Application of Machine Learning Models for Predictions on Cross-Border Merger and Acquisition Decisions with ESG Characteristics from an Ecosystem and Sustainable Development Perspective

Abstract

From an ecosystem perspective, mergers and acquisitions (M&A) are one of the key paths for firms to foster complementary sectors and gain complementary assets. From the perspective of sustainable development, M&A can reallocate resources from target to asset to achieve better synergy and prolong the operation of a merged firm. However, M&A activities are characterized by high risk due to the high cost and uncertainty. Thus, a prediction model of M&A decisions is valuable for firms’ strategy design from an ecosystem and sustainable development perspective. By adopting a machine learning technique, this study measured the cross-border M&A decisions by analyzing firm-level cross-sectional data of the global financial marketplace under ecosystem mapping for the application of various country, deal and firm-level indicators related to sustainable development. Our paper can support the hypotheses of corporate governance, ecosystem stakeholder theory, ecosystem risk and institution theory in explaining that firms can increase their success rate of M&A to achieve sustainable development. Methodologically, we used AdaBoost to train several weak classifiers (decision trees) to achieve a strong decision-making model with a large financial transaction database of 215,160 deal activities. Results achieved 80.1% prediction accuracy by using the AdaBoost model through 10-fold cross validation. We found that differences exist on prediction features of M&A with different characteristics of sustainable development. For a robustness check, comparable results were obtained with a support vector machine (SVM) model. By analyses of the features during the cross-border M&A decision-making processing, this study is expected to contribute to the utilization of machine learning in ecosystem studies.

Energy M&A Market in the Baltic States Analyzed through the Lens of Sustainable Development

“…Hong et al [37] Resource reallocation and synergy potential: complementarity for both parties can exert more potential synergy, thereby increasing the capacity of the merged firms to develop sustainably Guo et al [38] Motivation of access to natural resources. Global oil and gas M&A are mostly domestic M&A, because cross-border M&A risks are closely related to many complex political and economic relationships Zhou, Lingling et al [39] Green M&A improves operational efficiency…”

“…Furthermore, pursuit of integration, solidarity, and cooperation between EU countries by consolidating energy policies has the capacity to improve EU-wide energy security. Moving from the industry to the firm level, Hong et al [37] acknowledge the synergy that pursuit of M&A may reallocate resources from target to asset and prolong the operation of the combined firms. Similarly, Zhou, Lingling, et al [39] found that green M&A improves operational efficiency and strengthens firms' development capacity.…”

“…Dasgupta et al [48] acknowledge the potential harm of a path towards digital transition and transformation that involves geomagnetic storms, malware, ransomware, phishing, botnets, etc., and raises significant risks to national security. Moving from industry to the firm level, Hong et al [37] recognize that due to the significant cost and uncertainty, M&A activities involve high risk. Cultural compatibility and corporate culture may serve as potential threats to M&A, especially cross-border M&A, because different cultures may not align common visions regarding certain aspects and subsequently reduce M&A performance [51].…”

Industrial Policy’s Effect on Cross-Border Mergers’ Decisions—Theoretical and Empirical Analysis

“…State-owned enterprises and private enterprises have different sensitivities to industrial policy. Due to the differences in the social responsibilities of SOEs and private firms, there are also significant differences in the selection of industrial policy support targets in M&As [85]. SOEs bear more policy burdens than non-SOEs.…”

Financial Constraint’ Impact on Firms’ ESG Rating Based on Chinese Stock Market

“…Under the impact of the downward pressure on the economy and the impact of "black swan" events such as the new crown epidemic, enterprises are not interested in broadening financing channels, and reducing the demand for financing costs is even stronger. With the implementation of the dual carbon goals and the launch of the national carbon emission trading market, the public's attention to environmental protection and social responsibility has been unprecedentedly high [8], which has also continuously promoted the construction and development of China's ESG information disclosure [9].…”