Data-driven approaches to root cause analysis (RCA) have received attention recently due to their ability to exploit increasing data availability for more effective root cause identification in complex processes. Advancements in the field of causal inference enable unbiased causal investigations...

There is commonly a large volume of data and several types of features in the production process that impact the final product's quality and can be used for process control. Quality control in the production process plays a key role to ensure product quality. So, defect prediction can help...

This study presents a comprehensive and systematic review of the data mining (DM) techniques used to predict employee turnover in the past decade. A total of 36 relevant peer-reviewed studies published between 2012 and 2022 were selected. The results indicate that over 20 DM techniques have been...

In recent years, the advancement of technology, including the Internet, portable machines, decision support systems, computing, and transmission, has driven the concept of big data. This progress has greatly improved the speed of data processing and storage. This study determines how the big...

We nowcast world trade using machine learning, distinguishing between tree-based methods (random forest, gradient boosting) and their regression-based counterparts (macroeconomic random forest, linear gradient boosting). While much less used in the literature, the latter are found to outperform...

The application of machine learning (ML) to big data has become increasingly important. We propose a model where firms have access to the same ML, but incumbents have access to historical data. We show that big data raises entrepreneurial barriers making the creative destruction process less...

Purpose: The objective of the paper is to find trends of research in relic tourism-related topics. Specifically, this paper uncovers all published studies having latent issues with the keywords “relic tourism” from the Web of Science database.Methods: A total of 109 published articles...

The purpose of this study is to analyze innovation activities in the agricultural sector using an association rule mining algorithm to understand the different types of innovation activities and their combinations that ultimately result in product, process, organizational, and marketing...