In general, scholars have different interpretations and responses to the ideas and principles of organizational effectiveness (Hartnell et al., 2011; Denison et al., 2012; Grabowski et al., 2014). With the complexity of modernity, the idea of effectiveness continues to grow with organizational effectiveness being exchanged to increase organizational employee performance productivity. Thus, Quinn and Rohrbaugh (1981, p. 131) have described organizational effectiveness “as agility in decision-making, innovativeness, adaptability to the changing environment, competing with rivals, optimal utilization of resources and talent retention”. Nevertheless, the literature has stressed that organizational culture is a critical factor in determining organizational effectiveness and efficiency (Heracleous, 2001; Denison et al., 2012; Hassan et al., 2021). Organizational culture is one of the most important features of effectiveness as it determines the standards and values of an organization. Furthermore, Denison et al. (2012) and Chatman and O'Reilly (2016) highlighted that organizational culture shapes organizations and provides a better understanding of their effectiveness. Therefore, organizational culture is related to organizational effectiveness. The competing values by Langer and LeRoux (2017) described that organizational culture is suggestively related to organizational effectiveness Gregory et al. (2009). and Zheng et al. (2010) also indicated a positive relationship between organizational culture and effectiveness. Furthermore, recent research has shown that organizational culture has a significant impact on organizational effectiveness (Baek et al., 2019; Adisa et al., 2020; Volkova & Chiker 2020). Thus, the following theory is developed based on the logical argument:

Hypothesis 1. Organizational culture has a positive effect on organizational effectiveness.

Organizational innovation is a crucial factor in an organization's development and growth (Cameron & Quinn, 2011a) Hult et al. (2004)., explore an organization's overall innovative capability of bringing new products to the market or opening up new markets by integrating strategic orientation with innovative behavior and procedures.

Therefore, employees’ behavior at an individual level, team behaviors, and management behaviors are all examples of behaviors that can be experienced by management or decision-makers at different stages (Wang & Ahmed, 2004; Azar & Ciabuschi, 2017). Thus, behavioral innovation has a continuous impact on the culture of innovation. Furthermore, individual innovation is an employee's perception toward the innovation process, whereas organizational innovation is the behavior of a firm or company to embrace new things, ideas, and the company's attitude toward innovation (Shahzad et al., 2017; Alexe & Alexe, 2018). The central principle of strategic innovation is an organization's ability to track and evaluate its goals. Nonetheless, strategic innovation considers business as a whole and proceeds to make it workable over time (Haned et al., 2014; Grillitsch et al., 2019). Additionally, strategic innovation is formed when an organization identifies gaps in industry positioning and products, and employees’ behaviors help the innovation process in the hope of filling the gaps (Duan et al., 2020; Ode & Ayavoo, 2020). Further, Khessina et al. (2018) stated that organizational innovation could be compromised due to low employee expectations. Therefore, the implementation of a new concept or behavior that improves organizational effectiveness is referred to as organizational innovation (Jung & Lee, 2016; da Silva Lopes et al., 2019; Ghazali et al., 2022).

Furthermore, owing to their need for competitive advantage and sustainability, companies place a high value on organizational innovation. Eventually, when considering a competing value framework (Ashraf & Khan 2013; Domínguez-Escrig et al., 2019), organizational culture is expected to be effective to the extent of organizational effectiveness. The influence of organizational culture on organizational innovation varies based on the required effectiveness of the organization. Thus, we predict that organizational culture forms the organizational innovation perceptions of employees, such that these employees perceive procedures and practices that require and reinforce innovation behaviors in the workplace (Szczepańska-Woszczyna, 2015; Shanker et al., 2017). Therefore, we propose the following hypothesis:

Hypothesis 2. Organizational innovation mediates the relationship between organizational culture and organizational effectiveness.

Organizational culture contributes toward maintaining a positive workplace environment as well as organizational performance and effectiveness (Ahmad et al., 2009; Janicijevic, 2011; Taylor, 2014). Organizational culture and employee behavior are prime concerns in the workplace to achieve organizational effectiveness; therefore, cultural characteristics are essential for sustaining and enhancing organizational culture (Millett, 2000; Zhang & Zhu, 2012). Additionally, the biggest challenge in changing an organization is overcoming opposition to the number of organizational culture mechanisms to increase effectiveness (Rafferty & Jimmieson, 2016; Lenka et al., 2018). Generally, culture can both help and impede the transition process, thus it can be both a blessing and curse when it comes to enduring change successfully (Taylor, 2014; Bereznoy, 2019; Hammood et al., 2020). Thus, employees will continue to work against a change initiative because they feel they have no stake in the process, do not want to take on the increased work that comes with change, are concerned about their lack of required skills to succeed in the organization after the change, or are concerned that they may lose their jobs (Starzyk & Sonnentag, 2019; Lashitew et al., 2020).

Moreover, according to Oreg (2006) and Cameron and Quinn (2011b), organizational resistance is concerned with how organizational principles and productivity are influenced by employees Oreg (2006). and Lenka et al. (2018) divided organizational resistance into three categories: affective, cognitive, and behavioral resistance. Affective resistance is a reaction that focuses on workers' negative feelings about organizational change (Szabla, 2007; Oreg et al., 2011). Employee emotions are represented by cognitive components of resistance. For instance, in cognitive resistance, employees have a strong desire to learn whether the change is mandatory or advantageous to them or the organization. Additionally, cognitive reactions involve employees’ critical thinking about organizational change (Oreg, 2006; Oreg et al., 2011; Ming-Chu et al., 2015). Finally, the behavioral factor of resistance refers to workers' intentions, behaviors, or responses as top management tries to implement changes. Typically, employees would argue about the negative aspects and try to justify the negative consequences of organizational change, but when they feel they are at stake in the change process, they will respond positively (Oreg et al., 2011; Merhi & Ahluwalia, 2019).

Thus, we premise that organizational resistance is significantly contingent on the relationship between organizational innovation and organizational effectiveness with different supporting reasons. Employees’ support for or resistance to new values is related to an organization's cultural innovation. Owing to the significance of organizational culture and resistance factors for the betterment of an organization, it is necessary to understand the relationship between resistance and culture (Pakdel, 2016; Merhi & Ahluwalia, 2019). Sometimes, change is unsuccessful because of resistance, either active or passive, from those within the organization. Hence, as stated earlier, people resist change for various reasons (Oreg et al., 2018). For example, employees may actively work against a change initiative because they feel that they have no stake in the change process, do not want to take on the increased workload, are concerned about their lack of needed skills to thrive in the organization after the change, or are worried that they might lose their jobs (Starzyk & Sonnentag, 2019; Alfes et al., 2019). Thus, true change in an organization may mean that job positions and titles also change, which means that roles and responsibilities may shift as well (Garcia-Lorenzo, 2020; Gillebaart & Kroese, 2020). Resistance occurs when employees understand how they fit in with a new way of doing things, such that the positive impact of organizational innovation on effectiveness is stronger when employees understand how they may shift with a new change that would change their job and salary position, so they react differently. Thus, according to the above-mentioned argument, the following hypothesis is proposed:

Hypothesis 3. Organizational resistance moderates the relationship between organizational innovation and organizational effectiveness, such that the relationship is stronger when employees highly accept a change that is low.

Organizational resistance, the expected indirect impact of organizational culture on effectiveness through organizational innovation, may have interaction factors. Organizational culture is regarded as one of the most significant factors in assessing an organization's effectiveness as well as one of the most powerful components of an organization that forms norms and values (Felipe et al., 2017). Thus, organizations that pay attention to their employees’ perceptions to increase their effectiveness, developed through social relationships of employees with managers and colleagues, contribute to shared perceptions of the cultural content of workplace procedures and practices (Rafferty & Jimmieson, 2017; Metwally et al., 2019). Therefore, it is no surprise that organizational resistance might moderate and strengthen the positive indirect impact of organizational culture on effectiveness, which can maximize the effectiveness of the organization. Consequently, organizational resistance can be a powerful influence because the organization creates an environment that leads to positive effectiveness via innovation within the organization, especially when employees have a positive perspective to accept the change in the organization (Stanley et al., 2005; Lenka et al., 2018). Thus, we predict the following:

Hypothesis 4. Organizational resistance moderates the indirect effect of organizational culture on organizational effectiveness through organizational innovation, such that the indirect effect is stronger for followers who are higher in accepting the change than lower.

This study followed the deductive approach using a non-probability purposive sampling technique (Hulland et al., 2018). Therefore, managers and employees working in the commercial banking industry in Pakistan are this study's target population.

To reduce the probability of common method variance (CMV), the surveys were sent to 15 banks. Thus, we gathered data from a variety of sources, including managers and their subordinates, over two time periods (Podsakoff et al., 2003; 2012). We distributed surveys to 310 employees and 135 managers. In the first wave of data gathering, employees provided their demographic data and assessed organizational culture, organizational innovation, and organizational resistance. One week later, in the second wave, managers evaluated the organizational effectiveness. In these two waves of employee surveys, a total of 280 participants completed the survey (response rate =90%). One week later (second wave), we distributed questionnaires to 135 managers, out of which only 124 responses were returned (response rate =91%). Thus, across the two waves of data collection, we obtained 280 matched dyad surveys. Furthermore, senior human resource personnel in each bank were contacted prior to conducting the survey to obtain the approval for the study; the survey was administered after the permission was given. Survey packets containing the questionnaire, a pre-stamped envelope, and a cover letter were sent to respondents. The cover letter clarified the survey's aim, informed participants that their responses would be kept private, and asked them to return the completed questionnaire using the pre-stamped envelope. We also prepared the questionnaire to make the variables appear in a way that increased the psychological distance between the predictors and criterion variable (Afthanorhan et al., 2021).

All variables were measured by self-reporting on multi-item scales derived from previous studies. Therefore, all measures were evaluated using a seven-point Likert-type scale, with 1 representing strongly disagree and 7 representing strongly agree. All the items are presented in Appendix 1.

When examining a latent construct, the distinction between reflective and formative indicators should be carefully considered (Becker et al., 2012; Sarstedt et al., 2019). Reflective measures are strongly correlated indicators (interchangeable) assumed to be caused by a targeted latent construct, and are generally suggested when personality and attitudinal variables are modeled. However, formative measures encompass indicators that may govern the construct without necessarily being highly correlated (uninterchangeable) such that traditional reliability and validity criteria may be inappropriate and irrelevant (Cheah et al., 2019; Sarstedt et al., 2019).

We used the above-mentioned parameters to differentiate between reflective and formative constructs (i.e., the direction of causality, interchangeability, covariation and antecedents/consequences of indicators or dimensions) (Sarstedt et al., 2019). Hence, our study encompassed two types of reflective and formative variables, which are composed of multiple first-order constructions, each representing an important aspect of the targeted construct second-order constructs. Given its complexity, organizational culture, organizational innovation, and organizational resistance were modeled as a second-order formative construct. Therefore, the type of formative construct is sensitive as dropping any of the dimensions would alter the conceptual domain (e.g., Becker et al., 2012; Cheah et al., 2019; Sarstedt et al., 2019).

Organizational Culture: 24-items were adapted from previous studies to measure organizational culture (Cameron & Quinn, 2011a), which encompasses four dimensions: clan, adhocracy, market, and hierarchy (6-items) for each dimension, which were measured reflectively as first-order constructs. Therefore, in the next stage, the four dimensions form the second-order construct of organizational culture, such that higher scores indicate a stronger organizational culture.

Organizational Innovation: 8-items were adapted from (Wang & Ahmed, 2004) which comprises both behavioral (4-items) and strategical innovation (4-items), these two dimensions were measured reflectively as first-order constructs and later these two dimensions established organizational innovation formatively where the high scores of these dimensions indicate a stronger organizational innovation.

Organizational Resistance: We measured organizational resistance using three dimensions: effective, cognitive, and behavioral (6-items) for each dimension, which were slightly adapted from prior studies (Oreg, 2006). Nevertheless, these three dimensions–effective, cognitive, and behavioral–were treated reflectively as first-order constructs, and these dimensions formatively established the higher-order construct, which is organizational resistance.

Organizational Effectiveness: Organizational effectiveness was measured using 13-items taken from Gold, Malhotra, and Segars (2001). Thus, we combined these responses for each participant to form a Mode A first-order composite variable, for which higher scores indicated stronger organizational effectiveness among respondents.

Control Variables: Finally, we used firm size and age as control variables for their potential relationship with organizational effectiveness. Firm size was measured as the number of full-time employees, and age was measured by the number of years in business.

Our data included demographic data such as gender, age, education, job experience, and banks’ name. A total of 75.4% of the respondents were male and 24.6% female, 22.1% were under 30 years old, 42.5% were aged between 31 and 40, 21.1% were aged between 41 and 50, and 8.6% were aged above 50. Regarding education, 14.6% had completed high school, 16.1% had a diploma, 56.8% had a bachelor's degree, 5.7% had a master's degree, 4.6% had a Ph.D. Regarding experience, 5.7% had less than two years of experience, 18.6% had 3-5 years, 38.9% had 6-10 years, 10.4% had 11-15 years, and 26.4% had more than 16 years. Finally, with regard to the bank's names, 17.9% of our data came from MCB Bank Ltd, 13.6% from National Bank of Pakistan, 13.7% from Allied Bank Ltd, 17.1% received from Habib Bank Ltd, 16.5% from Bank Alfalah Ltd, and 10.6% from United Bank Ltd. The details are presented in Table 1.

Appendix 1 contains the indications for individual reliability, construct reliability, and convergent validity of all reflective latent variables. Additionally, Appendix 1 contains indices that aid in the accurate calculation of second-order formative constructs.

As shown in Appendix 1, the reliability of individual items encompassing the reflective constructs (clan, adhocracy, market, hierarchy, behavioral innovation, strategic innovation, effective resistance, cognitive resistance, behavioral resistance, and organizational effectiveness) was considered good because their standardized loadings were higher than the minimally acceptable value of 0.7 (Hair et al., 2017). Furthermore, the construct reliability was supported in that the composite reliabilities (CR) for all the reflective constructs were 0.7 or better (Hair et al., 2017). Finally, the average variance extracted (AVE) also exceeded 0.50, supporting convergent validity (Henseler et al. 2009; Hair et al., 2017). Formative variables revealed minimal collinearity, as the respective variance inflation factors (VIF) ranged between 1.426 and 2.270 (see Appendix 1), far below the common cutoff threshold of 5 (Hair et al., 2017). Therefore, it can be concluded that collinearity does not reach critical levels in any formative construct. Finally, the significance and relevance of the outer weights and t-values of the formative constructs are examined. Thus, as Appendix 1 shows, all the formative indictors are significant (Hair et al., 2017). Therefore, we can also conclude that the formative measurement model was achieved.

Regarding discriminant validity of reflective measures, Table 2 presents evidence that the AVE for each of the reflective constructs is greater than the variance shared with the remaining constructs (Henseler et al., 2009). Discriminant validity was also supported in that an additional alternative analysis (e.g., cross-loading matrix) reflected that all the indicators of measures loaded more heavily on their intended constructs than in others (Fornell & Larcker, 1981; Henseler et al. 2009). In addition, the heterotrait-monotrait (HTMT) ratio values were analyzed to assess discriminant validity. HTMT is defined as the ratio of the average heterotrait-heteromethod correlation to the average monotrait-heteromethod correlation, according to Henseler et al. (2015). The results of the HTMT ratios in Table 3 reveal that they are below the 0.85 threshold recommended by Kline (2015). Thus, the results of this study validated the second-order formative construct, including organizational culture (clan, adhocracy, market, and hierarchy) and organizational innovation (behavioral and strategic) for organizational resistance (effective, cognitive, and behavioral).

The control variables aid in determining whether there are any possible reasons for our results, as well as in reducing errors. Thus, none of our control variables, such as size or age, had a significant effect on organizational effectiveness (see Fig. 2).

Fig. 2.

Research model: hypotheses testing.

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Table 4 and Fig. 2 present the direct, indirect, and interaction effects of H1–H3. In support of H1, organizational culture was significantly related to organizational effectiveness (β = 0.311, t = 4.811, p < 0.000). Regarding H2, we predicted that the positive influence of organizational culture on organizational effectiveness is significantly mediated by organizational innovation. Therefore, we employed a bootstrapping technique with 5,000 subsamples, which revealed a significant indirect effect of organizational culture on organizational effectiveness through organizational innovation (indirect effect = 0.176, t = 3.957, p < 0.000). So, as Preacher and Hayes (2004, 2008) mentioned when the 95% CI does not include 0 (lower limit = 0.069, upper limit = 0.283), this indicates that there is mediation. Therefore, this study confirms the mediating effect of organizational innovation on the relationship between organizational culture and organizational effectiveness; hence, H2 is supported.

Additionally, we examined H3 as a simple model. Based on the results presented in Table 4 and Fig. 2, the interaction between organizational innovation and resistance has a significant effect toward organizational effectiveness (β = 0.197, t = 2.167, p < 0.001). Therefore, the moderation of organizational resistance, H3, is supported. Thus, for the purpose of interoperation, we followed Dawson's (2014) method, where we plotted high versus low organizational resistance regression lines (+1 and –1 standard deviation from the mean). This step indicates that the positive relationship between organizational innovation and organizational effectiveness is stronger (the slope is more pronounced) when organizational resistance is high rather than low (see Fig. 3). Thus, organizational resistance is a positive moderation.

Fig. 3.

Interaction plot of organizational innovation × organizational resistance on organizational effectiveness.

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Finally, we examined moderated mediation (H4) (Hayes, 2015), which suggests that the indirect effect of organizational culture on organizational effectiveness through organizational innovation is strengthened by the level of organizational effectiveness. We followed the recommendations of (Preacher et al., 2007; Hayes, 2013, 2015), and the bootstrapping procedure with 5,000 subsamples was run. Thus, according to the results shown in Table 4, the positive indirect effect of organizational culture changes at distinct levels of organizational resistance acts as a moderator (Preacher et al., 2007; Hayes, 2013). Also, Table 5 indicates that the positive indirect effect matches our prediction when organizational resistance levels are higher: at -1 standard deviation below the mean (low organizational resistance), the positive effect is weaker (B = 0.310, SE = 0.054, 95% CI = 0.321, 0.511) than at +1 standard deviation above it (high organizational resistance) (B = 0.518, SE = 0.054, 95% CI = 0.421, 0.612). Finally, the index of moderated mediation did not include 0 (index = 0.182, SE = 0.053, 95% CI = 0.158, 0.244), which meets the condition and provides evidence of moderated mediation (Hayes, 2015, 2017). Thus, organizational resistance strengthens the positive indirect effect of organizational culture on organizational effectiveness (Table 5).

First, to evaluate the model's in-sample fit, we consider R2. Thus, we find that the endogenous constructs (Organizational Effectiveness) gain R2 values of around (R2=0.415) which can be considered to have a moderate to substantial effect (Hair et al., 2017).

Second, we consider out-of-sample predictive power, using PLSpredict with 10 folds and one repetition to mimic how the PLS model will eventually be used to predict a new observation, rather than using the average across multiple models (Shmueli et al., 2019; Hair et al., 2019b). However, we concentrate our research on the model's main target construct to demonstrate the interpretation (organizational effectiveness) but also state the predictor estimation statistics for all other endogenous constructs. Therefore, in the first step, we find that all the endogenous constructs’ indicators outperform the most naïve benchmark (i.e., the training sample's indicator means), as all indicators yield Q2 prediction values above 0 (see Table 6). Next, the linear regression model (LM) approach regresses all exogenous indicators on each endogenous indicator to generate predictions. In comparison with the LM outcomes, the PLS-SEM results should have a lower prediction error (e.g., in terms of RMSE or MAE) and greater Q2 values. This means that a theoretically defined path model enhances (or at the very least does not worsen) the statistical output of available indicator data. This is the case with our model. All RMSE and MAE values for the PLS model are lower than those for the LM model. Additionally, the Q2 values for the indicators of the PLS model are larger than those generated for the LM model (Table 6). Therefore, we can assume that our model has a high level of predictability. (Hair et al., 2019b),

This study makes vital contributions to the literature by expanding the competing value framework, which explains the relationship between organizational culture and effectiveness in the banking sector. The competing values framework is a specific theory that provides empirical evidence regarding organizational culture and effectiveness. Previous studies have revealed a positive and significant relationship between organizational culture and organizational effectiveness (Gochhayat et al., 2017; Meng & Berger, 2019). However, this study verifies and re-establishes this relationship in the context of the Pakistani banking sector. Consequently, by investigating how organizational resistance influences organizational effectiveness in an underdeveloped country like Pakistan, this study will contribute significantly in confidently generalizing the findings to different cultures and sectors. Second, this study contributes to the extant literature on the relationship between organizational culture and effectiveness through a mechanism such as organizational innovation. To the best of our knowledge, previous studies have overlooked the link between this relationship and the underlying mechanism. This study makes a significant contribution by expanding this limited stream of research.

Importantly, this study argues that organizational culture and innovation have a positive effect on organizational effectiveness. Thus, clarifying that these effects may be contingent on the situation and, particularly, on follower-related variables, such as adapting to changes. We identify organizational resistance as an important boundary condition for the effect of organizational culture on organizational effectiveness through organizational innovation. Thus, this study proves that adapting to changes embedded in workplace procedures and positive perception (i.e., organizational culture and innovation) prompts the effectiveness of the organization to survive in a competitive advantage in this rapid change of technology and market. Thus, organizational resistance acts as a moderator.

This study has several practical implications. Usually, the banking sector in Pakistan plays a vital role in the country's economy (Asrar-ul-Haq & Kuchinke, 2016). However, most bankers, banking leaders, and executives focus on financial aspects such as how to increase sales, improve profitability, and maintain credit limits. Unfortunately, non-financial aspects that concentrate on organizational culture and major changes in banks regarding structure or employees’ attitude toward change have been ignored. This is a common problem in eastern and developing countries (Aibar-Guzmán et al., 2022). They do not focus on and invest in behaviors and changes. The present study recommends to the Pakistani banking sector that they should consider banking culture as an “asset” like the assets of banks. Organizational culture can be an intangible asset of banks that can help improve banking effectiveness. Bank managers, change management practitioners, organizational development practitioners, business leaders, and change agents are beginning to raise their awareness of the importance of organizational culture. The current study hopes that awareness regarding organizational culture will be extensively increased because it has implications for the Pakistani banking sector. The Pakistani banking sector can enhance banking effectiveness by giving due attention to organizational culture, as it is an integral part of their organizations.

In addition, this study advises that the banking sector in Pakistan focus more on building organizational culture because this value is related to the organization. Practically, this culture can be viewed by both employees and customers. For instance, adapting innovation aspects that can help develop new products and services helps explore new markets and strategies. The top management of organizations always tries to improve innovation habits among employees (Wang & Ahmed, 2004). Therefore, shaping and organizational innovation with a proper introduction of innovation and a better understanding of change dynamics could be shared among employees, that leads to positive outcomes such as organizational effectiveness.

Finally, the current study suggests that Pakistan's banking sector focuses more on building organizational culture because this value is related to the organization. However, the banking sector should differentiate between change and innovation. Resistance is a hidden factor influencing development. This study shows that the Pakistani banking sector does not have any specific culture, but uses the four cultures simultaneously. Thus, our results reveal that organizational culture, innovation, and resistance are important predictors of organizational effectiveness. Therefore, bankers and banking management in Pakistan must recognize the importance of these factors. In addition, bankers in Pakistan need to focus on resistance practically to improve their effectiveness. Most importantly, bankers should know what kind of resistance (affective, cognitive, or behavioral) is present. By controlling for the resistance factor among employees, culture, change, and innovation can provide positive results. The current study adds new knowledge regarding organizational culture, innovation, and resistance in South Asian countries, such as Pakistan, in the banking sector.

While this study has some implications, it also has some limitations that leave an area for future research. The first drawback of this study is that it is based on cross-sectional results, which means that a causal inference cannot be drawn, making it difficult to draw conclusive conclusions about causality. Nevertheless, analyzing critical issues such as organizational culture, innovation, and effectiveness requires total anonymity, making longitudinal research difficult (e.g., Podsakoff et al., 2003). This opens the path for additional investigations into formulas for longitudinal or experimental designs that can help improve the causality of the results. The second limitation is that the sample of this study is from the banking industry in Pakistan. The cultural context in the banking industry is unlike other organization policies. Thus, future work can choose to concentrate on a different sector to validate and generalize recent evidence. Third, we gain a better understanding of the links between organizational culture and effectiveness in the banking industry. Nevertheless, other additional variables, such as knowledge management, organizational learning, employee performance, and corporate suitability, should also be analyzed in future research to explain the mediating role of organizational resistance. Furthermore, there should be more integration and a different set of values to measure aspects of organizational culture. Therefore, it is necessary to incorporate a broader set of culture types (Hartnell et al., 2011). Finally, as mentioned previously, this study was conducted in Pakistan. As it is limited to the Pakistani context, the results cannot be generalized to other South Asian countries due to geographical, political, cultural, and other differences.