• International Journal of Quality Innovation
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• v.9 no.2
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• pp.57-77
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• 2008

The $21^{st}$ century is a new century of environmental protection. Environmental protection is one of the most important subject matters yet to come. Moreover, as the public pays more attention to environmental problems, enterprises should increase their investment in environmental management. Therefore, determining the investment level for environmental management and allocating the investment to associated environmental management activities has become a major task. The principal and agent theory and sales response functions are used for analysis in this research. The allocation of capital investment in environmental management is found to have significant impact on the aggregate sales response, aggregate profit and investment level. Therefore, in preparing the budget for environmental management, enterprises should focus on investment allocation decisions, determine the investment level and allocation method using integrated means, and apply submarket data in the allocation decision-making process. In other words, in setting the investment level, executive management should take managers' willingness into consideration. In allocating capital investment, managers should identify the optimal allocation method based on submarket characteristics.

• Journal of the Chungcheong Mathematical Society
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• v.32 no.2
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• pp.215-224
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• 2019

We investigate the optimal consumption and investment decision problem of an agent whose time preference is time-inconsistent. Specifically, for a time-separable utility function, the agent's subjective discount factor is supposed to be changed randomly in the future. We provide closed-form solutions in the presence of income process. The method can be extended into the case with a stochastic income process.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.19 no.2
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• pp.109-124
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• 2024

The value of platform companies is rapidly increasing, exerting significant influence across industries. Identifying and fostering promising platform companies is crucial for enhancing national competitiveness. Consequently, tailored evaluation standards are necessary for such companies. This study derived investment decision factors specific to platform companies and compared the importance of each factor using Analytic Hierarchy Process (AHP) analysis. Key factors included platform characteristics, finance, entrepreneur (team), market, and product/service attributes. The findings revealed that platform characteristics were deemed the most crucial factor for investors. Specifically, factors such as platform size, ease of value fixation, core participant group, and data value were identified as pertinent for evaluating platform companies. Moreover, analysis distinguished between investors with prior platform investment experience and those without. Significantly, investors with platform investment experience placed greater emphasis on the value of data secured by platform Furthermore, it was observed that investors prioritized future value and growth potential over current value when investing in platform. Notably, founder/team characteristics, typically highly regarded in previous studies, ranked lower in importance in this study, highlighting a shift in focus. The discrepancy between this study's results and prior research on investment decision factors is attributed to the specificity of the questions posed. By focusing on investment decision factors for platform startups rather than generic startup inquiries, investor responses aligned more closely with platform-focused considerations. Given the burgeoning venture investment landscape, there's a growing need for detailed research on startups within specific sectors like IT, travel, and biotech. This approach can replace extensive research covering all startup types to identify investment decision factors suited to the characteristics of each individual industry.

• Journal of Venture Innovation
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• v.1 no.2
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• pp.47-59
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• 2018

With the recent, rapid changes in the socio-economic environment, organizations of today are now required to present a framework of realistic consumer behaviors based on psychology, economy, and finance, in order to understand their investing customers. Stock investors show differences in terms of their decisions or evaluations in the process of investing. This is due to what is called the 'framing effect.' The decision frames of the investors are defined differently, and, as a result, this affects the decisions made by the investors. Preceding studies on stock investment rarely touched the topic of the effect of message framing on market participants in their stock investment, especially regarding the differences in terms of their risk management behaviors based on the message framing in stock investment. Therefore, the purpose of this study is to examine the influence of stock investment message framing on market participants in their investment decision making and empirically validate whether this message framing effect has a moderating effect on the factors of investment satisfaction. For this, 494 participants with stock investment experiences were interviewed from May 1 to 26, 2018, and the results were used as the data for the empirical analysis. The analysis of the data was conducted using SPSS 22.0 statistical analysis software. The results of this study were as follows; First, of the stock investment behavioral factors, the stock comprehension, recommendation by others for a stock, and the degree of risks of a stock affected stock investment satisfaction in a positive manner. And, of the behavioral factors of stock investment, stock comprehension, stock brand, recommendation on the stocks from others, past performances, and risk levels of stocks affected the intent of continued stock investment in a positive manner. Second, message framing turned out to affect stock investment satisfaction in a positive manner, and it also had a significant moderating effect to the relationship between the stock investment behavior and stock investment satisfaction. Third, message framing was found to affect continued stock investment intent significantly, with a significant moderating effect in the relationship between stock investment behavioral factor and continued stock investment intent.

• Journal of Information Technology Services
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• v.11 no.3
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• pp.205-225
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• 2012

The purpose of this study is to examine negative IT performances produced by irrational fashion-mimic IT investments in firms. Since most studies have been carried out on the assumption of rational investment decisions, many of them have revealed positive investment process and performances in firms. However, fashion-mimic investments to follow the paths of market leaders rather than rational investment decisions have been of frequent occurrence in many firms. This study divided types of mimic investments into subgroups where one subgroup has fashion-mimic properties and the other subgroup retains rational-mimic properties. We compared differences in performance of these subgroups to investigate effects of irrational investments in IT projects. The results indicated that there are differences in performance between fashion-mimic and rational-mimic investments. Additional analysis also revealed differences in performance at the presence of CEO control in the case of fashion-mimic investment subgroup.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.6 no.8
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• pp.73-79
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• 1983

Industrial management can be achieved in the improvement of productivities and goods qualities, only copy with international competition through technological renovation, This compels the renewal and augment of production equipments, for which more investment has to be projected. Equipment investment, However, has the possibility of assuring the expectation of profit, but the capricious reality of economical situation caused by inflation requires the precedent study of exmining, analyzing and assaying the effect of equipment investment for a long term. The resolution must depend on a technique of what is called engineering economy, which scrutinizes some samples of investment analysis under price fluctuations, which designates through a method of direct calculation that the only less scale of primal investment never bestows wider profit, and recognizes what contribution engineering economy has to the decision making of management.

• Proceedings of the SAREK Conference
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• 2008.06a
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• pp.231-236
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• 2008

The purpose of this study is to develop assessment model for selection of new DSM investment programs. In this research, MAUT method which find assessment value by each attributes related to selecting new DSM investment programs using utility function and integrate with structural frame was used to develop assessment model. In order to validate the usefulness of the model, assessment model was applied for actual candidate group of new DSM investment programs in natural gas domain. By utilize this assessment model to select new DSM investment programs, it is expected to minimize risk of new program launching and to maximize efficiency of DSM investment programs.

• Environmental and Resource Economics Review
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• v.27 no.4
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• pp.639-666
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• 2018

This paper analyses the investment options of groundwater development project under water price uncertainty. The optimal investment threshold price which trigger the investment are calibrated base on monopolistic real options model. Stochastic dynamic model is set to reflect the uncertainty of water price which follows the GBM (Geometric Brownian Motion) process. Our finding from non-cooperative investment decision model is that uncertainty of water price could deter the groundwater investment by considering the existence of option values. For policy markers, it is easy to manage 'charges for utilization of groundwater' rather than 'performance guarantee ratio' when managing groundwater investment with pricing policy. And it is necessary to make comprehensive and well-designed policies considering the characteristics of regional groundwater reservoir and groundwater developers.

• Journal of Digital Convergence
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• v.10 no.6
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• pp.181-187
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• 2012

This study inquires into what effect the tax burden of investors, for typical taxes related to real estate investment; acquisition tax, comprehensive real estate holding tax, and transfer income tax, might have on the real estate investment behaviors; the purpose of long-term investment. These real estate investment behaviors have been analyzed to see how much they affect investment performance such as realized compound yield. This study model, which considers the fact that the choice of investment behavior for the degree of tax burden of investors may lead to different results in real estate investment, is expected to be an effective decision-making tool for investment.

• International journal of advanced smart convergence
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• v.8 no.2
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• pp.102-108
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• 2019

Big data was associated with three key concepts, volume, variety, and velocity. Securities and investment services produce and store a large data of text/numbers. They have also the most data per company on the average in the US. Gartner found that the demand for big data in finance was 25%, which was the highest. Therefore securities and investment companies produce the largest data such as text/numbers, and have the highest demand. And insurance companies and credit card companies are using big data more actively than banking companies in Korea. Researches on the use of big data in securities and investment companies have been found to be insignificant. We surveyed 22 major securities and investment companies in Korea for activating big data. We can see they actively use AI for investment recommend. As for big data of securities and investment companies, we studied open API. Of the major 22 securities and investment companies, only six securities and investment companies are offering open APIs. The user OS is 100% Windows, and the language used is mainly VB, C#, MFC, and Excel provided by Windows. There is a difficulty in real-time analysis and decision making since developers cannot receive data directly using Hadoop, the big data platform. Development manuals are mainly provided on the Web, and only three companies provide as files. The development documentation for the file format is more convenient than web type. In order to activate big data in the securities and investment fields, we found that they should support Linux, and Java, Python, easy-to-view development manuals, videos such as YouTube.