Moderating Effect of CSR on Transformational Leadership and Organizational Performance of State Corporations in Kenya

The purpose of this study was to assess the associated relationships between transformational leadership, corporate social responsibility, and organizational performance. A total of 217 questionnaires were gathered from employees operating the various key state energy corporations in Kenya and then were analyzed using structural equation modelling (SEM). Findings The results of studies show that moderating’s does not significantly affect the relationship between organizational performance, transformational leadership. The results of the data further show that first, transformational leadership did not have a positive influence on organizational performance. Second, transformational leadership did have a positive influence on corporate social responsibility. Third, corporate social responsibility did have a positive influence on organizational performance. These findings may aid future researchers in their quest in understanding the inherent relationships that lie between the variables in question and may provide a platform for managers in their efforts to improve organizational performance.

obligation should be to maximize its positive influence and minimize the negative effects of it actions by taking the long term needs of society into consideration (Garbac and Loncaric, 2009).

Economic Responsibility
A company's first responsibility is its economic responsibility. This is due to the fact that organizations that don't make money fail to and disappear leading to employees losing their jobs. As a result, organizations must be profitable in order for them to be good citizens (Scilly, 2014). Economic responsibility refers to the profitability and competitiveness of an organization and its subsequent socioeconomic impact (Wang, 2011). Here organizations produce products and services required by society and sell them for a profit (Jones et al, 2009). However, organizations need to acknowledge that their economic performance is not something they do only for themselves but also for society (Carroll and Shabana, 2010).
In the end economic responsibility is considered the most important responsibility as businesses that are not profitable cannot move on to fulfil their other responsibilities (Smirnova, 2012).

Legal Responsibility
The society in which organizations operate encompasses specific regulations, laws, and standards of behaviour that organizations are expected to follow and respect in all their business activities (Longo et al, 2005;Jourdan & Kivleniece, 2016). Legal responsibility refers to the positive and negative obligations placed by the laws and regulations of society on organizations (Carroll and Shabana, 2010). It includes obeying and respecting the rules, laws, regulations developed by society (Grbac and Loncaric, 2009;Jones et al, 2009).
Obeying all the laws is considered the most important responsibility for firms after economic responsibility according to the theory of CSR (Scilly, 2014). However, laws are not sufficient to address every aspect and scenario required for individual and organizational behaviour (Vives, 2008).

Ethical Responsibility
Economic and legal responsibilities are considered to be a company"s biggest obligation. After meeting these two requirements organizations are free to pursue their ethical responsibilities (Scilly, 2014). Ethical responsibility can be defined as "a corporation"s voluntary actions to promote and pursue social goals that extend beyond their legal responsibilities" (Carroll and Shabana, 2010). It refers to organizations doing what is right, just and fair (Grbac and Loncaric, 2009). By undertaking ethical responsibility organizations transcend economic and legal considerations as they voluntarily try to satisfy certain expectations that are not backed up by regulations but are expectations that society wants businesses to fulfil (Longo et al, 2005). However, knowing what is right or wrong is difficult as ethical standards are not explicit or codified (Smirnova, 2012).

Philanthropic/Discretionary Responsibility
After organizations have met all of their other responsibilities, they can begin to meet their philanthropic responsibilities which involves companies going above and beyond what is required or what the company believes is right (Scilly, 2014).
Philanthropic responsibility is considered to be the highest level of social responsibility and includes a company"s voluntary contributions to society (Grbac and Loncaric, 2009). According to Carroll and Shabana (2010) philanthropic/discretionary responsibility encompasses "those corporate actions that are in response to society"s expectations that business be a good citizen, this includes actively engaging in acts or programs to promote human-welfare or goodwill" (p.96). Philanthropic responsibility represents voluntary actions of organizations such as charity, donations, financial and other contributions that aim to improve the quality of life in the community (Smirnova, 2012). The most prominent philanthropic activity organizations engage in is donation. Organizations usually make donations directed at various causes such education, community improvement, and arts and culture (Seifert et al, 2004).

Organizational Performance
Organizations today are trying to adapt to all the changes surrounding them by improving their performance through the competitive advantage they create (Ramezan et al, 2013;Masa'deh et al., 2015). Researchers have always looked at organizational performance as the ultimate dependent variable concerned with almost every area in management. This is because organizational performance allows researchers to evaluate organizations, their actions, and environments and compare them to those of their rivals (Richard et al, 2006;Obeidat, 2016).
Most literature suggests that when it comes to organizational performance, researchers find it difficult to define, conceptualize, and measure this concept (Taghian et al., 2015). Regarding the definition of organizational performance each person tends to have a different conceptualization of performance in general and organizational performance in particular. From a process point of view, performance refers to the transformation of inputs into outputs to achieve specific outcomes. From and economic point of view, performance is the relation between effective cost, realized output, and achieved outcomes (Abu Jarad et al, 2010;Masa'deh et al., 2016). Organizational performance can be defined as the degree to which an organization is able to meet its own needs and the needs of its stakeholders in order to survive (Griffin, 2003). Carton (2004) suggested that organizational performance is the voluntary association of productive assets that lead to the achievement of European Journal of Business and Management www.iiste.org ISSN 2222-1905(Paper) ISSN 2222-2839(Online) Vol.11, No.35, 2019 shared purpose. Another definition of organizational performance refers to it as "the ability to acquire and process properly human, financial, and physical resources to achieve the goals of the organization" (Ramezan et al, 2013).
The performance of organizations is affected by internal and external factors. Internal factors are considered firm specific and include leadership style, organizational culture, job design, and human resource policies. External factors can be the same for all firms, these include market preferences and perceptions, country rules and regulations, and the economy of the country (Chien, 2004;Mirza and Javed, 2013).
In this study the dimensions of financial and non-financial performance will be used to measure organizational performance based on the study conducted by Hernaus et al (2012).

Financial Performance
Organizational performance measurement has become an increasingly important matter in order for organizations to survive under the pressure of world class competition (Skrinjar et al, 2008;Al-Syaidh et al., 2015;Mahadeen et al., 2016). Financial performance refers to "a measure of the change of the financial state of an organization, or the financial outcomes that results from management decisions and the execution of those decisions by members of the organization" (Carton, 2004). Thus financial performance is regarded as a direct indicator of a firm"s financial condition from various perspectives (Shi and Yu, 2013;Cegarra-Navarro et al., 2016). Financial measures can be found in financial statements and accompanying notes (Wang et al, 2015). An example of financial measures includes: economic values added, revenue growth, costs, profit margins, cash flow, and net operating income (Rasula et al, 2012;Obeidat et al., 2014). These measures are considered to be more objective compared to non-financial measures which are more subjective in nature (Abu Jarad et al, 2010;Masa'deh et al., 2014). Prieto and Revilla (2006) stated that numerous factors affect a firm"s financial performance some of these factors are; economic conditions, changing government regulations, technological developments, and changes in the cost of producing and delivering products or services.
Despite its popularity, financial measures of performance are no longer considered adequate means for exercising management control as they encompass many weaknesses such as failing to convey strategies and priorities effectively within an organization (Hernaus et al, 2012). Furthermore, they fail to supply sufficient data to executives to assure continued performance improvement and invention (Wang et al, 2015).

Non-financial Performance
By the 1980s it became clear that traditional financial measures of performance were no longer sufficient to manage organizations competing in demanding and competitive markets (Ramezan et al, 2013). This implies that financial measures that emphasize short-term indicators such as profit, turnover, and cash flow are not suitable anymore for measuring organizational performance and as a result non-financial measures have increased in importance (Tseng, 2010;Maqableh et al., 2014).
According to Khan et al (2011) non-financial performance measures focus on achieving long-term success and incorporates factors that lead to improved organizational and financial performance. These non-financial measures include customer satisfaction, internal business process efficiency, innovation, employee satisfaction, and organizational commitment (Abu Jarad et al, 2010;Khan et al, 2011;Al-Sarayrah et al., 2016). In addition, Kaplan and Norton (2001) suggested that non-financial performance measures help managers in various ways. They help them assess the changes that occur in their business environments, determine and evaluate progress towards organizational goals, and affirm achievement of performance. Figure 1 demonstrates the research's conceptual framework and the hypothesized relationships between the adopted constructs.   Vol.11, No.35, 2019 relationships and to test the hypotheses between the observed and latent constructs in the proposed research model. SEM can be divided into two sub-models: a measurement model and a structural model. While the measurement model defines relationships between the observed and unobserved variables, the structural model identifies relationships among the unobserved/latent variables by specifying which latent variables directly or indirectly influence changes in other latent variables in the model (Byrne, 2001;Hair et al., 2010). Furthermore, the structural equation modeling process consisted of two components: validating the measurement model and fitting the structural model. While the former is accomplished through confirmatory factor analysis, the latter was accomplished by path analysis with latent variables (Kline, 2005). Using a two-step approach assures that only the constructs retained from the survey that have good measures (validity and reliability) will be used in the structural model (Hair et al., 2010 NP3: Reputation of our company in eyes of the customers has improved. NP4: We consider our relations with suppliers to be excellent because we maintain genuine partnerships with them.
NP5: There is a mutual trust between our company and our suppliers. NP6: Quality of our products is well above the industry average.

Sample and Procedure
A survey questionnaire was used to gather data for hypotheses testing from the state corporations in energy sector in Kenya. Before implementing the survey, the instrument was reviewed by four employees at four different state corporations in order to identify problems with wording, content, and question ambiguity. Some minor edits were introduced and some changes were made based on their suggestions. The population of this study consists of all employees at all the managerial levels working at the five major energy sector state corporations in Kenya, which counts of more than 1200 according to their human resource units. The sample size of this study was determined based on the rules of thumb for using SEM within AMOS 23.0 in order to obtain reliable and valid results. Kline (2010) suggested that a sample of 200 or larger is suitable for a complicated path model. Furthermore, taking into account the complexity of the model which considers the number of constructs and variables within the model and after eliminating the incomplete surveys, our sample size (217) meets the recommended guidelines of Kline (2010), Krejcie and Morgan (1970) and Pallant (2005). The demographic data of the respondents are reported in Table 2.  Table 2, the demographic profile of the respondents for this study revealed that the sample consisted of more males, most of them experienced, 83% of them are more than 30 years old.

Descriptive Statistics
All the 46 items were tested for their means, standard deviations, skewness, and kurtosis. The descriptive statistics presented below in Table 3 indicate a positive disposition towards the items. While the standard deviation (SD) values ranged from 0.71109 to 1.13895, these values indicate a narrow spread around the mean. Also, the mean values of all items were greater than the midpoint (2.5) and ranged from 2.1131 (TL3) to 4.2836 (TL12). However, after careful assessment by using skewness and kurtosis, the data were found to be normally distributed. Indeed, skewness and kurtosis were normally distributed since most of the values were inside the adequate ranges for normality (i.e. -1.0 to +1.0) for skewness, and less than 10 for kurtosis (Kline, 2010). Furthermore, the ordering of the items in terms of their means values, and their ranks based on three ranges (i.e. 1-2.33 low; 2.34 -3.67 medium; and 3.68 -5 high) are provided.   Table 4 shows different types of goodness of fit indices in assessing this study initial specified model. It demonstrates that the research constructs fit the data according to the absolute, incremental, and parsimonious model fit measures, comprising chi-square per degree of freedom ratio (x²/df), Incremental Fit Index (IFI), Tucker-Lewis Index (TLI), Comparative Fit Index (CFI), and Root Mean Square Error of Approximation.
(RMSEA). The researchers examined the standardized regression weights for the research"s indicators and found that all indicators had a high loading towards the latent variables. Moreover, since all of these items met the minimum recommended value of factor loadings of 0.50; and RMSEA less than 0.10 (Newkirk and Lederer, 2006;Hair et al., 2010;Kline, 2010), they were all included for further analysis, except TL3, TL6, TL15, LR2, LR5, PR5, PR6, PR10 and NP5 which has a loading of 0.411, 0.398, 0.298, 0.391, 0.369, 0.377, 0.345, 0.349, and 0.406 respectively, thus excluded from further analysis. Therefore, the measurement model showed a better fit to the data (as shown in Table 4). For instance, x²/df was 1.562, the IFI = 0.86, TLI = 0.85, CFI = 0.86; and RMSEA 0.028 indicated better fit to the data considering all loading items.

Measurement Model
Confirmatory factor analysis (CFA) was conducted to check the properties of the instrument items. Indeed, prior to analyzing the structural model, a CFA based on AMOS 20.0 was conducted to first consider the measurement model fit and then assess the reliability, convergent validity and discriminant validity of the constructs (Arbuckle, 2009). The outcomes of the measurement model are presented in Table 5, which encapsulates the standardized factor loadings, measures of reliabilities and validity for the final measurement model.

Unidimensionality
Unidimensionality is the extent to which the study indicators deviate from their latent variable. An examination of the unidimensionality of the research constructs is essential and is an important prerequisite for establishing construct reliability and validity analysis (Chou et al., 2007). Moreover, in line with Byrne (2001), this research assessed unidimensionality using the factor loading of items of their respective constructs. Table 5 shows solid evidence for the unidimensionality of all the constructs that were specified in the measurement model. All loadings were above 0.50, except TL3, TL6, TL15, LR2, LR5, PR5, PR6, PR10 and NP5, which is the criterion value recommended by Newkirk and Lederer (2006). These loadings confirmed that 37 items were loaded satisfactory on their constructs.

Reliability
Reliability analysis is related to the assessment of the degree of consistency between multiple measurements of a variable, and could be measured by Cronbach alpha coefficient and composite reliability (Hair et al., 2010). Some scholars (e.g. Bagozzi and Yi, 1988) suggested that the values of all indicators or dimensional scales should be above the recommended value of 0.60. Table 5 indicates that all Cronbach Alpha values for the eight variables exceeded the recommended value of 0.60 (Bagozzi and Yi, 1988) demonstrating that the instrument is reliable. Furthermore, as shown in Table 5, composite reliability values ranged from 0.85 to 0.96, and were all greater than the recommended value of more than 0.60 (Bagozzi and Yi, 1988) or greater than 0.70 as suggested by Holmes-Smith (2001). Consequently, according to the above two tests, all the research constructs in this study are considered reliable. As shown in Table 5, since the measurement model has a good fit; convergent validity and discriminant validity can now be assessed in order to evaluate if the psychometric properties of the measurement model are adequate.

Content, Convergent, and Discriminant Validity
Although reliability is considered to be a necessary condition of the test of goodness of the measure used in research, it is not sufficient (Creswell, 2009;Sekaran, 2003;Sekaran and Bougie, 2013). Thus validity is another condition used to measure the goodness of a measure. Validity refers to which an instrument measures is expected to measure or what the researcher wishes to measure (Blumberg, et al., 2005). Indeed, the items selected to measure the six variables were validated and reused from previous research.
Moreover, in order to enhance the content validity of the instrument, seven academics were asked to give their feedback about the questionnaire, thus confirming that the knowledge presented in the content of each question was relevant to the studied topic.
Furthermore, as convergent validity test is necessary in the measurement model to determine if the indicators in a scale load together on a single construct; discriminant validity test is another main one to verify if the items developed to measure different constructs are actually evaluating those constructs (Gefen et al., 2000). As shown in Table 5, all items were significant and had loadings more than 0.50 on their underlying constructs. Moreover, the standard error for the items ranged from 0.072 to 0.126 and all the item loadings were more than European Journal of Business and Management www.iiste.org ISSN 2222-1905(Paper) ISSN 2222-2839(Online) Vol.11, No.35, 2019 twice their standard error. Discriminant validity was considered using several tests. First, it could be examined in the measurement model by investigating the shared average variance extracted (AVE) by the latent constructs. The correlations among the research constructs could be used to assess discriminant validity by examining if there were any extreme large correlations among them which would imply that the model has a problem of discriminant validity. If the AVE for each construct exceeds the square correlation between that construct and any other constructs then discriminant validity is occurred (Fronell and Larcker, 1981). As shown in Table 5, this study showed that the AVEs of all the constructs were above the suggested level of 0.50, implying that all the constructs that ranged from 0.54 to 0.71 were responsible for more than 50 percent of the variance in their respected measurement items, which met the recommendation that AVE values should be at least 0.50 for each construct (Bagozzi and Yi, 1988;Holmes-Smith, 2001). Furthermore, as shown in Table 6, discriminant validity was confirmed as the AVE values were more than the squared correlations for each set of constructs. Thus, the measures significantly discriminate between the constructs.

Structural Model and Hypotheses Testing
Following the two-phase SEM technique, the measurement model results were used to test the structural model, including paths representing the proposed associations among research constructs. Further, in order to examine the structural model, it is essential to investigate the statistical significance of the standardized regression weights (i.e. t-value) of the research hypotheses; and the coefficient of determination (R²) for the research endogenous variables as well. The coefficient of determination for corporate social responsibility, and organizational performance were 0.62, and 0.54 respectively, which indicates that the model does moderately account for the variation of the proposed model. The two hypotheses were supported by the data. The results showed that transformational leadership did not have a direct significant influence on organizational performance (α=0.235, t-value=1.105, p<0.05), and thus H1 was not supported. However, transformational leadership did have a significant influence on corporate social responsibility (α=0.992, t-value=4.761, p<0.05), and the latter on organizational performance (α=0.921, t-value=3.571, p<0.05), supporting H2 and H3.

Discussion and Conclusion
The results of the analysis did not support the hypothesis stating that transformational leadership will have a direct significant positive influence on organizational performance. This result is consistent with the conclusions reached by various scholars. For instance, Liberson and O"Connor (1972) concluded that the relationship between leadership and organizational performance is weak, non-existent, and even contradictory. Jaffee (2001) furthers this conclusion by stating that theories of the effect of leadership on organizational performance are simply false. Fenwick and Gayle (2008) study results revealed that the relationship between leadership and performance is considered inconclusive and difficult to interpret. Obiwuru et al (2011) also found that the dimensions of transformational leadership have an insignificant relationship with performance. The reason behind such conclusions is that leadership on its own is not sufficient to explain the variance in organizational performance, other more powerful influences should be taken into consideration. Unless leadership is studied as part of an interrelated set of forces, one would not be able to measure its effect (Liberson and O"Connor, 1972). It can also be noted that the results obtained in this study contradict the works of other researchers. Koech and Namusonge (2012) and Sahaya (2012), for example, found that transformational leadership is positively related to organizational performance. Several other researchers have supported these results that propose a positive association between transformational leadership and organizational performance (See Nohria and Khurana, 2010;Wasserman et al, 2010;Katou, 2015).
The premise behind the conclusion of these researchers is that organizations seeking efficient ways to outperform others, focus on the effects of leadership. This is due to the fact that intangible assets such as leadership styles are considered vital sources of strength that merge together people, processes, and organizational performance (Obiwuru et al, 2011). Furthermore, transformational leadership is reported to have a strong relationship with organizational performance given its ability to exert greater effort and performance from subordinates by inspiring them to elevate their capabilities for success and developing their problem solving European Journal of Business and Management www.iiste.org ISSN 2222-1905(Paper) ISSN 2222-2839(Online) Vol.11, No.35, 2019 skills (Koech and Namusonge, 2012). In addition, transformational leadership creates an environment characterized by high levels of trust, commitment, and inspiration exerted by subordinates that leads to performance beyond expectations (Pradhan and Pradhan, 2015).
Transformational leadership has been found to have a significant positive relationship with corporate social responsibility. This finding is supported by the results of several studies present throughout the literature which indicated that transformational leadership and corporate social responsibility are significantly positively associated (See Turner et al, 2002;Waldman et al, 2004;De Lacerda, 2010;Groves and Larocca, 2011;Verissimo and Lacerda, 2012;Tuan, 2012;Du et al, 2013). The reason for this association can be traced back to the characteristics of charismatic and intellectual stimulation exhibited by transformational leaders. Charismatic leaders are likely to engage in behaviors and advocate policies that relate to corporate social responsibility, thus gaining the admiration of followers as their visions are based on values of altruism, justice, and humanistic notions of the greater good. Such values are in turn likely to increase the tendency to accomplish goals, especially those connected to corporate social responsibility. Moreover, intellectually stimulated leaders possess the ability to scan and broadly think about the environment and the manner in which various organizational stakeholders may be served. Such an understanding enhances followers" thinking regarding how to balance organizational goals with the desire to pursue corporate social responsibility (Waldman et al, 2004). According to Pradhan and Pradhan (2015) CEOs that exhibit transformational leadership behaviors, inspire followers and encourage a mutual vision of value creation in the governing body and its stakeholder, indicating to the role leaders play in developing and implementing CSR strategies. As such, it can be suggested that transformational leaders are likely to exhibit responsible behaviors that relate to protecting and advancing the interests of both primary and secondary stakeholders indicating that the organization does not exist in isolation from the environment surrounding it (Du et al, 2013).
Significant effort has been made to understand the relationship between corporate social responsibility and organizational performance. This study revealed that a positive significant relationship exists between corporate social responsibility and organizational performance. Other studies proposed similar findings, for example, Rettab et al. (2009) conducted a study in Dubai to examine the relationship between corporate social responsibility and organizational performance. Results showed that corporate social responsibility positively affects organizational performance. Buiciuniene and Kazlauskaite (2012) suggested that one of the key findings of their study was the determination of a positive association between corporate social responsibility and performance outcomes. Ali et al (2010), Erhenjamts et al (2013), Okwemba et al (2014), and Valmohammadi (2014) have also reached the same conclusion regarding the relationship between corporate social responsibility and organizational performance. Corporate social responsibility aims to encourage business entities to perform their activities ethically, reduce the negative effects on the community and the environment, thereby enabling them to continue gaining economic benefit (Valmohammadi, 2014). As such, researchers suggest that taking an interest in the various stakeholders of the firm may improve the firm"s reputation and image and hence positively affecting productivity, financial performance, and value creation of the firm (Hillman and Keim, 2001). This is supported by Buiciuniene and Kazlauskaite (2012) who suggested that corporate social responsibility is a major contributor to gaining a competitive advantage by developing the firm"s internal and external image and reputation, and facilitating changes in the organization"s values and processes. However, the findings of this study contradict those reported by other scholars. According to them a negative or neutral relationship exists between corporate social responsibility and organizational performance (See Baron et al, 2011;Crisostomo et al, 2011;Vance, 1975;Aupperle et al, 1985). Such a contradiction may be attributed to the differences in measures used to measure organizational performance as the previous studies have focused solely on financial measures of organizational performance, whereas this study incorporated both financial and nonfinancial measures to refer to organizational performance. The outcomes recommend a progression of issues that should be considered by managers and researchers. Keeping in mind the end goal to have an important translation of the outcomes with respect to the connections between study variables, it is constantly key to evaluate the part of the third variable in the relationship. As mentioned by Rosenberg (1968), a relationship study that does not address the mediating mechanism ends up with facts but with inadequate comprehension. Also, the study that neglects to think about the possibility of a mediator effect in the data may miss more clarification for a result. A model that addresses mediation effects will thus offer a more precise estimation of the relationship between the variables studied. In this regard the significance of corporate social responsibility on the association between transformational leadership and organizational performance should always be addressed by scholars and practitioners if legitimate decisions and conclusions are to be made. In this way, findings can help management intensify initiatives to support more noteworthy comprehension and acknowledgment of the concept of transformational leadership which boosts firms" corporate social responsibility and in turn superior performance. Although transformational leadership did not influence organizational performance directly in this study, its effect may be enabled by the presence of corporate social responsibility. European Journal of Business and Management www.iiste.org ISSN 2222-1905(Paper) ISSN 2222-2839(Online) Vol.11, No.35, 2019