A conjoint analysis of landholder preferences for reward-based land-management contracts in Kapingazi watershed, Eastern Mount Kenya

Unsustainable land-use decisions and agricultural practices have become the key drivers of deteriorating watershed services in developing countries. However, landholders may have little or no incentives to take these impacts into account in their decision-making process. In recent years, reward-based provision of environmental services has emerged as an important market-based incentive for motivating landholders to adopt environmentally friendly land-use changes and agricultural practices. In this regard, for instance, the Pro-Poor Rewards for Environmental Services in Africa (PRESA) project has emerged as a large network to support and facilitate reward mechanisms in Africa. However, in many African rural settings, little is known about landholder attitudes and preferences related to the alternative land-management schemes. Using locally identified sets of six key land-management attributes, this paper applies conjoint methods to evaluate landholder preferences towards alternative land-management schemes aimed at enhancing the provision of watershed services in the River Kapingazi catchment in central Kenya. Data were collected from primary sources through focus groups and a questionnaire based conjoint survey. Three conjoint models were used; a traditional conjoint ratings model, a binary logit model, and an ordered logit model. Results from the focus groups indicated that shortage of water for both domestic use and irrigation was perceived as the most acute environmental problem in the area. Deforestation, poor river bank management and agricultural practices were identified as the major causes of the problem. Results from conjoint models show that the three principal attributes influencing landholder's ratings and probability of adopting the proposed land management options were 'size of land area to be committed', 'length of contract period', and 'granting or prohibiting rights to harvest environmental products from the committed land'. Thus, these attributes should be the focal points in designing land-management contract for watershed services in the study area.     

Evaluating the management strategies of a forestland estate--the S-O-S approach

Connecting Multiple Criteria Decision Support (MCDS) methods with SWOT (Strengths, Weaknesses, Opportunities, and Threats) analysis yields analytical priorities for the factors included in SWOT analysis and makes them commensurable. In addition, decision alternatives can be evaluated with respect to each SWOT factor. In this way, SWOT analysis provides the basic frame within which to perform analyses of decision situations. MCDS methods, in turn, assist in carrying out SWOT more analytically and in elaborating the results of the analyses so that alternative strategic decisions can be prioritized also with respect to the entire SWOT. The A'WOT analysis is an example of such hybrid methods. It makes combined use of the Analytic Hierarchy Process (AHP) and SWOT. In this study, a hybrid method of the Stochastic Multicriteria Acceptability Analysis with Ordinal criteria (SMAA-O) and SWOT is developed as an elaboration of the basic ideas of A'WOT. The method is called S-O-S (SMAA-O in SWOT). SMAA-O enables the handling of ordinal preference information as well as mixed data consisting of both ordinal and cardinal information. Using SMAA-O is enough to just rank decision elements instead of giving them cardinal preference or priority ratios as required by the most commonly used MCDS methods. Using SMAA-O, in addition to analyzing what the recommended action is under certain priorities of the criteria, enables one to analyze what kind of preferences would support each action. The S-O-S approach is illustrated by a case study, where the shareholders of a forest holding owned by a private partnership prepared the SWOT analysis. Six alternative strategies for the management of their forest holding and of old cottage located on the holding were formed. After S-O-S analyses were carried out, one alternative was found to be the most recommendable. However, different importance orders of the SWOT groups would lead to different recommendations, since three of the six alternatives were efficient according to S-O-S analyses.