• East Asian Journal of Business Economics (EAJBE)
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• v.12 no.2
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• pp.1-7
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• 2024

Purpose: This study delves into the application of the Ohlson 1995 valuation model, particularly addressing the intricacies of the "Other information" variable. Our goal is to pinpoint the most suitable variables for substitution within this category, focusing specifically on the Mongolian Stock Exchange (MSE) context. Research design, data, and methodology: Employing data spanning from 2012 to 2022 from 60 MSE-listed companies, we conduct a comprehensive analysis encompassing both financial and non-financial indicators. Through meticulous examination, we aim to identify which variables effectively substitute for the "Other information" component of the Ohlson model. Results: Our findings reveal significant outcomes. While all financial variables within the model exhibit importance, certain non-financial indicators, notably the company's level and state ownership participation, emerge as particularly influential in determining stock prices on the MSE. Conclusions: This study not only contributes to a deeper understanding of valuation dynamics within the MSE but also provides actionable insights for future research endeavors. By refining key variables within the Ohlson model, this research enhances the accuracy and efficacy of financial analysis practices. Moreover, the implications extend to practitioners, offering valuable insights into the determinants of stock prices in the MSE and guiding strategic decision-making processes.

• Korea Journal of Hospital Management
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• v.16 no.3
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• pp.57-74
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• 2011

The purpose of this study is to analyze the relationship between the BSC model's non-financial factors such as learning and growth, internal process, customer and financial factor in general hospitals. To achieve research purpose, the data were collected from 293 employees of 5 hospitals using a standardized questionnaires which were constructed to include BSC model, and applied the structural equation modeling to examine the relationship between non-financial and financial factor. The results show that the learning and growth factor of the model has positive effects of the internal process and customer factor. The internal process and customer factor are strongly related to financial factor. Hospitals have to know non-financial factor which has positively relate to financial factor. Therefore, the results of this study help to enhance the health care center to become aligned and focused on implementing the long-term competitive strategy. This study proposes an effective performance indicators for general hospitals and it is expected to be likely to have positive influence upon enhancing services of general hospitals.

• Health Policy and Management
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• v.12 no.3
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• pp.54-76
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• 2002

This study investigated how much EVA which evaluate firm's value can explain hospital bankruptcy prediction as a explanatory variable including financial indicators in Korea. In this study, artificial neural network and logit regression which are traditional statistical were used as the model for bankruptcy prediction. Data used in this study were financial and economic value added indicators of 34 bankrupt and -:4 non-bankrupt hospitals from the Database of Korean Health Industry Development Institute. The main results of this study were as follows: First, there was a significant difference between the financial variable model including EVA and the financial variable model excluding EVA in pre-bankruptcy analysis. Second, EVA could forecast bankruptcy hospitals up to 83% by the logistic analysis. Third, the EVA model outperformed the financial model in terms of the predictive power of hospital bankruptcy. Fourth, The predictive power of neural network model of hospital bankruptcy was more powerful than the legit model. After all the result of this study will be useful to future study on EVA to evaluate bankruptcy hospitals forecast.

• The Journal of Information Systems
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• v.33 no.1
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• pp.115-131
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• 2024

Purpose This study aims to analyse the impact of the development of fintech and the emergence of internet primary banks due to the increasing use of smartphones on the performance of traditional local banks from both financial and non-financial perspectives. Return on equity (ROE) and return on assets (ROA) are used to assess the performance differences between the two types of banks and how these differences are affected by their financial characteristics. Design/methodology/approach Using return on equity (ROE) and return on assets (ROA) as indicators, we identified the differences in operating performance between the two types of banks. In addition, this study analysed the impact of financial characteristics on profitability through regression analysis with various control variables. We further studied the impact of non-financial characteristics (customer reviews, social media reactions, etc.) on operating performance. Findings The net interest margin ratio of local banks had a positive impact, while the marketable securities ratio of Internet primary banks had a negative impact. The non-financial analysis shows that the number of customer reviews and social media reactions have a significant impact on the performance of Internet primary banks, suggesting that customer satisfaction and positive market perception are important factors in the performance of Internet primary banks.

• Journal of the Korean Operations Research and Management Science Society
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• v.27 no.2
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• pp.123-152
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• 2002

This study establishes key success Predictors of internet venture enterprises in Korea. The five factors are derived from the relevant literature and clarified the concept of entrepreneurship, industrial level, enterprise strategy, organizational capability, and resource procurement by distinguishing between its components and determinants. Organizational performance indicators were derived from the previous studies classifying by financial performance indicator and non-financial performance indicator using by recent evaluation method as BSC (Balanced Scorecard). We then examine the impact of critical success factors on the internet venture performance. Hypotheses on five factors of internet venture were tested for 103 organizations. Results indicate that critical success factors may serve as key predictors. Organizational strategy and resource capability was found to be positively influenced on both financial performance indicator and non-financial performance indicator while entrepreneurship, industrial level and organizational capability positively affected only non-financial performance indicator.

• Journal of Construction Engineering and Project Management
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• v.2 no.4
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• pp.42-45
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• 2012

In construction industry, the term 'procurement' is considered as a project based job where clients and contractors are always keen to observe performance indicators. These indicators represent financial and non-financial efficiency of project activities. Among these, the monitoring of financial indicators such as cost monitoring is an ongoing process and its importance cannot be undermined during the project life cycle. It can be monitored by using traditional approach of direct reporting of actual cost against budget. However, the comparison of budget versus actual spending does not indicate the worth of the work which is completed at any given time. This approach does not represent the true cost performance of the project. Because of these limitations, this paper discusses the applications of Earned Value Analysis (EVA) for cost monitoring of construction projects in Malaysia. Besides traditional approach, EVA is a three-dimensional approach that compares three cost indicators i.e. the budgeted value of work scheduled with the earned value of physical work completed and the actual cost of work completed. Therefore, cost monitoring by EVA is an objective measure of actual work performed. This paper uses a case study, an example application of EVA as a cost monitoring tool. This case study reaffirms the benefits of using EVA for project cash flow analysis and forecasting.

• Journal of the Korean Society of Food Culture
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• v.24 no.5
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• pp.486-495
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• 2009

The purpose of this research was to investigate whether the perception of KPIs by restaurant managers from financial and non-financial perspectives was affected by BSC implementation. The perceptions that were examined were importance, adoption, performance, and utilization of KPIs. We surveyed managers from multinational restaurant chains that were adopting BSC and those that were not. From a non-financial perspective, the difference in perceived importance between BSC adopted firms and firms that did not adopt BSC was significant. The managers of BSC adopted firms perceived KPIs more seriously than the others. Secondly, according to the managers' working experiences, the difference of perceived utilization in the internal business process perspective was significant between BSC adopted firms and firms that did not adopt BSC. In addition, from the learning and growth perspective, the difference in perceived adoption and utilization between the two groups was significant. Finally, in the BSC adopted firms, the perceived importance of the managers affected the other perceptions like adoption and utilization from both the financial and non-financial perspectives.

• Journal of the Korea Society of Computer and Information
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• v.28 no.8
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• pp.67-75
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• 2023

Stock price prediction is an important topic extensively discussed in the financial market, but it is considered a challenging subject due to numerous factors that can influence it. In this research, performance was compared and analyzed by applying time series prediction models (LSTM, GRU) and non-time series prediction models (RF, SVR, KNN, LGBM) that do not take into account the temporal dependence of data into stock price prediction. In addition, various data such as stock price data, technical indicators, financial statements indicators, buy sell indicators, short selling, and foreign indicators were combined to find optimal predictors and analyze major factors affecting stock price prediction by industry. Through the hyperparameter optimization process, the process of improving the prediction performance for each algorithm was also conducted to analyze the factors affecting the performance. As a result of feature selection and hyperparameter optimization, it was found that the forecast accuracy of the time series prediction algorithm GRU and LSTM+GRU was the highest.

• The Journal of Society for e-Business Studies
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• v.11 no.1
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• pp.91-112
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• 2006

Unlike typical corporate investments, IT expenditures have direct impact on many aspects of a business, including those that are difficult to quantify. Therefore, financial indicators alone do not do justice to the full effect of an If investment. Proposed in this paper is a methodology to measure the return on IT investments, including non-financial impacts expressed in terms of monetary values. This methodology shows tangible cost as well as hidden cost by analyzing total cost of ownership. The methodology also produces ROI by performing cost benefit analysis including financial and non-financial factors. This paper suggests a more objective validation of If's impact on the business activities. It rationalizes investment priorities and provides a systematic approach to effective IT investment.

• Journal of Korean Institute of Industrial Engineers
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• v.39 no.4
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• pp.260-270
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• 2013

This paper proposes a strategic portfolio model for managing performance of online games. The portfolio matrix is composed of two dimensions: financial performance and non-financial performance. Financial performance is measured by the conventional measure, average revenue per user (ARPU). In terms of non-financial performance, five non-financial key performance indicators (KPIs) that have been widely used in the online game industry are utilized: RU (Register User), VU (Visiting User), TS (Time Spent), ACU (Average Current User), MCU (Maximum Current User). Data envelopment analysis (DEA) is then employed to produce a single performance measure aggregating the five KPIs. DEA is a linear programming model for measuring the relative efficiency of decision making unit (DMUs) with multiple inputs and outputs. This study employs DEA as a tool for multiple criteria decision making (MCDM), in particular, the pure output model without inputs. Combining the two types of performance produces the online game portfolio matrix with four quadrants: Dark Horse, Stop Loss, Jack Pot, Luxury Goods. A case study of 39 online games provided by company 'N' is provided. The proposed portfolio model is expected to be fruitfully used for strategic decision making of online game companies.