Training provision and regulation: an analysis of the temporary help industry

This paper studies from an economic viewpoint the juridical rationality of mandatory training provisions on Temporary Help Agencies through the Spanish Law 14/94. No positive relationship is found between the improvement in Temporary Help Agencies' added value levels and their investments in temps' training. In analyzing this specific provision of Spanish Labor Law we adopt a positive focus with the aim of finding economic causes for its adoption and of explaining its effect on the functioning of the labour intermediation sector. The application of the non-market failure theory leads us to conclude that an efficient use of this legal prescription is limited. The investigated issue is of relevance in order to understand the economic effects of regulation from a Law and Economics perspective

TRAINING PROVISION AND REGULATION: AN ANALYSIS OF THE TEMPORARY HELP INDUSTRY

This paper studies from an economic viewpoint the juridical rationality of mandatory training provisions on Temporary Help Agencies through the Spanish Law 14/94. No positive relationship is found between the improvement in Temporary Help Agencies’ added value levels and their investments in temps’ training. In analyzing this specific provision of Spanish Labor Law we adopt a positive focus with the aim of finding economic causes for its adoption and of explaining its effect on the functioning of the labour intermediation sector. The application of the non-market failure theory leads us to conclude that an efficient use of this legal prescription is limited. The investigated issue is of relevance in order to understand the economic effects of regulation from a Law and Economics perspective.

Impact of the Operations Manager's dual role on inventory policy

In modern corporations, the Operations Manager’s role in defining of firm’s strategy is becoming more important. In this paper we describe how firms can use this tendency for Operations Managers to make strategic decisions as a mechanism to prevent inventory mismanagement. These managers have incentives to speculate with inventory cost reductions, thereby avoiding sharp reductions in a single period, because it would hinder further reductions in the future. Remarkably, firms may prevent such behavior by stimulating the Operations Managers’ strategic orientation, without losing sight of inventory-efficient management

Alphabetical Listing of ILR School Theses and Dissertations by Authors

Compiled by Susan LaCette.AlphabeticalListing.pdf: 1703 downloads, before Oct. 1, 2020

Impact of the Operations Manager's dual role on inventory policy

In modern corporations, the Operations Manager’s role in defining of firm’s strategy is becoming more important. In this paper we describe how firms can use this tendency for Operations Managers to make strategic decisions as a mechanism to prevent inventory mismanagement. These managers have incentives to speculate with inventory cost reductions, thereby avoiding sharp reductions in a single period, because it would hinder further reductions in the future. Remarkably, firms may prevent such behavior by stimulating the Operations Managers’ strategic orientation, without losing sight of inventory-efficient management.

Approximate Dynamic Programming Algorithms for United States Air Force Officer Sustainment

The United States Air Force (USAF) officer sustainment system involves making accession and promotion decisions for nearly 64 thousand officers annually. We formulate a discrete time stochastic Markov decision process model to examine this military workforce planning problem. The large size of the motivating problem suggests that conventional exact dynamic programming algorithms are inappropriate. As such, we propose two approximate dynamic programming (ADP) algorithms to solve the problem. We employ a least-squares approximate policy iteration (API) algorithm with instrumental variables Bellman error minimization to determine approximate policies. In this API algorithm, we use a modified version of the Bellman equation based on the post-decision state variable. Approximating the value function using a post-decision state variable allows us to find the best policy for a given approximation using a decomposable mixed integer nonlinear programming formulation. We also propose an approximate value iteration algorithm using concave adaptive value estimation (CAVE). The CAVE algorithm identities an improved policy for a test problem based on the current USAF officer sustainment system. The CAVE algorithm obtains a statistically significant 2.8% improvement over the currently employed USAF policy, which serves as the benchmark

* ILR School Theses and Dissertations: A Listing

Compiled by Susan LaCette.revILRThesesComplete.pdf: 4443 downloads, before Oct. 1, 2020

Management: A continuing bibliography with indexes

This bibliography lists 344 reports, articles, and other documents introduced into the NASA scientific and technical information system in 1978