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Debates about the value of pro-poor tourism indicated a need to revisit the links between the dynamics of tourism and hospitality enterprises and community poverty in rural South African towns. The numbers of tourism and hospitality enterprises in these towns are related to population numbers by a power law with a sub-linear exponent. The residents of smaller South African towns are more dependent on the tourism and hospitality sector than are the residents of larger towns. Measurement of the enterprise dependency indices (EDIs) of these towns provides a valid measurement of their wealth/poverty states. Their EDIs are directly and negatively associated with the strength of their tourism and hospitality sectors. Communities in towns with more tourist and hospitality enterprises are overall wealthier, and vice versa. This finding contrasts with a previous view about tourism and poverty reduction in South Africa. Debates about the benefits of pro-poor tourism should include information about the impact of tourism on community wealth/poverty. The EDI is a simple, yet powerful, measure to provide poverty information. Expressing the number of tourism and hospitality enterprises per 1000 residents of towns enables comparisons of towns of different population sizes. Based on ideas of the ‘new geography of jobs’, it is clear that tourism is part of what is called the traded sector and results in inflows of external money into local economies. Tourism is a driver of prosperity and a reducer of poverty in South African towns.
Biosphere reserves face the challenge of sustainable development. They have to foster economic development that is ecologically and culturally sustainable. Paradoxically, the demographic-economic-entrepreneurial nexus of biosphere reserves has not been researched, an omission addressed here by studying the towns of the Gouritz Cluster Biosphere Reserve in South Africa. There is extensive orderliness in the above nexus and the interlinkages of many of its characteristics have been quantified. Systematic regularities, some time-independent, occur in the socioeconomic domain and between population sizes of towns and their enterprise numbers. Power-laws describe population-based scaling of a number of characteristics, indicating differences between small and large towns. Enterprise profiles have changed over time, with the tourism and hospitality services sector the biggest winner and the trade services sector the biggest loser. Productive knowledge, measured as enterprise richness, is a significant driver of the scaling of enterprise and population numbers. The wealth/poverty states of towns, measured as their enterprise dependency indices, modify the relationship between enterprise richness and population numbers. The development of plans for sustainable development without consideration of the quantitative orderliness of the demographic-economic-entrepreneurial nexus of this biosphere reserve and the factors that control it, would be dealing in ‘a strategy of hope’ rather than ‘a strategy of reality’. Achieving the latter in a system with regularities, some of which that have existed over decades, is a huge challenge. Understanding of how productive knowledge can be leveraged, should be a key component in any strategy.
Statistically significant Pareto-like log-log rank-size distributions were recorded for population and enterprise agglomeration in the towns of three different regions of South Africa, and are indicative of skewed distributions of population and enterprise numbers in regional towns. There were no distinct differences between groups of towns of regions from different parts of the country. However, the regional agglomerations differed from those of groups of towns randomly selected from a database. Regions, therefore, appear to have some uniqueness regarding such agglomerations. The identification of Zipf-like links between population and enterprise growth in regional towns still does not fully explain why some towns grow large and others stay small and there is a need to further explore these issues. The extreme skewness in population and enterprise numbers of different towns’ distributions should, however, be considered in local economic development planning and execution.
Some small towns regress whilst others grow, i.e. a 'Small Town Paradox' (STP). Differential accumulation of productive knowledge could possibly be its cause. Suggestions that small towns in the Eastern Cape (EC) Karoo, South Africa survive only as a result of a state welfare system suggest that the STP does not occur in this semi-arid region. Productive knowledge (measured as enterprise richness) and demographic shifts between 1946 and 2015 in EC Karoo towns were analysed. Whilst all populations increased, the productive knowledge of three small towns increased but that of five small towns regressed. The STP is present in the EC Karoo. The contrarian success of the three towns is apparently due to strength in two business sectors: agricultural products and services, and tourism and hospitality services. These sectors are important in generating monetary inflows into the local economies of EC Karoo towns. The successful small towns are innovatively using tourism resources available to them, including tourists on national routes, the attractions of wilderness areas and a national park, gay tourism, game farms and hunting. Productive knowledge seems to play a part but aridity not. Development plans of towns in arid and semi-arid environments could benefit from these findings.
Two concepts, (1) companies are 'living' entities and (2) 'company ecology', stimulated our hypothesis that towns are 'enterprise ecosystems'. This hypothesis cannot be tested directly. However, if it is correct, application of clustering and ordination techniques used frequently in studies of natural ecosystems, should reveal clusters of towns that are statistically significantly different (p < 0.05). A dataset of 47 towns in the Karoo, South Africa served as study material and their enterprise assemblages were profiled through the use of a simple method based on the examination of telephone directories. Clustering and ordination techniques revealed six different clusters of towns at a correlation coefficient level of 0.65 and the clusters differed significantly (p < 0.05) in some respects. The agricultural products and services, the tourism and hospitality, and the trade sectors were particularly important in defining these clusters. We concluded that enterprise ecology is a valid concept and towns are 'ecosystems' that also cluster together in larger groupings. An array of potentially important techniques and approaches for the study of business development in towns now provide support to, and intriguing questions confront, academic and practical researchers of enterprise development in towns.