International Journal of Emergency Mental Health and Human Resilience
Open Access

Distributive justice, Affective commitment, Leader-member exchange, Job characteristics model, Organizational citizenship behaviour, Antecedents, Banking employees.

IMPORTANCE OF THE STUDY: Researchers have found many more predictors of OCB including leader characteristics and the quality of an employee’s relationship with his leader (Podsakoff et. al, 1996, Kaya, 2015; Kwak and Kim, 2015; Lu, 2014; Luo and Liu, 2013), procedural justice (Moorman, 1991; Aquino, 1995, Altuntas & Baykal, 2010; Duffy and Lilly, 2013; Lee and Peccei, 2011), personality (Organ, 1990; Penner et al., 1997, Guay et al. 2013, Arshadi & Danesh, 2013), motivational theories job satisfaction (Bateman and Organ 1983; Hemakumara, 2020; Ingrams, 2020; Magdalena, 2014; Shafazawana, et al., 2016; Soelton, et al., 2020), perceptions of fairness (Folger, 1993; Tepper and Taylor, 2003) and commitment (O’Reilly and Chatman, 1986, Staufenbiel and Konig (2010), Fu, 2013; Magdalena, 2014; Magdalena, 2014; Ruhana, 2020; Shafazawana, et al., 2016). The present study experimented with four predictors namely distributive justice, affective commitment, LMX and JCM of OCB in the Indian banking industry. (Adams JS,1965).

Numerous Western researchers have empirically investigated OCB and its predictors across industries, sectors, and academic disciplines. (Adil M, 2020).In contrast, only a fewer attempts at OCB research with regard to antecedents in India have been noted in manufacturing (e.g. Vijayabanu et al 2014; Dash and Pradhan 2014; Valliappan and Revathi 2015; Kar and Tewari 1999; Subramani et al 2015; Moideenkutty, 2000; Niranjana and Pattanayak, 2005; Singh, 2006; Jain and Sinha, 2006; Biswas and Varma, 2007; Gondlekar and Kamat, 2016) and service sector (e.g., Shaheen et al 2016; Gupta and Singh 2013; Mohanty J. 2013, Moideenkutty et al 2006; Mohanty and Rath 2012, Suresh and Venkatammal 2010; Narayana et al 2013; Bhatnagar and Sandhu, 2005; Pradhan et al 2016; Ajgaonkar et al (2012) and Qureshi 2015) (Ajgaonkar M, 2012).Most studies focused on psychological capital, job satisfaction, organizational justice, personality, HR practices and organizational culture and climate as predictors of OCB (Allen N.J,1990). As far as the Banking sector is concerned very negligible studies have been traced (e.g., Karthiga, V. 2016; Prathiba, Srividya and Balakrishnan 2017; Garg and Samta 2013) (Altuntas S,2010).

THEORETICAL BASE AND HYPOTHESES DEVELOPMENT:

A. DISTRIBUTIVE JUSTICE AND OCB: Wang et al, (2010) described that distributive justice justifies treatment based on ethical and objective criteria among individual workers (Aquino K, 1995).Empirical research supports the relationship between overall fairness and organizational citizenship behaviour (Greenberg, 1993; Niehoff and Moorman, 1993; Williams, Pitre and Zainuba, 2002). Using equity theory, Organ (1990) suggested a theoretical basis for the relationship between distributive justice and organizational citizenship behaviour (Arshadi N, 2013). According to equity theory (Adams, 1965), the perception of the unfair distribution of work rewards relative to work inputs creates tension within an individual, and the individual is motivated to resolve the tension (Baghersalimi S, 2011). Spector and Che (2014) found that distributive justice is positively correlated with organizational citizenship behaviour (Bateman T.S, 1983). Several other pieces of research also found the strength of the relationship between distributive justice and OCB like Samad (2006); Kumar et al (2009); Mortazavi, (2000); Walumbwa, Hartnell and Oke, (2010); Iqbal, Aziz, and Tasawar, (2012); Spector and Che, (2014); Sohn and Shin, (2015) (Bhatnagar J, 2005 ).

HYPOTHESIS-1: Distributive justice would be the positive antecedent of organizational citizenship behaviour (Biswas S, 2007).

B.AFFECTIVE COMMITMENT AND OCB: Previous research in Western settings indicates that affective commitment is the key factor in predicting OCB (Morrison, 1994; Shore & Wayne, 1993; Wiener, 1982) (Bolon D.S, 1997). In a Meta-analysis of attitudinal and dispositional factors of OCB, Organ and Ryan (1995) reported that affective commitment had a significant average correlation with altruism and generalised compliance (Campbell D. T, 1959). This also appears to be true in some non-western settings (Cardona P, 2004). Chen and Francesco (2003) found that affective commitment related significantly to OCB in China while Kuehn and Al-Busaidi (2002) also found a similar correlation in Oman (Chaurasia S, 2015). Other researchers also identified it as an antecedent of organizational citizenship behaviour (Schappe 1998; Wasko & Faraj, 2005; Rahman and Karim, 2022; Subramaniam, 2022) (Chen C.C, 2009).

HYPOTHESIS II: Affective commitment is probably the predictor of organizational citizenship behaviour (Chen Z.X, 2003).

C. LMX AND OCB: Leader-Member Exchange (LMX) is a unique leadership approach byfocuses on the special relationship that leaders create with each of their subordinates (Septiadi et al. 2017; Shanty et al. 2019; Setyawan 2018; Suherman, 2018; Suryana et al. 2019; Triyanthi Subudi ,2018). Liden and Graen (1980) proved that members in high-quality LMX relationships will receive more support, job discretionary and trust from the leader, and will exhibit higher OCB (Chiu S.F, 2005). Similarly, Hui, Law and Hackett (2004) also suggested that the LMX is significantly positively related to OCB. LMX is a better predictor of OCB (Settoon, Bennett, & Liden, 1996, Podsakoff et al., 2000; Hackett et al., 2003; Lo et al., 2006; Chaurasia & Sukhla, 2015). Deluga (1994) found a positive relationship between employee OCB and the quality of LMX (Churchill G, 1979). Seminal research shows that subordinates reporting high- quality LMX not only assume greater job responsibilities but also express contributing to other units (Liden & Graen, 1980) (Coakes S. J, 2005).

HYPOTHESIS III: Leader-member exchange would be a positive predictor of organizational citizenship behaviour (Cohen J, 1983).

D. JCM AND OCB: Literature evident relatively few studies on the relationship between job characteristics and OCB (Chiu and Chen, 2005) (Dash S, 2014). Specifically, this relationship has been examined in the substitutes for leadership literature (Podsakoff, MacKenzie, and Bommer, 1996; Podsakoff, Niehoff, MacKenzie, and Williams, 1993; Farh, Podsakoff, and Organ, 1990). Several other studies indicated that job characteristics significantly contributed to the prediction of OCB (Cardona, Lawrence, and Bentler 2004; Podsakoff and colleagues 1996; Organ and colleagues 2006; Podsakoff, Niehoff, MacKenzie, and Williams, 1993; Chen and Chiu 2009; Todd and Kent 2006; Singh et al 2021; Adil et al 2020) (Deluga R.J, 1994).

HYPOTHESIS IV: Job characteristics have a significant positive influence on organizational citizenship behaviour (Duffy J. A, 2013)

RESEARCH PURPOSE:

➢ To validate the dimensions of Organizational Citizenship Behaviours;

➢ To measure the strength of association between select antecedents and dimensions of organizational citizenship behaviours; and

➢ To investigate the antecedents of organizational citizenship behaviours among Indian banking employees ( D Van Dyne L, 1994).

RESEARCH QUESTIONS:

➢ Whether the combination of eastern and western measures of OCB validate in the Indian cultural context?

➢ What are the prominent factors (antecedents) that affect organizational citizenship behaviour?

➢ Whether dimensions of OCB associated positively with select antecedents?

PARTICIPANTS AND PROCEDURES: The population was a managerial annon- managerial employee in the public and private sector banks situated in Varanasi district, India) (Farh J, 1997). The researcher contacted individually in 94 branches of 10 public sector banks and 17 branches of 10 private banks provided them with a description of the research project and delivered the set of printed questionnaires to the branch manager or to employees (Farh J, 1990). A total of 350 employees (respondents) located in Varanasi bank branches were randomly selected for participation in the study (Folger R, 1993). The “drop-off” and “pick-up” methods were employed and arrangements were made for the questionnaires to be collected from banks 1 week from the date of “drop-off” (Fu, C, 1983).

RELIABILITY AND VALIDITY OF THE INSTRUMENT/DIMENSIONS: Specific scales for measuring Distributive justice (Niehoff and Moorman, 1993); Affective commitment (Allen and Meyer, 1990); Leader-Member exchange (Liden and Maslyn, 1998) and Job Characteristics Model (Hackman and Oldham, 1975, 1976, and 1980) have been used (Fu Y K, 2013). The study has used select measures of Podsakoff, Mackenzie, Moorman and Fetter (1990) based on Organ (1988); Farh, Earley and Lin (1997) for assessing organizational citizenship behaviour (Garg A,2013).

VALIDATING THE INSTRUMENTS OF PREDICTOR VARIABLES: Cronbach’s Alpha value was calculated and its acceptance (Gondlekar S, 2016). Limit has been determined as per the reliability condition suggested by prior studies (e.g., Hair et al., 1998; Creswell, 2003; Nunnally, 1978; Hair et al., 2010; Griffee, 2012; and Reid 1990). On the other hand, this study followed Hair et al. (2006); Fornell and Larcker (1981) and Campbell and Fiske (1959) to check the construct validity of the scale by conducting the convergent and discriminant validity.(Table 1) (Graham J W, 1989).

Table 1. Reliability Statistics

According to Cronbach (1961), a Likert scale model should be accessed via Cronbach’s alpha to determine the reliability of the survey. (Greenberg J, 1993).The present study is composed of 54 statements with a Likert scale ranging from (1) to seven (7) following “strongly agree to strongly disagree” respectively aiming to determine whether select antecedents (distributive justice, affective commitment, leader-member exchange relationship and job characteristics model) have any impact on OCB (Griffee D, 2012). From affective commitment two items and from the job characteristics model one item has been deleted from the scale (Guay R P, 2013). Cronbach’s alpha values ranged from 0.746 to 0.933, thereby surpassing the minimum threshold of 0.7 recommended (Creswell, 2003). The results show that the researcher’s scales are highly reliable. (Table 2) (Gupta V, 2013).

Table 2. Inter-correlation of Major Predictors

The study used four factors as predictors of organizational citizenship behaviour which is subject to validity analysis (Hackett R D, 2003). Discriminant validity assesses the extent to which the construct does not correlate with other measures that are different from it (Hair, Babin, Money and Samouel, 2003: 174) (Hackman J R, 1975). In other words, it is a type of validity representing a measure’s uniqueness or uniqueness (Salkind, 2012: 127) (Hackman J R, 1976). Correlation analysis was done on the four factors and the result is presented (Hackman J R, 1980). All the factors are not perfectly correlated where their correlation coefficients range between 0 or 1. Hence, it can be concluded that discriminant validity has been established.(Table 3) (Hair J F Jr,1998).

Table 3. Convergent Validity of Select Predictors

Convergent validity was carried out through a ‘within factor’ factor analysis in order to obtain a more in-depth judgment of the dimensionality of the construct under study (Hair J, 2003). In this study, convergent validity was weighted by its average variance extracted through exploratory factor analysis (Hema kumara M G,2020).Five select factors displayed uni- dimensionality with distributive justice; KMO was 0.88 explaining 75.89 per cent of the variation (Hui C, 2004). Affective commitment shows KMO of 0. 71 explaining 79 percent of the variation, whereas leader-member exchange relationship KMO projects 0.74 explaining 57.7 percent of the variation (Ingrams A, 2020). The KMO measure of sampling adequacy is 0.74 for job characteristics, explaining 57.76 percent variations. Thus, the analysis provided evidence of convergent validity (Iqbal H K, 2012).

VALIDATING OCB SCALES IN INDIAN CULTURAL CONTEXT: The objective laid down at the beginning of the study is to develop a concise measure of organizational citizenship behaviour for the banking industry based on Eastern and Western scales (Jain A K, 2006). Research studies have revealed several scales to measure Organizational citizenship behaviour, though they vary in a number of dimensions (Kar D P, 1999). The OCB scale was developed by Smith, Organ, and Near (1983), Organ and Bateman (1983); Organ (1988); Graham (1989); Moorman and Blakely (1995); George and Jones (1997); Podsakoff and MacKenzie (1994); Van dyne, Graham and Dienesch (1994); Buenetello et al, (2007), Yaghoubi, et al, (2011); Baghersalimi et al, (2011); and Lambert and Hogan (2013). The study adopts the eastern scale of OCB given by Farh et al (1997) and the Western scale includes 24 item OCB scale developed by Podsakoff et al (1990) using recommendations postulated by Schwab (1980) and Churchill (1979). (Karthiga V, 2016).

FACTOR ANALYSIS IN OCB: The study identified thirty useful items out of thirty-one which were composed of six-factor solutions through Exploratory Factor Analysis (EFA), explaining 62.59% of the total variance (Kaya A,2015). Six items loaded in the first factor (named harmony and resources) project an Eigenvalue of 6.131 and the total variance explained is 15.437% (Kemery E R, 1996). Variables under the second factor are comprised of six items whose Eigenvalue is 4.747 and total variance explained is 12.866%, (named as conscientiousness) (Kuehn K N,2002). Six items are loaded on factor-3 (named civic virtue) with an Eigenvalue of 3.457 and the total variance explained rate is 11.652% (Kumar K, 2009). Factor-4 retained the original (05) items of courtesy having Eigenvalues of 1.880 and the total variance explained is 10.681%. Factor-5 (named altruism) loaded four items with Eigenvalues of 1.292 which explained 7.246% of the variance (Kwak W,2015).Factor-6 composed of three items (named sportsmanship), explained 4.795% of the variance with Eigenvalues of 1.262. (L Cummings, 2014). Out of the six factors extracted, four factors project internal consistency of more than 0.7, but the last two factors (5 and 6) show Cronbach’s alpha less than 0.7 and retained as their average variance explained is more than 0.5. (Lambert E G, 2013).

CONSTRUCT VALIDITY: Convergent validity was carried out through a ‘within factor’ factor analysis in order to obtain a more in-depth judgment of the dimensionality of the construct under study. (Table 4). (Lee J, 2011).

Table 4. Convergent Validity of OCB Scale

All the six factors displayed one-dimensionality with Harmony & Resources (Factor-1), KMO was 0.90 explaining 75.89 per cent of the variation (Liden R C, 1998). Conscientiousness (Factor-2), KMO was 0.83 explaining 56.91 per cent of the variation (Liden R C, 1980). Civic Virtue (Factor-3), KMO was 0.84 explaining 51.43 per cent of the variation. Courtesy (factor-4), KMO was 0.83 explaining 57.18 per cent of the variation (Lo M.C, 2006). Altruism (Factor-5), KMO was 0.72 explaining 53.71 per cent of the variation(Lu X,2014). finally Sportsmanship (Factor-6), KMO was 0.51 with average variance explained is 47.61 percent (Luo H,2013). Thus, the analysis provided evidence of convergent validity. (Table 5). (Magdalena S.M,2014).

Table 5. Correlation among the Constructs of OCB

DISCRIMINANT VALIDITY: It is the precondition for discriminant validity that constructs must be distinctive which means the coefficient of correlation is neither an absolute value (Meyer J P, 1993). It can be seen all the factors are not perfectly correlated where their correlation coefficients range between 0 or 1 thus discriminant validity has been established (Mohanty J, 2012).

CORRELATION ANALYSIS (PREDICTOR VARIABLES VS.OCB): The bivariate correlation analysis was conducted on distributive justice, affective commitment, leader-member exchange relationship and job characteristics model as well as on the OCB dimensions of harmony and resources, conscientiousness, civic virtue, courtesy, altruism and sportsmanship and role- prescribed customer service behaviour (Mohanty J,2013). The values of Pearson’s r range from .50 to –.031. This suggests that most variables have a low to medium correlation (Moideenkutty U, 2000). According to Cohen and Holliday (1982) in Bryman and Cramer, 1997), a correlation coefficient between .40 to .69 is modest and those below 19 are considered very low (Moideenkutty U, 2006). Based on that guideline, most correlations in this study should be considered modest (Moorman R.H, 1995).

Results of correlation analysis found a negative relationship between distributive justice and harmony and resources (r=- .157, p<.01)(Moorman R H, 1991).. But rest of the cases positive correlation has been observed. Affective commitment positively correlated with harmony and resources, courtesy, and altruism (r= .44, r=.14, r=.17 respectively; p < .01), whereas in the case of sportsmanship, it is negatively correlated (r=-.17, p<.01) (Morrison E W, 1994). Positive correlation was also obtained between leader-member exchange and conscientiousness (r= .198) and sportsmanship (r=.155); all significant at p<.01, whereas harmony and resources (r=-.13), civic virtue (r=-.15), and altruism (r=- .16) are negatively correlated and to be significant at 1% level (Mortazavi Sh, 2000). Results of correlation analysis also show that the job characteristics model is positively correlated with conscientiousness behaviour (r=.11, p<.05), civic virtue (r=.29, p<.01), courtesy (r=.24, p<.01), altruism (r=.17, p<.01) and sportsmanship (r=.24, p<.01). (Table 6). (Narayana S, 2013).

Table 6. Correlation Matrix (Predictor Variables and Organizational Citizenship Behaviour)

IMPACT ANALYSIS: Hierarchical regression analysis (Cohen and Cohen, 1983) was used to evaluate the relationships among the four predictor variables i.e., distributive justice, affective commitment, leader-member exchange, and job characteristics model and the seven categories of citizenship behaviour namely harmony and resources, conscientiousness, civic virtue, courtesy, altruism, and sportsmanshi.(Niehoff B P, 1993). Prior to conducting a hierarchical multiple regression, the relevant assumptions of this statistical analysis were tested (Niranjana P, 2005). An examination of correlations revealed that no independent variables were highly correlated collinearity statistics (i.e., Tolerance and VIF) were all within acceptable limits (Nunnally J, 1978) .The assumption of multicollinearity was deemed to have been met (Coakes, 2005; Hair et al., 1998). (O Reilly C.A, 1986).

Three basic principles underlie the hierarchical order of predictor variable entry (Cohen and Cohen, 1983; Petrocelli, 2003) are presumed causal priority/direction of causal flow, the hierarchical relevance of each predictor to the criterion, and interactions among predictor variables (Organ D W,1990). Based on the literature review and proposed theoretical relationships as stated in the hypotheses, predictors were entered into the analysis in the following order: distributive justice, affective commitment leader- member exchange and job characteristic model (Organ, D W, 1989).The procedure used for analysis was the same for each of the seven dependent variables. The ΔR2 and its corresponding change in F (ΔF) and r values are the statistics of greatest interest in these hierarchical regression results (Organ D W, 1995). If the addition of an independent variable caused a statistically significant increase in the R2, in addition of that variable to the model was found to have significantly improved (Organ D W,1988). The model’s ability to predict the dependent variable.As suggested by Thompson and Borello (1985), β coefficients reported for predictor variables are those computed for the step in which the variable was first entered (Organ D.W, 2005).

EFFECTS OF SELECT ANTECEDENTS ON HARMONY AND RESOURCES (OCB): It was proposed that four select independent variables are the positive antecedents of harmony and resources (Organ D.W,1988). Prior to the hierarchical regression analyses, the independent variables were examined for collinearity (Luo H,2013) . Results of the variance inflation factor (all less than 2.0) suggest that the estimated β’s are well established in the following regression models (Penner L.A,1997). The results of step one indicated that the variance accounted for (R2) with the first predictor (distributive justice) equalled .025 (adjusted R2=.022), which was significantly different from zero F (1,348) =8.76, p<.01) (Petrocelli J.V, 2003). Next, affective commitment scores were entered into the regression equation (Podsakioff P.M, 1996). The change in variance accounted for (ΔR2) was equal to .177, which was statistically significant increase in variance accounted for over the step one model ΔF (1, 347)=77.16, p<.001) (Podsakoff P. M, 1994). In steps three and four, the leader- member exchange (LMX) and job characteristics model were entered into the regression equation.The change in variance accounted for (ΔR2) was equal to .001 in both cases which was a statistically insignificant increase in variance accounted above the variability contributed by the previous predictor variables entered in step two (Podsakoff P M,1996a).Hence, the findings partially supported the Hypothesis. (Table 7). (Podsakoff P. M, 1996b).

Table 7. Hierarchical Regression Analysis Predicting Harmony and Resources

EFFECTS OF SELECT PREDICTORS ON CONSCIENTIOUSNESS: The results of the hypothesis which tested the predicting conscientiousness from distributive justice, affective commitment, leader-member exchange and job characteristic model are reported in. (Podsakoff P. M, 1990). In block 1, distributive justice accounted for 13.2% of the variance in Conscientiousness, F (1, 348) =52.774, p<.001 contributing significantly (Podsakoff P.M, 2000).However, the inclusion of affective commitment in block 2, resulted insignificant change in variance (Podsakoff P.M, 1993). In the 3rd block, the inclusion of LMX resulted in 13.9% variation (change of 0.7%) and insignificant variance has been observed (Pradhan R. K, 2016). Finally, the inclusion of JCM in the regression on conscientiousness yielded no significant variance. Overall, the findings partially supported the Hypothesis. (Table 8). (Prathiba S, 2017).

Table 8. Hierarchical Regression Analysis Predicting Conscientiousness

EFFECTS OF SELECT ANTECEDENTS ON CIVIC VIRTUE: Hypothesis proposed that four predictor variables have influences on civic virtue and the results of the regression analysis have been presented in (Qureshi H, 2015). The hierarchical regression revealed that at stage one, distributive justice contributed significantly to the regression model, F (1, 348):12.86, p<.001, and accounted for 3.6% of the variation in civic virtue (Rahman M H A, 2022). Introducing affective commitment, no additional variation in civic virtue has been explored (Reid J, 1990). Adding LMX to the regression model explained an additional 1% of the variation in civic virtue and this change in R2 was found to be insignificant (Ruhana I, 2020). Finally, the addition of JCM to the regression model explained an additional 6.6% of the variation in civic virtue and this change in R2 was found significant F (1, 345) = 25.82, p<.001. Together the four independent variables accounted for 11.2% of the variance in civic virtue. Overall, the findings partially supported the Hypothesis. (Table 9) (Salkind N,2012).

Table 9. Hierarchical Regression Analysis Predicting Civic Virtue

PREDICTING COURTESY (OCB) FROM SELECT ANTECEDENTS: This part test hypothesis which predicts courtesy behaviour by four independent variables was evaluated in separate hierarchical regression analyses (Schappe P,1998). Initially, distributive justice was introduced in regression analyses which accounted for negligible variation in the courtesy behaviour of baking employees (Schwab D. P, 1980).But the inclusion of affective commitment resulted in a 2.8% variation in courtesy behaviour (F2, 347= 4.922, p<.01) (Septiadi S A, 2017). The inclusion of a third variable (LMX) creates a 3.8% variation in courtesy (adding 1% variance) and found insignificant change (Settoon R P, 1996). Finally, the addition of JCM to the regression model explained an additional 5.1% of the variation in courtesy and this change of R² was found significant (F 1, 345: 19.31, p<.001) (Setyawan S, 2018). Altogether, the four independent variables accounted for 8.9% of the variance in the courtesy behaviour of bank employees. Overall, the findings partially supported the Hypothesis. (Table 10). (Shafazawana M T, 2016).

Table 10. Hierarchical Regression Analysis Predicting Courtesy

PREDICTING ALTRUISM (OCB) FROM SELECT INDEPENDENT VARIABLES: Hypothesis proposed that Distributive justice, Affective commitment, Leader- member exchange and Job characteristics model would be positive antecedents of altruism (organizational citizenship behaviour) (Shaheen M, 2016). The hierarchical multiple regression revealed that at block one, distributive justice not contributed significantly to the regression model and accounted for 0.1% of the variation in employees’ altruism behaviour (Shanty, D, 2019).Introducing affective commitment variables explained an additional 2.7% of the variation in altruism and this change in R2 was significant (F1,347=9.639, p<.01) (Shore L. M, 1993).Adding LMX to the regression model explained an additional 1.4% of the variation in altruism and this change of R2 was significant (F1,346=5.181, p<.05) (Singh V, 2006).Finally, the addition of variables of job characteristics to the regression model explained an additional 3.1% of the variation in altruism behaviour and this change in R² was also significant (F 1,345= 11.70, p<.01) (Smith C. A, 1983). Together the four independent variables accounted for 7.4% of the variance in altruism (Soelton M, 2020). Overall, the findings partially supported the Hypothesis. (Table 11) (Sohn Y. W, 2015).

Table 11. Hierarchical Regression Analysis Predicting Altruism.

PREDICTING SPORTSMANSHIP BEHAVIOUR (OCB) FROM SELECT INDEPENDENT VARIABLES: The study hypothesised that four select independent variables would be a positive predictor of sportsmanship (Spector P E, 2014). Accordingly, hierarchical regression analysis was conducted and their results are shown in (Staufenbiel T, 2010). In block one, composite variables of distributive justice accounted for 6.1% of the variance in sportsmanship and contributed significantly (F 1, 348=22.599, p<.001) (Subramani A K, 2015).But the inclusion of affective commitment resulted in a 7.6% variation in OCB (Suherman U. D,2018). (adding 1.5%) and was found to be significant (F 1, 347=6.65, p<.05) (Suresh S, 2010). The inclusion of a third antecedent (i.e., LMX) yielded 7.8% variation (change of .2%) on sportsmanship yielded no significant variation (Suryana A, 2019). But the introduction of the fourth variable (Tepper B J, 2003). (JCM) resulted in a significant variance of 11.6% (F1, 345=14.858, p<.001) ( Thompson B, 1985). Overall, the findings partially supported the Hypothesis. (Table 12). (Todd S. Y, 2006).

Table 12. Hierarchical Regression Analysis Predicting Sportsmanship.

ANTICIPATING ORGANIZATIONAL CITIZENSHIP BEHAVIOUR FROM SELECT INDEPENDENT VARIABLES: Hypothesis proposed that Distributive justice (Triyanthi M,2018). Affective commitment, Leader-member exchange and Job characteristic model are positive predictors of organizational citizenship behaviour (Valliappan,2015). In the first model, distributive justice significantly predicted organizational citizenship behaviours (Vijayabanu C K, 2014). (F 1,348=12.78, p<.001) (Walumbwa F O,2010). The addition of affective commitment to the equation in the second step enhanced the model’s ability to predict OCB (ΔF1,347=17.59, p<.001), and an increase in explained variation (ΔR2=.047) (Wang X,2010). The addition of LMX, a minor improvement in the model, but the change in variation was found insignificant (Wasko M, 2005).When JCM was added to the equation in the fourth step, the model was found significant with an F4,349=14.28, p<.001, and R²(.14) revealed that the combination of four variables was accounted for 14% of the variation in OCB. Besides, the R2 change (.06) showed that JCM significantly contributed to the prediction of OCB and the standard coefficient β=.25, p<0.001 showed that jobs with high core job characteristics resulted in engagement in OCB. (Table 13) (Wiener Y, 1982).

Table 13. Hierarchical Regression Analysis Predicting Organizational  Citizenship Behaviour

CONCLUSIVE REMARKS:

DIMENSIONALITY AND VALIDITY: The study has used Western measures of Podsakoff, Mackenzie, Moorman and Fetter (1990) based on Organ (1988) and eastern counterparts of Farh, Earley and Lin (1997) for assessing the dimensionality of organizational citizenship behaviour. Through appropriate diagnostic statistics (Reliability, construct validity and common method variance) the scholar identified six factors with 31-item scales in the Indian context. Therefore, the scale developed in the study was found to be perfect for Indian banking organizations and it is suggested that bankers/policy-makers can use this scale for any further studies regarding the development of OCB (Williams S, 2002).

RELATIONSHIP: Based on scales for measuring Distributive justice (Niehoff and Moorman, 1993); Affective commitment (Allen and Meyer, 1990); Leader-Member Exchange (Liden and Maslyn, 1998) and Job Characteristics Model (Hackman and Oldham, 1975, 1976, and 1980), a significant positive correlation with specific dimensions of OCB have been found using the Pearson coefficient of correlation.

PREDICTORS: For tracing the predictors of organizational citizenship behaviour, seven (07) hypotheses have been tested. The research found that all of the predictors do not create significant variation in OCB dimensions and hence hypotheses were partially supported. Prior researchers also found that all of the dimensions were not influenced by specific predictors. Out of four predictors, affective commitment was found to be a strong predictor of organizational citizenship behaviour. Conscientiousness behaviour of bank employees uncovered a least affected variable by predictors except for distributive justice.

IMPLICATIONS FOR HRD PURPOSE: Bank authorities must emphasize this approach when distributing resources so that the issue of unequal or unfair distribution of resources can be eliminated. Fostering effective commitment across organizational levels could help to develop and unleash the entrepreneurial potentials of employees thereby enabling them to contribute maximally to the long-term growth, development, and sustainability of organizations. Management should invest time, effort, and commitment to elevate their employees’ OCB level through fostering quality dyadic relationships since OCB has been identified as a low-cost vehicle for promoting and developing HR and overall organizational effectiveness.

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