News-based soft information as a corporate competitive advantage
Abstract
This study establishes a decision-making conceptual architecture that evaluates decision making units (DMUs) from numerous aspects. The architecture combines financial indicators together with a variety of data envelopment analysis (DEA) specifications to encapsulate more information to give a complete picture of a corporate’s operation. To make outcomes more accessible to non-specialists, multidimensional scaling (MDS) was performed to visualize the data. Most previous studies on forecasting model construction have relied heavily on hard information, with quite a few works taking into consideration soft information, which contains much denser and more diverse messages than hard information. To overcome this challenge, we consider two different types of soft information: supply chain influential indicator (SCI) and sentimental indicator (STI). SCI is computed by joint utilization of text mining (TM) and social network analysis (SNA), with TM identifying the corporate’s SC relationships from news articles and SNA to determining their impact on the network. STI is extracted from an accounting narrative so as to comprehensively illustrate the relationships between pervious and future performances. The analyzed outcomes are then fed into an artificial intelligence (AI)-based technique to construct the forecasting model. The introduced model, examined by real cases, is a promising alternative for performance forecasting.
First published online 21 November 2019
Keyword : supply chain network, sentimental analysis, decision making, data envelopment analysis
How to Cite
Hsu, M.-F., Chang, T.-M., & Lin, S.-J. (2020). News-based soft information as a corporate competitive advantage. Technological and Economic Development of Economy, 26(1), 48-70. https://doi.org/10.3846/tede.2019.11328
This work is licensed under a Creative Commons Attribution 4.0 International License.
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Hsu, M. F., Yeh, C. C., & Lin, S. J. (2018). Integrating dynamic Malmquist DEA and social network computing for advanced management decisions. Journal of Intelligent & Fuzzy Systems, 35(1), 231241. https://doi.org/10.3233/JIFS-169583
Hsu, M. F. (2019a). Integrated multiple-attribute decision making and kernel-based mechanism for risk analysis and evaluation. Journal of Intelligent & Fuzzy Systems, 36(3), 2895-2905. https://doi.org/10.3233/JIFS-171366
Hsu, M. F. (2019b). A fusion mechanism for management decision and risk analysis. Cybernetics and Systems, 50(6), 497-515. https://doi.org/10.1080/01969722.2018.1541596
Igelnik, B., & Pao, Y. H. (1995). Stochastic choice of basis functions in adaptive function approximation and the functional-link net. IEEE Transactions on Neural Networks, 6(6), 1320-1329. https://doi.org/10.1109/72.471375
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