Accounting Information Systems and Performance of Manufacturing Companies in Rwanda. Case of CIMERWA Plc
DOI:
https://doi.org/10.47604/ijfa.3073Keywords:
Accounting Information Systems, Accuracy, Reliability, Performance, SecurityAbstract
Purpose: The general objective of this study was to assess the effect of Accounting Information Systems (AIS) on the performance of manufacturing companies in Rwanda, focusing on a case study of CIMERWA Plc. Specifically, the study assessed the effect of Accounting Information Systems security on the performance of CIMERWA Plc, examined the effect of Accounting Information Systems accuracy on the performance of CIMERWA Plc and analysed the effect of Accounting Information Systems reliability on the performance of CIMERWA Plc.
Methodology: The study was descriptive as well as correlational. A population of 157 from various departments within CIMERWA Plc. A sample size of 113 was determined by the researcher using Slovin's formula. Every member of the population has an equal chance of getting chosen when a simple random sampling is used. Questionnaire and interview guide all played a role in the data collection process. Within the scope of the research, SPSS 25 was used.
Findings: The results indicate coefficient for AIS security is 0.307, suggesting that for each unit increase in AIS security, performance improves by 0.307 units, with this relationship being statistically significant. Similarly, the coefficient for AIS accuracy is 0.323, indicating that a one-unit increase in AIS accuracy corresponds to a 0.323 increase in performance, which is also statistically significant. Additionally, the coefficient for AIS reliability is 0.348, signifying those improvements in AIS reliability enhance performance by 0.348 units, with a statistically significant impact.
Unique Contribution to Theory, Practice and Policy: The study recommends that CIMERWA PLC enhance AIS security through multi-factor authentication, employee training, and advanced technologies; improve AIS accuracy via audits, automated validation, and staff training; and strengthen AIS reliability through regular updates, user support systems, and feedback mechanisms to ensure seamless operations and optimal data management.
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