singapore shrm

message frequently found in cor-porate mission statements, annu-al reports and plaques on officewalls is that people are a firm’smost valuable resource. Havingthe right personnel at the rightplace and at the right time is ofutmost importance to the survivaland success of any organization.

The 1990s saw the emergenceof a new generation of workers whoare characterized by decreasedloyalty to their company andincreased expectations for auton-

omy, self-development and greater involvementin company decision making. Simultaneously,in Singapore and in many parts of the world,the increasing emphasis on knowledge-based

competitiveness in the current turbulent envi-ronment also accelerated the importance ofhuman capital.1 Careful management of thisimportant resource calls for a strategic focus onhuman resource management (HRM) in theorganization.

Strategic HRM involves designing and imple-menting a set of proactive HR policies/practicesthat ensures that an organization’s human capi-tal contributes to the achievements of its corpo-rate objectives. Fundamental to this perspectiveis an assumption that organizational perfor-mance is influenced by the set of HRM practicesin place. This article investigates the relationshipbetween strategic HRM practices and organiza-tional performance in Singapore and looks at theimplications of the findings for both managersand practitioners.

© 2002 Sage Publications JULY/AUGUST 2002 33

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Strategic Human Resource Management and Organizational Performance in Singapore

David Wan, Ph.D.Assistant Professor of ManagementFaculty of Business Administration

National University of Singapore

Chin Huat OngResearch Fellow, Centre for Business

Research & DevelopmentFaculty of Business Administration

National University of Singapore

Research indicates thatstrategic HRM practicesbring higher levels of organizational performance in Singapore.

Victor KokGraduateFaculty of Business AdministrationNational University of Singapore

Past Studies on Strategic HRMThe era of strategic HRM was ushered in nearlytwo decades ago,2 and since then, a behavioralperspective has emerged as the predominate par-adigm for research. However, it was only in the1990s that the concept of bundling of humanresource practices became popular and attractednumerous studies. Ferris, Russ, Albanese, andMartocchio3 made one of the first major attemptsto examine how effective management of humanresources might contribute to positive organiza-tional performance. In their study of 2,236 firmsfrom the U.S. construction industry, the Ferrisgroup addressed the roles played by three impor-tant organizational functions and activities on firmperformance: the status and importance of theHRM function, the role of unions and strategicplanning. They found that firms that had HRMdepartments were generally high performers (i.e.,larger total sales volume), firms that had a higherpercentage of their workforce unionized also per-formed better than firms with a lower percentageand, finally, firms performed better when theyengaged in more formalized strategic planning.

Cutuher-Gershenfeld4 developed and tested athesis that linked the industrial relations climateand economic performance. Based on a longitu-dinal analysis of changing patterns in labor-management relations across workgroups in theprimary manufacturing facility for XeroxCorporation, he classified labor-managementrelations into traditional, adversarial and trans-formational relations. His conclusion was thattransformational labor relations are associatedwith higher levels of organizational perfor-mance than the other types of industrial relationsclimates.

Based on questionnaire responses fromhuman resource managers at 30 of the 54 existingU.S. steel mini-mills between November 1988and March 1989, Arthur5 found that mills with“commitment” systems had higher productivity,lower scrap rates and lower employee turnoverthan those with “control” systems.

The first empirical research on an HR “bundle”or system was carried out by MacDuffie.6 Usingan international data set from 1989 to 1990, hesurveyed 62 automotive assembly plants. Hismost significant finding was that innovative HRpractices affect performance not individually butas a group. Huselid7 found that high performancework practices were associated with loweremployee turnover, greater productivity andhigher corporate financial performance. His

results were consistent across diverse measuresof firm performance after corrections for selectiv-ity and simultaneity biases.

Using 590 profit and nonprofit firms from theNational Organizations Survey, Delaney andHuselid8 found positive associations betweenHRM practices such as training and staffingselectivity, and perceptual firm performancemeasures. In a subsequent study of 293 U.S.firms, Huselid, Jackson and Schuler9 evaluatedthe impact of human resource managers’ capa-bilities on HR management effectiveness and thelatter’s impact on corporate performance. Theirfindings showed that large firms in the UnitedStates are more proficient in their technical HRMcapabilities than in their strategic HRM capabili-ties. As time goes on, however, a ceiling effect maybegin to constrain the ability of the U.S. firms togain competitive advantage through continuedimprovement in technical HRM activities. Inaddition to this finding, they noted significant cor-relation between HRM effectiveness and employ-ee productivity, cash flow and market value.

All of these studies generally reveal a positiverelationship between HRM policies/practicesand firm performance. We decided to test sixstrategic HRM variables that have been consis-tently identified in the literature as proactiveHRM practices. First, we tested each strategicHRM variable against firm performance. Second,we examined how this bundle of strategic HRMvariables together affect firm performance. It isthe combination of these practices, rather thanindividual ones, that shapes employee relationsand firm outcomes.

We tested the following specific hypotheses:

1. Extensive training is positively related tofirm performance (financial and HR).

2. Selective staffing is positively related tofirm performance.

3. Empowerment is positively related to firmperformance.

4. Performance appraisal is positively relatedto firm performance.

5. Broad job design is positively related tofirm performance.

6. Performance-based pay is positively relat-ed to firm performance.

7. A bundle of strategic HRM variables arepositively related to firm performance.

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34 COMPENSATION & BENEFITS REVIEW

MeasurementsThe prime objective of this study is to ascertainthe relationship between strategic HRM and firmperformance. The various variables used to mea-sure these two constructs are described as follows.

Strategic HRM VariablesSix different variables are used to measure a firm’sstrategic HRM system. They are the following:

• selective staffing,

• extensive training,

• empowerment,

• performance evaluation,

• broad job design and

• performance-based pay.

These six variables are considered sufficientlybroad enough to capture the key dimensions of astrategic HRM system.

Selective staffing was assessed using five itemsadapted from Snell and Dean.10 These items cap-ture aspects of staffing practices such as theamount of resources (time and money) spent onstaffing. A sample item is, “Great importance isplaced on the whole staffing process in our firm”(1= very inaccurate, 6= very accurate). Likewise,extensive training was measured by a six-itemLikert-type scale. A sample item is, “The trainingprocess for non-managerial employees in ourfirm is formal and systematically structured.”

Scale measurements for empowerment,appraisal, job design and performance-based paywere adapted from Bae and Lawler.11 Elevenitems were used to measure empowerment. Highvalues represent such factors as high employ-ment involvement, delegation, autonomy, pur-suit of a cooperative climate and egalitarianism.A sample item is, “The jobs in our firm providenon-managerial employees with many chancesto use personal initiative or judgment in carryingout their work.”

Five items were used to assess performanceappraisal. This reflects the extensiveness ofappraisal efforts and whether the purpose of theevaluation is developmental or administrative. Asample item is, “Much effort is given to measur-ing employee performance for non-managerialemployees in our firm.” Broad job design is mea-sured by four items to reflect the extent to whichjobs involve multiple skills and competencies. Asample item is, “Most jobs are simple and repeti-

tive in our firm.” Five items were used to assessperformance-based pay. This variable reflects thedegree of the linkage of performance and paylevel. A sample item is, “Pay for non-managerialemployees is closely tied to individual or groupperformance in our firm.”

Finally, the bundle of strategic HRM variablesis obtained by summing the factor scores of thevarious strategic HRM variables as derived fromexploratory factor analysis.

Organizational Performance VariablesWe used a subjective measurement for organiza-tional performance. Companies in Singapore arevery reluctant to disclose their financial perfor-mance. Although financial data for publicly listedcompanies are readily available from their annu-al reports, taking such an approach would reducethe sample of multinationals in Singapore.

Eight items were adapted from Khandwalla12

because they involve both financial and HR per-formances of a firm. These include the following:employee job satisfaction, employee commitmentor loyalty to the firm, public image and goodwill,growth rate of sales or revenues, product (or ser-vice) quality, employee productivity and financialstrength. These items are segregated into twoscales. Long-run level of profitability, growth rateof sales or revenues and financial strength areclassified under financial performance. The restof the items are classified under HR performance.For these items, subjects were asked to respondto a 6-point Likert-type scale based on the follow-ing statement: “Compared to your industry aver-age, how do you compare on each of the follow-ing?” (1 = very low, 6 = very high).

Five control variables were used:

• firm size,

• union status,

• industry,

• ownership type and

• country of origin for foreign firms.

Firm size was measured as the sum of the num-ber of full-time employees and part-timeemployees. Dummy variables include union sta-tus (unionized firm is coded 1, 0 otherwise),industry (manufacturing firm is coded 1, 0 other-wise) and ownership type (1 for joint venture, 0otherwise). In addition, the firm’s national originis coded by a set of dummy variables: Singapore,the United States, Japan and Europe.

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The SampleA mail survey approach was used in the study. Aquestionnaire was administered to the person incharge of the human resource department in thecompany. Each questionnaire was accompaniedby a cover letter explaining the purpose of thestudy. Units of observation for this study are sub-sidiaries of multinational companies (MNCs) andlocal firms operating in Singapore. Each firmincluded in the sample had at least 50 full-timeemployees. The sample comes from different sec-tors of the economy. In the case of subsidiaries,both wholly owned MNC subsidiaries and jointventures were included.

A total of 2,160 companies compiled from theSingapore 1000 and Singapore Exchange Directorywere targeted as the initial respondents. Thesecompanies were used because they fulfilled therequirements for this study. Companies in theSingapore 1000 are either public limited or pri-vate limited companies with at least two full yearsof operation. These companies are the top-performing companies in Singapore in terms ofsales turnover and profits. Firms in the SingaporeExchange Directory are generally the large, localcompanies in Singapore.

To pretest the questionnaire, five humanresource executives from Singapore-based com-panies were chosen. The questionnaires werefirst administered to these respondents. Issuesassessed during the pilot test were face validity,instructions and statement clarity, questionnairelayout and length. Improvements were made tothe questionnaire based on the respondents’comments. We are aware of the possibility ofcommon-source bias as we only surveyed the HRmanager. To reduce this problem, scale itemswere deliberately intermingled with one another.In addition, we left the organizational perfor-

mance section toward the end of the question-naire so as to limit the possibility of respondentsrationalizing their answers.

ResultsBecause there are 36 statements representing thesix strategic HRM variables, factor analysis wasconducted to reduce the number of statements toa more manageable set. Internal consistency ofall the scales was then assessed using Cronbach’sreliability alpha. The interitem correlationresults, available in exploratory factor analysis,were used to test the bivariate relationshipbetween the strategic HRM variables and firmperformance. This provides a first test for the sixhypotheses.

We next analyzed the data by hierarchicalregression, which incorporates all explanatoryand control variables. Two regression modelswere built. In the first model, the control vari-ables were used as independent variables againstfirm performance (both financial and HR). In thesecond model, in addition to all the control vari-ables deployed in the first model, the variousstrategic HRM factors identified in the explorato-ry factor analysis stage were added to the model,one factor at a time. The “significant” factors werethen grouped together to form a bundle of strate-gic HRM variables and tested in the same manner.The change in F ratio assesses any statistical dif-ference between the two models. Hierarchical mul-tiple regression provided a confirmatory test forHypotheses 1 to 6 and the test for Hypothesis 7.

General FindingsA total of 191 companies responded to the survey.The organizations were classified into six differ-ent industries: manufacturing, construction,

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EXHIBIT 1Breakdown of Respondents

Ownership

Sector Local Japan United States Europe Other Asia Total

Manufacturing 16 29 11 10 2 68

Construction 11 2 2 1 4 20

Commerce 9 4 3 6 1 23

Transport/storage/communications 4 1 1 1 1 8

Finance 4 1 1 1 2 9

Other services 18 16 15 10 4 63

Total 62 53 33 29 14 191

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EXHIBIT 2Factor Analysis of Strategic Human Resource Management Variables

Factor Loadings

Questionnaire Item Factor 1 Factor 2 Factor 3 Factor 4 Factor 5 Factor 6

Training: � = 0.8194

Amount of money spent on training 0.790 0.384 0.101 0.003 –0.018 0.181

Availability of different kinds of training 0.788 0.322 0.150 0.108 –0.040 0.138

Opportunities for training 0.650 0.366 0.148 0.146 –0.027 0.108

High priority on training 0.636 0.249 0.346 0.148 0.179 0.099

Systematically structured training process 0.578 –0.105 0.054 0.091 0.241 0.019

Extensive training for general skills 0.542 0.242 0.118 0.058 0.166 0.450

Extensive transference of task and responsibilities 0.433 0.088 0.408 0.003 0.394 0.218

Selection: � = 0.8324

High selection criteria 0.292 0.760 0.191 0.147 0.058 0.117

Much efforts in appraisal performance 0.274 0.724 0.118 0.272 0.002 0.027

Much efforts to select the best person 0.089 0.639 0.234 0.041 0.018 0.087

Great importance on staffing process 0.371 0.581 0.114 0.029 0.466 –0.006

Extensive selection process 0.059 0.570 0.008 0.131 0.173 0.171

Participation in wide range of issues 0.337 0.417 0.012 0.247 0.259 0.351

Amount of money spent on selection 0.361 0.400 0.028 0.300 0.141 0.127

Empowerment: � = 0.7867

Permitting enough discretion in doing work –0.060 0.036 0.654 –0.237 0.049 0.059

Providing chances to use personal initiative 0.093 0.392 0.650 0.102 0.094 0.144

High pay level compared to same industry 0.199 –0.163 0.621 0.129 0.220 0.099

Focus on long-term potential of candidates 0.155 0.221 0.603 0.323 0.067 –0.061

Participation in very wide range of issues 0.293 0.343 0.562 0.115 0.137 0.260

Engagement in problem solving and decisions 0.257 0.405 0.538 0.103 0.136 0.212

Require multitasking 0.311 0.032 0.315 0.175 0.306 0.048

Performance appraisal: � = 0.7867

Pay raise and promotion tie to performance appraisal 0.102 0.223 0.048 0.816 –0.070 0.021

Pay tie to group performance 0.062 0.068 0.035 0.774 0.172 0.079

Emphasis on personal development 0.417 0.162 0.316 0.466 0.043 0.041

Team-based work: � = 0.5402

Minimum status differentials for egalitarianism –0.028 0.062 0.341 –0.029 0.709 0.084

Coordination and control based on shared goals 0.130 0.165 0.140 0.155 0.665 0.252

Clearly defined jobs and duties 0.449 0.333 –0.099 0.025 0.461 –0.089

Performance-based pay: � = 0.7396

Employee financial participation 0.137 0.122 0.142 0.020 0.210 0.797

Provide employees’ ownership plan 0.109 0.130 0.148 0.059 0.005 0.786

Eigenvalue 9.678 2.144 1.544 1.356 1.305 1.189

Percentage of variance explained 33.374 7.393 5.323 4.677 4.502 4.099

commerce, transport and communication, finan-cial and business services and other services.Firms in the manufacturing sector accounted formost of the respondents (35.6%). The breakdownof industries is shown in Exhibit 1 below. In termsof ownership, local firms comprise the highestproportion (32.5%).

Exploratory Factor Analysis ResultsAs discussed, the strategic HRM system covers 36items. We undertook factor analysis to group theseitems into a smaller number of constructs. In thefinal varimax rotation, six factors (comprising 29items) with eigenvalue greater than 1.0 wereidentified. This criterion is in line with Kaiser’srule, which states that only factors with eigenval-ues greater than 1.0 are significant for analyticalpurposes. The six factors explained 59.4% of thetotal variance. More details, including theCronbach test results, are shown in Exhibit 2.

The category “broad job design” was discardedbecause all the variables that were supposed tomeasure the factor did not load together. A newfactor, which had three variables loaded on it,was renamed “team-based work” to replace thefactor. Consequently, Hypothesis 5 was changedto “team-based work” (instead of the initial broadjob design) and is positively related to firm per-formance (financial and HR).

The interitem correlation matrices for thescales used in the analysis are shown in Exhibit 3.The exhibit shows that there are significant rela-tionships among the various factors, lending sta-

tistical support to the positive relationshipbetween the specific strategic HRM variables andfirm performance stipulated in Hypotheses 1 to6. In particular, all the strategic HRM variableshave consistently higher correlations with a firm’sHR performance than financial performance.

Financial PerformanceThe regression results for the firm financial per-formance are shown in Exhibit 4. With the excep-tion of team-based work and performance-basedpay, all the other strategic HRM componentshave a positive impact on the financial perfor-mance of a firm. As such, the two are not includ-ed in the final analysis. Regression results revealthat the bundle of strategic HRM variables is alsopositively related to financial performance.However, the change in F ratio for the inclusion ofthis bundle, compared to the explanatory powerof using the control variables alone, is minimal.

Among the individual strategic HRM variables,the change in F ratio is the highest (∆F = 8.109)when performance appraisal is added into theinitial equation. Empowerment comes next (∆F =7.369), followed by selection (∆F = 6.730) andtraining (∆F = 4.454).

HR PerformanceThe regression results for the firm’s HR perfor-mance are shown in Exhibit 5. The finding revealsthat all the strategic HRM variables have a posi-tive impact on HR performance. As measured bythe change in F, empowerment exhibits the

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EXHIBIT 3Descriptive Statistics and Interitem Correlations of Variables

StandardVariable 1 2 3 4 5 6 7 8 Mean Deviation

1. Training 1.00 3.701 1.026

2. Selection 0.663*** 1.00 3.817 0.783

3. Empowerment 0.562*** 0.531*** 1.00 3.944 0.697

4. Performance appraisal 0.426*** 0.490*** 0.393*** 1.00 4.319 0.885

5. Team-based work 0.455*** 0.481*** 0.473*** 0.255** 1.00 4.166 0.953

6. Performance-based pay 0.387*** 0.390*** 0.382*** 0.98*** 0.327*** 1.00 2.550 1.399

7. Financial performance 0.320*** 0.294*** 0.276*** 0.243** 0.187** 0.246** 1.00 4.251 0.578

8. HR performance 0.480*** 0.452*** 0.456*** 0.393*** 0.410*** 0.370*** 0.605*** 1.00 4.453 0.721

Note: The numbers in the exhibit represent the correlation coefficients of the variables.**p < .01. ***p < .001.

largest incremental contribution (∆F = 35.868).Second is training (∆F = 35.165), followed byselection (∆F = 31.389). Performance appraisal,

which contributes the most to firm financial per-formance incrementally, is ranked fifth in its con-tribution to HR performance.

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Financial Performance

Equation Equation Equation Equation Equation Equation Equation EquationVariable 1 2a 3a 4a 5a 6a 7a 8a

Constant 3.325*** 2.849*** 2.435*** 2.262*** 2.348*** 2.823*** 3.225*** 2.265***(0.352) (0.404) (0.483) (0.508) (0.476) (0.475) (0.362) (0.504)

Joint ventures 0.337 0.330 0.391 0.253 0.325 0.344 0.313 0.306(0.330) (0.325) (0.326) (0.325) (0.322) (0.329) (0.331) (0.325)

Union dummy –0.093 –0.123 –0.154 –0.103 –0.151 –0.102 –0.108 –0.112(0.179) (0.181) (0.179) (0.181) (0.176) (0.179) (0.180) (0.184)

Industry: manufacturing 0.004 0.058 0.029 0.032 0.019 –0.029 0.003 0.022(0.157) (0.158) (0.155) (0.156) (0.154) (0.159) (0.158) (0.157)

ln size 0.195*** 0.153*** 0.176*** 0.195*** 0.195*** 0.191*** 0.188*** 0.161**(0.054) (0.056) (0.054) (0.054) (0.053) (0.054) (0.055) (0.056)

United States 0.525 0.508 0.481 0.381 0.440 0.502 0.468 0.403(0.329) (0.324) (0.324) (0.326) (0.322) (0.328) (0.333) (0.326)

Japan –0.381 –0.301 –0.319 –0.379 –0.331 –0.332 –0.354 –0.290(0.317) (0.315) (0.313) (0.311) (0.310) (0.318) (0.319) (0.314)

Europe 0.546 0.5420† 0.542† 0.414 0.590† 0.527 0.489 0.470(0.330) (0.326) (0.325) (0.327) (0.323) (0.332) (0.335) (0.330)

Singapore –0.113 –0.003 –0.046 –0.111 –0.094 –0.059 –0.126 –0.054(0.298) (0.297) (0.297) (0.293) (0.292) (0.300) (0.299) (0.296)

Training 0.167*(0.073)

Selection 0.247**(0.092)

Empowerment 0.283**(0.980)

Appraisal 0.227**(0.076)

Team-based work 0.122(0.077)

Performance-based pay 0.059(0.052)

Bundleb 0.321**(0.107)

Adjusted R2 0.153 0.175 0.186 0.189 0.192 0.156 0.153 0.188

F 4.783*** 4.928*** 5.211*** 5.290*** 5.437*** 4.438*** 4.348*** 5.181***

df 168 167 166 166 168 167 167 162

∆ adjusted R2 0.022 0.033 0.036 0.039 0.003 — 0.035

∆ F 4.453 6.730 7.369 8.109 0.594 — 6.983

EXHIBIT 4Regression Model of Firm Financial Performance

Note: Numbers in parentheses are standard errors.a. Statistics refer to the comparison of Equation 1.b. Excluding team-based work and performance-based pay.†p < .10. *p < .05. **p < .01. ***p < .001.

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EXHIBIT 5Regression Model of Firm Human Resource Performance

HR Performance

Equation Equation Equation Equation Equation Equation Equation EquationVariable 1 2a 3a 4a 5a 6a 7a 8a

Constant 4.331*** 3.474*** 2.959*** 2.764*** 3.029*** 3.103*** 4.091*** 2.335***(0.267) (0.284) (0.344) (0.360) (0.347) (0.331) (0.362) (0.329)

Joint ventures 0.020 0.002 0.121 –0.122 –0.002 0.046 –0.038 –0.031(0.251) (0.228) (0.232) (0.229) (0.233) (0.232) (0.240) (0.211)

Union dummy 0.271* 0.197 0.147 0.210 0.202 0.233† 0.237 0.134(0.137) (0.127) (0.128) (0.128) (0.127) (0.126) (0.131) (0.120)

Industry: manufacturing –0.060 0.064 –0.025 0.004 –0.036 –0.149 –0.062 –0.037(0.120) (0.112) (0.111) (0.110) (0.111) (0.112) (0.115) (0.102)

ln size 0.040 –0.035 0.021 0.045 0.042 0.030 0.017 0.000(0.040) (0.284) (0.038) (0.038) (0.037) (0.037) (0.039) (0.036)

United States 0.250 0.227 0.191 0.052 0.131 0.193 0.115 0.043(0.252) (0.229) (0.232) (0.231) (0.234) (0.233) (0.243) (0.213)

Japan –0.432† –0.304 –0.339 –0.439* –0.384† –0.323 –0.364 –0.266(0.245) (0.223) (0.226) (0.222) (0.227) (0.226) (0.234) (0.206)

Europe 0.251 0.233 0.234 0.039 0.306 0.286 0.138 0.189(0.252) (0.229) (0.232) (0.231) (0.233) (0.234) (0.243) (0.214)

Singapore –0.320 –0.149 –0.176 –0.355† –0.293 –0.197 –0.358 –0.199(0.228) (0.209) (0.212) (0.207) (0.211) (0.212) (0.218) (0.193)

Training 0.302***(0.052)

Selection 0.373***(0.066)

Empowerment 0.414***(0.070)

Appraisal 0.227***(0.056)

Team-based work 0.300***(0.054)

Performance-based pay 0.156***(0.038)

Bundle 0.321**(0.107)

Adjusted R2 0.119 0.270 0.257 0.274 0.246 0.256 0.196 0.381

F 3.885*** 7.970*** 7.505*** 8.049*** 7.211*** 7.503*** 5.593*** 12.205***

df 171 170 169 168 171 170 170 164

∆ adjusted R2 0.151 0.138 0.155 0.127 0.137 0.077 0.263

∆ F 35.165 31.389 35.868 28.803 31.304 16.281 69.682

Note: Numbers in parentheses are standard errors.a. Statistics refer to the comparison of Equation 1.†p < .10. *p < .05. **p < .01. ***p < .001.

In addition, the HR bundle (rather than indi-vidual HR components) contributes the mostexplanatory power to HR performance. Hence, allthe hypotheses are supported here. On the whole,our finding suggests that strategic HRM has amore positive role in explaining a firm’s HR per-formance than financial performance.

Conclusions and ImplicationsThis study examined the relationship betweenstrategic HRM variables and firm performance.As revealed in our analysis, the strategic HRMvariables are found to have a positive effect onorganizational outcomes, especially with respectto a firm’s HR performance—employee produc-tivity, job satisfaction and commitment. Thus,our evidence suggests that effective implementa-tion of key strategic HRM practices should beable to bring in higher levels of organizationalperformance.

Second, our hierarchical regression resultsshow a possibility that different aspects of perfor-mance could be affected by different strategicHRM variables. For a company promoting finan-cial performance, performance appraisal appearsto be the most important issue to tackle. On theother hand, companies interested in enhancingHR performance may emphasize the need forempowerment and training.

There are a number of limitations that presentopportunities for future research. One major lim-itation of this study is the relatively small samplesize. With larger samples, there will be a more bal-anced breakdown of companies according totheir countries of origin. In the present study, for-eign firms are dominated by Japanese companies.

Second, we have not investigated how organi-zational values affect HRM strategy and henceorganizational performance. One way to assessan organization’s HRM values is to examine itsmanagement philosophies and core values. Wecould then proceed to find out whether firms thatorganize human resource practices into systemsconsistent with their culture and organizationalstrategy do in fact perform better.

Future studies should aim to obtain a morerepresentative sample, investigate the possibilityof the HRM system as a mediator variablebetween HRM values and organizational perfor-

mance as well as use multiple channels of datacollection and consider longitudinal analysis.

AcknowledgmentThe authors would like to acknowledge financialsupport of the study from a research grant(RP991007) by the National University ofSingapore.

Notes1. Business Times, Singapore, July 23, 1999.2. Tichy, N. M., Fombrun, C. J., & Devanna, M. A.

(1982). Strategic human resource manage-ment. Sloan Management Review, 23, 47-61.

3. Ferris, G. R., Russ, G. S., Albanese, R., &Martocchio, J. J. (1990). Personnel/humanresources management, unionization, andstrategy determinants of organizational per-formance. Human Resource Planning, 13,215-227.

4. Cutcher-Gershenfeld, J. (1991). The impacton economic performance of a transforma-tion in workplace relations. Industrial andLabor Relations Review, 44, 241-260.

5. Arthur, J. B. (1994). Effects of human resourcesystems on manufacturing performance andturnover. Academy of Management Journal,37, 670-687.

6. MacDuffie, J. P. (1995). Human resource bun-dles and manufacturing performance:Organizational logic and flexible productionsystems in the world auto industry. Industrialand Labor Relations Review, 48, 197-221.

7. Huselid, M. A. (1995). The impact of humanresource management practices on turnover,productivity, and corporate financial perfor-mance. Academy of Management Journal, 38,635-670.

8. Delaney, J. T., & Huselid, M. A. (1996). Theimpact of human resource managementpractices on perceptions of organizationalperformance. Academy of ManagementJournal, 39, 949-968.

9. Huselid, M. A., Jackson, S. E., & Schuler, R. S.(1997). Technical and strategic humanresource management effectiveness as deter-minants of firm performance. Academy ofManagement Journal, 40, 171-188.

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10. Snell, S. A., & Dean, J. W., Jr. (1992). Integratedmanufacturing and human resource man-agement: A human capital perspective.Academy of Management Journal, 35, 467-504.

11. Bae, J., & Lawler, J. J. (2000). Organizationaland HRM strategies in Korea: Impact on firm

performance in an emerging economy.Academy of Management Journal, 43, 502-517.

12. Khandwalla, P. (1977). The design of organiza-tions. New York: Harcourt Brace Jovanovich.

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David Wan is an assistant professor of management in the Faculty of Business Administration at theNational University of Singapore. He earned his Ph.D. in business administration from the University ofManchester, United Kingdom. His research interests include the industrial relations climate, unioniza-tion, international HRM, interlocking directorates, strategic compensation and innovation management.He is also actively involved in the teaching of industrial relations modules at the Singapore Institute ofLabor Studies.

Chin Huat Ong is a research fellow at the Centre for Business Research & Development in the Faculty ofBusiness Administration at the National University of Singapore (NUS). He has a master’s degree from theNUS and is now working on his doctoral thesis on board of directors and corporate governance. Hisresearch interests include HRM, industrial relations, innovation management, industry studies, econom-ic forecasting and strategic management.

Victor Kok is an honors graduate from the Faculty of Business Administration at the National Universityof Singapore.

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