Bilateral Delegation in Duopoly Wage and Employment Bargaining

We study bilateral delegation in wage and employment bargaining between firms and unions in a Cournot duopoly. Incentive delegation creates frictions for each party between its objectives of within‐firm rent extraction and market/job stealing from the rival firm. The net effect is restraint in production, resulting in a larger bargaining pie. But each player's payoff will be inversely related to his bargaining power. We also show that if players are given a choice to delegate, they will not resort to delegation when their bargaining power is sufficiently high. This is in contrast to the scenarios commonly assumed in many models. Copyright © 2016 John Wiley & Sons, Ltd.     

Unification of some multivariate process capability indices for asymmetric specification region

In manufacturing industries, it is often seen that the bilateral specification limits corresponding to a particular quality characteristic are not symmetric with respect to the stipulated target. A unified superstructure of univariate process capability indices was specially designed for processes with asymmetric specification limits. However, as in most of the practical situations a process consists of a number of inter‐related quality characteristics, subsequently, a multivariate analogue of , which is called C_M(u,v), was developed. In the present paper, we study some properties of C_M(u,v) like threshold value and compatibility with the asymmetry in loss function. We also discuss estimation procedures for plug‐in estimators of some of the member indices of C_M(u,v). Finally, the superstructure is applied to a numerical example to supplement the theory developed in this article.     

Connection between uniformity and minimum moment aberration

The issue of uniformity in symmetrical fractional factorial designs is studied in this paper. The so-called discrete discrepancy is employed as a measure of uniformity. In this paper we give linkages between uniformity measured by the discrete discrepancy and minimum moment aberration, which provide a significant statistical justification of the discrete discrepancy.     

CREDIBILITY AND STRATEGIC LEARNING IN NETWORKS

We analyze a model of diffusion in a fixed, finite connected network. There is an interested party that knows the quality of the product being propagated and chooses an implant in the network to influence other agents to buy. Agents are either “innovators,” who adopt immediately, or rational. Rational consumers buy if buying instead of waiting maximizes expected utility. We consider the conditions on the network under which optimal diffusion of the good product with probability 1 is a perfect Bayes equilibrium.