The importance of the services sector can not be overstated; it employs 82.1 percent of the U. S. workforce and 69 percent of graduates from an example technological university. Yet, university research and education have not followed suit. Clearly, services research and education deserve our critical attention and support since services — and services innovation — serve as an indispensable engine for global economic growth. The theme of this paper is that we can and should build services research and education on what has occurred in manufacturing research (especially in regard to customization and intellectual property) and education; indeed, services and manufactured goods become indistinguishable as they are jointly co-produced in real-time. Fortunately, inasmuch as manufacturing concepts, methodologies and technologies have been developed and refined over a long period of time (i.e., since the 1800s), the complementary set of concepts, methodologies and technologies for services are more obvious. However, while new technologies (e.g., the Internet) and globalization trends have served to enable, if not facilitate, services innovation, the same technologies (e.g., the Internet) and 21st Century realities (e.g., terrorism) are making services innovation a far more complex problem and, in fact, may be undermining previous innovations in both services and manufacturing. Finally, there is a need to define a “knowledge-adjusted” GDP metric that can more adequately measure the growing knowledge economy, one driven by intangible ideas and services innovation.

In this paper, relations between vector and weak vector variational inequalities and equilibrium principles for multiclass, multicriteria traffic network equilibrium problem in the fixed demand case and elastic demand case are established, respectively.

In this paper, we propose a new model for improving the lot size obtained with the model of Woo, Hsu, and Wu (2001) proposed in their paper “An integrated inventory model for a single vendor and multiple buyers with ordering cost reduction” (Int. J. Production Economics 73 203–215). The new model can provide a lower or equal joint total cost as compared to Woo, Hsu, and Wu’s model due to the relaxation of their integral multiple material ordering cycle policy to a fractional-integral multiple material ordering cycle policy. The proposed model is analyzed and an algorithm for calculating the optimal lot size of the model is developed. A numerical study based on the example used by Woo, Hsu, and Wu is presented.

In this paper we introduce a method of analysis for the automated ordering and selection of solutions of a multicriteria shortest path model. The method is based on a reference point approach, where the paths in a specific priority region are ranked by non-decreasing order of a Chebyshev metric. In order to list paths according with this objective function a labelling algorithm is proposed. The developed method is applied in a video-traffic routing context. Computational results are presented and analysed, for randomly generated networks of significant dimension.

This paper studies the decision-making and coordination of supply chain (SC) considering the effect of price-dependent demand. By assuming demand decreases as the price increases, we analyse the impacts of the dependence on the SC in three different models: decentralized without coordination, centralized coordination and decentralized with coordination by revenue sharing contract. The existence of the best solution in the different models is proved, and the performance of revenue sharing coordination SC is similar to the centralized one. We find that the more evidently the price affects the demand, the more revenue sharing contract improves the performance of SC. The dependence affects the decision-making and the parameter setting of revenue sharing contract is also found.

This paper investigates the ordering decision problem for a short-life-cycle product under Bayesian updating. For a product characterized by a single manufacturing cycle and two selling periods, we depict a Two-Stage (TS) ordering strategy with a stochastic dynamic programming model in the view of the whole system, and prove that the expected profit function of the whole system is concave on the first ordering quantity and the remedial ordering quantity, respectively. Then, the optimal ordering decision is developed. Finally, characteristics of the optimal ordering quantities are analyzed with several examples. Our results show that the suggested TS decision model is better than a Quick Response (QR) decision model.

In the real world, revenue maximization behavior may prevail in various markets. To understand this phenomenon, we develop a two-population model with two-vertically integrated channels. Every channel consists of one manufacturer and many (a sufficiently large number of) retailers that sell products in different markets by adopting pure marketing objective strategies: profit maximization and revenue maximization. We study the marketing objective behaviors in the quantity-setting duopoly and the price-setting duopoly situations respectively from an indirect evolutionary point of view. In the quantity-setting duopoly situation, we find that whether the equilibrium is an evolutionarily stable strategy depends on the type of strategic interaction (substitutes or complements), relative unit cost, market scale, etc. We extend it to the case with continuous preferences. We argue that revenue maximization may be an evolutionarily stable strategy and profit maximization strategy may be unstable. Under proper conditions, revenue maximization behavior can coexist with profit maximization behavior. In the price-setting duopoly situation with linear demand functions, we find that profit maximization is always an evolutionarily stable strategy and revenue maximization behavior will gradually become extinct. The extended model has a similar result but the retailers may compromise the two pure strategies.

In this paper, the issue of quality evaluation level decision problem in outsourcing is studied under different information backgrounds. Based on the quality contracting optimization models of Stanley and others, a principal agent model concerned with quality prevention level and evaluation level is set up with regards to buyer as principal and supplier as agent. In the models, quality prevention level is a variable decided by the supplier, quality evaluation level and transfer payment are variables decided by the buyer. We focus on the study of quality evaluation level and transfer payment decision in outsourcing under asymmetric information. Maximal principle is used to get the solution to quality evaluation level when supplier quality prevention level information is hidden. At last simulation calculation is performed concerned with tractor production outsourcing business of an agricultural machine company. Simulation results under different information backgrounds are analyzed and compared.