Examining the effect of emotional intelligence on socio-demographic variable and job stress among retail employees

Abstract

The purpose of the present study is to explore the relationship between emotional intelligence, socio-demographic variable, job stressors and examine the moderating effect of emotional intelligence on the relationship between socio-demographic variable and job stress. The data were analyzed on the sample of 564 retail employees using descriptive statistics, Pearson correlations, and hierarchical multiple regression. The result shows that there is a socio-demographic difference with respect to trait emotional intelligence (EI) and job stress. The proposed model is a good predictor of job stress. Trait EI is more significant influencing factor for job stress than gender, age, marital status, education, annual income and work experience. Specifically, the present study suggests that intervention aimed at reducing job stress if it includes enhancement of employees with high emotional intelligence rather than just decreasing external stressors.

Keywords:

• job stress
• emotional intelligence
• retail
• socio-demographic variables, correlation analysis

Public Interest Statement

Emotions are set to be an important to handle stress in modern workplace. Emotional intelligence is one of the ability to recognize and handle emotions according to different situation. In the present study, the relationship between emotional intelligence, socio-demographic variable, and job stressors has been explored and examined the moderating effect of trait emotional intelligence on the relationship between socio-demographic variable and job stress. It is found in India that there is a socio-demographic difference with respect to emotional intelligence and job stress. Emotional intelligence in Indian workplace becomes more significant factor for handling job stress than gender, age, marital status, education, annual income, and work experience. Training of emotional intelligence to Indian employees can decrease the job stress.

1. Introduction

Over the last three decades, Job stress becomes very crucial factor among the human resource practitioners in India. Job stress is defined as the harmful physical and emotional responses that occur when role (job) requirements do not match with the employees’ capabilities, resources, and needs (National Institute for Occupational Safety & Health (NIOSH), 1999). There are many studies referred to the job stress and their consequences. The negative effects of job stress on health have been extensively reported (Shirom, 2003; Smith, Sulsky, & Uggerslev, 2002), and all the studies indicated that there is an increase in job stress due to escalating, profound and rapid changes in organizations affect the workforce (McGowan, 2001; Shader, Broome, Broome, West, & Nash, 2001). Organizations are facing issues due to changes in the demographic composition of the workforce, which is due to labor and market trends, legislation, and demographic realities (Triandis, Kurowski, & Gelfand, 1993). Because of the changing composition, human resource managers are encountering demographic diversity “much more frequently and at higher levels both inside and outside their organizations” (Triandis et al., 1993, p. 669) than they have in the past.

The theory of Person Environment Fit states that stress becomes apparent from the match or more precisely mismatch between an individual ability and his or her environment (French, Capplan, & Harrison, 1982). This mismatch occurs at different levels such that stress can occur if there is mismatch between the organizational demand and an individual’s ability. The ability of an individual differs from demographic point of view (McDermott, 1995). Mismatch between objective work environment and an individual’s subjective perceptions of the work environment can result into stress. Stress results into psychological strains such as job dissatisfaction, which leads to negative emotions that individual experience in their jobs (Spector, 1997). Studies revealed that there is a demographic difference in coping with stress (Chang et al., 2006). Lazarus and Folkman (1984) defined coping, as the cognitive and behavioral efforts in order to manage, reduce or tolerate the internal or external demands that created by the stressful situations. There are different factors that have influence on the selection and effectiveness of coping strategies. Coping strategies are of two types: externally (problem focused) and internally (emotion focused). Problem-focused coping (externally) is attempting to manage or change the problem which causing the stress, whereas emotion-focused coping (internally) attempts to diminish emotional distress. In other words, problem-focused coping include problem-solving activities and seeking information related to problem, whereas emotion-focused coping include managing own emotion related to stress. Therefore, coping of stress is depending on the individual capabilities and strategies.

Over the last few years, much attention has been paid to emotional intelligence (EI) in the organizational literature (e.g. Petrides, Pita, & Kokkinaki, 2007; Saklofske, Austin, & Minski, 2003; Smith, Ciarrochi, & Heaven, 2008). Petrides et al. (2007) proposed two different conceptualization of EI, i.e. trait EI and ability EI. Ability EI refers to individual ability to perceive, understand, use and regulate emotions in self and others. Whereas, trait EI is conceptualized as a trait which refers to an assemblage of behavioral dispositions and self-perceptions located at the lower levels of personality hierarchies (Petrides et al., 2007). Trait EI is measured through self-report inventories, whereas ability EI is measured through performance-based tests. The current study focuses on the second conceptualization of EI, i.e. trait EI.

EI is another mechanism that could reduce stress (Edward & Warelow, 2005; Limonero, Tomas-Sabato, Fernández-Castro, et al., 2004; Slaski & Cartwright, 2002). EI is a construct related to an individual skill that help individual to understand why some persons are prone to negative consequences of stress. EI is defined as individual ability to perceive, understand and express emotions (Mayer & Salovey, 1997). In accordance with the definition of EI, which refers to: (1) abilities to identify our own and other’s emotions; (2) abilities to regulate and modify our mood in an adequate manner; and (3) abilities to improve our own though (Mayer & Salovey, 1997). In the present study, EI is considered as a trait, which helps to reduce stress of an individual and can be a substitute of emotion based coping technique. Therefore, the purpose of this study is to examine the relationship of individual difference and job stress. In addition, this study investigates how an individual EI trait plays an important role in reducing job stress in India.

The Indian retail sector has matured and went through from major transformation over the last decade with a noticeable shift towards organized retailing. India ranked as the 15th most attractive country for retail investment among 30 flourishing markets (Kearney, 2015). The retail market is expected to reach Rs 47 trillion by 2016–17, as it expands at a compounded annual growth rate of 15% (The Associated Chambers of Commerce & Industry of India (ASSOCHAM) & Yes Bank, 2014). The Indian retail sector is highly fragmented into organized and unorganized retails. Unorganized sector has around 13 million retail outlets that account for around 95–96% of the total Indian retail industry. However, “the organized sector’s growth potential is expected to increase due to favorable demographics, increasing urbanization, nuclearization of families, rising affluence directly to the consumers, growing preference for branded products and higher aspirations are other factors which will drive retail consumption in India,” (Rawat, 2014). According to the study, organized retail, which comprised only 7% of overall retail market in 2011–12 is estimated to grow at a CAGR of 24% and attain 10.2% share of total retail by 2016–17.

According to consultants, rapid growth in organized retail have raised attrition levels steep high to 96% a year (Attrition analysis, 2011), which is very high in comparison with past years. Indian retailers, big and small, are facing high personnel attrition issues across different stores. The McKinsey study claims retail productivity in India is very low compared to international peer measures. The employee productivity in Indian retail was just 6% of the employee productivity in the United States in 2010. India’s employee productivity in food retailing is about 5% compared to Brazil’s 14%; while India’s employee productivity in non-food retailing is about 8% compared to Poland’s 25%.

1.1. Socio-demographic variable and job stress

In an organizational context, occupational stress is also known as job stress and/or work stress. These terms are often used interchangeably in organizations, but its meaning refers to the same thing (AbuAlRub, 2004; Larson, 2004). Occupational health problems and a significant cause of economic loss increasing due to job stress. Job stress may produce both overt psychological and physiologic disabilities. However, it may also cause subtle manifestation of melancholy that can affect personal well-being and productivity (Quick, Murphy, Hurrell, & Orman, 1992). A job stress affected individual have higher probability of job dissatisfaction, increased absenteeism, increased frequency of drinking and smoking, increase in negative psychological symptoms and reduced aspirations and self esteem (Jick & Payne, 1980). Job stress affected customer orientation and had direct and indirect effects on job performance mediated by customer orientation (Knight, Kim, & Crutsinger, 2007). If employees cannot control physiological and psychological stresses, this may negatively affect their work attitudes and behavior (satisfaction, commitment, productivity, quality, and health) in the workplace (Newell, 2002; Seaward, 2005; World Health Organization (WHO), 2005). Previous study shows that stress levels of teachers were found to vary with biographical variables such as gender, age, and experience in teaching, school size and location (Manthei & Gilmore, 1996). Research studies have reported that socio-demographic factors such as age, gender, marital status, academic qualifications and experience may influence the causes of stress among sports personnel (Rintaugu, 2013). Researchers often have reported that there is no effect of demographic factors on job stress. Deaux (1984) concluded in an analysis of psychological research on sex and gender that in most research little variance is accounted from sex. Martocchio and O’Leary (1989) conducted a meta-analysis of 15 studies that had examined gender differences in work stress and they concluded that there are no gender differences in occupational stress. Spielberger and Reheiser (1994) conducted a study and found that there were no significant differences in the overall stress levels for the two genders. Whereas few researchers reported that, there is a significant relationship between gender and job stress. Previous studies found that female experienced more stress as compared to men (Bogg, Cooper ogg, & Cooper, 1994; Davidson & Cooper, 1984; Davidson, Cooper, & Baldini, 1995; Jick & Mitz, 1985). Whereas, some researcher also found that male medical doctors experienced more occupational stress and less job satisfaction than their female counterparts (Swanson, Power, & Simpson, 1998). Rauschenbach, Krumm, Thielgen, and Hertel (2013) conducted meta-analysis showed no general correlation between age and irritation as a short-term indicator of work-related stress. However, according to the EWCS (1995–2005) respondents from all age categories report that work affects their health. The highest stress levels observed among middle-aged workers, and the lowest among older and younger workers. These mixed research findings relative to demographic factors affecting job stress poses issues for researchers and human resource professionals charged with designing and implementing strategies for ameliorating job stress in the workplace. If these conflicting results can be resolved, human resource professionals can improve their chances of successfully targeting employees who most need job stress management program.

Among the different professions, retail has been considered a profession, highly susceptible to stress in India. According to Sanjay Jog (Head HR, Future Group), the attrition rate in retail industry is 30–35%. The reason behind high in retail industry is the physical efforts perform by sales person, fixed emotion has to be depicted, the job is reaction intensive and the business is mainly transactional. In a survey conducted in between 2014 and 15 by Tata Consultancy Services and the Retailers Association of India (Business Standard, 2013), with 34 retailers, it was found that customer service and time management is a major source of stress in this population of retail employees. For example, studies that have investigated the risks involved in customer service show that time pressure, mainly arising from insufficient staffing and demanding supervisors, are one of the main sources of stress or dissatisfaction for sales employees in retail stores (St-Vincent, Denis, Imbeau, & Trudeau, 2006). Serving difficult customers (“nasty”, hostile, restless, demanding) is another source of stress and dissatisfaction for sales people (Broadbridge, Swanson, & Taylor, 2000; Guignon & Cholet, 2003; Mahiou, 2002; Zackos, Runyan, Schulman, Dunn, & Evensen, 1998). Authors also state that supervisor’s attitude is also one of the major sources of the stress. Supervisors demand for the higher customer service with taking less time, which always have pressure on the retail employees. Younger aged employees are afraid to approach their managers with problems. Some younger workers are even afraid of being admonished or will be fired if they do not comply with their managers’ order (Zackos et al., 1998). High psychological demands (Karasek’s model) have shown the strongest relationship to burnout (emotional exhaustion from the Maslach Burnout Inventory) in the retail sector, followed by interpersonal conflicts with co-workers or superiors, and low job control (Tuuli & Karisalmi, 1999). Narayanan, Menon, and Spector (1999) have shown that besides interpersonal conflicts between co-workers, time/effort wasters, and work overload are two other major sources of stress for sales personnel.

The survey conducted by workspace provider Regus in 2012, showed that Indian workers are getting more stress. The survey revealed that work (51%) and personal finances (50%) are the contributing factors for the increased stress levels of the Indian workforce. Bhat, Shet, and Nayanatara (2014) conducted a study and evaluated the stress levels on software professionals (n = 155) from Karnataka State, Southern India, found that young technical professionals of Bangalore and Mangalore did not have much professional stress but they were influenced by other factors which produce overall stress as evidenced by the elevated PSS scores. Whereas Kumari, Joshi, & Pandey, 2015 conducted a study on IT professionals in Delhi region (n = 100), found that 93% of employees from >40 age group felt high level of stress impact on body followed by 84% from 35 to 39 age group, 72% from 30 to 34 age group, and 66% from 20 to 29 age group. Suparna, Sharma, and Khandekar (2005) conducted cross-sectional study among 200 Information Technology (IT) professionals in the National Capital Region (NCR) to study the computer related health problems and role of ergonomic factors. The study revealed that the visual problems were seen in 76% and musculoskeletal in 77.5% while 35% felt stressful symptoms. Another survey conducted by ASSOCHAM revealed that the NCR has the most number of heart patients followed by Mumbai, Ahmedabad, and Bangalore between the ages of 25 and 45. The reasons found from the survey for high heart patients in NCR region is the job stress, smoking, increased consumption of alcohol, and unhealthy diet.

One of the study conducted by D&B, India, among 24 popular locations for organized retail in India, the northern region is popular among these companies as 35.6% of the companies denoted their preference to have their retail stores in the northern region. Present study is conducted in NCR region due to it stress factor and retail economic factor. Firstly, it was found from the past literature and surveys that NCR region of India is more prone to job stress as compared to southern part of India (Kumari et al., 2015; Suparna et al., 2005). Secondly, as the economic factor, NCR has the largest customer base for retail across all seven urban centers, making it an ideal catchment for retail. NCR surpasses Mumbai and Bengaluru in the total modern retail expenditure that stands at INR 269 bn. Modern retail penetration in NCR is set to increase from the current 26–50% by 2028. This region has been riding high on the success of the IT and ITeS-BPO companies operating in the region, especially the NCR that has witnessed a spurt in the development of shopping malls, which appears as the primary reason for the region’s increasing preference among retailers. Another reason to concentration of these companies is attractiveness of these locations for diverse young and mobile professionals as these cities are cosmopolitan cities.

1.2. Socio-demographic variable and trait EI

In recent years, the individual characteristics played significant role in the workplace. The characteristics of particular individuals may add some explanatory power to show how some individuals are able to control job stress. Employees have different stress experience when exposed to the same stressors due to unique personal characteristics. Emotions are one of the unique characteristics, which help to cope up from the stress (Folkman & Lazarus, 1988). Although the importance of research related to emotions in organizations was ignored for a significant period, research related to the impact of emotions on organizational behavior is increasing (Ashkanasy, Härtel, & Zerbe, 2000). Therefore, it is important to evaluate whether and how individual differences in emotion-related individual characteristics moderate the effect of emotions on self-reported job stress. One such emotion trait is EI. EI reflects the ability to adaptively perceive, understand, regulate, and utilize one’s emotions and those of others (Salovey & Mayer, 1990; Salovey, Mayer, & Caruso, 2002). Over the recent years, the use of EI has increased with respect to organizational behavior (Mayer, Salovey, & Caruso, 2000). EI significantly contributed to understanding the different relationship in the organizational settings (Jordan & Troth, 2002; Mayer et al., 2000). Research on EI with regard to certain demographic factors such as age, sex, education, and socioeconomic status has been reported widely. Numerous studies were intended to find out the impact of demographic variables on EI of individuals. Findings from previous studies have corroborated the fact that there is a significant gender differences in EI among professionals. In line with other studies, women scored higher than men in EI (Charbonneau & Nicol, 2002; Ciarrochi, Chan, & Bajgar, 2001; Day & Carroll, 2004; Ergin, İşman, & Özabacı, 1999; Goleman, 2000; Ismen, 2001; Joseph & Newman, 2010; Mayer, Caruso, & Salovey, 1999; Palmer, Gignac, Manocha, & Stough, 2005; Reiff & Hatzes, 2001; Schutte et al., 2001; Van Rooy, Dilchert, Viswesvaran, & Ones, 2006). Some found no significant relation between gender and EI (Abdullah, 2006; Aquino & Alberto, 2003; Cavallo & Brienza, 2002; Hopkins & Bilimoria, 2008; Khalili, 2004; Whitman, Van Rooy, Viswesvaran, & Kraus, 2009).

1.3. Job stress and trait EI

Job stress has been previously studied with respect to job satisfaction, motivation, performance, and job withdrawal behavior (Antón, 2009; Beehr, Walsh, & Taber, 1976; Duraisingam, Pidd, & Roche, 2009). There are various factors which contribute in job stress such as the employee’s role, their physical environment, and social environment stress (Blau, 1981). Role stress in particular occurs when role requirements of the job outweigh the employee’s ability to cope with the demands (Lambert, Hogan, & Tucker, 2009). Further to this, it is often that stress in workplace leads to job dissatisfaction and negative emotions, such as anger, fear, and anxiety (Spector, Fox, & Domagalski, 2006). Negative emotions can be treated as disease in the modern workplace. “People who continually suppress their emotions have been found to be more prone to disease than those who are emotionally expressive” (Mann, 1999), which leads to decrease in job performance (Pervez, 2010). Therefore, emotion regulation, which is one of the dimensions of EI, becomes more important in the workplace, so that employees are able to recognize negative emotions and suppress it. The relationship between trait EI and job stress has come in limelight among researchers in recent years.

1.4. Purpose

There are mixed results found with respect to gender, job stress, and EI. Some previous studies reported that women have more job stress than men (Davidson & Cooper, 1984; Davidson et al., 1995; Jick & Mitz, 1985; Miller et al., 2000; Nelson & Quick, 1985) and some studies found that men have more stress than women. Studies also found that gender does not have significant relationship with EI (Bar-On & Parker, 2000; Slaski & Cartwright, 2002). Even there is a contradiction in the results of Nikolaou & Tsaousis (2002) and Slaski and Cartwright (2002) with respect to relationship between age and EI, it was found that these studies do not reached to similar conclusions related to socio-demographic variables, job stress, and EI, but have reported the significant relationship. In order to make it generalize, more research work is needed which encompasses different countries, sectors and demographic samples. It was found that there were few studies conducted in Western countries which relates EI, demographic variable and job stress, but in Asian region and specifically in India such studies were found to be non-existent. We extend the previous findings (Nikolaou & Tsaousis, 2002) by adding more demographic characteristics and their by attempting to identify EI as moderator in the stress management process on Indian demographic sample. The limitations of previous studies (Nikolaou & Tsaousis, 2002; Rintaugu, 2013; Salguero, Extremera, & Fernández-Berrocal, 2012) have been addressed in the present study.

Although several questionnaires-based studies have investigated the conditions leading to stress in the retail sector, a search of the literature could not yield any field study analyzing the work and relationship of retail employees. To our knowledge, EI has never been examined as a moderating variable on the relationship between demographic variable and job stress of Indian retail employees .The aim of the study is to examine the effect of EI on socio-demographic variable and job stress of retail employees in India, which is shown in conceptual model (Figure 1).

Figure 1. Conceptual model.

The present study verifies the following hypotheses:

Hypothesis 1. Socio-demographic variables (age, gender, marital status, education, annual income, and work experience) do not have significant relationship with Job stress, as well as, trait EI, among Indian retail employees.

H1 (a1): Gender is not related with trait EI.

H1 (a2): Gender does not have any relation with job stress.

H1 (b1): Age is not related with trait EI.

H1 (b2): Age is not related with job stress.

H1 (c1): Education is not related with trait EI.

H1 (c2): Education is not related with job stress.

H1 (d1): Income is not related with trait EI.

H1 (d2): Income is not related with job stress.

H1 (e1): Work experience is not related with trait EI.

H1 (e2): Work experience is not related with job stress.

H1 (f1): Marital status is not related with trait EI.

H1 (f2): Marital status is not related with job stress.

Hypothesis 2 (H2). EI is negatively related to job stress, among Indian retail employees.

Hypothesis 3 (H3). EI significantly moderate the relationship between socio-demographic variable and job stressors.

2. Method

2.1. Participants

A study was administered on 546 retail employees from various retail stores in New Delhi (India). All participants selected for the study had sumptuous experience of working in retail stores having prime responsibility to interact with customers. A total of 52.66% of the employees were male with a mean age of 26 years (SD = .73). About 57.45% of the participants were single and 42.55% were married. About 59.57% of the employees are graduates, whereas 27.66% are 12th pass and 12.77% are postgraduates. Current study was duly approved by the ethical committee of the retail stores and all participants signed the consent form.

2.2. Procedure

Researcher explained the purpose of study to the human resource manager of the retail stores. Only after obtaining the consent (voluntary participation), the questionnaires were distributed to the potential participants having a cover letter, explaining the purpose of the study and assuring them about the anonymity and confidentiality of the data. The data are further used for data analysis using different tools.

2.3. Measures

Job stress was assessed using new job stress scale (Shukla & Srivastava, 2015). The questionnaire for this investigation comprised of 22 items categorized in five different dimensions (time stress, anxiety stress, work–life balance, job expectation conflict, and co-worker support). These items were rated on a five-point likert scale ranging from 1 (Strongly disagree) to 5 (Strongly agree). In this 22 item scale, Cronbach’s alpha coefficient was found to be .81.

To measure EI we used a 16-item multidimensional scale (WLEIS), developed by Wong and Law (2002) and further validated by Law, Wong, and Song (2004) and Shi and Wang (2007). The scale has four dimensions, with four items measuring self-emotions appraisal (SEA), other-emotions appraisal (OEA), use of emotion (UOE), and regulation of emotion (ROE), respectively. All items are positively keyed and rated on a five-point likert scale ranging from 1 (Strongly disagree) to 5 (Strongly agree). A sample item from SEA is “I have a good sense of why I have certain feelings most of the time.” A sample item from OEA is “I always know my friend’s emotions from their behavior.” “I always set goals for myself and then try my best to achieve them” and “I have good control of my own emotions” are items from UOE and ROE, respectively.

2.4. Socio-demographic and professional information

Personal details were obtained about gender, age, education, income, marital status, and work experience.

3. Data analysis

Descriptive analyses were carried out to examine job stress and the predicting variables. Predicting variables included in the model were the socio-demographic variables (gender, age, education, income, and marital status) and EI (self-emotions appraisal, other-emotions appraisal, use of emotion, and regulation of emotion). Pearson product–moment correlation coefficients were computed to examine the relationship of job stress dimensions with the predicting variables. Hierarchical stepwise multiple regressions were conducted to identify the predictors of each job stress dimension (time stress, anxiety stress, work–life balance, job expectation conflict, and co-worker support). In order to determine the effects of the predictors on job stress sub-dimensions, socio-demographic characteristics were entered first, and then job stressors and EI were entered sequentially in the model. The increase in R² (ΔR²) was computed to determine the relative contributions of each set of variables. Standardized coefficients (β) were computed to compare the relative importance of each variable in the model. The data were checked for multicollinearity, using tolerance and the variance inflation factor (VIF). VIF-values greater than 10 and tolerance values smaller than .10 may indicate multicollinearity. There were no signs of multicollinearity in any of the regression models. All analyses were performed with the SPSS-program (Kleinbaum, Kupper, & Muller, 1988; SPSS, 1990a, 1990b).

4. Results

4.1. Descriptive data

Table 1 represents the descriptive statistics along with the reliability coefficient for EI measures and the job stressors. All EI dimensions were reliable in the present sample (N = 564). Similarly, job stress dimensions are also reliable for the same sample.

Table 1. Means, standard deviation, and reliability coefficient of EI and Job stressors

Measure	Mean	SD	α
Emotional intelligence measure
Self emotion appraisal	12.27	2.81	.929
Other emotion appraisal	12.51	2.62	.928
Use of emotion	12.58	2.66	.910
Regulation of emotion	13.16	2.41	.919
Total emotional intelligence	50.53	8.18	.930
Job stressors
Time stress	10.62	3.43	.876
Anxiety stress	13.39	3.25	.856
Role expectation conflict	13.61	4.65	.916
Co-worker support	11.96	1.99	.881
Work-life balance	10.71	3.21	.873
Overall job stress	60.31	10.06	.817

4.2. Emotional intelligence, job stress, and socio-demographic variable

Inter-correlations, means, standard deviations, and reliabilities of all variables were calculated to explore associations among different variables. The correlations confirmed the theoretical model. Table 2 shows the relationship of the socio-demographic variables such as gender, age, education, work experience, income, marital status, and job stress dimensions with EI dimensions. Independent Pearson correlation was conducted to investigate whether gender affects both EI or job stress or both. It was found that there were significant difference between male and female in terms of total EI (TEI = .372, p < .01). These findings contradict the results of previous studies (Bar-On & Parker, 2000; Gunkel, Schlägel, & Engle, 2013; Slaski & Cartwright, 2002). In the present study, it was found that female performed better than males in all trait EI dimensions (SEA = .261, p < .01; OEA = .173, p < .01; UOE = .352, p < .01; ROE = .381, p < .01). Hence, H1 (a1) is rejected. The present findings corroborates with the findings of Mayer and Geher (1996), Mayer et al. (1999), Mandell and Pherwani (2003) and Goldenberg, Matheson, and Mantler (2006). As far as job stress is concerned, excluding time stress, all the job stress dimensions are significantly related with gender. Time stress is not significantly related with gender (TS = −.009, p > .05). It is also found that male experienced more stress than female (OJS = −.645, p < .01). Therefore, H1 (a2) is rejected. Stress has been found more in males as compared to female as evident from the fact that male encompasses more personal as well as professional responsibilities as compared to females. Indian society is dominated by males, who hold most of the responsibilities of family, which results in stress. Even in the current study, it was also found that females are good in EI as compared to males, which can be one of the factors for decreased job stress among females.

Table 2. Means, standard deviations, and correlations among all variables

Measure	1	2	3	4	5	6	7	8	9	10	11
1. Self emotion appraisal	1 (.929)
2. Other emotion appraisal	.550**	1 (.928)
3. Use of emotion	.483**	.485**	1 (.910)
4. Regulation of emotion	.317**	.360**	.631**	1 (.919)
5. Total emotional intelligence	.772**	.774**	.834**	.726**	1 (.930)
6. Time stress	−.402**	−.248**	−.137**	−.369**	−.372**	1 (.876)
7. Anxiety stress	−.451**	−.349**	−.328**	−.273**	−.455**	.258**	1 (.856)
8. Role expectation conflict	−.544**	−.400**	−.512**	−.357**	−.588**	.147**	.146**	1 (.916)
9. Co-worker support	−.034*	−.102*	−.206**	−.236**	−.181**	−.083*	.125**	.503**	1 (.881)
10. Work–life balance	−.509**	−.452**	−.268**	−.170**	−.458**	.167**	.060**	.506*	.103**	1 (.873)
11. Overall job stress	−.705**	−.547**	−.516**	−.481**	−.728**	.530**	.474**	.821**	−.181**	.650**	1 (.847)

Notes: 1–5 represents emotional intelligence and its dimensions; 6–11 represents job stressors and its dimensions; reliability coefficients (Cronbach’s alpha) in parentheses along main diagonal. Analyses based on n = 564.

^* Level of significance at p < .05.

^** Level of significance at p < .01.

As far as, the relationship between age, trait EI dimensions and job stress is concerned, Pearson correlation coefficient were analyzed (Table 3). In terms of trait EI, significant positive relation found between age and self-emotion appraisal (SEA = .471, p < .01), age and other emotion appraisal (OEA = .709, p < .01), age and use of emotions (UOE = .307, p < .01), age and regulation of emotions (ROE = .203, p < .01), and age and total trait EI (TEI = .549, p < .01). The present findings are contradicted the results of Goldenberg et al. (2006), Adeyemo (2007) and Reddy, Haritha, and Neeraja (2012). Therefore, H1 (b1) is rejected. In terms of Job stress, negative correlation has been found between age and time stress (TS = −.304, p < .01), age and anxiety stress (AS = −.249, p < .01), age and role expectation conflict (REC = −.183, p < .01), age and work–life balance (WLB = −.220) and overall job stress, and age (OJS = −.327, p < .01). These results also contradict the results reported by Slaski and Cartwright (2002), and Nikolaou & Tsaousis (2002). Hence, H1 (b2) is rejected. This may be due to as age increases ability of recognizing and regulating emotions according to situation increases, which leads in reduction of job stress.

Table 3. Correlation between emotional intelligence, occupational stress and demographic variable

Measure	Gender (male = 0; female = 1)	Age	Education	Income	Experience	Marital status (single-0; married-1)
Emotional intelligence measure
Self emotion appraisal (SEA)	.261**	.471**	.311**	.422**	.452**	.230**
Other emotion appraisal (OEA)	.173**	.709**	.527**	.609**	.573**	.465**
Use of emotion (UOE)	.352**	.307**	.247**	.316**	.260**	.312**
Regulation of emotion (ROE)	.381**	.203**	−.155**	.254**	.217**	.044
Total emotional intelligence (TEI)	.372**	.549**	.325**	.518**	.488**	.343**
Job stressors
Time stress (TS)	−.009	−.304**	−.031	−.430**	−.382**	−.010
Anxiety stress (AS)	−.162**	−.249**	−.208**	−.396**	−.476**	−.319**
Role expectation conflict (REC)	−.829**	−.183**	−.011	.078	.149**	−.042
Co-worker support (CS)	−.634**	.062	.375**	.260**	.350**	−.059
Work–life balance (WLB)	−.257**	−.220**	−.137**	.031	−.020	.087*
Overall job stress (OJS)	−.645**	−.327**	−.052	−.177**	−.153**	−.110**

Note: N = 564.

^* Level of significance at p < .05.

^** Level of significance at p < .001.

Person correlation coefficient estimated that trait EI significantly positively correlated with education. Significant positive relation found between education and self-emotion appraisal (SEA = .311), education and other emotion appraisal (OEA = .527), education and use of emotions (UOE = .247), education and regulation of emotions (ROE = −.155), and education and total trait EI (TEI = .325). Therefore, H1 (c1) is rejected. In terms of job stress, negative correlation has been found between education and anxiety stress (AS = −.208), education and co-worker support (CS = .375), education and work–life balance (WLB = −.137), and overall job stress is not significant with education (OJS = −.52, p < .01). Hence, H1 (c2) is accepted.

The relationship between income status and all trait EI and job stress variables is concerned, again Person correlation coefficient were conducted (Table 3). In terms of trait EI, significant positive correlation found between income and self-emotion appraisal (SEA = .422, p < .01), income and other emotion appraisal (OEA = .609, p < .01), income and use of emotions (UOE = .316, p < .01), income and regulation of emotions (ROE = .254, p < .01), and income and total EI (TEI = .518, p < .01). In light of the above evidence H1 (d1) is rejected. In terms of Job stress, negative correlation has been found between income and time stress (TS = −.430, p < .01), income and anxiety stress (AS = −.396, p < .01) and overall job stress and income (OJS = −.177, p < .01). Whereas, the relation between income and co-worker support found low but positive correlation (CWS = .260, p < .01) and role expectation conflict and work–life balance is not significantly correlated with income of individual. Therefore, H1 (d2) is rejected. In other words, as income increases trait EI and co-worker support increases and overall job stress decreases. This is found that individuals who are getting handsome salary is more educated and having good experience in the organization, which increases the level f trait EI and results in reduction of job stress.

The results revealed that work experience is having positive relationship with all dimensions of trait EI. Therefore, H1 (e1) is rejected. In terms of trait EI dimensions, significant positive correlation found between work experience and self-emotion appraisal (SEA = .452, p < .01), income and other emotion appraisal (OEA = .573, p < .01), income and use of emotions (UOE = .260, p < .01), income and regulation of emotions (ROE = .217, p < .01), and income and total trait EI (TEI = .488, p < .01). In terms of Job stress, negative correlation has been found between income and time stress (TS = −.382, p < .01), income and anxiety stress (AS = −.476, p < .01and overall job stress and income (OJS = −.153, p < .01). Whereas, the relation between income, role expectation conflict and co-worker support WAS found low but positive (REC = .149, CWS = .350). Hence, H1(e2) is rejected.

In order to investigate whether marital status (Single & married) affect their EI and Job stress. With respect to EI, it was found that marital status affects total EI (TEI = .343, p < .01). More specifically, married employees scored significantly higher on EI than Single employees. Therefore, H1 (f1) is rejected. In terms of job stress, it was found that marital status has significantly relation with overall job stress (OJS = −.110; p < .01). Anxiety stress found significantly related with marital status (AS = −.319, p < .01). Hence, H1 (f2) is rejected. In other words, married employees feel less anxiety stress as compared to bachelor employees. This is due to married employees are found high in EI skills as compared to bachelor employees.

The result of the current study found that EI is negatively related with job stress (JS = −.728, p < .01). Therefore, H2 is accepted. In other words, As EI of the retail employees increases they are able intervene job stress. This result is supported by previous studies (Nikolaou & Tsaousis, 2002; Mikolajczak, Menil, & Luminet, 2007; Oginska-Bulik, 2005; Slaski & Cartwright, 2002).

4.3. The moderation effect of EI on the relationship between socio-demographic variable and job stress

To examine the potential moderating effect of EI on the relationship between socio-demographic variable and job stress, we conducted a series of hierarchical regression analysis in line with recommendations given by Aiken and West (1991). In the regression process, socio-demographic variable was entered in the first step. In the second step, we included scores of trait EI. Finally, a multiplicative term between EI and socio-demographic variables was entered (scores in EI were mean-centered prior to creating the product term). Results showed that the interaction term met the assumptions for a significant moderation. That is, (a) the increment in the squared multiple correlation was significantly greater than zero for interaction, (b) the coefficient b of the interaction term differed from zero. Results are presented in Table 4. As can be seen, a significant effect of the EI and gender interaction was found (β = −.98, p < .001). To illustrate and corroborate this interaction we followed the procedures outlined by Hayes and Matthes (2009). As Figure 2(a) shows, there was a significant negative relation between trait EI and Job stress for male as well as for female employees (r = −.645, p < .01). It was found that at a lower score of EI, female experienced less job stress as compared to male employees. However, as the scores of trait EI increases both male and female reduce their job stress. As results revealed that age is a significant predictor of job stress (β = −.327, R² = .107, p < .001), indicating that age accounted for 10% of the variance of predicting job stress, but trait EI makes a vital significant contribution as a moderator in the interaction of 53.8% of the variance of predicting job stress (β = −.785, R² = .538, p < .001). Results indicated that marital status individually accounted 1.2% of the variance in predicting job stress, but interaction with trait EI makes 55.2% of variance for predicting job stress (β = −.782, R² = .552, p < .001). Further, EI makes a significant contribution in the interaction with education, annual income and work experience, respectively, as shown in Table 4 in predicting job stress. The significance of the trait EI as a moderating effect with each socio-demographic variable is shown in Figure 2(a)–(f), respectively. Hence, H3 is accepted. This study is important for stressing the significance and unique contribution of trait EI in predicting job stress with respect to socio-demographic variable for Indian sample.

Table 4. Stepwise hierarchical regressions analyses predicting change in job stress, with socio-demographic variable, EI, and their interaction as the predictors

Variables	β	p-value	R^2	ΔR^2
Gender	−.645	.000	.417**	.417**
Total EI	−.566	.000	.693**	.276**
Gender* total EI	.098	.000	.702**	.009**
Age	−.327	.000	.107**	.107**
Total EI	−.785	.000	.538**	.431**
Age* total EI	.192	.000	.574**	.037**
Marital status	−.110	.009	.012*	.012*
Total EI	−.782	.000	.552**	.540**
Marital status* total EI	.147	.000	.572**	.019**
Education	−.052	.215	.003	.003
Total EI	−.795	.000	.568**	.565**
Education* total EI	.212	.000	.613**	.044**
Annual income	−.177	.000	.031**	.031**
Total EI	−.870	.000	.585**	.553**
Annual income* total EI	.050	.000	.586	.002
Work experience	−.153	.000	.023**	.023**
Total EI	−.857	.000	.584**	.560**
Work experience* total EI	.147	.000	.601**	.017**

^* Level of significance at p < .05.

^** Level of significance at p < .001.

Figure 2. Effect of emotional intelligence on job stress with reference to socio-demographic variable. Total_JS stands for overall job stress and Total_EI stands for total emotional intelligence. Moderating effect of (a). Gender and emotional intelligence (b). Age and emotional intelligence (c). Marital status and emotional intelligence (d). education and emotional intelligence (e). Annual Income and emotional intelligence (e). Work experience and emotional intelligence on job stress.

5. Discussion

Previous work examined the relation between trait EI, job stress and socio-demographic variable has revealed the existence of significant, but low correlations found between trait EI, job stress and socio-demographic variable (Martins, Ramalho, & Morin, 2010; Schutte, Malouff, Thorsteinsson, Bhullar, & Rooke, 2007). In this study, we aimed to examine the existence of EI differences in the demographic and job stress relationship and effect of trait EI on the relationship of socio-demographic variable with job stress on Indian sample. The most significant finding in this study is the strong relationship among trait EI, job stress and socio-demographic variable. This study is important and contributes significantly in EI literature because it contributes the significance of Indian socio-demographic variable with job stress and trait EI, which gives the opportunity for other research to extent the findings of this study from cross-cultural point of view.

Firstly, findings corroborated gender differences in trait EI. In line with other studies, women scored higher than men in EI (Charbonneau & Nicol, 2002; Ciarrochi et al., 2001; Ergin et al., 1999; Goleman, 2000; Ismen, 2001; Mayer et al., 1999; Reiff & Hatzes, 2001; Sartorius, 1999; Schutte et al., 2001). Some found no significant relationship between gender and EI (Abdullah, 2006; Aquino & Alberto, 2003; Cavallo & Brienza, 2002; Hopkins & Bilimoria, 2008; Khalili, 2004). This result is consistent with the other previous studies. A growing body of research has documented that women are more skilled in emotional domains than men, including reading feelings from facial expressions and non-verbal clues (Hall, 1984; Rotter & Rotter, 1988), UOEs vocabulary (Fivush, Brotman, Buckner, & Goodman, 2000), or emotional memory (Bloise & Johnson, 2007). Even age, education, annual income, and work experience found significant positive relationship with EI. In this study, it has been established that married employee’s EI level is higher than the single status employees. In other words, married employees are more emotional intelligent as compared to single status employees. This may be due to the fact that in Indian social environment, married employees are more experienced of understanding others emotions and are also able to make UOEs according to situations in comparison to single status employees (OEA = .465, p < .01; UOE = .312, p < .01).

Whereas, with respect to relationship between gender and job stress, it is found that there is gender difference in handling job stress. Male employees scored higher job stress as compared to female employees. In other words, female employees are more efficient in handling job stress in retail organization, due to higher level of EI (TEI = .372, p < .01). It gives the opportunity in future to examine the gender (masculine and feminine) difference in EI perspective with respect to Indian culture. More research examining specific biology, heritability and sociocultural variables is needed for a better understanding of gender differences in EI (Palmer et al., 2005; Thory, 2013).

The result also revealed that there is significant negative but moderate relationship between age, annual income and work experience and EI. As the experience, age and income increases, employees are able to overcome from their job stress. Education was not found having any significant relationship with job stress. This may be because employees participated in the study were less educated.

The interaction analysis corroborated the moderator role of EI in the socio-demographic and job stress relationships. Although the correlation between EI and Job stress in the total sample was similar to the correlation reported in previous studies (Darolia & Darolia, 2005; Oginska-Bulik, 2005), there were differences in the strength of these correlations. Figure 2(a)–(f), respectively, shows there was a significant moderating effect of EI on the relationship between all the socio-demographic variable and job stress (Table 4). In this way, our results have significantly contributed to EI research area (e.g. Nikolaou & Tsaousis, 2002; Rintaugu, 2013; Salguero et al., 2012).

6. Implications

The problem has practical significance in that the appropriateness of approaches used to manage employee’s job stress which is dependent on socio-demographic profile or the level of EI. Employees high in EI scored lower in job stress scale. As far as relationship between demographic variable, EI and Job stress are concerned, some contradictions were found in comparison to the findings of previous studies (Bar-On & Parker, 2000; Slaski & Cartwright, 2002). This might be explained by the fact that employees who are more emotional intelligent experience less stress, which will be reflected in their behavior.

An interesting finding of the present study is the moderating effect of the EI in the relationship between demographic variable and job stress. It was found that EI would be more effective competency as compared to individual demographic characteristics. Previous studies found that individual difference will affect the job stress, even it was known that EI also affects in coping job stress. However, this study reveals that EI would be more powerful competency as compared to any biological socio-demographic characteristics. The interaction between demographic characteristics and EI is effective in reducing job stress in organizations.

Considering the findings of this study from a practical perspective, the identification of EI as a moderator in the stress process will have a significant potential as a stress management technique. EI training is well established and widely used in western countries. However, Asian countries such as India are lagging behind from EI perspective. Therefore, this study helps human resource practitioners to use the results of the study and implement the training sessions for better organizational environment. Organizations that offer a combination of EI and stress management training according to the demographic characteristics of their employees provide them opportunity to acquire necessary skills, in order to deal with the customer service in retail organizations. EI questionnaire can be included in the psychometric test used in recruitment and selection seems very effective technique in order to improve the accuracy in selection methods and may decrease the attrition rate. Although there is lack of a well established and widely researched instrument of EI (Dulewicz & Higgs, 2000) in recruiting and selecting employees with high level of EI, especially in top management position where the stress is very high.

7. Limitations and future directions

It is important to note the limitations of present study, and directions for further research. Firstly, this study is limited by its cross-sectional design. Future research should examine the relations of socio-demographic variables, jobs stressors, and trait EI over time in order to address issues of consistent relationship. Secondly, our study relied on the sample of north India. Future studies that include some other population of India. In addition, future research should include other individual differences (cultural diversity, religion, and organizational climate).

In conclusion, this study contributes further to the significance of trait EI in applied settings. Although the study was limited to employees working in retail organization, the similarity of this professional group in terms of stress levels, offers a significant insight in understanding the effectiveness of trait EI. Further the contribution of trait EI in handling job stress provides a major step in further understanding employees’ behavior.

Additional information

Funding

Funding. The authors received no direct funding for this research.

Notes on contributors

Abhishek Shukla

Abhishek Shukla did his postgraduation in Business Management with specialization in Human Resource Management. He also did postgraduation in Psychology. He has also completed his BE. Abhishek Shukla has vast industrial experience of five years in various industries. He has been involved in the training and recruitment.

Publications are included: (i) “New Dimensions of HR Role in global Recession” Journal Drishtikon of Symbiosis Center for Management and Human Development 2009, Vol. 1, p. 37. (ii) “Pattern of OB in Recovery Phase,” in International HR Conference, Organized by IES, 2010, Mumbai.

Rajeev Srivastava

Rajeev Srivastava has completed PhD from the Department of Economics, Lucknow University in 2010. The area of his research has been “Economics of Micro & Small Scale Industrialization.” Rajeev does possess an enriched professional and research experience of 15 years in the institutions of repute.