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Abstract

Organizational performance has made it imperative for rural and community bank management to employ the best organizational conditions that influence employee’s performance. Recent banking clean-up in Ghana has also emphasized the need for employees’ performance. This has become necessary to espouse management practices, employee behaviors, and attitudes that predict job performance. Drawing on social exchange theory and reciprocity norm, the study examines the effect of organizational climate on job performance. Valid responses received through a structured questionnaire were 431. Hierarchical multiple regression was employed to validate the hypotheses from the literature review. Relying on empirical data from Ghana, the findings revealed that, first, harmonious work passion partially mediated organizational climate and job performance relationship. Second, leader–member exchange negatively moderated the relationship between organizational climate and harmonious work passion. Finally, however, coaching as a management practice positively strengthened organizational climate and job performance relationship. The theoretical and practical contribution is also discussed.

Keywords

organizational climate job performance harmonious work passion coaching leader–member exchange

Introduction

The formation of rural and community banks (RCBs) was mainly to alleviate poverty among the farming and fishing communities. Given this, RCBs engaged in banking services activities such as funds mobilization and provision of credit facilities to farmers, rural manufacturing operatives, fishermen, and regular salaried workers (Mensah et al., 2017). To improve upon these services, behaviors shown by employees concerning their organizations as well as the workplace environment of the organization are significant concerns in the extant literature of organizational behavior. Individual characteristics, as well as the environment, are determined by superiors’ and employees’ attitudes in organizations in which they work. Given this, to understand employees’ work-related behavior, organizational climate (OC) has become an imperative factor that has gained numerous deliberations and attention in organizational behavior literature since the 1960s. However, OC exercises a huge effect on employee’s attitudes taking their relationships, a sense of belonging, and job performance (JP) into consideration (Berberoglu, 2018). Reichers and Schneider (1990) defined OC as “the shared perceptions of organizational policies, practices, and procedures.” Moreover, Hadiyatno (2018) presented climate as the perceptions of the objective work condition, comprising the features of the organization and the nature of relationships among employees while executing jobs. Besides, Stringer (2002) found that the characteristics of OC affect the reward and performance of organizational members, hence, related to JP. Scholarly assess that high JP becomes possible through the inquiry of workloads, work time, and cost-effectiveness (Saleem et al., 2019).

Consequently, it is unclear how OC influences JP through harmonious work passion (HWP), but scholarly opinions indicate that HWP promotes JP (Trépanier et al., 2014). Furthermore, drawing on the dualistic model of passion that provides passion as either harmonious or obsessive (Vallerand et al., 2003), this research aims at adapting HWP as a mediating mechanism as it is more consistently related to positive outcomes as compared with obsessive passion (Vallerand et al., 2014). Vallerand et al. (2003) described HWP as “results from an autonomous internalization of a favorite activity into one’s identity; individuals willingly engage in the activity and sustain it in harmony with other aspects of their lives.” Moreover, managers with HWP practically excel at work (Fisher et al., 2018). Besides, HWP is used consistently in predicting higher performance (Curran et al., 2015). Subsequently, researchers have established that HWP has a significant positive correlation with JP (Tang & Xiao, 2019).

Although not new, coaching has recently materialized as an important role in employee growth and performance enhancement (Gray, 2006). Empirically, studies show that coaching is a developmental tool to enhance the learning of employees and boost the efficiency of employees (Agarwal et al., 2009; Ellinger et al., 2011, 2003). Coaching within an organization sometimes aims to meet developmental goals, learning, and performance. However, it has been suggested by Hsu et al. (2019) that managerial coaching influences JP. Thus, coaching is used as a moderator here to express the restricting circumstances and the useful possibility of OC influencing JP.

Furthermore, the relationship that occurs between a leader and a follower is specifically enshrined in the theory of leader–member exchange (LMX). LMX argued that managers build diverse quality relationships within an organization with their subordinates and predict JP (Lee et al., 2019). Hence, LMX is used as a moderator in expanding the OC-HWP relationship. Social exchange theory (SET) and the reciprocity norm of repayment are used to espouse the relationships in this study as it is the most common exchange rule between parties in an organization (Blau, 1964; Gouldner, 1960). Numerous researches conducted on OC and JP overlooked the possibility of considering the moderating impact of leadership and management practices, such as LMX and coaching, a gap which is sought to be addressed in this study. In our quest to contribute to academic knowledge and to fill this gap, this study seeks to examine the (a) effect that OC will exert on JP, (b) mediating effect of HWP on the OC and JP relationship, (c) moderating role of LMX on OC and HWP relationship, and (d) the mitigating effect of coaching on the relationship between OC and JP.

Literature and Hypotheses Development

OC and JP

OC has been of key interest to scholars and experts in the years past (Shen & Zhang, 2019). OC is assumed to be very pivotal in an organization’s existence due to its unblemished influence on supervisory activities. According to Jung and Ali (2017), OC is considered as an important feature of a gratified workplace. Nonetheless, it is emphasized that the impact of OC on employee behavior is stronger concerning interpersonal relationships and JP (Berberoglu, 2018). In a business organization perspective, Zhu et al. (2016) describe JP as the discrete activities an individual performs during a standard unit of time that contributes to the core activities of an organization. Research has it that the two-dimensional notion of the task and contextual performance (CP) has gained broader acceptance from researchers. Task performance (TP) refers to the behaviors prescribed concerning job proficiency, whereas CP refers to a set of voluntary, interpersonal, organizational, or group-oriented behaviors that build good psychological and social environments in organizations (Borman & Motowidlo, 1993; Wang et al., 2003). Similarly, JP is highly predictive by staff attitude, behavior, motivation, abilities as well as their commitment level which are impacted by OC (Semu & Tadesse, 2019). OC influences staff performance and contentment, hence leading to the success and continually enhanced capabilities of the organization (Shanker et al., 2017). Thus, if a leader builds a great work climate, it will upsurge JP. Moreover, enormous studies have established that OC has a close association with performance (Supriyati et al., 2019). Also, Obeng et al. (2020) assessed that OC has a positive effect on performance. Given this, JP is considered to be one of the functioning components and a vital part of organizational studies. We, therefore, hypothesized that

Hypothesis 1: OC positively and significantly influences JP.

OC and HWP

The discernment individuals have about their work environment is determined primarily by OC and sometimes predicts the individual values and psychological passions (Permarupan et al., 2013). Behavior plays an important role in our very actions. The right OC leads to HWP and in turn JP. Also, individuals committed to an intense HWP may feel that the job is an innermost call of a person’s soul (Vallerand et al., 2003). Besides, HWP is somehow a feeling that augments individual satisfaction with competence and autonomy (Astakhova & Porter, 2015). Moreover, individuals’ attitudes characterized by high HWP are considered as talented and valuable assets needed by the organization to enhance effectiveness, efficiency, and productivity (Indriasari & Setyorini, 2018). We, therefore, proposed that

Hypothesis 2: OC will exert a positive and significant effect on HWP.

HWP and JP

A few years past, debates have been put forward by researches on HWP. Zigarmi et al. (2011) viewed HWP as a persistent, optimistic, internalized state of satisfaction occasioned by favorable cognitive and affective work evaluations. Moreover, HWP was developed and defined by Vallerand et al. (2003), as “a strong inclination towards an activity that people like, find important, invest significant time and energy in, and internalize in their identity.” Owing to this, assessing the relationship between HWP and JP has become very significant (Vallerand et al., 2003), and present-day researchers are seeking to explore more into this seemingly apparent relationship. Ahmed et al. (2016) as well as Fisher et al. (2018) found that both harmonious and obsessive forms of passion emanated from the internalization into one’s personality of the desired behavior. Ahmed et al. (2016) established that linking HWP to JP is positive. Based on the conservation of resources theory by Hobfoll (1989), an individual associated with the HWP level will invest time and energy because of the love for the work. This will be an effect on the development of one’s self-esteem (Baumeister et al., 2003), which will make employees feel the necessity to improve their JP. Research indicates that HWP has been related to enhanced performances in multiple settings, such as sports, gambling, and work (Ho et al., 2011). Hence, it is proposed that

Hypothesis 3: HWP has a direct positive effect on JP.

Mediating Role of HWP

The association between an organization and its employees has been regarded as a form of social exchange for time past (Blau, 1964). The hypothesized model suggests that the more OC impacts individuals positively, the more they will enjoy their work and connect to the work (i.e., feeling HWP) leading to JP. HWP is associated with different attitudes and outcomes that are cognitive (Indriasari & Setyorini, 2018). However, Vallerand et al. (2007) discovered that HWP generates activities that influence JP. Furthermore, Patel et al. (2015) posit that individuals with high HWP, concerning projects, improve performance making HWP positively correlate with JP. Moreover, cross-cultural research by Burke et al. (2015) in Russia and China further corroborates that HWP positively correlates with JP. Whereas positive HWP—JP association is commonly supported (Ahmed et al., 2016). In addition, it is viewed by other studies that HWP directly and positively predicts employee JP (Bonneville-Roussy et al., 2011). This study, however, explores HWP as a mediator in the OC and JP nexus. Hence, we proposed that

Hypothesis 4: HWP will mediate the relationship between OC and JP.

Moderating Role of LMX

The LMX theory’s basic assumption which explains the positive impacts of LMX on employee JP presupposes that a leader’s treatment of followers determines the follower’s responses (Liden et al., 1997). Also, the essential underlying principle of LMX theory is therefore that leaders discriminate their treatment toward followers via diverse ways of exchanges (Altinay et al., 2019; Liden et al., 1997), resulting in diverse quality relationships between the leader and each follower. Followers, however with high-quality LMX relationships, may do well because of the extra support giving by managers including resources and opportunities (Nandedkar & Brown, 2017). The LMX theory helps us to go beyond cognitive theories and to consider how the nature of the relationship of exchange for an employee’s job can affect his or her HWP. Martin et al. (2016) posit that leaders develop special relationships with each of their followers and that the quality of this relationship influences the work attitudes and behaviors of the followers. Nevertheless, behaviors of employees as underpinned in HWP could be affected greatly by the LMX. LMX adherence intensifies productivity and job satisfaction when HWP is positively affected. This means LMX boosts individuals’ HWP leading to JP. With LMX moderating the relation between OC and HWP, it may strengthen or weaken HWP depending on the nature of relationship outcomes delivered through the LMX dynamics. Based on this conceptualization, it is proposed that

Hypothesis 5: LMX will moderate the relationship between OC and HWP.

Moderating Role of Coaching

Previous studies show that coaching encourages better JP (Tanskanen et al., 2019; Wheeler, 2011). Leaders frequently permit subordinates to participate in self-development training programs for them to acquire specific knowledge and skills in handling daily challenges encountered in executing tasks effectively. Moreover, employees become highly motivated when professional guidance and encouragement are received from managers which in turn influence JP. Also, organizations that propagate these opportunities institute employees’ potentials in the acquisition of skills in turn increase JP outcomes. However, OC becomes a vital element in any results-oriented coaching environment. Stated differently, effective coaching thrives for its objectives in a setting characterized by a positive OC. Therefore, leadership skills, precisely the genuineness, and quality of coaching skills in an organization may influence the OC on employee JP. For instance, coaching positively correlates with job satisfaction (Yuan et al., 2019), which numerous researches have linked to improved JP. Implementing coaching strategies increases productivity and job satisfaction (Bozer & Jones, 2018). Hence, it is hypothesized that

Hypothesis 6: Coaching moderates the relationship between OC and JP.

Theoretical Framework

The theory of social exchange (SET) explains how two or more parties exchange resources, how successions of exchanges take place, and how exchanges affect the relationship between the parties concerned (Cropanzano et al., 2017). The fundamental premise of this theory is human interaction (Blau, 1964). Empirical evidence on SET (cf. Cropanzano and Mitchell (2005)) highlights that relationships grow gradually into trust, loyalty, and requisite commitments if those concerns (e.g., superiors and subordinates) live by limited “rules” of exchange. As constructs under investigation in this study are positive initiating action and need a positive response, it is imperative to use SET in accounting for their relationships. Figure 1 presents the conceptual framework of the study. The framework depicts OC has a direct effect on HWP, and in turn OC and HWP to have a direct positive effect on JP. LMX is used as moderator on the positive relationship between OC and HWP. Finally, coaching was seen to act as a moderating effect on OC and JP nexus.

Figure 1.

Proposed framework.

Method

Sample and Data Collection

The study used a questionnaire to gather data on how employees in RCBs in Ghana perceive the influence of OC on their JP. Letters were sent to 127 RCBs seeking permission to use their banks for the study. The response was received from 105 RCBs permitting us to use their employees to assess how the workplace climate affects their JP. Meetings were held with employees of the various RCBs together with the managers of the banks to explain the study’s objectives and offer assurances of confidentiality and non-bank-specific aggregation of data for purposes of analysis. The total accessible population of 105 RCBs branches was 955 employees who met selection criteria in accordance with Asiamah et al. (2017). The selection criteria required that (a) one was a permanent employee of the bank; (b) one had worked in the bank for at least 6 months, this was to ensure each participant had substantial experience with the bank’s climate; (c) one had at least basic education or the ability to read and write in the English language, which was a medium of communicating items in questionnaires; and (d) the existence of demographic information about the employee. The simple random sampling method was used to select representative samples from each branch resulting in a sample size 431 as the valid response received from the employees. After determining the sample size, we then assigned codes that were in IBM SPSS (Statistical Package for the Social Sciences) Version 23 to them. In the SPSS framework, the random sampling function was used to select codes to make up the sample size for each branch. The data collection period was 1 month. Table 1 presents the demographics of the study.

Table 1.

Respondents’ Demographic Characteristics.

Variable	Characteristics	Frequency	Percent
Gender	Male	226	52.4
Gender	Female	205	47.6
Age	18–25	29	6.7
	26–45	388	90
	46–60	14	3.3
Educational qualification	Postgraduate degree	177	41.1
	Bachelor and higher national diploma	251	58.2
	Professional educational	3	0.7
Position at work	Senior-level management	104	24.1
	Middle-level management	153	35.5
	Lower level management	152	35.3
	Others	22	5.1
Years of service	Less than a year	44	10.2
	1–5	211	49
	6–10	134	31.1
	11–15	41	9.5
	15 years and above	1	0.2

Measures

The main variables of this study are OC, JP, LMX, HWP, and Coaching. The main dependent variable is JP. HWP is a mediator in the relationship between OC and JP, whereas LMX moderates the direct effect of OC and HWP. Coaching acts as a moderator in the OC/JP nexus.

OC scale was adopted from the study by Peña-Suárez et al. (2013), that is, CLIOR Scale. The short version adopted for this study comprises 15 items. A sample item is the following: “When I do something well, my superiors congratulate me” and “Opportunities for training are offered.” The study of Berberoglu (2018) also adopted the short version of the scale and had an alpha value of .884 after dropping one item. In this study, Cronbach’s alpha coefficient (α) value is .93 indicating high internal consistency. HWP scale was derived from the passion scale developed by Vallerand et al. (2003) and adopted by Vallerand et al. (2010) which comprises two subscales of six items each. In the study of Vallerand et al. (2010), each subscale had an alpha coefficient of .72. HWP was assessed with six items in this study with a sample item “My work is in harmony with other activities in my life” and “My work reflects the qualities I like about myself.” HWP had Cronbach’s alpha coefficient (α) value of .85 indicating high internal consistency which supports the reliability of the scale. JP was measured with subscale items (contextual and task) derived from the study of Wang et al. (2003) and adopted by Zhu et al. (2016) which comprises 21 items in total. Fifteen items were used to measure CP with Cronbach’s alpha value of .88 and six task-performance items with an alpha value of.94 with a sample as “I adequately complete assigned duties.” In the work of Zhu et al. (2016), CP had an alpha coefficient value of .91 and TP (α = .87) depicting a high internal consistency and external validity of variables. Coaching was measured and tested using 8-item scale originally developed by Ellinger et al. (2003). Researchers have used and validated the reliability of the scale from other settings (Hagen & Williams, 2019; Nguyen et al., 2019). The sample item includes “my coach encourages me to broaden my perspectives by helping me to see the big picture; ‘my coach asks questions rather than provide solutions, to help me think through issues.” Coaching, in this study, had a Cronbach alpha coefficient value of .90 showing high internal consistency. We measured the LMX construct with 11 items from the LMX and Employee Behavior Scale developed by Wayne and Green (1993). Sample items are the following: “I keep my boss informed of what I have accomplished on the job” and “I ask my boss about his or her non-work life (e.g., asking his or her family).” The LMX had .93 as an alpha coefficient value for this study. All the scales were measured on a 5-point Likert-type scale ranging from 1 (strongly disagree) to 5 (strongly agree).

Control Variables

The study controlled for five potential variables that could potentially influence RCBs’ employee JP. These were gender, age, educational qualification, position, and years of service. Moreover, the variables controlled correlated with each other significantly, positively, or negatively.

Data Analysis

The SPSS (Version 23) was used to conduct exploratory factor analysis (EFA) to ascertain the appropriateness of the factor loadings under their respective components. The EFA resulted in the deletion of 20 items (six items from OC scale, two items from HWP scale, one item from LMX scale, one item from task-performance scale, and 10 items from contextual-performance scale). Amos (Version 21) was subsequently used to conduct the confirmatory factor analysis (CFA). Items deleted during the EFA process were 20 (32.26%) out of 62 items and hence did not affect the reliability, validity, and dimensionality of the measures. Hierarchical regression analysis was employed as the main statistical technique in SPSS (Version 23) to estimate the path analysis. The procedures outlined by Baron and Kenny (1986) for performing the mediation-moderation analysis (i.e., (a) the independent variable significantly predicts the dependent variable, (b) the independent variable significantly predicts the mediator variable, (c) the mediator variable significantly affects the dependent variable, and (d) the dependent variable is regressed on both variables (the independent variable and the mediator), the mediator significantly predicts the dependent variable, whereas the predictive utility of the independent variable is reduced) were also followed. A normed chi-square (χ²/df) of 3 or less, standardized root mean square residual (SRMR) of 0.08 or less, root mean square error of approximation (RMSEA) of 0.08 or less, Tucker–Lewis fit index (TLI) of 0.90 or higher, and comparative fit index (CFI) of 0.90 or higher indicate a great sign of unidimensionality for the data set (Byrne, 1994; Issac et al., 2006). It does also show that the model excellently fits the data. CFA results show the overall model had a normed chi-square χ²/df = 2.129, SRMR = 0.044, RMSEA = 0.051, TLI = 0.944, CFI = 0.947, and Pclose = 0.269 which are indications that the model fits the data well.

The reliability and validity analysis was then performed for the variables using Amos plug-ins developed by Gaskin and Lim (2016). These plug-ins can generate the construct validity, convergent validity (average variance extracted [AVE]), and discriminant validity as well as generate a correlation matrix table using standardized coefficients and coefficients of inter-factor correlations. The construct reliability of the variables ranged from 0.877 to 0.978 which exceeds 0.70 threshold suggested by Nunnally (1978), hence displaying high internal consistencies. The AVE for the variables ranged from 0.593 to 0.813 which exceeds the 0.50 threshold suggested by Nunnally (1978), hence indicating high convergent validity. The discriminant validity bolded and shown along the inter-factor correlation matrix was also greater than the correlation coefficients, hence showing that the variables were distinct from each other. The validity and reliability are presented in Table 2.

Table 2.

Mean, Standard Deviation, Reliability, Validity, and Inter-Factor Correlation Matrix.

Variables	M	SD	1	2	3	4	5	6	7	8	9	10	11
1 Gender	1.48	0.500	—
2 Age	1.97	0.314	.017	—
3 Edu.Qua.	1.60	0.505	.200**	−.103*	—
4 Position	2.21	0.869	.055	.036	.250**	—
5 Yr.ser.	2.41	0.807	−.001	−.063	−.065	−.220**	—
6 OC	3.376	0.852	−.139**	−.160**	.026	−.149**	.08	.795
7 LMX	2.903	1.262	.115*	−.129**	.006	−.052	−.109*	.122*	.902
8 HWP	3.611	0.974	.074	−.114*	−.118*	−.032	−.008	.261**	.182**	.808
9 TP	2.581	1.234	−.089	.092	−.044	.054	−.071	.08	.051	.053	.866
10 CP	3.490	0.996	−.139**	.129**	.160**	.059	−.005	.131**	−.008	.176**	.118*	.770
11 Coach	2.816	0.977	−.075	.111*	.014	−.167**	.055	.014	.066	.101*	.058	.242**	.798
CR								.938	.978	.903	.937	.877	.932
AVE.								.631	.813	.653	.749	.593	.637

Note. Edu.Qua. = educational qualification; Yr.ser. = years of service; OC = organizational climate; LMX = leader–member exchange; HWP = harmonious work passion; Coach = coaching; TP = task performance; CP = contextual performance; CR = construct reliability; AVE = average variance extracted;

p < .05. **p < .01.

Results

Common Method Variance (CMV)

Buckley et al. (1990) assessed that the sum of spurious variance exchanged between variables as a consequence of common methods employed in data gathering is called a CMV. Podsakoff et al. (2003) explained that CMV occurs from possessing a common rater, the common context of measurement and common context of items, or characteristics of the items used. Hence, as these research data were gathered using a self-report questionnaire, it is vital to address some issues about CMV. In empirical research such as this one, failure to control CMV will adversely cause an effect on the magnitudes of the proposed relationships illustrated in the conceptual framework. The procedure outlined by Podsakoff et al. (2003) was followed to avoid CMV. We assured participants that their views would be treated strictly confidential. All scales were subjected to reliability and validity testing. The data used for the study were self-reports from RCBs’ employees which were taken through several methodological tests, which proved CMV did not affect the results. CMV was not a problem in our research as participants were schooled on the purpose of the study and assured of confidentiality.

Means, Standard Deviation, and Correlation Analysis

From Table 2, we presented the means, standard deviations, reliability, validity, and inter-factor correlations of the scales considered for this study. OC had positive significant correlations with variables of JP thereby suggesting some preliminary support for H1. OC also had a positive significant correlation with HWP, suggesting some initial support for H2. HWP had a significant correlation with CP; hence, it suggests some level of support for H3.

Hypothesis Testing

Model testing of the major and mediating effects

We performed hierarchical regression on the bases of the control variables by using SPSS Version 23 to estimate the relationships among the variables. Table 3 presents the unstandardized coefficient estimates for the study model. In the organization, OC positively and significantly correlated with JP (β = .165, p < .001) and HWP (β = .320, p < .001) in Models 2 and 3, respectively, providing support for H1 and H2. These results indicate that when there is a good work environment that affects the behavior of employees positively, employees are more likely to be harmoniously passionate about their work resulting in improved JP. In Model 4, HWP positively and significantly correlated with JP (β = .160, p < .001) indicating that at high HWP of employees, JP increases, hence supporting H3. When HWP was introduced into the statistical regression model, HWP partially mediated the relationship between OC and JP, hence H4 is supported. It is evident that the mediated effects of HWP between OC (β = .123, p < .05) and JP (β = .130, p < .01) indicate that OC is positively and significantly correlated with JP through HWP in Model 5.

Table 3.

Hierarchical Regression Analysis of Variables.

Variables and analysis steps	Job performance	Job performance	HWP	Job performance	Job performance
Variables and analysis steps	Model 1	Model 2	Model 3	Model 4	Model 5
(Control variables)
Constant	2.219***	1.481***	3.236***	1.473***	1.059*
Gender	−0.145	−0.105	0.287**	−0.179*	−0.142
Age	0.401**	0.465***	−0.291	0.468***	0.503***
Edu.Qua.	0.136	0.114	−0.341***	0.184*	0.159
Position	0.045	0.069	0.046	0.045	0.063
Yr.ser.	−0.031	−0.039	−0.047	−0.026	−0.033
Second step
OC		0.165***	0.320***		0.123*
Third step
HWP				0.160***	0.130**
R²	.038	.064	.115	.071	.084
∆R²	.038	.026	.073	.033	.047
F	3.336***	4.823***	9.145***	5.390***	5.564***

Note. HWP = harmonious work passion; Edu.Qua. = educational qualification; Yr.ser. = years of service; OC = organizational climate; R² = R squared; ∆R² = R² change; unstandardized coefficient of regression = β.

Sig. at .05. **Sig. at .01. ***Sig. at .001.

Model testing of the moderating effect of LMX on OC and HWP relationship

To test for the moderating effect of LMX on OC and HWP, the mean centralized method was used to centralize OC and LMX variables. The moderating effect of LMX on the relationship between OC and HWP is negative and significant (β = −.119, p < .01). As shown in Figure 2, the positive relationship between OC and HWP is weakened with low LMX, indicating that when LMX is low, OC positive relationship with HWP is lessened, whereas it becomes stronger when LMX is high. Hence, this supports H5, in Model 3. OC still exerts positive and significant influence on HWP (β = .302, p < .001) indicating that even with the mitigating presence of LMX, OC correlated positively with HWP in Model 2. Moreover, in Model 2, LMX also had a positive and significant correlation with HWP (β = .097, p < .01), indicating that when LMX is high, HWP increases thereby leading to JP.

Figure 2.

Moderating effect of LMX on OC and HWP.

Model testing of the moderating effect of coaching on OC and JP

In an attempt to estimate the moderation effect of coaching, we mean-centered coaching and OC. Finally, we tested the moderated effect of coaching on the relationship between OC and JP via HWP in Table 5, Model 3. The moderating effect of coaching on the relationship between OC and JP is significant (β = .116, p < .05), indicating that the presence of coaching strengthens the positive relationship between OC and JP. Figure 3 shows that when coaching is high OC also becomes high increasing JP. This indicates that coaching influences the relationship between OC and JP positively and significantly, hence providing support for Hypothesis 6. In Model 2, OC had a positive significant effect on JP (β = .166, p < .001), indicating that with the presence of coaching, OC still correlated positively with JP. Coaching, though a moderator, positively and significantly correlated with JP (β = .157, p < .001), indicating that irrespective of the presence of the independent variable, coaching positively predicts JP, which also is an assumption met in the moderation procedure.

Figure 3.

Moderating effect of coaching on OC and job performance relationship.

Discussion

In this study, we observed when and how OC promotes JP. Relying on our findings, it indicates that OC is positively and significantly related to JP via HWP. Moreover, coaching strengthens the positive influence of OC on JP. Furthermore, LMX weakens the positive effect of OC on HWP. The study’s first hypothesis stated that OC positively and significantly influences JP. The linear regression analysis confirmed this hypothesis, as a direct and positive relationship between OC and JP was shown. Thus, when role clarity, participative decision-making, reward, communication, and so on are practiced in the organization, it is expected that employees will exhibit behaviors leading to JP, not only by achieving their required jobs but also by adapting to changes in their work environments. These outcomes are consistent with the previous studies that disclosed positive relations between OC and JP (Haryono et al., 2019; Luqman et al., 2020). For an organization to survive the competition and uphold to the competent workforce, good OC practices should be improved by management.

Furthermore, SET has been used to corroborate the connection between relational behaviors and attitudes (Cropanzano & Mitchell, 2005), which underpin this study. The mediating effect hypothesis stated that in the OC and JP relationship, HWP exerted a mediating effect. The results show that the mediation effect of HWP was partially exercised. Stated differently, HWP partially mediated the relationship between OC and JP in that OC had a significant and positive effect on the employee HWP, and HWP had a positive and significant influence on JP, which is consistent with the findings of other studies (Luqman et al., 2020; Permarupan et al., 2013). Interestingly, it appears that while OC would foster HWP toward achieving JP, policies and strategies that project good OC should be employed to ignite employee’s HWP. This signifies that organizations should introduce policies that will embrace employee welfare to make employees feel passionate about the job they undertake. However, a study by Haryono et al. (2019) predicted JP with OC as an independent variable through job satisfaction which resulted in OC influencing JP positively and significantly. But our study contributed to the literature by focusing on HWP as a conduit through which OC predicted JP which also revealed positive and significant results. The implications are that whenever good OC policies such as reward, leadership, group spirit, responsibility and inclusive decision-making, goals, effective functional structure, influence, motivation, and clear communication procedures make up the work climate, irrespective of the mediating mechanism, JP would be attained.

Drawing on the norm of reciprocity (Gouldner, 1960), LMX advocates that positive evaluations of leader/member quality tend to have positive effects on employees’ work behaviors and attitudes (Liden et al., 1997). LMX was hypothesized to moderate the relationship between OC and HWP which was supported and negatively significant (β = −.119, p < .01). This practically implies that work-related attitudes and behaviors exhibited by employees depend on the treatment leaders give to them which is considered as a crucial principle of LMX theory (Liden et al., 1997). Thus, HWP which is considered a work attitude could only be enhanced in an organization if there are cordial and productive engagements between leaders/managers on one hand and followers/subordinators on the other hand. As indicated in Figure 2, low LMX led to low OC in the organization which reduced the positive effect of OC on HWP. When leaders fail to integrate very well with members, it can affect the work climate which may lead to these circumstances (Van Knippenberg & Hogg, 2003), who stated, “leaders not only lead groups of people but are also themselves members of these groups.” Sometimes when there is a loss of respect and loyalty for authority, it affects employee’s attitudes and behaviors which could result in low LMX impact resulting in a compromise of the popularly espoused idea that “subordinates are expected to show unreserved loyalty and obedience toward their superiors.” According to Gómez and Rosen (2001), trust subordinates have in leaders is also vital in an organization as a lack of mutual trust in their relationships results in a low LMX effect. We, therefore, encourage future researchers to also consider LMX trust in related relationships as LMX encourages employees to reciprocate the favorable conduct gained from their supervisor through positive attitudes and behavior (Dulebohn et al., 2012).

The study conceptualized coaching as a moderator in the positive relationship between OC and JP. The results confirmed the hypothesis as coaching exerted a positive moderating effect on the relationship between OC and JP. This indicates that the introduction of coaching in an organization’s scheme of talent management reinforces the net positive effect of OC on employee JP. Regarding Figure 3, it was established that the higher the coaching, the higher the OC leading to improved JP. This shows that activities in the organization which is geared toward effective coaching practices stimulate the improved performance of work (Ellinger et al., 2011). Stated differently, the amount of coaching managers provides tends to impact positively on employee behaviors. This is consistent with Kim et al. (2013) who opine that coaching intensifies goal-directed awareness of employees which is a critical factor in employee JP. The practical implications are that RCBs that uphold to coaching as a deliberate policy with maximum organizational support in coaching skills and strategies training would become very effective in creating a meaningful OC for enhanced employee JP. This is corroborated in research which suggests that the heart of managerial effectiveness is managerial coaching (Hamlin et al., 2006). It is advised that the management of RCBs should uphold coaching as a strategic talent management tool and invest in it to impact their work climate to improve employee JP.

To further justify the findings, the control variables’ effects on the various relationships were also looked at in this study. Demographic variables are characteristics associated with one’s origin such as age, gender, race, income, education, family history, ethnicity, and work experience (Benard & Victor, 2013; Parvin et al., 2012). Demographic variables contribute significantly toward employee job and firm’s performance (Harpriya et al., 2020). Regarding this, the study takes into account the demographic characteristics of gender, age, educational qualification, position at work, and years of service. First, a significant demographic characteristic that has an effect on JP is gender. Mostly, it is deemed that female employees experience stress at the workplace (He et al., 2002) owing to the organizational culture, characteristics of the work environment, and demands from family. In view of this, male employees are sometimes considered as more productive compared with female employees. Even though the employees are dominated by male, gender had no impact on JP in Model 1 in Tables 3 and 5. However, in Table 4, gender had a significant impact on JP, justifying the appropriateness of controlling. Second, in Table 3, age had a significant impact on JP in Model 1 in Tables 3 to 5, with majority of the youth employees exercising greater JP. The greater levels of JP could be because majority of the youth employees need recognition and also have a greater level of harmonious passion in the work they perform. Besides, youth are more susceptible to change and are adaptable to learning new things which leads to improved JP despite these assertions and possibilities, Age was controlled. Third, Harpriya et al. (2020) opine that an individual’s investment in his or her education, knowledge, and skills are human capital investments as these could improve one’s JP. However, educational qualification had no significant impact on JP in Model 1 in Table 3. Conversely, educational qualification of the employees had significant impact on JP in Model 1 in Tables 4 and 5 in the analysis. A clear indication is set out here that the educational level of the employees played a pivotal role in the LMX and coaching moderation effect in performing their task, hence controlling educational qualification. These findings presuppose that when employees are highly educated, the employees find their job important, invest significant time and energy in, and internalize in their identity to improve performance as relationship between HWP and JP has become very significant (Vallerand et al., 2003). Fourth, position at work as a demographic factor in this research experienced no significant effect on JP in all the analyses in Model 1 in Table 3. This finding suggests that the position of the employees in the organizations matters not when it comes to their JP. Employees’ positions in the organization played a neutral role in employees’ JP by not exercising positive or negative effect. However, in the moderation analysis of LMX and coaching in Tables 4 and 5, position at work had no significant effect on JP in Model 1 in Table 4. Nevertheless, position at work had a little positive influence on JP when coaching interacted with OC in Model 3 in Table 5. This outcome implies that the positions employees occupy in the organization being senior-level management, middle-level management, and lower-level management exercise little impact on JP as coaching strategies targeted to all the levels of management are meant for improvement of JP. Finally, years of service in Tables 3 to 5 was not significant in influencing JP in all the relationships under the models. Years of service could not impact positively or negatively on the performance of the employees. In view of the researchers, years an employee spends in an organization do not determine the performance of the employee which makes this result not much astonishing. However, future researchers are entreated to investigate into this outcome to find the causal effect of this finding as well as other control variables that could not have any significant impact on JP. The demographics variables that did not have any significant effect on JP were, however, controlled; nevertheless, these variables had influence on R² and ∆R² as their values increased in the models (see Tables 3 –5), hence were controlled.

Table 4.

Moderating Effect of LMX on OC and HWP Relationship.

Variables	HWP
Variables	Model 1	Model 2	Model 3
Constant	4.673***	2.892***	2.912***
Gender	0.208*	0.252**	0.250**
Age	−0.414**	−0.244	−0.234
Edu.Qua.	−0.298**	−0.333***	−0.337***
Position	0.000	0.054	0.062
Yr.ser.	−0.032	−0.026	−0.031
OC		0.302***	0.280***
LMX		0.097**	0.116**
OC × LMX			−0.119**
R ²	.042	.129	.145
∆R²	.042	.088	.104
F	3.690**	8.978***	8.960***

Note. LMX = leader–member exchange; OC = organizational climate; HWP = harmonious work passion; Edu.Qua. = educational qualification; Yr.ser. = years of service; R² = R squared; ∆R² = R² change; unstandardized coefficient of regression = β.

Sig. at .05. **Sig. at .01. ***Sig. at .001.

Table 5.

Moderating Effect of Coaching on OC and Job Performance Relationship.

Variables	Job performance
Variables	Model 1	Model 2	Model 3
Constant	2.219***	1.101**	1.153**
Gender	−0.145	−0.078	−0.075
Age	0.401**	0.402**	0.382**
Edu.Qua.	0.136**	0.086	0.098
Position	0.045	0.101	0.107*
Yr.ser.	−0.031	−0.045	−0.045
OC		0.166***	0.153***
Coaching		0.157***	0.157***
OC × Coaching			0.116*
R ²	.038	.096	.145
∆R²	.038	.058	.104
F	3.336**	6.404***	8.960***

Note. OC = organizational climate; Edu.Qua. = educational qualification; Yr.ser. = years of service; R² = R squared; ∆R² = R² change; standardized coefficient of regression = β.

Sig. at .05. **Sig. at .01. ***Sig. at .001.

Theoretical/Practical Contribution of the Study

The significant theoretical contributions made by this article to complement the management literature particularly in the management of RCBs in Ghana are as follows: First, that OC, explained as an assessment of the social relations and qualities that characterize the entity of the perspective of its members (Ostroff et al., 2013) or the sum of the processes and activities (including but not limited to policies, practices, and relations) within the organization as perceived by the organization’s staff (Griffin et al., 2000), is a significant ingredient in employee JP. OC influence on employee JP, however, makes more theoretical sense when viewed through HWP of employees. Management in their quest to create or improve OC must gauge their effort through HWP—the collective, persistent, optimistic, internalizes state of work satisfaction of employees (Zigarmi et al., 2011). Hence, where HWP is dominated, OC is inflated and impact more significantly on employee JP. This contribution is significant because of the apparent absence of this direction of theorization in the extant literature.

Second, we have corroborated the moderating effect of coaching on the relationship between OC and JP as espoused in the study of Jones et al. (2016). It has been established that coaching comes with applying goal-setting which is proved to be a technique to improve JP (Morisano et al., 2010). Also, coaching has been viewed as a learning and development practice in the RCBs to promote work performance behavior among employees. The implementation of coaching in this manner offers workplace learning and development.

Third, we have validated the moderating effect of LMX on the relationship between OC and HWP by proving that LMX had the potency to interact with OC to influence HWP which confirms its (LMX) role as a moderator (e.g., Stewart & Johnson, 2009) in the field of organizational behavior and SET.

Conclusion

Drawing on our findings, the reliability and validity of all the constructs considered in this study have been demonstrated in the context of RCB. Also, our findings show that OC is a predictor of HWP and this corroborates with the findings of Permarupan et al. (2013) and OC predicting JP of RCBs’ employees and this outcome corroborates with Berberoglu (2018) findings on nursing workers’ JP. Furthermore, HWP also led to predicting JP among RCBs’ workers and these results validate the study of Burke et al. (2015) . Similarly, it can be concluded that coaching strengthens the positive effect of OC on JP, and also LMX weakens the positive effect of OC on HWP.

Limitations and Future Research Prospect

This research came with some limitations that may create opportunities for future study. Generalization of the findings is a limitation as the study covered only private sector entities where all collaborators came from private companies. Future researchers should consider a comparative study on both private and public entities. The study used cross-sectional data which sometimes have its limitations compared with longitudinal data for causative analysis. This study was, however, grounded on theories, literature, and methodology, making the results more reliable. However, future researchers should consider longitudinal data to test the relationships. Future researchers should consider the dualistic model approach of passion as a mediating mechanism as it could account for the diverse ways employees feel passionate about their work.

Footnotes

Acknowledgements

The authors are very grateful to Mrs. Patricia Eshun of Lower-Pra Rural Bank and Mr. Eric Boakye of Pan-African Savings and Loans Company for their assistance in the data collection.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Anthony Frank Obeng

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Organizational Climate and Job Performance: Investigating the Mediating Role of Harmonious Work Passion and the Moderating Role of Leader–Member Exchange and Coaching

Abstract

Keywords

Introduction

Literature and Hypotheses Development

OC and JP

OC and HWP

HWP and JP

Mediating Role of HWP

Moderating Role of LMX

Moderating Role of Coaching

Theoretical Framework

Method

Sample and Data Collection

Measures

Control Variables

Data Analysis

Results

Common Method Variance (CMV)

Means, Standard Deviation, and Correlation Analysis

Hypothesis Testing

Model testing of the major and mediating effects

Model testing of the moderating effect of LMX on OC and HWP relationship

Model testing of the moderating effect of coaching on OC and JP

Discussion

Theoretical/Practical Contribution of the Study

Conclusion

Limitations and Future Research Prospect

Footnotes

Acknowledgements

Declaration of Conflicting Interests

Funding

ORCID iD

References