Consumer Expectations on Supermarkets in Organized Retailing

The study emphasise on the consumer expectations on supermarkets in organised retailing and factors which acts as driving force for consumers to opt for the same, with reference to Chennai city. The sample size is 120 respondents who were retail customers of Supermarkets under Non- Probability Judgment Sampling method. The growth of Supermarkets of India in recent years has been witnessed due to increased consumer expectations. As most of the retail segments try to find their way to come out of the COVID-19 pandemic, it must be noticed that the consumers are already evolving at great speed in their expectations in all fields. At the pandemic situations, people try to venture out most importantly for essential items with the available outlets, taking care of all safety measures. The immediate next option available for consumers is online shopping. The blowout of virus has not only changed the way how consumers shop, but also their buyer behaviour pattern and what they actually expect from retailers. By 2025, India is expected to become the world’s third largest economy as it is experiencing the world’s fastest growing economies. According to various reports, it is known that these new spending and shopping patterns is expected to continue even after the crisis comes down. With more developments as well as challenges in the field of organized retailing, consumer preferences are changing from region to region.

The Development of Spatial–Temporal, Probability, and Covariation Information to Infer Continuous Causal Processes

This paper considers how 5- to 11-year-olds’ verbal reasoning about the causality underlying extended, dynamic natural processes links to various facets of their statistical thinking. Such continuous processes typically do not provide perceptually distinct causes and effect, and previous work suggests that spatial–temporal analysis, the ability to analyze spatial configurations that change over time, is a crucial predictor of reasoning about causal mechanism in such situations. Work in the Humean tradition to causality has long emphasized on the importance of statistical thinking for inferring causal links between distinct cause and effect events, but here we assess whether this is also viable for causal thinking about continuous processes. Controlling for verbal and non-verbal ability, two studies (N = 107; N = 124) administered a battery of covariation, probability, spatial–temporal, and causal measures. Results indicated that spatial–temporal analysis was the best predictor of causal thinking across both studies, but statistical thinking supported and informed spatial–temporal analysis: covariation assessment potentially assists with the identification of variables, while simple probability judgment potentially assists with thinking about unseen mechanisms. We conclude that the ability to find out patterns in data is even more widely important for causal analysis than commonly assumed, from childhood, having a role to play not just when causally linking already distinct events but also when analyzing the causal process underlying extended dynamic events without perceptually distinct components.

The Linda who skipped the logic classes

The letter points to a logical mistake found in “The conjunction fallacy in probability judgment” published by Tversky and Kahneman. Currently, at least 5,100 research papers reference this work, and an entire field of associated studies has been created based on the paper. These works assume the correctness of the original publication and reproduce the error without due critical analysis.

Higher Risk Taking and Impaired Probability Judgment in Behavioral Addiction

Background Accumulating evidence suggests that deficits in decision-making and judgment may be involved in several psychiatric disorders, including addiction. Behavioral addiction is a conceptually new psychiatric condition, raising a debate of what criteria define behavioral addiction, and several impulse control disorders are equivalently considered as types of behavioral addiction. In this preliminary study with a relatively small sample size, we investigated how decision-making and judgment were compromised in behavioral addiction to further characterize this psychiatric condition. Method Healthy control subjects (n = 31) and patients with kleptomania and paraphilia as behavioral addictions (n = 16) were recruited. A battery of questionnaires for assessments of cognitive biases and economic decision-making were conducted, as was a psychological test for the assessment of the jumping-to-conclusions bias, using functional near-infrared spectroscopy recordings of prefrontal cortical (PFC) activity. Results Although behavioral addicts exhibited stronger cognitive biases than controls in the questionnaire, the difference was primarily due to lower intelligence in the patients. Behavioral addicts also exhibited higher risk taking and worse performance in economic decision-making, indicating compromised probability judgment, along with diminished PFC activity in the right hemisphere. Conclusion Our study suggests that behavioral addiction may involve impairments of probability judgment associated with attenuated PFC activity, which consequently leads to higher risk taking in decision-making.

Improving Probability Judgment in Intelligence Analysis: From Structured Analysis to Statistical Aggregation

As in other areas of expert judgment, intelligence analysis often requires judging the probability that hypotheses are true. Intelligence organizations promote the use of structured methods such as “Analysis of Competing Hypotheses” (ACH) to improve judgment accuracy and analytic rigor, but these methods have received little empirical testing. In this experiment, we pitted ACHagainst a factorized Bayes theorem (FBT) method, and we examined the value of recalibration (coherentization) and aggregation methods for improving the accuracy of probability judgment. Analytic techniques such as ACH and FBT were ineffective in improving accuracy and handling correlated evidence, and ACH in fact decreased the coherence of probability judgments. In contrast, statistical post-analytic methods (i.e., coherentization and aggregation) yielded large accuracy gains. A wide range of methods for instantiating these techniques were tested. The interactions among the factors considered suggest that prescriptive theorists and interventionists should examine the value of ensembles of judgment-support methods.