Work engagement & work alienation: distinct or opposites?

Pati, Surya Prakash ; Kumar, Pankaj

Work engagement and work alienation are considered as bipolar opposites of each other by many researchers. This paper examines whether the sets of items measuring work engagement and work alienation indeed measure similar experiences. Confirmatory factor analysis on 269 responses drawn from various occupational groups reveals that it is erroneous to consider both the constructs as opposite ends of a single continuum. This inference is also reinforced by the pattern of relationship observed between work engagement and work alienation with their antecedents (i.e. occupational self efficacy and meaning) on the one hand and the consequences (job satisfaction and turnover intention) on the other.

Introduction

Brought to prominence by the writings of Marx (1932), research on alienation gradually peaked to establish the same as a central concept in the social sciences of the twentieth century, specifically in the emerging discipline of sociology (Case, 2008). Mann (2001), citing the Oxford Dictionary, defines alienation as "the state or experience of being isolated from a group or an activity to which one should belong or in which one should be involved". The definition summarizes to a large extent the various perspectives on the construct. Thus Horowitz (1966) discusses alienation to be an intense separation first from the objects of the world, second from the people and third from the shared understanding about the world held by other people. Similarly Overend (1975) defines alienation to be a separation of the individual from citizen body, from nature, from production, from other individuals and ultimately from oneself, thereby echoing a "disturbance in a relationship" (Schabracq & Cooper, 2003). The depiction of the construct by Fromm (1955) is also in similar lines. He refers alienation as a state where the individual experiences oneself as an alien, i.e. become estranged from the self. It is a disconnection or a cognitive state of separation in relation to some other element in his or her environment (Kanungo, 1979).

In recent years many researchers are increasingly considering work engagement (1) as the hypothetical obverse of alienation (e.g. Mann, 2001; Case, 2008; Nair & Vohra, 2010; Bothma & Roodt, 2012). Work engagement has been defined as expressed empowerment pertaining to a role, which manifests as passionate task performance and organization citizenship behaviors (Pati & Kumar, 2011; Pati, 2012). While passionate task performance (PTP) refers to investment of discretionary effort in one's assigned task, i.e. investment of extra time, brainpower and energy (Towers-Perrin, 2003), in not just generating more of the usual (Macey & Schneider, 2008), but bringing about something different and beneficial, organization citizenship behaviors (OCB) comprise specific behavior facets that contribute to enhancement of organizational effectiveness yet are often overlooked and inadequately measured in traditional assessment of job performance. Anchoring their view on the premise of many authors opposing the in-role/extra-role approach of studying OCB (e.g. Graham, 1991; Vey & Campbell, 2004), Pati & Kumar (2011) highlighted the importance of OCB as a prime medium to bring about an engaging culture in the workplace and hence to be regarded as a necessary role behavior as well as a dimension of work engagement.

However there exists little empirical evidence to support the assumption of bipolarity between work alienation and work engagement. The aim of this study is to investigate whether the items assessing the hypothesized opposites of work alienation and work engagement, are embeddable on a single underlying bipolar dimension. The current study is an addition to the extant stream of research centered on unearthing the bipolar opposite of work engagement.

Background Research

In an earlier attempt, Maslach & Leiter (1997) theorized burnout to be the negative antithesis of work engagement. They argued burnout to be interpreted as loss of engagement with the job, and is characterized by exhaustion, cynicism, and inefficacy (2). Consequently, the diametrical opposites of the above constructs, i.e. energy, involvement and efficacy respectively characterize work engagement. Further, in line with their argument, they contended that the reverse of the score as assessed through the Maslach Burnout Inventory--General Survey (MBI-GS) (Schaufeli, Leiter, Maslach & Jackson, 1996), provided an insight into an individual's degree of work engagement.

The above theory received further credence with the construction of the Oldenburg Burnout Inventory (OLBI) (Demerouti & Bakker, 2008), which assesses the two burnout dimensions of exhaustion and disengagement. However, unlike MBI-GS, which contains one directional formulation of items in each subscale, OLBI includes both positively and negatively worded items for each dimension, and hence argued to be psychometrically superior. Thus, positively worded items had to be reverse- coded to assess burnout while the same applies to the negatively worded items if one wishes to measure work engagement (Demerouti & Bakker, 2008).

In contrast, Schaufeli, et al (2002) refuted the bipolar measurement of work engagement and burnout, arguing that theoretical opposites need not necessarily translate to antithetical treatment of a single measure (i.e. MGI-GS). They contended that since MBI-GS exclusively comprised unidirectional items, it is, thus, difficult to infer that a respondent's rejection of a negatively worded item means her/his acceptance of a positively worded item. Accordingly they concluded that burnout and work engagement should be conceived as two opposite yet independent concepts, which therefore needs to be assessed through two independent instruments. Their perspective resulted in the design of the Utrecht Work Engagement Survey (UWES -9) (Schaufeli, Bakker & Salanova, 2006), arguably the most widely used measure of work engagement in recent times (Alok, 2013).

However, it was only Gonzalez-Roma, et al. (2006), who originally attempted to explore empirically the existence of a bipolar relationship between the core burnout and engagement dimensions. Accordingly they investigated whether items reflecting exhaustion (burnout) and vigor (work engagement) dimensions are scalable on a single dimension labeled as 'energy' (as labeled by Schaufeli et al., 2002). Similarly, they also investigated whether items corresponding to the dimensions of cynicism (burnout) and dedication (work engagement) are scalable on a single dimension labeled as 'identification' (as labeled by Schaufeli et al. 2002). Employing Mokken analysis across three distinct samples, they found adequate evidence to establish that the core burnout and engagement dimensions could be viewed as inverses along two distinct bipolar dimensions of energy and identification.

Recently Demerouti, Mostert & Bakker (2010) conducted a more detailed study towards testing of the bipolar proposition between the core burnout and work engagement dimensions. Subjecting the items of exhaustion-vigor and cynicism-dedication dyads (borrowed from MBI-GS and UWES respectively) to confirmatory factor analysis (CFA), as well as observing their pattern of relationship shared with other constructs, they inferred that while cynicism and dedication could be construed to be opposites along a single 'identification' dimension, exhaustion and vigor were best represented as distinct yet highly related dimensions, unscalable on a single 'energy' dimension.

Hypotheses

With partial negation of the propositioned bipolar relationship between burnout and work engagement, off late researchers across disciplines (e.g. Mann, 2001; Case, 2008; Nair & Vohra, 2010; Bothma & Roodt, 2012) have indicated work alienation to be the transpose of work engagement. Such advocacy should not be surprising, for both the constructs arguably share the same conceptual foundation. While work engagement is understood to be an expression of empowerment pertaining to a role (Pati & Kumar, 2011), work alienation results from a sense of powerlessness at work (Kanungo, 1992). Similarly, while work engagement results from psychological enabling of employees that provides opportunity for decision making as well as an avenue to influence the organizational outcome significantly (Pati & Kumar, 2011), work alienation, in contrast, is an outcome of management practices that reinforce an inorganic myopic view of employees and their contributions thereby disabling them (Sarros et al., 2002). However, despite the intuitive appeal of a possible bipolar relationship between the constructs, empirical support for the same is absent. Consequently, we state the following hypothesis:

Hypothesis 1 (HI): Work engagement and work alienation are opposite ends of one dimension.

Moving further, if work engagement and work alienation are indeed theoretical transposes, they must exhibit similar pattern of relationships with relevant psychological constructs. Such similarity in relationships shall provide decisive proof of their bipolarity, while differential relationship shall reflect their distinctiveness. Therefore in this study we propose to examine and compare the relationships of both the constructs with psychological meaningfulness, occupational self-efficacy, turnover intention, and job satisfaction. The above constructs were selected owing to their rich relevance to the literature of work engagement.

With reference to his ethnographic study, Kahn (1990) asserted psychological meaningfulness to be a necessary condition for expression of work engagement. His argument was subsequently supported empirically, with numerous studies across contexts consistently reporting a significant positive relationship between the constructs (e.g. May et al., 2004; Rothmann & Hamukang'andu, 2013; Woods & Sofat, 2013). Similarly occupational self-efficacy was reported to relate positively with work engagement (Pati & Kumar, 2010), while turnover intention was found to relate negatively with the same (Harter et al. 2002; Saks, 2006). Finally work engagement was also found to relate positively with job satisfaction (Harter et al., 2002; Saks, 2006).

Consequently work alienation must share an equivalently strong, yet negative relationship with the constructs of psychological meaningfulness, occupational self-efficacy, and job satisfaction. Further it must relate equivalently yet positively with turnover intention. The above discussion leads to the following hypothesis:

Hypothesis 2 (H2): Work engagement and work alienation shall be equally related to other constructs (psychological meaningfulness, occupational self efficacy, turnover intention and job satisfaction), but in opposite directions.

Sample

A cross sectional survey was conducted using a convenience sample of employees belonging to various organizations across industrial sectors (N = 269). The respondents were participants in an executive development program at a premier management institute in India. After explaining to them the purpose of this research and assuring them of the anonymity and confidentiality of their responses (also communicated through a note), they were sent a link to an online survey designed for the study over electronic mail. The participants were requested to fill up the same. Two email reminders were also sent to ensure a sizeable response.

The demographic analysis revealed that while a little more than 50% of respondents were employed with the Information Technology (IT) industry, 18.2% of them worked in the High Technology industry. Similarly it was observed that approximately 7.8% and 7.4% of the participants were employed with the Pharmaceutical industry and Banking & Financial Service (BFS) industry respectively. The remaining respondents belonged to Education (7.8%), Real Estate (4.4.%) and Automobile Manufacturing (2.6%) industries. The average age of the sample was calculated to be 34.33 years (S.D. = 5.17), while the average work experience was determined to be 6.42 years (S.D. = 4.78). Educationally, 7 respondents possessed a Doctoral degree, while approximately 62% possessed an Undergraduate degree. The rest of the respondents possessed a Master's degree. Females consisted of only 10.5% of the respondents.

Instruments

Work engagement: Work engagement (WE) was measured with the 7-item Employee Engagement Instrument (EEI-7) developed by Pati (2012). It is a self-report scale and is anchored on the theoretical insights of Pati & Kumar (2011), who defined engagement to be expressed empowerment pertaining to a role. It encases two subscales, designed to tap into each of the sub-dimensions of the engagement construct, i.e. passionate task performance (PTP, 3 items) and organization citizenship behavior (OCB, 4 items). All items are scored on a 5-point Likert scale (1--strongly disagree, 5--strongly agree). A representative item for PTP is "I give my all to my job", while for OCB is "I frequently suggest coworkers on how the group can improve".

Work alienation: Work alienation (WA) was measured with the 8-item self-report instrument designed by Nair & Vohra (2010). All the items are to be responded on a 5-point Likert continuum (1--strongly disagree, 5--strongly agree), and load on a single factor. A sample item is "Work to me is more like a chore, a burden".

Job satisfaction: Job satisfaction (JS) was assessed with 3 items from the Michigan Organizational Assessment Questionnaire (Cammann et al., 1979). Response choices for the items range on a 5-point scale (1--strongly disagree, 5--strongly agree). An example of one such item is : "All in all, I am satisfied with my job".

Turnover intention: Turnover intention (TOI) was measured using the 3-item self-reported turnover intention scale from the Michigan Organization Assessment Questionnaire (Cammann et al., 1979), scored on a 5-point Likert scale (1--strongly disagree, 5--strongly agree). A representative item is: "I am seriously thinking of quitting my job".

Occupational self-efficacy: Occupational self-efficacy (OSE) was measured with the self-report instrument developed by Rigotti et al. (2008) containing 6--items. Responses are captured on a 5-point scale (1--strongly disagree, 5--strongly agree). A sample item is: "I meet the goals that I have set for myself in my job".

Meaning: Meaning was assessed with items borrowed from the empowerment scale designed by Spreitzer (1995). It is a 3-item self-report that solicits responses from participants on a 5-point Likert continuum (1--strongly disagree, 5--strongly agree). An example of an item is: "The work I do is meaningful to me.

Procedure

To test the existence of the hypothesized bipolarity between work engagement and work alienation, we defined five competing models (fig. 1). In these models, we inputted the scores captured through the work alienation instrument to investigate its convergence with the scores of EEI-7. Model 1 explains the responses to the items in terms of three first-order factors [i.e. PTP, OCB and WA] (3). In Model 2 and Model 3, we propose to investigate the existence of possible bipolarity between the subscales of work engagement with that of work alienation. Thus, in Model 2 we constrained the correlation coefficient between PTP and WA to -1 (thereby implying bipolar constructs), while in Model 3 we constrained the correlation coefficient between OCB and WA to -1. Models 4(a), 4(b) and 5 are higher order models, whose aim is to describe correlations among various factors in terms of higher order factors. Thus, in Model 4 (a) we constrained the correlation coefficient between second order factors WE and WA to -1, while in Model 4 (b) we relaxed the same to -0.7 (4). Finally in Model 5, WA and WE were allowed to correlate with each other without any constraints.

[FIGURE 1 OMITTED]

Data Screening

The means, standard deviations, internal consistency reliability estimates (through Cronbach Alpha) and the first order correlation coefficients among the study variables are presented in Table 1. Their z values for skewness (ranges from -0.419 to -1.499) and kurtosis (ranges from 0.026 to 1.803) were found to be within acceptable limits (5). Thus there were no serious departures from normality. Further all the variables reported were found to have an acceptable Cronbach Alpha (6).

Confirmatory Factor Analysis

AMOS 6.0 software was employed to calculate the fit indices for the proposed models (Model 1-5). Maximum Likelihood (ML) estimation was used to estimate the parameters (7).

Table 2 presents the findings of overall model fit for Models 1-5. The fit indices of Model 1 were within the recommended parameters (8). It means all the factor structures are well defined with all factor loadings statistically significant and each of the three factors accounting for a significant portion of the variance. Model 2 and Model 3 fitted the data significantly worse than Model 1, thereby implying that WA is dissimilar to PTP and OCB respectively. Thus WA is not the bipolar opposite of either PTP or OCB. On examining the fit indices of the higher order models (i.e. Model 4 (a); Model 4 (b) and Model 5), we found Model 5 fitted the data significantly better than Model 4 (a) and Model 4 (b). Thus WA does not measure the same experience as WE. Hence we conclude that WA and WE are distinguishable factors and do not represent the two ends of a bipolar construct. Thereby we reject Hypothesis 1.

Work Alienation & Engagement

Considering that work alienation and work engagement are bipolar opposites, the strength of their relationship with other constructs should be equal, albeit in opposite direction. Thus we investigated their relationship with the constructs of occupational self-efficacy, meaning, turnover intention, and job satisfaction. Table 1 displays the calculated correlation coefficients.

We utilized Guildford's (1973) rule to interpret the strength of the relationships which suggests that correlation coefficients less than 0.20 may be labeled as "negligible", between 0.20 and 0.40 may be labeled as "low", between 0.41 and 0.70 may be termed as "moderate", between 0.70 and 0.90 may be marked as "high" and more than 0.90 may be considered as "very high". Accordingly, while the relationship between work engagement and job satisfaction (r = 0.344. p < 0.01) was found to be low, work alienation moderately correlated with job satisfaction (r = -0.673, p < 0.01). Similarly, work engagement recorded a moderate correlation with occupational self--efficacy (r = 0.540, p < 0.01) while work alienation revealed a low correlation with it (r = -0. 392, p < 0.01). However meaning moderately correlated with both work alienation (r = .0500, p < 0.01) and work engagement (r = 0.441, p < 0.01). Finally we found that only work alienation registered a significant relationship with turnover intention (r = 0.499, p < 0.01) while the relationship with work engagement was non-significant.

Hence, based on the evidence from this study, we can state that hypothesis 2 (H2) was partially supported, for while work alienation and work engagement correlated with other constructs in opposite directions, however the effect size was not equal. Thus work engagement and work alienation are related constructs, indicating contrasting experiences, and are not bipolar opposites of each other.

Common Method Variance

Since various self-report inventories formed the source of data for this research, there is a possibility of data contamination due to common method variance. Although various initiatives like anonymity of respondents and counterbalancing item orders (Podsakoff et al. 2003) were consciously incorporated during research design to limit the effect of common method variance, yet a statistical proof shall increase the confidence on the findings. Thereby we conducted the Harman's single factor test, which is popular among researchers to address this issue (Podsakoff et al., 2003). Accordingly, we conducted an exploratory factor analysis of all the items. Six distinct factors were identified explaining 66.16% of the variance thereby removing any apprehension that common method variance was a likely contaminant of the study findings (9).

Discussion & Limitations

The aim of the study was to ascertain whether the dimensions of work alienation and work engagement were indeed opposites as postulated. Our findings revealed that the items of work engagement and work alienation were not scalable on a single bipolar dimension. Thus, it could safely be concluded that the constructs were explaining distinct experiences. Based on the available evidence, they could at best be indicated as bivariates but not bipolar.

Our study makes a significant contribution towards the conceptual development of the work engagement construct, the literature on which is still nascent (Pati & Kumar, 2011), and the legitimacy of which is still questioned (Schaufeli & Bakker, 2010). It may be reiterated that many researchers argue work engagement and work alienation to be opposites (e.g. Mann, 2001; Case, 2008; Nair & Vohra, 2010; Bothma & Roodt, 2012). To the best of our knowledge, no empirical study had verified the claim. Our study provides empirical proof towards rejection of this proposition.

In practice, the importance of uncovering whether work alienation and work engagement are each other's opposites relates mainly to psychometric concerns within organizational studies. Organizations need short and valid instruments to evaluate the work attitudes and behaviors of their employees (Demerouti, Mostert & Bakker, 2010). Viewed from this light, the current study cautions organizations towards interpreting the reverse of their employees' work alienation scores as their extent of work engagement (or vice versa). Further, the findings also indicate that both the constructs may have separate antecedents.

However, our study is not without its limitations. The most important limitation is that our inference is anchored on a single measure of work engagement (by Pati, 2012). There are four additional conceptualizations of engagement and associated measures available in literature (i.e. May et al., 2001; Schaufeli et al., 2002; Saks, 2006; Rich, Lepine & Crawford, 2010). Future research should explore the validity of our findings in relation to the above. Such investigations shall help enhance the generalizability of our findings and contribute significantly to theory and practice.

Another possible drawback of our study is the use of English language in communicating the survey instruments. Since English is not the native language of Indians, there is a possibility that participants had misunderstood and misinterpreted the items while responding. Our apprehension draws support from Alok (2013) who, upon subjecting the items of Utrecht Work Engagement Survey (UWES--9) in India, reported a single factor, which was in contrast to the original three-factor model that UWES-9 was supposed to comprise and assess. Such an anomaly may result due to limited knowledge of English language.

Finally, although the sample of participants represented a diverse number of jobs across sectors, yet it was not representative of full range of possible occupations. Moreover, males dominated the sample. Future studies might focus on testing the possible invariance of our study findings through representative samples drawn across age groups, occupational groups, gender and cultures.

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Surya Prakash Pati is Assistant Professor, HRM Group, Indian Institute of Management Kozhikode. E-mail: [email protected]. Pankaj Kumar is Professor (HRM). Indian Institute of Management Lucknow. Email: [email protected]

(1) Engagement, work engagement, and employee engagement are synonymous constructs, indicating the very same experience. The literature is replete with evidence that suggests interchangeable usage of the terms (e.g. Schaufeli et al.,2013).

(2) MBI-GS contains items that measure professional efficacy and not inefficacy. The scores thus obtained are to be reversed and added to the scores of exhaustion and cynicism if one needs to calculate the total burnout score.

(3) Marsh, Antill & Cunningham (1989) lionize the importance of the first order model. They state that the goodness of fit of the first order model establishes an upper limit for higher order models on the same data.

(4) Mathiowetz (2003) reports that if correlation coefficient between two assessments ranges between r = 0.70 and 1, then the two assessments most likely are measuring the same construct. Therefore in this research we propose to examine the model fit while constraining the correlation coefficients between WA and WE at both ends of the above limit, i.e. r = -0.70 (Model 4b) and r = 1 (Model 4a).

(5) Cramer (1997) asserts that a z value within +2 and -2 for both skewness and kurtosis indicates that the data is normally distributed.

(6) Nunally (1978) restricts the minimum acceptable Cronbach Alpha for a factor to 0.7

(7) There is no single fit criterion in CFA. Instead, several indices exist that measure the fit of the model from varied perspectives. Therefore several authors (e.g. Hoe, 2008) recommend the use of multiple indices to infer about the global fit of a proposed model. The most popular of these fit indices are the CMIN/df, CFI, TL1, and RMSEA (Hoe, 2008), whose scores are provided in this research.

(8) It must be noted that the modification indices suggested us to correlate the errors of the items OCB3 and OCB4 for a better fit. Upon incorporating the suggestion it did improve the fit indices (specifically RMSEA). This was a departure from the original scale of Pad (2012), which suggested no such modification. To explain such an action, we examined the content of both the items. A convergence of content was inferred, which we identified as persistence under duress. [OCB3 reads as "For issues which may have serious consequences, I express my opinions honestly even when others may disagree"; OCB4 reads as "I show genuine concern and courtesy towards coworkers, even in the most trying business or personal situations"]

(9) The items of job satisfaction and turnover intention loaded on a single factor. Such a result was surprising yet was not alarming in this study for they were not the primary variables of interest. On closer examination of the items of both the constructs, we found them to represent opposite experiences that probably could have influenced such a result, e.g. the item "In general I like working at my job", belonging to the construct of job satisfaction appears to be an exact opposite of "I am seriously thinking of quitting my job", that measures turnover intention.

Table 1 Means, Standard Deviations, Reliability and Inter-correlations

Constructs   Mean    Std. Dev.   Reliability   PTP        OCB

PTP          12.28   2.16        0.794
OCB          16.58   2.25        0.702         .436 **
WE           28.86   3.73        0.783         .840 **    .854 **
WA           15.07   6.49        0.908         -.324 **   -.332 **
JS           11.68   2.52        0.845         .295 **    .287 **
TOI          7.22    3.37        0.888         -.073      -.105
OSE          25.05   3.10        0.840         .412 **    .501 **
MEANING      15.98   3.25        0.916         .405 **    .344 **

Constructs   WE         WA         JS         TOI        OSE

PTP
OCB
WE
WA           -.387 **
JS           .344 **    -.673 **
TOI          -.106      .499 **    -.625 **
OSE          .540 **    -.392 **   .386 **    -.097
MEANING      .441 **    -.500 **   .524 **    -.292 **   .470 **

Note: ** p < 0.01; PTP: passionate task performance; OCB: organization
citizenship behavior; WE: work engagement; WA: work alienation; JS: job
satisfaction; TOI: turnover intention; OSE: occupational self efficacy

Table 2 Comparison of Fit Indices of Competing Models Post CFA

Model fit   Acceptable   Model 1   Model 2   Model 3
indices       values

CMIN/df        < 3        2.627     3.691     4.485
TLI           0.9-1       0.909     0.850     0.805
NFI           0.9-1       0.886     0.838     0.803
GFI           0.9-1       0.899     0.873     0.857
CFI           0.9-1       0.926     0.875     0.839
RMSEA         < 0.08      0.078     0.100     0.114

Model fit   Model 4(a)   Model 4(b)   Model 5
indices

CMIN/df       3.691        3.223       2.627
TLI           0.850        0.876       0.909
NFI           0.838        0.859       0.886
GFI           0.873        0.889       0.899
CFI           0.875        0.897       0.926
RMSEA         0.100        0.091       0.078

Note: The guidelines for "Acceptable values" were borrowed from
Hoe (2008); CMIN-df: Ratio of chi-square statistic to the degrees
of freedom; TLI: Tucker-Lewis Index; NFI: Normed Fit Index; GFI:
Goodness of Fit Index; CFI: Confirmatory Fit Index; RMSEA: Root
Mean Square Error of Approximation