CSRC Publishing: Open Journal Systems (Center for Sustainability Research and Consultancy)
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Artificial Intelligence and Big Data Analytics: Transforming Supply Chain and Sustainable Manufacturing to Achieve SDGs Agenda
No full textPurpose: The purpose of this work is to understand the changes brought by artificial intelligence (AI) and big data analytics (BDA) to supply chain management (SCM) and sustainable manufacturing (SM) in the developing countries context. It seeks to identify key enablers, advantages, and challenges of implementing those technologies toward advancement to the UN SDGs.
Design/Methodology/Approach: Cross-sectional survey research method was adopted; specifically, structured questionnaires were administered to 356 mid to senior level managers of various industrial organizations in Pakistan. Hypothesis testing was done by using Partial Least Squares Structural Equation Modeling (PLS-SEM) to determine the relations between the four variables, namely: AI, BDA, SCM, and sustainable manufacturing. The evaluation of such key drivers also involved proving the demographic and organizational factors such as Technology Maturity and Investment.
Findings: This study further shows that AI and BDA improve the supply chain performance and manufacturing sustainability. It can be pointed out that BDA has the strongest direct effect on environmental efficiency and waste saving. But there are certain factors that limit adoption, such as budget issues, lack of skilled IT people, and organizational culture that goes against adoption.
Implications/Originality/Value: This paper presents important implications for the policy makers as well as the business strategists. AI and BDA require investment in infrastructure and development of the workforce and the human ability to cope with the change that comes with the implementation of these Two technologies. Such efforts can enhance operational reliability, cost effectiveness and sustainability of the environment. This study fills such a gap in literature by providing empirical results from a developing economy setting. It is helpful to expand the existing information about Industry 4.0 technologies and offer practical recommendations for further sustainable development of digitalization in emerging economies
Organizational Commitment as a Moderator in the Relationship Between Transformational Leadership and Job Satisfaction: A Study of Banking Sector in Multan, Pakistan
No full textPurpose: This study investigates the impact of transformational leadership on job satisfaction and organizational commitment among employees in the banking sector of Multan, Pakistan. It further examines the moderating role of organizational commitment in the relationship between transformational leadership and job satisfaction.
Design/Methodology/Approach: The research employed a descriptive correlational design and survey method. A sample comprising 160 employees working in both public and private sector was selected through a convenient sampling approach. The data was collected through structured questionnaires. The study utilized descriptive statistics, correlation analysis, and regression techniques to evaluate the relationships and test hypotheses.
Findings: The results indicated a significant positive relationship between transformational leadership and job satisfaction. However, organizational commitment did not moderate this relationship. These findings highlight that transformational leadership independently contributes to higher levels of job satisfaction and employee commitment within the banking sector.
Implications/Originality/Value: The study offers valuable insights for banking institutions aiming to enhance employee satisfaction and commitment through effective leadership practices. It emphasizes the importance of leadership development programs tailored to promote transformational leadership. Future research may explore additional factors that influence these organizational outcomes
Credit Risk Management Practices and Financial Sustainability of Development Finance Institutions in Kenya
No full textPurpose: The study concentrated on Credit Risk management practices and Financial sustainability of Development Finance institutions in Kenya.
Background: Development Finance Institutions (DFIs) are essential for funding high-priority economic sectors in Kenya, yet they face a severe financial sustainability crisis. This challenge is characterized by alarmingly high non-performing loan (NPL) ratios, often exceeding 30%, which points to significant deficiencies in credit risk management. While the importance of credit risk management is acknowledged, a specific gap exists in empirically understanding how foundational, qualitative lending practices specifically the assessment of a borrower's character and the evaluation of collateral contribute to mitigating this NPL crisis within the unique Kenyan DFI context. This study’s primary objective was to determine the specific effect of borrowers' character, borrowers' collateral, loan monitoring and loan recovery on the financial sustainability of Development Finance Institutions in Kenya.
Methodology/Design: The study adopted an explanatory research design, collecting primary data through structured questionnaires from a stratified random sample of 150 credit management personnel at the Agricultural Finance Corporation (AFC), Kenya Industrial Estates (KIE), and Kenya Development Corporation (KDC). The data was subsequently analyzed using descriptive statistics, Pearson correlation, and Ordinary Least Squares (OLS) multiple regression to test the hypotheses.
Findings: The results demonstrated strong, positive, and statistically significant relationships. The OLS regression model was highly significant (F=160.00, p<0.05) and explained 81.5% of the variance in financial sustainability (R²=0.815). Both borrowers' character (Beta=0.18, p<0.05) and borrowers' collateral (Beta=0.12, p<0.05) emerged as statistically significant positive predictors of financial sustainability, leading to the rejection of both null hypotheses. The study concludes that rigorous assessment of borrower character and effective collateral evaluation are not merely procedural but are critical, quantifiable, and indispensable components of risk management that directly impact DFI financial health. The findings suggest that the high NPLs plaguing Kenyan DFIs are, in part, a failure to effectively execute these fundamental assessments. Therefore, it is recommended that DFIs enhance qualitative character assessment capabilities and strengthen collateral management processes to ensure long-term viability.
Implication/Value: This research provides critical insights for several key stakeholders. For the Development Finance Institutions (DFIs) themselves, this study offers empirical evidence on the effectiveness of their core risk assessment techniques. By highlighting the specific impact of character and collateral assessment, it provides a basis for refining these practices to reduce NPLs and enhance long-term financial health. For policymakers and the Kenyan government, the findings can inform the development of more effective regulatory frameworks governing DFI operations, ensuring these state-backed institutions can sustainably fulfill their economic development mandate. Finally, this research contributes to the academic literature by filling a gap, as most studies on credit risk in Kenya have focused on commercial banks, leaving the unique DFI sector largely under-examined
Using LLM-Generated Data to Create a Roman Urdu Scam Call Detector
No full textPurpose: Scam calls are spreading at an alarming pace where it is estimated that the world will lose more than a thousand billion dollars in 2024. Current machine-learning systems to classify scam-calls are not yet generalized: most of such systems are only monolingual detectors, with the multilingual systems based on LLM models proving impractical because of their high computational costs. In addition, due to the high rate of innovation of scam-call strategies, most of the implemented models are obsolete. This paper aims to suggest and analyze a multilingual, cheap, and easily updateable architecture to detect scam-calls with the help of LLM-generated synthetic data.Design/Methodology/Approach: The paper presents a model that was trained purely on scam and non-scam conversations of the multilingual nature as generated by the LLM. Evaluation was done using a small human-written data of actual scam and non- scam call transcripts. The method focuses on scalability, linguistic flexibility, and speedy re-generation of data with the help of synthetic generation.Findings: The experimental results indicate that an experimental model that has been trained on synthetic data can transfer to actual scam-call data. The model, when tested on the human-written data, obtained an average score of more than 90 percent accuracy, and F1-score, proving the viability of synthetic multilingual training data, which can be used to detect scam-calls.Implications/Originality/Value: The study represents a solution to addressing the practical constraints of conventional scam-call detection systems which have linguistic and adaptability limitations. The suggested framework, based on the data produced by LLM, can provide multilingual coverage, help minimize computational costs, and update regularly, with minimal costs, thus being not only operationally viable but also able to adapt to changing scam-call tactics
Assessment of Knowledge Regarding Prevention of Catheter Associated Urinary Tract Infection Among Nurses
No full textBackground: This research was carried out to assess the knowledge of nurses on the prevention of catheter-associated urinary tract infection (CAUTI). The cross-sectional research design was descriptive in nature and was aimed at assessing the knowledge level of the nurses working at Jinnah Hospital Lahore. The survey questionnaire was an adopted, modified, and translated 15-item questionnaire, used to gather data on 114 nurses.
Materials and methods: The study population included nurses who had at least two years of experience and who were willing to participate. The majority of respondents were female (71.9%), most were aged 26–30 years (57.0%), and 57.9% held a diploma qualification, while 48.2% had six to ten years of work experience. The analysis shows that participants’ correct responses ranged from 45.6% to 77.2%, indicating that nurses had fair to moderate knowledge regarding CAUTI prevention.
Results: The highest proportion of correct response (77.2%) was recorded for the statement “bladder irrigation/washout using antiseptic/antimicrobial agents reduces risk of CAUTI.” However, the least correct response (45.6%) was about day before clamping if drain op and clamp-off indicated after removal of a catheter. Nurses had moderate knowledge on the significance of the use of silicone catheters for long-term use, hand hygiene and antiseptic cleansing prior to catheter insertion, and continuous irrigation when obstruction was expected. Nevertheless, misperceptions persisted with respect to urine specimen collection, catheter removal processes and antimicrobial prophylaxis.
Conclusion: Overall, the study demonstrates that nurses possess a reasonable but improvable level of knowledge, highlighting the need for continued education and training to strengthen infection prevention practices in clinical settings
Individual Cultural Values and Brand Awareness: A Gender Perspective in Higher Education Sector of Pakistan
No full textPurpose: The research investigates the influence of individual cultural values on brand (university) awareness. The first objective of research is to find the impact of individual cultural values like collectivism, long term orientation, masculinity, power distance, and uncertainty avoidance on university awareness. The second objective was to find out the role of gender in these relationships.
Methodology: The research uses quantitative research methodology. The population has been all the students enrolled in all the universities of Pakistan. Probability based stratified sampling technique used. Questionnaire based survey conducted among seventeen universities of Islamabad Pakistan. Data collected from 1001 students out of which 842 respondents considered for data analysis. Reliability of measurement model verified through Cronbach’s alpha and composite reliability. The validity of measurement model verified through outer loadings, cross loadings and average variance extracted. Smart PLS 4 software and bootstrapping technique used to analyze the data.
Findings: The results reveal that collectivism, long term orientation, masculinity, and uncertainty avoidance except power distance impact university awareness of students. The results also show that gender plays an important role in these intricate relationships with varying results. Finally, the research shows that long term orientation found to be the most important and the strongest individual cultural value affecting university awareness among male students. While uncertainty avoidance found to be the strongest individual cultural value affecting university awareness among female students
Macroeconomic Growth, Challenges and Human Development: A Long Run Analysis for Pakistan
No full textPurpose: This study investigates the interrelationship between macroeconomic determinants and the Human Development Index (HDI) in Pakistan, with the objective of understanding both short- and long-term dynamics to guide development policy.
Methodology: The study employs yearly time-series data from the World Development Indicators covering 1990–2021. The Auto Regressive Distributed Lag (ARDL) bounds testing approach is applied to capture cointegration among variables with different levels of stationarity, I(0) and I(1). Diagnostic tests are conducted to ensure the robustness and validity of the model.
Findings: The results reveal a significant long-run relationship between HDI and macroeconomic indicators. GDP per capita positively influences human development, highlighting the importance of economic expansion. Inflation, when moderate, shows a modest but beneficial long-term effect through improved wages, demand, and fiscal outcomes. Conversely, poverty, unemployment, and real effective exchange rate exert negative effects on HDI, with exchange rate volatility undermining household welfare and competitiveness. Short-term results indicate strong effects of GDP and poverty, while inflation and unemployment exert weaker influences.
Practical Implications: The findings suggest that economic growth alone is insufficient to ensure sustainable human development. Policymakers in Pakistan must adopt comprehensive strategies to promote inclusive growth, reduce poverty, stabilize the exchange rate, generate employment, and invest in education, health, and social protection systems to enhance human welfare.
Originality/Value: This study provides novel evidence on the dynamic interplay between macroeconomic indicators and HDI in Pakistan using the ARDL approach. By combining both short- and long-term perspectives, it contributes to the literature on human development and offers policy-relevant insights for achieving inclusive and sustainable development in emerging economies
Effect of Board Accountability on Quality of Financial Disclosure by Commercial and Service Companies in Kenya
No full textPurpose: To determine the effect of board accountability on quality of financial disclosure by Commercial and Service Companies in Kenya
Design/Methodology/Approach: The study adopted descriptive and correlational research design. The target population was commercial and service companies’ departments in charge of financial statements making thus accounting and finance giving 145 stakeholders of which sample size was 106 utilized. The stratified and basic random sampling techniques were employed. Closed-ended questions were employed for primary data collection. A pilot research was executed at Nairobi Business Ventures Ltd. The researcher employed Cronbach’s Alpha to assess reliability at a threshold of 0.7. Establish validation through the application of multiple factor analyses, employing variable rotation, and excluding variables with a factor loading below 0.4. Descriptive statistics, including frequencies, percentages, measures of central tendency and dispersion, as well as inferential statistics such as regression and Pearson’s correlation analysis, were calculated using SPSS version 23. Data was presented as tables.
Findings: There was a positive significant influence of board accountability on financial disclosure among Commercial and Service Companies in Kenya.
Implications/Originality/Value: The study concludes that board accountability is a viable measure in ensuring quality of financial disclosure. The study recommendations that Commercial and Service Companies should formulate feasible board accountability policies that guides board on financial disclosure
Organizational Inclusivity Commitment and Performance of Employees in County Government of Vihiga
No full textPurpose: To establish the influence of organizational inclusivity commitment on employee performance in county government of Vihiga
Approach: Applied descriptive design. A target of 1734 workers at Vihiga County Government.
Findings: Inclusivity commitment had a resultant significant role on employee Performance (p=0.000). Basically inclusivity commitment enables performance within the county.
Implications: The study concluded that organizational inclusivity commitment had a strong correlation with performance. Therefore retention, satisfaction and engagement of employees and therefore Vihiga County governments should retain committed workforces, satisfy employees through promotions where applicable and later engage employees for better output
Effect of Technical Competencies on Trainers’ Performance in Tvet Institutions in Kakamega County, Kenya
No full textPurpose: To examine the effect of technical competencies on trainers’ performance in TVET institutions in Kakamega County, Kenya.
Design/Methodology/Approach: Trainers and human resource officers in 10 public TVET Institutions within Kakamega County were the target population of the study. Therefore 262 respondents were identified as a sample of a target population of 693 respondents by the use of Yamane formula. They employed simple random sampling and purposive sampling method. This was done as a pilot study within Kisiwa Technical in Bungoma County. The research instrument used in the study also had content and construct validity, which was done by assessing by university supervisors and content validity index. Cronbach Alpha formula was used to determine the reliability of the research instrument where a score of 0.7 was used as a benchmark. Data were obtained by means of questionnaires and interview schedules. Thematic analysis was employed in the analysis of qualitative data but quantitative data was analyzed with SPSS version 19 with descriptive and inferential statistics methods.
Findings: The findings of the study indicated a positive significance effect between technical competencies and trainers’ performance (R=0.672, P=0.000)
Implications/Originality/Value: Therefore, there was adequate evident to reject the null hypothesis that posits: technical competencies have no significant effect on trainers’ performance in TVET institutions in Kakamega County, Kenya