EL MERCADO LABORAL ECUATORIANO

The expert participants working in governmental and non-governmental organisations at the district and national level had various experiences of using AI in tourism planning. They expressed their experience with various examples of tourism projects implemented in different parts of Nepal.

Dambur is affiliated with an NGO working for sustainable tourism, and has considerable experience in using AI in conservation as well as in tourism. He worked as a ranger in a national park, and also worked in the TRPAP project in the Rasuwa district. He explained: “We used AI as a planning tool for pro-poor tourism planning through local authorities – DDCs in Nepal. I was actively involved while using this tool in nine VDCs in Rasuwa and developed 33 settlement based tourism plans.”

Kamal, a senior programme manager, working in an international NGO for more than two decades, is experienced in using AI in tourism planning and development. He first used it in tourism in 1995, while implementing tourism programmes in five VDCs of the Makalu Barun area in the Sankhuwasava district in the eastern part of Nepal. The programme followed 4-D models (Discovery, Dream, Design and Destiny) of the AI process in programme identification, development, planning and implementation, as referred in Cooperrider et al. (2008). Kamal explained the context in the society, and shared his experience on how the process was used in the community:

[Nepalese] society has a trend of emphasising problems rather than what positive things we do have, but AI focuses on positive aspects. When we worked in a community, local people identified the positive aspects of their village such as cultural and natural resources for tourism at the discovery phase. Then in the dream phase they envisioned the future followed by the design phase of planning.

Since all dreams listed by the community cannot be fulfilled within a short period of time, Kamal explained that the dreams need to be categorised on the basis of priority for local people by using various ranking tools. As described earlier in section 3.2.2.1, the AI design phase selects activities to fulfil the dreams, prioritise activities, and prepare a plan. Then the destiny phase focuses on implementation of the plan, with personal commitment and contribution from the stakeholders. Kamal elaborated:

After completing the design phase, participants at the meeting took immediate action which was considered to be helpful towards fulfilling their dream. For example, if a person contributes 10 minutes, then 60 people in the meeting can do a lot. With that esteem, a toilet can be constructed within an hour, or a half kilometre trail can be improved for tourists. This type of action is taken in order to support and reflect their discovery and dream.

The AI approach emphasises the role of local people in the planning and implementation of the programmes, develop ownership, and enable their capacities for sustainable

development (Chapagain, 2009; Cooperrider, et al., 2008). The expert participants, who were involved in the TRPAP project, suggested that the AI approach places local people in the centre of the process of planning and implementing the programmes. For example,

consistent with the perspectives of local residents, Mingphuti (who worked in a TRPAP project in the Junbesi region) said:

We organised APPA workshops at the village level to identify human, natural and cultural resources available within the village. After identification of those resources, local people developed a plan to promote and preserve those resources. We looked to the local people as centre for information, that’s why the planning was effective as compared to VDC or DDC.

Karma worked for a TRPAP project in Junbesi, and is currently working for one of the local NGOs in Solukhumbu. He explained that “local people identified many issues during the planning exercises which were essential for their livelihood as well as village

development.” The project categorised those issues under the theme of “pro-poor, pro- women, pro-environment and pro-community”. Karma added that “all issues were not possible to include in the plan, so priorities were given to more feasible activities for the project.” This indicates that the process was used to identify different activities for the project, where priorities were given to activities that were of interest and feasible to the project.

Most expert participants involved in tourism planning process using AI were consultants for different national and international organisations. During this fieldwork, it was revealed that the experts had no further role after the planning exercises, and in most cases, they were not aware of the progress of the project they designed. For example, Tharke (a consultant involved in various tourism planning exercises with different organisations) indicated, “I was involved in various planning exercises, but I am not sure whether those programmes were successfully implemented or not.” This statement shows that the programmes developed by an AI consultant may not be implemented effectively due to lack of follow-up assessment and knowledge on AI process among stakeholders.

Ongel works for NTB and was closely involved in a TRPAP project. He believes that the APPA process is helpful in identifying local strengths and resources. But, he said:

Sometimes all the tourism products identified by local people are not realistic. For example, local people might think the small lake in the village which is sacred to

them could be developed as important tourism product, but tourists may not find it as important and interesting as the villagers think it is.

The above argument challenges the ‘building on strength’ concept of AI that identifies the strengths and resources of community for development, as mentioned in Chapagain (2004).

In summary, the general opinion of the expert participants indicated that AI can be a useful approach in planning, because it emphasises participation by the local people and considers them as the main source of information. The 4-D model is a planning cycle in AI, where the locals are involved in all phases: Discovery Dream, Design and Destiny. The expert participants also claimed that the AI process develops ownership of the programme among local people, and also builds on their capacity. Many expert participants were consultants who worked only for a short term with the project, and they were not aware of the outcome of the project they designed. There was also a lack of follow-up assessments on the projects. In this case, the project designed by AI consultants may not be able to achieve the goal if the implementing body is not familiar with AI concept.

As mentioned in section 3.2.2.3, there are differences between AI and other approaches. The following section presents the expert participants’ views on what distinguishes AI from other planning approaches.