® Academy of Management Journal2002, Vol. 45, No. 3, 587-597.

MANAGING CUSTOMER SERVICES:HUMAN RESOURCE PRACTICES, QUIT RATES,

AND SALES GROWTH

ROSEMARY BATTCornell University

This study examined the relationship between human resource practices, employeequit rates, and organizational performance in the service sector. Drawing on a unique,nationally representative sample of call centers, multivariate analyses showed thatquit rates were lower and sales growth was higher in estahlishments that emphasizedhigh skills, employee participation in decision making and in teams, and humanresource incentives such as high relative pay and employment security. Quit ratespartially mediated the relationship hetween human resource practices and salesgrowth. These relationships were also moderated hy the customer segment served.

Research in strategic human resource manage-ment has made considerable progress in document-ing a link between organizational performance andhuman resource (HR) strategies that invest in thehuman capital of the workforce (Becker & Gerhart,1996; Huselid, 1995; Ichniowski, Kochan, Levine,Olson, & Strauss, 1996). These strategies, often re-ferred to as high-involvement or high-performancesystems, generally include coherent sets of HRpractices that enhance employee skills, participa-tion in decisions, and motivation (Appelbaum,Bailey, Berg, & Kalleberg, 2000; Delery, 1998).

Recent reviews, however, have identified severaltheoretical and methodological weaknesses in thisliterature (Becker & Gerhart, 1996; Delery, 1998;Wright & Sherman, 1999). First, prior research istheoretically undeveloped and has not specifiedthe mediating employee behaviors that explain therelationship between HR practices and perfor-'mance. Second, although the strategic human re-source theory prediction is that external factorssuch as business strategy should moderate the hu-man resources-performance link, only a few stud-ies support this view (Arthur, 1992; Wright, Smart,& McMahan, 1995; Youndt, Snell, Dean, & Lepak,1996). In addition, despite the fact that three-quar-ters of employment is in services, empirical evi-dence of a HR-performance link is based largely onblue-collar workers in manufacturing plants (Ap-pelbaum et al., 2000; Ichniowski et al., 1996). For avariety of reasons, manufacturing studies may notgeneralize to service settings; differences in demog-raphy, occupational groups, technologies, workprocesses, the level of technically required interde-pendence among workers, and the role of the cus-tomer in the production process may all be relevant(Bowen & Schneider, 1988; Mills, Ghase, & Mar-guiles, 1983; Zimmerman & Enell, 1988). Thus, ex-

tension of previous findings to the service sector isneeded.

This study contributes to the strategic humanresource literature in three ways. First, I elaborate atheory of how high-involvement human resourcepractices allow firms to build the kind of firm-specific human capital that leads to better perfor-mance, and I test whether the effects of HR prac-tices on performance are mediated by employeequit rates. Second, drawing on a nationally repre-sentative sample of establishments in the U.S. tele-communications services industry, I extend thestudy of high-involvement practices to a new con-text that has grown dramatically in employmentand strategic importance—technology-mediatedcustomer service and sales operations, or call cen-ters. Third, I consider whether the HR-performancelink is moderated by customer segment, an impor-tant component of business strategy in sales andmarketing.

PRIOR RESEARCH

High-involvement systems have been defined invarious ways, but they generally include three di-mensions: relatively high skill requirements; workdesigned so that employees have discretion andopportunity to use their skills in collaboration withother workers; and an incentive structure that en-hances motivation and commitment (Appelbaum etal., 2000; Delery & Doty, 1996; Huselid, 1995; Mac-Duffie, 1995). Glassic mass production approaches,by contrast, emphasize low skill requirements, nar-row jobs with low discretion, and few incentivesfor discretionary effort.

Empirical studies have shown that high-involve-ment systems are associated with better performancein manufacturing plants (Appelbaimi et al., 2000;

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588 Academy of Management Journal June

Arthur, 1992, 1994; Ichniowski et al., 1996; Mac-Duffie, 1995; Youndt et al., 1996). Few quantitativestudies of high-involvement practices in servicesettings exist, but one study of bank loan officersdid find that three HR practices (results-orientedappraisals, employment security, and profit shar-ing) were associated with higher financial perfor-mance (Delery & Doty, 1996).

In this research, I extend past work by develop-ing the argument that high-involvement HR prac-tices allow a firm to build firm-specific humancapital, which in turn influences organizationalperformance in two ways: directly, via its effect onemployee performance, and indirectly, via em-ployee attachment to the firm. Below, I elaboratehow this theory applies to customer-contact serviceemployees in call centers.

HR Practices, Firm-Specific Capital,and Performance

The argument for a direct link between humanresource practices and employee performance incustomer service settings hinges on the idea thathigh-involvement practices help employees de-velop the kind of firm-specific human capital—knowledge of a firm's products, customers, andwork processes—that enables them to interact ef-fectively with customers. Firm-specific human cap-ital is important because these customer-contactemployees manage the boundary between the firmand its customers (Mills et al., 1983), and the be-havior of these employees shapes customers' buy-ing behavior. To persuade customers to buy a firm'sproducts and services, employees need a clear un-derstanding of specific product features, serviceagreements, pricing, packaging, promotions for par-ticular customer segments, and legal regulations.They need customer-specific knowledge regardingthe demand characteristics of particular individu-als or segments and need to know how to use thatknowledge to negotiate customized offerings. Em-ployees also require specific knowledge of thestructure and content of the firm's information sys-tems, the work flow from point of sales to delivery,and how the company's processing capabilities af-fect each customer and product offering.

The three dimensions of high-involvement HRsystems help employees acquire this firm-specifichuman capital. First, high-involvement systemsemphasize the selective hiring of employees withhigh general skills (or formal education) plus a firminvestment in initial training. This combinationprovides a firm with a skilled workforce capable ofongoing learning. The capacity to learn is criticalbecause in current markets, intense competition

and proliferation of new products lead to constantchange in marketing, pricing, and packaging. Em-ployees need to integrate new product and salesinformation into their existing knowledge and toexplain these changes to customers.

The second dimension of high-involvement sys-tems involves the design of work to provide oppor-tunities for individual discretion and ongoinglearning through collaboration with other employ-ees. Gustomer-contact employees with high indi-vidual discretion are able to respond immediatelyto customer demands and to take advantage of salesopportunities when interacting with customers.High-involvement systems also provide opportuni-ties for continuous learning through participationin "off-line" problem-solving groups (in which em-ployees and supervisors meet periodically) and"on-line" groups (such as self-directed teams inwhich groups rather than individuals form the ba-sic unit of production and are responsible for manydecisions). Reviews of the teams literature showsignificant, positive relationships between semiau-tonomous work groups and performance outcomes(Gohen & Bailey, 1997). For customer-contact em-ployees, participation in both types of teams islikely to pay off because it creates opportunities forongoing learning—not because participationchanges the content of their work (for instance,sales agents still interact individually with custom-ers). Batt (1999), for example, found that sales rep-resentatives in self-directed teams had the same jobduties as those in traditionally supervised groups,but the former had higher sales productivity be-cause they benefited from better learning and prob-lem solving on how to handle customers and newtechnology.

The third dimension of high-involvement sys-tems includes HR incentives such as ongoing in-vestment in training, employment security, highrelative pay, and performance management sys-tems that build trust. Firm-provided training re-wards employees with additional skills and op-portunities for higher-paying jobs. Employmentsecurity allows workers to suggest labor-saving im-provements without fear of job loss. Efficiencywage theory posits that employees with high rela-tive pay and low performance monitoring will bemore productive in order to avoid the prospect of aworse job on the external market (Krueger & Sum-mers, 1987). The use of electronic monitoring forperformance management is a common practice incall centers, and extensive research shows that itcreates employee disaffection and stress (Garayon,1993), which can have negative spillover effects oninteractions with customers.

2002 Batt 589

Quit Rates as Mediating Mechanisms

High-involvement practices also may influenceorganizational performance indirectly, throughlower employee quit rates. Some empirical studies,for example, have shown a significant, inverse re-lationship between high-involvement practices andquit rates (Arthur, 1994; Shaw, Delery, Jenkins, &Gupta, 1998) and quit rates and productivity(Huselid, 1995). For example, firms that are lessselective or hire lower-skilled employees are likelyto experience higher quit rates. The design of workis likely to influence quit rates through its impacton intrinsic motivation, as demonstrated in thelarge body of research on job characteristics (Hack-man & Oldham, 1980). Greater autonomy is associ-ated with higher satisfaction and lower intentionsto quit at the individual level of analysis (Gotton &Tuttle, 1986; Hom & Griffeth, 1986). Employees inproblem-solving and self-directed teams experi-ence greater autonomy and satisfaction (Gohen &Bailey, 1997), which in turn should reduce quitrates (Gotton, 1993).

Finally, human resource incentives such as train-ing, employment security, high relative pay, andpractices that build trust are likely to induce em-ployee attachment and commitment. Some em-pirical research has shown significant, negativerelationships between individual turnover and em-ployment security measured at an individual level(Gotton & Tuttle, 1986; Shaw et al., 1998) and be-tween turnover and higher compensation levels(Leonard, 1987; Powell, Montgomery, & Gosgrove,1994; Shaw et al., 1998). Pervasive use of electronicmonitoring creates dissatisfaction and stress amongemployees, providing incentives for workers toquit, as demonstrated in prior research (Garayon,1993; Shaw et al., 1998; Wilson & Peel, 1991).

In customer-contact settings, high quit rates notonly increase the costs of recruitment and selec-tion, but negatively affect sales growth because newemployees face a learning curve. Long-term em-ployees have the tacit firm-specific skills andknowledge—and often the personal relationshipswith customers—needed to more effectively inter-act with customers. Some case studies have shownthat employee turnover (or, conversely, loyalty) iscorrelated with customer turnover (or loyalty) (Hes-kett, Sasser, & Schlesinger, 1997). Loyal customersare critical to sales growth because they tend to buya wider range of products and more value-addedproducts (Reichheld, 1996). Long-term employeeshave the accumulated tacit knowledge of products,customers, and work processes needed to providehigh-quality service to these loyal customers. Thus,

high quit rates are likely to negatively affect salesgrowth.

In sum, high-involvement practices are likely tocontribute to higher sales directly by creating aworkforce capable of customizing service and salesto its particular customer segment. They also arelikely to induce employee attachment, and long-term employees with firm-specific skills are likelyto be more productive. These arguments are consis-tent with a resource-based theory of the firm (Bar-ney, 1995): by building a workforce with deep tacitknowledge of products, customers, and processes,high-involvement practices create resources thatare valuable, rare, and hard to imitate, thereby con-ferring competitive advantage. The arguments arealso consistent with theories of social capital(Leana & Van Buren, 1999): it is not only that eachindividual has firm-specific knowledge, but alsothat the social capital, or stable relationships andcollaboration among employees, allow them to con-tinually deepen their knowledge and service andsales capabilities.

An alternative approach to services would followthe engineering logic of mass production manufac-turing. In such an alternative to the high-involve-ment model, individual efficiency is high becauseworkers learn standardized tasks through repeti-tion (Levitt, 1972). Labor costs are minimizedthrough low investment in selection, training, par-ticipation, and compensation. Information tech-nology is used primarily to automate tasks andelectronically monitor performance. However, cus-tomer satisfaction and loyalty are likely to sufferbecause employees have little discretion to meetcustomer needs and because the greater division oflabor increases the number of employees customersmust deal with (Heskett et al., 1997). In sum, exist-ing literature suggests three hypotheses:

Hypothesis 1. High involvement human re-source practices will be negatively related toemployee quit rates.

Hypothesis 2. High involvement human re-source practices will be positively related tosales growth.

Hypothesis 3. Employee quit rates will par-tially mediate the relationship between high-involvement human resource practices andsales growth.

Exploring the Moderating Effect ofMarket Segment

If the customer-employee relationship is the crit-ical factor in customer-contact service work, then a

590 Academy of Management Journal June

central question is whether high-involvement prac-tices confer greater competitive advantage whenemployees serve some customer segments ratherthan others. To confer competitive advantage, re-sources must be valuable, rare, and hard to imitate(Barney, 1995).

One way to consider the question of customersegments as moderating factors is to view high-involvement practices as a strategy for quasi-professionalizing nonmanagers—enhancing skills,opportunity for independent judgment, and moti-vation. In manufacturing, for example, high-involvement practices enhance the capability ofhigh school educated blue-collar workers, notengineers or technical staff. In customer-contactsettings, however, "production-level" jobs rangefrom those held by high school educated workersselling to mass-market consumers, to those ofcollege-educated professionals serving as ac-count executives. In markets serving customersfor high-value-added products, such as largebusinesses, customers may demand professionalattention. Hence, use of high-involvement prac-tices is likely to be viewed as the price of marketentry: a firm needs them if it is to compete (theyare valuable), but their use is not sufficient toconfer any special competitive advantage (theyare not rare or inimitable).

For lower-value-added residential and smallbusiness consumers in the mass market, however,the workforce is comparable to blue-collar workersin manufacturing. Firms typically adopt a produc-tion line approach to services, emphasizing high-volume, low-cost transactions. High-involvementpractices may be perceived as costly and as notsufficiently valuable to confer competitive advan-tage. Nevertheless, the literature on mass customi-zation (e.g.. Pine, 1993) suggests that such practicesindeed are sufficiently valuable in mass marketsbecause consumers are increasingly demandingcustomization and "service bundling." In telecom-munications services mass markets, for example,customers demand bundled billing and provisionof services for local and long-distance calling, wire-less services, high-speed data lines, Internet access,and enhanced features such as call waiting, callforwarding, voice messaging, and the like. If em-ployees have the skills and discretion to createcustomized packages of multiple services, ratherthan being limited by standardized menus, theywill sell more and sell more value-added services.This line of argument suggests that the characteris-tics of mass customized markets make high-involvement HR practices valuable; but cost pres-sures and the conventional focus on a transactionalapproach make high-involvement practices rare

and difficult to imitate. This line of argument sug-gests the following hypothesis:

Hypothesis 4. The positive effect of high-involvement human resource practices onsales growth will be stronger for establishmentsserving low-value-added (residential and smallbusiness) customers than for those servinghigh-value-added (large business) customers.

METHODS

Sample

The sample for this study is a nationally repre-sentative stratified random sample drav«i from theDun & Bradstreet listings of establishments. An es-tablishment is defined as one work location, suchas a manufacturing plant, or in this study, a callcenter. A call center provides telephone-mediatedservice and/or sales to customers. This study in-cluded only centers customers call into, not out-bound telemarketing centers. Establishments werestratified by size (10-99 or 100-plus employees),industry segment (cellular, wire-line, cable, or In-ternet services), and location (U. S. state). I over-sampled establishments with over 100 employeesso that the results would represent a larger percent-age of the industry's workforce. The sample break-down is as follows: 53 percent were in wire-linecommunication; 24 percent were in wireless; 16percent were in cable TV; and 7 percent were inInternet services.

As Becker and Gerhart (1996: 792) suggested, Ianalyzed comparable establishments (call centers)in one industry and, because HR practices varyconsiderably by occupational group, I focused onthe "core" workforce, defined as the largest groupof nonmanagerial employees (e.g., Arthur, 1992;Delery & Doty, 1996; Osterman, 1994). In thisstudy, the core workers were customer service andsales representatives.

Because the data were from a large nationallyrepresentative sample of service centers, it was notfeasible to survey multiple respondents in eachestablishment. Gerhart, Wright, McMahan, andSnell (2000) noted that establishment-level surveysare more reliable than corporate-level surveys be-cause the numbers are smaller, the managers arevery familiar with the HR practices they are respon-sible for implementing, and the HR practices aremore homogenous. The average size of the coreworkforce in our study was 93.

To improve reliability, I surveyed only generalmanagers, who have been found to be less optimis-tic about HR practices than HR managers (Wright etal., 1998). To develop and pretest the survey used

2002 Batt 591

in the study, I did extensive site visits to 15 serviceand sales centers in four distinct markets (local,long distance, cellular, and cable) and three cus-tomer segments (residential, small business, andlarge business) in six telecommunications compa-nies in five geographic regions. Each visit includedinterviews with the site's general manager, middlemanagers, supervisors, and service workers.

I also used outside information as a randomcheck to verify survey responses. First, I comparedsurvey items (the date an establishment wasfounded, its primary market, and its size) to datacontained in the Dun & Bradstreet listing. Them'eans for each variable in the two data sets werenot statistically significantly different. Second, Iexamined union contracts and found that the wagerates and job titles reported by managers at specificcompanies were comparable to those in the corre-sponding union contracts.

A survey team administered the survey by tele-phone. The survey averaged 52 minutes andyielded a 54 percent response rate. To check forresponse bias, I estimated a logit model with thedependent variable set equal to 1 if the establish-ment participated in the survey. Internet serviceproviders were somewhat less likely to respond,and single establishments were somewhat morelikely to respond, and these differences were con-trolled for in the data analysis.

Measures

As discussed above, I conceptualized high-involvement practices along three dimensionsbased on prior research: skill level, work design,and involvement-enhancing HR incentives. In myfield research, I did not find discrete systems intelecommunications service and sales centers thatresembled the kind of "best practice" model of leanproduction found in the auto industry (e.g., Mac-Duffie, 1995). Following Appelbaum et al. (2000),MacDuffie (1995), and Youndt et al. (1996), amongothers, I used theoretically driven additive indexes.The use of additive indexes rests on the assumptionthat high-involvement practices are additive in re-lation to performance and that different practicescan be substituted for one another to obtain similareffects (Delery, 1998). An additive index provides aconservative estimate that may understate the syn-ergies or multiplicative effects of combining prac-tices. It implies that firms can achieve incrementalresults by investing in some high-involvementpractices but that they will achieve more positiveresults using a full range of high-involvement prac-tices (e.g., Appelbaum et al., 2000; Ichniowski etal., 1996).

To capture the basic skill requirements of thecustomer service or sales job at each call center, Icreated a skill index based on the mean of twovariables: (1) the number of years of formal educa-tion of the typical (median) core employee and (2)the number of years of formal and on-the-job train-ing needed for a new employee to become profi-cient. The variables were transformed to z-scores.

For the work design index, I used two measuresfor individual discretion and two for employee col-laboration in teams. The individual discretionscales used a 1-5 Likert response format, where 1 is"little or no control" and 5 is "complete control."Discretion over work methods included eight ques-tions adapted from MacDuffie (1995); these as-sessed degree of influence over tasks, tools, workmethods, pace of work, schedules, vacations, andtechnology design (a = .79). I developed four ad-ditional questions for this study to capture discre-tion over customer interactions. Two of the fourwere highly correlated and were used in this anal-ysis: control over handling nonroutine requests andcontrol over the pace of serving customers (a =.60). Team participation included the percentage ofemployees that participated in regular off-lineproblem-solving groups and the percentage thatparticipated in self-directed teams. To create theindex, I transformed the variables to z-scores andcalculated the mean value of the four variables.

The human resource incentives measured wereof four types: ongoing training, employment secu-rity, pay level, and electronic performance moni-toring. Ongoing training indicated a firm's commit-ment to developing employees and was measuredby the number of weeks of training a typical coreemployee received each year. Pay was the naturallogarithm of the median annual base pay of the coreworkforce. Employment security was the percent-age of the core workforce that was permanent andfull-time, as opposed to part-time or contingent.Employers use part-time and contingent workers tocut costs (Houseman, 2001) and, under these cir-cumstances, full-time workers worry that their jobswill be turned into part-time or contingent ones,with lower pay and benefits. The availability oftemporary workers as substitutes for core employeealso puts downward pressure on the wages of in-cumbent employees (Katz & Krueger, 1999), provid-ing incentives for them to quit. Electronic monitor-ing was measured as the percentage of the workperformance of the typical employee that was elec-tronically monitored (reverse-coded). I transformedall variables to z-scores and took their mean valuefor the HR incentive index.

In addition, I created a mean index of the ten HRpractices in order to test the models of mediation

592 Academy of Management Journal June

and moderation. The high-involvement work sys-tems (HIWS) index was transformed into a z-scoreand then interacted with the z-score for each cus-tomer segment variable. The use of standardizedz-scores in interaction terms allows for them to bedirectly interpreted in relation to the mean of theinteracted variable; it also reduces multicollinear-ity (Gohen & Gohen, 1983: 325).

Establishments were dummy-coded as serving allcustomers in their market (these are called univer-sal centers) or as serving a particular segment (largebusiness, small business, or residential). If theyserved two segments, I asked their respondents toanswer all questions as they pertained to thesegment with the largest volume of customers. Inall analyses, universal center was the omittedcategory.

The mass market is comprised of two customersegments: residential consumers and small busi-nesses. Residential consumers demand standard-ization with some potential for customization viaservices such as call forwarding, voice messaging,or Internet provision. Small businesses demandsomewhat more complex products than residentialcustomers and are a slightly higher value-addedtier in the mass-market center. Also, because thissegment includes a large proportion of "mom andpop" businesses and home offices, it resembles theresidential market more than the large businessmarket. Large business customers are high-value-added customers that usually require the bundlingof complex products such as private branch ex-change systems (PBX) and local area networks(LANs) to handle voice, data, and video transac-tions. This study does not capture larger national orglobal accounts because they are often based insmall offices inside larger establishments, and sothey are not identifiable through Dun & Bradstreet.I also separated out operator service centers (forinstance, directory assistance) because they pro-vide a mass-market service likely to generate littleor no revenue (thus, they were included in theanalysis of quit rates but not in the analysis of salesgrowth). In this sample, 22 percent of call centersserved all customers; 19 percent targeted large busi-nesses; 24 percent targeted small businesses; 30percent targeted residences; and 5 percent were inoperator services.

Dependent variables. Dependent variables werethe average annual quit rate and the percent changein sales in the prior two-year period. The measureof quits excluded discharges, retirements, transfers,and promotions. The measiu-e of sales growth wasthe natural logarithm of the percent change in thevalue of sales to the particular customer baseserved by the center.

Control variables. I included several controlsthat have been found to influence HR practices. Forexample, investment in human capital is likely tobe greater among firms that have more resources orare seeking legitimacy (e.g., Osterman, 1994). Gon-trols for organizational characteristics includedwhether an organization was a branch of a parentcompany, whether it was owned by a former Bellsystem affiliate, and the percentage of the work-force constituted by women. A series of dummyvariables controlled for industry segment: cellular,Internet service, cable TV, or wire-line (the omittedcategory). Union presence was a dummy variablebecause the core workforce was narrowly definedso that all core workers in an establishment wereeither all union or all nonunion.

RESULTS

Table 1 provides the means, standard deviations,and "pairwise" correlations of the variables. Foranalyses of quit rates (Hypothesis 1), I estimated aTobit model because the dependent variable (quitrates) is "left-censored" at zero, and ordinary leastsquares (OLS) regression with censored data pro-duces biased estimates. The Tobit model uses all ofthe information, including information about thecensoring, and provides consistent estimates of theparameters (Long, 1997: 187-189). For the salesequations, I used OLS regression because there wasno censoring of the data.

High-Involvement HR Practices and Quit Rates

For analyses of quit rates (Hypothesis 1), I esti-mated three equations. Table 2 reports these re-sults. The first equation, model 1, includes the basecase of industry segment and organizational controlvariables alone. The second equation estimates thethree HR practices dimensions (skill, work design,and incentives) together; and the third, the fulladditive HR practices index. The results providepartial support for Hypothesis 1. In model 2, thework design index is significant; the incentive in-dex is marginally significant (p < .10); and the skillindex is insignificant.

To estimate the effect sizes of coefficients in To-bit models, the coefficients must be decomposedinto changes in the probability of observing an out-come above the left (censored) limit and changes inoutcomes above the left limit, the latter of whichprovides an interpretation equivalent to OLS esti-mates (McDonald & Moffit, 1980). In this case, theeffect sizes of the Tobit coefficients are equal to0.51 of the OLS coefficients. A one-standard-devi-ation change in the work design index is associated

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594 Academy of Management Journal June

TABLE 2Aggregate Quit Rates as a Function of

HR Practices"

Variable

Industry segmentWireless marketCable TV marketInternet market

Organizational featuresBell companyPart of larger organizationFemale (percent)Union presence

Customer segmentLarge businessSmall businessResidential servicesOperator services

HR practicesSkill indexWork design indexHR incentives indexHigh-involvement work

index

ConstantSampleLikelihood ratio x'Probability > x^Pseudo R^

Model 1

7.86**-0.28

4.53

1.235.26^1.21

-9.87**

3.834.74^6.60*

14.90**

0.2432637.890.000.10

Model 2

5.52*-3 .06

7.62^^

1.845.20^

-0.52-11.85***

5.85"^2.244.397.97

-1 .70-4 .45***-1.98^

3.74326

67.120.000.17

Model 3

5.43*-3.16

7.33^

1.955.80*

-1.01-11.19***

6.52*2.364.347.84

-6.34***

3.40326

65.720.000.17

Unstandardized Tobit estimates are reported."̂ p < .10* p < .05

** p < .01*** p < .001

with a quit rate that is 2.27 (0.51 X 4.45) percentagepoints lower, and a one-standard-deviation changein the high-involvement work systems index is as-sociated with a quit rate 3.22 percentage pointslower (p < .001).

The relationship between the customer segmenttargeted, HR practices, and quit rates is noteworthy.Residential and operator services centers have sig-nificantly higher quit rates than universal centers (aTobit-adjusted estimate of 3.36 percentage pointshigher in residential and 7.6 percentage pointshigher in operator services). Also, the coefficientson residential and operator services becomesmaller and insignificant when the HR indexes areadded, suggesting that it is the variation in HRpractices across segments, not the segment itself,that influences quit rates. However, for the largebusinesses, the coefficient on the segment becomesmore significant in the presence of the HR index.That is, once HR practices are controlled for, thequit rate in establishments serving large business

customers is 3.3 percentage points (Tobit-adjusted)higher than that in universal centers.

High-Involvement Practices and Sales Growth

Table 3 reports the results for the analysis ofHypothesis 2. The three indexes together in model2 explain an additional 2.9 percent of the varianceover the base case. The HR incentive index has themost highly significant, positive relationship withsales growth (0.18, p < .01), and the work designindex is also significant (0.11, p < .05). The skillindex is insignificant. Finally, with industry seg-ments and organizational factors controlled for, aone-standard-deviation change in the high-involve-ment index is associated with a 16.3 percentagepoint increase in sales (Table 3, model 3).

Other Analyses

Test of mediation. Following the procedure out-lined in Baron and Kenny (1986:1176), I found thatthe results provide support for a partially mediatedmodel (Hypothesis 3). The high-involvement workindex is a significant predictor of quit rates (Table2, model 3) and sales growth (Table 3, model 3),and quit rates are a significant predictor of salesgrowth (Table 3, model 4). In the presence of quitrates, however, the size and significance of thehigh- involvement work index is significantly re-duced (from j3 = 0.17 to j3 = 0.13, p < .01), thoughits effects remain significant (Table 3, model 5).Thus, quit rates partially mediate the relationshipbetween high-involvement HR practices and salesgrowth. Further analyses (not shown) revealed thatthe partial mediation was particularly accountedfor by the work design index rather than the skillindex or the HR incentive index.

Test of moderation. To test whether customersegment moderates these relationships (Hypothesis4), I examined a series of interaction terms. Theresults (Table 3, model 6) show that the segmenttargeted moderates the relationship between high-involvement practices and sales growth. The use ofhigh-involvement practices is associated with sig-nificantly higher sales growth in residential centers(0.29, p < .001) and small businesses (0.15, p < 05),but not in large business centers (compared to uni-versal centers).

DISCUSSION AND CONCLUSIONS

The findings in this study can be summarized asfollows: First, greater use of high-involvementpractices is associated with lower quit rates andhigher sales growth in customer service and sales

2002 Batt 595

TABLE 3Sales Growth as a Function of HR Practices and Quit Rates"

Variable

Industry segmentWireless marketCable TV marketInternet market

Organizational featuresBell companyPart of larger organizationPercentage of womenUnion presence

Customer segmentLarge businessSmall businessResidential

HR practicesSkill indexWork design indexHR incentives indexHigh-involvement work indexAnnual quit rate

InteractionsLarge business X high-involvement work

indexSmall business X high-involvement work

indexResidential x high-involvement work

index

Sample sizeF

Adjusted R^A adjusted R^

Model 1

0.00-0.24***

0.37***

-0.16*0.13*

-0.02-0.07

0.110.13^0.13^

2608.40***0.250.22

Model 2

0.03-0.21**

0.36***

-0.15*0.13*

-0.01-0.05

0.090.17*0.15*

-0.080.12*0.18**

2607.70***0.290.250.033.133*

Model 3

0.03-0.20**

0.35***

-0.16**0.12*0.00

-0.06

0.090.16*0.15*

0.17**

2608.48***0.270.240.025.29**

Model 4

0.03-0.25***

0.39***

-0.15*0.15*

-0.01-0.09

0.13^0.15*0.15*

-0.17**

2608.67***0.280.250.026.44***

Model 5

0.05-0.21**

0.37***

-0.16*0.14*0.01

-0.08

0.110.17*0.16*

0.13*-0.14*

2608.37***0.290.260.013.99*

Model 6

0.00-0.20**

0.35***

-0.17**0.13*0.01

-0.08

0.120.13^0.16*

0.19**

0.04

0.13*

0.26***

2608.31***0.320.280.044.19*

' Standardized coefficients are reported.•̂ p < .10* p < .05

**p < .01'**p < .001

centers. Second, quit rates partially mediate therelationship between high-involvement practicesand sales growth. The findings are consistent withthe idea that high-involvement practices have adirect effect on employee performance as well as anindirect effect on performance via lower quit rates.

Third, the relationship between high-involve-ment practices and sales growth is moderated bythe identity of an establishment's primary customerbase. High-involvement practices are associatedwith higher sales growth in small business andresidential centers. In large business centers, high-involvement practices appear to be the price ofentry and to affect sales growth primarily indi-rectly, through quit rates. These results are consis-tent with a resource-based view of the firm: high-

involvement practices are rare in more cost-conscious markets, but they confer value becauseemployees are better able to meet the demand forcustomization and service bundling.

It could be that the moderated relationship be-tween HR practices and sales growth is a functionof variation in sales opportunities for distinct cus-tomer segments. However, managers reportedmuch greater opportunities for growth in sales rev-enues in large business markets than in residentialor small business markets because of the former'sdemand for high-value-added information systemsfor handling internal communications, data trans-fer, and video. The data in the current survey areconsistent with that view: the large business cen-ters had the highest average sales growth (38 per-

596 Academy of Management Journal June

cent); small business centers were next, with 37percent, followed by residential, with 28 percent.

This explanation, however, may account for theoutcomes found for universal centers. They investconsiderably in high-involvement practices (at alevel second to the large business centers) and ben-efit through low quit rates (11 percent), but theyhave the lowest average sales growth (22 percent).A review of the establishments. that follow thisapproach showed that they were disproportion-ately more likely to be small, to define their mar-kets as local, and to be located in small towns andrural areas. These factors suggest that their invest-ment in high-involvement practices does not payoff because the restricted scope of their marketslimits sales opportunities.

There are several limitations to this study. As inall cross-sectional studies, the issue of causality isproblematic. To explore alternative explanations, Iexamined other variables that might account for theresults, including the local 1998 unemploymentrate for each establishment indicated in the U.S.Bureau of Labor Statistics Local Area Unemploy-ment Series (ftp.bls.gov/pub/time.series/la.) andthe local cost of living, given in the 1999 Geo-graphic Reference Report from the Economic Re-search Institute. I considered factors such as size,age, ownership changes, size of customer base,market share, market scope, and age of parent com-pany. These measures, however, are highly corre-lated with those already in the study and did notproduce any significant differences in the results.

This study contributes to the literature on strate-gic human resource management by examining therole of high-involvement work systems in creatingfirm-specific human capital. It identifies one typeof employee behavior—quitting—that mediates therelationship between HR practices and perfor-mance. The work design dimension accounts formost of the mediation results, suggesting that itmay be useful for future researchers to examinehow different dimensions of the HR system affectdifferent types of employee behaviors.

The study also focuses on an increasingly strate-gic but neglected context —technology-mediatedcustomer contact centers. These call centers havebecome a primary point of contact for customerservice and sales delivery in many industries. Thecurrent study is based on a nationally representa-tive sample of establishments in the telecommuni-cations industry, so that the findings are generaliz-able to call centers in that industry. However, giventhat call center management has become an indus-try in itself, serving many other service and manu-facturing organizations, the findings of this study

have implications for those contexts as well. Be-cause mass customization arguably characterizesmarkets in banking, insurance, airlines, computersoftware, and goods-producing industries, invest-ing in the human resource capabilities of customer-contact employees in call centers serving these in-dustries is also likely to have an economic payoff.Future empirical work is needed to assess thisquestion in a wide array of industry contexts.

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Rosemary Batt is an associate professor of human re-source studies at the Industrial and Labor RelationsScbool, Gornell University. Sbe received ber B.A. fromGornell University and ber Ph.D. from the Sloan Schoolof Management, Massachusetts Institute of Technology.Her research interests include strategic human resourcemanagement, service sector productivity and competi-tiveness, work organization and teams, and labor marketanalysis. Sbe bas written extensively on service manage-ment strategies and tbe restructuring of tbe telecommu-nications services industry.