Consumer Perceptions of Credibility and Selling Intent Among Advertisements,Advertorials, and Editorials: A Persuasion Knowledge Model Approach

This article presents the results of a study of consumer reaction to three different types of information delivery in magazines: editorials, advertorials, and advertisements. The study draws on the Persuasion Knowledge Model to examine the effect of each form of information delivery on source influence, source credibility, perceived selling intent and purchase intention. The analysis indicates that the form of information delivery in print media affects the perceived credibility of the source of the information, the perceived selling intention and the purchase intention. Implications for marketers and policy-makers are also discussed.     

CRIMINAL PERCEPTIONS AND VIOLENT CRIMINAL VICTIMIZATION

This paper explores the relationship between various measures of prior victimization and indicators of both the perceived victimization risk and fear of crime. Equations are specified and estimated both for the fear of crime/perception of risk and for prior victimization. Since prior victimizations are exogenous to the determination of the current assessment of risk or fear of crime, it is possible to isolate the independent effects of victimization and extraneous factors, like racial neighborhood composition, in a recursive model structure. The analysis also examines the contribution that individual victimization and extraneous factors make to the overall gap between average victimization rates and average indicators of fear.
Prior victimization explains some of the rather enormous perception of future victimization, but a sizable gap between perceived risk and actual risk remains. Much of that gap appears to be related to proximity to nonwhites, a possible proxy for racial prejudices and beliefs that nonwhite neighborhoods contribute to heightened crime.     

Value conflicts in computing developments: Developed and developing countries

The author examines the value conflicts engendered by computing developments in two different institutional settings: electronic funds transfer systems and instructional computing in primary and secondary schools. While specific values depend upon culture and upon the character of the particular institutional setting studied, these two cases can serve as instructive points of departure for examining the value conflicts which generally accompany different modes of computerization in other developed and developing countries. In particular, computing developments in Brazil illustrate some of the parallels and contrasts between developed and developing countries.     

Budget Balancedness and Optimal Income Taxation

We make two contributions to the theory of optimal income taxation. First, assuming conditions sufficient for existence of a Pareto optimal income tax and public goods mechanism, we show that if agents' preferences satisfy an extended notion of single crossing called capacity constrained single crossing, then there exists a Pareto optimal income tax and public goods mechanism that is budget balancing. Second, we show that, even without capacity constrained single crossing, existence of a budget balancing Pareto optimal income tax and public goods mechanism is guaranteed if the set of agent types contains no atoms.     

The Private Provision of Public Goods under Uncertainty: A Symmetric-Equilibrium Approach

Various studies have examined whether increased uncertainty about the non‐Nash response of others to an individual's voluntary contribution to a public good affects that individual's contribution so as to mitigate the free‐rider problem. We extend this single‐agent approach to the analysis of a symmetric equilibrium. We provide conditions on group size and endogenous relative risk aversion that imply increased equilibrium contributions in response to greater uncertainty about the productivity of each individual's contribution to the actual level of the public good. These results enable us to broaden the circumstances in which the theory predicts that increased uncertainty reduces free riding.