Abstract Stock Market Forecasting (SMF) has become a spotlighted area and is receiving
increasing attention due to the potential that investment returns can generate profound …

Data envelopment analysis (DEA) is a widely used mathematical programming approach for
assessing the efficiency of decision-making units (DMUs) in various sectors. Inverse DEA is …

This paper identifies the causal effect of low-carbon city pilot (LCCP) policy on carbon
emission efficiency (CEE). Specifically, we first develop a general nonconvex metafrontier …

In recent years there has been an exponential growth in the number of publications related
to theory and applications of Data Envelopment Analysis (DEA). Charnes, Cooper, and …

The evolution of the COVID‐19 pandemic is highly unpredictable; however, its impacts are
limited to neither a single sector nor a single country. This study evaluates the performance …

In recent years, globalization has highlighted the vital role of sustainable supply chains
(SSCs) in the development of organizations and production systems to increase profits. The …

Given a (combinatorial) optimization problem and a feasible solution to it, the corresponding
inverse optimization problem is to find a minimal adjustment of the cost function such that the …

This review introduces the history and present status of data envelopment analysis (DEA)
research, particularly the evaluation process. And extensions of some DEA models are also …

Mergers and acquisitions (M&A) in the hospitality sector involve consolidating assets among
hotels through partnerships. While data envelopment analysis (DEA) has been widely used …

Strategic alliances and partnerships including mergers and acquisitions have been a
growing trend in many industries in the past decades. There are many studies in the …