2-effects of hrm on economic perofrmance

8/3/2019 2-Effects of HRM on Economic Perofrmance

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The Effects of Human Resource Management Systems on Economic Performance: An

International Comparison of U.S. and Japanese PlantsAuthor(s): Casey Ichniowski and Kathryn ShawSource: Management Science, Vol. 45, No. 5 (May, 1999), pp. 704-721Published by: INFORMSStable URL: http://www.jstor.org/stable/2634726

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T h e E f f e c t s o f Human ResourceManagementSystems o n Economic

Performance: n InternationalComparisono f U . S . a n d Japanese P l a n t s

Casey Ichniowski * KathrynShawColumbiaUniversity,BusinessSchool,713 Uris Hall, 3022 Broadway, ew York,New York10027CarnegieMellonUniversity,Graduate choolof IndustrialAdministration, oom250, Pittsburgh, ennsylvania 5213

This study uses personally collected data from41 steel production ines to assess the effectsof Japaneseand U.S. human resourcemanagement (HRM)practiceson workerproduc-tivity. TheJapaneseproductionlines employ a common system of HRMpractices ncluding:problem-solving teams,extensiveorientation, raining throughout employees' careers,exten-sive information sharing, rotation across jobs, employment security, and profit sharing. Amajorityof U.S. plants now have one or two featuresof this systemof HRMpractices,but onlya minorityhave a comprehensive system of innovative work practicesthat parallelsthe fullsystem of practices found among the Japanesemanufacturers.We find that theJapaneseines aresignificantlymoreproductive han theU.S.lines.However,U.S.manufacturershat have adopteda full system of innovativeHRMpracticespattemedafterthe Japanese ystemachieve levels of productivityand quality equalto the performance f theJapanese manufacturers.This study's evidence helps reconcile conflicting views about theeffectiveness f adoptingJapanese-style orker nvolvement chemes n theUnitedStates.UnitedStatesmanufacturershat have adopteda definitionof employee participationhat extendsonlyto problem-solvingeamsor information haringdo not see large mprovementsn productivity.However,U.S. manufacturershatadopt a broaderdefinitionof participationhat mimicsthe fullJapaneseHRMsystemsee substantialperformance ains.(HumanResourceManagement; roductivity;apan)

1. IntroductionRecent researchfinds that systems of innovative hu-man resourcemanagement (HRM)practicesthatpro-mote employee participation improve a firm's eco-nomic performance.' A natural way to provide afurther test of the performance effects of systems ofHRMpracticesis to make internationalcomparisonsof the performanceof similarJapaneseand U.S. man-1For a review of recent evidence, see Ichniowski et al. (1996).

ufacturers. Large Japanese manufacturing firms arenow well known for a distinctive system of workpractices that promote worker participation. Workpractices that long characterized the labor-manage-ment relations of many U.S. manufacturers offer asharp contrast to the more participatory Japanesesystem, although many U.S. manufacturershave nowadopted theirown approachesto employee participa-tion by introducinga number of work practice inno-vations (Osterman1994).

0025-1909/99/4505/0704$05.00Copyright ? 1999, Institute for Operations Research704 MANAGEMENT SCIENCE/VOl. 45, No. 5, May 1999 and the Management ciences


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To make direct cross-national, establishment-levelcomparisons of HRMpractices and performanceout-comes, we extend our previous research on the per-formanceeffects of HRMpractices n a sample of steelfinishing lines (Ichniowskiet al. 1997) by personallyassembling data for a sample of comparableJapanesesteel lines. To our knowledge, this is the firststudy toprovide a direct comparisonof the work practicesandperformanceoutcomes for a sample of U.S. and Japa-nese manufacturing establishments that employ acommon production technology. These unique U.S.and Japanese establishment data enable us to makethree important comparisons.1. We compare the performance of the Japanesesteel finishing lines with their distinctive set of HRMpractices to the performance of all comparableU.S.lines to determine whether the Japanese ines have aproductivity advantage on average.2. We comparetheperformanceof Japanese ines tothat of the U.S. lines that have adopted systems ofHRM practicesthat match closely the system used bythe Japanese ines to test whether a similarsystem ofHRMpractices produces similarperformance n U.S.and Japaneseplants.3. We compare the performance of lines in theUnited States that have more traditionalHRM prac-tices to the-performanceof Japanese lines and U.S.lines with the most innovativeHRMsystems to deter-mine whether the latterapproachesraiseperformancelevels comparedto the more traditionalapproachinthe United States.2. A.Systems Perspective on HRMPracticesRecent theoreticalresearcharguesthat it is importantto analyze a firm's work policies "notin isolation,butas part of a coherent incentive system" (Holmstromand Milgrom 1994,p. 990).Thissystems perspectiveisbased on the notion that employment practicesoftencomplementeach other, so that the adoption of oneemployment practice is only effective when it isadopted in combinationwith one or more supportingwork practices.This systems perspective is especially importantwhen analyzing the work environment of Japanese

manufacturersnvestigatedin this study. Itoh (1994,p.258) concludes that "many distinct features of Japa-nese human resource management .. are likely toconstitute a 'system': hey areclosely interrelated,andone aspect could not exist without all the others."Milgrom and Roberts (1990) argue that the HRMpractices typically found in large Japanese manufac-turers provide a particularlyclear illustration of asystem of complementaryelements.2For example, problem-solving teams are central tothe kaisen,or continuous improvement, process andare a prominent feature of the work organization oflarge Japanese manufacturers. Yet by themselves,these teams are not likely to elicit worker participa-tion in continuous improvement activities. Problem-solving teams may require employment securitypolicies to be effective because an employmentsecurity policy helps allay workers' fears that theirproductivity-improving deas could lead to a loss ofjobs. Employmentsecuritywill in turnbe complemen-tary with other HRMpractices, ncluding flexiblejobassignments,to allow businesses to reassignworkersto more productive jobs in response to changes inproduct demand. Flexible assignment of workers tomultiple jobs requirestrainingto provide workers theskills needed in multiple jobs.Carefulemployee selec-tion and greater employee voice also become morevaluable due to the longer expected careers for em-ployees and the lower probabilitiesof exit.According to this view, employee participation ni-tiatives such as problem-solvingteamsrequirea set ofcomplementary practices in order to improve eco-nomic performance. Existing empirical research onproductivity effects of HRM practices supports thisview. Several recent studies find that systems ofcomplementarypracticesthatpromote employee par-2 Baker et al. (1994) and Kandel and Lazear (1992) also identifycomplementarities among specific HRM practices. Note that Aoki(1994) argues that the system of practices governing the employ-ment relations of Japanese firms is itself complementary with otherattributes of the Japanese firm including information processingsystems, companies' relations with suppliers and banks, and fea-tures of the broader institutional environment. Because our sampleis restricted to production lines in a very narrow product line witha single technology, it is beyond the scope of this study to investi-gate these broader complementarities.

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ticipation improve productivity while work practiceinnovations, such as work teams or quality circles,adopted in isolation do not (Ichniowski et al. 1996,Ichniowskiet al. 1997).3. HRM Practices in Japanese andU.S. Production SitesTheoreticaland empirical research therefore suggeststhat studies must measure a firm'sentireset of workpractices o specify heHRMenvironment orrectly.Thissectiondescribes he systemsof HRMpracticesn the41U.S. and Japanesesteel finishing lines that providedperformancedata for this study. We collecteddata onthe actualHRMpracticesat each line from extensiveon-site interviews with labor relations managers,miiioperationsmanagers,supervisors, ocal union officers,and productionworkers.We measure the HRMprac-tices in the steel making facilitiesfor the 1986-1992periodto match the timeperiodcoveredby the perfor-mancedataavailable orthis study.3.1. The Japanese System of HRM PracticesAccording to our interviews,HRM practicesfor blue-collarworkers arevery comparableacrossallJapaneseintegrated steel mills during the time period consid-ered in this study. The HRM practicesdescribed inthis sectionapplyto allJapanese teel finishing ines inour sampleand correspondclosely to the prototypicaldescriptionof work practices employed by large Jap-anese manufacturers.Theorganizationof work in Japanesesteel finishinglines is characterizedby significantworker participa-tion in problem-solving eamsand rotationof workersacross jobs. Problem-solvingteams-known as jishukanri(JK)teams in the Japanesesteel industry-arecentralto the work activitiesof Japanese teel employ-ees.3JKteams in the finishing lines are comprisedof3While the term jishu kanri is widely applied throughout theJapanese steel industry, some mill sites in Japan may use differentnames for these activities depending on the evolution of theseproblem-solving teams at the site. Some mills had introducedpredecessors of these team-based work activities, such as zerodefect programs and quality circles by the early 1960s. In 1969, afterzero defect and quality circle programs were widespread in theJapanese steel industry, the Japanese Iron and Steel Federation

six to eight workers (including a team leader) and arethe direct vehicle through which kaisen,or continuousimprovement, activities take place. Team membersidentify a problem area from several broad categories,such as cost reduction, productivity and efficiencyimprovements, quality, workplace safety, and envi-ronmental improvement, and typically complete sev-eralJKprojects n a year. Accordingto data from oneJapaneseproduction site, 55%of the hours devoted toJKactivitieswere outside the workers' scheduled shifthours, for which workers are compensated,and theremainderwere during regularlyscheduled shift time.JK themes are evaluated through several commenda-tion procedures.A second important eature of work organization sthe regularpracticeof planned job rotation.A produc-tion employee in one of this study's Japanese steelfinishing lines begins work on the simpler jobs at theentry end of this production process and then rotatesthrough all the other jobs on the line in a plannedprogression.Productionworkersareexpected to mas-ter all jobs on the line within the first ten years ofemployment.Japanese steel mills identify new candidates fortheirproductionand maintenance obs through closerelations they maintain with high schools and indus-trial schools in their regions. Screeningof the candi-dates involves tests in English, Japanese,and mathe-matics, and industrialschool graduates are tested intheir particularareas of specialization, for examplemechanical or electricalengineering. In addition toemployee screening, employee orientation is espe-cially extensive. During his first twelve months, anemployee receives extensive trainingunder the closesupervisionof seniorcoaches,who stress the natureofcompany policies and strive to instill norms of behav-ior on the job.Training n Japanese steel mills encompassestrain-ing in production skills, communicationand problemsolving skills, and a set of other activitiesdesigned toimprove workers' understanding of production is-sues. This training is provided through a lifetime

adopted the term jishu kanri for these activities, leading to wide-spread adoption of this name.

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education system that is designed to match the needsof employees progressing through a typical employ-ee s career path. New employees receive extensiveoff-site trainingin productionskills during their firsttwelve months with the company. Then, as employeesrotate through differentproduction jobs, they receiveadditionalskills trainingspecific to thenew jobs. Aftera period of seven or eight years, a cohort of employeeswho have learned many production jobs reconvenefor additional off-site classroom training. After thispoint, as employees are promoted to the ranks ofdeputy assistant foremen, assistant foremen,and fore-men, they receive additional training in technicalmattersor managerialskills. In addition to technicalskills, trainingin safety and maintenanceoccurs on aregular basis over these years.Managersand employeesin interviewsalso attestedto the considerableknowledge about production op-erations that they gain through JK problem-solvingactivities. Employees receive basic problem-solvingtraining to support JK activities, and the JK teamleaders receive special JK training. In addition, em-ployee knowledge about their finishedsteel product isenhanced through a regular practice of employeevisits to customersand suppliers to understandspe-cial needs of thosebusinesses or to investigate specificquality problemsthat customers are experiencing.Japanese steel mills also maintain high levels oflabor-managementcommunication through numer-ous jointlabor-management ommitteesestablishedatthe level of the company, mill site, department,andshop production unit. Joint meetings, particularlythose at higher levels of the organization, considerissues related to the company's employment policies.Topics include production plans, investment plans,staffing projections and adjustments, safety andhealth, education and training,and some aspects ofthe workers' pay and work schedules. According tointerviews with union and managementofficials,be-cause joint labor-managementcommittees considersuch a wide range of topics, the distinctionbetweenjoint meetings and formal collective bargaining hasbecomeblurredover time.Still, changes"n wages andbenefits are determinedthrough separateformal col-lective bargaining.Finally,while a formal grievance

procedure is set forth in labor contractsas part of thelabor-management communication procedures ofmost Japanesemills, these procedures are little if everused.4The Japanesesteel companies in this study follow apolicy of employment security. The companies havemaintained this policy even though the total numberof workers directlyemployed in the companies' millshas declined substantiallywith the seculardecline indemand for steel production since the 1970s.5 Tomaintain employment security during a prolongedindustry contraction,Japanesesteel mills rely heavilyon worker mobility. Workersaffected by a plannedreduction in force may be transferred inside theircurrentdepartment, nside theirmill, to a subcontrac-tor or other firm nearby their currentworks, to an-other mill of the same parent company, or to asubcontractorof anothermill of the parentcompany.Depending on the type of transferbeing considered,the companynegotiateswith union officials hrough heappropriatemill- or company-level abor-managemencommittee. For example, transferring employees towork outside the company, referred o as "seconding"the employees, typicallyinvolves negotiationsin mill-or company-level labor-management committees.When a steel company "seconds"an employee, thecompanysubsidizes the difference n pay between thepay at the parent company and the pay rate at thesubcontractor or whom the employee works.Compensationfor productionworkers in the Japa-nese steel mills has up to fourmaincomponents.First,wages increasewith the number of yearsof servicean

According to interviews, grievance procedures have atrophiedbecause of the ample opportunity for labor-management commu-nication through joint committees, the willingness of managementto adopt changes after discussions with workers or union officials,and a seemingly shared desire to resolve issues among members ofa given shop's own local work community without interventionfrom outsiders. At one mill, workers will still occasionally availthemselves of their mill's grievance procedure, and labor andmanagement representatives there point to the stronger socialistfaction at this mill for the continued reliance on grievance ma-chinery.5 At one Japanese steel company, the total number of employeesworking at the company's steel mills declined by over 30% between1970 and 1990.



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employee has with the company. Seniority-based,ornenko, pay is a common feature of compensationdetermination hroughout arge Japanesemanufactur-ing establishments.Second, the Japanesesteel compa-nies in this study awardpay differentials o individualemployees based on meritevaluations by supervisors.While this componentof pay accounts for 24%of thewage bill according to one company, there is littleinter-workervariation n merit payments so that mostof the variationin wages among workers is attribut-able to the seniority-based nenkopayments. Third,workers receive a semiannual bonus payment, theterms of which are negotiated each spring by thecompanies and unions and determined largely byrecent profitability evels of the company. Finally,inone of the Japanese companies, a worker'sjob classi-fication is a fourth determinant of his pay. In thiscompany, pay rates vary accordingto an assessmentof the knowledge, skills,and level of responsibility oreach job.In sum, the Japanese production lines employ acommon system of HRM practices including:problem-solving teams, rotation across jobs, extensiveorientation, training throughout employees' careers,extensivelabor-management ommunication, mploy-ment security, and compensation based largely onseniority-basedwages and profit sharing.We refertothe combination of HRM:practicesused in Japanesefinishing lines as the JapaneseHRM system.3.2. HRM Systems in U.S. Work SitesSteelfinishing ines in the U.S. sample exhibitsubstan-tially more variation in their HRM practicesthan doJapaneseproducers.We groupedlines according o thefour differentsystems of HRMpractices hat the linesemploy,as shown in the last four columnsof Table 1.

The Traditional System. The traditionalHRMsys-tem n U.S. finishinglines is comprisedof a distinctiveset of work practices: narrowly defined jobs; strictwork rules;incentive pay based on quantity and notquality of output; no work teams; no practice ofmanagers sharing financial information or meetingregularlyoff-line with workers or their union repre-sentatives;no screening; rainingonly from "whatyoupick up on the job";close supervision by a relatively

large number of foremen;and communicationschan-neled through an adversarialgrievance procedure.The Low Teamwork and Communication System.A second group of lines has borrowed the work-team

policy common to Japanese establishments,but hasfew innovative work practices.Lines which we cate-gorize as following the low teamworknd communications systemhave all made some attempt to initiateworker involvementin teams,and this effort s alwayscoupled with some labor-managementcommunica-tion practices, either sharing of financial informationor regularmeetingsbetween line managersand work-ers or their union representatives. However, otherthan these two work practice innovations, the set ofHRM:practices that comprise this HRM:system issimilar to those that comprise the traditionalsystem.Furthermore,despite the formal work team policy, noline with the low teamwork and communication sys-tem has a high level of worker involvement in teams.

The High Teamwork and Training System. Athird set of lines in the United States moves furtheraway from the traditionalU.S. system by adoptingadditional innovative work practices.As in the lowteamwork and communication system, lines in thisthird group also have work teams and informationsharing procedures.All lines in this group also pro-vide regularand extensive skills trainingfor workers.Furthermore, t all lines in this third group, a majorityof workers participatein problem-solving activities,with workers receiving training in problem-solvingprocesses. We therefore refer to this category as thehigh teamwork nd trainingsystem.Lines in this cate-gory always lack one or more of the following inno-vative HRM:practices: extensive screening, job rota-tion or reducedjob classifications,performance-basedpay schemes, or employment security.

The Innovative System. A fourth group of pro-duction lines in the U.S. sample employs a system ofHRMpracticeswith elements that parallel the entiresystem of work practicesfound in Japaneseestablish-ments. Managersof these lines spent well over a yearcarefully selecting, orienting, and training new em-ployees before employees began work on the line. Allemployees are trained in technical line operations,



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Table 1 Percentage of ProductionLines with Specific HRMPractices WithinFive DifferentHRM ystem CategoriesaPractices n Seven HRM Japanese Innovative HighTeamwork& LowTeamwork& Traditional

PolicyAreas HRM ystem U.S. System TrainingU.S. System Communic. .S. System U.S. System

1. Incentive aya. Multi-Attributencentive ay 0.00 1.00 0.31 0.00 0.00b. Extensive rofit haring 1.00 0.00 0.15 0.31 0.002. Recruitinga. VeryExtensive creening 0.00 1.00 0.15 0.00 0.00b. LengthyOrientationeriod 1.00 0.00 0.00 0.00 0.003. Teamworka. High%In Prob.Solv. Teams 1.00 1.00 0.85 0.10 0.00b. Workersn Multiple eams 1.00 1.00 0.62 0.00 0.00c. Some Teamwork ractice 1.00 1.00 1.00 1.00 0.004. Employmentecuritya. Employ. ecurityPledge 1.00 1.00 0.23 0.48 0.005. JobFlexibilitya. Job Rotation 1.00 1.00 0.15 0.03 0.00b. Combined ob Classes 0.00 1.00 0.38 0.00 0.006. Traininga. Off-SiteTrain,AllWorkers 1.00 1.00 0.69 0.00 0.00b. Off-SiteTrain,Some Workers 1.00 1.00 0.92 0.07 0.007. Labor-Management

Communicationa. Informationharing 1.00 1.00 0.54 0.62 0.00b. RegularMeetingswith Workers 1.00 1.00 0.77 0.72 0.00

Note:aThe ample or Table1 is basedon productionines andnot production-lineonths.Column shows means orthe 5 Japaneseproductionines nthe dataset. Columns -5 showsmeans ordifferentategories f U.S.productionines.This ample or columns2-5 includes 4 observations,ndnot ust36 U.S.productionlines, because, or U.S. ines hatswitchHRM racticesduringhe sampleperiod,t includes ne observationor each different ombinationf HRM racticeshat helines experience.For he sample of line-month bservations sed inthe productivitynalyses(n = 2594), 15.6%are fromJapanese ines. Of he U.S. sample (n= 2190, 9.3% havethe innovative .S.system,13.8%have the high eamwork ndtraining ystem,41.7% havethe lowteamwork ndcommunicationystem,and 35.2% have the traditional .S.system.statistical process control, and team problem-solvingtechniques, and are involved in on-going problem-solving teams. Workers are trained to do all jobs onthe line and regularly rotate across tasks. Employeepay is based on a multiattributegain-sharingplan or a"pay-for-knowledge" ystem in which employees' sal-aries increase as they progress through a series ofknowledge and skill banks. Finally, workers enjoy animplicit employment security pledge and have regularcontactwith union officialsand with the relativelyfewmanagers on the line. We referto U.S. finishing linesthat have this full complement of innovative workpractices hat match closely the JapaneseHRM systemas lines with the innovativeHRMsystem.We will usethe terms "work practice innovation" or "innovativeHRM practice" when referring to individual HRM

practices, such as work teams, employment security,or on-going training in U.S. establishments,that arefound in the low teamwork and communicationsys-tem and in the high teamwork and training system aswell as in the innovative HRM: ystem.3.3. A Comparison of the Japanese System and theInnovative U.S. SystemTable 1 summarizesthe distinctive featuresof the fourU.S. systems and the Japanese system of work prac-tices.6 The four HRM: ystems in U.S. steel finishing6 To classify the U.S. lines shown in Table 1, we used three differentstatistical procedures to categorize lines according to their HRMpractices-Nominate scaling, Guttman scaling, and a simple 0 to 7HRM index. Each procedure identifies four distinctive HRM cate-gories, and the assignment of lines to the four categories is nearly



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lines representa hierarchywith the traditionalsystemadopting none of the features of the Japanesesystem,the low teamworkand communication ystem adoptinga quality circle-typepracticeand a labor-managementcommunicationpractice,and the high teamwork andtraining system showing high participation n teams,informationsharing procedures,extensive skills train-ing, and occasionallysome other innovative practicecommon to the Japanesesystem. The HRM:practiceswhich comprise the innovative U.S. system matchclosely the entire set of practiceswhich constitutetheJapanesesystem.Still,some differences xist between the specificprac-ticesin theJapanese ystemand in the innovativeHRMsystem in the United States. The degree of screeningthroughskills testsand personality ests is considerablymoreextensivein the U.S. system,while the period oforientationand indoctrinationasts much longerin theJapanesesystem.Jobflexibility s accomplished n theinnovative U.S. system throughmore frequentmove-ment of workersacross asksthan n theJapanesemodelwhere workers'rotations hrough obs s a moregradualprocess.Finally,U.S. lines have incentivepay plans thattie employees'pay to several ine-specific riteria,whilein Japanese ines, incentive pay comes in the form ofcompany-level rofitsharingpayments hatare a sizablepercentof annualpay.73.4. Is the Japanese HRM System Transferable to

the United States?Based on case study evidence of failed employeeparticipationefforts n some firms,some have claimedthat "Japanese-styleHRM" s not transferable o U.S.

identical across all procedures (see Ichniowski et al. 1997, pp.296-298 for further explanation). While we use the categoriesshown in Table 1 to describethe HRMenvironmentof the lines inthe productivityregressions o follow, the results of the productiv-ity regressionsare again nearly identicalwhen the HRMcategoriesderived from the alternative tatisticalproceduresare used.7The U.S. producers have profit sharing plans 48 percent of thetime, but these plans tend to pay from zero to ten percent ofcompensation; n Japan, profit sharingpays closer to 40 percent.Still, while profit sharing payments may be a larger shareof totalcompensation, he variation n theJapaneseprofitsharingpaymentsmay be less, as some of the profit sharing payment is in fact aguaranteedpayment.

manufacturers-that the Japanese approachcan onlywork in the context of the Japanese culture. Thesystems perspective described in ?2.1 suggests thatkey Japanese practices, such as problem-solvingteams, can be effectively transferred to the UnitedStates if U.S. firms also adopt other complementarypractices. Many scholars of work relations in Japanecho this view. Cole (1979)arguesthatJapanesequal-ity control circles "may well be applicable [in theUnited States]if appropriateadaptationsare made toaccommodate the circles to U.S. conditions." Dore(1973) argues that the "Japaneseemploymentsystemis an emergent organizational orm which representsan evolutionaryadvance over the [formadopted by]early industrializers"and will become more commonamong newer firms in the U.S. (Dore 1973,as quotedin Lincoln and Kalleberg 1985, p. 739). Similarly,Florida and Kenney argue that this evolution hashelped firms "harness the intellectualas well as thephysical capabilitiesof workers" (1991, p. 383).No prior study has assembled the data necessarytoprovide a direct test of the performance ffects of theJapanese ystemand a comparablework systemin theU.S., such as the innovativesystem described above.8Existingempirical vidence aboutadoptionof participa-tory work practices does not conclusively addresswhetherHRMpractices hat are commonamong largeJapanesemanufacturerswork in U.S. finrs. Evidenceshowing that innovativeHRMpracticessuch as workteams are becoming more common among U.S. firmssuggests that U.S. firms are findingit increasinglym-portantto adopt the work practicesused by Japanesemanufacturers.9 owever,other studies that trackem-8 While not directlyaddressingthe issue of whetherparticipatoryHRM systems have different effects on performance n differentcountries, MacDuffie'sanalysis (1995),which considers the effi-ciency of auto assembly plants in differentcountries, ncluding theUnitedStatesandJapan,providesthe mostrelevantcomparisonsonthese questions.'Osterman's study (1994)of a representative ample of U.S. workestablishments finds that some 62%of U.S. establishmentshavesome experience with employee participation,defined as use ofwork teams, qualitycircles,or job rotation.Among a sampleof largeFortune1000 firms,Lawleret al. (1992) ind that 70%reporthavingexperience with employee involvement. These figures representsignificant growth in employee participation.For example, Oster-



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ployee involvement effortsover longerperiods paintadifferentpicture, howing thatmostemployeeparticipa-tionefforts n the U.S.are not long-lived,but are nsteaddisbanded soon after adoption, suggesting that mostemployeeinvolvement nitiativesn the U.S.may not beeffective.10ycomparing he performanceevels of steelfinishing ines that have the Japanese ystem,the inno-vativeU.S.HRMsystem, andotherHRMsystems n theU.S. with fewer innovativework practices,we providean explicit test of whether the JapaneseHRM systemworksin the U.S.4. Sample, Model of the ProductionProcess, and Performance Data4.1. SampleThrough site visits and extensive interviews withmanagers, production supervisors, and line employ-ees, we collected precise data on performancemea-sures and the technologyof the steel finishinglines inadditionto the comprehensivedata on HRMpracticesdetailed in the previous section. The sample for ouranalysis includes data from 36 U.S. production linesand 5 Japaneseproduction lines.11'12he productivityanalysis below is based on a panel sample of up to2,594 monthly observations on these 41 U.S. andJapanese production lines-or an average of aboutfive years of monthly observations on a given U.S. orJapanesefinishing line.13

4.2. Modeling the ProductionProcessTo develop convincing models of the productivityofthese lines, we toured each line with an experiencedengineer, areaoperationsmanager,or superintendent.These tours gave us a detailed understandingof thisproductionprocess and an opportunityto discuss thebest ways to measure and compare the performanceoutcomes of differentfinishing lines. All lines in thesample use the same continuousproductionprocess.These lines treatvery long flat sheets of steel that areabout 8th-inch hick. A coiled roll of this steel stripweighing some 12 tons is loaded on the entry end ofthe line and the beginning of this steel stripis weldedto the end of the coil currentlyrunning through theline. A long, continuous sheet of steel unrollsfrom thecoil at the front end of the processand threads ts waythrough the machinerythat treatsthe steel. After thefinishingtreatment, he steel is recoiledand cut at theexit end of the process.The very specificnature of this productionprocessmakes it possible to develop a specific model ofproduction. The potentialtonnage producedby line iin month t, or output Qi, is a function of three things:the amount of tonnage loaded onto the line, or steelinput Iij, the speed of the line, sit, and the numberofhours thatthe line is scheduled to run thatmonth,h :Potential Qit = y(sth)(1)

man reports that only one-third of the employee involvementprograms in his sample are more than five years old.10Drago (1988) finds that a majority of quality circle initiatives fail tosurvive more than a few years." In total, we visited 45 U.S. lines at 22 different locations. Four ofthe 45 U.S. lines visited had only recently begun operations or hadnot yet started operating and so could not supply productivityinformation. Of the remaining 41 lines, 36 provided comparableinformation for estimating the performance models.12 In Japan, we visited four steel mills of one company and one millof a second company. These five sites had a total of 21 lines. The firstJapanese company provided data on all three finishing lines inoperation at one of the four sites. The second company provideddata on the two lines in operation at that site. No performance datawere provided for a third line at the mill site of company two sincethat line had been operating for less than one-half year.13 Because the Japanese sample covers fewer lines than the U.S.sample, we were particularly concerned about how representative

the sample of Japanese lines was of the broader population of thesetypes of finishing lines among the four large Japanese steel manu-facturers. HRM practices for the Japanese lines in the sample for ourproductivity analyses are identical to the practices at all other millsites of the two Japanese companies participating in this study.Furthermore, labor relations and personnel managers from thesetwo companies concurred that their employment practices were alsothe same ones used by all other integrated steel makers in Japan.Concerning performance of the lines, while officials of the Japanesecompanies would only provide monthly line-specific data from onemill site each, covering a total of five finishing lines, company-levelstatistics indicated that the performance of these lines was typical ofother finishing lines owned by these companies. Furthermore,foremen at the mill sites for which performance data were providedindicated that the performance of the five lines in this sample istypical of performance levels of other finishing lines of this kind inJapan, based upon information shared across companies at industry-wide meetings for foremen and superintendents.

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where the quantity n parentheses n (1) is the volumeof steel through the line in month t, and y is anestimate of the density of steel. Thus, potential outputis determinedby the capacityof the line (and thereforethe sizes of coils that are loaded on the line), the speedof the line, and the amount of scheduled runningtime.The actual steel produced on the line differs frompotential production defined in (1) because the linedoes not run all of its scheduled hours. Unscheduled"delays" are line stoppages due to problems on theline. Thus, actual production is a function:Actual Qit = [y(I*shSt)f](1 - dit) (2)

where ditis delays, or the fractionof scheduled hourswhich are lost due to unscheduled line stops, and (1- d t) is uptime. Once the technological parameters ofthe line are specified and coil size is determinedbytechnology and product demand conditions, actualproduction epends ntirelyon uptime. ncreasesin up-time are increases in tonnage and productivity.Equation (2) models tons of output, but the qualityof these tons is a key issue when examining theeffectivenessof HRMpractices.Thestandard ndustrymeasure of quality performance or these lines is the"primeyield"rate.The prime yield rateis the percentof total production in a month that meets specificindustry standards for designation as "prime" fin-ished steel, denoted Yithere.Adding to Equation (2),quality tons is defined:

Quality Qit = Yit[,y(I*ts*)](1 - dit) (3)Thenumber of quality tons depends upon uptime andprime yield rates.Thoughthese two variables are notdirectly related to one another,there can be indirectrelationshipsbetween the variables. For example, amechanicalproblem that causes a delay might alsohave been causing quality problems.4.3. Dependent Productivity and Quality VariablesThe dependent productivity variable,uptime (Uit = 1- dit),is the percentof scheduled operatingtime thatthe line actually runs. It has a mean of 0.928 and astandard deviation of 0.047 in the sample of 2,594"line-month"observationsused in the empiricalanal-yses. It ranges from 0.398 to 1.0. The dependent

quality variable,prime yield rate, has a mean of 0.946and a standarddeviation of 0.043 n our panel data set.It ranges from 0.407 to 1.0. Because the percent primeyield variable is the ratio of prime tons to total tons,estimates of the effects of HRM measures or othercontrol variables on this measure of quality will notreflect any effects of these variables on the uptimeproductivity variable.4.4. Variables in the Performance EquationsGiven the uptime and prime yield measures of per-formance,the regressionswe estimate are:

Uit= f(MNTit, VNit, CAPit,IQit,HRMit)+ eit (4)Yit= g(MNTit, VNit, CAPit, IQit, HRMit) + uit (5)

where the same vector of variables affectuptime andyield, though the coefficientsdiffer, and the measure-ment error n the residualsis assumed (for now) to beindependentlyand identicallydistributed.14The uptime productivityvariablemeasuresthe per-cent of scheduleduptimethelineoperates. fincreasesnscheduled downtime makeit easier for lines to achievehigher levels of uptime,and if scheduleddowntimeiscorrelatedwith the HRMmeasures, hencoefficients nthe HRM variablesobtained from (4) will be biasedestimatesof their effectson productivity.Thereare twocategories of scheduled downtime. One category isdowntime due to lack of orders.During our sampleperiod, downtime due to lack of orders is virtuallynonexistent n the finishing ines.A second categoryofscheduleddowntime is downtime for scheduledmain-tenance.Some inesmayhave low levels of unscheduleddelays simplybecause heyschedulemore downtime ormaintenancework. We controlfor this possibilitydi-rectly by includingthe variableMNT in Equations 4)and (5) which measures the numberof annual eight-hour maintenance hiftsfor the line.Finishinglines in the sample vary in the vintage oftheir capital. Older finishing lines will have more14 Given the natureof the productionfunction, t is possible thatacross-sectional orrelation xists betweenthe residuals n Equations(4) and (5), suggestingthe need for seeminglyunrelatedregressionestimates. However, such estimation cannot result in efficiencygainswhen the sets of right-hand-side ariablesare identical n thetwo equations,which is the case here (Greene1997, page 676).



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equipment failures and lower uptimes. Because olderlines also tend to have more traditional work prac-tices, apparent negative effects of more traditionalHRM environments on uptime could therefore reflectthe effects of older, less efficient capital. Equations (4)and (5) therefore include the vector VN which mea-sures the year the line was built, current age of theline, and the squares of these variables. Unscheduleddowntime is also high, and quality low, during startupperiods for new lines. Therefore, we also include adummy variable indicating whether the line is in thefirst twelve months of operations and a 1 to 12 timecounter for the first twelve months of operations.

While the basic steel finishing technology for thelines in this sample is very homogeneous, there aresome differences across lines in certain pieces ofequipment. Through our on-site inspections and inter-views, we identified and collected a comprehensiveset of data on technological features of the lines thataffect their productivity. CAP in Equations (4) and (5)is a vector of up to nine dummy variables indicatingthe presence of specific features of the equipmentalong the line that could complicate the productionprocess, making delays more likely, or streamliningoperations and thereby reducing delays. CAP alsoincludes a variable for periods when new equipmentwas being installed on a line, since these periods tendto have relatively high levels of delays and lowquality, and a dummy variable for the degree ofcomputer automation of the line.'5 Finally, IQ is a 1 to5 index of the quality of the steel input from industrysources based on the quality of steel provided by eachline's steel supplier. Lower quality steel input tends tocause more line delays and yield lower quality output,according to those interviewed. The IQ control vari-able changes over time for lines that switch suppliersduring the sample period.In total, the uptime productivity equation includesup to twenty-five controls for detailed characteristics15 Data needed to create more fine-grained measures of computerautomation of the lines were not available. We created the computerautomation dummy based on our direct observations of the linesand discussions with line engineers. Because computer automationis higher in newer lines, this dummy serves as another control forvintage and sophistication of the capital stock.

of the lines. The prime yield models include the sameset of controls as in the uptime models, but alsoinclude a set of five dummy variables to control forslight differences in the ways in which different linesdefine prime yield.The HRM practices in (4) and (5) are measuredwith a vector of five dummies for the different U.S.and Japanese HRM systems described in ?3. Thus,by including this vector of HRM system variables inthe performance equations represented in (4) and(5), we are able to provide direct evidence on thethree comparisons listed in the introduction con-cerning the impact of participatory HRM systems onperformance of U.S. and Japanese manufacturingfacilities.

5. The Effects of U.S. and JapaneseHRM Systems on ProductivityBecause the panel data set includes longitudinalmonthly data on each of the 41 finishing lines, we firstrewrite the uptime productivity equation in (4) tointroduce a serially correlated error:

Uit = ,B'Xit+ eit (6)where Xit is the vector of right-hand-side variablesin (4), and eit = peit-i + uit. We allow for line-specific serial correlation by estimating pit sepa-rately for each line using generalized least squares(GLS).16 Table 2 reports the coefficients on the HRMvariables from GLS productivity equations. Thecolumn 1 regression estimates the average uptimedifferential between Japanese and all U.S. lines thatis independent of the effects of the controls fortechnological and vintage differences in the produc-tion process. The coefficient on the Japan dummyvariable indicates that Japanese lines are signifi-cantly more productive than U.S. lines. On average,16 Because the dependent productivity variable is bounded at one,we also estimate the performance regression as tobits with a masspoint at one. While not reported in the table, the magnitude andlevel of significance of all coefficients in the tobit estimations arevirtually identical to those obtained in the GLS specifications, mostlikely because very few lines have uptimes or yield levels at theupper boundary of 1.0.



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Table 2 The Effects of U.S. and Japanese HRM ystems on Productivity[dependent ariable:% uptime;n = 2594]

[GLS; anel-specificerialcorrelation](1) (2) (3) (4) (5) (6)

la. JapaneseHRM ystem 0.049*** 0.073*** - 0.052*** 0.077***(0.005) (0.006) (0.005) (0.006)

1b. JapaneseHRM ystem-Company#1 - - 0.074*** - - 0.076***(0.006) (0.006)

1c. JapaneseHRM ystem-Company#2 - - 0.068*** - - 0.074***(0.008) (0.008)

2a. U.S.Innovative RM ystem - 0.073*** 0.072*** - 0.074*** 0.072***(0.008) (0.008) (0.008) (0.008)

2b. U.S. HighTeamwork& TrainingHRM ystem - 0.036*** 0.037*** - 0.039*** 0.039***(0.005) (0.005) (0.005) (0.005)

2c. U.S. LowTeamworknd Communication - 0.015*** 0.014*** - 0.020*** 0.019***HRM ystem (0.004) (0.004) (0.004) (0.004)3. Controlsor Production rocessTechnologya yes yes yes yes yes yes

4. YearDummies no no no yes yes yesLog-likelihood 7228.9 7282.8 7283.3 7256.1 7306.8 7306.7

TableNotes:aOtherontrolsn the uptimeproductivityodel nclude: umber f years ine has beenoperating ndyearssquared; ear inewas builtandyearbuiltsquared;dummy orstartupperiod first welve monthsof operation)nda 1-to-12 time trend or monthof startup; -to-5 indexof quality f steel input;number fannual ight-hourmaintenancehifts;dummyor ypeof customer;maximum idth f lineand tssquare;maximumine peedand tssquare;ninedummies o indicatespecificpiecesof equipment n the line and theage of one of these equipmenteatures; dummyo indicatehighand low levels of computerizationf linecontrols;anda variable o measure6-monthperiods rom he dateany new majorpieces of equipment re introduced.***Significantt the 0.01-level.

The mean value of the line-specific erial correlationoefficient s 0.46 for column 2).

line delays in Japanese lines are some 4.9 percentagepoints lower than in U.S. lines, or Japanese lines areabout five percent more productive.

Column 2 breaks out the group of all U.S. lines intothe four different HRM categories-the innovativesystem, the high teamwork and training system, thelow teamwork and communication system, and thetraditional U.S. system which is the omitted group.The results in the column 2 model show a clearhierarchy of productivity effects. Compared to theproductivity of the traditional U.S. system, the lowteamwork and communication system achieves pro-ductivity that is 1.5 percentage points higher; the highteamwork and training system 3.6 percentage pointshigher; and the innovative U.S. system 7.3 percentagepoints higher.

The column 1 and 2 results support two importantconclusions. First, Japanese production lines oper-

ating under their distinctive approach to HRM aresignificantly more productive than the average U.S.production line. Second, U.S. production lines withthe innovative system that parallels closely theJapanese system perform equally as well as theJapanese lines. Specifically, the coefficient on theJapanese system variable is not statistically differentfrom the coefficient on the U.S. innovative systemvariable (F[1, 2564] = 0.09). This evidence sup-ports the view that U.S. producers that follow theJapanese system of HRM practices match the high levelsof productivity of Japanese producers.The productivityof these lines far outpaces the productivity of U.S.lines that continue to follow the traditional U.S.system. When U.S. lines confine their adoption ofinnovative practices to work teams and informationsharing without other supporting work practices,productivity levels are only slightly higher than the



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productivity of U.S. lines with the traditional U.S.system. 17

The column 3 specification allows for different pro-ductivity effects for lines owned by different Japanesecompanies. The lines of the two different Japanese com-panies exhibit very similar levels of line uptime. AnF-test cannot reject the hypothesis that coefficients on theJapan Company 1 and Japan Company 2 variables areequal (F[1, 2563] = 1.74), indicating equally high levels ofproductivity across all Japanese lines. Finally, the modelsin columns 4-6 replicate the columns 1-3 models butadd a set of year dummies to the models. The inclusionof the year dummies has virtually no effect on thepattern of results shown in the column 1-3 models.

The coefficients on the control variables in theproductivity equations are largely in the expecteddirections and most are statistically significant (see theAppendix table). These coefficients indicate that lineshave more delays with: lower quality steel input; olderproduction technologies; start-up periods; higher linespeeds and wider coils; and the periods when newequipment is being installed. Contrary to expectations,scheduled maintenance does not, on average, signifi-cantly raise uptime (though it does raise yield). Onepossible explanation, suggested by our field research,is that problem-solving teams in Japanese and inno-vative U.S. lines have helped make maintenance work17 As shown in Table 1, the specific HRM practices within any HRMsystem category are always very similar. In three of the HRMsystem groupings, the general HRM practices are identical (i.e.,mean value of 1.0). However, some variation in HRM practicesoccurs within the high teamwork system and in the low teamworksystem. The variation of individual HRM practices within theseHRM system groups allows for an interesting test of the marginalbenefits of individual work practices.

We show in Ichniowski et al. (1997,309-311) that the adoption of anadditional individual HRM policy within a given HRM system grouphas no impact on productivity, and that the HRM system variables addexplanatory power to models that already contain the full vector ofindividual HERM ractices. While these tests support the conclusionthat it is the HRM system variables (and not the effects of thecomponent practices) that matter, other interesting tests are precludedby the lack of variation in HERM ractices within the most innovativegroups. For example, we are unable to test whether all components ofthe innovative or Japanese systems are essential for problem-solvingand JK teams to be effective, because there is no variation in theindividual FERM ractices within these systems.

more efficient, leading to fewer hours of maintenancein the lines that have achieved high levels of uptime(see footnote 26 for examples).

Inclusion of the control variables in the productivitymodels is consequential, because control variables arecorrelated with the HRM variables. For example, themore innovative HRM systems tend to be in newer lines.Average years of startup for lines in the different HRMcategories are: 1986 for innovative lines, 1969for the highteamwork lines, 1961 for the low teamwork lines, and1956 for the traditional lines. The sample's Japanese linesopened in the late 1960s and early 1970s. Several vari-ables measuring features of the capital equipment arealso related to capital vintage and so are also correlatedwith the HRM system variables.'8 Because newer equip-ment has higher uptimes, models that exclude controlsfor detailed features of the capital equipment yield evenlarger estimates of the performance impacts of moreinnovative HRM systems.196. The Effects of Japanese and U.S.HRM Systems on Product QualityEstimates of the performance effects of differentHRM systems in Table 2 focus on one dimension of18 More detailed descriptive statisticson the control variables byHRMgroup are available romthe authors.19It would be instructive o estimate ixed effectsmodels in additionto the GLSmodels presented.Forexample, becauselines with theinnovativeHRMsystemscreenworkerscarefully, t is possiblethatthe innovativesystemof HRMpracticesmay onlybe effectivewithspecifickinds of U.S. employees. Unfortunately,no U.S. line withthe innovative system and no Japanese ine changed their HRMpractices during the data period;thus fixed effectsmodels cannottest this possibility. However, some U.S. lines did switch from thetraditional ysteminto the communication ystemand intothehighteamworkand training system. Estimates of the coefficients(andstandarderrors) orthe low teamworkand communications ystemvariableand the high teamworkand trainingsystemvariable roma fixedeffectsmodel are0.025 0.006) nd 0.035 0.008) espectively-similar o the estimatedeffectsforthesevariables n the GLSmodelsin rows 2b and 2c of Table 2. While fixed effects models cannotestimate the productivity effects of the Japanese or innovativesystems,the fixed effects coefficients hat can be estimatedprovideparticularly trongevidence thatchanges away from the traditionalsystemto HRMsystemswith more innovativepracticesdo improveproductivity.For a detaileddiscussion of fixedeffectsestimates, eeIchniowskiet al. (1997).



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performance-productivity. However, when con-sidering the competitive advantages that Japanesemanufacturers are thought to possess, it is commonto think of higher levels of product quality ofJapanese manufacturers. Table 3 presents estimatesof the effects of the U.S. and Japanese HRM systemsvariables on the prime yield quality measure. Theresults in column 1 indicate that on average Japa-nese lines have significantly and substantiallyhigher prime yield rates than do the U.S. lines. Thecoefficients in subsequent columns indicate that thefour U.S. HRM system variables exhibit a hierarchyof quality effects as in the productivity models, butnow there is less difference between the middle twoHRM systems. The prime yield rates in the Japaneseand innovative U.S. lines are significantly and sub-stantially higher than the prime yield rates achieved

under either the high teamwork and training systemor the low teamwork and communication system.The lowest levels of quality are found in lines withthe traditional U.S. system. Japanese lines have thehighest prime yield rates, which are somewhathigher than the prime yield rates in those U.S. lineswith the innovative system.

The Table 3 column 3 specification allows theestimated quality levels to vary across the lines ofthe two Japanese companies, and there is littledifference. The coefficients on the HRM systemvariables are virtually unaffected when year dum-mies are added to the prime yield models in col-umns (4)-(6). The general pattern of findings dem-onstrates that Japanese lines and innovative U.S.lines achieve substantially higher quality levels thanU.S. lines with any of the other three HRM systems,

Table 3 The Effects of U.S. and Japanese HRM ystems on ProductQuality[dependent ariable:%primeyield;n = 2154]

[GLS; anel-specificerialcorrelation](1) (2) (3) (4) (5) (6)

1a. JapaneseHRM ystem 0.069*** 0.146*** - 0.065*** 0.145***(0.006) (0.010) (0.006) (0.010)

lb. JapaneseHRM ystem-Company#1 - - 0.155*** - - 0.154***(0.011) (0.011)lc. JapaneseHRM ystem-Company#2 - - 0.144*** - - 0.145***(0.011) (0.010)

2a. U.S. Innovative RM ystem - 0.107*** 0.113*** - 0.104*** 0.110***(0.010) (0.011) (0.010) (0.011)

2b. U.S.HighTeamwork& TrainingHRM ystem - 0.053*** 0.059*** - 0.052*** 0.058***(0.007) (0.008) (0.007) (0.008)

2c. U.S. LowTeamwork nd Communication - 0.053*** 0.055*** - 0.050*** 0.053***HRM ystem (0.007) (0.008) (0.007) (0.007)

3. Controlsor Production rocessTechnologya yes yes yes yes yes yes4. YearDummies no No no yes yes yesLog-likelihood 7471.2 7591.5 7591.9 7491.5 7616.7 7621.6

TableNotes:aOtherontrolsn the uptimeproductivity odel nclude: umber fyearsline has been operating ndyearssquared; ear inewas builtandyearbuiltsquared; ummyorstartupperiod first welvemonthsof operation)nd a 1-to-12 time trend or monthof startup; -to-5 indexof quality f steel input;number fannual ight-hourmaintenancehifts;dummyor ypeofcustomer;maximum idthof lineand tssquare;maximuminespeedand tssquare;ninedummies o indicatespecificpiecesof equipment nthe line andthe age of one of these equipmenteatures; dummyo indicatehighandlow levels of computerizationf linecontrols;a variableo measure6-monthperiods rom he dateanynew majorpieces of equipment re introduced;nd fivedummies orslightdifferences n how primeyieldis defined n differentines.***Significantt the 0.01-level.

Themean value of the line-specific erialcorrelationoefficients 0.52 for column 2).

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though the Japanese system is superior to the inno-vative U.S. system.20

The empirical results show that technologically sim-ilar production lines achieve gains in both productivity(or uptime) and product quality when systems ofinnovative HRM practices are introduced. This is anoteworthy outcome, because managers typically ex-perience the negative tradeoff between productivityand quality-on any given production line, an in-crease in line speed lowers quality. However, whentechnological change is introduced on a productionline, such a negative tradeoff need not exist: New,more technologically sophisticated, physical capitaloften simultaneously raises both productivity andproduct quality.2" The introduction of innovativeHRM systems is analogous to a technological change,because problem-solving teams can devise ways ofimproving the production line to elevate one perfor-mance outcome without harming the other, or toelevate both (for examples, see footnote 26).7. Accounting for the LimitedAdoption of the Innovative HRMSystem in the U.S.The results in Tables 2 and 3 consistently show that thefinishing lines achieve superior performance under theJapanese HRM system and the innovative HRM systemin the U.S. The magnitudes of the performance effectsattributable to the different HRM systems are economi-20 In fixed effects quality models, estimated coefficients (and stan-dard errors) on the high teamwork and training variable and on thelow teamwork and communication variable are 0.042 (0.007) and0.050 (0.008), respectively, providing further evidence that thechanges in the HRM systems are themselves responsible for thedifferences in the observed levels of performance.21 The coefficients on the control variables in the uptime and yieldregressions provide some evidence of a tradeoff between uptimeand yield-numerous coefficients are opposite in sign in yieldversus uptime (see the Appendix table). Overall, the control vari-ables are simultaneously picking up two effects: the static cross-sectional correlations across lines, when there is a negative tradeoffbetween uptime and yield, and the dynamic correlations (withinlines over time and between new and old lines) when there is apositive correlation between yield and uptime due to technologicalimprovements. On balance, the correlation between yield anduptime is 0.489 in the raw data.

cally important. Using data on these costs made avail-able by one line in the United States, we calculate that aconservative estimate of the difference in operating in-come due to a one percentage point increase in uptime tobe about $30,000 per month.' The uptime advantage ofseven to eight percentage points enjoyed by the innova-tive system over the traditional U.S. HRM system, andthe two to three percentage point advantage of interme-diate HRM systems over the traditional system in theUnited States, translate into large gains in revenues andoperating incomes. The increases in prime yield ratesdue to more innovative HRM systems add to thesealready substantial improvements in operating incomes.

Given these large performance differentials associ-ated with innovative HRM systems, an importantquestion is why the innovative system is not morewidespread in the U.S. Several explanations can beruled out. First, the direct costs of the innovative HRMpractices themselves appear to be far less than thebenefits of increased performance.23 Second, the pat-tern of results does not support an interpretation thatthe estimated performance gains due to HRM systemscan only be achieved in certain types of lines, such asnewer lines, thereby limiting the adoption of the

2 Operations managers explained to us the losses caused by linedelays. During an unscheduled line stop, the line loses revenuefrom planned output, but still incurs fixed costs, such as capitaldepreciation charges (that exceed $5,000 perhouirn some lines), andcertain variable costs, such as wages, which are typically paidduring downtime. Lines do not incur other variable costs, such ascosts of steel inputs and substantial portions of the energy costs,during line stops. Our calculation of the effect of a delay onoperating income is based on this information.23 We estimate that the direct costs of the innovative HRM policiesis about $2,100 per month for each percentage point gain inuptime-considerably below the gains in revenue and operatingincome due to a one percent gain in uptime. According to inter-views at the sites, the main differences in the costs of HRM policiesbetween the traditional system and the innovative system include:the time production workers would meet off the line, additionalHRM staff, consultants for training and team development, fixedcosts for developing policies, and costs of employment security forwages paid during idle time. The innovative system also saves oncertain costs, such as fewer management personnel. In our calcula-tion here, we assume one less foreman in innovative lines than intraditional lines, and amortize any fixed costs of innovative HRMpolicies over a five-year period.



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innovative system among older lines. The perfor-mance models include direct controls for differencesin the vintages of the lines. While a positive correlationexists between innovative HRM systems and newercapital stocks, some old lines do have innovative HRMpractices and exhibit higher performance than olderlines with more traditional HRM practices.24Third, theevidence also does not support an explanation thatsome unmeasured aspect of line quality makes themore innovative HRM systems ineffective amonglines with more traditional HRM systems. The stron-gest evidence against this interpretation is from thefixed effects models which show that the same lineswith the same workers have higher productivity andquality after adopting more innovative systems thanwhen they had the traditional HRM system.25

While an analysis of the overall effects of innovativeHRM systems on profitability is beyond the scope ofthe data available for this study, the pattern of empir-ical results suggest that difficult-to-measure "switch-ing costs" are likely to be the most important obstacles24 Old U.S. lines that were closed and later reopened by new ownersand managers typically adopt more innovative HRM systems.Several Japanese lines in our sample date back to the 1960s and areolder than some U.S. lines with the traditional or low teamwork andcommunication HRM systems. Results from the performance mod-els show that older lines in Japan and older lines in the U.S. withsome innovative work practices in their HRM systems, exhibitsubstantially higher levels of productivity and quality than do otherold lines with more traditional practices.25 See footnotes 19 and 20 supra. While the absence of lines thatswitch to the most innovative HRM system or the Japanese systemprecludes fixed effects estimates of the impacts of these two HRMsystems, other pieces of evidence suggest that unobservable mea-sures of quality are not likely to be the explanation for the estimatedHRM coefficients. First, coefficients on control variables in OLS andfixed effects models are very similar providing some assurance thatthe OLS models include all important line-specific determinants ofproductivity. Second, the collection of precise data and the on-siteinspections of each production line in our sample with experiencedmanagers make it unlikely that the models omit any technologicaldeterminants of performance. Finally, the qualitative evidence re-ported in ?8 identifies real differences in worker behavior foundonly in Japanese and innovative U.S. HRM systems that are respon-sible for productivity differences. The HRM practices themselvesand not some unobserved factor would seem to be the most likelycausal factor behind these performance-enhancing differences inworker behavior.

to more widespread adoption of the productivity- andquality-improving HRM systems. In particular, brandnew lines in greenfield sites uniformly adopt innova-tive work practices. As startups, these lines do not faceswitching costs. Those older lines that adopt the mostinnovative practices are typically "reconstituted"lines-lines that have been closed and later reopenedby new owners-and these lines also would not haveswitching costs because the lines had been closed.Changing the traditional U.S. HRM system to theinnovative system in an on-going line would cause acostly upheaval in work relations among employees.This dramatic change in HRM systems would alter therights and privileges of different groups of workers,change the status of foremen and senior workers, andrequire new investments in training to develop newtechnical and social skills.

8. Worker Behavior and the HighPerformance of JapaneseProduction SitesThe conclusion that the Japanese and innovative HRMsystems are themselves responsible for the high levelsof productivity and quality, rather than some omittedmeasure of line quality, would be strengthened withevidence on differences in worker behavior betweenlines with innovative HRM systems and lines withmore traditional systems. During our field investiga-tions, we observed dramatic differences in workerbehavior across lines with these different HRM sys-tems. In particular, extensive problem-solving activityexists only in the Japanese lines and in the U.S. lineswith the innovative system, and this activity directlyimproves uptime and prime yield rates.

One Japanese mili provided data on the JK problem-solving activity for its two finishing lines for 1992.Workers on one line completed 52 JK projects in 1992and workers on the second line completed 39 projects.During our tours of Japanese lines and the innovativeU.S. lines, engineers showed us concrete examples ofmany of the recent continuous improvement projects,and described how these projects help produce consis-

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tently higher levels of productivity and quality.26Thenumber of projects for a finishing line is only a smallpercentage of the total number of projects implementedmill-wide. Records for one Japanese mill show thatduring the 1980s total JK projects completed fluctuatedbetween 2,000to 3,000 per year, and the majority of theseprojects focused on improving productivity or quality oron reducing operating costs. Production workers inJapanese lines and innovative U.S. lines also collaboratedmore with co-workers, responded more quickly to qual-ity imperfections in the steel, and made more productivedecisions on the line. In contrast, problem-solving wasnonexistent in U.S. lines with the traditional system andvery limited in lines with the intermediate systems. Theessential point here is that a system of human resourcepractices that supports employee participation enablesworkers to fine tune their production process with fairlyminimal investments, and these productive worker be-haviors are much less common in lines with other HRMsystems.9. ConclusionThis study uses a unique body of personally collecteddata on one very specific kind of steel-making produc-tion process to compare the work practices and per-formance outcomes for very similar U.S. and Japaneseproduction lines. The homogeneity of the sample andthe careful specification of the productivity model26 Examples of JK projects in Japanese lines include the installationof dust collectors or tents to reduce foreign substances settling ontothe steel coils in the line, thereby increasing prime yield. Employeesfigured out ways to reduce water spraying on the line and toimprove the clamps when steel coils are sheared, both leading toreduced delays. One award-winning JK project involved the instal-lation of newly designed rollers which reduced scrap rates by 900tons per month and increased output on the line by 2.9 tons per manhour. Similar examples of problem-solving team projects in U.S.lines include: the addition or repositioning of line gauges; a processto stamp job numbers on the steel and visible crd displays of jobnumbers for operators; and improved exit end stands to limit coildamage. One team of production workers at a U.S. line describedhow they used their continuous improvement process to eliminatebreaks in welds between subsequent coils, a problem that numerousoutside experts could not solve, thereby reducing delays consider-ably. Problem-solving teams also find ways of reducing time spenton maintenance, by reconfiguring rolls, changing their standbylocation, or increasing the number of standby rolls.

permit particularly precise performance comparisons.The study's empirical results directly address thethree comparisons listed in the Introduction:

1. We find that Japanese lines are five percent moreproductive than U.S. lines, on average, after controllingcarefully for differences in the quantity and quality of thetechnology on the production line. Thus, the question is,what causes this productivity advantage?

2. We find that U.S. lines that adopt a full set ofinnovative HR practices that are comparable to those ofthe Japanese lines are as productive as the Japaneselines.There is no statistically significant difference in theproductivity levels of the Japanese and innovative U.S.lines. Thus, the productivity advantage of Japanese linesarises primarily from the HRM practices they employ,not from other factors, like cultural differences.3. We find that the set of lines having innovativeHR practices, in Japan and in the U.S., are on averageseven percent more productive than the U.S. linesemploying traditional HR practices. This provides animportant confirmation of our earlier work that usesonly U.S. data to evaluate the effectiveness of innova-tive HRM practices that promote employee participa-tion (Ichniowski et al. 1997).

We also find that quality gains accompany theproductivity gains-that both uptime and yield risewith innovative HRM systems. The early detractors ofthe "quality movement" believed that quality im-provement would come at the expense of lower pro-ductivity (Cole and Scott 1999). We find that theintroduction of innovative HR practices is comparableto the introduction of technological change-produc-tion lines can simultaneously achieve improvementsin two performance outcomes that were long consid-ered tradeoffs.

There are also reasons to suspect that the perfor-mance improvements due to these HRM systemsmay be greater than the productivity and qualitygains measured here. First, U.S. and Japanese prob-lem-solving teams also devote considerable time tosaving materials, energy, and other input costs,which are not captured in the two performancemeasures we investigate. Second, the data indicatethat the problem-solving teams in the highest per-forming lines devised ways to reduce maintenance



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hours. Third, innovative HRM systems appear tocreate an "option value." That is, highly skilled,well-trained employees create the capacity to re-spond quickly to future changes in production andmarket conditions. Specifically, Japanese finishinglines in our sample have long maintained very highlevels of uptime and prime yield between 98 to100%, yet JK projects still produce "continuousimprovements" in these lines. Japanese managersindicated that this result was not paradoxical. Theyemphasized that there are constant "shocks" to theproduction line-the depreciation of the existingcapital that lowers performance, the introduction ofnew pieces of equipment on the line, and changes inproduct types and customer specifications-thatwould all normally contribute to reductions in per-formance. JK teams are a primary vehicle for achiev-ing continuous improvement in this dynamic pro-duction environment to maintain the highestpossible levels of productivity and quality.

Finally, the evidence in this paper helps reconcileconflicting views about the effectiveness of Japa-nese-style worker involvement schemes in the U.S.While more research is required on the limitedadoption of innovative HRM systems in the U.S., thedebate about the effectiveness of Japanese-styleemployee participation can be addressed by clarify-ing what is meant by the "Japanese" approach.Limited effects of participatory work practices in theU.S. do not appear to be due to differences in theculture or characteristics of U.S. and Japanese workforces. Rather, U.S. manufacturers will realize onlymodest performance gains when they limit theirparticipation initiatives to only one or two innova-tive practices, such as quality circles or informationsharing. U.S. manufacturers who embrace a broaderdefinition or participation, that calls for the adop-tion of a comprehensive set of innovative HRMpractices, will match the higher levels of productiv-ity and quality found in Japanese plants.

AppendixTable FullSet of Coefficient stimates ptime nd PrimeYieldModels Table Column UptimeModel ndTable Column PrimeYieldModel)

Variable Uptime Yield Variable Uptime Yield1a. InnovativeRMystem 0.073*** 0.107*** 8c. Equipmentummyc 0.078*** 0.044***(0.008) (0.010) (0.008) (0.009)lb. High eamworkTrainingystem 0.036*** 0.053*** 9. Equipmentummy 0.004 0.001(0.005) (0.007) (0.003) (0.002)1c. LowTeamworkCom. ystem 0.01 *** 0.053*** 10.Equipmentummy 0.008*** 0.0002(0.004) (0.007) (0.003) (0.002)2. JapaneseHRMystem 0.073*** 0.146*** 11. Equipmentummy 0.016*** 0.004(0.006) (0.010) (0.004) (0.003)3. Index f Steel nput uality 0.007*** 0.0044*** 12. Ageof Dummy Equipment -0.0011*** 0.0005**(0.001) (0.0010) (0.0002) (0.0001)4a.YearBuilt 0.018*** -0.013*** 13. Equipmentummy 0.038*** 0.018***(0.003) (0.002) (0.008) (0.006)4b.YearBuilt2 -0.0001*** 0.0001*** 14. DummyorLowComputerization -0.020*** -0.027***(0.00002) (0.00002) (0.003) (0.003)5a. Lineage 0.005*** 0.0018*** 15a.Maximumine peed -0.018*** 0.017***(0.001) (0.0007) (0.005) (0.004)5b.Lineage2 -0.0001*** -0.0003*** 15b.Maximumine peed2 0.0015*** -0.0019***(0.00002) (0.00001) (0.0004) (0.0004)6a. DummyorStart-uperiod -0.066** -0.014 16a.Maximum idth -0.0057*** 0.01 ***(0.017) (0.010) (0.0018) (0.001)6b.TimeTrendorStart-up eriod 0.006** 0.0018 16b.Maximum idth2 0.00005*** -0.0001*(0.002) (0.001) (0.00001) (0.00001)7a.Equipmentummya 0.01 *** 0.004*** 17. DummyorType f EndUser 0.0065 -0.029***(0.004) (0.002) (0.006) (0.005)



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AppendixTable ContinuedVariable Uptime Yield Variable Uptime Yield

7b. Equipment ummy b 0.018*** -0.007*** 18. New Equipment-Valueuring ix -0.0025*** -0.0008***(0.004) (0.003) month nstallation (0.0005) (0.0002)8a. Equipment ummy a 0.017*** -0.026*** 19. Maintenancehifts Per Year -0.00001 0.000006(0.008) (0.006) (0.000006) (0.000017)

8b. Equipment ummy b 0.033 -0.002 20. Intercept 0.378*** 0.935***(0.009) (0.005) (0.088) (0.067)

Meanp 0.46 0.52 Log-likelihood 7282.8 7591.5TableNote:PrimeYieldModel lso includes ourdummies orslightdifferences n how differentinesdefineprime ield.***Significanttthe0.01 level;**Significan

at the 0.05 level;*Significantt the 0.10 level.

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Acceptedby GabrielBitran; received October,1996. This paperhas been with the authors 11 months or 2 revisions.


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