Evaluating the Impact of Organizational and Cultural Barriers on Organizational Performance Indicators and the Moderating Effect of Management Support: An In-Depth Exploration of Ghana’s Oil, Gas, and Telecommunication Sectors

Evaluating the Impact of Organizational and Cultural Barriers on Organizational Performance Indicators and the Moderating Effect of Management Support: An in-Depth Exploration of Ghana’s Oil, Gas, and Telecommunication Sectors

Suleman Mohammed Yakubu, Kingsley Tornyeva

Accra Institute of Technology (AIT) Department of Business Administration Accra-North-Ghana

DOI: https://dx.doi.org/10.47772/IJRISS.2025.90500061

Received: 15 April 2025; Accepted: 23 April 2025; Published: 29 May 2025

ABSTRACT

The study “Evaluating the Impact of Organizational and Cultural Barriers on Organizational Performance Indicators and the Moderating Effect of Management Support” considers various configurations on how internal impediments impact performance metrics within the oil, gas, and telecommunications industries in Ghana. The main research question is as follows: What impacts do organizational and cultural barriers have on key performance indicators (KPIs), and how do they interact with management support as a moderator? The method adopted is mixed with explanatory sequential design with the quantitative data collected through questionnaires completed by a purposive sample of 240 employees across the private and public sectors. It was followed by qualitative interviews. The validity, reliability, and relationships concerning the structural model were assessed using statistical techniques, among which was Partial Least Squares Structural Equation Modeling, (PLS-SEM) and descriptive statistics. It turned out that there exist a significant positive relationship between organizational and cultural barriers and performance indicators being investigated; for instance, return on asset (ROA) and market share. Financial and market performance are ironically improved by barriers structurally increasing consistency, discipline, and strategic alignment, contrary to the traditional obstacle paradigm of successfully performing with barriers. The moderating influence of management support seems weak and does not have much direct influence on market share. The study takes the position that internally existing constraints convert into organizational assets contingent upon their strategic alignment, pointing at the need for process-oriented leadership and sector-specific strategies. Recommendations included creating a culture of adaptive management, promoting structured systems together with creative methodologies, and adopting leadership styles according to the culture of the organization. It is recommended that latter studies evaluate how these interactions play across different sectors and what potential long-term effects these barriers may have on innovation and organizational agility.

KEYWORDS: Organizational Barriers, Cultural Barriers, Performance Indicators, Management Support, Organizational Performance.

INTRODUCTION

Organizational performance is pivotal for companies aiming to meet strategic goals, secure competitive advantages, and ensure sustainability over the long term. Yet, internal challenges, particularly organizational and cultural barriers, frequently hinder performance. These barriers can manifest as ineffective communication, resistance to change, misaligned values, and diminished trust (Schein, 2020). The importance of recognizing and addressing these obstacles has become increasingly relevant, particularly in dynamic industries such as oil, gas, and telecommunications. Management support has emerged as a critical moderating factor, influencing how these barriers impact performance outcomes. Organizational barriers refer to structural and procedural impediments that disrupt effective decision-making, communication, and collaboration (Cameron & Quinn, 2011). Examples include hierarchical rigidity, bureaucratic inefficiencies, lack of coordination, and insufficient technological integration. Conversely, cultural barriers stem from the underlying values, beliefs, and behavioural norms that dictate employee interactions and institutional practices. Hofstede (2001) highlights dimensions such as power distance, collectivism versus individualism, and uncertainty avoidance, which can profoundly affect organizational dynamics. In high-stakes sectors like oil, gas, and telecommunications, where agility, collaboration, and innovation are essential, cultural rigidity and ineffective organizational design can lead to decreased efficiency, project delays, and low employee morale (Alvesson, 2012; Ogbonna & Harris, 2000).Key performance indicators such as productivity, profitability, customer satisfaction, employee retention, and innovation are directly influenced by an organization’s internal health. Research indicates that organizations with high cultural congruence and effective structures tend to outperform those plagued by internal conflicts and siloed operations (Denison, D. R., Nieminen, L., & Kotrba, L. (2021). For instance, a disconnect between organizational objectives and employee values can result in disengagement and diminished productivity (Kotter & Heskett, 1992). Management support is vital for cultivating a positive organizational culture and addressing structural challenges. This support encompasses leadership commitment, resource allocation, transparent communication, and employee empowerment (Yukl, 2021). When management actively promotes change and inclusivity, the adverse effects of organizational and cultural barriers on performance can be alleviated. Research by Eisenberger et al. (2002) demonstrates that perceived organizational support, particularly from leadership, boosts employee engagement and performance. Furthermore, effective management can create a climate of trust and psychological safety, encouraging employees to express concerns, innovate, and collaborate essential drivers of performance in complex sectors (Edmondson, A., & Moingeon, B. (1999).  In the Ghanaian context, where hierarchical leadership is often pronounced, intentional management support can mitigate cultural constraints like high power distance and resistance to innovation (Agyemang et al., 2020). Addressing organizational and cultural barriers is crucial not only for enhancing performance but also for achieving strategic alignment, regulatory compliance, and market adaptability. Interventions such as leadership training, cross-cultural workshops, process re-engineering, and participatory management models are increasingly recognized as effective strategies (Burnes & Jackson, 2011). In conclusion, if left unaddressed, organizational and cultural barriers can significantly impede performance indicators. However, robust management support can transform these challenges into opportunities for innovation and strategic growth. Organizations, particularly in complex industries such as oil, gas, and telecommunications in Ghana, must implement proactive strategies to realign cultural norms and organizational structures with their performance objectives

Statement of the Problem

Organizational and cultural barriers critically hinder the achievement of essential performance metrics, especially in dynamic industries like oil, gas, and telecommunications. In Ghana, these sectors grapple with on-going issues related to bureaucratic inefficiencies, ineffective communication, and deeply rooted cultural practices that stifle innovation, teamwork, and adaptability (Amponsah-Tawiah & Mensah, 2016). Consequently, these barriers contribute to low employee engagement, diminished customer satisfaction, and less-than-ideal financial performance (Gyensare, Anku-Tsede, Sanda, & Okpoti, 2016). For instance, rigid hierarchical structures and ethnocentric management styles can create disconnects between leadership and operational teams, obstructing effective decision-making and service delivery. Research indicates that robust management support can mitigate the negative impacts of organizational and cultural barriers on performance outcomes (Boateng, Dzandu, & Agyemang, 2020). Effective management encourages open communication, inclusive leadership, and cultural competence, all of which are vital for overcoming resistance to change and boosting employee morale. In Ghana’s oil and gas sector, for example, proactive management in promoting diversity and inclusivity has been associated with increased job satisfaction and productivity (Amoako-Gyampah & Boye, 2020). Similarly, in telecommunications, leadership commitment to organizational development is linked to improved service quality and enhanced customer loyalty (Owusu-Mintah & Emmanuel, 2019). Despite these findings, there is a notable lack of contextualized research exploring how management support interacts with organizational and cultural barriers to affect performance metrics within these industries. This study aims to fill that gap by offering actionable recommendations to enhance organizational effectiveness, thereby contributing to a more nuanced understanding of the interplay between management practices and performance in Ghana’s dynamic sectors.

General Objectives

The general objective is to investigate the effect of organizational and cultural barriers on organizational performance indicators and examine the moderating effect of management support on the relationship between organizational and cultural barriers and organizational performance indicators.

Theoretical Framework

The study is pined on Balanced Scorecard (BSC) framework and Contingency Theory. Contingency Theory suggests that there is no single best way to manage or lead an organization. Instead, what works best depends on the situation. This theory says that the effectiveness of a company depends on how well its internal systems (like structure, strategy, and leadership) match with external factors such as the environment, market conditions, and size (Fiedler, 1964). The theory was introduced in the 1960s by Fred Fiedler, an Austrian psychologist. He believed that a leader’s style, shaped by life experiences, is hard to change. Therefore, for a leader to be successful, their style must match the situation they are in (Fiedler, 1964). Tanzi and Zee (2001) and Uwauwa & Ordu (2021) supported this idea, showing that different elements in a business are connected and affect each other. According to Katz and Kahn (1966), no single method works in all business contexts. Different situations require different approaches. For example, Burns & Stalker (1961) found that leadership style, employee roles, decision-making, and company structure all influence business outcomes. A major turning point came in the 1950s when Joan Woodward studied how different production technologies required different management styles. Koontz (1961) also stated that management practices should depend on the situation. Effong and Ejabu (2020) further explained that decisions in a company should consider factors like company size, market uncertainty, and available technology. The key idea in Contingency Theory is flexibility. Managers should adjust their strategies based on the specific needs of their companies and environments. Aghonfoh et al. (1996) emphasized that because all companies and people are different, one method may work for one company but not another. So, solutions should be customized. This theory also supports a “fit” between company structure and its environment to achieve better performance (Betts, 2003). For example, Shu’ara and Amin (2022) argued that leaders must change their approach depending on the situation, which shows the importance of adaptability. Research by Chandler (1962), Miles and Snow (1978), and Rumelt (1974) showed that a company’s strategy and structure must align with market opportunities to succeed. This connection between strategy, structure, and performance is a major part of the theory. Similarly, Chenhall & Langfield-Smith (2007) pointed out that management accounting systems should be tailored to suit different business needs like budgeting, costing, and measuring performance. However, the theory has some criticisms. Galunic & Eisenhardt (1994) argue it can be too rigid, assuming companies remain static once they find a “fit.” Rollinson et al. (1998) added that managers often face conflicting demands in a single situation, and the theory doesn’t always guide how to resolve these conflicts. Still, Ayres, Kolb, & Seashore (1997) and Baker (1973) pointed out that how a manager handles these situations depends on what they consider most important in each case. Despite its flaws, Contingency Theory remains useful because it helps businesses respond to change. New developments like the Structured Adaptation to Re-establish Fit (SARFIT) model help businesses redesign strategies to match changing situations. Ouchi & Maguire (1957) highlighted how this theory encourages creativity and flexibility, helping firms remain competitive. In Ghana, this theory is especially useful for industries like oil and gas and telecommunications. These sectors face constant change due to price shifts, regulations, and technology. For these companies, combining financial and non-financial performance measures is essential. Managers must look at both internal factors (like company culture and resources) and external ones (like laws and customer demands) to succeed. The theory also supports the study’s goal of understanding how cultural and organizational barriers affect business performance in these sectors. It shows how management support can moderate the relationship between these barriers and company performance. In conclusion, Contingency Theory is a valuable tool for understanding how businesses can align their strategies with their specific situations. It highlights the need for flexible leadership and context-based decision-making. By using this theory, companies in Ghana’s oil, gas, and telecom sectors can better handle change and improve performance by creating strategies that suit their unique challenges.

 Empirical Review

Organizational and cultural barriers notably hinder performance within Ghana’s oil, gas, and telecommunications industries. Research indicates that management support plays a crucial role in moderating these challenges, thereby fostering adaptability and operational efficiency. Effective leadership is essential in reducing resistance to change, aligning organizational processes and culture with strategic objectives, ultimately leading to enhanced performance outcomes in these sectors. This alignment not only facilitates smoother transitions during periods of change but also promotes a culture of continuous improvement, which is vital for sustaining competitive advantage in the rapidly evolving energy and telecom markets in Ghana. In a study by (Mueller, R. R. (2024) performed a research on the link between the Balanced Scorecard and corporate culture in different enterprises across the United States. The purpose of the study was to assess how the adoption of the BSC impacts corporate culture. The research revealed that the Balanced Scorecard can significantly influence corporate culture by promoting tactical thinking, which improves general corporate efficiency. Even though the study presents significant perspectives into the relationship between the Balanced Scorecard and corporate culture, it did not adequately assess the various mechanisms by which the BSC influence culture. Future research could incorporate qualitative data to better comprehend the multifaceted nature of corporate culture and examine how the BSC could be implemented in various sectors.  (Lastre Sierra, H., Ruiz Molina, A., & Barrón Villaverde, D. 2025) performed a qualitative study to assess the association between the Balanced Scorecard and corporate culture in several entities in Mexico. The study emphasized how adopting the BSC impacts the development of a performance-driven and transparent culture. The study concluded that the BSC develops a culture that focuses on performance measurements, thereby improving corporate efficiency and transparency among staff. Even though the study presents significant perspectives into the association between the Balanced Scorecard and corporate culture, it overlooked possible biases in data gathering and the effect of external variables on culture variations. A comprehensive review incorporating quantitative metrics and a bigger demographic sample would offer a deeper comprehension of how BSC impacts organizational culture, as well as broader evaluation of its influence in different corporate contexts. (Cameron and Quinn 2020) performed a qualitative study on the use of the Balanced Scorecard in the United States. The study attempts to determine whether introducing cultural measurements into the BSC paradigm could improve performance management. The findings showed that including cultural metrics not only improves the efficiency of performance management systems, but also promotes a more integrated and driven corporate culture. Nonetheless, the study emphasizes the positive impacts of cultural measures while ignoring the diversity of cultural dynamics across sectors and organizational sizes. A detailed examination of the problems that company’s faces while adopting the Balanced Scorecard would reinforce the argument and provide experts with concrete guidance cantered around actual-life situations. (He, M. 2024) performed a study on the adoption of the Balanced Scorecard in multinational corporations in Asia and Europe. The study sought to determine whether cultural factors influence the implementation and adjustment of the BSC across countries. The study found that cultural effects have a crucial role in influencing the efficiency of the BSC, underlining the necessity for adopted approaches to enable efficient implementation in different foreign contexts. However, the study did not discuss the cultural aspects influencing the Balanced Scorecard implementation. While the study acknowledges the value of cultural factors, it did not provide specific examples or case studies. An in-depth analysis of the relationship between culture and corporate structure would strengthen the investigation, rendering it more useful and pertinent for professionals seeking to adopt the Balanced Scorecard in varied cultural contexts. (Sharma, M. 2024) investigated the obstacles and techniques of implementing the Balanced Scorecard across varied regions, each characterized by unique cultures, market dynamics, and regulatory framework. Focusing on international companies within the automotive and consumer products industries, the study used qualitative analysis to examine how BSC implementation could be customized to fit specific circumstances. The study concluded that, while the BSC offers a strong framework for tactical coordination, its measures should be modified to each region’s unique requirements and challenges. Nevertheless, the research did not discuss the possible effect of regional technological breakthroughs or technological advancements on the efficiency of the BSC adoption. Future studies should look into how advances in data analytics or systems powered AI could streamline more successful and dynamic localizations of BSC indicators. Additionally, exploring how firms in developing markets, with various cultural and economic situations, encounter unique constraints when implementing a global BSC would be valuable.( Kaufmann, L., & Becker, A. 2006), examined the barriers to implementing the Balanced Scorecard in top multinational corporations, focusing on leadership, culture and technology incorporation. Using case studies from multinational corporations in the Unites States, Europe, and Asia, the study concluded that effective leadership, staff engagement, and a tactical alignment between BSC and corporate culture are crucial to addressing implementation challenges. The study further asserts that firms are more inclined to succeed in implementing the BSC paradigm if they have a compelling executive vision and a comprehensive approach to employee engagement. However, the study did not discuss the role of sector-specific variables or regional variances in technical preparedness. A comprehensive review of the challenges to Balanced Scorecard adoption encountered by firms in industries such as technology and manufacturing would yield significant conclusions. Additionally, investigating the effect of the digital age, specifically AI and big data in addressing these constraints would provide an enhanced comprehension of how these technologies aid in the resolution of BSC hurdles and enhance the effectiveness of organizational performance in different sectors.

METHODOLOGY

Research Design, Method and Approach

The research employed a case study design. An explanatory sequential research design has been chosen because it allowed the researcher to administer questionnaire to a quantitative larger sample size and conduct random interviews with a smaller qualitative sample size. For this study, the study used a population size of 500 employees from major sectors in Ghana, particularly the oil and gas, and telecommunication industries, both of which are crucial to the nation’s economy. The sample will encompass private companies such as MTN Ghana, Telecel, Airtel/Tigo, as well as public sectors entities such as Ghana Post Company, Bulk Oil Storage and Transportation Company Limited, National Petroleum Authority, Ghana National Petroleum Corporation, Petroleum Commission, Ghana Gas, and Ghana Oil Company. The sample size was derived from the formula;

Population size (N) =500, Sample size (n): 240, Z-value for 95% confidence level (Z):1.96

Estimated proportion (P):0.5, Margin for error (E):4.56% or 0.0456

n= NxZ2x P x (1-p)

       (N-1) x E2 +Z2x P x (1-p)

Z2=1.962 = 3.8416

P x (1-p) = 0.5 x (1-05) = 0.5×0.5=0.25

N x Z2 x P x (1-p) = 500 x 3.8416 x 0.25

500×0.9604=480.2

(N-1) x E2

(N-1) x E2= (500-1) x 0.04562

(N-1) x E2= 499 x 0.00207936

(N-1) x E2 =1.03889364

(N-1) x E2 +Z2x p x (1-p) = 1.03889364+0.9604=1.99929364

n =   480.2

   = 240

The approximate sample size of 240 is 5% of the target population of 500 which was representative enough of the entire population. For this research, purposive sampling was applied to intentionally target individuals which offers the most important perspectives related to the research objectives. Both closed and open-ended questions were used to allow easy compilation of responses collected in the questionnaires. This is to ask for more information on answers to closed ended questions as to the reasons why that answer so that we can have an in-depth understanding of the topic at hand. The collected data was analyzed using PLS–SEM as well as Microsoft Excel where descriptive statistical analysis were obtained, and results were summarized as graphs and tables for discussion.

Ethical considerations for this study included obtaining informed consent from participants, ensuring anonymity and confidentiality, and minimizing any potential harm to the participants

RESULTS AND DISCUSSION

This chapter presents the findings of this study. The purpose of this study is to exploring the role of financial perspective measures on organizational performance indicators and the moderating effect of management support: An empirical analysis of the oil and gas, and telecommunication sectors in Ghana. These findings enhance performance management literature by providing insights for decision-makers aiming to reconcile financial imperatives with strategic growth initiatives. The findings are presented in the form of tables and figures.

Table 4.1 Descriptive Statistical Analysis Result -Demographic

Source: Field Data (2025)

The demographic analysis Overview studied participants by sex, age, level of education, sector of industry, and work experience. Almost, equal representation of males and females in the sample. The female participants slightly outweighed the males as 122 out of 239 total participants were women (51.05%) while those that were men were 117 (48.95%). This balanced representation makes the research results more credible and generalizable. The higher numbers of female participants may denote the increasing participation of females in the sectors studied. Most subjects formed the 20-30 age category which made up 31.38% (or 75 respondents) showing a young workforce. Next came individuals of age 41-50, comprising 27.62% (66 respondents), while 31-40-year-olds constituted 25.52% (61 respondents). Older age groups, particularly those 51-60 (14.64%) and above 60 (0.84%), were less represented’. This alludes, however, to generational diversity, and it also appears that younger and mid-career professionals dominate the workforce, indicating a renewal. Bachelor’s degree holders made up the majority at 36 percent (86 respondents), followed by master’s degree holders at 29.7 percent (71 respondents). As much as 26.4 percent (63 participants) were professional certification holders, accounting for the high value put on specialized skills acquired. Only 7.9 percent (19 participants) possessed a doctorate, thus indicating fewer highly specialized academicians in the workforce. In general, the data state that bachelor’s and master’s levels were the most obtained qualifications augmented by relevant professional training. Most of participants’ results came from the telecommunication industry (60.3%, 144 respondents), with the oil and gas industries accounting for the remaining 39.7% (95 respondents). From this data, it is likely that the conclusions of this study would still lean towards those from the telecommunications sector, while also bringing in a valuable outside perspective from the oil and gas industry. The highest number of respondents showed between 4 to 6 years of experience (31.8%, 76 respondents), indicating a good percentage of mid-career professionals. In addition, 1 to 3 years (21.8%, 52 respondents) and below 1 year (21.3%, 51 respondents) formed a combined significant percentage representing many beginners in the professions. Meanwhile, 20.5% (49 respondents) had experience spanning between 7-10 years while only a small 4.6% (11 respondents) had above 10 years of experience indicating an under-representation of senior professionals. From demographic data, most people are young, mid-career, moderately experienced, fairly balanced in terms of gender with diverse educational backgrounds, and mainly drawn from the telecommunications sector

Measurement Assessment Model

The first stage in the evaluation of a measurement model is called outer model assessment, which uses Partial Least Squares (PLS) for Confirmatory Factor Analysis (CFA). This step addresses the relationship between the indicators (i.e. questions or items) and the hidden concepts (termed as latent constructs) proposed in the model. It acts as a confirming check for whether the data reasonably fits with the theoretical proposition. For tests of reliability and consistency of the indicators, researchers resort to Cronbach’s alpha and composite reliability. High reliability indicates that the indicators provide stable results. Validity is also established to ascertain that what is being measured is being measured. Convergent validity asserts that related indicators are strongly correlated, verified via Average Variance Extracted (AVE) and factor loadings. Accordingly, AVE has good indicators exceeding 0.50 and that the factor loadings are greater than 0.70. Tests regarding discriminant validity assure that each concept is clearly distinct from each other. Tests like the Fornell-Larcker criterion were then conducted. In all, the model proved to be reliable and usable to proceed to the next analysis.

Factor Loading

The numbers used to show how strongly an observed variable corresponds to a hidden or latent construct factor in factor analysis are factor loadings. A number that means between -1 and +1 belongs to this specific kind of value. A number closer to ±1 means there is a stronger link between that variable and that factor; on the other hand, values in the vicinity of 0 show a far weaker connection between the two. Factor loading values may be used in theory help understand how well items reflect those latent constructs under study in methods like PCA (Principal Components Analysis) and CFA (Confirmatory Factor Analysis). According to researchers, loadings above 0.70 are strong and reflect that the item is a good fit. Loadings below 0.40 are said to be weak and that the item might not belong in the model (Hair et al., 2019). These loadings test the validity and reliability of the model. The higher the loading, the better the indicator (item) represents the theory-the more accurate and trustworthy the measurement tool will be. In Table 4.2, those loading values can be observed.

Table 4.2 Factor Loading

Source: Field Data (2025)

Indicator multicollinearity

The Variance Inflation Factor (VIF) is an important diagnostic tool used to assess the existence of multicollinearity among predictors in regression analysis. Multicollinearity arises when independent variables exhibit significant intercorrelations, resulting in distortion of parameter estimates, inflated standard errors, and undermined statistical significance of predictors (Fornell 8 Bookstein, 1982). Consequently, this would provide unreliable coefficient estimation and decreases the model’s explanatory power (Gujarati 8 Porter, 2009). Hair, Ringle, and Sarstedt (2016) suggested the corrective measures including transformation, removal, or model re-specification if VIF values were more than five, indicating the presence of significant multicollinearity. The study indicated that VIF values in Table 3 were significantly lower than the critical threshold, confirming that there were no multicollinearity problems. The absence of strong collinearity will guarantee that their predictor variables influence their model independently, minimizing any bias in estimation and enhancing the precision of interpreting their coefficients (Kline 2015). The consequent strengthening of estimation robustness confirms the reliability of statistical inferences; hence the relationships observed among variables would not be spuriously magnified by redundancies among the predictors. Thus, the results of this study were fortified into validity and reliability, providing a strong basis for inferential conclusions.

Table 4.3 Indicator Multicollinearity

Source: Field Data (2025)

Table 4.4 Cronbach’s Alpha Evaluation Results and Composite Reliability

Source: Field Data (2025)

Convergent Validity Assessment

Thus, the thrust of or convergent validity indicates that how various indicators measure a same underlying latent construct should relate, at least to some extent, in terms of consistent representation of a theoretical construct. To establish converging measurement validity, (Urbach and Ahleman 2010) bring up the issue of measurement models and their adequacy in regard to the representation of intentional constructs. This statistical average variance extracted (AVE), is one cut out of two and is important in examining convergent validity. What the AVE does is measure the same variance distribution in latent constructs under an indicator but in the light of measurement error. The measurement AVE further serves in judging the adequacy of representations for the construct and also for the reliability of the measurement model. The average variance extracted (AVE) values were calculated for each construct to evaluate convergent validity.  Hair et al. (2017) indicate that an AVE threshold of 0.50 signifies satisfactory convergent validity, demonstrating that over half of the variance in the indicators is accounted for by the latent construct.  The AVE values obtained in this analysis varied from 0.568 to 0.766, as presented in Table 4.5, surpassing the 0.50 threshold. The results, thus, testify to the indicators’ strong representational accuracy and theoretical coherence, which, in turn, assures that the measurement model, captured the desired constructs reliably. The high AVE values strengthen the constructs for structural analysis, minimizing measurement error risks and enhancing model robustness.  The empirical confirmation of convergent validity provides more confidence in the measurement tool, which hence supports meaningful interpretations and valid statistical inferences.  The results in Table 4.5 further affirm the validity of the measurement model in capturing the theoretical constructs under investigation, thereby enhancing the rigor and validity of the study itself.

Table 4.5 Construct Convergent Validity (AVE)

Source; Field Data (2025)

Discriminant validity

Discriminant fidelity is an essential aspect of structural equation modelling (SEM). It proves that each of the concepts or “constructs” in a research study is different from the other ones and measures something unique. Fornell and Larcker (1981) introduced an approach to check this condition. As they argued, the Root of Average Variance Extracted (AVE) regarding a construct has to be higher than the correlations of this construct with any other construct. Simply put, it means that the construct should link more to its own indicators than to others.

This method helps researchers in proving that such multiple constructs have not been overlapping too much, which could further weaken the study results. In this study, the Fornell-Larcker criterion has been applied. A table highlights that the square-foot value of AVE (highlighted in bold and italics) is greater than the correlations with other constructs. This implies that constructs are indeed discrete and further strengthens the accuracy of the model. Robust discriminant validity is the key, for under cases when constructs are not distinctly different, it may confuse results, leading to debates over whether reduced overlapping among constructs leads to false conclusions. Constructs adequately dissimilar layers on which, to build reach prediction and explanation abilities into models. Nonetheless, some things limit the Fornell-Larcker method; the method is sometimes unable to detect an emerging issue when constructs are greatly correlated. Therefore, other methods such as the Heterotrait-Monotrait (HTMT), which is considered stringent and more credible for researchers, should also be used just to make sure. In conclusion, this study established the constructs as distinct by using the Fornell-Larcker test. Hence, the reliability of the model is boosted. However, researchers need to use multiple procedures in the measurement of discriminant validity to achieve strong and reliable results.

Table 4.6 Discriminant validity- Fornell-Larcker criterion

Source: Field Data (2025)

Discriminant Validity – Heterotrait-Monotrait Ratio

The Heterotrait-Monotrait ratio (HTMT) serves as a recent approach for scrutinizing whether different constructs in a research model are really different from each other. This concern is especially relevant for structural equation modeling (SEM), which requires that each “construct” is indeed measuring a different thing. A low HTMT value signifies that constructs are readily distinguishable this is a good thing. Conversely, a high HTMT value indicates too great a degree of similarity among the constructs, such that discriminant validity may be in question. There is, however, some disagreement among experts on the HTMT cutoff. Kline (2011) suggests values smaller than 0.85 for confirming discriminant validity, whereas Teo et al. (2008) consider values up to 0.90 acceptable, given constructs are somewhat related in natural settings. Hence, the correct threshold is context-dependent and varies with how closely related the constructs are to each other. In this case, all construct pair’s exhibit values less than 0.90, thus affirming and supporting that constructs are distinct. This in return gives testimony to the reliability and validity of the entire model. It also signifies that relationships between constructs-like attitude and intention-actually hinge on real differences and not on common measurements. Establishing discriminant validity is thus worth all the pains. Without discriminant validity, it is conceivable that research findings mislead, entailing dire consequences for policy or strategy. While the HTMT ratio stands firmly, it is at times too sensitive in instances when constructs are closest to one another, or measurement error comes into play. For that matter, researchers would do well not to use HTMT in a vacuum; they should seek corroboration with alternative method-such as the Fornell-Larcker criterion.

In sum, the study’s HTMT analysis proves that its constructs present clear distinctions, further reinforcing reliability regarding the conclusions drawn. Nevertheless, application of additional techniques in order to verify these results preserves the credibility and strength of the model.

Table 4.7 Discriminant Validity (HTMT)

Source: Field Data (2025)

Model Fit – R²

Already it is known that the coefficient of determination R² is a standard statistic to measure how well the given predictive model describes reality. In this sense, R² shows what percentage of the variance of the dependent variable is accounted for by the set of independent variables entered into the model in structural equation modelling (SEM). The R² results provide any knowledge on the model fitting and general credibility of the model, guiding researchers on how well the predictor variables explain the dependent constructs. The analysis of the R² values for two dependent variables, that is, market share (MARKS) and return on assets (RETA), guided evaluation of model fit.  The analysis showed that MARKS had an R² value of 0.477, implying that the predictor variables, namely FP, CUSTP, IBP, LGP, OCB, MANST, explained 47.7% of the variance in MARKS.  An R² value of 0.604 for RETA indicates that the physical and human factors accounted for 60.4% of the variation in RETA.

Table 4.8 Model Fit- (R²)

Source: Field Data (2025)

Figure 4.1 Measurement Model Analyses

Structure Model Assessment

A structural model is a very important tool in research that helps to understand and explain complex relationships between different variables. It essentially provides an opportunity for researchers to test whether one factor might produce a change in another, thereby providing theoretical credibility to any study in question (Rindskopf, 2023). On the other hand, structural modelling excels at informing any outcome predictions because it draws the links clear and therefore between the ideas or constructs under consideration. There are two basic kinds of constructs in the structural model-exogenous ones and endogenous ones. That is, exogenous constructs function like independent variables, that is, they are variables that influence the other variables but are not they influenced. On the other hand, endogenous constructs function like dependent variables; they are affected by the exogenous variables and may also act as exogenous variables to endogenous variables (Dai & Fang, 2023).Path analysis, structural equation modelling (SEM), and multiple regression analysis are among the techniques employed by researchers in the study of the relationship. These tools assist them in estimating direct and indirect effects among those variables in question (Dai & Fang, 2023). An important step when assessing a structural model is to assess the extent to which the model is able to explain data. It is important to look at how well the model predicts outcome in relation to predictive ability and whether the model makes sense on the basis of theory (convergent validity and explanatory power). The stronger the structure model, the more valid the research results and applicable to real-life situations (Shaukat & Wang, 2022).

Typically, graphical models are drawn with arrows that indicate which variables exert influence over which, basically in reference to both theory and factual data. Analysis along these pathways helps researchers understand the process by which a change in one variable leads to changes in the other. This complements the explanation and predictive capability of the model. To summarizes, structural modelling is an effective way to investigate cause-effect relationships. It allows researchers to understand direct and indirect effects and better comprehend how external factors affect internal processes. A well-specified structural model will not only enhance the validity of research itself, but also aid in building better theories and more concrete applications.

Table 4.13 Direct Relationship Result (OCB)

Source: Field Data (2025)

4.4.5 To investigate the effect of organizational and cultural barriers on organisational performance indicators and examine the moderating effect of management support on the relationship between organisational and cultural barriers and organizational performance indicators.

To what extent does organisational and cultural barriers impact return on assets as a measure of performance indicator?

The findings in Table 4.13 show that organisational and cultural barriers have a surprising positive impact on a company’s financial performance, measured by return on assets (ROA). The statistics (β = 0.719, t = 17.863, p > 0.001) suggest that a 1% increase in such barriers is linked to a 71.9% increase in ROA. This unexpected result implies that these barriers might not always hurt companies in some cases, they may actually help. Typically, barriers like strict decision-making structures, resistance to change, and rigid corporate cultures are seen as negative. But this study suggests they can also push companies to become more innovative, efficient, and better at managing resources. For instance, internal constraints may compel companies to rationalize operations, establish more clever strategies, or use resources a little less poorly-all of which could be beneficial to an organization’s financial performance.

In fact, the rules and cultural norms might lead to better discipline, quality control, and risk management, making these barriers competitive advantages in highly regulated or complex environments. Also, when a strong culture creates loyalty and unity among employees, it can boost productivity and profits. This positive link between barriers and ROA shows that some constraints can help firms grow and stay stable. Having clear roles, efficient decision-making, and accountability structures often leads to better performance. While too much rigidity can block innovation, a moderate level of structure helps ensure consistency especially in industries where rules and standards are important. The results highlight the importance of good leadership. Managers who encourage adaptability and continuous improvement can turn these barriers into strengths. Overall, the study shows that organisational and cultural barriers, often viewed as problems, can actually support financial success when handled well.

What is the effect of organizational and cultural barriers on market share as a measure of performance indicator?

The data in Table 4.13 indicate that organisational and cultural barriers significantly influence market share (β = 0.593, t = 10.718, p > 0.001). A 1% increase in these barriers is expected to enhance the market share by 59.3%, breaking the traditional notion that barriers impede growth. Conversely, it now indicates that when properly managed, such barriers would augment a firm’s growth and better position it in the marketplace. Organisational barriers such as bureaucratic rules, rigid procedures, and well-established hierarchies can actually support organizational effectiveness. They ensure uniformity in service delivery and safeguard quality and regulatory compliance. Not balancing excessive control against the slight relaxation of norms may inhibit creativity and flexibility, but the right amount of control enables consistency, which earns customer trust important for increasing market share. Cultural resistance to change and rigidity can also be leveraged. Companies that incorporate such cultural traits in their ethics, heritage, or branding will make it stand out from competitors and cultivate loyal customers. An articulate culture impels employee engagement, increasing the level of service to customers and, hence, the growth of market shares. These findings stress the importance of strong leadership and adaptable strategies. Companies that work to improve and adapt their internal systems can turn these barriers into strengths. For example, using technology to simplify bureaucratic processes helps maintain structure while also staying responsive to market needs. Similarly, mixing tradition with innovation helps companies keep their brand identity while also meeting modern consumer expectations. Overall, the research highlights how internal structures and culture can impact external performance. Businesses that manage their internal barriers well can gain market trust, build a strong brand, and lead in their industry One should be rigid to an extent but not to the point of blocking innovation from going into one’s processes. The balance should therefore be kept in strengthening both structure and culture and at the same time staying flexible. Conclusively, with strategic management, organizational and cultural barriers can be profitably leveraged to boost market share through improvements in brand identity, customer trust, and consistency, thereby clearly demanding that an internal alignment of a company be done to the market demands for competition. Future research could investigate the contextual factors that influence the role of such barriers as enablers or constraints across various industry contexts.

How does management support moderate the relationship between organizational and cultural barriers and organisational performance indicators?

The influence of managerial support on learning and growth measures, organizational and cultural barriers, and key performance indicators return on assets (ROA) and market share is studied in Table 4.13.It indicates that management support has a negative and statistically insignificant direct effect on ROA and market share. Specifically, the results show (β = -0.027, t = 0.490, p = 0.624) for ROA, and (β = -0.041, t = 0.630, p = 0.529) for market share. This means that management support alone is not significantly affecting the performance with respect to the two measures. However, inserting management support as a moderating variable, that is interplaying, it with other factors such as organizational and cultural barriers manifests the otherwise complex influence. Effect remains negative yet significant at the 10% level for market share with (β = -0.118, t = 1.810, p = 0.070). For ROA, it is still not significant (β = -0.073, t = 1.320, p = 0.187). This indicates management support moderates the relationship between barriers and market share but bears no other adequate moderating effect on ROA. Management support would boost performance by guiding strategy and motivating staff only but may not totally meet the objective. Poor implementation or too much rigidity in that could backfire, progress. Effects on market share may be limited due to some internal reasons, such as rigid rules and resistance to change, which make it difficult for organizations to adapt to market needs. This is also supported by previous studies that found that too much formal management structures could restrict flexibility and innovation. No significant relationship with ROA implies that factors such as internal efficiency, strategic investments, and sound operations have a greater influence on financial performance, not always associated with managements support. In brief, whereas management is often fancied the key to success, this study confines its effect on performance particularly as a moderating factor. Organizations need to ensure strong management systems that are strategically aligned with broader improvements in technology and process efficiency to improve financial outcomes and market presence. Future research should investigate the contextual factors that influence the conditions under which management support acts as a significant moderating variable in organisational performance models.

DISCUSSIONS AND IMPLICATIONS OF THE FINDINGS

The research found that organisational and cultural barriers had a positive and statistically significant relationship with company performance as measured through return on assets (ROA) and market share. In other words, various organisational and cultural problems were sometimes seen as benefactors, in direct contradiction to the general mind-set of the person in charge, toward better financial and marketing performance. Most times, such things as hierarchies, bureaucratic patterns, and inertia towards change are seen to be detrimental to performance, whereas, from the survey results, these very barriers may improve outcomes. For instance, since very structured environments sustain repeatable strategies, standardized processes, and tough operational discipline-the present finding seems consistent with Denison et al. (2021), who argued that clear structures and cultures specialize in stability, which in turn supports improved financial performance. Khan et al. (2022) also argue that some constraints within an organization will shape performance through accountability and logical decision-making, thus enhancing market and financial performance. Sorensen (2022) and Tushman and O’Reilly (2021) also add that market firms with strong cultural and structural systems outperform their counterparts. Among the reasons for this relationship is that strict organizational systems maintain efficiency in sectors that require consistency and compliance. Some researchers do not agree with this view. Kotter and Heskett (2021) argue that inflexible structures impede decision-making, which also affects financial performance. Schein (2020) warned that a culture resistant to change poses a considerable threat to employee motivation and productivity. Burnes (2021) also states that organizations with tightly controlled norms have a hard time changing, which makes them vulnerable in unstable markets. Similarly, Lewin and Grabowski (2022) suggested that exceptionally high barriers will hinder firms from keeping their competitive edge and consequently lessen their market share. These contrary findings suggest that other intervening factors may dictate whether these barriers will enhance or mar performance. Management support stands out as one of those intervening factors. The study found that management support exerted little direct impact on ROA or market share, albeit it could have a very small indirect influence on market share, suggesting that leadership might influence barriers in the domain of performance. Cameron and Quinn (2020) also maintained that it is the management that allows the organization to become more flexible under tight control-system constraints. But Yukl (2021) holds a different view, arguing that achieving better outcomes through overcoming the barriers is achievable only with strong leadership. The bottom line is that the study findings of the present study suggest that the impact of organizational and cultural barriers is context-dependent. They can be value-added as they provide some short in discipline and stability; however, conversely, they can become obstructionists-forcing the necessity of good leadership and adaptability. It will be interesting for future studies to look at under what specific conditions these barriers can be turned into opportunities, concentrating on the industries, market situations, and leadership roles involved. The study also showed that management support does not invariably lead to performance enhancement, but it can affect the effectiveness of barriers. There should be a form of leadership style that encourages innovation without disregarding the existing structures. Equilibrium between control and freedom within the task teams enhances the success of organisations operating within structured environments.

CONCLUSIONS

These study results reveal a range of implementation implications for organizations interested in enhancing their performance, with particular reference to return on assets (ROA) and in relation to market share. The finding that increased organizational and cultural barriers proved to be positively related to gaining a larger market share contradicts the accepted thinking according to which such barriers impede growth and innovation. This has practical implications for managers, who often perceive cultural and organisational resistance to change as negative.

• Organisations should enhance their cultural identity and reinforce organisational processes to improve market share, particularly in competitive and differentiated environments.
• Policymakers should advocate for organizational transformation initiatives that address Cultural barriers hindering the effective use of integrated performance measurement systems.
• Internal structures as well as management policies must be viewed in the particular context and environment in which they are functioning, rather than just advocating removal of barriers or depending too heavily on management support, to ensure maximum internalization of management policies.
• Organisations should be able to prioritize those management styles that can encourage innovation and flexibility as influenced by the already imprinted culture and organizational infrastructure. An ideal environment would maintain a balance of leadership involving team members and autonomy concerning teams for innovative contributions within defined structures.
• All possible policies that will eventually affect organizations at large impacts highly on performance-related though through their organizational and cultural frameworks.
• Policymakers must reexamine how culture and rigid structures drive success in states of organizations. If strategic policies of management focus on creating current structures and cultures, organizations will then be able to derive considerable advantages through operational consistency, discipline among employees, and incorporating objective targets.
• Policies would favor promotion stability and control in organizations, especially in sectors with significant regulatory reliance and operational reliability, enhancing the financial performance of organizations. Organizations need to develop and implement policies that cultivate performance, discipline, and innovation within the confines of such frameworks since this can greatly contribute to enhanced organizational success.
• Policymakers should promote leadership styles that support empowerment, autonomy, and innovation at lower organizational levels instead of relying on managerial support from higher levels.
• Organizations that promote management in setting the strategic direction while avoiding micromanagement of daily operations will prove much more successful in growing market shares.

Future studies should explore more nuanced customer perspective measures that may have an Indirect impact on organizational performance, Research should examine the long-term effects of financial and non-financial measures on organizational performance over extended periods. Further studies should investigate how performance measurement effectiveness varies across different industries and organizational structures.

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