FORNELL教授经典的顾客满意度论文英文PDF 14页(1)

1、中企资料中国最大的资料下载网站Foundations of the American Customer Satisfaction IndexEugene W. Anderson & Claes FornellNational Quality Research Center, University of Michigan Business School, Ann Arbor, MI 48109-1234, USAABSTRACT How do we know if an economy is performing well? How do we know if a com

2、pany is performing well? The fact is that we have serious difficulty answering these questions today. The economyfor nations and for corporationshas changed much more than our theories and measurements. The development of national customer satisfaction indices (NCSIs) represents an important step to

3、wards addressing the gap between what we know and what we need to know. This paper describes the methodology underlying one such measure, the American Customer Satisfaction Index (ACSI). ACSI represents a uniform system for evaluating, comparing, and_ timately enhancing customer satisfaction across

4、firmsy industries and nations. Other nations are now adopting the same approach. It is argued that a global network of NCSIs based on a common methodology is not simply desirable but imperative.IntroductionHow do we know if an economy is performing well? How do we know if a company is performing wel

5、l? The fact is that we have serious difficulty answering these questions today. It is even more difficult to tell where we are going.Why is this? A good part of the explanation is that the economyfor nations and for corporationshas changed much more than our theories and measurements. One can easily

6、 make the case that the measures on which we rely for determining corporate and national economic performance have not kept pace. For example, the service sector and information technology play a dominant role in the modem economy. An implication of this change is that economic assets today reside h

7、eavily in intangiblesknowledge, systems, customer relationships, etc. (see Fig. 1). The building of shareholder wealth is no longer a matter of the management of financial and physical assets. The same is true with the wealth of nations.As a result, one cannot continue to apply models of measurement

8、 and theory developed for a 4tangible manufacturing economy to the economy we have today. How important is it to know about coal production rail freight textile mill or pig-iron production in the modern economy? Such measures are still collected in the US and reported in the media as if they had the

9、 same importance now as they did over 50 years ago.The problem gets worse when we take all these measures, add them up and draw conclusions* For example in early 1999, the US stock market set an all time record highCorrespondence: E. W. Anderson, National Quality Research Center, University of Michi

10、gan Business School, Ann Arbor, MI 48109-1234, USA. Tel: (313) 763-1566; Fax: (313) 76头9768; E-mail: geneaumich.cduISSN 0954-4127 print/ISSN 1360-0613 online/00/07S869-l 402000 Taylor & Francis LtdDow Jones Industrials:Priceto-Book Ratios8ouroe: Businns Week. March B. 1999Figure 1. Tangible versus i

11、ntangible sources of value, 1970-99.with the Dow Jones Index passing 11 000 points, unemployment was at record lows, the economy expanded and inflation was almost non-existent. These statistics suggested a strong economy, which was also what was reported in the press and in most commentary by econom

12、ists. As always, however, the real question is: Are we better off? How well are the actual experiences of people captured by the reported measures? Do the things economists and Governments choose to measure correspond with how people feel about their economic well-being? A closer inspection of the n

13、umbers and their underlying statistics reveals a somewhat different picture of the US economy than that typically held up as an example. Corporate earnings growth for 1997 and 1998 were much lower than in the previous 2 years, with a negative growth for 1998. The major portion of the earnings growth

14、 in 1995 and 1996 was due to cost-cutting rather than revenue growth. The trade deficit in 1999 was at a record high and growing. Wages have been stagnant in the last 15 years (although there were small increases in 1997 and 1998) The proportion of stock market capitalization versus GDP was about 15

15、0% of GDP in 1998 (the historical average is 48%; the proportion before the 1929 stock market crash was 82%). Consumer and business debt were high and rising. Even though many new jobs were created, 70% of those who lost their jobs got new jobs that paid less. The number of bankruptcies was high and

16、 growing. Worker absenteeism was at record highs. Household savings were negative.Add the above to the fact that there is a great deal of worker anxiety over job security and lower levels of customer satisfaction than 5 years ago, and the question of whether we areCQ71 Aibetter off is cast in a diff

17、erent light. How much does it matter if we increase productivity, that the economy is growing or that the stock market is breaking records, if customers are not satisfied? The basic idea behind a market economy is that businesses exist and compete in order to create a satisfied customer. Investors w

18、ill flock to the companies that are expected to do this well. It is not possible to increase economic prosperity without also increasing customer satisfaction. In a market economy where suppliers compete for buyers, but buyers do not compete for products, customer satisfaction defines the meaning of

19、 economic activity, because what matters in the final analysis is not how much we produce or consume, but how well our economy satisfies its consumers.Together with other economic objectivesuch as employment and growththe quality of what is produced is a part of standard of living and a source of na

20、tional competitiveness. Like other objectives, it should be subjected to systematic and uniform measurement. This is why there is a need for national indices of customer satisfaction. A national index of customer satisfaction contributes to a more accurate picture of economic output, which in turn l

21、eads to better economic policy decisions and improvement of standard of living. Neither productivity measures nor price indices can be properly calibrated without taking quality into account.It is difficult to conduct economic policy without accurate and comprehensive measures. Customer satisfaction

22、 is of considerable value as a complement to the traditional measures. This is true for both macro and micro levels. Because it is derived from consumption data (as opposed to production) it is also a leading indicator of future profits- Customer satisfaction leads to greater customer loyalty (Ander

23、son & Sullivan, 1993; Bearden & Teel, 1983; Bolton & Drew, 1991; Boulding et ah, 1993; Fomell, 1992; LaBarbera & Maznrski, 1983; Oliver, 1980; Oliver & Swan, 1989; Yi，1991). Through increasing loyalty, customer satisfaction secures future revenues (Bolton，199& Fomell, 1992; Rust et ah、1994, 1995), r

24、educes the cost of future transactions (Reichheld & Sasser, 1990), decreases price elasticities (Anderson， 1996), and minimizes the likelihood customers will defect if quality falters (Anderson & Sullivan, 1993). Word-of-mouth from satisfied customers lowers the cost of attracting new customers and

25、enhances the firms overall reputation, while that of dissatisfied customers naturally has the opposite effect (Anderson, 1998; Fornell, 1992). For all these reasons, it is not surprising that empirical work indicates that firms providing superior quality enjoy higher economic returns (Aaker & Jacobs

26、on, 1994; Anderson et 1994, 1997; Bolton, 1998; Capon et al., 1990)Satisfied customers can therefore be considered an asset to the firm and should be acknowledged as such on the balance sheet. Current accounting-based measures are probably more lagging than leadingthey say more about past decisions

27、than they do about tomorrows perfonnance (Kaplan & Norton, 1992). If corporations did incorporate customer satisfaction as a measurable asset, we would have a better accounting of the relationship between the enterprisers current condition and its future capacity to produce wealth.If customer satisf

28、action is so important, how should it be measured? It is too complicated and too important to be casually implemented via standard market research surveys The remainder of this article describes the methodology underlying the American Customer Satisfaction Index (ACSI) and discusses many of the key

29、findings from this approachNature of the American Customer Satisfaction IndexACSI measures the quality of goods and services as experienced by those that consume them. An individual firms customer satisfaction index (CSI) represents its served market一its customers vcrall evaluation of total purchase

30、 and consumption experience, both actual and anticipated (Anderson et oZ., 1994; Fomell 1992; Johnson & Fornell, 1991)-The basic premise of ACSI, a measure of overall customer satisfaction that is uniform and comparable requires a methodology with two fundamental properties. (For a complete descript

31、ion of the ACSI methodology please see the American Customer Staisfaction Index: Methodology Report5 available from the American Society for Quality Control, Milwaukee, WI.) First, the methodology must recognize that CSI is a customer evaluation that cannot be measured directly. Second, as an overal

32、l measure of customer satisfaction CSI must be measured in a way that not only accounts for consumption experience, but is also forward- looking.Direct measurement of customer satisfaction: observability with errorEconomists have long expressed reservations about whether an individuals satisfaction

33、or utility can be measured, compared, or aggregated (Hicks, 1934, 1939a,b, 1941; Pareto, 1906; Ricardo, 1817; Samuelson 1947). Early economists who believed it was possible to produce a cardinal measure of utility (Bentham 1802; Marshall, 1890; Pigou, 1920) have been replaced by ordinalist economist

34、s who argue that the structure and implications of utility-maximizing economics can be retained while relaxing the cardinal assumption. However, cardinal or direct measurement of such judgements and evaluations is common in other social sciences. For example, in marketing, conjoint analysis is used

35、to measure individual utilities (Green & Srinivasan, 197& 1990; Green & Tull, 1975).Based on what Kenneth Boulding (1972) referred to as Katonas Law (the summation of ignorance can produce knowledge due to the self-canceling of random factors), the recent advances in latent variable modeling and the

36、 call from economists such as the late Jan Tinbergen (1991) for economic science to address better what is required for economic policy, scholars are once again focusing on the measurement of subjective (experience) utility. The challenge is not to arrive at a measurement system according to a unive

37、rsal system of axioms, but rather one where fallibility is recognized and error is admitted (Johnson & Fomell, 1991).The ACSI draws upon considerable advances in measurement technology over the past 75 years- In the 1950s, formalized systems for prediction and explanation (in terms of accounting for

38、 variation around the mean of a variable) started to appear. Before then, research was essentially descriptive, although the single correlation was used to depict the degree of a relationship between two variables. Unfortunately, the correlation coefficient was often (and still is) misinterpreted an

39、d used to infer much more than what is permissible. Even though it provides very little information about the nature of a relationship (any given value of the correlation coefficient is consistent with an infinite number oflinear relationships) it was sometimes inferred as having both predictive and

40、 causal properties. The latter was not achieved until the 1980s with the advent of the second generation of multivariate analysis and associated software (e.g. Lisrel).It was not until very recently, however, that causal networks could be applied to customer satisfaction data. What makes customer sa

41、tisfaction data difficult to analyze via traditional methods is that they are associated with two aspects that play havoc with most statistical estimation techniques: (1) distributional skewness; and (2) multicollinearity. Both are extreme in this type of data. Fortunately, there has been methodolog

42、ical progress on both fronts particularly from the field of chemometrics where the focus has been on robust estimation with small sample sizes and many variables.Not only is it now feasible to measure that which cannot be observed、it is also possible to incorporate these unobservables into systems o

43、f equations. The implication is that the conventional argument for limiting measurement to that which is numerical is no longer allCopyright 2000. All rights reserved.Overall Customization ReliabilityOverallSatisfactionComplaints toManagementftComplaints toPersonnelPrice Given、 QualityQuality/ Given

44、 / Price (ACSIL AQiualityIDisconfirmation Distance ofFromIdealExpectationsCu8tOm，Z1，On Overall Re，ab，ty/RepurchaseLikelihoodPriceToleranceFigure 2. The American Customer Satisfaction Index modeL中企资料网中国最大的资料下载网站=A ya873that compelling. Likewise, simply because consumer choice, as opposed t

45、o experience, is publicly observable does not mean that it must be the sole basis for utility measurement. Such reasoning only diminishes the influence of economic science in economic policy (Tinbergen 1991).Hence, even though experience may be a private matter, it does not follow that it is inacces

46、sible to measurement or irrelevant for scientific inquiry, for cardinalist comparisons of utility are not mandatory for meaningful interpretation. For something to be meaningful/ it does not have to be flawless or free of error. Even though (experience) utility or customer satisfaction cannot be dir

47、ectly observed, it is possible to employ proxies (fallible indicators) to capture empirically the construct. In the final analysis, success or failure will depend on how well we explain and predict.Forward-looking measurement of customer satisfaction: explanation and predictionFor ACSI to be forward

48、-looking, it must be embedded in a system of cause-and-effect relationships as shown in Fig. 2, making CSI the centerpiece in a chain of relationships running from the antecedents of customer satisfactionxpectations perceived quality and valueto its consequencesvoice and loyalty. The primary objecti

49、ve in estimating this system or model is to explain customer loyalty. It is through this design that ACSI captures the served markets evaluation of the firms offering in a manner that is both backward- and forward-looking.Customer satisfaction (ACSI) has three antecedents: perceived quality, perceiv

50、ed value and customer expectations. Perceived quality or performance, the served markets evaluation of recent consumption experience, is expected to have a direct and positive effect on customer satisfaction. The second determinant of customer satisfaction is perceived value, or the perceived level

51、of product quality relative to the price paid. Adding perceived value incorpo rates price information into the model and increases the comparability of the results across firms, industries and sectors. The third determinant, the served markets expectations, represents both the served markets prior c

52、onsumption experience with the firms offering中企资料网中国最大的资料下载网站W Hb * Q 0T d including non-experiential information available through sources such as advertising and word-of-mouthand a forecast of the suppliers ability to deliver quality in the future.Following Hirschmans (1970) exit-voice

53、theory, the immediate consequences of increased customer satisfaction are decreased customer complaints and increased customer loyalty (Fomell & Wemerfelt, 1988). When dissatisfied, customers have the option of exiting (e.g. going to a competitor) or voicing their complaints. An increase in satisfac

54、tion should decrease the incidence of complaints. Increased satisfaction should also increase customer loyalty. Loyalty is the ultimate dependent variable in the model because of its value as a proxy for profitability (Reichheld & Sasser, 1990).ACSI and the other constructs are latent variables that

55、 cannot be measured directly, each is assessed by multiple measures as indicated in Fig. 1. To estimate the model requires data from recent customers on each of these 15 manifest variables (for an extended discussion of the survey design, see Fomell et al 1996). Based on the survey data, ACSI is est

56、imated as shown in Appendix BCustomer satisfaction index properties: the case of the American Customer Satisfaction IndexAt the most basic level the ACSI uses the only direct way to find out how satisfied or dissatisfied customers arethat is, to ask them. Customers are asked to evaluate products and

57、 services that they have purchased and used. A straightforward summary of what customers say in their responses to the questions may have certain simplistic appeal, but such an approach will fall short on any other criterion. For the index to be useful it must meet criteria related to its objectives

58、. If the ACSI is to contribute to more accurate and comprehensive measurement of economic output, predict economic returns, provide useful information for economic policy and become an indicator of economic health, it must satisfy certain properties in measurement. These are: precision; validity; reliability; predictive power; coverage; simplicity; diagnostics; and comparabilityPrecisionFrecision refers to the degree of certainty of the estimated value of the ACSL ACSI results show that the 90% confidence interval (on a 0-100 scale) for the national index is 0.2 points throug