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...

Innovative technologies such as big data and predictive analytics are facilitating a global revolution in operational management. The present study aims to investigate the extent of their adoption among micro-, small and medium enterprises. The context of choice is Malaysia—a growing economy...

Firms facing complex objectives often decompose the problems they face, delegating different parts of the decision to distinct sub-units. Using comprehensive data and internal models from a large U.S. airline, we establish that airline pricing is not well approximated by a model of the firm as a...