Identifying Perverse Incentives in Buyer Profiling on Online Trading Platforms

With advance machine learning and artificial intelligence models, the capability of online trading platforms to profile consumers to identify and understand their needs has substantially increased. In this study, we use an analytical model to study whether these platforms have an incentive to profile their customers as accurately as possible. We find that “payments-for-transactions” platforms (i.e., platforms that charge for transactions that occur on the platform) indeed have such incentives to accurately profile the customers. However, surprisingly, “payments-for-discoveries” platform (i.e., platforms that charge customers for discoveries) have a perverse incentive to deviate from accurate consumer profiling. Our study provides insights into underlying mechanisms that drive this perverse incentive and discuss circumstances that lead to such a perverse incentive.

A Governmentality of Online Gambling: Quebec’s Contested Internet Gambling Website Blocking Provisions

This article examines Canada’s first internet gambling website blocking scheme, which was enacted in Quebec as part of the implementation of the province’s 2015 budget. Using qualitative research methods, the article illustrates the complexities of regulating online gambling. Influenced by critical sociological and anthropological studies of gambling, and taking a socio-legal, governmentality perspective, it shows how socio-legal studies can illuminate research on the regulation of gambling, and how the study of online gambling can, as a sentinel site for the regulation of online consumption, contribute to the development of socio-legal studies. Our analysis shows that the governmentality of online gambling is framed so as to exclude 1) a range of risks (e.g., related to consumer profiling and the capacity to stimulate “addictive consumption”), 2) the heterogeneity of everyday experience that connects online gambling with online addictive consumption more generally, and 3) a range of possibilities for governing online gambling otherwise.

Food literacy and food choice – a survey-based psychometric profiling of consumer behaviour

PurposeThe purpose of this paper is to explore the associations between food literacy, consumer profiling and purchasing behaviour in a sample of Italian consumers.Design/methodology/approachParticipants (N = 194) completed an online survey including personal data, two questionnaires on purchase behaviour and food consumption, the General Trust Scale (GTS), a questionnaire assessing individual chronotype and two scales about food literacy: one investigating nutritional knowledge (short food literacy questionnaire, SFLQ) and the other focussing on procedural skills (self-perceived food literacy scale, SPFL). Associations between food literacy, consumer profiling and purchase behaviour were analysed with linear regression models.FindingsParticipants with specific education in nutrition reported higher scores in food literacy. The final score of food literacy was predicted by a greater attention to nutritional content and nutritional properties of products. Women paid more attention to nutritional properties than men, and they obtained higher scores in SFLQ. Evening types obtained lower scores in SFPL compared to intermediate and morning chronotypes. Body mass index (BMI) was negatively correlated to SPFL score, while it was associated with the easy availability of a product, so that obese (BMI ≥ 30) subjects considered the easy availability of a product more important compared to non-obese ones (BMI < 30).Originality/valueThis study investigates the influence of personal and psychometric variables of consumer profiling on food literacy and consequently on purchase behaviour, paving the way for implementing healthier food consumption policies. These findings reinforce the primacy of specific education in building healthy eating habits.

Implementation of Data Mining Technique for Performance of WFH and WFO Agents Using the K-Means Method Case Study Study of PT. Infomedia Telkom Consumer Profiling Services

Outbound Call Center PT. Infomedia, consumer profiling service PT. Telkom during the pandemic period divided its agents into 80% WFH agents (Work at Home) and 20% agents WFO (Work from Office). For the division of the working mechanism, it is necessary to measure its performance. In the discussion of this paper, we will discuss the measurement with the application of data mining using the K-Means method, so it is hoped that it will provide an overview, how the cluster of each WFH or WFO agent in terms of performance. The results of this discussion indicate that there is a significant difference between the performance of WFH and WFO Agents.