strategic frameworks for understanding employer participation in school-to-work programs

Strategic Management JournalStrat. Mgmt. J., 26: 523–539 (2005)

Published online in Wiley InterScience (www.interscience.wiley.com). DOI: 10.1002/smj.467

STRATEGIC FRAMEWORKS FOR UNDERSTANDINGEMPLOYER PARTICIPATION IN SCHOOL-TO-WORKPROGRAMS

FRANK LINNEHAN* and DONNA De CAROLISLeBow College of Business, Drexel University, Philadelphia, Pennsylvania, U.S.A.

The knowledge and skills inherent in human capital are increasingly recognized as the essenceof competitive advantage. Extending the emerging literature on capability building, this paperexplores the strategic decision of participating in school-to-work programs from the transac-tion cost and resource-based view of the firm. Using data from a national sample, we find thatboth strategic perspectives help to explain decisions to participate in school-to-work activi-ties. Our findings indicate that school-to-work programs and activities may be understood asinterorganizational strategies from a transaction cost view and evidence of a firm’s motivationto develop human capital to build competitive advantage from a resource-based view. Impli-cations for school-to-work public policy development in the United States and future researchare identified. Copyright 2005 John Wiley & Sons, Ltd.

It is strategically important for firms to develophuman capital, since this is the essence of com-petitive advantage. The escalating importance ofhuman capital in a knowledge-based economy hasbecome a major strategic concern for managers.Recent theoretical frameworks have emerged thatemphasize the importance of intangible assets suchas knowledge resources to competitive advantage(Grant, 1996a, 1996b; Kogut, 1996). The knowl-edge and skills generated from human capital havebeen identified as part of a firm’s core capabilities(Leonard-Barton, 1992, 1995) along with physicalsystems, managerial systems, and culture. Devel-oping human capital then is a managerial task thatprovides a resource that is firm specific and noteasily imitated, thus leading to competitive advan-tage.

Keywords: school-to-work transition; transaction costs;resource-based view*Correspondence to: Frank Linnehan, LeBow College of Busi-ness, Drexel University, 101 North 33rd Street, Academic Build-ing, Philadelphia, PA 19104, U.S.A. E-mail: [email protected]

Yet, cultivating firm capabilities is a complexmatter. The literature has examined capabilitydevelopment from several perspectives such asmarket entry decisions (Holbrook et al., 2000;Klepper and Simons, 2000); the role of foundersin the evolution of firm capabilities (Raff, 2000);acquisitions and the reconfiguration of capabili-ties (Karim and Mitchell, 2000); and adaptationand change in capabilities (Cockburn, Henderson,and Stern, 2000). However, many questions arestill unanswered with respect to the emergence oforganizational knowledge and skills that are partof human capital. In particular, there has beenlittle investigation into how capabilities such asknowledge and skills arise in organizations (Helfat,2000). An explanation of the emergence of firmcapabilities, such as the knowledge embedded inhuman capital, will inform the strategic issue ofwhy some firms have better resources and capabil-ities than others.

The purpose of this research is to extend thisemerging literature on capability building by speci-

Copyright 2005 John Wiley & Sons, Ltd. Received 23 January 2003Final revision received 10 January 2005

524 F. Linnehan and D. De Carolis

fically examining how firms source human cap-ital resources (Makadok, 2001). We do this byinvestigating an active supply of human capitalfor firms: school-to-work (STW) programs. Thissource of human capital has been overlooked in thetraditional management literature. Prior researchon STW programs, found primarily in the voca-tional and educational literatures, has focused onthe effects of these educational–business partner-ships on students (for example, Stern et al., 1997;Stern, Raby, and Dayton, 1992; Linnehan, 1996,2001). Compared to these student-centered stud-ies, there have been significantly fewer inquiriesexploring STW programs from the firm’s perspec-tive (Bailey, 1995; Bailey, Hughes, and Barr, 2000;Shapiro, 1999).

STW programs in the United States have largelyevolved from concerns over the adverse economicconsequences of an educational system that manyperceive has failed to adequately prepare youth forwork (Cappelli, Shapiro, and Shumanis, 1998). Inparticular, the focus of these programs has been onimproving the qualifications and work prepared-ness of high school students who have no plansto pursue post-secondary education. Firms havefaced a serious decline in the quantity and qualityof entry-level employees (Cappelli, 1995; NationalCommission on Excellence in Education, 1983).These shortages coincided with an increase in theknowledge and skill requirements for entry-levelpositions, as firms attempted to meet the chal-lenges of emerging global markets by enhancingworker productivity (Fortune, 1986; Goodridge,2001; Griffin and Fox, 2000; ABA Banking Jour-nal, 1990).

The 1994 School-to-Work Opportunities Act(STWOA) was intended to fund activities and pro-grams that would bring educational and businessinstitutions together in a partnership to promoteand enhance student learning in both academic andwork environments. The STWOA gave flexibilityto state and local governments to seek funding forany type of program that brought the academic andbusiness communities into a working partnership.This flexibility led to the development, implemen-tation, and growth of a multitude of activities,programs, and educational models all falling underthe STW rubric.

Researchers have generally concluded that eco-nomic concerns are the most common employerincentive to participate in STW programs and theseconcerns focus primarily on meeting the staffing

needs of the organization (Cappelli et al., 1998).This self-interest assumption has influenced thedevelopment of U.S. public policy toward school-to-work initiatives. For example, tax incentives areoften offered to motivate businesses to participatein STW programs. Alternatively, educators oftenviewed STW programs as a vehicle to improvethe quality of education overall. Educators andpublic policy-makers have assumed that businessinvolvement in education will improve the qualityof the educational systems by providing much-needed resources to the schools.

In this paper, we delve deeper into the motiva-tions of firms to participate in STW programs byapplying insights from transaction cost economics(TCE) and the resource-based view of the firm(RBV). From transaction cost theory, the adop-tion of school-to-work activities may be seen as anintegration of the human capital development pro-cess that traditionally took place outside a firm’sboundaries, that is, in the educational system. Assuch, decisions to participate in STW programsare consistent with structural decisions and bound-ary choices of a firm. The deterioration of thequality of education in the United States maybe viewed as a failure of the market to producea quality product (i.e., qualified, entry-level jobapplicants). This market failure has been the impe-tus for the creation of hybrid structures betweenschools and businesses that fall between marketsand hierarchies. As such, decisions to participatein STW programs are consistent with structuraldecisions and boundary choices of a firm. TheseSTW arrangements may represent interorganiza-tional strategies with the potential to create valuefor all the constituents (Tsang, 2000; Zajac andOlsen, 1993). From this perspective, the value ofengaging in STW programs from the employer sideoutweighs the cost considerations in interorganiza-tional strategies (Zajac and Olsen, 1993).

While recognizing the relevance of a marketfailures approach and the benefits of using TCE tobetter understand firm STW decisions, we proposethat the basis for firm decisions to participate inSTW programs may be understood not only asstructural choices, but resource-based decisions aswell. We base this strategic explanation on thepremise that firms compete on the basis of theircapabilities and, when these capabilities are rareand not easily imitated, they become determinantsof the firm’s competitive advantage (Barney, 1986,1991). From this perspective, participating in STW

Copyright 2005 John Wiley & Sons, Ltd. Strat. Mgmt. J., 26: 523–539 (2005)

Strategic Frameworks: School-to-Work Programs 525

programs may be explained as a firm’s desire tobuild unique human resource capabilities eitherwhile students are in school or by ensuring thatthere will be a steady, sufficient supply of qualifiedapplicants into the firm.

In the present study, then, we offer and testthese two perspectives of employer participationin STW: transaction cost economics and resource-based views. We discuss these theories and howthey are relevant to a firm’s school-to-work deci-sion in the next section.

THEORY AND HYPOTHESES

Transaction cost economics

Transaction cost economics is a framework thatis used to study economic exchanges betweentwo parties (Williamson, 1975). The theory viewsmarkets and hierarchies as structures (governancemechanisms) that regulate these exchanges(Williamson, 1975, 1981). Accordingly, if it ismore efficient for the firm to regulate an exchangethan the market, the firm will make a decision totransfer the economic process to within its ownboundaries. While markets and hierarchies repre-sent two extreme governance mechanisms, hybridstructures fall between these opposing ends ofthe continuum (Williamson, 1991). TCE hypothe-sizes that the most efficient (least costly) structurewill ultimately be used to regulate an exchange(Williamson, 1981, 1985).

An exchange or transaction occurs when a goodor service is transferred across a separate boundary(Williamson, 1981). In transaction cost economicterms, the school-to-work transition is a transac-tion that has a cost, as the student crosses intoa firm’s boundaries. These costs include the costof recruitment, selection, socialization, and subse-quent training of entry-level employees. Consistentwith TCE, the basis of the decision to take partin STW programs is the perception that condi-tions are such that it is more efficient for the firmto enter into agreements with educational institu-tions to develop high-quality applicants than to relyexclusively on the market mechanism.

If schools fail to provide applicants who are wellprepared for work, the cost to the firm of recruit-ment, selection, and training will increase, as qual-ified applicants become harder to find, select, andtrain. This is a signal to the firm of the mar-ket’s inefficiency and an alternative, more efficient

mechanism is needed to regulate this exchange,i.e., the preparation and hiring of new employees.As such, we hypothesize:

Hypothesis 1: There is a negative relationshipbetween market efficiency and a firm’s decisionto participate in STW activities. The more inef-ficient the market is in preparing students forwork (the poorer the quality of HS graduates),the more the firm will participate in STW activ-ities.

In the TCE framework, the key dimensions usedto describe transactions are frequency, uncertainty,and the specificity of the asset involved(Williamson, 1996). TCE predicts a direct rela-tionship between hierarchical governance mech-anisms and the frequency of transactions. Thegreater the frequency of the transaction, the morelikely it is that the firm will internalize the pro-cess. Increasing levels of transaction uncertaintyalso serve to increase the cost of transactions. Inthis event, it becomes more efficient for the firm totake over the market mechanism by regulating theexchange internally. Similarly, the more specificthe asset is to the firm, the more likely it becomesthat the firm is able to produce that asset moreefficiently (at lower costs) than the market, thusproviding an incentive to internalize the processand supersede the market mechanism. In each ofthese cases—high transaction frequency, environ-mental uncertainty, and firm-specific assets—thefirm is thought to possess inherent advantagesover the market in regulating economic exchanges(Williamson, 1981). Based on these premises, wepropose:

Hypothesis 2a: There is a positive relationshipbetween transaction frequency and participatingin STW activities. The more frequently a firmhires entry-level employees, the more the firmwill participate in STW activities.

Hypothesis 2b: There is a positive relationshipbetween transaction uncertainty and participat-ing in STW activities. The greater uncertainty afirm faces in hiring entry-level employees, themore a firm will participate in STW activities.

Hypothesis 2c: There is a positive relationshipbetween asset specificity and participating inSTW activities. The more specific an entry-level



employee’s skills are to a firm, the more a firmwill participate in STW activities.

TCE also incorporates certain behavioral assump-tions. In particular, individuals are assumed to actin their own self-interest or with opportunism. Thisassumption of opportunism accounts for the needfor monitoring systems and/or hierarchical struc-tures within organizations. As such, according toTCE, it is prudent to develop ex ante safeguardsfor transactions that are subject to ex post oppor-tunism (Williamson, 1996). If this assumption istrue, firms will establish linkages with schools anduse hierarchies to monitor and control the behaviorof entry-level employees, so as to ensure they actin the interest of the firm.

The degree to which a firm believes entry-level employees will act in their own self-interestwill influence its employee monitoring and con-trol practices. The more managers believe employ-ees will act opportunistically, the greater the needto monitor employees. While bureaucratic struc-tures or hierarchies may exert the most directcontrol over employee behavior (and may be cre-ated because managers believe it to be necessary),informal social structures may also be used as con-trol mechanisms (Ouchi, 1980). Rather than usingrules and regulations as mechanisms of controlin hierarchies, informal social structures use theshared beliefs and values of their members.

An example of organizational structure basedon an informal social structure is self-managedwork teams. Besides being able to respond morequickly to customer needs, these teams have thepotential of enhancing learning and commitmentto the organization (Wageman, 1997). As theseteams control their own behavior, advocating andusing self-managed work teams presupposes thatemployees will not act in their own self-interest.As such, the more managers believe opportunismis low, the more likely it is that self-managed workteams will be used in the organization. Alterna-tively, if managers believe opportunism is high,it is highly unlikely that the organization wouldinclude self-managed work teams. Since there is adirect, positive relationship between opportunismand hierarchical structures, we propose:

Hypothesis 3: There is a positive relationshipbetween employee opportunism and a firm’sparticipation in STW activities. The more a firm

uses self-managed work teams, the less the firmparticipates in STW partnership activities.

A capabilities perspective

As a complement to transaction cost economics,another way to understand firm decisions to par-ticipate in STW partnerships is to view the deci-sions as approaches to building inimitable humanresources. The RBV asserts that firms create valueby being more effective than their rivals at choos-ing resources (Makadok, 2001). From a Ricardianperspective of rent creation, a firm is able to cre-ate economic value by acquiring resources forless than their marginal productivity when usedin combination with its stock of other resources.Performance differences of firms are a functionof owning resources that have differential produc-tivity (Barney, 1986; Conner, 1991; De Carolis,2003; Montgomery and Wernerfelt, 1988; Werner-felt, 1984).

An extension of the RBV is the dynamic capa-bilities (DC) approach to firm behavior (Teece,Pisano, and Shuen, 1997). Under this framework,creating value is a function of building capabil-ities that yield competitive advantage. The DCapproach presents a Schumpeterian perspective ofrent creation, one that assumes that competitiveadvantage is elusive and that firms must contin-ually reinvent themselves to survive (Makadok,2001). Thus, dynamic capabilities are the ‘firm’sability to integrate, build, and reconfigure inter-nal and external competencies to address rapidlychanging environments’ (Teece et al., 1997: 516).The DC framework echoes a basic premise in theRBV—that the combination of firm-specific assetsheightens their level of imitability and yields acompetitive advantage. However, the process bywhich assets are acquired, built, and accumulatedinside firms is still relatively unexplored (Thomkeand Kuemmerle, 2002).

Related to both of these perspectives is theknowledge-based view of the firm (Kogut and Zan-der, 1992; Nonaka, 1994). This perspective accen-tuates knowledge as the most strategically impor-tant of the firm’s resources. Firms exist becausethey create, absorb, and apply knowledge in amore efficient and effective manner than markets(Kogut and Zander, 1992). Knowledge creation isan individual activity and the primary role of firmsis the application of existing knowledge to theproduction of goods and services (Grant, 1996a).



Under the assumption of individual knowledge, therole of the firm is to integrate specialized knowl-edge through organizational design. The manner inwhich firms accomplish this creates firm-specificcapabilities that impact competitive advantage.

STW programs can be thought of as channel-ing human capital into the organization, whichthen transforms this capital into firm-specific capa-bilities. Consistent with the above literatures, wesuggest that specific micro-level mechanisms ofcapability development are the forces that directand unleash individual knowledge into an organi-zational capability.

Assets that are valuable, rare, firm specific, inim-itable, and are organized by the firm to take advan-tage of them will lead to competitive advantage(Barney, 1991). Firm-specific assets are criticalin the successful implementation of a strategyas opposed to undifferentiated inputs. Firms mayacquire undifferentiated assets as substitutes for thedesired strategic input and then must adapt themat a cost to the specific intended use.

We focus here on human asset specificity and itsadaptation to strategic uses. With respect to humancapital, firms do not gain competitive advantagefrom generic human capital. Generic human cap-ital can be rented in the market. Firm-specifichuman capital is accumulated through on-the-joblearning (Dierickx and Cool, 1989). This is con-sistent with the RBV in that assets or resourcesthat are combined with other firm resources leadto superior returns.

Moreover, the knowledge-based view regardsknowledge as the ultimate basis for competi-tive advantage while simultaneously emphasiz-ing the criticality of how firms develop, coordi-nate, and integrate individual knowledge. Withinthe dynamic capabilities framework, Teece et al.(1997) describe processes as one element of creat-ing capabilities. Processes refer to the manner inwhich tasks are accomplished; they are sometimescalled routines or patterns of learning (Nelson andWinter, 1987; Teece et al., 1997).

Learning is a dynamic process that supportscapabilities (Teece et al., 1997). Although indi-vidual skills are pertinent, their value dependson their deployment. Learning requires commoncodes of communication and joint contributionsto the understanding of complex problems (Teeceet al., 1997). For example, training programs arean organizational mechanism that enhances learn-ing. Firms that engage in training programs for

all levels of personnel may be viewed as activelyinvesting in developing unique knowledge, tai-lored for that firm’s strategies. Thus, organizationalmechanisms for employee learning, such as train-ing, job rotation, empowerment and the like, maybe viewed as a method for building firm-specifichuman capital.

Related to the incentive to build firm-specifichuman capital is the likelihood that companiesdesire to recruit that human capital. School-to-work activities provide an opportunity for firms togain access to a continuous pool of human capital.A school-to-work program as a source of humancapital has many advantages. Firms can initiaterelationships with potential employees, can assessindividual abilities, and can establish communityrelationships to ensure future pools of capital.

Hypothesis 4: There is a positive relationshipbetween building firm-specific human capitaland the extent firms participate in STW activi-ties. The more firm-specific training offered, themore a firm will participate in STW activities.

Barney’s (1986) concept of strategic factor mar-kets suggests that the required resources for afirm’s strategy may be bought and sold in the mar-ket for those resources. The concept of strategicfactor market has significant ramifications for strat-egy implementation in that the size of the returns toany given strategy depend on the cost of resourcesnecessary to implement them. According to theRBV, companies want to acquire resources whosecost to implement those resources in strategies isless than their economic value—that is, firms areexploiting competitive imperfections in strategicfactor markets (Barney, 1986).

School-to-work initiatives are a way for firmsto acquire human capital at a relatively inexpen-sive cost, yet the deployment of this resource couldbring potential returns in excess of that cost. How-ever, firms would not want to acquire a resourcethat does not have that valuable potential. There-fore, how firms perceive how well schools in theirregional environment prepare youth for employ-ment may impact whether or not they participatein this factor market. An element of a firm’s posi-tional assets are the institutions that surround them,including educational systems (Teece et al., 1997).As a component of this institutional environment,local and regional schools represent a factor market



for human capital. If companies perceive surround-ing educational institutions as producing qualifiedindividuals with a capacity for learning, then theywould be inclined to participate in that factor mar-ket and acquire this resource for future use—eitherby itself or in combination with other resources.

Hypothesis 5: There is a positive relationshipbetween the quality of a firm’s factor market forhuman capital and STW participation. The morequalified entry-level candidates are for work, themore a firm will participate in STW activities.

Physical resources such as plant, equipment, andtechnical systems can determine a firm’s compet-itive advantage. Physical systems are an elementof core capabilities (Leonard-Barton, 1992, 1995;Teece et al., 1997). These resources are part ofthe strategic positioning of firms. Accumulation ofcritical physical resources builds asset stocks. Infact, it has been suggested that a key aspect ofstrategy creation is making choices about strategicexpenditures so as to accumulate competitive andinimitable resources (Dierickx and Cool, 1989).Companies eager to maintain competitive physicalsystems would necessarily require as a comple-mentary asset the human capital to operate thesesystems. There is an interconnectedness of assetstocks—that is, the accumulation and deploymentof one stock is related to the level of another com-plementary stock (De Carolis and Deeds, 1999;Dierickx and Cool, 1989). To the extent that newphysical systems are an indication of building aninimitable asset stock, then school-to-work pro-grams may be viewed as one type of complemen-tary asset. Companies that exhibit a strategy ofquality production or efficiency through their phys-ical systems are likely to be involved in school-to-work initiatives so as to build the complementaryassets required.

Hypothesis 6: There is a positive relationshipbetween a firm’s inimitable asset stock and par-ticipating in STW activities. The greater the firmhas invested in new physical assets relative totheir total physical assets, the more the firm willparticipate in school-to-work activities.

The term ‘dynamic capabilities’ explicitly con-notes change. The DC framework suggests thatcompetencies can be renewed to achieve con-gruence with the changing business environment.

The framework also emphasizes the role of man-agers in adapting and reconfiguring organizationalskills, resources, and functional competencies tomatch the contingencies of a dynamic environment(Teece et al., 1997).

At any point in time, companies must be pre-pared and able to reconfigure their asset structureto adapt to changing environmental demands (Lan-glois, 1994; Teece et al., 1997). In order to dothis, firms must relentlessly scrutinize the environ-ment and adopt new innovations and best practices.One of the most effective ways of doing this isthrough benchmarking (Teece et al., 1997). Bench-marking is an organizational process that maintainsparity with competitors and cultivates continuousimprovement.

Companies who practice benchmarking willadopt new procedures and practices and, accord-ingly, require new skills. Existing employees canlearn new skills but firms can also seek a fresh tal-ent pool so that it can more easily manipulate themto learn a different or altered skill set. School-to-work programs make available a fresh talent poolthat can be adapted to changing practices.

Hypothesis 7: There is a positive relationshipbetween reconfiguring organizational practicesand participating in STW activities. The practiceof benchmarking and the extent a firm partici-pates in school-to-work activities will be posi-tively related.

Similar to the above position regarding bench-marking and school-to-work, we can postulate arelationship between changing employee skills setsand school-to-work. Knowledge is the underlyingcomponent of firm success and firms exist to cre-ate, recombine, and apply their knowledge (Kogutand Zander, 1992). Knowledge is dynamic givena changing internal and external environment. Therequired knowledge set for a company will change.As skill requirements transform, the firm’s knowl-edge base must be updated as well.

School-to-work programs may be consideredavenues for skill reconfiguration. An influx offresh ideas and malleable talent to the companywill accommodate a company’s need for changingskills.

Hypothesis 8: There is a positive relationshipbetween skill reconfiguration and the extent afirm participates in school-to-work activities.



Firms that have experienced increases in skilllevel requirements for entry-level employees willparticipate in more STW activities than firms inwhich skill level requirements have decreased orremained the same.

METHOD

Data used to test our hypotheses were taken fromthe public use file of the 1997 National EmployerSurvey (NES). The 1997 NES was part of a long-term research project originated by the NationalCenter on the Educational Quality of the Work-force (EQW). This project was intended to identifyemployment and educational issues from employerperspectives (Shapiro, 1999). The 1997 survey(NES-II) was co-sponsored by the National Cen-ter for Postsecondary Improvement and the Con-sortium for Policy Research in Education. It wasa follow-up to previous surveys and specificallyexplored employer participation in school-to-workpartnerships. Similar to earlier surveys from EQW,the 1997 phone survey was administered by theU.S. Bureau of the Census and used computer-assisted telephone interviewing to collect the data.

In the NES-II survey, the Census Bureau con-tacted 6971 private employers from across theUnited States. Of those contacted, 5400 establish-ments agreed to participate in the survey. Thesurvey excluded public sector, not-for-profit orga-nizations, corporate headquarters, and establish-ments with fewer than 20 employees. The overallresponse rate was 78 percent for partially com-pleted interviews and 59 percent (approximately4100) for completed interviews. The public usedatabase, which was used in the present study,is a stratified sample based on two-digit industrycode and establishment size (number of employ-ees) that consists of 3081 responses,1 all madeat the establishment level. Manufacturing estab-lishments were oversampled in the study (59.5%of all usable responses were from manufactur-ing concerns), as were larger establishments (66%of the responses were from establishments withmore than 100 employees). In the manufacturingsector, the respondent to the survey was the plant

1 This dataset is available on the Web for research purposes(http://www.thelearningalliance.info/Publications.php). The ini-tial sample had oversampled establishments in five states forother sponsor purposes. The public use file corrects for thisoversampling.

manager; for responses from all other sectors, itwas the local manager (Cappelli et al., 1998).

Measures

School-to-work activities

Previous research has looked at the intensity ordegree to which firms offer work-based learn-ing activities or establish linkages with schools(Bailey et al., 2000; Shapiro, 1999). The 1997NES included 20 such activities that representthese linkages. These activities or programs rangedfrom establishing a formal partnership arrangementto such activities as providing internships, youthapprenticeships, student mentoring, participatingin school-based enterprises, developing academiccurricula, sponsoring student visits to the work-place and/or employee visits to schools. Employerswere asked if they would sponsor or participate ineach of these activities.2 Consistent with the humanresource literature of high-performance work prac-tices (e.g., Guthrie, 2001; MacDuffie, 1995; Way,2002), we added the number of activities eachemployer offered to create a composite intensityindex. The larger the employer’s score on thisindex, the more STW activities it provided thatconnected work to school. This measure is sim-ilar to that used by Bailey et al. (2000) and wasinternally consistent (α = 0.87).

Measures common to both transaction cost andresource-based theories

Three variable measures in the RBV are identicalto measures of variables in transaction cost the-ory: (1) firm-specific training (asset specificity inTCE and building firm-specific human capital inRBV); (2) quality of entry-level employees (mar-ket efficiency in TCE and the factor market forhuman resources in RBV); and (3) increasing skillrequirements of entry-level positions (asset speci-ficity in TCE and skill reconfiguration in RBV).

The NES asked questions about training pro-grams conducted in the establishment. These pro-grams ranged from non firm-specific skills trainingsuch as improving teamwork or problem-solvingskills and providing remedial skills in literacyand arithmetic, to firm-specific instruction such astraining in sales, new equipment and the safe use

2 The responses were recoded from 1 = Yes, 2 = No, to 1 = Yes,0 = No.



of equipment and tools. We used responses to theitems concerning firm-specific training as one ofour measures of asset specificity in TCE and forbuilding firm-specific human capital in the RBV.

An index of the training given to three typesof employees—(1) production, (2) office/clerical/sales/customer service, and (3) technical/technicalsupport—was calculated to assess the degree towhich the establishment engages in firm-specifictraining. This index is the mean of the responses(weighted by the percentage of the type of employ-ees in the establishment) to three items (i.e., 1 =Yes, 0 = No, multiplied by the percentage of theestablishment’s employees in each of the three cat-egories): ‘Which of the following areas did (typeof employees) cover during their training: (1) salesand customer service (e.g., 1 = Yes, 0 = No mul-tiplied by the percentage of sales and customer ser-vice employees in the establishment); (2) trainingin the use of computers or new equipment; and(3) training on the safe use of equipment andtools.’ As such, the training composite index is theaverage percentage of the establishment’s employ-ees across each of three employee categories thatreceive firm-specific training.

We measured market efficiency (TCE) and thequality of the factor market for human resources(RBV) as the mean of the responses to threeitems assessing the quality of recent high schoolgraduates: ‘Based on your experience with hiringtheir graduates, how would you rate your localhigh schools’ overall performance in preparing stu-dents for work in your establishment?’ The twoother questions were created from this item bysubstituting ‘technical institutes’ and ‘communitycolleges’ for ‘high schools.’ Responses to thesequestions were made on a five-point scale, rang-ing from 1 = Unacceptable to 5 = Outstanding.Respondents indicating the establishment had nothired any graduates of local high schools, technicalinstitutes, or community colleges, or that no onefrom these institutions had applied were eliminatedfrom the analysis. Chronbach’s alpha for this scalewas moderate (α = 0.68).

A second measure of asset specificity in TCEand the measure of skill reconfiguration in theRBV was the response to an item assessing thechange in the skill level of entry-level positionsover the last 3 years: ‘During the last 3 years,have the skills required to perform (the positiontitle the respondent had identified) at an acceptablelevel increased, decreased or remained the same?’

We created a dummy variable from this responseindicating an increase in skills (1 = increased, 0 =decreased or remained the same).

Unique transaction cost measures

We based our measure of transaction uncertaintyon theories of employer search models found inlabor economics (Gorter and van Ommeren, 1999;van Ours and Ridder, 1992). In these models,employers are seen as adopting search strategiesdue to their lack of complete control over hiringnew employees and the uncertainty they face inthe time in which it takes to find new employ-ees to fill vacancies (van Ours and Ridder, 1992).Accordingly, we measured transaction uncertaintyas the average number of weeks the establishmenttook to fill an entry-level position. The longerit takes to hire entry-level employees, the moreuncertain this process would be for the establish-ment. We measured transaction frequency as a ratioof the number of 18- to 25-year-old employeeshired over the last 2 years to the total number ofemployees in the establishment. Total number ofemployees in this ratio was calculated from theranges that were used to measure the size of theestablishment (fewer than 50 = 25, 50–99 = 75,100–249 = 175, 250–999 = 650, 1000 or more =2000).

We used the response to the question ‘Whatpercentage of non-managerial and non-supervisoryemployees is currently involved in self-managedteams?’ to measure the extent to which firmsbelieved employees engage in opportunistic behav-ior. Establishments that utilize these teams exten-sively are less likely to believe employees engagein this type of behavior.

Unique RBV measures

An establishment’s investment in new physicalassets is an indicator of its imitable asset stock.As such, our measure for this variable is the logof the establishment’s total assets that are lessthan 4 years old. We measured asset reconfigu-ration from the response to an item concerningthe establishment’s use of benchmarking practices:‘Has your establishment participated in any bench-marking programs that compare your practices andperformances with other organizations?’3

3 Response was recoded from the original survey into a dichoto-mous variable (1 = Yes, 0 = No).



Controls

Company size is significantly related to the imple-mentation of work-based activities and participa-tion in STW partnerships (Bailey et al., 2000),the larger the company, the more likely it is toparticipate in STW. The NES II included fivedummy variables (1 = Yes, 0 = No) to designatethe establishment’s size (fewer than 50 employ-ees, 50–99 employees, 100–249, 250–999, and1000 or more). The ‘fewer than 50 employees’category was omitted from the analysis and actedas the referent category. Given that manufacturingestablishments were oversampled from the popula-tion, a dummy variable (1 = Manufacturing sector,0 = All other) was also used as a control in theanalyses.

The high-performance work systems (HPWS)literature (Cappelli and Neumark, 1999; Guthrie,2001; Way, 2002) has identified human resourcepractices whose purpose is to develop human cap-ital. Many of these practices are different from theTCE and RBV measures. Given their importancein the HPWS literature, we also controlled for thepresence of these work practices in our analy-ses. Following the methodology of Way (2002),we calculated a unitary index for HPWS by sum-ming the scores of seven work practice compo-nents (maximum possible score: 7). These compo-nents are the same as those in the HPWS studies,which have also used the NES-II data (Cappelliand Neumark, 1999; Way, 2002). They include:extensiveness of staffing (a composite of fiveselection devices); group-based performance pay(employer contribution to a stock option or profitsharing plan); percentage of non-managerial/non-supervisory employees in job rotation; percent-age of non-managerial/non-supervisory employeesinvolved in regular meetings to discuss work-related issues (Way, 2002); and the percentage ofmanagers and production/non-supervisory person-nel who use computers in their jobs (Cappelli andNeumark, 1999).4

Since employee turnover may have an impacton the ability of the selection process or STWactivities to change the skill set of its workforce,this variable was also included as a control andmeasured as the sum of two items from the NES-II:the percentage of permanent workforce employees

4 Way’s (2002) index also included the pay level of front-lineemployees. We were not able to include this component in ourindex as the public use NES-II sample eliminated this response.

who left voluntarily (e.g., retired or quit) andinvoluntarily (e.g., fired or laid off) during thatsame time period. Similarly, we also controlledfor the establishment’s use of contingent workers(1 = Yes, 0 = No) since this source of employeesmay help to enhance the talent pool and be relatedto the establishment’s decision to participate inSTW activities.5

ANALYSIS STRATEGY

Descriptive statistics and correlations between allvariables were calculated initially. Hypotheseswere tested with five OLS regression models. Thefirst model included control variables only (size,manufacturing establishment, human resource pra-ctices, contingent employees and turnover). Thesecond model adds variables that are common toboth the TCE and RBV perspectives. These vari-ables are training (TCE: asset specificity; RBV:building firm-specific capital), quality of schoolgraduates (TCE: market efficiency; RBV: qualityof factor market for human resources), and theincrease in skill level requirements (TCE: assetspecificity; RBV: skill reconfiguration. A TCE-only model was tested next, which added the aver-age time to fill a position (uncertainty), the percent-age of new hires at lower levels (frequency), andthe percentage of employees in self-managementteams (opportunism). This was followed by anRBV-only model, which included the benchmark-ing measure (asset reconfiguration) and the per-centage of assets less than 4 years old (inimitableasset stock). Finally, reflecting the complementar-ity of the two theories, an all-inclusive model wastested.

RESULTS

Table 1 shows the means, standard deviations, andcorrelations between all variables in the study.As expected, establishment size is significantly,positively related to the number of STW activi-ties offered, thus necessitating the dummy vari-ables inclusion in the regression models. This wasalso true for the other control variables. Therewas a significant relation between school-to-work

5 We wish to thank an anonymous reviewer for bringing theimportance of these last three control variables to our attention.



Tabl

e1.

Des

crip

tive

stat

istic

san

dpa

irw

ise

corr

elat

ions

a

Var

iabl

eM

ean

S.D

.1

23

45

67

89

1011

1213

1415

1617

1.50

–99

empl

oyee

s0.

170.

372.

100

–24

9em

ploy

ees

0.19

0.39

−0.2

2∗∗

3.25

0–

999

empl

oyee

s0.

300.

46−0

.29∗∗

−0.3

2∗∗

4.10

00or

mor

eem

ploy

ees

0.17

0.38

−0.2

0∗∗−0

.22∗∗

−0.3

0∗∗

5.M

anuf

actu

ring

indu

stry

0.59

0.49

−0.0

6∗∗−0

.06∗∗

0.20

∗∗0.

06∗∗

6.H

RM

prac

tices

2.96

1.16

−0.0

7∗∗−0

.02

0.08

∗∗0.

07∗∗

−0.0

47.

Use

ofco

ntin

gent

empl

oyee

s0.

660.

47−0

.11∗∗

−0.0

10.

14∗∗

17∗∗

0.15

∗∗0.

13∗∗

8.E

mpl

oyee

turn

over

21.4

27.9

0.02

0.02

−0.0

20.

01−0

.12∗∗

−0.0

6∗∗−0

.03

9.Fi

rm-s

peci

fictr

aini

ng11

.97.

2−0

.05∗∗

0.01

0.07

∗∗0.

10∗∗

−0.0

4∗0.

24∗∗

0.10

∗∗0.

0110

.E

valu

atio

nof

scho

olgr

adua

tes

3.2

0.59

−0.0

5∗∗0.

010.

030.

06∗∗

−0.0

20.

07∗∗

0.00

−0.0

6∗∗0.

08∗∗

11.

Incr

ease

insk

illre

quir

emen

ts0.

510.

50−0

.07∗∗

−0.0

20.

06∗∗

0.08

∗∗0.

030.

28∗∗

0.14

∗∗−0

.10∗∗

0.17

∗∗0.

07∗∗

12.

Tim

eto

fill

apo

sitio

n3.

193.

1−0

.02

−0.0

2−0

.05∗

0.05

∗−0

.10∗∗

0.19

∗∗0.

06∗∗

−0.1

4∗∗0.

09∗∗

0.00

0.12

∗∗

13.

%of

new

hire

sat

low

erle

vels

0.22

0.71

0.04

0.01

−0.1

0∗∗−0

.09∗∗

−0.0

4∗−0

.07∗∗

−0.0

5∗0.

18∗∗

−0.0

2−0

.05∗

−0.0

6∗∗−0

.10∗∗

14.

%se

lf-m

anag

edte

ams

16.1

29.9

0.02

−0.0

20.

00−0

.01

0.04

0.26

∗∗0.

06∗∗

−0.0

6∗∗0.

10∗∗

0.02

0.13

∗∗0.

11∗∗

0.00

15.

Ben

chm

arki

ng0.

330.

47−0

.08∗∗

−0.0

4∗0.

07∗∗

0.20

∗∗0.

05∗

0.22

∗∗0.

18∗∗

−0.0

7∗∗0.

21∗∗

0.04

∗0.

18∗∗

0.11

∗∗−0

.08∗∗

0.13

∗∗

16.

%as

sets

less

than

4ye

ars

18.9

2.4

−0.2

1∗∗−0

.11∗∗

0.23

∗0.

39∗∗

0.19

∗∗0.

12∗∗

0.14

∗∗−0

.08∗∗

0.21

∗∗0.

06∗

0.16

∗∗0.

07∗∗

−0.0

5∗0.

000.

26∗∗

17.

Num

ber

ofST

Wac

tiviti

es4.

84.

3−0

.17∗∗

−0.0

90.

13∗∗

0.34

∗∗0.

09∗∗

0.30

∗∗0.

22∗∗

−0.1

0∗∗0.

29∗∗

0.14

∗∗0.

25∗∗

0.12

∗∗−0

.07

0.13

∗∗0.

38∗∗

0.39

∗∗

aN

sra

nge

from

2078

to30

81∗p

<0.

05;

∗∗p

<0.

01



activities with both the HRM measure and themanufacturing dummy variable, as well as betweenthese activities with the percentage of contingentemployees and the measure of employee turnover.There is also a significant, positive relationshipbetween the establishment’s evaluation of howwell schools prepare their graduates and the STWactivity variable. This is consistent with the RBV,as firms may be creating these linkages to fun-nel high-quality, human capital into their orga-nizations, but is inconsistent with a market fail-ure perspective. Other significant correlations withthe dependent variable include firm-specific train-ing, the use of benchmarking and the perceivedincrease in skill requirements at the entry-levelposition.

Table 2 shows the results of the regression anal-yses and Table 3 summarizes the hypotheses andresults. Large establishments (over 100 employ-ees) participated in more STW activities thansmall establishments with fewer than 50 employ-ees. However, the control variable for the manu-facturing industry was not significant in any of themodels.6

6 The public use, NES-II dataset includes 21 industry dummyvariables. At the suggestion of an anonymous reviewer, we alsoran regression models which included 20 of these variables. Thesignificant levels of the theory variables did not differ in thesemodels from those that are reported in this table.

Contrary to Hypothesis 1, which predicted anegative relationship between quality of the prepa-ration schools give their graduates and STW activ-ities, there is a positive relationship in each modelbetween the establishment’s evaluation of howwell local high schools, technical institutes, andjunior colleges prepare their graduates with STWactivities.

There is no support for Hypothesis 2a, whichpredicted a positive relation between hiring fre-quency and participating in STW activities.Hypothesis 2b predicted that STW activities wouldbe positively related to uncertainty. In supportof this hypothesis in the TCE model, there wasa positive relation between the time it takes tofill a position with STW participation. This rela-tion remained positive in the inclusive model aswell, but was no longer significant. The coef-ficients in both the TCE and inclusive regres-sion models for the increase in skill level vari-able and firm-specific training are also significant,supporting Hypothesis 2c. This hypothesis pre-dicted a positive relationship between STW activ-ities and asset specificity. Contrary to the expec-tation of Hypothesis 3, that employee participa-tion in self-managed work teams would be nega-tively related to STW activities, the coefficient forthis variable was significantly, positively relatedto STW.

Table 2. Summary of constructs, theories, measures, predictions, and resultsa

Construct Theory Measure/variable name Hypothesis Predicted Results

Market efficiency TCE Evaluation of high schoolgraduates

1 Negative Positive

Transaction frequency TCE Hiring frequency 2a Positive Not significantTransaction uncertainty TCE Time to fill position 2b Positive PositiveAsset specificity TCE Increase in employee skill

levelsFirm-specific training

2c Positive Positive

Opportunism TCE % of employees inself-managed workteams

3 Negative Positive

Building firm-specificcapital

RBV Firm-specific training 4 Positive Positive

Factor market forhuman resources

RBV Evaluation of high schoolgraduates

5 Positive Positive

Inimitable asset stock RBV % of assets less than4 years old

6 Positive Positive

Asset reconfiguration RBV Benchmarking 7 Positive PositiveSkill reconfiguration RBV Increase in employee skill

levels8 Positive Positive

a TCE, transaction cost economics; RBV, resource-based view.



Table 3. Results of hierarchical OLS regression analysesa

Model Model IControl only

Model IIBaseline

Model IIITCE

Model IVRBV

Model VInclusive

Constant 0.12 (0.258) −2.20∗∗ (0.479) −2.45∗∗ (0.508) −2.35∗∗ (0.565) −2.55∗∗ (0.572)Controls50–99 employees 0.55∗ (0.239) 0.39 (0.254) 0.47 (0.265) 0.23 (0.292) 0.31 (0.293)100–249 employees 1.14∗∗ (0.233) 0.87∗∗ (0.248) 0.99∗∗ (0.261) 0.67∗ (0.286) 0.78∗∗ (0.288)250–999 employees 2.53∗∗ (0.221) 2.16∗∗ (0.237) 2.33∗∗ (0.252) 1.79∗∗ (0.277) 1.95∗∗ (0.282)1000 or more 4.79∗∗ (0.247) 4.32∗∗ (0.265) 4.48∗∗ (0.281) 3.63∗∗ (0.316) 3.79∗∗ (0.321)Manufacturing

establishment−0.02 (0.147) 0.03 (0.156) 0.05 (0.164) 0.01 (0.180) 0.03 (0.181)

HRM practices 0.88∗∗ (0.061) 0.66∗∗ (0.068) 0.59∗∗ (0.073) 0.54∗∗ (0.078) 0.49∗∗ (0.081)Use of contingent

employees0.77∗∗ (0.155) 0.68∗∗ (0.164) 0.63∗∗ (0.172) 0.48∗∗ (0.189) 0.45∗ (0.189)

Employee turnover −0.01∗∗ (0.003) −0.01∗∗ (0.003) −0.01∗∗ (0.003) −0.01∗∗ (0.003) −0.01∗∗ (0.003)Common RBV and TCE

variablesTraining 0.05∗∗ (0.007) 0.05∗∗ (0.008) 0.04∗∗ (0.009) 0.04∗∗ (0.009)Evaluation of high school

graduates0.59∗∗ (0.125) 0.60∗∗ (0.130) 0.57∗∗ (0.143) 0.58∗∗ (0.143)

Increase in skillrequirements

0.93∗∗ (0.156) 0.88∗∗ (0.163) 0.75∗∗ (0.180) 0.72∗∗ (0.180)

Unique TCE variablesTime to fill a position 0.07∗ (0.026) 0.05 (0.028)Entry-level hiring frequency 0.21 (0.112) 0.22 (0.123)% of employees in

self-managed teams0.01∗∗ (0.003) 0.01∗ (0.003)

Unique RVB variablesBenchmarking 1.96∗∗ (0.191) 1.92∗∗ (0.192)% of assets less than

4 years old0.03∗ (0.014) 0.03∗ (0.014)

Adjusted R2 0.26 0.29 0.30 0.33 0.34F 123.4∗∗ 91.15∗∗ 67.51∗∗ 67.24∗∗ 55.52∗∗

N 2841 2420 2218 1735 1735

a Non-standardized, estimated coefficient with standard error below in parentheses.∗ p < 0.05; ∗∗ p < 0.01

Based on the RBV, Hypothesis 4 predictedthat STW activities would be positively related tobuilding firm-specific human capital. This hypoth-esis was supported, as the coefficients for the train-ing measure were significant in all the models.Hypothesis 5, which predicted a positive relationbetween STW activities and quality of graduatepreparation, was also supported in all the models.Hypothesis 6, which predicted a positive relation-ship between investment in new physical assetsand STW activities, was also supported. Consistentwith the RBV and Hypothesis 7, benchmarkingwas also positively related to the degree to whichit provides STW activities. Finally, Hypothesis 8was supported. Skill reconfiguration, measured byincreases in skill requirements, was significantly,positively related to STW activities.

DISCUSSION

The purpose of this study was to delve deeperinto employers’ motivations to participate in STWinitiatives by applying the principles of transactioncost and resource-based theories. From TCE, themarket failure perspective is consistent with theview of other researchers in this area, and isimplicit in public policy—that firms attribute theshortage of qualified entry-level job applicants toan educational system that has failed to adequatelyprepare the non-college bound student for employ-ment (Bailey, 1991; Lewis et al., 1998). Alterna-tively, RBV suggests that employers’ motivation toparticipate in STW is based on the ultimate devel-opment of human capital for competitive advan-tage.



Under TCE assumptions, decisions to partici-pate in school-to-work initiatives may be seen asvertical integration decisions, taking over some ofthe responsibilities that were once the sole respon-sibility of the educational system. To test this,we examined the relationship between employerperception of graduates and employer participationin STW. Our results indicate that the firm’s eval-uation of how well graduates were prepared foremployment was positively related to STW activ-ities and participation. Thus, the TCE perspectiveis not fully supported here.

Some support for the transaction cost view wasfound, however, particularly in the positive relationbetween asset specificity (firm-specific training andincreasing skill levels) and STW. In addition, in theTCE model, positive relations were found betweenSTW and the two other dimensions that describetransactions, frequency (percentage of new hires atlower levels in the organization), and uncertainty(average number of weeks it takes to fill a posi-tion).

From the RBV view, school-to-work programsrepresent a way for firms to access labor that canbe critical in the development of capabilities. Inparticular, this investigation contends that theseperspectives provide an explanation of why firmsengage in school-to-work programs—to improvetheir internal capabilities.

We hypothesized that if employers perceivedstudents as well prepared they would be motivatedto participate in STW. We justified this by specu-lating that STW programs provide a way for firmsto source potentially valuable human capital. Inter-estingly, we found a positive relation between thefirm’s evaluation of how well schools prepare theirgraduates and school-to-work. Perceived quality oflabor is positive and significant in the models. Con-trary to the market failure perspective, this findingsuggests that firms will participate more intenselyin school-to-work activities when the labor pool isconsidered exceptionally good. This represents acase of firms choosing resources (Makadok, 2001)that they believe can be manipulated, developed,and transformed into organizational competencies.Therefore, they will invest more in school-to-workactivities to develop these competencies as they arestarting with a more qualified tool of raw talent.

We further predicted a positive relation betweenschool-to-work activities and actively buildingfirm-specific human capital through on-the-job

training and learning. The models showed posi-tive and significant relationships between trainingprograms and school-to-work. This supports thedynamic capabilities approach to firm behavior,which predicts that factors of production are orga-nized and coordinated by the firm in ways that can-not be done through a market mechanism. Theseresults may imply that not only are school-to-workprograms important as a labor input, but they workin conjunction with training programs to produceinimitable firm-specific assets.

Again, consistent with the resource-based anddynamic capabilities views, the models show apositive and significant relation between chang-ing skills and school-to-work intensity. Firms areactively engaged in seeking labor sources, as thelevel of skills needed to compete increases. Thepractice of benchmarking is also positive andsignificant with school-to-work in both models.Again, this speaks to the issue of reconfiguration offirm skills. Those firms that watch, evaluate, andimplement new practices in the interest of qual-ity, efficiency, and productivity are also looking toschool-to-work to acquire the resources to keep upwith the new practices.

Our findings suggest that the ‘make’ or ‘buy’ ormarket failures perspective may not fully uncoverthe reasons why employers decide to participatein STW. Rather, it may be more constructiveto consider the basis of these decisions to be avalue-creating, interorganizational strategy (Zajacand Olsen, 1993). Zajac and Olsen (1993) haveproposed a transactional value approach that isuseful in understanding such interorganizationalstrategies as STW alliances. From this perspective,STW partnerships are best considered a type ofinterorganizational alliance with the potential oflong-term value creation.

The main goal of these hybrid organizationalstructures is not the minimization of costs, butthe ultimate creation of value. We believe thatour results support the implications of this the-ory. For employers, the pay-off is the develop-ment of firm-specific human capital capabilitiesthat may contribute to competitive advantage, con-sistent with the RBV approach and empiricallysupported here. For the educational system, thepay-off is the advancement of graduates into jobtraining and perhaps permanent employment.

With respect to the costs of this interorganiza-tional alliance, we did not address the ‘negative’effects of human capital. Throughout this paper,



we have assumed that human capital is a positivebenefit to the firm, that is, that generally, humancapital can be a source of competitive advan-tage. An alternative view of human capital andits relationship to competitive advantage is pro-posed by Coff (1997, 2002), who suggests thathuman capital, owing to its specificity, social com-plexity, and causal ambiguity, may entail negativeconsequences, in particular, turnover, opportunisticbehavior, and shirking (Coff, 1997).

The findings in this analysis neither negate norsupport this idea. Our premise, as stated in theintroduction, is to explicate the sourcing and build-ing of human capital. Firm decisions to participatein STW are, according to our empirical results,attempts to build human capital that can lead tocompetitive advantage. Coff’s (1997) contentionis that the dark side of human capital is a real-ity that managers must deal with through copingmechanisms such as rent sharing, organic struc-tures, shared governance, and current informationon employees. We do not disagree. However, ourintent is to examine the sourcing and building ofhuman capital as they relate to firm participation inSTW programs, not the human resource strategiesused by firms to retain employees and constrainthe possible negative side effects.

Moreover, under a transactional value lens(Zajac and Olsen, 1993) the potential costs ofturnover, shirking, and opportunism that emanatefrom human capital may be outweighed by theanticipated value created by employees embed-ded in firm-specific systems and corporate culture.Thus, while STW programs may not be the mostefficient in terms of alleviating the potential risksof building human capital, STW programs may bean alternative to building potential value of humancapital.

Implications

Exploring firm decisions to participate in STWmay be particularly valuable at this point in time,as the United States is entering a critical juncture indeveloping a new public policy toward preparingnon-college-bound high school students for theirprofessional careers. While there is some contro-versy over its effectiveness (Guest, 2000), the fed-eral government’s financial impetus for STW pro-grams in the 1990s was provided by the School-to-Work Opportunities Act, signed into law in 1994.With the expiration of this legislation in 2001, U.S.

policy needs to be reformulated either to continueto finance STW programs as currently constitutedor to develop alternative approaches to adequatelyprepare youth for their professional careers.

Educators and public policy-makers have oftenassumed that one of the primary reasons businessesshould be motivated to create linkages with edu-cation is the poor quality of graduates entering theworkforce, the underlying assumption being thatbusiness involvement in education will improve itsquality, thus improving the quality of job appli-cants. However, this study suggests a differentmotive. The business community may look at itsinvolvement in STW as a way to develop firm-specific capabilities, not to enhance educationalquality. While this, too, is a self-interest motive,our study suggests that this self-interest may bedriven by a desire to build capability through thechoosing of quality human capital that can betransformed into firm-specific capabilities. Thus,businesses may be less motivated to participate inSTW when schools are failing, which may be areason why many businesses end their school-to-work relationships (Shapiro, 1999).

Limitations

While this study has many strengths, i.e., thesize and the nationally representative data sample,as well as our use of established managementtheory, there are certain limitations inherent in itsdesign. For example, the composite index we useto measure STW activities is an indication thatthese activities are used in the firm, yet it doesnot explain the extent to which they are usedthroughout each establishment.

The cross-sectional nature of the data limits itsinternal validity. Given that the data were collectedat one point in time, and the time at which the firmsentered into STW partnerships or offered STWactivities is unknown, the direction of causalitybetween the dependent and independent variablescannot be assessed. For example, a plausible expla-nation for the significant, positive relation betweenhow well local high schools, technical institutes,and community colleges have prepared their gradu-ates with the decision to participate in STW is thatthis assessment is a consequence, not a determi-nant, of the firms working with these institutions.Collecting data over time would be the only wayto establish the direction of this relationship.



Besides using longitudinal data, future researchshould also make an effort to employ different datasources to minimize the effects of common methodvariance. Since all the data in this study werecollected from a single source, common methodvariance may account for some of the relationshipsfound among the study’s variables. The strengthof the some of the relations between the variablesmay be due to ‘response sets’ that introduce errorinto the data (Converse and Presser, 1986). Thiserror may lead to spurious relationships among theindependent and dependent variables. We tested forthe possible influence of common method vari-ance, using Harmon’s one-factor test (see Blum,Fields, and Goodman, 1994; Konrad and Linnehan,1995). Four factors with eigenvalues greater thanone emerged from a factor analysis of the 11 vari-ables in this study (cumulative variance explained:50%). Since there were multiple factors and thefirst factor accounted for only 19 percent of thevariance, common method variance may not havesignificantly influenced the results of the data anal-ysis.

SUMMARY

In this paper, we have used two theoretical per-spectives of the firm to explore employer decisionsto participate in school-to-work programs. We havepresented evidence that firms may be motivated touse STW as a way to gain competitive advantageby establishing linkages to schools with graduateswho will be successful in organizations. If simi-lar evidence were demonstrated in future researchusing longitudinal designs, it would indicate thatthe future of school-to-work programs might bemore dependent upon the success of the educa-tional system, rather than its perceived failure.

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strategic frameworks for understanding employer participation in school-to-work programs

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