Often, data in multi-criteria decision making (MCDM) problems are imprecise and changeable. Therefore, an important step in many applications of MCDM is to perform a sensitivity analysis on the input data. This paper presents a methodology for performing a sensitivity analysis on the weights of the decision criteria and the performance values of the alternatives expressed in terms of the decision criteria. The proposed methodology is demonstrated on three widely used decision methods.These methods are the weighted sum model (WSM), the weighted product model (WM), and the analytic hierarchy process (AHP). This paper formalizes a number of important issues on sensitivity analysis and derives some critical theoretical results. Also, a number of illustrative examples and computational experiments further illustrate the application of the proposed methodology.

The topic of residents' attitudes toward tourism development has been analyzed by many authors, but there have been few studies that have included: (1) the impacts resulting from tourism perceived by residents of a particular region in a very early stage of tourism development, where, consequently, this industry is not yet economically important; (2) the relationship between the impacts of tourism perceived by residents and their degree of satisfaction with their community; and (3) a specific tourism segment, such as industrial tourism. The article presented here addresses these gaps in the literature, and focuses attention on the attitudes of the residents of Minas de Riotinto—a locality of the Spanish province of Huelva, traditionally involved in mining activity, which is now in decline and in the very initial phase of tourism development—toward greater development of tourism in their municipality, and on the factors that may determine and explain those attitudes.

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Over time, the acronym DMO has evolved from a meaning centered on marketing (i.e. Destination Marketing Organization) to a meaning centered on management (i.e. Destination Management Organization). Expanding the role of DMOs to one of management implies a greater need to engage stakeholders both within the destination and external to the destination. We assert that this places the DMO in a fundamentally unique position of being a boundary spanner between the internal destination environment and the external competitive environment. This boundary-spanning role requires higher capabilities in knowledge management. The successful DMO of the future will be an intelligent agent of the destination that is able to identify, engage and learn from disparate stakeholders both within and outside the destination. It must acquire, filter, analyze and prioritize data and information from various sources to create knowledge that can be used to fulfill its role in destination management. Our paper is conceptual in nature, advocating an organizing framework to help understand the DMO's role as an intelligent agent that acts as a boundary spanner between the destination and the external competitive environment generating and disseminating knowledge. Outside the destination, the DMO must gain knowledge about the competitive environment, opportunities and threats, and trends that will change the future competitive landscape. Within the destination, the DMO must use this knowledge to strategically assess the strengths and weaknesses of the destination, align the resources of stakeholders and develop adequate competencies to formulate a strategy that is both competitive and sustainable. We conclude with a set of prescriptions for destination managers seeking to create an intelligent DMO that maximizes their knowledge management capabilities.

In this study several extrinsic and intrinsic variables, from different theoretical approaches, have been integrated with the object of building an explanatory model for residents' attitude toward tourism development. This model is applied to a destination not yet overcrowded but with a high, and increasing, seasonality. Its most notable contribution is in its findings regarding the influence of seasonality on the residents' attitudes and in the factors impacting on it. These findings show that, in the low season, the effects of tourism, and tourists themselves, are perceived more favorably, leading to a more positive attitude toward further tourism development. Two hypotheses in the proposed model reveal a disparate seasonal behavior: only in the high season does the perception of the level of tourism development determine the net perception of the effects of tourism, and residents' community attachment exerts a direct and negative influence on their attitude toward tourism. Keywords seasonality, theory of social exchange, community attachment approach, residents' attitude, cycle of tourism development