The Predictors of Employee Engagement: A Study in a Ferro Alloys Company of India

Abstract

Employee engagement is now the buzzword for any organization. Although it was initially believed that a satisfied employee is the most engaged employee, contradictory findings have compelled researchers to identify alternate models of engagement. In the same line of thought, this study aims at identifying the triggers of employee engagement. Employees in the payroll of a reputed ferro alloys company of India were surveyed to obtain relevant information on employee engagement. Data analysis on 250 responses reveals that factors such as age, senior leadership, manager, colleagues, customers, work, resources, processes, career opportunities, learning and development, work–life balance, physical work environment, policies, people practices, performance assessment, diversity, company reputation, pay, benefits and recognition significantly correlated with employee engagement. However, on account of multicollinearity, when stepwise regression was conducted, following factors were found to be significantly predicting employee engagement: senior leadership, work, company reputation, manager, process, colleague and physical work environment. Results were discussed in relations to recent findings in other industries.

Keywords

Employee engagement factors influencing engagement manufacturing company India

Introduction

Employee engagement has become a buzzword in the lexicon of management in recent times. The popularity of the concept has increased manifold due to the advantages that accrue to organizations on account of the presence of engaged employees in their payrolls. According to resource-based view (RBV), engaged employees are strong organizational strategic assets which is difficult to imitate (Joo & Mclean, 2006) and hence, provide competitive advantage to organizations.

The employee engagement construct is not only popular for its relationship with employee productivity, it is also an evolving construct and researchers are trying to define it in different ways and accordingly number of measures have been developed for measuring the same. Studies have also been done to identify the predictors of employee engagement. Despite the large number of research studies undertaken in the area of employee engagement, there is an acknowledgement of the fact amongst researchers that the predictors of employee engagement has to be further explored in various industry contexts to fully appreciate the rich nuances of this complex construct and its workings.

Experts (Harman & Rama Rao, 2012) in the field of ferro alloys hold that the burgeoning steel industry in the country as well as across the globe is slated to increase ferro alloys consumption manifold in this decade. They have further observed that the cost of raw materials in the industry is increasing. In such a scenario, an engaged employee can only strive to work hard, understand the complex production process, take steps to cut costs and economize so as to keep the final price of the product in check. Therefore, it becomes imperative that the ferro alloys companies fully understand the predictors of employee engagement and nourish them adequately to promote an engaged employee culture in the organization.

Literature Review

Employee engagement generally refers to intellectual and emotional commitment to organizations. Many scholars have given definitions of employee engagement. To mention few, Falcone (2006), has defined engagement as the state of emotional and intellectual commitment to an organization or group. According to Richman (2006) ‘an engaged employee is seen to be fully involved in his or her work and exhibits great deal of enthusiasm about the same’.

Researchers have also identified different underlying dimensions of employee engagement. Rothbard (2001) has identified two dimensions of engagement: attention and absorption. While attention means ‘cognitive availability and the amount of time one spends thinking about a role’, absorption refers to ‘being engrossed in a role and the intensity of one’s focus on a role’.

Kahn (1990) has proposed a three-dimensional definition of employee engagement. According to him, employee engagement comprises emotional, cognitive and physical engagement. Emotional engagement refers to forming meaningful connections with peers, colleagues and showing empathy and concern for other’s feelings. Cognitive engagement happens when employees are aware of their mission and role in their work environment. Physical engagement refers to being physically active and involved in the job. However, employees can be engaged in one dimension while being low in other dimension.

Often employee engagement construct is confused with very similar constructs like intrinsic motivation, organizational citizenship behaviour (OCB), job involvement and organizational commitment. However, researchers have tried to clarify such confusions. For example, Ryan and Deci (2000) states that employee engagement is to some extent similar to the autonomous regulation aspect of motivation. As explained in self-determination theory (SDT), autonomous regulation is dependent on the basic psychological needs for competence, autonomy and relatedness.

Engagement is different from organizational commitment and organizational citizenship behaviour. While organizational commitment is an attitude and mostly refers to attachment towards organization, engagement refers to the extent of attentiveness and absorption of the employee in his/her job. Similarly, employee engagement is different from OCB in the way the job/role is handled. While the OCB refers to the informal and voluntary behaviour that benefits co-worker and the organization, the latter refers to the focus on one’s formal role and does not involve any extra role (Robinson, Perryman & Hayday, 2004). Employee engagement is also different from job involvement concept which refers to cognitive evaluation about the need satisfying ability of the job. But, engagement refers to being cognitively, emotionally and physically involved in the job. Further, psychological state of engagement is just opposite of burnout. If we look at the three dimensions of engagement, that is, energy, involvement and efficiency, these are contradictory to the exhaustion, cynicism and inefficiency dimension of burnout (Maslach, Schaufelli & Leiter, 2001). Hence, it can be concluded that employee engagement is a distinct and unique construct that refers to ‘a positive, fulfilling, work–related state of mind that is characterized by vigor, dedication, and absorption’ (Schaufeli et al., 2002).

Research on the nature of employee engagement reveals that engagement is a relentless and pervasive affective–cognitive state of mind (Schaufeli et al., 2002). Further he adds, this is neither directed towards any object, event and individual behaviour nor a momentary state of mind. Hence, inculcating employee engagement will result in long-term gains.

Predictors of Employee Engagement

Numbers of studies have been conducted to identify the factors affecting employee engagement (Cropanzano & Mitchel, 2005; Kahn, 1990; May, Gilson & Harter, 2004). Identification of predictors or ‘hot buttons’ of engagement help the HR to better understand what practices and policies in their organization would effectively promote employee motivation, attendance, retention and productivity. Kahn (1990) has provided a three-dimensional framework of organizational culture for employee engagement. According to him, a workplace culture characterized by psychological conditions of meaningfulness (achieved through job enrichment, work–role fit), safety (induced by supportive manager and co-worker) and availability (refers to availability of all kinds of resources) makes people more engaged. Vance (2006) has identified some factors such as learning and development opportunities, mission and values of the company, treatment of people, work–life balance policies and practices and rewards to employees for their effort influencing employee engagement. Similarly, Jose and Mampilly (2014) found out that psychological empowerment leads to employee engagement. Some researchers believe that clear, consistent and honest communication is an important management tool for employee engagement (Ruck & Trainor, 2012). To put these altogether, engagement germinates and grows in an organizational culture where trust, respect, openness, connectedness, integrity and opportunities for learning and development exist.

The Maslach et al. (2001) model of engagement and burnout states that there are six factors that influence engagement, that is, workload, control, reward and recognition, community and social support, perceived fairness and values. In other words, employees are highly engaged when, (i) employees perceive that the workload is in a sustainable state; (ii) they have choice and control; (iii) are getting appropriate reward and recognition; (iv) the work community is supportive; (v) fairness and justice prevail in the organization; and (vi) finally they find meaning in their work; they tend to be highly engaged.

Saks (2006) has found that the factors such as job characteristics, perceived organizational support, perceived supervisor support, reward and recognition, procedural justice and distributive justice influence employee engagement. According to Eisenberger et al. (1986), employee engagement will happen when there is employee–job fit; employee expectations for the job are met; there is perceived organizational justice; and perceived organizational support.

In line with the previous findings, the research by Richman, Civian, Shannon, Hill and Brennan (2008) reveals that perceived flexibility and supportive work–life policies influence employee engagement. In addition to this, they have found out that formal and occasional use of flexibility is positively associated with perceived flexibility and engagement.

Some experts have attempted to summarize the concept related to employee engagement and have prescribed some facilitators of employee engagement for leadership effectiveness. For example, Seijts and Crim (2006) have stated that 10 Cs are important for employee engagement. These are: clarity, connect, convey, career, contribute, congratulate, control, credibility, collaborate and, finally, confidence. They assert that a leader can make employees engaged by following this 10 Cs framework, not by compelling them.

This study joins the identification of triggers of employee engagement spree. The triggers identified here are based on employee engagement literature and discussion with the management of the studied organization.

The Study Context

The existence and growth of ferro alloys industry in India has been spanning over a period of almost six decades. At present, the industry has a production capacity of 5.15 million tons per annum. The products include manganese alloys, ferro alloys, ferro silicon, chrome alloys, noble ferro alloys etc. (www.ifapaindia.org). Steel and aluminium companies are the consumers of ferro alloys products.

The company studied here is a 50-year-old ferro alloys company with a production capacity of around 90,000 MTs per annum. It has best management practices such as Six Sigma, Total Production Management (TPM), Quality Circle (QC) etc., in place. The present study on employee engagement is one such attempt towards overall organizational effectiveness.

The objectives of the study are

to find out the level of engagement and employee satisfaction across different managerial levels, age and experience groups and

to study the factors influencing employee engagement in the studied company.

Method

Sample Profile

Table 1 presents the sample profile. The demographic information of the respondents included gender, age, location, years of experience and managerial level. As is seen in Table 1, almost all the respondents were male (98 per cent), and belonged to junior management level (84 per cent). However, in case of age and years of experience, the distribution was uniform to some extent across levels.

Table 1.

Sample Profile

		Frequency	Percentage
Gender	Male	245	98
	Female	5	2
Age group	60+ years	0	0
	50+ years	42	16.8
	40+ years	103	41.2
	30+ years	69	27.6
	20+ years	35	14.0
	10+ years	1	0.4
Location	L–A	193	77.2
	L–B	11	4.4
	L–C	44	17.6
	L–D	1	0.4
	L–E	1	0.4
Years of experience	=20 years	50	20.0
	11–20 years	33	13.2
	6–10 years	33	13.2
	1–5 years	91	36.4
	<1 year	43	17.2
Managerial level	Junior management	212	84.8
	Middle management	33	13.2
	Senior management	5	2.2

Source: Authors’ own findings.

Data Collection

The target of the study was to cover all staff in the pay role of the studied company. For this purpose, an online survey instrument was developed and the employees were informed to login and respond to the questionnaire. It was a one-month long activity and at the end of the month, 318 employees could fill up the questionnaire. However, after screening for completeness of the responses, 250 respondents were found to have responded to all the questions. Consequently, these 250 responses were used in final analysis.

Measures

A survey instrument was prepared to measure the level of engagement and other job-related perceptions. Responses were collected in 6-point rating scale where ‘1’ denoted ‘strongly disagree’ and ‘6’ ‘strongly agree’. Along with demographic variables, the survey instrument captured 20 other constructs such as engagement, senior leadership, manager, colleagues, customers, work, resources, processes, career opportunities, learning and development, work–life balance, physical work environment, policies, people practices, performance assessment, diversity, company reputation, pay, benefits and recognition. Based on review of literature and consultation with the top management, 113 statements were generated to measure the above 20 constructs. Particularly to measure employee engagement, Aon Hewitt’s (2015) dimensions of employee engagement was considered. The items of Aon Hewitt measure of employee engagement were pertaining to three dimensions: say, stay and strive. Say implied to what extent employees speak positively about the organization, stay refereed to what extent the intention of employees to be a part of the organization and strive implied the desire of employees to go above and beyond their job. In consultation with the management, six statements were used to capture the above three dimensions of employee engagement (see Table A1). Involvement of top management in the scale construction process helped in making the items more context-specific and appropriate. The reliability of the survey instrument was very good (α = 0.98). The construct validity of the engagement scale was measured using exploratory factor analysis. The six items loaded on 3 factors (stay: 1 and 4, say: 3 and 5, strive: 2 and 6). The cumulative percentage was 71.67 per cent, indicating the high construct validity of the scale. Since the items were developed by consulting valid literature source and in consultation with the management of the company, it was also high on content and face validity.

Results

ANOVA tests, correlation analysis and regression analysis were conducted to analyze the data. ANOVA tests were conducted to know whether people across different demographic groups differed on the 20 constructs.

The descriptive statistics and one-way ANOVA test results are presented in Tables 2, 3 and 4. Results reveal that colleagues, company reputation and work–life balance are the areas where people from different managerial levels differed (F = 5.907, 4.07 and 4.482) and df = 2/247. People belonging to lower management had better perception about colleagues, company reputation and work–life balance. As it is seen in Table 2, senior management had lower mean scores on these dimensions.

Table 2.

Difference in Management Level vis-à-vis Engagement and Other Perceptual Dimensions

		N	Mean	Std. Deviation	F
Colleagues	Junior	212	19.6651	2.66913	5.907^**
	Middle	33	19.3333	3.12916
	Senior	5	15.2000	7.91833
Work–life balance	Junior	212	23.0566	3.76144	4.482^*
	Middle	33	22.1212	4.06015
	Senior	5	18.2000	7.01427
Company reputation	Junior	212	4.75	1.030	4.07**
	Middle	33	4.79	0.992
	Senior	5	3.40	2.074

Source: Authors’ own findings.

Notes: F = one-way ANOVA, degrees of freedom, df = 2/247; **p < 0.01, *p < 0.05.

Table 3.

Difference in Age Level vis-à-vis Engagement and Other Perceptual Dimensions

		N	Mean	Std. Deviation	F
Engagement	20+	35	24.97	4.64	1.99^*
	30+	69	26.47	4.92
	40+	103	27.08	4.68
	50+	42	27.95	5.40
Senior leadership	20+	35	44.11	9.56	2.44^*
	30+	69	44.23	9.09
	40+	103	46.85	8.32
	50+	42	48.83	9.21
Work	20+	35	55.80	11.75	3.047^**
	30+	69	56.11	8.93
	40+	103	58.38	7.57
	50+	42	61.28	6.45
Resources	20+	35	18.82	3.84	3.169^**
	30+	69	17.75	3.55
	40+	103	18.75	2.57
	50+	42	19.88	2.76
Processes	20+	35	13.11	2.63	2.435^*
	30+	69	13.15	2.15
	40+	103	13.77	1.91
	50+	42	14.09	1.67
Recognition	20+	35	24.88	6.15	2.116^*
	30+	69	26.23	4.88
	40+	103	26.82	4.31
	50+	42	27.97	4.66

Source: Authors’ own findings.

Notes: F = one-way ANOVA, degrees of freedom, df = 2/247; **p < 0.01, *p < 0.09.

Table 4.

Difference in Experience vis-à-vis Engagement and Other Perceptual Dimensions

		N	Mean	Std. Deviation	F
Senior leadership	=20 years	50	48.40	8.35	2.08^*
	11–20 years	33	46.57	9.199
	6–10 years	33	47.42	7.66
	1–5 years	91	44.20	9.56
	<1 year	43	45.81	8.66
Colleague	=20 years	50	20.10	2.28	2.61^*
	11–20 years	33	19.72	2.11
	6–10 years	33	19.81	2.83
	1–5 years	91	19.63	2.92
	<1 year	43	18.27	3.93
Work	=20 years	50	60.42	5.65	2.27^*
	11–20 years	33	58.84	5.46
	6–10 years	33	58.90	7.53
	1–5 years	91	56.43	10.79
	<1 year	43	56.46	8.55
Resources	=20 years	50	19.62	2.72	3.09^**
	11–20 years	33	19.00	1.62
	6–10 years	33	19.33	2.56
	1–5 years	91	18.26	3.66
	<1 year	43	17.69	3.41
Processes	=20 years	50	13.96	1.68	2.35^*
	11–20years	33	14.15	1.39
	6–10years	33	13.75	2.26
	1–5 years	91	13.30	2.36
	<1year	43	13.00	2.02
People and practices	=20 years	50	19.34	2.27	2.55^*
	11–20years	33	18.03	2.89
	6–10years	33	19.00	2.01
	1–5 years	91	18.02	3.47
	<1year	43	17.76	3.22
Diversity	=20 years	50	23.18	3.02	2.75^*
	11–20 years	33	21.00	3.91
	6–10 years	33	22.96	3.09
	1–5 years	91	21.50	4.19
	<1 year	43	21.95	3.87
Company reputation	11–20 years	33	4.55	1.09	4.06^**
	6–10 years	33	5.06	0.80
	1–5 years	91	4.61	1.09
	<1 year	43	4.40	1.21

Source: Authors’ own findings.

Notes: F = one-way ANOVA, degrees of freedom, df = 2/247; **p < 0.01, *p < 0.09.

People from different age groups were found to be differing in engagement, senior leadership, work, resources, processes and recognition. Older employees were found to be giving higher ratings than their younger counterparts. On the other hand, people from different experience level differed in the areas of senior leadership, colleagues, resources, processes, people practices, company reputation and diversity. What remains constant with increasing age and experience is the appreciation towards senior leadership, resources and processes.

To understand how all the dimensions are related to each other, multiple correlation was conducted. As is revealed from Table 5, all the perceptual dimensions highly correlated with engagement. Among the demographic factors, age was positively correlated with engagement. This result also indicates existence of multicollinearity (Willis et al., 1978) among studied variables. Hence, a stepwise regression was conducted to identify the predictors of engagement. Stepwise regression method looks for independent variable that most correlates with the dependent variable. The ‘forward’ stepwise method using SPSS 20.0 identified seven significant factors influencing employee engagement.

Table 5.

Correlation among Demographic Variables, Satisfaction Factors and Employee Engagement

	mgt	Age	Exp	Eng	SrL	Man	Col	Cus	Wrk	Res	Pro	COp	L&D	WLB	PWE	Policy	PPr	PAp	Div	CRp	PAY	Ben	Rec
mgt	1	0.341**	0.083	0.067	0.037	–0.030	–0.159*	–0.020	0.027	0.009	–0.036	–0.044	–0.054	–0.167**	0.002	–0.072	–0.100	0.002	0.020	–0.10	0.016	0.047	–0.029
Age		1	−0.529**	00.172**	00.186**	00.035	00.077	0.174**	0.203**	0.143*	0.181**	0.047	0.110	0.041	0.105	0.149*	0.121	0.096	0.123	0.14	0.125*	0.149*	0.176**
Exp			1	−0.041	−0.141*	−0.022	−0.157*	−0.124*	−0.179**	−0.206**	−0.179**	−0.006	−0.084	−0.061	−0.125*	−0.114	−0.161*	−0.012	−0.102	−0.19	−0.007	−0.084	−0.149*
Eng				1	0.597**	0.585**	0.410**	0.307**	0.585**	0.432**	0.248**	0.550**	0.467**	0.462**	0.447**	0.469**	0.504**	0.510**	0.412**	0.52**	0.275**	0.419**	0.465**
SrL					1	0.724**	0.400**	0.351**	0.613**	0.578**	0.423**	0.597**	0.547**	0.614**	0.498**	0.586**	0.669**	0.586**	0.543**	0.51***	0.426**	0.502**	0.663**
Man						1	0.404**	0.349**	0.633**	0.445**	0.360**	0.616**	0.505**	0.573**	0.407**	0.555**	0.586**	0.639**	0.507**	0.44***	0.330**	0.420**	0.637**
Col							1	0.347**	0.458**	0.334**	0.344**	0.436**	0.405**	0.380**	0.261**	0.288**	0.483**	0.391**	0.291**	0.39***	0.209**	0.337**	0.386**
Cus								1	0.517**	0.393**	0.347**	0.402**	0.367**	0.374**	0.375**	0.254**	0.426**	0.336**	0.401**	0.38***	0.147*	0.244**	0.411**
Wrk									1	0.633**	0.440**	0.651**	0.601**	0.587**	0.511**	0.493**	0.624**	0.556**	0.516**	0.53***	0.295**	0.445**	0.657**
Res										1	0.497**	0.539**	0.565**	0.506**	0.644**	0.415**	0.589**	0.382**	0.510**	0.53***	0.304**	0.400**	0.557**
Pro											1	0.435**	0.460**	0.413**	0.481**	0.439**	0.553**	0.351**	0.479**	0.39***	0.269**	0.383**	0.476**
COp												1	0.733**	0.646**	0.463**	0.558**	0.618**	0.631**	0.548**	0.53***	0.515**	0.508**	0.668**
L&D													1	0.641**	0.505**	0.559**	0.636**	0.503**	0.475**	0.50***	0.428**	0.527**	0.682**
WLB														1	0.527**	0.508**	0.645**	0.559**	0.568**	0.45***	0.426**	0.464**	0.644**
PWE															1	0.525**	0.607**	0.448**	0.475**	0.48***	0.265**	0.404**	0.515**
Policy																1	0.682**	0.616**	0.452**	0.50	0.401**	0.504**	0.609**
PPr																	1	0.655**	0.624**	0.61	0.421**	0.592**	0.744**
PAp																		1	0.536**	0.44	0.463**	0.512**	0.612**
Div																			1	0.49	0.488**	0.528**	0.577**
CRp																				10.00	0.32**	0.52***	0.49***
Pay																					10.00	0.691**	0.562**
Ben																							0.690**
Rec																							1

Source: Authors’ own findings.

Notes: ***p < 0.000, **p < 0.01, *p < 0.05; SrL, senior leadership; Man, manager; Col, colleague; Cus, customer; Wrk, work; Res, resource; Pro, process; COp, career opportunity; L&D, learning and development; WLB, work/life balance; PWE, physical work environment; PPr, people practices; PAp, performance appraisal; Div, diversity; CRp, company reputation; Ben, benefits; Rec, recognition; Exp, years of experience; Eng, Engagement level; mgt, Level of management.

The regression results are presented in Table 6. Beta coefficients, standard error of beta, standardized beta coefficients and t-values reveals how statistically different the coefficient is from zero. R² value of the seventh step reveals that the seven factors together explained 71 per cent variance of employee engagement (F = 35.05/df = 236/7). The Durbin–Watson test for multicollinearity index for the final model is 1.87 and Table 6 shows collinearity tolerance statistics.

Coming to the seven individual predictors of employee engagement, company reputation was the most significant predictor (B = 0.87). The beta values of physical work environment (B = 0.19), satisfaction with colleagues (B = 22), senior leadership (B = 0.11), satisfaction with work (B = 0.10), and process (B = 0.40) were also found to be significant. This implies that employees of the studied company are more engaged when they have better perception about company reputation. At the same time, when they felt that senior leaders and colleagues are cooperative and caring, they became more engaged in their work. Similarly, their satisfaction with work, processes and physical work environment was also found to be influencing their engagement level.

Table 6.

Stepwise Regression to Predict Employee Engagement

Step–1		Step–2		Step–3			Step–4				Step–5					Step–6						Step–7
IVS	SrL	SrL	Wrk	SrL	Wrk	CRp	SrL	Wrk	CRp	Man	SrL	Wrk	CRp	Man	Pro	SrL	Wrk	CRp	Man	Pro	Col	SrL	Wrk	CRp	Man	Pro	Col	PWE
B	0.32	0.21	0.20	0.18	0.16	0.97	0.12	0.12	0.95	0.08	0.13	0.13	10.05	0.08	−0.30	0.12	0.12	0.98	0.07	−0.33	0.18	0.11	0.11	0.87	0.08	−0.40	0.19	0.22
SEB	0.02	0.03	0.03	0.04	0.04	0.27	0.04	0.04	0.27	0.03	0.04	0.04	0.27	0.03	0.13	0.04	0.04	0.27	0.03	0.13	0.09	0.04	0.04	0.27	0.03	0.13	0.09	0.11
b	0.60***	0.39***	0.35***	0.27***	0.27***	0.21***	0.21**	0.21***	0.20***	0.21***	0.24**	0.24**	0.23**	0.20***	−0.12**	0.24***	0.22***	0.21***	0.19**	−0.14*	0.11*	0.21**	0.19**	0.18**	0.20**	−0.17**	0.12*	0.12*
t	110.66	6.26	5.65	4.28	4.29	3.57	2.94	3.224	3.56	2.87	3.30	3.62	3.93	2.86	−2.33	3.24	3.22	3.65	2.69	−2.58	1.99	2.86	2.80	3.18	2.75	−3.05	2.14	2.07
R ²	0.60	0.66		0.68			0.69				0.70					0.71						0.71
F																									35.06***
DW test																							1.87

Source: Authors’ own findings.

Notes: ***p < 0.000, **p < 0.01, *p < 0.05; SrL, senior leadership; Man, manager; Col, colleague; Wrk, work; Pro, process; PWE, physical work environment; CRp, company reputation.

Discussion and Conclusion

The main aim of the study was to find out the factors influencing employee engagement in a ferro alloys company of India. Results revealed that age, senior leadership, manager, colleagues, customers, work, resources, processes, career opportunities, learning and development, work–life balance, physical work environment, policies, people practices, performance assessment, diversity, company reputation, pay, benefits and recognition etc., were positively associated with employee engagement. In case of age, it was found that the level of engagement increased with age. The reason may be that older people tend to be more involved in their job (Ueda, 2012) and have higher level of affective and continuous commitment (Ogba, 2008). However, the finding needs to be tested further. On the other hand, the younger lot was found to be less engaged. As the concept of engagement refers to cognitive, emotional and physical engagement and the younger people are full of cognitive, emotional and physical energies, logically they should have been more engaged than their older counterparts. Hence, further probe into the matter can help the organization to find ways to channelize such youth energies for better engagement.

The way employees perceive the senior leadership and leadership style (Carter, 2012) matters a lot in individual-level organizational behaviour. Studies reveal that it has multiplier effect. Senior leadership involvement facilitates other drivers of engagement which include career opportunities, learning and development, warm organizational culture etc. (Hewitt, 2011). Similarly, another study by Aon Hewitt (2011) reveals that engaged managers can make an engaged team and it is the manager who has to play the most important role in reviewing the engagement survey results and prepare action plan for the team. Our study also confirms the above finding indicating senior leadership and manager. Thus, our finding such as the perception towards senior leadership and manager influences engagement, has lots of implications.

Two most sensitive aspects of organizational life, that is, employees’ satisfaction with career development and performance appraisal did not influence employee engagement in our study. There are studies pertaining to employee engagement literature which support (Sardar et al., 2011) and contradict (Rothmann & Rothmann, Jr., 2010) our findings. However, several studies and research reports (Hewitt, 2012; Marescaux, Winne & Sels, 2013) have found strong evidence for the impact of good HR practices on employee engagement. Hence, why such motivating factors such career development and performance appraisal fail to elicit employee engagement can be an issue before the researchers of this field.

On the other hand, surprisingly, hygiene factors such as physical work environment and company processes were found to be strongly related to employee engagement. This is suggestive about this factor’s relevance in the minds of people.

Despite criticisms of using statistical tools to understand the drivers of employee engagement (Gerst, 2013), there is increase in popularity of employee engagement surveys. Companies are trying to understand the level of engagement and the significant drivers of employee engagement. However, Gerst’s (2013) pleading about qualitative studies on employee engagement cannot be completely overlooked. According to him, organizations should conduct qualitative studies to understand in detail what drives employee engagement.

Although, utmost caution was taken while designing and implementing this study, certain shortfalls still existed. Since data were collected with similar rating scales and self-report method, it suffered from the limitation of common method bias. Second, this study is limited to one organization only and has less generalizability. Certain factors that could not be fitted into the study are how people derive meaning from their work and, thereby, feel an urge to get engaged in their work and the level of engagement (Penna, 2007). However, the strength of the study lies in covering large number of variables and wholehearted involvement of management and employees in completing the survey. Companies in similar industry can gain some insight from this study while developing strategies for employee engagement. These findings from Indian context add to the existing literature on drivers of employee engagement.

Table A1.

Employee Engagement Scale

	Strongly Disagree	Disagree	Slightly Disagree	Slightly Agree	Agree	Strongly Agree
It would take a lot to get me to leave this company.	1	2	3	4	5	6
I would not hesitate to recommend this company to a friend seeking employment.	1	2	3	4	5	6
This company inspires me to do my best work every day.	1	2	3	4	5	6
I rarely think about leaving this company to work somewhere else.	1	2	3	4	5	6
Given the opportunity, I tell others great things about working here.	1	2	3	4	5	6
This company motivates me to contribute more than is normally required to complete my work.	1	2	3	4	5	6

Source: Developed in consultation with sponsoring organization’s management.

Footnotes

Acknowledgements

The authors are grateful to the anonymous referees of the journal for their extremely useful suggestions to improve the quality of the paper article. Also to the management of the studied company and the personnel involved in the study for their valuable support and input..

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