• Title/Summary/Keyword: Business Process Performance

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The Efficiency Analysis of CRM System in the Hotel Industry Using DEA (DEA를 이용한 호텔 관광 서비스 업계의 CRM 도입 효율성 분석)

  • Kim, Tai-Young;Seol, Kyung-Jin;Kwak, Young-Dai
    • Journal of Intelligence and Information Systems
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    • v.17 no.1
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    • pp.91-110
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    • 2011
  • This paper analyzes the cases where the hotels have increased their services and enhanced their work process through IT solutions to cope with computerization globalization. Also the cases have been studies where national hotels use the CRM solution internally to respond effectively to customers requests, increase customer analysis, and build marketing strategies. In particular, this study discusses the introduction of the CRM solutions and CRM sales business and marketing services using a process for utilizing the presumed, CRM by introducing effective DEA(Data Envelopment Analysis). First, the comparison has done regarding the relative efficiency of L Company with the CCR model, then compared L Company's restaurants and facilities' effectiveness through BCC model. L Company reached a conclusion that it is important to precisely create and manage sales data which are the preliminary data for CRM, and for that reason it made it possible to save sales data generated by POS system on each sales performance database. In order to do that, it newly established Oracle POS system and LORIS POS system concerned with restaurants for food and beverage as well as rooms, and made it possible to stably generate and manage sales data and manage. Moreover, it set up a composite database to control comprehensively the results of work processes during a specific period by collecting customer registration information and made it possible to systematically control the information on sales performances. By establishing a system which unifies database and managing it comprehensively, impeccability of data has been greatly enhanced and a problem which generated asymmetric data could be thoroughly solved. Using data accumulated on the comprehensive database, sales data can be analyzed, categorized, classified through data mining engine imbedded in Polaris CRM and the results can be organized on data mart to provide them in the form of CRM application data. By transforming original sales data into forms which are easy to handle and saving them on data mart separately, it enabled acquiring well-organized data with ease when engaging in various marketing operations, holding a morning meeting and working on decision-making. By using summarized data at data mart, it was possible to process marketing operations such as telemarketing, direct mailing, internet marketing service and service product developments for perceived customers; moreover, information on customer perceptions which is one of CRM's end-products could feed back into the comprehensive database. This research was undertaken to find out how effectively CRM has been employed by comparing and analyzing the management performance of each enterprise site and store after introducing CRM to Hotel enterprises using DEA technique. According to the research results, efficiency evaluation for each site was calculated through input and output factors to find out comparative CRM system usage efficiency of L's Company four sites; moreover, with regard to stores, the sizes of workforce and budget application show a huge difference and so does the each store efficiency. Furthermore, by using the DEA technique, it could assess which sites have comparatively high efficiency and which don't by comparing and evaluating hotel enterprises IT project outcomes such as CRM introduction using the CCR model for each site of the related enterprises. By using the BCC model, it could comparatively evaluate the outcome of CRM usage at each store of A site, which is representative of L Company, and as a result, it could figure out which stores maintain high efficiency in using CRM and which don't. It analyzed the cases of CRM introduction at L Company, which is a hotel enterprise, and precisely evaluated them through DEA. L Company analyzed the customer analysis system by introducing CRM and achieved to provide customers identified through client analysis data with one to one tailored services. Moreover, it could come up with a plan to differentiate the service for customers who revisit by assessing customer discernment rate. As tasks to be solved in the future, it is required to do research on the process analysis which can lead to a specific outcome such as increased sales volumes by carrying on test marketing, target marketing using CRM. Furthermore, it is also necessary to do research on efficiency evaluation in accordance with linkages between other IT solutions such as ERP and CRM system.

Estimation of GARCH Models and Performance Analysis of Volatility Trading System using Support Vector Regression (Support Vector Regression을 이용한 GARCH 모형의 추정과 투자전략의 성과분석)

  • Kim, Sun Woong;Choi, Heung Sik
    • Journal of Intelligence and Information Systems
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    • v.23 no.2
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    • pp.107-122
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    • 2017
  • Volatility in the stock market returns is a measure of investment risk. It plays a central role in portfolio optimization, asset pricing and risk management as well as most theoretical financial models. Engle(1982) presented a pioneering paper on the stock market volatility that explains the time-variant characteristics embedded in the stock market return volatility. His model, Autoregressive Conditional Heteroscedasticity (ARCH), was generalized by Bollerslev(1986) as GARCH models. Empirical studies have shown that GARCH models describes well the fat-tailed return distributions and volatility clustering phenomenon appearing in stock prices. The parameters of the GARCH models are generally estimated by the maximum likelihood estimation (MLE) based on the standard normal density. But, since 1987 Black Monday, the stock market prices have become very complex and shown a lot of noisy terms. Recent studies start to apply artificial intelligent approach in estimating the GARCH parameters as a substitute for the MLE. The paper presents SVR-based GARCH process and compares with MLE-based GARCH process to estimate the parameters of GARCH models which are known to well forecast stock market volatility. Kernel functions used in SVR estimation process are linear, polynomial and radial. We analyzed the suggested models with KOSPI 200 Index. This index is constituted by 200 blue chip stocks listed in the Korea Exchange. We sampled KOSPI 200 daily closing values from 2010 to 2015. Sample observations are 1487 days. We used 1187 days to train the suggested GARCH models and the remaining 300 days were used as testing data. First, symmetric and asymmetric GARCH models are estimated by MLE. We forecasted KOSPI 200 Index return volatility and the statistical metric MSE shows better results for the asymmetric GARCH models such as E-GARCH or GJR-GARCH. This is consistent with the documented non-normal return distribution characteristics with fat-tail and leptokurtosis. Compared with MLE estimation process, SVR-based GARCH models outperform the MLE methodology in KOSPI 200 Index return volatility forecasting. Polynomial kernel function shows exceptionally lower forecasting accuracy. We suggested Intelligent Volatility Trading System (IVTS) that utilizes the forecasted volatility results. IVTS entry rules are as follows. If forecasted tomorrow volatility will increase then buy volatility today. If forecasted tomorrow volatility will decrease then sell volatility today. If forecasted volatility direction does not change we hold the existing buy or sell positions. IVTS is assumed to buy and sell historical volatility values. This is somewhat unreal because we cannot trade historical volatility values themselves. But our simulation results are meaningful since the Korea Exchange introduced volatility futures contract that traders can trade since November 2014. The trading systems with SVR-based GARCH models show higher returns than MLE-based GARCH in the testing period. And trading profitable percentages of MLE-based GARCH IVTS models range from 47.5% to 50.0%, trading profitable percentages of SVR-based GARCH IVTS models range from 51.8% to 59.7%. MLE-based symmetric S-GARCH shows +150.2% return and SVR-based symmetric S-GARCH shows +526.4% return. MLE-based asymmetric E-GARCH shows -72% return and SVR-based asymmetric E-GARCH shows +245.6% return. MLE-based asymmetric GJR-GARCH shows -98.7% return and SVR-based asymmetric GJR-GARCH shows +126.3% return. Linear kernel function shows higher trading returns than radial kernel function. Best performance of SVR-based IVTS is +526.4% and that of MLE-based IVTS is +150.2%. SVR-based GARCH IVTS shows higher trading frequency. This study has some limitations. Our models are solely based on SVR. Other artificial intelligence models are needed to search for better performance. We do not consider costs incurred in the trading process including brokerage commissions and slippage costs. IVTS trading performance is unreal since we use historical volatility values as trading objects. The exact forecasting of stock market volatility is essential in the real trading as well as asset pricing models. Further studies on other machine learning-based GARCH models can give better information for the stock market investors.

Two Faces of Entrepreneurial Leadership: The Paradoxical Effect Reflecting Followers' Regulatory Focus (기업가적 리더십의 양면성: 구성원의 조절 초점 성향에 따른 패러독스 효과)

  • Sang-Jib Kwon
    • Asia-Pacific Journal of Business Venturing and Entrepreneurship
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    • v.18 no.4
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    • pp.165-175
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    • 2023
  • In venture creation research, studying 'entrepreneurial leadership' is important for uncovering and comprehending the underlying causal process in innovative behavior performance. Although previous studies provide that entrepreneurial leadership enhances followers' innovative behavior, there is few research on entrepreneurial leadership and followers' characteristics interaction. The present study's focus is paradoxical effects of entrepreneurial leadership on self-efficacy and innovative behavior. On the basis of individual regulatory focus, this study suggests that interaction effects of entrepreneurial leadership and followers' regulatory focus differed in promotion view and prevention view followers' innovative behavior. To strengthen the casual mechanism, this study conducted in priming experiment method using employees in SMEs. This study used a 2(entrepreneurial leadership vs. control) x 2 (regulatory focus: promotion vs. prevention) between-participants design. The results of this study provide that (1) Individuals in promotion focus especially benefited from entrepreneurial leadership in terms of its effect on their self-efficacy and innovative behavior; (2) whereas entrepreneurial leadership was negatively related to self-efficacy and innovative behavior of followers' prevention focus. In sum, results of the present study supporting evidence for hypotheses, combined effect of entrepreneurial leadership and regulatory focus on innovative behavior through self-efficacy. Experimental results confirmed hypotheses of this study, revealing that promotion focus show more innovative behavior than prevention focus when their leaders' leadership style is entrepreneurial leadership. Also, the paradoxical effect of entrepreneurial leadership and regulatory focus of followers on innovative behavior was mediated by followers' self-efficacy. This study helps explain how leaders' entrepreneurial leadership boost followers' innovative behavior, particularly for those employees who have promotion focus. The current study contributes to the theory of entrepreneurial leadership and regulatory focus and innovation literature. Findings of this study shed light on the organizational processes that shape innovative behavior in venture/startup corporations and provide contributions for venture business field.

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Business Strategies for Korean Private Security-Guard Companies Utilizing Resource-based Theory and AHP Method (자원기반 이론과 AHP 방법을 활용한 민간 경호경비 기업의 전략 연구)

  • Kim, Heung-Ki;Lee, Jong-Won
    • Korean Security Journal
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    • no.36
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    • pp.177-200
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    • 2013
  • As we enter a high industrial society that widens the gap between the rich and poor, demand for the security services has grown explosively. With the growth in quantitative expansion of security services, people have also placed increased requirements on more sophisticated and diversified security services. Consequently, market outlook for private security services industry is positive. However, Korea's private security services companies are experiencing difficulties in finding a direction to capture this new market opportunity due to their small sizes and lack of management-strategic thinking skills. Therefore, we intend to offer a direction of development for our private security services industry using a management-strategy theory and the Analytic Hierarchy Process(AHP), a structured decision-making method. A resource-based theory is one of the important management strategy theories. It explains that a company's overall performance is primarily determined by its competitive resources. Using this theory, we could analyze a company's unique resources and core competencies and set a strategic direction for the company accordingly. The usefulness and validity of this theory has been demonstrated as it has often been subject to empirical verification since 1990s. Based on this theory, we outlined a set of basic procedures to establish a management strategy for the private security services companies. We also used the AHP method to identify competitive resources, core competencies, and strategies from private security services companies in contrast with public companies. The AHP method is a technique that can be used in the decision making process by quantifying experts' knowledge and unstructured problems. This is a verified method that has been used in the management decision making in the corporate environment as well as for the various academic studies. In order to perform this method, we gathered data from 11 experts from academic, industrial, and research sectors and drew distinctive resources, competencies, and strategic direction for private security services companies vis-a-vis public organizations. Through this process, we came to the conclusion that private security services companies generally have intangible resources as their distinctive resources compared with public organization. Among those intangible resources, relational resources, customer information, and technologies were analyzed as important. In contrast, tangible resources such as equipment, funds, distribution channels are found to be relatively scarce. We also found the competencies in sales and marketing and new product development as core competencies. We chose a concentration strategy focusing on a particular market segment as a strategic direction considering these resources and competencies of private security services companies. A concentration strategy is the right fit for smaller companies as a strategy to allow them to focus all of their efforts on target customers in a single segment. Thus, private security services companies would face the important tasks such as developing a new market and appropriate products for such market segment and continuing marketing activities to manage their customers. Additionally, continuous recruitment is required to facilitate the effective use of human resources in order to strengthen their marketing competency in a long term.

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The Relationship Between DEA Model-based Eco-Efficiency and Economic Performance (DEA 모형 기반의 에코효율성과 경제적 성과의 연관성)

  • Kim, Myoung-Jong
    • Journal of Environmental Policy
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    • v.13 no.4
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    • pp.3-49
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    • 2014
  • Growing interest of stakeholders on corporate responsibilities for environment and tightening environmental regulations are highlighting the importance of environmental management more than ever. However, companies' awareness of the importance of environment is still falling behind, and related academic works have not shown consistent conclusions on the relationship between environmental performance and economic performance. One of the reasons is different ways of measuring these two performances. The evaluation scope of economic performance is relatively narrow and the performance can be measured by a unified unit such as price, while the scope of environmental performance is diverse and a wide range of units are used for measuring environmental performances instead of using a single unified unit. Therefore, the results of works can be different depending on the performance indicators selected. In order to resolve this problem, generalized and standardized performance indicators should be developed. In particular, the performance indicators should be able to cover the concepts of both environmental and economic performances because the recent idea of environmental management has expanded to encompass the concept of sustainability. Another reason is that most of the current researches tend to focus on the motive of environmental investments and environmental performance, and do not offer a guideline for an effective implementation strategy for environmental management. For example, a process improvement strategy or a market discrimination strategy can be deployed through comparing the environment competitiveness among the companies in the same or similar industries, so that a virtuous cyclical relationship between environmental and economic performances can be secured. A novel method for measuring eco-efficiency by utilizing Data Envelopment Analysis (DEA), which is able to combine multiple environmental and economic performances, is proposed in this report. Based on the eco-efficiencies, the environmental competitiveness is analyzed and the optimal combination of inputs and outputs are recommended for improving the eco-efficiencies of inefficient firms. Furthermore, the panel analysis is applied to the causal relationship between eco-efficiency and economic performance, and the pooled regression model is used to investigate the relationship between eco-efficiency and economic performance. The four-year eco-efficiencies between 2010 and 2013 of 23 companies are obtained from the DEA analysis; a comparison of efficiencies among 23 companies is carried out in terms of technical efficiency(TE), pure technical efficiency(PTE) and scale efficiency(SE), and then a set of recommendations for optimal combination of inputs and outputs are suggested for the inefficient companies. Furthermore, the experimental results with the panel analysis have demonstrated the causality from eco-efficiency to economic performance. The results of the pooled regression have shown that eco-efficiency positively affect financial perform ances(ROA and ROS) of the companies, as well as firm values(Tobin Q, stock price, and stock returns). This report proposes a novel approach for generating standardized performance indicators obtained from multiple environmental and economic performances, so that it is able to enhance the generality of relevant researches and provide a deep insight into the sustainability of environmental management. Furthermore, using efficiency indicators obtained from the DEA model, the cause of change in eco-efficiency can be investigated and an effective strategy for environmental management can be suggested. Finally, this report can be a motive for environmental management by providing empirical evidence that environmental investments can improve economic performance.

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An Empirical Study on Technological Innovation Management Factors of SMEs (중소기업의 기술혁신 관리요소에 관한 실증연구)

  • Im, Chae-Hyon;Shin, Jin-Kyo
    • Journal of Technology Innovation
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    • v.20 no.2
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    • pp.75-107
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    • 2012
  • Previous researches on technological innovation have several limitations such as lack of general mechanism for technological innovation(inputs, throughputs and outputs of technological innovation), large company oriented studies, and ignoring importance of technology management capabilities. So, this study suggested a new model using resource-based theory and system theory, and empirically applied that to SMEs. Structural equation model analysis by using 223 SMEs in Daegu region provided a support for most of hypotheses. Research results showed that all of factors on technological innovation were significantly and positively related with each other: inputs(R&D leadership, innovation strategy, R&D investment, R&D human resource management, external network), throughputs(portfolio management, project management, technology commercialization) and output(technological innovation). In case of technological innovation inputs, R&D leadership influenced on innovation strategy positively and significantly. And R&D leadership and innovation strategy had positive and significant effects on R&D investment, R&D human resource management and external network. R&D human resource management and external network exerted positive and significant influences on technological innovation throughputs such as portfolio management and project management. But R&D investment did not significant impacts on technological innovation throughputs. Among technological innovation throughputs, both portfolio management and project management had positive and significant effect on technology commercialization. In addition, technology commercialization acted positively and significantly technological innovation output. This study suggests necessary of efforts to implement innovation strategy and manage R&D human resource effectively based on CEO's innovativeness and entrepreneurship. Also, if SMEs want to develop technology and commercialize it, they have to cooperate with external technology resources and informations. Research results revealed that proper level of R&D investment, internal and external communication, information sharing, and learning and cooperative culture were very important for improvement of technological innovation performance in SMEs. Especially, this research suggested that if SMEs manage technological innovation process effectively based on resource-based and system approaches, then they can overcome their resource limitations and gain high technological innovation performance. Also, useful policy support for technological innovation of central or regional government by this research model is important factor for SMEs' technological innovation performance.

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Social Network Analysis for the Effective Adoption of Recommender Systems (추천시스템의 효과적 도입을 위한 소셜네트워크 분석)

  • Park, Jong-Hak;Cho, Yoon-Ho
    • Journal of Intelligence and Information Systems
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    • v.17 no.4
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    • pp.305-316
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    • 2011
  • Recommender system is the system which, by using automated information filtering technology, recommends products or services to the customers who are likely to be interested in. Those systems are widely used in many different Web retailers such as Amazon.com, Netfix.com, and CDNow.com. Various recommender systems have been developed. Among them, Collaborative Filtering (CF) has been known as the most successful and commonly used approach. CF identifies customers whose tastes are similar to those of a given customer, and recommends items those customers have liked in the past. Numerous CF algorithms have been developed to increase the performance of recommender systems. However, the relative performances of CF algorithms are known to be domain and data dependent. It is very time-consuming and expensive to implement and launce a CF recommender system, and also the system unsuited for the given domain provides customers with poor quality recommendations that make them easily annoyed. Therefore, predicting in advance whether the performance of CF recommender system is acceptable or not is practically important and needed. In this study, we propose a decision making guideline which helps decide whether CF is adoptable for a given application with certain transaction data characteristics. Several previous studies reported that sparsity, gray sheep, cold-start, coverage, and serendipity could affect the performance of CF, but the theoretical and empirical justification of such factors is lacking. Recently there are many studies paying attention to Social Network Analysis (SNA) as a method to analyze social relationships among people. SNA is a method to measure and visualize the linkage structure and status focusing on interaction among objects within communication group. CF analyzes the similarity among previous ratings or purchases of each customer, finds the relationships among the customers who have similarities, and then uses the relationships for recommendations. Thus CF can be modeled as a social network in which customers are nodes and purchase relationships between customers are links. Under the assumption that SNA could facilitate an exploration of the topological properties of the network structure that are implicit in transaction data for CF recommendations, we focus on density, clustering coefficient, and centralization which are ones of the most commonly used measures to capture topological properties of the social network structure. While network density, expressed as a proportion of the maximum possible number of links, captures the density of the whole network, the clustering coefficient captures the degree to which the overall network contains localized pockets of dense connectivity. Centralization reflects the extent to which connections are concentrated in a small number of nodes rather than distributed equally among all nodes. We explore how these SNA measures affect the performance of CF performance and how they interact to each other. Our experiments used sales transaction data from H department store, one of the well?known department stores in Korea. Total 396 data set were sampled to construct various types of social networks. The dependant variable measuring process consists of three steps; analysis of customer similarities, construction of a social network, and analysis of social network patterns. We used UCINET 6.0 for SNA. The experiments conducted the 3-way ANOVA which employs three SNA measures as dependant variables, and the recommendation accuracy measured by F1-measure as an independent variable. The experiments report that 1) each of three SNA measures affects the recommendation accuracy, 2) the density's effect to the performance overrides those of clustering coefficient and centralization (i.e., CF adoption is not a good decision if the density is low), and 3) however though the density is low, the performance of CF is comparatively good when the clustering coefficient is low. We expect that these experiment results help firms decide whether CF recommender system is adoptable for their business domain with certain transaction data characteristics.

Quantification of a Global Construction Core Competencies for Korean Construction/Engineering Firms (국내 건설업체의 해외 진출역량 계량화 연구)

  • Kim, Sang-Bum;Kim, Yong-Bi
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.33 no.6
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    • pp.2541-2549
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    • 2013
  • The Construction industry has been dealing with much trouble due to global economic recession and domestic political trends emphasizing on welfare than development. Consequently, domestic construction market has been dramatically shrunk during the last a few years, and international market has become the only potential solution for the industry. However, there has been lack of efforts in developing a quantified measure of global competencies for Korean engineering and construction organizations. This study attempted to develop quantified indices for Korean engineering and construction contractors with which the level of global construction competencies can be objectively monitored. In doing so, a survey questionnaire was developed to identify relative importances of core competency elements which were derived from extensive literature reviews and experts interviews. AHP (Analytic Hierarchy Process) was employed as a main analysis method in developing quantification measures. The analysis results reveal little differences in competency requirements between engineering and construction firms and it implies that the global market becomes more integrated and requires a total solution for a construction project. The developed core competency measures can be used to quantify the level of preparedness of Korean engineering and construction firms at the time of evaluation and also be used as a basis for performance benchmarking indicators if they are compared with business showings.

The Effect of Strategic and Operational Integration of 1st supplier's buyer and supplier on Production Flexibility (1차 협력사의 구매자 및 공급자와의 전략적·운영적 통합이 생산의 유연성에 미치는 영향)

  • Kim, Jong Hoon;Lee, Tae Hee
    • International Commerce and Information Review
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    • v.18 no.4
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    • pp.285-310
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    • 2016
  • The purpose of this study empirically verified impact of strategic and operational integration between first-tier supplier and their supplier and strategic and operational integration between first-tier supplier and their buyer on operation performance. In order to achieve our goal, we tested reliability, validity and path coefficient using structural equation modeling-partial least square (SEM-PLS) over 284 first-tier manufacturing suppliers data that Korea Productivity Center (KPC) surveyed in 2013. This study results indicated that operational integration between first-tier supplier and their supplier or buyer has positive impact on production process flexibility. Meanwhile, strategic integration between first-tier supplier and buyer has positive impact on production flexibility. On the other hand, strategic integration between first-tier supplier and supplier has negative impact on production flexibility. And production process flexibility has positive impact on production flexibility. By empirically testing to departmentalize level and scope of supply chain integration, this study has academic and managerial implications from first-tier perspective on.

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The Changing Characteristics of Office Location in Central Seoul (서울 도심 사무활동입지의 변화와 특성)

  • Kee-Bom Nahm
    • Journal of the Economic Geographical Society of Korea
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    • v.1 no.2
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    • pp.85-102
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    • 1998
  • The Changing Characteristics of Office Location in Central Seoul In recent years, central Seoul has been experiencing a dynamic transformation. In the process of reorganization of urban industrial structure including tertiarization and quaternarization of the economic base of Seoul, business services are growing very rapidly and large scale urban renewal projects are agilely implemented. Downtown office activities become a nucleus for economic performance of Seoul and high-rise office buildings steer the landscape transformation of central Seoul. Even though there appear to exist some evidences that office districts have dispersed to several subcenters, major office activities are still concentrated in the central Seoul. This paper redefines office industry in a narrow meaning comprising only relevant economic sectors and office buildings as office activity-functioning units. It then explores the industrial networking and territorial specialization of office activities focusing on the dual process of concentration and dispersion in Seoul. The changing characteristics of the downtown linkages of office activities in this post-industrial era transforms the spatial economy of central Seoul into more flexible and volatile, while territorial concentration of power and control functions are fortified at the same time. Finally, the paper addresses the development of manufacturing-tertiary-quaternary industrial complex, which can be regarded as new industrial clusters, selling cultural economy of urban space and possessing placeness or images for clients and customers, in relation to urban competitiveness and territorial specialization of large metropolitan areas.

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