Performance Analysis of Small Hotels in Tanzania

By Sharma, Amit; Sneed, Jeannie | Journal of Services Research, February 2008 | Go to article overview
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Performance Analysis of Small Hotels in Tanzania

Sharma, Amit, Sneed, Jeannie, Journal of Services Research

The purpose of this research was to analyze performance of small hotels in three major cities in Tanzania - Dar es Salaam, Arusha, and Mwanza - using unit-level financial data. Results showed that small hotel efficiency in these three cities is being impacted by scale and location effects, and an inefficient use of labour input. Continued focus on increasing capacity utilization and allocating resources to develop human resources are the challenges facing industry practitioners and government policy makers. This study contributed to literature through a comparative spatial analysis of small hotels' performance using novel data collection methods.


Tanzania is amongst the few African nations allocating resources to develop entrepreneurial activity, especially in hospitality industry. Amongst the primary source of this entrepreneurial activity are small hotels, restaurants, tour operators, and travel agencies. A recent study showed that small hotels have the potential to contribute significantly to Tanzania's economic development (Sharma, 2006). Government officials in Tanzania are aware of these opportunities and are attempting to develop a conducive environment so that these businesses can be successful. Recent descriptive studies also have shown that operating efficiencies in Tanzania's small hotels may not be at their optimum levels (Sharma & Upneja, 2005). In view of these recent industry developments and previous studies, this paper is not only timely but fills a critical gap of spatially evaluating performance in the small hotel sector. It goes further to compare these efficiencies in the three largest cities in Tanzania. The purpose of this study was to provide a comparative analysis that would lead to suggestions for industry action and policy development.


Evidence shows that small businesses are an important source of economic development and an important link to entrepreneurial activity, innovation, and job creation (Acs, 1992; Audretsch, 1995; Thurik & Wennekers, 2001). Studies also show that such businesses contribute to economic progress in the number of firms and their diversity (Cohen & Klepper, 1992), and provide a shift from a managed to an ownership economy (Audretsch & Thurik, 2001). Many other consequences of small businesses have been theorized (Schmitz, 1989) yet few have been empirically observed like lower orientation towards exports; higher demand for capital, consultancy, and related services; and more variety of supply of products and services (Acs, 1992). Studies also have shown that there is a global shift of industry structures tending towards an increased role of small businesses (Carree,, 2001). However, this shift is heterogeneous and highly dependent on country-specific factors. In general, researchers believe that countries that are lagging in small business activity (and therefore in entrepreneurship) will pay a penalty through lower economic growth (Thurik & Wennekers, 2001).

Among other factors (like entrepreneurship activity, innovation, etc.) economic growth from small businesses can be derived from their linkages with the rest of the economy (Sharma, 2006). For instance, small hotels may tend to buy inputs locally due to their inability to take advantage of economies of scale while importing across international borders. Therefore, input sourcing patterns of small business could provide information regarding the types of producer inputs that have local demand. This could be valuable information for policy makers, especially when local demand is from a group or cluster of small businesses.

Production and profit efficiency analysis literature, using nonparametric techniques such as Data Envelopment Analysis (DEA), has recently become popular amongst researchers (Cooper,, 2004). While there are certain limitations to the use of the DEA technique, especially as the results are sample specific, it still provides a powerful tool to analyze small sample data.

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