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    사회연결망이 구전과 고객 추천가치에 미치는 영향 = The Influence of Social Network on Word-of-Mouth and Customer Referral Value

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    https://www.riss.kr/link?id=A82728765

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    다국어 초록 (Multilingual Abstract) kakao i 다국어 번역

    While social network which was originated from complex theory has extensively been studied in other social sciences, a serious attention has not been paid yet in Marketing. Increasing number of firms are gradually using referral marketing campaign to attract more customers. This research is to investigate the influences of social network on word-of-mouth (WOM) and customer referral value in the context of B2C and B2B industries. This research consists of two studies. In study 1, we performed two experiments. The purposes of experiment 1, as a preliminary experiment, were to examine the strength of tie in the social network and the type of social network in each sample service industry. Data were collected from customers in two sample service industries, mobile telephone service (B2C) and tax/accounting service (B2B) and were analyzed with Pajek. Each service customers were divided into high and low groups based on the strength of tie, resulting in four groups (B2C-A & B; B2B-C & D). Analysis results show that the strength of tie and centrality indices of four groups appeared to be very different from one another. In addition, the social network of all the four groups was a scale-free type. Specifically, groups A and B a were decentralized type, and groups C and D were a centralized type. Experiment 2 was conducted to examine the influence of the strength of tie in the social network on WOM effect. The respondents of the above four groups were given to read a positive or negative WOM-related scenario and were asked to answer a questionnaire. WOM effect was measured by two ways: one was how much the recipient would trust the received information and the other was how likely the recipient would transfer the information. The analysis results showed that the customer referral value was meaningful to B2C as well as B2B industry (H1). When an individual received a negative (vs. positive) WOM information, he/she was more likely to transfer the information to another individual (H3a). In addition, in the case of negative WOM, an individual`s intention to transfer the information was higher when the network tie was stronger, whereas in the case of positive WOM, an individual`s intention to transfer was higher when the network tie was weaker (H3b). However, when the WOM effect was measured by the degree of trust, the results were directionally consistent to the hypotheses but were not statistically significant (H2a and H2b). The purposes of study 2 were to measure the customer lifetime value (CLV) and customer referral value (CRV) of the sample subjects, to implement cluster analysis based on those values, and to show how customer value would contribute to firms. In this study, subjects answered a questionnaire including their annual service cost, frequency of communication in the given group, etc. The cluster analysis resulted in three groups and showed that CRV was significantly different although CLV was not significantly different among the three groups. The result indicates that CLV can not be used as a predictor of CRV and that customers with similar CLV could have very different CRV. It implies that marketers should pay more attention to the customers with much higher CRV than average CRV.
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    While social network which was originated from complex theory has extensively been studied in other social sciences, a serious attention has not been paid yet in Marketing. Increasing number of firms are gradually using referral marketing campaign to ...

    While social network which was originated from complex theory has extensively been studied in other social sciences, a serious attention has not been paid yet in Marketing. Increasing number of firms are gradually using referral marketing campaign to attract more customers. This research is to investigate the influences of social network on word-of-mouth (WOM) and customer referral value in the context of B2C and B2B industries. This research consists of two studies. In study 1, we performed two experiments. The purposes of experiment 1, as a preliminary experiment, were to examine the strength of tie in the social network and the type of social network in each sample service industry. Data were collected from customers in two sample service industries, mobile telephone service (B2C) and tax/accounting service (B2B) and were analyzed with Pajek. Each service customers were divided into high and low groups based on the strength of tie, resulting in four groups (B2C-A & B; B2B-C & D). Analysis results show that the strength of tie and centrality indices of four groups appeared to be very different from one another. In addition, the social network of all the four groups was a scale-free type. Specifically, groups A and B a were decentralized type, and groups C and D were a centralized type. Experiment 2 was conducted to examine the influence of the strength of tie in the social network on WOM effect. The respondents of the above four groups were given to read a positive or negative WOM-related scenario and were asked to answer a questionnaire. WOM effect was measured by two ways: one was how much the recipient would trust the received information and the other was how likely the recipient would transfer the information. The analysis results showed that the customer referral value was meaningful to B2C as well as B2B industry (H1). When an individual received a negative (vs. positive) WOM information, he/she was more likely to transfer the information to another individual (H3a). In addition, in the case of negative WOM, an individual`s intention to transfer the information was higher when the network tie was stronger, whereas in the case of positive WOM, an individual`s intention to transfer was higher when the network tie was weaker (H3b). However, when the WOM effect was measured by the degree of trust, the results were directionally consistent to the hypotheses but were not statistically significant (H2a and H2b). The purposes of study 2 were to measure the customer lifetime value (CLV) and customer referral value (CRV) of the sample subjects, to implement cluster analysis based on those values, and to show how customer value would contribute to firms. In this study, subjects answered a questionnaire including their annual service cost, frequency of communication in the given group, etc. The cluster analysis resulted in three groups and showed that CRV was significantly different although CLV was not significantly different among the three groups. The result indicates that CLV can not be used as a predictor of CRV and that customers with similar CLV could have very different CRV. It implies that marketers should pay more attention to the customers with much higher CRV than average CRV.

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    참고문헌 (Reference)

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    2 김경민, "친분 없는 구전의 영향력에 대한 소비자의 과도한 조정 효과에 관한 연구" 한국마케팅학회 25 (25): 71-95, 2010

    3 날리지앳와튼, "최적의 ‘입소문 마케팅’ 타깃은" (36) : 120-122, 2009

    4 한상만, "사회적 네트워크에서의 고객무형가치에 대한 연구" 한국마케팅학회 10 (10): 99-121, 2009

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    7 전성률, "부정적 구전정보의 유형에 따른 구전효과의 차이에 관한 연구" 한국소비자학회 14 (14): 2-44, 2003

    8 한상만, "마케팅에서 Network 연구를 위한 탐색적 고찰" 한국소비자학회 17 (17): 61-88, 2006

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    10 Gladwell, Malcom, "Tipping Point: How Little Things Can Make a Big Difference" Back Bay Books 2000

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    36 Anderson, Eugene W., "Customer Satisfaction and Word of Mouth" 1 : 5-17, 1998

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    38 Hogan, John E., "Customer Equity Management: Charting New Directions for the Future of Marketing" 5 (5): 4-12, 2002

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    42 Helm, Sabrina, "Calculating the Value of Customers' Referrals" 13 (13): 124-133, 2003

    43 Boorman, Scott, "A Combinatorial Optimization Model for Transmission of Job Information Through Contact Networks" 6 (6): 216-249, 1975

    44 류강석, "'고객만족-구전의도'의 관계에 영향을 미치는 상황요인에 관한 연구 : 유대강도와 구전계기의 역할을 중심으로" 한국소비자학회 15 (15): 27-44, 2004

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