Significant recent research has focused on the marriage of consumer preferences and engineering design in order to improve profitability. The extant literature has neglected the effects of marketing channels, which are becoming increasingly important. At the crux of the issue is the fact that channel dominating retailers, like Wal-Mart, have the ability to unilaterally control manufacturer’s design decisions as gatekeepers to the consumers or market. In this paper, we propose a new methodology that accounts for this power asymmetry. A chance constrained optimization framework is used to model retailer acceptance of possible engineering designs and accounts for the important effect on the profitability of the retailer’s assortment through a latent class estimation of demand from conjoint surveys. Our approach allows the manufacturer to optimize a product design for its own profitability while reliably ensuring that the product will make it to market by making the retailer more profitable with the addition of the new product to the assortment. As a demonstrative example, we apply the proposed approach for product design selection in the case of an angle grinder. For this example, we analyze the market and are able to improve expected manufacturer profitability while simultaneously presenting the designer with trade-offs between slotting allowances, market share, and risk of retailer acceptance.

Refers to the SME sector, which represents a crucial area of the UK economy, yet there is little research into the use of TQM in this sector. ISO 9000 has been described by many as one of the means by which an organization may embrace TQM. Although there has been some research into the SME experience of ISO 9000, none has considered the standard's effectiveness as an SME route to TQM. Examines the use of basic TQM principles in a sample of diverse ISO 9000-registered SMEs. In addition, an implementation strategy is proposed that is designed to ensure that ISO 9000 implementation facilitates progress towards TQM.

We examine, in a strategic setting, the broad issue of how retail channel structures--retail monopoly versus retail duopoly--impact a manufacturer's optimal new product design, both in terms of engineering design specifications as well as manufacturer and retailer profits. Our strategic framework enables manufacturers in specific contexts to anticipate the reactions of the retailers and competitive manufacturers to new designs in terms of the retail and wholesale pricing and to understand how different channel structures and channel strategies (such as an exclusive channel strategy) impact the engineering design of the new product, conditional on consumer preference distributions and competitor product attributes. Based on a simple numerical and a power tool design example, we illustrate how the insight from the framework translates to design guidelines; specifically, understanding which designs are optimal under differing channel structure conditions, and which design variables need precise targeting given their profit sensitivity. This paper was accepted by Christoph Loch, R&D and product development.new product design, engineering design, research and development, retail channels, marketing, game theory, genetic algorithms, latent class models, structural models

Sensitivity analysis has received significant attention in engineering design. While sensitivity analysis methods can be global, taking into account all variations, or local, taking into account small variations, they generally identify which uncertain parameters are most important and to what extent their effect might be on design performance. The extant methods do not, in general, tackle the question of which ranges of parameter uncertainty are most important or how to best allocate Investments to partial uncertainty reduction in parameters under a limited budget. More specifically, no previous approach has been reported that can handle single-disciplinary multi-output global sensitivity analysis for both a single design and multiple designs under interval uncertainty. Two new global uncertainty metrics, i.e., radius of output sensitivity region and multi-output entropy performance, are presented. With these metrics, a multi-objective optimization model is developed and solved to obtain fractional levels of parameter uncertainty reduction that provide the greatest payoff in system performance for the least amount of “Investment.” Two case studies of varying difficulty are presented to demonstrate the applicability of the proposed approach.