Businesses overcome with a high degree of competition that necessitates customer-focused strategies in most industries. In a digitalized business environment, the implementation of such strategies often requires the analysis of customer data. Market basket analysis is a well-known method in marketing that examines basket data to discover useful information about customers’ purchase intentions. The analysis has been a playground for data mining researchers that aim to overcome with its practical challenges. Our study extends the conventional basket analysis by incorporating demographic variables along with purchase transactions. With such modification, we provide an example for the extraction of segment-specific rules that relate product-level purchase decisions with gender, location, and age group. For this purpose, we present a case study on monthly basket data obtained from an e-retailer in Turkey. Our findings demonstrate association rules that might guide marketing practitioners who need to discover segment-specific purchase patterns to designate personalized promotions.

The transportation of non-standard cargoes and related logistics operations are considered as a niche area that requires expertise. Logistics operations of non-standard cargoes must be carried out carefully in order to deliver the cargo on time and in undamaged conditions. Although a significant amount of literature has been published on service provider selection, there is no study in the field of project logistics. For this reason, it is necessary to investigate and determine the selection criteria for project logistics service providers. In the study, fuzzy analytical hierarchy process (FAHP) is used for project logistics service provider selection. The results are that for project logistics management, logistics service providers need to improve vehicle availability, cargo security, on-time delivery, etc. to become more competitive.

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Digital transformation undoubtedly has important implications on the discipline of Operations Management. To unveil these effects and interpret the future research directions requires an in-depth review and analysis of the scientific literature on this research area. This study uses a two-stage approach including Systematic Literature Review and bibliometric analysis to draw a broad perspective on the relationship between DT and OM, reveal the thematic evolution of this research area, and inference about potential future research directions. The scope of the analysis includes the articles drawn from the Web of Science and Scopus databases published between 2007 and 2021 in this research area. With the descriptive analysis of 3021 selected articles to the research sample, top articles, authors, countries, journals, and keywords in this research field were determined. Following the descriptive analysis of the data, the co-occurrence analysis of keywords, thematic evolution, and thematic map analysis was conducted using RStudio and VOSviewer.. All bibliometric analyzes were performed using the R Bibliometrix package.