Financial and Non-Financial Practices Driving Sustainable Firm Performance: Evidence from Banking Sector of Developing Countries

Since independence, state-owned enterprises in Pakistan have been struggling for performance enhancement. The goal of sustainable performance is still unachievable. Therefore, the paper evaluates sustainable corporate performance based on financial, social, and environmental performance areas. The organizational restructuring framework for sustainable performance enhancement is developed on software PLS-SEM. The financial and economic performance (FEP) was evaluated through financial reports and surveys; however, social and environmental performances (SEP) were quantified through survey questionnaires for seven performance areas with multiple sub factors, based on Weisbord’s six box model. The study time period in focus is 2011 to 2015. Data was collected from 517 employees of 19 public, private, and privatized banks of Pakistan. The results demonstrate that the total effect of FEP and SEP is much stronger (t-value = 7.619) than the individual direct impact of FEP (t-value = 5.189) on sustainable firm performance (SFP). This is a clear indication of the mediating role of SEP for SFP evaluation. Furthermore, FEP depends on significant indicators include net assets, total deposits, profit before tax, and earnings per share of total deposits with outer loadings, which are given as 0.995, 0.992, 0.978, and 0.954, respectively. Moreover, SEP depends on indicators, i.e., reward policies, redefining organizational purpose, coordination mechanism among employees, and supervisor relationships, with correlations of 0.864, 0.849, 0.805, and 0.761, respectively. The framework will assist in the enhancement of the performance of economically unviable public and loss-making privatized entities.


Introduction
Corporations are striving to achieve long-term benefits by adopting sustainable activities at the core of their corporate strategy. Corporate sustainable performance mainly focuses on the environmental, social, and economic performances of sustainable development [1]. So, it is defined as the development that meet the needs of the present without compromising the ability of future generations to meet their own needs [2]. There is a need for proper balance among the three parameters, i.e., environmental, social, and economic to achieve sustainability in organization. The concept of corporate performance usually refers to financial aspects, such as profit, return on assets, and economic value added. According Sustainability 2020, 12 to slack resource theory, higher financial performance leads to an increase in wealth of stakeholders and creates corporate opportunities to improve social performance [3]. Ownership change has the capability to cure the sick economies for the growing conviction in today's economic world. These ownership changes fall in the areas of industrialization, nationalization, and privatization of state owned enterprises (SOE's) [4]. The motive behind the international financial institutions and free market economies is that the state should confine itself to regulation only, whereas the operation and ownership of industrial enterprises and utilities should be handed over to private ownership, as it is in United States of America [5]. The privatization programs of Pakistan, Kenya, India, and Zambia similar. The historical trends of restructuring in Pakistan and India are based on similar process of industrialization, nationalization, and privatization.
In order to succeed in today's competitive business environment, a firm should have a clear business strategy supported by organizational strategies [6]. No research seems to have investigated the mediating role of organizational development indicators on sustainable firm performance. Several studies have been carried out to identify the effect of privatization; however, these studies have number of short comings. Most studies compare economic and financial performance of SOE's only; however, the role of non-financial factors cannot be mitigated [7][8][9]. In developing countries, the failures of nationalization and the industrialization of firms have prompted privatization. Mostly, restructuring is done prior to privatization to cure sick economies and make them sustainable. If restructuring fails to achieve the desired objectives, then privatization is the only solution to make the firm sustainable. Privatization is believed to be the source of generating economic efficiency by switching non-profit organizations to profit making organizations, but this is not possible without the role of organizational development.

Literature Review and Hypothesis Development
This section represents the existing literature on impact of financial factors on sustainable firm performance and how non-financial factors are incorporated to enhance performance. In the end of the section, we derive the hypothesis to be tested.
In order to compete globally, firms have to continuously innovate and redefine their strategies by focusing on their local needs. They cannot adopt unethical business practices, i.e., unfair labor practices, environmental pollution and focusing not only on profit but on the stakeholder needs. A responsible company should focus on the social and environmental impact of its business processes by collaborating with customers and suppliers [10]. The term "sustainable performance" is extended to include not only the financial aspect, but also the social and environmental aspects. Sustainable corporate performance includes components of financial, social, and environmental performance measures [11,12]. Research shows a positive relationship between corporate social responsibility and the financial performance of banks [13,14]. The literature also confirms that the relationship between firm environmental performance and corporate financial performance has been extensively studied in developed countries [13]. The inclusion of the two additional aspects in the measurement and evaluation of corporate performance can be understood by the fact that the responsibility of the company is not only to generate economic profit, but also to care for society and the environment [15]. As a performance measure, the sustainability concept in accounting consists of two aspects namely financial and social performances in which the environmental is part of social aspect [11,16]. It is proposed that the content of each measurement element may vary along contexts and time. Therefore, the concept of sustainable firm performance should be interpreted as a relative rather than static. Although social and environmental responsibility is regarded as universal concept but it differs over time to time and region due to varying socio political and cultural circumstances [13]. Most of the previous studies have focused primarily on factors that are driving the financial performance of banks [17][18][19]. Their major focus was to investigate factors affecting firm's competitiveness which is proxied by financial performance. Gervase Iwu [20] estimated the effectiveness of firms through inclusion of non-financial factors, i.e., customer satisfaction, quality of service, social responsibility, complaints per client, quality of management, and improvement in facilities. The relationship of financial and economic factors on social and environment performance is found missing. FEP and SEP had shown their individual impact on SFP, whereas the current study model develops the direct dependence of FEP on SEP.
The new approach is shown in Figure 1 which highlights the significance of indirect approach. The paths between the independent and dependant variables are shown by a, b and c. In previous study model there are two paths followed by three paths in the current study model with the addition of mediating path c.
Sustainability 2020, 12, x FOR PEER REVIEW 3 of 17 effectiveness of firms through inclusion of non-financial factors, i.e., customer satisfaction, quality of service, social responsibility, complaints per client, quality of management, and improvement in facilities. The relationship of financial and economic factors on social and environment performance is found missing. FEP and SEP had shown their individual impact on SFP, whereas the current study model develops the direct dependence of FEP on SEP.
The new approach is shown in Figure 1 which highlights the significance of indirect approach. The paths between the independent and dependant variables are shown by a,b and c. In previous study model there are two paths followed by three paths in the current study model with the addition of mediating path c. The conceptual model and hypothesis have been presented in Figure 2, which includes indicators of financial and economic performance (FEP), social and environmental performance (SEP), and sustainable firm performance (SFP), along with their individual sub factors. The model constitutes three hypotheses as explained i.e., H1: financial and economic performance is positively related to sustainable firm performance; H2: social and environmental performance is positively related to sustainable firm performance; H3: social and environmental performance is a mediator in the relationship between the financial and economic performance and sustainable firm performance.  Figure 2, which includes indicators of financial and economic performance (FEP), social and environmental performance (SEP), and sustainable firm performance (SFP), along with their individual sub factors. The model constitutes three hypotheses as explained i.e., H1: financial and economic performance is positively related to sustainable firm performance; H2: social and environmental performance is positively related to sustainable firm performance; H3: social and environmental performance is a mediator in the relationship between the financial and economic performance and sustainable firm performance.
The purpose of this research is to develop a sustainable firm performance (SFP) framework for performance enhancement of public and private firms of the country. It includes three interlinked stages i.e., financial and economic performance (FEP), social and environmental performance (SEP) and, sustainable firm performance (SFP). Sustainability assessment of service sector cannot be ignored, due to the increasing contribution of the service sector in the global economy. Majority of the studies have focused merely on the financial effect on sustainable performance but inclusion of primary data of social and environmental parameters have added robustness in the sustainable performance model. This research aims to develop a sustainable organizational restructuring framework by evaluating the combine effect of FEP and SEP factors on sustainable corporate performance.  The purpose of this research is to develop a sustainable firm performance (SFP) framework for performance enhancement of public and private firms of the country. It includes three interlinked stages i.e., financial and economic performance (FEP), social and environmental performance (SEP) and, sustainable firm performance (SFP). Sustainability assessment of service sector cannot be ignored, due to the increasing contribution of the service sector in the global economy. Majority of the studies have focused merely on the financial effect on sustainable performance but inclusion of primary data of social and environmental parameters have added robustness in the sustainable performance model. This research aims to develop a sustainable organizational restructuring framework by evaluating the combine effect of FEP and SEP factors on sustainable corporate performance.

Materials and Methods
A combinational research methodology is employed in this research project. This encompassed literature review, mix method research (MMR), longitudinal path analysis, and questionnaire development. The literature review conducted at initial stages of this research demonstrated the existence of finding the require niche. Figure 3 shows detailed schematic flowchart of the research.

Materials and Methods
A combinational research methodology is employed in this research project. This encompassed literature review, mix method research (MMR), longitudinal path analysis, and questionnaire development. The literature review conducted at initial stages of this research demonstrated the existence of finding the require niche. Figure 3 shows detailed schematic flowchart of the research.

Financial and Economic Performance
The financial variables are the most dominant factors for accessing a firm's sustainable performance; alterations in these factors can transform the performance of companies [21,22].

Financial and Economic Performance
The financial variables are the most dominant factors for accessing a firm's sustainable performance; alterations in these factors can transform the performance of companies [21,22]. Organizations select their own specific factors to estimate the quality of performance based on their financial statements [20]. The effects of FEP is quantified through net assets, total deposits, liquidity, staff cost, profit before tax, operating cost to net interest income, net provisions, current account and savings account (CASA), and earnings per share.

Social and Environmental Performance
Organizational development (OD) is precisely explained as the planned developmental effort focused at accelerating organizational usefulness and health through organized and programmed intervention [23]. Besides increasing performance and competitive advantage, OD adds worth and utility to human potential, participation, and development of an organization [24]. Enhancement in OD programs leads to sustainable organizational performance in parallel or even ahead of privatization [25]. Number of studies has used organizational diagnosis questionnaire (ODQ) to measure the organizational health for non-financial analysis [26][27][28]. Organizational development (OD) is quantified through redefining organizational purpose, well-defined organizational structure, supportive leadership, employee to supervisor relationships, reward policies, helpful coordination mechanism, and attitude towards change [29,30]. Detailed questionnaire is attached in Supplementary material (Questionnaire S2).

Performance Indicators
Different firms have employed various methods to precisely measure performance, with some focusing on financial and economic performance to measure organizational performance [31]. The most important results of organizational assessment are their level of performance [32]. While many firms dealt with non-financial and economic performance only, the shortcoming of traditional performance measures (based solely on financial and economic performance) leads to the development of new systems that include both financial and non-financial and economic performance. SFP was evaluated through profitability (ROE), efficiency (NIM), capital adequacy ratio (CAR), return on assets (ROA), and spread. The FEP and SFP data is collected through financial reports available from KPMG's (an international audit firm) annual banking surveys.
Based on the indicators of FEP, SEP, and SFP, a leader-laggard analysis has been performed on 19 banks of Pakistan. The banking sector was selected as a research population due to its large and diverse number of branches. In this analysis, the banks were grouped into two categories (laggards and leaders) for a period of 5 years (2011-2015). The analysis has been presented in Figure 4 that shows that majority of the banks are laggards in financial performance during the years 2011 to 2014.

Proposed Scheme
The data for the extraction of results is obtained at different time intervals (2011)(2012)(2013)(2014)(2015). So, longitudinal path analysis will be employed as independent and dependent variables are measured at different times [33]. Banking sector was selected for the evaluation of SFP. These 19 banks were either public, privatized after 1991 or developed as a private bank. The financial data (quantitative) of last five years has been collected through financial reports available from KPMG (an international audit firm) annual banking surveys. These banks were contacted by telephone, emails, and letters. ODQ had been distributed among branch managers, operations manager, general banking officers, credit officers, business development officers, and cashiers, after an inquiry of initial contact, for SEP evaluation. The ODQ, comprising of 35 questions, was developed based on the seven areas of extended Weisbord's six box model to evaluate SEP.   The minimum sample size required in this study was decided based on suggestions, i.e., to have five times observation as the number of variables to be analyzed [34]. Following this rule of thumb, the minimum samples needed are 175 = (35 × 5) [35]. Moreover, the sample size in PLS-SEM analysis depends upon the maximum number of arrows pointing towards the latent variables [36]. The minimum sample size required for this study is 91 samples, as the model has maximum 10 arrows pointing towards a single latent variable. In this study, 700 questionnaires were distributed; in return, 525 employees responded to the questionnaires and 517 are usable for the analysis of private and public banks (74% response rate), as attached in Supplementary Material (Table S2). Finally, the conclusive research was applied for the hypothesis testing and relationship examination among financial and economic performance, social and environmental performance, and sustainable firm performance [37].

Model Evaluation
The research hypotheses stated above were explained through structural equation modelling using partial least squares (SEM-PLS). Smart PLS (3.2.4) were used to analyze the data. For the determination of a significant level of factor loadings and path coefficients, the bootstrapping procedure within smart PLS was applied. SEM-PLS is explained by two sets of linear models: the inner and outer model [36]. The inner model defines the interconnections between the latent variables while the outer model specifies the relationship between latent variables and their and their related observed variables [38].
The inner model includes FEP, SEP, and SFP. The outer model includes the three latent variables (FEP, SEP, and SFP) and their respective unobserved variables, which can be clearly seen in Figure 5.

Model Evaluation
The research hypotheses stated above were explained through structural equation modelling using partial least squares (SEM-PLS). Smart PLS (3.2.4) were used to analyze the data. For the determination of a significant level of factor loadings and path coefficients, the bootstrapping procedure within smart PLS was applied. SEM-PLS is explained by two sets of linear models: the inner and outer model [36]. The inner model defines the interconnections between the latent variables while the outer model specifies the relationship between latent variables and their and their related observed variables [38].
The inner model includes FEP, SEP, and SFP. The outer model includes the three latent variables (FEP, SEP, and SFP) and their respective unobserved variables, which can be clearly seen in Figure 5.

PLS Result Evaluation
The SEM-PLS results were evaluated in two steps. In steps 1, the measurement model is examined with the analysis of reflective or formative nature of model. The model is reflexive in nature, as the indicators are dependent on each other, so indicators reliability, internal consistency, convergent validity, and discriminant validity is evaluated in the first step [39]. After evaluating these four criteria, the researcher proceeds to step 2. It evaluates the structural model by evaluating predictive relevance and collinearity. The reflexive significant model achieved after step by step

PLS Result Evaluation
The SEM-PLS results were evaluated in two steps. In steps 1, the measurement model is examined with the analysis of reflective or formative nature of model. The model is reflexive in nature, as the indicators are dependent on each other, so indicators reliability, internal consistency, convergent validity, and discriminant validity is evaluated in the first step [39]. After evaluating these four criteria, the researcher proceeds to step 2. It evaluates the structural model by evaluating predictive relevance and collinearity. The reflexive significant model achieved after step by step elimination of the non-significant indicators from SMART-PLS model, which is illustrated in Figure 6 (with latent variables in blue color and indicators in yellow color).

Measurement Model Evalutaion
For the reflectively measured constructs, indicator reliability, internal consistency reliability, convergent validity, and discriminant validity are evaluated [40]. In the first step, indicator loadings are examined. All the loadings provided in table were above 0.7, so it was clear that constructs explains over 50% of the indicator's variance [41]. The second step involved the assessment of the constructs internal consistency reliability, which was evaluated by using composite reliability (CR). In assessing reliability, higher values indicated higher level of reliability and values above 0.7 were in the acceptable range [42], as indicated in Table 1. In smart PLS, the bootstraping procedure can be used to test the significance of structural path using T-statistics. The bootstrap result approximates the normality of the data. Using two tailed t test with significance level of 0.5%, the path coefficient would be significant if the T-stat value is above 1.96 [36]. All T-stat values in Table 1 are above 1.96, which shows significance of the paths. Moreover, a smaller p-val represents that there is strong evidence in favor of the alternate hypothesis [43]. The weightage of all the parameters involved in the SFP base SEM-PLS mode is presented in Figure 7.

Measurement Model Evalutaion
For the reflectively measured constructs, indicator reliability, internal consistency reliability, convergent validity, and discriminant validity are evaluated [40]. In the first step, indicator loadings are examined. All the loadings provided in table were above 0.7, so it was clear that constructs explains over 50% of the indicator's variance [41]. The second step involved the assessment of the constructs internal consistency reliability, which was evaluated by using composite reliability (CR). In assessing reliability, higher values indicated higher level of reliability and values above 0.7 were in the acceptable range [42], as indicated in Table 1. In smart PLS, the bootstraping procedure can be used to test the significance of structural path using T-statistics. The bootstrap result approximates the normality of the data. Using two tailed t test with significance level of 0.5%, the path coefficient would be significant if the T-stat value is above 1.96 [36]. All T-stat values in Table 1 are above 1.96, which shows significance of the paths. Moreover, a smaller p-val represents that there is strong evidence in favor of the alternate hypothesis [43]. The weightage of all the parameters involved in the SFP base SEM-PLS mode is presented in Figure 7.   Next, the convergent validity of the reflectively measured constructs was examined. It measures the extent to which the construct converges in its indicators by explaining the item's variance. It was assessed by the average variance extracted (AVE) for all items associated with the construct [42]. An acceptable AVE is 0.50 or higher as is indicated in Table 2.
Table2. Acceptable ranges of composite reliability and convergent validity.

Constructs
Composite Once the reliability and convergent validity of the constructs were successfully evaluated, the next step was to access the discriminant validity of the constructs. This estimates the extent to which a construct is empirically distinct from other constructs in the path model [38]. The diagonal elements in the matrix must be larger than the entries in corresponding columns and rows to satisfy discriminant validity [44]. The discriminant validity of the model is indicated in Table 3. Next, the convergent validity of the reflectively measured constructs was examined. It measures the extent to which the construct converges in its indicators by explaining the item's variance. It was assessed by the average variance extracted (AVE) for all items associated with the construct [42]. An acceptable AVE is 0.50 or higher as is indicated in Table 2. Once the reliability and convergent validity of the constructs were successfully evaluated, the next step was to access the discriminant validity of the constructs. This estimates the extent to which a construct is empirically distinct from other constructs in the path model [38]. The diagonal elements in the matrix must be larger than the entries in corresponding columns and rows to satisfy discriminant validity [44]. The discriminant validity of the model is indicated in Table 3.

Structural Model Evalutaiton
The results of measurement model evaluation indicate that model quality is satisfactory. The next stage is the evaluation of structural model, as indicated in Figure 8. PLS-SEM does not have standard goodness of fit statistics [45]. Instead the evaluation of the structural model is based on its ability to predict the endogenous constructs (SFP). The evaluation criteria used includes collinearity assessment, coefficient of determination (R 2 ), cross validated redundancy (Q2), and the path coefficients. The first step is to examine the collinearity between SEP and FEP, as these serve as exogenous constructs in the prediction of SFP. The variance inflation Factor (VIF) ranged between 1(FEP) and 1.092 (OD) provides confidence that the structural model results are not negatively affected by collinearity.

Structural Model Evalutaiton
The results of measurement model evaluation indicate that model quality is satisfactory. The next stage is the evaluation of structural model, as indicated in Figure 8. PLS-SEM does not have standard goodness of fit statistics [45]. Instead the evaluation of the structural model is based on its ability to predict the endogenous constructs (SFP). The evaluation criteria used includes collinearity assessment, coefficient of determination (R 2 ), cross validated redundancy (Q2), and the path coefficients. The first step is to examine the collinearity between SEP and FEP, as these serve as exogenous constructs in the prediction of SFP. The variance inflation Factor (VIF) ranged between 1(FEP) and 1.092 (OD) provides confidence that the structural model results are not negatively affected by collinearity. The second step involves the measurement of the predictive relevance of R 2 . It is a measure of variance explained in each of the endogenous constructs and is thus calculation of the model's predictive accuracy [38]. R 2 ranges from 0 to 1, with higher levels showing greater degree of predictive accuracy. The examination of the endogenous construct's predictive power demonstrates the SFP has a substantial R 2 value of 0.597. This means that the two latent variables (FEP and SEP) moderately The second step involves the measurement of the predictive relevance of R 2 . It is a measure of variance explained in each of the endogenous constructs and is thus calculation of the model's predictive accuracy [38]. R 2 ranges from 0 to 1, with higher levels showing greater degree of predictive accuracy. The examination of the endogenous construct's predictive power demonstrates the SFP has a substantial R 2 value of 0.597. This means that the two latent variables (FEP and SEP) moderately explain 59.7% of variance in SFP, whereas, the prediction of FEP is comparably weak (R 2 = 0.084), explaining 8.4% of the variance of SEP.
The third step involves the measurement of predictive relevance (Q2) for each of the endogenous constructs. Blindfolding procedure is applied to estimate the model's predictive relevance. This procedure yields results of SFP: 0.485; OD: 0.018 (all values greater than zero), providing support for the model's predictive relevance.
Once the predictive relevance is established, the final step of the structural model evaluation is the measurement of significance and relevance of the structural model relationship. For this step, the bootstrapping procedure is used, which reveals results highlighted in Figure 8. The results reveal that a FEP has significant effect on SFP (path coefficient: 5.189), whereas the role of FEP on SEP (path coefficient: 1.087) is not as strong as of SFP. Further analysis shows that SEP also has a weaker effect on SFP (path coefficient: 1.236).
A noteworthy result emerges when considering the indirect effect of FEP on SFP via the mediator (SEP). The corresponding total effect is given by the Equation (1) [38]: Total effect = Direct effect + Indirect effect (1) As shown in Equation (1), the total (with mediator) effect is much stronger than the direct effect of FEP on SFP, underling the important role of FEP. For instance, the direct effect of 5.189 and indirect effect of 1.087 times of 2.236 gives the total effect of 7.619. In addition, these findings indicate that SEP mediates the relationship between FEP, and SFP.

Mediation Analysis
OD mediates the relationship between FEP and SFP. It is worthwhile to explicitly test for this potential mediation effect [46]. To do so, the analysis draws on [42,45] by answering the following three research questions.

1.
Is the direct effect between financial and economic performance and sustainable firm performance significant when the mediator variable is excluded from the path model? 2.
Is the indirect effect via the mediator variable significant after organizational development has been included in the path model? 3.
How much of the direct effect does the indirect effect via the mediator absorb?
To answer the first question, exclude OD from the path model and run the bootstrapping routine with previously described specifications. The direct effect value is 5.189 (p-value = 0.00). Answering the second question requires re-estimating the full model (mediator included) and testing the indirect effect significance. The corresponding bootstrapping results indicate that the indirect effect of 2.430 is significant at p ≤ 0.05. Finally, we compute the variance accounted factor (VAF) using the formula indicated in Equation (2) [45].
The result of this final step yields a VAF value of 0.3190, which according to [45] suggest that OD partially mediates the relationship between FEP and SFP. In this model, both FEP and SEP impacted on the SFP. The findings suggest that it is important to recognize the role of OD as a mediator in SFP evaluation. The framework identifies SOEs that are promising candidates for privatization, their successful transition into a privatized firm, and their continuance as efficient private sector firm. Successful performance evaluation requires accuracy in FEP and SEP, and active participation of the shareholder to improve performance. Previous research shows that cross-country analysis and country case studies conclude that privatization of firms improves their performance as compared to continued state ownership [47,48]. It is also seen that the benefits from the privatization of firms are less if foreign firms are not allowed to participate in the privatization process [49].
This study conceives the future of firms in terms of performance and develops an organizational restructuring framework for performance enhancement of public and private firms of the country.
The role of SEP is indeed not to be ignored. It behaves as a mediator in estimating performance. The paper systematically examined the direct role of FEP in examining performance and also by involving the mediating role of SEP. It is depicted in Table 4 that FEP affects SFP, as indicated in hypothesis H1. Moreover, SEP also affect the SFP. However, the results of the study also support the mediation hypothesis H3 by showing the total effect is much stronger than direct effect, which is a clear indication of mediating role of SEP.

Conclusions
The developed framework anticipates a strategy for 'what to do', and 'what to avoid' during privatization of firms. The framework is based on three interlinked stages of FEP, SEP, and SFP. The order plan for the performance enhancement begins with the FEP of the firms with sincere effort from the top management and the government followed by SEP is done by professional managers.
The first stage is FEP. The government must plan to revive dead entities by financially restructuring them according to the transaction structure proposed by its financial advisors. This stage includes four of the most important contributing factors according to the priority level. i.e., profit before tax, net assets, earnings per share, and total deposits. Firstly, steps must be taken to increase operating income by generating more interest money on its loans, which would increase the profit before tax. Secondly, firms must be evaluated by the worth of their net assets. Evaluation of net assets is necessary to be done by the financial experts at appropriate time and conditions for successful FEP. Thirdly, per share earnings must be accelerated by increasing net assets. Retained earnings of the firms can be used to invest into profitable activities, which will make the firms grow in future and rise in share prices. Fourthly, the total deposits of the firms need to be increased by enhancing their reserves. Besides increasing reserves, total deposits can be accelerated if authorities can minimize their loans. These set of financial policies would make FEP a reasonable proxy for SFP enhancement.
Performance can never be attained by achieving financial goals only; instead, SEP must be performed to revive the stalled privatization transactions. Therefore, the developed framework's stage 2 consists of SEP formulated by professional managers, team leaders, supervisors, and other stakeholders directly concerned with the firms. Strategies must be introduced in the areas of reward policies, redefining organizational purpose, coordination mechanism among employees, and employee supervisor relationships to eliminate conflicts. There is a core need to develop reward policies for employees by providing them opportunities to grow their areas of skills. Furthermore, promotion opportunities and salaries given as per performance may be enhanced to improve employee effectiveness. Secondly, the organizational purpose must be redefined as per organization's vision and mission. The policy makers must emphasize better utilization of human resources by improving their morale, motivation, and commitment to work. Likewise, the organization's goals and priorities are needed to be clearly understood by the employees. Thirdly, the professional managers must devise strategies for coordination mechanisms among the employees and their supervisors. Lastly, the organization needs a friendly and professional environment to enhance relationships among members, which is the responsibility of the seniors and professional managers. SFP is estimated in stage 3, which is the resultant impact of stage 1 and stage 2. Performance can be measured by return on assets and profitability. The financial manager must measure how well a firm's assets are used to generate profits, since the firm owners care more about profitability, which is the measure of firm's earning in its equity investments. The alignment of FEP coupled with SEP is helpful in achieving significant performance not only for the public entities, which are in the list of upcoming transactions, but also for the private firms, which are privatized earlier on their financial performance only.
The current research adds to the existent literature in two ways. On one hand, the mediating role of organizational development in evaluating firm performance has not been addressed in literature. Researchers are mainly interested in only evaluating the financial constraints and other non-financial constraints independently affecting the firm performance. On the other hand, the study brings forward the exploration of sustainable firm performance using an important statistical tool which is still less used and valued by researchers in the developing countries.
Focusing on the practical and theoretical implications of the study, several aspects may be considered important. The study brings a frame of reference for the new entrepreneurs exploring the market dynamics. They have the chance to consolidate and promote seven areas of organizational development model and significant financial indicators to compete with other banks despite difference in their financial position.

Limitation of Study
Given the real-life context of our research, we face several problems that limits our findings to some extent. The first limitation of the study is that it only covers the banking sector of Pakistan, due to the non-availability of updated organizational development data as it is easy to gather data from banking sector due to personal references. Another limitation relates to the specific period (2011-2015) considered for the analysis. It would be worthwhile to analyze a different period to confirm whether the relationship examined in the paper holds true for the non-crisis periods of banks and to check for any effects on strength of the linkage. The third limitation is related to the staff considered for survey; only those staff members were taken into account who had 5 consecutive years of experience (2011)(2012)(2013)(2014)(2015) in that specific bank.

Suggestion for Future Research
The limitation of this research point towards topics to be addressed in future. A comparative analysis can be made among different category of organizations to categorize the sectors according to their financial and social ranking. What additional statistical tools are available that assist us to identify the changes occurring in firm? The research model could be improved by the inclusion of more detailed and focused measures of the constraints.