EVALUATING THE ECONOMIC COST OF ENVIRONMENTAL MEASURES IN PLANTATION HARVESTING THROUGH THE USE OF MATHEMATICAL MODELS

An important issue being discussed for Chilean pine plantation policies is the application of environmental protection measures when managing its timber areas. Typical measures, already in place in more developed countries, include imposing riparian strips and protecting fragile soils from the use of heavy machinery. While environmental protection measures have been considered vital for decades, so far there has been almost no attempt to quantify both the benefits and costs of these measures. This paper attempts to measure the costs associated with the main measures which can help both the forestry firms and the government evaluate the cost impact of the new environmental protection regulations being studied. The analysis for different environmental scenarios is carried out by modifying a mixed integer LP, currently used for tactical planning by one forestry firm.     

THE INEFFICIENCY OF WORKER TIME USE

Much work is carried out in short, interrupted segments. This phenomenon, which we label task juggling, has been overlooked by economists. We study the work schedules of some judges in Italy documenting that they do juggle tasks and that juggling causally lowers their productivity substantially. To measure the size of this effect, we show that although all these judges receive the same workload, those who juggle more trials at once instead of working sequentially on few of them at each unit of time, take longer to complete their portfolios of cases. Task juggling seems to have no adverse effect on the quality of the judges' decisions, as measured by the percent of decisions appealed. To identify these causal effects we estimate models with judge fixed effects and we exploit the lottery assigning cases to judges. We discuss whether task juggling can be viewed as inefficient, and provide a back‐of‐the‐envelope calculation of the social cost of longer trials due to task juggling.     

THE LOT OF THE UNEMPLOYED: A TIME USE PERSPECTIVE

This paper provides new evidence on the time use of employed and unemployed individuals in 14 countries. We devote particular attention to characterizing and modeling job search intensity, measured by the amount of time devoted to searching for a new job. Job search intensity varies considerably across countries, and is higher in countries that have higher wage dispersion. We also examine the relationship between unemployment benefits and job search.     

OPTIMAL PLANNING: THE USE OF SALES FORECASTS

Budgets are established and decisions in a firm are made on the basis of the sales forecast. In the majority of firms this forecast is a single value estimate of sales. The decisions made on the basis of the single value estimate frequently fall short of optimal strategies because of costs that occur when actual sales differ from forecast sales. These costs, measured in terms of opportunity losses, can be minimized when considered in conjunction with a probability distribution of sales. Three methods for determining the probability distribution of sales are considered in this paper. These are regression analysis Schlaifer's approach for establishing a subjective distribution, and Bayesian regression. The use of the distribution in conjunction with linear and quadratic loss functions is illustrated.     

THE FAILURE TO PREDICT THE GREAT RECESSION—A VIEW THROUGH THE ROLE OF CREDIT

Much has been written about why economists failed to predict the latest crisis. Reading the literature, it seems that this crisis was so obvious that economists must have been blind not to see it coming. We approach this failure by looking at one of the key variables in this analysis, the evolution of credit. We compare the conclusions reached in the recent literature with those that could have been drawn from an ex‐ante analysis. We show that the effect of credit on the business cycle cannot be exploited from a policymaker's point of view.     

ON THE USE OF VERBAL PROTOCOLS IN CONJOINT ANALYSIS STUDIES

A recent study by Olshavsky and Acito helped gain insight into (a) the decision process used by respondents when asked to do a conjoint task, (b) the predictive validity of conjoint models compared to models derived from verbal protocols, and (c) the reasons for prediction errors. In this article, the author argues that the Olshavsky and Acito results do not lead one to believe that the compensatory conjoint models can be potentially more misleading than models that try to represent more accurately the underlying evaluation process with noncompensatory and compensatory rules. Hence, it does not seem necessary to try to identify noncompensatory rules in a conjoint study.     

THE USE OF MODERATED REGRESSION IN JOB REDESIGN DECISIONS*

This paper describes the use of moderated regression in job redesign decisions. The procedures outlined are intended to augment the job redesign strategy described by Hackman and his colleagues. Different regression models based on a theory of job design are shown to lead to different job redesign decisions. Comparisons are also made between the moderated regression procedures and the more commonly used subgroups analysis.     

PERFORMANCE DIFFERENCES IN THE USE OF GRAPHIC AND TABULAR DISPLAYS OF MULTIVARIATE DATA

It has been suggested that graphically displayed multivariate data help decision makers better understand information they are called on to analyze. This study compares judgments made from one recently suggested multivariate display technique with judgments made from traditional tabular displas of financial figures. Significant differences in task performance are found to be related both to differences in the stimulus sets and to individual differences among the subjects. Our results suggest that the relative contribution of graphic displays to decision making may vary considerably from situation to situation.     

EXPERIENCES WITH THE USE OF SUPPLY CHAIN MANAGEMENT SOFTWARE IN EDUCATION

This paper discusses four experiments and experiences with the use of supply chain management software, in this case the CAPS Logistics software, at different levels of undergraduate and graduate education at the School of Industrial and Systems Engineering at the Georgia Institute of Technology. We hope that the readers will get an idea of the commitment and resources necessary to integrate supply chain software into the classroom as well as the potential rewards.     

REALIZATION OF THE VIRTUAL ENTERPRISE PARADIGM IN THE CLOTHING INDUSTRY THROUGH E‐BUSINESS TECHNOLOGY

This paper presents a methodology and a case study for supply chain management in the clothing industry that makes extensive use of the virtual enterprise paradigm. The main research goal was to design and implement a prototype e‐business software component and carry out tests in several industrial users. The research effort resulted in the extended production data management system (epms), which supported the business processes of customer order management, subcontractor selection, and multi‐site/multi‐firm production orders release. The enablers of this software application were business‐to‐business (b2b) e‐commerce technologies in the operating context of application service providers (asps).     

USE OF FEEDBACK AND REINFORCEMENT TO INCREASE THE TELEPHONE REPORTING OF INDEPENDENT AUTOMOBILE APPRAISERS

This case study describes a behavioral management program to modify the performance of employees of independent appraisal firms involved in the processing of insurance claims. Delays in appraising and reporting automobile damages had produced a corresponding delay in the payment of claims. The latter slowed the productivity of the claim department and often led to customer dissatisfaction, complaints and time consuming telephone conversations to explain the delay. Although appraisers were required by a contractual agreement. to report financial estimates of damages within twenty-four hours after receiving a request, informal observations indicated that appraisal forms typically failed to meet this criteria.     

REDUCTION IN THE LONG‐TERM UNEMPLOYMENT OF THE ELDERLY: A SUCCESS STORY FROM FINLAND

In several European countries the elderly unemployed are allowed to collect unemployment benefits up to a certain age limit, after which they can retire via some early retirement scheme. In Finland the eligibility age of persons benefiting from this kind of scheme was raised from 53 to 55 in 1997. We consider layoff risks, unemployment durations, and the exit states before and after the reform. Since the reform the group aged 53–54 has had a lower risk of unemployment, shorter unemployment durations, and higher exit rates to employment, and it is almost indistinguishable from the group aged 50–52. We estimate that the amount of unemployment benefits saved due to the reform is close to $100 million for each age cohort turning 53. (JEL: J64, J26, C14, C41)     

The leadership of emergence: A complex systems leadership theory of emergence at successive organizational levels

Complexity science reframes leadership by focusing on the dynamic interactions between all individuals, explaining how those interactions can, under certain conditions, produce emergent outcomes. We develop a Leadership of Emergence using this approach, through an analysis of three empirical studies which document emergence in distinct contexts. Each of these studies identifies the same four “conditions” for emergence: the presence of a Dis-equilibrium state, Amplifying actions, Recombination/“Self-organization”, and Stabilizing feedback. From these studies we also show how these conditions can be generated through nine specific behaviors which leaders can enact, including: Disrupt existing patterns through embracing uncertainty and creating controversy, Encourage novelty by allowing experiments and supporting collective action, Provide sensemaking and sensegiving through the artful use of language and symbols, and Stabilize the system by Integrating local constraints. Finally, we suggest ways for advancing a meso-model of leadership, and show how our findings can improve complexity science applications in management.     

Concepts,Theory, and Techniques ON THE USE OF THE GEOMETRIC MEAN IN LONG-TERM INVESTMENT

Application of the geometric mean to holding-period returns is discussed from a statistical theory standpoint. The population geometric mean is considered a parameter of the probability distribution of returns its relationship to moments of the distribution is discussed. The sample geometric mean and its relation to sample moments is assessed through its sampling distribution it is viewed as an estimator of the population geometric mean. For application to long-term investment where a geometric mean is maximized, the distributional properties of the geometric mean should be used. The terms statistic, approximation, and parameter are differentiated.     

AN ANALYSIS AND DISCUSSION OF THE OPTIMIZED PRODUCTION TECHNOLOGY SOFTWARE AND ITS USE

During the 19805 much attention, both pro and con, was directed toward optimized production technology (OPT). Criticism was directed at the proprietary nature of the scheduling algorithms within the software. Despite these criticisms, many large companies installed OPT. Little has been written on how the software is constructed and operates. This article introduces the software, provides a discussion of how it interfaces with management, and how various algorithms are imbedded in the software function. Last, a survey of companies that had implemented the software revealed that the major users are in the automotive industry.     

PREDICTING STOCK MARKET BEHAVIOR THROUGH RULE INDUCTION: AN APPLICATION OF THE LEARNING-FROM-EXAMPLE APPROACH*

An artificial intelligence-based rule-induction approach to the analysis of stock market prediction is presented. A single investment analyst was used as the expert for this study. Predicting intermediate fluctuations in the movement of the market for nonconservative investors was selected as the decision to analyze. Commercially available rule-induction software was used to generate rules that predicted the market calls of the market analyst and the actual movements of the market. Rules predicting actual market movement performed better than rules predicting the analyst's calls and better than the analyst himself. Such an approach may prove useful in designing a decision support system for market analysts or in improving the decision-making processes of such analysts. The dynamic nature of the stock market represents a substantially different decision environment than those previously analyzed by learning-from-example (LFE) techniques. This study provides insights into the limits and applications of LFE approaches.     

SOME CAUTIONARY NOTES ON THE USE OF CONJOINT MEASUREMENT FOR HUMAN JUDGMENT MODELING*

Conjoint measurement has been suggested as a methodology that might be useful in assisting research concerned with the identification of the structural form of a judge's model. This paper synthesizes the results of some recent research that examined the robustness of this methodology. This research suggests that conjoint measurement has three major weaknesses: (1) certain biases exist when diagnosing model structure, (2) model diagnosis is limited to a small set of potential models, and (3) error substantially compromises conjoint measurement's ability to diagnose model structure. An empirical example that demonstrates some of the difficulties of using this methodology with experimental data is also presented.     

THE USE OF INDUSTRIAL SOFTWARE TO CREATE EXPERIENTIAL LEARNING ACTIVITIES IN OPERATIONS MANAGEMENT COURSES

Computer-based manufacturing planning and control (MPC) systems are widely used in industry to gain competitive advantage through integration and coordination of managerial activities. In collegiate business schools, important operations management activities are taught and studied, often by sequential examination of discrete topics such as aggregate production planning, master production scheduling, capacity planning, material planning, and production activity control. This paper explores the potential use of industrial MPC software in the classroom to create experiential learning activities that address the dynamic and integrative nature of operations management. Experiences with this pedagogical approach over the past decade are reported.     

THE USE OF FORECAST ERROR MEASURES AS SURROGATES FOR AN ERROR COST CRITERION IN THE PRODUCTION SMOOTHING PROBLEM

This paper presents research on the problem of selecting a proper surrogate for a forecast error cost criterion in the production smoothing problem. Various forecast models estimated future selected demand process values. Resultant error costs were computed and the coincidence of the selection of a forecast model on the basis of least error cost and the various error measures was noted. The error measures used were the mean absolute deviation, average algebraic error(bias), and the mean squared error. Computations necessary to develop the mathematical form of the error cost criterion are presented in an Appendix. Also presented are the penalty costs of using an error measure as a surrogate for an error cost criterion.