Decision Making by Extracting Soft Information From CSR News Report

Lin, Sin-Jin; Hsu, Ming-Fu

doi:10.3846/tede.2018.3121

Cited by 17 publications

(8 citation statements)

References 58 publications

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“…Even a small improvement in forecasting quality can translate into large future savings for market participants. Due to the essence of textual information, the forecasting model construction should take this kind of information into consideration in order to reach a win-win station [17,63]. According to all of the experimental designs, the proposed model is a promising alternative for corporate operating performance forecasting.…”

Section: The Practical Resultsmentioning

confidence: 99%

Corporate Social Responsibility and Corporate Performance: A Hybrid Text Mining Algorithm

Lee

Huang

2020

Sustainability

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Until now, the works regarding the relationships between corporate operating performance and corporate social responsibility (CSR) could not reach a conclusive result (positive, natural, and negative). This circumstance can be attributed to two main reasons: (1) inadequate performance measurement and (2) ignoring the multi-dimensional nature of CSR. To combat this, we provided a hybrid decision framework that consisted of two main procedures: (1) performance measurement via linear programming algorithm and (2) CSR’s multi-dimensional nature extraction via text mining. By joint utilization of a linear programming algorithm and text mining, we could gain more insights from the outcome. The proposed decision framework, tested by real cases, is a promising alternative method for performance prediction. Managers can take this model as a roadmap and allocate resources to suitable places, as well as reach the goal of sustainable development.

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Section: The Practical Resultsmentioning

confidence: 99%

Corporate Social Responsibility and Corporate Performance: A Hybrid Text Mining Algorithm

Lee

Huang

2020

Sustainability

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“…Initiated by Gabus and Fontela (1972), DEMATEL is a structural technique that analyzes interdependent relationships and models the cause-and-effect relationships between complex elements of a system. It has been widely and successfully applied to resolve real-life problems (Chen et al 2015(Chen et al , 2018Hu et al 2020;Lin and Hsu 2018;Liou et al 2016; Peng and Tzeng 2019; Petrovic and Kankaras 2020; Tzeng and Huang 2012). Given the cluster of intertwined issues in complex systems, DEMATEL is appropriate and suitable for dealing with such problems (Hu et al 2018a, b).…”

Section: Dematelmentioning

confidence: 99%

Identifying the key factors of subsidiary supervision and management using an innovative hybrid architecture in a big data environment

Hsu

Chen

et al. 2021

Financ Innov

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In a highly intertwined and connected business environment, globalized layout planning can be an effective way for enterprises to expand their market. Nevertheless, conflicts and contradictions always exist between parent and subsidiary enterprises; if they are in different countries, these conflicts can become especially problematic. Internal control systems for subsidiary supervision and management seem to be particularly important when aiming to align subsidiaries’ decisions with parent enterprises’ strategic intentions, and such systems undoubtedly involve numerous criteria/dimensions. An effective tool is urgently needed to clarify the relevant issues and discern the cause-and-effect relationships among them in these conflicts. Traditional statistical approaches cannot fully explain these situations due to the complexity and invisibility of the criteria/dimensions; thus, the fuzzy rough set theory (FRST), with its superior data exploration ability and impreciseness tolerance, can be considered to adequately address the complexities. Motivated by efficient integrated systems, aggregating multiple dissimilar systems’ outputs and converting them into a consensus result can be useful for realizing outstanding performances. Based on this concept, we insert selected criteria/dimensions via FRST into DEMATEL to identify and analyze the dependency and feedback relations among variables of parent/subsidiary gaps and conflicts. The results present the improvement priorities based on their magnitude of impact, in the following order: organizational control structure, business and financial information system management, major financial management, business strategy management, construction of a management system, and integrated audit management. Managers can consider the potential implications herein when formulating future targeted policies to improve subsidiary supervision and strengthen overall corporate governance.

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“…If a pre-warning model of financial distress is trustful and reliable, then top-level managers can initiate remedial treatment to prevent the situation from getting worse, and stakeholders can subsequently adjust their investment portfolio so as to maximize their personnel wealth under anticipated risk exposure. Thus, how to establish an accurate forecasting model for managers to form decisions is an urgent and important aspect in finance, especially as today's global economic growth has begun to slow down [17,30].…”

Section: Introductionmentioning

confidence: 99%

An emerging online business decision making architecture in a dynamic economic environment

Lin

Chang

Hsu

2019

IFS

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It is widely acknowledged that a corporate's profitability that decreases dramatically not only threatens both potential and current investors, but also can freeze stock market transactions as well as deteriorate the flow of economic resources. However, far too little attention has been paid to this issue, which also has been deemed as a main trigger for a financial crisis. To confront this problem, a decision support system can be built up to evaluate a corporate's operating performance. Thus, this study introduces a novel architecture for forecasting the online operating performance of a firm when entering data at different time intervals. The introduced architecture is grounded on multiple data envelopment analysis specifications, dynamic fuzzy c-means (DFCM), and extreme support vector machine (ESVM). Because obtaining a comprehensible architecture is essential for achieving high accuracy in today's knowledge-based economy, this study advances the opaque nature of the introduced architecture and extracts the inherent knowledge to represent it in a transparent, human-readable format. The decision logics can be judged or examined by users, which will increase the acceptance rate of the architecture as well as enhance its practical application. Our built-up architecture, tested by real cases, is a promising alternative for financial performance forecasting.

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Decision Making by Extracting Soft Information From CSR News Report

Cited by 17 publications

References 58 publications

Corporate Social Responsibility and Corporate Performance: A Hybrid Text Mining Algorithm

Corporate Social Responsibility and Corporate Performance: A Hybrid Text Mining Algorithm

Identifying the key factors of subsidiary supervision and management using an innovative hybrid architecture in a big data environment

An emerging online business decision making architecture in a dynamic economic environment

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