Abstract Growing consumer preference for environmentally conscious brands underscores the importance of sustainable practices in retail. The present study demonstrates the combined impact of carbon regulation policies and customer care service quality on operational efficiency, sustainability, and customer satisfaction within smart multi-channel retailing under an intelligent production process. Owing to the real-world applicability of the model, the demand is considered as a function of advertising, channels’ selling prices, and investment in product greenness. Furthermore, the model incorporates intelligent autonomous inspection to minimize waste generation through proper imperfection detection. Flexibility in the manufacturing process and automation investment increase the profit by 2.36% by reducing waste generation. Numerical experiments and sensitivity analyses ensure enhanced customer care services can increase retail system profitability by 82.13% while advertising and green investment contribute a 57.38% profit increase by increasing product demand. The study’s findings claim that carbon cap-and-trade regulation policy yields the highest profitability. These findings provide remarkable insights for retailers to balance environmental responsibility with economic performance in a multi-channel environment.
Criminal investigations are structured as sequential processes of information production and transmission. Police authorities generate the first formal description of events, which is then transmitted to prosecutors and, ultimately, relied upon by judges when taking precautionary and adjudicative decisions. While this informational chain is institutionally necessary, it introduces a structural asymmetry: downstream actors rarely assess primary evidence independently, but instead form probabilistic beliefs on the basis of progressively filtered information. This article develops a descriptive probabilistic model of informational dependence in criminal investigations. Rather than treating judicial risk as deviation from an objective probability of guilt or as the result of correlated statistical errors, the model conceptualizes belief formation as a function of nested information sets and institutional belief mappings. Informational distortion arises endogenously from filtering, summarization, and reliance across institutional boundaries, even in the absence of bias or strategic manipulation. The analysis shows how early investigative framing can exert disproportionate influence on precautionary decisions taken under conditions of high uncertainty. As institutional reliance intensifies, judicial beliefs become increasingly sensitive to upstream information, reducing the corrective role of independent assessment. The article concludes by outlining a framework of epistemic decoupling aimed at restoring informational independence and mitigating judicial risk.
In the forensic source identification problem, two objects (typically from known and questioned sources) are compared; statistical methods using a score function applied to all pairs of objects may be used for this evaluation. Due to the limited number of samples per source typical of forensic data, a usual assumption is that all within-source scores follow the same distribution of scores and, therefore, can be pooled together to estimate a common within-source distribution of scores. However, this may not be a reasonable assumption, and published tests do not work well for the small sample sizes (per source) commonly encountered in forensic science. Here, we propose and develop a test for deciding if two within-source distributions of scores should not be considered statistically similar, which is applicable to small sample sizes. To complement the developed test, we present an ad-hoc strategy for pooling sources that accounts for significant discrepancies between the within-source distributions of scores. We then evaluate the Type I error and power of this test on several univariate and multivariate distributions. Finally, we apply the test to a forensic research data set consisting of micromorphometric measurements of aluminum powders.
Abstract This commentary summarizes the novel aspects of the paper by Luby and Kadane, discusses specific points raised by the authors, and presents broader considerations, critical aspects, and remaining problems in the field.
