The effectiveness of personalized e-mail newsletters and the role of personal characteristics

Personalizing communication means creating persuasive messages that refer to aspects of a person's self. Although the use of personalization is increasing, research on its effectiveness is limited and the results are mixed. This study examined the persuasiveness of personalized e-mail newsletters in terms of increased attention, cognitive activity, evaluation, attitude, intention, and behavior by means of an experiment (n=109). Participants randomly received either a personalized or a generic newsletter advertising a sports center. Personalization triggered a more positive evaluation of the message; however, it did not influence the other effect variables. The effects were moderated by consumers' need for uniqueness, trust, and privacy concerns, suggesting that personalization is a good strategy to increase message evaluation only among individuals who have a high need for uniqueness.     

Ethical values and motives driving organic food choice

• The role of ethical motives in consumers' choice of organic food was investigated. A self‐administered questionnaire was conducted on a representative sample of 1283 Norwegian adults. The relations between ethical food choice motives, attitudes and intention to consume organic food was studied by estimating a structural equation model. Environmental and animal rights issues had a strong influence on attitudes towards organic food, suggesting that the more people are concerned about these issues, the more positive attitude they have towards organic food, and the more likely it is that they will consume organic food. Also, political motives had some positive influence on attitudes, while religion was not important as a food choice criterion. Implications of our findings for marketers are discussed.

Copyright © 2006 John Wiley & Sons, Ltd.     

Motivated decision making: effects of activation and self-centrality of values on choices and behavior

Six studies examined the value-behavior relation and focused on motivational properties of values, the self, and value activation. Priming environmental values enhanced attention to and the weight of information related to those values, which resulted in environmentally friendly consumer choices. This only occurred if these values were central to the self-concept. Value-congruent choices were also found in response to countervalue behavior in an unrelated context. Donating behavior congruent with central altruistic values was found as a result of enhanced self-focus, thus demonstrating the importance of the self in the value-behavior relation. The external validity of the value-centrality measure and its distinction from attitudes were demonstrated in the prediction of voting. Values were thus found to give meaning to, energize, and regulate value-congruent behavior, but only if values were cognitively activated and central to the self.     

Belief and the problem of Ulysses and the sirens

While self-contained, this paper is a sequel to my Belief and the Will (1984); see theBibliographical Note at the end of this paper for a survey of the relevant literature since then and supplementary references. I have meanwhile benefitted greatly from Brad Armendt's commentary and Richard Foley's How should future opinion affect current opinion?, both presented at a symposium at the APA Central Division, April 1993.     

Intention-behaviour consistency: Effects of consideration set size,involvement and need for cognition

This study focuses on the strength of the relationship between behavioural intentions and actual behaviour in a multi-alternative choice context. Two separate moderating processes of intention-behaviour consistency were hypothesized, i.e. the amount of reasoning during intention formation, and the degree of confidence in the intention. Involvement (as an issue-specific factor), and need for cognition (as an individual difference factor) were investigated as antecedents of amount of reasoning. confidence in the intention was predicted from the size of the consideration set (i.e. the number of alternatives that one considers for choice), and involvement. The study comprised a longitudinal two-wave survey conducted before and after national elections in The Netherlands, in which pre-election voting intentions were compared with actual voting behaviour. A high degree of intention-behaviour consistency was found, which was significantly related to both amount of reasoning and confidence. The expected relations were found. The results extend current process models of attitude–behaviour relations. Furthermore, the results indicate that processes related to the consideration set size and content account for variance in intention-behaviour consistency in choice contexts that cannot be accounted for by traditional attitude-behaviour perspectives.     

What is morally at stake when using algorithms to make medical diagnoses? Expanding the discussion beyond risks and harms

In this paper, we examine the qualitative moral impact of machine learning-based clinical decision support systems in the process of medical diagnosis. To date, discussions about machine learning in this context have focused on problems that can be measured and assessed quantitatively, such as by estimating the extent of potential harm or calculating incurred risks. We maintain that such discussions neglect the qualitative moral impact of these technologies. Drawing on the philosophical approaches of technomoral change and technological mediation theory, which explore the interplay between technologies and morality, we present an analysis of concerns related to the adoption of machine learning-aided medical diagnosis. We analyze anticipated moral issues that machine learning systems pose for different stakeholders, such as bias and opacity in the way that models are trained to produce diagnoses, changes to how health care providers, patients, and developers understand their roles and professions, and challenges to existing forms of medical legislation. Albeit preliminary in nature, the insights offered by the technomoral change and the technological mediation approaches expand and enrich the current discussion about machine learning in diagnostic practices, bringing distinct and currently underexplored areas of concern to the forefront. These insights can contribute to a more encompassing and better informed decision-making process when adapting machine learning techniques to medical diagnosis, while acknowledging the interests of multiple stakeholders and the active role that technologies play in generating, perpetuating, and modifying ethical concerns in health care.