HuoMing Wang

Mr. HuoMing Wang


Research Focus & Metrics

Academic Career Length

6Years (2021-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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11 March 2021 in Sustainability
Verified
Journal Article
Open access
PDF file
KCKuo-Chih Cheng
Kuo-Chih Cheng
MHMu-Jung Huang
Mu-Jung Huang
CFCheng-Kai Fu
Cheng-Kai Fu
KWKuo-Hua Wang
Kuo-Hua Wang
HWHuoMing Wang
HuoMing Wang
LLLan-Hui Lin
Lan-Hui Lin
This study attempts to integrate the decision tree algorithm with the Apriori algorithm to explore the relationship among financial ratio, corporate governance, and stock returns to establish a stock investment decision model. The sports and leisure related industries are employed as the research target. The data are collected and processed for generating decision tree and association rules. Based on the analysis outcome, an investment decision model is constructed for investors expecting to decrease their investment risks and further increase their profits. This stock investment decision model is one type of multiple-criteria decision-making model. This study makes three critical contributions to investors. (1) It proposes a systematical model of exploring related data through the decision tree algorithm and the Apriori algorithm to reveal the implicit investment knowledge. (2) An effective investment decision model is established and expected to provide a reference basis during stock-picking decisions. (3) The investment decision model is enhanced with implicit rules found among variables using association rules.

18 May 2021 in Sustainability
Verified
Journal Article
Open access
PDF file
MHMu-Jung Huang
Mu-Jung Huang
KCKuo-Chih Cheng
Kuo-Chih Cheng
SCShao-Hsi Chung
Shao-Hsi Chung
HWHuoMing Wang
HuoMing Wang
KWKuo-Hua Wang
Kuo-Hua Wang
As the relationship between the execution of budget participation and innovation performance is still full of controversy, and the innovation capability formed by the important control elements of the organization is the key to bring about product innovation performance, this study aims to explore the impact of the formation of product innovation capabilities on product innovation performance under the demand for budget participation. This study proposes the concept of budget participation capacity configuration (BPCC), which is the integration of procedural justice, self-efficacy, and trust in superiors. This study adopted a questionnaire survey to collect sample data from production managers of the electronics-related companies listed on the Taiwan Stock Exchange and employed structural equation modeling to verify measurement model fit and research hypotheses. The study results present that budgeting participation requirement does not directly affect product innovation performance and confirms that the three organizational control elements together constitute BPCC, which plays a fully intermediary role between budget participation requirement and product innovation performance. The contribution of this research for academic theory is to put forward an explanation of the budget participation-innovation performance dispute, and propose an integrated viewpoint for organizational control elements instead of fragmental studies in the past. For practice, this research provides new evidence for budget participation requirements and sources of innovation capabilities.

27 May 2021 in Sustainability
Verified
Journal Article
Open access
PDF file
MHMu-Jung Huang
Mu-Jung Huang
KCKuo-Chih Cheng
Kuo-Chih Cheng
CHChing-Ju Huang
Ching-Ju Huang
KLKun-Meng Lin
Kun-Meng Lin
HWHuoMing Wang
HuoMing Wang
MWMing-Cheng Wu
Ming-Cheng Wu
In order to reconsider the changes of adjustment speed caused by the recapitalization cost, this research adopted dynamic capital structure theory with adjustment speed as one of the independent variables to analyze the relationship between capital structure and company performance. Instead of applying the commonly used regression models, this research used the decision tree C4.5 algorithm and association rules of priori algorithm. Taking the predictive models created by the decision tree as the main result and supporting it with association rules which help to explain the relationships between capital structure and company performance, this research shows how capital structure influences company performance. As the result presents, a company tends to have better performance when its debt ratio is low, and Tobin’s Q and ROA will turn worse as the ratio gets higher. However, maybe because of the financial leverage, ROE will not decrease when the ratio is high but will increase instead. In addition, this research found out that adjustment speed is negatively related to company performance, meaning that even though a company is more flexible in adjusting itself, it might still perform badly since it is deviating from its optimum leverage. This research found that not only capital structure, but other variables such as price-earnings ratio, research and development expense ratio, and dividend payout ratio also determine a company’s performance.