Mitigate cross-market competition caused by the risk of uncertainty and improve firm performance through business intelligence.

In the face of various risks and uncertainties including political instability, technological advancements, and natural disasters, businesses involved in cross-market activities are encountering a more competitive environment. This study investigates the relationship between competitive intensity, business intelligence, internal process efficiency, and the performance of small and medium-sized manufacturing enterprises in China. By incorporating the Technology-Organization-Environment (TOE) framework and Dynamic Capabilities Theory, a research model is developed to demonstrate that competitive intensity improves firms' performance through the utilization of business intelligence capabilities and internal process efficiency.

Revealing the energy paradox: Assessing the asymmetric impact of pandemic uncertainty on consumption of renewable and nonrenewable energy.

Uncertainties have grown around the world during the last few decades. Pandemic uncertainty has a substantial impact on economic activities, which may have a big influence on energy consumption. The goal of this investigation is to appraise the asymmetric influence of pandemic uncertainty on nonrenewable and renewable energy consumption in the top 10 energy consumer economies of the European Union (Germany, Poland, Spain, Netherlands, France, Italy, Belgium, Sweden, Czech Republic, and Finland).

Optimal location of logistics distribution centres with swarm intelligent clustering algorithms.

A clustering algorithm is a solution for grouping a set of objects and for distribution centre location problems. But the common K-means clustering algorithm may give local optimal solutions. Swarm intelligent algorithms simulate the social behaviours of animals and avoid local optimal solutions.