UNPACKING COUNTRY EFFECTS: ON THE NEED TO OPERATIONALIZE THE PSYCHOLOGICAL DETERMINANTS OF CROSS-NATIONAL DIFFERENCES

Most cross-national research examines employees from two or more countries, who are assumed to differ on psychological dimensions in ways that influence their work attitudes or behaviors. However, the psychological dimensions assumed to influence employees’ attitudes or behaviors sometimes have not been operationalized (i.e. measured or manipulated) in previous research. Moreover, even when the relevant psychological dimensions have been operationalized, their role in mediating the relationships between people’s country and their work attitudes and behaviors have not been fully examined. By operationalizing (and appropriately examining the mediating role of) these psychological dimensions, cross-national researchers may make a variety of conceptual contributions, including: (a) accounting for both between- and within-country differences in work attitudes and behaviors; (b) providing greater clarity in accounting for unexpected null effects of country; and (c) providing insight into the basic theoretical processes underlying the relationships between people’s country and their work attitudes and behaviors. Future research opportunities based on operationalizing the psychological dimensions hypothesized to account for country effects also are discussed.     

NATURE OF PROBLEM ILL-STRUCTUREDNESS: IMPLICATIONS FOR PROBLEM FORMULATION AND SOLUTION

The distinction between ill-structured and well-structured decision problems is extended in this paper to include the degree of familiarity that a decision maker has with the initial state of the problem, its desired state, and appropriate transformations for resolving the problem. It is shown that problem ill-structuredness may result from inadequate information regarding any of these components and that the nature of problem ill-structuredness has important implications for problem formulation and solution. A decision tree is presented which represents strategies for either reformulating primary problems of each class of ill-structuredness to a more readily solved form, or solving the problem as initially formulated.     

A COMPARISON OF INVESTMENT ALLOCATION STRATEGIES FOR DISTRIBUTION INVENTORIES

Management goals in distribution inventories are often expressed in terms of the maximum percentage of aggregate sales that should be back ordered. This paper compares several strategies for allocating total inventory investment to each item stocked in order to meet such goals. Computational results are given from a wholesale distribution inventory. The results show that multi-item strategies (which consider the interactions between items) require substantially less investment to meet management goals than strategies that treat each line item independently. All models in this research are approximations based on the assumptions commonly used in practice.     

A COMPARISON OF ALTERNATIVE FORECASTING STRATEGIES FOR MULTI-STAGE PRODUCTION-INVENTORY SYSTEMS

In multi-stage production-inventory systems, the demand for precursor items derives from the demand for successor items at the later stages in the system. This paper presents a method for evaluating the performance of two different strategies for forecasting the demand for precursor items. The dependent strategy relies on successor item forecasts to build a precursor item forecast, while the independent strategy relies on the extrapolation of past precursor demand. An expression indicating the conditions under which one strategy is preferred to the other is developed, and the effect of changing these conditions is illustrated with simulation results.     

PREFERENCE MAPPING OF PERCEIVED INFORMATION STRUCTURE: IMPLICATIONS FOR DECISION SUPPORT SYSTEMS DESIGN

In a recent issue of this journal, Watkins [13] presented an approach for discovery of decision-maker perceptions of the complexity (dimensionality) of information items that might be supplied by a decision support system. Through use of multidimensional scaling and cluster analysis, relatively homogeneous groups of decision makers, sharing common perceptions of various information items, were formed. This prior research was referred to as a first step in suggesting that information reports could be tailored to groups of decision makers classified on the basis of common perceptions of information. The current research extends the prior study by evaluating decision maker preferences for information in a variety of decision-making scenarios in relation to the previously identified perceptions of the information. Based on the results of the study, conclusions are made which suggest that the tailoring of information to groups of decision makers should be based on both perceptions and preferences for information. Even so, it is demonstrated that the decision tasks have an impact on the preferences for information which may affect the attempt to tailor information to groups of decision makers.     

A CANONICAL ANALYSIS OF MANAGERIAL-ENVIRONMENTAL RELATIONSHIPS: IMPLICATIONS FOR METHODOLOGY AND POLICY*

The present study uses canonical analysis to examine the contingency model of organizations in the nursing home field. Data on environmental pressures and managerial practices relevant to the decision-making process are analyzed. Results support the theory that managerial practices are contingent on environmental pressures. The implications of these results for health-care decision makers and for future assessments of managerial-environmental relationships are discussed.     

ON CONSUMER- VERSUS FIRM-LEVEL ANALYSIS OF ADVERTISING EFFECTIVENESS: IMPLICATIONS FOR MODEL BUILDING*

Issues relating to the construction of marketing models are discussed. These include determining the level of aggregation of model construction, specifying the structure of the model, and the aggregation level of data to be employed in estimating model parameters. These issues are addressed through specifying and estimating both consumer-level and firm-level models and comparing the results. An important conclusion is that inferences about consumer behavior should not be drawn from firm-level models since aggregation bias may exist.     

A MULTIATTRIBUTE DECISION-MAKING APPROACH TO THE SELECTION OF AN AUXILIARY DEVICE FOR ICEBREAKERS*

This paper describes the use of multiattribute decision making by the U.S. Coast Guard when choosing the most appropriate auxiliary device to use on an icebreaker. Five different missions of icebreakers are defined, and the objectives and attributes that describe the effectiveness of each auxiliary device in accomplishing these missions are established. For each geographical area of interest, the missions are weighted using the analytical hierarchy process. Also, group utilities are developed for attribute vectors in order to incorporate the judgments of different icebreaker operators.     

BUILDING REPUTATION FOR CONTRACT RENEWAL: IMPLICATIONS FOR PERFORMANCE DYNAMICS AND CONTRACT DURATION

We study how career concerns affect the dynamics of incentives in a multi‐period contract, when the agent's productivity is a stochastic function of his past productivity and investment. We show that incentives are stronger and performance is higher when the contract approaches its expiry date. Contrary to common wisdom, long‐term contracts may strengthen reputational effects whereas short‐term contracting may be optimal when investment has persistent, long‐term effects.     

PERCEIVED INFORMATION STRUCTURE: IMPLICATIONS FOR DECISION SUPPORT SYSTEM DESIGN

Top-level decision making in business organizations is characterized by high degrees of uncertainty, incomplete information, and conflicting objectives. To support top-level decision making effectively, decision support systems (DSSs) have been proposed. Information supplied by a DSS must be selective in that not all possible information sets may be feasibly or economically represented in the data base. This study suggests that discovery of perceptual complexity (dimensionality) of information items, and the subsequent categorization of decision makers having the same perceptions of those information items, is a first step in the ultimate design of an effective DSS. Through the use of multidimensional scaling in a field setting, this study shows the feasibility of creating relatively homogeneous groups of decision makers according to the content and number of dimensions associated with various information items. Further results of the research suggest that information can be tailored to classes of users, which has cost-benefit implications as well as the potential to improve the quality of the resultant decisions.     

A NOTE ON DECISION-MAKING CRITERIA FOR ALGORITHM SELECTION: REDUCING GOAL PROGRAMMING COMPUTATIONAL EFFORT

Most linear goal programming (LPG) algorithms are based on a simplex-type solution method that begins with an initial simplex tableau with solution-set variables (basic variables) consisting of all-negative deviational variables or all-positive deviational variables. This note (1) demonstrates how computational solution effort can be reduced by selecting the appropriate all-negative or all-positive deviational variable algorithm and (2) describes a procedure that can be used to aid decision makers in selecting the appropriate algorithm for all types of applied goal programming (GP) models. Results of this study reveal the procedure as accurate and providing computational time savings when applied to a large sample of GP problems.     

STRUCTURED OBSERVATION OF THE DECISION-MAKING ENVIRONMENT: A RELIABILITY AND VALIDITY ASSESSMENT

Information analysts gather and interpret information regarding organizational decision making. One source of information is the physical environment of the decision maker. A system for structured observation of the environment (STROBE) was developed and was used to gather information on administrators and medical directors of regional blood service organizations in the United States and Canada. Our results suggest that the reliability of STROBE is high and validity is acceptable, suggesting that STROBE may be useful in gathering data usually obtained through interviewing or observing behavior of decision makers.     

ACADEMIC ADMISSIONS STANDARDS: IMPLICATIONS FOR OUTPUT,DISTRIBUTION, AND MOBILITY

We examine the trade‐offs implicit in academic admissions standards when students are charged cost‐based tuition and offered loans that remove liquidity constraints. Lowering entry requirements while holding graduation requirements fixed increases aggregate output and promotes a more equal distribution of wages, but reduces relative income mobility and diminishes the scope for affirmative action. Lowering admissions standards while raising graduation requirements, so that the number of graduates remains constant, has little direct effect on output, distribution, or mobility, but again reduces the scope for affirmative action. Income‐based affirmative action offers a better trade‐off between output and relative mobility than income‐neutral admissions. (JEL: D31, H42, I23, I28, J24)     

STAUNCHING EMIGRATION FROM EAST GERMANY: AGE AND THE DETERMINANTS OF MIGRATION

Following the unification of Germany in 1990, eastern wages and unemployment both rose rapidly. I demonstrate that rising wages reduced eastern emigration greatly, while rising unemployment had little effect. This reflects the behavior of the young, who are very sensitive to source region wages, and relatively insensitive to source unemployment. I show that most of the effect of source unemployment comes from the contemporaneous effect on those laid‐off, who are more likely to be older. I find that, compared to stayers, young emigrants are much more skilled, older emigrants are slightly more skilled, and commuters are not more skilled, as measured by education and pre‐move wages. My conclusions are based on a comparison of results from aggregate inter‐state migration data and individual data from the eastern sample of the German Socio‐Economic Panel for 1990–2000. (JEL: J61, P23)     

A LOGIT-MARKOVIAN MODEL OF CONSUMER PURCHASE BEHAVIOR BASED ON EXPLANATORY VARIABLES: EMPIRICAL EVALUATION AND IMPLICATIONS FOR DECISION MAKING*

This study describes and empirically evaluates an approach to modeling purchase behavior that integrates a Logit-Markov-based multivariate brand-choice model structure with stochastic components. Using actual market data for a frequently purchased consumer product obtained from a consumer purchase panel survey, the paper highlights some marketing applications of the model. Given its general structure, the model can aid marketing managers in defining and evaluating target market segments and in assessing the impact of alternative marketing strategies.     

TOWARD UNDERSTANDING THE CONTENTS OF THE “BLACK BOX” FOR PREDICTING COMPLEX DECISION-MAKING OUTCOMES

The purpose of this research is to show the usefulness of three relatively simple nonlinear classification techniques for policy-capturing research where linear models have typically been used. This study uses 480 cases to assess the decision-making process used by 24 experienced national bank examiners in classifying commercial loans as acceptable or questionable. The results from multiple discriminant analysis (a linear technique) are compared to those of chi-squared automatic interaction detector analysis (a search technique), log-linear analysis, and logit analysis. Results show that while the four techniques are equally accurate in predicting loan classification, chi-squared automatic interaction detector analysis (CHAID) and log-linear analysis enable the researcher to analyze the decision-making structure and examine the “human” variable within the decision-making process. Consequently, if the sole purpose of research is to predict the decision maker's decisions, then any one of the four techniques turns out to be equally useful. If, however, the purpose is to analyze the decision-making process as well as to predict decisions, then CHAID or log-linear techniques are more useful than linear model techniques.     

THE EFFECTS OF TWO NORMATIVE STRUCTURAL INTERVENTIONS ON ESTABLISHED AND AD HOC GROUPS: IMPLICATIONS FOR IMPROVING DECISION MAKING EFFECTIVENESS1

This paper focuses on a direct comparison of consensual, nominal, and conventional decision making techniques in established and ad hoc groups. The impact of the structural interventions on group decision quality and group attitudes is examined, and the appropriateness of the techniques in various situations is discussed.     

DETERMINANTS OF TECHNOLOGY ADOPTION: PEER EFFECTS IN MENSTRUAL CUP TAKE‐UP

We estimate the role of peer effects in technology adoption using data from a randomized distribution of menstrual cups in Nepal. Using individual randomization, we estimate causal effects of peer exposure on adoption. We find strong evidence of peer effects: two months after distribution, one additional friend with access to the menstrual cup increases usage by 18.6 percentage points. Using the fact that we observe both trial and usage of the product over time, we examine the mechanisms that drive peer effects. We show evidence that peers impact learning how to use the technology, but find less evidence that peers impact an individual desire to use the menstrual cup.     

Applications and Implementation THE ALLOCATION OF TIME IN ACADEME: RENT-SEEKING IMPLICATIONS

The allocation of time in academe is influenced by artificial constraints such as wage-fund pools and quotas on promotion and tenure. These constraints affect the potential productivity of professors. An analysis of the time-allocation process and of rent-seeking implications for that process suggests various ways to shift supply curves to counteract the effects of these constraints.