• The Journal of Industrial Distribution & Business
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• v.6 no.4
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• pp.23-26
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• 2015

Purpose - To mislead shareholders about a firm's actual economic performance, managers frequently manage dividends. Earnings management also affects performance reviews. Managers attempt to manage reported earnings caused by current economic events to accurately reflect their current performance. Research design, data, and methodology - The sample consisted of 312 company-years from companies in the pharmaceutical distribution industry listed on the Tehran Stock Exchange. A study period from 2004 to 2014 was selected. In this study, a model for measuring the performance of the net profits to total assets of a division of Jones was used to measure earnings management. Results - This study found a negative correlation between corporate performance and earnings management. Conclusions - The results for the earnings management company indicated a significant inverse relationship. Therefore, the company's performance weakened as its earnings management activity increased. In other words, the results showed that the company's performance-based accruals earnings management, the actual management of profits, and the general level of earnings management had significant inverse relationships. Thus, as the company's profits declined, earnings management activity increased.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.2
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• pp.21-31
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• 2020

Environmental pollution and climate change in Vietnam are now becoming a major concern. This situation is increasing the pressure on the companies to improve their social responsibility in production and business activities and disclose the environmental information to meet the requirements of stakeholders. This study investigates the internal and external factors of the company that affects the environmental information disclosure of listed companies on the Vietnam stock market as business sector, firm size, corporate manager perceptions, profitability, financial leverage, community pressure, pressures from stakeholders, government pressure influencing environmental information disclosure. Analytical data collected through the survey of 120 listed companies on the Ho Chi Minh City Stock Exchange (HOSE). By testing Cronbach's Alpha, exploratory factor analysis (EFA) and logistic regression analysis, the results of the study show that the level of environmental information disclosure of listed companies on the stock market in Vietnam depends heavily on government regulations, followed by the pressure from stakeholders, community pressure, views of business managers, companies size, business sector, and particularly profitability and financial leverage factors that have a negative relationship with environmental information disclosure.

• The Journal of Information Systems
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• v.16 no.3
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• pp.1-20
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• 2007

Most researches on the corporate credit rating are generally classified into the area of bankruptcy prediction and bond rating. The studies on bankruptcy prediction have focused on improving the performance in binary classification problem, since the criterion variable is categorical, bankrupt or non-bankrupt. The other studies on bond rating have predicted the credit ratings, which was already evaluated by bond rating experts. The financial institute, however, should perform effective loan evaluation and risk management by employing the corporate credit rating model, which is able to determine the credit of corporations. Therefore, this study presents a corporate credit rating method using business failure probability map(BFPM) and AHP(Analytic Hierarchy Process). The BFPM enables us to rate the credit of corporations according to business failure probability and data distribution or frequency on each credit rating level. Also, we developed AHP model for credit rating using non-financial information. For the purpose of completed credit rating model, we integrated the BFPM and the AHP model using both financial and non-financial information. Finally, the credit ratings of each firm are assigned by our proposed method. This method will be helpful for the loan evaluators of financial institutes to decide more objective and effective credit ratings.

• Journal of the Korean Institute of Navigation
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• v.24 no.4
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• pp.269-283
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• 2000

Service is the source of firm's competitive advantage in recent years. The importance of service quality in any service industry doesn't need to be disputed. Customers have expected the improvement of the quality of service they receive ,so providers are struggling to meet these expectations. This study aims at finding factors of service quality in passenger transportation. An empirical investigation and the measurement on the perceived Service Quality by customers in the passenger transportation system was carried out. The purpose of this study is to clarify the factors of service quality on the basis of service marketing concept. In order to fulfill the objectives, this paper combines research tools that include both empirical study and documentary research. Data was gathered from 239 passengers by the use of questionnaire. In this study, the established hypotheses were generated on the basis of the service quality evaluation (SERVQUAL) model. Research findings through empirical test are as follows. First, five service quality dimensions in passenger transportation are identical to SERVQUAL dimensions defined by Parasuraman, Zeithaml, and Berry in 1988. Second, demographic segments such as gender and age don't have significant different dimension of service quality. Third, there is no significant difference between groups by experiences such as price level, abroad tour and vehicle type in determinants of transportation service quality.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.7
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• pp.323-331
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• 2021

This paper examines the relationship between ownership structure and level cash holdings in an emerging country, namely, Saudi Arabia, by constructing a corporate governance mechanism (foreign ownership, family ownership, institutional and managerial ownership). This paper uses data from 100 listed firms at Saudi Stock Exchange (TADAWUL) from 2011 to 2019. The firm's decision to hold cash has come to the fore in the last two or three years as a result of the recent global financial crisis, and the impact that this has had on the firms' ability to raise funds from external sources. Using the random-effect generalized least square (GLS) regression model, the findings reveal that foreign and family ownership negatively influences cash holdings, while managerial ownership has a positive association with cash holdings. Further, institutional ownership did not have a direct effect on cash holdings in Saudi Arabia. Our results suggest that ownership structure include foreign ownership, family and managerial ownership is an essential vehicle to promote the performance of cash holding of all the 100 public-listed non-financial firms in Saudi Arabia. We recommend that sound policies should be targeted toward foreign ownership, family, and managerial ownership since they are essential to improve cash holding in Saudi Arabian firms.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.6
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• pp.231-243
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• 2022

The objective of this study is to analyze the impact of conservative financial reporting on investment during uncertainty. It was assumed that during uncertainty conservative financial reporting can play an important role to improve investment decision-making. For our analysis, data sets from 2005-2020 of nonfinancial companies are used. To measure the impact of conservative financial reporting in the non-financial sector of Pakistan, Khan and Watts' (2009) model is applied. "Prospector" and "Defender" Business strategy is applied for measuring firm-level uncertainty. Investment is measured by adding the change in fixed assets (property, plant, and equipment). To check the robustness of conservative financial reporting, Givoly and Hayn's (2000) Negative Accruals measure is applied. To measure the robustness of uncertainty, environmental scanning and alertness technique is applied. According to environmental scanning and alertness technique, companies are divided into two groups named 'inert' and 'alert'. 'Inert' are those firms that are not scanning their environment, and 'alert' are those firms who continuously analyze their environment. The empirical estimations support our hypothesis. The empirical findings provide the proof that in the wake of uncertainty conservative financial reporting may facilitate to take optimal investment decisions in the developing economy of Pakistan. Our results provide critical and practical implications for investors, researchers, and standard setters.

• Journal of Distribution Science
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• v.21 no.6
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• pp.83-89
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• 2023

Purpose: This paper considers the issue of corporate tax avoidance (CTA) in the distribution of the tax burden across companies in Vietnam because the high level of CTA leads to unfairness in taxation. In particular, we aim for discussing the way to measure the extent of CTA and explore the determinants of CTA that reflect the features of high-tax risk-taking companies. Research design, data and methodology: The study investigates factors influencing the CTA behavior of legal entities listed on the Vietnam stock market between 2012 and 2018 to fill the empirical research vacuum in the country. we employ the dynamic GMM estimate method. Interestingly, CTA is considered through three approaches, including two effective-tax-rate-based methods and especially accrual earnings Results: The results highlight tax - accounting book disparities have significant effects on CTA. In addition, firm size, net asset value, debt leverage, and tax-accounting books are related to CTA. Conclusions: Tax avoidance is shown to have a positive correlation with financial distress in this case. The higher a company's capital adequacy ratio, the fewer tax avoidance opportunities it has. The paper draws some recommendations to deal with tax avoidance that improves the fairness in the distribution of the tax burden among corporations.

• International conference on construction engineering and project management
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• 2011.02a
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• pp.534-541
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• 2011

Risk evaluation approaches for bidding on international construction projects are typically partitioned into three stages: country selection, project classification, and bid-cost evaluation. However, previous studies are frequently under attack in that they have several crucial limitations: 1) a dearth of studies about country selection risk tailored for the overseas construction market at a corporate level; 2) no consideration of uncertainties for input variable per se; 3) less probabilistic approaches in estimating a range of cost variance; and 4) less inclusion of covariance impacts. This study thus suggests a three-staged risk evaluation model to resolve these inherent problems. In the first stage, a country portfolio model that maximizes the expected construction market growth rate and profit rate while decreasing market uncertainty is formulated using multi-objective genetic analysis. Following this, probabilistic approaches for screening bad projects are suggested through applying various data mining methods such as discriminant logistic regression, neural network, C5.0, and support vector machine. For the last stage, the cost overrun prediction model is simulated for determining a reasonable bid cost, while considering non-parametric distribution, effects of systematic risks, and the firm's specific capability accrued in a given country. Through the three consecutive models, this study verifies that international construction risk can be allocated, reduced, and projected to some degree, thereby contributing to sustaining stable profits and revenues in both the short-term and the long-term perspective.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.1-19
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• 2018

Since stock movements forecasting is an important issue both academically and practically, studies related to stock price prediction have been actively conducted. The stock price forecasting research is classified into structured data and unstructured data, and it is divided into technical analysis, fundamental analysis and media effect analysis in detail. In the big data era, research on stock price prediction combining big data is actively underway. Based on a large number of data, stock prediction research mainly focuses on machine learning techniques. Especially, research methods that combine the effects of media are attracting attention recently, among which researches that analyze online news and utilize online news to forecast stock prices are becoming main. Previous studies predicting stock prices through online news are mostly sentiment analysis of news, making different corpus for each company, and making a dictionary that predicts stock prices by recording responses according to the past stock price. Therefore, existing studies have examined the impact of online news on individual companies. For example, stock movements of Samsung Electronics are predicted with only online news of Samsung Electronics. In addition, a method of considering influences among highly relevant companies has also been studied recently. For example, stock movements of Samsung Electronics are predicted with news of Samsung Electronics and a highly related company like LG Electronics.These previous studies examine the effects of news of industrial sector with homogeneity on the individual company. In the previous studies, homogeneous industries are classified according to the Global Industrial Classification Standard. In other words, the existing studies were analyzed under the assumption that industries divided into Global Industrial Classification Standard have homogeneity. However, existing studies have limitations in that they do not take into account influential companies with high relevance or reflect the existence of heterogeneity within the same Global Industrial Classification Standard sectors. As a result of our examining the various sectors, it can be seen that there are sectors that show the industrial sectors are not a homogeneous group. To overcome these limitations of existing studies that do not reflect heterogeneity, our study suggests a methodology that reflects the heterogeneous effects of the industrial sector that affect the stock price by applying k-means clustering. Multiple Kernel Learning is mainly used to integrate data with various characteristics. Multiple Kernel Learning has several kernels, each of which receives and predicts different data. To incorporate effects of target firm and its relevant firms simultaneously, we used Multiple Kernel Learning. Each kernel was assigned to predict stock prices with variables of financial news of the industrial group divided by the target firm, K-means cluster analysis. In order to prove that the suggested methodology is appropriate, experiments were conducted through three years of online news and stock prices. The results of this study are as follows. (1) We confirmed that the information of the industrial sectors related to target company also contains meaningful information to predict stock movements of target company and confirmed that machine learning algorithm has better predictive power when considering the news of the relevant companies and target company's news together. (2) It is important to predict stock movements with varying number of clusters according to the level of homogeneity in the industrial sector. In other words, when stock prices are homogeneous in industrial sectors, it is important to use relational effect at the level of industry group without analyzing clusters or to use it in small number of clusters. When the stock price is heterogeneous in industry group, it is important to cluster them into groups. This study has a contribution that we testified firms classified as Global Industrial Classification Standard have heterogeneity and suggested it is necessary to define the relevance through machine learning and statistical analysis methodology rather than simply defining it in the Global Industrial Classification Standard. It has also contribution that we proved the efficiency of the prediction model reflecting heterogeneity.

• Journal of Internet Computing and Services
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• v.14 no.6
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• pp.95-105
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• 2013

Recently, SME's Collaboration activities have become one of a vital factor for sustaining competitive edge. This is because of the rapidly changing and competitive market environment, and also to leverage performance by overcoming obstacles of having limited internal resources. Discussing about the effects and relationships of the firm's collaboration activities and its outputs are not new. However, as ICT and various technologies have been diffused into the traditional industries, boundaries and practice capabilities within the industries are becoming ambiguous. Thus contents of the products/services and their development methods are also go and come over the industries. Although many researchers suggested the relations of SME's collaboration activities and innovation performances, most of the previous literatures are focusing on broad perspectives of firm's environmental factors rather than considering various SME's idiosyncrasy factors such as their major product and customer types at once. Therefore, the purpose of this paper is to analyze how SME(Small Medium Enterprise)'s external collaboration activities by their idiosyncrasy act as an input to types of innovation performance. In order to analyze collaboration effects in detail, we defined factors that can represent the SME's business environment - Perceived importance of using external resources, Perceived importance of external partnership, Collaboration and Collaboration levels of Major Product types, Customer types and lastly the Firm Sizes. We have also specifically divided the performance of innovation types as product innovation and process innovation based on existing research. In this study, the empirical analysis is based on Probit Regression Model to observe the correlations with the impact of each SME's business environment and their activities. For the empirical data, 497 samples were collected which, this sample data was extracted from the 'Korean Open Innovation Survey' performed by ETRI(Korean Electronics Telecommunications Research Institute) in 2010. As a result, empirical test results indicated that the impact of collaboration varies depend on the innovation types (Product and Process Innovation). The Impact of the collaboration level for the product innovation tend to be more effective when SMEs are developing for a final product, targeting on for individual customers (B2C). But on the other hand, the analysis result of the Process innovation tend to be higher than the product innovation, when SMEs are developing raw materials for their partners or to other firms targeting on for manufacturing industries(B2B). Also perceived importance of using external resources has effected to both product and process innovation performance. But Perceived importance of external partnership was statistically insignificant. Interesting finding was that the service product has negative effects on for the process innovation performance. And Relationship between size of the firms and their external collaboration activities with their performance of the innovations indicated that the bigger firms(over 100 of employees) tend to have better for both product and process innovations. Finally, implications of the results can be suggested as performance of innovation can be varied depends on firm's unique business idiosyncrasy as well as levels of external collaboration activities. The Implication of this research can be considered for firms in selecting an appropriate strategy as well as for policy makers.