Given the research interest on Big Data in Marketing, we present a research literature
analysis based on a text mining semi-automated approach with the goal of identifying the …

This paper develops a three-step customer clustering based approach to solve two-echelon
location routing problems with time windows. A bi-objective model minimizing costs and …

Nowadays, banks use data mining and business intelligence tools and techniques to
analyze their customers' behavior. Customer segmentation is a widely adopted analytical …

Purpose–Process mining is a research area used to discover, monitor and improve real
business processes by extracting knowledge from event logs available in process-aware …

In logistics operation, delivery times are often uncertain for customers, and accommodating
this uncertainty poses operation challenges as well as extra cost for logistics service …

Partitional data clustering with K-means algorithm is the dividing of objects into smaller and
disjoint groups that has the most similarity with objects in a group and most dissimilarity from …

Exploring and forecasting customers' behavior via time series analysis techniques has
gained much attention in recent years. In this context, distance-based time series clustering …

Online customer reviews complement information from product and service providers. While
the latter is directly from the source of the product and/or service, the former is generally from …

In today's highly competitive market, organizations face significant challenges in accurately
understanding and segmenting customer behavior due to the inherently dynamic and …

Cluster analysis often addresses a specific point in time, ignoring previous cluster analysis
products. The present study proposes a model entitled Cluster Evolution Analysis (CEA) that …