Abstract
Over time, firms have adopted various measures to enable them to improve their performance; one such measure is the adoption of technology. Shipping lines’ performance, just like any other organisation’s performance, is highly pegged on proper implementation and use of the right technology. The need for technology adoption arises from the fact that Kenya’s shipping sector has been characterised by low logistics efficiency due to high transportation costs, delayed delivery, clearance at the port, the influx of substandard goods into the country as well as poor tracking and tracing. If well utilised, the sensor technology can help solve these problems. The objective of this study, therefore, was to assess the relationship between sensor technology and the performance of shipping lines in Kenya and the moderating effect of international maritime regulations. The main theory of the study was the technology acceptance model supported by the task technology fit theory, institutional theory and theory of the firm. The positivist research philosophy and explanatory survey research design were utilised in this study. The target population was all the 2835 respondents who are logistics, IT, sales and marketing and finance staff of the 53 shipping lines listed in Kenya business directory 2021. The study sample size was 438 respondents who were staff from four departments and was determined by the use of the Yamane formula. A random stratified sampling design was utilised to arrive at specific respondents. Quantitative data were collected using structured questionnaires administered to the respondents. A pilot study was conducted in Mombasa from six shipping lines using 10% of the sample size; 50 questionnaires, but only 44 were filled and returned. The questionnaire was tested for both validity and reliability. Reliability was tested using Cronbach's alpha index at 0.7, while the use of factor analysis ascertained validity. Quantitative data was appropriately coded and entered into SPSS version 20 for analysis to generate descriptive statistics (minimum, maximum, mean, standard deviation kurtosis and Skewness) and inferential statistics (Pearson correlation coefficient, multiple linear regression and hierarchical regression model), which was then be presented in frequency tables and graphs. Results showed that there was a significant and positive relationship between sensor technology and the performance of shipping lines in Kenya. Also, international maritime regulations had a statistically significant moderating effect on the relationship between sensor technology and the performance of shipping lines in Kenya. It was concluded that shipping lines in Kenya utilised localisation technology to help in locating cargo during transportation, forecasting lead time accurately, mapping the route, eliminating delay, checking route deviation and tracking vessels. The study recommends that in order to enhance the shipping line's performance through efficient operations, the managers of these companies need to adopt and make use of the sensor technology.
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