Influence of Organizational Strategy on Implementation of Electronic Project Monitoring Information System in Public Tertiary Institutions in Kenya
Mburugu, Kirema N.
Mulwa, Angeline Sabina
Kyalo, Dorothy Ndunge
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The principal objective of the study reported in this article was to empirically assess on the influence of organisational strategy on the implementation of Electronic Project Monitoring Information System (e-ProMIS) in Public Tertiary Institutions in Kenya. The population of the study comprised members of staff from public tertiary institutions in Kenya. A sample of 210 members of staff was selected using stratified and simple random sampling techniques. Questionnaire with both open and closedended items with Likert-type interval scale anchored on a five point scale was used to collect data. Descriptive statistics show that majority of the public tertiary institutions in Kenya applied reactor strategy (M=3.40, SD=1.13) followed by defender strategy (M=2.46, SD=0.56) and a few of them used prospector strategy (M=2.26, SD=0.68). Reactor which was the dominant strategy utilised in tertiary institutions is not a stable strategy since institutions that adopt it are not able to respond effectively to the environment. They adapt only when environmental pressures force them to do so. Results from inferential statistics show that r is equal to 0.513, indicating that organisational strategy has a moderately strong influence on implementation of e-ProMIS. The value of R squared is 0.263, indicating that organisational strategy explains 26.3% of the variation in the implementation of electronic project monitoring information system in public tertiary institutions in Kenya. The β coefficient of prospector strategy is 0.025, that of defender strategy is 0.397 and reactor strategy is 0.217. These results indicate that prospector strategy had no statistically significant influence on the implementation of e-ProMIS (β=0.025, t=0.280, p=0.780>0.05). Comparing the p values, it can be noted that the p values for defender strategy (p=0.000) and reactor strategy (p=0.003) are both statistically significant. The β values imply that one unit change in implementation of e-ProMIS is associated with 2.5% changes in prospector strategy, 39.7% changes in defender strategy and 21.7% changes in reactor strategy.