Organisational buying behaviour in changing times

In a recent paper, Johnston and Lewin (1996) analyse the stream of research on organisational buyer behaviour published over the past 25 to 30 years isolating eight propositions which they encapsulate in their ‘Risk Continuum'. Our paper, reports a comparison between Johnston and Lewin's analysis of the extant literature and current buying practices as revealed by interviews with senior UK buyers. We found that business practice has changed in the intervening years. New, process-driven management styles are changing the way in which UK buyers and suppliers interact, yet work reflecting this change (by, for instance, the European based IMP Group) is under-represented in textbooks and teaching. We question the continuing predominance of the established risk management view of organisational buyer behaviour based upon research conducted in the USA 30 years ago.     

Risk Perception in the U.K. Oil and Gas Production Industry: Are Expert Loss‐Prevention Managers' Perceptions Different From Those of Members of the Public?

This article investigates potential differences in risk perception between experts (loss-prevention managers in the U.K. oil and gas production industry) and nonexperts (managers and students). Extant research on expert versus nonexpert perceptions of risk is reviewed, followed by the present study concerning risk perceptions of seven pen-picture scenarios involving the occurrence of hazardous events in the U.K. oil and gas production industry. In contrast to many of the earlier studies of expert versus nonexpert perceptions of risk, the present analysis concludes that experts did not judge the overall riskiness of the portrayed hazardous events as less risky than the nonexperts. Nevertheless, the experts believe more strongly than our nonexperts that the risks portrayed in the scenarios pose little threat to future generations, are more precisely known, and are relatively controllable. Use of multiple regression analysis to help uncover the basis of overall riskiness assessments for expert and lay respondents was inconclusive, however. Finally, little evidence was found that nonexperts were any more heterogeneous in their risk perceptions than experts. It may be that the nature of the risks assessed in the present study may account for the general lack of clear expert versus nonexpert differences in overall perceptions of the riskiness of hazardous events in the North Sea. Earlier findings of strong expert versus nonexpert differences in risk perception assessed hazards of major public concern. It is inferred that using such extreme hazards may have resulted in an exaggerated view of differences in expert versus public (nonexpert) perception of risk.     

Perceptions of Partners' Attributions for Depression in Relation to Perceptions of Support and Conflict in Romantic Relationships

People's attributions for their own psychological problems are linked to their interpersonal behaviors and attitudes. However, depressed individuals' inferences about their romantic partners' attributions for their depressive symptoms have yet to be studied in relation to their perceptions of relationship quality. This study examined perceived support from and conflict with partners in relation to perceptions of partners' attributions for depression in 165 individuals experiencing at least mild depressive symptoms. After controlling for relevant demographic characteristics, perceived internal/controllable psychological attributions were related to greater perceived conflict and lower perceived support, and perceived controllable biological attributions were related to greater perceived conflict. Perceived external/uncontrollable psychological and uncontrollable biological attributions were unrelated to perceived support and conflict. Findings suggest that perceived attributions may help explain the link between depression, support, and conflict in romantic relationships.     

Insurance Policies for Monetary Policy in the Euro Area

In this paper, we aim to design a monetary policy for the euro area that is robust to the high degree of model uncertainty at the start of monetary union and allows for learning about model probabilities. To this end, we compare and ultimately combine Bayesian and worst‐case analysis using four reference models estimated with pre–European Monetary Union (EMU) synthetic data. We start by computing the cost of insurance against model uncertainty, that is, the relative performance of worst‐case or minimax policy versus Bayesian policy. While maximum insurance comes at moderate costs, we highlight three shortcomings of this worst‐case insurance policy: (i) prior beliefs that would rationalize it from a Bayesian perspective indicate that such insurance is strongly oriented towards the model with highest baseline losses; (ii) the minimax policy is not as tolerant towards small perturbations of policy parameters as the Bayesian policy; and (iii) the minimax policy offers no avenue for incorporating posterior model probabilities derived from data available since monetary union. Thus, we propose preferences for robust policy design that reflect a mixture of the Bayesian and minimax approaches. We show how the incoming EMU data may then be used to update model probabilities, and investigate the implications for policy. (JEL: E52, E58, E61)     

The distribution of cook's d statistic

Cook (1977) proposed a diagnostic to quantify the impact of deleting an observation on the estimated regression coefficients of a General Linear Univariate Model (GLUM). Simulations of models with Gaussian response and predictors demonstrate that his suggestion of comparing the diagnostic to the median of the F for overall regression captures an erratically varying proportion of the values.

We describe the exact distribution of Cook's statistic for a GLUM with Gaussian predictors and response. We also present computational forms, simple approximations, and asymptotic results. A simulation supports the accuracy of the results. The methods allow accurate evaluation of a single value or the maximum value from a regression analysis. The approximations work well for a single value, but less well for the maximum. In contrast, the cut-point suggested by Cook provides widely varying tail probabilities. As with all diagnostics, the data analyst must use scientific judgment in deciding how to treat highlighted observations.     

Quasiextinction Probabilities as a Measure of Impact on Population Growth

A probabilistic language based on stochastic models of population growth is proposed for a standard language to be used in environmental assessment. Environmental impact on a population is measured by the probability of quasiextinction. Density-dependent and independent models are discussed. A review of one-dimensional stochastic population growth models, the implications of environmental autocorrelation, finite versus "infinite" time results, age-structured models, and Monte Carlo simulations are included. The finite time probability of quasiextinction is presented for the logistic model. The sensitivity of the result with respect to the mean growth rate and the amplitude of environmental fluctuations are examined. Stochastic models of population growth form a basis for formulating reasonable criteria for environmental impact estimates.