| dc.description.abstract | The study was guided by the following specific objectives; to determine the influence
of technology integration on operational performance of formal manufacturing firms
in Mombasa County, to establish the influence of customer integration on operational
performance of formal manufacturing firms in Mombasa County, to determine the
influence of product integration on operational performance of formal manufacturing
firms in Mombasa County and to determine the influence of process integration on
operational performance of formal manufacturing firms in Mombasa County. The
study was anchored by the following theories; Innovation Diffusion Theory,
Stakeholder Theory, Product Life Cycle theory and Transaction Cost Economics
Theory. The target population of the study consisted of 100 general operation
managers 50 Head of Procurement Section and 100 warehouse managers in the 50
selected manufacturing firms in Mombasa County. The sample size was determined
using Yamane allocation sample formulae to obtain 152 respondents. The researcher
used questionnaires as a tool for data collection. The questionnaires contained close
ended questions that solicited respondents’ views. Data analysis involved sorting,
coding and transforming data into statistical information for the purpose of analysis
and interpretation by use of SPSS. This study used quantitative data specifically
descriptive statistics. Regression analysis was used. The findings were presented in
the form of tables and percentages. Normality testing involved examining whether
the residuals of the regression model followed a normal distribution, with normal QQ
plots revealing a close alignment between observed and expected data points,
indicating normal distribution. Additionally, the Shapiro-Wilk test confirmed
normality for all variables. Multicollinearity was assessed using variance inflation
factor (VIF), with values indicating no issues. Heteroscedasticity was checked using
Breusch-Pagan and Koenker tests, which showed no significant problems.
Autocorrelation was tested using the Durbin-Watson statistic, with results indicating
no autocorrelation. Finally, linearity was assessed through Sig. linearity and Sig.
deviation from linearity tests, confirming the presence of a linear relationship between
variables. The findings revealed that technology integration significantly enhances
operational performance by improving operational efficiency and effectiveness.
Customer integration practices were found to have a strong positive influence on
operational performance by fostering customer relationships and meeting their needs.
However, product integration had a limited influence on operational performance,
suggesting a need for organizations to realign their product strategies. Process
integration emerged as a significant determinant of operational performance,
highlighting the importance of optimizing processes and fostering collaboration
across departments. The study concluded that technology integration positively
influences operational performance for Formal Manufacturing firms in Mombasa
County. Customer integration practices were found to significantly enhance
operational performance. Process integration was identified as crucial for improving
operational efficiency and productivity by optimizing workflows and promoting
collaboration across departments. The study recommended that firms invest in
technology, prioritize customer relationships, reassess product strategies, and
streamline processes to enhance overall performance. Further research is needed to
explore the influence of supply chain integration on operational performance across
different industries and regions in Kenya | en_US |
