• Journal of Distribution Research
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• 제17권4호
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• pp.55-80
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• 2012

I. Introduction Developing the relationships between companies is very important issue to ensure a competitive advantage in today's business environment (Bleeke & Ernst 1991; Mohr & Spekman 1994; Powell 1990). Partnerships between companies are based on having same goals, pursuing mutual understanding, and having a professional level of interdependence. By having such a partnerships and cooperative efforts between companies, they will achieve efficiency and effectiveness of their business (Mohr and Spekman, 1994). However, it is difficult to expect these ideal results only in the B2B corporate transaction. According to agency theory which is the well-accepted theory in various fields of business strategy, organization, and marketing, the two independent companies have fundamentally different corporate purposes. Also there is a higher chance of developing opportunism and conflict due to natures of human(organization), such as self-interest, bounded rationality, risk aversion, and environment factor as imbalance of information (Eisenhardt 1989). That is, especially partnerships between principal(or buyer) and agent(or supplier) of companies within supply chain, the business contract itself will not provide competitive advantage. But managing partnership between companies is the key to success. Therefore, managing partnership between manufacturer and supplier, and finding causes of conflict are essential to improve B2B performance. In conclusion, based on prior researches and Agency theory, this study will clarify how business hazards cause conflicts on supply chain and then identify how developed conflicts have been managed by two control mechanisms. II. Research model III. Method In order to validate our research model, this study gathered questionnaires from small and medium sized enterprises(SMEs). In Korea, SMEs mean the firms whose employee is under 300 and capital is under 8 billion won(about 7.2 million dollar). We asked the manufacturer's perception about the relationship with the biggest supplier, and our key informants are denied to a person responsible for buying(ex)CEO, executives, managers of purchasing department, and so on). In detail, we contact by telephone to our initial sample(about 1,200 firms) and introduce our research motivation and send our questionnaires by e-mail, mail, and direct survey. Finally we received 361 data and eliminate 32 inappropriate questionnaires. We use 329 manufactures' data on analysis. The purpose of this study is to identify the anticipant role of business hazard (environmental dynamism, asset specificity) and investigate the moderating effect of control mechanism(formal control, social control) on conflict-performance relationship. To find out moderating effect of control methods, we need to compare the regression weight between low versus. high group(about level of exercised control methods). Therefore we choose the structural equation modeling method that is proper to do multi-group analysis. The data analysis is performed by AMOS 17.0 software, and model fits are good statically (CMIN/DF=1.982, p<.000, CFI=.936, IFI=.937, RMSEA=.056). IV. Result V. Discussion Results show that the higher environmental dynamism and asset specificity(on particular supplier) buyer(manufacturer) has, the more B2B conflict exists. And this conflict affect relationship quality and financial outcomes negatively. In addition, social control and formal control could weaken the negative effect of conflict on relationship quality significantly. However, unlikely to assure conflict resolution effect of control mechanisms on relationship quality, financial outcomes are changed by neither social control nor formal control. We could explain this results with the characteristics of our sample, SMEs(Small and Medium sized Enterprises). Financial outcomes of these SMEs(manufacturer or principal) are affected by their customer(usually major company) more easily than their supplier(or agent). And, in recent few years, most of companies have suffered from financial problems because of global economic recession. It means that it is hard to evaluate the contribution of supplier(agent). Therefore we also support the suggestion of Gladstein(1984), Poppo & Zenger(2002) that relational performance variable can capture the focal outcomes of relationship(exchange) better than financial performance variable. This study has some implications that it tests the sources of conflict and investigates the effect of resolution methods of B2B conflict empirically. And, especially, it finds out the significant moderating effect of formal control which past B2B management studies have ignored in Korea.

• Journal of Intelligence and Information Systems
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• 제18권4호
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• pp.117-127
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• 2012

Due to the recent expansion of the Web 2.0 -based services, along with the widespread of smartphones, online social network services are being popularized among users. Online social network services are the online community services which enable users to communicate each other, share information and expand human relationships. In the social network services, each relation between users is represented by a graph consisting of nodes and links. As the users of online social network services are increasing rapidly, the SNS are actively utilized in enterprise marketing, analysis of social phenomenon and so on. Social Network Analysis (SNA) is the systematic way to analyze social relationships among the members of the social network using the network theory. In general social network theory consists of nodes and arcs, and it is often depicted in a social network diagram. In a social network diagram, nodes represent individual actors within the network and arcs represent relationships between the nodes. With SNA, we can measure relationships among the people such as degree of intimacy, intensity of connection and classification of the groups. Ever since Social Networking Services (SNS) have drawn increasing attention from millions of users, numerous researches have made to analyze their user relationships and messages. There are typical representative SNA methods: degree centrality, betweenness centrality and closeness centrality. In the degree of centrality analysis, the shortest path between nodes is not considered. However, it is used as a crucial factor in betweenness centrality, closeness centrality and other SNA methods. In previous researches in SNA, the computation time was not too expensive since the size of social network was small. Unfortunately, most SNA methods require significant time to process relevant data, and it makes difficult to apply the ever increasing SNS data in social network studies. For instance, if the number of nodes in online social network is n, the maximum number of link in social network is n(n-1)/2. It means that it is too expensive to analyze the social network, for example, if the number of nodes is 10,000 the number of links is 49,995,000. Therefore, we propose a heuristic-based method for finding the shortest path among users in the SNS user graph. Through the shortest path finding method, we will show how efficient our proposed approach may be by conducting betweenness centrality analysis and closeness centrality analysis, both of which are widely used in social network studies. Moreover, we devised an enhanced method with addition of best-first-search method and preprocessing step for the reduction of computation time and rapid search of the shortest paths in a huge size of online social network. Best-first-search method finds the shortest path heuristically, which generalizes human experiences. As large number of links is shared by only a few nodes in online social networks, most nods have relatively few connections. As a result, a node with multiple connections functions as a hub node. When searching for a particular node, looking for users with numerous links instead of searching all users indiscriminately has a better chance of finding the desired node more quickly. In this paper, we employ the degree of user node vn as heuristic evaluation function in a graph G = (N, E), where N is a set of vertices, and E is a set of links between two different nodes. As the heuristic evaluation function is used, the worst case could happen when the target node is situated in the bottom of skewed tree. In order to remove such a target node, the preprocessing step is conducted. Next, we find the shortest path between two nodes in social network efficiently and then analyze the social network. For the verification of the proposed method, we crawled 160,000 people from online and then constructed social network. Then we compared with previous methods, which are best-first-search and breath-first-search, in time for searching and analyzing. The suggested method takes 240 seconds to search nodes where breath-first-search based method takes 1,781 seconds (7.4 times faster). Moreover, for social network analysis, the suggested method is 6.8 times and 1.8 times faster than betweenness centrality analysis and closeness centrality analysis, respectively. The proposed method in this paper shows the possibility to analyze a large size of social network with the better performance in time. As a result, our method would improve the efficiency of social network analysis, making it particularly useful in studying social trends or phenomena.

• Korean Journal of Agricultural Science
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• 제15권2호
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• pp.143-152
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• 1988

This study was conducted to obtain basic data which affected engine performance of the power tiller being widely used in the rural area. Among the various factors affected engine performance, only flywheel weight was considered as the major factor in this study. Fuel consumption ratio, motoring loss, torque, vibration and mechanical efficiency of the engine tested were measured and analyzed on the four levels of flywheel weight (32.2, 29.7, 26.4, 24.2 kg). The results obtained were as follows: 1. The maximum output of 6 and 7.5 kW engine was 7.43 kW and 7.85 kW respectively. When flywheel weight was reduced from 32.2 kg to 24.2 kg, output power of the engine was increased 0.27 kW in 6 kW engine and increased 0.39 kW in 7.5 kW engine. 2. The fuel consumption ratio was decreased from 300.8 to 296.8 g/kW-hr in 6 kW engine and decreased from 313.6 to 312.8 g/kW-hr in 7.5 kW engine when the flywheel weight was reduced from 32.2 kg to 24.2 kg. 3. The mechanical efficiencies of the engine was increased from 76.1 to 76.8% in 6 kW engine and increased from 76.7 to 77.0% in 7.5 kW engine when the flywheel weight was reduced from 32.2 kg to 24.2 kg. 4. When the flywheel weight was reduced from 32.2 kg to 24.2 kg, a tendency of a little decrease of vibration at X- and Z-axis in 6 kW engine and of a little increase of vibration at Y-axis in 6 kW engine and all directions in 7.5 kW engine was observed. 5. Motoring losses was decreased from 2.33 to l.76 kW in 6 kW engine and decreased from 2.46 to 1.84 kW in 7.5 kW engine when the flywheel weight was reduced from 32.2 kg to 24.2 kg. From the above results and the flywheel weight calculated theoretically, it was recommendable that the flywheel weight should be reduced about 7 kg in 6 kW engine and about 10 kg in 7.5 kW engine, respectively.