This study was conducted to assess the determinants of tourists’ loyalty to Serengeti National Park (SENAPA) in Tanzania. The study involved 1,148 respondents who were international tourists visiting the park from March to December 2018. Data were collected using a structured survey questionnaire. Structural Equation Modelling (SEM) technique was used in the analysis. Findings revealed that service quality was a positive predictor of tourists’ loyalty. Accordingly, destination image and perceived value had positive effects on tourists destination loyalty. Also, satisfaction was found to have positive effect on destination loyalty. Furthermore, the findings revealed that satisfaction had a partial mediation effect on the relationship between service quality, destination image and perceived value on the one hand and destination loyalty on the other. It was concluded that provision of high-quality services increased tourists’ loyalty to the park. Similarly, tourists’ satisfaction and realization of value during their trips increased loyalty. The study calls for SENAPA management to strive to maintain high quality of services provided to tourists by introducing service provision charter that would guide the operations of different stakeholders inside the park. Also, the park’s management should make efforts that would enhance perceived value among the tourists by reviewing costs of items charged on tourists like park entry fees in view of making them competitive compared to similar parks found in Africa.

In the recent days, microcredit schemes have been proliferating in all parts

This article provides assessment of the effects of four credit characteristics including size, interest rate, repayment period and borrowing experience on business performance. The article makes use of survey data collected from 217 women microcredit clients from Arusha, Dar es Salaam and Mwanza regions in Tanzania. Bivariate correlation analysis was used to find out specific effect of each of those four credit characteristics on three business performance measures namely total sales revenue, net profit and business net worth. The combined effect of all four credit characteristics on business performance was estimated by a multiple linear regression model. The findings revealed that size of credit was positively correlated with total sales revenue and business net worth at significant level. Interest rate was negatively correlated with all three measures of business performance at significant level. It was also found out that repayment period was positively correlated with all three business performance indicators at significant level. Furthermore, the study established that borrowing experience was positively correlated with total sales revenue at significant level but not with other two indicators. The model accounted for 25% of sales revenue, 9% of net profit and 28% of business net worth.

No abstract

This article provides assessment of the effects of four credit characteristics including size, interest rate, repayment period and borrowing experience on business performance. The article makes use of survey data collected from 217 women microcredit clients from Arusha, Dar es Salaam and Mwanza regions in Tanzania. Bivariate correlation analysis was used to find out specific effect of each of those four credit characteristics on three business performance measures namely total sales revenue, net profit and business net worth. The combined effect of all four credit characteristics on business performance was estimated by a multiple linear regression model. The findings revealed that size of credit was positively correlated with total sales revenue and business net worth at significant level. Interest rate was negatively correlated with all three measures of business performance at significant level. It was also found out that repayment period was positively correlated with all three business performance indicators at significant level. Furthermore, the study established that borrowing experience was positively correlated with total sales revenue at significant level but not with other two indicators. The model accounted for 25% of sales revenue, 9% of net profit and 28% of business net worth.