• KDI Journal of Economic Policy
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• v.12 no.2
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• pp.95-120
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• 1990

The underpricing of new shares of a firm that are offered to the public for the first time (initial offerings) is well known and has puzzled financial economists for a long time since it seems at odds with the optimal behavior of the owners of issuing firms. Past attempts by financial economists to explain this phenomenon have not been successful in the sense that the explanations given by them are either inconsistent with the equilibrium theory or implausible. Approaches by such authors as Welch or Allen and Faulhaber are no exceptions. In this paper, we develop a signalling model of capital investment to explain the underpricing phenomenon and also analyze the efficiency of investment. The model focuses on the information asymmetry between the owners of issuing firms and general investors. We consider a firm that has been owned and operated by a single owner and that has a profitable project but has no capital to develop it. The profit from the project depends on the capital invested in the project as well as a profitability parameter. The model also assumes that the financial market is represented by a single investor who maximizes the expected wealth. The owner has superior information as to the value of the firm to investors in the sense that it knows the true value of the parameter while investors have only a probability distribution about the parameter. The owner offers the representative investor a fraction of the ownership of the firm in return for a certain amount of investment in the firm. This offer condition is equivalent to the usual offer condition consisting of the number of issues to sell and the unit price of a share. Thus, the model is a signalling game. Using Kreps' criterion as the solution concept, we obtained an essentially unique separating equilibrium offer condition. Analysis of this separating equilibrium shows that the owner of the firm with high profitability chooses an offer condition that raises an amount of capital that is short of the amount that maximizes the potential profit from the project. It also reveals that the fraction of the ownership of the firm that the representative investor receives from the owner of the highly profitable firm in return for its investment has a value that exceeds the investment. In other words, the initial offering in the model is underpriced when the profitability of the firm is high. The source of underpricing and underinvestment is the signalling activity by the owner of the highly profitable firm who attempts to convince investors that his firm has a highly profitable project by choosing an offer condition that cannot be imitated by the owner of a firm with low profitability. Thus, we obtained two main results. First, underpricing is a result of a signalling activity by the owner of a firm with high profitability when there exists information asymmetry between the owner of the issuing firm and investors. Second, such information asymmetry also leads to underinvestment in a highly profitable project. Those results clearly show the underpricing entails underinvestment and that information asymmetry leads to a social cost as well as a private cost. The above results are quite general in the sense that they are based upon a neoclassical profit function and full rationality of economic agents. We believe that the results of this paper can be used as a basis for further research on the capital investment process. For instance, one can view the results of this paper as a subgame equilibrium in a larger game in which a firm chooses among diverse ways to raise capital. In addition, the method used in this paper can be used in analyzing a wide range of problems arising from information asymmetry that the Korean financial market faces.

• Journal of the Korea Knowledge Information Technology Society
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• v.13 no.1
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• pp.11-23
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• 2018

This paper empirically investigates the factors that influence the consumer choice of an app market based on the rational choice theory. The app market is the only channel where a consumer can buy smartphone apps, which give various functional convenience and are considered to be a major contributor to the proliferation of smartphones. Analyses of 281 questionnaires show that usability and structural guarantees as benefit factors significantly influence the app market choice. From the cost perspectives, both monetary and non-monetary conversion costs are found to significantly influence the app market choice. On the other hand, customer trust, information quality, and market image were found to have no significant effect on app market selection. In particular, Korean app market platform providers (KT, LG U +) seem to be superior in terms of structural guarantees, such as customer center operation and damage compensation regulations, compared to overseas app market platform operators (Google). However, in the case of the Google App Market, it is pre-installed on all Android phones, so it is not inconvenient to install additional apps to use other app market. This is disadvantageous to domestic app market platform operators, and it is necessary to establish a policy solution point. In terms of operator costs, both monetary and non-monetary conversion costs have a significant impact on app market choice. In particular, non-monetary conversion costs have a negative impact on Korean app market platform operators. It can be explained that the service expectation level of the domestic app market is low and it is recognized that the time cost factor such as membership is large for new users to use. It seems to be necessary to improve the domestic app market business. Meanwhile, extant research on smartphone apps focuses on the purchase of apps themselves, but not on the selection of the app market itself. In order to fill in this gap, this study focuses on the determinants of app market selection, including the characteristics of an app market and the switching costs.

• Journal of the Korean Electrochemical Society
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• v.10 no.1
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• pp.25-30
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• 2007

Proton exchange membrane fuel cell(PEMFC) performance could be affected by various factors such as cell temperature, total pressure, partial pressure of reactants and relative humidity. Hydrogen ion is combined with water to form hydronium ion [$H_3O^+$] and pass through membrane resulting electricity generation. Cooling system is needed to remove heat and other uses on large scale fuel cell. In case that collant conductivity is increased, fuel cell performance could be decreased because produced electricity could be leaked through coolant. In this study, triple distilled water(TDW) and antifreeze solution containing ethylene glycol was used to observe resistance change. Resistance of TDW was taken 28 days to reach preset value, and effect on fuel cell operation was not observed. Resistance of antifreeze solution was not reached to preset value up to 48 days, but performance failure occurred presumably caused by bipolar plate junction resulting stoppage resistance experiment. Generally PEMFC humidification is performed near-saturated operating conditions at various temperatures and pressures, but non-humidifying condition could be applied in small scale fuel cell to improve efficiency and reduce system cost. However, it was difficult to operate large scale fuel cell without humidifying, especially higher than $50{\sim}60^{\circ}C$. In case of small flux such as 0.78 L/min, temperature difference between inlet and outlet was occurred larger than other cases resulting performance decrease. Non-humidifying performance experiments were done at various cell temperature. When both of anode and cathode humidification were removed, cell performance was strongly depended on cell operating temperature.

• Economic and Environmental Geology
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• v.55 no.4
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• pp.377-388
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• 2022

Laboratory-scale experiments were performed to identify the As removal mechanism of the residual slag generated after the mineral carbonation process. The residual slags were manufactured from the steelmaking slag (blast oxygen furnace slag: BOF) through direct and indirect carbonation process. RDBOF (residual BOF after the direct carbonation) and RIBOF (residual BOF after the indirect carbonation) showed different physicochemical-structural characteristics compared with raw BOF such as chemical-mineralogical properties, the pH level of leachate and forming micropores on the surface of the slag. In batch experiment, 0.1 g of residual slag was added to 10 mL of As-solution (initial concentration: 203.6 mg/L) titrated at various pH levels. The RDBOF showed 99.3% of As removal efficiency at initial pH 1, while it sharply decreased with the increase of initial pH. As the initial pH of solution decreased, the dissolution of carbonate minerals covering the surface was accelerated, increasing the exposed area of Fe-oxide and promoting the adsorption of As-oxyanions on the RDBOF surface. Whereas, the As removal efficiency of RIBOF increased with the increase of initial pH levels, and it reached up to 70% at initial pH 10. Considering the PZC (point of zero charge) of the RIBOF (pH 4.5), it was hardly expected that the electrical adsorption of As-oxyanion on surface of the RIBOF at initial pH of 4-10. Nevertheless it was observed that As-oxyanion was linked to the Fe-oxide on the RIBOF surface by the cation bridge effect of divalent cations such as Ca²⁺, Mn²⁺, and Fe²⁺. The surface of RIBOF became stronger negatively charged, the cation bridge effect was more strictly enforced, and more As can be fixed on the RIBOF surface. However, the Ca-products start to precipitate on the surface at pH 10-11 or higher and they even prevent the surface adsorption of As-oxyanion by Fe-oxide. The TCLP test was performed to evaluate the stability of As fixed on the surface of the residual slag after the batch experiment. Results supported that RDBOF and RIBOF firmly fixed As over the wide pH levels, by considering their As desorption rate of less than 2%. From the results of this study, it was proved that both residual slags can be used as an eco-friendly and low-cost As remover with high As removal efficiency and high stability and they also overcome the pH increase in solution, which is the disadvantage of existing steelmaking slag as an As remover.

• Journal of the Speleological Society of Korea
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• no.63
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• pp.1-8
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• 2004

The non-magnetic materials with non-conductive showing high structure dispersity were developed on the base of natural quartz and lava-scoria which was collected from Je-ju island in Korea, and treated by methane-chemical technology those were obtained novel properties of magnetization through the analyzing. Depending on the processing conditions and subsequent applications the materials produced by strong methane-chemical reaction (MCR) in alcohol solution showed concurrently magnetic, dielectric and electrical properties. The obtained magnetic-electrical powders classified by aggregate complex of their features as segnetomagnetics, containing a dielectric material as a carrying nucleus, particularly the quartz on that surface one or more layers of different compounds were synthesized having thickness up to 10～50 nm and showing magnetic, electrical and other properties. It was confirmed in magnetizing process that powders of quartz and lava-scoria produced by MCR were better oil adsorbent as of oleophilic and floating matter on water surface although their specific gravities are comparably more than 1 in quartz or less than unity, as that of water, in lava-scoira. Therefore, it will be Possible and very useful to remove low density and light gravity oil spillage in difficult recovery from sea and inland water contamination spread on water surface, by marine accident and ship sinking accident occurring frequently in recent years, by way of magnetic adsorbent conveyer system in continuous, if it could be built up the mass Production system of water-floating magnetizable oleophilic adsorbent materials with use of iow cost and good Qualify lava-scoria spread on volcano district in Je-ju island. And, there will also be urgent advent of necessity with strong possibility to develop useful applications of various magnetic functional materials include oleophilic adsorbent for removal of sea oil-contaminants and maritime pollutants, and other kinds of various utilities in industrial applications and practical uses of novel functional materials in the fields of environments and health care applications with in deep expectation.

• The Korean Journal of Nuclear Medicine Technology
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• v.18 no.1
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• pp.62-68
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• 2014

Purpose: After I-131 therapy, SPECT/CT is useful in identifying location of thyroid remnants and metastasis of thyroid cancers. An excessive uptake of thyroid leads to a ringing artifact in the SPECT images. The aim of this study is to investigate and suggest a proper post filters to remove ringing artifact and produce better image quality. Materials and Methods: A low-cost, customized thyroid-mimicking phantom, consisting of an acrylic bottle and a hollow sphere was used for SPECT/CT Discovery (GE Healthcare, USA). It was filled with I-131 solution. The ratio of hollow sphere to background were varied as 50:1, 200:1, 1000:1 and 4000:1. Acquired images were reconstructed by OSEM (2 iterations, 10 subsets) with and without Evolution (resolution recovery correction, GE). Three different post-filters were applied; Butterworth (cut off: 0.38 to 0.58 with intervals of 0.05), Hanning (cut off: 0.8 to 1 with intervals of 0.05) and Gaussian (FWHM: 3 to 5 with intervals of 0.5) filters. Contrast, background variability, air area variability, and full width half maximum (FWHM) were compared. Results: Higher contrasts were obtained from the SPECT images with Evolution than without Evolution. In the case of images without Evolution, image distortion such as star artifact was generated. For all sphere-to-background ratio, the Butterworth filter showed better constrasts and FWHMs than other two filters, but the ringing artifact was still generated in all studies except 50:1 and it was decreased as cutoff value was increased. The ringing artifact didn't appear with Hanning and Gaussian filters at all studies, however constrats and FWHMs with Gaussian was worse than Hanning filter. For the images having ringing artifacts, the background variability and air area variability were increased. Conclusion: In this study, we suggested that it is desirable to use Hanning filter when the ringing artifact is generated and to use Butterworth filter when ringing artifact is not generated in I-131 SPECT.

• Clean Technology
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• v.27 no.4
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• pp.359-366
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• 2021

Halloysite nanotubes (HNTs), the multiwalled clay mineral with the composition of Al₂Si₂O₅(OH)₄·nH₂O, have been highlighted as a low-cost adsorbent for the removal of dyes from wastewater. Although a powder of halloysite presents a high specific surface area, forming media are significantly considered due to sludge-clogging induced by the water-bound agglomeration. However, higher firing temperature to achieve the structural durability of the media and lower utilization rate due to longer penetration depth into the media act as hurdles to increase the dye-adsorption capacity. In this work, the retention of the adsorption capacity of halloysite was evaluated with methylene blue solution after the heat treatment at 750 ℃. In order to improve the utilization rate, tubular media were fabricated by extrusion. The images taken by transmission electron microscopy show that HNTs present excellent structural stability under heat treatment. The HNTs also provide superb capacity retention for MB adsorption (93%, 18.5 mg g^-1), while the diatomite and Magnesol^® XL show 22% (7.65 mg g^-1) and 6% (11.7 mg g^-1), respectively. Additionally, compositing with lignin enhances adsorption capacity, and the heat treatment under the hydrogen atmosphere accelerates the adsorption in the early stage. Compared to the rod-type, the tubular halloysite media rapidly increases methylene blue adsorption capacity.

• Resources Recycling
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• v.31 no.4
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• pp.56-65
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• 2022

Copper is one of the non-ferrous metals used in the electrical/electronic manufacturing industries due to its superior properties particularly the high conductivity and less resistivity. The effluent generated from the surface finishing process of these industries contains higher copper content which gets discharged in to water bodies directly or indirectly. This causes severe environmental pollution and also results in loss of an important valuable metal. To overcome this issue, continuous R & D activities are going on across the globe in adsorption area with the purpose of finding an efficient, low cost and ecofriendly adsorbent. In view of the above, present investigation was made to compare the performance of a plant root (Datura root powder) as a bio-adsorbent to that of the synthetic one (Tulsion T-42) for copper adsorption from such effluent. Experiments were carried out in batch studies to optimize parameters such as adsorbent dose, contact time, pH, feed concentration, etc. Results of the batch experiments indicate that 0.2 g of Datura root powder and 0.1 g of Tulsion T-42 showed 95% copper adsorption from an initial feed/solution of 100 ppm Cu at pH 4 in contact time of 15 and 30 min, respectively. Adsorption data for both the adsorbents were fitted well to the Freundlich isotherm. Experimental results were also validated with the kinetic model, which showed that the adsorption of copper followed pseudo-second order rate expression for the both adsorbents. Overall result demonstrates that the bio-adsorbent tested has a potential applicability for metal recovery from the waste solutions/effluents of metal finishing units. In view of the requirements of commercial viability and minimal environmental damage there from, Datura root powder being an effective material for metal uptake, may prove to be a feasible adsorbent for copper recovery after the necessary scale-up studies.

• Journal of Global Scholars of Marketing Science
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• v.20 no.2
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• pp.110-122
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• 2010

The emergence of the field of organizational buying behavior in the mid-1960’s with the publication of Industrial Buying and Creative Marketing (1967) set the stage for a new paradigm of thinking about how business was conducted in markets other than those serving ultimate consumers. Whether it is "industrial marketing" or "business-to-business marketing" (B-to-B), organizational buying behavior remains the core differentiating characteristic of this domain of marketing. This paper explores the impact of several dynamic factors that have influenced how organizations relate to one another in a rapidly increasing interdependence, which in turn can impact organizational buying behavior. The paper also raises the question of whether or not the major conceptual models of organizational buying behavior in an interdependent world are still relevant to guide research and managerial thinking, in this dynamic business environment. The paper is structured to explore three questions related to organizational interdependencies: 1. What are the factors and trends driving the emergence of organizational interdependencies? 2. Will the major conceptual models of organizational buying behavior that have developed over the past half century be applicable in a world of interdependent organizations? 3. What are the implications of organizational interdependencies on the research and practice of organizational buying behavior? Consideration of the factors and trends driving organizational interdependencies revealed five critical drivers in the relationships among organizations that can impact their purchasing behavior: Accelerating Globalization, Flattening Networks of Organizations, Disrupting Value Chains, Intensifying Government Involvement, and Continuously Fragmenting Customer Needs. These five interlinked drivers of interdependency and their underlying technological advances can alter the relationships within and among organizations that buy products and services to remain competitive in their markets. Viewed in the context of a customer driven marketing strategy, these forces affect three levels of strategy development: (1) evolving customer needs, (2) the resulting product/service/solution offerings to meet these needs, and (3) the organization competencies and processes required to develop and implement the offerings to meet needs. The five drivers of interdependency among organizations do not necessarily operate independently in their impact on how organizations buy. They can interact with each other and become even more potent in their impact on organizational buying behavior. For example, accelerating globalization may influence the emergence of additional networks that further disrupt traditional value chain relationships, thereby changing how organizations purchase products and services. Increased government involvement in business operations in one country may increase costs of doing business and therefore drive firms to seek low cost sources in emerging markets in other countries. This can reduce employment opportunitiesn one country and increase them in another, further accelerating the pace of globalization. The second major question in the paper is what impact these drivers of interdependencies have had on the core conceptual models of organizational buying behavior. Consider the three enduring conceptual models developed in the Industrial Buying and Creative Marketing and Organizational Buying Behavior books: the organizational buying process, the buying center, and the buying situation. A review of these core models of organizational buying behavior, as originally conceptualized, shows they are still valid and not likely to change with the increasingly intense drivers of interdependency among organizations. What will change however is the way in which buyers and sellers interact under conditions of interdependency. For example, increased interdependencies can lead to increased opportunities for collaboration as well as conflict between buying and selling organizations, thereby changing aspects of the buying process. In addition, the importance of communication processes between and among organizations will increase as the role of trust becomes an important criterion for a successful buying relationship. The third question in the paper explored consequences and implications of these interdependencies on organizational buying behavior for practice and research. The following are considered in the paper: the need to increase understanding of network influences on organizational buying behavior, the need to increase understanding of the role of trust and value among organizational participants, the need to improve understanding of how to manage organizational buying in networked environments, the need to increase understanding of customer needs in the value network, and the need to increase understanding of the impact of emerging new business models on organizational buying behavior. In many ways, these needs deriving from increased organizational interdependencies are an extension of the conceptual tradition in organizational buying behavior. In 1977, Nicosia and Wind suggested a focus on inter-organizational over intra-organizational perspectives, a trend that has received considerable momentum since the 1990's. Likewise for managers to survive in an increasingly interdependent world, they will need to better understand the complexities of how organizations relate to one another. The transition from an inter-organizational to an interdependent perspective has begun, and must continue so as to develop an improved understanding of these important relationships. A shift to such an interdependent network perspective may require many academicians and practitioners to fundamentally challenge and change the mental models underlying their business and organizational buying behavior models. The focus can no longer be only on the dyadic relations of the buying organization and the selling organization but should involve all the related members of the network, including the network of customers, developers, and other suppliers and intermediaries. Consider for example the numerous partner networks initiated by SAP which involves over 9000 companies and over a million participants. This evolving, complex, and uncertain reality of interdependencies and dynamic networks requires reconsideration of how purchase decisions are made; as a result they should be the focus of the next phase of research and theory building among academics and the focus of practical models and experiments undertaken by practitioners. The hope is that such research will take place, not in the isolation of the ivory tower, nor in the confines of the business world, but rather, by increased collaboration of academics and practitioners. In conclusion, the consideration of increased interdependence among organizations revealed the continued relevance of the fundamental models of organizational buying behavior. However to increase the value of these models in an interdependent world, academics and practitioners should improve their understanding of (1) network influences, (2) how to better manage these influences, (3) the role of trust and value among organizational participants, (4) the evolution of customer needs in the value network, and (5) the impact of emerging new business models on organizational buying behavior. To accomplish this, greater collaboration between industry and academia is needed to advance our understanding of organizational buying behavior in an interdependent world.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.231-252
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• 2021

Artificial intelligence (AI) is a key technology that will change the future the most. It affects the industry as a whole and daily life in various ways. As data availability increases, artificial intelligence finds an optimal solution and infers/predicts through self-learning. Research and investment related to automation that discovers and solves problems on its own are ongoing continuously. Automation of artificial intelligence has benefits such as cost reduction, minimization of human intervention and the difference of human capability. However, there are side effects, such as limiting the artificial intelligence's autonomy and erroneous results due to algorithmic bias. In the labor market, it raises the fear of job replacement. Prior studies on the utilization of artificial intelligence have shown that individuals do not necessarily use the information (or advice) it provides. Algorithm error is more sensitive than human error; so, people avoid algorithms after seeing errors, which is called "algorithm aversion." Recently, artificial intelligence has begun to be understood from the perspective of the augmentation of human intelligence. We have started to be interested in Human-AI collaboration rather than AI alone without human. A study of 1500 companies in various industries found that human-AI collaboration outperformed AI alone. In the medicine area, pathologist-deep learning collaboration dropped the pathologist cancer diagnosis error rate by 85%. Leading AI companies, such as IBM and Microsoft, are starting to adopt the direction of AI as augmented intelligence. Human-AI collaboration is emphasized in the decision-making process, because artificial intelligence is superior in analysis ability based on information. Intuition is a unique human capability so that human-AI collaboration can make optimal decisions. In an environment where change is getting faster and uncertainty increases, the need for artificial intelligence in decision-making will increase. In addition, active discussions are expected on approaches that utilize artificial intelligence for rational decision-making. This study investigates the impact of artificial intelligence on decision-making focuses on human-AI collaboration and the interaction between the decision maker personal traits and advisor type. The advisors were classified into three types: human, artificial intelligence, and human-AI collaboration. We investigated perceived usefulness of advice and the utilization of advice in decision making and whether the decision-maker's personal traits are influencing factors. Three hundred and eleven adult male and female experimenters conducted a task that predicts the age of faces in photos and the results showed that the advisor type does not directly affect the utilization of advice. The decision-maker utilizes it only when they believed advice can improve prediction performance. In the case of human-AI collaboration, decision-makers higher evaluated the perceived usefulness of advice, regardless of the decision maker's personal traits and the advice was more actively utilized. If the type of advisor was artificial intelligence alone, decision-makers who scored high in conscientiousness, high in extroversion, or low in neuroticism, high evaluated the perceived usefulness of the advice so they utilized advice actively. This study has academic significance in that it focuses on human-AI collaboration that the recent growing interest in artificial intelligence roles. It has expanded the relevant research area by considering the role of artificial intelligence as an advisor of decision-making and judgment research, and in aspects of practical significance, suggested views that companies should consider in order to enhance AI capability. To improve the effectiveness of AI-based systems, companies not only must introduce high-performance systems, but also need employees who properly understand digital information presented by AI, and can add non-digital information to make decisions. Moreover, to increase utilization in AI-based systems, task-oriented competencies, such as analytical skills and information technology capabilities, are important. in addition, it is expected that greater performance will be achieved if employee's personal traits are considered.