building, measuring, and profiting from customer loyaltyvariation in the conceptualization and...

ORIGINAL EMPIRICAL RESEARCH

Building, measuring, and profiting from customer loyalty

George F. Watson IV1& Joshua T. Beck2

& Conor M. Henderson3& Robert W. Palmatier4

Received: 5 September 2014 /Accepted: 23 March 2015# Academy of Marketing Science 2015

Abstract Achieving customer loyalty is a primary marketinggoal, but building loyalty and reaping its rewards remain on-going challenges. Theory suggests that loyalty comprises atti-tudes and purchase behaviors that benefit one seller over com-petitors. Yet researchers examining loyalty adopt widely vary-ing conceptual and operational approaches. The present inves-tigation examines the consequences of this heterogeneity byempirically mapping current conceptual approaches using anitem-level coding of extant loyalty research, then testing howoperational and study-specific characteristics moderate thestrategy → loyalty → performance process through meta-analytic techniques. The results clarify dissimilarities in loy-alty building strategies, how loyalty differentially affects per-formance and word of mouth, and the consequences of study-specific characteristics. Prescriptive advice based on 163

studies of customer loyalty addresses three seemingly simplebut very critical questions:What is customer loyalty?How is itmeasured? and What actually matters when it comes to cus-tomer loyalty?

Keywords Customer loyalty . Relationshipmarketing .

Content analysis . Meta-analysis .Word ofmouth

Customer loyalty is the central thrust of marketing efforts(Dick and Basu 1994; Evanschitzky et al. 2012), and U.S.firms spend dramatically to build and manage customer loy-alty. For example, annual loyalty program outlays have grown27% since 2010 to exceed $48 billion across 2.7 billion pro-gram enrollees in the United States alone, yet less than half ofthe 22 memberships per household are active (Berry 2013).However, the financial returns of many loyalty-building ef-forts fail to meet expectations (Henderson et al. 2011; Nunesand Dréze 2006). Even though the concept of Bcustomerloyalty^ has been debated for more 60 years (Brown 1952),the mixed returns of loyalty efforts still stem, in part, fromdivergent theoretical and operational approaches, such as thevaried use of attitudinal loyalty without behavioral loyalty orthe use of modified word-of-mouth measures as proxies forcustomer loyalty (Dick and Basu 1994; Keiningham et al.2007; Oliver 1999; Reinartz and Kumar 2002). To test theconsequences of this heterogeneity empirically, we synthesizeextant loyalty research to provide parsimonious guidance toboth academics and managers seeking to understand the strat-egy → customer loyalty → performance process.

Although there is no consensus definition of loyalty, extantresearch generally agrees that it represents a mix of attitudesand behaviors that benefit one firm relative to its competitors(Day 1969; Dick and Basu 1994; Melnyk et al. 2009). Within

* George F. Watson, [email protected]

Joshua T. [email protected]

Conor M. [email protected]

Robert W. [email protected]

1 University of Washington, 4295 E. Stevens Way NE, MacKenzieHall, Box 353226, Seattle, WA 98195-3200, USA

2 University of Cincinnati, 2925 Campus Green Dr., 106 Carl H.Lindner Hall, Cincinnati, OH 4522-1106, USA

3 Lundquist College of Business, University of Oregon, 486 LillisBusiness Complex, Eugene, OR 97403-1208, USA

4 University of Washington, 4295 E. Stevens Way NE, 418 PaccarHall, Box 353226, Seattle, WA 98195-3200, USA

J. of the Acad. Mark. Sci.DOI 10.1007/s11747-015-0439-4

this conceptual umbrella, researchers often selectively exam-ine loyalty as an attitude, purchase behavior, or multidimen-sional construct (e.g., attitudes and purchase behaviors, wordof mouth). Beyond this broad description there is significantvariation in the conceptualization and operationalization ofloyalty, which may explain heterogeneity in loyalty-relatedeffects. We map 163 studies published in marketing journalssince 1980, at the measurement item level, to capture theirheterogeneous research approaches. We then evaluate the de-gree to which this heterogeneity leads to disparate empiricalresults, by examining the structural relationships among loy-alty, its antecedents, and its outcomes according to meta-analytic data (Zablah et al. 2012). Finally, we examine possi-ble moderators of the effect of loyalty on outcomes with ameta-regression (Rubera and Kirca 2012).

The results of these analyses produce three main contribu-tions. First, we reconcile the differential effects of two theo-retical elements of customer loyalty—attitudes and behav-iors—according to meta-analytic results. The antecedents dif-ferentially build attitudinal and behavioral loyalty, and attitu-dinal and behavioral loyalty differentially influence manage-rially relevant outcomes such as word of mouth and perfor-mance (i.e., sales, share of wallet, profit performance, andother measurable changes). The common research practiceof using single-element measures of loyalty (i.e., only attitudeor behavior) thus leads to mixed guidance regarding the effectof loyalty on performance. This concern is especially prob-lematic when we note that most research (65% of studies inour sample) examines loyalty as an end outcome, such that itserves as a potentially misleading proxy for performance.

Second, we examine the moderating role of the measure-ment composition (e.g., ratio of attitudinal vs. behavioral loy-alty items, inclusion of word-of-mouth items) and study-specific characteristics (e.g., temporal orientation) to explainadditional variance in loyalty-related effects, using a meta-analysis of the sources of variation identified by our literaturereview and item-level coding procedure. We find for examplethat measures composed of combined attitudinal and behav-ioral items are more effective than attitude-only or behavior-only measures. Varying measurement compositions andstudy-specific characteristics of loyalty also produces differenteffects, depending on the type of loyalty and the outcome ofinterest. These analyses help clarify the heterogeneity in loy-alty effects that stem from conceptualizations and the studycontext.

Third, we provide prescriptive guidance for researchers andmanagers. In particular, we recommend strategies that buildattitudinal and behavioral loyalty, the use of loyalty itemsobtained from the measures that are most predictive of perfor-mance and word of mouth, and consideration of contextualinformation (e.g., business vs. consumer markets) that canleverage the effect of customer loyalty. We thus attempt toadd clarity to the varied conceptual and empirical findings

achieved through decades of research by answering three sim-ple but important bquestions: What is customer loyalty? (the-oretical), What are researchers doing? (measurement ap-proaches), and What actually matters? (empirical results).

Theoretical domain of customer loyalty

The rich early history of customer loyalty research allowedJacoby and Chestnut (1978) to cite more than 50 definitions ofit. Following more recent, elaborate theoretical expositions(Dick and Basu 1994; Oliver 1999), current theories mostoften delineate attitudinal loyalty and behavioral loyalty ascustomer loyalty’s primary elements (Chaudhuri andHolbrook 2001).

Loyalty as favorable attitudes and purchase behaviors

Attitudes are the first element of customer loyalty. People aremotivated information processors who use information toform their attitudes (Ahluwalia 2000; Moorman et al. 1993).Attitudinal loyalty then is a Bcognition^ or Bpleasurablefulfillment^ that favors a particular entity (Oliver 1999, p.35; see also Chaudhuri and Holbrook 2001). Strong, loyalattitudes result from systematic evaluations (Petty andCacioppo 1986) and influence many customer performance–related behaviors (Park et al. 2010; Petty, Haugtvedt, andSmith 1995). Strong positive attitudes induce Bdefensiveprocesses^ in the face of competition that cause customers toresist competitive offers, even when they are objectively better(Ahluwalia 2000, p. 230). Oliver (1999, p. 34) captures thisidea when he notes that loyalty persists Bdespite situationalinfluences and marketing efforts [that have] the potential tocause switching behavior.^

Purchase behaviors, the second element of loyalty, are alsocentral in loyalty research (Ailawadi et al. 2008; DeWulf et al.2001). Behavioral loyalty entails repeated purchases that stemfrom a conation or action orientation involving a Breadiness toact^ to the benefit of a particular entity (Oliver 1999, p. 35; seealso Chaudhuri and Holbrook 2001; De Wulf et al. 2003).Various examinations of customer loyalty focus on measuringbehaviors, such as repeated purchase behaviors, that have ob-vious benefits for a firm’s financial performance. This viewhas given rise to stochastic models of loyalty, including theuse of recency, frequency, monetary theory; churn/retention;and purchase sequences. Prior research also demonstrates thebenefits of behavioral loyalty. For example, Gupta et al.(2004) find that the impact of a 1% improvement in customerretention is five times greater than the effects of a similarincrease in margin. Yet purely behavioral approaches are oftenagnostic about the psychological processes associated withcustomer action. They ignore the real possibility that repetitivepurchase behavior arises from situational constraints, such as a

J. of the Acad. Mark. Sci.

lack of viable alternatives, or usage situations, such as habit(Henderson et al. 2011). Regardless of their cause, customerbehaviors can explain financial outcomes as loyalty-basedpurchase activities.

Measurement composition and study-specificcharacteristics in loyalty research

Despite clear delineations between attitudes and purchase be-haviors, theories of customer loyalty suggest both are integral(Dick and Basu 1994; Oliver 1999). Furthermore, some re-searchers characterize loyalty as a general orientation reflectedby non-purchase behaviors, such as advocacy (Jones et al.2008), willingness to pay a premium (Chaudhuri andHolbrook 2001), or continued silence in the hope that thingsget better (Hirschman 1970). As a result, loyalty measures areoften fuzzy; despite its duration, literature on loyalty presentsad hoc measures that are sometimes composed of attitudinalitems, sometimes composed of behavioral items, or both—oreven both together with items that measure ancillary con-structs. For example, many researchers include word of mouth(WOM) items in their operationalization of customer loyalty(Evanschitzky et al. 2012), despite both theoretical (Dick andBasu 1994) and empirical (de Matos and Rossi 2008;Söderlund 2006) arguments for their separation.

In addition, researchers examine customer loyalty in vari-ous research settings, creating research-specific measurementcharacteristics that may exert influences on results. We con-sider two key characteristics: temporal orientation and target.Temporal orientation refers to whether loyalty is measured asa past account or future predictions of loyal attitudes and be-haviors. For example, a customer might be asked to recallprevious instances of being loyal (Ailawadi et al. 2008;Davis-Sramek et al. 2009) or else estimate future intentionsto be loyal (Johnson et al. 2006; Wagner et al. 2009). Thetarget is the attribution customers make about to whom orwhat they are loyal. For example, loyalty may be Bownedby^ or directed toward the selling firm or a salesperson(Palmatier et al. 2007). We consider the effects of both mea-surement composition and study-specific characteristics in thesubsequent sections.

Conceptual model and hypotheses

To understand how loyalty may vary depending on itsoperationalization, we first consider how linkages in the ante-cedents → customer loyalty → outcomes framework varydepending on the use of attitudinal or behavioral loyalty. Byexamining attitudinal and behavioral loyalty as separate me-diators, we can isolate relative differences in both their mainand interaction effects. Therefore, we evaluate how the theoryunderlying each element supports distinct predictions. We

only include constructs in our conceptual framework if priorstudies have demonstrated at least three empirical links be-tween the antecedent and attitudinal and behavioral loyalties,to enable our tests of the differences through meta-analysis.We also include measures that feature both attitudinal andbehavioral loyalties to support moderation analyses. We iden-tified four antecedents (commitment, trust, satisfaction, andloyalty incentives) and two outcomes (WOM and perfor-mance) that meet these criteria. Table 1 summarizes the con-structs included in the model, their definitions, and commonaliases. Furthermore, we evaluate other sources of heteroge-neity identified in our literature review (measurement compo-sition, study-specific characteristics) and probe for additionalsources of heterogeneity by coding study-level factors to testtheir effects on loyalty-to-outcome linkages. Consistent withour research questions, our hypotheses focus on comparativedifferences among the links in our model.

Loyalty antecedents

Commitment, trust, satisfaction, and loyalty incentives (e.g.,reward programs, perks, favorable treatment) have all beenpositively linked to customer loyalty, but we expect them tohave differential effects on attitudinal and behavioral loyalties.Attitudinal loyalty results from positive evaluations of a sellerbased on previous exchange experience (Brakus et al. 2009;Liu-Thompkins and Tam 2013). Drivers of loyalty that pri-marily enhance a customer’s evaluation of the exchangeshould have a stronger effect on attitudinal than on behavioralloyalty. Conversely, behavioral loyalty results from situationaltriggers and habit (Gustafsson et al. 2005; Johnson et al.2006), which may not involve a strong attitudinal component.Thus drivers of loyalty that primarily operate as situationaltriggers in an exchange should have a stronger effect on be-havioral than on attitudinal loyalty. Commitment, or the desireto maintain a valued relationship (Moorman et al. 1992), trust,which is confidence in the reliability and integrity of a seller(Morgan and Hunt 1994), and satisfaction, which is the per-ceived difference between prior expectations and actual per-formance (Tse andWilton 1988), all contribute to a customer’spositive experience. Commitment and trust create the sensethat customers are in a pleasurable relationship rather than apassing transaction (Palmatier et al. 2006); satisfaction pro-vides a comparative basis (prior expectation versus actual ex-perience) on which to develop attitudes (Geyskens andSteenkamp 2000). Therefore, commitment, trust, and satisfac-tion should have stronger effects on attitudinal loyalty than onbehavioral loyalty. Alternatively, loyalty incentives are addi-tional Bextrinsic^ enticements meant to encourage repeat pa-tronage (De Wulf et al. 2001), so they might operate as repur-chase reminders that reduce effortful purchase considerationsand encourage habitual purchasing or as rewards for the pos-itive behavior of repurchasing (Henderson et al. 2011). Thus


Tab

le1

Reviewof

constructd

efinitions,aliases,andrepresentativ

epapers

Constructs

Definitions

Com

mon

aliases

Representativepapers

Loyalty

Attitudinalloyalty

ABcognitio

n^or

Bpleasurablefulfillment^

favoring

oneentitysuch

asa

firm

,itsbrand,its

salespersons,orits

offerings(O

liver

1999,p.35).

Affect,preference,w

armth

ChaudhuriandHolbrook2001;C

haudhuriand

Ligas

2009;Y

imetal.2008

Behavioralloyalty

Repeatedpurchasesthatstem

from

aconatio

nor

actio

norientation

involvingaBreadiness

toact^

favoring

oneentity(O

liver

1999,p.35).

Purchase,repurchase,repurchase

intentions,retentio

n,return

Brown1952;C

haudhuriandHolbrook2001;D

eWulfetal.2003;

Ehrenberg

etal.1

990;

Horsky

etal.2006

Loyalty

Acollectionof

attitudes

alignedwith

aseries

ofpurchase

behaviorsthat

system

atically

favoroneentityover

competin

gentities.

Customer

loyalty,trueloyalty

Brady

etal.2012;

DickandBasu1994;O

liver

1999;S

irdeshmukhetal.2002

Antecedents

Com

mitm

ent

Adesire

tomaintainavalued

relatio

nship.

Affectiv

e,behavioral,obligation,

andnorm

ativecommitm

ent

AndersonandWeitz1992;M

oorm

anetal.1992;

MorganandHunt1

994

Trust

Confidencein

thereliabilityandintegrity

ofaseller.

Trustworthiness,credibility,

benevolence,andhonesty

Hibbard

etal.2

001;

MorganandHunt1

994;

Sirdeshm

ukhetal.2002

Satisfaction

The

perceiveddifference

betweenpriorexpectations

andactualperformance.

Overallsatisfactionor

satisfaction

with

relatio

nship,product

orservice

GeyskensandSteenkamp2000;T

seandWilton

1988

Loyalty

incentives

Enticem

entsmeant

toencouragerepeatpatronage.

Rew

ards,gifts,perks,benefits,

resources,investments,and

loyalty

programs

DeWulfetal.2001;

Ganesan

1994

Outcomes

Wordof

mouth

Acustom

er'spositiv

ereferralor

endorsem

ento

fthesellerto

others.

Referralsandcustom

erreferrals

BergerandSchw

artz2011;S

öderlund

2006

Perform

ance

Actualsellerperformance

enhancem

entsincludingsales,shareof

wallet,

profitperformance,and

othermeasurablechangesto

theseller’sbusiness.

Sales,share,sales

effectiveness,

profit,

revenue,To

bin’sQ,and

salesperformance

Guptaetal.2004;

Kum

ar2013;P

almatieretal.

2007;P

etersenetal.2009


we expect loyalty incentives to operate primarily through be-havioral rather than attitudinal loyalty. Finally, as the theory ofplanned behavior predicts and prior research demonstrates, weexpect attitudinal loyalty to affect behavioral loyalty positive-ly (Ajzen and Fishbein 1980; Chaudhuri and Holbrook 2001).

H1: (a) Commitment, (b) trust, and (c) satisfaction havestronger positive effects on attitudinal loyalty than onbehavioral loyalty.

H2: Loyalty incentives have stronger positive effects on be-havioral loyalty than on attitudinal loyalty.

H3: Attitudinal loyalty positively affects behavioral loyalty.

Loyalty outcomes

We anticipate that the evaluation- and action-based mecha-nisms underlying attitudinal and behavioral loyalties differen-tially influence WOM and performance outcomes. Becauseattitudinal loyalty is associated with positive evaluations of aseller, and evaluations are abundant and easy to communicate,the effect of attitudinal loyalty should be strongest for WOM.Behavioral loyalty instead might not include a strong, acces-sible attitudinal component, which provides the basis forWOM (Berger and Schwartz 2011). Therefore, the effect ofbehavioral loyalty on WOM should be weaker than that ofattitudinal loyalty. For performance, we expect an oppositepattern of effects. Attitudinal loyalty tends to be based onconformity (Berger and Heath 2008) and may exist despitesituational constraints (e.g., financial, location) that impedeactual purchases (i.e., loyalty can be aspirational), so we ex-pect its effect on performance to be weaker. Instead, behav-ioral loyalty, which is based on a conation or readiness to actand is tied directly to purchase, should have a stronger effecton performance.

H4: The effect of attitudinal loyalty onWOM is greater thanthe effect of behavioral loyalty.

H5: The effect of behavioral loyalty on performance is great-er than the effect of attitudinal loyalty.

Role of measurement composition and study-basedcharacteristics

Researchers use different compositions of loyalty measures,which should moderate the effect of loyalty on outcomes.Dick and Basu (1994) provide a strong conceptual argumentthat neither a relatively high attitude nor a behavioral inclina-tion to purchase repeatedly are sufficient to capture customerloyalty fully. Customers with high attitudinal loyalty go togreater lengths to support a seller, and their cognitive biaseshelp them resist competitive persuasion attempts through

mechanisms such as avoidance or counterarguments(Ahluwalia 2000; Park et al. 2010). However, these customersalso may lack the ability or opportunity to support the seller(e.g., financial constraints). Behavioral loyalty directly in-creases seller revenues through frequent repurchasing anddemonstrates the customer’s ability and opportunity to sup-port the seller. However, these benefits may be short lived ifcustomers lack the motivation to continue their purchase be-haviors when their environment changes. Behaviorally loyalcustomers with low attitudinal loyalty also may be more likelyto exploit their relative importance and seek to extract extraconcessions from the seller. Thus, customer loyalty shouldcapture both behavioral and attitudinal aspects, to reflect cus-tomers’ desire, opportunity, and ability to support the sellerfinancially while avoiding competitors. Because measuresthat combine attitudes and behaviors capture the varianceaccounted for by each aspect of loyalty, we expect combinedmeasures of loyalty to exert a stronger effect on performanceoutcomes than either attitudinal or behavioral measuresalone.

Yet broad measures of loyalty that include WOM itemsmight attenuate the predictive effect of loyalty on performanceoutcomes, because WOM is a socially complex phenomenonthat involves self-image concerns, consideration for others’interests, and serendipitous accessibility (Berger andSchwartz 2011; De Matos and Rossi 2008; Söderlund 2006).Therefore, even though WOM and loyalty are correlated,measures of loyalty that include WOM items may captureunrelated or even countervailing effects (e.g., customers maybe very loyal to a condom company but unlikely to recom-mend it), so they will be less effective at predicting overallperformance.

H6: Measures of loyalty that include both attitude and be-havioral items have a stronger positive effect on WOMthan separate measures of attitudinal or behavioralloyalty.

H7: Measures of loyalty that include both attitude and be-havioral items have a stronger positive effect on perfor-mance than separate measures of attitudinal or behav-ioral loyalty.

H8: The positive effect of loyalty on performance appearsweaker when loyalty measures include WOM.

We also find systematic variation in the characterization ofcustomer loyalty across extant literature, particularly in termsof the temporal orientation and loyalty target(s). Althoughresearch questions or contexts might restrict researchers’choices of forward-looking versus backward-looking loyaltymeasures, we expect backward-looking loyalty measures toexhibit a stronger effect on both objective performance andpositive WOM. First, backward-looking loyalty assessmentstend to be more accurate, because customers avoid the


difficulty of imagining obstacles (e.g., price) that might inter-fere with future purchase behaviors (Ajzen 2002; Zimbardoand Boyd 1999). Second, forward-looking loyalty relies ontop-of-mind factors, whereas backward-looking loyalty bene-fits from subtle psychological mechanisms that offer powerfulpredictors of future behavior (e.g., cognitive dissonance, hab-it, sunk costs, switching costs; Henderson et al. 2011).Therefore, both attitudinal and behavioral loyalty should havegreater influences onWOM and firm performance when mea-sured as backward-looking rather than forward-lookingorientation.

H9: Backward-looking loyalty exhibits a stronger effect on(a) objective performance and (b) word of mouth thandoes forward-looking loyalty.

Although targets of loyalty frequently vary, researchoften ignores the potential implications of this variance.Loyalty to the firm should be a better predictor of objec-tive performance than loyalty to a salesperson, for severalreasons (Palmatier et al. 2007). First, loyalty to a sales-person creates dangers, in that salespeople frequentlychange positions, so the time when firms can benefit fromthis loyalty is relatively short; this loyalty also mighttransfer to a competitor if the salesperson switches firms.Second, salespeople may act opportunistically as agentsof the firm and offer their favorite customers unnecessarydiscounts or perks to gain personal favor (Palmatier et al.2009). Third, the salespeople to whom the customer ismost loyal represent only a limited portion of the firm’stotal offering, such that customers usually must deal withmultiple salespeople, brands, and locations. This narrowrepresentation restricts the benefits that might accrue ifthe same amount of loyalty were directed to the firm asa whole. Thus, we expect firm loyalty to have a greaterimpact on performance than salesperson loyalty does.

However, loyalty to a salesperson may be a better predictorof WOM, because customers can be more confident thatothers following their recommendations will enjoy a similarlypositive experience if they recommend a specific salesperson.Customers view salespeople as more consistent or entatitivetargets than firms, which comprise multiple salespeople,brands, and locations. Thus, when assessing an individual asopposed to a firm, Bcustomers are quicker to form judgments,believe the judgments more strongly, and are more likely toact on the beliefs^ (McConnell et al. 1997, p. 759). Loyalty tosalespeople therefore should have a greater impact on positiveWOM than loyalty to a firm, because it is based on a moreconsistent target.

H10a: The positive effect of customer loyalty on objectiveperformance increases when loyalty targets the firmrather than the individual salesperson.

H10b: The positive effect of customer loyalty on word ofmouth increases when loyalty targets the individualsalesperson rather than the firm.

Empirical study

To determine BWhat is customer loyalty?^ we begin by de-scribing our data collection process. Then, to investigateBHow is loyalty measured?^ and BWhat actually matters?^we code the composition of the measurement items that wefind in individual studies and perform a random effects meta-analysis of reliability adjusted, r-to-Z–transformed correla-tions between the constructs in our conceptual model. Withthese meta-analytic data, we perform a structural path analysis(Model 1), followed by a multivariate moderation analysis, orBmeta-regression^ (Models 2 and 3), to test our hypotheses.

Methodology

Data sample and criteria for inclusion We used several ap-proaches to identify potential studies for inclusion in our anal-yses. In the search process, we referred to the EBSCO data-base and reviewed journals ranked in the highest tier(Polonsky and Whitelaw 2006), namely, Journal ofMarketing, Journal of Marketing Research, MarketingScience, Journal of the Academy of Marketing Science,Journal of Consumer Research, and Journal of Retailing, dur-ing 1980–2013. For each article of each volume of thesejournals we evaluated whether the authors measured any con-struct with Bloyalty^ in its name (e.g., Bconsumer loyalty,^Bcustomer loyalty,^ attitudinal loyalty,^ Bbehavioral loyalty^),with the exception of employee loyalty or similar unrelatedconstructs. We then performed a more targeted search of theseand related journals, dissertations, and working papers usingthe Business Source Premier EBSCO, Social ScienceResearch Network (SSRN), ABI/Informs, and PsychINFOglobal databases. To find studies that investigated issues relat-ed to customer loyalty, we used search terms such as Bloyalty,^ Battitudes,^ Brepurchase,^ and related synonyms (seeTable 1) across all scholarly, peer-edited marketing and man-agement journals and dissertations that were electronicallyavailable. Finally, we inspected the reference lists of the majornarrative and empirical reviews of customer loyalty and relat-ed research to identify any potentially missing studies.

The criteria for inclusion required that survey-based studiesprovide the exact item wording and observational studies pro-vide exact measurement definitions, or else reference to theirorigins. So that we could examine the empirical implicationsof heterogeneity across loyalty research, we included a studyif it reported a Pearson correlation coefficient or other statisti-cal information (e.g., β, univariate F, t-statistics, χ2) that we


could use to calculate a correlation coefficient according to theformulas provided by Hunter and Schmidt (1990) or Petersonand Brown (2005).

Our sample does not include studies that rely on choicemodeling to estimate the extent to which loyalty exists in aparticular context. Such studies often estimate the amount ofbrand/retail patronage loyalty by detecting a brand–house-hold-specific utility (e.g., Guadagni and Little 1983; Horskyet al. 2006). This stream of literature is large and well under-stood, but the estimates of brand loyalty are rarely tied to othertheoretical constructs, which precludes them from enteringour analyses.

Item-level coding We examined the exact item wording ofthe measures or the citation that provided the source of themeasures to categorize the type of loyalty studied by the re-searcher accurately. We extracted, coded, and categorizedeach measurement item (i.e., questions responded to by eachstudy’s participants, objective measures), following apredefined set of rules (Kolbe and Burnett 1991).Definitions that reflect the types and elements of customerloyalty outlined in our prior theoretical review are summa-rized in Table 1. Guided in part by our literature review, wedeconstructed each sentence and coded the language of theitems in each study for common content (e.g., attitudes, be-haviors, WOM, temporal orientation, target). Two coders in-dependently evaluated each article. Fewer than 6% of the ef-fects differed across the double coding procedures, and dis-agreements were resolved through discussion.

With this procedure, we could examine the bundle of itemsthat each researcher chose to measure loyalty and therebydetermine their choice of loyalty conceptualization and theextent to which they maintained content validity. The insightsfrom this content analysis stemmed from our determination ofhow each sample conceptualized loyalty, using (1) only atti-tudinal measures, (2) only behavioral measures, (3) both atti-tudinal and behavioral measures as separate constructs, or (4)attitudinal and behavioral measures in the same scale as asingle construct. The loyalty conceptualization thus reflectsthe researchers’ choice and bundling (e.g., mean average) ofitems. Table 7 in the Web Appendix provides a summary ofthe final database of 163 studies and their corresponding cod-ing decisions.

Meta-analysis To examine the differential effects of attitudi-nal and behavioral loyalty and to maintain construct validity,we used a subsample that included attitude-only and behavior-only measures (i.e., no mixed or Binclusive^ loyalty mea-sures). In addition, we included constructs only if we had atleast three effects between each construct and all otherconstructs in the model in our effort to develop the inputcorrelation matrix (Palmatier et al. 2006). Thus, the structuralpath analyses used to test H1–H5 were based on 126 studies,

151 separate samples, and 713 effects using attitude-only andbehavior-only measures of loyalty.

To this subsample, we applied meta-analytic techniques togenerate a correlation matrix of all constructs to use as inputfor the structural path models (Rubera and Kirca 2012; Zablahet al. 2012). After compiling the data, we adjusted every cor-relation for reliability (attenuation correction) by dividing it bythe product of the square root of the reliabilities of the twoconstructs (Hunter and Schmidt 2004). We transformed thereliability-corrected correlations into Fisher’s z-coefficients,and then performed a random-effects meta-analysis on theFisher z-coefficients. Following standard procedures(Shadish and Haddock 2009), we next transformed the z-scores back to r-correlations to obtain the revised, sample-weighted, reliability-adjusted correlation coefficients and95% confidence intervals with associated t-statistics (Hedgesand Olkin 1985; Zablah et al. 2012). The random-effects ap-proach provides more realistic, less inflated estimates of aver-age effect sizes; accounts for variability in true effect sizesacross studies; and is generalizable to a population of potentialstudies (Raudenbush 2009). We addressed the potential prob-lem of selective publication bias in several ways. First, wecomputed and report the Q statistic (d.f.=n–1) test of homo-geneity (Rosenthal 1979). Second, we tested for publicationbias with funneling and trim-and-fill analyses (Homburg et al.2012), neither of which suggested publication bias was anissue.

Structural path analysis Meta-analytic correlations be-tween all constructs in the model produced by the anal-ysis and formed into a meta-analytic correlation matrixprovided the input for the structural path analyses inMplus 7.11 (Zablah et al. 2012). Our conceptual modelincludes commitment, trust, satisfaction, and loyalty in-centives as antecedents and WOM and performance asoutcomes. Model 1 tests our hypotheses in the presenceof paths from all antecedents to both attitudinal and be-havioral loyalties and with both loyalties linked to bothoutcomes, such that attitudinal loyalty is modeled as anantecedent of behavioral loyalty. All the constructs areobserved variables, antecedents may covary, and we usedthe harmonic mean (n=5671) across all correlations asthe sample size (Rubera and Kirca 2012). Our choiceto use the harmonic mean provides more conservativetesting than the use of the arithmetic mean or medianbecause it give less weight to substantially large cumu-lative samples sizes typical of meta-analyses, and as suchis a common and strongly recommended decision formeta-analytic structural equation models (Pick andEisend 2014). We examined within-model hypothesizeddifferences in path coefficients by setting the correspond-ing paths to be equal and testing for significance usingWald Chi-square tests.


Multivariate moderation analysis To examine the moderat-ing effects of sources of heterogeneity, we expanded the sam-ple that we used for the structural path analysis to includeBinclusive^ measures of loyalty. With this approach, we cancompare the effects of attitudinal-only, behavioral-only, andvarious inclusive forms of customer loyalty elements with ahierarchical linear model (HLM), in which the effects arenested within studies. We performed our analysis byregressing the moderator variables on correlations (meta-regression) to account for within-study error correlation be-tween effect sizes (Homburg et al. 2012; Rubera and Kirca2012), coding for the specific qualities of each construct weexamine. To evaluate how the effect of loyalty on WOM andperformance varies across (1) loyalty aspects (H4–H7), (2)other conceptual features (H8–H10; WOM inclusive, tempo-ral orientation, and target), and (3) study-level factors thatserved to test robustness (e.g., business vs. consumer markets,common method susceptibility), we included studies with anytype of loyalty that reported an effect on either WOM or per-formance. By including all forms of loyalty in this analysis,we established a sample that is sufficiently large to supporttests of all moderation effects simultaneously while also ac-counting for loyalty aspects. Thus, the multivariate HLMmoderation analyses were based on 32 (30) studies, 41 (32)separate samples, and 68 (57) effects for WOM (perfor-mance), using all measures of loyalty.

As a replication and robustness test, we also evaluated thedifferences between loyalty operationalizations by dummycoding an effect as equal to 1 if the loyalty measure was amixture of attitudes and behaviors in a single scale, consistentwith 35% of our sample, and 0 if it included only attitudes orbehaviors. In addition, as an alternative test of H4 and H5, wecaptured the moderating effect of the mixture of attitudinaland behavioral items by coding the ratio of attitudinal to totalitems used in the measure of loyalty (1 = all attitudinal, 0.5 =half attitudinal and half behavioral, 0 = all behavioral). Thesetwo moderators reflect extant research, where (0, 0) indicatesbehavioral loyalty, (0, 1) is attitudinal loyalty, and (1, ratio)serves as a loyalty proxy with varying mixtures of attitudinaland behavioral items, as is common.

We also evaluated other conceptual features by dummycoding whether a loyalty effect was WOM inclusive to testH8 (1 = measure included at least one WOM item, 0 = mea-sure did not include any WOM items). To evaluate the mod-erating effect of temporal orientation, we coded the ratio offorward-looking to total loyalty items for each study effect totest H6 (1 = all forward-looking, 0.5 = half forward- and halfbackward-looking, 0 = all backward-looking). For the moder-ating effect of the target, we dummy coded the measure foreach study effect for the loyalty target to test H10 (1 = indi-vidual salesperson, 0 = ambiguous, −1 = the firm).

Finally, to understand and control for potential influencesof study-based features on our results, we coded and tested the

moderating effects of six study characteristics (Albers et al.2010; Homburg et al. 2012; Sethuraman et al. 2011).Specifically, we used a dummy to code whether a loyaltyeffect was from business or consumer markets (1 = business,0 = ambiguous, −1 = consumer), pertained to brand loyalty (1= Bbrand^ was included in the construct name, context, or anyitems, 0 = not brand-related in any way), appeared in an un-published journal article or dissertation (1 = unpublished ordissertation, 0 = published), and was susceptible to commonmethod bias (1 = used a method or sample susceptible tocommon method bias, 0 = not susceptible to common methodbias). To account for the last two study features, we usedmean-centered continuous coding schemes. We evaluatedany longitudinal effects according to the four-digit year ofthe study’s publication date; for journal quality, we codedthe Journal Eigenfactor Scores for the source of each loyaltyeffect, such that unpublished journal and dissertation effectswere assigned the sample mean value (West and Bergstrom2013).

Results

Item-level content analysis Table 2 shows the breakdown ofthe loyalty constructs in our sample, coded at the item level,which helps address our second research question. Overall, wefind that though many researchers maintain attitudinal loyaltyand behavioral loyalty as separate constructs (65% of studies),a substantial set combine attitudinal and behavioral items to-gether (35% of studies). Furthermore, many researchers ex-amine only behavioral (43% total) or attitudinal (7%) loyalty,but only 15% examine both attitudinal and behavioral loyal-ties in the same study, as separate constructs. Studies withbehavior-only or attitude-only measures of loyalty, typicallylabeled Bloyalty^ without qualifiers, potentially misrepresentthe effects of the antecedents on loyalty and loyalty’s impacton outcomes, because attitudes and behaviors have divergenteffects (Baker et al. 2002; Brexendorf et al. 2010; Burton et al.1998; Maxham and Netemeyer 2002).

Among the 35% of researchers examining customer loyaltyusing both attitudinal and behavioral measures in the sameconstruct, more than half (18% of total sample) operationalizeloyalty with WOM as an indicator of loyalty (Table 2, PanelA). Although WOM and loyalty are related, the prevalence ofWOM as a measure of customer loyalty conflicts with boththeoretical (Dick and Basu 1994) and empirical (De Matosand Rossi 2008; Söderlund 2006) arguments for their separa-tion. In addition, the use of forward- versus backward-lookingloyalty measures is unevenly divided across studies, at 59%and 41%, respectively (Table 2, Panel B). Prior researchshows that the abstract cognitive processes of reconstructingthe past and constructing the future influence decision making(Zimbardo and Boyd 1999), so the selection of a particulartemporal measurement may create variance in empirical


results. The selling firm is the primary target of customerloyalty (72%), with the remainder of the research attentiondivided approximately equally between loyalty to a brand

(15%) and to an individual salesperson (13%). However, re-searchers typically fail to qualify or acknowledge the loyaltytarget (Table 2, Panel C), even though firm- and salesperson-

Table 2 Item-level content analysis

Attitudinal and behavioral loyalty mixed 35%

(18% WOM inclusive)

Attitudinal and behavioral loyalty

separately 15%

Behavioral loyalty only

43%

Attitudinal loyalty only

7%

Forward-looking loyalty 59%

Backward-looking loyalty 41%

Individual 13%

Brand 15%

Firm 72%

The underlined terms highlight the coding criteria at the item level


Tab

le3

Results:m

eta-analysisof

directeffects

Relationship

Num

berof

estim

ates

Totaln

Sampleweighted

reliability-adjusted

meanr

t-value

S.E.

C.I.low

erC.I.upper

Q-statistic

Qd.f.

Attitudinal

loyalty

↔Behavioralloyalty

3313,715

0.50

8.58

***

0.06

0.40

0.60

1390.36

(32)

Com

mitm

ent

83505

0.65

10.85***

0.07

0.54

0.74

95.41

(7)

Trust

186850

0.63

15.38***

0.05

0.56

0.68

192.90

(17)

Satisfaction

258701

0.63

12.87***

0.06

0.55

0.69

528.56

(24)

Loyalty

incentives

42755

0.29

2.63

.0.11

-0.06

0.58

41.01

(3)

Objectiv

eperformance

72673

0.25

4.45

**0.06

0.11

0.38

40.43

(6)

Wordof

mouth

104081

0.68

13.02***

0.06

0.60

0.75

77.78

(9)

Behavioral

loyalty

↔Com

mitm

ent

4131,664

0.60

13.41***

0.05

0.53

0.66

1522.16

(40)

Trust

4226,392

0.55

13.35***

0.05

0.48

0.61

854.43

(41)

Satisfaction

77332,280

0.50

12.56***

0.04

0.43

0.56

32,112.44

(75)

Loyalty

incentives

58131,165

0.31

6.61

***

0.05

0.22

0.40

5910.43

(57)

Objectiv

eperformance

3327,965

0.39

5.61

***

0.07

0.26

0.51

3481.81

(32)

Wordof

mouth

5040,565

0.55

9.96

***

0.06

0.46

0.63

4323.70

(49)

Com

mitm

ent↔

Trust

2611,275

0.66

16.71***

0.05

0.60

0.71

281.15

(25)

Satisfaction

2716,564

0.68

20.82***

0.04

0.64

0.73

395.38

(26)

Loyalty

incentives

3131,346

0.48

6.41

***

0.08

0.35

0.60

1860.28

(30)

Objectiv

eperformance

69985

0.43

3.38

*0.13

0.11

0.67

334.02

(5)

Wordof

mouth

117356

0.65

7.26

***

0.11

0.49

0.77

203.17

(10)

Trust↔

Satisfaction

4219,759

0.66

21.68***

0.04

0.62

0.70

759.90

(41)

Loyalty

incentives

3327,866

0.39

7.65

***

0.05

0.30

0.48

2348.86

(32)

Objectiv

eperformance

89694

0.32

4.90

**0.07

0.17

0.46

130.80

(7)

Wordof

mouth

128486

0.54

9.76

***

0.06

0.44

0.63

233.26

(11)

Satisfaction↔

Loyalty

incentives

3867,667

0.39

6.16

***

0.07

0.27

0.50

3474.03

(37)

Objectiv

eperformance

33163,514

0.17

3.94

***

0.04

0.08

0.25

10,533.30

(32)

Wordof

mouth

3025,172

0.55

10.29***

0.06

0.46

0.63

1971.99

(29)

Loyalty

incentives

↔Objectiv

eperformance

24209,446

0.23

5.16

***

0.05

0.14

0.32

5877.44

(23)

Wordof

mouth

148775

0.23

4.85

***

0.05

0.13

0.32

107.46

(13)

Objectiv

eperformance

↔Wordof

mouth

247162

0.26

2.20

*0.12

0.02

0.47

990.30

(23)

*p<.10;

**p<.05;

***p<.01

Notes:M

eancorrelations

calculated

usingrandom

effectsmodel.R

eportedcorrelations

wereadjusted

forattenuation,convertedtoFisher’sZtostabilize

variance,and

then

convertedback

torfor

reporting

purposes.C

.I.=

confidence

interval


based loyalty reflect different decision processes that differen-tially affect performance (Palmatier et al. 2007).

Meta-analysis and structural path analysis (Model1) Table 3 contains the sample-size weighted mean meta-analytic correlations, total Ns, number of effects, coefficientt-values, 95% confidence intervals, and corresponding Q sta-tistics among the antecedents, attitudinal and behavioral loy-alty, and outcomes in our model. We used this information tocalculate our structural path analysis in Mplus 7.11. The mod-ification indices suggested modifications to the initial hypoth-esized model to improve fit, by allowing the conceptuallyrelated constructs of commitment, trust, and satisfaction tocorrelate with outcomes. Importantly, prior research supportsthe inclusion of these links considering the well documentedinfluence of all three constructs on performance and word ofmouth (Morgan and Hunt 1994; Palmatier et al. 2006). Thesechanges resulted in acceptable fit statistics for Model 1: chi-square (χ2 (2)) = 174.75, comparative fit index (CFI) = 0.99,and standardized root mean residual (SRMR) = 0.04. Figure 1shows the results of our final structural path analysis usingmeta-analytic data (Model 1), with standardized beta coeffi-cients and construct R-square values.

Examining our model in relation to our third research ques-tion, we find that trust (βAtt=0.27 vs. βBeh=0.22, χ

2(1) =16.41, p<.01) and satisfaction (βAtt=0.25 vs. βBeh=0.04,χ2(1)=115.06, p<.01) have stronger positive effects on attitu-dinal than on behavioral loyalty, in support of H1b and H1c,respectively. However, commitment is equally powerful forbuilding both attitudinal and behavioral loyalty (βAtt=0.34vs. βBeh=0.35, χ

2(1) = 2.80, p>.05), so we cannot confirmH1a. Furthermore, loyalty incentives (βAtt=−0.08 vs. βBeh=0.01 (n.s.), χ2(1) = 31.16, p<.01) do not have a significantlystronger positive effect on behavioral loyalty than on attitudi-nal loyalty, so we reject H2. Consistent with H3, attitudinal

loyalty has positive, significant impact on behavioral loyalty(βAtt=0.10, χ

2(1) = 174.75). We also find support for H4, inthat the effect of attitudinal loyalty on WOM is stronger thanthe effect of behavioral loyalty on WOM (βAtt=0.41 vs.βBeh=0.19, χ

2(1) = 94.06). On the flipside, the effect of be-havioral loyalty on performance is greater than that of attitu-dinal loyalty (βAtt=0.02 (n.s.) vs. βBeh=0.27, χ

2(1) =133.98), in support of H5.

Multivariatemoderation analysis (Models 2 and 3) Table 4shows the results of our two moderation analyses (WOM inModel 2; performance in Model 3). By using an expandedsample (all measures of loyalty linked to outcomes rather thanjust attitude-only and behavior-only measures) for these twopaths and simultaneously controlling for other potential mod-erators, we retested some hypotheses to increase confidence inour findings related to our third research question, BWhatmatters?^ The positive effects of loyalty on WOM (β=0.33,p<.05) and performance (β=−0.34, p<.05) are significantlymoderated in opposite directions by the ratio of attitudinalitems in the loyalty measure, corroborating our support forH4 and H5. A higher percentage of attitudinal items enhancesthe effect of loyalty on WOMwhile simultaneously suppress-ing its effect on performance. Similarly, the positive effects ofloyalty on bothWOM (β=0.31, p<.05) and performance (β=0.11, p<.05) are significantly moderated by measures that usea mix of attitudinal and behavioral items in the same constructrather than attitude- and behavior-only loyalty measures, infurther support of H7 and H8. A non-significant intercept of0.35 further reflects that the effect of loyalty on WOM isdependent upon its conceptualization.

The positive effect of loyalty on performance decreases(β=−0.44, p<.05) in loyalty measures that contain at leastone WOM item, which implies that WOM-inclusive loyaltymeasures are less predictive of performance, in support of H6.

Commitment

Trust

Satisfaction

Loyalty incentives

Attitudinal loyaltyR = .542

Behavioral loyaltyR = .402

Word of mouthR = .482

PerformanceR = .142

Fig. 1 Results: structural pathmodel analysis (Model 1)


Tab

le4

Results:m

ultiv

ariatemeta-regression

ofmoderationeffects

Moderator

variables

Hypotheses

Allloyalty

→WOM

(Model2)

Allloyalty

→performance

(Model3)

αβ

(SE)

αβ

(SE)

Intercept

0.35

(0.23)

0.64

***

(0.11)

Loyalty

aspects

1.Mixed

(attitudinaland

behavioralitems)versus

pure

aspects

H6,H

70.31

***

(0.04)

0.11

***

(0.03)

2.Ratio

ofattitudinalloyalty

itemsto

totalloyalty

items

H4

0.33

***

(0.03)

−0.40**

(0.09)

Other

loyalty

conceptualfeatures

3.WOM

inclusiveloyalty

H8

––

−0.44***

(0.06)

4.Temporalo

rientatio

nof

loyalty

:ratio

offorw

ard-lookingloyalty

tototalitems

H9

0.13

***

(0.02)

−0.20***

(0.05)

5.Targetof

loyalty

:individualv

ersusfirm

loyalty

H10

0.10

(0.08)

0.03

(0.02)

Study-basedfeatures

6.Businessversus

consum

ermarkets

0.14

*(0.05)

−0.06

(0.14)

7.Brand

versus

non-brandloyalty

−0.17

(0.09)

−0.08

(0.27)

8.Unpublishedversus

publishedresearch

0.22

(0.19)

0.02

(0.18)

9.Com

mon

methodsusceptib

ility

0.15

(0.24)

−0.14

(0.09)

10.Y

earof

publication(m

ean-centered)

0.03

**(0.01)

0.01

(0.01)

11.Journalquality

usingjournaleigenfactor

(mean-centered)

−0.69

(1.00)

−0.99

(1.00)

*p<.10;

**p<.05;

***p<.01

Notes:α

=random

effectsintercept,β

=random

effectsregression

coefficient.Significantregression

coefficients

indicate

supportformoderationof

thespecifiedrelatio

nship.

Allmoderatorsran

simultaneouslyandareshow

nas

standardized

coefficients

Coding

1.1=constructm

ixed

both

attitudinalandbehavioralitemsin

singlemeasure;0

=only

attitudinalor

only

behavioralitems

2.1=100%

attitudinalitems;0=100%

behavioralitems

3.1=constructincludesWOM

item(s);0=no

WOM

items

4.1=100%

forw

ard-lookingitems;0=100%

backward-lookingitems

5.1=loyalty

targetisan

individual;0

=targetwas

ambiguous;−1

=loyalty

targetisafirm

6.1=business-to-business

marketstudy;0

=am

biguousmarketstudy;−

1=business-to-consum

ermarketstudy

7.1=Bbrand^was

includein

constructn

ame,context,or

anyitems;0=notb

rand-related

inanyway

8.1=unpublishedor

dissertatio

n;0=publishedin

peer

editedjournal

9.1=studyused

sample/methodology

susceptib

leto

common

methodbias;0

=unlik

elysusceptib

leto

common

methodbias

10.F

our-digity

earin

which

studywas

reported

11.Journaleigenfactorscores

forthejournalo

feveryloyalty

effect(http

://www.eigenfactor.org/).U

npublished/dissertatio

neffects=samplemean


http://www.eigenfactor.org/

We also find support for H9a and H9b, focused on the tempo-ral orientation of loyalty, because the effects of loyalty onWOM (β=0.13, p<.05) and performance (β=−0.20, p<.05)are significantly moderated in opposite directions by the ratioof forward-looking items in the loyalty measure. A higherpercentage of forward-looking, relative to backward-looking,loyalty items enhances the effect of loyalty on WOM whilesimultaneously suppressing its effect on performance.However, we did not find support for H10a and H10b, whichproposed that the effect of loyalty on outcomes would bemoderated by the target (individual versus firm) (WOM: β=0.10, p>.10; performance: β=0.03, p>.10).

With respect to other (non-hypothesized) study fea-tures, we find that the effect of loyalty on WOM is slight-ly stronger in business (vs. consumer) markets (β=0.10,p<.05), and the effect of loyalty on WOM has grownstronger over time (β=0.03, p<.05). However, the effectof loyalty on outcomes did not vary significantly forbrand loyalty, unpublished sources, methods susceptibleto common method bias, or journal quality. These find-ings increase our confidence that our sample is represen-tative and unlikely to suffer from potential inclusion ormethod biases that emerge when aggregating a sampleof studies for meta-analytic research (Sethuraman et al.2011).

Post hoc analysis (Model 4)

Researchers often conceptualize customer loyalty as aBfavorable correspondence between attitudes and behaviors,^ stemming from an underlying motivation to maintain a re-lationship with a particular entity (Dick and Basu 1994, p.102;see also Brady et al. 2012; Sirdeshmukh et al. 2002). Ourmoderation analysis (Model 2 and 3) shows that the positive

effects of loyalty on both WOM and performance are signif-icantly and positively moderated by measures that use a mixof attitudinal and behavioral items in the same construct(WOM β=0.31, p<.05; performance β=0.11, p<.05); weinvestigated this finding with a post hoc structural path anal-ysis that parallels Model 1. Specifically, we modeled attitudi-nal and behavioral loyalties as reflective indicators of a latentconstruct (i.e., loyalty), with all antecedents and outcomeslinked to it according to the data we used in our first structuralpath analysis. As with Model 1, we modeled all constructs asobserved variables (except for loyalty as a latent construct),allowed the antecedents to covary, and used the harmonicmean (n=5671) across all correlations as the model’s samplesize (Rubera and Kirca 2012).

Figure 2 contains the results of our post hoc structuralModel 4, which provides slightly improved model fit sta-tistics: χ2(4) = 130.38, p<.05, CFI=0.99, and SRMR=0.01. To gain insight into the nature of customer loyalty,we compared the 95% confidence intervals of the stan-dardized beta coefficients from Model 1 against our posthoc model with loyalty as a latent construct. Mirroring theresults from our moderation analyses, modeling customerloyalty as a single latent construct results in stronger stan-dardized coefficients for performance (βLoyalty=0.51,[0.46, 0.57]) compared with either attitudinal (βAtt=0.02, [−0.01, 0.06]) or behavioral (βBeh=0.27, [0.24,0.30]) loyalty alone. We find a similar pattern of resultsfor the effect of loyalty on WOM (βLoyalty=0.54, [0.47,0.62]; βAtt=0.41, [0.39, 0.43]; βBeh=0.19, [0.17, 0.21]);the model that includes both attitudinal and behavioralelements to capture customer loyalty results in better fitand stronger effects than models that maintain either ele-ment separately. These findings support the concept thatfirms benefit most from Btrue customer loyalty,^

Loyalty

Attitudinal measures

Behavioral measures

Commitment

Trust

Satisfaction

Loyalty incentives

Word of mouthR = .442

PerformanceR = .122

Fig. 2 Post Hoc: structural pathmodel analysis (Model 4)


involving a positive cognitive state (attitudinal loyalty)manifested as positive behavioral actions (behavioral loy-alty) (Dick and Basu 1994; Oliver 1999; Sirdeshmukhet al. 2002).1

Strengthening the loyalty framework for researchersand practitioners

From this precise inventory and examination of the primaryconceptualizations of customer loyalty, we derive theoreticaland practical insights to guide marketing research and prac-tice. By synthesizing decades of research, we (1) provide asingle conceptual definition of loyalty, (2) describe how re-searchers should approach empirical definitions to clarify cru-cial aspects of their treatment of loyalty and reduce measure-ment heterogeneity, and (3) provide exemplary loyalty mea-sures, which we summarize in Table 5. We also provide adatabase of recent loyalty-related studies in marketing (WebAppendix, Table 7) and a summary of best practices in termsof study design and methodological choices (Table 6).

From a conceptual standpoint, customer loyalty is a collec-tion of attitudes aligned with a series of purchase behaviorsthat systematically favor one entity over competing entities.However, empirical definitions should append a temporal as-pect (backward-looking vs. forward-looking), because of itsinfluence on how loyalty gets processed psychologically andits ultimate impact on performance outcomes. To address var-ious combinations of empirical definitions, we offer 10 exem-plary items, extracted from various studies that broadly cap-ture elements (attitudes and behaviors) and study-specificcharacteristics (temporal aspect, target) that influence loyalty.We thus offer specific advice to researchers and practitionersto help them capture the customer loyalty construct more ac-curately and reap its benefits.

Guidance for researchers

Every loyalty study should consider four primary conceptualguidelines. First, if researchers seek to understand how ante-cedents create loyalty, loyalty must be measured and reportedas an attitude or behavior separately, because the antecedentsdifferentially build each element. Satisfaction (Model 1) haslittle effect on behavioral loyalty (β=0.04, p<.05) but a strongeffect on attitudinal loyalty (β=0.24, p<.05), for example.Other antecedents that we did not consider in the current studyplausibly should exert similarly distinct effects, and ignoringsuch differences could produce misleading results that dependmore on the loyalty element measured than on the actual effi-cacy of the loyalty-building strategy. Second, if researchersseek to understand the effect of loyalty on objective

performance outcomes (e.g., revenue, profit), they must mea-sure loyalty as both an attitude and a behavior, because thiscomposition offers the strongest effect on objective perfor-mance (β=0.11, p<.05; Table 1, Model 3). Third, if researchaims to investigate WOM outcomes, attitudinal loyalty maybe the best predictor, because behaviors reflect potential con-straints (e.g., size of wallet, store location) that are less impor-tant for WOM outcomes, whereas technology and other socialshifts appear to enhance the effect of loyalty on WOM overtime (β=0.03, p<.05; Table 4, Model 2). Although re-searchers are cognizant of fusing WOM items into their mea-sures of loyalty, they should work to avoid doing so, accord-ing to our empirical evidence this common practice under-mines the linkage between loyalty and performance, as wellas the theoretical reasons for the separation (de Matos andRossi 2008; Dick and Basu 1994; Söderlund 2006). Fourth,researchers studying loyalty will be better served byemploying backward-looking measures, which also helpguard against potential inflation of the link between loyaltyand WOM (β=0.13, p<.05; Table 4, Model 2). In Table 6 wesummarize best practices derived from recent meta-analysespublished in Journal of Marketing, Journal of MarketingResearch, Journal of Consumer Research, and Journal ofthe Academy of Marketing Science for key research decisions(sample, measurement, heterogeneity, and analyses), whichwe used to guide our methodological approach.

Guidance for practitioners

We offer three primary practical recommendations. First,even if assessed with just two questions (e.g., BWhat isyour attitude about X relative to its competitors?^ andBHow often do you purchase from X instead of itscompetitors?^), customer loyalty measures need to reflectboth attitudes and behaviors, because both aspects ofloyalty together have a stronger effect on objectiveperformance than either alone. The loyalties expressedby a firm’s loyal customers often differ in composition:some customers are only attitudinally loyal or only behav-iorally loyal, and others are both simultaneously, and eachgroup exerts significantly different effects on outcomes(Dick and Basu 1994). Thus, the value of loyalty for aseller depends on not only the level of loyalty but also itscomposition in the customer portfolio. A customer withvery high attitudinal loyalty could report a high net pro-moter score (NPS), which is a popular metric amongFortune 500 companies for measur ing loya l ty(Reichheld 2003), but a lack of corresponding behavioralloyalty may reduce the effect of this NPS on objectiveperformance outcomes (Keiningham et al. 2007). Fromthis perspective, the ultimate effect on a specific outcomedepends largely on which loyalty (attitudinal or behavior-al) the firm considers, such that marketing investments1 We thank an anonymous reviewer for their guidance on this point.


Tab

le5

Summaryof

keyfindings

andim

plications

forresearchersandpractitioners

Definingloyalty

Conceptuald

efinition

Customer

loyalty

isacollectionof

attitudes

alignedwith

aseries

ofpurchase

behaviorsthatsystem

atically

favoroneentityover

competin

gentities.

Measuring

loyalty

Exemplar

attitudinalloyalty

measures

Representativearticles

1.Iprefer

[target]over

competitors.

Breivik

andThorbjørnsen(2008);Y

imetal.(2008)

2.Ienjoydoingbusiness

with

[target].

3.Iconsider

[target]myfirstp

reference.

4.Ihave

apositiv

eattitudetoward[target].

5.Ireally

like[target].

Exemplar

behavioralloyalty

measures

Representativearticles

1.Ioftenbuyproducts/servicesfrom

[target].

Brady

etal.(2012);DeWulfetal.(2001)

2.Ionly

buyproducts/servicesfrom

[target].

3.The

lasttim

eIpurchase

aproduct/service,I

bought

from

[target].

4.Ifrequently

buyfrom

[target].

5.Ibuymostfrom

[target].

Key

findings

Researchandmanagerialimplications

Loyalty

compositio

n

Sixty-five

percento

fresearchersadoptthe

separateloyalty

perspective,

despite

weakerandless

consistent

predictio

nsof

loyalty

outcom

es.

Disagreem

entabout

thenature

ofloyalty

results

invaryingconclusionsaboutloyalty’seffectiveness.

Com

mitm

ent,trust,andsatisfactionhave

stronger

effectson

attitudinal

than

behavioralloyalty,and

loyalty

incentives

have

anegativ

eeffect

onattitudinalloyalty

buta

nonsignificant

effecton

behavioralloyalty.

Consistentw

iththisperspective,antecedentsdifferentially

affectattitudinalandbehavioralloyalty

constructswhenseparated.Researchersseparatin

gattitudinalandbehavioralloyalty

mustq

ualify

thefindings

associated

with

each,because

they

may

notg

eneralizeto

theothermeasure

ofloyalty.

Behavioralloyalty

hasasignificantly

stronger

effecton

performance

(β=0.27)than

attitudinalloyalty

(β=0.02),butb

ehavioralloyalty

hasaweakereffecton

WOM

(β=0.19)than

attitudinalloyalty

(β=0.41).

Conclusions

aboutloyalty’seffectivenessdepend

largelyon

which

loyalty

constructismeasured.

Managersexam

iningloyalty

aseither

attitudes

orbehaviorsmay

beover-or

under-predictin

gloyalty

’strue

effectson

outcom

es,and

over-or

under-valuingcustom

ersas

aresult.

Inmixed

measuresof

custom

erloyalty,a

higher

percentage

ofattitudinal

itemsenhances

theeffectof

loyalty

onWOM

(β=0.33),whilesimultaneouslysuppressingits

effecton

performance

(β=0.40).

Single-constructmeasurementscalesof

aggregateloyalty

should

balanceattitudinalandbehavioral

items.For

exam

ple,holdingallm

easuresattheirmeanin

Model4,a1%

increase

intheratio

ofattitudinalitemsin

abehavioralloyalty

measure

increasestheperformance

predictiv

enessby

25%

(r=.40forpure

behavioral,r

=.50with

1%attitudinalitems).

Factorsthatleverage

theeffectivenessof

loyalty

WOM-inclusive

measure

ofcustom

erloyalty

areless

predictiv

eperformance

(β=− 0

.44).

Researcherscontam

inatingloyalty

measureswith

WOM

may

beunderestim

atingloyalty

’strue

effecton

performance.M

anagersshould

avoidusingNPS

tomeasure

true

loyalty.

Backw

ard-looking(evidence-based)

measuresof

loyalty

arestronger

predictorsof

performance

than

forw

ardlooking(expectatio

n-based)

measures,butthe

reverseistrue

forWOM.

Managersandresearchersshould

carefully

consider

theirloyalty

measurementsaccordingtotheir

objectives.A

lthough

forw

ard-lookingmeasureshave

astronger

associationwith

WOM,the

ease

ofWOM

intentionmay

overstateloyalty

’seffect.

The

effectof

custom

erloyalty

onWOM

hasbeen

increasing

over

thepast10

years(β

=0.03).

Enhancementsin

onlin

etechnology

have

madeiteasier

forcustom

ersto

engage

inWOM

activ

ities.

Decreased

personalrelatio

nships

also

may

increase

theprevalence

andim

portance

ofexchange-

basedrelatio

nships.


Tab

le6

Benchmarkof

methods

inmeta-analyses

publishedin

marketin

gjournalssince2012

a

Reference

DataSetdevelopm

ent

Effectsizestatistic

Moderatorsto

assess

heterogeneity

inprim

arysamples

Analysisapproach

Robustnesschecks

Measurement

heterogeneity

Additional

heterogeneity

Pick

andEisend

2014

170samples.D

atabase

search

supplemented

with

manualsearch

ofkeyjournalsand

referencelisto

fkey

articles.Contacted

leadingauthorsfor

working

orunpublished

samples.

Correlatio

ncoefficeint

(converted

from

other

statisticsifcorrelation

notreported)

inverse

variance

weightedand

adjusted

formeasurement

reliability.

Type

ofmeasuremento

fmain

constructs,intentions

vs.

behaviorsandmonetary

vs.non-m

onetarycosts.

Characteristicsof

the

context(e.g.,service

vsgoods,B2C

vs.B

2B)

andstudydesign

(e.g.,

fieldvs

experimental

design,singlevs.

multip

lefirm

sin

sample)

HunterandSchm

idt

(2004)

bivariateanalysis.

SEM

path

analysison

meta-analyticcorrelation

matrix.Moderationwith

Qstatistic

andcomparison

ofeffectsizesaccounting

forsamplesize.

Reportedresults

fortwocompetin

gSE

Mmodels.

vanLaeretal.

2014

132samples.S

earched

13yearsof

manuscripts

across

five

languages,

includingunpublished

studiesandbook

sections.

Measurementscalewas

prim

aryinclusioncriteria.

Correlatio

ncoefficeint

(converted

from

other


notreported)

inverse

variance

weightedand

adjusted

formeasurement

reliability.

Type

ofmeasurement

scaleused

formain

construct.

Characteristicsof

average

subject(e.g.,average

ageof

respondent)in

each

prim

arystudy.

HunterandSchm

idt(2004)

bivariateanalysis.C

hecked

formoderationwith

Q-statistic.

Reportedresults

for

rawcorrelations,

inverse-variance

weightedcorrelations,

andinverse-variance

weightedwith

reliability

adjustmentcorrected

correlations.

Ruberaand

Kirca

2012

159samples.S

earchfocused

on15

journals.S

upplem

ented

with

unpublishedwork

andpapersfoundfrom

anexam

inationof

review

articles’

referencesections.

Correlatio

ncoefficeint

(converted

from

other


notreported)

inverse

variance

weightedand

adjusted

formeasurement

reliability.

Type

ofmeasurement

ofmainconstruct,

threedifferenttypes

ofoutcom

es,and

objectivevs.subjective

measures.

Characteristicsof

average

firm

s(e.g.,advertising

intensity

)in

prim

ary

studies,research

context

(e.g.,industry,location,

year),andpublication

(i.e.,marketin

gvs.

managem

entjournal).

HunterandSchm

idt

(1990)

bivariateanalysis.

SEM

path

analysison

meta-analyticcorrelation

matrix,andmultilevel

modelsformoderation

analysis.

Investigated

reverse

causality

usingstudies

thatreported

correlations

betweenoutcom

esmeasuredattim

etand

predictorattim

et+1.

Investigated

possiblebias

from

omitted-variables

andmulticolinearity.

Zablahetal.

2012

323samples.D

atabase

search

supplementedwith

manualsearchof

related

specialized

journals.L

imited

inclusionto

studiesconducted

inEnglishto

limitinfluence

ofculture.

Correlatio

ncoefficients.

Estim

ated

meancorrelations

andvariance

usingrandom

effects,multilevelmodels

(Raudenbush2009).

Did

nottransform

raw

correlations

toz-scores

(HunterandSchm

idt2

004).

None;prim

arystudies

wereconsistent

intheir

measurementapproach.

Researchcontext

(e.g.,jobs

where

employeesinteract

with

alargenumber

ofcustom

ers).

Estim

ated

averagecorrelation

coefficientsandvariance

usingrandom

effectsmodels,

then

SEM

path

analysis

onestim

ated

correlations,

andmultilevelmodels

formoderationanalysis.

Dropped

allstudies

publishedin

journals

oflower

quality

(based

onjournalscore

onSS

CI)

andrepeated

path

analysis

tocheckforconsistent

results.

Hom

burg

etal.

2012

431samples.T

horough

search

ofarticlesfrom

6influentialjournalsover

a13-yearwindow.

Correlatio

n(Pearson’s’

randICC)andagreem

ent

statistics.Correlatio

nstransformed

toz-scores

andcorrectedformeasurement

errorandconstructsim

ilarity.

Type

ofreliability

(Pearson’sror

ICC),

five

characteristicsof

measures(e.g.,present

vs.pastfocused,objectiv

evs.subjective,peoplevs.

nonpersonalentities),and

twocharacteristicsof

Characteristicsof

averageinform

ant

(e.g.,organizational

role),characteristics

ofaverageorganizatio

n(e.g.,firm

age),and

research

context(e.g.,

industry

dynamism).

HunterandSchm

idt(2004)

weightedmeanwith

subgroup

analysisby

context.

Weightedregression

for

testinghypothesis,w

eightin

gby

inverseof

standard

errors

ofeach

study’seffects.

Usedmultilevelmodels

unless

missing

values

Com

paredresults

from

reliabilityandagreem

ent

(twoseparateindicators).

Investigatepublication

bias

with

failsafe

Nand

Btrim

andfill^

methodto

checkforpotentialm

issing

studiesthatmight

pulldown

theaverageeffectsize.


Tab

le6

(contin

ued)

Reference

DataSetdevelopm

ent

Effectsizestatistic

Moderatorsto

assess

heterogeneity

inprim

arysamples

Analysisapproach

Robustnesschecks

Measurement

heterogeneity

Additional

heterogeneity

triangulation(e.g.,archival

vs.customer

data).

required

analysisat

studylevel.

Steenkam

pand

Geyskens2012128samples

represented

companies

in12

countries.

Correlatio

ncoefficient

(converted

from

other


notreported),corrected

fornon-independence,

outliers,andsevenstatistical

artifacts(e.g.,measurement

error,rangerestriction).

Initialcorrectio

nfor

variance

inmeasurement

artifacts(e.g.,dichotom

ization

ofacontinuous

variable),

butn

ottested

asmoderator.

Characteristicsof

studies’

context(e.g.,cultural

dimensions,region,

country,year)and

exchange

governance

(e.g.,hierarchicalvs.

relatio

nal).

Modelestim

ated

study

correlations

asafunctio

nof

characteristicsusing

GLSestim

ationtechniques

formeta-analysisthat

accountsfordependencies

amongcorrelations

that

comefrom

thesamestudy.

Tested

twoalternative

(but

overlapping)

theoretical

modelsof

cultu

raleffects

onTCE.U

sedeffectcoding

toremoveinfluenceof

unequally

sizedgroups

from

theoverall

estim

ated

meancorrelations.

Tested

moderationby

estim

atinginteraction

coefficients.

Summaryof

best

practices

Casta

widenettoobtain

alargesampleof

studies

estim

atingrelevant

effects,

andusecoding

totest

ifdifferencesin

theoriginal

studies’contextand

publication

status

(e.g.,region,year,publication

status,journalreputatio

n)system

atically

altereffectsizes.

Unit-less

indicatorof

effect

sizes:correlationcoefficients

(com

plex

multiv

ariatemodels)

orestim

ated

elasticities

(variables

measuredwith

objectiveindicators).

Exercisecautionwith

transformations

and

conversions,checkifit

influences

results.

Testifheterogeneity

inoperationald

efinition

and/or

measurementscalesof

keyconstructsystematically

influences

effectsizes.

Consider:Average

unit/

respondent,research

context,publicationoutlet,

datacollectionmethod,

andmodel(w

henusing

modelestim

ates

rather

than

correlations).

Estim

atemeaneffectsize

using

random

effectsmodels.Test

ifheterogenietyacross

prim

arystudiesinfluences

meaneffectsize.M

eta-analytic

SEM

path

analysisifstudying

acomplex

multiv

ariatemodel,

exploringsystem

ofrelatio

nships.

Consideralternativemodels

totestkeyrelatio

nships.

Testmoderatorsindividually

andin

groups

ifmulticollin

earity

isan

issue.Run

analysis

with

andwith

outaccounting

forweights(e.g.,samplesize).

Check

forpublicationbias

andjournalq

ualityby

testingitas

apredictorof

effectsizes.Use

funnelplots

andtrim

andfillto

checkfori

ssueswith

sampleandinclusion.

aTablesummarizes

recently

publishedarticlesfrom

Journalo

fMarketin

g,Journalo

fMarketin

gResearch,Journalo

fthe

Academyof

Marketin

gScience,andJournalo

fConsumer

Research.Marketin

gSciencedidnotp

ublishanyarticlesusingmeta-analytictechniques

during

thistim

ewindow


may be misallocated simply because of the type of loyaltyused to evaluate the investment. Similarly, assessments ofcustomers’ future value may be biased by the loyalty metricused as an intermediate indicator of future performance.

Second, our findings suggest that customer loyaltycannot be bought using incentive strategies but can bebuilt with relational strategies (commitment, trust, andsatisfaction). The $48 billion spent on U.S. loyalty pro-grams likely is not building Btrue^ loyalty (Berry 2013).For an average customer, adding another loyalty card tothe dozens he or she already owns may be less effectivefor building attitudinal and behavioral loyalties (β=−0.08 and 0.01) than building relationships throughcommitment (β=0.34 to 0.35) and trust (β=0.27 to0.22) or improving transaction performance though sat-isfaction (β=0.25 and 0.04) (Model 1).

Third, strategies for capitalizing on WOM should beseparate from strategies aimed at increasing customerloyalty. Including WOM in loyalty measures detractsfrom the construct’s accuracy for predicting performance(β=−0.44, p<.05, Model 3). This point is especiallyimportant in light of our finding that customer loyaltyhas a stronger effect on WOM, but not performance, inbusiness markets than in consumer markets, which like-ly reflects the greater interrelatedness in business rela-tionships. Customers with high attitudinal loyalty likelyspread WOM (β=0.41, p<.05, Model 1) but might notcontribute much to a seller’s bottom line (β=0.02,p>.05) though their behaviors. Therefore, managerswho take a portfolio approach to marketing invest-ments—such that they recognize customer referral valueas separate from customer lifetime value (Petersen et al.2009)—should invest in attitudinal loyalty only insofaras it maximizes their overall customer portfolio lifetimevalue. This implication may be especially relevant forservice settings and business-to-business markets, inwhich the effect of loyalty on WOM is much stronger.

Limitations and directions for research

Typical of meta-analyses, this study has several limita-tions. First, we attempted to include many loyalty con-structs and samples across publication outlets, but wemay have overlooked some. Second, the constructs weinclude and our results are limited to variables forwhich there exist enough data for analysis. Our frame-work is a summary of important loyalty-related con-structs, not an exhaustive list. Our primary objectivewas to ascertain the implications of heterogeneity inextant loyalty conceptualizations and measurements,which required a thorough examination of loyalty’s re-lationship to a few key constructs rather than all con-structs. Third, the heterogeneity in effect sizes that was

not accounted for by our moderation analysis suggeststhat including other, unmeasured moderating factorsmight influence the reported effect sizes.

Further research thus might expand the constructs in-cluded in our customer loyalty framework to examinehow they differentially affect attitudinal loyalty, behav-ioral loyalty, and customer loyalty. Dependence, cooper-ation, communication, conflict, and unfairness all mightexert distinct influences on types of loyalty. Additionally,new research may also consider whether and how vari-ous types of financial outcomes (e.g., Tobin’s Q vs. ROI)are differentially impacted by attitudinal, behavioral, orcombined loyalty. Clarifying these effects would providea richer set of options for managers to tailor their mar-keting actions to enhance WOM and performance, giventheir unique circumstances.

Conclusion

Practitioners recognize the importance of repeat patron-age, but Bfew say they have cracked the code on build-ing long-term loyalty^ (Weissenberg 2013). Despite ele-gant conceptualizations (Dick and Basu 1994; Oliver1999), academics have failed to demonstrate consistentlyhow loyalty builds and when it is most effective. It istherefore no surprise that many of the promises associ-ated with building customer loyalty remain unrealized.We find evidence in support of the premise that thisfailure stems, in part, from a systematic divergence be-tween the conceptualizations (What is customerloyalty?) and measurement (How is it measured?) ofloyalty. We aggregate more than three decades of loyal-ty research to address this divergence and explicatewhen differences between theory and practice influencethe strategy → loyalty → performance process (Whatactually matters?).

Our results offer clear evidence in support of con-struct divergence. Although loyalty is primarily concep-tualized as the alignment of attitudes and behaviors,items used to measure loyalty often include extraneousconstructs (Table 2). In addition, study-specific charac-teristics get incorporated into conceptualizations and/oroperationalizations of loyalty, often with little or no dis-cussion of their potential effects. We have assessed themoderating effect of several aspects of loyalty across163 studies published in marketing journals since 1980that measure loyalty as an attitude, a behavior, or bothto determine when loyalty is most effective forpredicting performance outcomes.

Acknowledgments The authors thank the Marketing Science Institute(MSI) for their feedback and publication of a working paper of thisresearch.


App

endix

Tab

le7

Alphabeticallisto

fstudies

Reference

Unpublished

Loyalty

perspective

Temporal

orientation

Target

Market

Com

mon

method

bias

susceptib

ility?

Journalq

uality

(Eigenfactor)

Aaltonen,Priscilla

(2004),BCustomer

RelationshipMarketin

gandEffectsof

Dem

ographicsandTechnology

onCustomer

SatisfactionandLoyalty

inFinancialServices,^

doctoral

dissertatio

n,Departm

ento

fMarketin

g,Old

Dom

inion

University.

Unpublished

Inclusive

Forw

ard-looking

Firm

B2C

Yes

0.004057

Agustin,C

lara,and

JagdipSingh

(2005),BCurvilin

earE

ffectsof

Consumer

Loyalty

Determinantsin

RelationalE

xchanges,^

Journalo

fMarketin

gResearch,42

(February),96–108.

Published

Behavioral

Forward-looking

Firm

B2C

Yes

0.014522

Algesheim

er,R

ené,UtpalM.D

holakia,andAndreas

Herrm

ann

(2005),BThe

SocialInfluenceof

Brand

Com

munity

:Evidencefrom

EuropeanCar

Clubs,^

Journalo

fMarketin

g,69

(July),19–34.

Published

Behavioral

Forward-looking

Brand

B2C

Yes

0.012337

Anderson,Erin,andBartonWeitz(1989),BDeterminantsof

Contin

uity

inConventionalIndustrialC

hannelDyads,^

Marketin

gScience,8(September),310–323.

Published

Behavioral

Forward-looking

Individual

B2B

No

0.011581

Anderson,EugeneW.,andMaryW.S

ulliv

an(1993),BThe

AntecedentsandConsequencesof

Customer

Satisfactionfor

Firm

s,^Marketin

gScience,12

(March),125–143.

Published

Behavioral

Forward-looking

Firm

B2C

No

0.011581

Anderson,Rolph

E.,andSrinivasan

Swam

inathan(2011),

BCustomer


inE-M

arkets:A

PLS

PathModelingApproach,^Th

eJournalofM

arketin

gTheory

andPractice,19

(March),221–234.

Published

Aggregate

Backw

ard-looking

Firm

B2C

Yes

0.000000

Arnett,DennisB.,SteveD.G

erman,and

Shelby

D.H

unt(2003),

BThe

IdentitySalienceModelof


gSu

ccess:The

Caseof

NonprofitMarketin

g,^Journalo

fMarketin

g,67

(April),89–105.

Published

Behavioral

Backw

ard-looking

Firm

B2C

Yes

0.012337

Arnold,MarkJ.,and

KristyE.R

eynolds(2009),BAffectand

RetailS

hoppingBehavior:Understanding

theRoleof

Mood

RegulationandRegulatoryFo

cus,^Journalo

fRetailin

g,85

(September),308–320.

Published

Behavioral

Backw

ard-looking

Firm

B2C

Yes

0.002899

Ashok,K

alidas,W

illiam

R.D

illon,and

SophieYuan(2002),

BExtending

DiscreteChoiceModelsto

Incorporate

Attitudinaland

OtherLatentV

ariables,^JournalofM

arketin

gResearch,39

(February),31–46.

Published

Attitudinal,

Behavioral

Backw

ard-looking

Individual

B2C

Yes

0.014522

Auh,Seigyoung,Sim

onJ.Bell,ColinS.McL

eod,andEricShih

(2007),BCo-ProductionandCustomer

Loyalty

inFinancial

Services,^

Journalo

fRetailin

g,83

(August),359–370.

Published

Behavioral

Forward-looking

Individual

B2C

No

0.002899

Bagchi,RajeshandXingboLi(2011),BIllu

sionaryProgress

inLoyalty

Program

s:MagnitudesRew

ardDistances

andStep-

Size

Ambiguity,^

Journalo

fConsumer

Research,37


Published

Behavioral

Forward-looking

Individual

B2C

Yes

0.012091


Tab

le7

(contin

ued)

Reference

Unpublished

Loyalty

perspective

Temporal

orientation

Target

Market

Com

mon

method

bias

susceptib

ility?

Journalq

uality

(Eigenfactor)

Baker,Julie,A

.Parasuram

an,D

hruv

Grewal,and

Glenn

B.V

oss

(2002),BThe

Influenceof

Multip

leStore

EnvironmentC

ues

onPerceivedMerchandise

Value

andPatronageIntentions,"

Journalo

fMarketin

g,66

(April),120–141.

Published

Inclusive

Forw

ard-looking

Firm

B2C

Yes

0.012337

BarksdaleJr.,Hiram

C.(1997),BA

RelationshipMaintenance

Model:A

Com

parisonBetweenManaged

Health

Careand

Traditio

nalF

ee-for-Service,^

Journalo

fBusinessResearch,

40(N

ovem

ber),237–247.

Published

Behavioral

Forward-looking

Individual

B2C

Yes

0.009203

Barnes,James

G.(1997),BC

loseness,Strength,andSatisfaction:

ExaminingtheNatureof

Relationships

betweenProvidersof

FinancialS

ervicesandTheirRetailC

ustomers,^Psychology

andMarketin

g,14

(Decem

ber),765–790.

Published

Inclusive

Backw

ard-looking

Individual

B2C

Yes

0.002793

Ben-Rechav,Gila

Gabay

(2000),BRelationshipSellin

gand

Trust:A

ntecedentsandConsequences,^doctoraldissertatio

n,Marketin

gDepartm

ent,Portland

StateUniversity.

Unpublished

Inclusive

Backw

ard-looking

Individual

B2C

No

0.004057

Bettencourt,L

ance

A.(1997),BC

ustomer

Voluntary

Performance:C

ustomersas

Partnersin

Service

Delivery,^

Journalo

fRetailin

g,73


Published

Aggregate

Backw

ard-looking

Firm

B2C

Yes

0.002899

Biong,H

arald(1993),BSatisfactionandLoyalty

toSuppliers

with

intheGrocery

Trade,^

EuropeanJournalo

fMarketin

g,27

(July),21–38.

Published

Behavioral

Forward-looking

Firm

B2B

Yes

0.002564

Blocker,C

hristopherP.,D

anielJ.F

lint,Matthew

B.M

yers,and

StanleyF.Slater(2011),BProactiveCustomerOrientatio

nand

itsRoleforCreatingCustomerValue

inGlobalM

arkets,^

Journalo

fthe

Academyof

Marketin

gScience,39

(April),

216–233.

Published

Behavioral

Forward-looking

Firm

B2B

Yes

0.005403

Blodgett,JeffreyG.(1993),"The

Effectsof

PerceivedJusticeon

Com

plainants’NegativeWord-of-M

outh

Behaviorand

Repatronage

Intentions,^

Journalo

fRetailin

g,69

(Decem

-ber),399–428.

Published

Behavioral

Forward-looking

Firm

B2C

Yes

0.002899

Bodet,G

uillaum

e,andIouriB

ernache-Assollant

(2011),

BConsumer

Loyalty

inSportSp

ectatorshipServices:T

heRelationships

with

Consumer

SatisfactionandTeam

Identification,^PsychologyandMarketin

g,28

(Decem

ber),

781–802.

Published

Behavioral

Forward-looking

Firm

B2C

Yes

0.002793

Boles,Jam

esS.,Julie

T.Johnson,andHiram

C.B

arksdaleJr.

(2000),BHow

SalespeopleBuild

QualityRelationships:A

ReplicationandExtension,^JournalofB

usinessResearch,48

(April),75–81.

Published

Behavioral

Forward-looking

Individual

B2B

Yes

0.009203

Boonajsevee,B

hoom

ipan

(2005),BRelationshipMarketin

g:Loyalty

Intentions

inNew

Era

ofThaiB

ankMarketin

g,^

Marketin

gDepartm

ent,NovaSoutheasternUniversity.

Unpublished

Inclusive

Forw

ard-looking

Firm

B2C

Yes

0.004057


Tab

le7

(contin

ued)

Reference

Unpublished

Loyalty

perspective

Temporal

orientation

Target

Market

Com

mon

method

bias

susceptib

ility?

Journalq

uality

(Eigenfactor)

Bow

den,Jana

Lay-H

wa(2011),BEngagingtheStudent

asa

Customer:A


gApproach,^Marketin

gEducatio

n,21


Published

Inclusive

Backw

ard-looking

Firm

B2C

Yes

0.000000

Brady,M

ichaelK.,ClayM.V

oorhees,andMichaelJ.Brusco

(2012),BService

Sweethearting:

ItsAntecedentsand

CustomerConsequences,^JournalofM

arketin

g,76

(March),

81–98.

Published

Aggregate

Backw

ard-looking

Firm

B2B

Yes

0.012337

Breivik,E

inar,and

Helge

Thorbjørnsen(2008),BConsumer

Brand

Relationships:A

nInvestigationof

TwoAlternative

Models,^Journalo

fthe

Academyof

Marketin

gScience,36

(Decem

ber),443–472.

Published

Attitudinal,

Behavioral

Forw

ard-looking

Brand

B2C

Yes

0.005403

Brexendorf,Tim

Oliv

er,Silk

eMühlm

eier,Torsten

Tomczak,and

Martin

Eisend(2010),BThe

Impactof

Sales

Encounterson

Brand

Loyalty,^

Journalo

fBusinessResearch,

63(N

ovem

ber),1148–1155.

Published

Attitudinal,

Behavioral

Forw

ard-looking

Brand

B2C

Yes

0.009203

Candi,M

arina(2010),BBenefits

ofAestheticDesignas

anElemento

fNew

Service

Development,^

Journalo

fProduct

Innovatio

nManagem

ent,27

(October),1047–1064.

Published

Behavioral

Backw

ard-looking

Firm

B2B

Yes

0.003957

Cases,A

nne-So

phie,C

hristopheFo

urnier,P

ierre-LouisDubois,

andJohn

F.Tanner

Jr.(2010)BW

ebSite

SpillOverto

Email

Cam

paigns:T

heRoleof

Privacy,Trust,and

Shoppers’

Attitudes,^Journalo

fBusinessResearch,63

(September-

October),993–999.

Published

Attitudinal

Backw

ard-looking

Firm

B2C

Yes

0.009203

Castaldo,Sandro,Francesco

Perrini,N

icolaMisani,andAntonio

Tencati(2009),BT

heMissing

LinkBetweenCorporateSocial

Responsibility

andConsumer

Trust:T

heCaseof

FairTrade

Products,^

Journalo

fBusinessEthics,84

(January),1 –15.

Published

Aggregate

Forward-looking

Brand

B2C

Yes

0.013950

Chaudhuri,A

rjun,and

MorrisB.H

olbrook(2001),BThe

Chain

ofEffectsfrom

Brand

TrustandBrand

AffecttoBrand

Performance:T

heRoleof

Brand

Loyalty,^

Journalo

fMarketin

g,65

(April),81–93.

Published

Attitudinal,

Behavioral

Forw

ard-looking

Brand

B2C

No

0.012337

Chebat,Jean-Charles,M

.JosephSirgy,StephanGrzeskowiak

(2010),BHow

Can

Shopping

MallM

anagem

entB

estC

apture

MallImage?^JournalofB

usinessResearch,63

(2010),735–

740.

Published

Attitudinal,

Behavioral

Backw

ard-looking

Firm

B2C

Yes

0.009203

Chittu

ri,R

avindra,RajagopalRaghunathan,and

VijayMahajan

(2008),BDelight

byDesign:

The

Roleof

HedonicVersus

Utilitarian

Benefits,^JournalofM

arketin

g,72

(May),48–63.

Published

Behavioral

Forward-looking

Firm

B2C

Yes

0.012337

Collishaw,M

aryAnn,L

inda

Dyer,andKathleenBoies

(2008),

BThe

Authenticity

ofPositive

EmotionalD

isplays:Client

Responses

toLeisureServiceEmployees,^JournalofL

eisure

Research,40

(January),23–46.

Published

Inclusive

Backw

ard-looking

Individual

B2C

Yes

0.000870


Tab

le7

(contin

ued)

Reference

Unpublished

Loyalty

perspective

Temporal

orientation

Target

Market

Com

mon

method

bias

susceptib

ility?

Journalq

uality

(Eigenfactor)

CroninJr.,J.Joseph,and

MicahelK.B

rady,and

G.T

omas

M.

Hult(2000),BA

ssessing

theEffectsof

Quality,Value,and

Customer

Satisfactionon

Consumer

BehavioralIntentio

nsin

ServiceEnvironments,^

JournalofR

etailin

g,76

(June),193–

218.

Published

Inclusive

Forw

ard-looking

Firm

B2C

Yes

0.002899

CroninJr.,J.Joseph,and

Steven

A.T

aylor(1992),BMeasuring

ServiceQuality:AReexaminationandExtension,^Journalof

Marketin

g,56

(July),55–68.

Published

Behavioral

Forward-looking

Firm

B2C

Yes

0.012337

Davis-Sramek,B

eth,Cornelia

Droge,JohnT.

Mentzer,and

Matthew

B.M

yers(2009),BCreatingCom

mitm

entand

Loyalty

BehaviorAmongRetailers:W

hatare

theRoles

ofServiceQualityandSatisfaction?^Journalofthe

Academyof

Marketin

gScience,37

(Decem

ber),440–454.

Published

Attitudinal,

Behavioral

Backw

ard-looking

Firm

B2B

Yes

0.005403

Daw

es,John(2009),BThe

Effecto

fService

Price

Increaseson

CustomerRetentio

ntheModeratingRoleof

CustomerTenure

andRelationshipBreadth,^

Journalo

fService

Research,11


Published

Behavioral

Backw

ard-looking

Firm

B2C

No

0.002729

DeWulf,Kristof,G

abyOdekerken-Schröder,andDaw

nIacobucci(2001),BInvestm

entsin

Consumer

Relationships:

ACross-Country

andCross-IndustryExploratio

n,^Journal

ofMarketin

g,65

(October),33–50.

Published

Behavioral

Backw

ard-looking

Firm

B2C

Yes

0.012337

Dem

oulin

,Nathalie,and

Pietro

Zidda

(2009).BDriversof

Customers’AdoptionandAdoptionTim

ingof

aNew

Loyalty

Cardin

theGrocery

RetailM

arket,^

Journalo

fRetailin

g,85


Published

Behavioral

Backw

ard-looking

Firm

B2C

Yes

0.002899

Deng,Zhaohua,Y

aobinLu,Kwok

Kee

Wei,and

JinlongZhang

(2010),"Understanding

Customer

SatisfactionandLoyalty:

AnEmpiricalS

tudy

ofMobile

InstantM

essagesin

China,"

InternationalJournal

ofInform

ationManagem

ent,30

(August),289–300.

Published

Inclusive

Forw

ard-looking

Firm

B2C

Yes

0.001389

Dröge,C

ornelia

(1989),BSh

apingtheRoutetoAttitude

Change:

CentralVersusPeripheralP

rocessingThrough

Com

parativ

eVersusNoncomparativ

eAdvertising,^Journalo

fMarketin

gResearch,26

(May),193–204.

Published

Attitudinal,

Behavioral

Forw

ard-looking

Brand

B2C

Yes

0.014522

Echam

badi,R

aj,R

upinderP.Jindal,and

Edw

ardA.B

lair

(2013),BEvaluatingandManagingBrand

RepurchaseAcross

Multip

leGeographicRetailM

arkets,^

Journalo

fRetailin

g,89

(Decem

ber),409–422.

Published

Behavioral

Backw

ard-looking

Brand

B2C

No

0.002899

Evanschitzky,H

einer,B.R

amaseshan,David

M.

Woisetschläger,VerenaRichelsen,M

arkusBlut,andChristof

Backhaus(2010),BConsequencesof

CustomerLoyaltytothe

Loyalty

Program

andto

theCom

pany,^

Journalo

fthe

Academyof

Marketin

gScience,40


Published

Inclusive

Forw

ard-looking

Firm

B2C

Yes

0.005403


Tab

le7

(contin

ued)

Reference

Unpublished

Loyalty

perspective

Temporal

orientation

Target

Market

Com

mon

method

bias

susceptib

ility?

Journalq

uality

(Eigenfactor)

Evanschitzky,H

einer,Gopalkrishnan

R.Iyer,Hilk

ePlassmann,

JoergNiessing,andHeribertM

effert(2006),BThe

Relative

Strength

ofAffectiv

eCom

mitm

entinSecuring

Loyalty

inServiceRelationships,^

Journalo

fBusinessResearch,

59(N

ovem

ber),1207–1213.

Published

Inclusive

Forw

ard-looking

Firm

B2C

Yes

0.009203

Farrelly,F

rancisJohn,and

Quester,P

ascaleGenevieve

(2003),

BWhatD

rivesRenew

alof

Sponsorship

Principal/A

gent

Relationships?^

Journalo

fAdvertisingResearch,43

(April),

353–360.

Published

Behavioral

Forward-looking

Firm

B2B

Yes

0.000000

Fletcher,K

eithP.,and

Linda

D.P

eters(1997),BTrustandDirect

Marketin

gEnvironments:A

ConsumerPerspectiv

e,^Journal

ofMarketin

gManagem

ent,13

(August),523–539.

Published

Aggregate

Forward-looking

Firm

B2C

Yes

0.000000

Friend,S

cottB.,G.A

lexanderHam

wi,andBrian

N.R

utherford

(2011),BBuyer–S

ellerRelationships

With

inaMultisource

Context:U

nderstanding

Customer

Defectio

nandAvailable

Alternatives.^

Journalo

fPersonalS

ellin

gandSales

Managem

ent,31

(April),383–395.

Published

Behavioral

Forward-looking

Individual

B2B

Yes

0.000000

Ganesh,Jaishankar,M

arkJ.Arnold,andKristyE.R

eynolds

(2000),BUnderstanding

theCustomer

Baseof

Service

Providers:AnExaminationof

theDifferences

Between

SwitchersandStayers,^

Journalo

fMarketin

g,64

(July),p

65–87.

Published

Inclusive

Backw

ard-looking

Firm

B2C

Yes

0.012337

Garbarino,E

llen,andMarkS.Johnson

(1999),BThe

Different

Roles

ofSatisfaction,Trust,and

Com

mitm

entinCustomer

Relationships,"Journalo

fMarketin

g,63

(April),70–87.

Published

Attitudinal,

Behavioral

Forw

ard-looking

Firm

B2C

Yes

0.012337

Garnefeld,Ina,A

ndreasEggert,SabrinaV.H

elm,and

StephenS.

Tax(2013),"GrowingExistingCustomers'Revenue

Stream

sThrough

Customer

ReferralP

rogram

s,^Journalo

fMarketin

g,77

(July),17–32.

Published

Attitudinal,

Behavioral

Forw

ard-looking

Firm

B2C

Yes

0.012337

Gelbrich,Katja(2011),BIHavePaid

LessThanYou!The

Emotionaland

BehavioralC

onsequencesof

Advantaged

PriceInequality,^Journalo

fRetailin

g,87

(June),207–224.

Published

Behavioral

Forward-looking

Firm

B2C

Yes

0.002899

Gilly,MaryC.,andBetsy

D.G

elb(1982),BPo

st-Purchase

Consumer

ProcessesandtheCom

plaining

Consumer,"

Journalo

fConsumer

Research,9(D

ecem

ber),323–328.

Published

Behavioral

Backw

ard-looking

Firm

B2C

Yes

0.012091

Gil-Saura,Irene,andMariaEugeniaRuiz-Molina(2011),"Lo-

gisticsService

QualityandBuyer–C

ustomer

Relationships:

The

ModeratingRoleof

Technology

inB2B

andB2C

Contexts,^Services

Industries

Journal,31

(May),1109–

1123.

Published

Aggregate

Backw

ard-looking

Firm

B2C

Yes

0.002556

Gottlieb,B

.H.,Grewal,D

.,&

Brown,S.

W.1994.Consumer

satisfactionandperceivedquality

:Com

plem

entary

ordivergentconstruct?JournalofA

ppliedPsychology,79:875–

885.

Published

Behavioral

Forward-looking

Firm

B2C

Yes

0.032970


Tab

le7

(contin

ued)

Reference

Unpublished

Loyalty

perspective

Temporal

orientation

Target

Market

Com

mon

method

bias

susceptib

ility?

Journalq

uality

(Eigenfactor)

Gruen,T

homas

W.,TalaiO

smonbekov,AndrewJ.Czaplew

ski

(2007),BCustomer-to-Customer

Exchange:ItsMOA

Antecedentsandits

Impacton

valueCreationandLoyalty,^

Journalo

fthe

Academyof

Marketin

gScience,35

(2007),

537–549.

Published

Inclusive

Forw

ard-looking

Firm

B2C

Yes

0.005403

Guo,C

hinquan(2001),BMarketO

rientatio

nandCustomer

Satisfaction:

AnEmpiricalInvestig

ation,^Departm

ento

fMarketin

g,So

uthern

Illin

oisUniversity

atCarbondale.

Unpublished

Behavioral

Backw

ard-looking

Firm

B2B

Yes

0.004057

Gustafsson,Anders,MichaelD.Johnson,and

IngerRoos

(2005),BThe

Effectsof

Customer

Satisfaction,Relationship

Com

mitm

entD

imensions,andTriggerson

Customer

Retentio

n,^Journalo

fMarketin

g,69

(October),210–218.

Published

Behavioral

Backw

ard-looking

Firm

B2C

No

0.012337

Harris,Lloyd

C.,andMarkM.H.G

oode

(2004),BThe

Four

Levelsof

Loyalty

andthePivotalRoleof

Trust:A

Studyof

OnlineService

Dynam

ics,^Journalo

fRetailin

g,80


Published

Aggregate

Backw

ard-looking

Firm

B2C

Yes

0.002899

Heitm

ann,Mark,DonaldR.L

ehmann,andAndreas

Herrm

ann

(2007),BChoiceGoalA

ttainmentand

Decisionand

ConsumptionSatisfaction,^Journalo

fMarketin

gResearch,

44(M

ay),234–250.

Published

Behavioral

Forward-looking

Brand

B2C

No

0.014522

Hennig-Thurau,Thorsten,Kevin

P.Gwinner,andDwayne

D.

Gremler(2002),BUnderstanding


gOutcomes

anIntegrationof

RelationalB

enefits

and

RelationshipQuality,^Journalo

fService

Research,4


Published

Aggregate

Forward-looking

Firm

B2C

Yes

0.002729

Hennig-Thurau,Thorsten,MarkusF.Langer,andUrsulaHansen

(2001),BModelingandManagingStudentL

oyalty

An

ApproachBased

ontheConcept

ofRelationshipQuality,^

Journalo

fService

Research,3(M

ay),331–344.

Published

Inclusive

Forw

ard-looking

Individual

B2C

Yes

0.002729

Hennig-Thurau,Thorsten,MarkusGroth,M

ichaelPaul,and

Dwayne

D.G

remler(2006),BAreAllSmilesCreated

Equal?

How

EmotionalC

ontagion

andEmotionalL

abor

Affect

ServiceRelationships,^

Journalo

fMarketin

g,70

(July),58–

73.

Published

Inclusive

Forw

ard-looking

Firm

B2C

Yes

0.012337

Hew

ett,Kelly,R

.Bruce

Money,and

SubhashSh

arma(2002),

BAnExploratio

nof

theModeratingRoleof

Buyer

Corporatio

nCulture

inIndustrialBuyer-Seller

Relationships,^

Journalo

fthe

Academyof

Marketin

gScience,30

(June),229–239.

Published

Behavioral

Forward-looking

Firm

B2B

Yes

0.005403

Ho,Hung-Hsin(2009),BThe

Roleof

Com

mitm

entintheRela-

tionshipbetweenCustomer

SatisfactionandCustomer

Loy-

alty

intheBanking

Industry:T

heMediatin

gEffecto

fCom

mitm

ent,^

Departm

ento

fMarketin

g,University

ofMarylandUniversity

College

Unpublished

Inclusive

Forw

ard-looking

Firm

B2C

Yes

0.004057


Tab

le7

(contin

ued)

Reference

Unpublished

Loyalty

perspective

Temporal

orientation

Target

Market

Com

mon

method

bias

susceptib

ility?

Journalq

uality

(Eigenfactor)

Hom

burg,C

hristian,andAndreas

Fürst(2005),BH

owOrganizationalC

omplaint

HandlingDrivesCustomer

Loyalty:A

nAnalysisof

theMechanisticandtheOrganic

Approach,^Journalo

fMarketin

g,69

(July),95–114.

Published

Aggregate

Forward-looking

Firm

B2B

Yes

0.012337

Hom

burg,C

hristian,Andreas

Fürst,and

Jana-K

ristin

Prigge

(2010),BACustomer

Perspectiv

eon

ProductE

liminations:

How

theRem

ovalof

RroductsAffectsCustomersandBusi-

ness

Relationships,^

Journalo

fthe

Academyof

Marketin

gScience,38

(October),531–549.

Published

Aggregate

Forward-looking

Firm

B2B

Yes

0.005403

Hom

burg,C

hristian,JanWieseke,and

Wayne

D.H

oyer(2009),

BSocialIdentity

andtheService–P

rofitC

hain,^

Journalo

fMarketin

g,73

(March),38–54.

Published

Inclusive

Forw

ard-looking

Firm

B2C

Yes

0.012337

Hong,IlyooB.,andWhihyungCho

(2011),BThe

Impactof

Consumer

Truston

AttitudinalL

oyalty

andPu

rchase

Intentions

inB2C

e-Marketplaces:Interm

ediary

Trustvs.

SellerTrust,^


ofInform

ation

Managem

ent,31

(October),469–479.

Published

Behavioral

Forward-looking

Firm

B2C

Yes

0.001389

Hur,Y

oungjin

,YongJaeKo,andJoseph

Valacich(2011),BA

StructuralModelof

theRelationships

BetweenSportWebsite

Quality,e-Satisfaction,ande-Loyalty.^

Journalo

fSport

Managem

ent,25

(May),458–473.

Published

Attitudinal

Backw

ard-looking

Firm

B2C

Yes

0.000705

Jayawardhena,Chanaka,A

nneL.S

ouchon,A

ndrewM.F

arrell,

andKateGlanville(2007),BOutcomes

ofServiceEncounter

Qualityin

aBusiness-to-BusinessContext,^

Industrial

Mar-

ketin

gManagem

ent,36

(July),575–588.

Published

Inclusive

Backw

ard-looking

Firm

B2B

Yes

0.004051

Jillapalli,R

aviK

.,andJames

B.W

ilcox

(2010),BProfessor

Brand

Advocacy:

DoBrand

Relationships

Matter?^Journal

ofMarketin

gEducatio

n,32


Published

Attitudinal

Forward-looking

Individual

B2C

Yes

0.000000

Johnson,Jean

L.(1999),BStrategicIntegrationin

Industrial

DistributionChannels:ManagingtheInterfirm

Relationship

asStrategicAsset,^

Journalo

fthe

Academyof

Marketin

gScience,27

(January),4–18.

Published

Attitudinal

Forward-looking

Firm

B2B

Yes

0.005403

Johnson,Julie

T.,H

iram

C.B

arksdaleJr,and

James

S.B

oles

(2001),"The

StrategicRoleof

theSalespersonin

Reducing

Customer

Defectio

nin

BusinessRelationships,"Journalo

fPersonalSellin

gandSalesManagem

ent,21

(February),123–

134.

Published

Aggregate

Forward-looking

Individual

B2B

Yes

0.000000

Jones,MichaelA.,andKristyE.R

eynolds(2006),BThe

Roleof

RetailerInterestonShoppingBehavior,^

JournalofR

etailin

g,82

(June),115–126.

Published

Attitudinal,

Behavioral

Forw

ard-looking

Firm

B2C

Yes

0.002899

Jones,MichaelA.,David

Mothersbaugh,andSharonE.B

eatty

(2000),BSw

itching

BarriersandRepurchaseIntentions

inServices,^

Journalo

fRetailin

g,76

(June),259–274.

Published

Behavioral

Forward-looking

Firm

B2C

Yes

0.002899


Tab

le7

(contin

ued)

Reference

Unpublished

Loyalty

perspective

Temporal

orientation

Target

Market

Com

mon

method

bias

susceptib

ility?

Journalq

uality

(Eigenfactor)

Jones,Tim

,Shirley

F.Taylor,H

arvirS.

Bansal(2008),

BCom

mitm

enttoaFriend,aServiceProvider,oraService

Com

pany—arethey

Distin

ctions

WorthMaking?^Journalof

theAcademyofMarketin

gScience,36

(Decem

ber),473–487.

Published

Attitudinal,

Behavioral

Forw

ard-looking

Firm

B2B

Yes

0.005403

Keiningham,T

imothy

L.,Bruce

Cooil,

TorWallin

Andreassen,

andLerzanAksoy

(2007),BALongitudinalE

xaminationof

NetPromoter

andFirm

Revenue

Growth,^

Journalo

fMarketin

g,71

(July),39–51.

Published

Behavioral

Forward-looking

Firm

B2C

No

0.012337

Kim

,Keysuk(2000),BOnInterfirmPow

erChannelClim

ateand

Solid

arity

inIndustrialDistributor-SupplierDyads,^

Journal

oftheAcademyof

Marketin

gScience,28

(June),388–405.

Published

Attitudinal,

Behavioral

Forw

ard-looking

Firm

B2B

No

0.005403

Kim

,SungS.

andJai-YeolS

on(2009),BOut

ofSedicationor

Constraint?ADualM

odelof

Post-AdoptionPhenomenaand

itsEmpiricalT

estintheContext

ofInlin

eServices,^

MIS

Quarterly,33(January),49–70.

Published

Attitudinal,

Behavioral

Forw

ard-looking

Firm

B2C

Yes

0.009769

Kuenzel,S

ven,andEwaKrolik

owska(2008),BThe

Effecto

fBonds

onLoyalty

TowardAudito

rs:T

heMediatin

gRoleof

Com

mitm

ent,^

Services

Industries

Journal,28

(June),685–

700.

Published

Attitudinal,

Behavioral

Forw

ard-looking

Firm

B2B

Yes

0.002556

Kum

ar,N

irmalya,L

isaK.S

cheer,andJan-BenedictE

.M.

Steenkam

p(1995),BThe

Effectsof

SupplierFairnesson

VulnerableResellers,^

Journalo

fMarketin

gResearch,32

(February),54–65.

Published

Attitudinal,

Behavioral

Forw

ard-looking

Firm

B2B

Yes

0.014522

Kwak,D

aeHee,S

tephen

McD

aniel,andKiT

akKim

(2011),

BRevisiting

theSatisfactionLoyaltyRelationshipintheSport

Video

Gam

ingContext:T

heMediatingRoleof

Consumer

Expertise,^JournalofS

ports

Managem

ent,26

(January),81–91.

Published

Behavioral

Forward-looking

Firm

B2C

Yes

0.000705

Lacey,R

ussellWayne

(2003),BCustomer

Loyalty

Programs:

StrategicValue

toRelationshipMarketin

g,^Departm

ento

fMarketin

g,University

ofAlabama.

Unpublished

Behavioral

Forward-looking

Firm

B2C

Yes

0.004057

Lam

bert-Pandraud,Raphaëlle,G

illes

Laurent,and

Eric

Lapersonne(2005),BRepeatP

urchasingof

New

Autom

obiles

byOlder

Consumers:EmpiricalE

videnceand

Interpretatio

ns,^

Journalo

fMarketin

g,69

(April),97–113.

Published

Behavioral

Backw

ard-looking

Brand

B2C

Yes

0.012337

Lanza,K

erry

M.(2008),BT

heAntecedentsof

Autom

otive

Brand

Loyalty

andRepurchaseIntentions,^

University

ofPh

oenix.

Unpublished

Inclusive

Forw

ard-looking

Brand

B2C

Yes

0.004057

LeC

lerc,F

rance,andJohn

D.C.L

ittle(1997),BCan

Advertising

CopyMakeFS

ICoupons

MoreEffectiv

e?^Journalo

fMarketin

gResearch,34

(Novem

ber),473–484.

Published

Attitudinal,

Behavioral

Forw

ard-looking

Brand

B2C

Yes

0.014522

Lee,JiY

eon(2009),BInvestigatingtheEffecto

fFestival

Visito

rs’EmotionalE

xperiences

onSatisfaction,

PsychologicalC

ommitm

ent,andLoyalty,^

Departm

ento

fMarketin

g,TexasA&M

University.

Unpublished

Inclusive

Forw

ard-looking

Firm

B2C

Yes

0.004057


Tab

le7

(contin

ued)

Reference

Unpublished

Loyalty

perspective

Temporal

orientation

Target

Market

Com

mon

method

bias

susceptib

ility?

Journalq

uality

(Eigenfactor)

Lee,K

yootai,and

Kailash

Joshi,andYoung

KyunKim

(2011),

BIdentificationof

theFour-FactorStructureof

Customers’

PerceivedFairness,^

Journalo

fTargetin

g,Measurementa

ndAnalysisforMarketin

g,19

(May),113–126.

Published

Aggregate

Backw

ard-looking

Firm

B2C

Yes

0.000000

Leenheer,Jorna,HaraldJ.vanHeerde,TammoH.A.B

ikmolt,

andAleSm

idts(2007),BDoLoyalty

Program

sReally

Enhance

BehavioralL

oyalty?AnEmpiricalA

nalysis

AccountingforSelf-Selectin

gMem

bers,^

International

Journalo

fResearchin

Marketin

g,24

(March),31–47.

Published

Behavioral

Backw

ard-looking

Firm

B2C

Yes

0.002847

Lei,Jing,Kode

Ruyter,andMartin

Wetzels(2008),BConsumer

Responses

toVerticalService

LineExtensions,^Journalo

fRetailin

g,84


Published

Inclusive

Forw

ard-looking

Brand

B2C

Yes

0.002899

Liang,C

hiung-Ju,and

Wen-H

ungWang(2006),BEvaluatingthe

Interrelationof

aRetailer’sRelationshipEffortsandCon-

sumers’AttitudesandBehavior,^

Journalo

fTargetin

g,Measurementa

ndAnalysisforMarketin

g,14

(2006),156–

172.

Published

Attitudinal,

Behavioral

Backw

ard-looking

Firm

B2C

Yes

0.000000

Lin,H

sin-Hui,and

Yi-Sh

unWang(2006),BAnExaminationof

theDeterminantsof

Customer

Loyalty

inMobile

Com

merce

Contexts,^Inform

ationandManagem

ent,43

(April),271–

282.

Published

Aggregate

Backw

ard-looking

Firm

B2C

Yes

0.005060

Liu,A

nnieH.,andMarkP.Leach

(2001),BDevelopingLoyal

Customerswith

aValue-A

ddingSalesForce:E

xamining

Customer

SatisfactionandthePerceived

Credibilityof

Con-

sultativ

eSalespeople.,^

JournalofP

ersonalSellin

gandSales

Managem

ent,21


Published

Aggregate

Backw

ard-looking

Individual

B2B

Yes

0.000000

Liu,Y

uping,andRongYang(2009),BCom

petin

gLoyalty

Programs:Im

pactof

MarketS

aturation,MarketS

hare,and

CategoryExpandability,^JournalofM

arketin

g,73

(January),

93–108.

Published

Behavioral

Backw

ard-looking

Firm

B2C

Yes

0.012337

Liu-Thompkins,Yuping,andLeona

Tam

(2013),BNot

All

RepeatC

ustomersAre

theSam

e:Designing

Effectiv

eCross-

Selling

Promotionon

theBasisof

AttitudinalL

oyalty

and

Habit,^Journalo

fMarketing,77


Published

Attitudinal,

Behavioral

Backw

ard-looking

Firm

B2C

No

0.012337

Lueg,JasonE.,NicolePo

nder,SharonE.B

eatty,and

MichaelL.

Capella(2006),BTeenagers’Use

ofAlternativeSh

opping

Channels:AConsumerSocializationPerspective,^Journalof

Retailin

g,82

(June),137–153.

Published

Behavioral

Forward-looking

Individual

B2C

Yes

0.002899

Macintosh,G

errard,and

Law

renceS.

Lockshin(1997),BRetail

Relationships

andStoreLoyalty:A

MultiLevelPerspectiv

e,^


ofResearchin

Marketin

g,14

(Decem

ber),487–497.

Published

Attitudinal

Backw

ard-looking

Individual

B2C

Yes

0.002847


Tab

le7

(contin

ued)

Reference

Unpublished

Loyalty

perspective

Temporal

orientation

Target

Market

Com

mon

method

bias

susceptib

ility?

Journalq

uality

(Eigenfactor)

Maignan,Isabelle

andO.C.F

errell(2001),BAntecedentsand

Benefits

ofCorporateCitizenship:AnInvestigationof

French

Businesses,^JournalofB

usinessResearch,51

(January),37–

51.

Published

Aggregate

Backw

ard-looking

Firm

B2B

Yes

0.009203

Maxham

III,James

G.,andRichard

G.N

etem

eyer

(2002),

BModelingCustomer

Perceptions

ofCom

plaint

Handling

OverTim

e:The

Effectsof

Perceived

Justiceon

Satisfaction

andIntent,^

Journalo

fRetailin

g,78

(April),239–252.

Published

Behavioral

Forward-looking

Firm

B2C

Yes

0.002899

Mende,M

artin

,RuthN.B

olton,andMaryJo

Bitn

er(2009),

BRelationships

take

two:

Customer

AttachmentS

tyles’

Influenceon

Consumers’DesireforClose

Relationships

and

LoyaltytotheFirm

,^MSI

working

paper,Marketin

gScience

Institu

te.

Unpublished

Behavioral

Forward-looking

Firm

B2C

Yes

0.004057

Mende,M

artin

,RuthN.B

olton,andMaryJo

Bitn

er(2013),

BDecodingCustomer–F

irm

Relationships:H

owAttachment

Styles

HelpExplain

Customers'Preferences

forCloseness,

RepurchaseIntentions,and

Changes

inRelationship

Breadth,^

Journalo

fMarketin

gResearch,50

(February),

125–142.

Published

Behavioral

Forward-looking

Firm

B2C

Yes

0.014522

Mittal,V

ikas,and

WagnerA.K

amakura(2001),BSatisfaction,

RepurchaseIntent,and

RepurchaseBehavior:Investigating

theModeratingEffecto

fCustomer

Characteristics,^Journal

ofMarketin

gResearch,38


Published

Behavioral

Backw

ard-looking

Brand

B2C

No

0.014522

Monika,Koller,ArneFloh,and

Alexander

Zauner(2011),

BFurther

Insightsinto

Perceived

Value

andConsumer

Loyalty:A

BGreen^Perspectiv

e,^Psychologyand

Marketin

g,28

(Decem

ber),1154–1176.

Published

Inclusive

Forw

ard-looking

Brand

B2C

Yes

0.002793

Moore,M

elissa

Lunt(2000),BTow

ardUnderstanding

the

Consumer

Psychology

ofRelationshipMarketin

g,^

Departm

ento

fMarketin

g,University

ofConnecticut.

Unpublished

Attitudinal,

Behavioral

Backw

ard-looking

Firm

B2C

Yes

0.004057

Morgan,NeilA

.,andLopoL.R

ego(2006),BThe

Value

ofDifferent

Customer


Metrics

inPredictin

gBusinessPerformance,^

Marketin

gScience,25

(September/October),426–439.

Published

Behavioral

Forward-looking

Firm

B2B

No

0.011581

Morgan,NeilA

.,andLopoL.R

ego(2009),BBrand

Portfolio

Strategy

andFirm

Perform

ance,^

Journalo

fMarketin

g,73

(January),59–74.

Published

Behavioral

Backw

ard-looking

Firm

B2B

No

0.012337

Morgan,Rober

M.,andSh

elby

D.H

unt(1994),BT

heCom

mitm

ent-TrustTheoryof


g,^

Journalo

fMarketin

g,58

(July),20–39.

Published

Behavioral

Forward-looking

Firm

B2B

Yes

0.012337

Neerakkal,JojiA

lex(2011),BConsumerEvaluations

ofProduct

LineBrand

Extension,^

The

IUPJournalo

fBrand

Managem

ent,8(M

arch),22–35.

Published

Attitudinal

Backw

ard-looking

Brand

B2C

Yes

0.000000


Tab

le7

(contin

ued)

Reference

Unpublished

Loyalty

perspective

Temporal

orientation

Target

Market

Com

mon

method

bias

susceptib

ility?

Journalq

uality

(Eigenfactor)

Nijssen,Edw

in,JagdipSingh,D

eepakSirdeshm

ukh,and

Hartm

utHolzm

ueller(2003),BInvestig

atingIndustry

Context

EffectsinConsumer-Firm

Relationships:P

relim

inaryResults

From

aDispositio

nalA

pproach,^Journalo

fthe

Academyof

Marketin

gScience,31

(January),46–60.

Published

Aggregate

Backw

ard-looking

Firm

B2C

Yes

0.005403

Nitzan,Iritand

Barak

Libai(2010),BSo

cialEffectson

Customer

Retentio

n,^MSI

working

paper,Marketin

gScience

Institu

te.

Unpublished

Behavioral

Backw

ard-looking

Firm

B2C

Yes

0.004057

Nunes,JosephC..,andXavierDrèze

(2006),BThe

Endow

edProgress

Effect:How

ArtificialA

dvancementIncreases

Effort,^

Journalo

fConsumer

Research,32

(March),504–

512.

Published

Behavioral

Backw

ard-looking

Firm

B2C

Yes

0.012091

Palm

atier,RobertW

.,LisaK.S

cheer,andJan-BenedictE

.M.

Steenkam

p(2007),BCustomer

Loyalty

toWhom?Managing

theBenefits

andRisks

ofSalesperson-O

wnedLoyalty,^

Journalo

fMarketin

gResearch,44

(May),185–199.

Published

Inclusive

Forw

ard-looking

Individual

B2B

No

0.014522

Palm

atier,RobertW

.,CherylB

urke

Jarvis,JenniferR

.Bechkoff,

andFrank

R.K

ardes(2009),BThe

Roleof

Customer

Gratitudein


g,^Journalo

fMarketin

g,73

(September),1–18.

Published

Behavioral

Forward-looking

Firm

B2B

No

0.012337

Palm

atier,RobertW

.,LisaK.S

cheer,Kenneth

R.E

vans,and

Todd

J.Arnold(2008),BAchieving


gEffectiv

enessin

Business-to-BusinessExchanges,^

Journal

oftheAcademyof

Marketin

gScience,36

(June),174–190.

Published

Attitudinal,

Behavioral

Backw

ard-looking

Individual

B2B

Yes

0.005403

Palm

atier,RobertW

.,LisaK.S

cheer,MarkB.H

ouston,

Kenneth

R.E

vans,and

SrinathGopalakrishna,BUse

ofRelationshipMarketin

gProgramsin

BuildingCustomer–

SalespersonandCustomer–F

irm

Relationships:D

ifferential

Influences

onFinancialO

utcomes,^InternationalJournal

ofResearchin

Marketin

g,24


Published

Behavioral

Backw

ard-looking

Firm

B2B

No

0.002847

Park,C

.Whan,Deborah

J.MacInnis,Joseph

Priester,Andreas

B.E

isingerich,and

Daw

nIacobucci(2010),BB

rand

Attachmentand

Brand

Attitude

Strength:C

onceptualand

EmpiricalD

ifferentiatio

nof

TwoCriticalBrand

Equity

Drivers,^

Journalo

fMarketin

g,74

(Novem

ber),1

–17.

Published

Attitudinal,

Behavioral

Backw

ard-looking

Brand

B2C

Yes

0.012337

Park,C

.Whan,Su

ngYoulJun,and

Deborah

J.MacInnis(2000),

BChoosingWhatI

WantV

ersusRejectin

gWhatI

DoNot

Want:AnApplicationof

DecisionFramingtoProductO

ption

ChoiceDecisions,^

Journalo

fMarketin

gResearch,37

(May),187–202.

Published

Behavioral

Forward-looking

Firm

B2C

Yes

0.014522

Patterson,PaulG

.,andTasm

anSm

ith(2003),BACross-Cultural

Studyof

Switching

BarriersandPropensity

toStay

with

Ser-

vice

Providers,^Journalo

fRetailin

g,79

(June),107–120.

Published

Behavioral

Forward-looking

Firm

B2C

Yes

0.002899


Tab

le7

(contin

ued)

Reference

Unpublished

Loyalty

perspective

Temporal

orientation

Target

Market

Com

mon

method

bias

susceptib

ility?

Journalq

uality

(Eigenfactor)

Perrini,Francesco,SandroCastaldo,NicolaMisani,andAntonio

Tencati(2009),BT

heIm

pactof

SocialR

esponsibility

Associatio

nson

Trustin

OrganicProductsMarketedby

Mainstream

Retailers:A

Study

ofItalianConsumers,^

BusinessStrategy

andtheEnvironment,19

(Decem

ber),512–

526.

Published

Aggregate

Backw

ard-looking

Brand

B2C

Yes

0.000000

Ping

Jr.,RobertA

.(1993),BT

heEffectsof

Satisfactionand

StructuralConstraintson

RetailerExitin

g,Voice,L

oyalty,

Opportunism

,and

Neglect,^

Journalo

fRetailin

g,69


Published

Behavioral

Backw

ard-looking

Firm

B2B

Yes

0.002899

Porter,C

onstance

Elise,andNaveenDonthu(2008),

BCultiv

atingTrustandHarvestingValue

inVirtual

Com

munities,^Managem

entScience,54(January),113–128.

Published

Contaminated

Forw

ard-looking

Brand

B2C

Yes

0.032442

Ranaw

eera,C

hatura

andJaideepPrabhu(2003),BOnthe

RelativeIm

portance

ofCustomer

SatisfactionandTrustas

Determinantsof

Customer

Retentio

nandPositive

Wordof

Mouth,^JournalofTargetin

g,Measurementand

Analysisfor

Marketin

g,12

(2003),82–90.

Published

Behavioral

Forward-looking

Firm

B2C

Yes

0.000000

Reynolds,KristyE.,andSharonE.B

eatty

(1999),BCustomer

Benefits

andCom

pany

Consequencesof

Customer-

SalespersonRelationships

inRetailin

g,^JournalofR

etailin

g,75

(March),11–32.

Published

Behavioral

Forward-looking

Individual

B2C

Yes

0.002899

Roehm

,Michelle,L

.,EllenBolman

Pullin

s,andHarperA.

Roehm

Jr.(2002),BD

esigning

Loyalty-BuildingProgramsfor

Packaged

Goods

Brands,^JournalofM

arketin

gResearch,39

(May),202–213.

Published

Attitudinal

Backw

ard-looking

Brand

B2C

Yes

0.014522

Russell-Bennett,

Rebekah,JanetR.M

cColl-Kennedy,L

eonard

V.C

oote(2007),BInvolvem

entS

atisfactionandBrand

Loyalty

inaSm

allB

usinessServicesSettin

g,^Journalo


(Decem

ber),1253–1260.

Published

Attitudinal,

Behavioral

Backw

ard-looking

Firm

B2C

Yes

0.009203

Sánchez,José

ÁngelLópez,MaríaLeticiaSantos

Vijande,

and

Juan

Antonio

TrespalaciosGutiérrez

(2011),BThe

Effectsof

Manufacturer's

OrganizationalL

earningon

Distributor


inIndustrialMarkets,^

Industrial

Marketin

gManagem

ent,40

(May),624–635.

Published

Inclusive

Forw

ard-looking

Firm

B2B

Yes

0.004051

Sanchez-Franco,M

anuel,andFranciscoJ.Rondan-Cataluna

(2010),BConnectionBetweenCustomer

Emotions

andRela-

tionshipQualityin

OnlineMusicServices,^Behaviorala

ndInform

ationTechnology,29(June),633–651.

Published

Attitudinal

Backw

ard-looking

Firm

B2C

Yes

0.001428

Scheer,L

isaK.,C.F

redMiao,andJasonGarrett(2010),"The

Effectsof

SupplierCapabilitieson

IndustrialCustomers’

Loyalty:T

heRoleof

Dependence,^Journalo

fthe

Academy

ofMarketin

gScience,38

(2010),90–104.

Published

Aggregate

Backw

ard-looking

Firm

B2B

Yes

0.005403


Tab

le7

(contin

ued)

Reference

Unpublished

Loyalty

perspective

Temporal

orientation

Target

Market

Com

mon

method

bias

susceptib

ility?

Journalq

uality

(Eigenfactor)

Seiders,Kathleen,Glenn

B.V

oss,AndreaL.G

odfrey,D

hruv

Grewal(2007),BSE

RVCON:D

evelopmentand

Validationof

aMultid

imensionalServiceConvenience

Scale,^Journalo

ftheAcademyof

Marketin

gScience,35

(March),144–156.

Published

Inclusive

Forw

ard-looking

Firm

B2C

No

0.005403

Seiders,K

athleen,Glenn

B.V

oss,Dhruv

Grewal,and

AndreaL.

Godfrey

(2005),BDoSatisfied

CustomersBuy

More?

ExaminingModeratingInfluences

inaRetailin

gContext,^

Journalo

fMarketin

g,69

(October),26–43.

Published

Behavioral

Forw

ard-looking

Firm

B2C

Yes

0.012337

Shankar,Venkatesh,A

myK.S

mith

,and

ArvindRangasw

amy

(2003),BCustomer


inOnlineand

Offlin

eEnvironments,^


ofResearchin

Marketin

g,20

(June),153–175.

Published

Attitudinal,

Behavioral

Backw

ard-looking

Firm

B2C

Yes

0.002847

Simpson,Jam

esT.

(1997),BRelationshipManagem

ent:ACall

forFewer

InfluenceAttempts?^Journalo

fBusiness

Research,39

(July),209–218.

Published

Attitudinal

Backw

ard-looking

Firm

B2B

Yes

0.009203

Sirdeshm

ukh,Deepak,Jagdip

Singh,andBarry

Sabol(2002),

BConsumer

Trust,V

alue,and

Loyalty

inRelational

Exchanges,^

Journalo

fMarketin

g,66

(January),15–37.

Published

Aggregate

Backw

ard-looking

Firm

B2C

Yes

0.012337

Sirdeshm

ukh,Deepak,Jagdip

Singh,andBarry

Savol(2001),

BConsumer

Trust,V

alue,and

Loyalty

inRelational

Exchanges,^

MSI

working

paper,Marketin

gScience

Institu

te.

Unpublished

Inclusive

Forw

ard-looking

Firm

B2C

Yes

0.004057

Smith

,RodneyE.,andWilliamF.Wright(2004),BD

eterminants

ofCustomerLoyalty

andFinancialP

erform

ance,^Journalof

Managem

entA

ccountingResearch,16

(Decem

ber),183–205.

Published

Behavioral

Forw

ard-looking

Firm

B2C

Yes

0.000000

Snoj,B

oris,B

orutMilfelner,andVladimirGabrijan(2007),BAn

Examinationof

theRelationships

amongMarketO

rientatio

nInnovatio

nResources

ReputationalR

esources

andCom

pany

Performance

intheTransitionalEconomyof

Slovenia,^

CanadianJournalo

fAdm

inistrativeSciences,24


Published

Aggregate

Backw

ard-looking

Firm

B2B

Yes

0.000457

Soman,D

ilip(1998),BThe

Illusion

ofDelayed

Incentives:

EvaluationFu

ture

Effort-Money

Transactio

ns,^

Journalo

fMarketin

gResearch,35

(Novem

ber),427–437.

Published

Attitudinal

Backw

ard-looking

Individual

B2C

No

0.014522

Steinhoff,Lena,andRobertP

almatier(2013),BUnderstanding

theEffectiv

enessof

Loyalty

Programs,^MSI

working

paper,

Marketin

gScience

Institu

te.

Unpublished

Behavioral

Forw

ard-looking

Firm

B2C

Yes

0.004057

Stokburger-Sauer,N

icola,S.R

atneshwar,and

SankarSen

(2012),BDriversof

Consumer–B

rand

Identification,^


ofResearchin

Marketin

g,29

(Decem

ber),406–418.

Published

Behavioral

Forw

ard-looking

Brand

B2C

Yes

0.002847

Suh,Jung-Chae,andYiY

oujae(2006),"WhenBrand

Attitudes

Affectthe

Customer

Satisfaction-Loyalty

Relation:

The

ModeratingRoleof

ProductInvolvement,^

Journalo

fCon-

sumer

Psychology,16

(March),145–155.

Published

Inclusive

Forw

ard-looking

Brand

B2C

Yes

0.003690


Tab

le7

(contin

ued)

Reference

Unpublished

Loyalty

perspective

Temporal

orientation

Target

Market

Com

mon

method

bias

susceptib

ility?

Journalq

uality

(Eigenfactor)

Sum,K

a-man

(2007),BMarketO

rientatio

nandtheUse

ofIn-

ternetas

aRelationshipMarketin

gTo

olin

Service

Industries,^

Departm

ento

fManagem

entand

Marketin

g,HongKongPo

lytechnicUniversity.

Unpublished

Behavioral

Forward-looking

Firm

B2C

Yes

0.004057

Tariq,Abdul

Naveed,andNadiaMoussaoui(2009),BThe

Main

Antecedento

fCustomer

Loyalty

inMoroccanBanking

Sector,^


ofBusinessandManagem

ent

Science,2(2009),101–115.

Published

Aggregate

Forward-looking

Firm

B2C

Yes

0.000000

Taylor,S

tevenA.,andThomas

L.B

aker

(1994),"An

Assessm

entoftheRelationshipBetweenServiceQualityand

Customer

Satisfactionin

theFormationof

Consumers’

Purchase

Intentions,^

Journalo

fRetailin

g,70

(June),163–

178

Published

Aggregate

Forward-looking

Firm

B2C

Yes

0.002899

Tellis,GerardJ.(1988),BAdvertisingExposureLoyalty

and

Brand

Purchase:A

Two-StageModelof

Choice,^Journalo

fMarketin

gResearch,25

(May),134–144.

Published

Behavioral

Backw

ard-looking

Firm

B2C

Yes

0.014522

Thiripurasundar,U

.and

P.Natarajan

(2011),BAnEmpirical

Studyon

Determinantand

Measurm

ento

fBrand

Equity

inIndian

Car

Industry,^

AsiaPacificJournalo

fResearchin

BusinessManagem

ent,2(June),158–169.

Published

Aggregate

Backw

ard-looking

Brand

B2C

Yes

0.000000

Thomson,Matthew

(2006),BHum

anBrands:Investigating

Antecedentsto

Consumers’Strong

Attachmentsto

Celebrities,^Journalo

fMarketin

g,70

(July),104–119.

Published

Attitudinal

Backw

ard-looking

Brand

B2C

Yes

0.012337

Tsiros,M

ichael,and

VkasMittal(2000),BRegret:AModelof

it’sAntecedentsandConsequencesin

Consumer

Decision

Making,^Journalo

fConsumer

Research,26

(March),401–

407.

Published

Behavioral

Backw

ard-looking

Brand

B2C

Yes

0.012091

vanDoor,Jenny,andPeterC.V

erhoef

(2007),BManaging

Customer

Relationships

inBusinessMarkets:T

heRoleof

CriticalIncidents,^MSI

working

paper,Marketin

gScience

Institu

te.

Unpublished

Behavioral

Backw

ard-looking

Firm

B2B

Yes

0.004057

vanDoorn,Jenny,PeterS.H.L

eeflang,andMarleen

Tijs

(2013),

BSatisfactionas

aPredictor

ofFu

ture

Performance:A

replication,^InternationalJournalofResearchIn

Marketin

g,30

(Decem

ber),314–318.

Published

Behavioral

Forward-looking

Firm

B2C

No

0.002847

Vogel,V

erena,HeinerE

vanschitzky,and

B.R

amaseshan(2008),

BCustomer

Equity

DriversandFu

ture

Sales,^Journalo

fMarketin

g,72

(Novem

ber),98–108.

Published

Inclusive

Forw

ard-looking

Firm

B2C

No

0.012337

Voss,Glenn

B.,AndreaGodfrey,and

KathleenSeiders(2010),

BHow

Com

plem

entarity

andSu

bstitutionAltertheCustomer

Satisfaction–RepurchaseLink,^Journalo

fMarketin

g,74

(Novem

ber),111–127.

Published

Behavioral

Backw

ard-looking

Firm

B2C

Yes

0.012337


Tab

le7

(contin

ued)

Reference

Unpublished

Loyalty

perspective

Temporal

orientation

Target

Market

Com

mon

method

bias

susceptib

ility?

Journalq

uality

(Eigenfactor)

Wagner,Tillmann,ThorstenHennig-Thurau,andThomas

Rudolph

(2009),BDoesCustomer

Dem

otionJeopardize

Loyalty?^

Journalo

fMarketin

g,73

(May),69–85.

Published

Behavioral

Forward-looking

Individual

B2C

Yes

0.012337

Walsh,G

ianfrancoandBorisBartik

owski(2013),BE

xploring

CorporateAbilityandSocialR

esponsibility

Associatio

nsas

Antecedentsof

Customer

SatisfactionCross-Culturally,^

Journalo


(August),989–995.

Published

Aggregate

Forward-looking

Firm

B2C

Yes

0.009203

Walsh,G

ianfranco,andSh

aron

E.B

eatty

(2007),BCustomer-

basedCorporateReputationof

aServiceFirm

:Scale

Developmentand

Validation,^Journalo

ftheAcademyof

Marketin

gScience,35(M

arch),127–143.

Published

Aggregate

Backw

ard-looking

Firm

B2C

Yes

0.005403

Walsh,G

ianfranco,Edw

ardShiu,LouiseM.H

assan,Nina

Michaelidou,and

Sharon

E.B

eatty

(2011),BEmotions,S

tore-

EnvironmentalC

ues,Store-ChoiceCriteria,andMarketin

gOutcomes,^

Journalo


(July),737–

744.

Published

Aggregate

Forward-looking

Firm

B2C

Yes

0.009203

Walsh,G

ianfranco,ThorstenHennig-Thurau,KaiSassenberg,

andDanielB

ornemann(2010),BDoesRelationshipQuality

Matterin

e-Services?ACom

parisonof

OnlineandOfflin

eRetailin

g,^Journalo

fRetailin

gandConsumer

Services,17


Published

Aggregate

Forward-looking

Firm

B2C

Yes

0.000000

Woisetschläger,David

M.,Patrick

Lentz,and

Heiner

Evanschitzky

(2011),BHow

Habits,S

ocialT

ies,and

EconomicSw

itching

BarriersAffectC

ustomer

Loyalty

inContractualService

Settings,^Journalo

fBusinessResearch,

64(A

ugust),800–808.

Published

Behavioral

Forward-looking

Firm

B2C

Yes

0.009203

Wu,Wei-ping,T.S.

Chan,andHengHwaLau

(2008),BDoes

Consumers’PersonalR

eciprocity

AffectF

uturePu

rchase

Intentions?^

Journalo

fMarketin

gManagem

ent,24


Published

Attitudinal,

Behavioral

Forw

ard-looking

Brand

B2C

Yes

0.000000

Xu,Yingzi(2004),BA

ssessing

theService-ProfitChain:A

nEmpiricalStudy

inaChinese

Securities

Firm

,^Departm

entof

Managem

ent,MaastrichtS

choolo

fManagem

ent.

Unpublished

Behavioral

Forward-looking

Firm

B2C

Yes

0.004057

Yang,Zhilin

,and

Robin

T.Peterson(2004),BCustomer

PerceivedValue

SatisfactionandLoyalty:T

heRoleof

Switching

Costs,^

PsychologyandMarketin

g,21

(October),

799–822.

Published

Behavioral

Forward-looking

Firm

B2C

Yes

0.002793

Yen,T

sai-fa,H

sious-hsiang

J.Lui,and

Chao-lin

Tuan(2009),

BManagingRelationshipEfforttoInfluenceLoyalty:A

nEmpiricalS

tudy

ontheSun

LinkSea

Forestand

Recreational

Park

Taiwan,^


ofOrganizational

Innovatio

n,2(2009),179–194.

Published

Behavioral

Backw

ard-looking

Firm

B2C

Yes

0.000000


Tab

le7

(contin

ued)

Reference

Unpublished

Loyalty

perspective

Temporal

orientation

Target

Market

Com

mon

method

bias

susceptib

ility?

Journalq

uality

(Eigenfactor)

Yim

,Chi

Kin

(Bennett),D

avid

K.T

se,and

Kim

myWaChan

(2008),BStrengtheningCustomer

Loyalty

Through

Intim

acy

andPassion:R

oles

ofCustomer–F

irm

Affectio

nand

Customer–S

taffRelationships

inServices,^

Journalo

fMarketin

gResearch,45

(Decem

ber),741–756.

Published

Attitudinal,

Behavioral

Forw

ard-looking

Firm

B2C

Yes

0.014522

Yim

,Frederick

Hong-kit,Rolph

E.A

nderson,andSrinivasan

Swam

inathan(2004),BCustomer

RelationshipManagem

ent:

ItsDim

ensionsandEffecto

nCustomer

Outcomes,^

Journal

ofPersonalS

ellin

gandSalesManagem

ent,24

(April),263–

278.

Published

Behavioral

Backw

ard-looking

Firm

B2B

Yes

0.000000


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