Testing Consumer Rationality using Perfect Graphs and Oriented Discs

Given a consumer data-set, the axioms of revealed preference proffer a binary test for rational behaviour. A natural (non-binary) measure of the degree of rationality exhibited by the consumer is the minimum number of data points whose removal induces a rationalisable data-set.We study the computational complexity of the resultant consumer rationality problem in this paper. This problem is, in the worst case, equivalent (in terms of approximation) to the directed feedback vertex set problem. Our main result is to obtain an exact threshold on the number of commodities that separates easy cases and hard cases. Specifically, for two-commodity markets the consumer rationality problem is polynomial time solvable; we prove this via a reduction to the vertex cover problem on perfect graphs. For three-commodity markets, however, the problem is NP-complete; we prove thisusing a reduction from planar 3-SAT that is based upon oriented-disc drawings

Revealed Preference Dimension via Matrix Sign Rank

Given a data-set of consumer behaviour, the Revealed Preference Graph succinctly encodes inferred relative preferences between observed outcomes as a directed graph. Not all graphs can be constructed as revealed preference graphs when the market dimension is fixed. This paper solves the open problem of determining exactly which graphs are attainable as revealed preference graphs in $d$-dimensional markets. This is achieved via an exact characterization which closely ties the feasibility of the graph to the Matrix Sign Rank of its signed adjacency matrix. The paper also shows that when the preference relations form a partially ordered set with order-dimension $k$, the graph is attainable as a revealed preference graph in a $k$-dimensional market.Comment: Submitted to WINE `1

A cross impact methodology for the assessment of US telecommunications system with application to fiber optics development, volume 1

A cross impact model of the U.S. telecommunications system was developed. It was necessary to prepare forecasts of the major segments of the telecommunications system, such as satellites, telephone, TV, CATV, radio broadcasting, etc. In addition, forecasts were prepared of the traffic generated by a variety of new or expanded services, such as electronic check clearing and point of sale electronic funds transfer. Finally, the interactions among the forecasts were estimated (the cross impact). Both the forecasts and the cross impacts were used as inputs to the cross impact model, which could then be used to stimulate the future growth of the entire U.S. telecommunications system. By varying the inputs, technology changes or policy decisions with regard to any segment of the system could be evaluated in the context of the remainder of the system. To illustrate the operation of the model, a specific study was made of the deployment of fiber optics throughout the telecommunications system

The Impact of Individual Expertise and Public Information on Group Decision-Making

In this open-access-book the author concludes that expertise could be the key factor for global and interconnected problems. Experimental results have shown that expertise was a stronger predictor than public information regarding change in behavior and strategy adaption. Identifying non-routine problem-solving experts by efficient online assessments could lead to less volatile system performance, from which all decision-makers could potentially profit

The Impact of Individual Expertise and Public Information on Group Decision-Making

In this open-access-book the author concludes that expertise could be the key factor for global and interconnected problems. Experimental results have shown that expertise was a stronger predictor than public information regarding change in behavior and strategy adaption. Identifying non-routine problem-solving experts by efficient online assessments could lead to less volatile system performance, from which all decision-makers could potentially profit

“Economic man” in cross-cultural perspective: Behavioral experiments in 15 small-scale societies

Researchers from across the social sciences have found consistent deviations from the predictions of the canonical model of self-interest in hundreds of experiments from around the world. This research, however, cannot determine whether the uniformity results from universal patterns of human behavior or from the limited cultural variation available among the university students used in virtually all prior experimental work. To address this, we undertook a cross-cultural study of behavior in ultimatum, public goods, and dictator games in a range of small-scale societies exhibiting a wide variety of economic and cultural conditions. We found, first, that the canonical model – based on self-interest – fails in all of the societies studied. Second, our data reveal substantially more behavioral variability across social groups than has been found in previous research. Third, group-level differences in economic organization and the structure of social interactions explain a substantial portion of the behavioral variation across societies: the higher the degree of market integration and the higher the payoffs to cooperation in everyday life, the greater the level of prosociality expressed in experimental games. Fourth, the available individual-level economic and demographic variables do not consistently explain game behavior, either within or across groups. Fifth, in many cases experimental play appears to reflect the common interactional patterns of everyday life

Relative sales and matching analysis of consumers' brand choices in open settings

The dissertation is a methodological exploration of the relevance of in-store behavioural experiments with relative sales and matching analysis to study consumers' brand choices in real open settings. Three extensive in-store experiments, using alternating treatment design with baseline—testing the effects of Place, Price, and Promotion—were performed in different types of stores (convenience, supermarkets, and budget) in order to investigate the application of the consumer behaviour analysis research framework to real open consumer settings. Four choice-based behaviour analytical analyses—relative sales analysis, amount matching, cost matching and probability matching—were performed on the data when applicable. The results show that the relative sales analyses for the in-store experiments often show orderliness and functionally interesting, and in some cases contradicting, buying behaviour patterns. As for previous correlational consumer behaviour analysis research there is—as should be expected—strong relationship between relative spending and relative buying (amount matching). Although methodologically peculiar, the application of this compelled matching relationship lies in the ability of the free parameters of the generalised matching equation to indicate dimensions of the substitutability of brands to some degree. Cost matching analyses, generally, did not show downward sloping curves, as is sometimes the case in previous studies. It, as well as amount matching, hides functional relations but can be appropriate if represented with a relative sales analysis, which gives clearer picture of behaviour-environment relationships than matching analysis. Results also show that the probability matching analysis, as applied in consumer behaviour analysis, gives misleading results. The ingathering of the study is a new in-store behavioural experimental project which can appraise consumer behaviour analytical advantages, fallacies, and verification seen with the lenses of in-store experimental techniques, and the inclusion of relative sales analysis to real and affluent consumer settings.EThOS - Electronic Theses Online ServiceGBUnited Kingdo