The International Journal of Human Resource Management, 2015

Vol. 26, No. 5, 616–639, http://dx.doi.org/10.1080/09585192.2014.934883

Role of line managers in human resource management:

empirical evidence from India
Feza Tabassum Azmi* and Shahid Mushtaq

Department of Business Administration, Faculty of Management Studies and Research,

Aligarh Muslim University, Aligarh, India
Of late, the line management role has been reorganized in business organizations and
they are now increasingly taking up responsibility for core HRM functions. Line
managers’ role in HRM has been recognized in academic research but it is likely impact
on the effectiveness of HRM that has remained relatively under researched, especially in
India. The focus of the study was, thus, to empirically examine the relationship between
dimensions of line managers’ role in HRM and effectiveness of HRM in the Indian
context. Primary data were obtained from HR managers of top-ranking companies
through a single cross-sectional survey based on a research instrument designed by the
researcher. The instrument was tested for unidimensionality, reliability and validity.
SEM capabilities of LISREL 8.50 were utilized to test the conceptual research model
based on the hypothesized relationships. The findings provided mixed support for the
conceptual model. The present research has implications for both academicians and
practitioners. The study is expected to serve as a guide in understanding the role of line
managers vis-a-vis HRM, a largely unexplored area in the Indian context.
Keywords: construct validity; effectiveness of HRM; line managers; role measures;
status of HRM; structural equation modelling

Conceptual background
With an unpredictable economy looming large and dramatic changes happening in the
business environment across the globe, business organizations need to react quickly – they
must exhibit strategic agility. Organizations need to constantly renew themselves for long-
lasting advantage. This clearly mandates the need for a sound people management
approach to be adopted by organizations at all levels.
In this context, Valverde, Ryan and Soler (2006) pointed out that human resource
management (HRM) is not limited to human resource (HR) departments; other internal
agents such as line managers are also involved in management of HR. Papalexandris and
Panayotopoulou (2005) and Whittaker (1990) considered all managers as people
managers. Line managers, who traditionally have held only operational responsibility of
managing people, have emerged as an important participant in managing HRs and their
role in HRM has continued to increase over time (Lowe 1992; Schuler 1992; Storey 1992;
Hutchinson and Wood 1995; Keen and Vickerstaff 1997; Papalexandris and
Panayotopoulou 2003).
The role of line managers vis-à-vis HRM has been examined by several researchers
(e.g. Budhwar and Sparrow 1997; Keen and Vickerstaff 1997; Budhwar 2000a, b;
McCracken and Wallace 2000; Macneil 2001; Gibb 2003; Kulik and Bainbridge 2006;
Valverde et al. 2006; Šiugždiniene 2008; Agrawal 2010; Srimannarayana 2010). Line
managers or middle managers are placed below the top managers and are responsible for

*Corresponding author. Email: ftazmi@gmail.com

q 2014 Taylor & Francis

 The International Journal of Human Resource Management 617

supervising other managers. Apart from this, supervisors, first line managers, lower-level
line managers, front-line manager, operational managers are also considered line
managers (Heraty and Morley 1995; Hall and Torrington 1998; Budhwar 2000a, b; Bond
and Wise 2003; Kulik and Bainbridge 2006, and others). The scope of these mangers has
traditionally been limited to establishing and meeting the goals in their respective
departments.
Of late, the line management role has been reorganized in the organizations and they
are now responsible for core HRM functions. Line managers play an important role in
producing the synergy between physical and HRs for the development of their
subordinates (Brewster and Larsen 1992). Line managers are responsible for achieving the
HRM goals and making sure that their subordinates show commitment, quality and
flexibility (Lowe 1992).
In this context, researchers have used the term devolution to define the role of line
manangers. The word devolution has been defined as the reallocation of personnel tasks to
line managers (Armstrong and Cooke 1992; Storey 1992; Cunningham, Hyman and
Baldry 1996; Hall and Torrington 1998; Brewster and Larsen 2000; Renwick 2000).
Devolution as a subject of inquiry has received considerable research attention (e.g. Tsui
and Milkovich 1987; Poole and Jenkins 1997; Currie and Procter 2001, among others).
Devolution to the line implies that line managers should become more involved in HRM
so that HR staff can take on a greater strategic role (Legge 1995; Sisson and Storey 2000;
Finegold and Frenkel 2006).
A number of scholars have carried out studies dealing with specific areas of HR
devolution, for instance Marchington’s (2001) and Fenton-O’Creevy’s (2001) studies of
middle managers’ attitudes towards employee involvement, Redman’s (2001) study about
devolvement of performance appraisal function, Currie and Procter’s (2001) work on the
area of pay and Dunn and Wilkinson’s (2002) study in the area of absence management.
Line managers are responsible for the implementation of HR practices at the operational
level (Marchington 2001; Gratton and Truss 2003). Further, the effective implementation
of these HR practices is dependent on line managers’ capability and commitment
regarding their HR role (Guest 1987; Storey 1992; Purcell and Hutchinson 2007).
Cunningham and Hyman (1999) reported that many organizations are increasingly
devolving personnel responsibility to line managers. This has been attributed to growing
competition. The study finds that devolved responsibilities of personnel are formally
geared to securing commitment from employees by promoting an integrative culture of
employee management through line managers.
Line management has been identified as the perfect location to position HR
responsibilities as it would make HR more effective (McGovern, Gratton, Hope-Hailey,
Stiles and Truss 1997; Hope Hailey, Farndale and Truss 2005). Restructuring of the business
organizations entails the reallocation of HRM responsibilities to line managers (Brewster
and Larsen 1992; Cunningham et al. 1996; Hall and Torrington 1998; Renwick 2000). At the
same time, line managers’ involvement in HRM helps the HR managers to take on strategic
roles in their organizations (Legge 1995; Storey 1995; Finegold and Frenkel 2006).
Previous research studies in the area suggest that the involvement of these line managers in
HRM is critical to the effectiveness of HR (Currie and Procter 2001; Brewster, Mayrhofer
and Morley 2004; Purcell and Hutchinson 2007). Watson and Maxwell (2007), on the basis
of case study evidence, argued that line managers’ knowledge on the basis of their
involvement in HR tasks may improve their performance in HR activities.
The decentralization of HR responsibilities to the line is an important aspect of
strategic HRM. Line management has been viewed as increasingly taking HR
618 F.T. Azmi and S. Mushtaq

responsibility (Clark 1998). In many organizations today, line managers carry out
activities which were traditionally performed by HR specialists (Storey 1992). According
to Green, Cindy, Whitten and Medlin (2006), partnership between HRM and line is getting
acceptance in business organizations.
One of the major changes that affect line managers’ involvement in HRM is the
advancement of technology. The growth in the field of information technology can help
simplify HR processes and deliver HR services to the line managers making it possible for
the line to have greater involvement in day-to-day HR activities (Papalexandris and
Panayotopoulou 2003). Renwick and MacNeil (2002) noted that the use of information
technology tools has made it possible for line managers to deal with HR tasks without the
assistance of the HR department (Brewster and Larsen 2000).
Various research studies have recognized the role of line managers in HRM decision-
making (Hall and Torrington 1998; Bond, Hyman, Summers and Wise 2002; Larsen and
Brewster 2003). Researchers such as Bond et al. (2002), Hall and Torrington (1998),
McCracken and Wallace (2000) have vouched for enhancing the decision-making power
of line managers vis-a-vis HRM. In addition to this, some researchers have explored the
line management responsibility in operational aspects of HRM processes/activities, while
some have also explored the dimension of financial power and pointed out its importance
in performing HR tasks (e.g. McConville and Holden 1999; Brewster et al. 2004; Cascón-
Pereira, Valverde and Ryan 2006).
The involvement of line managers in different HRM functions such as workforce
expansion and reduction, performance appraisal, pay and benefits, recruitment and
selection, training and development and industrial relations has been reported in various
studies (Hope-Hailey, Gratton, McGovern, Stiles and Truss 1997; Budhwar 2000a;
Mahoney and Brewster 2002; Larsen and Brewster 2003; Srimannarayana 2010). As a result
of line managers’ involvement in HRM, there is a paradigm shift in role and responsibilities
of HR mangers. Also, the reallocation of HR responsibilities to line managers has helped
business organizations to become leaner and improve overall organizational performance
(Guest 1987; Gennard and Kelly 1997; Thornhill and Saunders 1998).
The role of line managers vis-a-vis HRM deserves special research attention in the
Indian context. India has witnessed phenomenal growth during the last two decades and its
economy is growing at a rapid pace (Grossman 2008). The resulting HR challenges of
business organizations in India are thus becoming evident (Rao, Silveria, Shrivastava and
Vidyasagar 1994; Sodhi 1994; Venkata Ratnam 1995). Of late, Indian industry has
realized the importance of effectively managing its HRs. Subsequently, studies in the
Indian context have highlighted the emerging HR policies, practices and roles in business
organizations (e.g. Jain 1991; Stening 1994; Lawler, Jain, Venkata Ratnam and
Atmiyanandana 1995; Bhatnagar and Sharma 2004; Sharma and Khandekar 2006).
As the role of HR managers become more strategic in nature, traditional HR
responsibilities of HR managers are being reallocated to other stakeholders such as line
managers. Budhwar and Sparrow (1997) have explored the nature of devolution in India.
Azmi’s study (2010) examines the devolution-organizational performance link in the
Indian context. Gopalakrishnan (2008) makes a case for placing HR on line managers’
schedule. In a number of studies conducted in the Indian context, the focus is on working
relationship between line and HR (Agrawal 2010), line managers responsibility for HR
activities (Srimannarayana 2010) and perception of line managers on strategic HR roles
(Bhatnagar and Sharma 2004).
Although a number of perspectives exist on the theme of line management
involvement in HRM, there is still a dearth of sound empirical evidences. Most
 The International Journal of Human Resource Management 619

perspectives remain only theoretical discourses on line managers’ role vis-à-vis HRM.
Since most of the research in the area is based on qualitative methodology, there is a
scarcity of reliable and valid measures to study the role of line managers in HRM, more
specifically in the Indian context. Although prior studies have recognized the role of line
managers in HRM, yet there is limited empirical research on the key areas where these
roles are being played. Also most existing scales focus on a single dimension of the role of
line managers. The present study is an attempt to assimilate the leading viewpoints in the
area and construct a scale that incorporates the major dimensions. Owing to the increasing
importance of line management involvement in HRM, Hall and Torrington (1998) pointed
out the need to further explore the phenomenon and its impact on HRM outcomes.
Consequently, a need was felt to explore the role of line managers vis-a-vis HRM.
Since India is one of the world’s most compelling markets offering many business
opportunities for Indian and multinational companies, an investigation into the role of line
managers vis-a-vis HRM is likely to offer useful insights into the corporate terrain of
India. The dynamic business environment of India provides a unique opportunity for such
type of research studies.
Thus, the current study was carried out to achieve the following objectives:
. to develop a research instrument for measuring the role of line managers vis-a-vis
HRM;
. to establish unidimensionality, reliability, and validity of the instrument in the
Indian context; and
. to investigate the impact of line manager involvement vis-a-vis HRM on status and
effectiveness of HRM.

Study constructs
Study constructs were identified on the basis of an extensive review of literature.

Measures of role
The involvement of line manangers in HRM implies that HR staff can take on a greater
strategic role (Legge 1995; Sisson and Storey 2000; Finegold and Frenkel 2006). Various
studies have reported the rationale for placing HRM responsibility at the level of line
management. It gives line managers an opportunity to be directly involved in HRM and is
also likely to increase the speed of decision-making on HRM issues (e.g. Renwick 2000;
Larsen and Brewster 2003). Valverde et al.’s (2006) study revealed the contribution of line
managers’ involvement in HR decisions and day-to-day people management activities. In
addition to this, Cascón-Pereira et al. (2006) identified the tasks that are reallocated and the
degree of devolution along a number of dimensions such as decision-making power, tasks/
responsibilities, financial power and expertise power.
Storey (1995) suggested that line managers should be closely involved as both the
deliverers and drivers of HR policies. Besides, Kulik and Bainbridge (2006) found
evidence of a trend within Australian organizations to reallocate people management
processes and activities to the line manangers. Hsu and Leat (2000) indicated the role of
line managers in HRM decision-making. Larsen and Brewster’s (2003) study revealed that
HR tasks and activities are increasingly transferred to line managers. Hall and Torrington
(1998) opined that budgetary controls have an important effect vis-a-vis involvement of
line managers in HR activities.
620 F.T. Azmi and S. Mushtaq

Numerous research studies have indicated the role of line managers in HRM (Brewster
and Larsen 1992; Legge 1995; Budhwar and Sparrow 1997; Clark 1998; Hall and
Torrington 1998; Budhwar 2000a, b; Renwick 2000; Papalexandris and Panayotopoulou
2005; Cascón-Pereira et al. 2006; Valverde et al. 2006; Lemmergaard 2009) but the degree
of involvement varies in light of different HRM functions. Researchers in the area have
pointed out the need to explore the role of line managers with respect to their involvement
in HRM decision-making, involvement in routine HRM processes and activities and
involvement in HRM budgeting (Cascón-Pereira et al. 2006; Valverde et al. 2006). Prior
studies have recognized the increasing role of line managers in decision-making vis-a-vis
HRM issues (Hall and Torrington 1998; Bond et al. 2002; Larsen and Brewster 2003). The
participation of line managers in HRM process/activities has been recognized by several
researchers (Fombrun, Tichy and Devanna 1984; Guest 1987; Thornhill and Saunders
1998; Brewster et al. 2004; McConville 2006; Nehles, van Riemsdijk, Kok and Looise
2006). In addition to this, some researchers such as McConville and Holden (1999) and
Cascón-Pereira et al. (2006) have also explored the dimension of financial power and
pointed out its importance in performing HR tasks. In the individual HR areas too, role of
line managers in HR decision-making and process/activities has been assessed (Budhwar
and Sparrow 1997; Poole and Jenkins 1997; Hall and Torrington 1998; Budhwar 2000a;
Currie and Procter 2001; McConville 2006). Hutchinson (1995) and Industrial Relation
Survey (1995) reported increasing line managers’ involvement in recruitment, discipline
and training decisions. Thus, it can be seen from the above discussion that decision-
making, process/activities and budgeting vis-à-vis HRM are the major dimensions of
interest in the studies on the role of line managers in HRM.
The above three dimensions have been explored in light of individual as well as groups
of HR activities in different studies. Some of the individual HR areas, where role of line
managers has been explored, include performance appraisal (Redman 2001; Andersen,
Cooper and Zhu 2007), pay (Hope-Hailey et al. 1997; Currie and Procter 2001), family
leave policies (Bond and Wise 2003), employee engagement (Fenton-O’Creevy 2001;
Marchington 2001), identification of training needs (Green et al. 2006), counseling (Nixon
and Carroll 1994), absence management (Dunn and Wilkinson 2002), training and
development (Heraty and Morley 1995), training (Ardichvili and Gasparishvili 2001;
Woodall, Alker, McNeil and Shaw 2002), HR development (Watson and Maxwell 2007),
industrial relations, health and safety (Hope-Hailey et al. 1997), recruitment and selection
(Wood 1995; Hope-Hailey et al. 1997), workforce expansion and reduction (Kramar and
Lake 1998) and reward management (Brown and Purcell 2007). However, several studies
have focused on more than one HRM function (Hall and Torrington 1998; Budhwar
2000b; Andolšek and Štebe 2005; Cascón-Pereira et al. 2006; Gautam and Davis 2007;
Watson, Maxwell and Farquharson 2007).
It can be inferred from the literature that most researches centre down to the role of line
managers in HRM with respect to their involvement in decision-making, budgeting and
process/activities vis-a-vis HRM. Therefore, in the present research too, role of line
managers was studied on the above dimensions The dimension decision-making seeks to
explore the level of involvement of line managers in HRM decisions and policy-making.
The second dimension, i.e. process/activities aims at exploring the level of involvement of
line managers in actual day-to-day HR activities. The third dimension, i.e. budgeting,
focuses on the level of involvement of line managers in financial issues vis-à-vis HRM.
The above three dimensions were explored in the present study with reference to the HRM
functions of HR planning, recruitment and selection, training and development, pay
management, performance appraisal and industrial relations. Thus, the independent
 The International Journal of Human Resource Management 621

variables considered for the study were:

. Line managers involvement in decision-making vis-a-vis HRM (LDM).
. Line managers involvement in process/activities vis-a-vis HRM (LPA).
. Line managers involvement in budgeting vis-a-vis HRM (LBU).

Effectiveness of HRM
Prior studies have indicated the new role of line managers in management of HR function.
This new role of line managers has led to the enhanced organizational effectiveness in
addressing people management issues (Schuler 1990). Besides, research studies have
indicated the positive impact of involvement of line managers on the overall effectiveness
of HRM (Budhwar and Sparrow 1997; Budhwar 2000a, b; Valverde et al. 2006). Several
research studies have supported the viewpoint that reallocation of HR responsibilities to
line managers has helped in enhancing overall performances (Guest 1987; Gennard and
Kelly 1997; Thornhill and Saunders 1998).
The involvement of line managers in HRM helps in motivating employees as well as
enhancing the people management and decision-making skills of line managers (Budhwar
and Sparrow 1997; Budhwar 2000a, b). As a result of line managers’ involvement in
HRM, the status and effectiveness of HRM are enhanced (Schuler 1990; Larsen and
Brewster 2003). Participation between HR and line helps in engendering positive
outcomes both for HR department and for the organization (Gennard and Kelly 1997).
In order to study the impact of the involvement of line managers in HR activities, the
effectiveness of HR function was considered as an important variable. Ferris, Hochwarter,
Buckley, Harell-Cook and Frink (1999) reveal that there are two perspectives of HRM
effectiveness that are in need of theoretical and empirical attention: (1) the effectiveness
with which HRM policies and practices are implemented; and (2) the effectiveness of
these practices in producing desired results.
Teo and Crawford (2005) have tested three measures of effectiveness of HRM which
were used in this study too:
. Influential effectiveness: This item measures the influence of HR department on the
organization.
. Relationship effectiveness: This item measures the relationships of HR department
with major stakeholder.
. Overall effectiveness: This item measures the overall effectiveness of HR
department.

Status of HRM
Edwards and Lambert (2007) and Frazier, Tix and Barron (2004) state that mediator is an
intervening variable that explains the relation between exogenous and endogenous
variables. Mediating variable helps to identify the mechanism through which the change
occurs (Tang, Yu, Crits-Christoph and Tu 2009). Prior studies have indicated that there is an
indirect relationship between the role of line managers in management of HRs and the
overall effectiveness of HRM (Hope Hailey et al. 2005; Valverde et al. 2006; Guest and
Conway 2011).
In order to study the impact of role of line managers in HRM on effectiveness of HRM,
status of HRM was seen as an indirect intervening variable. Various indicators of status of
HRM have been identified by researchers (e.g. Wood 1995; Kelly and Gennard 1996;
622 F.T. Azmi and S. Mushtaq

Hope-Hailey et al. 1997; Truss 2003; Budhwar and Boyne 2004; Mayrhofer and Brewster
2005; Sheehan 2005; Teo and Crawford 2005; Green et al. 2006; Azmi 2011). In the
current study, status of HRM was measured through items focusing on whether the HR
function had an important place in strategic affairs, position of HR departments,
representation of HR department at board level, position and responsibility of HR
executives, etc.

Organizational performance
Research studies on role of line managers have suggested the positive implications of
redistribution of HR activities among line managers for the business organization (e.g.
Bond and Wise 2003; Renwick 2003; Dany, Guedri and Hatt 2008; Azmi 2010). In this
context, some studies have established that participation between HR and line helps in
improving organizational performance (e.g. Gennard and Kelly 1997; Thornhill and
Saunders 1998; Dany et al. 2008; Azmi 2010). Renwick (2003) also argued in favour of
devolving HR tasks to line managers since significant organizational benefits exist from
involving the line in HR work. Moreover, devolvement of HR responsibilities helps in
configuration of HRM with business objectives and strategies associated with the firm
performance (Andersen et al. 2007). Some researchers have specifically reported the
positive implications of line managers’ involvement in HRM decision-making on
organizational performance (Hutchinson and Purcell 2003; McGuire, Stoner and Mylona
2008). Hutchinson and Purcell’s (2010) study revealed that front-line managers’
involvement is important for the delivery of effective HRM. Additionally, argued in
favour of the moderating impact of distribution of roles and influence between HRM
specialists and line managers on the link between HRM integration and organizational
performance.
For the current study, organizational performance was deemed as the final dependent
variable in order to examine the outcomes of line managers’ role in HRM. Organizational
performance was measured through data obtained from Business World.1
Table 1 lists down the study variables and the sources from where they were drawn.

Research model and hypotheses

Based on the above mentioned study constructs, the conceptual research model and
corresponding research hypotheses were specified. Exhibit 1 presents the conceptual
research model.
Specifications of the conceptual research model is:

PERF ¼ f fEFF; STA; LDM; LPA; LBU}

STA ¼ f fLDM; LPA; LBU};
EFF ¼ f fSTA; LDM; LPA; LBU};

where
PERF ¼ organizational performance
EFF ¼ effectiveness of HRM
STA ¼ status of HRM
LDM ¼ line managers involvement in decision-making vis-a-vis HRM
 The International Journal of Human Resource Management 623

Table 1. Constructs and items used in the study.

Constructs Indicative items Source

Line managers role HRM areas: Cascón-Pereira et al. (2006),
vis-a-vis HRM 1 HR Planning Budhwar (2000a, b), Hall and
1 Involvement in 1 Recruitment and selection Torrington (1998), among
decision-making 1 Training and development others
1 Involvement in 1 Pay management
process/activities 1 Performance appraisal
1 Involvement in 1 Industrial relations
budgeting
Effectiveness of HRM 1 Influential effectiveness Teo and Crawford (2005)
1 Relationship effectiveness
1 Overall effectiveness
Status of HRM 1 HR function has an important Azmi (2011), Budhwar and
place in strategic affairs Boyne (2004), Green et al.
1 Top-level teams include HR managers (2006)
1 Position of HR departments
1 Representation of HR department at
board level
1 Position and responsibility of HR
executives
Organizational 1 Overall company performance Business World (2009)
performance ranking

LPA ¼ line managers involvement in process/activities vis-a-vis HRM

LBU ¼ line managers involvement in budgeting vis-a-vis HRM.

Based on the above specified conceptual research model, following hypotheses were
considered for the study:
Hypothesis 1: Line managers involvement in decision-making vis-a-vis HRM (LDM)
has a direct and positive relationship with effectiveness of HRM (EFF).
Hypothesis 2: Line managers involvement in process/activities vis-a-vis HRM (LPA)
has a direct and positive relationship with effectiveness of HRM (EFF).

Exhibit 1. Conceptual model of research.

624 F.T. Azmi and S. Mushtaq

Hypothesis 3: Line managers involvement in budgeting vis-a-vis HRM (LBU) has a

direct and positive relationship with effectiveness of HRM (EFF).
Hypothesis 4: Line managers involvement in decision-making vis-a-vis HRM (LDM)
has a direct and positive relationship with status of HRM (STA).
Hypothesis 5: Line managers involvement in process/activities vis-a-vis HRM (LPA)
has a direct and positive relationship with status of HRM (STA).
Hypothesis 6: Line managers involvement in budgeting vis-a-vis HRM (LBU) has a
direct and positive relationship with status of HRM (STA).
Hypothesis 7: Line managers involvement in decision-making vis-a-vis HRM (LDM)
has a direct and positive relationship with organizational performance
(PERF).
Hypothesis 8: Line managers involvement in process/activities vis-a-vis HRM (LPA)
has a direct and positive relationship with organizational performance
(PERF).
Hypothesis 9: Line managers involvement in budgeting vis-a-vis HRM (LBU) has a
direct and positive relationship with organizational performance
(PERF).
Hypothesis 10: Status of HRM (STA) has a direct and positive relationship with
effectiveness of HRM (EFF).
Hypothesis 11: Status of HRM (STA) has a direct and positive relationship with
organizational performance (PERF).
Hypothesis 12: Effectiveness of HRM (EFF) has a direct and positive relationship with
organizational performance (PERF).

Methodology
The current research is conclusive, descriptive and based on single cross-sectional
research design. In order to attain the study objectives, primary data were collected from
leading business organizations operating across India. Following the footsteps of other
researchers in the area (Kydd and Oppenheim 1990; Budhwar and Sparrow 1997; Wan,
Kok and Ong 2002; Chan, Shaffer and Snape 2004), a list of top-ranking companies as
published in Business World was considered as the sampling frame for the present study.
Studying such organizations that are high performing, researchers could assume that HRM
is at least nominally supported (McGovern et al. 1997; Sheehan 2005).
Since the study was based on top-ranking organizations operating across India, it included
companies from different sectors and industries. This helps in generalizing the findings as
indicated by other researchers (e.g. Dyer and Reeves 1995; Purcell 1999). In order to collect
the data from the selected companies, a census approach to sampling was used.
The respondents of the study were senior HR executives (one from each firm). These
are assumed to be in a good position to provide the required information (Huselid and
Becker 2000; Chan et al. 2004). Senior HR executives have been used as respondents in
similar other studies too (e.g. Cunningham and Hyman 1995; Budhwar and Sparrow 1997;
Budhwar 2000a; Hsu and Leat 2000; Larsen and Brewster 2003; Andolšek and Štebe
2005; Valverde et al. 2006; Andersen et al. 2007; Gautam and Davis 2007; Perry and Kulik
2008). These studies considered the perception of senior HR practitioners since they have
direct responsibility for HR issues. Therefore, selection of senior level HR executives is
appropriate to obtain the information concerning HR issues.
Huselid and Becker (2000) have opined that choosing a knowledgeable informant
provides researchers more valid and reliable data than that gathered from multiple
 The International Journal of Human Resource Management 625

respondents. Becker and Huselid (2006) and Arthur and Boyles (2007) have also
supported the appropriateness of the use of a single ‘key’ informant. Empirical HRM
research has generally assumed HR systems to be objective and observable characteristics
of organizations, not individuals, and hence the data gathered from single HR manager do
not suffer much from subjectivity problems (Arthur and Boyles 2007). Moreover, Becker
and Huselid (2006) argued that multi-respondent designs in multi-industry HRM studies
are generally not practical because of the difficulty of obtaining sufficient response rates.

Research instrument
For primary data collection, a research instrument was designed based on the above
identified study constructs. The research instrument contained the following scales:
. Line managers involvement in decision-making vis-a-vis HRM: six item scale.
. Line managers involvement in process/activities vis-a-vis HRM: six item scale.
. Line managers involvement in budgeting vis-a-vis HRM: six item scale.
. Effectiveness of HRM (EFF): six item scale.
. Status of HRM (STA): three item scale.
Data on organizational performance were obtained from a published source, viz.
Business World, which also served as the sampling frame for the study (as already
discussed above).
The research instrument deployed a five-point Likert scale anchored with end points
marked as No involvement (1) to High Involvement (5), while for certain items Strongly
Disagree (1) to Strongly Agree (5) scale was used. Five-point scale has been commonly
used in HR research (e.g. Heraty and Morley 1995; Budhwar and Sparrow 1997; Budhwar
2000a; Ahmad and Schroeder 2003; Valverde et al. 2006).
A preliminary draft instrument was prepared keeping in view the constructs identified
from literature. Both types of translation validity, viz. face and content validity, were
ensured by following Ahmad and Schroeder’s (2003) method of having three senior
researchers in the area propose items for the instrument, which were then broadly
compared with the items in the draft instrument and changes were made accordingly.
Thereafter, it was reviewed by four researchers/academicians, two from HRM area and the
other two from research methodology area in order to ensure that the questionnaire
appeared reasonable and acceptable.

Pilot testing and data collection

The research instrument was pilot tested by administering it on 15 HR managers who were
asked not only to give their responses but also to provide their critical feedback of the
instrument in general and scale items in particular. After pilot testing, the questionnaire was
slightly modified thereby enhancing the translation validity (content and face validity) of
the instrument. Efforts were made to keep the items as simple, unambiguous and objective
as possible to avoid bias as recommended by researchers (e.g. Huselid and Becker 2000;
Podsakoff, MacKenzie, Lee and Podsakoff 2003; Chang, Witteloostuijn and Eden 2010).
In addition to this, the questionnaire colour was given due consideration to make the
questionnaire attractive and distinct as the questionnaire colour has an effect on the
response rate (Bender 1957; Jobber and Sanderson 1983; Fox, Crask and Kim 1988;
Phipps, Robertson and Keel 1991). Keeping this in view, the researcher has used different
colour combinations (Bender 1957) for both electronic and hard forms of the
626 F.T. Azmi and S. Mushtaq

questionnaire. Final data were collected from the sample organizations through mail
methodology (both e-mail and posts) and personal visits. Mail methodology has been used
by other researchers in the area too (e.g. Wood 1995; Budhwar and Sparrow 1997; Perry
and Kulik 2008).

Estimation of response rate and non-response bias

Completed survey questionnaires were received from 176 companies from a population of
550 giving a response rate of 32%. A response rate of 32% may be considered to be
reasonably high as compared to other studies conducted in the area (e.g. 16% Wood 1995;
8.56% Hall and Torrington 1998; 18.6% Budhwar 2000a; 17% Larsen and Brewster 2003;
10.5% Valverde et al. 2006; 5% Perry and Kulik 2008).
Hence, in the current study, the response rate of 32 % gives a sizeable number of
respondents to generate consistent statistical results. Following Jöreskog and Sörbom’s
(1993) formula [k (k 2 1)/2, where k equals the number of variables] to compute the minimum
sample size for estimation of the asymptotic covariance matrices, the total number of latent
variables in this research was 11, resulting in a recommended minimum sample size of 51
significantly smaller than our final sample size of 174. Thus, it can be safely concluded that
structural equation modelling was appropriate for the present research.
Non-response bias is checked to ascertain any potential bias due to the failure of
elements in the sample to respond. It is usual to use late respondents as substitute for non-
respondents to test for non-response bias since non-respondents have been found to
descriptively resemble late respondents (Armstrong and Overton 1977; Dean, Shook and
Payne 2007). Following this approach, the respondents were classified into two groups,
viz. early and late respondents and their responses were compared. The comparison of
responses did not reveal any significant differences which indicate that non-response bias
was not an issue in this study.

Estimation of common method bias

When predictor and criterion variable data are collected from a single respondent and with
similar methods, common method bias may lead to inflated estimates of the relationships
(Podsakoff and Organ 1986; Bagozzi, Yi and Phillips 1991; Doty and Glick 1998;
Podsakoff, MacKenzie, Lee and Podsakoff 2003; Spector 2006; Chang, Witteloostuijn and
Eden 2010).
Both procedural and statistical remedies recommended by different researchers were
followed to address the above problem (e.g. Podsakoff et al. 2003; Wall and Wood 2005;
Malhotra, Kim and Patil 2006; Chang et al. 2010).
Through procedural methods, the bias is minimized by appropriate design of the
research instrument such as scale reordering and respondent anonymity as recommended
by researchers (e.g. Salancik and Pfeffer 1977; Podsakoff and Organ 1986; Williams and
Buckley 1989; Podsakoff et al. 2003). The survey instrument used in this study was
structured such that role-related items for line managers preceded the items indicating
status and effectiveness of HRM.
Under statistical remedies, Harman’s one-factor test was used to examine the presence of
bias in the data. Common method variance is indicated by the emergence of either a single
factor or one general factor that explains a majority of the variance (Podsakoff and Organ
1986; Podsakoff et al. 2003; Gibbons and O’Connor 2005). The findings of exploratory factor
analysis (EFA) on all the variables together showed that five principal components with
 The International Journal of Human Resource Management 627

Eigen-values greater than 1 were extracted that accounted for 63.639% of the total variance.
Hence, the results suggest that the study does not suffer from common method bias.

Measurement model
Following the two-step approach as suggested by Anderson and Gerbing (1988) and
Gerbing and Anderson (1988), the measurement model was assessed before the structural
model. Measurement model helps to describe how well the observed indicators serve as a
measurement instrument for the latent variables (Garver and Mentzer 1999). If the chosen
indicators for a construct do not measure that construct, the specified theory cannot be
tested (Anderson and Gerbing 1991). Thus, the measurement model was estimated for all
the study scales in order to establish scale unidimensionality, reliability and validity.

Scale unidimensionality
Unidimensionality is an essential condition for assigning meaning to estimated constructs
before assessing reliability and validity of the constructs. For unidimensionality of the
scales, all cross-loadings are hypothesized to be zero (Hair, Black, Babin, Anderson and
Tatham 2008; Malhotra and Dash 2011). Factorability is assessed using Kaiser– Meyer –
Olkin (KMO) measure of sampling adequacy and the overall significance of correlation
matrix with Bartlett’s Tests of Sphericity (Dziuban and Shirkey 1974; Williams, Onsman
and Brown 2010). In the present case, KMO and Bartlett’s tests reveal the appropriateness
of the data for factor analysis in line with the recommendations of various researchers (e.g.
Peterson, Wahlquist and Bone 2000; Liu and Treagust 2005; Ang and Huan 2006). The
results of KMO and Bartlett Test of Sphericity for all scales are given in Table 2.
EFA was performed to assess unidimensionality. The results of EFA revealed that all
the scales were unidimensional with items loading of all the scales within the generally
acceptable limit of 0.5 as recommended by different researchers such as Bagozzi et al.
(1991), Garver and Mentzer (1999), Hair et al. (2008) and Malhotra and Dash (2011).
However, in case of LDM and LPA scales, one item was deleted in each scale having low
loadings (i.e. less than 0.5) following the procedure recommended by Hair et al. (2008).
Consequently, the loadings improved, thus giving a unidimensional scale. The
standardized loadings of the retained items of all the scales are listed in Table 3.

Reliability
After obtaining unidimensional scales, reliability estimates were generated For the current
study, two types of reliability estimates were computed: (1) indicator reliability and (2)

Table 2. KMO and Bartlett’s test of sphericity.

Bartlett’s test of sphericity
Kaiser – Meyer –Olkin measure of
Measures sampling adequacy (KMO) Approx. x 2 df Sig.
LDM 0.750 178.826 10 0.000
LPA 0.774 167.286 10 0.000
LBU 0.874 731.853 15 0.000
STA 0.852 439.407 15 0.000
EFF 0.694 159.844 03 0.000
628 F.T. Azmi and S. Mushtaq

Table 3. Scales-component matrix.

Scales Item 1 Item 2 Item 3 Item 4 Item 5 Item 6

LDM 0.724 0.834 0.702 0.629 0.575 X
LPA 0.604 0.682 0.758 0.739 0.706 X
LBU 0.815 0.905 0.867 0.860 0.820 0.789
STA 0.787 0.814 0.825 0.625 0.746 0.798
EFF 0.876 0.824 0.826 – – –
Note: Above table presents the standardized loadings of the retained items of all the scales; extraction method:
principal component analysis; rotation method: Varimax with Kaiser normalization.

scale reliability. Indicator reliability is measured for every single indicator (Wu 2005) and
should preferably be 0.5 or greater (Long 1983; Schumacker and Lomax 2004; Wu 2005).
Indicator reliability for majority of the scale items was more than 0.5 or close to it.
Scale reliability was assessed using Cronbach’s a. The generally agreed upon lower
limit for Cronbach’s a is 0.70 (Nunnally and Bernstein 1994; Hair et al. 2008) even values
as low as 0.35 that have been found acceptable when used with other measures (Roberts
and Wortzel 1979). Reliability estimates of the refined scales LDM, LPA, LBU, EFF and
STA returned Cronbach’s a values that were more than the lower limit of 0.70. Since
coefficient a may sometimes underestimate or overestimate scale reliability, therefore,
apart from Cronbach’s a, SEM based measures such as construct-reliability and variance
extracted were also assessed using LISREL as recommended by researchers (e.g. Garver
and Mentzer 1999; Hair et al. 2008). Hair et al. (2008) suggested that CR value higher than
0.6 implies that there is high internal consistency. Variance extracted at 0.5 or higher is
generally considered acceptable (Fornell and Larcker 1981). In the present case, the CR
and VE values either exceeded or were close to the recommended values. Cronbach’s a,
CR and VE values of all the scales as given in Table 4 suggest high reliability of the scales.

Validity
Since unidimensionality and reliability of the scales have been established, the researcher
proceeded with assessment of different types of validity such as convergent, discriminant
and nomological validity (Cooper and Schindler 2006; Trochim 2009).
Convergent validity: Convergent validity is the degree to which two measures of the
same concept are correlated and the items that are indicators of a specific construct should
converge or share a high proportion of variance in common (Kaplan and Sacuzzo 1993).
For the current study, factor loading of all scales was more than 0.5, thus indicating
presence of convergent validity as recommended by researchers (e.g. Mentzer, Flint and

Table 4. Indicator and scale reliability of the scales.

Scale reliability estimates
Scale Indicator reliability range Cronbach’s a Construct reliability Variance extracted
LDM 0.33– 0.69 0.726 0.74 0.37
LPA 0.40– 0.57 0.728 0.73 0.36
LBU 0.62– 0.81 0.919 0.91 0.65
STA 0.39– 0.68 0.849 0.86 0.51
EFF 0.67– 0.76 0.794 0.79 0.57
 The International Journal of Human Resource Management 629

Table 5. Bentle – Bonett coefficient (NFI, NNFI) and GFI values.

Scale LDM LPA LBU STA EFF

NFI 0.957 0.962 0.960 0.957 0.951
NNFI 0.956 0.966 0.946 0.949 0.947
GFI 0.978 0.981 0.927 0.957 0.951

Kent 1999; Malhotra and Dash 2011). As unidimensionality and high internal consistency
of the scales have already been established, this is proof of at least moderate convergent
validity.
Several researchers (Bentler and Bonett 1980; Byrne 1994; Ahire, Golhar and Waller
1996) have recommended SEM-based CFA fit indices, viz. normed fit index (NFI),
goodness of fit index (GFI) and non-normed fit index (NNFI) with values of more than
0.90 as indicative of high convergent validity. In the present case, values of the scales as
presented in Table 5 provide strong evidence of convergent validity of study scales.
Further, for convergent validity, Anderson and Gerbing (1988) recommended that all
the t-values should exceed 2 ( p ¼ 0.001). Table 6 shows the t-values of items in each scale
were more than the prescribed limit of 2, which is an indication of high convergent
validity.
Discriminant validity: In order to assess the discriminant validity of the scales, results
of Harman’s one-factor test were considered to see whether all of the variables loaded onto
a single factor. The findings revealed that five factors were generated having Eigen-values
greater than 1 and no single factor accounted for the majority of the variance. Hence, the
results indicate that all the items did not load on a single construct, thereby indicating the
presence of discriminant validity of the scales as shown in Table 7.
Nomological validity: Nomological validity is the degree to which the scale correlates
in a theoretically predicted ways with measures of different but related constructs
(Malhotra 2007; Hair et al. 2008; Malhotra and Dash 2011). Garver and Mentzer (1999)
recommend measuring nomological validity by determining whether the scales correlate
as expected. The correlation values between the scales were positive and significant, hence
giving a proof of nomological validity as presented in Exhibit 2

Structural model fit

SEM was deployed to test the conceptual research model. SEM programmes such as
LISREL (Jöreskog and Sörbom 1993, 1996) make it easier and faster for the researcher to
investigate the multifaceted structural models (Widaman and Thompson 2003; Cooper
and Schindler 2006; Hair et al. 2008; Malhotra and Dash 2011). The structural model was

Table 6. T-values of scale items.

Items LDM LPA LBU STA EFF
1 7.78 5.80 11.93 10.87 11.40
2 11.00 6.95 15.50 11.65 9.31
3 7.16 8.59 13.79 11.86 9.36
4 6.49 8.25 13.28 7.03 –
5 5.85 7.74 11.40 9.29 –
6 – – 10.51 11.12 –
630 F.T. Azmi and S. Mushtaq

Table 7. Discriminant validity-total variance explained.

Extraction sums of squared Rotation sums of squared

Initial Eigen-values loadings loadings
% of % of % of
Items Total variance Cum. % Total variance Cum. % Total variance Cum. %
1 8.339 33.356 33.356 8.339 33.356 33.356 5.327 21.307 21.307
2 3.714 14.854 48.210 3.714 14.854 48.210 5.067 20.267 41.574
3 2.130 8.518 56.728 2.130 8.518 56.728 2.550 10.199 51.772
4 1.086 4.345 61.074 1.086 4.345 61.074 1.948 7.793 59.565
5 1.013 4.053 65.127 1.013 4.053 65.127 1.391 5.562 65.127
Note: Only the five factors that were generated are shown in the table; extraction method: principal component
analysis.

assessed using exogenous variables (LDM, LPA and LBU), endogenous variable (EFF)
and mediating variable (STA).
When the structural model was determined using LISREL 8.50, it was found that the
structural model fits the data well. The standardized path coefficients of structural model
are given in Exhibit 3. The path coefficients are used to assess the magnitude and direction
of relationships and thus test the study hypotheses:
Hypothesis 1: Line managers involvement in decision-making vis-a-vis HRM (LDM)
had a direct and positive relationship with effectiveness of HRM (EFF)
as indicated by the path from LDM to EFF. Thus, the Hypothesis 1 was
not rejected.

Exhibit 2. Nomological validity: measurement model with correlations.

 The International Journal of Human Resource Management 631

Exhibit 3. Structural model and path coefficients.

Hypothesis 2: Line managers involvement in process/activities vis-a-vis HRM (LPA)

had a direct and positive relationship with effectiveness of HRM (EFF)
as indicated by the path from LPA to EFF. Thus, the Hypothesis 2 was
not rejected.
Hypothesis 3: Line managers involvement in budgeting vis-a-vis HRM (LBU) had a
direct and positive relationship with effectiveness of HRM (EFF) as
indicated by the path from LBU to EFF. Thus, the Hypothesis 3 was not
rejected.
Hypothesis 4: Line managers involvement in decision-making vis-a-vis HRM (LDM)
had no direct and positive relationship with status of HRM (STA) as
indicated by the non-significant path from LDM to STA. Thus, the
Hypothesis 4 was rejected.
Hypothesis 5: Line managers involvement in process/activities vis-a-vis HRM (LPA)
had a direct and positive relationship with status of HRM (STA) as
indicated by the path from LPA to STA. Thus, the Hypothesis 5 was not
rejected.
Hypothesis 6: Line managers involvement in budgeting vis-a-vis HRM (LBU) had a
direct and positive relationship with status of HRM (STA) as indicated
by the path from LBU to STA. Thus, the Hypothesis 6 was not rejected.
Hypothesis 7: Line managers involvement in decision-making vis-a-vis HRM (LDM)
had a direct and positive relationship with organizational performance
(PERF) as indicated by the path from LDM to PERF. Thus, the
Hypothesis 6 was not rejected.
Hypothesis 8: Line managers involvement in process/activities vis-a-vis HRM (LPA)
had a direct and positive relationship with organizational performance
(PERF) as indicated by the path from LPA to PERF. Thus, the
Hypothesis 6 was not rejected.
632 F.T. Azmi and S. Mushtaq

Hypothesis 9: Line managers involvement in budgeting vis-a-vis HRM (LBU) had no

direct and positive relationship with organizational performance
(PERF) as indicated by the non-significant path from LBU to PERF.
Thus, the Hypothesis 4 was rejected.
Hypothesis 10: Status of HRM (STA) had a direct and positive relationship with the
effectiveness of HRM (EFF) as indicated by the path from STA to EFF.
Thus, the Hypothesis 10 was not rejected.
Hypothesis 11: Status of HRM (STA) had a direct and positive relationship with
organizational performance (PERF) as indicated by the path from STA
to PERF. Thus, the Hypothesis 4 was not rejected.
Hypothesis 12: Effectiveness of HRM (EFF) has a direct and positive relationship with
organizational performance (PERF) as indicated by significant path
from STA to PERF. Thus, the Hypothesis 4 was not rejected.
Despite the fact that the structural model converged, mixed support was found for the
hypothesized relationships in the model. While in majority of the cases, significant direct
and positive relationship existed between exogenous and endogenous study variables; in
some cases, the relationship was indirect through the mediating variable. However, the
results of hypothesized relationship provide sufficient support for criterion-related
validity, which is a measure of how well scales representing the various exogenous
variables are related to endogenous variables.
LISREL fit indices should preferably correspond to a minimum threshold value as
recommended by researchers in the area (e.g. Bagozzi and Yi 1988; Jöreskog and Sörbom
1993; Schumacker and Lomax 2004). The fit indices of the current study suggest that the
structural model represent the data well. Root mean square error of approximation value
of 0.080 is within the recommended value of 0.10. Bentler –Bonett Coefficient and
comparative fit index, values are more than the minimum recommended value of 0.90,
indicating a good fit. The GFI and adjusted goodness of fit index values are also close to
the recommended value of 0.90. Moreover, relative x 2/degrees of freedom value of 2.27
were less than the suggested value of 3.00.

Discussion and conclusions

After obtaining unidimensional scales through testing of the measurement model, scale
reliability and validity were assessed. All the scales demonstrated high indicator and scales
reliability. Thereafter, different types of construct validity such as convergent,
discriminant and nomological validity were also assessed.
When the structural model was assessed, mixed support was found for the
hypothesized relationships. The findings suggested that there was significant direct and
positive impact of LDM, LPA, LBU on EFF; LPA, LBU on STA; STA on EFF; LDM,
LPA, STA, EFF on PERF. Although, a significant direct and positive relationship between
LDM and STA could not be established; LDM had a direct positive impact on EFF and
PERF, which signifies that there is direct relationship of line manager’s involvement in
decision-making with effectiveness of HRM and overall organizational performance. In
addition to this, LBU had a positive impact on STA and EFF which signifies that there is
indirect impact of LBU on EFF through STA and it had no direct and positive relationship
with PERF which is indicated by the non-significant path from LBU to PERF.
The above results provide partial support to the findings of previous researchers (e.g.
Gennard and Kelly 1997; Hall and Torrington 1998; Thornhill and Saunders 1998; Bond
 The International Journal of Human Resource Management 633

and Wise 2003; Hutchinson and Purcell 2003; Renwick 2003; Cascón-Pereira et al. 2006;
Andersen et al. 2007; Dany et al. 2008; McGuire et al. 2008; Perry and Kulik 2008). The
hypothesized relationships in the conceptual research model were primarily drawn from
studies that have been conducted in the Western context. Since all the hypothesized
relationships could not be established in the study, it indicates that the theory is not fully
supported in the Indian context which has different HR dynamics. Since the present model
was not fully supported, it is believed that the relationship between the measures could
possibly be affected by the interplay of other mediating variables which needs to be
explored in future researches.
By the linking of various dimension of role of line managers vis-a-vis HRM with status
of HRM, effectiveness of HRM and organizational performance, the results of the present
study provide ample support to the idea that involvement of line manager in HRM has
positive implications. Thus, it can be inferred from the findings of the study that the
involvement of line manager vis-a-vis HRM has favourable outcomes.
The present research has implications for both academicians and practitioners. The
contributions of the study include development of a reliable and valid instrument for
measuring various dimensions of role of line managers vis-a-vis HRM as well as to
establish the impact of their involvement on status and effectiveness of HRM and
organizational performance in the Indian context. Thus, helps the HR researchers and
practitioners in the analysis of role of line managers in HRM. While most of studies on role
of line managers have been conducted in the Western world, the current research will add
to the literature by drawing its sample from India, where economic reforms have attracted
a large number of multinationals and as a result of which there is paradigm shift in the
HRM scenario. In the current research, SEM is deployed which is a robust technique for
addressing a wide range of managerial and theoretical issues by examining multiple
relationships simultaneously in a single model (Anderson and Gerbing 1988; Garver and
Mentzer 1999; Malhotra and Dash 2011). Thus, the current research is expected to
contribute methodologically to the existing stream of research. However, since the current
study focused on companies operating in India, thus, there is a need to cross-validate the
findings of the current study in other countries and cultural contexts.

Note
1. Business World and Centre for Monitoring Indian Economy (CMIE) – an independent research
house – annually publish rankings of companies in India.

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