The effects of channel power, destination attractiveness and destination political risk events on U.S. tourism channel firms' performance: the case of tourism destinations in Africa

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This is an exploratory study that empirically examines the relationships between United States' tourism channel firms' power, African country destination's political risk events and touristic attributes and their effects on firm performance. Tourism channel firm performance is conceptualized as having five dimensions: the number of trips generated, repeat business, package tour sales, profits and new destinations. The link between these dependent variables and their relationship to channel power, destination attractiveness and political risk is the principal focus of this study.

Data for the study were collected using a structured questionnaire mailed to the population of tour operator, travel agents and other destination marketing organizations, airline and hotel companies who are members of the Africa Travel Association (N=450) between December 1995 and February, 1996. One hundred and twenty nine respondents completed the survey, yielding a response rate of 28.6%. Nonrespondents were also profiled to ensure respondent representativeness. Data were analyzed using Factor Analysis and Multiple Regression.

The results from factor analysis delineated tourism channel power into two main factor groupings - internalization power factors and technological power factors. The internalization power factors include the use of staffing, management, proprietary research and acquisition of supply firms as techniques used by U.S. tourism channel firms to dominate; while the technological factors used include expert systems, computerized communications and reservation systems. These factors explain 68.5% of the total variance.

Three main factor groupings emerged from the factor analysis of touristic attributes in African destinations: (1) Natural resource factors, which constituted climatic, geographic, beach, floral and faunal stock, scenery, landscape, vegetation and wildlife activities; (2) Cultural/Ethnic factors, constituting tribal life, ethnic customs and historic monuments; (3) Activity factors - hunting safaris, local tribal life participation and local shopping .Overall, the total variance explained by these factors amount to 51.5%.

Regarding the factor groupings for political nsk, two main factors emerged: (1) Regionalized Political Risk Events, constituting civil wars, revolution, coups d’etat, factional conflicts, border conflicts and the like; (2) Globalized Political Risk Events- high inflation rates, high external debt ratio, profit repatriation restriction, and negative world public opinion among others. These factors account for 70.8% of the total variance.

Overall, five models emerged from the multiple regression procedure, constituting each of the individual dependent variables of performance: trip generation, repeat business, package tours, profits new destinations.

The overall model for the dependent variable of percentage of trips generated was found to be statistically significant. Furthermore, this model explains 34.7% of the total variance for trips generated by United States’s tourism channel firms to Africa.

The model of the dependent variable of repeat business reveals that only 29.5% of the variance is explained by the dependent variable. Furthermore, the model is not statistically significant.

The model depicting the dependent variable of package tours and the individual independent variables explains 47.2% of the variance, and is statistically significant.

The multiple regression model for the dependent variable of number of new destinations entered in Africa constitutes the fifth model. The overall model explains 45.85% of the total variance, and is highly significant. However, of all the factors included in the model regionalized political risk factors appears to affect new destinations negatively.