Identifying “best” applicants in recruiting using data envelopment analysis

Selecting the most promising candidates to fill an open position can be a difficult task when there are many applicants. Each applicant achieves certain performance levels in various categories and the resulting information can be overwhelming. We demonstrate how data envelopment analysis (DEA) can be used as a fair screening and sorting tool to support the candidate selection and decision-making process. Each applicant is viewed as an entity with multiple achievements. Without any a priori preference or information on the multiple achievements, DEA identifies the non-dominated solutions, which, in our case, represent the “best” candidates. A DEA-aided recruiting process was developed that (1) determines the performance levels of the “best” candidates relative to other applicants; (2) evaluates the degree of excellence of “best” candidates’ performance; (3) forms consistent tradeoff information on multiple recruiting criteria among search committee members, and, then, (4) clusters the applicants.     

Evidence on agglomeration economies,diseconomies, and growth

Conventional urban economic analysis suggests that a local economy's size is closely related to a number of features, including levels of human capital and the availability of specialized inputs, which are likely to influence positively the rate at which it accumulates further economic activity. At the same time, urban theory also suggests that once cities reach a certain level of size, these agglomeration benefits begin to peter out, while diseconomies rise rapidly. Consequently, we should see an ‘inverted U‐shaped’ pattern of growth with respect to economic size—rates of growth first rise, then fall as size increases. This paper shows that, while such a pattern is largely absent from recent data on growth in metropolitan area population and employment, it emerges strikingly in county‐level data. Copyright © 2002 John Wiley & Sons, Ltd.     

Changes in food provision in Russian households experiencing perestroika

The purpose of this article is to describe how households in Novgorod the Great, Russia, deal with food provision in everyday life. The study focuses on changes experienced in food provision and consumption in Russian society, in order to illustrate how households respond to the transformation towards a market economy. The study reflects women's perspective on food provision. Students from Novgorod the Great visited 105 households and asked the women in the household to answer a questionnaire. Results from the study show that in order to cope with changes in society related to economic reforms, Russian households had changed both their food consumption and food production patterns. There was no big difference between urban and rural households. Nearly all of the households were self‐sufficient in the provision of vegetables and potatoes. Many households had a ‘dacha’ (plot), where they produced most of what they needed. Among the changes experienced during recent years (i.e. during the end of the 1990s), a decade after perestroika was initiated, households mentioned the rise in food prices and the decrease of income. Households reported that they consumed less fruit and/or meat. Some households also mentioned that the quality of nourishment had decreased, thereby indicating lower general quality, lower nutrition value, or less healthy foodstuffs.     

An Empirical Analysis of Entrant and Incumbent Bidding in Road Construction Auctions

This paper explores differences in the bidding patterns of entrants and incumbents in road construction auctions. We find that entrants bid more aggressively and win auctions with significantly lower bids than incumbents. The differences in their bidding patterns are consistent with a model of auctions in which the distribution of an entrant's costs exhibits greater dispersion than that of an incumbent's and relations of stochastic dominance in the distributions do not persist for the entire range of estimated costs. We also find that more efficient firms bid, on average, more aggressively and firms with greater backlogs bid less aggressively.     

Why students take elective business ethics courses: Applying the theory of planned behavior

Despite the prevalence of elective business ethics courses, little research has sought to explain and predict why some students enroll in these courses and while others do not. Using the theory of planned behavior (Ajzen and Madden, 1986) as a theoretical foundation, 178 graduate students in Ireland were surveyed about their intention to sign up for an elective ethics class. Their behavior was measured two months later. The results reveal the power of the theory of planned behavior to explain and predict who takes elective ethics classes.Donna M. Randall is an associate professor and chair in the Department of Management and Systems at Washington State University. Her research interests include business ethics, organizational commitment, and reproductive risk in the work place. Her work has appeared inJournal of Business Ethics, Decision Sciences, Academy of Management Review, Journal of Vocational Behavior, Journal of Business Research, and others.     

DURATION MOMENTS AND YIELD CURVE MOVEMENTS

In this paper we will analyze the relationship between the value and duration moments of a cash flow and movements in the yield curve. We will show that for changes in the yield curve which can be related to tⁿ , the 1st order changes in the net present value of a cash flow are linearly dependent on the n + lth duration moments, and that the 2nd order changes are dependent on the sum of duration moments of order 2 n + 1 and 2 n + 2. We will use this relationship to tilt tracking portfolios so as to protect them against specific changes in the yield curve.     

Negotiation support using the Graph Model for Conflict Resolution

The Graph Model for Conflict Resolution is a flexible methodology for systematically studying strategic conflicts in the real world, and is therefore a natural tool for negotiation support. The basic definitions underlying the graph model are reviewed, and the techniques for analysis and interpretation are discussed. The modeling and analysis of a case study, an international trade negotiation concerning the export of Canadian softwood lumber to the United States, are used to demonstrate the practical application of the Graph Model for Conflict Resolution as a negotiation support tool. The modeling and analysis is carried out using the GMCR software system. The ability of the Graph Model for Conflict Resolution to provide insights and advice to negotiators is emphasized.