Transformational Leadership’s Impact on Organizational Innovation: The Mediating Role of Management Control System

Abstract

Contemporary organizations are made up of various tangible and intangible components. While several of these components have been subjected to a variety of scholarly studies, both individually and in relation to one another, a number of organizational components still require deeper investigation. The present study looks at the direct and indirect effects of transformational leadership (TL) on organizational innovation (OI) through management control system (MCS) as a mediating variable. This objective has been achieved through an exhaustive review of the literature on the impacts of TL and MCS on OI. The data were collected through questionnaire distribution among 400 high-level managers of seven universities in Saudi Arabia, within the period of May–July 2019. Subsequently, 264 surveys were acquired for the final analysis, indicating 66 per cent accuracy in the response rate. Furthermore, Partial least squares SmartPLS 3.0 used to assess the measurement model and the structural model. It is revealed that TL and MCS have a significant correlation with OI. However, the levels of influence of TL and MCS are quite different in terms of the influence on OI. Finally, our study proposes a few future studies for the research scholars and practitioners.

Keywords

Transformational leadership organizational innovation management control system resource-based view theory structural equation modelling SmartPLS

Introduction

The dynamic nature of the modern-day world is based on a fast and competitive society, where the ability for an organization to adapt to changes and transformation is of substantial value (Alharbi et al., 2019a). Managing innovation is the key to ensuring that an organization can gain a competitive advantage over its rivals (Tohidi & Jabbari, 2012). For this reason, successful organizations, especially those with effective managers, prioritize the development of mechanisms that aim to achieve greater innovation. It is an undisputed fact that organizational innovation (OI) is the key to ensure the future development and survival of any business. Innovations help organizations synchronize themselves with changes in consumer needs, market and environment. Therefore, due to the intricate nature of contemporary organizations, various factors could impact OI. These factors include transformational leadership (TL) (García‐Morales et al., 2008; Gumusluǒlu & Ilsev, 2009; Li et al., 2016; Suifan & Al-Janini, 2017; Tajasom et al., 2015; Wan et al., 2013) and management control system (MCS) (Karmeni et al., 2018; Lopez-Valeiras et al., 2016). The present article aims to investigate the relationship between TL and OI through MCS as a mediating variable.

However, the research on both TL (e.g., Howell & Avolio, 1993; Samad, 2012; Vargas, 2015; Waldman & Bass, 1991; Wang & Howell, 2010) and MCS (e.g., Ouchi, 2006; Tessier & Otley, 2012) has focused on the achievement of organizational aims with the corresponding individuals goals, on the one hand, and fostering employee creativity, empowerment for innovation and commitment to change, on the other. While OI is a much more organization-oriented type of innovation than the others, it is an impressive field for investigating TL and MCS. TL style is a leader who exchanges ideas with followers, and both go to the level of higher motivation (Bass & Avolio, 1994). The MCS employed the information based on the procedures, processes and routines of the managers to ensure that the behaviour of employees and the decisions that are made are associated with organizational goals (Merchant & Van der Stede, 2012).

Organizational innovation involves the creation or selection of a new idea as a way of providing services, products and processes that are unique to that particular organization (Li et al., 2018). OI has emerged as a key difference between competing organizations (Bhaumik, 2018). Innovation is required in order to be competitive and to achieve economic prosperity and social development (Alharbi et al., 2019b). Innovation is a key factor for visionary and competitive organizations. TL can either encourage or discourage innovation, which ultimately affects the performance of various sectors, including universities and institutions (Ryan & Tipu, 2013). It has also been argued that the MCS could promote innovation development (Simons, 1995, 2000). Although OI is closely related to such factors, the management literature has not yet looked closely at the relationship between TL, MCS and OI.

In recent years, empirical researchers have started to focus on the relationships between TL and MCS (Davila & Foster, 2007; Nguyen et al., 2017) because TL consists of norms and values for clarifying the structures and tools of control (Abernethy et al., 2010). Various authors (e.g., García-Morales et al., 2012; Gumusluoglu & Ilsev, 2009; Jung et al., 2008; Samad, 2012; Vargas, 2015) have found that TL can catalyse and exploit talent in organizations to foster creativity and innovation. This is consistent with Nguyen et al. (2017), who found that the MCS mediates between TL and managerial performance. Therefore, the present study assumes that organizations employ MCS as a mediating role in the relationship between TL and OI.

Universities play a critical role in modern society, which is constantly changing and where innovation affects all such changes (Fritsch & Slavtchev, 2007; Vlok, 2012). The economy is heavily dependent on innovation. The new World Economic Forum report from 2018 found that approximately 133 million new jobs will be created by 2022 and that 75 million jobs will move to technical innovation (WEF, 2018). According to the McKinsey report, approximately 84 per cent of managers feel that innovation enables an organization to grow and succeed in a competitive market (Julia Myllylä, 2019). Therefore, rather than being isolated from their role in economic and social growth, universities should participate in scientific research, which would lead to progress in innovation, as well as in society and the economy overall (Viana-Baptista, 1999). Regarding the relationship between TL and OI, the theoretical discussions and empirical studies have been somewhat ambiguous; this could be affected by the mediating role of MCS. Therefore, the present study sought to examine the mediating effect of the MCS in the relationship between TL and OI in Saudi universities. Finally, this study expands the empirical research on OI (Crossan & Apaydin, 2010; Keupp et al., 2012).

This article is structured as follows: the first section consists of literature review, objectives and rationale of the study. The second section presents the methodology, survey and sample design, variables measurement, data analysis and results. Finally, the third section consists of discussion with conclusion, managerial significance, limitations and future research.

Literature Review

Nowadays, organizational competitive strategies rely on objectives related to OI aimed at optimization of capacity or improvements in quality, an increase of flexibility and cost reductions (Bunduchi et al., 2011; Tang et al., 2013). OI relates to the use of new managerial and working concepts and practices (Damanpour, 1991; Damanpour & Evan, 1984). OI is a non-technological innovation, which deals with humans, not with technology; it is about performing and reshaping organizations’ procedures regarding the internal or external organization relations (Camisón & Villar-López, 2014).

Innovation has been reviewed from various angles, regarding areas such as services; products; marketing; and organizational, national and individual innovations (Ganzer et al., 2017; Kjellberg et al., 2015; Lee, 2007; Mothe & Thi, 2010). These studies have helped extend the innovation literature and require in-depth awareness of the subject. Although these studies have contributed to the extension of innovation literature, they have also obscured in-depth knowledge on the subject. Therefore, the present study will contribute to the growth of innovation literature by revealing the knowledge on the topic. The fundamental proposition of resource-based view (RBV) theory is that the organizations are different in terms of the strategic resources they hold and control (Poazi et al., 2017). TL and control system are considered as resources for the organization. There is no doubt that the resources are the bases of organizations. In other words, resources are permanently linked to the organization (Maijoor & Witteloostuijn, 1996). Hooley et al. (1998) divided the resources-based view into assets (which includes systems, brands, machines, plant, people, etc.) and capabilities (market orientation, organization learning, innovation, customer care, leadership skills, etc.). In the present study, the resources used the capabilities resources-based view in terms of leadership and control system, and that leads to innovation. The RBV theory is used for formulating relationships, while the structural model is as described below.

Innovation is essential for organizations in a competitive environment, that TL can encourage or discourage the innovation that may ultimately affect the overall performance of organizations, firms, institutions and universities (Samad, 2012; Vargas, 2015). According to Szczepańska-Woszczyna (2015), members of organizations are recognized as assets, but can also be considered capabilities. However, according to Makri and Scandura (2010), an influential and effective leader is one who can invent, develop and commercialize and is also able to develop human and social capital. TL has a significant positive effect on innovation (Ryan & Tipu, 2013).

Transformational leadership used intellectual stimulation and inspirational motivation, which are important for OI (Elkins & Keller, 2003). TL encourages creative ideas within their organizations, and their behaviours are proposed to act as ‘creativity-enhancing forces’, inspirational motivation ‘provides encouragement into the idea generation process’, intellectual stimulation ‘encourage the exploratory thinking’ and individualized consideration ‘works as a reward’ for the workers (Sosik et al., 1998). Howell and Higgins (1990) pointed that this style reflects the ‘championing role’ of the TL. This leadership style develops the esteem, confidence and efficacy of their followers (Bass, 1991). Moreover, this leadership style motivates its followers by increasing their performance beyond expectations and encouraging them to adopt innovative ways in their work. The resulting heightened levels of self-esteem and motivation in the followers are expected to enhance OI (Mumford et al., 2002). TL is one of the most effective parts of contemporary organizations. Many social scientists have observed how TL affects OI. For example, several studies have looked into the relationship between TL and OI. Denti and Hemlin (2012) reviewed 30 empirical studies to find out when and how leadership relates to innovation. They concluded that leadership has been repeatedly treated as an independent variable, whereas innovation has been considered a dependent variable. Uusi-Kakkuri (2017) sought to determine the impact of TL on creativity and innovation. That study found that TL, particularly the dimensions of intellectual stimulation and inspirational motivation, is the most appropriate leadership style for creativity and innovation. Al-Husseini and Elbeltagi (2016) studied how TL can support innovation in public and private higher education in Iraq. They found that dimensions of TL (idealized influence, inspirational motivation, intellectual stimulation, and individualized consideration) affect innovation more strongly in public education organizations than in private ones. There is a dearth of the literature on the relationship between TL and OI. Therefore, this study examines the direct relationship between TL and OI.

In addition, leadership is also inherent in the design and implementation of MCS, and very few studies have addressed this topic over the past 20 years (Abernethy et al., 2010; Ansari & Bell, 1991; Tsamenyi et al., 2008). The current empirical researchers have started to examine the relationships between TL and MCS. Management control and leadership are inseparable. MCS has been defined as a system within social, cultural, political and economic environments that management uses to align employee behaviour with organizational objectives and to manage internal and external interdependencies (Efferin & Hopper, 2007). Anthony (1965) views MCS as tools through which top managers assess the achieved levels of their employees’ performance and match these levels to predetermined targets and make the corrective action if necessary (Green & Welsh, 1988). Newer and broader conceptualities (e.g., Merchant & Van der Stede, 2012), however, describe MCS as ‘all the devices or systems managers use to ensure that the behaviors and decisions of their employees are consistent with the organization’s objectives and strategies’ (p. 6). The powerful of MCS tools are not limited to the feedback of financial performance only, but also through a compound of various control tools (Bisbe & Otley, 2004; Malmi & Brown, 2008; Otley, 1980; Ouchi, 1979; Widener, 2007). Although it has been widely recognized that leadership and management control are related, advancements of knowledge have often been made in isolation from each other, leaving the various links between both disciplines largely unexplored (Davila & Foster, 2007; Otley & Pierce, 1995). Existing empirical evidence suggests that the use of an organization’s MCS (e.g., the use of specific performance measures, the delegation of decision rights or the use of planning systems) is dependent to some extent on individual differences in top executives’ personal characteristics, such as their leadership styles (e.g., Abernethy et al., 2010; Hartmann et al., 2010; Jansen, 2011). Literature in the area of management accounting and control provides evidence that certain leader behaviours trigger the choice of specific MCS practices (Hartmann et al., 2010; Kyj & Parker, 2008) that are instrumental to the development of an OI. Also, the study of Kleine and Weißenberger (2014) proposed two elements of MCS (formal and informal control system) to examine how leadership and MCS interact in the process of creating organizational commitment. The study showed that leadership can significantly transfer its behaviors and affecting on organizational commitment through informal control elements. However, neither of those studies discussed TL explicitly. Given the important roles of the leadership in the implementation of MCS, there is a need to add literature on the relationship between TL and MCS. Accordingly, there is a need to examine the direct relationship between TL and MCSs.

Despite the importance of OI in organizations’ competitiveness, MCS literature has limited the focus to analysing the influence of the interactive use of MCS on product innovation (Lopez-Valeiras et al., 2016). OI is driven by strategic motivations (Hervas-Oliver et al., 2014), which commonly involve analysing the supporting competitive advantages, defining the market position and competitive environment (Casadesus-Masanell & Ricart, 2010). MCS is concentrated on the uncertainties that lead to the formulation of the competitive strategy ‘by which the innovating organization will gain and hold the advantage over rivals’ (Chesbrough, 2007). The control system gives some proofs for example: ‘data generated by the system are interpreted and discussed in face-to-face meetings of superiors, subordinates, and peers’ and called interactive control systems (Robert Simons, 1995, p. 97) that ‘trigger revised action plans’ (Robert Simons 1995, p. 108). Thus, the goal of MCS is to give useful information for planning, evaluation and decision-making (Merchant & Otley, 2006), as well as to influence the followers’ behaviours by means of managers’ controls (Malmi & Brown, 2008). MCS is used intensively by top management in a challenging environment, and in facilitating the inspirational involvement (Bisbe et al., 2007). However, there is an ambiguity in the literature regarding the relationship between innovation and MCS (Bisbe & Otley, 2004). Specifically, it does not clearly specify the OI that MCS may foster. Therefore, there is a need to examine the direct relationship between the MCS and OI.

As described in the previous sections, there is insufficient literature on the direct effects of TL on OI. However, several studies have recognized these effects as indirect, unlike the studies mentioned in previous sections (Nguyen et al., 2017). To sum up, there is a dearth of literature available on the relationship between TL and OI, as well as between MCS and OI. Hence, the study also examines the mediating effect of MCS on the relationship between TL and OI. Therefore, the present study has employed a new framework in which MCS mediates the impact of TL on OI. The proposed framework of this study is represented in Figure 1.

Objectives

The universities sector of Saudi Arabia is an important sector that leads to community development; therefore, this study seeking to examine the impact of TL and MCS, together directly and indirectly, on OI by using MCS as a mediating factor in the relationship between TL and OI, in the context of Saudi Arabian universities.

Figure 1.

Source: The authors.

The Rationale of the Study

Saudi Arabia ranks the biggest country in the Middle East with 34 million people (Saudi Statistics, 2020). The universities sector is considered an important sector in Saudi Arabia with 30 universities distributed across the country (Saudi Ministry of Education, 2020). Universities play a critical role in modern society, which is constantly changing and where innovation affects all such changes (Fritsch & Slavtchev, 2007; Vlok, 2012). Therefore, rather than being isolated from their role in economic and social growth, universities should participate in scientific research, which would lead to progress in innovation, as well as in society and the economy overall (Viana-Baptista, 1999). However, the literature has observed that different factors such as TL and MCS might significantly affect OI. Hence, it is imperative that organizations understand these factors together. To this end, the present study contributes to leadership and OI literature to understand the role of TL and MCS variables on OI. Moreover, this study shows the effects of TL styles on OI are rather significant. Instead, the more significant effects of TL styles are largely due to the concurrent use of MCS as a mediating tool to translate TL behaviour into OI. We, therefore, provide evidence that TL style precedes OI. Given our findings, we recommend that the process of developing and improving an organization’s top management needs to be accompanied by the characteristics of leadership style and the MCS elements to enhance OI. Therefore, our results extend the findings provided by Kleine and Weißenberger (2014) and Lopez-Valeiras et al. (2016), especially with regard to how managers use particular MCS.

Methodology

Survey and Sample Design

Through the use of an empirical approach, this study analysed the relationship between TL, MCS and OI among high-level managers. Non-probability sampling (Sekaran & Bougie, 2013) was used. The questionnaires were distributed online using Google Forms among top managers at seven Saudi Arabian universities. These potential respondents were selected based on their decision-making power and their in-depth knowledge of their organization’s abilities. From 400 questionnaires distributed from May to July of 2019, 264 were returned (a response rate of 66%). Respondents were mostly males (79.2%) and the age ranges were as follows: 41–50 years (51.8%), 51–60 (31.3%), 31–40 (15.1%) and more than 60 (1.8%). All respondents have a PhD degree; most work in colleges (70.4%), deanship (24.6%), and just a few in university agency (5%). Most of the respondents were deans (82.6%), followed by vice-rectors (17.4%). Almost one-third (31.8%) of respondents have between 3 and 5 years of experience in that position, while 24.2 per cent had 6–10 years, 19.3 per cent had more than 15 years, 14.4 per cent had less than 3 years, and 10.2 per cent had 11–15 years of experience.

Variables’ Measurement

In this study, it was used different measures for measuring the variables. Bass and Avolio’s (2000) model are adopted for measuring the Transformational Leadership style. That model comprised 20 items using 5-point Likert scales, where 1 indicates “strongly disagree” and 5 indicates “strongly agree”. The MCS measurement incorporated 20 comprehensive items that were measured by 2 main dimensions: formal control and informal control. The formal control consisted of actions and results, and 10 items were adopted from Hutzschenreuter (2009), Wargitsch (2010) and Widener (2007). The informal control consisted of culture and personal, with 10 5-point Likert scale items adopted from Hutzschenreuter (2009) and Jaworski and Macinnis (1989), again anchored by 1 (‘strongly disagree’) and 5 (‘strongly agree’). The OI measurement was based on the T&B model (Tidd & Bessant, 2009). The T&B model comprised 40 items with 5-point Likert scales ranging from 1 (‘strongly disagree’) to 5 (‘strongly agree’). The T&B model also conceptualizes all five major innovation traits which are the strategic, organization, process, developing, and linkages. Eight items were used to measure each of the five major component indices. An academic lecturer translated the questionnaire into Arabic and then another lecturer back-translated it into English, to make sure the contents were valid.

Data Analysis

Partial least squares SmartPLS 3.0 was used in the present study to assess the measurement model and the structural model. This is a variance-based approach to structural equation modeling (SEM), which is used for analysing and testing multiple construct relationships between variables. SmartPLS is used particularly when the data have a non-normal distribution (Hair et al., 2017; Ringle et al., 2012), and the model being tested has several latent variables with indicators (Hair et al., 2017) and high-order constructs (Becker et al., 2012). SmartPLS is applied when the knowledge about the relationships among causal constructs is fluid (Hartmann et al., 2010). Figure 2 illustrates the model of TL, MCS, and OI analysed by SmartPLS 3.0.

Figure 2.

Source: The authors.

Results

Measurement Model

The measurement model was assessed with regard to indicator reliability, convergent validity, discriminant validity and internal consistency reliability. Indicator reliability had a satisfactory factor loading that exceeded the 0.4 threshold (Hair et al., 2017). However, all the items have achieved the threshold. Composite reliability (CR) and Cronbach’s alpha (CA) were used to assess internal consistency. The threshold of critical values for both CA and CR was 0.7 (Hair et al., 2014). All of the latent variables showed high values for both CA and CR, which indicates a high level of internal consistency. Average variance extracted (AVE) is used to determine the variables’ convergent validity (Fornell & Larcker, 1981). Because none of the AVEs were below the critical threshold of 0.5, the results can be considered significant (Byrne, 2016). Table 1 presents the results of the measurement model.

Finally, discriminant validity occurs at the construct level if correlations of a latest variable with all other latent variables are lower than the square root of a latest variable’s AVE (Hair et al., 2017). This was confirmed, as shown in Table 2, where the diagonal elements are higher than the off-diagonal ones. Discriminant validity was assessed at the item level by evaluating the HTMT criterion. The HTMT ratio uses geometric correlations, which means measuring different phenomena with sets of within-construct. As Table 2 shows, the latent variables were below the critical threshold of −1 < HTMT < 1 (Henseler, Ringle, & Sarstedt, 2015).

Table 1.

Measurement Model Results

Construct	Items		Loading	Cronbach’s Alpha	Composite Reliability	Average Variance Extracted
Management control system	Formal	MFA	0.95	0.96	0.96	0.58
		MFR	0.94
	Informal	MIC	0.94
		MIP	0.95
Transformational leadership	TIA		0.90	0.96	0.96	0.59
	TIB		0.91
	TIC		0.81
	TIM		0.89
	TIS		0.91
Organizational Innovation	OIDL		0.94	0.98	0.98	0.64
	OIL		0.93
	OIO		0.94
	OIP		0.93
	OIS		0.94

Source: The authors.

Table 2.

HTMT Analysis

	MCS	TL	OI
Management control system
Transformational leadership	0.70
Organizational Innovation	0.88	0.73

Source: The authors.

Structural Model

The Evaluation of structural model was done with the significance of (t-values), path coefficients (p-values), effect sizes (f²) for the paths, variances of the endogenous constructs (R²) and (Q²) measures for the endogenous variables (Hair et al., 2017). Bootstrapping was used to obtain the structural model’s path coefficients, with 500 runs for 264 cases. The variables TL and MCS were positive and had significant effects on OI. The empirical results support the direct relationship between TL and OI (TL → OI: β = 0.23, t = 4.64, p < 0.01). The results of TL and MCS indicated a relationship between the constructs, so the results support the direct relationship between TL and MCS (TL → MCS: β = 0.68, t = 18.11, p < 0.01). The results showed a relation between MCS and OI, so the results support the direct relationship between MCS and OI (MCS → OI β = 0.70, t = 15.49, p < 0.01). The results of the mediating effects of the MCS between TL and OI supported the mediating effect, so the results were accepted (TL → MCS → OI β = 0.48, t = 12.39, p < 0.01). The results indicated that TL and MCS have a high impact on OI directly, while the mediating role of MCS shows a higher impact on the relationship between TL and OI indirectly. The values of (R²) suggest that TL style explains 46.6 per cent of the variance of MCS, and the MCS positively related to OI, which explains 77.8 per cent of the OI, that is above the threshold of (Cohen, 1988) 0.26 and indicates a substantial model. Moreover, the effect sizes (f²) observed that MCS (1.20) has a large effect on OI, TL (0.87) has a substantial effect on MCS, and TL (0.12) has medium effect on OI (Cohen, 1988). The values of (Q²) by using blindfolding assessment, all values of MCS (Q² = 0.25) and OI (Q² = 0.46) are more than zero which indicates that the model has sufficient predictive relevance (Hair et al., 2017). Table 3 summarizes the results of the structural model.

Table 3.

Structural Model Results

	Path coefficient	Standard Error	t-Value	p-Value	f ²	R ²	Q ²	Decision
TL → OI	0.23	0.05	4.64	0.00	0.12			Support
TL → MCS	0.68	0.03	18.11	0.00	0.87			Support
MCS → OI	0.70	0.04	15.49	0.00	1.20			Support
TL → MCS → OI	0.48	0.03	12.39	0.00				Support
MCS						0.46	0.25
OI						0.77	0.46

Source: The authors.

Note: p-Value < 0.01 and t-value > 2.58 (two-tailed).

Discussion and Conclusion

Earlier, scholars have stated that TL is a determinant factor of OI (Amankwaa et al., 2019; Gumusluǒlu & Ilsev, 2009; Li et al., 2018). There is a rich body of management literature indicating the effect of TL on OI. However, management scholars have claimed that MCSs are important tools in terms of influencing OI. Although there are potential overlaps between these research constructs, knowledge advancements have often been made in isolation. The present article sought to combine the two streams of research by introducing a model for TL’s direct and indirect effects on OI, with MCS as a mediating factor between the two conceptuses.

Our study contributes to recent literature in the following ways. First, our study shows that the direct effects of TL styles on OI are rather significant. Instead, the more significant effects of TL styles are largely due to the concurrent use of MCS as a mediating tool to translate TL behaviour into OI. Our study provides evidence that TL style precede OI (e.g., Li et al., 2018; Mokhber et al., 2011; Tajasom et al., 2015), has to be more examined and that future studies should focus on the indirect links or potential mediating effects (e.g., Haustein et al., 2014; Lopez-Valeiras et al., 2016).

Second, we find a strong connection between the MCS and the OI. Whereas previous studies have elaborated on the various results of performance measurement systems in general, the current study supports a more comprehensive view of MCS (Malmi & Brown, 2008; Sandelin, 2008). The adoption of this perspective takes into account that the control system works to some extent implicitly and is isolated totally from results-based tools. This study suggests that a more comprehensive perspective of MCS is more important (Luft & Shields, 2003) as different controls affect OI in different ways. Moreover, our study found that TL uses a comprehensive of MCS for purposes of effecting OI. Furthermore, we provide evidence that the positive effects of top management TL on OI are mediated by the use of MCS. Our results are therefore in line with previous research, which questions the universal assumption that MCS leads to more positive OI (e.g., Lopez-Valeiras et al., 2016). In addition, our findings support the notion that research on the MCS factor is particularly worthwhile (Kleine & Weißenberger, 2014), as this factor triggers positive behavioural responses to an organization’s control environment (Widener, 2007).

Third, this study finds that top managers (deans—vice-rectors) use a comprehensive control system tools that can be effected via the use of comprehensive tools of MCS (formal and informal controls). However, a nearly perfect mediation of the effect of TL on OI suggests that the use of MCS tools is particularly important when top managers express their behaviours. Although TL has an effect on OI, our results showed a small direct effect of TL on OI. We, therefore, agree with previous literature in stating that TL style builds a friendly, trusting and respectful work climate within an organization (e.g., Gumusluǒlu & Ilsev, 2009). Therefore, we recommend top managers who strive to influence all parts of an organization to essentially focus on the good relationships with their followers

Fifth, our analysis draws attention to MCS as a necessary factor to foster TL’s influence on OI. The struggle for effective MCS must therefore not be restricted to ‘financial metrics’, that is, finding the ideal financial key performance indicators. Instead, top management has to focus on a comprehensive use of an MCS, which aligns the formal and informal tools of control (Caldwell et al., 2011). Given our findings, we recommend that the development and improvement of an organization’s top management needs to be accompanied by the characteristics of leadership style and the MCS elements to enhance OI. Therefore, our results extend the findings provided by Kleine and Weißenberger (2014) and Lopez-Valeiras et al. (2016), especially with regard to how managers use particular MCS.

Finally, this study contributes to the leadership and OI literature by presenting empirical evidence of a positive relationship between TL and OI in the context of Saudi Arabia universities. Our results in this study extend the theorization of the relationship between TL and OI by demonstrating that the link is mediated by MCS. Therefore, our present findings add to the mediational theorization of prior studies (e.g., Li et al., 2018; Sağanak et al., 2015; Wan et al., 2013). Different from these earlier studies which reported organizational culture (Li et al., 2018), psychological empowerment (Sağanak et al., 2015) and organizational learning (Wan et al., 2013) as mediating factors in the TL and OI relationship, our results reveal MCS as simultaneously mediating path between the TL and OI link. Our results contribute to the existing literature by linking TL, MCS and OI in an integrated model with a sample of 264 top managers (deans—vice-rectors) from seven large universities in Saudi Arabia. Thus, this study provides a general understanding of the TL, MCS and OI relationship in the context of universities in Saudi Arabia. However, this study opens the window to understanding the natural relationship between these factors, which may increase competence in the organization.

Managerial Significance

From a managerial viewpoint, this study encouraged the knowledge to recognize different factors such as TL and MCS that affect OI. Accordingly, the results of this study showed that TL and MCS influenced on OI directly, and also confirmed that the MCS is significantly affecting indirectly as a mediating factor between TL and OI, , thus it might help the top management in universities to implement TL style and utilize MCS tools (formal and informal control tools) in improving the organizational innovation. Such considerations may improve the capability of Saudi universities and universities in other countries to be innovative universities by taking into account TL and MCS factors.

Limitations and Future Research

Ideally, TL should be measured through a combination of quantitative and qualitative approaches. Moreover, using a larger sample size than the one in the present study could better show how OI can be accelerated. The present study also focused on OI as a whole and the results cannot be generalized.

Future research could discriminate between various types of leadership and innovation. It could also incorporate additional organizational factors using a qualitative approach to focus on the generational effects of TL, which could affect OI in universities. We also recommend that future studies examine other leadership styles (such as transactional leadership, laissez-faire leadership, democratic leadership and autocratic leadership) for comparison purposes and also identify which other leadership styles could influence organizational control and innovation. Finally, the present study could be applied in different sectors or countries in order to learn about the impact the TL has on MCSs and OI.

Footnotes

Acknowledgement

I am grateful to the anonymous referees of the journal for their extremely useful suggestions to improve the quality of the article. Also, special thanks to my supervisors at UTM University in Malaysia for their guidance and motivation. I am also grateful to my College of Community at Taibah University in Madinah, in the Kingdom of Saudi Arabia, for their support.

Declaration of Conflicting Interests

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

Funding

The authors received no financial support for the research, authorship and/or publication of this article.

ORCID iD

Ibrahim Bader Alharbi

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