Int. Journal of Business Science and Applied Management, Volume 6, Issue 1, 2011
Test of a causal Human Resource Management-Performance
Linkage Model: Evidence from the Greek manufacturing sector
Anastasia Katou
Department of Marketing and Operations Management, University of Macedonia
540 06 Thessaloniki, Greece
Tel: + 30-2310-819921
Email: akatou@uom.gr
Abstract
Although a number of studies have recognized the relationship between Human Resource Management (HRM)
policies and organisational performance, the mechanisms through which HRM policies lead to organisational
performance remain still unexplored. The purpose of this paper is to investigate the pathways leading from
HRM policies to organisational performance by using structural equation modelling. Specifically, this analytical
tool has been used to test a research framework that is constituted by a set of causal relationships between
organisational and other contingencies, business strategies, HRM policies, HRM outcomes, and organisational
performance. Employing data from organisations operating in the Greek manufacturing sector, results indicate
that the impact of HRM policies on organisational performance is mediated through the HRM outputs of skills,
attitudes and behaviour, and moderated by business strategies, organisational context and other contingencies.
Thus, the paper not only supports that HRM policies have a positive impact on organisational performance but
also explains the mechanisms through which HRM policies improve organisational performance.
Keywords: HRM policies, business strategies, HRM outputs, mediating model, organisational context, Greek
manufacturing
Anastasia Katou
17
1 INTRODUCTION
In today‟s global and highly competitive environment organisations are turning to the human resource
management (HRM) function to facilitate the development of a competitive strategy (Ulrich, 1997) that will
help the development of the organisation‟s core competencies (Levine, 1995), which in turn will advance
performance (Jackson & Schuler, 1995; Shih, Chiang, & Hsu, 2006). The „universalistic‟, „contingency‟,
„configuration‟ (Delery & Doty, 1996) and the „fully integrated‟ (Hall & Torrington, 1998) perspectives are
identified among existing theories that investigate the relationship between HRM and performance. The
universalistic perspective or HRM as an ideal set of practices suggests that a specified set of HR practices (the
so called “best practices”) will always produce superior results whatever the accompanying circumstances
(Pfeffer, 1994; Huselid, 1995; Brewster, 1999; Claus, 2003). The contingency perspective or HRM as strategic
integration argues that an organisation‟s set of HRM policies and practices will be effective if it is consistent
with other organisational strategies (Fombrum, Tichy, & Devanna 1984; Gomez-Mejia & Balkin, 1992; Dyer,
1985; Golden & Ramanujam, 1985; Schuler & Jackson, 1987; Lengnick-Hall & Lengnick-Hall, 1988;
Milkovich, 1988; Schuler & Jackson, 1987a; Butler, Ferris, & Napier, 1991; Cappelli & Singh, 1992). The
configurational perspective or HRM as bundles makes use of the so-called “bundles” of HR practices, which
imply the existence of specific combinations, or configurations of HR practices depending on corresponding
organisational contexts, where the key is to determine which are the most effective in terms of leading to higher
business performance (Arthur, 1992; Guest & Hoque, 1994; MacDuffie, 1995; Huselid & Becker, 1996; Delery
& Doty, 1996; Ichniowski, Shaw, & Prennushi 1997; Wright & Snell, 1998; Boudreau, 2003; Alcazar,
Fernandez, & Gardey, 2005). Finally, the fully integrated perspective argues that HRM strategy does not exist as
a separate functional strategy but both HRM strategy and business strategy are developed “simultaneously”
(Katou & Budhwar, 2008) rather than separately (Hall & Torrington, 1998).
Although each of the four perspectives - universalistic, contingency, configurational, fully integrated -
complements the others by adding constructs, variables or relationships (Alcazar et al., 2005), a serious
limitation that recent reviews of the literature points out is that the link between HRM and business performance
is considered like a „black box‟, i.e., lack of clarity regarding „what exactly leads to what‟ (Park, Mitsuhashi,
Fey, & Bjorkman, 2003; Gerhart, 2005; Alcazar et al., 2005). In empirically investigating the four perspectives
most studies were based on cross-sectional data and the analysis employed was either „hierarchical regression
models‟ (Youndt, Snell, Dean, & Lepak, 1996; Delery & Doty, 1996) or „competing regression models‟ (Baron
& Kenny, 1986) without proving causality. Thus, Becker and Gerhart (1996) and Fey, Bjorkman and
Pavlovskaya (2000) exhorted researchers to use „structural equation modelling‟ (SEM) to illuminate the „black
box‟ (Wright, Gardner, & Moynihan, 2003; Wright, Gardner, Moynihan, & Allen, 2005) between HRM systems
and organisational performance. This is because the use of SEM is particularly appropriate when testing direct
and indirect relationships between HRM policies and organisational performance (Dyer & Reeves, 1995) and
when testing theoretically derived paths among various exogenous and endogenous variables (Guthrie, Datta, &
Wright, 2004).
Therefore, the aim of this study is to propose a research model that includes the core constituents of the
HRM-performance linkage perspective, and to empirically test it by employing the structural equation
modelling methodology, instead of the usual regression equation methodology. Furthermore, except the
different analytical tool that we use in this study, we consider the path of several contextual variables on
organisational performance, such as management style, organisational culture, translation of HRM strategy into
clear set of work programmes and deadlines, and the proactiveness of HRM in strategy making. Considering
further, that there are no studies that test theoretically derived paths among various exogenous and endogenous
variables in the Greek context, an attempt has been made in this paper to investigate how HRM influences
organisational performance in the Greek context.
The remaining paper is organised as following. The next section presents the proposed research HRM-
performance linkage framework and the hypotheses to be tested. Next, in order to empirically test this
framework and the raised hypotheses the methodological approach is presented. Following this section the
results of the estimated model are presented and explained. Finally, the paper ends with discussion and
conclusions referring to the findings of the study.
2 RESEARCH MODEL AND HYPOTHESES
Although the resource-based-view (RBV) literature had a significant impact on strategic human resource
management (SHRM) (Barney & Arikan, 2000), very few empirical studies up to date have tested the complex
manner in which HRM policies create organisational value in the form of a sequence of linked variables
(Huselid, 1995; Fey et al., 2000; Boselie, Paauwe, & Jansen, 2001; Guest, 2001; Batt, 2002; Park et al., 2003;
Paul & Anantharaman, 2003; Katou & Budhwar, 2006; Vlachos, 2009). The usual causal pathway suggested by
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theorists, depict the following sequence (Becker, Huselid, Pickus, & Spratt, 1997; Delery & Shaw, 2001;
Edwards & Wright, 2001):
HRM (individual policies or systems) → HRM outcomes (skills, attitudes, behaviour) → performance
(organisational or financial)
Considering this causal pathway the general framework of mediating models refer to an „indirect linkage‟
through HRM outcomes, between HRM and business performance. In these models we may also see a “direct
linkage”, between individual HRM policies, as well as internally consistent systems of HRM policies, and
business performance (Schuler & Jackson, 1999; Harel & Tzafrir, 1999). However, it is not required these
linkages to be simultaneously present. It is very possible even in the absence of a direct linkage, some policies to
significantly contribute to business performance through the intervening process.
Furthermore, this intervening process may be „moderated’ according to business strategies relationship
between individual HRM policies, as well as internally consistent systems of HRM policies, and business
performance (Youndt et al., 1996). The moderation process is implied by the contingency perspective, which as
we said supports that business strategies are followed by HRM policies in determining business performance.
However, organisational contextual variables (Miles & Snow, 1984; Trompenaars, 1993; Brewster &
Hegewisch, 1994; Budhwar & Sparrow, 1997; Budhwar, 2000) and other contingencies (Delaney & Huselid,
1996; Youndt et al., 1996) may also moderate this intervening process.
The major objective of mediating-moderating models has been to determine the extent to which individual
HRM policies and/or HRM systems directly or indirectly enhance business performance (Katou & Budhwar,
2006). Such a model is presented in Figure 1, which is constituted by two parts. The mediating part refers
mainly to the variables (circles) of HRM policies, HRM output, and Organisational performance. The
moderating part refers mainly to the variables of Business strategies, Organisational context, and other
Contingencies. The arrows connecting two circles (variables) indicate the hypotheses to be tested, as follows:
H1-1: Organisational context will be associated with Business strategies
H1-2: Organisational context will be associated with Organisational performance
H1-3: Organisational context will be associated with HRM output
H1-4: Organisational context will be associated with HRM policies
H2-1: Contingencies will be associated with Business strategies
H2-2: Contingencies will be associated with Organisational performance
H2-3: Contingencies will be associated with HRM output
H2-4: Contingencies will be associated with HRM policies
H3-1: Business strategies will be positively associated with Organisational
performance
H3-2: Business strategies will be positively associated with HRM output
H3-3: Business strategies will be positively associated with HRM policies
H4-1: HRM policies will be positively associated with Organisational performance
H4-2: HRM policies will be positively associated with HRM output
H5: HRM output will be positively associated with Organisational performance
Anastasia Katou
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Figure 1: The Research Model
Organizational
Perform ance
HRM Output
Business
Strategies
Contingencies
Organisational
Context
HRM Policies
H1-1
H2-4
H1-2
H1-3
H1-4
H2-3
H2-2
H2-1
H3-1
H3-2
H4-1
H4-2
H3-3
H5
Specifically, although it is expected organisational context and contingencies to be associated with business
strategies, organisational performance, HRM output, and HRM policies, the sign of this association depends on
the specific variables constituting the organisational context and contingencies constructs. For example, capital
intensity and employment size that are two of the major variables constituting contingencies, it is expected to
positively be associated with organisational performance (Youndt et al., 1996; Richard & Johnson, 2001). On
the contrary, life cycle stage and union intensity may not be positively associated with organisational
performance (Delbridge & Whitfield, 2001; Christensen Hughes, 2002). Similarly, the translation of HRM
strategy into clear set of work programmes and deadlines, and the proactiveness of HRM in strategy making that
are two of the major variables constituting organisational context, it is expected to positively be associated with
HRM output (Budhwar & Sparrow, 1997; Budhwar, 2000). On the contrary, management style and
organisational culture may not be positively associated with HRM output (Miles & Snow, 1984; Trompenaars,
1993), depending on the specific constructs used.
The picture with respect to hypotheses referring to business strategies is clear. It is expected business
strategies such as cost reduction, quality enhancement, and innovation to positively affect organisational
performance (Porter, 1980, 1985), HRM policies (Schuler, 1989; Armstrong, 1996; Huselid, 1995; Delery &
Doty, 1996), and HRM outcomes (Huselid, 1995; Paul & Anamtharaman, 2003). Furthermore, the picture with
respect to the interrelationships of primary interest that are depicted by the hypotheses H4-1, H4-2 and H5, is
also clear. For example, Doty and Delery (1997) argued that HRM policies positively influence firm
performance by creating a workforce that is skilled, motivated, and empowered. Fey et al. (2000) provided some
support for the use of HRM outcomes (motivation, retention and development) as mediating variables between
HRM policies and firm performance. Guest (2001) used employee satisfaction and commitment, or employee
quality, commitment and flexibility, as mediating variables. Boselie et al. (2001) indicated employee
satisfaction, motivation, retention, presence, social climate, and involvement as HRM mediating outcomes
between HRM policies and firm performance. Park et al. (2003) used employee skill, attitudes, and motivation
as mediating variables between HRM systems and firm performance. Paul and Anantharaman (2003) indicated
that the intervening variables of employee competence, teamwork, organisational commitment, and customer
orientation affect the organisational performance variables of employee retention, employee productivity,
product quality, speed of delivery, operating cost, which then determine financial performance.
In the following section the research methodology is presented that will be employed in order to test the
model of Figure 1. The model specifies all the direct and indirect relationships between HRM policies, HRM
outcomes and organisational performance, and moderates for business strategies, organisational context, and
contingencies that may influence the endogenous variables of interest.
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3 METHOD
3.1 Sample
A large questionnaire survey in 23 sector industries in the Greek manufacturing sector was carried out
between March 2002 and September 2002. A sample of 600 Greek organisations was used from the main Greek
directory ICAP (2001). The sample was obtained by employing the stratified methodology. The strata were the
23 manufacturing sector industries including organisations with more than 20 employees. 20 per cent of the
approximately 3000 organisations were randomly chosen from each stratum of the directory. One hundred and
seventy eight (178) usable self-administered questionnaires were received, a response rate of approximately 30
per cent.
3.2 Measures
HRM policies: For the classification of the HRM policies we followed Armstrong (1996) and Foot and
Hook (1999). HRM policies were measured by the four key HRM areas of resourcing (recruitment; selection;
separation; flexible work arrangements), development (individual and team training and development;
monitoring training and development; careers; work design; performance appraisal), rewards (job evaluation;
compensation; promotion arrangements; incentive schemes; benefits), and relations (employee participation;
employee involvement; communications; health and safety). These 18 items were measured on a five-level scale
ranging from 1 = not very effective to 5 = highly effective (Cronbach‟s alpha = 0.952).
Business strategies: For the classification of the business strategies we followed the methodologies of
Snell and Dean (1992), Youndt et al. (1996), Sanz-Valee, Sabater-Sanchez, and Aragon-Sanchez (1999) and
Huang (2001). Business strategies were measured by 8 items (cost reduction, customer service, distribution
channels, quality enhancement, brand image, innovation, improvement of existing products, wide range of
products) that define potential competitive priorities in manufacturing, including cost, quality and innovation.
The business strategy items were measured on a five-level scale ranging from 1 = not very important to 5 =
totally essential (Cronbach‟s alpha = 0.772).
HRM outcomes: We have classified HRM outcomes with respect to skills, i.e., competent (Guest, 2001;
Park et al., 2003) and cooperated (Richardson & Thompson, 1999); attitudes – motivation, commitment,
satisfaction (Park et al., 2003); and behaviour, i.e., employees staying within the organisation (counterpart of
turnover) and presence (counterpart of absenteeism) (Richardson & Thompson, 1999; Guest, 2001). The HRM
outcomes items were measured on a five-level scale ranging from 1 = very bad to 5 = very good (Cronbach‟s
alpha = 0.952).
Organisational Performance: Organisational performance is usually indicated by indices such as
effectiveness, i.e. if the organisation meets its objectives (Dyer & Reeves, 1995), efficiency, i.e. if the
organisation uses the fewest possible resources to meet its objectives (Rogers & Wright, 1998), development,
i.e. if the organisation is developing in its capacity to meet future opportunities and challenges (Phillips, 1996),
satisfaction, of all participants – owners and investors, customers, society, other organizations, and organization
members (Schuler & Jackson, 2005), innovation, for products and processes (Guest, 2001), and quality, % of
products of high quality Richardson & Tompson, 1999). The organisational performance items were measured
on a five-level scale ranging from 1 = very bad to 5 = very good (Cronbach‟s alpha = 0.929).
Organisational contextual variables: Several organisational contextual forces may influence the adoption
of business strategies such as ‘management style’ (1 = heavily centralised to 2 = heavily decentralised) (Miles
and Snow, 1984), ‘organisational culture’ (1 = power-oriented, 2 = role-oriented, 3 = project-oriented, 4 =
fulfilment-oriented) (Trompenaars, 1993), ‘type of involvement of HRM department in developing business
strategies’ (1 = from the outset, 2 = consultative, 3 = implementation) (Brewster and Hegewisch, 1994),
‘translation of HRM strategy into clear set of work programmes and deadlines’ (0 = no, 1 = yes) (Budhwar and
Sparrow, 1997; 2002), ‘proactiveness of HRM in strategy making’ (0 = no, 1 = yes) (Budhwar, 2000). The five
organisational context items used produced Cronbach‟s alpha = 0.533 that is rather low.
Contingencies: Several contingencies may influence the adoption of business strategies, HRM policies and
performance (Delaney & Huselid, 1996; Youndt et al., 1996), such as „size’ (employment in logs) (Youndt et al.,
1996), ‘age’ (in logs) (Delaney & Huselid, 1996), „life cycle stage’ (introductory, growth, maturity, decline,
turnaround) (Christensen Hughes, 2002), „union intensity’ (percent of employees in unions) (Delbridge &
Whitfield, 2001), „capital intensity’ (total assets by employment, in logs) (Richard & Johnson, 2001), „industry‟
(0 = industries that their primary inputs for their production come mainly from the agricultural sector, and 1 =
Anastasia Katou
21
industries that their primary inputs for their production do not come from the agricultural sector) (Koch &
McGrath, 1995). The six contingency items used produced Cronbach‟s alpha = 0.644.
3.3 Statistical analysis
To test the developed research hypotheses of the proposed framework regression analysis may be used.
Specifically, for testing whether business strategies moderate HRM policies, „hierarchical regression models‟
may be used (Youndt et al., 1996; Delery & Doty, 1996) and for testing whether HRM outcomes mediate HRM
policies and business performance „competing regression models’ may be used (Baron & Kenny, 1986).
However, it is argued that the methodology of „structural equation models’ or ‘latent variable models’ (Hair,
Anderson, Tatham, & Black, 2008; Agresti, 2002) is much more powerful in investigating causal relationships
between categorical variables (Bollen, 1989; Bollen & Long, 1993; Mels, 2004), and thus this methodology was
used in this study.
4 RESULTS
We tested the theoretical model presented in Figure 1 using the structural equation modelling (SEM) via the
Statistical Package LISREL (Linear Structural Relations) and the maximum likelihood estimation (see Jöreskog
& Sörbom, 2004). We used MLE because tests of departure from normality, skewness and kurtosis for all
variables used (except union intensity) were all within acceptable statistical limits. Furthermore, the sample size
of 178 in this study is within the range of 100 to 200 for using MLE procedures (Hair et al., 2008). Moreover,
the general rule for SEM is that the number of observations needed for each parameter estimated must be
between 5 and 10 observations (Hair et al., 2008), fact that is fulfilled in the present study. We assessed the
overall model fit employing the chi-square test and the normed-chi-square test and examining the root mean
squared error of approximation (RMSEA) and the comparative fit index (CFI). A non-significant chi-square (i.e.
p > 0.05) and a value of the normed-chi-square (i.e. value of chi-square / degrees of freedom) between 1 and 2
or 3 indicate that the proposed model is an adequate presentation of the entire set of relationships (Seo, Han, &
Lee, 2005). The RMSEA considers the fit of the model to the population covariance / correlation matrix. A
value of RMSEA less than 0.05 indicates a close fit and a value less than 0.08 represent a reasonable
approximation (Browne & Cudeck, 1993; Byrne, 2001). The CFI traces the relative improvement of the
assessed model over a null where all observed variables are assumed to be uncorrelated. The CFI ranges from
zero to 1.00, with values over 0.95 indicating a well-fitting model (Bentler, 1990; Hu & Bentler, 1999).
Each latent variable model is accompanied with a path diagram indicating all the causal relationships
between the variables involved. The path diagram for the estimated HRM-performance linkage model proposed
in Figure 1 is presented in Figure 2. In this figure the boxes represent exogenous or endogenous observed
variables and the circles represent the related latent variables. The light arrows indicate the observed variables
that constitute the related latent variable and the bold arrows indicate the structural relationships between the
corresponding variables. The figures that are assigned to each arrow show the estimated standardised
coefficients. The statistics presented in Figure 2 suggest that our estimated model possesses a satisfactory degree
of fit with the data (p of Chi-Square = 0.15, Normed Chi-Square = 1.06, RMSEA = 0.018, CFI = 0.99).
Turning now to the SEM specific results the significant arrows between the various variables of the model
suggest the following relationships.
With respect to contingencies, it is seen that life cycle stage, union intensity, age, capital intensity,
size and industry have directly linked to organisational performance (Becker & Olson, 1989;
Huselid, 1995).
Considering the organisational performance variables, management style, organisational culture,
HRM involvement in developing business strategies, translation of HRM strategy into clear set of
work programmes and deadlines, and proactiveness of HRM in strategy making have directly
linked with business strategies and HRM outcomes.
However, business strategies are followed by HRM policies in determining HRM outcome that
consequently determines organisational performance. This result supports the contingency
principle (Delery & Doty, 1996), advocating that HRM policies are determined by business
strategies, and the mediation principle (Doty & Delery, 1997; Fey et al., 2000), arguing that HRM
output mediates HRM polices and organisational performance.
Int. Journal of Business Science and Applied Management / Business-and-Management.org
22
Figure 2: The Estimated Model using LISREL
Effectiveness
Efficiency
Quality
Organizational
Performance
HRM Policies HRM Output
Business
Strategies
Contingencies
Life cycle stage
Union intensity
Cost
Cooperation
with
management
Service
Cooperation
with
employees
Competence Motivation Commitment Satisfaction Presence
Recruitment
Selection
Training
Careers
Performance
appraisal
Job evaluation
Compensation
Promotion
Incentives
Participation
Involvement
Communication
Health and Safety
0.41***
Chi-Square = 733.59 df = 695 p-value = 0.15049 Normed Chi-Square = 1.06 RMSEA = 0.018 CFI = 0.99
+ p < 0.10, * p < 0.05, ** p < 0.01 *** p < 0.001
Organisational
Context
Style
Culture
Involvement
Translation
Proactive
Age
Capital
intensity
Size
Development
Satisfaction
Innovation
0.39***
0.16*
0.20**
0.18**
0.21**
0.19**
0.17**
0.60***
0.54***
0.50***
0.58***
0.56***
0.60***
0.57***
0.57***
0.58***
0.59***
0.57***
0.11** 0.58*
0.59***
0.57***
0.58*** 0.62***
0.63*** 0.44***
0.21**
0.60***
0.55***
0.54***
0.51***
0.41***
0.25**
0.53***
0.56***
0.27**
0.25**
0.90***1.00* 1.00***
0.08+
0.29+
0.12*
Industry
0.63***
Although we used 8 items in describing business strategies, only the items of cost reduction and
customer service gave significant results in determining the business strategy latent variable.
With respect to the 18 HRM policy items used to describe the HRM policies latent variable, 13
items produced significant results. Specifically, recruitment and selection for resourcing, careers
for development, incentives for employee rewards and communication, health and safety,
participation, and involvement for employee relations presented the highest standardised
coefficients.
With respect to the 8 HRM output items used to describe the HRM output latent variable, 7 items
produced significant results. Specifically, cooperation with management, cooperation with
employees and competence for skills, motivation, commitment and satisfaction for attitudes, and
presence for behaviour presented the highest standardised coefficients.
All six organisational performance items (effectiveness, efficiency, development, satisfaction,
innovation, quality) that describe organisational performance produced significant results.
Summarising the above, the path estimates displayed in Figure 2 indicate some divergence from
the corresponding paths indicated in the proposed model in Figure 1. Specifically, Table 1
presents all testing results with respect to the hypotheses developed in Figure 1.
Anastasia Katou
23
Table 1: Results of Hypothesis Testing
Path
Hypothesis
Result
Organisational context → Business strategies
H1-1
Support
Organisational context → Organisational performance
H1-2
Reject
Organisational context → HRM output
H1-3
Support
Organisational context → HRM policies
H1-4
Reject
Contingencies → Business strategies
H2-1
Reject
Contingencies → Organisational performance
H2-2
Support
Contingencies → HRM output
H2-3
Reject
Contingencies → HRM policies
H2-4
Reject
Business strategies → Organisational performance
H3-1
Reject
Business strategies → HRM output
H3-2
Reject
Business strategies → HRM policies
H3-3
Support
HRM policies → Organisational performance
H4-1
Reject
HRM policies → HRM output
H4-2
Support
HRM output → Organisational performance
H5
Support
5 DISCUSSION
The contribution of this study is two-fold. First, although previous studies on the HRM-performance
linkage perspective are based on regression – like analyses, the present study has adopted the different analytical
tool of the structural equation modelling, following thus the suggestion of Becker and Gerhart (1996) and Fey et
al. (2000). Second, the proposed and tested conceptual HRM-performance linkage framework put some light
into the „black box‟ mediating HRM policies and organisational performance, by considering also new
organisational context variables.
5.1 Findings
Starting with the latent variable of ‘business strategies’ (cost reduction, customer service), path coefficients
reveal that it is positively influenced by the ‘organisational context’ variable. This means that the more heavily
decentralised is the management style, the more fulfilment – oriented (i.e. emphasis on expertise and orientation
toward the person) is organisational culture, the more active the involvement of the HRM department is in
developing business strategies, the more the HRM strategy is translated into clear set of work programmes and
deadlines, and the more proactive of HRM is in strategy making, the more positive is the influence of
organisational context variables on the development of business strategies. However, we must note here, that
although we used 8 items constituting the three types of Porter‟s (1980, 1985) business strategies of ‘cost’ (cost
reduction), „quality’ (customer service, distribution channels, quality enhancement, brand image), and
„innovation’ (innovation, improvement of existing products, wide range of products), only the variables of cost
reduction and customer service fit into the model. This is may be due to the fact that Greek manufacturing firms
put more emphasis on cost reduction and customer service than on quality or innovation (World Economic
Forum, 1998).
Although, path coefficients reveal that the latent variable of ‘HRM outcomes’ (cooperation with
management, cooperation with employees, competence, motivation, commitment, satisfaction, presence) is
indirectly influenced by the organisational context variable, through business strategies and HRM policies, it has
been found that it is directly, moderately and positively influenced by the organisational context variable. This
result seems to be very important because it reveals that the internal environment of the organisation influences
the skills, attitudes and behaviour of the employees, which in turn affect organisational performance (Keats &
Hitt, 1998; Terpstra, Mahamed, & Rozell, 1996; Murphy & Southey, 2003). We must note here that to our
surprise the variable of employee retention (counterpart of turnover) did not fit into the model, contrary to the
findings of other researchers such as Katz, Kochan, and Weber (1985), Arthur (1994), d‟Arcimoles (1997),
Boselie et al. (2001), Fey et al. (2000) and Guthrie et al. (2004), who advocate that it affects organisational
performance.
The latent variable of „HRM policies’, that is constituted by resourcing (recruitment, selection),
development (individual and team training and development, careers, performance appraisal), rewards (job
evaluation, compensation, promotion arrangements, incentive schemes), and relations (employee participation,
employee involvement, communications, health and safety), path coefficients reveal that it is heavily and
positively influenced by the ‘business strategies’ variable. This result indicating that business strategies are
followed by HRM policies in determining business performance supports the contingency perspective, arguing
that an organisation‟s set of HRM policies and practices will be effective if it is consistent with other
organisational strategies. The variables of separation, flexible work arrangements, monitoring training and
development, work design, and benefits did not fit into the model. Although Becker and Gerhart (1996) have
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24
identified only three HRM policies that influence organisational performance to be common among various
empirical studies, we decided to include in this study as many HRM policies as possible, considering that the
proposed research model is tested for the first time in the Greek context using structural equation modelling.
However, the HRM policies that fit into the model are all included in the classification key HRM areas
suggested by Armstrong (1996) and Foot and Hook (1999).
In terms of mediation we found that the latent variable of „HRM outcomes‟ mediates the relationship
between „HRM policies’ and „organisational performance’. The results show that HRM outcomes strongly and
positively affect organisational performance. Furthermore, it is seen that employee skills (cooperation between
management and employees, cooperation among employees, competence), attitudes (motivation, commitment,
satisfaction) and behaviour (presence) positively affect organisational performance. This finding demonstrates
that the relationships between HRM policies and organisational performance may be mediated by HRM
outcomes, such as employee skills, attitudes and behaviour. This finding coincides with Doty and Delery (1997)
and Park et al. (2003) who argued that HRM policies influence organisational performance by creating a
workforce that is skilled and has the right attitudes and behaviour. It also partially supports Guest (2001) for
satisfaction and commitment, Boselie et al. (2001) for satisfaction and motivation, and Paul and Anantharaman
(2003) for competence and commitment, arguing that these HRM outcomes affect organisational performance.
With respect to the latent variable of „organisational performance’ it is seen that all the variables
(effectiveness, efficiency, development, satisfaction, innovation, quality) used to constitute this construct fit
properly into the model. However, path coefficients reveal that organisational performance is moderately and
positively influenced by the other ‘contingencies’ variable, supporting thus the argument of Harel and Tzafrir
(1999) whereby organisations do not operate in a vacuum. Specifically, with the introduction of the „life cycle
stage‟ variable we tried to capture maturity effects of the organisation, or to assess the stage of organisational
development. It is argued that HRM policies change over time depending on whether the organisation is in a
stage of formation, growth, maturity, or decline (Budhwar & Sparrow, 1997). There is much evidence that
unions affect a firm‟s performance (Freeman and Medoff, 1984). In our study we found that union intensity is
positively related to organisational performance, supporting thus similar findings of Arthur (1994) and Huselid
(1995). Superior performance becomes crucial in firms that make large investment in plant, equipment and other
assets. In our research we found that capital intensity is positively related to organisational performance (Hayes,
Wheelwright, & Clark, 1988). We also found that the variable of size is positively related to organisational
performance. Such results are expected as it is now known that large firms tend to have established HRM
systems, which facilitate in improving performance of the organisation (Brewster et al., 1996). Furthermore, we
found that the variable of age, that is used to capture any founding values of the organisation (Delaney &
Huselid, 1996), positively influences organisational performance. Finally, we found that organisational
performance depends on the industry specific effects (Shih et al., 2006).
5.2 Limitations and further research
A number of issues may limit the findings of the study. First, the data was collected using a questionnaire
at a single point in time. As a result, the study based on cross-sectional data does not allow for dynamic causal
inferences (Cavanaugh & Noe, 1999). Second, a single respondent from each organisation provided information
on HRM policies and practices, HRM outcomes and perceived measures of organisational performance,
respondent bias may have set in the form of upward or downward reporting of the measures (Paul &
Anatharaman, 2003). Third, the survey was conducted in 2002. Although the scope of the study was focused in
investigating structural relationships in the HRM-organisational performance framework, this framework may
not be relevant today under the context of economic crisis. Last but not least, the study was applied in the
context of Greece, with specific labour relations and institutional conditions, and thus the findings from the
Greek sample may not generalise across borders (de Jong, Schalk, & Cuyper, 2009). Nevertheless, considering
the limitations of the study we may propose paths for future research. Specifically, in this study we tried to
explore the question of causality using cross-section data. However, causality can only really be tested with data
collected at different points in time. Thus, the field would greatly benefit from some longitudinal studies in the
future. Further, considering the pace of globalisation, there is a strong need for such investigations in emerging
markets, through the inclusion of organisational context variables (Katou & Budhwar, 2006). Additionally, it
would be very interesting to repeat the same study under the context of economic crisis and compare the
findings.
5.3 Contribution of the study
In spite of such limitations, the study makes some important contributions. It tests theoretical assumptions
in smaller firms and in a non- USA/UK context. It provides support to the mediation and contingency
perspective. The study supports for the use of HRM outcomes (skills, attitudes, behaviours) as mediating
variables between HRM policies and business performance. Thus, the research suggests that models depicting
direct relationships between HRM policies and business performance may be too simplistic and does not show
Anastasia Katou
25
the causalities involved. This meets the advice of Becker and Gerhart (1996) and Fey et al. (2000) to test models
with mediating variables such as HRM outcomes, using the methodology of structural equation modelling, and
thus, contributing to this academic area of research.
5.4 Implications
The argument that HRM makes an impact on the bottom line may not be in dispute. However, what is of
interest is in knowing how this impact has taken place. Thus, a managerial implication of this study is not only
the demonstration that HRM policies are positively related to organisational performance in the Greek context,
but also that employee skills, attitudes, and behaviours are three major components of the “black-box” that
generate organisational competitiveness from HRM policies. Managers should recognise that changes in
employee skills, attitudes, and behaviours that are caused by HRM policies precede changes in organisational
performance (Katou & Budhwar, 2006). Specifically, (considering the highest standardised loadings of the
constructs in Figure 2) the study argues that HRM policies with respect to employee incentives, communication
and health and safety, create positive employee attitudes with respect to employee commitment, motivation and
cooperation, which in turn will improve organisational effectiveness, innovation and satisfaction. Thus,
practitioners should emphasise the proper use of these HRM policies, in order to improve organisational
performance.
6 CONCLUSIONS
Concluding, we may say that although past research has demonstrated that there exists a relationship
between HRM policies and organisational performance, it has neglected to investigate the mediating
mechanisms, usually called the “black box”, through which HRM policies are hypothesised to affect
organisational performance (Park et al., 2003). The results of this study support that HRM policies positively
affect organisational performance of Greek manufacturing companies. Specifically, the relationship between
HRM policies and organisational performance is mediated through the HRM outcomes of skills, attitudes and
behaviour, and is moderated by business strategies, organisational context and other contingencies, giving
support to the contingency perspective of the HRM-performance linkage. Thus, this paper not only supports that
HRM policies have a positive impact on organisational performance, but it additionally explains the
mechanisms through which HRM policies improve organisational performance and that too in a non US/UK
context where most of research related to this field has been conducted.
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