Customer Focus as a Critical Success Factors for Business Process Re-engineering to Achieve Academic Performance. A Case of Higher Education Institutions in Kinshasa, Democratic Republic of Congo (DRC)

Customer Focus as a Critical Success Factors for Business Process Re-engineering to Achieve Academic Performance. A Case of Higher Education Institutions in Kinshasa, Democratic Republic of Congo (DRC)

Jean Bosco Mukolo*, Dr. Susan Wasike (Ph.D) & Rev. Dr. Paul Mathenge

Department of Graduate Business Studies, School of Business & Economics, The Catholic University of Eastern Africa

*Corresponding Author

DOI: https://dx.doi.org/10.47772/IJRISS.2024.806164

Received: 27 May 2024; Accepted: 17 June 2024; Published: 15 July 2024

ABSTRACT

In this study, the authors are proposing an innovative business process re-engineering improvement strategy by adopting, adapting and focusing on customers (students as the primary customers of higher education) concept to improve their quality of education and achieve academic performance. The research aims to investigate the influence of customer focus (student) variables on academic performance.  Customer focus is one of the components of BPR and administrative process at higher education. The study uses BPR as Business strategic management approach to be applied in educational sector to enhance performance. The findings reveal a complex interplay of factors influencing academic performance within higher education institutions in Kinshasa, DRC. While certain aspects, such as orientation processes and the Ministry of Education’s selection process, were positively regarded, there is room for improvement in other areas, particularly in considering academic performance during admission and addressing non-academic factors that can ameliorate students’ performance. The findings can inform various stakeholders to design policies that enhance academic performance by adopting a more customer focus (student oriented) approach, while also addressing socio-economic issues and other non-academic factors preventing students’ performance.

Keywords: Business process re-engineering (BPR), higher education, performance.

INTRODUCTION

Students are regarded in this study as customers. This is an innovative approach to meet the students’ needs, expectations and enhance their academic performance. Higher educational institutions should be more focused on factors that enhance students’ academic performance. Rubio-Arostegui (2017) suggests that higher education students should considered as customers from business-oriented mindset, a shift from the traditional viewpoint. This shift is part of a new paradigm in higher education, focusing on the satisfaction of the needs and expectations of the students to improve their academic performance.

Now, let us initiate this section by discussing the variable customer focus as a component of Business Process Re-engineering which is the independent variable in the study. While academic performance is considered as dependent variable.  Several definitions suggest that Business Process Reengineering (BPR) is an offshoot of Business Process. BPR has frequently been used since it was first introduced in the United States in the 1990s. The concept of BPR was first used in Hammer‟s article: Reengineering Work: Don’t Automate, Obliterate (Hammer, 1990). According to Dey (2001) Business Process Re-engineering is a strategic methodology that focuses on enhancing organizational efficiency and effectiveness by fundamentally redesigning critical business processes. Business Process Re-engineering is an approach where processes are re-structured, re-designed and re-engineered so as to maximize an organization’s potential (Rajabion et al., 2010). The concept of BPR aims at enabling organizations improve productivity and relationships with customers and reduce time to launch new products and services in terms of cost, quality, customer satisfaction and shareholders value by identifying and re-engineering the important processes of the firm. It is a way in which organizations become more functional by identifying the critical business processes, analyzing these processes and redesigning them for efficient improvement and benefit (Uchena & Joel, 2021). Our study evaluated academic performance by analyzing graduation rates and indicators of academic achievement (grades) of graduate students. The research defines academic performance as the extent to which the educational institution fulfills the needs and expectations of its customers (students) (Abdullah & Mirza, 2019).

Customer focus (students) is one of the components of BPR. Customer focus in this study is referred to as students of higher education both private and public institutions. According to Patyal & Maddulety (2015), quality gurus have consistently emphasized the importance of understanding customer (students) requirements, needs and expectations.  The management teams of HEIs should be encouraged to listen to the voice of the customers (students) and then respond to their needs and expectations in acquiring knowledge and skills. The study encourages higher education stakeholders in general and the management to adopt and adapt customer focus (students) orientation philosophy to identify, analyze and improve the o educational processes related to the students that can enhance the quality of education and achieve academic performance. The study is focused on academic and non-academic factors, mainly orientation, selection, admission, financial, previous educational background) as independent variables that can influence the academic performance of the students measured by graduation rates (completion of the study) and grades both at undergraduate and master’s levels from the 2016-2021.

Statement of the Problem

Education serves as the cornerstone for the socio-economic, cultural, political, and peace sustainability of every nation globally. It plays a pivotal role in shaping both individual destinies and national economies (Thondhlana & Garwe, 2021). The quality of higher education institutions in the Democratic Republic of Congo is subpar when compared to those in other countries at the global and regional levels. Prior empirical studies argued that the Congolese educational system is known to be both ineffective and outdated (Virima, 2008, Mokonzi &Kadongo, 2010; Eyanganunga, 2006). The World Bank (2018) report revealed that education system in the Democratic Republic of Congo is struggling to provide the country with a skilled labor force capable of turning the country into an industrialized economy by 2030. Almost half the working-age population in the country has either no education (28 percent) or less than primary education attainment (19 percent), suggesting a need for programs that increase education quality.

Furthermore, the World Bank (2018) report revealed that higher education sector needs significant leaps in quality and improvements in efficient use of resources. Half of enrolled university students drop out before they reach their third year. Students’ dropouts and poor students’ academic performance is among the challenges facing higher education. The completion rate is around 60 percent. A number of  empirical studies  agreed upon and revealed several fundamental problems facing higher education institutions in the Democratic Republic of Congo including: the quality of education, degradation of education system, teaching and learning infrastructures, inadequate libraries,  laboratories , skilled, qualified and competent human resources are highlighted by many studies  (De Herdt & Titeca, 2016; Etshim, 2017; Kilongo & College, 2020; Mitonga-Monga & Mayer, 2020; Republique & Du, 2018; Teferra & Altbach, 2004). A recent investigation on higher education institutions by Gudiño León. et al., (2021) observed that higher education in DR Congo is facing several problems including outdated educational system, poor quality education, and student’s underperformance due to poor previous educational background, admission process, socio-cultural factors and financial problems.

Objective of the Study

The main objective of this study is to find out whether Business Process Re-engineering can contribute to the academic performance.  While the specific objective of the study is to examine the influence of customer focus (student) on academic performance.

Research Hypothesis

Based on the specific objective, the study examined the following null hypothesis:

H₀: There is no relationship between customer focus (student) and academic performance.

LITERATURE REVIEW

In this study, students are considered as customers. Giving consideration to the highly competitive international education market, the necessity of creating and delivering higher customer value become significant in keeping a continued advantage. Customer satisfaction is a basic marketing term. Although the terms ‘customer satisfaction’ and ‘service quality are sometimes used interchangeably, they are quite different from each other (Glennie, 2016). Parasuraman et al. (1988) consider satisfaction as a criterion for measuring and evaluation while the service quality is regarded as an achievement based on the assessments. In this sense, satisfaction is seen an antecedent to service quality but (Cronin & Taylor, 1992) argues in contrast that it is the service quality that determines satisfaction. In education market, the term ‘student satisfaction’ is also used commonly because students are the main customers in that market. Having affected by many factors, the student satisfaction represents one of the basic issues in this context.

Mbithi et al. (2021) highlighted challenges in African higher education institutions, requiring intervention from governments, development partners, and new investment paradigms to enhance students’ work-ready skills. Many students who manage to enroll in education or training programs do not complete their studies and miss out on obtaining formal qualifications, which can dramatically reduce the return on educational investments in terms of lifetime earning potential (Assari et al., 2019). Student engagement, mobility and employability are inadequately addressed. Occupational mobility and portability of qualifications from one HEI to another HEI within and across African countries remain low. Employability of HEI graduates remains equally low due to several factors such as skills mismatch and low levels of literacy. For instance, of the entire working-age population more than 80% in Ghana and more than 60% in Kenya cannot infer simple information from relatively easy texts (World Bank, 2018).

Florence (2012) found that family structure significantly influences undergraduate economics students’ academic performance, with income, educational levels, and entrance exams determining achievement. Similarly, Mutiso & Muthama (2019) found that final high school grades positively affect all undergraduate students, including male and female students, local students, and those taking business and social science-based courses. Numerous studies confirm the importance of high school types in determining students’ academic performance. The study conducted by Article et al. (2019) concluded that an admission criterion is one of the key indicators of academic success. Thus rigorous admission criteria can predict academic performance, decrease failure rate and successful completion of degree. The results reported a significant relationship between admission criteria and the academic performance of nursing students. The shift towards students as customers in university systems, particularly in competitive markets like the US, UK, and Australia, is gaining traction. Marc C. Taylor from Columbia University emphasizes that denying this shift is a missed opportunity. Heather Rolfe supports this shift, stating that students deserve excellent service.

Higher education students are increasingly being seen as customers or clients, a shift in traditional notions of students. This paradigm includes factors like competitiveness, public reputation, student investment, professional development, and satisfaction-focused curricula. This shift is prevalent in some countries, while in others, like Spain, it is slowly gaining traction (Rubio-Arostegui, 2017). According to Or-Bach ( 2013) preparing students for a knowledge-based economy is a challenge that requires curriculum design that puts more emphasis on learning skills and on content to be taught. Cognitive skills should be practiced in a context of some content, but the choice of content, the choice of the learning environment and the choice of the assessment procedures can enhance the development of such skills. According to the Ministry of Higher Education of the Democratic Republic of Congo, low internal efficiency is one of the factors affecting the quality of higher education sector. It is characterized by very high level of dropout and repetition rates, particularly in the first years of study at university, varying between 30 and 40% depending on the discipline (Republique & Du, 2018).

Addressing quality issues in the service sector like education, the customer focus approach should be emphasized, adopted and adapted to re-engineer teaching, research and administrative process. The paper is focused on customer (students) issues which is concerned with the academic administrative process.  The provision of quality services at HEIs begins with understanding the customer (students) needs and ends when those needs when are met and satisfied. The needs and expectations of the customer (student) such as skills and knowledge acquired should become the focal point when managing and re-engineering educational institution to improve the quality and achieve performance. Students serve a vital role as one of the many customers of higher education. Student can be treated as customer, product and raw material under different perspectives. The customer is the person or group who receives the work output such as knowledge, skills and attitude in the context of higher education. That work output may be a product or service. The students in the classroom serve as the immediate internal customer of the lectures and discussions. In turn, the student then gains from a number of different experiences and becomes a product of the system (Durga Prasad et al., 2012).

Jenicke et al. (2008) argued that students may be viewed as both the product and the customer of higher education. As participants in the educational process, they may be viewed as a product in process, a completed product (graduate), a customer for campus facilities and a customer for course material. The student’s employer may also be viewed as the customer as can the parents/family, the community and society in general. BPR focuses on the customer (students) by listening to the voice of the customer (student) and then making improvements to the product or service (Harrison et al., 2010).,

Ho et al. (2006) emphasize the importance of understanding a student’s role in higher education. They argue that focusing on student satisfaction is insufficient for effective customer focus. Students play multiple roles in higher education, including internal customers, internal customers, and external customers like parents, stakeholders, and industry. The education sector faces significant challenges due to its unique nature, long-term operations, and complex governance. It is difficult to observe change due to the longitudinal nature of learning and performance, and the human element in the process. Additionally, education often produces heterogeneous output, with each student having unique features and responses to changes.

Ibrahim (2016), observed that when the re-engineering education process is modeled as manufacturing process, students (graduates) are viewed as products. Whereas, Staiou (2006) argued that in the context of an analogy with a manufacturing organization, higher education institutions produce graduates. Students move through the various courses required for a degree, as raw material flows through the successive stages of a manufacturing process. When they graduate, graduates compete for jobs just as products compete for a market share. Thus, graduates may be interpreted as the finished product and that industry future employers are the customers of higher educational institutions. The clients are the students and the excellence of learning they achieve is the service. We can also conclude this section by stating without being contradicting that student is the product, which the education institutions sell to the future employer. Therefore, customer focus as strategic approach in managing higher education sector is becoming a necessity for all educational stakeholders.

Previous empirical studies have revealed the relationship between Business Process Re-engineering and academic performance (Harb & Abazid, 2018; Hargrove & Burge, 2002; Jenicke et al., 2008; Polytechnic & State, 2019; Ramasubramanian, 2012).

Theoretical Review

Students Involvement Theory (SIT)

The Students Involvement Theory was proposed by Alexander W. Astin in 1975, and aimed to improve the academic performance of students in higher education institutions. The introduction of Astin’s involvement theory, as highlighted in the research findings of Foreman & Retallick (2013), has prompted researchers and professionals to incorporate it into programs and refine curricula, streamlining administrative decision-making processes, and conducting investigations to identify both academic and non-academic variables that can enhance students’ academic performance. In Astin’s (2014) student involvement theory, the emphasis is placed on the level of physical and psychological factors that students put into their academic pursuits. Consequently, a deeply involved student can be characterized by their substantial commitment to studying, extensive presence on campus, active engagement in various academic and extracurricular activities, and frequent interaction with faculty members and peers (Astin, 2014). In contrast, an average uninvolved student shows a lack of interest in academics, spends limited time in school, avoids extracurricular activities, and has minimal interaction with faculty members, administrators, and peers. These examples are meant to be illustrative, as there are numerous other forms of involvement that can influence student academic performance, including institutional policies, non-academic factors like student associations and financial assistance, and various other aspects of campus life.

To conclude this section, Astin (2014) found that students who take part in a variety of activities, encompassing both pedagogical and non-pedagogical pursuits, within an educational setting, demonstrate a greater propensity for academic success compared to their non-participating counterparts. Student involvement theory emphasizes the importance of the student’s engagement in their own learning and their responsibility in establishing a connection with the learning environment throughout their educational journey (Jones, 2012). The student involvement theory holds significance in this study as it assists higher education managers in identifying and examining the various academic and nonacademic variables that can enhance student involvement, ultimately leading to improved academic performance.

RESEARCH METHODOLOGY

This study is based on positivism philosophy. A census was done to gather information from all higher education institutions in Kinshasa both public and private. The study was carried out from August 2022 to May 2023. Primary data for the study was obtained from the Registrars and Directors of Quality Assurance of all higher education institutions in Kinshasa. The sample population of the study consisted of 57 higher education institutions in the City of Kinshasa. Quantitative data from this study was collected from primary source. Questionnaire was used to collect quantitative data. Questionnaires were distributed to all 114 (respondents 57 Registrars and 57 Directors of quality assurance) of HEIs. Out of these, 101 questionnaires were completed and returned (46 registrars and 55 Directors of quality assurance), while 10 were incompletely filled, and three were never returned. The questionnaire was measured on a 1-5 Likert scale, where 1= strongly disagree (SD) and 5= strongly agree. The scale was adapted from Business Process Re-engineering variable customer focus/students and measured by the sub-variables such as student orientation and selection process, admission process, financial resources and previous academic background indicators to examine their influence on academic performance. The overall response rates were calculated at 89%%, which significantly exceeds the typically recommended response rate for surveys. The researcher employed factor analysis as the primary tool for data analysis and furthermore, quantitative analysis was done. After factor analysis, descriptive statistics (frequencies, percentages, averages, mean, and standard deviations) were used in the study and therefore, the results were presented via tables, figures and graphs. In addition, Pearson correlation was used to measure linear relation between independent (BPR) and dependent variables (academic performance). Finally, multiple regression analysis was done to determine the correlation between customer focus (students) and academic performance. Two sets of scaled items were compared using the Cronbach Alpha reliability coefficient. The findings revealed correlation values greater than acceptable threshold of r= 0.05, with 0.798 and 0.816. The Cronbach Alpha values were greater than 0.7 affirming an acceptable level of internal consistency.

DATA ANALYSIS

This section of the study discusses the analysis of data from survey which was conducted by the researcher. The research was conducted with a total of 101 respondents, comprising 46 Registrars and 55 Directors of Quality Assurance from higher education institutions in the city of Kinshasa. Questionnaires were distributed to all 114 participants. Out of these, 101 were completed and returned, while 10 were incompletely filled, and three questionnaires were never returned. The overall response rate was calculated at 89. %, which significantly exceeds the typically recommended response rate for surveys, set at 30% (Baruch & Holtom, 2021; Baruch, 1999). This high response rate, surpassing two-thirds of the total sample, is instrumental in mitigating potential nonresponse bias and bolstering the validity and reliability of the survey findings (Saldivar, 2012; Fincham, 2008). As a result, the study findings can be confidently considered reliable and valid with respect to the research questions. They serve as a valuable reference point for the Government, Ministry of Higher Education, policymakers and higher education institutions.

RRR = (Total number of response/Sample Size) × 100

= (101/114) × 100

= Ans = 89%

The KMO value is 0.642. This value suggests that the data is moderately suitable for factor analysis. While it doesn’t reach the ideal value of 0.7 or higher, it is still within an acceptable range. It indicates that there is a reasonable amount of shared variance among your variables, which is a prerequisite for factor analysis. This result is consistent with the common threshold for acceptability in factor analysis (Kaiser, 1970). In addition, the Bartlett’s Test of Sphericity yields an approximate chi-square value of 589.094 with 190 degrees of freedom and a significance level of .000 (essentially 0). This indicates that the correlation matrix is significantly different from an identity matrix, supporting the idea that there are correlations among the variables. The small p-value (typically below 0.05) in Bartlett’s Test suggests that the correlation matrix is not an identity matrix, which is a positive sign for factor analysis

Table 1. KMO test Customer Focus

(Source researchers Computation, 2023)

The identification of items with values exceeding 0.5 signifies their importance in further analyses, contributing to a richer understanding of this critical area of study. Table 12 shows items which were considered for further analysis.

Table 2. Items considered for further analysis for customer fucus (students)

(Source researcher computation, 2023)

Table 3. Component Matrix for customer Focus

1. Customer Focus (Student) Influence Academic Performance

Factors influencing academic performance

Table 4. Descriptive Statistics for Factors Influencing Academic Performance

(Source Researcher computation, 2023).

The general objective of the research aimed to investigate the contribution of Business Process Re-engineering (BP) on Academic Performance within Higher Education Institutions in Kinshasa, Democratic Republic of Congo. The specific objective was to examine if customer focus can influence academic performance of the students.

The survey results indicated that the orientation process before students join higher education institutions was generally viewed favourably, with an average score of 3.22 out of 4. This suggests that a well-structured orientation process may positively influence academic performance by facilitating a smoother transition into higher education. Similarly, respondents generally held a positive view of the Ministry of Education’s student selection process, as indicated by an average score of 3.32. This implies that the selection process is perceived as effective in ensuring that suitable candidates are admitted to higher education institutions. In contrast, the consideration of prior academic performance, such as results in higher education tests and grades during admission, received a relatively lower average score of 2.28. This suggests that respondents believe there should be a greater emphasis on academic merit during the admission process.

Student satisfaction with their grades at various stages of their academic journey varied. While satisfaction with first-year grades during the 2020-2021 academic year was moderate (average: 2.95), satisfaction with grades obtained after completing the first degree was slightly lower (average: 2.60). This could imply that there is room for improvement in academic performance throughout students’ educational journeys. Respondents also moderately agreed (average: 2.55) with the organization of admission tests for students who scored less than 60% in national examinations, as recommended by the Ministry of Higher Education. This suggests some support for this approach as a means to identify potentially successful students.

Concerning non-academic factors, respondents did not appear to assign high importance to motivation, creativity, perseverance, or social integration in relation to academic performance, as indicated by relatively low average scores. This finding underscores the need for attention to these factors, as they can significantly influence students’ success in higher education. Family-related factors, such as economic status and parents’ level of education, were perceived as influential in academic performance, with relatively higher average scores. This highlights the role of socio-economic factors in students’ ability to succeed in higher education. Finally, the development of a competency-based approach at the university level received an average score of 1.92, indicating that respondents may not see this approach as highly valuable for enhancing academic performance.

These findings suggest a complex interplay of factors influencing academic performance within higher education institutions in Kinshasa, DRC. While certain aspects, such as orientation processes and the Ministry of Education’s selection process, were positively regarded, there is room for improvement in other areas, particularly in considering academic performance during admission and addressing non-academic factors that can impact students’ success. These findings can inform strategies to enhance academic performance by adopting a more customer/student-focused approach, while also addressing socio-economic disparities and non-academic factors affecting students’ learning experiences.

2. Correlation between Customer Focus (Students) and Academic Performance

Table 5. Correlation Between Customer Focus and Academic performance

Source (Field Data, 2023)

The presented correlation matrix scrutinizes the interrelationships among distinct variables: Customer/Students Focus (an independent variable), Enrolment, Master Grades, Master Completion, and Undergraduate Completion rate (dependent variables). Employing Pearson correlation coefficients, the matrix also divulges the statistical significance of these associations.

In the first set of correlations, Customer Focus is unveiled as weakly and insignificantly inversely correlated with Enrolment (-0.029, p = 0.880). This observation negates the presence of a substantial linear nexus between customer focus and student enrolment. Likewise, Customer Focus demonstrates feeble non-significant negative correlations with Master Grades (-0.231, p = 0.257) and Master Completion (-0.148, p = 0.461), intimating the absence of a substantive linear relationship with these indicators of academic accomplishment. Analogously, a comparable pattern emerges with Undergraduate Completion rate, where Customer Focus showcases a slight negative correlation (-0.269), yet remains statistically insignificant (p = 0.159).

Moving on to Enrolment, it is established that a moderate and statistically significant positive correlation exists with Master Grades (0.356, p = 0.074), Master Completion (0.703**, p < 0.01), and Undergraduate Completion (0.642**, p < 0.01). This revelation underscores that heightened enrolment correlates with enhanced Master Grades, elevated Master Completion rates, and improved Undergraduate Completion rates. The analysis of Master Grades further accentuates its robust and statistically significant positive correlations with Master Completion (0.767**, p < 0.01) and Undergraduate Completion (0.846**, p < 0.01). This substantiates that superior performance in Master’s programs heightens the likelihood of successful completion in both Master’s and undergraduate degrees.

Significantly, the association between Master Completion and Undergraduate Completion (graduation rate) emerges as notably robust and statistically significant (0.880**, p < 0.01), signifying a compelling linkage between successful Master’s program finalization and triumph in undergraduate studies.

Notably, the lack of a consequential correlation between Customer Focus and academic performance indicators suggests that, within this contextual framework, the concept of customer focus – possibly encapsulating a university’s attentiveness to student contentment and feedback – does not wield a direct impact on enrolment, academic grading, or completion rates. This conclusion resonates with the scholarly stance of (Endalamaw & Yigermal, 2017), indicating that student satisfaction might not consistently align with academic outcomes.

Evident alignment surfaces through the positive correlation between Enrolment and academic performance metrics (Master Grades, Master Completion, and Undergraduate Completion), echoing antecedent studies positing that augmented enrolment equips institutions with greater resources to elevate academic provisions and bolster support services, thereby fortifying student outcomes (Etshim, 2017). Furthermore, the robust positive correlations between Master Grades and both Master Completion and Undergraduate Completion accentuate the pivotal role academic achievement plays in prognosticating degree attainment. Flourishing in Master’s programs augments the likelihood of triumph in both Master’s and undergraduate pursuits. The pronounced positive correlation linking Master Completion with Undergraduate Completion serves to underscore the intertwined nature of accomplishing advanced degrees and undergraduate success, often grounded in the earlier triumphs of the undergraduate phase.

3. Testing Hypothesis Customer Focus/Students and Academic Performance

H₀: There is no relationship between customer focus (students) and academic performance.

Table 6. Testing Hypothesis customer focus and academic performance

(Source field data, 2023)

Based on the regression analysis results, it is evident that the study has unveiled a notably low R Square value of 0.022. This value signifies that only a minute fraction of the variance in academic performance can be elucidated by the factor of customer focus/students. Notably, the Adjusted R Square value appears to be negative, specifically -0.013. This is an unusual finding and may raise doubts about the appropriateness of the model for explaining the data. Furthermore, examining the F-Statistic, which stands at 0.639 with a corresponding p-value of 0.431, provides additional insights. A notably high p-value such as this suggests that the model lacks statistical significance. It implies that the observed relationship between customer/students focus and academic performance is not sufficiently robust to draw meaningful conclusions. Turning attention to the coefficient associated with customer focus/students, it is evident that it stands at -162.293. This negative coefficient suggests an inverse relationship between customer/students focus and academic performance. However, it is critical to note that this coefficient does not possess statistical significance. The p-value of 0.431 exceeds the conventional threshold for significance (typically set at 0.05). Collectively, these findings collectively fail to furnish compelling evidence to reject the null hypothesis. The trifecta of a low R Square value, non-significant ANOVA results, and an insignificant coefficient for customer/students focus collectively point to the absence of a substantial relationship between customer focus and academic performance within the purview of this analysis.

SUMMARY OF FINDINGS

The research instrument’s return rate for this study was remarkably high, with 101 out of 114 distributed questionnaires being satisfactorily completed and subsequently returned. This outcome translates to an overall response rate of 89%, a figure that notably surpasses the established response rate benchmark of 30% for surveys. This elevated response rate serves a dual purpose, not only mitigating the potential for nonresponse bias but also significantly augmenting the survey findings’ validity and reliability. Consequently, the study’s findings can be ascribed a high degree of reliability and validity with regard to the research inquiries (Baruch & Holtom, 2021; Baruch, 1999; Saldivar, 2012; Fincham, 2008). In summary, while certain facets of customer focus (students) in higher education institutions in Kinshasa, DRC received positive evaluations, there exists potential for improvement in other areas, particularly in terms of considering academic performance during the admission process and addressing non-academic factors that can significantly impact students’ educational journeys. These findings underscore the necessity for a comprehensive approach to enhancing academic performance, encompassing a broader spectrum of variables beyond customer/student focus approach. Addressing socio-economic disparities and non-academic factors that influence students’ learning experiences should be integral to this approach.

CONCLUSIONS

In summary, this study aimed to investigate whether customer focus which is a critical component of Business Process Reengineering (BPR), can have an influence on academic performance of the students in the context of higher education institutions in Kinshasa, Democratic Republic of Congo (DRC). The null hypothesis (H01) concluded that there is no relationship between customer focus and academic performance. The p-value for customer focus was -0.013<0.05. Therefore null hypothesis (H01) was not rejected. These findings suggest that customer focus may not directly contribute to academic performance in this context. The finding is supported by the Student Involvement Theory. Student Involvement Theory is relevant in seeking to assist higher education institutions in identifying and evaluating the various academic and non-academic factors that can enhance student involvement, ultimately leading to improved academic performance. Our findings provide valuable insights into this complex interplay of academic and non-academic factors and their implications for academic performance in this specific context. Finally, our study provides valuable insights into the factors influencing academic performance in higher education institutions in Kinshasa, DRC. While certain aspects, such as the orientation process and student selection, are viewed favourably, there are areas for improvement, including admissions criteria and non-academic factors that contribute in achieving academic performance

RECOMMENDATIONS

In light of the research findings, a set of recommendations can be formulated, addressing both educational institutions in Kinshasa, Democratic Republic of Congo (DRC), and offering guidance for future research endeavours.

A. The study recommends that HEIs in Kinshasa, DRC should re-engineer their administrative processes in particular, the admission process with a particular emphasis on academic merit as a criterion for student selection to enhance academic performance. This includes developing support mechanisms for students as they progress beyond their initial year of study, the holistic approaches on the factors that can enhance academic performance, the provision of academic assistance & guidance, comprehensive counselling services and strategic allocation of resources can substantially contribute to students’ performance.

1. 1. Empirical evidence from this study accentuates the substantial influence of socio-economic factors to enhance academic performance. In this response, HEIs should to strategize and implement initiatives aimed at providing equitable support, scholarships, or resources to students hailing from disadvantaged socio-economic backgrounds. This proactive stance is instrumental in mitigating educational disparities and advancing the cause of equitable academic performance.
   2. The study recommends that HEIs should consider strategic management and competency-based approaches at higher education level and critically re-engineer and adapt their pedagogical processes to improve academic performance. This adaptive process should be oriented towards a more efficacious alignment with the evolving needs and expectations of students, the society and ensuring the relevance of educational strategies.
   3. Subsequent longitudinal, comparative and cross-cultural comparisons investigations should be conducted to explore the intricate web of academic and non-academic factors that exert influence on academic performance.

About the Author

Jean Bosco Mukolo is a PhD candidate in Business Administration, Strategic Management at the Catholic University of Eastern Africa (CUEA), Nairobi-Kenya.  He hold a Master Degree in Project Planning and Management from University of Nairobi.

Co-authors (My PhD Supervisors):  Dr Susan Wasike (Ph.D) and Rev. Dr Paul Mathenge

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