Performance Evaluation of Construction Companies in Malaysia with Entropy-VIKOR Model

Construction industry is an important industry that has an enormous impact on the country’s economic development. Nowadays, the government strives to encourage the construction industry to develop the advanced and modern infrastructure that related to health, transport, education, and housing. As a result, the Malaysian construction sector companies’ financial performance is studied in this paper based on the crucial financial ratios. This paper aims to assess and compare the Malaysian construction sector companies’ financial performance based on Entropy-VIKOR model. In this paper, the listed construction companies in Malaysia are investigated. The findings of this paper demonstrate that ZECON, DKLS, GADANG, TRIPLC, and MELATI are ranked as the top five construction companies based on the proposed model. The importance of this paper is to assess the construction companies’ financial performance as well as identify the weights of the financial ratios in assessing the Malaysian construction sector companies’ financial performance with the proposed Entropy-VIKOR model

Data-Driven Decision Analysis on the Selection of Course Programmes with AHP-TOPSIS Model

The course selection has become a favorite issue among the students who pursue their tertiary study in university nowadays. This is because there are a lot of course programmes offered in this knowledge-based education system. Besides that, other factors such as the financial problem, motivation, self-interest, moral support from friends and family are important criteria in the selection of course programmes. The objective of this study is to propose a data-driven conceptual framework to determine the student preference in the selection of course programmes with Analytic Hierarchy Process Technique for Order of Preference by Similarity to Ideal Solution (AHP-TOPSIS) model. Moreover, this study also aims to determine the priority of the decision criteria that influence the selection of course programmes among the students. In this study, the target respondents are the science stream students from Universiti Tunku Abdul Rahman, Malaysia who provide the inputs as data-driven decision analysis on the selection of course programmes. The results of this study show that medical science is the most preferred course programmes among the students followed by engineering, science and lastly information system. On the other hand, career prospect has been identified as the most concerned decision criterion by the student in the selection of course programmes. This study is significant because it helps to determine the most preferred course programme as well as the most influential criteria in the selection of course programmes among the students with the proposed conceptual framework based on AHP-TOPSIS model

An Optimal Control on the Efficiency of Technology Companies in Malaysia with Data Envelopment Analysis Model

Technology company is a type of business entity that focuses primarily on the development and manufacturing of technology. Technology sector plays an imperative role in the country as technological advancement can lead the country to move forward for continuous improvement. Therefore, efficiency is important in the evaluation on the performance of companies. The efficiency of the companies can be measured by using Data Envelopment Analysis (DEA) model. DEA is a linear programming model which measures the relative efficiency of the companies as the ratio of the sum-weighted outputs to sumweighted inputs. Efficiency is used to describe how well an organizational unit is performing in utilizing resources to generate outputs or outcomes. The objective of this study is to propose a DEA model by using financial ratio to evaluate and compare the efficiency of the companies from the technology sector in Malaysia. Besides that, this study aims to determine the optimal control of inputs and output weights in maximizing the efficiency for each company. The data consists of the listed companies from the technology sector in Malaysia stock market from year 2011 until 2015. In this study, LINGO software is used to solve the DEA model. The major findings of this study indicate that AMTEL, ELSOFT, GRANFLO, GTRONIC, KESM, MPI, UNISEM and VITROX are ranked as efficient companies. This implies that 44% of the listed companies from technology sector in Malaysia stock market are efficient. This study is significant because it is a pioneer study of proposing a DEA model by using financial ratio to evaluate and compare the efficiency of the listed companies from technology sector in Malaysia stock market

The Efficiency and Performance Evaluation of Government-Linked Companies (GLCs) in Malaysia using Data Envelopment Analysis

Efficiency is a vital criterion in global competitive business and sustainable growth. Efficiency has always been reflected in company’s performance based on the existing input or resources available against the optimum output generated. A highly strong organizations capability will attract higher revenue and more investors to the company. The purpose of this study is to evaluate, compare and rank the overall efficiency based on annual report of companies in Malaysia stock market by using Data Envelopment Analysis (DEA). The analysis is carried out on 15 government-linked companies (GLCs) where cross-sectional data between periods of 2013 to 2017 were evaluated. Three efficiency input were considered including return on assets, return on equity and tobin’s q where the outcome or outputs were profitability. The results indicate the significance to the investors as the overall efficiency of the companies is ranked according to several years of reports using the DEA model. The implication of this research would benefit the organizations to perform better

Selection of Materials in Construction Industry with Multi-Criteria Decision Making Models

Construction companies play a central role in the development of a country. The construction products stimulate the growth of private physical structures and public infrastructure for many productive activities such as utilities, commerce, and services. A good material selection is an essential part that needs to be studied in order to come out with a product that is of high quality and safe to be used. As a result, materials selection in the field of construction has also become an interesting topic for many researchers. Based on the previous literature, several multiple criteria decision making (MCDM) models are proposed to choose the best materials for a particular application in recent years. With multiple decision criteria, material selection is treated as an MCDM problem. According to past studies, the researchers have emphasized the integration of MCDM models to tackle complicated decision making problems. MCDM model is a good tool and has been widely proposed in various fields as MCDM models are capable to tackle the decision making problems that are taking multiple decision criteria into consideration. The intended purpose of this paper aims to provide a literature review on the material selection in the field of construction with MCDM models

Financial Network Analysis on the Performance of Companies Using Integrated Entropy–DEMATEL–TOPSIS Model

In this paper, we propose a multi-criteria decision making (MCDM) model by integrating the entropy–DEMATEL with TOPSIS model to analyze the causal relationship of financial ratios towards the financial performance of the companies. The proposed model is illustrated using the financial data of the companies of Dow Jones Industrial Average (DJIA). The financial network analysis using entropy–DEMATEL shows that the financial ratios such as debt to equity ratio (DER) and return on equity (ROE) are classified into the cause criteria group, whereas current ratio (CR), earnings per share (EPS), return on asset (ROA) and debt to assets ratio (DAR) are categorized into the effect criteria group. The top three most influential financial ratios are ROE, CR and DER. The significance of this paper is to determine the causal relationship of financial network towards the financial performance of the companies with the proposed entropy–DEMATEL–TOPSIS model. The ranking identification of the companies in this study is beneficial to the investors to select the companies with good performance in portfolio investment. The proposed model has been applied and validated in the portfolio investment using a mean-variance model based on the selection of companies with good performance. The results show that the proposed model is able to generate higher mean return than the benchmark DJIA index at minimum risk. However, short sale is not allowed for the applicability of the proposed model in portfolio investment

Decision Analysis on the Financial Performance of Companies Using Integrated Entropy-Fuzzy TOPSIS Model

Sustainable economic development plans have been shattered by the devastating COVID-19 crisis, which brought about an economic recession. The companies are suffering from financial losses, leading to financial distress and disengagement from sustainable economic goals. Many companies fail to achieve considerable financial performances, which may lead to unachieved organizational goal and a loss of direction in decision-making and investment. According to the past studies, there has been no comprehensive study done on the financial performance of the companies based on liquidity, solvency, efficiency, and profitability ratios by integrating the entropy method and fuzzy technique for order reference based on similarity to the ideal solution (TOPSIS) model in portfolio investment. Therefore, this paper aims to propose a multi-criteria decision-making (MCDM) model, namely the entropy-fuzzy TOPSIS model, to evaluate the financial performances of companies based on these important financial ratios for portfolio investment. The fuzzy concept helps reduce vagueness and strengthen the meaningful information extracted from the financial ratios. The proposed model is illustrated using the financial ratios of companies in the Dow Jones Industrial Average (DJIA). The results show that return on equity and debt-to-equity ratios are the most influential financial ratios for the performance evaluation of the companies. The companies with good financial performance, such as the best HD company, have been determined based on the proposed model for portfolio selection. A mean-variance (MV) model is used to validate the proposed model in the portfolio investment. At a minimum level of risk, the proposed model is able to generate a higher mean return than the benchmark DJIA index. This paper is significant as it helps to evaluate the financial performance of the companies and select the well-performing companies with the proposed model for portfolio investment