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dc.contributor.authorNderitu, Duncan Mathenge
dc.contributor.authorNjuguna, Reuben Kinyuru
dc.date.accessioned2017-09-13T06:40:15Z
dc.date.available2017-09-13T06:40:15Z
dc.date.issued2017
dc.identifier.citationInternational Journal of Sales, Retailing and Marketing Vol. 6 No. 2 2017en_US
dc.identifier.urihttp://ir-library.ku.ac.ke/handle/123456789/17793
dc.descriptionResearch paperen_US
dc.description.abstractThe advent of liberalization in October 1994 in Kenya’s petroleum sub-sector has witnessed unprecedented influx of players into this sector. This has led to stiff competition, as the fight for customers seems to be a never-ending war. The increased number of firms in this sector has given the consumers a wide variety of choices from which to make a choice. This coupled with changes in socio-cultural trends such as education and the increased importance of time has forced oil companies to be more sensitive and responsive as customers are now demanding value for their money. This study therefore sought to determine the influence of retail network expansion on the competitive advantage of oil marketing firms in Kenya. This study used a descriptive research design. The target population of this study was all the 110 staff working at the headquarters of Vivo Energy. Stratified random sampling technique was used to select 50% of the target population. The sample size was 55 staff. This study used both primary and secondary data. Secondary data was collected from the financial statements and the strategic plan of Vivo energy. Primary data was collected by use of semi-structured questionnaires and key informant interview guide. Before the main data collection a pilot test was conducted to test the validity and reliability of the research instrument. Quantitative data was analyzed by use of both descriptive and inferential statistics by use of statistical package for social sciences (SPSS version 22). Descriptive statistics included frequency distribution, percentages, measures of central tendencies (mean) and measures of dispersion (standard deviation). The data was then presented in tables and graphs. Inferential statistics such as correlation analysis and multivariate regression analysis were used to establish whether there is a relationship between the dependent and the independent variables. The study applied a 95% confidence level. A 95% confidence interval indicates a significance level of 0.05. This implies that for an independent variable to have a significant influence on the dependent variable, the p-value ought to be below the significance level (0.05). The study found that retail network expansion had a positive and significant influence on the competitive advantage of Vivo energy. The study recommends that Vivo Energy should seek to increase its branch network even more. In addition, they should focus more on areas lacking fuel stations, upcoming residential areas and developing cities. To improve its distribution network, Vivo Energy needs to adopt the franchising strategy as it requires little or no resources. Also, since the company has beenen_US
dc.language.isoenen_US
dc.subjectCompetitive advantageen_US
dc.subjectRetail network expansionen_US
dc.subjectOil Marketing Firmsen_US
dc.subjectDistribution Strategiesen_US
dc.titleThe influence of retail network expansion on the competitive advantage of oil marketing firms in Kenya: case of vivo energyen_US
dc.typeArticleen_US


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