많은 기업들이 고객만족을 강조하면서 고객만족경영시스템을 도입하였으며, 고객만족도는 기업성과를 결정짓는 중요한 요 소로 인식되어 왔다. 이에 따라 학계에서는 고객만족도와 기업성과와의 관계를 실증적으로 규명함으로써 고객만족경영의 타당성을 확보하려는 노력을 기울여왔다. 최근 들어 고객가치경영의 관점에서 구전의 중요성에 대해 관심이 모아지고 있다. Reichheld(2003)는 고객추천에 기반 을 둔 순추천지수(NPS)라는 새로운 지표를 소개하였으며, NPS는 평가 및 진단이 용이하고 기업성과와의 관련성이 가장 높은 이상적인 지표라는 주장을 하였다. 그러나 일부 연구자들이 NPS와 기업 성과지표의 관련성을 분석한 결과, NPS가 기업성과에 통계적으로 유의한 영향을 주고 있다는 근거를 발견하지 못했다고 반박하였다. 이에 따라 본 연구는 고객만족과 고객추천이 기업성과에 미치는 영향을 한국고객만족지수(KCSI)와 한국순추천지수(KNPS) 를 이용하여 실증적으로 분석해보았다. 이를 위해 기업성과에 대한 고객만족과 추천의향의 당기적인 효과뿐만 아니라 동 태적인 효과를 고려하였다. 연구결과, 고객만족과 추천의향은 기업성과에 단기뿐만 아니라 장기적으로 영향을 주는 것으로 나타났다. 산업별 분석결 과를 보면, 서비스와 비내구재의 경우 기업성과에 대한 고객만족의 효과는 단기뿐만 아니라 동태적 효과가 존재하는 것으 로 나타났다. 내구재의 경우 단기효과는 존재하지 않지만 동태적인 효과가 존재하는 것으로 나타났다. 추천의향과 기업성 과의 관계 분석에 있어서는 모든 산업에서 단기 효과뿐만 아니라 동태적 효과가 존재함을 확인할 수 있었다.

It is commonly claimed that customer satisfaction is one of the most important determinants of a firm’s performance. Thus, practitioners have shown growing interest in customer satisfaction as a means of ensuring company’s future profits, and researchers have attempted to validate this relationship with empirical analysis. Several recent studies based on nationwide satisfaction indices show that customer satisfaction (CS) has a significant impact on firm performance. By using a customer satisfaction index (CSI) at the firm level, such studies have illustrated that customer satisfaction is an important determinant of a firm’s performance. While many studies have focused on word-of-mouth(WOM) as a consequence of customer satisfaction at the customer level, relatively few studies have investigated the relationship between WOM and a firm’s performance. Although this relationship is taken for granted by many researchers, few studies have empirically examined the effect of referral on firm‘s performance. Reichheld (2003) introduced a new loyalty metric, Net Promoter Score(NPS), based on customer referral intentions. He claimed that NPS is superior to other metrics such as CS and retention as a predictor of firm performance. Nevertheless, there has been considerable debate as to whether NPS is truly superior to CS or not. This study thus attempts to investigate the effects of CS and referral intention on firm performance by using CSI and NPS. Specifically, this study considers not only current effects but also carry-over effects of CS and referral intention on firm performance. For the purpose of estimation, this study assumes that the effect of CS and referral intention on a firm’s performance in period t is geometrically decreasing over time. The data on CSI and NPS used in the analysis were obtained from KCSI (Korean Customer Satisfaction Index) and KNPS (Korean Net Promoter Score). The KCSI and KNPS were introduced by the KMAC (Korean Management Association Consulting), and they are available to the public. Our sample includes 142 firms in 53 different industries from 2001 to 2007 KCSI and KNPS. The data on financial performance of these firms were complied from the KIS-Value database by Korea Information Service Inc. Additionally, we included several control variables: firm’s age, firm’s size, the number of brands, and a dummy variable indicating whether a firm is listed or not. The results show that CS and referral intention have dynamic effects on firm’s performance, respectively. It is also found that CS has both current and lagged effects on firm’s performance in services and nondurables, but only lagged effects in durables. On the other hand, referral intention has both current and lagged effects on firm performance in all industries. The dynamic effects of CS and referral on firm’s performance imply that the effects of CS and referral should be evaluated over the time span longer than the current period. Practitioners should adjust their CS and referral strategy and policy in terms of these dynamic effects. Additionally, a CSI-NPS matrix analysis is performed to identify the priority between CSI and NPS. The results reveal that the group with high CSI and NPS scores has higher performance than other groups. Especially, in services, a high CSI group shows higher performance, and in durables, a high NPS group shows higher performance.