• Journal of the Korea Society for Simulation
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• v.24 no.4
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• pp.97-106
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• 2015

In recent, hybrid market segmentation techniques have been widely adopted, which conduct segmentation using both general variables and transaction based variables. However, the limitation of the techniques is to generate incorrect results for market segmentation even though its methodology and concept are easy to apply. In this paper, we propose a novel scheme to overcome this limitation of the hybrid techniques and to take an advantage of product information obtained by customer's transaction data. In this scheme, we first divide a whole market into several unit segments based on the general variables and then agglomerate the unit segments with higher QAP correlations. Each product network represents for purchasing patterns of its corresponding segment, thus, comparisons of QAP correlation between product networks of each segment can be a good measure to compare similarities between each segment. A case study has been conducted to validate the proposed scheme. The results show that our scheme effectively works for Internet shopping malls.

• Proceedings of the SAREK Conference
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• 2006.06a
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• pp.245-251
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• 2006

The main idea of this study is to turn attention on the question of good cooling ability of customer substations in large district heating networks. The main reason for that is based on our experience that the optimization of district heating very often is directed toward production, whereas questions of optimal distribution are neglected if only the necessary load can be supplied and the customer's request for comfort is met. Our view is that low return temperature(operational temperature differences, ${\Delta}T$) in district heating systems is an Important feature for efficient net operation and gives both economic and operational benefits to the district heating supplier Furthermore, it is as well a prerequisite for meeting the customers demand for reliable supply of the heat load. However, in many practical cases we have seen that district heating return temperatures are higher than necessary. Hence, the aim of the study is to propose and verify a method for detection of the most critical consumers of the net and to identify the reasons for resulting high return temperature. From the results, temperature control system is presented as one of the most important reason of high return temperature in DH networks.

• 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 the Economic Geographical Society of Korea
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• v.13 no.1
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• pp.1-18
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• 2010

This paper examines characteristics of producer service networks by comparing the Capital region with Gyeongsang region in Korea and provides implications for regional policies of producer services. We employ the data of the Korea Innovation Survey, compiled by Science & Technology Policy Institute in 2006 and analyze producer service networks in the two regions. According to the results of production networks analysis, producer service firms in Gyeongsang region serve to relatively limited areas of market whereas those in the Capital region serve to a larger market. No difference is found between producer service firms in the Capital region and those in Gyeongsang region for the types of major customers. Analysis of knowledge/information networks demonstrates that firms in the Capital region mostly count on informal networks while those in Gyeongsang region primarily rely on their suppliers as a source of key information. Firms in Gyeongsand region often gain key information from the Capital region. The results of Social Network Analysis show that both of the innovation networks for two regions are poorly connected. In order to promote producer services, each region needs strategic approach reflecting regional characteristics and demands of regional industries.

• Journal of Distribution Research
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• v.11 no.3
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• pp.55-78
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• 2006

In business-to-business setting, dyadic relationships between firms are of paramount interest. Recent developments in business practice strongly suggest that to understand these business relationships, greater attention must be directed to the embedded context within which dyadic business relationships take place. As a result, it is important to develop an understanding which is to move from dyadic business relationship to business networks. The purpose of the current study is (1) to identify types of network benefits: information acquisition, access to tangible resources, cooperative support from network members, (2) to model network benefit efforts on a customer orientation for customer firm, (3) to examine the relationship between network characteristics and network benefits. Adopting resource-based view and social capital theory, the conceptual model is proposed. In order to develop and test a model, this paper was empirically to examine how network characteristics can reinforce network benefits leading to focal firm's customer orientation using 123 firms. Through structural equation modeling, this research found that (1) density influences information acquisition, access to tangible resources, cooperative support from network members, (2) centrality increases information acquisition, access to tangible resources. We also find that information acquisition, access to tangible resources, cooperative support from network members enhances focal firm's customer orientation. Finally, We discuss several theoretical and practical implications, and suggest limitations for the research and future research issue.

• Journal of Intelligence and Information Systems
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• v.10 no.2
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• pp.1-13
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• 2004

This paper presents a method for the multilingual product retrieval agent through XML and the semantic networks in e-commerce. Retrieval for products is an important process, since it represents interfaces of the customer contact to the e-commerce. Keyword-based retrieval is efficient as long as the product information is structured and organized. But when the product information is expressed across many online shopping malls, especially when it is expressed in different languages with cultural backgrounds, buyers' product retrieval needs language translation with ambiguities resolved in a specific context. This paper presents a RDF modeling case that resolves semantic problems in the representation of product information and across the boundaries of language domains. With adoption of UNSPSC code system, this paper designs and implements an architecture for the multilingual product retrieval agents. The architecture is based on the central repository model of product catalog management with distributed updating processes. It also includes the perspectives of buyers and suppliers. And the consistency and version management of product information are controlled by UNSPSC code system. The multilingual product names are resolved by semantic networks, thesaurus and ontology dictionary for product names.

• Journal of the Korean Operations Research and Management Science Society
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• v.34 no.2
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• pp.35-54
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• 2009

The recent economic crisis not only reduces the profit of department stores but also incurs the significance losses caused by the increasing late-payment rate of credit cards. Under this pressure, the scope of credit prediction needs to be broadened from the simple prediction of whether this customer has a good credit or not to the accurate prediction of how much profit can be gained from this customer. This study classifies the delinquent customers of credit card in a Korean department store into homogeneous clusters. Using this information, this study analyzes the repayment patterns for each cluster and develops the credit prediction system to manage the delinquent customers. The model presented by this study uses Kohonen network, which is one of artificial neural networks of data mining technique, to cluster the credit delinquent customers into clusters. Cox proportional hazard model is also used, which is one of survival analysis used in medical statistics, to analyze the repayment patterns of the delinquent customers in each cluster. The presented model estimates the repayment period of delinquent customers for each cluster and introduces the influencing variables on the repayment pattern prediction. Although there are some differences among clusters, the variables about the purchasing frequency in a month and the average number of installment repayment are the most predictive variables for the repayment pattern. The accuracy of the presented system leaches 97.5%.

• Annual Conference on Human and Language Technology
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• 2018.10a
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• pp.652-657
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• 2018

With the rapid development of e-commerce, many customers can now express their opinion on various kinds of product at discussion groups, merchant sites, social networks, etc. Discerning a consensus opinion about a product sold online is difficult due to more and more reviews become available on the internet. Opinion Mining, also known as Sentiment analysis, is the task of automatically detecting and understanding the sentimental expressions about a product from customer textual reviews. Recently, researchers have proposed various approaches for evaluation in sentiment mining by applying several techniques for document, sentence and aspect level. Aspect-based sentiment analysis is getting widely interesting of researchers; however, more complex algorithms are needed to address this issue precisely with larger corpora. This paper introduces an approach of knowledge representation for the task of analyzing product aspect rating. We focus on how to form the nature of sentiment representation from textual opinion by utilizing the representation learning methods which include word embedding and compositional vector models. Our experiment is performed on a dataset of reviews from electronic domain and the obtained result show that the proposed system achieved outstanding methods in previous studies.

• The Journal of Engineering Research
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• v.3 no.1
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• pp.85-95
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• 1998

In this study, we consider a recursive procedure to obtain the stationary probability distribution for analyzing Coxian queueing networks with finite queues. This network deals with multiple class customers. Due to the state space representing multiple class customers, the sub-matrices corresponding to states can not be square matrices and can not be inverted. Therefore, we introduce more complex recursive method to avoid the singular problem. The open queueing network that we study consists of 3 parallel first-level sources linked to a single second level queue. We consider two types of schemes for entering a queue. The first scheme is assumed to be the first-blocked-first-enter (FBFE) and the second scheme is the higher-priority-first-enter (HPFE). Arrival and service times are assume to have a Coxian distribution with two phases. Comparison between the resulting using Gauss-Seidel method and recursive procedure will be shown.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.23 no.8
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• pp.2096-2105
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• 1998

As there can be coincident bursts which may result in congetsion in a node of ATM network, reactive flow control schemes are required to guarantee user's Quality of Service. But, the high speed characteristics of ATM networks make it difficult to control source transmission rate in reacting to congestions in intermediate nodes. Therefore, flow control in Customer Premise Network may be more efficient than end-to-end flow control. In this paper, we propose a management model for flow ontrol in CPN and new Network Access Flow/Congestsion control scheme to utilize efficiently Virtual Path Connection.