Problem shifts and market research: The role of networks in business relationships

This article discusses changes in approach to the study of business relationships, and sees the paradigm concept as constituting an inadequate basis for describing gradually evolving changes in the perception of business. The frequent references to paradigms appear to focus more on state aspects than on change aspects of theory building. The article attempts to trace some of the changes in the perception of markets preceding the emergence of network theories, and relates the presence of an interactional approach to business studies to the concept of problem shifts (Lakatos). The development of interactional approaches in marketing is seen as representing a shift away from theory building commonly found in economics and organizational theory. Changes in the approach to the study of business relationships are interpreted as theoretical or empirical problem shifts, and are thus related to the a priori and a posteriori relevance of the continual evolution of alternative business theories. The article explores some of the epistemological relevance of the network theories to the study of market relationships, and the potential impact on continual changes in approach to the study of markets.     

On Conformity Testing and the Use of two Stage Procedures

Conformity testing is a systematic examination of the extent to which an entity conforms to specified requirements. Such testing is performed in industry as well as in regulatory agencies in a variety of fields. In this paper we discuss conformity testing under measurement or sampling uncertainty. Although the situation has many analogies to statistical testing of a hypothesis concerning the unknown value of the measurand there are no generally accepted rules for handling measurement uncertainty when testing for conformity. Usually the objective of a test for conformity is to provide assurance of conformity. We therefore suggest that an appropriate statistical test for conformity should be devised such that there is only a small probability of declaring conformity when in fact the entity does not conform. An operational way of formulating this principle is to require that whenever an entity has been declared to be conforming, it should not be possible to alter that declaration, even if the entity was investigated with better (more precise) measuring instruments, or measurement procedures. Some industries and agencies designate specification limits under consideration of the measurement uncertainty. This practice is not invariant under changes of measurement procedure. We therefore suggest that conformity testing should be based upon a comparison of a confidence interval for the value of the measurand with some limiting values that have been designated without regard to the measurement uncertainty. Such a procedure is in line with the recently established practice of reporting measurement uncertainty as “an interval of values that could reasonably be attributed to the measurand”. The price to be paid for a reliable assurance of conformity is a relatively large risk that the procedure will fail to establish conformity for entities that only marginally conform. We suggest a two‐stage procedure that may improve this situation and provide a better discriminatory ability. In an example we illustrate the determination of the power function of such a two‐stage procedure.     

A market model of analysts’ opinions to explain changes in the dispersion of opinions

The demand for and supply of analysts’ opinions in this model yield an equilibrium that demonstrates how the information content of the opinions reacts to changes in exogenous parameters. The model also shows how changes in the parameters make analysts’ opinions more or less dispersed; for example, a decline in investor risk aversion, a decrease in market volatility, and an increase in information costs can lead to analysts’ opinions becoming more similar. Recognizing how exogenous factors can affect the supply and demand of analysts’ opinions gives additional insights into questions concerning what may appear to be herd behavior by analysts and also the relationship between forecast dispersion and information content. (JEL: G29, C71)     

Did the Federal Crop Insurance Reform Act Alter Farm Enterprise Diversification?

We estimate how much United States farms changed enterprise diversification in response to a marked increase in crop insurance coverage brought about by the 1994 Federal Crop Insurance Reform Act, which substantially increased insurance subsidies. The analysis exploits farm‐level panel census data to compare farm‐specific changes in enterprise diversification over time. By examining diversification decisions of the same farms over time, we control for time‐invariant unobserved individual heterogeneity. We then use pooled cross‐sectional data from the United States Department of Agriculture (USDA) Agricultural Resource Management Survey to estimate the relationship between farm diversification and average returns. We find that the insurance subsidies caused a modest increase in enterprise specialisation and production efficiency. Estimated efficiency gains are far less than the subsidies.