Robust design (RD) has received much attention from researchers and practitioners for years, and a number of methodologies have been studied in the research community. The majority of existing RD models focus on the minimum variability with a zero bias. However, it is often the case that the customer may specify upper bounds on one of the two process parameters (i.e., the process mean and variance). In this situation, the existing RD models may not work efficiently in incorporating the customer’s needs. To this end, we propose two simple RD models using the ε-constraint feasible region method — one with an upper bound of process bias specified and the other with an upper bound on process variability specified. We then conduct a case study to analyze the effects of upper bounds on each of the process parameters in terms of optimal operating conditions and mean squared error.

A multi-agent model is presented to discuss the market dynamics and the size distribution of firms. The model emphasizes the effects of increasing returns to scale and gives the description of the born and death of adaptive producers. The evolution of market structure and its behavior under the technological shocks are investigated. Its dynamical results are in good agreement with some empirical “stylized facts” of industrial evolution. With the diversity of demand and adaptive growth strategies of firms, the firm size in the generalized model obeys the power-law distribution. Three factors mainly determine the competitive dynamics and the skewed size distributions of firms: 1. Self-reinforcing mechanism; 2. Adaptive firm growing strategies; 3. Demand diversity or widespread heterogeneity in the technological capabilities of firms.

Health care consumers no longer want to be passive receivers of treatment and care, they want to be involved. This shift is driven by the new information technology and a ‘social revolution’. Easy access to health information, thanks largely to the Internet, and active health consumer organizations have provided consumers with enabling independent health information. Individual consumers are also more willing to enter into a dialogue, participate and influence decisions concerning their own care. At the same time the consumer role becomes more diverse. Populations in many countries today are culturally, socially, and demographically diverse. Understanding consumer diversity is one of the greatest challenges facing health care providers. There is a risk that the quality of health care provided to consumers can vary depending on the skills of the professionals to tune into the values and preferences of the individual consumer. Health care providers need to listen to and incorporate consumers’ experiences into their health service offerings in new and creative ways. They need to engage in a dialogue with various consumer groups using multiple channels. There is a need for a new business logic, which would structurally help the providers, on an individual basis to deal with more sophisticated health care consumers. This is a review paper and provides a framework and a set of strategies for dealing with health consumer diversity. We draw on three interrelated theories — open systems theory, service management research and the concept of consumer segmentation to understand health care consumers’ attitudes and behaviour, and their expectations.

The Web Quality Analyser (WQA) is a new benchmarking tool for industry. It has been extensively tested across services industries. Forty five critical success features are presented as measures that capture the user’s perception of services industry websites. This tool differs to previous tools, in that it captures the information technology (IT) related driver sectors of website performance, along with the marketing-services related driver sectors. These driver sectors capture relevant structure, function and performance components.

An ‘on-off’ switch measurement approach determines each component. Relevant component measures scale into a relative presence of the applicable feature, with a feature block delivering one of the sector drivers. Although it houses both measurable and a few subjective components, the WQA offers a proven and useful means to compare relevant websites.

The WQA defines website strengths and weaknesses, thereby allowing for corrections to the website structure of the specific business. WQA benchmarking against services related business competitors delivers a position on the WQA index, facilitates specific website driver rating comparisons, and demonstrates where key competitive advantage may reside. This paper reports on the marketing-services driver sectors of this new benchmarking WQA tool.

Solving complex decision problems requires the usage of information from different sources. Usually this information is uncertain and statistical or probabilistic methods are needed for its processing. However, in many cases a decision maker faces not only uncertainty of a random nature but also imprecision in the description of input data that is rather of linguistic nature. Therefore, there is a need to merge uncertainties of both types into one mathematical model. In the paper we present methodology of merging information from imprecisely reported statistical data and imprecisely formulated fuzzy prior information. Moreover, we also consider the case of imprecisely defined loss functions. The proposed methodology may be considered as the application of fuzzy statistical methods for the decision making in the systems analysis.

This paper introduces a software agent as a virtual player of the business game called Bakery Game. The business game is a tool to understand business and management principles through experience in a virtual world. In order to construct software agents for the gaming simulation, which is able to participate in a game and become human players’ worthy rival, we combine a simple model that considers the property of Bakery Game with a strategy adjustment model. The agent has so-called strategy parameters that are updated through the experience. The agent changes his strategy depending on particular situation. The agent participates in the game that is regenerated from log data in various situations.

Member enterprises engaged in a virtual enterprise are prone to shirk both productive efforts and risks because their efforts are unobservable to any other member enterprises. How to design a revenue sharing contract to prevent the member enterprises from free riding is one of the most important issues to be considered to cut down risks that virtual enterprises may meet. Based on the work of profit sharing in partnerships and the research on revenue sharing in supply chains and joint ventures, we propose a model of the revenue sharing contract aimed at coordinating a virtual enterprise composed of n risk-averse member enterprises where every member enterprise performs different tasks and contributes distinct core resources. We characterize the optimal productive efforts, risk-taken and incentive intensity in the revenue sharing contract, and indicate that improving the evaluation precision of productive efforts and selecting weakly risk-averse member enterprises with close power are the key factors to the success of VEs.

In this paper, we consider two competitive parallel distribution channels (PDCs) each of them consisting of a manufacturer and a retailer. In every PDC, the manufacturer sells differentiated products to the retailer and the retailer chooses the retail price (margin). We explore the effects of the move sequence on the system performance not only in each distribution channel, but also in the inter-parallel distribution channels subject to the deterministic demand. Under some assumptions, we show that the PDC has the second-mover advantage in this scenario. The system performance will be improved in our model when the parameters satisfy certain conditions. Furthermore, we discuss the results and find some implications.