{'fraction_non_alphanumeric': 0.019327731092436976, 'fraction_numerical': 0.0, 'mean_word_length': 6.047337278106509, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Integrated Business Prestige and Artificial Intelligence for Corporate Decision Making in Dynamic Environments

ABSTRACT A precise measure of corporates’ operating performance plays a critical role in it achieving sustainable development during turbulent financial markets, because bad operating performance has been widely recognized as the main cause of financial crises. Thus, this study introduces an innovative approach to estimate a corporate’s risk (profit) utilizing the variance of the performance function derived from hybridized random projection (RP) and data envelopment analysis (DEA). Furthermore, this study considers firms citation from large number of business news, establish an interfirm network from the firm citation by social network technique and implement to determine the firm’s position embedded in the network that can be viewed as its competitive edge. Finally, this study incorporates industrial position with artificial intelligence (AI)-based techniques to construct the forecasting mechanism for managers to assess their firm's performance ranking. Empirical results reveal that the introduced model is a promising alternative for corporate risk management.