Revealing the Effect of Customer-Perspective Measures on Organizational Performance Indicators and the Moderating Role of Management Support: A Comprehensive Review of Ghana’s Oil and Gas, and Telecommunication Sectors

Revealing the Effect of Customer-Perspective Measures on Organizational Performance Indicators and the Moderating Role of Management Support: A Comprehensive Review of Ghana’s Oil and 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.2025.905000132

Received: 02 May 2025; Accepted: 05 May 2025; Published: 03 June 2025

ABSTRACT

This study explores the influence of customer-focused initiatives on organizational performance measures with particular emphasis on management support as a moderating factor in the telecommunications and oil and gas sectors in Ghana. Grounded in Market Orientation Theory and adopting the Balanced Scorecard (BSC) framework, this research investigates the degree to which performance measures such as market share and return on assets (ROA) are affected by customer satisfaction, loyalty, and perceived value.  The study uses explanatory sequential sampling incorporating qualitative interviews and quantitative questionnaires, which are provided to a sample of 240 employees of major public and private organizations. Findings, interpreted using Partial Least Squares Structural Equation Modeling (PLS-SEM), support that the measures identified by the customer perspective have a statistically significant and positive effect on return on assets (ROA) and market share. Yet, managerial support has no significant effect on the relationships, suggesting that while managerial support is necessary, it doesn’t play a direct role in the success of customer-focused strategies. The findings suggest that performance measures related to customers can be more greatly influenced by operating programs and market conditions external to the organization. This research improves the understanding of specific areas in line with the management of performance and shows the limited impact of managerial decisions in customer-service oriented environments, and therefore contributes to the academic literature base. It shows that organizations need to alleviate customer satisfaction and service excellence by embracing more integrated management practices that support adapting to changing consumption patterns. In pursuit of a more enduring framework, this research recommends the support of market-driven innovation policies and calls for further exploration of the situational factors affecting managerial performance

KEYWORDS: Market orientation theory, customer perspective, balanced scorecard, management support, and organizational performance.

INTRODUCTION

With the dynamic and rapidly changing business world of today, organizations continuously seek to enhance productivity and develop sustainably. Kaplan and Norton developed the Balanced Scorecard (BSC) framework in 1992, and it has since gained remarkable traction as a tool to operationalize organizational strategy in terms of achievable targets in four perspectives: internal processes, learning and growth, customer relationships, and financial performance. Among these influences, the perspective of the customer is central to determining the organization’s overall success. Customer-centric measures such as satisfaction, loyalty, and perceived value have been linked directly to critical performance indicators such as profitability, market share, and efficiency. Yet for such practices to be effective, a central but commonly neglected ingredient is often needed: management approval. The function of management, such as leadership commitment, resource assignment, and alignment with strategic objectives, plays a critical role in exploiting customer-oriented strategies. The oil and gas industry in Ghana is a prime illustration of the necessity of customer-oriented measures in a setting that is characterized by intricate stakeholder relationships. As a prime driver of the national economy, the industry is confronted with mounting pressure to harmonize profitability with stakeholder satisfaction, environmental stewardship, and community involvement.  In this context, customer-perspective measures frequently go beyond traditional metrics, addressing stakeholder expectations that have a substantial impact on organizational performance.  Offei, Amankwah, and Nyarko (2019) found that stakeholder participation is critical in determining operational efficiency and public perception.  In this industry, managerial assistance is crucial, particularly in allocating resources and prioritizing customer-centric goals despite different stakeholder interests. Similarly, Ghana’s telecommunications sector makes a convincing argument for implementing customer-perspective initiatives using the BSC framework.  In this competitive and rapidly changing business, telecommunications companies must exceed customer expectations while maintaining operational efficiency.  Customer-centric measures like satisfaction, retention rates, and service quality are crucial to gaining a competitive advantage.  Addo, Mensah, and Nkansah (2021) discovered that customer happiness in the Ghanaian telecoms market is highly related to organizational success measures such as market share and revenue growth.  However, management’s role in integrating customer-centric initiatives with organizational goals is critical.  Leadership’s dedication to harnessing customer insights and supporting innovation is a critical factor of success in this area. Despite the growing acceptance of customer-perspective measurements as a means of improving organizational performance, the relationship between these metrics and managerial support has received little empirical attention, particularly in developing economies such as Ghana.  This study seeks to reveal the impact of customer-perspective measurements on organizational performance indicators in Ghana’s oil and gas and telecommunications sectors.  By using the BSC framework, the research aspires to provide a comprehensive understanding of how customer-centric strategies can align with organizational objectives. Additionally, the study will explore the moderating role of management support, offering practical insights for optimizing performance in these vital industries.

Problem Statement

In today’s competitive world, firms’ success is increasingly contingent on their ability to implement customer-centric initiatives.  Measures that reflect the customer perspective, including as satisfaction, loyalty, and perceived value, are critical for matching organizational plans to customer expectations.  Despite the awareness of the importance of these measurements in research, their direct impact on key performance indicators such as revenue growth, profitability, market share, and operational efficiency has received insufficient attention Anderson et al., (2004); Homburg et al., (2012).  Furthermore, managerial support appears to play an important moderating effect in the link between customer-perspective indicators and organizational performance.  Leadership commitment, resource allocation, and the consistency of decision-making procedures all play an important role in determining the effectiveness of customer-focused strategies. Nevertheless, the moderating impact of management support is not well articulated in empirical research, which hampers organizations’ ability to leverage customer-perspective measures for sustainable performance enhancements Kumar et al., (2019). This research highlights the necessity for comprehensive research into unveiling the impact of customer-perspective measures on organizational performance indicators. It also stresses the importance of exploring how management support moderates this relationship, thereby providing valuable insights for organizations seeking to secure long-term competitive advantages.

General Objectives

The general objective is to determine the effect of customer perspective measures on organizational performance indicators and examine the moderating effect of management support on the relationship between customer perspective measures and organizational performance indicators.

Theoretical Framework

The study centers on the Market Orientation Theory (MOT). Marketing Orientation Theory has had a substantial impact on how organizations aim to develop and sustain long-term competitive edge over time. The theory, based on the significant works of Kohli and Jaworski (1990) and Naver and Slater (1990), advocates that long-term can be maximized by focusing the company’s integrated activities on meeting the needs sections of specific market Deng & Dart. (1994). According to Narver and Slater, (1990), market orientation is a strategic orientation which seeks to establish the necessary steps for creating products of higher value for customers and, subsequently, persistent superior outcome for the firm. Other academics (Jaworski and Kohli, 1994) describe market orientation as organization-wide creation of market intelligence pertaining to the current and potential needs of customers, dissemination of intelligence both vertically and horizontally in the organization, and across the company broad action or responsiveness to market intelligence. This perspective considers the natural world to be a stakeholder in the market orientation implementation Riven, (1995). Furthermore, it recognizes the nation’s strategic focus on gaining its competitive edge Gatignon & Xureb, (1997).   Different insights on the market orientation construct have been presented Kirca et al., (2005). Kohli and Jaworksi (1990) described market orientation as a three-dimensional behavioral activity which encompasses intelligence generation, dissemination, and market responsiveness. Therefore, a company’s success will largely be identified by its ability to constantly collect information concerning its customers’ demands and disseminate that knowledge in order to react appropriately to those needs. This is crucial if the organization intends to constantly offer excellent customer value. Information development is important because it is seen as important endeavor for identifying customer needs and aspirations Kohli, (1993). Furthermore, a common interpretation of information occurs between dissemination and responsiveness Daft & Weick, (1984). According to Harrison-Wlaker (2001), the dissemination phase provides a common ground for multiple departments to coordinate their actions. Nonetheless, until organization responds to market demands, no progress is achieved; consequently, responsiveness refers to actions carried out in accordance with intelligence gathered and disseminated, as well as the generation and execution of a plan of action Shapiro, (1998).A number of scholars have contributed to the theoretical knowledge concerning marketing orientation and its potential implications in practice. A research carried out in Japan by Deshpande et al. (1993) indicated that market orientation has a significant correlation with revenue, profitability, return on assets and the performance of organizations in general. While the impact of market orientation on economic performance has received the most attention, it has also been linked theoretically and empirically to customer and employee outcomes (Jaworski & Kohli; Slater & Narver, 2000). Empirical evidence suggests that a market orientation enhances several indicators of innovative characteristics and performance Atuahene-Gima, (1996). Other studies have focused on the factors that affect the market orientation-performance relationship. A solid argument has been made for innovativeness as a mediating variable. The core premise is that market-oriented organizations have a knowledge advantage over their rivals, allowing them to become more adept skilled in innovation strategies Langerake et al., (2004).While market orientation theory can assist businesses connect with the need of their consumers, it is not without criticism. The main problem with the current concept of market orientation is that it is excessively theoretical and wide. Market orientation is currently a cohesive, multifaceted and multidimensional construct which provides limited and ambiguous strategic guidance to firms in different competitive scenarios. Market orientation also supports short-term focus over long-term strategic objectives, which leads to a lack of innovation and a reactive as opposed to proactive reaction to market advancements Jaworski & Kohli, (2017). Although customer feedback is important, overreliance on it can impede creativity and imaginative thinking. Developing a market-oriented strategy can be resource-intensive, requiring significant expenditure in market research, data analysis, and constant customer engagement Kohli & Jaworski, (1990). A strong focus on market orientation can lead to homogeneity, in which businesses create similar products and services to satisfy the same perceived   customer demands, reducing diversity and leading to price competition which diminishes profit margins. Market orientation emphasizes external market concerns and customer demands while possibly overlook internal capabilities and strengths, leading to an imbalance between what the market expects and what the business can effectively and economically provide Lukas & Ferrel, (2000). To address these issues, different studies have proposed solutions. One approach is to create a harmony between short-term customer requirements and long-term strategic objectives by allowing organizations to address short-term customer demands while still focusing on future development and innovations varadarjan, (2017). To mitigate the possible changing impact of excessive customer feedback, firms should cultivate a culture of innovation and calculated risk-taking by means of committed effort to research and development, and promoting innovative thinking beyond the present situation Cramer, (2013). To prevent product homogenization, firms must invest in brand development, produce unique products and services, and offer excellent customer service to distinguish themselves apart from rivals. Blending customer focus and innovation can lead in the development of innovative products and services. Utilizing customer perspectives as a foundation for innovation instead of a rigid framework, they can produce products and services that meet current requirements while also predicting future needs Lukas & Ferrel, (2000).Market Orientation theory emphasizes the significance role of firms in efficiently reacting to market changes, comprehending competitors operate, and nurturing collaboration among departments to promote superior results. This theory is important for understanding how firms deal with market changes and competitive challenges, especially when evaluating the integrated effect of financial and non-financial measures on performance. In Ghana’s oil and gas and telecommunication sectors, where market conditions are extremely competitive and rapidly changing, a robust market orientation enables organizations to link their plans with client requirements, resulting in enhanced performance. By focusing on consumer satisfaction, competitor analysis, and cross-functional collaboration, organizations can leverage both financial and non-financial measures to improve operational effectiveness. Furthermore, marketing orientation enhances stakeholder collaborations, ensures greater adherence to legislation, and increases brand reputation all of which contribute to sustainable achievements in these industries. Consequently, market orientation addresses the gap between short-term financial results and long-term tactical goals, promoting an integrated strategy to growth and profitability. The market orientation theory aligns with the research objective of determining the effect of customer perspective measures on organizational performance indicators and examining the moderating effect of management support on the relationship between customer perspective measures and organizational performance indicators in oil and gas, and telecommunications sectors in Ghana. This theory underscores the need of comprehending and reacting to consumer demands, tastes, and actions in order to improve corporate success. Within the realm of the oil and gas and telecommunication sectors in Ghana, market orientation has a significant impact on how companies develop their customer-centric approaches. These approaches, which encompass consumer satisfaction, loyalty, and involvement, are critical for promoting general performance of companies. Moreover, the theory encourages the research into how management support can moderate the relationship between financial perspective metrics such as profitability and cost control and corporate performance measures, as well as the role of management support in guaranteeing that financial objectives are not only accomplished but also aligned with customer-focused approaches which satisfy stakeholder needs. By exploring market orientation theory, this study examines the complex relationships between customer-centric metrics and financial results, underscores the importance of a balanced strategy in increasing customer satisfaction and financial success. This comprehensive strategy is especially important in sectors such as the oil and gas and telecommunications, where fierce competition and market dynamics necessitate constant changes to consumer expectations and demands. To achieve the research objectives, market orientation theory will assess how customer perspective metrics such as satisfaction, loyalty, and perceived value affect performance in oil and gas and telecommunication sectors in Ghana. The theory argues that a solid market orientation, as indicated by proactive application of consumer data, leads to increased financial performance, market share, and customer retention. By focusing on customer requirements and incorporating this priority into strategic and operational procedures, companies can improve their performance. This strategy also promotes innovation, which helps to meet changing consumer needs and maintaining a competitive edge. Incorporating customer-focused KPIs helps organizations remain flexible, responsive to market changes, and profitable in an increasingly competitive marketplace. The continuous feedback loop from customer metrics enable firms to refine their strategy, fostering continuous improvement and innovation. Ultimately, market orientation theory underscores the significance of customer measurement and their changing influence on corporate strategy, resulting in improved performance in oil and gas and telecommunication sectors in Ghana.

Empirical Review

Customer-focused metrics are critical for determining how successfully an organization meets its customers’ requirements and expectations.  These metrics investigate characteristics such as customer happiness, loyalty, and perceived value, which combined reflect an organization’s effectiveness in meeting its customer-centric goals.  Narver and Slater, (1990). The Market Orientation Theory provides an effective framework for understanding the strategic implications of these customer-centric measures.  According to this notion, firms improve their performance by systematically gathering and responding to market knowledge about customers and competitors.  Kohli and Jaworski, (1990).This theory emphasizes the connection between organizational performance, customer orientation, and the moderating function of management in the context of Ghana’s oil and gas and telecommunications industries.  The limitations of expanding the Balanced Scorecard to incorporate customer experience metrics were examined in a study by Green and Wilson (2024), particularly in industries like retail, telecommunications, and hotels where customer satisfaction is a key metric of advancement. Using qualitative analysis, the study explored case studies to better understand the challenges and solutions that businesses face while adopting customer experience into BSC.  The study discovered that incorporating customer experience measurements demands the creation of new measuring methods as well as a strong corporate commitment to using customer feedback for continuous improvement.   Nonetheless, the study did not investigate how various consumer requirements across industries or geographic regions can influence the adoption of customer experience measures in the BSC.  A more in-depth examination of sector-specific challenges, such as the level of personalization in hospitality versus the financial aspects of telecommunications, will help determine how these variables influence the conception and performance of consumer experience assessments in the BSC. Furthermore, researching the use of electronic consumer experience tools, such as AI-powered feedback mechanisms, could provide valuable insights into improving real-time customer experience assessment in the BSC paradigm.  Martin and Lee (2024) looked into how businesses may expand their Balanced Scorecard frameworks to improve customer experience measures, focusing on sectors such as hospitality, retail, and technology.  Using a qualitative method, the study examined how BSC models are updated to include customer experience data and identified the challenges of integrating them with traditional financial and operational objectives.  The study revealed that incorporating customer experience indicators is a complex but valuable effort because it promotes customer happiness and loyalty. They stressed that the issue hinge on developing unified, quantifiable customer experience measures which is consistent with financial and operational performance goals. However, while the study presents significant perspectives, its dependency on the hospitality and retail sectors restricts its relevance to more complex industries. A more thorough examination of real-world examples or case studies would enhance the results by providing more concrete insights.  Furthermore, researching the impediments to incorporating consumer feedback, particularly the use of technology or methods to facilitate this process, would yield important insights.  Furthermore, investigating how the BSC design may be expanded to incorporate client experiences in a more dynamic and responsive manner will provide useful insights into improving performance assessment frameworks.  Patel and Kumar (2022) investigated the usage of customer measures in the Blanked Scorecard as a strategic management tool in several Indian organizations. The research sought to assess whether a customer-centric approach within the BSC paradigm can improve customer experience. The findings demonstrated that integrating customer measures greatly boosts customer happiness and loyalty, indicating the effectiveness of the BSC in matching corporate tactics with customers’ demand. However, the study offers significant conclusions in relation to customer satisfaction, but the lack of detailed information on sample selection, data collection methods, and possible biases raises questions concerning the research’s credibility. A comprehensive review of the research design and its consequences for broader uses would increase the research’s dependability and offer a broader comprehension of the subject. Martin and Clark (2024) explored how staff involvement affects the effectiveness of the Balanced Scorecard in enhancing business performance. The study employed qualitative analysis of case studies from the retail, hospitality, and education industries. The study concluded that engaged staff are more inclined to make significant contribution to accomplishing tactical goals, thereby increasing the efficacy of the BSC. However, the study could not fully account for sector-specific contexts or business characteristics that could limit or enhance employee engagement.  A detailed examination into how techniques of involvement differ throughout industries and countries, particularly in sectors with specific cultural or operational characteristics, would yield useful information.  Furthermore, looking into the long-term effects of employee involvement on BSC results, beyond immediate performance improvements, would provide valuable insights into maintaining success and corporate progress.  Mitchell and Nelson (2023) used the Balanced Scorecard model to study main challenges that businesses face when analyzing non-financial objectives such as customer satisfaction, employee involvement, and social impact. Using a mixed-methods approach, the study examined case studies from the education, healthcare, and non-profit industries to assess the difficulty of aligning these outcomes with traditional financial measurements.  The study revealed that, while non-financial outcomes are critical for long-term organizational success, they are often difficult to quantify, complicating their incorporation into the BSC. However, the study did not consider how industry-specific factors, such as legal constraints or stakeholder expectations, can influence the measurement of non-financial outcomes.  Future study should investigate how industry-specific limitations affect the development and acceptability of BSC models.  Furthermore, investigating how emerging technologies, such as big data analytics, might improve the accuracy and flexibility of non-financial measurement will boost the BSC’s efficiency in capturing these vital outcomes.  Singh and Parker (2024) explored the barriers and approaches of adopting the Balanced Scorecard across many areas, each with unique cultures, market dynamics, and regulatory environment. The study focused on worldwide corporations in the automotive and consumer products industries and used qualitative analysis to investigate how BSC implementation may be tailored to individual conditions.  The study indicated that, while the BSC provides a good framework for tactical coordination, its measurements should be adapted to each region’s unique needs and challenges. Nevertheless, the study did not address the potential impact of regional technology breakthroughs or developments on the efficiency of BSC adoption.  Future research should investigate how developments in data analytics or AI-powered systems can facilitate more successful and dynamic localizations of BSC indications.  Furthermore, investigating how organizations in developing regions, with varying cultural and economic contexts, face particular obstacles while implementing a global BSC may be beneficial.  Lopez and Patel (2023) investigated the limits that firms face while assessing non-financial objectives such as customer happiness, employee involvement, and innovation using the Balanced Scorecard paradigm. The study concluded that non-financial variables frequently lack concise descriptions and consistent measuring methodologies, preventing their adoption into the BSC.  It emphasizes that firms should prioritize easily quantifiable facts above qualitative insights that provide a comprehensive understanding of corporate success.  Nonetheless, the study did not look at how different organizational settings or external environmental factors can influence the evaluation of non-financial outcomes. A thorough investigation of how industry-specific challenges influence the widespread use of non-financial metrics within the Balanced Scorecard is required to increase the framework’s scalability among sectors. Additionally, investigating the impact of technology in promoting the assessment of intangible benefits would improve the scheme’s general efficiency. Nguyen and Robinson (2024) investigated performance measures adoption in the logistics industry, highlighting challenges such as balancing financial efficiency with service quality and resolving regional differences in data reporting, which hinder effective performance administration and operational effectiveness. Nevertheless, the research did not take into account challenges associated with metric integration, indicating the necessity for additional research. A comprehensive review of the impact of technology in accelerating data reporting processes can results in greater precision and more easily accessible insights.  Additionally, the significance of cross-functional cooperation in the advancement of measures should not be ignored, as it can increase general alignment. Resolving these difficulties thoroughly would allow the logistic industry to increase its performance evaluation systems, resulting in improved decision-making and operational efficacy’ Brien and Hughes (2024) examined the challenges of performance measurement in the telecommunication industry. Their results showed obstacles in effectively integrating measurements and inconsistencies in data collection, limiting informed strategic choices across the industry. However, the research ignored general hurdles which give rise to these concerns, revealing a knowledge gap. A thorough analysis of the effect of leadership in developing a cultural of transparency and accountability in companies would assist in discovering important areas for development. Additionally, rigorous information gathering is critical for reliable performance assessment resulting into a more informed choices and effective tactical planning in the telecommunication sector. Turner and Collins (2024) examined the difficulty of incorporating performance metrics within the construction industry discovered important hurdles such as the lack of consistency across different projects, challenges in implementing metrics effectively, and a significant staff opposition. These challenges frequently led to ineffectiveness, resulting in significant cost overruns. However, the research did not explore the underlying causes of employee resistance to adopting performance indicators, which remains a major source of worry. A more thorough analysis of vigorous training initiatives would help raise staff satisfaction while enhancing the general efficacy of performance measurement in the construction sector. Additionally, exploring strategies to facilitate stakeholder participation could offer important perspectives into the adoption of measures, thereby increasing the effectiveness of performance assessment within the industry. Wang and Garcia’s (2024) conducted a quantitative analysis to assess the differences between financial and non-financial measures and their effect on corporate performance, highlighting on the constraints of incorporating these measures into cohesive organizational tactics. Nonetheless, the research did not address sector-specific issues which affect metric integration, possibly overlooking significant variables influencing organizational success. A thorough investigation of industries types and organizational characteristics would offer an increased comprehensive knowledge of how different sectors and firm sizes maintain the integration of financial and non-financial measurements. Additionally, evaluating the impact of technological advancement in metric adoption would enrich the investigation by providing a broader perspective into how developing technologies impact the balance between financial and non-financial metrics. Singh and Mehta (2024) performed a research on the implementation of corporate social responsibility measures into the Balanced Scorecard paradigm in Indian companies. The research sought to examine how the BSC can stimulate the integration of CSR into tactical planning. The findings indicated that using the BSC allows companies to efficiently implement CSR programs, boosting tactical alignment and general outcome. However, the study presents significant perspectives into the integration of corporate social responsibility into the Balanced Scorecard but did not address the obstacles that businesses experience during implementation. A more thorough analysis of case studies or instances from different sectors would offer an improved comprehension of the Balanced Scorecard’s role in supporting CSR initiatives, hence increasing the study’s practical relevance and breadth. Bennet and Watson (2024) investigated how executive leadership could help overcome obstacles related to the Balanced Scorecard’s acceptance and use. The research focuses on how leadership influences resistance to change and aligning corporate plans with performance measures based on qualitative analysis of case studies from sectors such as manufacturing, healthcare, and education in the United States and Europe. The study concluded that executive leadership is essential for fostering corporate buy-in, encouraging a performance oriented culture, and making sure that the BSC is in line with company’s general vision and plan. Nevertheless, the research did not fully account for the larger organizational and cultural elements which could influence leadership efficiency in diverse industries. A thorough investigation of how leadership strategies varies by sector and geography, as well as an evaluation of the impacts of various approaches to leadership on the successful execution of BSC, would offer important perspectives into its efficacy in a variety of settings. Tanka and Sato (2024) investigated the use of the Balanced Scorecard as a tactical management model in smart manufacturing environments in Japan. The purpose of the research was to examine whether the BSC could increase operational performance and tactical coordination in these environments. The research demonstrated that the adoption of the BSC considerably enhances manufacturing operations by incorporating different views, linking internal processes with tactical goals, and generating a more effective corporate structure. Nevertheless, the research lacks a comprehensive exploration of the obstacles to adopting the BSC in smart manufacturing. Future studies should include case studies or practitioner interviews to provide a deeper comprehension of the real-world challenges and their contextual significance. This could deepen the research and offer a more balanced view of the BSC’s efficacy in various manufacturing settings, and also providing a more in-depth understanding of the incorporation process. Khan and Malik (2023) undertook a research on the use of the Balanced Scorecard in retail chains in Pakistan. The research aims to determine how the BSC could increase operational efficiency and customer satisfaction in the retail industry. The study concluded that the BSC efficiently enhances customer satisfaction and operational effectiveness by linking tactical goals from diverse perspectives, hence contributing to the growth of retail companies. While the results indicate the BSC’s efficiency in increasing customer satisfaction and operational effectiveness, its dependency on a single case study restricts its generalizability to Pakistan’s diversified retail sector. A comprehensive review with a bigger sample size or comparative analysis would further strengthen the results. Additionally, integrating several case studies would explore the BSC’s adaptation to diverse corporate settings.

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 also conduct random interviews with a smaller qualitative sample size. For the purpose of this study, this research the population of interest constituted 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, purposing sampling was applied to intentionally target individuals which offer 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 solicit 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 Microsoft Excel as well as PLS –SEM where simple descriptive statistics 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 unveil the impact of customer-perspective measures on organizational performance indicators and the moderating role of management support: A comprehensive review of Ghana’s oil and gas, and telecommunication sectors. The findings will enhance the performance management literature by providing insights for decision-makers aiming to reconcile financial imperatives with strategic growth initiatives. The findings are presented in form of tables and figures.

Table 4.1 Descriptive Statistical Analysis Result -Demographic

Source: Field Data (2025)

Table 4.1 presents a demographic analysis that emphasizes gender distribution among the study participants.  The results showed that female respondents comprised the majority, with a count of 122, accounting for 51.05% of the overall sample.  Conversely, 117 participants (48.95 %) were male.  Near-equal gender representation indicates a balanced distribution of perspectives, thereby enhancing the generalizability of the findings of the study.  The slight variation in participation rates between genders may indicate wider trends within the research context, possibly shaped by sector composition, organizational culture, or societal influences.  Higher female representation may suggest an increasing presence of women in the targeted professional domain, indicating shifts in workforce dynamics.  Minimal disparity ensures that gender-based biases do not disproportionately influence the study’s insights, thereby reinforcing the robustness of the analysis.  This demographic structure establishes a robust basis for evaluating gender-related differences in organizational performance metrics. The demographic analysis of participants by age distribution, as shown in Table 4.1, indicated that the majority of respondents were in the 20–30-year age group, with a frequency of 75, accounting for 31.38% of the total sample.  This indicates a relatively young workforce, suggesting a significant presence of early career professionals within the study population.  The second-largest age group was 41–50 years, consisting of 66 respondents (27.62%), followed by the 31–40-year age group, which included 61 participants (25.52%).  The age group of 51–60 years was underrepresented, comprising 35 participants (14.64%), whereas individuals aged 60 years and above represented the smallest proportion, with only two respondents (0.84%). This distribution demonstrates a varied age composition, which is crucial for understanding generational perspectives on organizational performance.  The limited representation of older participants may indicate trends in workforce retirement or the predominance of mid-career professionals in the sampled population. The examination of participants’ educational qualifications, as illustrated in Table 4.1, underscores their varied academic backgrounds.  The results show that the majority of participants possessed a bachelor’s degree, with a count of 86, accounting for 36% of the overall sample.  This indicates that undergraduate education is the main academic qualification among the study population, likely mirroring industry-hiring trends.  Subsequently, 71 respondents (29.7%) held a master’s degree, indicating a significant representation of advanced degree holders, potentially influencing strategic decision making and improving competencies within the workforce.  Furthermore, 63 participants (26.4%) possessed professional certifications, highlighting the importance of specialized skills and industry-specific knowledge.  Ultimately, only 19 participants (7.9%) achieved a doctorate (PhD), reflecting a comparatively low representation of highly specialized academic professionals.  This distribution highlights the workforce’s dependence on bachelor’s and master’s degrees while acknowledging the significance of professional certifications in enhancing formal education. The demographic analysis of participants’ age distribution, as shown in Table 4.1, offers essential insights into the workforce composition.  The results show that the 20–30-year age group comprised the largest percentage of respondents, with a count of 75, accounting for 31.38% of the overall sample.  This indicates that young workers are likely to be predisposed to adaptability and innovation.  The 41–50-year age group accounted for 27.62% (66 respondents), indicating a significant representation of experienced professionals in mid-to-senior management positions.  The 31–40-year age group represented 25.52% (61 respondents), highlighting a notable portion of employees in the critical stage of their careers.  The 51–60-year age group, comprising 14.64% (35 respondents), indicates a lower representation of late-career professionals.  Individuals aged 60 and above represented the smallest demographic group, comprising only 0.84% (two respondents), and indicating limited workforce participation among retirees or senior executives exiting active employment. Table 4.1 illustrates the sectorial distribution of participants, revealing that the telecommunications industry comprised 60.3% (144 respondents) of the total sample.  This signifies a notable representation of a sector characterized by swift technological progress and competitive market dynamics.  The oil and gas sector constituted 39.7% (95 respondents) of the sample, indicating a significant yet relatively low representation.  The distribution indicates that the findings of this study are likely more representative of the operational environment in the telecommunications sector, whereas insights from the oil and gas sector offer a complementary perspective on the dynamics of organizational performance specific to that industry. The evaluation of the participants’ experience levels, as shown in Table 4.1, indicated that most respondents had a moderate level of professional experience.  Individuals with four to six years of experience represented the largest cohort, comprising 31.8% (76 respondents).  This indicates that a considerable segment of the workforce is in the mid-career stage, likely combining foundational knowledge with industry experience.  Participants with 1–3 years of experience constituted 21.8% (52 respondents), whereas those with less than one year of experience accounted for 21.3% (51 respondents), indicating a significant representation of early career professionals.  Furthermore, 20.5% (49 respondents) possessed 7–10 years of experience, indicating a robust skill set.  Only 4.6% (11 respondents) had more ten years of experience, indicating the limited presence of highly experienced professionals.  This distribution highlights a workforce that is primarily composed of emerging and mid-level professionals.

Measurement Assessment Model

The first phase of assessing the measurement model, known as outer model assessment, uses Partial Least Squares (PLS) for Confirmatory Factor Analysis (CFA).  This phase is essential for confirming the proposed relationships between the latent constructs and their corresponding indicators within the model.  The PLS-based CFA assesses the extent to which empirical data align with a theoretically defined measurement framework, confirming that reflective indicators accurately represent their associated latent constructs.  Confirming the validity and reliability of the measurement model is essential to ensure methodological rigor and analytical robustness. The evaluation of internal consistency reliability, commonly assessed using Cronbach’s alpha and composite reliability (CR), confirms that items related to a specific construct reliably reflect the underlying latent variable.  High internal consistency reliability indicates that the indicators produce stable and coherent results across repeated measurements, thereby enhancing the credibility of the model.  The validity of the measurement model was examined through assessments of convergent and discriminant validity in addition to reliability.  Convergent validity assesses the degree to which the indicators designed to measure the same construct demonstrate significant intercorrelations. This evaluation is commonly conducted using Average Variance Extracted (AVE) and standardized factor loadings.  An AVE value exceeding 0.50 demonstrates sufficient convergent validity, indicating that the latent construct accounts for a significant portion of the variance in its related indicators.  Item loadings exceeding 0.70 signify strong associations between indicators and their respective constructs. Discriminant validity ensures that each construct retains conceptual distinctiveness by showing that it shares greater variance with its own indicators than any other construct in the model.  The Fornell-Larcker criterion and cross-loading analysis are typically employed for evaluation, demonstrating that each construct shows stronger relationships with its corresponding indicators compared to other constructs.  The validity and reliability parameters were rigorously examined, confirming that the measurement model was methodologically sound and statistically robust, thereby establishing a reliable foundation for subsequent structural analysis.

Factor Loading

Factor loadings are essential metrics in factor analysis that measure the extent of association between observed variables and their respective latent constructs or principal components.  Pett, Lackey, and Sullivan (2003) indicated that factor loadings vary from -1.0 to +1.0, where higher absolute values denote a stronger association between the observed variable and its corresponding factor.  Loadings near ±1.0 signify a strong representation of the underlying construct, while values close to 0 indicate a weak association.  In the context of Principal Component Analysis (PCA) and Confirmatory Factor Analysis (CFA), factor loadings indicate the degree to which individual items account for variance in latent constructs Anderson et al., (2019).Factor loadings above 0.70 are typically considered significant, indicating that an item effectively represents the conceptual characteristics of the related construct Fornell & Larcker, (1981).  Loadings below 0.40 may indicate weak representation, suggesting potential issues with the item’s appropriateness within the model and possibly necessitating its exclusion Tabachnick & Fidell, (2019).  Table 4.2 presents the factor loadings, which offer essential insights into the alignment of observed variables with their corresponding latent constructs, thus enabling an empirical assessment of construct validity within the measurement model.  Increased loadings strengthen the theoretical framework of the model by validating the effectiveness of the indicators in representing latent constructs, thereby improving the accuracy and dependability of the measurement tool (Hair et al., 2019).  This empirical alignment confirms the model’s ability to accurately represent underlying theoretical constructs.

Table 4.2 Factor Loading

Source: Field Data (2025)

Indicator multicollinearity

The Variance Inflation Factor (VIF) is a key diagnostic tool used to identify multicollinearity among the predictor variables in regression analyses.  Multicollinearity arises when independent variables demonstrate significant intercorrelations, potentially distorting parameter estimates, inflating standard errors, and undermining the statistical significance of predictors Fornell & Bookstein, (1982).  This can result in unreliable coefficient estimations and diminish the explanatory power of the model (Gujarati & Porter, 2009).Hair, Ringle, and Sarstedt (2016) suggest that VIF values greater than five indicate significant multicollinearity, requiring corrective measures such as variable transformation, removal, or model re-specification.  This study indicates that The VIF values presented in Table 3 are significantly lower than the critical threshold, demonstrating no multicollinearity issues.  The absence of significant collinearity guarantees that predictor variables independently influence the model, thus reducing estimation bias and improving the accuracy of coefficient interpretation Kline, (2015).  The robustness of the model’s estimations enhances the credibility of the statistical inferences, confirming that the observed relationships among variables are not artificially inflated because of the redundancy among predictors.  Thus, the study’s findings were enhanced in validity and reliability, establishing a robust foundation for inferential conclusions.

Table 4.3 Indicator Multicollinearity

Source: Field Data (2025)

Construct Reliability and Validity Analysis

Evaluating the reliability of individual items is essential for validating measurement instruments, with standardized factor loadings acting as primary indicators of the strength of the relationship between the observed variables and their corresponding latent constructs.  This study used Composite Reliability (CR) and Cronbach’s alpha to assess item reliability, ensuring that the measurement model effectively represented the intended theoretical constructs Hair et al., (2017).  Factor loadings served as the main criterion for assessing item reliability, as highlighted by Hulland (1999), who argued that loadings exceeding 0.70 indicate strong item reliability, meaning that an item accounts for more than 50% of the variance in its corresponding construct.  Items that did not meet this threshold were deemed unreliable and were excluded from further analysis, as indicated in Table 4.4.  This method guarantees the retention of only the most dependable indicators, thus strengthening the model’s construct validity. The internal consistency reliability of the measurement instrument was evaluated using Cronbach’s alpha and Composite Reliability (CR) coefficients to enhance its validity.  Cronbach’s alpha quantifies the internal consistency of the items within a construct. Hair et al. (2017) observed that values above 0.70 are typically deemed acceptable, reflecting adequate inter item correlation, are typically deemed acceptable. This study demonstrated that all constructs achieved Cronbach’s alpha values that exceeded the recommended threshold, thereby confirming the reliability of the measurement scale. In addition to Cronbach’s alpha, Composite Reliability (CR) offers a more comprehensive assessment of reliability by evaluating how well a group of indicators collectively reflects the intended latent construct.  Ramayah et al. (2018) indicate that CR values ranging from 0.70 to 0.90 reflect an optimal balance, providing adequate construct representation while reducing redundancy.  CR values under 0.70 indicate insufficient reliability, while values above 0.90 may suggest excessive redundancy among items.  The computed CR values in this study varied from 0.70 to 0.90, thereby affirming the reliability of the selected indicators and reducing the risk of multicollinearity. The alignment of Cronbach’s alpha and CR values within the acceptable range of 0.70 to 0.90 highlights the internal consistency and strength of the measurement model.  This equilibrium is crucial for accurately capturing latent constructs, while avoiding redundancies and statistical distortions. The removal of underperforming items along with the strong internal consistency of the retained indicators improves the reliability and validity of the measurement instrument.  This study adhered to strict reliability standards, ensuring that the measurement model was sufficiently robust to support subsequent structural analyses. The results presented in Table 4.4 offer empirical evidence supporting the model’s reliability, confirming its appropriateness for examining hypothesized relationships among the constructs.

Table 4.4 Cronbach’s Alpha Evaluation Results and Composite Reliability

Source: Field Data (2025)

Convergent Validity Assessment

Convergent validity assesses the degree to which various indicators accurately measure the same latent construct and demonstrates consistency in representing an underlying theoretical concept. Urbach and Ahleman (2010) highlighted the importance of establishing convergent validity to confirm that the observed indicators effectively represent the intended construct in a measurement model.  The Average Variance Extracted (AVE) serves as a key statistical metric for evaluating convergent validity, measuring the proportion of variance in indicators that can be attributed to the latent construct while also considering measurement error.  AVE is an essential criterion for assessing the adequacy of the construct representation and 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 confirm that the indicators demonstrate strong representational accuracy and theoretical coherence, ensuring that the measurement model reliably captured the intended constructs. The high AVE values support the suitability of the constructs for further structural analysis, reducing the risk of measurement errors, and strengthening model robustness.  Empirical confirmation of convergent validity enhances confidence in the measurement instrument, thereby supporting its ability to enable meaningful interpretations and valid statistical inferences.  The results in Table 4.5 confirm that the measurement model successfully operationalized the theoretical constructs being examined, thus improving the rigor and validity of the study.

Table 4.5 Construct Convergent Validity (AVE)

Source; Field Data (2025)

Discriminant validity

Discriminant validity is a critical criterion in structural equation modeling (SEM), which ensures that constructs within a measurement model are empirically distinct, thereby confirming their ability to capture the unique dimensions of the underlying phenomenon.  Fornell and Larcker (1981) established a criterion for evaluating discriminant validity, asserting that the square root of the Average Variance Extracted (AVE) for each construct must exceed its correlation with any other construct in the model.  This method is essential for assessing the empirical reparability of conceptually distinct constructs, addressing issues of construct overlap, and preserving theoretical integrity (Fornell and Larcker 1981).  This criterion is based on the premise that indicators assessing different constructs should not exhibit excessive shared variance as this would undermine the distinctiveness of the constructs. The Fornell-Larcker criterion was employed to assess discriminant validity by comparing the square root of the AVE for each construct with its correlation coefficients with other constructs.  Table 5 displays the findings, emphasizing the square root of the AVE in bold and italics to highlight its uniqueness in comparison with the inter-construct correlations.  The findings indicate that the square root of the AVE for each construct consistently exceeds its correlation with other constructs, thereby affirming their empirical distinctiveness and supporting the validity of the measurement model.  This confirmation of discriminant validity guarantees that each construct retains both conceptual and empirical independence, mitigates redundancy and strengthens the robustness of the model’s structural relationships. Establishing discriminant validity is essential for maintaining the theoretical accuracy of the model because the uniqueness of the constructs directly influences the validity of their relationships.  Insufficient discriminant validity can result in construct overlap or multicollinearity, which may distort the genuine nature of the associations and produce misleading results Hair et al. (2016).  Excessive correlations among constructs raise concerns about their ability to represent distinct theoretical dimensions versus reflect a singular underlying concept.  This ambiguity complicates the empirical analysis and reduces confidence in the measurement instrument. In addition to providing theoretical rigor, discriminant validity improves the predictive accuracy and reliability of the structural model.  Empirically distinct constructs allow for a more accurate estimation of interrelationships, enhance predictive power, and enable meaningful interpretation.  This is especially important in complex models with multiple interacting latent variables, as insufficient discriminant validity may result in inflated estimates and incorrect conclusions due to the shared variance among constructs Hair et al., (2016).The Fornell-Larcker criterion, which is widely utilized, exhibits certain limitations.  A significant limitation is its potential to be excessively permissive in identifying discriminant validity concerns, particularly in models in which constructs demonstrate high correlations Henseler et al., (2015). Researchers have recommended complementary approaches to address these limitations, such as the hetero trait-mono trait (HTMT) ratio, which provides a more rigorous evaluation of discriminant validity Henseler et al., (2015).  The use of various validation techniques offers a thorough assessment, thereby improving the reliability of the measurement model and minimizing potential biases in construct validation. This study’s application of the Fornell-Larcker criterion provided strong evidence for the discriminant validity of the constructs examined. This study establishes empirical distinctiveness and enhances the validity of the measurement framework by demonstrating that the square root of the AVE for each construct exceeds its correlation with other constructs.  These findings enhance the model’s reliability, confirming that the constructs effectively represent the intended theoretical dimensions.  Researchers must acknowledge the limitations of the Fornell-Larcker criterion and integrate additional methodologies, such as the HTMT ratio, to validate construct distinctiveness and strengthen the robustness of their findings.

Table 4.6 Discriminant validity- Fornell-Larcker criterion

Source: Field Data (2025)

Discriminant Validity – Heterotrait-Monotrait Ratio

The Heterotrait-Monotrait (HTMT) ratio is a modern and robust approach for evaluating discriminant validity, particularly within the context of structural equation modeling (SEM) applications. This measures the correlation between the indicators of different constructs and functions as a diagnostic tool to assess the level of construct overlap.  A lower HTMT ratio signifies robust discriminant validity, confirming that the constructs are empirically distinct.  An increased HTMT value indicates a high level of construct correlation, raising issues regarding conceptual redundancy and measurement integrity Henseler et al. (2015).A suitable threshold for the HTMT ratio continues to be a topic of scholarly debate.  Kline (2011) establishes a strict threshold of 0.85, indicating that discriminant validity is confirmed when the HTMT ratio between any two constructs is below this threshold.  Teo et al. (2008) proposed a threshold of 0.90, arguing that, in complex models with interrelated constructs that naturally display stronger associations; a marginally elevated HTMT value does not inherently compromise discriminant validity.  The choice of an appropriate threshold must be informed by the research context, characteristics of the constructs being examined, and theoretical framework of the study. The HTMT ratio was calculated to assess discriminant validity and the results are displayed in Table 6.  The results demonstrate that all construct pairs show HTMT values under the 0.90 threshold suggested by Teo et al. (2008).  This empirical evidence supports the assertion that the constructs in the measurement model are adequately distinct, ensuring that each construct represents a unique theoretical dimension.  The observed HTMT values alleviate concerns regarding multicollinearity, thereby reinforcing the model’s structural integrity and enabling meaningful interpretation of the relationships among the latent variables. The establishment of discriminant validity through the HTMT criterion notably improves the theoretical rigor of the study.  This guarantees that the identified relationships between constructs are not artifacts of measurement redundancy but instead reflect genuine conceptual distinctions.  This is essential in models that involve closely related constructs, such as “attitudes” and “intentions”, where empirical validation of construct reparability is required to maintain theoretical accuracy.  Additionally, the confirmation of discriminant validity enhances construct validity, mitigates the risk of spurious findings, and guarantees that any policy recommendations or practical interventions derived from the model are based on solid empirical evidence.  Insufficient discriminant validity can result in incorrect inferences, which may lead to misguided strategic decisions or ineffective policy developments. The HTMT criterion, although robust, has certain limitations.  In specific contexts, particularly when constructs are conceptually interconnected or measurement errors occur, the HTMT ratio may demonstrate heightened sensitivity, erroneously suggesting a deficiency in discriminant validity Henseler et al. (2015).  Therefore, dependence on the HTMT alone may produce inaccurate conclusions, especially in research contexts in which latent constructs inherently exhibit conceptual closeness.  Researchers should use additional validation methods, such as the Fornell-Larcker criterion, to enhance the assessment of discriminant validity and address these limitations.  Utilizing multiple validation approaches to triangulate the findings increases the credibility of the measurement model and reduces the likelihood of measurement bias. This study’s application of the HTMT ratio offers strong evidence for the discriminant validity of the constructs analyzed.  The HTMT values are all below the 0.90 threshold suggested by Teo et al. (2008), confirming that the constructs are empirically distinct and support the reliability and validity of the measurement framework.  The sensitivity of the HTMT ratio necessitates that these findings be interpreted alongside alternative validity assessments to ensure an accurate representation of construct relationships and to maintain the theoretical and empirical rigor of the study.

Source: Field Data (2025)

Table 4.7 Discriminant Validity (HTMT)

Source: Field Data (2025)

Table 4.10 Direct Relationship Result (CUSTP)

Source: Filed Data (2025)

4.4.2 To determine the effect of customer perspective measures on organisational performance indicators and examine the moderating effect of management support on the relationship between customer perspective measures and organizational performance indicators.

How does customer perspective measure influence return on assets as an organisational performance indicator?

The results shown in Table 4.10 demonstrate that customer perspective measures have a positive and statistically significant impact on ROA, as indicated by the statistical values (β = 0.487, t = 9.593, p > 0.001).  The strength and significance of this relationship indicate that organizations prioritizing customer-oriented strategies are likely to achieve enhanced financial performance. The results indicate that a 1% increase in customer perspective is associated with a 48.7% increase in return on assets.  This significant impact highlights the essential role of customer satisfaction, loyalty, and engagement in influencing the financial results. This notable positive effect indicates that firms engaging in customer-oriented initiatives achieve better resource utilization and revenue generation, thereby increasing profitability. The elevated t-value (t = 9.593) substantiated the strength of this relationship, suggesting that the observed effect was not attributable to random fluctuations.  The p-value (p > 0.001) supported the statistical reliability of the findings, indicating that the likelihood of these results occurring by chance was very low.  This finding supports the notion that organizations that successfully adopt customer-focused strategies are more likely to improve their market competitiveness and financial sustainability.  Prioritizing customer satisfaction and experience enables firms to enhance brand loyalty, decrease churn rates, and boost repeat business, thereby contributing to increased revenue and improved return on assets.  Furthermore, organizations that prioritize exceptional customer service and engagement may experience advantages in positive word-of-mouth marketing and customer referrals, thereby enhancing long-term profitability.  Firms that engage in customer relationship management, personalized service offerings, and integration of customer feedback may achieve a competitive advantage in the marketplace.  These strategies may result in elevated customer retention rates, greater cross-selling and up-selling opportunities, and enhanced cost efficiency, collectively contributing to improved financial performance.  These results emphasize the necessity of a balanced financial management approach that incorporates customer-oriented strategies. Traditional financial indicators are crucial for performance assessment; however, organizations must acknowledge that sustainable growth and profitability largely hinge on their capacity to fulfill customer expectations. This finding indicates that organizations aiming to improve financial performance should not exclusively concentrate on cost reduction and efficiency strategies; they must also prioritize customer engagement, service quality, and value creation.  The findings offer substantial empirical evidence that customer perspective measures significantly enhance organisational performance, especially regarding return on assets. This statistically significant positive relationship highlights the strategic relevance of customer satisfaction and engagement in influencing financial results. Organizations that effectively utilize customer-oriented strategies are likely to achieve greater profitability, enhanced market positioning, and sustained long-term viability.

What effect does customer perspective measure have on market share as an organisational performance indicator?

The findings in Table 4.10 reveal a positive and statistically significant correlation between customer perspective measures and market share, as evidenced by the statistical values (β = 0.473, t = 9.253, p > 0.001).  The significant positive coefficient indicates that organizations improving their customer perspective measures achieve considerable growth in market share.  The findings indicate that a 1% increase in customer perspective measures may result in a proportional increase in the market share.  This finding underscores the importance of customer-focused strategies in enhancing competitive advantage and broadening the market reach. The elevated t-value (t = 9.253) signifies that the impact of the customer perspective measures on market share is statistically significant and not attributable to random fluctuations.  The p-value (p > 0.001) further substantiated the strength of the relationship, indicating that the probability of the results arising by chance was minimal. The findings indicate that organizations emphasizing customer satisfaction, loyalty, and engagement are more likely to achieve a stronger market position, resulting in enhanced brand equity and an expanded customer base.  This result suggests that organizations that invest in customer experience, service quality, and responsiveness to customer needs may achieve a competitive advantage.  Companies that prioritize customer satisfaction typically experience enhanced brand recognition, increased customer referrals, and higher rates of repeat purchases, all of which facilitate the growth of their market presence.  The positive impact of customer perspective measures on market share indicates that organizations that engage with customers, address concerns, and provide superior value propositions can surpass competitors and enhance their industry positions. The significant correlation between customer perspective measures and market share highlights the necessity for customer-centric business models in the current competitive landscape.  Businesses that utilize customer feedback, personalized services, and relationship management strategies are likely to achieve sustained growth in their market share. Furthermore, companies that develop robust customer relationships can create brand advocates who endorse their products and services via word-of-mouth, thereby facilitating market growth. Organizations with a strong customer focus are likely to achieve higher customer retention, which directly contributes to an increased market share.  Maintaining current customers is generally more economical than attracting new ones, and satisfied customers tend to participate in repeat transactions, thus contributing to sustained market leadership.  Moreover, firms that cultivate robust relationships with their clientele can respond more adeptly to market fluctuations, thereby securing their ongoing growth and stability. The findings provide empirical evidence that the customer perspective significantly affects market share. The statistically significant positive relationship indicates that organizations aiming to improve their market position should prioritize investments in customer engagement, satisfaction, and value creation.  Adopting a customer-centric approach enables firms to enhance their market share, strengthen brand loyalty, improve competitive positioning, and ensure long-term business sustainability.

Does management support moderate the relationship between customer perspective measure and organisational performance indicators?

The examination of the moderating effect of management support on the relationship between customer perspective measures and market share yielded significant results.

 Table 4.10 indicates that the direct effect of management support on market share and return on assets is positive, yet statistically insignificant (β = 0.080, t = 0.939, p = 0.348). This finding indicates that when evaluated in isolation, management support does not significantly influence organisational performance metrics.  The lack of significance of the direct effect indicates that changes in management support do not directly result in alterations in market share or return on assets, suggesting that other underlying factors may play a more critical role in determining these outcomes. The introduction of management support as an interactive variable in the relationship between customer perspective measures and market share reveals a negative and statistically insignificant effect.  The interaction term shows a negative coefficient for market share (β = -0.137, t = 1.602, p = 0.109) and return on assets (β = -0.132, t = 1.690, p = 0.091). The coefficients indicate an inverse relationship. However, their insignificance suggests that the moderating effect of management support is insufficient to significantly influence the impact of customer perspective on market share.

This finding indicates that management support does not significantly influence customer-related strategies’ impact on market performance.  This finding indicates that although management support contributes to organisational decision making and strategic execution, its impact on the effectiveness of customer perspective measures in enhancing market share is limited. A potential explanation for this result is that customer perspective initiatives, including customer engagement, service quality, and satisfaction programs, may function autonomously, without direct managerial involvement.  This suggests that customer-driven strategies are primarily influenced by frontline employees, customer service protocols, and external market forces rather than by decisions made by top management.  The negative, albeit statistically insignificant, interaction effect may indicate that excessive managerial intervention can impede the effectiveness of customer perspective measures. Rigid managerial controls or overly structured support mechanisms can restrict the flexibility necessary to implement customer-focused initiatives. Organizations that prioritize bureaucratic decision-making processes may face limitations in responding to customer needs within a dynamic market environment, potentially reducing the effectiveness of customer-centric strategies.  The statistical insignificance of the moderating effect underscores the necessity for organizations to reevaluate the structure of management support to better align with customer-focused strategies.  Management may need to adopt a more integrative and participatory approach to ensure that customer engagement initiatives are supported in ways that enhance their impact on the market share. The results indicate that management support does not significantly influence the relationship between customer perspectives and market share.  The direct impact of management support on performance indicators is statistically insignificant, and its interaction with customer perspective measures does not significantly influence market-share outcomes.  These findings highlight the necessity for organizations to reassess the significance of managerial support in enhancing customer-driven strategies.

DISCUSSIONS AND IMPLICATIONS OF THE FINDINGS

The findings of this study significantly enhance the understanding of the relationship between customer perspective measures and organisational performance, specifically regarding Return on Assets (ROA) and market share. The findings indicate a significant positive correlation between customer perspective metrics and return on assets (ROA), implying that organizations adopting a customer-centric strategy tend to achieve enhanced financial performance. This finding aligns with previous research, which highlights the essential role of customer-focused strategies in improving profitability. Homburg et al. (2017) posited that customer satisfaction and loyalty are critical determinants of financial performance, suggesting that businesses prioritizing these elements are more likely to attain favorable financial outcomes. Anderson et al. (2014) identified a positive correlation between customer orientation and superior financial performance, reinforcing the idea that customer-centric strategies enhance profitability. This study identifies a positive and statistically significant correlation between customer perspective and market share. This finding is consistent with the existing literature indicating that organizations enhancing customer service and engagement strategies are more likely to increase their market share. Kumar and Shah (2004) illustrate that customer retention and satisfaction are essential factors influencing market share growth because satisfied customers are more likely to remain loyal and refer to new customers, thereby increasing the customer base. The findings of this study support the conclusion that an organization’s capacity to meet and surpass customer expectations markedly improves its competitive standing in the market. This study reveals a notable deviation from the previous literature regarding the role of management support. The findings indicate that management support, when examined independently, does not significantly affect organisational performance metrics, such as ROA and market share. This contradicts earlier research, which highlights the significance of managerial support in enhancing performance. Lee and Lee (2020) emphasized that management support is essential for the effective implementation of customer-centric strategies, as it supplies the required resources, commitment, and strategic direction to fulfill organisational objectives. Shams and Abolhasani (2018) indicate that strong managerial backing is directly correlated with enhanced performance outcomes, such as improved financial performance and market positioning. The contradiction observed in this study may be attributed to the context and operational dynamics of the specific organizations examined. This study indicates that the positive influence of management support on performance may depend on mediating variables, including organisational culture and the specific industry context, contrary to past research that has predominantly emphasized its benefits. The influence of management support may be more pronounced in industries in which customer service and relationships are vital to organisational success, particularly in the service and retail sectors. In certain contexts, particularly within highly technical or product-oriented industries, management support’s influence may be less evident. The inclusion of management support as an interactive variable in the relationship between customer perspective and performance indicators demonstrates a negative moderating effect on market share and ROA, although this effect is statistically insignificant. This finding confirms the dominant belief that management support enhances the connection between customer orientation and performance. Excessive or misaligned management support may lead to inefficiency and obstruct the effective implementation of customer strategies. This argument aligns with the findings of Johnson et al. (2016), who propose that management intervention may hinder frontline employees’ capacity to make customer-focused decisions, resulting in a misalignment between the organization’s strategic objectives and operational implementation. The negative moderating effect of management support may stem from the discrepancies between management’s vision and the customer experience strategies implemented within the organization. Management support that is not fully aligned with the organization’s customer-focused initiatives or a lack of clear and consistent direction from management may inadvertently undermine the performance-enhancing effects of customer orientation Liu et al., (2019). This finding aligns with recent research that highlights the intricacies of implementing customer-centric strategies, necessitating a suitable alignment between top-down support and bottom-up initiatives for operational effectiveness Zhang et al. (2020). This study supports the literature on the positive relation between customer perspective measures and performance indicators such as ROA and market share, except for the critical part of management support. The divergent effects of management support suggest that the role of management as a factor in organizational performance should be multifaceted than previously understood. Future research can be contextual, dealing with the effectiveness of management support, depending on the interaction between different organizational culture, type of leadership, and customer-oriented strategy in determining performance outcomes. Further research can consider whether such negative moderating effects are temporary or monotonous as well as focusing on the better management optimization for enhancement towards the customer-centric initiatives. The findings of this study enhance the theoretical understanding of the relationship between customer perspective measures and organisational performance, especially in relation to Market Orientation Theory (MOT). MOT suggests that companies exhibiting a robust market orientation, characterized by a focus on customer insights, awareness of competitors, and coordination among departments, generally achieve superior financial and market performance compared with their rivals Narver & Slater, (1990). The findings of this study support the existence of a positive and statistically significant relationship between customer perspective measures and Return on Assets (ROA) and market share, closely in line with various tenets of the theory. The more important finding is that organizations emphasizing customer-oriented strategies are likely to achieve financial results beyond others. This implies that a firm’s ability to respond to customer needs and satisfaction is an important driver of its profitability. This finding corresponds to the assertion by Narver & Slater (1990) that customer orientation is one of the most important components of market orientation and implementation of market orientation must result in superior financial results. The positive relationship between customer perspective measures and market share established in this study reaffirms the Market Oriented Theory (MOT) postulates. Firms that create value for customers and respond to their changing needs are more likely to gain market share Kohli & Jaworski, (1990).The positive sign of the coefficient per customer perspective measures and market share in this study indicates that organizations that adopt a customer focus can meet present customers’ needs and attract new customers, therefore strengthening their market position. This finding is consistent with previous studies indicating that customer satisfaction and loyalty, achieved through successful market orientation, propel growth in market share Homburg et al., (2009).The Market Orientation Theory expected some serious departures in management support, but the study shows that it has not worked in this way. The significance of management support in contributing to market-oriented behaviors is often emphasized, but studies have shown that when it is taken independently, there is no significant effect of management support on either ROA or market share. In addition, the role of management support as an interaction variable in the relationship between customer perspective measures and performance exhibited a negative moderating effect. This fact contest the much-approved notion in technology management that management support would in all cases increase the effectiveness of market-oriented behaviors. Thus, because management commitment is critical in facilitating customer-focused strategies, its effects oftentimes will tend to be inexact correlations or nondiscriminatory benefits, especially in cases where misalignment occurs between strategic objectives held by management and the actual implementation of customer-oriented initiatives. Although it was often stressed that management support is an important preceding condition of market-oriented behavior (Slater & Narver 1995), the findings tend to indicate that by them management support has no significant effect on either ROA or market share. Further, the introduction of management support as an interactive variable between customer perspective measures and performance made a matter-of-fact negative moderating effect. This aspect unseals the much-believed proposition in technology management that management support would in all cases increase the effectiveness of market-oriented behaviors. It signals that though management commitment is essential for implementation of customer-focused strategies, its effects may sometimes be very erratic and could even be nondiscriminatory benefits, especially when there is misalignment of strategic objectives held by management and actual execution of customer-oriented initiatives. This evidences the introduction of complexity into the MOT framework, meaning that management support may not always directly support market-oriented behaviours and performance. The findings substantiating the fundamental tenets of Market Orientation Theory show the positive influences of customer-oriented strategies on financials and market performance, with some notable contingencies on the impact of management support. This finding urges a more sophisticated understanding of the dynamics between organizational culture, management practices, and market orientation. It thus indicates that future research should also look at what situations would see management support working for or against the effectiveness of market-oriented Behaviour. The findings of this study have considerable practical implications for organizations that are trying to improve their performance through customer-oriented strategies. The findings also suggest that there will be a positive relationship between customer perspective measures and return on assets (ROA), market share, thus showing the need for a customer-oriented focus. Companies that are highly committed to and concerned with customers being satisfied with their services, retained, and loyal can expect to witness great improvements in financial performance and competitive standing in the market. All the outcome results show that companies should be very interested in customer feedback integration, investment in customer service innovations, and realignment of products and services with customers’ needs in their strategic agendas. They were able to improve their financial performance by increasing profitability measured by ROA and also increased market positioning as shown by the increase in market share. Managers should understand that giving priority to customer experience may be one of the important items for long-term financial soundness. This perspective would require understanding consumers and what drives them in terms of expectations; this is fundamental to an organization’s strategy. Managers should pay attention to customer-centric practices that shape the direct financial results. The investment in customer relationship management systems, personalized services, and targeted marketing initiatives designed to enhance customer satisfaction is expected to yield a significant return on market share and profitability. The findings of this research go far beyond organizational policies and render direct contributions to regulatory agencies and industry stakeholders towards promoting financial performance and market competitiveness through cu customer-oriented strategies. They also demonstrate the even more pronounced impact of measures tapping customer perception on return on assets (ROA) and market share, which will call for policies geared towards a customer-oriented organizational strategy, making customer satisfaction, service quality, and market responsiveness the key elements of business governance and economic growth. Policymakers should promote the adoption of customer-centric policies by organizations to ensure that business operations align with consumer needs. Regulatory frameworks may require customer service excellence, ethical marketing practices, and transparent consumer engagement strategies to achieve sustainable financial performance. Policies that encourage organizations to adopt customer feedback mechanisms, invest in customer relationship management (CRM) systems, and improve customer experience may lead to enhanced profitability and market positioning.

CONCLUSION

The results highlight the importance of customer need-focused strategies as means to improve finances and secure competitiveness in rapidly changing industry environments. Notably, the research concludes that managerial support is not an effective mediator in the links among customer focus and performance, contrary to preconceived expectations that engaged leadership automatically develops more effective implementation of such strategies. Instead, the data implies that frontline engagement, responsive customer service, and real-time market adaptation may exert a more immediate effect on organizational success than top-down management initiatives. These findings highlight the necessity for leadership to embrace more integrative and adaptable approaches that empower employees while aligning with customer needs. The findings have far-reaching implications for academic research and business practice in varied organizational settings. It is recommended that organizations invest in customer relationship management, data-driven innovations, and personalization strategies. It is equally important for policymakers and regulatory agencies to start dialogue processes with an aim to developing guidelines that will help integrate customer-focused initiatives in organizational governing frameworks. In conclusion, this study contributes to the literature on performance management by highlighting the importance of including the customer’s perspective, while making a strong case for a more complex understanding of managerial support. Follow-up research should focus its attention on sector-specific relationships and organizational cultures that could influence these relationships.

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