{"title":"风险识别对肯尼亚税收机关税收绩效的影响","authors":"STEPHEN MAINA KARIUKI, MARK SUVA, PhD","doi":"10.61426/sjbcm.v10i4.2733","DOIUrl":null,"url":null,"abstract":"This study assessed the effect of identifying risk on performance of Kenya Revenue Authority in collection of national revenue in Kenya. The ultimate intention of the study was to benefit policy makers and academicians in the same quest. The study's time frame was from 2018 to 2022. The study was anchored on stakeholder theory. The study adopted a descriptive research method, from a population of 3906 KRA employees. A total of 294 divisional representatives were sampled using a mix of stratified, purposive and judgmental sampling. To the representatives of KRA there was a survey questionnaire structured according to the objectives of the study. The questionnaire was presented on a drop- and-pick method in order to ensure high response rate. In two steps, the data was coded and examined. In the first stage there was confirmatory factor analysis, the second stage was structural regression equation model. The imminent primary data was coded and analyzed statistically using R in lavaan programing language. Under the assumption of no linearity the data was analyzed using the structural equation model methodology to specifically identify the confirmatory factor structure followed by a measurement model in the form of multiple regression. The model was diagnosed using normality, model identification status testing, multicollinearity and model fit diagnostics of fit test. This was done by standardizing all the covariances. As part of ethical consideration the researcher created rapport with the respondents by assuring them of utmost confidentiality and presenting them with an authorization letter from NACOSTI. From the findings, risk identification had significant positive effects on KRA performance in national revenue collection. Policy recommendations from this study was that KRA can improve revenue collection performance by exploiting the potential in harmonizing the application of risk identification practices. Key Words: Revenue Collection, Risk Identification, KRA, Taxation CITATION : Kariuki, S. M., & Suva, M. (2023). Effect of identifying risk on performance of Kenya Revenue Authority in collection of tax revenue in Kenya. The Strategic Journal of Business & Change Management, 10 (4), 41 – 47. http://dx.doi.org/10.61426/sjbcm.v10i4.2733","PeriodicalId":22086,"journal":{"name":"Strategic Journal of Business & Change Management","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"EFFECT OF IDENTIFYING RISK ON PERFORMANCE OF KENYA REVENUE AUTHORITY IN COLLECTION OF TAX REVENUE IN KENYA\",\"authors\":\"STEPHEN MAINA KARIUKI, MARK SUVA, PhD\",\"doi\":\"10.61426/sjbcm.v10i4.2733\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This study assessed the effect of identifying risk on performance of Kenya Revenue Authority in collection of national revenue in Kenya. The ultimate intention of the study was to benefit policy makers and academicians in the same quest. The study's time frame was from 2018 to 2022. The study was anchored on stakeholder theory. The study adopted a descriptive research method, from a population of 3906 KRA employees. A total of 294 divisional representatives were sampled using a mix of stratified, purposive and judgmental sampling. To the representatives of KRA there was a survey questionnaire structured according to the objectives of the study. The questionnaire was presented on a drop- and-pick method in order to ensure high response rate. In two steps, the data was coded and examined. In the first stage there was confirmatory factor analysis, the second stage was structural regression equation model. The imminent primary data was coded and analyzed statistically using R in lavaan programing language. Under the assumption of no linearity the data was analyzed using the structural equation model methodology to specifically identify the confirmatory factor structure followed by a measurement model in the form of multiple regression. The model was diagnosed using normality, model identification status testing, multicollinearity and model fit diagnostics of fit test. This was done by standardizing all the covariances. As part of ethical consideration the researcher created rapport with the respondents by assuring them of utmost confidentiality and presenting them with an authorization letter from NACOSTI. From the findings, risk identification had significant positive effects on KRA performance in national revenue collection. Policy recommendations from this study was that KRA can improve revenue collection performance by exploiting the potential in harmonizing the application of risk identification practices. Key Words: Revenue Collection, Risk Identification, KRA, Taxation CITATION : Kariuki, S. M., & Suva, M. (2023). Effect of identifying risk on performance of Kenya Revenue Authority in collection of tax revenue in Kenya. 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EFFECT OF IDENTIFYING RISK ON PERFORMANCE OF KENYA REVENUE AUTHORITY IN COLLECTION OF TAX REVENUE IN KENYA
This study assessed the effect of identifying risk on performance of Kenya Revenue Authority in collection of national revenue in Kenya. The ultimate intention of the study was to benefit policy makers and academicians in the same quest. The study's time frame was from 2018 to 2022. The study was anchored on stakeholder theory. The study adopted a descriptive research method, from a population of 3906 KRA employees. A total of 294 divisional representatives were sampled using a mix of stratified, purposive and judgmental sampling. To the representatives of KRA there was a survey questionnaire structured according to the objectives of the study. The questionnaire was presented on a drop- and-pick method in order to ensure high response rate. In two steps, the data was coded and examined. In the first stage there was confirmatory factor analysis, the second stage was structural regression equation model. The imminent primary data was coded and analyzed statistically using R in lavaan programing language. Under the assumption of no linearity the data was analyzed using the structural equation model methodology to specifically identify the confirmatory factor structure followed by a measurement model in the form of multiple regression. The model was diagnosed using normality, model identification status testing, multicollinearity and model fit diagnostics of fit test. This was done by standardizing all the covariances. As part of ethical consideration the researcher created rapport with the respondents by assuring them of utmost confidentiality and presenting them with an authorization letter from NACOSTI. From the findings, risk identification had significant positive effects on KRA performance in national revenue collection. Policy recommendations from this study was that KRA can improve revenue collection performance by exploiting the potential in harmonizing the application of risk identification practices. Key Words: Revenue Collection, Risk Identification, KRA, Taxation CITATION : Kariuki, S. M., & Suva, M. (2023). Effect of identifying risk on performance of Kenya Revenue Authority in collection of tax revenue in Kenya. The Strategic Journal of Business & Change Management, 10 (4), 41 – 47. http://dx.doi.org/10.61426/sjbcm.v10i4.2733