Using a decision-making process to evaluate efficiency and operating performance for listed semiconductor companies

Today’s high-tech industries face increasing competition and challenges. Thus, for hightech companies, making effective use of resources to enhance business performance and maintain the competitive advantage in the market has become increasingly important. Therefore, this study aimed to design a decision-making model for evaluating the efficiency and operating performance of Taiwan’s listed semiconductor companies in 2010 to provide a basis for improving business performance. In view of this, this study combines data envelopment analysis (DEA) and improved grey relational analysis (IGRA) as efficiency tools to measure relative efficiencies; the semiconductor companies are divided into two groups, efficient and inefficient. We then integrate the multiple criteria decision making (MCDM) method (e.g. VlseKriterijumska Optimizacija I Kompromisno Resenje, VIKOR), IGRA and the entropy weight method to evaluate the operating performance of the efficient and inefficient groups, respectively. Establishing a reasonable, objective and valid evaluation model to measure semiconductor companies’ operating efficiency can provide company managers, investors and policy makers with a reference for performance evaluation. First published online: 20 Jun 201

A hybrid multiple criteria decision-making model for investment decision making

Investments are accompanied by risks. How investors choose the right investment tools to assist in the selection of investment targets is a topic worth exploring. Therefore, this study aimed to develop an investment decision-making process to deal with this issue. Firstly, we proposed a globalized modified grey relational analysis to select the representative indicators including the financial indicators and risk measurement indicators. Then we combined financial and risk evaluation indicators, and divided companies into low, moderate and high-risk groups through the grey clustering analysis. Finally, Vlse Kriterijumska Optimizacija Kompromisno Resenje (VIKOR) combined with the grey entropy weighting method was applied to business performance evaluation and sorting of each grouping. In order to verify this study, a combination of 21 financial ratios and four risk indicators was utilized in order to verify the evaluation and decision-making process in the operating performance of 62 listed opto-electronics companies in Taiwan. The results of ranking the operating performance for each group can be made available to company managers as a reference in order to enhance competitiveness and business performance. The results can also be used as the basis for decision-making to aid investors who are facing many investment portfolios

A Novel Evaluation Approach for Tourist Choice of Destination Based on Grey Relation Analysis

The decision-making process of choosing an ideal tourism destination is influenced by a number of psychological and nonpsychological variables. Tourists need a method to quickly and easily select a suitable destination. Driven by this practical decision issue, a novel approach of tourist destination evaluation, grey relation analysis (GRA), is developed and applied to the ranking evaluation of Taiwan tourism destinations in China. In the evaluating process, we apply entropy to calculate the weight of each index, which is a more objective method of calculating weights. The results of the study indicate that although the same size is small and the distribution of data is unknown, GRA can still be successfully used in evaluating tourist destinations. In addition, we compare the GRA results with the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and show that more accurate ranking results can be obtained

Ranking of firms by performance using I-distance method

The objective of this article is to rank firms by their financial performance using statistical I-distance method, which has the ability to determine both ranking and important factors. For this purpose, the method was first applied to 110 Turkish industrial firms without any sectorial separation and then to 7 different sectors, and various findings about firms, sectors and variables were obtained. The I-distance method is used to get rid of the high correlation between variables during the analysis. The reason for choosing the I-distance method is that it allows you to sort the variables by importance and eliminate insignificant variables, as well as take into account correlations between variables. The authors believe that the method is superior to other alternative methods thanks to these qualities. Through a number of analyses, it was possible to see positions of firms both within the whole sample and their own sectors. Furthermore, this method provided valuable information on which factors were important in assessing firms’ financial performance. It has been observed in the analyses that the most effective factors in ranking firms and separating them from each other were profitability ratios, and the fact that liquidity and financial leverage ratios are not effective at all. When examined from a sectoral perspective, the nonmetal mining sector and the chemical, petroleum and plastic sectors seem to be better than other sectors in the performance rankings

Investment decision making using a combined factor analysis and entropy-based topsis model

Traditionally, the return on assets and the return on equity are used as the criteria in the evaluation of financial performance, while risk considerations are ignored. Therefore, this study combined financial ratio variables and the RAROC (risk-adjusted rate of return on capital) as the evaluation criteria and developed a financial performance evaluation model. The proposed evaluation model combines factor analysis with entropy weight and the TOPSIS (technique for order performance by similarity to ideal solution) to evaluate the financial performance of Taiwan's 50 listed opto-electronic companies. Finally, Spearman's and Kendall's rank correlations are used to verify that there is no significant difference between the 2007 and 2008 rankings of the companies. The empirical results show the financial performance rankings of the companies before and after the global financial turmoil. These findings not only help investors making investment decisions, but also can help managers make decisions to improve their company's financial performance

The Influence of Institutional Factors on the Value Relevance of Accounting Information: Evidence from Jordan

The purpose of the study was to present empirical evidence on the value relevance of accounting information in Jordan; whether institutional factors influence this value relevance and to determine which share price proxy is more reliable in indicating value relevance. The study examines the influence of institutional factors (foreign ownership, trading volume, financial disclosure time, financial disclosure level, number of shareholders, listing status, company’s age and type of industry) on the value relevance of accounting information (earnings, book value and cash flows relative to three share price proxies including average annual share price, annual closing share price and share price after a three-month period following the financial year-end) for Jordanian services and industrial companies during the period from 2004-2009. The study found that book value has the greatest value relevance and the best predictor for firm value. The value relevance of earnings and book value is greater for companies having foreign ownership, larger trading volume, larger shareholder numbers that conform to financial disclosure time, that are listed on the main board and that are older in age. Value relevance of book value is greater for companies complying with disclosure requirements and for services companies. Finally, annual closing share price proxy is more reliable in detecting the value relevance of accounting information. The findings suggest that market participants might be able to extract the firm value through the aforementioned institutional factors. The study extends the valuation model by including cash flows together with earnings and book value. The findings demonstrate that there is a shift away from earnings towards book value as the basis of firm valuation

Development of decision support systems towards supply chain performance appraisement

Purpose: The aim of this research is to develop various Decision Support Systems (DSS) towards supply chain (SC) performance appraisement as well as benchmarking. The purpose of this work is to understand multi-level (measures and metrics) performance appraisement index system to evaluate overall supply chain performance extent, monitor ongoing performance level and to identify ill-performing areas of the supply chain network. Design/methodology/approach: Fuzzy logic as well as grey theory has been explored in developing a variety of SC performance appraisement modules (evaluation index systems). Generalized fuzzy numbers, generalized intervalvalued fuzzy numbers theory have been utilized in order to tackle decision-makers’ linguistic evaluation information towards meaningful and logical interpretation of procedural hierarchy embedded to the said appraisement modules. Fuzzy-grey relation theory, MULTIMOORA method coupled with fuzzy logic as well as grey theory have also been adapted to facilitate overall SC performance assessment, performance benchmarking and related decision making. Findings: Supply chain performance index has been computed in terms of fuzzy as well as grey context, suggesting the present performance status of the said organizational supply chain. Ill-performing areas of the SC have been identified too. Fuzzy as well as grey based MULTIMOORA (MOORA: Multi-Objective Optimization by Ratio Analysis), fuzzy-grey relation analysis, thus adapted, appeared helpful in evaluating performance ranking order (and selecting the best) of various candidate alternatives (industries/enterprises) operating under similar supply chain architecture according to the ongoing SC performance. Empirical illustrations exhibited the fruitful application potential of the developed decision support tools. Practical implications: The decision support tools thus proposed may be proved fruitful for companies that are trying to identify key business performance measures for their supply chains. Ill-performing areas can easily be identified; companies can seek for possible means in order to improve those SC aspects so as to improve/enhance overall SC performance extent. Benchmarking may help in identifying best practices in relation to the SC which is performing as ideal (benchmarked practices). Best practices of the ideal organization need to be transmitted to the others. Companies can follow their peers in order to improve overall performance level of the entire supply chain. In view of this, the work reported in this dissertation may be proved as a good contributor for effective management of organizational SC. Research limitations: The methodology and presentation is conceptual, yet the tool can provide very useful interpretations for both researchers as well as management practitioners. Accessibility and availability of data are the main limitations affecting which model will be applied. Procedural steps towards implementing the said decision support tools have been demonstrated through empirical research. The decision support tools tools have neither been validated by practical case study nor have these been tested for assessing their reliability. Originality/value: This work articulates various approaches for supply chain performance evaluation considering multiple evaluation criteria (subjective evaluation indices), with a flexibility to modify and analyze using the available data sets collected from a group of experts (decision-makers). The approaches of performance evaluation index system are attempted due to structure and fuzzy (as well as grey) sets. The work is aimed at operational researchers, engineers and special managers

The value relevance of comprehensive income reporting in Nigeria

The transition to International Financial Reporting Standards (IFRS) requires Nigerian companies to mark-to-market certain financial assets and liabilities and to recognize holding gains and losses relating to these transactions as items of other comprehensive income. The two main objectives of this study are: 1) to investigate the relative and the incremental value relevance of comprehensive income and its components and 2) to examine the effects of reliability factors on the value relevance of other comprehensive income and its components. Using 349 firm-year observations, the result of Pooled Ordinary Least Square regression indicates the relative value relevance of net income and comprehensive income, but net income dominates comprehensive income. The aggregate other comprehensive income and fair value gains and losses on non-current assets were incrementally value relevant, but with coefficients lower than the traditional net income. These results are consistent for both financial and nonfinancial firms when using the price and the return model. The result on the first test of reliability shows a positive influence of corporate governance mechanisms on investors’ pricing of other comprehensive income. The result of the second test of reliability indicates that fair value gains and losses measured based on the quoted prices and observable input are value relevant, but unobservable input was not. However, when level measures were interacted with the corporate governance mechanisms, the impact was more on the unobservable input. Finally, findings regarding compliance with relevant accounting standards suggest low compliance, but compliance enhances the value relevance of the components of other comprehensive income. The results documented, herein, constitute a pioneering role on the relative and the incremental value relevance of comprehensive income reporting in Nigeria. One primary recommendation of the study is that reporting entities should pursue compliance with IFRS standards in order to increase reliability of financial process for investor

Analysis of Decision Support Systems of Industrial Relevance: Application Potential of Fuzzy and Grey Set Theories

The present work articulates few case empirical studies on decision making in industrial context. Development of variety of Decision Support System (DSS) under uncertainty and vague information is attempted herein. The study emphases on five important decision making domains where effective decision making may surely enhance overall performance of the organization. The focused territories of this work are i) robot selection, ii) g-resilient supplier selection, iii) third party logistics (3PL) service provider selection, iv) assessment of supply chain’s g-resilient index and v) risk assessment in e-commerce exercises. Firstly, decision support systems in relation to robot selection are conceptualized through adaptation to fuzzy set theory in integration with TODIM and PROMETHEE approach, Grey set theory is also found useful in this regard; and is combined with TODIM approach to identify the best robot alternative. In this work, an attempt is also made to tackle subjective (qualitative) and objective (quantitative) evaluation information simultaneously, towards effective decision making. Supplier selection is a key strategic concern for the large-scale organizations. In view of this, a novel decision support framework is proposed to address g-resilient (green and resilient) supplier selection issues. Green capability of suppliers’ ensures the pollution free operation; while, resiliency deals with unexpected system disruptions. A comparative analysis of the results is also carried out by applying well-known decision making approaches like Fuzzy- TOPSIS and Fuzzy-VIKOR. In relation to 3PL service provider selection, this dissertation proposes a novel ‘Dominance- Based’ model in combination with grey set theory to deal with 3PL provider selection, considering linguistic preferences of the Decision-Makers (DMs). An empirical case study is articulated to demonstrate application potential of the proposed model. The results, obtained thereof, have been compared to that of grey-TOPSIS approach. Another part of this dissertation is to provide an integrated framework in order to assess gresilient (ecosilient) performance of the supply chain of a case automotive company. The overall g-resilient supply chain performance is determined by computing a unique ecosilient (g-resilient) index. The concepts of Fuzzy Performance Importance Index (FPII) along with Degree of Similarity (DOS) (obtained from fuzzy set theory) are applied to rank different gresilient criteria in accordance to their current status of performance. The study is further extended to analyze, and thereby, to mitigate various risk factors (risk sources) involved in e-commerce exercises. A total forty eight major e-commerce risks are recognized and evaluated in a decision making perspective by utilizing the knowledge acquired from the fuzzy set theory. Risk is evaluated as a product of two risk quantifying parameters viz. (i) Likelihood of occurrence and, (ii) Impact. Aforesaid two risk quantifying parameters are assessed in a subjective manner (linguistic human judgment), rather than exploring probabilistic approach of risk analysis. The ‘crisp risk extent’ corresponding to various risk factors are figured out through the proposed fuzzy risk analysis approach. The risk factor possessing high ‘crisp risk extent’ score is said be more critical for the current problem context (toward e-commerce success). Risks are now categorized into different levels of severity (adverse consequences) (i.e. negligible, minor, marginal, critical and catastrophic). Amongst forty eight risk sources, top five risk sources which are supposed to adversely affect the company’s e-commerce performance are recognized through such categorization. The overall risk extent is determined by aggregating individual risks (under ‘critical’ level of severity) using Fuzzy Inference System (FIS). Interpretive Structural Modeling (ISM) is then used to obtain structural relationship amongst aforementioned five risk sources. An appropriate action requirement plan is also suggested, to control and minimize risks associated with e-commerce exercises