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The Romance of Human Resource Management and Business Performance, and the Case for Big Science

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It is often assumed that research over the last decade has established an effect of human resource management (HRM) practices on organizational performance. Our critical assessment of existing studies finds that, although collectively they have opened up a promising line of inquiry, their methodological limitations make such a conclusion premature. We argue that future progress depends on using stronger research methods and design that, in turn, will require large-scale long-term research at a level of magnitude that probably can only be achieved through partnerships between research, practitioner and government communities. We conclude that progress so far justifies investment in such big science.
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DOI: 10.1177/0018726705055032
2005 58: 429Human Relations
Toby D. Wall and Stephen J. Wood
and the case for big science
The romance of human resource management and business performance,
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The romance of human resource
management and business performance,
and the case for big science
Toby D. Wall and Stephen J. Wood
ABSTRACT It is often assumed that research over the last decade has established
an effect of human resource management (HRM) practices on
organizational performance. Our critical assessment of existing
studies finds that, although collectively they have opened up a
promising line of inquiry, their methodological limitations make such
a conclusion premature. We argue that future progress depends on
using stronger research methods and design that, in turn, will require
large-scale long-term research at a level of magnitude that probably
can only be achieved through partnerships between research, prac-
titioner and government communities. We conclude that progress
so far justifies investment in such big science.
KEYWORDS company performance
high performance work organization
high performance work systems
human resource
management
organizational performance
Picture the scene. A leading scholar specializing in human resource manage-
ment (HRM) is called to court as an expert witness by an international
company that has brought a case against a firm of consultants. The company
has paid several hundred thousand pounds in consultancy fees, and invested
many times that amount in its personnel function, to introduce the ‘perform-
ance-enhancing’ HRM practices recommended by the consultants. Three
years on there is no evident return on their investment. The company is suing
429
Human Relations
DOI: 10.1177/0018726705055032
Volume 58(4): 429–462
Copyright © 2005
The Tavistock Institute ®
SAGE Publications
London, Thousand Oaks CA,
New Delhi
www.sagepublications.com
03 055032 Wall (to_d) 20/6/05 1:05 pm Page 429
the consultants on the grounds that they created misleading expectations of
the effect of HRM practices on performance. The expert witness is asked to
prepare a report addressing two questions: (i) whether it was reasonable of
the consultants to assume an effect of HRM practices on performance on the
basis of both researchers’ accounts of their own findings and how prac-
titioners have been encouraged to view them; and (ii) the extent to which the
evidence can, in fact, be interpreted as establishing such a causal link. In this
article we present the report that we would have submitted were we the
expert witness. Having adopted this format, we conclude by considering the
implications of our assessment for future research. First, however, we intro-
duce the core concepts.
Conceptual background
HRM is a term used to represent that part of an organization’s activities
concerned with the recruitment, development and management of its
employees (Wood & Wall, 2002). Within that domain, current interest is
focused on HRM systems emphasizing all or most of the following practices:
sophisticated selection methods, appraisal, training, teamwork, communi-
cations, empowerment, performance-related pay and employment security.
Collectively, these are deemed to contribute to the skill and knowledge base
within the organization, and to employees’ willingness to deploy their
learning to the benefit of the organization. For this reason, authors have used
labels such as ‘human capital-enhancing’ (Youndt et al., 1996), ‘high
commitment’ (Wood & de Menezes, 1998) or ‘high involvement’ (Guthrie,
2001; Vandenberg et al., 1999) to characterize the approach. They often
contrast this with traditional, Tayloristic or control approaches to manage-
ment, which emphasize low skill, limited employee discretion and a tight
division of labour (e.g. Arthur, 1994; Lawler, 1986; Walton, 1985).
The rationale for focusing on the high-commitment approach to
HRM lies in the assumption that the practices will enhance organizational
performance. Related to this is the view that the practices will be a source
of unique and sustainable advantage because, unlike other initiatives such as
the introduction of new technology, they result in skills and knowledge that
are largely organization specific and are therefore difficult to imitate
(e.g. Barney, 1991, 1995). Companies can copy one another’s technologies
much more easily than they can their human resource capabilities.
The link between HRM and performance has been conceived in a
variety of ways. The simplest view is that practices are additive (the more
the better, e.g. Guest & Hoque, 1994), and that they enhance performance
regardless of circumstance (a universal effect, e.g. Pfeffer, 1994). Alternative
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430
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perspectives emphasize various kinds of ‘fit’, of which three main types have
been identified (Wood, 1999). ‘Internal fit’ posits synergy among the prac-
tices, meaning that their collective effect will be greater than the sum of their
individual parts. For example, it might be argued that selecting able people
without training them, or training employees but not empowering them to
use that training, will have little effect; whereas implementing the three prac-
tices together will. Indeed, Barney (1995) goes so far as to argue that indi-
vidual practices ‘have limited ability to generate competitive advantage in
isolation’ (p. 56).
The second type is ‘organizational fit’, which concerns the role of HRM
in enhancing the effectiveness of other organizational practices or technolo-
gies, and vice versa. Lawler et al. (1995), for example, link HRM to total
quality management (TQM), arguing that the two sets of practices are
‘complementary in their impact on organizational performance’ (p. 144).
Similarly, MacDuffie (1995) sees high commitment HRM practices as
integral to the effectiveness of lean production (Womack et al., 1990) initia-
tives and vice versa.
The third and final type is ‘strategic fit’. This assumes that HRM prac-
tices need to be aligned with the organization’s strategy (e.g. in the case of
private businesses to their competitive strategy) to have their full effect on
performance (e.g. Miles & Snow, 1984; Schuler & Jackson, 1987; Youndt
et al., 1996).
Empirical investigation of fit typically involves testing for interaction
effects (e.g. among different practices, or between HRM system measures
and strategy). Because fit is central to many accounts of the effects of HRM
on performance, it is relevant to determine the extent to which such inter-
actions have been examined. In practice, as we shall see, much empirical
work ignores or pays only limited attention to issues of fit, consciously or by
default taking the universal thesis propounded by Pfeffer (1994) and others.
Is an HRM effect on performance presumed by researchers
and practitioners?
We can now return to the first question we have been asked to consider as
expert witnesses, whether authors portray research findings as confirming a
causal effect of HRM on organizational performance, in support of the
guiding theory. There can be little doubt that such an interpretation is wide-
spread. Early reviews of the field fuelled this perception as they concluded
that studies supported the universal thesis (e.g. Becker & Huselid, 1998;
Guest, 1997). Becker and Gerhart (1996: 779), for example, argue that
‘conceptual and empirical work . . . has progressed enough to suggest that
Wall & Wood The romance of HRM
431
03 055032 Wall (to_d) 20/6/05 1:05 pm Page 431
the role of human resources can be crucial’. Such views have permeated
subsequent studies. Way (2002: 765), for instance, states that ‘Theoretical
and empirical HRM research has led to a general consensus that the method
used by a firm to manage its workforce can have a positive impact on firm
performance’.
A more subtle way in which authors imply an established performance
effect lies in the labels many use to denote salient HRM systems. For
example, in his seminal study, Huselid (1995) uses the expression ‘high
performance work practices’ (p. 635), mirroring Lawler et al.’s (1995, 1998)
choice of ‘high performance organizations’ for their book titles. Subse-
quently, Delaney and Huselid (1996) refer to ‘performance-enhancing’
(p. 949) HRM practices, Kalleberg and Moody (1996) to ‘high performance
work organizations’ (p. 114), and Appelbaum et al. (2000) and Way (2002:
765) to ‘high performance work systems’. The titles of many articles carry
the same message. For example, an early article by Arthur (1994) is entitled
‘Effects of human resource systems on manufacturing performance and
turnover’. Following Huselid’s (1995) lead in his article on ‘The impact of
human resource management practices on turnover, productivity and corpo-
rate financial performance’ (our italics), many other authors, also describing
cross-sectional results, use equivalent causal terminology (e.g. Ahmad &
Schroeder, 2003; Bae & Lawler, 2000; Delaney & Huselid, 1996; Jayaram
et al., 1999; Vandenberg et al., 1999; Wright et al., 2003). The idea of causal-
ity is thus embedded within the choice of label for HRM systems and in
the wording of titles. Such terminology is in danger of appearing to prejudge
the very relationship under investigation, as if the researcher’s role were to
find evidence for a widely expected (and one might say, even hoped for)
relationship.
A further way in which the discourse of research implies an established
effect of HRM on performance is through the argument that it is now time
to move on to other issues. In this vein, Delery (1998) suggests that ‘Estab-
lishing that HRM practices are linked with firm effectiveness is an import-
ant first step . . . however, there is little understanding of the mechanisms
through which HRM practices influence effectiveness’ (p. 289). Similarly,
there have been calls to broaden the outcomes studied to cover those of more
immediate interest to employees. Osterman’s (2000) study of ‘High perform-
ance work organization’ practices follows this lead, as he set his objective to
determine ‘whether their productivity and quality gains redounded to
employees’ benefit’ (p. 179). He examines the not unimportant question of
whether these practices are associated with layoff rates and compensation
gains; but in so doing he simply assumes, without proof, that there are gains
to redound (i.e. share among employees).
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432
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A final indication of the way in which a causal effect is assumed relates
to practice. In their review of research, Becker and Gerhart (1996) set their
goal as being to ‘demonstrate to senior human resources (HR) and line
managers that their HR systems represent a largely untapped opportunity to
improve firm performance’ (p. 780). That message has clearly got through,
as evident from Cooper’s (2000) article in a leading UK HRM practitioner
journal, which concludes: ‘Academic studies have established a link between
HR and profitability. The race is now on to find out how and why people
policies make a difference to shareholders’ (p. 28). Again, Philpott (2002)
concludes that:
What is missing, says the CIPD [the UK’s Chartered Institute of Person-
nel Development], is a genuine appreciation both that people manage-
ment holds the key to increased productivity and that meeting the
objective requires the appropriate application of a range of people
management practices. In general terms these practices encompass,
recruitment, training, job appraisal and reward, job design, job quality
and communication with staff.
(p. 5)
One should record that some have been more circumspect in their assess-
ments (e.g. Delaney & Godard, 2001; Marchington & Grugulis, 2000;
Wood, 1999). Wright and Gardner (2003), for example, go only so far as to
suggest that evidence mounts that HR practices are at least ‘weakly related
to firm performance’ (p. 312). Godard (2004) is even more sceptical. Though
not doubting that HRM ‘can be highly effective in some work places’
(p. 355), he concludes that, especially in liberal market economies, the gener-
alizability is likely to be low. Nevertheless, the message conveyed by a large
part of the literature is that HRM practices do promote performance.
Expert witness testimony: part 1
Our evidence on the first question is clearly in favour of the defence. It shows
that it was reasonable for the consultants to assume a positive effect of HRM
practices on performance on the basis both of researchers’ portrayal of their
own findings and how these have been presented in non-academic circles.
Does the evidence support an HRM–performance effect?
To address the second question, concerning the extent to which the evidence
can be interpreted as establishing a causal effect of HRM on performance,
Wall & Wood The romance of HRM
433
03 055032 Wall (to_d) 20/6/05 1:05 pm Page 433
we evaluate key empirical studies. What follows is an account of the method
we adopted, and our findings.
Sampling the studies
We used five criteria to select the studies to be evaluated. First, we restricted
our choice to those appearing in reputable refereed journals, to ensure that
we were assessing high-quality studies. This meant that other influential
work, published, for example, in books or reports, was excluded (e.g. Appel-
baum et al., 2000; Ichniowski, 1990; Lawler et al., 1995, 1998). Second, we
restricted our selection to studies published from 1994 onwards, when
research on HRM and performance first came to prominence. Third, we
included only those studies covering multiple HRM practices, because the
focus is on whether the HRM system as a whole promotes overall organiz-
ational performance. This excluded any studies of single practices such as
training, sophisticated selection, or job design. Fourth, we included only
studies using measures of economic performance such as productivity, profit
or return on assets. Thus we excluded studies limited to other performance
indicators such as labour turnover, absence or employee well-being. Finally,
because of the detailed assessment involved, we restricted the sample to
highly cited milestone studies of the mid- to late-1990s, and a selection of
more recent ones (whose citation rate is yet to be determined). The studies
we used are shown in Table 1.
Assessing the studies
In order to assess the evidence, we identified key criteria relevant to gener-
alization and causal interpretation against which to judge studies individu-
ally and collectively. Those criteria concern: the sample and response rate;
the reliability and validity of the HRM measure and source of data for it;
the adequacy of the research design; the extent to which other factors have
been controlled; the strength of the findings on the HRM–performance link;
whether there has been a test for fit; and finally if the effects of individual
HRM practices have been considered alongside those of the composite HRM
measure. We expand on these criteria and the rationale for their choice in
the course of presenting findings.
Sample and response rate
The size of samples used affects the power to detect main effects, and even
more so theoretically predicted synergies (interactions). Coupled with the
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response rate, size also affects the extent to which one can generalize. It can
be seen (Table 1, column 2) that the studies have diverse but often rather
small (< 300 in 18 of the 25 studies, and < 100 in 9 studies) samples (column
2). At the same time, the response rates, though varying between 4 and 84
percent, are generally low – albeit better than the 6–28 percent (mean 17.4%)
rate reported in an earlier review by Becker and Huselid (1998). This is not
a very secure foundation from which to generalize.
HRM dimensions
Evidence that the studies use appropriate and broadly equivalent measures
of HRM is important to justify treating them collectively. As previous
commentators have noted (e.g. Becker & Gerhart, 1996; Dyer & Reeves,
1995; Wright & Gardner, 2003) there is diversity across studies in the
particular practices covered. Nonetheless, there is much commonality as
studies typically cover a substantial range of the following: sophisticated
selection, appraisal, training, teamwork, communication, job design,
empowerment, participation, performance-related pay/promotion, harmo-
nization, and employment security (Table 1, column 3).
HRM measure type and source
In any empirical investigation reliable measurement of independent variables
(in this case HRM practices) is of paramount importance; and in cross-
sectional research, ensuring such measures are uncontaminated by those of
the dependent variables (i.e. performance) is of particular significance. In
studies of HRM, the measurement of relevant practices cannot be a straight-
forward process, because the focal construct is not of that nature. Whether
there is a bonus scheme in operation may be easy to establish, but judge-
ments of the extent of teamwork or empowerment are much more compli-
cated to gauge. Thus, quantifying HRM practices involves judgement.
Consequently, it is open to random measurement error. At the same time, it
is vulnerable to correlated error in the form of rater bias. For example, more
optimistic or organizationally committed individuals rating both the prac-
tices and performance in their own company might give systematically higher
scores than their more pessimistic counterparts elsewhere. Such ‘common
method variance’ alone could create spurious relationships among HRM
practices and between them and performance.
Given these considerations, the measurement of HRM practices would
ideally involve: assessments from two or more persons (to determine
reliability), the use of the same raters across different organizations (to
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Table 1 Measurement features of empirical studies on HRM and organizational performance
Study Sample and response HRM dimensions and illustrative HRM measure type and source Dependent variable measures
rate (%) components
1 Arthur (1994) 30 US mini steel Two contrasting types of HRM system: Questionnaire; single-source; Self-report: productivity and scrap
mills; 56 percent
a
control and commitment (low and high HR managers rate; same respondent as for
respectively on decentralization, independent variables; for previous
participation, training and skill) year
2 Guest and 119 UK Four a priori types: 2 2 – whether or Questionnaire; single-source; Self-report: productivity and
Hoque (1994) greenfield mainly not claim HRM strategy and use more or principal HR manager or quality; same respondent as for
manufacturing less than half of 22 HRM practices senior line manager independent variables; concurrent
companies; (e.g. selection, job design)
39 percent
a
3 Huselid 968 US Two scales: skills and structures Questionnaire; single-source; Objective: productivity, Tobin’s
(1995) companies with (e.g. communications, QWL, training, mailed to senior HRM Q and GRATE for subsequent year
100+ staff; grievance procedures); and motivation professional
heterogenous sample; (e.g. performance appraisals, promotion
28 percent on merit)
4 MacDuffie 62 car-assembly Two scales: work systems (participation, Questionnaire;‘a contact Objective: productivity (labour
(1995) plants, worldwide; teams, quality role) and HRM policies person, often the plant hours per vehicle) – adjusted for
69 percent
a
(selection, performance-related pay, manager’; sections completed vehicle size and number of welds;
training). Also a use of buffers (lean by different people; later quality from independent market
production) scale visits/telephone checks report; concurrent
5 Delaney and 590 for-profit and Five scales: staffing selectivity, training, Telephone survey; single-source Self-report: organizational and
Huselid (1996) non-profit US firms, incentive pay, decentralization, internal (multiple respondents in a few market performance; same
heterogenous; promotion cases); unspecified respondent as for independent
51 percent ‘representatives’ variables; concurrent
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Wall & Wood The romance of HRM
437
6 Delery and 216 US banks Seven scales: internal promotion, Questionnaire; single-source; Objective: return on assets (ROA),
Doty (1996) (down to 101 in training, appraisal, profit-sharing, senior HR manager (+ strategy return on equity (ROE);
some analyses); security, participation, job specification; from president) concurrent
18 percent
a
and two strategy measures
7 Koch and 319 US business Separate HR planning index, Hiring Questionnaire; single-source; Objective: labour productivity;
McGrath units; 4 percent
a
index and Development index; and sent to executives concurrent
(1996) composite HR sophistication index
(previous three added together)
8 Youndt et al. 97 US manufacturing Two scales: administrative HR Questionnaire; multiple source Self-report: customer alignment
(1996) plants (metal-working (e.g. appraisal, incentives) and human (at least two respondents per (quality), productivity and machine
industry); 19 percent
a
capital-enhancing HR (e.g. selection and plant, mean score); general and efficiency; same respondent as for
training for problem-solving, salaried pay) functional managers independent variables; average of
concurrent and subsequent
9 Huselid et al. 293 US firms: Two scales: strategic HRM (teamwork, Questionnaire; single-source; Objective: productivity, GRATE
(1997) heterogenous empowerment) and technical HRM executives in HR (92%) and Tobin’s Q; concurrent and
(e.g. manufacturing, (recruitment, training). Ratings are not and line (8%) positions subsequent year
finance, misc.); of reported use, but of perceived (effectiveness of HR practices,
response rate unclear effectiveness not use per se)
10 Ichniowski 36 steel production Four types of line ranging from innovative Interviews; multiple Objective: productivity (line
et al. (1997) lines in 17 companies; HRM (high on incentive pay, selection, respondents; labour relations and uptime); panel data
60 percent
a
teamwork, employment security, training) operations managers, line
to traditional HRM (low on all above workers and trade union reps
components)
11 Wood and Representative Four types of workplace, ranging from high Interviews; single-source; HR Self-report: productivity,
de Menezes sample of 1693 to low HCM (high commitment manager or senior manager productivity change over last 3
(1998) UK workplaces management) – (high HCM showing more responsible for HR years; and financial performance;
(806–926 in analyses); appraisal, information disclosure, same respondent as for
84 percent communication, monthly pay) independent variables; concurrent
03 055032 Wall (to_d) 20/6/05 1:05 pm Page 437
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438
Table 1 continued
Study Sample and response HRM dimensions and illustrative HRM measure type and source Dependent variable measures
rate (%) components
12 Hoque (1999) 209 UK hotels; Overall HRM (21 practices used, Questionnaire; single-source; Self-report: productivity, service
35 percent including harmonization, job design, respondents unclear quality and financial performance;
training, merit pay) same respondent as for
independent variables; concurrent
13 Jayaram et al. 57 firms supplying Five scales: cost, quality, flexibility and Questionnaire; single-source; Self-report: cost, quality, flexibility
(1999) automotive industry; time HRM (commitment to and training, CEOs and time performance; same
39 percent goals and support for), plus a generic respondent as for independent
scale (broad jobs, autonomy) variables; concurrent
14 Vandenberg 49 North American Five scales: flexibility, incentive Questionnaire; single-source; Objective: return on equity (ROE);
et al. (1999) life insurance practices, direction sharing, training, head of HR for subsequent year
companies; response work design
rate unclear
15 Wright 38 US petrochemical Four scales: selection, training, pay and Questionnaire; single-source; Self-report: financial performance;
et al. (1999) refineries; 20 percent appraisal; with participation as a HR manager independent source (refinery or
contingency variable operational manager); concurrent
16 Bae and 138 firms in Korea; Single ‘high involvement HRM strategy’ Questionnaire; single-source; Self-report global measure; same
Lawler (2000) response rate unclear index (five sub-scales covering training, head of HR respondent as for independent
empowerment, selection, performance- variables; concurrent. Objective
related pay, broad job design) (ROIC) for sub-sample (n = 68) –
concurrent and subsequent year
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Wall & Wood The romance of HRM
439
17 Fey et al. (2000) 101 foreign-owned Eight single-item measures for managers and Questionnaire; single-source; Self-report; overall performance
firms in Russia; non-managers separately: promotion on 38 percent HRM manager, (poor to outstanding); same
heterogenous sample; merit; job security; technical training; 63 senior managers respondent as for independent
25 percent non-technical training; career planning; variables; concurrent
decentralization; internal recruitment;
complaint resolution
18 Cappelli and 433–666 (see Extent of job rotation, self-managed Telephone survey; single- Self-report
b
: sales per employee,
Neumark research design) teams, teamwork training, cross-training, source; plant/site manager total labour cost per employee and
(2001) US manufacturing pay for skill/knowledge, profit/gain sharing, sales value/labour costs; same
plants; response rates meetings, and TQM (as index of involvement) respondent as for independent
unclear variables. Data collected by US
Bureau of the Census
19 Guthrie 164 New Zealand Single high-involvement work practices Questionnaire; single-source; Self-report: productivity (annual
(2001)
c
firms, heterogenous (HIWP) scale based on 12 practices various staff from CEO to junior sales per employee); same
sample; 23 percent (e.g. performance-based promotion, manager respondent; strongly related to
skill-based pay, training, participation) objective data in a sub-sample;
concurrent
20 Richard and 63–73 US banks; Single scale of effectiveness of strategic Questionnaire; single-source; Objective: return on equity (ROE)
Johnson (2001) 13–15 percent
a
human resource management (SHRM) HR director and productivity (net income per
practices (from Huselid et al., 1997) (Effectiveness of HR practices, employee); concurrent
tapping eight practices (e.g. participation not use per se)
and empowerment, teamwork,
employee and manager communications) Telephone survey; single- Self-report, percent change in sales
21 Batt (2002) 260 call centres; Skill level (education and training); job source; general managers in prior 2-year period; same
54 percent design (discretion and teamwork); HR respondent as for independent
incentives (supportive HR – training, variables; previous 2 years
feedback, high pay, security). Composite
HR index of all three
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Table 1 continued
Study Sample and response HRM dimensions and illustrative HRM measure type and source Dependent variable measures
rate (%) components
22 Way (2002) 446 small firms; Single index of ‘High Performance Telephone interview; single- Self-report
c
labour productivity
70 percent Work Practices’ covering seven practices source; plant manager. Data (income/labour costs) plus
(e.g. self-directed teams, job rotation, collected by US Bureau of the perceived relative (to competitors)
performance pay, training, involvement) Census productivity; concurrent
23 Ahmad and 107 manufacturing 12 practices including: selection, Self-report questionnaires; Self-report: single index covering –
Schroeder plants in USA, teamwork, performance-related pay, respondents differ between cost, quality, delivery, flexibility, new
(2003) Germany, Italy and training, employment security, practices, but single-source for product introduction; different
Japan; 60 percent harmonization any given measure; managers, respondent to that for the
engineers, supervisors and independent variables; concurrent
workers
24 Guest et al. 366 manufacturing Single overall use of HRM practices (48 Telephone survey; single-source; Objective: productivity (sales per
(2003) and service sector items on: recruitment and selection, training HR director or most senior employee) and profit for years
UK companies; and development, appraisal, financial flexibility, HR person before and after the period when
response rate unclear job design, two-way communication, the independent variables were
employment security and internal measured
labour market, harmonization, quality)
25 Wright et al. 50 business units, Single overall HR practices scale: nine items Employee attitude survey; Objective (from company records),
(2003) US food services covering selection, pay for performance, multiple source; rank-and-file productivity and profit – subsequent,
company; response training, participation employees for period 3–9 months after
rate unclear measurement of HR practices
a
Estimated by current authors as the number of companies in relevant analyses as a percentage of total available sample.
b
It is a requirement to ensure the accuracy of all data supplied to the US Bureau of the Census.
c
See also Guthrie et al.s (2002) article on the same data.
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reduce error resulting from differences in the use of rating scales), raters who
through knowledge of the use of practices in a range of organizations are
able to benchmark the development of the practice against that elsewhere (to
better calibrate the scale), and raters who are ignorant of the performance
or the organization in question (to eliminate the possibility that knowledge
of the outcome will contaminate measurement of the independent variables,
resulting in common method variance bias). In contrast, the least satisfac-
tory method is to use reports from single respondents, each describing their
own organization, and who have knowledge of, or worse still, are the source
of, the performance data.
The profile of the large majority of studies corresponds to the least
satisfactory measurement approach. Twenty-one of the 25 studies use single
respondents (see Table 1, column 4). Moreover, in only two of the four cases
with multiple respondents (Wright et al., 2003; Youndt et al., 1996) is any
information on inter-rater agreement provided. In the other two cases
(Ichniowski et al., 1997; MacDuffie, 1995), it is unclear how the information
was combined, and the extent to which it was consistent across sources. This
is not a trivial issue, given findings by Gerhart et al. (2000) and Wright et
al. (2001) of very low levels of reliability in HR measures.
It is also the case that 24 of the 25 studies rely exclusively on respon-
dents describing only their own context. The one exception is Ichniowski et
al. (1997) who characterized the HRM system across the 36 US steel
production lines in their sample themselves, on the basis of interview data
from multiple respondents (though quite how is unclear). Moreover, in those
24 studies it is reasonable to assume that those rating the extent of use of
the HRM practices were also aware of their organization’s performance. In
fact, this is certain in 12 cases in which data on HRM practices and perform-
ance were obtained from the same respondent.
Thus, across the studies as a whole, measures of HRM are generally
of unknown reliability, are likely to contain considerable random measure-
ment error, and at the same time in the majority of cases are open to conta-
mination from knowledge of performance and demand characteristics.
Random error will weaken the assessment of any underlying relationship
between HRM and performance; whereas contamination of the data will
create correlated error that could result in spurious associations.
Dependent variable measurement
Measures of the dependent variable (performance) minimally should come
from a different source from that used to measure HRM practices, and
ideally would be ‘objective’ – to reduce the likelihood of common method
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variance. In many cases, such as in for-profit businesses, measures of
productivity and profit taken from official accounts will be appropriate,
perhaps supported by more industry-specific indicators (e.g. defects per
1000 cars in auto assembly, as in MacDuffie, 1995). In other instances
different measures will be appropriate, for example in charitable organiz-
ations the percentage income redistributed will be relevant. So diversity of
performance measures consistent with the nature of the business is to be
expected. Of course such measures are not necessarily totally accurate (e.g.
organizations can bring forward or postpone costs for a given financial
year), but they are generally subject to external audit and, most importantly,
are collected independently from the measurement of the HRM practices.
This contrasts with the least desirable approach that relies on reported
performance from a single employee who is also the source of information
about the HRM practices.
The picture is more encouraging in this respect than for the measure-
ment of HRM, but is still far from ideal (Table 1, column 5). Ten of the 25
studies do use objective data, ensuring measures of performance come from
a different source than those of HRM practices. The other side of the coin,
of course, is that 15 of the studies rely on reported performance, in 12 of
which the information comes from the same person who assesses the HR
practices. It should be noted, however, that recent findings (Wall et al., 2004),
suggest that such common source self-report performance data may not
necessarily be as biased as one might expect.
Research design
There are two main types of HRM-performance study. Cross-sectional
studies are those in which both the independent and dependent variables are
measured on one occasion only (be these concurrent or not); whereas in
longitudinal studies either or both the independent and dependent variables
are measured on at least two occasions. Both types of study are of value.
Cross-sectional research is a cost-effective starting point for establishing that
two or more variables are related, and the absence of a cross-sectional
relationship would send warning signals that more costly longitudinal work
might not be justified. Also, cross-sectional work often allows the use of
much larger samples and hence augments generalizability. However, for
reasons that are well known, cross-sectional studies provide a weak
foundation for causal inference, for which longitudinal research designs are
to be preferred.
Within longitudinal studies, however, there are alternatives. The
simplest advance on a cross-sectional design is what we shall call the
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‘quasi-longitudinal’ study. Studies of this kind examine how the extent of use
of HRM practices at one point in time predicts subsequent performance,
while controlling for prior (or concurrent) performance. The advantage of
this over a simple cross-sectional study (e.g. concurrent performance only) is
that it can help control for reverse causality, that prior performance fostered
greater use of the HRM practices in question. This design, however, has some
problems, especially when the timing of the introduction of the HRM prac-
tices is unknown. If those practices had been introduced, say, 5 years before
the study, and had led to better performance over the 3 years prior to the
study, then controlling for that prior performance would effectively be
removing the effect of interest. Consequently, whereas quasi-longitudinal
research that shows a positive relationship with performance adds to our
understanding, if it fails to do so the interpretation is unclear.
A stronger option is what we shall call the ‘authentic longitudinal’
study. Research of this kind would involve measurement of both the inde-
pendent and dependent variables on two or preferably more occasions. For
example, at Time 1 one would measure both HRM practices and perform-
ance, at Time 2 the HRM practices again, and at Time 3 performance for a
second time. The timing of the measurements would be determined accord-
ing to a hypothesized lag for the effect of HRM on performance. Evidence
consistent with a causal interpretation would require change in HRM to be
associated with a subsequent change in performance. In this way, one is
testing whether an increase (or decrease) in the use of the relevant practice(s)
is associated with a subsequent improvement (or deterioration) in perform-
ance; and stable third factors (e.g. sector, product mix) are controlled for
through the repeated measures design. The design would be further improved
by focusing only on those organizations in which the HRM practices have
been introduced (or substantially enhanced) between the performance
measurement occasions; or by intervention studies (with controls).
Judged against the above criteria, the design of existing studies is
disappointing. As shown in Table 2, 21 of the 25 studies are purely cross-
sectional (Table 2, column 2), providing very weak grounds for causal infer-
ence. Moreover, 17 of these 21 cross-sectional studies are what Way (2002)
describes as ‘temporally backward predictive’ (p. 779), that is to say they
involve a relationship between current HRM and prior performance. This is
self-evident where authors explicitly report having used previous perform-
ance data (e.g. Arthur, 1994; Batt, 2002). Moreover, even in those studies
that use concurrent performance (e.g. Delery & Doty, 1996; Guthrie, 2001
– or the average of previous and concurrent performance data as in the case
of Youndt et al., 1996), the grounds for inferring causality, were it to be
linked to HRM, would be weak. This is because most concurrent measures,
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Table 2 Research design and findings of empirical studies on HRM and organizational performance
Study Research Control for Main effects (summary, Interaction Individual
design third factors statistical significance, hit rate) effects practice effects
1 Arthur Cross-sectional Age, size, Commitment systems show higher Not examined Not examined
(1994) unionization and reported productivity (p < .05) and
business strategy lower scrap rates (p < .05). 2/2 predicted
effects
2 Guest and Cross-sectional No No differences across four types. Not examined Not examined
Hoque (1994) 0/6 predicted effects
3 Huselid Cross-sectional For example size, Skills and structures related to GRATE Internal fit for skills and Not examined
(1995) capital, R&D, intensity, (p < .05, one-tail); motivation related structures motivation
unionization, sector to productivity and Tobin’s Q (p < .01, for GRATE; strategic fit
one-tail). 3/6 predicted effects for motivation HR
strategy – 2/14
4 MacDuffie Cross-sectional Degree of Work systems related to productivity Internal/organizational fit Not examined
(1995) automation, volume, (p < .05); and work systems and HRM – work systems HRM
complexity, product policies to quality (at p < .05 and p < .01, policies buffers for
design, age respectively). 3/4 predicted effects productivity; work systems
buffers, for quality – 2/8
5 Delaney and Cross-sectional Many, e.g. size, HRM practices collectively (block in Selected internal fit Training and incentive
Huselid (1996) age, product vs. regression) associated with perceived interactions examined (e.g. pay associated with
service, unionization, organizational and market performance staffing training) but organizational
sector (p values unspecified). 4/10 (i.e. five HR none found – 0/8 performance; staffing
practices two performance measures) selectivity and
predicted effects incentive with market
performance
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6 Delery and Cross-sectional Size (assets), age, Appraisals (p < .05), profit sharing Strategic fit, individual HR As for main effects
Doty (1996) district (p < .01) and security (p < .01) related practices with
to ROA; only profit-sharing with ROE product/market
(p < .01). 4/14 predicted effects innovation. One found
(appraisal innovation) – 1/14
7 Koch and Cross-sectional Size, sector, HR planning and hiring related to HR sophistication capital As for main effects
McGrath unionization, R&D, productivity (p < .05 and p < .01 intensity, showing the effect
(1996) capital intensity respectively); development and of HR is stronger for higher
sophistication not. 2/4 predicted effects capital intensity – 1/1
8 Youndt et al. Cross-sectional Size, growth, change Administrative HR no effects; human Single-instance of strategic Not examined
(1996) in sales, product capital-enhancing HR related to fit – administrative HR
complexity, strategy reported productivity (p < .01), but quality strategy at p < .05 –
(cost, quality, delivery, not to customer alignment or machine 1/8
scope) efficiency. 1/6 predicted effects
9 Huselid Quasi-longitudinal Unionization, size, Strategic HRM related to subsequent Not examined Not examined
et al. (1997) R&D, sector, GRATE (controlling for concurrent,
concurent p < .05) but not productivity or
performance and Tobin’s Q; technical HRM unrelated
others to any performance measure. 1/6
predicted effects
10 Ichniowski Cross-sectional Up to 25 for technical Lines with innovative HRM systems No conventional test; but All components (e.g.
et al. (1997) and longitudinal reliability (e.g. age have greater productivity (p < .01); lines system dummies explain selection, training)
and speed of line) becoming more innovative in HRM productivity over and above have individual effects,
over time showed increased additive effects of none additional to
productivity (p < .01). 1/1 predicted component practices system
results
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Table 2 continued
Study Research Control for Main effects (summary, Interaction Individual
design third factors statistical significance, hit rate) effects practice effects
11 Wood and Cross-sectional Many, e.g. size No difference across four types of Not examined Not examined
de Menezes sector, unionization workplace on productivity or change in
(1998) productivity; some effect for financial
performance but not as expected. 0/3
predicted effects
12 Hoque (1999) Cross-sectional Size, unionization, Overall HRM related to productivity, Not formally tested, but Not examined
country of quality and financial performance sub-group analyses suggest
ownership, strategy (p < .01 in all cases). 3/3 predicted effects interaction with business
strategy
13 Jayaram et al. Cross-sectional Size Cost (p < .01), flexibility (p < .05) and Not examined Not examined
(1999) time (p < .05). Each aspect of HRM
related to its own outcome
(e.g. HRM cost to cost performance);
HRM generic related to time
performance only (p < .05).
4/8 predicted effects
14 Vandenberg, Cross-sectional No Flexibility positively associated with Not examined Not examined
et al. (1999) ROE; incentives and direction-sharing
negatively related to ROE; training and
work design unrelated to ROE; p < levels
unclear, and insufficient detail of analysis.
1/5 predicted effects
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15 Wright Cross-sectional Technology, size, age Only training related to financial Internal fit – selection, pay and As for main effects
et al. (1999) performance – negatively (p < .05). 0/4 appraisal interact with
predicted effects participation (positive effect
where participation is high,
strong negative effect where
participation is low) – 3/4
16 Bae and Cross-sectional Unionization, sector, HRM strategy positively associated Not examined Not examined
Lawler (2000) country of origin with self-report (p < .05) and both
concurrent (p < .01) and subsequent
(p < .05) objective (ROIC) performance
measures. 3/3 predicted effects
17 Fey et al. Cross-sectional Sector, size, years Overal performance associated with Not examined As for main effects
(2000) operating in Russia promotion on merit for managers, and
job security for other employees. 2/16
predicted effects
18 Cappelli and Longitudinal: two Many, including For none of the eight practices did their Internal fit between self- As for main effects
Neumark sets of panel production function, introduction relate to either productivity managed teams and profit
(2001) data, 1977–93, age, sector or change in productivity in the sharing. No effects for nine
n = 433 and 1977–93 panel data set. Of the three other theoretically specified
1977–96, n = 666 practices in the 1977–96 panel data interactions (e.g. teamwork
set, one (job rotation) related to both training self-managing
outcomes, but negatively. Thus 0/8 and teams) – 1/10
0/3 predicted effects
19 Guthrie (2001) Cross-sectional Size, age, HIWP positively associated with HIWP with labour retention Not examined
unionization, sector, reported productivity (p < .01). 1/1 (positive effect of HIWP for
relative pay predicted effect firms with high labour
retention, negative for low)
– 1/1
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Table 2 continued
Study Research Control for Main effects (summary, Interaction Individual
design third factors statistical significance, hit rate) effects practice effects
20 Richard and Cross-sectional Size, part of holding SHRM not related to either ROE or Strategic fit, HRM with Not examined
Johnson (2001) company/not, productivity. 0/2 predicted effects capital intensity to predict
location, ROE (HRM has stronger
organizational stage positive relationship with ROE
(e.g. start up, growth) the greater the capital
intensity), but not
productivity – 1/2
21 Batt (2002) Cross-sectional Sector, unionization, Work design and HR incentives Composite HR index interacts As for main effects
customer segment positively related to sales growth with segment: stronger effect
(p < .05 and p < .01 respectively); no of HR on sales growth in
effect for skill level. 2/3 predicted effects residential and smaller centres
22 Way (2002) Cross-sectional Sector, unionization, No statistically significant relationship Not examined Only, performance
size, capital intensity with productivity ratio; positive pay associated with
relationship (p < .05) with overall perceived productivity
perceived productivity (p < .05)
23 Ahmad and Cross-sectional Country, sector Practices related to performance at Not examined As for main effects,
Schroeder p < .05 or p < .01 in 9/12 cases. But the but not controlling
(2003) analysis fails to control for other for others
practices (all of which are highly
intercorrelated), hence proportion
of predicted effects unclear
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24 Guest et al. Quasi-longitudinal Size, sector, Use of HRM practices unrelated to Not examined Not examined
(2003) unionization, subsequent productivity or profit (when
consultation, HR prior productivity or profit controlled).
cost strategy, prior 0/2 predicted effects
performance, others
25 Wright et al. Cross-sectional None, but all HR practices not statistically significantly Not examined Not examined
(2003) (HR T1, business units in related to productivity but positively
performance T2 same corporation and related to profit (p < .05). 1/2
– 3–9 months fairly homogenous predicted effects
later)
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and certainly financial ones, though ostensibly covering the same period
when the HR practices data were collected, necessarily reflect the result of
prior performance. There is a lag built into performance data, as it takes time
to sell, receive payment for and bank income, which is then aggregated over
a financial year. At face value, therefore, such cross-sectional studies could
be seen as examining the effect of performance on HRM practices rather
than vice versa.
Of the four non-cross-sectional studies, two are quasi-longitudinal
(Guest et al., 2003; Huselid et al., 1997). That is to say, they include repeated
measurement of performance, but a single measurement of HRM practices.
The first of these studies controls for concurrent performance, and the other
for prior performance (Table 2, column 5). However, in neither case is it clear
whether the earlier measurement of performance preceded the introduction
of the HRM practices, so causal inference is difficult. Only two studies
(Cappelli & Neumark, 2001; Ichniowski et al., 1997) have an authentic
longitudinal design on which causal inferences about the relationship
between HRM practices and performance could justifiably be based; and, as
we shall see later, they yield divergent results.
Control for third factors
Especially in cross-sectional studies there is a need to control for third
factors, that is, variables that may account for an association between HRM
practices and performance. For instance, if larger organizations, those with
greater (or lesser) trade union involvement, or those in particular sectors,
tend to have both more sophisticated HR provisions and better performance,
then a relationship between HR and performance would be found for one
or other of these reasons. Better studies will use controls for third factors,
less satisfactory ones will not.
Overall, the studies do well in this respect. Control for third factors is
evident in all but two studies (Table 2, column 3). Size is included in the large
majority of studies, but there is considerable variability with respect to which
other factors are controlled. Our judgement, however, is that the variability
is largely consistent with the nature of the study (e.g. controls for sector in
heterogenous samples, and for product complexity when examining build-
hours on assembly lines).
Main effects
Our summary of findings for the relationship between HRM and perform-
ance is based on the most sophisticated analysis presented by the authors,
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but before any tests for interactions. Thus if both zero-order correlations and
regression analyses controlling for third factors are presented, it is the
findings from this that are used. However, if regression analyses excluding
and including interaction terms are presented, we rely on the findings from
the former. We adopt the latter position to increase comparability between
studies that did and did not test for interactions (see next section). We also
only accept findings that are statistically significant at p < .05. For ease of
presentation in Table 2 (columns 46), and in places in the text that follows,
we refer to findings as effects in line with the allocation of variables to predic-
tor and outcome status within regression analysis. However, we do not
intend this to signify a causal link.
The main effect findings are summarized in Table 2, column 4. These
show that 19 of the 25 studies report some statistically significant positive
relationships between HRM practices and performance. At the same time,
however, six studies fail to find any such relationships (e.g. Cappelli &
Neumark, 2001; Guest et al., 2003), and in one of these (Wright et al., 1999)
there is a statistically significant negative relationship (between training and
financial performance). In parentheses, it is interesting to note that there is
no evidence that studies using self-report measures of performance provide
more positive findings than those using objective measures.
The balance of evidence towards positive relationships is weakened
by the lack of consistency within studies. The large majority used multiple
performance indicators, and many also used multiple HRM measures. This
means that there were multiple opportunities to show HRM–performance
relationships, of which only a few are statistically significant. This is shown
by the hit rate also reported in Table 2, column 4. In Huselid’s (1995)
seminal study, for example, we should judge the finding that the employee
motivation HRM scale was statistically significantly associated with
productivity and Tobin’s Q against the fact that the employee skills and
structures HRM scale was not statistically significantly related to either of
these performance outcomes. Correspondingly, though the employee skills
and structures HRM scale was related to GRATE, the employee motivation
HRM scale was not. Similarly, Delery and Doty (1996) identified seven
aspects of HRM and two performance indicators. Only 4 of the 14 relation-
ships were statistically significant. Other studies involving more than a
single relationship are equally patchy (e.g. Youndt et al., 1996, with one of
six predicted effects).
Moreover, effect sizes are typically small, and the criteria used to judge
statistical significance, and hence to draw conclusions about the reliability of
findings, are often lenient, even in large sample studies. With a sample of
more than 800, for example, Huselid (1995) recorded an effect size for his
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two comprehensive measures of HRM combined on productivity of only 1
percent, and treated one-tailed p-values of < .10 as statistically significant.
Similarly, Wood and de Menezes (1998), also with a sample of over 800
establishments, use a p < .10 statistical significance criterion.
The acceptance of small effect sizes and the use of moderate levels of
statistical significance are perhaps indicative of a more general tendency in
the literature towards over-positive interpretations of results. Guest and
Hoque (1994), for instance, distinguished between four types of HRM
system but found no statistically significant difference across them on
reported productivity or quality. This did not prevent them concluding that
‘the results demonstrate that strategic HRM pays off’ (p. 11). Virtually all
authors reach positive conclusions irrespective of the strength and consist-
ency of their findings.
Interaction effects (fit)
All studies of the HRM–performance relationship would benefit from tests
for interaction effects, and this is so for several reasons. If the hypothesis is
that HRM practices have a universal effect on performance, then it adds
strength to any observed main effect to show it is invariant across different
circumstances (e.g. according to sector or company size). Conversely, if
theory predicts internal, organizational or strategic fit, then tests of inter-
actions are relevant for that purpose. Whatever the particular theoretical
rationale, the basic point is that investigating possible interaction effects is a
means of more fully understanding the nature of any observed relationship
between HRM practices and performance, and enhancing the construct
validity of the study.
Twelve of the 25 studies do not report tests for interactions. Of the
other 13, 2 test for interactions using non-standard methods (e.g. sub-group
analysis), and the remaining 11 deploy orthodox tests (e.g. moderated regres-
sion). Looking at those studies in more detail, the emphasis is on internal
and strategic, rather than organizational, fit. However, the main impression
is of considerable variation in the interactions examined and inconsistency
in the findings recorded. Thus there is no compelling evidence either of
synergy within HRM systems (i.e. that the effects of systems as a whole is
greater than the additive sum of their parts), or of any systematic strategic
fit effects.
Individual practice effects
Most studies of the HRM–performance relationship aggregate individual
practices into multi-component scales (e.g. Huselid, 1995; Way, 2002), or
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less commonly they group organizations on the basis of their HRM profile
(e.g. Ichniowski et al., 1997; Wood & de Menezes, 1998), in order to test
for effects. An argument for this approach is that one would expect a
composite of HR practices to have a greater impact on overall organizational
performance than any single practice. Nonetheless, all those composite
measures include particular practices (e.g. training, empowerment, and
performance-related pay) each of which may enhance performance in its own
right. Thus the question arises as to whether one or a few among those
constituent practices may account more parsimoniously for any observed
effect of the overall HRM system on performance, or whether all are an
integral part of the whole. This is not only of theoretical importance, but is
also an issue with practical significance for managers wishing to stage the
implementation of beneficial HR practices and avoid ineffectual ones. Thus
examination of the relative effects of different component practices adds to
the construct validity of the investigation.
This issue has been ignored in the majority of studies. Fifteen of the
studies (Table 2, column 5) use composite measures of HRM without report-
ing any findings for their component practices. Results for component prac-
tices from the other 10 studies do not show any consistent pattern. Given
this lack of evidence, it is difficult to be certain that it is the HRM system
that relates to performance rather than one or particular sets of its
components.
A wider consideration
A final methodological issue, not covered in Tables 1 and 2 because it is
largely invariant, concerns the nature of the measurement of HRM practices.
With only one exception (Huselid et al., 1997), studies have focused simply
on the use of the practices. It could be argued, however, that effective use
may be a better measure. This is because the inadequate implementation of
a given practice may do more damage than no implementation at all. For
example, adopting team briefings without allowing employees to express
ideas may have a worse effect than not considering such involvement at all.
Expert witness testimony: part 2
The second question addressed to our expert witness concerned whether
available evidence could be interpreted as establishing a causal link between
HRM practices and performance. The advice has to be that the evidence is
promising but only circumstantial. The unknown reliability of measures of
HRM, the paucity of studies with adequate research designs, and the incon-
sistent results both across and within studies is troublesome. Taken together
with the likelihood that positive findings are more likely to be published than
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negative ones, it is clear that existing evidence for a relationship between
HRM and performance should be treated with caution.
Summary and discussion
The conclusion from our analysis is that it is premature to assume that HRM
initiatives will inevitably result in performance gains, either in all situations
or even where deemed appropriate by contingency arguments. Consultants
who promote the HRM model are reflecting a wider academic and business
school perspective in which this approach is central to definitions of moder-
nity in management. Governments, employers’ associations, professional
associations such as those representing personnel managers, and even trade
unions, throughout the world, have also promoted high-commitment HRM
as the approach most suited to the assumed increasingly turbulent inter-
national economy.
Our assessment is that, although consultants are acting in good faith,
and their views are seemingly reinforced by the presumption on the part of
academics that HRM systems actually do promote organizational perform-
ance, the empirical evidence is as yet not strong enough to justify that
conclusion. The cross-sectional evidence could be over-estimating such a
relationship due to contamination between measures of the HRM and
performance. Conversely, studies could be underestimating the strength and
consistency of the relationship through inadequate measurement of HRM
practices. We lean to the latter view, because while there is little evidence of
common method bias leading to spurious conclusions (Wall et al., 2004)
there are strong indications of poor measurement of HRM practices (Gerhart
et al., 2000) that would produce attenuated effects. Moreover, regardless of
the quality of data, the paucity of longitudinal studies also makes causal
inference dubious. So the evidence is at once encouraging but ambiguous.
Because there also remain strong theoretical grounds for believing an HRM
system centred on enhancing employee involvement should be beneficial for
organizational performance, research that overcomes the weaknesses of
current studies is required.
Implications
There are three main implications of our analysis. First, there is a need, on
the basis of the findings so far, to temper the claims being made. A first step
is to moderate the language used. The term ‘high performance’ clearly
presupposes the very effects researchers should be investigating, and should
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be avoided. Other terminological changes would also help foster a more
temperate debate. For example, use of words such as ‘impact’, ‘determinant’
and ‘effect’ when presenting cross-sectional findings, a practice too often
evident in the existing literature, should be avoided in favour of terms such
as ‘associated with’ or ‘related to’.
Second, adopting a strategy of articulating and investigating the
relative merits of competing hypotheses may encourage more rigorous and
disinterested research. This has long been advocated (see Chamberlin’s
‘method of multiple hypotheses’ as proposed in his presidential address to
the US Academy of Science in 1890; reprinted in Science, 1965) as a means
of combating bias in science, and is now more feasible than ever given
developments in computing and statistical methods, such as structural
equation modelling. By evaluating competing hypotheses it is less likely that
researchers will align themselves with a particular hypothesis. One of the
attractions of some of the early studies, most notably Huselid’s (1995) and
Delery and Doty’s (1996), was precisely that they aimed to test between the
universalistic and contingency theories of HRM. However, the selection of
competing hypotheses needs to be much broader. For example, these could
include hypotheses of differential impacts of HRM systems depending on the
performance measure used. Such development must, in our judgement, go
hand-in-hand with theoretical development.
Third, and most importantly, the need is for research designs that
overcome the problems of existing studies. Among these, three weaknesses
are paramount. The first is the reliance on single-source measures of HRM
practices (e.g. from CEO or HRM manager) of unknown reliability, sensi-
tivity and validity, often from the same source as the measure of perform-
ance. The second is the use of small samples coupled with low response rates.
The third is the lack of sophisticated longitudinal studies, especially ones
examining how change in HRM practices relates to subsequent change in
performance. We now discuss the methodological implications of those three
weaknesses for future research.
Independent audit of HRM practices
Others have already pointed to the need to improve the reliability and validity
of measures of HRM by obtaining data from multiple sources
(e.g. Wright & Gardner, 2003). We would go further to suggest that it is essen-
tial to have an independent audit of HRM and to cover comparison practices
(e.g. R&D emphasis, total quality management). The audit should be
conducted by individuals from outside the organization but familiar with the
wider use of the practices in question, so that they can calibrate their
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assessments accordingly. They would draw on multiple respondents and
sources of data within organizations, and develop methods to achieve a high
degree of concordance across different auditors. They would measure both
the extent and effective use of practices, and be unaware of the performance
of the organization. The use of selected comparator practices would enable
determination of the importance of HRM practices relative to others. Because
size of effect can have limited meaning, it is instructive to know if HRM prac-
tices have a stronger or weaker relationship with productivity than other prac-
tices or factors (e.g. R&D expenditure). Expanding predictor variables in this
way also allows tests for possible interactions between HRM and such other
practices (e.g. HRM with TQM, see Lawler et al., 1995).
Large samples, high response rates
Many of the important questions are ones that also require large samples.
Testing for a relationship between HRM and performance benefits from the
control of third factors, and also from examination of the effect of individual
component practices relative to each other and to measures of overall HRM.
The more such variables are taken into account, the more convincing any
relationship is observed. However, the greater the number of variables
involved, the larger the sample size required.
Sample size is even more of an issue when addressing theoretically
predicted interactions (i.e. the different types of fit), where the lack of sensi-
tivity of orthodox moderated regression means large samples are essential
(Aiken & West, 1991; Busmeyer & Jones, 1993). Of course, one could argue
that taking a universalistic perspective reduces the need for such large-scale
research. Yet, this is not so. Following our earlier call for testing competing
hypotheses, it is important to see whether the effect of HRM on perform-
ance is invariant across conditions (e.g. private vs. public sector; manufac-
turing vs. finance; strategic fit) rather than leave that issue unaddressed.
Finally, of course, large sample sizes, assuming also high response rates,
provide a firmer base for generalization.
Longitudinal research designs
The final requirement we emphasize, as do others (Guest, 1997; Wright &
Gardner, 2003), is the need for longitudinal research. Some such investi-
gations could be retrospective. Thorough independent audit of HRM prac-
tices, including evidence of when they were first introduced within
organizations, could be set alongside available data on performance going
back many years. Then the effect of the introduction of practices on
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performance could be estimated. Other studies should be prospective, based
on repeated independent audits, accepting the fact that findings will not be
available for several years. The advantage of prospective over retrospective
investigation is greater sensitivity and certainty in the measurement of
change, and better coverage of both use and effective use of HRM practices.
The case for big science
The principles underlying our design criteria are well known and widely
accepted as good practice. The weaknesses in the existing research designs
cannot, therefore, be attributed to investigators being unaware of how better
to conduct research. Rather, they stem from the almost inevitable limitations
of the small-scale funding that characterizes social science. Funding for an
individual or research team, over just a few years, does not provide the
resources to deploy the recommended methods. Consider the need for inde-
pendent audit, where experience suggests that it takes at least 2 days to
obtain the requisite information for a single organization (see Patterson et
al., 2004). Given such information should be obtained separately by at least
two individuals (to determine reliability), and for large samples of organiz-
ations (say 400 in five key sectors), the data collection task alone would take
many person years (i.e. 2 people 2 days 2000 organizations = 8000
days, which at 230 working days per year = some 35 person years). Add to
this the final recommendation, for the repeated measurement of practices and
performance as required by longitudinal research, and minimally the necess-
ary resource is doubled.
Research on that scale is seemingly beyond the scope of current funding
mechanisms. It is not, however, beyond the scope of more intensive collabor-
ation than is the current norm among the many potentially interested parties,
including academics, employer organizations, employee organizations,
professional bodies and government departments. The involvement of
government agencies is also important to encourage the desirable level of
compliance (i.e. high response rate). Moreover, there are precedents for such
activity. There are already numerous information-collecting exercises in
many countries with which individuals (e.g. the census) and organizations
(e.g. company financial reports) have to comply. There are assessments
within organizations based on independent audits (e.g. ‘Investors in People’
in the UK); and there are surveys based on collecting data through interviews
that are designed and managed by collaborative teams involving government
departments, research councils and academics, as in the case of the Work
Employee Relations Survey (WERS) series in the UK, or the equivalent
Australian survey.
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We propose that a big science project on management practices and
performance builds on the best features of these exercises by devising a new
study that covers practices well beyond employment relations and HRM,
uses independent audit of those practices, and is at the level of the company
or firm (rather than site) for which there is official financial performance
data. If academics, practitioners and policy makers are serious in wishing to
understand the effect of HRM and other practices on performance, then
these kinds of data will be required. They must also face the possibility, of
course, that no strong causal effects will be found.
Postscript
It will be appreciated that the focus of this article is on a particular issue
concerning HRM that has dominated recent research – the relationship of
high involvement forms of HRM with organizational performance. This
should not be allowed to mask the fact that, even if such a performance effect
were not demonstrable, the use of practices that enhance employee involve-
ment may be an end in itself. Such personnel management practices also may
be an important means of providing justice and equality of opportunity.
Other reasons for studying HRM practices and systems could then include,
for example, their role in enhancing employee well-being and promoting
non-discriminatory practices. It will also be recognized that the large-sample
quantitative approach taken here is a reflection of the question addressed.
Where an HRM effect on performance is established, then important ques-
tions concerning the conditions under which this applies, the mechanisms
through which it operates, and any unintended consequences of the HRM
practices, will require supplementary quantitative and qualitative investi-
gations. Such detailed research can also shed considerable light on why no
performance effects accrue when that is found to be the case. In other words,
our recommendation for big science should not be pursued to the exclusion
of complementary options.
Acknowledgements
The support of the Economic and Social Research Council (ESRC) UK is grate-
fully acknowledged. The work was part of the programme of the ESRC Centre
for Organisation and Innovation.
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Toby Wall is Professor of Work Psychology at the University of
Sheffield, where he is Director of the Institute of Work Psychology and
of the ESRC Centre for Organization and Innovation. His interests span
work design, innovation, employee well-being, absence, human resource
management, work and organizational performance, and applied research
design. He has published 12 books and over 150 articles in books and
journals. The latter include papers in the Academy of Management Journal,
Journal of Applied Psychology and Personnel Psychology. He has provided
policy advice to government departments and to numerous organiz-
ations.
[E-mail: t.d.wall@sheffield.ac.uk]
Stephen Wood is Research Chair and Deputy Director, Institute of
Work Psychology, Professor of Employment Relations, School of Manage-
ment, and Co-Director, ESRC Centre for Innovation and Organisation,
University of Sheffield. His current interests include high involvement
management, lean production, work design, idea capturing schemes,
family-friendly management, employment relations and the social and
economic challenges of nanotechnology. Publications include (with H.
Gospel) Representing workers: Trade union recognition and membership in
Britain (Routledge, 2003); The transformation of work (Unwin Allen, 1989);
and (with Richard Jones and Alison Geldart), The social and economic chal-
lenges of nanotechnology (Economic and Social Science Research Council,
2003). He has provided policy advice to government departments,
professional associations and public and private sector organizations.
[E-mail: s.j.wood@sheffield.ac.uk]
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Seven senior HR professionals, mainly general managers and HRs from various sectors viz. oil and gas sector, manufacturing, healthcare, construction, media, power and energy and retail were interviewed to understand how they are using AI in their respective fields. Inclusion Criteria: (1) Generally, the people covered under the research are from the decision-making level of their companies so they are in a position to give strategic perspective as well as day to day implication of implementation of AI. (2) Respondents have adequate knowledge of the respective industry to which they belong. (3) Respondents have reasonable industry of dealing with Human Resource Management and national economy as a whole assessment tool and its administration procedures. A narrative approach was adopted to have a better understanding of the research questions and comprehend their views regarding implementation of AI in their respective companies. A semi structured open ended interview was administered to steer the discussion around the research questions. The respondents were interviewed over the phone and each respondent shared their stories. Analysis of data: The narrations were then transcribed by online transcriber website otter.ai.com. The common keywords as prescribed by the website are as: AI, strategy, learning and implementation. The extracts of the discussions are noted in the next segment of the paper. As and when required this research also used secondary data from the journals, literature available in the websites to understand the implementation of AI globally. Findings A country where the government itself admits 90% of its workforce belongs to informal sector and conspicuously exits a multi-faceted stark digital divide (Huberman, 2001; DiMaggio et al. , 2001; Guillen, 2006; Servon, 2002) wherein gap of digital divide is significant between the rural and urban India (Dasgupta et al. , 2002; Nath, 2001; Singh, 2007; Mahajan, 2003; Dutta, 2003) talking of educating, applying and implementing AI seems to be “ a distant dream” but an “ambiguous ambition ” Research limitations/implications Prior to implementation of AI that India has to ensure, the basic hygiene factors of informal sector labor force like social security, 2008, low wages and lack of legal protection, unpaid overtime and occupational health problems, poor bargaining power, working without leave under coercion, child care issues and health ailments(for which mere legislation or statutarization is just a formality executed than taking real action) to take the majority of Indian workforce to attain the motivational factor to acquire the knowledge and skill of AI and to implement it. Practical implications The AI and its adoption are still at their embryonic stage in Indian companies. With the adoption of such sophisticated technology, in one side, the organizations are dreaming of efficiency, higher productivity and better organizational performance whereas on the other side requirement of changing skill sets and decreasing manpower, creating fear among the mass, which results in hard resistance against the implementation process of AI. On the other hand, lack of expertise and high cost of adoption is also hindering AI to implement in the organizations. The adoption and implementation stage of AI vary from organization to organizations, as well as functions to functions. While the marketing departments of several organizations are using advanced level of AI, there, the HR departments are using AI at the very initial stage. But it is evident from the above discussions that adoption of AI in business functions is inevitable and only it is a matter of time. With the COVID-19 pandemic this has become the utmost necessity for many organizations, particularly who works across the globe. HR partners of the businesses are also adopting AI at a fast pace to do away with the mundane works and deliver efficient services to the stakeholders. It is understood from the discourse that the prerequisite for a successful implementation of AI across the industries throughout the country, needs a concerted effort from industries, academia and government. Social implications The answer lies in Keynesian economics. The central tenet of which is government intervention rather investment to stabilize and progress the economy by way of spreading Internet connectivity, basic literacy and computer literacy, then only truly AI can be effective in a greater scale. Originality/value A study on application of artificial intelligence in the pandemic era from a wider perspective, this work is an empirical investigation into the benefits and limitations of artificial intelligence for human potential and labour -intensive pandemic ridden Indian economy.
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Purpose The absence of robust information on the application of Human resources managemnet (HRM) practices in the Arab Middle Eastern region has generated an urgent need to understand what and how HRM practices can be used to manage employees in the region. Therefore, building on the social exchange theory and job demands-resources (JD-R) model, this paper proposes a model to examine the effects of high-performance work systems (HPWS) on employees' work-related outcomes, namely, job performance, organizational citizenship behavior (OCB) and innovative work behavior (IWB) in a non-industry setting in an Arab Middle Eastern context. In this model, work engagement was theorized to serve as an intervening mechanism among the aforementioned relationships. Design/methodology/approach Data were collected from 210 academic staff working in the Palestinian higher education sector, together with evaluations from 30 supervisors. Structural equation modeling (SEM) was employed to analyze the data. Findings The results indicate that HPWS positively affect employees' job performance, OCB and IWB. Moreover, work engagement partially mediates these relationships. Practical implications The results can be useful for managers in the Middle East pertaining to the role HPWS can play in boosting employees' job performance, OCB and IWB. Originality/value HRM research in Middle East, although limited, is mainly focused on examining the impact of HPWS on organizational rather than individual outcomes. In response to the scholarly call made on the strong need to conduct more HRM research in the Middle East (Budhwar et al. , 2019), this research represents the first study that examines the impact of HPWS on in-role and extra-role performance in an Arab Middle Eastern context. Furthermore, the study contributes to the HRM research by relying on a sample from a non-industry sector rather than a sample from a manufacturing setting. Finally, this research is one of the few studies that explore the outcomes of HPWS in an academic setting through the intervening mechanism of work engagement.
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Purpose The paper investigates the moderating model of servant leadership (SL), customer citizenship behaviour (CCB) and Altruistic Work Value (AWV) among employees of 1-star and 2-star rated family hotels in Ghana. Design/methodology/approach Four hundred and fifty-two (452) respondents took part in the study. The respondents were selected using a convenient sampling technique and completed a self-reported questionnaire. Data were analysed using Partial Least Square Based Structural Equation Modelling (PLS-SEM). Findings Results of the study reveal that SL positively predicts customers’ Organisational Citizenship Behaviours (OCB). In addition, AWVs (1) directly influence customer OCB and (2) further moderate the nexus of SL and customer OCB. Practical implications Management of 1-star and 2-star family hotels should continuously monitor and evaluate employees' AWVs so that such behaviours can be constantly reinforced to retain them within their enterprise. Originality/value This paper is one of the pioneers to have tested a model including SL, OCB-C and AWVs in a family hotel context.
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