Goal clarity on the relationship between government ownership and financial performance of the listed companies in Kenya and Tanzania

Abstract This study investigates the moderating effect of company goal clarity on the relationship between government ownership and financial performance of the listed companies in Kenya and Tanzania. The results show that government ownership holds an average of 6% of the ownership stakes and a maximum of 74% in the selected listed companies. Furthermore, it is found that, listed companies that engage in goal-setting, pursue an average of 5 company goals concurrently, and a maximum of 13. Moreover, government ownership is found to be negatively related to financial performance, while a decrease in company goal clarity is both positively and negatively related to financial performance, for the Tobin’s q and the risk-adjusted ROA models, respectively. The implication is that, as government ownership in emerging economies is endowed with relatively more skills and resources compared to other owners in listed companies, it can effectively pursue a relatively higher number of company goals. The results also suggest that a decrease in goal clarity has a negative moderating effect on the relationship between government ownership and financial performance, whereby the moderating effect reduces the magnitude of the negative effects of government ownership on financial performance, up to an optimal point of seven company goals. The decrease of company goal clarity, which mainly emanates from the concurrent pursuit of all company goals plus the social welfare ones, reduces the negative effects of the ownership on financial performances, contrary to the assertions made in the goal-setting theory.


Introduction
Ownership structures in listed companies are known to have implications on financial performances (Arslan, 2021;Din et al., 2021) and how the companies are governed. The ownership structures are most often composed of a mixture of different ownership types, each with specific performance goals or interests. For example, government ownership in a listed company is known to pursue mainly political and social economic goals, while institutional ownership aims to maximize profits (Thomsen & Pedersen, 2000). Consequently, to differentiate the effects of each ownership type on financial performance, most studies, like Liu (2018) and Sunday et al. (2017), measure the ownership types by using a fraction, which is computed based on the amount of equity capital contributed by an ownership type, relative to the total equity capital of the listed company concerned. It is therefore known that, amongst the different owners in listed companies, government prefers to be the largest (Liu, 2018), in order to enjoy more controls and influence on performance, relative to other owners. This is because, governments are known to provide governmental support and political connections to the listed companies in which they have ownership stakes (Mei, 2013). Moreover, for the listed companies operating in emerging markets, government ownership is also known to set company financial goals, which are meant to guide towards the intended financial performances (Wei, 2020). However, most research studies on the relationship between government ownership and financial performance, like Alfaraih et al. (2012) and Laporšek et al. (2021), show that government ownership is associated with inferior financial performances relative to other ownership types. Principally, most of these studies focus on the direct relationship between government ownership and financial performance, without considering the potentials of company goals to moderate the relationship.
Company goals are meant to guide stakeholders towards a specific performance outcome through the goal clarity dimension. The dimension is defined as an emphasized degree of quantitative precision, outlined in a goal to reduce performance variability (Bang et al., 2010). It can be measured by the number of company goals pursued by an organization, whereby the higher the number of goals pursued the lower the clarity (Jung, 2011). Most studies on this goal dimension, such as Van der Hoek et al. (2018) and Bang et al. (2010), mainly focus on the direct relationship between goal clarity and organizational performance in the developed markets. Consequently, the empirical knowledge on this relationship falls short of at least two main important components: first, the emerging markets' contextual experience, and secondly, knowledge on the moderating role of goal clarity on the relationship between government ownership and financial performance of the listed companies operating in both emerging and developed markets. This knowledge is important based on the fact that, listed companies in emerging markets rely much on ownership structures to enhance financial performances. The reliance is generally based on listed companies' non-compliance to corporate governance practices in emerging markets (Arslan & Alqatan, 2020), due to the markets being characterized with relatively weak legal systems (Claessens & Yurtoglu, 2013). Moreover, government ownership priorities have always been ambiguously unpredictable, as it sometimes pursues political and social welfare goals to serve communities (Loch et al., 2020), while in other cases, it pursues profitability to ensure going concern (Makhlouf & Al-Sufy, 2018;Wei, 2020) in listed companies. Consequently, this kind of confusion makes goal clarity an important dimension to include in the current study.
In some of the emerging markets within the East African Community (EAC) area, government ownership is at times among the listed company owners with significant ownership stakes. In these markets, investors are sometimes concerned over the general financial performances of listed companies (Anyanzwa, 2018;CMA, 2018), which may consequently discourage potential investors. Moreover, the equity market capitalization values of some listed companies seem to regularly decline (CMSA, 2017(CMSA, , 2019DSE, 2019DSE, , 2020. Based on these financial performance observations, we ask three main questions: firstly, how does government ownership relate to financial performance of the listed companies in Kenya and Tanzania? Secondly, we ask the followup question: how does company goal clarity relate to financial performance of the listed companies in Kenya and Tanzania? And lastly, we ask: how does company goal clarity moderate the relationship between government ownership and financial performance of the listed companies in Kenya and Tanzania? Our main motivation to undertake the current study is based on the recent performance challenges the COVID-19 pandemic has had on the financial markets of Africa (Anyanwu & Salami, 2021) and the world at large (Gupta & Sharma, 2021). Particularly so, in the emerging equity markets of East Africa, like Nairobi Securities Exchange (NSE) and Dar es Salaam Stock Exchange (DSE), where equity market capitalization values declined significantly during the pandemic time in the year 2020 (DSE, 2020;NSE, 2020). The decline trend may be a signal of a potential going-concern crisis to both the listed companies and the two exchanges in which they are listed. This view is based on the two main facts: first, the current COVID-19 trend suggests of a regular recurrent pattern across the globe in the near future, and secondly, companies are allowed to cross-list within the two East African exchanges, which is a potential for contagion effects between the exchanges. Consequently, government ownership in the listed companies operating in the two exchanges, has the role of enhancing financial performances to encourage more investor participation in order to activate the markets (Abbas et al., 2016) during such challenging times. We pick government ownership in this current study, because it is known to champion for the use of goal-setting processes in listed companies (Wei, 2020) which produces company goals for guiding performances (Arasa & K'Obonyo, 2012). Its preferential use of company goals has the potential to guide listed companies in emerging markets towards intended financial performances, during difficult economic times.
Our study is therefore informed by the agency and the goal-setting theoretical framework. The main objective is to examine the moderating effect of company goal clarity on the relationship between government ownership and financial performance of listed companies in both Kenya and Tanzania.
The empirical setting of our study is on the two exchanges which are located in Kenya and Tanzania, respectively. Both countries are some of the leading economies in the East African community area. The choice of the two exchanges is also based on the fact that the two have a bidirectional causality relationship (Yunvirusaba et al., 2019), which in our view seems reasonable enough to consider them jointly. Moreover, the two exchanges have relatively higher market measures of both equity turnover and market capitalization in the East African region, for the study period under consideration. Specifically, the average equity turnover and market capitalization figures for the NSE were 2.42 billion US dollars and 19.26 billion US dollars, while for the DSE were 0.19 billion US dollars and 9.34 billion US dollars, respectively. For Uganda Stock Exchange (USE), based on the available data on its website, equity turnover was 0.05 billion US dollars, and market capitalization 4.49 billion US dollars. For Rwanda Stock Exchange (RSE), equity turnover figures were unavailable, while its market capitalization value, based on the available statistics was 2.96 billion US dollars. Therefore, based on the above background information, the two exchanges in Kenya and Tanzania provide a good ground for the study analysis.
Our study uses eight-year secondary panel dataset from selected listed companies in both Kenya and Tanzania. Data are specifically collected from the selected listed companies in both NSE and DSE. The study findings first show that government ownership is negatively related to financial performance. Furthermore, the findings show that decrease in company goal clarity has both positive and negative effects on financial performance. Also, the findings show that a decrease in company goal clarity has negative moderating effect on the relationship between government ownership and financial performance of listed companies in Kenya and Tanzania. However, the negative moderating effect reduces the magnitude of government ownership effect on financial performance.
Our study makes three contributions to the academic literature. Firstly, we demonstrate on the use of company owners, in this case government ownership, as the unit of enquiry for goal-setting studies. We do this by examining the effect of goal clarity on the relationship between government ownership and financial performance. Secondly, we introduce the use of listed companies operating in an emerging market context, as the unit of analysis in the goal-setting studies. This is because, most of the previous studies on goal setting were more biased towards using private companies and parastatals (i.e. government institutions) operating in the developed markets as the units of analysis, leaving out listed companies. Thirdly, we contribute to knowledge on how company goal clarity can be used to enhance corporate governance in addressing the agency problem in the listed companies that operate in the emerging markets environment.
This study is organized as follows: we first review both the relevant theoretical and empirical literature to develop the study hypotheses. Then, we elaborate on the research design of the study, the data used and the related variables. Furthermore, we present and discuss the findings of the study, which include both the descriptive and the inferential statistics. Finally, we make our conclusion by showing the implications and the recommendations to practitioners.

Theoretical literature review
This study is informed by both the agency (Ross, 1973) and the goal-setting (Locke & Latham, 1990, 2002Locke et al., 1981) theories. The agency theory informs on the nature of agency relationship that exists in a listed company setting, whereby the company owners are the principal and the management team is the agent. The agent has the contractual role of managing the listed company affairs for the principal at a fee. The theory conjectures that, as both the company owners and the management are each self-centered, their pursuit of individual interests is the main potential source for an agency problem (Jensen & Meckling, 1976;Ross, 1973). The problem is amplified in a listed company operating in an emerging market context, which is characterized with relatively weaker legal institutions (Claessens & Yurtoglu, 2013). This is particularly so, when owners transfer their decision-making controls to managers (Fama & Jensen, 1983;Jensen & Meckling, 1976). The control transfer may tempt managers to pursue business ventures that only favor their personal interests at the detriment of the company's financial welfare, such as the decline in market values and the increase in the riskiness of financial returns. For the current study, market value is measured by Tobin's q (Thomsen et al., 2006), and the riskiness of company financial returns is reflected in the risk-adjusted return on assets (ROA; Oanh Le Kieu et al., 2021).
The theory suggests on the use of government owners as the outsiders who are endowed with the appropriate resources and incentive to influence financial performance and to address the agency problem. Although government is one of the different owners who are commonly found in listed companies (Thomsen & Pedersen, 2000), it is considered superior over other owners in terms of financial resources and possession of extra attributes, such as governmental support and political connections (Aranda et al., 2014). The attributes facilitate easier access to various business support services, like cheaper funding for a listed company during difficult financial times (Loch et al., 2020). The superiority in resource endowment places government ownership in a better position to influence positively on financial performances of listed companies, especially when it is operating in an emerging market with relatively more business challenges. Furthermore, government ownership is also known to engage in goal-setting or target setting processes, which formulate company goals for guiding towards the intended financial performances (Wei, 2020).
Despite all these complimentary advantages, the ownership is more often found to have a negative relationship with financial performances (Liljeblom et al., 2019), most probably due to its preferred pursuit of social over profit maximization goals in listed companies. In that regard, the ownership possesses a potential risk of triggering the principal-principal and the principal-agent agency problems, which are the conflicts between the majority and minority company owners (Loch et al., 2020;Young et al., 2003), and between company owners and managers, respectively. The conflicts have potential negative consequences on financial performance. The pursuit of social over profitability goals has had negative consequences on financial performances across different sectors as well. For example, borrowing from the microfinance industry, the empirical experiences show that microfinance institutions (MFIs) face similar challenges related to the trade-off between the pursuit of social and financial sustainability goals (Navin & Sinha, 2020). The challenges were even more amplified in the recent times, when MFIs started to migrate from the nongovernmental to private ownership structures . However, despite the similar challenges government ownership brings to listed companies on the one hand, its preference for using company goals on the other aligns well with the main assumption in the goal-setting theory, which conjectures that goals moderate stakeholders' behaviour towards performance. Impliedly, the theory suggests that company goals have the potential to moderate the relationship between government ownership and financial performance.
The goal-setting theory (Locke & Latham, 1990;Locke et al., 1981) is a cognitive theory which focuses on the core properties of an effective goal to predict, explain and influence performance within a particular context (Christian et al., 2020;Locke & Latham, 2002). Therefore, the theory's proposal to use company goals to moderate the relationship in a listed company's context, is based on its core assumption, that human actions are guided by goal clarity. Goal clarity is defined as the degree to which a stakeholder understands well the task assigned (Bellamkonda et al., 2020). In a typical company setting, goal clarity guides the performance-related activities of the primary internal stakeholders (Jung, 2014;Stefan & Foss, 2018), and is related to superior performance. This view is however criticized by Ordóñez et al. (2009), that goal clarity has the risk of narrowing too much the attention of stakeholders to the point of missing the important features of a goal. The primary internal stakeholders in a listed company include at least company owners, employees and the managers (Benn et al., 2016;Roscoe et al., 2020). Therefore, given that government ownership in a listed company is a primary stakeholder to influence on financial performance, the company goal clarity serves it as the guidance towards the intended financial performance. In that regard, the goal-setting theory proposes that company goal clarity moderates the relationship between government ownership and financial performance in a listed company.

Government ownership and financial performance
The empirical literature on the relationship between government ownership and financial performance in a listed company context is also reviewed in the current section of this paper. Alfaraih et al. (2012) explored the effects of government ownership on financial performance and found government ownership had negative effects. Mei (2013) examined the relationship between government ownership and financial performance, and found that the relationship was u-shaped. Moreover, the study revealed that government ownership preferred to invest in the companies that were in some strategically important sectors, like oil, natural gas, and media, and also provided government support and political connections to them. Liu (2018) also studied government ownership in 47 countries and found that it prefers to be the largest owner in listed companies. Abramov et al. (2017) investigated the influence of government ownership on financial performance and found that it had negative influence. Moreover, Wang and Shailer (2018) conducted a meta-analysis study to find out how government ownership faired towards financial performance compared to private ownerships. The study results showed that government ownership had inferior financial performances relative to private ownership. Another study relating government ownership and financial performance is Muthoni and Nasieku (2018), which similarly found that government ownership had negative, though statistically insignificant, effect on financial performance. In the course of seeking knowledge on why government ownership is generally found negatively related to financial performance, Loch et al. (2020) conducted a qualitative study on the relationship, and found that the reason was partly due to its priorities being in the pursuit of political goals. Laporšek et al. (2021) studied the relationship between ownership structure and financial performance by comparing the performances of government-owned and privately owned listed companies. The study findings showed that the government-owned were less profitable than their counterparts.
Based on the above review of the relationship between government ownership and financial performance in listed companies, it is becoming apparent that, government is endowed with relatively more resources (Aranda et al., 2014) than other owners, which makes it the largest owner in most listed companies (Abramov et al., 2017) with more controls. Given that it prefers to pursue more of social welfare and political goals (Laporšek et al., 2021) than profitability, its presence in listed companies has the potential for inferior financial performances (Muthoni & Nasieku, 2018;Wang & Shailer, 2018). Based on these observations, we therefore conjecture that H1: Government ownership is negatively related to financial performance

Goal clarity and financial performance
In this section, the literature relating goal clarity and financial performance is also reviewed. Jung (2011) studied the impact of goal clarity, measured by the number of goals, on organizational performance. The results suggest that goal clarity has positive relationship with organizational performance. Another study by Chun and Rainey (2005), examined the relationship between ambiguity in comprehending organizational mission and performance. Their findings show that, the two were positively related. The findings therefore imply that, lack of clarity was positively related to performance, contrary to the findings in Jung (2011). Van der Hoek et al. (2018) examined to what extent goal setting affects organizational performance in public sector teams. The results of the study found that goal clarity positively affected team work performances, whereby performance was measured by both effectiveness and efficiency. Within the same public sector context, Bang et al. (2010) explored the relationship between having a clear goal for a particular agenda item and team effectiveness in top management meetings. The study found that goal clarity was positively associated with team effectiveness. Another study was Peralta et al. (2015), which studied if goal clarity moderated the relationship between employee teams' innovation processes and financial performance and found that goal clarity positively moderates the relationship. Furthermore, another study by Miyeon et al. (2020) examined the effects of goal ambiguity, which is lack of goal clarity, on organizational performance. The study results showed that high levels of goal ambiguity decreased organizational performance.
Furthermore, in order to understand how government ownership relates to the goal-setting process, the scanty literature relating ownership structure and goal setting is also reviewed. Wei (2020) is one such paper that examined how listed companies with majority government ownership set company goals for sales, compared with the other non-government-owned listed companies. The study found that listed companies, with government ownership, set easier company goals to achieve than the companies without government ownership. The findings therefore confirm that government ownership engages in goal setting.
Based on the above reviewed literature, we learn that, government ownership in listed companies engages in goal setting (Wei, 2020), which impacts positively on organizational team works (Van der Hoek et al., 2018) through goal clarity. As company owners, employees and managers constitute the primary stakeholders in a company (Benn et al., 2016;Roscoe et al., 2020), goal clarity moderates their performance-related activities (Jung, 2014;Stefan & Foss, 2018). Moreover, goal clarity is found to be positively related to organizational financial performances (Jung, 2011). Based on these arguments, we therefore conjecture that; H2a: Company goal clarity is positively related to financial performance H 2b : Company goal clarity positively moderates the relationship between government ownership and financial performance

Research design
This study uses the deductive research approach to test the two hypotheses developed from the reviewed literature. This approach is recommended for hypothesis testing in Saunders and Cornett (2015). The census strategy was used on the companies listed in the two exchanges located in Kenya and Tanzania. However, only 48 listed companies were used in the study, after having eliminated some companies which were unusable for various reasons such as, some being under receivership, others in the merger and acquisition process, and others having data accessibility problems.

Data and variables
Unbalanced secondary panel dataset of the selected listed companies is used to measure the study variables. The dataset period ranges from the year 2011 to 2018, which gives a maximum of 384 observations. This study period was arbitrarily chosen due to relatively easy access to data during the period concerned. Apparently, from the year 2019, the COVID-19 pandemic had affected operations of most listed companies and made them inaccessible for the study.
The dataset includes the financial data collected from the annual published reports of the selected listed companies, their respective share prices for the study period collected from the two exchanges, and the quantitative data related to company goals that were collected from the corporate strategic plans (CSPs) of the same listed companies. The published reports are accessed through the websites of the companies concerned, the two securities exchanges' websites and the African Financials' website, https://africanfinancials.com/.
Furthermore, the quantitative data related to company goals, which is documented in the corporate strategic plans (CSPs) of the selected listed companies, is collected by using a questionnaire (see appendix). The questionnaire is used to collect the quantitative details of company goals related to the period from 2011 to 2018, which are contained in the respective CSPs. Given that the CSPs are not statutorily publishable for public use (Arnold & Artz, 2015;Zhi et al., 2009), the questionnaire is administered to the relevant company officials who deal with corporate strategic plan issues, as the respondents. Summary profiles of the respondents in the selected listed companies is provided in Table 1. Studies that have similarly collected and used documentary data in a similar way include Arnold and Artz (2015), Mori and Mersland (2014), and Zhi et al. (2009).
In this study, financial performance (FP), government ownership (GO) and company goal clarity (GC) are used as the dependent, independent and the moderating variables respectively. Financial performance (FP) is defined by using both a market-based measure, Tobin's q, and an accountingbased measure, risk-adjusted rate of return (ROA). Tobin's q is computed by using the logarithm of the ratio of market capitalization to the book value of assets, as used in Thomsen et al. (2006). In computing the risk-adjusted ROA, return on assets (ROA) is first computed by dividing the annual net income of a listed company by its total assets (Al-Matari et al., 2014). Then thereafter, the Government ownership (GO) is measured by the number of equity shares held by the government in a listed company, divided by the total number of equity shares outstanding at the yearend (Sunday et al., 2017). The moderator variable goal clarity (GC), is measured by the total number (quantitative) of company goals a company pursues during the period under observation, as used in Jung (2011). The measure implies that, as the number of company goals increases goal clarity decreases. The moderator variable is hypothesized to affect the strength or nature of the relationship between government ownership and financial performance. Furthermore, the study appreciates for and include some control variables which contribute to financial performance, as previously used in Mori et al. (2013). The variables include company size (CS), company age (CA), gross domestic product (GDP), industry dummy (ID), country dummy (CD) and the year dummy (YD). Table 2 provides a summary of the operationalization of the study variables.

Data analysis
The dataset is sequentially analyzed by following two main steps. In the first step, descriptive analysis is performed on the dataset. The analysis entails, generation of summary statistics and performance of correlation analysis on the dataset. The second step is the performance of econometric analysis on the dataset using regression method. In this second step, data is analyzed using the moderated regression method (MRM) with the hierarchical approach. The method is appropriate for analyzing a relationship that has one moderator variable with a two-way interaction effect, as recommended in both Dawson (2014) and Helm and Mark (2012). The twoway interaction scenario arises when both the moderator variable GC and the interaction term, GO × GC, are included in the analysis. Our analysis includes also robust standard errors, as recommended by Williams et al. (2013), due to the detected presence of outlier and heteroscedastic problems in the dataset. The regression model therefore reads as After the analysis using the above model, robustness checks are conducted. The checks aim to establish the efficiency of the results produced in the MRM method. In performing the robustness check, the seemingly unrelated regression (SUR) method is used.

Descriptive statistics
Dataset from the 48 listed companies is used to develop descriptive statistics. There are 33 listed companies (69%) from NSE and the other 15 companies (31%) from DSE. Based on the respective industries' perspective, there are 16 companies (33%) which belong to the banks, finance and investment category, and 14 companies (29%) belonging to the commercial services category. There are also have 13 companies (27%), which belong to the industry and allied category, and further 4 companies (8%) which are in the oil and gas category. Then lastly, there is 1 company (2%) from the telecom category. In the analysis, all industries are used, due to the fact that listed companies engage in goal setting (Wei, 2020). Therefore, Table 3 is used to present the descriptive statistics of the dataset related to the 48 listed companies; From Table 3, the dependent variables are defined by Tobin's q and the risk-adjusted ROA. Tobin's q is a market-based measure of company's financial performance, while the riskadjusted ROA is an accounting-based measure, which accounts for the riskiness of the returns. The maximum value for Tobin's q during the 8-year period is 5.02, the minimum −0.80, and the mean value is 2.66. Based on the mean value, it is implied that during the 8-year period, the assets of the 48 listed companies were on average worth 2.66 times more in market values than their respective book values. For the risk-adjusted ROA, the maximum value during the study period is 11.76, the minimum −2.62, and the mean value is 1.69. This means, during the study period, listed companies in Kenya and Tanzania earned on their assets, an average of 1.69% risk-adjusted rate  (Greene, 2000) of return. Impliedly, a unit value of an asset produced 1.69 units of return after having adjusted for the related risks.
For the independent variable, which is government ownership, the maximum value is 74% and the mean value is 6%. This implies that, during the eight-year period, the listed companies were owned by their respective countries' governments by an average of 6% stake. During the same period, the maximum value of the moderator variable goal clarity was 13 company goals, and the minimum was 1 company goal. The respective mean value was also five company goals. The implication is that, during the 8-year period, on average each listed company had five company goals to pursue. During the same period also, the listed companies had at least a minimum of one company goal.
Furthermore, during the 8-year period, the maximum company size for the companies was USD 3,705.71 million, with a minimum of USD 0.49 million and a mean value of USD 494.94 million. The implication is that, during the study period, the listed companies in the two countries had each invested an average of USD 494.94 million in terms of assets for doing business. For the company age, the mean company age of the selected companies was about 48 years, with a maximum of 116 years and a minimum of 1 year. The implication is that, our study uses a heterogeneous selection of listed companies which have different experiences in doing business in their respective industries. On average, most of the listed companies have an average experience of 48 years in doing their respective businesses.

Correlation results
Our analysis includes multicollinearity test on the variables. The test is used to check on the collinearity status of the variables used in our study, which includes government ownership as the independent variable (IV), goal clarity as the moderator variable (MV) and the respective control variables mentioned in the earlier section. Table 4 provides a summary of the diagnostics.
In presenting the diagnostics, we first present the correlation coefficients between the dependent variables (DVs) and both the independent variable (IV) and the moderator variable (MV), respectively. Then, we present the correlation coefficients between the IV and the MV, followed by the ones for the IV and the control variables, and also for the MV and the control variables.
The correlation coefficient between Tobin's q and government ownership is negative and statistically significant (−0.27, p ˂ 0.05). However, for the risk-adjusted ROA and government ownership, the coefficient is positive but statistically insignificant (0.02). Furthermore, the correlation coefficient between Tobin's q and goal clarity is negative and statistically insignificant (−0.03), while between the risk-adjusted ROA and goal clarity, the coefficient is positive and statistically insignificant (0.09).
The correlation coefficient between government ownership and goal clarity is negative and statistically insignificant (−0.03). Furthermore, for government ownership and the other independent variables, the coefficients are as follows: with company size (0.53, p ˂ 0.05), with company age (−0.01, p ˂ 0.05), with GDP (−0.09), with industry dummy (−0.18, p ˂ 0.05), with country dummy (−0.14, p ˂ 0.05), and with year dummy (−0.01). Likewise, the coefficients for the relationship between goal clarity and the other independent variables read as follows: with company size (0.19, p ˂ 0.05), with company age (−0.06), with GDP (−0.02), with industry dummy (−0.03), with country dummy (−0.06), and with the year dummy (−0.20).
Furthermore, the correlation coefficients between the control variables themselves are reasonably low. For example, the highest correlation coefficient value (in absolute terms) observed is between country dummy and GDP (−0.62, p ˂ 0.05). We consider this coefficient value to be lower than the threshold levels prescribed in Saunders et al. (2016) and Mori et al. (2013), which were 0.90 and 0.70, respectively. Therefore, based on both thresholds, the observed correlation coefficients in our study lie within acceptable ranges.

Econometric results
After producing the descriptive statistics and performing correlation coefficient analysis, econometric analysis is conducted for the three hypotheses, H 1 ,H 2a and H 2b . The ordinary least squares (OLS) technique is used to analyze all the hypotheses. For H 2b , the OLS technique is applied using the MRM hierarchical approach. The respective results for all hypotheses are summarized in the following Tables 5, 6 and 7, respectively.

Government ownership and financial performance
We test the hypothesis H 1 , which hypothesizes that government ownership is negatively related to financial performance. Financial performance is measured by Tobin's q and the risk-adjusted ROA. Table 5 summarizes the estimation results from the OLS technique.
In testing H 1 , our estimation results show that the estimated coefficient for government ownership is negative and statistically significant (b 1 = −0.552, p ˂ 0.05), when financial performance is measured by Tobin's q. Likewise, when financial performance is measured by the risk-adjusted ROA, the results show that the estimated coefficient for government ownership is also negative and statistically significant (b 1 = −2.740, p ˂ 0.01). Therefore, the results for both models imply that government ownership has significant negative effect on financial performance. The implication is that, as government ownership increases, financial performances of the listed companies in Kenya and Tanzania decreases. The results suggest that, government ownership in the two countries is more focused on the welfare economics than the profit maximization goal of listed companies. This view is consistent with the general knowledge in the literature, that government ownership in a listed company pursues social welfare economics, such as boosting employment opportunities and pursuing low output consumer prices, instead of pursuing the profit related financial performances. These results do further suggest that in the emerging markets' context, goals of government ownership in listed companies are more contextually related to the specific needs of the environment concerned. The view is based on the fact that, as countries differ in their levels of development, the respective government ownership goals may either deviate away from or relate closely to the profit maximization goal of a typical listed company, depending on the respective government's priorities. Our findings are therefore also consistent with the main view in Thomsen and Pedersen (2000), that ownership types differ from one another in terms of the goals/interests each one pursues. Moreover, our results are also consistent with other studies, like Loch et al. (2020), Muthoni and Nasieku (2018), Abramov et al. (2017), and Laporšek et al. (2021).
Company size in our results shows a negative and statistically significant relationship with financial performance (b 2 = −0.325, p ˂ 0.01) when financial performance is measured by Tobin's q. This implies that, as the company size of a listed company in Kenya and Tanzania increases, financial performance decreases. From the market viewpoint, the results suggest that, as company resources in the listed companies increase, they pose some managerial challenges to the listed companies operating in the two emerging markets of East Africa, due to the interests of government ownership being more focused on the provision of social services contrary to the generally sought after goal of profit maximization. However, when financial performance is Significance levels: ***p ˂ 0.01, **p ˂ 0.05, *p ˂ 0.10; The figures in brackets are the robust standard errors. measured by the risk-adjusted ROA, the estimated coefficient for company size is positive and statistically significant (b 2 = 0.928, p < 0.01). Looking at it from the risk management viewpoint, the results suggest that, an increase in company resources for listed companies operating in the two emerging markets of East Africa, enables the pursuit of more profitable investment opportunities, although it also increases risks to the companies concerned. However, the results suggests on the importance of taking the requisite risk mitigation measures for a listed company operating in the emerging market, which are characterized with nascent institutions to support new investments.
For the company age, the estimated coefficient is positive and statistically significant (b 3 = 0.132, p ˂ 0.05) when financial performance is measured by Tobin's q. Likewise, when financial performance is measured by the risk-adjusted ROA, the estimated coefficient is also positive and statistically significant (b 3 = 0.523, p ˂ 0.05). This implies that, company age has a bearing on the financial performance of the listed companies operating in both Kenya and Tanzania. However, the estimated coefficient on the risk-adjusted ROA is relatively higher than the one in the Tobin's q model. This implies that, when risk mitigation measures are considered, the company's experience in doing business by considering all risks encountered in the past becomes a significant factor. Impliedly, the older the company's business experience is, the more likely it is well equipped Significance levels: ***p ˂ 0.01, **p ˂ 0.05, *p ˂ 0.10; The figures in brackets are the robust standard errors.
to tackle possible risk factors, in order to ensure higher financial performances. The constant terms b 0 for both the Tobin's q and the risk-adjusted ROA models are statistically significant, which are (b 0 = 4.262, p ˂ 0.01) and (b 0 = −3.352, p ˂ 0.01) respectively.
Therefore, generally our study results support the hypothesis H 1 , that government ownership is negatively related to financial performance.

Company goal clarity and financial performance
We then test hypothesis H 2a , which hypothesizes that company goal clarity is positively related to financial performance. In testing H 2a , we use the OLS technique to analyze data, and the results of the analysis are summarized in Table 6 below.
Our estimation results for H 2a , when financial performance is measured by Tobin's q, the estimated coefficient for goal clarity is positive and statistically insignificant (b 1 = 0.006). Moreover, when financial performance is measured by the risk-adjusted ROA, the results show that the estimated coefficient for goal clarity is negative and statistically insignificant (b 1 = −0.019). The results for the Tobin's q model imply that as the number of company goals increase there is an insignificant increase in financial performance too. This implies that, a decrease in goal clarity has insignificant positive effect on the financial performances of the listed companies in Kenya and Tanzania. The results further suggest that, as listed companies focus on many diverse company goals at a go, they increase opportunities for making more profits by pursuing a mixture of diversified ventures. The results also suggest that, for the listed companies operating in the emerging markets of EA, where there are more pressing societal and business challenges, companies should pursue a relatively higher number of goals to cater for more societal needs. The pursuit will however, consequently lead to lower company goal clarity. The results of the current study are consistent with Chun and Rainey (2005), but contradict the findings in Jung (2011), Van der Hoek et al. (2018), and Bang et al. (2010). Therefore, the current study results, using the Tobin's q model do not support hypothesis H 2a , that company goal clarity is positively related to financial performance.
For the risk-adjusted ROA model, the results show that there is an insignificant negative relationship between a decrease in goal clarity and financial performance. This implies that, as company goals increase in number, they expose companies to various risks due to diverted attention in operations. The attention diversion may lead into the misuse and mismanagement of company resources, which can result into decreases in financial performances. The decreased financial performances, as measured by the risk-adjusted ROA, which arise from the decrease in goal clarity indirectly supports the hypothesis H 2a , which hypothesizes that company goal clarity is positively related to financial performance.

Company goal clarity on government ownership and financial performance
Lastly, we also test hypothesis H 2b using the OLS technique in the MRM. Hypothesis H 2b hypothesizes that, company goal clarity positively moderates the relationship between government ownership and financial performance. Table 7 below presents the estimation results from the analysis that uses the MRM hierarchical approach. In the analysis, basic model I is used to test the basic relationship purported in H 1 first. Thereafter, basic model II together with the interaction model are used to test hypothesis H 2b on the moderating effect of company goal clarity and the respective interaction term GO × GC effect.
The results from the interaction model using Tobin's q as a measure of financial performance show that, the estimated coefficient of the interaction term GO × GC is negative and statistically significant effect (b 3 = −0.211, p ˂ 0.01). The implication is that, a decrease in goal clarity in the listed companies from Kenya and Tanzania, has moderating effect on the relationship between government ownership and financial performance. Similarly, for the model that uses the riskadjusted ROA to measure financial performance, the estimated coefficient of the interaction term GO × GC is negative and statistically significant too (b 3 = −1.052, p ˂ 0.01). Based on the negative and statistically insignificant coefficients of goal clarity, (b 3 = −0.003) and (−0.027) respectively from the basic model II, the results further imply that goal clarity is a pure moderator in the relationship between government ownership and financial performance. As according to Helm and Mark (2012), a pure moderator interacts with the independent variable only to change the form of the relationship between the IV and the DV. Therefore, the current study results suggest that, a decrease in goal clarity moderates the relationship between government ownership and financial performance by interacting with government ownership. However, we do further analysis to establish two main things: first, the direction of the moderating effect, and secondly, the optimal level of goal clarity.
The following equation is used for the analysis, with goal clarity squared.
The analysis follows two main sequential steps: computation of the first and the second derivative of the equation. The first derivative is used to establish the value of goal clarity at the turning point of the equation, which implies the optimal goal clarity value. The second derivative is then used to determine if the turning point is negative or positive. A positive value implies a maximum while a negative value implies a minimum turning point. Table 8 below summarizes the OLS estimation results from the analysis.
From Table 8 above, the Tobin's q model estimated coefficient of goal clarity squared (GC 2 ) is positive and statistically insignificant (b 3 = 0.004). This implies that, the moderating effect of goal clarity has an optimal point. This means, as goal clarity decreases beyond the optimal point, it will start having positive moderating effects on the relationship between government ownership and financial performance. However, for the model using the risk-adjusted ROA to measure financial performance, the estimated coefficient of goal clarity squared (GC 2 ) is negative and statistically insignificant (b 3 = −0.019). This suggests that, the moderating effect of goal clarity on the relationship has a maximum optimal point. The respective value of goal clarity at the optimal point is approximately 7 company goals. This means, the negative moderating effect of a decrease in goal clarity continues linearly up to a maximum of 7 company goals, beyond which the effects are no longer linear.
Moreover, the study findings generally conform to some similar views in Miyeon et al. (2020), that for multiple goals to have positive effects they should be well prioritized. The view is also backed-up by Ordóñez et al. (2009), that too much goal clarity may risk narrowing the performance focus of the managers, and therefore contribute to consequential wrong decisions. The findings also contradict with the common view in Jung (2011), which conjectures that lack of goal clarity reduces organizational performance.
However, our results conform to the general view that the preference of government ownership to pursue diverse social goals, which includes increasing employment opportunities, increasing wages and rendering social services, may still have positive effect on the financial performance of listed companies, if they are up to a an optimal number of company goals. The results therefore suggest that, in order for the government ownership in listed companies to have positive effects on financial performance, listed companies should also accommodate its diverse non-profit related goals up to a maximum of seven (7) company goals. Although this decision will increase the number of company goals and automatically reduce goal clarity gradually, it will however help to reduce the negative effect of government ownership on financial performance in the long run. The presence of government ownership will therefore, give listed companies a chance to tap on the vast and extensive experience of governments to render services to the general public even when they face various challenging environments. However, our results do not support hypothesis H 2b , that goal clarity positively moderates the relationship between government ownership and financial performance in a listed company in Kenya and Tanzania.

Robustness Check
For robustness check, we use the Seemingly Unrelated Regression (SUR) technique (Greene, 2000) on the same study data. We find the results from SUR analysis not different from the OLS results, which implies that, the results from the current study are efficient and robust when using a different model. The estimation results for the SUR technique appear in Table 9 below.

Conclusion and implications
In this study, we mainly examine the effect of company goal clarity on the relationship between government ownership and financial performance of listed companies in both Kenya and Tanzania. Our three specific objectives aim to (i) examine the relationship between government ownership and financial performance, (ii) examine the relationship between company goal clarity and financial performance, and (iii) investigate the moderating effect of company goal clarity on the Significance Levels: ***p ˂ 0.01, ** p ˂ 0.05, * p ˂ 0.10; The figures in brackets are the robust standard errors relationship between government ownership and financial performance. Our findings show a negative and statistically significant relationship between government ownership and financial performance. Furthermore, we also find a positive but statistically insignificant relationship between a decrease in company goal clarity and financial performance when using a Tobin's q model. However, when we use the risk-adjusted ROA model, we find a negative but statistically insignificant relationship between a decrease in company goal clarity and financial performance. Moreover, we also find that company goal clarity is a pure moderator whose decrease has a negative and statistically significant effect on the relationship between government ownership and financial performance, although the effect reduces up to an optimal point of seven company goals. Theoretically, our study contributes to literature, particularly to the agency theory (Ross, 1973) with knowledge that company goal clarity is a significant variable to complement other corporate governance tools in addressing the agency problem in listed companies. Company goal clarity is an important dimension in the goal-setting process (Aranda et al., 2014;Locke & Latham, 1990, 2002, which affects the relationship between government ownership and financial performance in listed companies. Methodologically, our study uses company owners (i.e. for our case government ownership) as the unit of enquiry and the listed companies which are operating in an emerging market environment as the units of analysis in the goal-setting literature. To the best of our knowledge, we do not know of any study in the goal-setting literature that had previously used the two in the analysis.
Practically, this current study makes the following recommendations to the practitioners and policy makers in both Kenya and Tanzania: To the governing boards of listed companies in Kenya and Tanzania, they should consider the inclusion of non-operative goals of government ownership, to allow companies to learn from the experience of the ownership, on how challenging goals are successfully pursued. This is owing to the negative moderating effect of the decrease in company goal clarity on the relationship between government ownership and financial performance of the listed companies in Kenya and Tanzania. The negative moderating effect makes a turn-around effect on the basic relationship between government ownership and financial performance, which was basically negative. We therefore recommend the inclusion of all government ownership goals in company goals. We also recommend to the policy makers of the two countries, Kenya and Tanzania, to enforce goal-setting practices in listed companies, in order to enhance corporate governance practices that will enhance financial performances.