1

WHO COMMITS? : WHO ENGAGES? : OPENING THE BLACK BOXES OF COMMITMENT AND ENGAGEMENT

John Sutherland

Scottish Centre for Employment Research (SCER) Department of Human Resource Management

University of Strathclyde, Glasgow

Email: john.sutherland@strath.ac.uk

2

WHO COMMITS? : WHO ENGAGES? : OPENING THE BLACK BOXES OF COMMITMENT AND ENGAGEMENT

Abstract

Commitment and engagement are central constructs in many of the prescriptive models of the management of human resources. Both, however, have been treated as if they are ‘black boxes’, non-problematically converting policy-type inputs into performance-type outputs. That the likelihood of an individual committing and/or engaging may differ across employees has received little attention. This paper addresses this research lacuna by addressing two questions: who commits?; and who engages? It uses data extracted from the Skills and Employment Surveys Series Dataset, 1986, 1992, 1997, 2001, 2006 and 2012. It constructs indicators which measure commitment and engagement and it identifies the covariates of the likelihoods of an individual committing and engaging. The empirical analysis suggests that who commits and who engages depends upon the indicator used to measure the attitude/behaviour in question. Nonetheless, it is possible to identify a set of variables which are associated with the likelihood that an individual commits across the three variables used to measure this attitude. Moreover, these include dummy variables which denote policies often used to engender commitment. Proportionately fewer variables produce consistent outcomes across the four indicators used to measure engagement, perhaps because of the more diverse set of indicators used. The statistical results which are produced are correlations between indicators of commitment and engagement and variables which denote the personal characteristics of individuals and the characteristics of the workplaces at which they are employed. Causation cannot be inferred from these correlations. Accordingly, it is important to acknowledge that the statistically significant outcomes which are observed may be explained by factors other than the independent variables which feature in the regression models estimated. That said, the likelihood that an individual commits and/or engages differs across the employed workforce. Consequently, neither commitment nor engagement can be assumed to be ‘black boxes’ which non-problematically convert policy inputs into performance outputs.

Key Words: Commitment: Engagement: Models of human resource management: the Skills and Employment Surveys Series Dataset, 1986, 1992, 1997, 2001, 2006 and 2012.

JEL Classification: M12 M54

3

WHO COMMITS? : WHO ENGAGES? : OPENING THE BLACK BOXES OF COMMITMENT AND ENGAGEMENT 1

Introduction

Commitment and engagement are central constructs in many of the prescriptive models of the management of human resources which detail policies by which management may, simultaneously, enhance worker well-being and improve organisational performance. Following the insider econometrics studies of high performance work systems in the United States, latterly, ‘commitment’ was introduced as one possible transmission mechanism to explain why the implementation of policies and practices central to these systems resulted in improved workplace performance. More recently, and more especially in the United Kingdom, ‘engagement’ has become the principal focus of policy makers, subsequent to the publication of case studies purporting to demonstrate how the introduction of enablers (or drivers) of engagement has resulted in improvements in organisational performance. Throughout, to borrow the much used metaphor, both commitment and engagement have been treated as if they are ‘black boxes’, non-problematically converting policy-type inputs into performance-type outputs. That the likelihood of an individual committing and/or engaging may differ across employees, for example according to their personal characteristics or the characteristics of the workplaces at which they are employed, has received little attention. This paper addresses this research lacuna. It does so by addressing two simple but fundamental questions: who commits?; and who engages? It uses data extracted from the Skills and Employment Surveys Series Dataset, 1986, 1992, 1997, 2001, 2006 and 2012 to do so, constructing indicators which measure commitment and engagement and identifying and explaining the covariates of the likelihoods of committing and engaging.

Context There are many, diverse, prescriptive models of human resource management which detail

the policies and practices by which management may fully realise labour’s capacity to produce, thereby simultaneously improving the performance of the organisation and enhancing worker well-being. Employee commitment to and employee engagement with organisations are central or complementary constructs in many of these models. However, the specific roles played by these constructs in these models are many and varied and frequently contested.2 Commitment in the early literature was conceptualised as a psychological contract between employee and employer, characterised by the former’s identification with the values and goals of the latter (Selznick, 1957: Porter et al, 1974: Kalleberg and Berg, 1987), and the tendency has been to interpret ‘organisational commitment’ as ‘affirmative commitment’ (Meyer and Allen, 1984). The construct was to become central to those models of human resources management which were

1 The Skills and Employment Survey, 2012 was financially supported by the Economic and Social Research

Council (ESRC), the UK Commission for Employment and Skills Strategic Partnership and the Wales Institute for Social and Economic Research, Data and Methods for the Welsh boost. The Skills Survey, 2006 was supported by the Department for Education and Skills, the Department of Trade and Industry, the Learning and Skills Council, the Sector Skills Development Agency, Scottish Enterprise, Futureskills Wales, Highlands and Islands Enterprise and the East Midlands Development Agency. The Skills Survey, 2001 was funded by the Department for Education and Skills. The Skills Survey, 1997 and the Social Change and Economic Life Initiative Surveys, 1986 -1987 were supported by the ESRC. Employment in Britain, 1992 was supported by the Leverhume Trust and an industrial consortium of funders. 2 The aim of this section is to provide a context to the empirical investigation. It attempts neither to survey nor

to evaluate the many issues in question.

4

influenced by writers associated with the neo-human relations school (e.g. Hertzberg, 1966: McGregor, 1960: Maslow, 1943) where it was viewed as a potentially important strategic asset.3 These models prescribed what Green (2006) identified as a ‘new ideology of control’ (p. 7), replacing traditional control structures reflected in, for example, compliance, hierarchy and bureaucracy (Legge 2005). Articulated well in Storey’s (1989) frequently cited ‘soft version’ of human resource management, these models advocated investments over the long term in human resources and the design and implementation of policies and practices which sought to motivate employees, gain their trust and, thereby, their commitment. Although these policies and practices were never widely adopted (Millward et al, 1992) – and, hence their efficacy rarely tested empirically – nonetheless the presumption which prevailed was that ‘committed’ employees were more likely to improve organisational performance. With their focus upon the organisation, often – although often implicitly rather than explicitly -these models of human resources management were embedded in the resource based model of the firm. This model assumed that resources were the ultimate source of a firm’s competitive advantage and the means by which its productivity and performance were enhanced and whereby super normal profits were to be generated through time, although not necessarily in perpetuity. Its intellectual origin was Penrose (1959) who conceived the firm to be a collection of productive, inherently dynamic, potentially malleable, resources and the services – or, alternatively competences or capabilities - which these resources provided and produced. Penrose related these resources to the economist’s traditional factors of production viz. land, labour and capital. Latterly, however, the focus was more upon combinations of people and processes (Morgan et al (2005). These resources, however defined and classified, were assumed to be distributed heterogeneously across firms, even firms within the same industry. Not all resources necessarily constituted distinctive capabilities with the potential to generate a sustained competitive advantage. Indeed, some resources were detrimental to the attainment of such a goal. Strategically, the task was to identify inputs which had distinctive capabilities and this, ultimately, was a matter for managerial or entrepreneurial insight and imagination (Kay, 1993) Nevertheless, the conventional wisdom was that human resource management policies and practices were of central importance (Boxall and Purcell, 2008). Establishing a competitive advantage was to be achieved not only by adopting appropriate process, product and price strategies but also by generating a greater degree of employee commitment to the goals of the organisation. Consequently, much within the relevant contemporary human resource (hereafter HR) management literature was about seeking to understand the conditions under which human resources became strategic assets capable of generating distinctive capabilities – and/or complementing other factors, notably technology, to produce this outcome – and then devising and implementing the appropriate strategies. The exercise, in principle, was one of developing and building a bundle of human and related technical resources, the latter manifest most especially in terms of work organisation, designed to enhance organisational performance (Boxall and Purcell, 2008). An unashamedly managerialist agenda dominated this mainstream research literature which focussed upon first identifying then prescribing ‘best practice’ (Delbridge and Keenoy, 2010). As the high performance paradigm literature both in the USA and the UK was to illustrate, however, there was neither an unambiguously unique bundle nor a definitive list of policies and practices appropriate to this task (e.g. Becker and Gerhard, 1996: Black and Lynch, 2001: 2004: Brown et al, 2011: Ichniowski et al, 1996: 2003: Ichniowski and Shaw, 1997: Pfeffer, 2008: Procter, 2008: Wood, 1999a: 1999b: Wood and de Menezes, 1998).

3 In time, these models came to be associated with the demise of ‘Personnel Management’ and the rise of

‘Human Resource Management’ as the terms of reference of those who were responsible for the ‘personnel’ function within organisations changed radically (Bach and Sissons, 2000).

5

The emergence of models reflecting the high performance paradigm was associated with empirical research published in the USA (e.g. Appelbaum and Batt, 1994: Huselid, 1995: Ichniowski et al, 1997: MacDuffie, 1995: Osterman, 1994). The principal focus of these studies was attempts to establish a causal relationship between work practices – reflected in various sets of HR policies and practices and equally various forms of work organisation – and organisational performance. Always fraught with problems pertaining to theory, methodology and data, this research sometimes succeeded in confirming some positive statistical associations between HR policy and practice and organisational outcomes. Nonetheless, it was less successful in explaining how this relationship came about (Boselie et al, 2005). Latterly, the research agenda was to change to one which sought to identify and examine the nature of the ‘transmission mechanisms’ (e.g. Proctor, 2008) – or ‘linkages’ (e.g. Ramsey et al, 2000) – by which this relationship came about. The conventional presumption was that this relationship had its explanations in changes made to employees’ attitudes and behaviours by the policies in question. Two possibilities were mooted: one associated with ‘commitment’ (following Walton, 1985) and termed ‘high commitment management’; and the other associated with ‘involvement’ (following Lawler, 1986) and termed ‘high involvement management’. The former required a policy framework designed to commit (or re-commit) the worker with the cultural norms and expectations of the organisation. By contrast, the latter emphasised the salience of employee participation, if somewhat nebulously defined (Lansbury and Wailes, 2008). According to this latter perspective, the essential assumption was that the implementation of policies and practices such as the creation of semi-autonomous work teams, the adoption of employee profit sharing schemes etc., all designed to create involvement, improved worker effort and, in turn, organisational performance. Effectively requisite employee behaviour became self-regulated (Levine, 1995).4 Irrespective of the transmission mechanism in question, however, and very much in accordance with the assumptions of the unitarist perspective of the organisation (Fox, 1966), the ultimate outcome was one of ‘mutual gains’. As well as the organisation improving its performance, employee well-being was enhanced (Guest, 2002: Kochan and Osterman, 1994).5 As with commitment, engagement is a contested construct. Consequently, there is no one agreed definition of what constitutes ‘employee engagement’. Further, there is considerable confusion as to whether the concept is an ‘attitude’, a ‘behaviour’ or an ‘outcome’ (MacLeod and Clarke, 2009). MacLeod and Clarke’s (“The MacLeod Report”) own definition of the concept illustrates this latter point well: “a workplace approach designed to ensure that employees are committed to their organisation’s goals and values , motivated to contribute to organisational success, and are able at the same time to enhance their own sense of well-being” (p. 9). Indeed, Guest (2013) questions whether employee engagement has construct validity. A variety of conceptual frameworks exist, most of which were drawn from the literature of (organisational/work) psychology (Rich et al, 2010). The first of note was Kahn (1990: 2010), who maintained that personal engagement occurred when “people bring in or leave out their personal selves during work-role performances” (Kahn, 1990, p. 702). When employees were engaged, they were assumed to express themselves cognitively, emotionally and physically. Engagement,

4 ‘High Involvement Management’ is not discussed in any further detail here because it is irrelevant to the

central themes of this paper. Nevertheless, as a research agenda in its own right it has generated a voluminous literature, not least because of the scope to incorporate trade unions into the analysis fulfilling the role of ‘employee voice’ in the transmission process (e.g. Addison, 2005: Bryson et al, 2005: Fernie and Metcalf, 1995). 5 Ramsey et al (2000) - among others - working from alternative perspectives, questioned the inevitability of

this outcome, arguing that high performance practices may also operate through work intensification and increased employee stress rather than employee commitment and involvement (Frost, 2008: Godard, 2004).

6

therefore, was the converse of attitudes and behaviours such as alienation, apathy and detachment (May et al, 2004). There have been subsequent theoretical developments, several making use of social exchange theory with its identification of reciprocity as a form of social exchange. This framework features in several important empirical studies (e.g. Saks, 2006: Shuck, 2011: Truss et al, 2013). To the extent that its roots lie within positive psychology, the concept of employee engagement fits well with the unitarist perspective of the organisation (Watson, 2010). That said, an employee may be ‘engaged’ but not necessarily behave in ways which benefit the organisation. Consequently, Arrowsmith and Parker (2013) maintain that “the pursuit of (employee engagement) is much more complex and dynamic, and the outcome uncertain” (p. 2697). A consultancy approach prevails.6 Consultancy companies devise engagement surveys and HRD professionals are called upon to develop strategies which improve employee engagement at the workplace (MacLeod and Clarke, 2009: Keenoy, 2013: Briner, 2014: Purcell, 2014). The tendency is to view employees as passive actors within the system. Consequently, engagement is assumed to be driven by the organisation and the search is for the ‘drivers’ of engagement (Emmott, 2010: Francis and Reddington, 2012: Robinson et al, 2004). To illustrate: summarising the evidence they collect and analyse, MacLeod and Clarke (2009, p. 75) identify four such ‘drivers’ (or enablers) of engagement viz. ‘leadership’ (which provides a “strong strategic narrative”); ‘engaging managers’ (who “facilitate and empower rather than control and restrict their staff”); ‘voice’ (i.e. “an effective and empowered employee” communicates, with management “listening and responding”); and ‘integrity’ (behaviour throughout the organisation is “consistent with stated values”). Research purports to demonstrate associations between levels of engagement and both individual and organisation performance. This research uses case study methodology, with most of this coming from case studies reported by consultancies (MacLeod and Clarke, 2009: Purcell et al, 2003). As noted above in the context of commitment, within this research there are many studies which seek to uncover the mechanisms by which HR policy and practice may impact upon individual behaviours. Rich et al (2010) argue that engagement may be that core mechanism. Consequently, Truss et al (2013) contend that “Engagement demonstrates the potential to become the ‘new best practice’ HRM approach, with the prospect of ‘high engagement HRM’ becoming the dominant discourse within mainstream HRM” (p. 2661). These discourses on commitment and engagement tend to assume that attitudes and behaviours are homogenous across individuals. Little attention is paid to the possibility that the propensity to commit and the propensity to engage differ between individuals, for example according to the personal characteristics of the individual and/or the characteristics of the workplace at which he/she is employed. To the extent that these likelihoods do differ, it is quite possible, therefore, that the impact of a given set of HR policies and practices on both individual and organisational outcomes will be heterogeneous rather than homogeneous.

6 This is principally associated with the ‘Engage for Success’ movement, launched in 2011 by David Cameron

(cf. www.engageforsuccess.org).

7

The possibility that commitment and/or engagement do vary across individuals and is influenced by factors such as personal and workplace characteristics is one feature of van Wanrooy et al’s (2013) recent study of employment relations in Great Britain. Applying Meyer and Allen’s (1984) concept of ‘affective commitment’, van Wanrooy et al examine commitment using three indicators derived by producing scalar variables from responses to three statements in the study’s survey of employees viz.

“I feel loyal to the organisation”;

“I share many of the values of my organisation”; and

“I am proud to tell people who I work for” van Wanrooy et al (2013) report an increase in commitment between 2004 and 2012 across each of the three indicators used. Further, they find that commitment tends to be higher among women; relatively older employees; those with relatively longer tenure at the workplace; and those who are employed in relatively smaller workplaces. In contrast, it is lower for those who have higher educational qualifications. Conventionally, engagement is associated with particular behaviours on the part of the employee, manifest, for example, in exercising discretionary effort (Daniels, 2011: Rees et al, 2013). Accordingly, to examine the nature of employee engagement, van Wanrooy et al analyse responses to the statement that “Using my own initiative, I carry out tasks that are not required as part of my job (p. 167)”.7 They report that engagement tends to be higher among relatively older workers and, in contrast to their finding for commitment, higher for those with higher educational qualifications. The specific objectives of this paper are to develop and extend the van Wanrooy et al study in three ways. First, it capitalises upon the questions available in the Skills and Employment Survey Series dataset to examine three indicators of commitment and four indicators of engagement. Secondly, it examines each of these indicators using ordered logit models, which some would argue is a preferred method for analysing Likert-type responses (Long and Freeze, 2014) (that is, rather than OLS regressions used by van Wanrooy et al) to identify their covariates. Thirdly, because responses to these questions are available for the years 1997, 2001, 2006 and 2012, it examines whether commitment and engagement have changed over time.

The Data Set The data set used in the investigation has its origin in the Skills and Employment Surveys

Series Dataset, 1986, 1992, 1997, 2001, 2006 and 2012 (Felstead et al, 2014). The ‘Skills Surveys’ is a series of surveys undertaken in 1997, 2001, 2006 and 2012 designed to investigate the employed workforce in Great Britain (from 2006, the United Kingdom). Although with a more explicit skills focus, the series builds upon two previous studies viz. the Social Change and Economic Life Initiative Surveys, 1986-7 and Employment in Britain, 1992. Each survey was administered to nationally representative samples of individuals aged 20 -60 in employment as employees. The Skills and Employment Surveys Series Dataset, 1986, 1992, 1997, 2001, 2006 and 2012 extracts data from the six original surveys where common questions are asked (cf. Table 1). Therefore, the data set is created by retrospectively pooling selected cross section data. Questions pertaining to commitment and engagement appear in the Skills Surveys of 1997, 2001, 2006 and 2012. Consequently, the analysis uses observations from only these four years in the series data set.

7 This was an additional question included in the 2011 WERS survey of employees. Consequently it was not

possible to ascertain whether the level of engagement had changed over time.

8

The indicators of commitment used in this paper are similar to those used by van Wanrooy et al (2013). It is investigated using three indicators which are produced by examining responses to the following three statements viz.:

“I feel little loyalty to this organisation” (where the name of the corresponding dependent variable in the analysis which follows is ‘loyal’);

“I find that my values and the organisation’s values are very similar” (where the name of the corresponding dependent variable in the analysis is ‘values’); and

“I am proud to be working for this organisation” (where the name of the corresponding dependent variable in the analysis is ‘proud’);

There are four possible responses to these statements viz. ‘strongly agree’; ‘agree’; ‘disagree’; and ‘strongly disagree’. The original responses in the data set are re-coded where necessary to produce outcomes whereby the highest (lowest) degree of commitment is associated with the highest (lowest) number. The percentage frequency distributions of responses to each statement are presented in Tables 2a to 2c. The response rate for voicing a positive commitment is (approximately) 75 per cent for each indicator. The pairwise correlations between the three indicators are positively signed and statistically significant at (P < 0.01). The highest value (at 0.5632) is for the correlation between ‘values’ and ‘proud’ (cf. Table 4). The number and nature of the indicators of engagement used in this analysis differ from those used by van Wanrooy et al. First, more indicators are available. Secondly, rather than probing the individual’s willingness to use her/his ‘own initiative’, engagement is probed in a more tangible, if sometimes hypothetical manner, reflected in the willingness of the individual to increase the supply of effort and to make potential monetary sacrifices. Engagement is investigated using four indicators which are produced by examining responses to one question and three statements viz.:

“How much effort do you put into your job beyond what is required?” (where the name of the corresponding dependent variable in the analysis which follows is ‘effort’)

“I am willing to work harder than I have to in order to help this organisation succeed” (where the name of the corresponding dependent variable in the analysis is ‘help’)

“I would take almost any job to keep working with this organisation” (where the name of the corresponding dependent variable in the analysis is ‘takeany’); and

“I would turn down another job with more pay to stay with this organisation (where the name of the corresponding dependent variable in the analysis is ‘turndown’)”

There are four possible responses to the question: ‘a lot’; ‘some’; ‘only a little’; and ‘none’. And there are four possible responses to the three statements: ‘strongly agree’; ‘agree’; ‘disagree’; and ‘strongly disagree’. Again, the original responses in the data set are re-coded where necessary to produce outcomes whereby the highest (lowest) degree of engagement is associated with the highest (lowest) number. The percentage frequency distributions of responses to the question and each statement are presented in Tables 3a to 3d. In contrast to the equivalent findings for commitment, marked differences are discernible in the context of engagement. Whereas (approximately) 80 per cent of respondents would ‘engage’ by increasing the supply of effort (i.e. the indicators ‘effort’ and ‘help’), (approximately) 70 per cent would not do so if this was to entail making personal monetary

9

sacrifices (i.e. the indicators ‘takeany’ and ‘turndown’). The pairwise correlations between these four indicators are presented in Table 4. The pairwise correlations are positively signed and statistically significant at (p < 0.01). Relative to the corresponding statistics for commitment, however, the values of these coefficients are low, with the lowest being for the correlation between ‘effort’ and ‘takeany’ (at 0.0926).

The Model The ordered logit model estimated conforms to convention (Cameron and Trivedi, 2010). It

is presented as a latent variable model which reflects an individual’s likelihood of committing/engaging (Long and Freese, 2014). Defining y* as this latent variable, which takes the values -∞ to ∞, the corresponding structural model is as follows: yi* = Xiβ + εi where ‘i’ is an observation, X a vector of independent variables, β a set of coefficients to be estimated and ε a random error term. In the corresponding measurement model, y* is divided into J (in this instance 4) ordinal categories, yi = m if Ƭm-1 ≤ yi* < Ƭm for m = J where the cutpoints (or thresholds) Ƭ1 through to Ƭ J-1 are estimated. The vector of independent variables contains two types of variables which reflect an individual’s characteristics (such as gender, age, qualifications, length of tenure with the organisation etc.) and the characteristics of the organisation at which he/she is employed (such as its size, the SIC of the activity undertaken, its sector etc.). Integral to the latter are four dummy variables identifying HR policies at the workplace often considered to be conducive to engendering commitment and engagement. To examine whether commitment and/or engagement has changed over time, a set of year dummies are included.8 For the purposes of interpreting the results, throughout the focus is upon the qualitative rather than quantitative relationships which exist between the dependent and independent variables.9 In this respect, a positive coefficient for an independent variable implies that an individual with this characteristic has a higher value of latent commitment/engagement and, hence, is more likely to report a higher value of self-reported commitment/engagement (and conversely when the coefficient of an independent variable is negatively signed).

Results The results are reported in two subsections first for commitment; then for engagement. The

aim of this section is to report these results. Comment and discussion are left to the subsequent section.

Commitment

The results of the ordered logit estimations for the three dependent variables reflecting indicators of commitment are presented in Table 5. There are four principal observations which may be made from an examination of these results.

8 For full details of the set of independent variables used in the estimations refer to column 1 of Table 5 and

the footnotes to this table. 9 Consequently, no marginal effects were computed.

10

First, the nature of the relationship between some independent variables and the dependent variable is consistent across each of the three dependent variables. To illustrate (where all the outcomes cited are relative to the appropriate reference category): individuals who are not union members or who work part time are likely to be more loyal to the organisation, share the values of the organisation and feel proud to be working with the organisation. In contrast, individuals who are not on a permanent contract of employment are likely to be less loyal to the organisation, share the values of the organisation or feel proud to be working with the organisation. Individuals who are managers are likely to be more loyal to the organisation, share the values of the organisation and feel proud to be working with the organisation, whereas individuals who are skilled tradespersons, operatives or in elementary occupations are likely to be much less so. Individuals who work at establishments at which there are no unions present; where quality circles operate and where meetings are held with management; and who have received training are likely to be more loyal to the organisation, share the values of the organisation and feel proud to be working with the organisation. The same outcomes are observed for those individuals employed in relatively small workplaces. Secondly, for some other independent variables, the nature of their relationships to the dependent variables differs across the three dependent variables. Again to illustrate (and again where all outcomes cited are relative to the appropriate reference category): females are likely to be more loyal to the organisation with which they work, but they are likely to have less positive views about either sharing its values or voicing pride in working for it. Older workers are likely to share more highly the values of the organisation with which they work, but they are likely to feel less loyalty towards it and to be less proud to be working for it. Individuals with qualifications are likely to be more proud of the organisation with which they work, but they are likely to have less loyalty towards it and be less likely to share its values. Individuals who work in the public sector are likely to be more proud of the organisation for which they work, but they are likely to have less loyalty towards it and to be less likely to share its values. Individuals who work for not for profit organisations are likely to have less loyalty towards the organisation for which they work, but they are likely to be more positive about sharing its values and expressing pride in working for it. Thirdly, there are some independent variables which are of no statistical consequence in any of the estimations of the three indicators of commitment, notably an individual’s tenure with the organisation with which he/she is employed. Finally, the year dummy variables are of statistical consequence only in the context of an individual’s loyalty to the organisation with which he/she works. Relative to the reference year of 1997, loyalty decreased in both 2006 and 2012. Engagement

The results of the ordered logit estimations for the four dependent variables reflecting indicators of engagement are presented in Table 6. The most notable observation from these results is that proportionately fewer independent variables produce consistent outcomes across the four dependent variables in question. Individuals working in establishments at which no unions are present; where quality circles operate; where meetings are held with management; and working in relatively small establishments are likely to be more willing to put more into their jobs than is required; be more willing to work harder to help the organisation; be more willing to take any job to keep working with the organisation; and to be more definite about turning down other jobs with more pay to stay with the organisation (where all outcomes are relative to the appropriate reference category).

11

Conversely, the majority of the independent variables produce outcomes which differ across the four estimations. To illustrate (where all outcomes reported are relative to the appropriate reference category): females are likely only to be more willing to put more effort in than is required and to be more definite about taking any job to allow them to stay with the organisation. Individuals who are not union members are likely only to be more willing to work harder to help the organisation and to be more definite about turning down another job with more pay to stay with the organisation. Individuals who are working part time are likely only to be more willing to put more effort into the job than is required; to be more likely to work harder to help the organisation; and to be more definite about turning down another job with higher pay to stay with the organisation. Individuals who have received training are likely only to be more willing to put more into the job beyond what is required and to be more definite about turning down another job with higher pay to stay with the organisation. In contrast, individuals who do not have a permanent contract of employment are likely only to be less willing to put more into the job than is required and be less willing to work harder to help the organisation. With reference to the year dummies, the likelihood of both putting more into the job than is required and working harder to help the organisation decreases in 2006, relative to the reference year category of 1997. However, the two likelihoods of taking any job to stay with the organisation and turning down a job with higher pay to stay with the organisation increase in 2012, again relative to the reference year of 1997.

Comment and Discussion The likelihood of an individual committing and/or engaging, ultimately, is contingent upon

how these constructs are measured, that is the indicators used to identify how commitment and engagement are made manifest by the individual when questioned about his/her attitudes and behaviours. Changing these indicators, therefore, may mean that an individual may/may not commit and/or engage. Commitment has been examined using three indicators, reflected in an individual’s responses to the following (somewhat opaque but nonetheless traditional) statements viz.

“I feel loyal to the organisation” (being ‘true’ to it, perhaps at the expensive of some other organisation?);

“I share many of the values of my organisation” (suggesting, perhaps, that its ‘principles’/’standards’ are compatible with one’s own?); and

“I am proud to tell people who I work for” (implying the ‘pleasure’/ ‘honour’, perhaps, to be associated with the organisation?)

12

Engagement has been examined using four indicators, reflected in an individual’s responses to one (self-evident) question and three (equally self-evident) statements viz.:

“How much effort do you put into your job beyond what is required?”;

“I am willing to work harder than I have to in order to help this organisation succeed”;

“I would take almost any job to keep working with this organisation”; and

“I would turn down another job with more pay to stay with this organisation” These four indicators of engagement are very different. The first probes the historical willingness of the worker to increase his/her supply of effort beyond the immediate demands of the job. The second indicator probes, if hypothetically, the willingness of the worker to increase his/her supply of effort again, but this time for the explicit benefit of the organisation. The third and fourth indicators are again based upon hypotheticals. However on both these occasions the individual is required to make, if in different ways, potential personal psychic and monetary sacrifices in favour of the organisation.

Accepting these admittedly problematical measures, the results demonstrate that no matter how commitment (engagement) is measured some individuals always commit (engage); some individuals never commit (engage); and some individuals will or will not commit (engage) depending upon the indicator in question. That said, the statistical analysis is one of correlation. An individual’s attitudes and behaviours, therefore, manifest in the indicators of commitment and engagement constructed, may be explained by circumstances and/or factors other than the independent variables specified in the regression model estimated. In terms of commitment, women are likely to express highly their loyalty to the organisation, relative to men, although they are less likely either to share its values or to voice pride in working for it. This loyalty may be reflected further in one measure of engagement, in their being more willing to work harder than necessary for the organisation. However, that women are likely to be more willing to take any job to keep working with the organisation, another measure of engagement, may be attributable more to their sometimes constrained labour supply rather than any particular engagement with the organisation. There are some discernible patterns to the age categories variables. While individuals in the older age categories (relative to the reference age category) are likely to report a higher value with respect to sharing the values of the organisation, their manifestation of commitment is restricted to this indicator. Individuals in these same age categories (again relative to the reference age category) are also likely to be more adamant about turning down outside job offers in favour of remaining with the organisation. Equally, however, this outcome may be attributable to the manifold costs associated with job changing rather than any particular manifestation of engagement with the organisation. Whereas individuals in the youngest age category are less likely to have increased their supply of effort beyond their immediate job demands, individuals in the oldest age category are more likely to have done so. Again, however, these outcomes could equally well be rationalised in terms of age differences in tacit knowledge as well as expressions of engagement. Individuals with educational qualifications (relative to those who do not have them) are likely to be much less willing to take any job to remain with the organisation. This particular outcome, however, may be attributable less to their engagement with the organisation than the ease with which this group of individuals believe they may find suitable alternative employment elsewhere. ‘Unionisation’, in all its forms, is incompatible with the unitary perspective of organisations which has been seen to dominate the managerially prescriptive literature as it relates to commitment and

13

engagement. Consequently, the outcomes that individuals who are not union members (relative to individuals who are union members) and individuals who do not work in organisations at which unions are present (relative to individuals who work for organisations at which unions are present) are likely to commit more highly across all three indicators accords with expectations. Similar outcomes are observed for the four indicators of engagement, although not all of these results are statistically significant. Managers (relative to the appropriate reference category) are likely to commit more highly, irrespective of the indicator used. To the extent that managers are ‘leaders’ within their respective organisations, often advocates and/or proselytizers of this set of attitudes, this outcome is not unexpected. Equally, engagement on the part of managers is to be expected for the same reasons. It is for three of the four indicators used. The exception is the unwillingness on the part of managers to take any job to keep working with the organisation, an outcome which may be rationalised also by reluctance on their part to lose their managerial status. In contrast, individuals who are in occupations such as skilled trades; sales; operatives; and elementary are less likely to commit or engage with the organisation, irrespective of the indicator used. For those who are skilled workers, this outcome may be because their commitment is less to any particular organisation than to a trade which facilitates movement between organisations. For those in the other occupational categories it may be an inevitable consequence of the organisation’s unwillingness to enhance their formal and informal organisational specific skills. Individuals who are not on permanent contracts of employment (relative to those who are on permanent contracts) are likely to commit less highly, irrespective of the indicator used, outcomes which are compatible with expectations because these individuals are, by definition, transients, willingly or unwillingly. Additionally, they are less likely to have worked beyond the terms of their existing contract or be prepared to do so to assist the success of the organisation. Again for the same reason, these outcomes are not unexpected. By way of contrast, individuals who have part time contracts of employment (relative to those who have full time contracts of employment) are likely to commit more highly across all three indicators. Furthermore, they are likely to engage more highly across all four indicators. Of course, these outcomes may be attributable to the precarious nature of the part timers’ employment situation and, therefore, their perceived need to be seen to demonstrate certain attitudes and behaviours, desired or expected by management. Or, alternatively, it could be that individuals on these particular employment contracts do indeed possess and demonstrate the attitudes and behaviours which are keenly sought by organisations. Since Rainnie (1989), there has been controversy about the nature of employment relations in small firms. This study suggests that individuals working in small workplaces (relative to those working at workplaces with 25 – 99 employees, the reference category) are likely to report high levels of commitment and engagement, irrespective of the indicators used. In contrast, although not uniformly across all workplace size categories, individuals employed at larger workplaces are likely to report low levels of commitment and engagement. One possible explanation for this may be that the informality sometimes associated with the management of control in small firms/workplaces is, from the perspective of workers, to be preferred to the formality of the same often found in the bureaucracy inevitable in larger organisations and this has positive consequences for commitment and engagement. Some organisations seek to engender commitment and engagement on the part of their workers by implementing particular policies and practices with respect to the management of human resources. The implications of four such policies are examined viz. i. that an individual has received training; ii. that an individual has been subject to some form of appraisal; iii. that an individual is employed at a workplace where quality circles operate; and iv. that an individual is employed at a workplace where

14

meetings are held with management. In the context of commitment, where the individual has received training; where the individual is employed at a workplace which uses quality circles; and where the individual is employed at a workplace where meetings are held with management, individuals are likely to commit more highly across all three indicators. The outcomes are more complex in the context of engagement. First, for each of the four policy variables, individuals are likely to have worked more than their immediate job demands necessitated. Secondly, where an individual is employed at a workplace which uses quality circles and where an individual is employed at a workplace at which meetings are held with management, individuals are likely to engage more highly whatever indicator is used. In essence, therefore, there are positive correlations between some if not all of the policies examined and some if not all of the indicators of commitment and engagement. As noted in the literature review, there is no definitive list of policies which appear to offer efficacious outcomes. There are two sets of variables where the statistical outcomes, perhaps, do not accord with expectations viz. tenure and sector of employment. Given that the opportunities to do so exist, an assumption could be made that employee-organisation mismatches would result, eventually, in an individual quitting voluntarily. Therefore, the expectation is that commitment and engagement would be higher for those with relatively long spells of tenure. This is never found in the context of commitment and is seldom found in the context of engagement. Admittedly, there is a positive correlation between the two longest tenure spells and a willingness to take any job to remain with the organisation, but this particular relationship could also be explained in terms of an individual’s awareness of the potential costs associated with job changes. Assumptions are often made about the psychic attractions of working in the public and not for profit sectors of the economy. Given the validity of these assumptions, ceteris paribus, the expectation is that this would be reflected in an individual’s commitment and engagement. On occasions, this is found in the context of the former. For example, individuals working for organisations in the public sector and in the not for profit sector (relative to those working in the private sector, the reference category) are likely to be more proud of the organisation for which they work. However, it is found in one instance only in the context of engagement, in that individuals who are working in the public sector (again relative to those working in the private sector) are more likely to turn down alternative job offers in favour of remaining with their present organisation. The variables correlated with commitment and engagement in this paper, therefore, differ from those found by van Wanrooy et al using the WERS (2011) data sets. One possible explanation is the statistical methodology used, ordered logits which acknowledge the nature of Likert-type responses rather than OLS regressions. However, another more likely explanation lies in the difference in the data sets used, where van Wanrooy et al are able to capitalise upon a set of establishment variables qualitatively and quantitatively superior to those available in a survey of employees. One advantage of the data set used in this investigation is the scope to examine whether there has been any secular change with respect to an individual’s likelihood of committing and/or engaging. The economic environment prevailing in 2006 and 2012 contrasted with that of 1997, the reference year. The former was a year when the economy was expanding; and the latter was a year when the economy remained within what van Wanrooy et al (2012) described as the shadow of the recession. In the context of commitment, there is no sign of any secular trend for either the ‘values’ or the ‘proud’ indicators. However, there is for the ‘loyalty’ indicator. This indicates that loyalty has decreased since 1997, although there is no ready explanation for this. Although there is no equivalent trend in the context of engagement, nonetheless, there are some noteworthy results. There is some suggestion that an individual’s willingness to increase his/her supply of labour voluntarily has decreased over time. Further, the results with respect to the indicator associated

15

with a willingness to accept monetary consequences to remain with the organisation suggest that engagement increased in 2012, relative to 1997. Equally, however, this result is also compatible with a hypothesis which features risk adverse employees being reluctant to accept the unknown of other organisations during a period of economic retrenchment.

Conclusions Who commits and who engages depends upon the indicator used to measure the

attitude/behaviour in question. For example, while women are likely to report greater loyalty to the organisation with which they work, there are no statistically significant gender differences with respect either to sharing the values of the organisation or to voicing pride in working for the organisation. Nonetheless, it is possible to identify a set of variables which are associated with commitment across the three variables used to measure this attitude. These are as follows: individuals who are not union members; who work part time; who are managers; who are employed at workplaces which do not recognise unions; who have received training; who are employed at workplaces where quality circles operate; who are employed at workplaces where meetings are held with management; and who are employed in small workplaces. Perhaps because of the more diverse set of indicators used to measure engagement, proportionately fewer variables produce consistent outcomes across the four indicators in question. These are as follows: individuals who are working in establishments which do not recognise unions; where quality circles operate; where meetings with management are held; and who are employed in small workplaces. Because of the nature of the cross section data set used and the statistical methodology applied, the statistical results are correlations between some indicators of commitment and engagement and some variables which denote the personal characteristics of individuals and the characteristics of the workplaces at which they are employed. Causation cannot be inferred from these correlations, although this is something which is often implicit in many of the models of the management of human resources. Accordingly, it is important to acknowledge that the statistically significant outcomes which have been observed may be explained by factors other than the independent variables specified in the models estimated. That said, incontrovertibly, the likelihood that an individual commits and/or engages does differ across the employed workforce. Consequently, neither commitment nor engagement can be assumed to be ‘black boxes’ which non-problematically convert policy inputs into performance outputs.

References Addison, J.T. (2005) The Determinants of Firm Performance: Unions, Works Councils, and Employee

Involvement/High Performance Work Practices. Scottish Journal of Political Economy, Vol. 52, pp. 406 -450.

Appelbaum, E. and Batt, R. (1994) The New American Workplace: Transforming Work Systems in the United States. ILR Press: Ithaca, New York, USA.

Arrowsmith, J. and Parker, J. (2013) The Meaning of ‘Employee Engagement’ for the Values and Roles of the HRM Function. The International Journal of Human Resource Management, Vol. 24, pp. 2692 -2712.

Bach, S. and Sissons, K. (2000) Personnel Management in Transition. In Bach, S. and Sissons, K. (eds) Personnel Management: A Comprehensive Guide to Theory and Practice. Blackwell: Oxford.

Becker, B. and Gerhard, B. (1996) The Impact of Human Resource Management on Organisation Performance: Progress and Prospects. Academy of Management Journal, Vol. 39, pp 779 -801.

Black, S.E. and Lynch, L. (2001) How to Compete: The Impact of Workplace Practices and Information Technology on Productivity. Review of Economics and Statistics, Vol. 83, pp 434 -445.

Black, S.E. and Lynch, L. (2004) What’s Driving the New Economy? The Benefits of Workplace Innovation. Economic Journal, Vol. 114 (February), pp F97 – F116.

16

Boselie, P., Dietz, G., and Boon, C. (2005) Commonalities and Contradictions in HRM and Performance Research. Human Resource Management Journal, Vol. 15, pp. 67–94.

Boxall, P. and Purcell, J. (2008) Strategies and Human Resource Management, 2nd edition. Palgrave Macmillan: Basingstoke.

Briner, R. (2014) What is Employee Engagement and Does it Matter? An Evidence Based Approach. Mimeo, accessed 18.03.2015.

Brown, S., McHardy, J., McNabb, R. and Taylor, K. (2011) Workplace Performance, Worker Commitment and Loyalty. Journal of Economics and Management Strategy, Vol. 20, pp. 925 -955.

Bryson, A., Forth, J. and Kirby, S. (2005) High Involvement Management Practices, Trade Union Representation and Workplace Performance in Britain. Scottish Journal of Political Economy, Vol. 52, pp. 451 -491.

Cameron, A.C. and P.K. Trivedi (2010) Microeconometrics Using Stata (revised edition). Stata Press: College Station, Texas, USA.

Daniels, K. (2011) Employee Engagement – Factsheet. CIPD: London. Delbridge, R., and Keenoy, T. (2010) Beyond Managerialism? International Journal of Human

Resource Management, Vol. 21, pp. 799–817. Emmott, M. (2010) Employee Engagement is a Strategic Issue. Strategic HR Review, Vol. 9, 40–41. Felstead, A., Gallie, D. and Green, F. (2014) Skills and Employment Series Dataset, 1986, 1992, 1997,

2001, 2006 and 2012 (computer file). 2nd edition. Colchester,UK Data Archive (distributer). Fernie, S. and Metcalf, D. (1995) Participation, Contingent Pay, Representation and

Workplace Performance: Evidence from Great Britain. British Journal of Industrial Relations, Vol. 33, pp. 379–415.

Fox, A. (1966) Industrial Sociology and Industrial Relations. Royal Commission on Trade Unions and Employers’ Associations, Research Paper No. 3. HMSO: London.

Francis, H. and Reddington, M. (2012) Employer Branding and Organisational Effectiveness. In Francis, H., Holbeche, L. and Reddington, M. (eds.) People and Organisational Development: A New Agenda for Organisational Effectiveness. CIPD: London.

Frost, A.C. (2008) The High Performance Work Systems Literature in Industrial Relations. In Blyton, P., Bacon, N., Fiorito, J. and Heery, E. (eds.) The Sage Handbook of Industrial Relations. Sage: London.

Godard, J. (2004) A Critical Assessment of the High-Performance Paradigm. British Journal of Industrial Relations, Vol. 42, pp. 349 -378.

Green, F. (2006) Demanding Work: The Paradox of Job Quality in the Affluent Economy. Princeton University Press: Princeton, New Jersey, USA.

Guest, D. (2002) Human Resource Management, Corporate Performance and Employee Wellbeing: Building the Worker into HRM", Journal of Industrial Relations, Vol. 44, pp. 335–358.

Guest, D.E. (2013) Employee Engagement: Fashionable Fad or Long-Term Fixture?’ In Truss, C., Alfes, K., Delbridge, R., Shantz, A and Soane, E.C. (eds.) Employee Engagement in Theory and Practice. Routledge: London.

Hertzberg, F. (1966) Work and the Nature of Man. World Publishing: Cleveland, Ohio, USA. Huselid, M. (1995) The Impact of Human Resource Management Practices on Turnover, Productivity

and Corporate Performance. Academy of Management Journal, Vol. 38, pp 635 -672. Ichniowski, C., Kochan, T., Levine, D., Olson, C. and Strauss, G. (1996) What Works at Work: Overview

and Assessment. Industrial Relations, Vol. 35, pp 299 -333. Ichniowski, C. and Shaw, K. (2003) Beyond Incentive Pay: Insiders’ Estimates of the Value of

Complementary Human Resource Management Practices. Journal of Economic Perspectives, Vol. 17, pp 155 -180.

17

Ichniowski, C. Shaw, K. and Prennushi, G. (1997) The Effects of Human Resource Management Practices on Productivity: A Study of Steel Finishing Lines. American Economic Review, Vol. 87, pp 291 -313.

Kahn, W.A. (1990) Psychological Conditions of Personal Engagement and Disengagement at Work. Academy of Management Journal, Vol. 33, pp. 692–724.

Kahn, W. 2010. The Essence of Employee Engagement: Lessons from the Field. In Albrecht, S. (ed.) Handbook of Employee Engagement. Edward Elgar: Cheltenham.

Kalleberg, A. L. and Berg, I. (1987) Work and Industry: Structures, Markets and Processes. Plenum: New York, USA.

Kay, J. (1993) Foundations of Corporate Success. Oxford University Press: Oxford. Keenoy, T. (2013) Engagement: A Murmuration of Objects. In Truss, C., Alfes, K., Delbridge, R.,

Shantz, A. and Soane, E.C. (eds.) Employee Engagement in Theory and Practice. Routledge: London.

Kochan, T. A. and Osterman, P. (1994) The Mutual Gains Enterprise. Harvard Business School Press: Harvard, Mass., USA.

Lansbury, R.D. and Wailes, N. (2008) Employee Involvement and Direct Participation. In Blyton, P., Bacon, N., Fiorito, J. and Heery, E. (eds.) The Sage Handbook of Industrial Relations. Sage: London.

Lawler, E.E. (1986) High-Involvement Management: Participative Strategies for Improving Organizational Performance. Jossey-Bass: San Francisco, CA, USA

Legge, K. (2005) Human Resource Management: Rhetorics and Realities. Palgrave Macmillan: Basingstoke.

Levine, D.I. (1995) Reinventing the Workplace: How Business and Employees Can Both Win. Brookings Institution: Washington DC, USA.

Long, J. S. and J. Freeze (2014) Regression Models for Categorical Dependent Variables Using Stata (3rd edition). Stata Press: College Station, Texas, USA.

MacDuffie, J. (1995) Human Resource Bundles and Manufacturing Performance: Organisational Logic and Flexible Production Systems in the World Auto Industry. Industrial and Labor Relations Review, Vol. 48, pp. 197 -221.

MacLeod, D. and Clarke, N. (2009) Engaging for Success: Enhancing Performance through Employee Engagement, A report to Government. Department for Business, Innovation and Skills: London.

McGregor, D.C. (1960) The Human Side of the Enterprise. McGraw-Hill: New York, USA. Maslow, A.H. (1943) A Theory of Motivation. Psychological Development, Vol. 50, pp 370 -396. May, D.R., Gilson, R.L., and Harter, L.M. (2004). The Psychological Conditions of Meaningfulness,

Safety, Availability and the Engagement of the Human Spirit at Work. Journal of Occupational and Organizational Psychology, Vol. 77, pp. 11–37.

Meyer, J.P. and Allen, N.J. (1984) Testing the “Side-Bet” Theory of Organizational Commitment: Influences of Work Positions and Family Roles. Journal of Applied Psychology, Vol. 69, pp. 372-378.

Millward, N., Stevens, M., Smart, D. and Hawes, W. (1992) Workplace Industrial Relations in Transition. Dartmouth: Aldershot.

Morgan, G., Whitley, R. and Moen, E. (2005) Changing Capitalisms? Internationalisation, Institutional Change and Systems of Economic Organisation. Oxford University Press: Oxford.

Osterman, P. (1994) How Common is Workplace Transformation and Who Adopts It? Industrial and Labor Relations Review, Vol. 47, pp 173 – 88.

Parkinson, J. (2003) Models of the Company and the Employment Relationship. British Journal of Industrial Relations, Vol. 41, pp 481 -510.

Penrose, E.T. (1959) The Theory of the Growth of the Firm. Wiley: New York, USA. Pfeffer, J. (2008) Human Resources from an Organisational Behaviour Perspective: Some Paradoxes

Explained. Journal of Economic Perspectives, Vol. 21, pp 115 -134.

18

Procter, S. (2008) New Forms of Work and the High Performance Paradigm. In Blyton, P., Bacon, N., Fiorito, J. and Heery (eds.) The Sage Handbook of Industrial Relations. Sage: London.

Purcell, J. (2014) Disengaging from Engagement. Human Resource Management Journal, Vol. 24, pp. 241 -254.

Purcell, J., Kinnie, N., Hutchinson, S., Rayton, B and Swart, J. (2003) Understanding the People and Performance Link: Unlocking the Black Box. CIPD: London.

Ramsay, H., Scholarios, D. and Harley, B. (2000) Employees and High-Performance Work Systems: Testing inside the Black Box. British Journal of Industrial Relations, Vol. 38, pp 501 -531.

Rees, C., Alfes, K. and Gatenby, M. (2013) Employee Voice and Engagement: Connections and Consequences. The International Journal of Human Resource Management, Vol, 24, pp. 2780 -2798.

Rainnie, A. (1989) Small Isn’t Beautiful: Industrial Relations in Small Firms. Routledge: London. Rich, B.L., LePine, J.A. and Crawford, E.R. (2010). Job Engagement: Antecedents and Effects

on Job Performance. The Academy of Management Journal Vol. 53, pp. 617–35. Robinson, D., Perryman, S., and Hayday, S. (2004) The Drivers of Employee Engagement. Institute for

Employment Studies: Brighton. Saks, A. (2006). Antecedents and Consequences of Engagement. Journal of Managerial Psychology,

Vol. 21, pp. 600–619. Selznick, P. (1957) Leadership in Administration: A Sociological Interpretation. Harper & Row: New

York, USA. Shuck, B. (2011) Integrative Literature Review: Four Emerging Perspectives of Employee

Engagement: An Integrative Literature Review. Human Resource Development Review, Vol. 10, pp. 304–328.

Storey, J. (1989) Introduction: From Personnel Management to Human Resource Management. In Storey, J. (ed) New Perspectives on Human Resource Management. Routledge: London.

Truss, C., Shantz, A., Soane, E., Alfes, K. and Delbridge, R. (2013) Employee Engagement, Organisational Performance and Individual Well-being: Exploring the Evidence, Developing the Theory. The International Journal of Human Resource Management, Vol. 14, pp. 2657 -2669.

van Wanrooy, B., Bewley, H., Bryson, A., Forth, J., Freeth, S., Stokes, L. and Wood, S. (2013) Employment Relations in the Shadow of Recession. Palgrave Macmillan: Basingstoke.

Walton, R. (1985) From Control to Commitment in the Workplace. Harvard Business Review, March –April, pp. 76 -84.

Watson, T.J. (2010) Critical Social Science, Pragmatism and the Realities of HRM. The International Journal of Human Resource Management, Vol. 21, pp. 915–931.

Wood, S. (1999a) Getting the Measure of the Transformed High Performance Organisation. British Journal of Industrial Relations, Vol. 37, pp 391 -417.

Wood, S. (1999b) Human Resource Management and Performance. International Journal of Management Reviews, Vol. 1, pp 367 – 413.

Wood. S. and de Menezes, L. (1998) High Commitment Management in the UK: Evidence from the Workplace Industrial Relations Survey and Employers’ Manpower and Skills Practices Survey. Human Relations, Vol. 51, pp 485 -515.

19

Table 1 Number of Observations in the Pooled Data Set and their Origin Year Frequency Percent Origin

1986 3,844 16.11 Social Change and Economic Life Initiative Surveys

1992 3,212 13.46 Employment in Britain survey

1997 2,394 10.03 Skills Survey

2001 4,367 18.30 Skills Survey

2006 7,281 30.52 Skills Survey

2012 2,762 11.58 Skills Survey

Total 23,860 100.00

Table 2 Percentage Frequency Distributions for the Three Statements Associated with Commitment Table 2a “I feel little loyalty to this organisation” (dependent variable ‘loyal’) Response Percent

Strongly agree 4.49

Agree 20.29

Disagree 69.54

Strongly disagree 30.46

Table 2b “I find that my values and the organisation’s values are very similar” (dependent variable ‘values’) Response Percent

Strongly disagree 3.47

Disagree 22.55

Agree 61.84

Strongly agree 12.14

Table 2c “I am proud to be working for this organisation” (dependent variable ‘proud’) Response Percent

Strongly disagree 3.51

Disagree 18.08

Agree 59.64

Strongly agree 18.77

20

Table 3 Percentage Frequency Distributions for the One Question and Three Statements Associated with Engagement Table 3a “How much effort do you put into your job beyond what is required?” (Dependent variable ‘effort’) Response Percent

None 1.89

Only a little 4.67

Some 24.12

A lot 69.32

Table 3b “I am willing to work harder than I have to in order to help this organisation” (Dependent variable ‘help’) Response Percent

Strongly disagree 2.76

Disagree 16.15

Agree 56.69

Strongly agree 24.40

Table 3c “I would take almost any job to keep working for this organisation” (Dependent variable ‘takeany’) Response Percent

Strongly disagree 23.93

Disagree 51.36

Agree 20.10

Strongly agree 4.61

Table 3d “I would turn down another job with more pay in order to stay with this organisation” (Dependent variable ‘turndown’) Response Percent

Strongly disagree 24.74

Disagree 45.85

Agree 23.84

Strongly agree 5.57

Table 4 Pairwise Correlations: ‘loyal’; ‘values’; ‘proud’; ‘effort’; ‘help’; ‘takeany’; and ‘turndown’ ‘loyal’ ‘values’ ‘proud’ ‘effort’ ‘help’ ‘takeany’ ‘turndown’

‘loyal’ 1.0000

‘values’ 0.4473 1.0000

‘proud’ 0.4966 0.5632 1.0000

‘effort’ 0.2041 0.1935 0.2422 1.0000

‘help’ 0.4189 0.4257 0.4757 0.2557 1.0000

‘takeany’ 0.1986 0.2972 0.3700 0.0926 0.2676 1.0000

‘turndown’ 0.3596 0.4000 0.4874 0.1562 0.3325 0.3980 1.0000

Footnote to the table: Results are statistically significant at (p < 0.01)

21

Table 5 Ordered Logit Results: ‘loyal’; ‘values’; and ‘proud’ Variable Coefficient

(Robust SE) ‘loyal’

Coefficient (Robust SE) ‘values’

Coefficient (Robust SE) ‘proud’

Female .1324 ** (.0537)

.0090 (.0575)

.0121 (.0546)

Age categories 20 -29

.0532 (.0624)

-.0825 (.0658)

.0019 (.0657)

30 -39 (the reference category)

40 -49 .0663 (.0535)

.1891 *** (.0584)

.0870 (.0548)

50 -60 .0049 (.0585)

.2142 *** (.0639)

.0289 (.0613)

Highest educational qualifications Categories None (the reference category)

Level 1 -.1043 (.0903)

.0124 (.0964)

-.3178 *** (.0968)

Level 2 -.0256 (.0747)

-.0202 (.0796)

-.2107 ** (.0828)

Level 3 .0409 (.0794)

.0153 (.0851)

-.2546 *** (.0876)

Level 4 or above -.0776 (.0845)

-.0705 (.0919)

-.3703 *** (.0933)

Not a union member .2187 *** (.0553)

.1629 *** (.0580)

.2136 *** (.0568)

SOC categories Manager

.4400 *** (.0880)

.4978 *** (.0937)

.4134 *** (.0887)

Professional -.0927 (.0985)

.1135 (.1052)

.0195 (.0954)

Associate professional and Technical

.0043 (.0826)

.0377 (.0853)

.1888 ** (.0835)

Administrative and secretarial (the reference category)

Skilled trades -.4426 *** (.0987)

-.2534 ** (.1027)

-.3957 *** (.1033)

Personal services -.2704 *** (.1008)

.1099 (.1086)

.1704 (.1054)

Sales -.2971 *** (.1023)

-.1527 (.1045)

-.0946 (.1050)

Operatives -.4855 *** (.1029)

-.3154 *** (.1047)

-.4465 *** (.1038)

Elementary -.4666 *** (.0945)

-.2835 *** (.0967)

-.3103 *** (.0982)

22

Table 5 cont. Coefficient

(Robust SE) ‘loyal’

Coefficient (Robust SE) ‘values’

Coefficient (Robust SE) ‘proud’

Tenure categories Less than 1 year

-.0277 (.0856)

.1778 * (.0963)

.0799 (.0967)

Between 1 and 2 years (the reference category)

Between 2 and 3 years -.0130 (.0941)

.0697 (.1057)

.0437 (.1051)

Between 3 and 5 years -.0045 (.0856)

-.0297 (.0940)

-.0457 (.0947)

Between 5 and 10 years .0707 (.0766)

.0007 (.0864)

.0474 (.0873)

10 years or more .1248 (.0787)

-.0514 (.0875)

-.0193 (.0870)

Not a permanent contract -.2911 *** (.1027)

-.2624 ** (.1099)

-.2895 *** (.1033)

Working part time .2253 *** (.0841)

.2314 ** (.0916)

.2285 *** (.0833)

Sector categories Private sector (the reference category)

Public sector .0243 (.0762)

.1074 (.0836)

.2224 *** (.0772)

Not for profit organisation .2312 (.1430)

.7498 *** (.1557)

.3935 *** (.1371)

Workplace size categories Less than 25 employees

.2316 *** (.0556)

.3209 *** (.0602)

.3784 *** (.0587)

Between 25 and 99 employees (the reference category)

Between 100 and 499 employees -.1925 *** (.0575)

-.1516 ** (.0609)

-.0295 (.0594)

500 or more employees -.1678 ** (.0672)

-.1556 ** (.0678)

.0498 (.0681)

No unions present at the workplace .2556 *** (.0583)

.3338 *** (.0597)

.2007 *** (.0601)

Received training .1754 *** (.0471)

.1072 ** (.0490)

.2411 *** (.0476)

Was appraised -. 0447 (.0554)

.0494 (.0575)

.1304 ** (.0589)

‘Quality Circles’ operate .2947 *** (.0454)

.3068 *** (.0483)

.3544 *** (.0464)

Meetings with management held .4565 *** (.0571)

.4691 *** (.0595)

.5432 *** (.0580)

1997 (the reference category)

2001 -.0412 (.0621)

.0726 (.0657)

.0684 (.0647)

2006 -.2612 *** (.0613)

-.0427 (.0661)

-.0116 (.0639)

2012 -.1829 ** (.0761)

-.0263 (.0807)

.1444 (.0810)

23

Table 5 cont. Coefficient

(Robust SE) ‘loyal’

Coefficient (Robust SE) ‘values’

Coefficient (Robust SE) ‘proud’

/cut1 -2.0520 (.3535)

-1.7335 (.3790)

-1.5872 (.3526)

/cut2 -.3242 (.3494)

.6046 (.3755)

.5343 (.3486)

/cut3 2.0498 (.3500)

3.8680 (.3788)

3.5428 (.3498)

Number of observations 12514 12319 12438

Wald chi2 (59) = 812.85

(59) = 790.91

(59) = 986.19

Prob > chi2 0.0000 0.0000 0.0000

Psuedo R-squared 0.0423 0.0467 0.0491

Test statistics for the age categories chi2 (3) = 2.14 Prob > chi2 = 0.5432

chi2 (3) = 23.80 Prob > chi2 = 0.0000

chi2 (3) = 3.00 Prob > chi2 = 0.3916

Test statistics for the highest educational qualification categories

chi2 (4) = 5.15 Prob > chi2 = 0.2721

chi2 (4) = 1.85 Prob > chi2 = 0.7634

chi2 (4) = 18.05 Prob > chi2 = 0.0000

Test statistics for the SOC categories

chi2 (8) = 142.48 Prob > chi2 = 0.0000

chi2 (8) = 86.43 Prob > F = 0.0000

chi2 (8) = 103.83 Prob > chi2 = 0.0000

Test statistics for the tenure categories

chi2 (5) = 6.69 Prob > chi2 = 0.2444

chi2 (5) = 8.74 Prob > chi2 = 0.1198

chi2 (5) = 3.57 Prob > chi2 = 0.6131

Test statistics for the sector categories

chi2 (2) = 2.65 Prob > chi2 = 0.2664

chi2 (2) = 23.24 Prob > chi2 = 0.0000

chi2 (2) = 12.66 Prob > chi2 = 0.0000

Test statistics for the workplace size categories

chi2 (3) = 53.48 Prob > chi2 = 0.0000

chi2 (3) = 64.24 Prob > chi2 = 0.0000

chi2 (3) = 55.87 Prob . chi2 = 0.0000

Footnotes to the table: Additionally, the estimated model controlled for the following: ethnicity (via a dummy variable); marital status (via a dummy variable); the length of time it took the individual to learn to do his/her present job well (via a set of 6 dummy variables); the log of the number of hours usually worked; and the SIC of the activity undertaken (via a set of 13 dummy variables). *, **, and *** statistically significant at (p < 0.1), (p < 0.05) and (p < 0.01), respectively.

24

Table 6 Ordered Logit Results: ‘effort’; ‘help’; ‘takeany’; and ‘turndown’ Variable Coefficient

(Robust SE) ‘effort’

Coefficient (Robust SE) ‘help’

Coefficient (Robust SE) ‘takeany’

Coefficient (Robust SE) ‘turndown’

Female .6090 *** (.0622)

.0073 (.0556)

.1229 ** (.0517)

-.0806 (.0527)

Age categories 20 -29

-.2257 *** (.0717)

.0199 (.0655)

.1002 (.0632)

-.0292 (.0622)

30 -39 (the reference category)

40 -49 .1002 (.0623)

.0299 (.0558)

.0106 (.0526)

.1106 ** (.0517)

50 -60 .1829 *** (.0687)

-.0383 (.0626)

-.1145 * (.0594)

.1528 *** (.0581)

Highest educational qualifications Categories None (the reference category)

Level 1 -.0475 (.1126)

-.1634 * (.0943)

-.3753 *** (.1001)

-.1446 (.0975)

Level 2 -.0922 (.0921)

-.0701 (.0750)

-.3244 *** (.0806)

-.0480 (.0790)

Level 3 -.2971 *** (.0955)

-.0062 (.0788)

-.4894 *** (.0848)

-.1199 (.0837)

Level 4 or above -.4189 *** (.0993)

-.0624 (.0846)

-.9464 *** (.0902)

-.2758 *** (.0898)

Not a union member .0113 (.0637)

.2204 *** (.0588)

.0023 (.0560)

.1801 *** (.0536)

SOC categories Manager

.4345 *** (.0988)

.2766 *** (.0887)

-.1004 (.0815)

.3415 *** (.0860)

Professional .0075 (.1089)

-.0867 (.0935)

-.3885 *** (.0906)

-.0038 (.0932)

Associate professional and Technical

.0897 (.0930)

-.0747 (.0844)

-.0753 (.0807)

.1000 (.0794)

Administrative and secretarial (the reference category)

Skilled trades -.1256 (.1092)

-.4428 *** (.1006)

.0074 (.0969)

-.2542 *** (.0979)

Personal services .1509 (.1231)

-.1847 * (.1045)

.1785 * (.0970)

.1033 (.1008)

Sales -.1017 (.1190)

-.3375 *** (.1037)

-.0473 (.1054)

-.2610 ** (.1040)

Operatives -.1587 (.1126)

-.4675 *** (.1009)

.0754 (.1048)

-.4100 *** (.1032)

Elementary -.0264 (.1062)

-.3858 *** (.0949)

.2615 *** (.0954)

-.2784 *** (.0910)

25

Table 6 cont. Coefficient

(Robust SE) ‘effort’

Coefficient (Robust SE) ‘help’

Coefficient (Robust SE) ‘takeany’

Coefficient (Robust SE) ‘turndown’

Tenure categories Less than 1 year

.1234 (.1035)

.0585 (.0910)

.0986 (.0895)

.0398 (.0896)

Between 1 and 2 years (the reference category)

Between 2 and 3 years .2189 * (.1138)

.0533 (.0982)

.1047 (.1011)

.0400 (.1038)

Between 3 and 5 years .2988 *** (.1057)

-.0099 (.0878)

-.0008 (.0877)

-.0023 (.0860)

Between 5 and 10 years .0777 (.0931)

.0575 (.0812)

.1950 ** (.0790)

.0988 (.0789)

10 years or more -.1183 (.0927)

-.0824 (.0830)

.3024 *** (.0813)

.2081 *** (.0794)

Not a permanent contract -.2370 ** (.1143)

-.2978 ** (.1148)

.1036 (.1073)

-.0595 (.1105)

Working part time .2877 *** (.1024)

.1943 ** (.0871)

.0747 (.0825)

.2215 *** (.0835)

Sector categories Private sector (the reference category)

Public sector -.0384 (.0896)

-.0504 (.0781)

-.0379 (.0743)

.0731 (.0760)

Not for profit organisation .1192 (.1600)

.2078 (.1552)

.0439 (.1239)

.5946 *** (.1432)

Workplace size categories Less than 25 employees

.1941 *** (.0670)

.2377 *** (.0578)

.3302 *** (.0554)

.1890 *** (.0555)

Between 25 and 99 employees (the reference category)

Between 100 and 499 employees .0111 (.0683)

-.1407 ** (.0606)

-.1464 ** (.0570)

-.1230 ** (.0565)

500 or more employees -.0837 (.0755)

-.1272 * (.0687)

-.0777 (.0661)

-.0747 (.0640)

No unions present at the workplace .1621 ** (.0689)

.1938 *** (.0589)

.1227 ** (.0572)

.2197 *** (.0559)

Received training .1677 *** (.0532)

.0536 (.0473)

.0612 (.0468)

.1250 *** (.0463)

Was appraised .1646 *** (.0624)

.0331 (.0576)

.0542 (.0573)

-.4575 (.0567)

‘Quality Circles’ operate .3861 *** (.0532)

.3202 *** (.0464)

.0925 ** (.0445)

.1919 *** (.0443)

Meetings with management held .1059 * (.0621)

.2115 *** (.0569)

.2956 *** (.0583)

.3225 *** (.0574)

1997 (the reference category)

2001 -.0519 (0727)

-.0130 (.0652)

-.0166 (.0612)

.0922 (.0615)

2006 -.1501 ** (.0723)

-.4576 *** (.0658)

-.0748 (.0603)

.0646 (.0611)

2012 -.0414 (.0865)

.1159 (.0761)

.3721 *** (.0758)

.1483 *** (.0760)

26

Table 6 cont. Coefficient

(Robust SE) ‘effort’

Coefficient (Robust SE) ‘help’

Coefficient (Robust SE) ‘takeany’

Coefficient (Robust SE) ‘turndown’

/cut1 .0660 (.4110)

-2.0490 (.3693)

-1.2117 (.3614)

-.1494 (.3619)

/cut2 1.3682 (.4083)

.0466 (.3624)

1.2193 (.3609)

1.9562 (.3618)

/cut3 3.3262 (.4086)

2.8220 (.3638)

3.1688 (.3638)

3.9609 (.3648)

Number of observations 12547 12489 12453 12198

Wald chi2 (59) = 1132.90

(59) = 740.97

(59) = 680.60

(59) = 510.25

Prob > chi2 0.0000 0.0000 0.0000 0.0000

Psuedo R-squared 0.0512 0.0393 0.0330 0.0282

Test statistics for the age categories chi2 (3) = 26.95 Prob > chi2 = 0.0000

chi2 (3) = 1.37 Prob > chi2 = 0.7117

chi2 (3) = 9.32 Prob > chi2 = 0.0253

chi2 (3) = 10.59 Prob > chi2 = 0.0000

Test statistics for the highest educational qualification categories

chi2 (4) = 28.66 Prob > chi2 = 0.0000

chi2 (4) = 4.39 Prob > chi2 = 0.3559

chi2 (4) = 142.03 Prob > chi2 = 0.0000

chi2 (4) = 15.64 Prob > chi2 = 0.0035

Test statistics for the SOC categories

chi2 (8) = 43.91 Prob > chi2 = 0.0000

chi2 (8) = 93.44 Prob > chi2 = 0.0000

chi2 (8) = 46.07 Prob > chi2 = 0.0000

chi2 (8) = 79.32 Prob > chi2 = 0.0000

Test statistics for the tenure categories

chi2 (5) = 30.21 Prob > chi2 = 0.0000

chi2 (5) = 6.90 Prob > chi2 = 0.2282

chi2 (5) = 26.00 Prob > chi2 = 0.0000

chi2 (5) = 13.72 Prob > chi2 = 0.0175

Test statistics for the sector Categories

chi2 (2) = 1.07 Prob > chi2 = 0.5844

chi2 (2) = 2.95 Prob > chi2 = 0.2292

chi2 (2) = 0.59 Prob > chi2 = 0.7427

chi2 (2) = 17.47 Prob > chi2 = 0.0002

Test statistics for the workplace size categories

chi2 (3) = 14.54 Prob > chi2 = 0.0023

chi2 (3) = 42.83 Prob > chi2 = 0.0000

chi2 (3) = 71.25 Prob > chi2 = 0.0000

chi2 (3) = 29.96 Prob > chi2 = 0.0000