Replacement policies for age and working numbers with random life cycle

It has been modeled for several replacement policies in literatures that the whole life cycle or operating interval of an operating unit should be finite rather than infinite as is done with the traditional method. However, it is more natural to consider the case in which the finite life cycle is a fluctuated parameter that could be used to estimate replacement times, which will be taken up in this article. For this, we first formulate a general model in which the unit is replaced at random age U, random time Y for the first working number, random life cycle S, or at failure X, whichever occurs first. The following models included in the general model, such that replacement done at age T when variable U is a degenerate distribution, and replacement done at working numbers N summed by number N of variable Y, are optimized. We obtain the total expected cost until replacement and the expected replacement cost rate for each model. Optimal age T, working number N, and a pair of (T, N) are discussed analytically and computed numerically.     

Preventive replacement policies with products update announcements

Abstract

When we consider the improvement of the functional performances that are released by the new updates of the products, it is an interesting problem to revisit the existing replacement policies. For such a viewpoint, four replacement models with product update announcements, i.e., PUA for abbreviation, are given in this paper: Model 1, the unit is replaced at time T or at PUA over time T. Model 2, the unit is replaced at the Kth failure or at PUA over the Kth failure. By considering both time T and failure K, Models 3 and 4 are obtained based on the approaches of replacement first and last. We obtain the expected cost rates for four models and discuss analytically their optimal replacement policies Further, numerical examples are given when the time for PUA has an exponential distribution.     

Managerial incentive, organizational slack, and performance: empirical analysis of Japanese firms’ behavior

The main purpose of this study is to investigate how organizational slack is created and how it affects a firm’s performance. To address these questions, we construct three equations: managerial incentive function, organizational slack formation function and performance function, and we apply 3SLS simultaneously to these functions by using the data sets of 2,791 Japanese firms from the years 2001 and 2006. From the empirical analysis of these Japanese firms, we obtain the following results: a firm’s performance declines as organizational slack increases; organizational slack is affected by annual change rate of revenues but not by managerial incentive; managerial incentive decreases as a firm’s performance improves while it increases as the structure of corporate governance is strengthened.