The Nexus Between Changes in CEO Successor’s Attributes and Firm Performance: Evidence from Emerging Countries

doi:10.21203/rs.3.rs-5297705/v1

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The Nexus Between Changes in CEO Successor’s Attributes and Firm Performance: Evidence from Emerging Countries

https://doi.org/10.21203/rs.3.rs-5297705/v1

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This paper aims to comprehensively analyze the impact of Chief Executive Officer (CEO) succession on the firm’s post-succession performance, specifically through investigating the direction of changes in CEO successor attributes compared to the predecessor CEO. The paper uses a sample of 1,729 firms in twenty-six emerging countries from 2000 to 2019. The sample yields 9,498 firm-year observations embracing 913 CEO successions. Using fixed effect (FE) regression, the findings conclude that hiring an insider CEO successor significantly decreases the negative impact of CEO succession on the firm’s asset utilization. However, hiring a CEO successor of the same gender, younger, less experienced, or with smaller social networks significantly amplifies the negative impact of CEO succession on the firm’s asset utilization. Moreover, the direction of change in CEO education and busyness has revealed mixed results on the firm’s asset utilization. In addition, hiring an insider, of the same gender, more experienced, with a larger social network and less busy CEO successor significantly decreases the negative impact of CEO succession on the firm’s liquidity. Finally, hiring an outsider, a different gender, younger, less educated, less experienced, with a larger social network or busier CEO successor significantly amplifies the negative impact of CEO succession on the firm’s liquidity.

JEL: C12, C23, G41, O16

Finance

Accounting

CEO

CEO Succession

CEO Attributes

Firm Performance

Emerging Countries

Corporate governance mechanisms and standards along with their impact on the firm’s different performance measures have been the focus of research during the past decades. One of the most critical topics in corporate governance is studying the impact of CEO attributes on the firm’s performance (Kim, 2005; Serra et al., 2016). The CEO is the main decision-maker in the firm and is responsible for shaping the organization’s structure and performance (Ghardallou et al., 2020). Accordingly, hiring a new CEO is a significant event for the firm and its future performance. Hence, the impact of CEO succession on the firm’s post-succession performance has been widely examined in previous studies (Khurana, 2002; Byrne et al., 2021). Hiring an unfitting CEO successor can cause the firm severe costs. Thus, selecting the adequate CEO successor to the firm with the best qualities and the most fitting attributes to the firm’s environment and objectives is a major topic of interest for both academics and practitioners (Qi, 2011).

However, very few studies have been conducted to test the impact of the change in CEO successor’s attributes on the firm’s performance. Elsaid and Ursel (2011) find a significantly negative relationship between hiring a female CEO successor preceding a male CEO predecessor and the firm’s post-succession financial performance. The study additionally finds a significantly positive impact on the firm’s cash holdings ratio. In addition, Elsaid and Ursel (2012) claim a significantly negative relationship between the change in the CEO successor’s age and the firm’s post-succession risk measures. Moreover, Huang and Kisgen (2013) find that having a female CEO successor following a male CEO has a significantly negative effect on the firm’s financial leverage and asset growth.

Another study by Elsaid (2014) concludes that hiring a male CEO successor preceding a female predecessor CEO significantly enhances the firm’s post-succession performance and significantly decreases its chance of bankruptcy. In addition, hiring a CEO successor with a different educational background significantly worsens the firm’s post-succession performance and significantly increases its chance of bankruptcy. Moreover, hiring a CEO successor with a different functional background significantly decreases the firm’s post-succession performance and significantly increases the firm’s chance of bankruptcy. Finally, the study has suggested that the best way to understand the impact of CEO attributes on the firm’s risk is during CEO successions, as during successions all other firm-specific characteristics and surrounding environment conditions are fixed, while the only variable changing is the CEO successor attributes.

Further, Knutsson (2015) finds that the negative impact of CEO succession on the firm’s risk level is moderated by hiring older CEO successors. This thesis shows that the change in CEO successor attributes may have different unexpected impacts on different firm performance measures from just studying the effect of CEO attributes on firm performance. Thus, succession-induced changes in CEO attributes have been critical in financial literature and need various explorations. Moreover, Zhang and Qu (2016) find that different-gender CEO successions have lower post-succession firm performance compared to same-gender CEO successions. Finally, Zhang et al. (2019) investigate the impact of the gap in six different CEO attributes (CEO gender, CEO age, CEO career variety, CEO highest education certificate, CEO social eliteness, and CEO cultural background) on the firm’s operating performance. In addition, the findings conclude that CEO successions are disruptive events in themselves and hence changes in CEO successor attributes due to CEO successions increase the firm’s post-succession disruptions, leading to negative post-succession performance.

Correspondingly, the study of the impact of each direction of change in CEO successor attributes separately (e.g., the impact of hiring an older CEO successor or hiring a younger CEO successor), can reveal new insights into the consequences of CEO succession on firm performance. However, empirical studies lack testing the impact of the direction of change (increase versus decrease) in CEO successor attributes compared to the predecessor CEO. Additionally, most of the empirical evidence regarding the impact of the change in CEO successor attributes is tested in a developed market setting like the United States, which cannot be employed in emerging economies due to their different characteristics (Karabag and Berggren, 2014). Though, this paper seeks not merely to provide more recent empirical evidence on the post-succession firm performance in emerging markets, but to explore and investigate how the direction of change in CEO successor attributes affects the impact of CEO succession on the firm’s post-succession performance in emerging markets.

Given the above, this paper seeks to identify the optimal CEO successor attributes that help emerging markets’ firms achieve their post-succession performance goals while considering the predecessor CEO’s attributes. Ultimately, this paper can provide more understanding to the firms on how to select their best CEO successor candidate, allowing their future post-succession goals to be achieved. Finally, this paper seeks to expand the CEO attributes, CEO succession, and firm performance literature by conducting a comprehensive analysis to provide a more complete picture of the impact of changes in CEO successor’s attributes on firm performance. This study is a cross-disciplinary study that has important implications for various fields by combining different financial, accounting, human resources, strategic management, and psychology concepts. As an original contribution, this paper is the first to examine the impact of the direction of change in CEO successor attributes on the firm’s post-succession performance. In addition, this paper is the first to examine the impact of the direction of change in seven different CEO successor attributes – CEO origin, gender, age, education, experience, social network, and busyness (using nine different attributes measures) – on the firm’s post-succession performance in emerging countries with available CEO succession data on BoardEx between 2000 and 2019. Finally, this is the first paper to test the impact on post-succession performance using asset utilization and liquidity measures.

2.1 CEO Succession

The CEO is the senior executive manager responsible for controlling the activities of the entire firm (Harymawan et al., 2020). CEOs’ responsibility is not limited to managing the company, they are also responsible for leading the firm, setting its structure and environment, shaping the organization’s culture, creating the firm’s vision, delivering a sense of solidity, and creating meaning for the employees directly doing the job (Ishak et al., 2013; Abdullahi et al., 2017). Accordingly, they are one of the most influential factors shaping organizational outcomes and affecting firm performance, as their role affects the firm’s daily operations (Von den Driesch et al., 2015; Serra et al., 2016; Burney et al., 2021).

The “CEO effect” is the degree of the CEO’s influence on the firm’s performance (Serra et al., 2016). When CEOs have adequate authority to make major decisions, they can best accomplish their objectives and maximize the firm’s value (D’Ewart, 2015). Having broad authority within the firm is essential, as they face ongoing challenging goals and objectives along with ambiguous cues and information. In such cases, CEO’s characteristics and attributes are key drivers of his actions and decisions (D’Ewart, 2015; Von den Driesch et al., 2015). Even though the degree of CEO’s and CEO succession impact on the firm’s performance is still debatable, any change in the CEO is a major corporate event influencing investors’ sentiments and hence the firm’s future performance (Elsaid and Ursel, 2011, 2012; Ishak et al., 2013; D’Ewart, 2015; Abdullahi et al., 2017).

In view of that, and with the increasing market competitiveness, CEO succession is a shift in the firm’s lifecycle and the new CEO selection defines a unique, critical, and very noticeable event to the firm. Therefore, CEO succession has reflective impacts on the firm’s strategy and performance (Datta and Rajagopalan, 1998; Kesner and Sebora, 1994; Finkelstein et al., 2009; Cragun et al., 2016; Shen, 2021). CEO successor should not be solely selected based on his profile, experience, or knowledge, but should also fit the firm’s culture and align with its strategy, vision, and goals (Ghazali, 2012; Ishak et al., 2013). There are several studies, but still, no full consensus in management, human resources, accounting, and finance addressing a range of views on the impact of CEO succession (Geddes and Vinod, 1997; Ishak et al., 2013; Cragun et al., 2016).

First, scholars claim that based on the “commonsense notion”, having a poor-performing predecessor CEO and an expert CEO successor who is qualified enough to meet the firm’s needs is appointed, the firm’s post-succession performance, image, and value can be enhanced, through presenting new strategies and policies to the firm (Kesner and Sebora, 1994; Ishak et al., 2013). Prior studies claim a positive post-succession firm performance and shareholder wealth (Du and Lin, 2011). Mohammad et al. (2020) conclude that CEO succession enhances the firm’s post-succession Return on Assets (ROA), Return on Equity (ROE), and Return on Sales (ROS). Moreover, Ghazali (2012) finds that CEO succession leads to better post-succession ROA. Further, Datta et al. (2003) claim that choosing a CEO successor with matching background and experience to the firm’s strategic direction leads to significant benefits.

Second, the “scapegoating notion” claims that CEO succession is just a signal of organizational changes and has no effect on the firm’s performance, as managers are not the only responsible parties for a firm’s performance (Kesner and Sebora, 1994; Ishak et al., 2013). Friedman and Singh (1989) claim that CEO successions in poor-performing firms have positive market reactions, while a negative market reaction in firms with good pre-succession performance. Third, based on the “vicious circle notion” and “the organizational theory”, scholars claim that CEO succession abolishes the internal authority relationship of the firm and its environmental fit causing firm disruptions and consequently poor post-succession performance (Ishak et al., 2013; Sun et al., 2020). In addition, frequent CEO changes can result in losing the firm’s competitive edge against its competitors due to losing knowledgeable senior managers (Sun et al., 2020). New CEOs as noted in previous studies face the “liability of newness” which is lacking the knowledge of the role and the understanding of its tasks (Zhang and Qu, 2016).

A study conducted by Korn Ferry International shows poor post–succession performance after comparing firms with CEO successions to those retaining their CEOs (Ghazali, 2012; Ishak et al., 2013). Similarly, Weisbach (1988) shows that both firms’ operating performance and stock returns are negatively related to CEO succession (Geddes and Vinod, 1997). In addition, Zhang et al. (2019) find that changes in CEO’s attributes lead to a significant negative impact on the post-succession firm performance. The study also concludes that CEO successions are disruptive events and that changes in CEO successor attributes increase the firm’s post-succession disruptions leading to negative post-succession ROA. Moreover, Sun et al. (2020) conclude that CEO succession has a significant positive impact on the firm’s short-term accounting performance and a significant negative impact on the firm’s short-term market performance. While a significant negative impact on the firm’s long-term accounting and market performance.

As a result, CEO succession should be a primary concern for organizations as it influences the firm’s performance (Ishak et al., 2013). However, CEO succession planning should reduce the disruptions caused by the succession process. Lacking proper CEO succession planning forces the firms to select a CEO who may not be competent with the firm’s goals and causes early successor departure (Zhang and Rajagopalan, 2004; Zhang and Qu, 2016). Furthermore, having proper succession planning allows new CEOs to rapidly use their knowledge and information and integrate it into the firm (Georgakakis and Ruigrok, 2017).

2.2 Theoretical Background

The Upper Echelons Theory (UET) claims that CEO’s decisions and actions are affected by their personalities, cognitive abilities, and demographic characteristics, which subsequently affect their values, behavior, and perceptions (Hambrick and Mason, 1984; Von den Driesch et al., 2015; Wang et al., 2016; Minh Ha et al., 2021). Besides, it is stated that information about the individual’s human capital, characteristics, skills, backgrounds, and abilities is critical to fully analyze and understand the CEO succession process (Cragun et al., 2016). Moreover, the agency theory explains the impact of different CEO characteristics on the firm’s short-term performance (Zhang, 2010; Knutsson, 2015). The theory states that to enhance a firm’s performance, agency costs and their accompanying problems should be mitigated (Udayasankar, 2008). For instance, Fama (1980) concludes a negative relationship between CEO age and the firm’s performance. The study states that as CEOs age, they seek to serve their interests and financial benefits rather than their principals’ interests. Younger CEOs, on the other hand, have higher career concerns and thus seek to serve their principals and reduce agency problems to maintain their reputations (Zhang, 2010; Knutsson, 2015).

Further, the Resource Dependence Theory (RDT) claims that the CEO’s characteristics and qualifications are considered important resources to the firm from two different aspects. First, their human capital quality, further explained by the human capital theory, claims that employees’ characteristics, skills, and backgrounds affect their cognitive ability and performance efficiency. CEOs’ human capital qualities may add unique qualifications to their firms. Human capital theory mentions that the CEO’s attributes additionally affect the firm’s reputation, influencing its ability to access different required resources and hence enhance the firm’s performance. Second, their relational capital quality, which is their ability to access different required resources that facilitates the firm’s ability to achieve its goals (Udayasankar, 2008; Farag and Mallin, 2018; Harymawan et al., 2019; Romano et al., 2020b; Harris and Brown, 2021). The RDT helps understand how different CEO attributes can influence their ability to access different resources and consequently benefit the firm’s performance (Mukherjee and Sen, 2022). Finally, the CEO’s characteristics also affect their ability to integrate accessed information and knowledge and accordingly, their ability to effectively use it in enhancing the firm’s performance (Harymawan et al., 2019).

H₁There is a significant relationship between CEO succession and the firm’s post-succession asset utilization.

H₂There is a significant relationship between CEO succession and the firm’s post-succession liquidity.

2.3 CEO Attributes

2.3.1 CEO Origin:

Various studies have been conducted on the impact of CEO origin on the firm’s post-succession performance. However, the results are yet inconclusive (Ishak et al., 2013; Georgakakis and Ruigrok, 2017; Choi et al., 2022). Studies claim that outsider CEO successors increase agency problems and agency costs by having higher information asymmetry. Outsider CEO successors’ prior behavior, performance, and the extent of their fitting within the organization are ambiguous (Zhang and Qu, 2016). In addition, they increase the firm’s post-succession disruptions as they need time to understand and adapt to their new firm’s environment and strategies leading to poor post-succession performance (Georgakakis and Ruigrok, 2017). However, Outsider CEO successors are considered experienced “Agents of change”, with a probability of having previous CEO experience (Bigley and Wiersema, 2002; Hamori and Koyuncu, 2015). They also increase the firm’s accessibility to different external resources from their external connections and prior job experiences, enhancing the firm’s performance as the RDT claims (Udayasankar, 2008; Harris and Brown, 2021). Le and Kroll (2017) find that outsider CEOs have a significant positive impact on both firm performance and strategic change. While Serra et al. (2016) find that outsider CEOs do not enhance the firms’ post-succession profitability, productivity, and operational efficiency.

On the other hand, insider CEO successors are aware of the firm’s culture and strategies and have been promoted based on their observed behavior and performance hence decreasing the adverse selection cost. In addition, demographic differences between the successor and the board – which may cause future disruptions – are mostly eliminated through their prior interactions, hence ensuring the firm’s post-succession stability. Therefore, insider successions are considered less disruptive especially if proper relay succession planning is considered (Kesner and Sebora, 1994; Shen and Cannella, 2002; Zhang and Rajagopalan, 2004; Zhang and Qu, 2016; Georgakakis and Ruigrok, 2017; Garcia-Blandon et al., 2019; Saidu, 2019; Wang, 2021; Choi et al., 2022). Qi (2011) concludes that insider successors with appropriate succession plans are the solution to enhancing the firm’s post-succession performance. However, insider CEOs’ prior connections with the board may affect the CEO selection process. The board of directors may just prefer the familiar candidate which will subsequently limit adding new firm perspectives (Hambrick and Mason, 1984; Garcia-Blandon et al., 2019; Wang, 2021). Saidu (2019) finds that insider CEOs have a significantly positive relationship with the firm’s ROA, ROE, and stock market price. In addition, Zhang and Qu (2016) find that insider CEOs have a significantly lower negative ROA compared to their outsider counterparts decreasing the negative impact of succession on the firm’s performance.

Finally, few studies find no significant difference between CEOs’ origin and firm performance concluding that the firm’s post-succession value decreases regardless of the CEO successor’s origin (Choi et al., 2022). Mohammad et al. (2020) conclude that CEO origin has an insignificant impact on the firm’s ROA, ROE, and ROS.

2.3.2 CEO Gender:

It is claimed that male and female CEOs have different leadership and communication styles. Male CEOs are known for controlling and giving orders to their subordinates, a leadership style known as “Hegemonic masculinity”. While female CEOs tend to be interactive and collaborative with their employees, inspiring a shared management style where everyone is inspired to participate and share information. In addition, male CEOs find communication and conflict confrontation challenging to attain. While female CEOs approach conflicts by communicating and weighing both emotional and personal factors to ensure maintaining better relationships between employees (Ashcraft, 1999; Zhang and Qu, 2016; Alqatamin, 2018; Byrne et al., 2021).

Accordingly, the change in CEO gender creates a gap and causes disruptions in the leadership and communication styles, hence, negatively affecting the firm’s performance (Finkelstein et al., 2009; Zhang and Qu, 2016; Zhang et al., 2019). Zhang and Qu (2016) find that different-gender CEO successions (male to female) have lower post-succession ROA compared to same-gender CEO successions. Finally, Davis et al. (2010) find that female CEOs have better ROI, profits, profits growth, and sales growth compared to their male counterparts.

2.3.3 CEO Age:

The impact of CEO age on the firm’s performance has also been a controversial issue during the past decades with conflicting results. Age is claimed to affect the individual’s cognitive ability and thus the decision-making process (Serfling, 2014; Belenzon et al., 2019; Burney et al., 2021; He et al., 2022). The UET claims that age affects the individual’s human capital quality and capabilities and hence the firm’s performance (Hambrick and Mason, 1984; Zhang, 2010; Wang et al., 2016; Burney et al., 2021; Minh Ha et al., 2021). Scholars claim that older CEOs have better firm performance, as they have more knowledge, greater experience, and better managerial skills. Thus, older CEOs are considered better human capital with better-expected firm performance as the human capital theory and the UET claim (Hambrick and Mason, 1984; Henderson et al., 2006; Herrmann and Datta, 2006; Zhang, 2010; Knutsson, 2015; Von den Driesch et al., 2015; Serra et al., 2016; Wang et al., 2016; Burney et al., 2021; Minh Ha et al., 2021; Zhao, 2021). Wang et al. (2016) conclude that CEO age has a significant positive relationship with firms performance measured by ROA, ROE, net income, and sales growth. Similarly, Kokeno and Muturi (2016) find a significantly positive relationship between CEOs’ age and firms’ performance. Likewise, Peni (2014) finds a significantly positive relationship between CEO age and ROA and an insignificant relationship with Tobin’s Q.

On the contrary, other scholars claim that younger CEOs perform better than their older counterparts. Researchers find that CEO’s career concerns shrink as they approach retirement age, and therefore firm’s performance is negatively influenced (Dechow and Sloan, 1991; Barker and Mueller, 2002; Zhang, 2010). Likewise, unlike old CEOs, young CEOs have higher concerns about their reputation in the labor market to ensure a better career path for themselves and thus try to enhance their firms’ performance (Burney et al., 2021). Additionally, Belenzon et al. (2019) find a significantly negative relationship between CEOs’ age and firms’ ROA and sales growth. Moreover, Serra et al. (2016) find that the CEO’s age has a significantly negative impact on both the firm’s ROA and EBITDA. Furthermore, Serfling (2014) finds that the CEO’s age has a significantly negative relationship with the firm's three-year average sales-to-operating income ratio. However, Liu and Jiang (2020) and Mukherjee and Sen (2022) find that CEO age has an insignificant impact on the firm’s performance. Likewise, Phan et al. (2017) find a non-linear relationship between CEO’s age and the firm’s performance. Finally, Kirchmaier and Stathopoulos (2008) find an insignificantly negative relationship between CEO’s age and both short-term and long-term ROA and ROE.

2.3.4 CEO Education:

The UET and the human capital theory claim that highly educated executives are better human capital and of higher quality to the firm. Hambrick and Mason (1984) state that an executive’s cognitive abilities, skills, and knowledge depend on his educational level. In addition, Highly educated CEOs are considered to be more effective managers, with higher skills and better ability to gather and integrate internal and external resources, which is an additional capital to the firm based on the RDT (Barker and Mueller, 2002; Serra et al., 2016; Wang et al., 2016; Garcia-Blandon et al., 2019; Saidu, 2019; Ghardallou et al., 2020; Zappalà, 2020; Minh Ha et al., 2021; He et al., 2022).

Most of the studies on the relationship between the CEO’s education level and the firm’s performance conclude a positive relationship. It is claimed that higher education provides better managerial knowledge, higher prospects of success, and greater firm stability. Thus, highly educated CEOs are expected to have better firm performance (Ghardallou et al., 2020). Saidu (2019) finds that CEO education is an important managerial qualification that enables a better decision-making process and thus has a significant impact on the firm’s performance. Similarly, Kokeno and Muturi (2016) and Datta and Rajagopalan (1998) find a significant positive relationship between the CEO’s education levels and the firm’s performance. Moreover, Wang et al. (2016) find that CEO’s formal education level has a significant positive relationship with the firm’s ROA, ROE, net income, and sales growth. Further, Bertrand and Schoar (2003) find a positive relationship between MBA holding and the firm’s ROA. Finally, Rajagopalan and Datta (1996) find that CEO education is an important managerial qualification that enables a better decision-making process and thus has a significant impact on the firm’s performance.

However, Mukherjee and Sen (2022) conclude that CEO education has an insignificant impact on the firm’s ROA. Similarly, Ghardallou et al. (2020) find that CEO education level has an insignificant impact on the firm’s ROA and ROE, while a significant positive effect on the firm’s Tobin’s Q. While Serra et al. (2016) find a significant negative impact on EBITDA, while an insignificant impact on the firm’s ROA, concluding that higher formal education does not enhance the firm’s performance. Finally, Ofe (2012) finds no relationship between CEO’s postgraduate degrees and the firm’s performance measured using ROA.

2.3.5 CEO Experience:

The UET states that experience is one of the key characteristics that should be considered when hiring CEOs. Experience enhances the CEOs’ communication, collaboration, and managerial abilities, which qualifies them for better decision-making and hence the firm’s performance. CEO’s experience shapes the wisdom, skills, knowledge, and cognitive ability required for efficient information interpretation and utilization. It is also mentioned that CEOs with higher experience decrease the agency problem and agency costs as they can better understand the surrounding environment and the stakeholders’ needs. Moreover, experienced CEOs are better at tackling the firm’s expected future problems, which will subsequently enhance the firm’s performance (Hambrick and Mason, 1984; Bigley and Wiersema, 2002; Henderson et al., 2006; Herrmann and Datta, 2006; Farag and Mallin, 2018; Serra et al., 2016; Wang et al., 2016; Minh Ha et al., 2021).

Further, CEOs with diverse experiences in different firms or on different boards facilitate the firm’s accessibility to different required resources through their connections from their prior experiences. Based on the RDT this enhances the firm’s performance. In addition, experienced CEOs are considered more prestigious and powerful, attracting better human capital quality to the firm and thus improving the firm’s performance (Bigley and Wiersema, 2002; Serra et al., 2016; Wang et al., 2016; Minh Ha et al., 2021). Various studies support the UET, RDT, and human capital theory concluding a positive relationship between CEO experience and the firm’s performance. Harymawan et al. (2019) find a significantly positive relationship between CEO tenure and the firm’s ROA, ROE, and ROS. Similarly, Wang et al. (2016) conclude that CEO experience has a significant positive impact on the ROA, ROE, net income, and sales growth. However, Serra et al. (2016) conclude that the CEO’s time in company has an insignificant negative impact on the firm’s ROA and a significantly negative relationship with EBITDA. In addition, the results find an inverted U-shape relationship between the CEO’s time in role and ROA, while a significant positive impact on EBITDA.

On the contrary, few scholars claim that powerful CEOs with high experience can increase agency problems and agency costs if not well monitored. Their long tenure in the firm may enhance their connections with the board of directors, which may eventually encourage experienced CEOs to take self-serving decisions that may not be in the principal’s best interest (Farag and Mallin, 2018; Ratri et al., 2021; Mukherjee and Sen, 2022). Likewise, others claim that according to the learning transfer theory, CEOs with prior experience hinder the firm’s post-succession performance (Hamori and Koyuncu, 2015; Ghardallou et al., 2020). The learning transfer theory states that prior CEOs tend to imitate their previous performance even if the firms are not similarly sized or operating in the same industry, hoping to transfer their prior success to their current firm. Accordingly, not considering the different environments, cultures, and new operational requirements for the success of their new firm hinders the firm’s post-succession performance (Hamori and Koyuncu, 2015; Ghardallou et al., 2020). Liu and Jiang (2020) conclude that CEO tenure has a significantly negative impact on the firm’s performance.

2.3.6 CEO Social Network:

The social network theory and the RDT claim that the CEO’s social network facilitates the CEO’s access to different information and resources through his connections (Kirchmaier and Stathopoulos, 2008). It is stated that the CEOs’ social network enhances their managerial efficiency and knowledge integration capabilities, which will subsequently enhance the firm’s efficiency and improve its performance (Kirchmaier and Stathopoulos, 2008; Horton et al., 2012; Von den Driesch et al., 2015; Harjoto and Wang, 2020). In addition, the CEO’s access to different resources improves his decision-making process and increases his power in the firm, which will subsequently influence the firm’s performance, especially in competitive environments (Von den Driesch et al., 2015; Harjoto and Wang, 2020).

Moreover, socially connected CEOs with good-quality network connections are considered more prestigious, helping their firms attract better human capital quality (Chuluun et al., 2014; Romano et al., 2020b; Griffin et al., 2021). Further, scholars claim that hiring a highly connected CEO reduces information asymmetry and consequently decreases agency problems and agency costs by decreasing the stakeholders’ concerns about the firm and its performance (Huang and Shang, 2019; Zhao, 2021). At the same time, CEOs with larger networks are more under monitoring and observation from the labor market and the public and thus more pressured to encounter the market’s expectations, enhance the firm’s performance, and prove themselves worthy (Griffin et al., 2021). Finally, larger social networks can improve the CEO succession process and guarantee a better firm-matching selected candidate (Wang, 2021). Burt (2000) has stated that social capital is an “advantage” to its owners and thus highly connected individuals have differential successes in their business and activities. Similarly, Horton et al. (2012) conclude that larger social networks allow the firm to access various resources that enhance its future profitability and performance.

On the contrary, other studies claim that the impact of the CEO’s social network on the firm’s performance could be explained by the agency theory. The agency theory argues that a higher CEO’s social network will increase the CEO’s managerial power and accordingly increase information asymmetry and agency problems, resulting in decisions serving their benefits and against their shareholders’ interest. Thus, a negative impact on the firm’s performance is expected (Kirchmaier and Stathopoulos, 2008; Horton et al., 2012; Griffin et al., 2021; Wang, 2021). Moreover, Sun et al. (2020) conclude that the CEO’s degree of network has a significant negative impact on the firm’s ROS, a significant positive impact on Tobin’s Q, and an insignificant impact on the firm’s ROA. Finally, Kirchmaier and Stathopoulos (2008) find a significantly negative relationship between the CEO’s social network and the firm’s ROA and ROE. However, Liu and Jiang (2020) conclude that the impact of CEOs’ political networks on the firm’s performance reveals mixed results.

2.3.7 CEO Busyness:

Scholars have been divided between two different beliefs in explaining the impact of busy CEOs on the firm’s performance. The first group supports the hypothesis stating that the RDT and the reputation theory explain the impact of busy CEOs on the firm’s performance, claiming that busy CEOs are more honest, reliable, reputable, and more valuable human capital. In addition, CEO busyness provides the firm with access to different required resources and hence enhances the firm’s performance (Sarkar and Sarkar, 2009; Andres et al., 2013; Kutubi et al., 2018; Harymawan et al., 2019; Ratri et al., 2021). Elyasiani and Zhang (2015) find a significantly positive relationship between directors’ busyness and the firms’ ROE, Tobin’s Q, and EBIT ratio.

The other group supports the hypothesis stating that the agency, busyness, and over-boarding theories explain the impact of busy CEOs on the firm’s performance. Scholars claim that the large number of board meetings and commitments imposed on busy CEOs will eventually force them to compromise some of their duties to fulfill others. Accordingly, CEO busyness hinders the CEO’s performance and hence the firm’s performance (Sarkar and Sarkar, 2009; Andres et al., 2013; Kutubi et al., 2018; Harymawan et al., 2019; Ratri et al., 2021). Mukherjee and Sen (2022) conclude that CEO busyness has a significant negative impact on the firm’s operating performance, while an insignificant impact on the firm’s sustainability performance. Additionally, Harymawan et al. (2019) find that CEO busyness has a significantly negative impact on the firm’s ROA, ROE, and ROS.

A third stream of research claims that the relationship between CEO busyness and the firm’s performance is nonlinear as it can have its benefits and drawbacks. They argue that a high level of director busyness is considered a valuable asset to the firm until a certain threshold where directors become over-committed (Andres et al., 2013; Kutubi et al., 2018). Sarkar and Sarkar (2009) find a significantly negative relationship between insider directors’ busyness and firms’ Market-to-Book Value, ROA, Tobin’s Q, and Net value added to assets. While a positive relationship between independent director’s busyness and the firm’s four performance measures.

Therefore, building on the pre-mentioned literature, the pre-discussed theories as well as the mentioned empirical findings, the following hypotheses are developed to test the impact of changes in the CEO successor’s attributes on the firm’s performance (ATO and OCF):

H₃There is a significant relationship between the change in the CEO successor’s attributes and the firm’s post-succession asset utilization.

H₄There is a significant relationship between the change in the CEO successor’s attributes and the firm’s post-succession liquidity.

3.1 Data and Sample

The initial sample of this study is utilized of all firms in Twenty-six Emerging Countries as identified by Morgan Stanley Capital International “MSCI ACWI & Frontier Markets Index” (2020) with available data on BoardEx[1]. Table 1 shows that 188 firms (10.9%) are listed in the Americas, 470 firms (27.2%) are listed in Europe, The Middle East, and Africa, and 1,071 firms (61.9%) are listed in Asia during the period under study. This study considers emerging markets to test the proposed hypotheses for various reasons. First, Emerging countries have transitional features and are defined as the markets moving towards higher developments and advancing economies. Second, emerging economies have underdeveloped corporate governance, accounting, and financial systems compared to developed countries, which makes such economies an interesting focus for this study to help enhance such systems. In addition, the study of emerging markets has been the trending focus of research during the past few decades since emerging economies are rapidly growing. Finally, emerging economies are very diverse in their financial, economic, institutional, and sustainability environments with fascinating multidisciplinary areas which makes studying these markets insightful to different theories and empirical evidence (Kearney, 2012).

The CEOs’ data and demographic information are derived from BoardEx from 1999 to 2019. Additionally, to ensure that the CEO successor is the one responsible for the firm’s future performance the sample of this study following Wang (2021) will not include Acting CEOs, Interim CEOs, Assistant CEOs, Deputy CEOs, Division CEOs, and Vice CEOs observations. The 1,729 firms under study have 9,498 firm-year observations and only 913 CEO succession observations (9.6% of the entire sample firm-year observations) during the period from 2000 to 2019: 86 CEO succession observations (9%) are in firms located in the Americas, 330 CEO succession observations (36%) are in firms located in Europe, The Middle East and Africa, while 497 CEO succession observations (55%) are in firms located in Asia, reflected in Table 1. Both firms’ observations whether experiencing CEO succession or not are considered in the tests to better capture the succession impact on the firm’s future performance through their comparison following Zhang et al. (2019). The study uses annual end-of-year financial data downloaded from years t_-1 to t₊₃, where t is the year of CEO succession, winsorized at the 1% and 99% levels (Harymawan et al., 2019; Zhang et al.; 2019). Finally, economic and institutional factors are downloaded from the World Bank Database over the same period.

3.2 Variables Definitions and Measurements

3.2.1 Dependent Variables

Concerning the dependent variables, annual end-of-year financial data for the period 2000 – 2019 are used. Firm performance has been measured using the firm’s asset utilization and liquidity. For the firm’s Asset Utilization/efficiency, Asset Turnover (ATO) is used and calculated by dividing total sales by total assets, while for the firm’s liquidity operating cash flow ratio (OCF) is used and calculated by dividing the cash flow from operating activities by total assets following Khurshed et al. (2005), Bhatia and Singh (2009) and Ali (2017).

Two- and three-year average post-succession firm performance is calculated to increase the validity of the results and ensure that annual outliers are not disturbing the analysis following Horton et al. (2012), Georgakakis and Ruigrok (2017), and Le and Kroll (2017). Following Zhang and Qu (2016) and Griffin et al. (2021), post-succession firm performance measures are all computed six months after the CEO succession, to ensure that the CEO successor has enough time to influence the firm’s strategies and performance (Le and Kroll, 2017; Griffin et al., 2021). This has been utilized based on the time in role for the CEO successor by the end of the financial year downloaded from BoardEx.

3.2.2 Independent Variables.

For independent variables, this study uses CEO succession (ΔCEO), a dummy variable with 1 for the CEO successor and 0 for both the predecessor CEO and when there is no change in CEOs following Ishak et al. (2013), Sun et al. (2020) and Mohammad et al. (2020). To identify the changes in CEO successor attributes, nine CEO measures capturing changes in seven CEO attributes are examined. Table 2 below shows the number of observations for the changes in each of the CEO successor attributes along with the number of increases and decreases in each attribute under study.

One of the CEO attributes utilized by this study is the CEO origin (ORIG) defining whether the CEO successor is an insider or an outsider. The change in CEO successor origin in this study and analysis demonstrates hiring an outsider CEO successor to the firm. Another CEO attribute is related to the CEO gender (GEN). This study identifies whether the CEO successor is of the same gender as the predecessor CEO or of a different gender. The aim of this paper is not merely testing whether males or females are better for the firm’s performance, but whether appointing a CEO successor of the same gender or different gender is better for the firm’s post-succession performance followingElsaid and Ursel (2011), Huang and Kisgen (2013), Elsaid (2014) and Zhang and Qu (2016).

For each of the five remaining attributes under study, the CEO successor’s attribute values are compared to the predecessor CEO’s values to identify the direction of change in CEO successor attributes, and two dummy variables are created: Increase (.INC) and Decrease (.DEC). In addition, this study considers CEO age (Age). Moreover, two measures of CEO education are employed: Number of qualifications (QUAL)identifyingthe number of certificates obtained by the CEO and postgraduate studies (PGS) which is a dummy variable with 1 if the CEO has any postgraduate degrees and 0 otherwise following Mukherjee and Sen (2022). Further, two measures of CEO experience are employed in this study. Total boards to date (TBD) to reflect the CEO’s board experience and time in company (TCOM) to reflect the CEO’s tenure. Finally, the study considers the CEO’s social network (NET), reflecting the CEO’s total number of ties and connections gained from education, previous work experiences or other activities, and CEO busyness measured by total current boards.

3.2.3 Control Variables

For all regression models under study, the pre-succession firm’s performance is one of the most important firm-specific factors that the study should control for CEO succession models. Post-succession firm performance is highly dependent on the firm’s pre-succession performance, especially if not all the post-succession firm performance variations are caught by the control variables in the models. Moreover, pre-succession firm performance can influence the CEO successor’s tendency to make changes in the firm and hence the CEO’s future firm performance (Datta and Rajagopalan, 1998; Zhang and Rajagopalan, 2004; Hamori and Koyuncu, 2015; Zhang and Qu, 2016; Le and Kroll, 2017; Mohammad et al., 2020). Pre-succession firm’s performance is expected to have a positive impact on the firm’s post-succession performance and is calculated as the one-year pre-succession firm performance (ATO_t-1 and OCF_t-1) following Kim (2005), Horton et al. (2012), Hamori and Koyuncu (2015), Zhang and Qu (2016), Georgakakis and Ruigrok (2017), Le and Kroll (2017), Zhang et al. (2019), and Sun et al. (2020).

To control for the potential of reverse causality concerns or endogeneity problems associated with the firm-specific control variables while utilizing the models, this study lags behind the independent control variables following Farag and Mallin (2018), Huang et al. (2020) and Shi and Veenstra (2020). Practically, this study considers control variables at t_0,while dependent variables are calculated on the two- and three-year average post-succession performance basis. To efficiently reflect the impact of changes in CEO successor attributes on the firm’s post-succession performance, this study additionally controls for the firm’s size and leverage following Kim (2005), Kirchmaier and Stathopoulos (2008), Ishak et al. (2013), Peni (2014), Serra et al. (2016), Zhang and Qu (2016), Alqatamin (2018), Saidu (2019), Zhang et al. (2019), Ghardallou et al. (2020), Sun et al. (2020), Mohammad et al. (2020), and Mukherjee and Sen (2022).

Firm size (SIZE) is calculated by the natural logarithm of total assets and is claimed to have a major impact on the firm’s performance (Ishak et al., 2013; Zhang and Qu, 2016; Le and Kroll, 2017). Larger firms are expected to have better firm performance than their small counterparts (Qi, 2011; Peni, 2014; Serra et al., 2016; Saidu, 2019). Moreover, larger firms are expected to have better adaptation to managerial changes and control of the firm’s post-succession responses (Mohammad et al., 2020). Additionally, the firm’s leverage (LVG) is measured by the ratio of total liabilities to total assets. The impact of the firm’s leverage on the firm’s post-succession performance has revealed mixed results (Ishak et al., 2013; Peni, 2014; Saidu, 2019; Zhang et al., 2019; Ghardallou et al., 2020).

Furthermore, all regression models under study control for several economic, institutional, and governance factors. It is claimed that macroeconomic variables may affect the decision-making process and the promptness of the firm’s strategic changes, which accordingly will influence the firm’s performance (Le and Kroll, 2017). This study controls for three main economic indicators downloaded from the World Bank Database: Gross domestic product (GDP), inflation (INF), and unemployment (UNEMP) following Bessler et al. (2013) and Belenzon et al. (2019). Additionally, Ashcraft (1999) mentioned that CEOs' decisions and actions are affected by their surrounding culture and environment. CEOs cannot be isolated from the firm’s system nor from the people they lead. Accordingly, institutional features of resistance and control affect the impact of CEO succession on the firm’s post-succession performance. Hence, this study controls the control of corruption (CORR) level downloaded from the World Bank Database.

Besides, this study controls for governance factors as previous studies claim that the firm’s governance level affects the attainment of the CEO succession process as it affects the CEO’s decisions and hence the firm post-succession performance (Weisbach, 1988; Serra and Ferreira, 2016; Zhang and Qu, 2016). This study controls the percentage of independent board members (%IND) and CEO duality (DUA) downloaded from BoardEx. Board structure, whether measured by size or number of independent directors, affects the firm’s networking ability with its external environment as it influences the firm’s risk level (Farag and Mallin, 2018). In addition, and as stated by the agency theory, the separation of the CEO and the chairman roles to two different individuals reduces agency costs as it reduces conflict of interests that may occur if only one individual is holding both positions (Romano et al., 2020a). Besides, Farag and Mallin (2018) claim that a lot of power is given to one individual if the CEO is holding the chairman position too. While Phan et al. (2017) claim that firms with CEO duality positions perform better.

Furthermore, for each change (increase or decrease) in the CEO attribute investigated, this study controls for the natural logarithm of the independent variable itself following Knutsson (2015). Finally, when testing the impact of changes in the CEO’s origin, gender, age, education, and social network variables, this study controls for the natural logarithm of the CEO’s time in company at t₀ following Serra et al. (2016). While when testing for the impact of changes in the CEO’s experience and busyness and due to the multi-collinearity between these variables and the CEO’s time in company, this study controls for the natural logarithm of the CEO’s age at t₀ following Serra et al. (2016) and Zhang and Qu (2016). Table 3 below demonstrates the dependent, independent, and control variables utilized in this paper along with their symbols and measurements.

3.3 Research Methodology

Based on Hausman’s (1978) specification test results using Stata, panel FE regression models are applied in this study. Below are the models utilized to investigate the impact of CEO succession-induced changes in CEO attributes on the firm’s post-succession performance. Finally, Fig.1 below shows a diagram of the research framework applied in this study representing all dependent, independent, and control variables.

Where,

ATTR: The natural logarithm of the CEO’s attribute under study.

CTRL.ATTR: The natural logarithm of the CEO’s time in company at t₀ (when the CEO attribute under study is the change in CEO’s origin, gender, age, education, or social network), or the natural logarithm of the CEO’s age at t₀ (when the CEO attribute under study is the change in CEO’s experience or busyness).

ΔATTR: CEO succession event, the increase, or the decrease in the CEO successor’s attribute under study.
[1] BoardEx is a private independent research firm that collects, classifies, and keeps record of all board members’ biographic, demographic and historical data in all countries around the world with information about the management team and the board members of both private and publicly listed firms. Such information provides detailed profiles about those firms’ members’ gender, age, nationality, education, degree of direct social network, indirect social networks, current and previous jobs and board experiences, their roles, their honorary positions, and all of their professional and non-professional memberships (BoardEx, 2018; Harjoto and Wang, 2020; Griffin et al., 2021; Wang, 2021).

Table 4 presents the descriptive statistics for the sample understudy during the period 2000 – 2019. The table reflects the number of observations (N), the mean, standard deviation, minimum, and maximum for the dependent variables (ATO and OCF), firm-specific variables (SIZE and LVG), economic variables (GDP, INF, UNEMP), institutional variables (CORR), and governance variables (%IND and DUA) under study. Statistics show that the mean of the two-year average effective ATO of the sample is 0.718 with a standard deviation of 0.665, a minimum of 0, and a maximum of 10.11, while the mean of the three-year average effective post-succession ATO is 0.719 with a standard deviation of 0.657, a minimum of 0 and a maximum of 9.489. Additionally, the mean of the two-year average effective OCF of the sample is 0.074 with a standard deviation of 0.115, a minimum of -2.031, and a maximum of 4.396, while the mean of the three-year average effective post-succession OCF is 0.076 with a standard deviation of 0.104, a minimum of -1.331 and a maximum of 2.928. For firm-specific variables, the average firm size is 13.847 with a standard deviation of 2.117, a minimum of 8.039, and a maximum of 18.891. Moreover, the average firm’s LVG is 0.547 with a standard deviation of 0.238, a minimum of 0.058, and a maximum of 1.278.

For the economic control variables, the average GDP is 27.531 with a standard deviation of 1.354, a minimum of 23.026, and a maximum of 30.27. The average inflation rate is 4.607 with a standard deviation of 5.932, a minimum of -4.863, and a maximum of 85.747. Further, the average unemployment rate is 8.584 with a standard deviation of 8.27, a minimum of 0.091, and a maximum of 33.473. The average rate for control of corruption, the institutional control variable in this paper, is 49.986 with a standard deviation of 14.8, a minimum of 9.596, and a maximum of 91.878. Finally, for the governance control variables, the average percentage of independent board members is 0.458 with a standard deviation of 0.188, a minimum of 0, and a maximum of 0.923. While the CEO duality has an average of 0.439 with a standard deviation of 0.496, a minimum of 0, and a maximum of 1.

To test the proposed hypotheses, the post-succession performance of opposite directions of change in CEO attributes is compared using three different models: the impact of the succession itself, the increase in the CEO successor attribute, and the decrease in the CEO successor attribute compared to the predecessor CEO. To get more insights into the impact of the changes in CEO successor attributes, the study tests the impact on two different periods: the two- and three-year average post-succession performance. Finally, to eliminate the potential bias of any existing multicollinearity, the maximum VIF score for each model is included.

Table 5 shows that the firm’s post-succession ATO is negatively related to CEO succession, hence (H1) is not rejected. For example, models 1 and 4 show -1.59 percent (significant at 5% significance level) and -1.27 percent (significant at 10% significance level) decrease in the firm’s post-succession ATO respectively. The results additionally show that hiring an insider CEO successor significantly reduces the negative impact of CEO succession on the firm’s post-succession ATO as reflected in the coefficient of model 2 denoting a -1.44 percent (significant at 10% significance level) decrease in the firm’s post-succession ATO. On the other hand, hiring an outsider CEO successor reveals mixed although insignificant results on the firm’s post-succession ATO.

Models 7 and 10 show that the firm’s post-succession OCF is negatively related to CEO succession, and hence (H2) is not rejected. The coefficients of Models 7 and 10 show -0.448 percent (significant at 10% significance level) and -0.665 percent (significant at 1% significance level) decrease in the firm’s post-succession OCF respectively. Models 8 and 11 show that hiring an insider CEO successor significantly reduces the negative impact of CEO succession on the firm’s post-succession OCF. The coefficient of Model 11 denotes a -0.439 percent (significant at 10% significance level) decrease in the firm’s post-succession OCF. On the other hand, hiring an outsider CEO successor significantly amplifies the negative impact of CEO succession on the firm’s post-succession OCF. For example, Models 9 and 12 show -1.16 percent (significant at 5% significance level) and -1.11 percent (significant at 1% significance level) decrease in the firm’s post-succession OCF respectively. The results presented in Table 5 conclude that outsider CEO successors have an insignificant impact on the firm’s post-succession asset utilization. Although, insider CEO successors have a significantly positive impact on the firm’s post-succession performance, (H3) is rejected. This conclusion is in support of scholars claiming that solely the origin of the CEO successor has an insignificant impact on the firm’s future performance (Ishak et al., 2013). Finally, the results are in support of Mohammad et al. (2020) concluding that CEO origin has an insignificant impact on the firm’s ROA, ROE, and ROS.

However, outsider CEO successors have significantly worse post-succession liquidity than insider CEO successors, amplifying the negative impact of CEO succession on the firm’s post-succession OCF. While insider CEO successors significantly reduce the negative impact of CEO succession on the firm’s post-succession OCF. Accordingly, there is a significant relationship between the change in CEO successor origin (hiring an outsider CEO successor) and the firm’s post-succession liquidity and hence (H4) is not rejected. The results are consistent with the agency theory and information asymmetry stating that outsider CEOs’ previous behavior and performance is unknown to the hiring firm, which may cause adverse selection problems and increase agency costs. Unlike insider CEO successors who are promoted based on their observed performance in the firm, and accordingly hiring an outsider CEO may lead to a negative firm performance (Zhang and Qu, 2016; Garcia-Blandon et al., 2019; Saidu, 2019; Wang, 2021).

The results are also in support of studies stating that hiring outsider CEO successors amplifies succession disruptions and leads to lower post-succession performance. While insider CEO successor’s familiarity with the firm’s culture and employees grants them an edge while reducing disruptions, and hence enhances the firm’s post-succession performance especially if proper relay succession planning is considered (Kesner and Sebora, 1994; Shen and Cannella, 2002; Zhang and Rajagopalan, 2004; Zhang and Qu, 2016; Georgakakis and Ruigrok, 2017; Garcia-Blandon et al., 2019; Saidu, 2019; Wang, 2021; Choi et al., 2022). Moreover, Serra et al. (2016) conclude that outsider CEOs do not enhance the firm’s profitability, productivity, and operational efficiency. Finally, Qi (2011) concludes that to enhance post-succession firm performance, an insider successor with an appropriate early set succession plan is the solution.

Table 6 shows that while controlling for CEO gender, both the firm’s post-succession ATO and OCF are negatively related to CEO succession, hence (H1 and H2) are not rejected. Hiring a CEO successor of a different gender reduces the negative impact of CEO succession on the firm’s post-succession ATO although the results are insignificant. On the other hand, hiring a CEO successor of the same gender significantly amplifies the negative impact of CEO succession on the firm’s post-succession ATO. For example, the coefficient of Model 3 shows a -1.64 percent (significant at 5% significance level) decrease in the firm’s post-succession ATO. The results conclude that the change in the CEO successor’s gender has an insignificant impact on the firm’s post-succession performance. Although, CEO successors of the same gender have a significantly negative impact on the firm’s post-succession performance, (H4) is rejected.

In addition, the coefficients of Models 8 and 11 show that hiring a CEO successor of a different gender significantly amplifies the negative impact of CEO succession on the firm’s post-succession OCF. For example, the coefficient of Model 11 is -1.48 percent (significant at 5% significance level) decrease in the firm’s post-succession OCF. On the other hand, the coefficient of Model 12 is -0.562 percent (significant at 5% significance level) decrease in the firm’s post-succession OCF, which demonstrates that hiring a CEO successor of the same gender significantly reduces the negative impact of CEO succession on the firm’s post-succession OCF.

The results conclude that the change in CEO successor's gender has a significantly negative impact on the firm’s post-succession liquidity amplifying the negative impact of CEO succession on the firm’s post-succession liquidity and thus (H4) is not rejected. These results are in support of the pre-mentioned literature stating that male and female CEOs have different leadership, managerial, and communication styles. Thus, hiring a CEO of a different gender may increase CEO succession disruptions and negatively affect the firm’s post-succession performance (Finkelstein et al., 2009; Zhang and Qu, 2016; Zhang et al., 2019).

Table 7 shows that while controlling for CEO age, both the firm’s post-succession ATO and OCF are negatively related to CEO succession, and hence (H1 and H2) are not rejected. The results show that hiring an older CEO successor reduces the negative impact of CEO succession on the firm’s post-succession ATO, although the results are insignificant. While hiring a younger CEO successor significantly amplifies the negative impact of CEO succession on the firm’s post-succession ATO. For example, the coefficient of Model 3 shows a -2.26 percent (significant at 5% significance level) decrease in the firm’s post-succession ATO. Additionally, the findings presented in Models 7 and 10 show that hiring an older CEO successor reduces the negative impact of CEO succession on the firm’s post-succession OCF although the results are insignificant. On the other hand, hiring a younger CEO successor significantly amplifies the negative impact of CEO succession on the firm’s post-succession OCF. For example, the coefficients of Models 9 and 12 show -0.625 percent (significant at 5% significance level) and -0.842 percent (significant at 1% significance level) decrease in the firm’s post-succession OCF respectively.

The results conclude that the direction of change in the CEO successor’s age is significantly positively related to the firm’s post-succession asset utilization and liquidity. Accordingly, hiring a younger CEO successor results in amplifying the negative impact of CEO succession on the firm’s post-succession asset utilization. Thus, (H3 and H4) are not rejected, signifying that hiring older CEO successors have better post-succession performance than hiring younger CEO successors. The results are in support of the UET and the human capital theory, stating that the CEO’s age affects his human capital quality and capabilities, and thus the firm’s performance. The results also support studies stating that older CEOs have more knowledge, greater experience, and better managerial skills and are thus considered better human capital with better-expected firm performance (Hambrick and Mason, 1984; Henderson et al., 2006; Herrmann and Datta, 2006; Zhang, 2010; Knutsson, 2015; Von den Driesch et al., 2015; Serra et al., 2016; Wang et al., 2016; Burney et al., 2021; Minh Ha et al., 2021; Zhao, 2021). Likewise, these results are in support of Peni (2014), Kokeno and Muturi (2016), and Wang et al. (2016).

Table 8 shows that while controlling for the CEO successor’s number of qualifications and postgraduate studies as presented in Panels A and B respectively, both the firm’s post-succession ATO and OCF are negatively related to CEO succession, thus (H1 and H2) are not rejected. As shown in Panel A, hiring a CEO successor with a lower education level significantly amplifies the negative impact of CEO succession on the firm’s post-succession ATO and OCF. For example, the coefficients of Models 3, 9, and 12 are -2.38 percent (significant at 10% significance level), -2.07 percent (significant at 1% significance level), and -1.87 percent (significant at 1% significance level) decrease in the firm’s post-succession performance respectively.

Furthermore, panel B shows that post-graduate degrees on the other hand have an insignificant impact on ATO. Accordingly, the direction of change in the CEO successor’s education reveals mixed results and hence (H3) is rejected. This shows that the number of CEO certificates influences the CEO’s cognitive ability and competence, which affects the firm’s asset utilization efficiency, however having a post-graduate degree does not have a significant impact on the CEO’s management efficiency. The results are in support of Ofe (2012), Serra et al. (2016), Ghardallou et al. (2020), and Mukherjee and Sen (2022) concluding that holding any postgraduate certificate has an insignificant impact on a firm’s performance. Finally, the results demonstrate that hiring a CEO successor without postgraduate degrees following a degree-holder CEO predecessor significantly amplifies the negative impact of CEO succession on the firm’s post-succession OCF. For example, the coefficients of Models 9 and 12 are -2.10 percent (significant at 1% significance level) and -1.15 percent (significant at 5% significance level) decrease in the firm’s post-succession OCF respectively. The results presented in Table 8 show that the direction of change in both CEO successor’s education measures is significantly positively related to post-succession liquidity. Thus, (H4) is not rejected.

The results are in support of the UET and the human capital theory claiming that education is an important managerial qualification, and hence highly educated executives are better human capital and of higher quality to the firm and thus can enhance the firm’s future performance. The results also support the RDT claiming that highly educated CEOs have better skills and cognitive ability to gather and integrate internal and external resources. Such capabilities help highly educated CEOs make better decisions and enhance the firm’s performance (Hambrick and Mason, 1984; Rajagopalan and Datta, 1996; Barker and Mueller, 2002; Serra et al., 2016; Wang et al., 2016; Garcia-Blandon et al., 2019; Saidu, 2019; Ghardallou et al., 2020; Zappalà, 2020; Minh Ha et al., 2021; He et al., 2022). Likewise, the results support Bertrand and Schoar (2003) claiming that CEOs with postgraduate degrees enhance the firm’s performance. Finally, the results are in support of Datta and Rajagopalan (1998) and Kokeno and Muturi (2016).

Table 9 demonstrates that while controlling for different CEO experience measures (CEO total number of boards to date and time in company) as shown in Panels A and B respectively, the firm’s post-succession ATO and OCF are negatively related to CEO succession, therefore (H1 and H2) are not rejected. The results additionally show that hiring a CEO successor with higher experience reduces the negative impact of CEO succession on the firm’s post-succession ATO, although the results are insignificant. Quite the opposite, the results show that hiring a CEO successor with less experience significantly amplifies the negative impact of CEO succession on the firm’s post-succession ATO. For example, the coefficients of Models 3 and 6 Panel A demonstrate -3.00 percent (significant at 1% significance level) and -3.14 percent (significant at 1% significance level) decrease in the firm’s post-succession ATO respectively. Additionally, the coefficient of Model 6 Panel B demonstrates a -1.72 percent (significant at 10% significance level) decrease in the firm’s post-succession ATO.

Moreover, hiring a CEO successor with larger board experience significantly reduces the negative impact of CEO succession on the firm’s post-succession OCF. While, hiring a CEO successor with more company tenure reduces the negative impact of CEO succession on the firm’s post-succession OCF, although the results are insignificant. However, hiring a CEO successor with less board experience or less company tenure significantly amplifies the negative impact of CEO succession on the firm’s post-succession OCF. The results show that hiring a CEO successor with less experience significantly amplifies the negative impact of CEO succession on both the firm’s ATO and OCF, hence (H3 and H4) are not rejected. The results are in support of the UET stating that experience affects the individual’s decision-making process and hence the firm’s performance; as it shapes the CEO’s wisdom, skills, knowledge, and cognitive ability required for efficient information interpretation and utilization. (Hambrick and Mason, 1984; Henderson et al., 2006; Herrmann and Datta, 2006; Serra et al., 2016; Wang et al., 2016; Farag and Mallin, 2018; Minh Ha et al., 2021).

In addition, the results support the RDT claiming that experienced CEOs facilitate the firm’s access to different required resources through their connections which subsequently enhances the firm’s performance. Moreover, experienced CEOs are considered more prestigious and powerful attracting better human capital to the firm and thus improving the firm’s performance as the human capital theory claims (Bigley and Wiersema, 2002; Serra et al., 2016; Wang et al., 2016; Minh Ha et al., 2021). The results also support the claim that CEOs with higher experience decrease agency problems and agency costs. This is explained by the implication that they can better understand the surrounding environment and the stakeholders’ needs which will subsequently enhance the firm’s performance (Bigley and Wiersema, 2002; Henderson et al., 2006; Herrmann and Datta, 2006; Serra et al., 2016; Wang et al., 2016; Farag and Mallin, 2018). Finally, the results are in support of Harymawan et al. (2019) and Wang et al. (2016).

Table 10 demonstrates that while controlling for the CEO social network, both the firm’s post-succession ATO and OCF are negatively related to CEO succession, and hence (H1 and H2) are not rejected. The findings show that hiring a CEO successor with a larger social network reduces the negative impact of CEO succession on the firm’s post-succession ATO, although the results are insignificant. On the other hand, the results show that hiring a CEO successor with a smaller social network significantly amplifies the negative impact of CEO succession on the firm’s post-succession ATO as demonstrated in Model denotes -1.89 percent (significant at 10% significance level) decrease in the firm’s post-succession ATO. Finally, the results demonstrate that hiring a CEO successor with a larger social network significantly reduces the negative impact of CEO succession on the firm’s post-succession OCF. For example, the coefficient of Model 11 shows a -0.638 percent (significant at 5% significance level) decrease in the firm’s post-succession OCF. On the other hand, the coefficients of Models 9 and 12 show -1.09 percent (significant at 1% significance level) and -0.770 percent (significant at 5% significance level) decrease in the firm’s post-succession OCF respectively.

The results conclude that the direction of change in the CEO successor’s social network is significantly positively related to both the firm’s ATO and OCF and thus (H3 and H4) are not rejected. Moreover, the results are consistent with Burt (2000) stating that social capital is an “advantage” to its owners, and thus highly connected CEOs have differential successes in their business and activities. Likewise, the human capital theory claims that socially connected CEOs with good quality network connections are considered prestigious, helping their firms attract better human capital quality (Chuluun et al., 2014; Romano et al., 2020b; Griffin et al., 2021). The results also support the claim that CEOs with larger networks are more pressured to meet the market’s expectations, enhance the firm’s performance, and prove themselves worthy (Griffin et al., 2021).

Furthermore, the results are in support of both the social network theory and the RDT claiming that the CEO’s social network facilitates the CEO’s accessibility to different information and resources through his connections. Thus, it is considered a critical resource and an asset as it improves the CEO’s decision-making process and increases his power in the firm, which improves the firm’s performance. In other words, the CEO’s social network allows him to access cheaper resources and hence effectively manage the firm’s expenses and enhance the firm’s performance (Harjoto and Wang, 2020; Kirchmaier and Stathopoulos, 2008; Von den Driesch et al., 2015; Romano et al., 2020b). The results also support the literature claiming that hiring highly connected CEOs reduces information asymmetry and adverse selection costs and consequently decreases agency costs by decreasing the stakeholders’ concerns about the firm and its future performance (Huang and Shang, 2019; Wang, 2021; Zhao, 2021). Finally, the results are in support of Kirchmaier and Stathopoulos (2008), Horton et al. (2012), and Sun et al. (2020).

Table 11 shows that while controlling for CEO busyness, both the firm’s post-succession ATO and OCF are negatively related to CEO succession, accordingly (H1 and H2) are not rejected. Additionally, the coefficients of Models 2, 5, 8, and 11 show -4.56 percent (significant at 1% significance level), -4.1 percent (significant at 1% significance level), -1.37 percent (significant at 1% significance level), and -1.2 percent (significant at 1% significance level) decrease in the firm’s post-succession ATO and OCF respectively. The results signify that hiring a busier CEO successor significantly amplifies the negative impact of CEO succession on the firm’s post-succession asset utilization and liquidity. However, hiring a less busy CEO reveals mixed significant results on the firm’s post-succession ATO, and thus (H3) is rejected.

While hiring a less busy CEO successor significantly reduces the negative impact of CEO succession on the firm’s post-succession liquidity, as shown by the coefficient of Model 12, signifying a -0.848% percent (significant at 5% significance level) decrease in the firm’s post-succession OCF, thus (H4) is not rejected. The results are in support of the agency, busyness, and over-boarding theories claiming that the large number of board meetings and commitments imposed on busy CEOs will eventually force them to compromise some of their duties to fulfill others. Accordingly, CEO busyness hinders the firm’s performance (Sarkar and Sarkar, 2009; Andres et al., 2013; Kutubi et al., 2018; Harymawan et al., 2019; Ratri et al., 2021). Finally, the results are in support of Mukherjee and Sen (2022) and Harymawan et al. (2019).

Using FE regression models, the findings show that while controlling for different CEO attribute measures across different models, CEO succession has a significant negative impact on all firms’ post-succession performance. Moving to the firm-specific control variables, for both ATO and OCF, the pre-succession firm performance is significantly positively related to the firm’s post-succession performance supporting Kim (2005), Horton et al. (2012), Hamori and Koyuncu (2015), Zhang and Qu (2016), Georgakakis and Ruigrok (2017), Le and Kroll (2017), Zhang et al. (2019), and Sun et al. (2020) results. Merely for some of the three-year post-succession OCF models, the pre-succession firm performance is positively, although insignificantly, related to the post-succession OCF. In addition, SIZE is significantly negatively related to both performance measures, contradicting the aforementioned literature.

Moreover, concerning the asset utilization measure (ATO), in all models, LVG is significantly positively related to the firm’s post-succession ATO. The results are consistent with Ishak et al. (2013) and Zhang et al. (2019) results. On the contrary, for the liquidity measure (OCF), in all models, LVG is significantly negatively related to the post-succession OCF in support of Peni, (2014), Saidu (2019), and Ghardallou et al. (2020). Finally, multi-collinearity is not a problem; all variables’ scores are less than 2.5, which is within all differently stated acceptable parameters (Menard, 2002; Vittinghoff et al., 2006; Gareth et al., 2013; Johnston et al., 2018).

This paper comprehensively examines the impact of the changes in CEO successor’s attributes associated with CEO succession taking place between 2000 and 2019 on the firm’s post-succession performance. The study uses a comprehensive sample of 1,729 firms in twenty-six emerging countries. The sample yields 9,498 firm-year observations embracing 913 CEO successions. This paper captures the impact of a wide range of CEO attributes on the firm’s post-succession ATO and OCF. To get more insights into the impact of the changes in CEO successor attributes, performance measures are calculated on the two- and three-year average post-succession performance basis. In all the tests, this study controls for the one-year pre-succession firm’s performance, firm size, and firm’s leverage ratio. In addition, as this study consists of panel data from different companies located in different countries, this study controls for economic factors (GDP, INF, and UNEMP), institutional factors (CORR), and governance factors (%IND and DUA). Additionally, for each change (increase or decrease) in each independent CEO demographic variable investigated, this study controls for the independent variable under study following Knutsson (2015). Finally, when testing the impact of changes in the CEO’s origin, gender, age, education, and social network variables, this study controls the CEO’s time in company. While controlling the CEO’s age when testing for the impact of changes in the CEO’s experience and busyness.

The overall findings disclose that while controlling for different CEO attributes across different models, CEO succession has a significant negative impact on both the firm’s post-succession asset utilization and liquidity. For the firm’s post-succession asset utilization, the direction of change in the CEO successor’s age, experience, and social network has a significant positive impact on the firm’s post-succession asset utilization. While the change in the CEO successor’s origin, gender, education, and busyness has revealed insignificant and mixed results on the firm’s post-succession asset utilization. Moreover, the direction of change in the CEO successor’s age, education, experience, and social network has a significant positive impact on the firm’s post-succession liquidity. Finally, the change in the CEO successor’s origin, gender, and busyness has a significant negative impact on the firm’s post-succession liquidity.

This paper is a cross-disciplinary study that has important implications for various fields by combining different financial, accounting, human resources, strategic, and psychology concepts. Besides, the findings have beneficial implications for regulators and policymakers to enhance the firm’s corporate governance practices and future performance. Firms should understand that CEO succession events may not only fail to enhance the firm’s post-succession performance but may be detrimental when not considering the CEO successor’s attributes. Accordingly, this paper addresses a topic that is vital for boards, CEO selection committees, and hiring firms. The results provide practitioners with a set of factors that may be useful at the time of CEO succession planning and during the hiring process. Moreover, this paper helps firms select the best-fit CEO successor who will be mostly willing to apply the required policies and achieve their future goals based on their designated plan and focus during a specific period.

Even though this study uses a large sample and numerous control variables, nevertheless it comes with limitations and suggests intriguing avenues for future research. This study has considered some of the most used control variables in cross-country studies. However, emerging countries are also very diverse in cultures and backgrounds (Kearney, 2012). Moreover, like most of the existing succession studies, this study investigates the impact of CEO succession up to three years after the succession. Hence, this study cannot tell whether the indicated impacts continue beyond this period. Accordingly, future research may consider cultural factors such as (masculinity, uncertainty avoidance, etc.), as different CEO attributes in different cultures may have different impacts on the CEO successor’s performance and subsequently the firm’s post-succession performance. Likewise, future studies can consider the magnitude of the changes in CEO successor’s attributes compared to the predecessor CEO, to have further insights into their impact on the firm’s post-succession performance. Future research should also test the changes in CEO attributes interactions and their impact on the firm’s post-succession performance. Further, future research can additionally apply quantile regression models to investigate the different effects of changes in CEO successor’s attributes on high-performing and low-performing firms. Finally, future research should assess the findings in developing and developed countries and compare the results across different markets.

The authors declare that they have not received any financial benefits in any form for writing this paper. In addition, the authors declare that they do not have any non-financial interests in any subject discussed in this article.

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The Nexus Between Changes in CEO Successor’s Attributes and Firm Performance: Evidence from Emerging Countries

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1. Introduction

2. Literature Review and Hypotheses Development

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3.2.1 Dependent Variables

3.2.2 Independent Variables.

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