, mass customization has some potential to reduce complexity. These interdependencies between mass customization and complexity form a Gordian knot that should be cut in order to point out that mass customization is not just an oxymoron linking two opposite production concepts, but a business strategy that contributes towards reaching a competitive advantage. On the one hand, mass customization increases the production program, manufacturing and configuration complexities. On the other hand, mass customization can contribute to reduce complexity at the levels of order taking process, product and inventories. The main results attained through the analysis are integrated in a comprehensive framework that shows the complexity increasing and complexity decreasing aspects due to mass customization.complexity; mass customization

Modularity and Delayed Product Differentiation in Assemble-to-order Systems: Analysis and Extensions from a Complexity Perspective

The paper assumes a product design around modular architectures and discusses the suitability of the principle of delayed product differentiation in assemble-to-order environments. We demonstrate that this principle does not enable one to make optimal decisions concerning how variety should proliferate in the assembly process. Therefore, we propose to complement this principle in that we additionally consider the variety induced complexity throughout the assembly process. The weighted Shannon entropy is proposed as a measure for the evaluation of this complexity. Our results show that the delayed product differentiation principle is reliable when the selection probabilities of module variants at each assembly stage are equal and the pace at which value is added in the whole assembly process is constant. Otherwise, the proposed measure provides different results. Furthermore, the entropy measure provides interesting clues concerning eventual reversals of assembly sequences and supports decisions regarding what modules in an assembly stage could be substituted by a common module.modularity; complexity; ATO; delayed product differentiation

From Mass Customization to Collaborative Customer CoDesign

The idea of integrating users into the design and production process is a promising strategy for companies being forced to react to the growing individualization of demand. The use of e-business applications has been discussed as a approach for mass customization for over one decade. There is a huge amount of literature on manufacturing and information systems for mass customization. However, there has been little research looking at the role of the customer within the co-design process. Customers face new uncertainties and risks (“mass confusion”) when acting as co-designers. We discuss possible risks evolving during the interaction between customers and suppliers. We propose solutions for the “mass confusion” problem, and we challenge the assumption made by most mass customization researchers that offering customized products requires an individual (one-to-one) relationship between the customer and the supplier. We envision a different way of addressing the problem by using communities instead of one-to-one relationships. The objective of our paper is to build and explore the idea of communities for customer co-design