Analyzing the commitment loyalty link in service contexts

Analyzing the Commitment-Loyalty Link in Service Contexts Mark P, Pritchard Arizona State University Mark E Havitz University of Waterloo Dennis R Howard University of Oregon This study addressed the ill-understood issue of how loyalty develops in service patrons Although many theorists hold commitment to be an essential part of this process, the link between commitment and loyalty has received little empirical attention To address this void, the study first portrayed commitment's root tendency to resist changing preference as a function of three antecedent processes Second, this portrayal formed the basis for developing a psychometrically sound scale to measure the construct of commitment Third, the scale was then used in a mediating effects model (M-E-M) to test the commitment-loyalty link Path analyses found this parsimonious structure to be a significant improvement over rival direct effects models (D-E-Ms) Results found the tendency to resist changing preference to be a key precursor to loyalty, largely explained by a patron's willingness to identify with a brand Implications of these findings for loyalty's development and research are explored Understanding how or why a sense of loyalty develops in customers remains one of the crucial management issues of our day While early interest in loyalty sought to understand why consumers repeatedly preferred certain brands of low-priced retail goods (e.g., Day 1969; Jacoby Journal of the Academy of Marketing Science Volume 27, No 3, pages 333-348 Copyright 1999 by Academy of Marketing Science 1971), attention has since shifted to look at this feature in service patrons (e.g., Pritchard and Howard 1997) In increasingly competitive markets, being able to build loyalty in consumers is seen as the key factor in winning market share (Jarvis and Mayo 1986) and developing sustainable competitive advantage (Kotler and Singh 1981) Yet, the "psychology" behind the development of customer loyalty is not well understood Several consumer theorists have recognized this deficiency and called for studies to investigate the cognitive mechanisms that form the construct (Dick and Basu 1994; Jacoby and Chesnut 1978) Until recently, one of the more frequently offered explanations of the psychology at work in a customer's loyalty was the confirmation/disconfirmation mechanism of satisfaction (e.g., Bitner 1990) However, the sufficiency of this explanation is debatable given current discussion that contends that a satisfied customer is not enough (Schulz 1998) and research that suggests that loyalty's antecedent relationships may be more complicated than we had thought (Oliva, Oliver, and MacMillan 1992) Indeed, Jacoby and Kyner (1973) argue that the thinking behind loyalty is much more complex, with several conditions or cognitions at work in the construct Another antecedent thought to provide a more accurate description of the sort of thinking that leads to customer loyalty is commitment (Day 1969) Some researchers hold that this construct could "provide the essential basis for distinguishing [and] assessing the relative degrees of brand loyalty" (Jacoby and Kyner 1973:3) Still, this view is not universally held, as others suggest that the two 334 JOURNALOF THE ACADEMYOF MARKETINGSCIENCE SUMMER 1999 constructs are either not related (Oliva et al 1992) or that they are synonymous and represent each other (Assael 1987) An intermediate view on the matter asserts the constructs are related, yet by definition are distinct, with commitment leading to loyalty (Beatty, Kahle, and Homer 1988) On the surface, some definitions of loyalty and commitment suggest that similar attitudinal biases are at work Recent work by Dick and Basu (1994) offered a delineation between loyalty and close psychological relatives like commitment Their model of effects inferred that commitment serves as a precursor to loyal attitude and its "appraisal [function]" of continued patronage Restated, the formative relationship, in essence, casts commitment as the "emotional or psychological attachment to a brand" that develops before a customer would be able to determine that their repeat purchase behavior was derived from a sense of loyalty (Beatty and Kahle 1988:4) Many in the marketing field have defined loyalty as a composite blend of brand attitude and behavior, with indexes that measure the degree to which one favors and buys a brand repeatedly (e.g., Day 1969; Pritchard and Howard 1997) These loyalty indexes typically describe what proportion of a patron's behavior was based on or attributed to loyal attitude (i.e., P[behavior]/attitude) Commitment differs from this composite definition as it is usually considered in purely cognitive terms that measure consumer attitudes of attachment to a brand Morgan and Hunt (1994) endorse this distinction and describe commitment as an enduring desire to continue an attachment [relationship] Kelley, Donnelly, and Skinner (1990:322) contend that the attitudinal domain of this attachment is best understood in symbolic terms (i.e., customer identification), as committed patrons tend to identify strongly with the goals and values of an organization Reviews have tracked loyalty's development through behavioral and attitudinal phases of measurement to the current composite perspective (e.g., Jacoby and Chesnut 1978) Over time, the field's attention to loyalty's assessment has been a dominant issue So much so, that few studies have investigated the nature of commitment's link and role in explaining the construct Instead, the dated lament that "no explanation of the phenomenon [loyalty], no indication of why?" continues to loom over the field (Jacoby 1971:26) The absence of work on the relationship is due, perhaps, to the fact that some still view the two constructs as one and the same Lack of attention may also be due to the paucity of consumer research on commitment's definition and measurement, a concern voiced by several authors in their call for that construct's development (e.g., Kelley and Davis 1994; Morgan and Hunt 1994) Our article attempts to address this void Specifically, our investigation of the commitmentloyalty relationship first asks, "What is the underlying psychology [cognitive mechanism] that defines commitment?" A comprehensive review of the literature helps form a theoretical basis for clarifying what commitment means We then examine the issue of how commitment influences loyalty CONCEPTUALIZATIONS OF COMMITMENT Definitional work on the construct of commitment began in the sociology and psychology disciplines Early sociological perspectives reflected an interest in the societal and social factors that constrained or committed individuals to a consistent line of action (Becker 1960; Kanter 1968), whereas psychologists defined commitment in terms of decisions or cognitions that fix or bind an individual to a behavioral disposition (Festinger 1957; Kiesler 1971) Conceptualizations of commitment as a relationship, in the context of marriage or work, have interpreted the construct within a social-psychological framework For example, research undertaken by organizational behavior theorists explained an employee's commitment to a job as "the relative strength of an individual's identification with and involvement in a particular organization" (Mowday, Porter, and Steers 1982:27) Here, the construct was conceptually characterized by intent to remain, along with certain personal and environmental factors that underpin that intent In this sense, commitment was inferred not only from the employee's beliefs and opinions (a series of binding cognitions) but also by their level of intent to act in a particular way Conceptual renderings in other disciplines characterize commitment as a multidimensional phenomenon composed of several cognitive features (e.g., Kiesler 1971) However, consumer research has seldom considered the complex nature of the construct For example, Kelley and Davis (1994) examined customer (service) commitment as a general trait, adapting Mowday, Steers, and Porter's (1979) measure of organizational commitment Similarly, Morgan and Hunt's (1994) study on relationship marketing used the same scale Viewing commitment as a single, general trait is somewhat problematic, given the multiple conceptual ingredients noted in the construct's definition and the fact that later work found some evidence of a more complex factor structure (Mowday et al 1982).1 Other consumer studies have used unidimensional measures to assess commitment (e.g., Beatty et al 1988), yet the epistemological depth and methodological sophistication of these instruments is questionable The primary criticism of such measures is the contention that any theory of commitment should move beyond a general expression of attachment and incorporate an understanding of the psychology inherent in binding a person to that disposition Other constructs have benefited from this sort of specification Satisfaction, for example, is recognized as a Pritchard et al / THE COMMITMENT-LOYALTY LINK level of emotional affect yet is more specifically described by its formative process, as a function of confirmation/ disconfirmation (Oliver 1980) Work by Crosby and Taylor (1983) provided a definition of commitment that articulated a more involved view of the construct Based on experimental research suggesting that commitment resists influence and change (e.g., Kiesler and Sakumura 1966), the authors described customer commitment as a stable preference that was bound by an attitude of resistance to change Crosby and Taylor maintained that the "tendency to resist changing preference" provided the principle evidence of commitment and that this attitude was best explained by two antecedent processes (p 414) The first formative process dealt with cognitive structure and how people managed information about their preference (informational processes) Crosby and Taylor (1983) argued that the need to maintain a consistent informational structure (e.g., beliefs, reasons for purchase/repurchase) helped maximize one's resistance to change The second process dealt with personal attachment and whether people identified with important values and self-images linked to a preference (identification processes) The more strongly consumers identified with the values and images embodied by a particular brand, the greater their sense of resistance to change that preference would become Earlier work by Salancik (1977) provides an interesting contrast, as he felt people became committed when three perceptual states revocability, publicness, and volition-were engaged Commitment was strengthened when people sensed their decision was (1) not easily reversed, (2) known to significant others, and (3) undertaken as an exercise of free choice The first two states, revocability and publicness, appear to be captured by the informational and identification processes implied in Crosby and Taylor's (1983) definition Revocability is determined by the psychological cost entailed in rethinking and altering the informational structure that supports one's commitment, while publicness involves a willingness to be explicitly identified with the images and values of a (brand) preference by significant others (e.g., friends, family) Volition, the third state mentioned by Salancik, refers to people's perception that their preferences are "free" (i.e., not dictated by any constraints) When people sense that their choices are unhindered, the resulting commitment is likely to be stronger and more deeply held While Salancik (1977) used the three processes mentioned above to define the construct, our view is consistent with Crosby and Taylor's (1983) definition This perspective specifies information, identification, and volition as antecedent processes of commitment that facilitate its root tendency, resistance to change Further review of these psychological processes and their effect on resistance to change follows 335 THE ANTECEDENT PROCESSES OF COMMITMENT Informational Processes Informational complexity One factor that contributes to the attitudinal stability of commitment uses the processing of information to form complex cognitive structures Deviation from an attitude (sense of resistance) that is supported by a complex cognitive structure is said to involve a high psychological cost to an individual Salancik (1977) discussed commitment's revocability in terms of the psychological cost involved in the cognitive reordering and rethinking of what was known (about the product) When complex informational schema gird a person's commitment, changing your mind becomes more difficult, as accommodating disparate cognitions requires even greater change (Millar and Tessar 1986) Much of a person's resistance to change may be driven by a desire to avoid the cost of dissonance and the disruption it brings to one's organization of salient cognitions (Festinger 1957) For the highly committed, these costs are more pronounced than those incurred when change is contemplated in the simple structure of the less committed (Robertson 1976) Cognitive consistency In addition to complexity, consistency is also part of commitment's informational processes While complex informational structures form a detailed array of cognitions that support commitment, consistency works by defending those structures and one's commitment when facing conflicting information In this sense, the informational processes of commitment not only serve as a cognitive blueprint to process and accumulate consistent information but also as a defense mechanism that reinterprets, suppresses, or loses information that is inconsistent (Tessar and Leone 1977) When this sort of "information processing parsimony" is at work, resistance to change is maximized, as people may seldom be challenged by conflicting information (Holbrook 1978) Based on Rosenberg's (1960) work, Crosby and Taylor (1983) described this operant condition as the need to maintain consistency in what one thinks and feels about a preferred brand Dick and Basu (1994) argued that when these "antecedents are consistently favorable for a brand the degree of differentiation in relative attitude [such as resistance] increases" (p 105) Just as consistency within each antecedent has an effect, congruency between all of them creates a further "psycho-logical" reason for commitment (Crosby and Taylor 1983:414) Confidence Another element at work in commitment's informational processes is confidence Berger and Mitchell (1989) noted that consistent information from repeated exposure can provide greater brand-relevant cognitive elaboration (i.e., informational complexity), and enhance a consumer's confidence in a resulting attitude 336 JOURNALOF THE ACADEMYOF MARKETINGSCIENCE SUMMER 1999 Attitudinal confidence has been described as an evaluative mechanism where consumers assess whether brand beliefs are accurate and their attitude warranted (Dick and Basu 1994) Day (1970) argued that when involved consumers are confident about their judgements, it stabilizes their brand attitude Burton and Netemeyer's (1992) causal model supported this notion, as voter confidence maintained election preference over time Whereas a lack of confidence, when reflected as uncertainty or ambiguity about the information to hand, increased the potential for attitude change subjective symbol (Solomon 1983) Some researchers consider that the highest form of commitment is driven by a need for social (symbolic) representation and selfidentity (Buchanan 1985) Theories about the impact of desired values and self-images on commitment have been tested and collectively suggest that the degree to which consumers publicly and personally identify with a brand directly effects the resistance to change that preference (e.g., Beatty et al 1988) Identification Processes Volitional choice Several theorists hold that consumer perceptions of volition also play an important role in any theory of commitment (e.g., Bagozzi 1993) Salancik (1977) argued that when perceived volition is high, a person should feel more personally responsible for their decisions than when perceived volition is low Kiesler (1971) also found that perceptions of free choice and selfresponsibility operate at the very core of one's commitment Indeed, free choice is seen by some as a required condition before attitudes of internal commitment can develop from behavior (Shamir 1988) This is because the freedom to choose greatly influences the internal organization of an action's meaning and hence the degree of commitment Volitional choice can best be described as a process that involves both a freedom from constraints and a freedom to choose Freedom from refers to the notion that brand choice is elicited freely and not constrained by external considerations that might limit one's sense of personal ownership in that decision As Shamir (1988) noted, we are less likely to feel personally committed (to our choice of product or service) if that decision had to first meet the requirements of certain external actors The freedom to component of volitional choice refers to the potential for choice to reflect meaningful action or effort (Bagozzi 1993) Research suggests that when people sense they are acting freely in choosing an object, they attribute attitude (meaning) toward that object (Bem 1967) For instance, when consumers choose Rainforest Crunch or another ice cream from a wide range of 31 flavors, they usually infer greater meaning in that selection (e.g., "It's my favorite or the best alternative") Cialdini, Cacioppo, Bassett, and Miller's (1978) investigation of the "low-ball phenomenon" noted that perceptions of free choice can form the basis for a customer's cognitive commitment to an outcome Their research argued that once volitional processes were engaged, consumers developed a sense of resistance to change in which they were prepared to continue with an initial decision even though certain sales incentives were withdrawn (e.g., "Those options are extra" or "The boss won't agree to the sale at this price") An experiment undertaken by Position involvement Some distinction should be made between product involvement (Zaichkowsky 1985) and the identification processes that operate in position involvement Freedman (1964) distinguished the two forms of involvement by noting that product involvement results when important values are made salient by a certain decision situation (e.g., the need to buy a hotel room or purchase an air ticket), whereas position involvement is evident when those values or self-images are identified with a particular stand or brand choice Crosby and Taylor (1983) suggest that this link between a preference and one's personal values and self-images strengthens resistance to change The process of identification can also be considered in terms of consistency People can evaluate their position involvement to determine whether their public association with the brand in question is consistent with certain values and self-images In this context, the values and self-images perceived in any public association with a brand (i.e., social self) would be personally evaluated to see if they are truly consistent with the consumer's internal views (i.e., personal self) Salancik (1977) takes a slightly different stance Rather than internal views determining consistency via an assessment of shared values (with a brand/ company), Salancik argued that commitment was maximized when that sense of consistency was driven by the public persona (publicness) Here, the more public or well known our association is, the greater one's desire is to remain consistent and resist changing that relationship Public connections or associations with certain brand images are often used for the purpose of self-presentation, with some being more prone than others to this sort of desire (Bearden, Netemeyer, and Teel 1989) The desire to appear consistent publicly is believed to exert considerable influence over a wide range of human actions Assael (1987) contends that purchasing or repurchasing in consumer behavior contexts is frequently based on symbolic rather than utilitarian value In this sense, symbolic purchasing indicates that the product is purchased not for what it is but for what it means as a Volitional Processes Pritchardet al / THE COMMITMENT-LOYALTYLINK 337 Freedman and Steinbruner (1964) also strongly supported the fact that high choice in the initial decision greatly increased one's resistance to change These findings and the previous discussion purport that volitional processes (i.e., perceptions of freedom) can influence the sense of self-responsibility and meaning choice reflects and enhance the tendency to resist changing preference In summary, the literature reviewed here suggests that psychological commitment is best defined by a tendency to resist change and that three formative processes activate this tendency Contrary to past consumer research that viewed commitment simplistically as a general attitude of attachment (e.g., Beatty and Kahle 1988), our study proposes that a more complex network is needed to assess the construct FIGURE Competing Models of Commitment and Its Link With Loyalty Antecedent Processes Pnnc:palEwdence LatentOutcome(s) of Commitment of Commttment of Commitment ~ r e c t Effects Model ] (D-E-M |) Resistance to Change: The Key Mediating Variable? Previous studies of purchase behavior (Beatty and Kahle 1988), consumer expectations (Kelley and Davis 1994), and advertising effectiveness (Robertson 1976) all attest to commitment's ability to affect a variety of outcomes Our conceptualization of commitment holds that informational, identification, and volitional processes are active precursors of the construct in that they maximize the tendency to resist changing preference As the principle evidence of commitment, resistance to change is central to a variety of outcomes, the foremost of which is loyalty (Jacoby and Kyner 1973) Path analytic work has shown that in some relationships, commitment is best portrayed as a key mediating variable (Kelley and Davis 1994; Morgan and Hunt 1994) In a similar vein, we postulate that resistance to change, as the primary evidence of commitment, will act as a mediator between the construct's antecedent processes and loyalty According to Baron and Kenny (1986), a variable is "said to function as a mediator to the extent that it accounts for the relation between the predictors [i.e., antecedents] and the criterion [i.e., outcomes]" (p 1176) With this in mind, our proposed mediating-effects-model (M-E-M) describes the relationship between resistance to change and loyalty as substantive and direct, while the informational, identification, and volitional processes, although related to loyalty, will have a significant yet indirect effect (via resistance to change) on that outcome In other words, commitment's antecedent processes will first foster a sense of resistance to change, which in turn will mediate the effect of these processes on loyalty (see Figure 1) Rival direct effects models A current practice in structural equation modeling calls for researchers to move beyond simply testing proposed models by comparing their performance with rival structures (Bagozzi and Yi 1988) Direct Effects Model II (D-E-M If) Jl~-~ProcessesJ ~ Morgan and Hunt (1994) examined commitment's role as a mediator in this manner, comparing proposed and rival models This work looked at whether outcomes (such as loyalty) were best explained by a key mediating variable model of direct and indirect effects or by a competing model of direct effects Their findings supported mediation by noting it offered the most parsimonious explanation of commitment's relationships Although our proposed model is a M-E-M that is consistent with Crosby and Taylor's (1983) definition, comparing its performance with direct-effects-models (D-E-Ms) will provide a way to (1) test this specification and (2) clarify whether mediation is in fact the most accurate way to describe the construct's link with loyalty In essence, the D-E-Ms shown in Figure can be used to represent a competing theory of commitment, which defines the construct as the sum of its informational, identification, and volitional processes (Salancik 1977) Resistance to change and loyalty are alike in these models in that they are both outcomes of commitment Given commitment's close link to loyalty, a simple test of the two competing definitions could be undertaken by noting which model (M-E-M or D-E-M I) offers the most effective explanation of the criterion, loyalty Another contrast with D-E-M I can determine whether the antecedent processes 338 JOURNAL OF THE ACADEMY OF MARKETING SCIENCE of commitment are discrete in maximizing the principle evidence of the construct or whether they should also be considered as formative agents of loyalty This tests the M-E-M network's discriminant validity by determining whether the processes distinguish between resistance to change and loyalty and explain more of the construct's root tendency (Burnkrant and Page 1982) D-E-M theses that direct links between commitment's processes and loyalty exist -do have some support Empirical studies have linked informational (i.e., that loyal users agglomerate more information about important brand decisions), identification (i.e., that the loyal are more interested than the nonloyal in status/value associations), and choice processes (i.e., that loyalty is a function of choice from a set of alternatives) as important correlates of brand loyalty (Carmen 1970; Jacoby, Chesnut, and Fisher 1978; Jacoby and Kyner 1973) Although this research does not directly support causality, recent conceptual work on loyalty's antecedents does propose several links that rival our view of commitment's processes Dick and Basu (1994) argued that loyalty is directly caused by attitude accessibility (i.e., the ease of retrieving an attitude from the informational structure), confidence, cognitive consistency, and centrality (i.e., the degree to which brand attitude is related to an individual's values) Empirically testing some of these proposed links (in the D-E-Ms) should clarify if such relationships actually exist or whether resistance to change intervenes and mediates these effects on loyalty Specific analyses can also be used to test whether resistance to change functions as a mediator These tests will address certain questions or "conditions" for mediation (Baron and Kenny 1986:1176) The first two questions are examined by the M-E-M They ask, (a) Do commitment's three antecedent processes have a significant effect on resistance to change? and (b) Does resistance to change have a significant effect on loyalty? A D-E-M (i.e., D-E-M I in Figure 1) will then examine condition (c) and address the question, Do the antecedent processes also have a significant direct effect on loyalty? D-E-M II will then answer a final question, (d) Do the previously significant effects of the antecedent processes on loyalty (noted in c) become nonsignificant when the path between resistance to change and loyalty is opened? These structural comparisons should corroborate the nature of commitment and the role of resistance to change in explaining customer loyalty METHODOLOGY The primary intent of this study was to examine the commitment-loyalty relationship However, prior to this investigation, a valid and reliable measure of commitment needed to be developed The following discussion outlines the methods involved in achieving these objectives SUMMER 1999 Overview of Scale Development The commitment items The development of a psychological commitment instrument followed scale construction procedures recommended by Churchill (1979) It began with a literature review that generated an item pool designed to measure psychological commitment's hypothesized components Sixty-five items were initially generated to reflect psychological commitment's tendency to resist change and the five components involved in that phenomenon's antecedent processes (informational complexity, cognitive consistency, confidence, position involvement, and volitional choice) A panel of judges examined the content validity of the item pool Three faculty members and three doctoral students were given the conceptual definitions of each component and asked to categorize each item by its theme Further panel evaluation of the face validity for each item was undertaken by rating its appropriateness and clarity (wording) Consensus on categorization, fit, and clarity ratings of and above (on a scale of to 5) admitted items to the final pool The rigor of repeatedly examining content validity during item generation suggested by Churchill resulted in the retention of 51 items (cf Bearden et al 1989; Zaichkowsky 1985) A 7point numeric bipolar scale ranging from strongly disagree (1) to strongly agree (7) was attached to each statement (e.g., "I would resist changing my preference to use brand X.") Wording for just less than half of the items was randomly reversed to avoid response bias A self-administered questionnaire was given to an initial sample of 391 airline and hotel patrons to determine the dimensionality and reliability of the scale items Commitment items that remained following an iterative sequence used in scale purification (i.e., internal reliability and exploratory factor analysis: Zaichkowsky 1985) were then examined with a confirmatory factor analysis (CFA) that included measures of the loyalty construct (cf Bearden et al 1989; Ruekert and Churchill 1984) CFA again tested the validity of this initial measurement model by reexamining it with data from a second sample of 290 patrons Following this, the two samples were combined (N = 681) for a final psychometric assessment The Loyalty Index Day (1969:30) first suggested using a simultaneous consideration of loyal attitude and behavior to generate a composite index of the construct He argued that the most effective way to view the behavioral aspect of loyalty was with a proportion of purchase measure that concentrated on a specific brand However, as Day noted, consistency in a person's purchase behavior did not necessarily mean that he or she was brand loyal That behavior might be spuriously driven by price and not the steadfast allegiance (attitude) attributed to loyalty Thus, brand attitude had to be assessed as well as brand behavior While Day had used a single statement to assess the attitu- Pritchardet al / THECOMMITMENT-LOYALTYLINK 339 dinal component, subsequent studies developed multiitem scales for this (Muncy 1983; Selin, Howard, Udd, and Cable 1988) By and large, these scales reflected work by Cunningham (1967) and asked questions about brand preference (e.g., was it their favorite or the best brand?) and the consumer's willingness to switch in given situations (e.g., if the brand was overpriced or not available or in stock) FIGURE Sample Frame and Content Inmal Data Collectson (n=391 ) Loyal attitude items were recoded so that indicated strongly agree and strongly disagree Using Day's (1969) equation, the ratio proportion of purchase P[B] was then divided by mean attitude scores [A] In this sense, high proportion of purchase when divided by strong attitude created index scores that were closer to (true loyalty), whereas low proportion of purchase when divided by weak attitude created scores that were closer to (low loyalty) Our study used two previously developed attitude scales to create two composite (i.e., P[B]/A) indicators of the construct (see the appendix) One of the advantages of assessing loyalty in this manner is that it "allows investigation of the phenomenon from a causal perspective" where questions about "how underlying processes influence loyalty" can be addressed (Dick and Basu 1994:102) Prior to addressing the issue of causality, measurement validity was examined with AMOS 3.61, a structural equations program (Arbuckle 1994, 1997) Study Samples A convenience sample of 421 consumers was asked to provide data for the initial stages of scale purification Missing data reduced this sample to 391 The age of the subjects, 46 percent of whom were female, ranged from 17 to 76 years, with amean age of 42 years Respondents were intercepted at a city airport and asked to complete the questionnaire in one of four contexts (see Figure 2); the consumer's favorite or most recently used brand of airline service or their favorite or most recently used brand of hotel service The use of favorite or most recent brand ensured response variability (i.e., different levels of attachment) A second convenience sample (n = 290) of customers was surveyed for two specific brands Specific brands of service were designated in the airline and the hotel industry to further confirm the commitment and loyalty measures developed with the first sample Convenience samples were collected on site at each of two designated services (United Airline patrons: N1 =148; Hilton Hotel guests: N2 =142) Sixty percent of this sample was male Respondents ranged from 17 to 80 years, with an average age of 46.6 years A primary screening question was used in both samples to ensure that respondents had used the respective brand of service more than once in the past year The two convenience samples were then combined as one data set (N = 681) to provide overall measurement and structural assessments Favorite Brand of AJrhne Service (n t =99) Favorite Brand of Hotel Serwce (n2=95) Most Recenl Brand of Airhne Service (n =101) Most Recent Brand of Hotel Service (n4=96) Second Data Colleetton (n=290) I Airline Servtce (n5=148l Hotel Service (n6=142) Airline Patrons Hotel Patrons (N =333) (N =348) RESULTS Developing and Evaluating the Measures Item reduction The 51 items that emerged from the content validity process were subjected to scale purification procedures using responses from the initial sample (n = 391) Survey responses were randomly split into two halves so as to cross validate the decisions made during the item reduction phase Cross validation is recommended to minimize error probability and capitalization on chance Scale purification began with the computation of alpha coefficients for resistance to change and the five components involved in that phenomenon's antecedent processes (informational complexity, cognitive consistency, confidence, position involvement, and volitional choice) The decision criteria for item deletion involved cross validation between the split samples, with item elimination improving corresponding alpha values to the point at which all items retained had corrected item-to-total correlations greater than 0.4 (cf Zaichkowsky 1985) The 36 items common to both split samples were then subjected to exploratory factor analysis (principal axis factoring with an oblique rotation) Cattel's scree test indicated that a fourfactor solution was appropriate in both cases The general structure of all four factors in both split samples was consistent, although the reduction of the hypothesized components to that of a four-factor solution did initially lead to some mixed item themes Further screening of items to en- 340 JOURNALOF THE ACADEMYOF MARKETINGSCIENCE SUMMER 1999 TABLE Developing the Psychological Commitment Instrument: Principal Axis Factoring Pattern Matrix for 16 Items (n = 391) Initial Item Theme Resistance to Change Resistanceto Change Resistance to Change Resistance to Change4 Volitional Choice Volitional Choice2 Volitional Choice Volitional Choice InformationComplexity InformationComplexity2 InformationComplexity3 InformationComplexity4 Position Involvement1 Position Involvement2 Position Involvement3 Position Involvement4 Eigenvalues % total variance Factor Factor Factor Factor 63 01 -.03 01 00 -.04 -.08 02 -.03 10 -.11 -.02 -.07 06 04 -.01 10 -.01 -.04 05 05 11 -.02 01 -.10 64 74 73 07 -.05 23 - 12 -.09 06 -.01 22 -.02 02 30 53 6.16 38.50 68 72 57 83 -.03 07 02 02 08 -.04 -.02 19 2.02 12.70 Communality -.03 -.01 00 - 14 86 80 47 49 43 46 59 39 49 48 55 47 46 55 36 60 55 43 15 62 1.49 9.30 1.02 6.40 66.90 - 78 -.65 -.81 -.49 NOTE: Item/factorloadings are italicized sure consistency and significance of factor loadings across samples resulted in a final four-factor structure with a common core of 24 items The split samples were then combined to analyze this common core (n = 391) Again, internal homogeneity was examined, and eight items were eliminated (item-to-total correlations < 0.4) The remaining 16 items were then subjected to a second principal axis factoring, with the solution restricted to four factors This structure was again supported, with eigenvalues greater than 1.0 for all four factors (see Table 1) Three additional items were eliminated Two had low communality estimates (< 0.4) in the volitional choice and information complexity factors (Tinsley and Tinsley 1987), and the third had a significant cross loading in the position involvement factor (see Table 1) The remaining 13 items provided a "simple structure" (Bearden et al 1989:475), with four thematically consistent factors providing an assessment of commitment's three antecedent processes and its central tendency, resistance to change (see the appendix) These findings represent a parsimonious explanation of the data in which cognitive consistency and confidence did not converge as discrete components While the scale methodology employed here sought to achieve parsimony by determining the principal components of the construct, the external validity of this four-factor solution requires further substantiation with confirmatory analyses For ease of the discussion, this measure of commitment is referred to hereafter as the psychological commitment instrument (PCI) Reliability and CFA The reliability and structure of the PCI was subsequently examined using alpha coefficients and CFA A CFA was conducted with the PCI's four factors and a two-item measure of brand loyalty adapted from previous studies (Muncy 1983; Selin et al 1988) The first analysis of the 15-item, five-factor measurement model was undertaken with the initial sample (n = 91) This produced a chi-square statistic of 124.1 (df= 80, p < 01), with goodness-of-fit (GFI) and adjusted goodness-of-fit (AGFI) indices of 96 and 94, respectively Each indicator loaded significantly on its designated factor (p < 01) Although the overall chi-square statistic is significant, the model's fit represents a substantial improvement over the chi-square values obtained from one-factor (X2 = 1495.0; df= 90,p < 01) and null models (Z2= 2696.4; df= 105, p < 01) The sensitivity of the X2 test does pose some problems for large samples as "even minute differences tend to be detectable" (Hayduk 1987:167) Several researchers have suggested that sample sizes should range from 100 to 200 to avoid these problems of misspecification Hoelter (1983) addressed the issue of sample size sensitivity by providing a formula for what he termed the "critical-N" This CN is "the size that a sample must reach in order to accept the fit of a given model on a statistical basis" (p 330) Using p > 05 as the criterion for acceptable fit, a CN of 326 was calculated for the current measurement model This exceeded Hoelter's rule of thumb, which argued that models with a CN greater than 200 were admissible, as problems with Z2 significance tended to Pritchardet al / THE COMMITMENT-LOYALTYLINK 341 reflect a trivial misspecification that was more a feature of sample size than design Given this initial support, the five-factor correlated model was again tested with the second population of hotel and airline patrons (n = 290) Here, the CFA generated a chi-square statistic of 205.3 (df= 80, p < 01), with a GFI and AGFI of 92 and 87, respectively Although not as strong as in the initial sample, these findings help to confirm the solution's fit For a final assessment of the measurement model's performance, we combined both samples and reexamined the data (N = 681) The results from this CFA are shown in Figure The GFI and AGFI both corroborate the solution's adequacy (i.e., > 9), and Bentler's (1990) comparative fit index (CFI) and Hoelter's (1983) CN size provide further evidence of an appropriate fit between the model and this larger data set In Figure 3, the loadings on the right of each of the 15 items are standardized regression weights On the left of each item are squared multiple correlations that reflect how much of each item's variance was explained by its respective factor Construct reliability estimates for the four PCI components and the loyalty measure were tabulated from these results (Bagozzi and Yi 1988) All of the scales demonstrated adequate internal consistency (construct estimates: Volitional Choice, 80; Position Involvement, 84; Information Complexity, 83; Resistance to Change, 81; and Loyalty, 91) The more conservative variance extracted estimates were also calculated and provided further support for the scales' soundness (Volitional Choice, 57; Position Involvement, 63; Information Complexity, 62; Resistance to Change, 53; and Loyalty, 84) Correlations between the five factors are also shown in Figure The PCI's four components are all positively correlated, which provides some evidence of convergent validity Although the strength of these associations vary, the measure's discriminant validity is supported by the fact that the three process-based components (volitional choice, position involvement, and informational complexity) have stronger relationships with commitment's principle tendency (resistance to change) than with a closely related outcome (loyalty) (cf Ruekert and Churchill 1984) Closer examination of the high correlation between position involvement and resistance to change does, however, raise another question about the PCI's discriminant validity Fornell and Larker (1981) recommended that the square of the correlations between constructs should not exceed their explained variance estimates While this condition was satisfied in all the other factors, it suggests that resistance and position involvement may not be distinct This particular dilemma was raised by Crosby and Taylor (1983) who noticed that "separating the influence of involvement from other commitment factors is problematic because of a tendency for these phenomena to coexist in the consumer's psyche" (p 415) FIGURE Confirmatory Factor Analysis (N = 681) 48 69 55 74 68 82 70 84 24 \ 51 78 71 3t ~ ,,/ / / NOTE: Chi-square = 232.17 (df 80); p < 01; goodness-of-fitindex (GFI)/adjustedgoodness-of-fitindex (AGFI) 96/.94; comparativefit index (CFI)/parsimoniousnormed fit index (PNFI) = 97/.73; CN = 299.00 Burnkrant and Page (1982) recommended a series of tests to help clarify whether such factors should stand alone or be combined In our case, this procedure compared the existing model (Z2 = 232.1, df= 80, p < 01), in which loyalty and the four separate PCI factors were allowed to correlate, to one in which resistance to change and position involvement were hypothesized to have a unity correlation that depicted them as unidimensional (Z2= 240.1, df = 81, p < 01) A chi-square difference test between the two structures supported Figure and established that the two should be considered as discrete factors (Ax2= 8.0, dr= 1,p < 01), a finding consistent with theory and our earlier factor analyses (see Table 1) The measurement work done to this point has used multiple samples to confirm the internal consistency and integrity of the factor structure proposed by our initial scale development procedures These findings hold that commitment is a multidimensional construct that is related to, yet distinct from, customer loyalty Additional evidence of validity Before testing the structural relationship between commitment and loyalty, the measurement model's validity was reexamined in different contexts and situations AMOS (3.6) was again used to review the validity of the model in two different con- 342 JOURNALOF THE ACADEMYOF MARKETINGSCIENCE SUMMER1999 texts A simultaneous CFA that fitted the model to data from both service populations was conducted (Arbuckle 1997:441) While the same model structure was specified for the airline (n = 348) and hotel patrons (n = 333), the regression weights and the unique and common variances were allowed to differ in each group Similar to Figure 3, these results substantiated the validity of the measurement model in both cases (Z2= 295.9, dr= 160, p < 01, GFI = 95, AGFI =.92, CFI = 97, CN = 439) Subsequent alpha reliability estimates in the aidine and hotel samples noted that all of the model's factors were internally consistent (i.e., > 80) The integrity of the model was again reviewed to see if its specifications held true in different situations Essentially, the favorite and most recent brand groups that generated the initial sample (see Figure 2) provided a variety of consumer-brand responses to test this feature Generally, most recent brand responses are thought to be characterized by lower levels of attachment due to the presence of habitual or happenstance purchasers (Beatty and Kahle 1988), whereas favorite brand responses tend to reflect higher levels of consumer attachment (Jacoby and Chesnut 1978) To examine the model's stability in both situations, we again used a simultaneous CFA with the two populations Regardless of whether low or high levels of attachment were being assessed, the parameters specified by the model demonstrated an acceptable fit (X2 = 237.7, df= 160, p < 01, GFI = 93, AGFI =.89, CFI = 97, CN= 313) Corroborating the model's fit in this manner encouraged a specific test of the PCI's nomological validity to determine whether the scale was not simply consistent in but also sensitive to different situations (Ruekert and Churchill 1984) Zaichkowsky (1985) tested her measure's validity by proving its ability to detect low and high involvement decision situations In a similar vein, a valid measure of commitment should also be able to differentiate between favorite and most recent brand responses CFA was again employed to test whether the favorite and most recent groups had different factor means (cf Arbuckle 1997:467) Analyses were run simultaneously for both groups The first analysis tested the significance of different factor means This imposed group-invariant factor loadings and intercept patterns on both groups and fixed the most recent brand group's factor means to zero (~2 = 269.8, dr= 180,p < 01) A second CFA tested the null hypothesis that the factor means were the same in both groups Group-invariant factor loadings and intercept patterns were again imposed; however, this time the favorite brand group's means were also set to zero (X~= 287.2, df= 185, p < 01) The chi-square difference between the first and second analysis (Ax2= 17.4, df= 5, p < 01) rejects the notion that the two groups had similar means and supports the contention that the measures were sensitive to different decision situations (Note that mean contrasts between the two groups consistently characterized the favorite brand group with stronger attitudes of commitment.) The Structure of the Commitment-Loyalty Relationship Testing the M-E-M The procedures used thus far have found the PCI to be a valid and reliable measure of commitment that is related to, yet distinct from, a composite indice of loyalty (Day 1969) This factor analytic work found three components (information complexity, position involvement, and volitional choice) to represent the effect of commitment's antecedent processes on the construct's principle tendency, resistance to change The ME-M holds that a single causal path from resistance to change provides the best explanation of why loyalty develops (see Figure 1) This model restricts the effects of commitment's three antecedent processes so that they only have indirect relationships with loyalty via resistance, the key mediating variable Three path analyses were conducted to examine the fit of the M-E-M: one with the total sample (N= 681) and the other two with the airline (n = 348) and hotel (n = 333) subsampIes Analysis of the combined data set noted a significant chi-square statistic (df= 83, p < 01), with a GFI and AGFI of.96 and 94 The strength of the latter fit indices (> 9) and the CN of 296 supported accepting the model In fact, indicators from all three analyses suggested a good fit between this model and the data (see results in Table 2) With the exception of the informational complexity resistance to change link in the hotel sample, 11 out of the 12 direct pathways specified in the three sample analyses had significant structural coefficients (p < 01) In each case, paths from the antecedent processes were able to explain more than 60 percent of the variance in resistance to change (simultaneous multiple correlations [SMCs] = 63, 67, 60) Identification, represented by position involvement, consistently made the strongest contribution to a consumer's sense of resistance (t3s = 66, 70, 64) The resistance to change ->loyalty link was also significant in each sample (SMCs > 30) This link was particularly strong in the airline sample, with more than half of the variance in customer loyalty accounted for by this path (SMC = 52) The first two conditions for mediation were supported by these results, namely, that the antecedent processes had an effect on resistance to change, and resistance to change had an effect on loyalty Testing the D-E-Ms Competing models that proposed direct links between commitment's processes and loyalty were also tested (see Figure 1) Like the M-E-M, analyses of D-E-M I with the airline, hotel, and combined samples noted significant chi-square statistics (df = 81, p < 01) Pritchard et al / THE COMMITMENT-LOYALTY LINK 343 TABLE Analysis of Competing Structural Models M-E-M Path Direct effects ([is) VC ~ RC PI ~ RC IC ->RC RC ->Loyalty VC ~ Loyalty PI ->Loyalty IC ->Loyalty SMCs (R2) RC Loyalty Model fit X2 (dJO GFI/AGFI Rmr CF1 / PNFI CN0s Airlines (n = 348) Hotels (n = 333) 15'* 66** 23** 72** 14"* 70** 11 56** 63** 52** 67** 31'* D-E-MI Combined (N = 681) 15"* 64** 17'* 59** 60** 35** D-E-MH Airlines (n = 348) Hotels (n = 333) Combined (N = 681) 14" 72** 24** 14' 72** 11 14'* 69** 17'* 17"* 51"* 16'* 11" 51"* -.06 70** 38** 70** 27** Hotels (n = 333) Combined (N = 681) 14"* 40** 04 14" 68** 24** 81'* 05 -.11 -.04 13" 68** 13 49** 04 13 -.10 14"* 65** 18"* 78** 03 -.18" -.09* 67** 22** 64** 55** 66** 31'* 62** 40** 147.7 (83)** 154.1 (83)** 242.6 (83)** 202.9 (81)** 167.2 (81)** 333.3 (81)** 95/.92 941.92 96/.94 93/.90 94/.91 94/.91 12 14 12 12 13 11 97/.74 97/.74 97/.75 95/.71 96/.72 95/.72 248 227 296 177 205 211 Airlines (n = 348) 145.0 (80)** 151.0(80)** 232.2 (80)** 95/.92 94/.92 96/.94 12 14 11 97/.72 97/.72 97/.73 244 225 299 NOTE: VC = volitional choice; RC = resistance to change; PI = positional involvement; IC = informational complexity; GFI = goodness-of-fit index; AGFI = adjusted goodness-of-fitindex; RMR = root mean residual; CFI = comparative fit index; PNFI = parsimonious normed fit index; CN = critical-N *p < 05 **p < 01 Again, other fit indices (GFI, AGFI, and CN) were used to examine this rival model (see Table 2) Although lower than their M-E-M counterparts, these suggested that this version of the commitment-loyalty link was also acceptable As both the proposed and rival models had met the fit criteria, chi-square difference tests were employed to determine if one of these structures performed better than the other (Bagozzi and Yi 1988) In all three instances, M-E-M provided a significant improvement over D-E-M I: airline sample, AX2= 55.2, df= 2, p < 01; hotel sample, AX2= 13.1, df= 2,p < 01; combined sample, AX2= 90.7, df= 2, p < 01 The second direct-effects structure was also compared with the M-E-M This model was slightly different to D-E-M I in that the resistance to change ->loyalty path was opened D-E-M II's fit indices (GFI, AGFI, and CN) in Table showed the model performed as well as the M-E-M Chi-square difference tests were again employed In two out of three instances, the more restrictive M-E-M was no different from D-E-M II in its fit: airline sample, AX2= 2.7, df= 3, p > 05; hotel sample, AZ~= 3.1, df= 3,p > 05 The third comparison with the combined sample marginally supported D-E-M II (Az2 = 10.4, df= 3, p < 05) Given the mixed result, other comparative criteria were used to examine the models (cf Morgan and Hunt 1994) First, the number of hypothesized parameters that were statistically significant varied D-E-M II failed to perform as well here, as only of its 21 paths were supported at the 01 level Second, although D-E-M II incorporated three further paths to M-E-M's single resistance to change -> loyalty link, the improvement in loyalty's explanation was negligible Third, the level of parsimony, as measured by the parsimonious normed fit index (James, Mulaik, and Brett 1982) supported the M-E-M more so than D-E-M II, as cross sample comparisons with this index consistently noted a stringent, yet slightly more efficient, explanation of the data Model assessments to this point lead us to conclude that the M-E-M provides the best description of commitment and its link with loyalty However, questions from earlier discussion about the accuracy of the M-E-M view of commitment needed to be addressed Two contrasts with the D-E-Ms were conducted to assess the credibility of Salancik's (1977) assertion that the antecedent processes together represent commitment These comparisons revealed that the D-E-M version of commitment explained much less of the criterion loyalty than the M-E-M version (see M-E-M and D-E-M I SMCs in Table 2) Instead, the (antecedent) processes were much more successful in explaining resistance to change Explained variance estimates for resistance to change were consistently higher than loyalty's This provided further evidence of the M-E-M's validity and the ability of the antecedent processes to discriminate 344 JOURNAL OF THE ACADEMY OF MARKETING SCIENCE SUMMER 1999 between the construct's root tendency and that of a closely related outcome (Ruekert and Churchill 1984) segment respondents (with the PCI) and determine the effectiveness of different tactics Nevertheless, it seems intuitive, for example, that marketing strategies developed for consumers whose self-images and values are tied to brand choice would differ markedly from those developed for consumers with little self-image invested in purchase, use, or participation Although efforts to strengthen loyalty may be based on data derived from the PCI, marketers armed with such information may simply choose to devote fewer institutional resources to those less committed target markets It is important to emphasize that PCI data should be interpreted in terms of commitment profiles rather than as a unidimensional score Considering resistance to change alone, without reviewing the antecedent processes, may lead to an errant specification based on spurious reasons In addition to the complex causal structure heretofore described, consumers must also negotiate a sequence of decisions prior to actual service selection (Assael 1987) While our work has visualized commitment and loyalty as brand-specific phenomena, separating product-level effects (i.e., involvement) from brand-specific effects (i.e., commitment) can be a confusing issue (Beatty et al 1988) Indeed, a fair question is, Commitment to what? Is a traveler committed to a particular destination or to a specific airline? Is a fitness center patron loyal to a specific fitness activity or to a particular service provider? Why are some fans loyal to specific sports, leagues (e.g., college), or particular teams? There is considerable evidence indicating that sports fans derive a great deal of personal meaning from their choice and affiliation with a sports team (e.g., Cialdini et al 1976) Cialdini and associates found that fans link (commit) themselves to successful teams to enhance their image in the eyes of others, a phenomenon they labeled BIRGing (Basking in Reflected Glory) More recently, Branscombe and Wann (199 l) reported that fans who identify strongly with their favorite sports team have a much greater propensity to watch and attend games featuring their favorite sports teams and to buy merchandise that publicly expresses their affiliation Further research on the M-E-M could take several different directions First, experiments that question the nature of commitment's processes and why they might differ and be more pronounced in some settings or situations than in others constitute a logical extension for future investigation (e.g., Kiesler 1971) Such questions could revisit the causal role of confidence and consistency in commitment's processes, as our study's factor analytic procedures by design identified only the principle factors at work and failed to support these two as discrete formative components Given their theorized importance in attitudinal stability, different methods should be employed to again test their potential contribution (Burton and Netemeyer 1992; Dick and Basu 1994) Testingfor mediation Adding to this conclusion, a review of the conditions for mediation with results from all three structures (see Table 2) established that the effect proposed by the M-E-M is indeed present (Baron and Kenny 1986) First, eight of nine paths in the M-E-M show that the antecedent processes have a significant effect on resistance to change Second, the M-E-M also notes that resistance to change has a significant effect on loyalty Third, D-E-M I reported that when resistance to change is constrained (i.e., not linked to loyalty), the three antecedent processes also have a significant direct effect on loyalty (seven of nine paths were significant, p < 05) Fourth, D-E-M II establishes that "mediation" exists, as it shows that the previously significant antecedent effects in D-E-M I became "non-significant or are substantially reduced" when the path between the mediator, resistance to change, and loyalty is opened (seven of nine paths now nonsignificant, p > 05) IMPLICATIONS The PCI developed in this study provides marketing managers with an easy to administer tool for identifying truly loyal consumers The PCI answers repeated calls for an approach to loyalty measurement that accounts for both consumers' purchase behavior as well as their attitude toward the brand or service (Jacoby and Chesnut 1978) The scale provides managers with the capability of moving beyond their traditional dependence on "purchase only" measures of brand loyalty to capture the strength of consumers' commitments to a particular brand Meaningful distinctions can be drawn between those who buy products and services strictly from habit or convenience and those whose repeat purchase behavior is based on genuine attachment The strength of a consumer's commitment is determined by a complex causal structure in which their resistance to change is maximized by the extent to which they (1) identify with important values and self-images associated with the preference, (2) are motivated to seek informational complexity and consistency in the cognitive schema behind their preference, and (3) are able to freely initiate choices that are meaningful Marketers, therefore, may strengthen customer loyalty by maximizing any or all of these antecedents Such strategies appear particularly germane in service contexts such as the hotel or airline industry, in which retention rates are regularly subject to competitive pressure (Jarvis and Mayo 1986) and fluctuate despite the tactics employed by largescale membership programs (Schulz 1998) Outlining specific strategies for strengthening loyalty is premature at this stage because no attempt was made in this research to Pritchardet al / THE COMMITMENT-LOYALTYLINK 345 Second, in this research, psychological commitment and resistance to change were examined as distinct attitudinal precursors to loyalty We deliberately avoided focusing on behavioral measures to concentrate on psychological antecedents Nevertheless, other behavioral links should be examined in subsequent research Day's (1969) measure itself could be reexamined For example, behavioral loyalty could be measured in numerous ways, including duration (participation over an extended time period), frequency (visits over a specified time period), intensity (e.g., hours per week devoted to participation), sequence (e.g., purchase patterns within or between brands), proportion of purchase relative to other product or brand options, and probability of purchase or participation It seems likely that such indicators will not only represent different nuances within loyal behavior but may also differ in their pertinence across service contexts Indeed, a unique combination of behavioral indicators may be most appropriate for measuring diverse loyalty contexts such as banks, brokerage services, sports teams, ski resorts, hotels, or airlines Third, questions about the formative structure of commitment's three processes themselves offer several avenues for exploration Investigations that recast the construct into a comprehensive nomological sequence could review how other important antecedents might fit in the network For example, the effect of service performance or satisfaction on resistance to change was not addressed Crosby and Taylor (1983) offered a general model of the effects of certain postpurchase factors (i.e., satisfaction) on commitment, and recent structural work has suggested a positive relationship between performance and commitment (Kelley and Davis 1994) Yet, our current conceptual model does not expressly show where or how the results of a service encounter (e.g., perceived differences or satisfaction) would be configured in commitment's formative network Theoretically, our definition of the committed person's informational processes could incorporate service performance as part of the reasoning (complexity) behind brand preference and the tendency to resist change One would also think that the process of identifying with a brand would be somewhat difficult to accommodate if that brand had first failed to perform Likewise, (ego) involvement is thought to strongly influence a person's psychological commitment (Iwasaki and Havitz 1998) Involvement provides an important context as to why stable brand preferences may develop in some psychologically committed consumers more than others (Burton and Netemeyer 1992) These sort of structural elaborations could help us to understand a variety of service-related effects An avenue of particular interest to us is the alternate perspective that the M-E-M offers to Oliva et al.'s (1992:86) conclusions about the relationship between satisfaction and loyalty Their study contends that the two are not directly related and that a"catastrophe model" of nonlinear effects is operating While the notion that a satisfaction "threshold" must be breached before loyalty would change has a ring of truth to it, our model accommodates this notion in a slightly different way Rather than nonlinear, the relationship may simply be indirect in nature, with resistance to change acting as the threshold measure that links satisfaction to loyalty In this sense, satisfying/dissatisfying service encounters may directly build or break down a person's resistance to change before loyalty is affected Much work remains to be done regarding commitment and its ability to mediate between loyalty and its antecedents (Dick and Basu 1994) Our current study's rejection of a direct effects model supports the notion that some formative processes are only indirectly related to loyalty This suggests that a wider review of other loyalty antecedents could be undertaken and considered in the light of commitment's mediating effect Finally, while our fundamental specification of commitment and its processes was drawn from observations common to a variety of settings (e.g., consumer/organizational behavior, voting behavior), longitudinal analysis and replication in product settings would help to clarify whether our sense of the construct is universal in its application ACKNOWLEDGMENTS This work acknowledges support provided to the lead author by a research fellowship awarded by the Graduate School of Management at the University of Western Australia APPENDIX Measurement Items in the Context of an Airline Service Resistance to Change RC1 My preference to fly with XYZwould not willingly change RC2 It would be difficult to change my beliefs about XYZ RC3 Evenif close friends recommended another airline, I would not change my preference for XYZ RC4 To change my preference from the XYZwould require major rethinking Position Involvement PI PI2 PI3 I prefer to fly with XYZbecausetheir image comes closest to reflecting my lifestyle When I fly with XYZit reflects the kind of person I am I prefer to fly with XF-Zbecause their service makes me feel important 346 JOURNAL OF THE ACADEMY OF MARKETING SCIENCE Volitional C h o i c e VC1 My decision to fly with XYZ was freely chosen from several alternatives a VC2 I did not control the decision on whether to fly with XYZ VC3 I am fully responsible for the decision to fly with XYZ Informational Complexity IC IC2 IC3 I d o n ' t really know that much about XYZ ~ I consider myself to be an educated consumer regarding XYZ I am knowledgeable about XYZ L o y a l t y E q u a t i o n : L = P[B] / A Loyal Attitude (A: abridged examples) Selin, Howard, Udd, and Cable (1988) I consider myself to be a loyal patron of XYZ airline I f I h a d to it o v e r again, I w o u l d fly with a n o t h e r airline, a Muncy (1983) I try to fly with XY-Zairline because it is the best choice for me To me, XYZ is the same as other airlines, a Loyal Behavior (P[B]: proportion of purchase) Please estimate how many times during the last 12 months you have flown with XYZ Please estimate how many times during the last 12 months you have used airlines in general NOTE: All attitudinal items were attached to a bipolar scale that ranged from (1) strongly disagree to (7) strongly agree a Item reversals NOTES I Procedures that use exploratory factor analysis alone in scale development (as was the case in Mowday, Porter, and Steers 1982) have been criticized for their tendency to generate "parsimonious explanations" that favor unidimensionality (Tinsley and Tinsley 1987:419) Day (1969) and Jaeoby and Kyner (1973) criticized loyalty's measurement at the time on a similar basis They argued that loyalty's assessment could not simply rest on loyal behavior (i.e., frequency of purchase) but must also take into account the attitude that supports that disposition One can make the same argument for commitment, as considering psychological attachment alone (e.g., Beatty, Kahle, and Homer 1988) fails to explain whether the disposition is based on attitudes of commitment or on the "situational exigencies" of a "spuriously" committed patron (Dick and Basu 1994:100) Day's (1969:30) equation, shown below, was used as the basis for this study's investigation of loyalty Service loyalty (L) was noted as a function of loyal attitude (A) and behavior (B): L = P[B] / A, where the level of patron loyalty for brand, L ~ P[B] = the proportion of total purchases of a service (i.e., A airlines flights) that buyers devoted to the brand over a set period of time, = the mean attitude score toward the brand SUMMER 1999 Two five-item attitudinal scales, developed by Muncy (1983) and Selin etal (1988), provided mean attitude scores for computing each composite indicator Abridged versions of the items used in the second sample (n = 290) are shown in the appendix A correlation coefficient (r = 84, p < 01) between the two indices with the total sample (N = 681 ) and the indicator loadings noted in Figure provide evidence of internal consistency REFERENCES Arbuckle, James L 1994 "AMOS: Analysis of Moment Structures?' Psychometrika 59:135-137 1997 Amos Users'Guide Version3.6 Chicago: SPSS Incorporated Assael, Henry 1987 ConsumerBehavior and MarketingAction 3rd ed Boston: Kent Bagozzi, Richard P 1993 "On the Neglect of Volition in Consumer Research: A Critique and Proposal." Psychology and Marketing 10 (May/June): 215-237 - and Youjae Yi 1988 "On the Evaluation of Structural Equation Models." Journal of the Academy of Marketing Science 16 (Spring): 74-94 Baron, Reuben, M and David A Kenny 1986 "The ModeratorMediator Variable Distinction in Social Psychologicial Research: Conceptual, Strategic, and Statistical Considerations." Journal of Personality and Social Psychology 51 (6): 1173-1182 Bearden, William O., Richard G Netemeyer, and Jesse E Teel 1989 "Measurement of Consumer Susceptibility to Interpersonal Influence." Journal of ConsumerResearch 15 (March): 473-481 Beatty, Sharon E and Lynn R Kahle 1988 "Alternative Hierarchies of the Attitude-Behavior Relationship: The Impact of Brand Commitment and Habit?' Journal of the Academy of Marketing Science 16 (Summer): 1-10 , - - , and Pamela Homer 1988 "The InvolvementCommitment Model: Theory and Implications." Journal of Business Research 16 (March): 149-167 Becker, H S 1960 "Notes on the Concept of Commitment'American Journal of Sociology 66 (July): 32-40 Bem, Daryl J 1967 "Self-Perception: An Alternative Interpretation of Cognitive Dissonance Phenomena." Psychological Review 74:183200 Bentler, P M 1990 "Comparative Fit Indexes in Structural Models?' Psychological Bulletin 107:238-246 Berger, Ida E and Andrew A Mitchell 1989 "The Effect of Advertising on Attitude-Accessibility, Attitude-Confidence, and AttitudeBehavior Relationship?' Journal of ConsumerResearch 16 (December): 269-279 Bitner, Mary J 1990 "Evaluating Service Encounters: The Effects of Physical Surroundings and Employee Responses." Journal of Marketing 54 (April): 69-82 Branscombe, N R and D L Wann 1991 "The Positive Social and SelfConcept Consequences of Sport Team Identification?' Journal of Sport and Social Issues 15:115-127 Buchanan, Thomas 1985 "Commitment and Leisure Behavior: A Theoretical Perspective?' Leisure Sciences (4): 401-420 Burnkrant, Robert E and Thomas J Page, Jr 1982 "An Examination of the Convergent, Discriminant, and Predictive Validity of Fishbein's Behavioral Intention Model?' Journalof Marketing Research 19 (November): 550-561 Burton, Scot and Richard G Netemeyer 1992 "The Effect of Enduring, Situational, and Response Involvement on Preference Stability in the Context of Voting Behavior." Psychology and Marketing (March/April): 143-156 Carmen, James M 1970 "Correlates of Brand Loyalty: Some Positive Results?' Journal of Marketing Research (February): 67-76 Churchill, Gilbert A 1979 "A Paradigm for Developing Better Measures of Marketing Constructs." Journal ofMarketing Research 16 (February): 64-73 Pritchard et al / THE COMMITMENT-LOYALTY LINK 347 Cialdini, R B., R J Borden, A Thorne, M R Walker, S Freeman, and L R Sloan 1976 "Basking in Reflected Glory: Three (Football) Field Studies" Journal of Personality and Social Psychology 34:366-375 9John T Cacioppo, Rodney Bassett, and John A Miller9 1978 "Low-Ball Procedure for Producing Compliance: Commitment then Cost:' Journal of PersonalityandSociaIPsychology 36 (5): 463-476 Crosby, Lawrence A and James R Taylor 1983 "Psychological Commitment and Its Effects on Post-Decision Evaluation and Preference Stability Among Voters:' Journal of Consumer Research (March): 413-431 Cunningham, Scott M 1967 "Perceived Risk and Brand Loyalty,' In Risk Taking and Information Handling in Consumer Behavior Ed D Cox Boston: Harvard University Press, 507-523 Day, George S 1969 "A Two-Dimensional Concept of Brand Loyalty:' Journal of Advertising Research (September): 29-35 1970 BuyerAttitades and Brand Choice Behavior New York: Free Press Dick, Alan S and Kunal Basu 1994 "Customer Loyalty: Toward an Integrated Conceptual Framework:' Journal of the Academy of Marketing Science 22 (Spring): 99-113 Festinger, Leon 1957 A Theory of Cognitive Dissonance Stanford, CA: Stanford University Press Fornell, Claes and David E Larker 1981 "Evaluating Structural Equation Models With Unobservable Variables and Measurement Error." Journal of Marketing Research 18 (February): 39-50 Freedman, Jonathon L 1964 "Involvement, Discrepancy and Change?' Journal of Abnormal and Social Psychology 69 (3): 290-295 and John D Steinbruner 1964 "Perceived Choice and Resistance to Persuasion?' Journal of Abnormal and Social Psychology 68:678-681 Hayduk, Leslie A 1987 Structural Equation Modelling with LISREL: EssentialsandAdvances Baltimore: John Hopkins University Press Hoelter, Jon W 1983 "The Analysis of Covariance Structures: Goodness-of-Fit Indices." Sociological Methods and Research 11:325-344 Holbrook, Morris B 1978 "Beyond Attitude Structure: Toward the Informational Determinants of Attitude?' Journal of Marketing Research 15 (November): 545-556 Iwasald, Y and Mark E Havitz 1998 "A Path Analytic Model of the Relationships Between Involvement, Psychological Commitment, and Loyalty." Journal of Leisure Research 30:256-280 Jacoby, Jacob 1971 "A Model of Multi-Brand Loyalty." Journal of Advertising Research 11 (June): 25-31 and Robert W Chesnnt 1978 Brand Loyalty Measurement and Management New York: John Wiley , and William A Fisher_ 1978 "A Behavioral Process Approach to Information Acquisition in Non-Durable Purchasing?" Journal of Marketing Research 15 (November): 532-544 and David B Kyner 1973 "Brand Loyalty vs Repeat Purchasing Behavior." Journal of Marketing Research 10 (February): 1-9 James, Larry R., Stanley A Mulaik, and J Brett 1982 CausalAnalysis: Models, Assumptions, and Data Beverly Hills, CA: Sage Jarvis, Lance P and Edward J Mayo 1986 "Winning the Market-Share Game?' Cornell Hotel Restaurant Administration Quarterly27 (November): 73-799 Kanter, Rosabeth M 1968 "Commitment and Social Organization: A Study of Commitment Mechanisms in Utopian Communities." American Sociological Review 33 (August): 499-517 Kelley, Scot W and Mark A Davis 1994 "Antecedents to Customer Expectations for Service Recovery" Journal of the Academy of Marketing Science 22 (Winter): 52-61 , James H Donnelly, and Steven J Skinner, Jr 1990 "Customer Participation in Service Production and Delivery,' Journal of Retailing 66 (3): 315-335 Kiesler, Charles A 1971 The Psychology of Commitment New York: Academic Press and Joseph Sakumura 1966 "A Test of a Model for Commitment?' Journal of Personalityand Social Psychology3 (3): 349-353 Kotler, Philip and Ravi Singh 1981 "Marketing Warfare in the 1980'sY Journal of Business Strategy (Winter):30-34 Millar, Murray G and Abraham Tessar 1986 "Thought-lnduced Attitude Change: The Effects of Schema Structure and Commitment:' Journal of Personality and Social Psychology 51 (2): 259-269 Morgan, Robert M and Shelby D Hunt 1994 "The Commitment-Trust Theory of Relationship Marketing" Journal of Marketing 58 (July): 20-38 Mowday, Richard T., Richard M Steers, and Lyman W Porter 1979 "The Measurement of Organizational Commitment:' Journal of Vocational Behavior 14:224-247 , Lyman W Porter, and Richard M Steers 1982 Employee- Organization Linkages: The Psychology of Commitment, Absenteeism, and Turnover New York: Academic Press Muncy, James D 1983 "An Investigation of the Two-Dimensional Conceptualization of Brand Loyalty" Ph.D dissertation, Texas Tech University, Lubbock9 TX Oliva, Terence A., Richard L Oliver, and lan C MacMillan 1992 "A Catastrophe Model for Developing Service Satisfaction Strategies:' Journal of Marketing 56 (July): 83-95 Oliver, Richard L 1980 "A Cognitive Model of the Antecedents and Consequences of Satisfaction Decisions:' Journal of Marketing Research 17 (November): 460-469 Pritchard, Mark P and Dennis R Howard 1997 "The Loyal Traveler: Examining a Typology of Service Patronage?' Journal of Travel Research 35 (Spring): 2-10 Robertson, Thomas S 1976 "Low-Commitment Consumer Behavior." Journal of Advertising Research 16 (April): 19-24 Rosenberg, Milton J 1960 "An Analysis of Affective-Cognitive Consistency." In Attitude Organization and Change: An Analysis of Consistency Among Attitude Components Eds M J Rosenberg, C I Hovland, W J McQuire, R P Abelson, and J W Brehm New Haven, CT: Yale University Press, 15-64 Ruekert, Robert W and Gilbert A Churchill, Jr 1984 "Reliability and Validity of Alternative Measures of Channel Member Satisfaction?' Journal of Marketing Research 21 (May): 226-233 Salancik, G R 1977 "Commitment and the Control of Organizational Behavior and Belief:' In New Directions in Organizational Behavior Eds B M Staw and G R Salancik Chicago: St Clair, 1-54 Schulz, Don E 1998 "Are We Too Loyal to Our Concept of Loyalty?" Marketing News 32 (13): 11 Selin, S., D R Howard, E Udd, and T Cable 1988 "An Analysis of Consumer Loyalty to Municipal Recreation Programs?' Leisure Sciences 10:210-223 Shamir, Boas 1988 "Commitment and Leisure?' Sociological Perspectives 31 (April): 238-258 Solomon, Michael R 1983 "The Role of Products as Social Stimuli: A Symbolic Interaetionist Perspective:'Journal of Consumer Research 10 (December): 319-329 Tesser, Abraham and Christopher Leone 1977 "Cognitive Schema and Thought as Determinants of Attitude Change" Journal of Experimental Social Psychology 13:340-356 Tmsley, Howard E A and Diane J Tinsley 1987 "Uses of Factor Analysis in Counseling Psychology Research:' Journal of Counseling Psychology 34 (October): 414-424 Zaichkowsky, Judith Lynne 1985 "Measuring the Involvement Construct" Journal of Consumer Research 12 (December): 341-352 ABOUT THE AUTHORS M a r k P P r i t c h a r d is an assistant professor with the Recreation Management and Tourism Department at Arizona State University and has published in Leisure Sciences, the Journal of Travel Research, and the Journal of Travel and Tourism Marketing His research concentrates on the application of consumer behavior theory in the travel industry, with a specific focus on commitment and loyalty 348 JOURNALOF THE ACADEMY OF MARKETING SCIENCE SUMMER 1999 M a r k E Havitz is a professor of recreation and leisure studies at the University of Waterloo He regularly publishes in the Journal of Leisure Research, Leisure Sciences, and the Annals of Tourism Research, and he has written for the Journal of Consumer Psychology His primary research interests relate to leisure involvement, commitment, and loyalty Dennis R Howard is a professor of marketing in the Charles H Lundquist College of Business at the University of Oregon He also serves as the academic coordinator of the college's James Warsaw Sports Marketing Center His research focuses on sports marketing with a particular interest on understanding factors that motivate and sustain consumer interest in sport