RELATIONSHIP BETWEEN ECONOMIC BENEFITS
Table 4.1: SWOT Analysis on the roles of stakeholders in biodiversity conservation implementation in Koussoukpa Zogbodomey Benin
According to table 4.1 organizations that participated in the biodiversity conservation measure ‘tourism’ implemented in Koussoukpa Zogbodomey Benin were national and state level owned while local/community level owned organisation were absent. This may have been caused by lack of knowledge on the importance of community members’ involvement. Also it could have been due to the community members’ perception of biodiversity conservation as a burden to agriculture. This absence of community level owned organizations is in contrast to Wilkinson’s (1991) interactional theory proposition (Section 2.1.4) which highlighted the importance of community relations in tourism implementation; and portrays Heyman and Stronza’s (2011) revelation that conservation projects lack local community members’ participation.Although BECG (2010) cited that the consent of the community members were obtained before implementation of tourism in Koussoukpa Zogbodomey Benin, it may not have been enough as their involvement through locally owned organizations, which likely shows their equal right to decision making in the project, were omitted. Also the community members may face the challenge of embracing the change of deviating from continuous use of biodiversity to conservation of biodiversity; which may in turn lead to their opposing the actions of the stakeholders in the national and state level organization towards conservation of biodiversity. As stated by Brennan, Flint and Luloff (2009) formation of community organizations aids addressing of the issues arising from changing conditions; changing conditions in this case are changes brought about by tourism on the community. Matarrita-Cascante (2010) also outlined that for tourism that will lead to development, practise should focus on strategies to ensure maintenance of economic growth, meet the needs of tourists, protect the biodiversity as well as cater for the requirements of the community members. Further widespread participation, communion and tolerance in communities are reflected in formation of formal and informal association working towards the community well-being (Matarrita-Cascante 2010). In addition sub sectors or units of the participating organizations were hardly mentioned, and for adequate management of project such as implementation of tourism in a community,administrative organizations are needed for effective management.Also local community involvement may lead to job creation in the community, as outlined by Serrano-Bernardo et al. (2009) tourism is a strong employment generator.
Figure 4.1: Scenario A’s NPV for 5, 10 and 15 years at DF of 3%, 8% and 12%.
Figure 4.1 illustrates that in scenario A, negative NPVs were obtained at the 5th year for the Discount Factors (DF) applied. However at the 10th and 15th year, NPVs were positive. Positive NPV’s observed after the 5th year may be due to increased performance of the ecotourism implementation as the number of years increased, which could have led to rise in the number of tourists, payment for tourism activities, recovery of the initial cash outlay and increased receipt of profit from the ecotourism activity. However at 12% DF, NPV was still negative after the 5th year up to about the 6/7th year, which is due to the higher discount applied unlike in 3% and 8%. Therefore in accordance with Brown and Kwansa’s (1999) rule which states that a project is favourable and acceptable when the NPV is greater than 1, the result implies that implementation of ecotourism in Koussoukpa Zogbodomey Benin is acceptable and favourable if executed and maintained to the 10th or 15th year.
Figure 4.2 outlines that in scenario B, NPVs were all positive after the 5th year at the three Discount Factors (3%, 8% and 12%). However, in this scenario ‘B’ a faster growth in performance and early recovery of investment may have eliminated the negative NPV at 12% DF after the 5thyear unlike occurred in Scenario A. This is because despite the percentage discount at 12%, the accelerated performance produced positive NPVs. Positive NPVs observed slightly before the 5th year at DF of 3% and 8%may also be attributed to the accelerated performance. Also, although not accounted for in this study economic and social issue surrounding ecotourism activity may have influenced its performance, as stated by Currie, Milton and Steencamp (2009) consideration of ecological, social and economic factors are needed for project success. Therefore following the deductions and in line with Brown and Kwansa (1999) ecotourism in Koussoukpa Zogbodomey Benin exhibiting the estimated growth rate applied in scenario B is favourable and acceptable.
Figure 4.2: Scenario B’s NPV for 5, 10 and 15 years at DF of 3%, 8% and 12%.
Figure 4.3: Scenario C’s NPV for 5, 10 and 15 years at DF of 3%, 8% and 12%.
Figure 4.3 illustrates that in scenario C, at a DF of 3% positive NPVs’ were obtained for the 5th, 10th to the 15th year; although at 8% and 12% DF NPV was negative at the 5th year but positive at the 10th and 15th year. The lowest discount factor 3% was positive for all the years because unlike 8% and 12% a lower amount were discounted from the cash outlay. Notwithstanding scenario C differed from A and B due to the fact that these positive NPVs at 3% DF obtained all year, were not experienced in scenario A and B. This high performance in scenario C may be due to similar factors as identified in scenario A and B which includes economic, ecological and social factors, further still, management in this scenario may have displayed optimum conduct and applied excellent ecotourism practises. As outlined by Aldebert, Dang and Longhi (2011) cooperation of diverse actors in tourism, application of innovative ideas and improved form of practises in tourism enhances tourism flow and performance. Therefore the result implies that performance of ecotourism implementation according to scenario C is acceptable and favourable.
According to figure 4.4, scenario A, B and C depicts a Profitability Index (PI) of less than 1 over 5 years but a greater than 1 PI over 10 and 15 years. Although PI of scenario C, over 10 and 15 years were higher when compared to scenario A and B; and the PI of scenario B over 10 and 15 years appeared higher than scenario A. As illustrated in appendix 2, 3 and 4, scenario C had a higher growth rate in the number of tourists when compared to B and A, and scenario B a higher growth rate than A. The difference in the growth rate of tourists may have influenced the difference observed in the profitability index among the three scenarios. Thissuggested influencing factor ‘i.e. increase in the number of tourists’ is in accordance with Mattarita-Cascante (2010) who implied that changes in the number of tourist outcome is one of the factors that lead to tourism success.
Figure 4.4: Profitability Index (PI) of ecotourism in the three different scenarios over 5, 10 and 15 years.
Ecotourism practise is viable in Koussoukpa Zogbodomey Benin according to this study, which shows that after the 5th year in scenario B, C and, about 7th year or up to 10th year in scenario A, positive NPVs were attained; in addition PI obtained also shows that over 10 years and 15 years PI was greater than 1. These results implies that tourism projects grow and the growth continues over years, affirmingDay-Rubeinstein and Frivold (2001) proposition that tourism benefits build up and supporting part of Mattarita-Cascante’s (2010) logic on tourism led development which explained that tourism grows continuously with time and may eventually leads to development. However, this growth depends on some factors such as adopted practises and performance of operations implemented and since the ecotourism initiative implemented in Koussoukpa Zogbodomey Benin wasbased on lessons and practises from thriving locations, the scenarios presented in this research may occur in Koussoukpa Zogbodomey Benin. This discovery is in line with the Song, Dwyer and ZhengCao (2012) Structure Conduct Performance (SCP) paradigm theory which signifies that the structure, content and strategy of ecotourism practise determines its performance.
Although the deductions from this study have portrayed that, economic benefits will most likely accrue from ecotourism implementation in Koussoukpa Zogbodomey Benin over years, the perception of the stakeholders, specifically the community members ((users of biodiversity), see Section 2.3) over years, have not been considered. There is the potential that the community members may not be patient enough for the benefits of tourism in Koussoukpa Zogbodomey Benin to accrue and they may be drawn back to their traditional practises such as Poaching and agriculture. As pointed out by BECG (2010) and Tanaka et al. (2013) 80% of the people in Koussoukpa Zogbodomey depended on agricultural practises for their livelihood. Meanwhile FAO (2013) have criticized agricultural practises, stating that despite agricultural practises, Benin still remains in poverty. Despite this criticism there is the possibility that agriculture may be further encouraged if the wait for the profit of tourism to accrue in the community seems to be pushing the indigenes to poverty.In other to ensure accelerated growth of tourism in Koussoukpa Zogbodomey Benin, actors both national, state and local may be required to play different roles (Section 2.3 and 2.3.4)as outlined by the interactional theory (Section 2.1.4). Also according to Matarrita-Cascante (2010) focus on the overall community good through exploration and identification of the community’s social processes will enhance tourism led development. Also on the long run, the biodiversity being explored by traditional practises such as poaching, agriculture, in Benin is gradually depleting (CEBEDES 2010), conservation measure i.e. tourism have shown in this study to be profitable and the country may likely focus on the activities that will sustainably alleviate its poverty situation.
Table 4.2: NCF, NPV, IRR, Payback, PI and EVA for different percentage growth rate over 15years at DF 12%.
In addition, the inference from Table 4.2 is in line with Neo-Classical growth theory (Sadallah 1994) which explained that in analysing production outflow, time now depends on other factors such as labour and capital, which in this study may be the increase in the number of tourists.
Scenario C which is the growth rate extrapolated from Bhutan’s growth rate yields the highest return in this study; and the growth rate from Pendjari National park Benin the lowest return. First, initiatives and policies governing Bhutan’s tourism are being adopted for Koussoukpa Zogbodomey Benin; these policies have led to increased growth in Bhutan’s tourism. Mongbo et al.(2008),Floquent, Alladatin and Abdelaziz (2010) outlined that the policies are replicable in Koussoukpa Zogbodomey Benin and according to Matarrita-Cascante (2010), policies are major factors that drive productivity of tourism initiative. Second BECG (2010) suggests that there are similar factors in value chains of the Hlan-Lokoli swamp (Zogbodomey Benin) and the Pendjari Park Benin. Third, Hlan (Zogbodomey Benin) has rich biodiversity like that of Bhutan which is of interest to biologists and scientists and is located near the urban markets which makes it easily accessible. It has exclusive cultural practises and tradition, and thereby portrays potential for the tourists’ number to grow.Finally, lessons and practise for the ecotourism implementation are drawn from Pendjari Benin, Costa Rica and Bhutan; and a combination of Costa Rica’s and Bhutan’s policy strategyand tourism initiatives may enhance Benin’s economic performance in tourism. This further suggests thatwith adequate implementation of strategies and lessons from thriving tourism locations, economic benefit from ecotourism in Zogbodomey is likely to increase; ensuring continued and improved source of livelihood for community members who, apparently, are being stirred away from some of their traditional practise such as agriculture and poaching.
More so, Benin receives $187,600,000 (90,628,019,323.67CFA) from tourism (World Bank 2013),contributing 6.5% to Benin’s GDP (Gross Domestic Product) of $15.84billion (7,660billionCFA) (CIA 2013). As suggested by this study, estimated revenue (GDP) of 60,528,557.16 CFA ($125,294.11)may be realised from ecotourism in Koussoukpa Zogbodomey Benin over 15years; which adds 0.07% to the tourism receipts in Benin and increases tourism contribution to GDP. This revenue generation is also likely to build up over more years as the ecotourism practise is continued. In this research, although the benefits from other economic activities were not analysed, according to (BECG 2010) there are potentials for job creation in accommodation provision, catering services, tour guiding, and media group. Also tourists’ expenditure on diverse activities such as cultural shows, artisans’ products or souvenirs will add to accruable revenue.
Table 4.3: Proposed distribution of funds from tourism in Koussoukpa Zogbodomey Benin (BECG 2010)
Table 4.3 shows that the guides receives the highest percentage of the revenue generated, followed by the town hall, community and operation. However, this study suggests that this distribution may cause bias among the community members as a portion of the population ‘guides’ will be receiving a higher rate than the rest of the community. In accordance with Clement et al.’s (2010) research which outlined the conflict caused by unequal distribution of ecotourism benefit, this bias may lead to opposition of the conservation measure by the community members and in turn hamper the growth of the conservation strategy. However, by adopting Bhutan’s indigenisation policy (Moreno et al. 2011) which favours mostly the community members, the percentage share to guides can be reduced and the share to the community increased. Since the guides have a specific percentage, they may not partake of the share assigned to the rest of the community except the revenue is used to erect structures for general use by the community members. Increasing the share of percentage to the community members serves as an incentive to encourage the conservation practise implemented. The size of the community people’s share may portray the income benefits accruable from conserving their natural resources; this follows Kniver’s (2013) suggestion that ecologists have to improve their efforts in convincing people on conservation by showing its importance (benefits).
‘Operation’ (Table 4.3) from their proposition was stipulated for 10% share, this may be too low as operation at an early stage may require improvement and several adjustments to increase the standard of the tourism practise. Therefore, at the initial stage of the ecotourism activity, more percentage may be channelled to ‘operations’, to increase the quality of the ecotourism initiative implemented, attract more tourists and yield more revenue. Further, at the later stage of the ecotourism practise the percentage stipulated for the ‘Town Hall’ (Table 4.3) may be subsequently invested in other developments that will enhance the life of the community members such as building of schools, hospitals, improved housing,training centres, and small enterprises.
Based on the result of this study, economic impact and benefits of ecotourism in Zogbodomey Benin looks promising on a long run and hence may have a positive impact on the lives of the community members and also conserve their biodiversity. However according to Perch-Nielson, Sesartic and Stucki (2010), tourism is seen as a threat to the environment which it is to conserve and most tourism project implementers are barely aware of the threats. The impact of tourism to the environment is on-going in different tourism locations and unless analysed, the extent of its impact cannot be discerned. The next section therefore examined the amount of GHG (CO2, accounting for direct and indirect warming effect of N2O and H2O) emitted into the environment in Benin due to tourism. The analyses is aimed at portraying the implication of the conservation measure ‘tourism’ chosen for Koussoukpa Zogbodomey Benin, and in turn propel conservationists and project executors to take precautions in their endeavour to conserve biodiversity in Koussoukpa Zogbodomey community and Benin as a whole. As suggested by Becken (2008) it is an avenue for tourism to stir towards being more strategic, systematic and sustainable.
Table 4.4: Number of tourists, CO2-e (CO2, NO2, and H2O) emissions and amount received per annum from tourism in Benin Republic
Year 2011 had the highest volume of emissions with 24,949,984.21 kg CO2-e and 2007 the lowest volume with 18,083,987.17 kgCO2-e. This indicates that tourism even though a conservation measure has some negative environmental impact; emissions alsoincreased by about 37.97% between year 2007 and year 2011 in Benin.This increase in the number of emissions may have been caused by some factors which will be identified further in the discussion. This finding on Benin Republic’s tourism GHGs(CO2, accounting for direct and indirect warming effect of N2O and H2O) emission is consistent with Serrano-Bernado et al.’s (2012) finding that GHGs emissions from tourism locations are increasing. Gossling et al. (2005), Kelly and William (2007) and Perch-Nielson, Sesartic and Stucki (2010) studies on some European countries (Appendix 1), Canada and Switzerland respectively also outlined tourism’s adverse environmental impacts in terms of GHG emission. The comparison of Benin Republic with these developed countries is however based on the fact that the analysis approach applied by this study on Benin is in line with that applied on these countries; however, the accuracy of this deductions may have been affected by the fact that developing countries and developed countries may differ in vehicular type, fuel type and fuel consumption(Section 3.2.4 explained the basis on which this approach was adopted).
Following the analysis and comparison of the different sector emissionsfrom year 2007 to 2011, the transport sector (18.49%) contributed the lowest GHGs, while the accommodation sector (44.04%) contributed the highest GHG and other activity sector contributed 37.47%. Unlike estimated in this study, Gossling et al. (2005) concluded that the transport sector contributes more GHG emissions when compared to other sectors; this variation may be due to higher number of tourists, distance covered and the number of movement made by the tourists in the locations analysed in Gossling et al. (2005), and also, a consideration of GHGs emissions from the international flights used by the tourists to tourism destination which was not accounted for in this study. However similar to the findings of this study ispart of Kelly and William’s (2007) researchwhich inferred that based on the high energy consumed by‘other activity sector’(that is asides transport sector) such as leisure, catering services and entertainment, it should have a higher impact in GHG emission than other sectors. Studies by these researchers vary in location and time when research was conducted, while Gossling et al. (2005) focused on European countries, Kelly and William (2007) focused on Whistler, Canada (2000). Therefore GHGs emitted into the environment varies with location, as well as time.
To better understand the variation of the GHGs emitted into the environment in Benin Republic, emissions are analysed alongside tourist number and amount of revenue generated.
Figure 4.5: GHG emissions and the number of tourists in Benin Republic from 2007 to 2011.
All through 2007 to 2011 a continuous increase in tourists’ number was observed. The increase experienced in the number of tourist from 2009 to 2010 was observed to be higher when compared to increase from 2007 to 2008 but the increase in GHG emissions from 2009 to 2010 was still lower than from 2007 to 2008, although in 2011, GHG emission increased alongside number of tourists. This variation in the number of tourists and GHG emission could have been caused by factors such as the activity offered by the tourism sector at that point, the extent of tourist participation in the activities, tourists’ length of stay in Benin at the different times. In support of this Peeters (2007) stated that the impact of tourism (i.e. GHGs emitted) are not evenly distributed but may be dependent on some determining factors such as mentioned in this section. Therefore the changes in GHGs emitted are not wholly dependent on the number of tourists visiting Benin Republic but are also likely caused by other factors further discussed in the analysis.
Figure 4.6: Income generated form tourists and GHG emissions in Benin Republic from 2007 to 2011
The revenue generated is driven by factors such as that which are paid for in tourism ‘transport, accommodation, feeding, entertainment’, entrance fees (BECG 2010). In line with this is Slootweg and Kolhoff (2003) postulation that a biophysical intervention brings about a biophysical change, which in this case the biophysical intervention can be seen as increase in revenue aimed at enhancing the economy while the biophysical change is the increasing GHGs emitted alongside revenue generated. Further the income generated in 2011 was only slightly higher than the previous year and not up to the amount generated in 2008 before the fall, while the increase in GHGs emissions were higher compared to emissions in the previous years, analysed (2007 to 2010). This is in contrast with the kuznet (1955) hypothesis (section 2.9.1) that says that environmental degradation increases alongside increasing income and at some point environmental degradation decreases, as in this case environmental degradation increased instead of decreasing. Consequently, the factors causing increasing GHG emissions in tourism are therefore, likely present in this activities performed by tourists such as transport, accommodation and other activities sector of tourism.
Furthermore, judging fromthe increase in the transport cost of the transport sector: cost of fuel, number of movement by tourists, amount paid by tourist per distance, could have affected the performance of tourism. Note also as shown in appendix 5, transport receipt increased from 2007 to 2008 and remained steady from 2008 to 2010 although tourists’ number increased between 2008 and 2010. The steadiness may also be attributed to increased cost of transport. Also from 2010 to 2011 transport receipts increased alongside increase in tourists’ number at moderate cost of transport. Hence it still follows that revenue generation from tourism increases as tourists’ number increases(Song, Dwyer and ZhengCao 2012), unless there are other underlying factors disrupting the balance. Although not shown in this study due to limited data, there is a possibility that the accommodation sector and other activity sector are affected by factors such as the cost of per unit service, purchase of services by tourists and cost of elements that drive the services in the sector such as man power and fuel. In line with this study is the part of Gossling et al.’s (2005) findings which outlined that distance travelled by tourists, expenditures of tourists per day, average lengths of day, are important factors in tourism performance (eco-efficiency).
Figure 4.7 generated from the eco-efficiency calculation (e.g. Appendix 15), illustrates that eco-system practise (ecotourism) in 2007 and 2008 were more favourable, when compared to 2009 where eco-efficiency became less favourable. In 2010 and 2011 eco-efficiency improved slightly due to the slight increase in revenue generated, but was still less favourable as GHGs (CO2, accounting for direct and indirect warming effect of N2O and H2O) emissions increased. As suggested bySong, Dwyer and ZhengCao’s (2012) Tourism Led Growth (TLG) hypothesis, growing ecotourism practise with increase in tourists’ number should lead to increase in revenue generation. Also in the analysis of the economic benefit of ecotourism in Koussoukpa Zogbodomey Benin (Section 4.3, 4.4, 4.5) revenue increased with increase in tourists number. Therefore tourism is aimed at conserving biodiversity and increasing economic benefit, however, this aim may be defeated with increasing GHG emissions into the environment. As shown in this study, as income generated was affected (Figure 4.6), ecological efficiency became less favourable (Figure 4.7) despite increase in the number of tourists (Table 4.4).
Figure 4.7: Eco-efficiency of tourism
In comparison to the estimated (CO2-e) world average eco-efficiency of 1.18 kg CO2-e/euro (Gossling et al. 2005) which is equivalent to 1.62 kg CO2/$ (when converted to US$), ecotourism in Benin from 2007 to 2011 is favourable. Using the eco-efficiency of year 2007 which is the closest year to when Gossling et al. (2005) estimated the world average, Benin’s eco-efficiency was more favourable by 94.6%. Gossling et al. (2005) also estimated that a sustainable eco-efficiency may be about 0.24 kg CO2/euro equivalent to 0.33 kg CO2/$, based on these and the result obtained in this study ecotourism ecological efficiency in Benin has been sustainable (2007 to 2011) and was found to be between 0.088kg CO2/$ and 0.143kg CO2/$ which are below 0.33 kgCO2/$. This variation in the sustainable eco efficiency and Benin’s eco efficiency may be due to the number of tourists in the different location, type of vehicles used, type of accommodation and the kinds of leisure activity in these locations. Notwithstanding, this finding implies that tourism in Benin as a sustainable conservation measure and development tool is not questionable, but there is potential for it to become questionable over years as GHG emissions are increasing and eco-efficiency is becoming less favourable. Hence there is need for more strategic tourism which will cause less adverse effect on the environment; and there is room for improvement and control in Benin tourism as it is still a growing sector in Benin; tourism can be curtailed and tailored to better achieve its aim of generating more revenue and preserving the environment. Therefore it can be seen that this finding counters Weaver’s (2011) suggestion that research into tourism’s negative impact to the environment will hamper the productivity of a sustainable tourism, however the finding is in accordance with Becken (2008) and Scoth (2011) who identified that research in tourism negative impact is for the good of the tourism industry.
Note that this study serves as an estimate; the efficiency and accuracy of the result obtained may have been affected by limited availability of data. For improved analyses of the sustainability of tourism practise in Benin Republic, data and reports are required on tourism activities taking place in Benin Republic, such as in the transport sector, accommodation sector and the activities sector.
Table 4.5: Sections, tables, figures and the objectives addressed.
4.1 INTRODUCTION
This chapter presents the study results, their interpretation and discussion.4.2 SWOT ANALYSIS
SWOT analysis as shown in Table 4.1 was carried out on the stakeholders and their roles identified from the pilot project in Koussoukpa Zogbodomey in Benin (see Section 2.3.4 and 2.8).Table 4.1: SWOT Analysis on the roles of stakeholders in biodiversity conservation implementation in Koussoukpa Zogbodomey Benin
| STRENGTH | WEAKNESSES |
| 1.) Presence of national and state level owned organization. 2.) Creation of job opportunity for indigenes. 3.) Ensures improved conservation practises. | 1.) Lack of organization at local level such as a community members’ organization. 2.) Absence of sub organizations/units/sector in the state and national level organization. 3.) Challenge posed to the community members on the need to accept the change from continued biodiversity use to biodiversity conservation. |
| OPPORTUNITY | THREAT |
| 1.) Potential to build capacity on biodiversity conservation through the already formed organizations. 2.) Potential to create sub sectors in the state and national level organization for improved practise. | 1.) Opposition from community members to the actions of stakeholders in the national level, state level and locally owned organization when established. |
4.3ASSESSMENT OF THE CASH FLOW
Three different cash flows were generated using the three economic scenarios created based on the growth rate from the three exemplary areas (Scenarios A, B, C). The cash flows can be found in Table A2.1, A3.1 and A4.1 (Appendix 2, 3 and 4). Figures 4.1, 4.2, and 4.3 represent NPVs from the cash flow generated. Discount Factor (DF) of 3% had the highest NPV in all the three scenarios.Figure 4.1: Scenario A’s NPV for 5, 10 and 15 years at DF of 3%, 8% and 12%.
Figure 4.1 illustrates that in scenario A, negative NPVs were obtained at the 5th year for the Discount Factors (DF) applied. However at the 10th and 15th year, NPVs were positive. Positive NPV’s observed after the 5th year may be due to increased performance of the ecotourism implementation as the number of years increased, which could have led to rise in the number of tourists, payment for tourism activities, recovery of the initial cash outlay and increased receipt of profit from the ecotourism activity. However at 12% DF, NPV was still negative after the 5th year up to about the 6/7th year, which is due to the higher discount applied unlike in 3% and 8%. Therefore in accordance with Brown and Kwansa’s (1999) rule which states that a project is favourable and acceptable when the NPV is greater than 1, the result implies that implementation of ecotourism in Koussoukpa Zogbodomey Benin is acceptable and favourable if executed and maintained to the 10th or 15th year.
Figure 4.2 outlines that in scenario B, NPVs were all positive after the 5th year at the three Discount Factors (3%, 8% and 12%). However, in this scenario ‘B’ a faster growth in performance and early recovery of investment may have eliminated the negative NPV at 12% DF after the 5thyear unlike occurred in Scenario A. This is because despite the percentage discount at 12%, the accelerated performance produced positive NPVs. Positive NPVs observed slightly before the 5th year at DF of 3% and 8%may also be attributed to the accelerated performance. Also, although not accounted for in this study economic and social issue surrounding ecotourism activity may have influenced its performance, as stated by Currie, Milton and Steencamp (2009) consideration of ecological, social and economic factors are needed for project success. Therefore following the deductions and in line with Brown and Kwansa (1999) ecotourism in Koussoukpa Zogbodomey Benin exhibiting the estimated growth rate applied in scenario B is favourable and acceptable.
Figure 4.2: Scenario B’s NPV for 5, 10 and 15 years at DF of 3%, 8% and 12%.
Figure 4.3: Scenario C’s NPV for 5, 10 and 15 years at DF of 3%, 8% and 12%.
Figure 4.3 illustrates that in scenario C, at a DF of 3% positive NPVs’ were obtained for the 5th, 10th to the 15th year; although at 8% and 12% DF NPV was negative at the 5th year but positive at the 10th and 15th year. The lowest discount factor 3% was positive for all the years because unlike 8% and 12% a lower amount were discounted from the cash outlay. Notwithstanding scenario C differed from A and B due to the fact that these positive NPVs at 3% DF obtained all year, were not experienced in scenario A and B. This high performance in scenario C may be due to similar factors as identified in scenario A and B which includes economic, ecological and social factors, further still, management in this scenario may have displayed optimum conduct and applied excellent ecotourism practises. As outlined by Aldebert, Dang and Longhi (2011) cooperation of diverse actors in tourism, application of innovative ideas and improved form of practises in tourism enhances tourism flow and performance. Therefore the result implies that performance of ecotourism implementation according to scenario C is acceptable and favourable.
According to figure 4.4, scenario A, B and C depicts a Profitability Index (PI) of less than 1 over 5 years but a greater than 1 PI over 10 and 15 years. Although PI of scenario C, over 10 and 15 years were higher when compared to scenario A and B; and the PI of scenario B over 10 and 15 years appeared higher than scenario A. As illustrated in appendix 2, 3 and 4, scenario C had a higher growth rate in the number of tourists when compared to B and A, and scenario B a higher growth rate than A. The difference in the growth rate of tourists may have influenced the difference observed in the profitability index among the three scenarios. Thissuggested influencing factor ‘i.e. increase in the number of tourists’ is in accordance with Mattarita-Cascante (2010) who implied that changes in the number of tourist outcome is one of the factors that lead to tourism success.
Figure 4.4: Profitability Index (PI) of ecotourism in the three different scenarios over 5, 10 and 15 years.
Ecotourism practise is viable in Koussoukpa Zogbodomey Benin according to this study, which shows that after the 5th year in scenario B, C and, about 7th year or up to 10th year in scenario A, positive NPVs were attained; in addition PI obtained also shows that over 10 years and 15 years PI was greater than 1. These results implies that tourism projects grow and the growth continues over years, affirmingDay-Rubeinstein and Frivold (2001) proposition that tourism benefits build up and supporting part of Mattarita-Cascante’s (2010) logic on tourism led development which explained that tourism grows continuously with time and may eventually leads to development. However, this growth depends on some factors such as adopted practises and performance of operations implemented and since the ecotourism initiative implemented in Koussoukpa Zogbodomey Benin wasbased on lessons and practises from thriving locations, the scenarios presented in this research may occur in Koussoukpa Zogbodomey Benin. This discovery is in line with the Song, Dwyer and ZhengCao (2012) Structure Conduct Performance (SCP) paradigm theory which signifies that the structure, content and strategy of ecotourism practise determines its performance.
Although the deductions from this study have portrayed that, economic benefits will most likely accrue from ecotourism implementation in Koussoukpa Zogbodomey Benin over years, the perception of the stakeholders, specifically the community members ((users of biodiversity), see Section 2.3) over years, have not been considered. There is the potential that the community members may not be patient enough for the benefits of tourism in Koussoukpa Zogbodomey Benin to accrue and they may be drawn back to their traditional practises such as Poaching and agriculture. As pointed out by BECG (2010) and Tanaka et al. (2013) 80% of the people in Koussoukpa Zogbodomey depended on agricultural practises for their livelihood. Meanwhile FAO (2013) have criticized agricultural practises, stating that despite agricultural practises, Benin still remains in poverty. Despite this criticism there is the possibility that agriculture may be further encouraged if the wait for the profit of tourism to accrue in the community seems to be pushing the indigenes to poverty.In other to ensure accelerated growth of tourism in Koussoukpa Zogbodomey Benin, actors both national, state and local may be required to play different roles (Section 2.3 and 2.3.4)as outlined by the interactional theory (Section 2.1.4). Also according to Matarrita-Cascante (2010) focus on the overall community good through exploration and identification of the community’s social processes will enhance tourism led development. Also on the long run, the biodiversity being explored by traditional practises such as poaching, agriculture, in Benin is gradually depleting (CEBEDES 2010), conservation measure i.e. tourism have shown in this study to be profitable and the country may likely focus on the activities that will sustainably alleviate its poverty situation.
4.4 RELATIONSHIP BETWEEN ECONOMIC BENEFITS, THE PERCENTAGE INCREASE IN THE NUMBER OF TOURISTS AND TIME
As shown in Table 4.2, as the percentage change in the number of tourists increases, NCF increases, this in turn raises NPV, IRR, EVA, PI, and reduces the payback year; revealing that the higher the tourists number, the higher the tourism receipts, the higher the economic value added and the higher the profitability index of ecotourism practise over time. This is in accordance with the principle of the time value of money (financial theory) outlined by Mohamed and McCowan (1999) which portrays the value of money over time; they also stated that NPV, IRR and Pay back year are appraisal technique based on the principle of time value of money. Also Holden (2008) stated that tourism success is usually evaluated by the number of tourist arriving at a location and their expenditure in the location; their expenditure which leads to increase in profitability, addition to economic value and Net present value.Table 4.2: NCF, NPV, IRR, Payback, PI and EVA for different percentage growth rate over 15years at DF 12%.
| Scenario | Percentage increase in number of tourist | NCF (CFA) | NPV at 12% | IRR | P/I | Pay back year | EVA (CFA) |
| A | 7.14 | 20,159,557,63 | 3,316,382.38 | 19 | 2.42 | Sixth year | 18,815,235.48 |
| B | 15.40 | 29,356,514.96 | 5,724,873.53 | 22 | 3.25 | Fifth year | 27,399,695.94 |
| C | 33.33 | 60,528,557.16 | 13,365,286.48 | 29 | 7.25 | Fifth year | 56,493,087.16 |
Scenario C which is the growth rate extrapolated from Bhutan’s growth rate yields the highest return in this study; and the growth rate from Pendjari National park Benin the lowest return. First, initiatives and policies governing Bhutan’s tourism are being adopted for Koussoukpa Zogbodomey Benin; these policies have led to increased growth in Bhutan’s tourism. Mongbo et al.(2008),Floquent, Alladatin and Abdelaziz (2010) outlined that the policies are replicable in Koussoukpa Zogbodomey Benin and according to Matarrita-Cascante (2010), policies are major factors that drive productivity of tourism initiative. Second BECG (2010) suggests that there are similar factors in value chains of the Hlan-Lokoli swamp (Zogbodomey Benin) and the Pendjari Park Benin. Third, Hlan (Zogbodomey Benin) has rich biodiversity like that of Bhutan which is of interest to biologists and scientists and is located near the urban markets which makes it easily accessible. It has exclusive cultural practises and tradition, and thereby portrays potential for the tourists’ number to grow.Finally, lessons and practise for the ecotourism implementation are drawn from Pendjari Benin, Costa Rica and Bhutan; and a combination of Costa Rica’s and Bhutan’s policy strategyand tourism initiatives may enhance Benin’s economic performance in tourism. This further suggests thatwith adequate implementation of strategies and lessons from thriving tourism locations, economic benefit from ecotourism in Zogbodomey is likely to increase; ensuring continued and improved source of livelihood for community members who, apparently, are being stirred away from some of their traditional practise such as agriculture and poaching.
4.5 ECONOMIC IMPACT OF ECOTOURISM IN KOUSSOUKPA ZOGBODOMEY BENIN
Based on the findings of this study, the best scenario ‘C’ indicates high revenue generation potentials, with 56,493,087.16CFA ($116,940.69)as the estimated economic value added over 15 years. This economic value is approximately 577% of the amount invested at start of project. The payback year was found to be in the fifth year and afterwards financial benefits accrued; these findings are in accordance with Brida et al.’s (2009) Tourism Led Growth (TLG) hypothesis that ecotourism leads to long term economic growth, and as the number of years increases, the benefits generated increases.Serrano-Bernardo et al. (2012) also stated that tourism is an important contributor to the economy which yields increased growth continuously, in areas where implemented. Deduced from the performance trend in this study is the potential for continued growth beyond 15 years. This may depend on operational performance which requires each stakeholder outlined in section 2.3 to efficiently execute their roles.More so, Benin receives $187,600,000 (90,628,019,323.67CFA) from tourism (World Bank 2013),contributing 6.5% to Benin’s GDP (Gross Domestic Product) of $15.84billion (7,660billionCFA) (CIA 2013). As suggested by this study, estimated revenue (GDP) of 60,528,557.16 CFA ($125,294.11)may be realised from ecotourism in Koussoukpa Zogbodomey Benin over 15years; which adds 0.07% to the tourism receipts in Benin and increases tourism contribution to GDP. This revenue generation is also likely to build up over more years as the ecotourism practise is continued. In this research, although the benefits from other economic activities were not analysed, according to (BECG 2010) there are potentials for job creation in accommodation provision, catering services, tour guiding, and media group. Also tourists’ expenditure on diverse activities such as cultural shows, artisans’ products or souvenirs will add to accruable revenue.
4.6 ECONOMIC BENEFIT (INCOME) AND THE IMPLICATION OF ITS DISTRIBUTION
Income distribution and its adequate use is an important aspect of its generation. According to BECG (2010), the distribution of income from tourism was proposed during the pilot project and is herein outlined on Table 4.3.Table 4.3: Proposed distribution of funds from tourism in Koussoukpa Zogbodomey Benin (BECG 2010)
| Group | Percentage |
| Guides | 40% |
| Community | 20% |
| Town Hall | 30% |
| Operation | 10% |
‘Operation’ (Table 4.3) from their proposition was stipulated for 10% share, this may be too low as operation at an early stage may require improvement and several adjustments to increase the standard of the tourism practise. Therefore, at the initial stage of the ecotourism activity, more percentage may be channelled to ‘operations’, to increase the quality of the ecotourism initiative implemented, attract more tourists and yield more revenue. Further, at the later stage of the ecotourism practise the percentage stipulated for the ‘Town Hall’ (Table 4.3) may be subsequently invested in other developments that will enhance the life of the community members such as building of schools, hospitals, improved housing,training centres, and small enterprises.
Based on the result of this study, economic impact and benefits of ecotourism in Zogbodomey Benin looks promising on a long run and hence may have a positive impact on the lives of the community members and also conserve their biodiversity. However according to Perch-Nielson, Sesartic and Stucki (2010), tourism is seen as a threat to the environment which it is to conserve and most tourism project implementers are barely aware of the threats. The impact of tourism to the environment is on-going in different tourism locations and unless analysed, the extent of its impact cannot be discerned. The next section therefore examined the amount of GHG (CO2, accounting for direct and indirect warming effect of N2O and H2O) emitted into the environment in Benin due to tourism. The analyses is aimed at portraying the implication of the conservation measure ‘tourism’ chosen for Koussoukpa Zogbodomey Benin, and in turn propel conservationists and project executors to take precautions in their endeavour to conserve biodiversity in Koussoukpa Zogbodomey community and Benin as a whole. As suggested by Becken (2008) it is an avenue for tourism to stir towards being more strategic, systematic and sustainable.
4.7 ASSESSMENT OF THE GREEN HOUSE GAS (GHG) EMISSIONS FROM TOURISM IN BENIN REPUBLIC
Table 4.4 outlines the estimated amount of GHGs (CO2, NO2, and H2O) emitted from transport, accommodation and other activity from 2007 to 2011 in Benin republic.Table 4.4: Number of tourists, CO2-e (CO2, NO2, and H2O) emissions and amount received per annum from tourism in Benin Republic
| YEAR | 2007 | 2008 | 2009 | 2010 | 2011 | %Contribution |
| Number of tourists | 186,000 | 188,000 | 190,000 | 199,000 | 209,000 | |
| Transport sector(kg CO2-e) | 1900457.57 | 4695298.14 | 2226720.65 | 3592964.82 | 6765265.21 | 18.49 |
| Accommodation sector (kg CO2-e) | 8743529.60 | 8837546.10 | 8931563.00 | 9354636.50 | 9824719.00 | 44.04 |
| Other Activity sector(kg CO2-e) | 7440000.00 | 7520000.00 | 7600000.00 | 7960000.00 | 8360000.00 | 37.47 |
| Total number of GHG emissions (kg CO2-e) | 18083987.17 | 21052844.24 | 18758283.65 | 20907601.32 | 24949984.21 | |
| Revenue generated per annum ($) | 206,300,000.00 | 236,400,000.00 | 131,400,000.00 | 149,400,000.00 | 187,600,000.00 | |
| Eco-efficiency (kg CO2-e/$ | 0.088 | 0.089 | 0.143 | 0.140 | 0.133 |
Following the analysis and comparison of the different sector emissionsfrom year 2007 to 2011, the transport sector (18.49%) contributed the lowest GHGs, while the accommodation sector (44.04%) contributed the highest GHG and other activity sector contributed 37.47%. Unlike estimated in this study, Gossling et al. (2005) concluded that the transport sector contributes more GHG emissions when compared to other sectors; this variation may be due to higher number of tourists, distance covered and the number of movement made by the tourists in the locations analysed in Gossling et al. (2005), and also, a consideration of GHGs emissions from the international flights used by the tourists to tourism destination which was not accounted for in this study. However similar to the findings of this study ispart of Kelly and William’s (2007) researchwhich inferred that based on the high energy consumed by‘other activity sector’(that is asides transport sector) such as leisure, catering services and entertainment, it should have a higher impact in GHG emission than other sectors. Studies by these researchers vary in location and time when research was conducted, while Gossling et al. (2005) focused on European countries, Kelly and William (2007) focused on Whistler, Canada (2000). Therefore GHGs emitted into the environment varies with location, as well as time.
To better understand the variation of the GHGs emitted into the environment in Benin Republic, emissions are analysed alongside tourist number and amount of revenue generated.
4.7.1 Number of tourists and GHGs emissions
GHG (CO2, accounting for direct and indirect warming effect of N2O and H2O) emission from year 2007 to 2011 fluctuated and this could have been caused by different factors. As illustrated in Figure 4.5, from 2007 to 2008 the number of tourists and GHG emissions equally increased, in contrast a decrease in GHG emissions was observed in 2009 and afterwards a slight increase from 2009 to 2010.Figure 4.5: GHG emissions and the number of tourists in Benin Republic from 2007 to 2011.
All through 2007 to 2011 a continuous increase in tourists’ number was observed. The increase experienced in the number of tourist from 2009 to 2010 was observed to be higher when compared to increase from 2007 to 2008 but the increase in GHG emissions from 2009 to 2010 was still lower than from 2007 to 2008, although in 2011, GHG emission increased alongside number of tourists. This variation in the number of tourists and GHG emission could have been caused by factors such as the activity offered by the tourism sector at that point, the extent of tourist participation in the activities, tourists’ length of stay in Benin at the different times. In support of this Peeters (2007) stated that the impact of tourism (i.e. GHGs emitted) are not evenly distributed but may be dependent on some determining factors such as mentioned in this section. Therefore the changes in GHGs emitted are not wholly dependent on the number of tourists visiting Benin Republic but are also likely caused by other factors further discussed in the analysis.
4.7.2 Income Generated and GHG emissions
Based on the study outcome as shown in Figure 4.6, increase in GHGs (CO2, accounting for direct and indirect warming effect of N2O and H2O)emitted and revenue generated was observed from 2007 to 2008, meanwhile in 2009 a decrease now occurred in both GHGs emissions and revenue generated; in 2010 and 2011 increase occurred in both GHGs emissions and revenue generated.Figure 4.6: Income generated form tourists and GHG emissions in Benin Republic from 2007 to 2011
The revenue generated is driven by factors such as that which are paid for in tourism ‘transport, accommodation, feeding, entertainment’, entrance fees (BECG 2010). In line with this is Slootweg and Kolhoff (2003) postulation that a biophysical intervention brings about a biophysical change, which in this case the biophysical intervention can be seen as increase in revenue aimed at enhancing the economy while the biophysical change is the increasing GHGs emitted alongside revenue generated. Further the income generated in 2011 was only slightly higher than the previous year and not up to the amount generated in 2008 before the fall, while the increase in GHGs emissions were higher compared to emissions in the previous years, analysed (2007 to 2010). This is in contrast with the kuznet (1955) hypothesis (section 2.9.1) that says that environmental degradation increases alongside increasing income and at some point environmental degradation decreases, as in this case environmental degradation increased instead of decreasing. Consequently, the factors causing increasing GHG emissions in tourism are therefore, likely present in this activities performed by tourists such as transport, accommodation and other activities sector of tourism.
4.8 GHG EMISSIONS, REVENUE GENERATION IN BENIN REPUBLIC AND ECO EFFICIENCY
A5.1 (Appendix 5) shows that there was a sharp increase in the cost of transport in 2009; this perhaps may have decreased the distance travelled by tourists causing a decrease in revenue generated from tourism. At first this resulted into a consequent decrease in GHG emissions, however subsequently as tourists number continued to increase over the years, GHG emission progressed and increased beyond the previous levels. It is therefore likely that a combination of the number of tourists and activity in tourism sector affect the amount of GHG emitted into the environment. As identified by Scott (2008), Peeter and Dubois (2010), tourism sector CO2 emissions to the atmosphere is increasing and has been projected to further increase as the tourism sector grows. In addition UNEP (2011) stated that the growth in the tourism industry is challenged by the growth in its GHGs emissions. This finding can also be applied to the Ecological Heterogeneity theory which according to Illuis (2003) explains the presence of heterogeneity in ecosystem activity with time, although discovered earlier that increase in tourists number and their activity in the ecosystem led to increase in revenue generation (section 4.3 and 4.4), this same factor ‘increase in tourists number and tourist activities’ is now found to lead to increasing emission of GHGs (CO2, N2O and H2O) into the environment.Furthermore, judging fromthe increase in the transport cost of the transport sector: cost of fuel, number of movement by tourists, amount paid by tourist per distance, could have affected the performance of tourism. Note also as shown in appendix 5, transport receipt increased from 2007 to 2008 and remained steady from 2008 to 2010 although tourists’ number increased between 2008 and 2010. The steadiness may also be attributed to increased cost of transport. Also from 2010 to 2011 transport receipts increased alongside increase in tourists’ number at moderate cost of transport. Hence it still follows that revenue generation from tourism increases as tourists’ number increases(Song, Dwyer and ZhengCao 2012), unless there are other underlying factors disrupting the balance. Although not shown in this study due to limited data, there is a possibility that the accommodation sector and other activity sector are affected by factors such as the cost of per unit service, purchase of services by tourists and cost of elements that drive the services in the sector such as man power and fuel. In line with this study is the part of Gossling et al.’s (2005) findings which outlined that distance travelled by tourists, expenditures of tourists per day, average lengths of day, are important factors in tourism performance (eco-efficiency).
Figure 4.7 generated from the eco-efficiency calculation (e.g. Appendix 15), illustrates that eco-system practise (ecotourism) in 2007 and 2008 were more favourable, when compared to 2009 where eco-efficiency became less favourable. In 2010 and 2011 eco-efficiency improved slightly due to the slight increase in revenue generated, but was still less favourable as GHGs (CO2, accounting for direct and indirect warming effect of N2O and H2O) emissions increased. As suggested bySong, Dwyer and ZhengCao’s (2012) Tourism Led Growth (TLG) hypothesis, growing ecotourism practise with increase in tourists’ number should lead to increase in revenue generation. Also in the analysis of the economic benefit of ecotourism in Koussoukpa Zogbodomey Benin (Section 4.3, 4.4, 4.5) revenue increased with increase in tourists number. Therefore tourism is aimed at conserving biodiversity and increasing economic benefit, however, this aim may be defeated with increasing GHG emissions into the environment. As shown in this study, as income generated was affected (Figure 4.6), ecological efficiency became less favourable (Figure 4.7) despite increase in the number of tourists (Table 4.4).
Figure 4.7: Eco-efficiency of tourism
In comparison to the estimated (CO2-e) world average eco-efficiency of 1.18 kg CO2-e/euro (Gossling et al. 2005) which is equivalent to 1.62 kg CO2/$ (when converted to US$), ecotourism in Benin from 2007 to 2011 is favourable. Using the eco-efficiency of year 2007 which is the closest year to when Gossling et al. (2005) estimated the world average, Benin’s eco-efficiency was more favourable by 94.6%. Gossling et al. (2005) also estimated that a sustainable eco-efficiency may be about 0.24 kg CO2/euro equivalent to 0.33 kg CO2/$, based on these and the result obtained in this study ecotourism ecological efficiency in Benin has been sustainable (2007 to 2011) and was found to be between 0.088kg CO2/$ and 0.143kg CO2/$ which are below 0.33 kgCO2/$. This variation in the sustainable eco efficiency and Benin’s eco efficiency may be due to the number of tourists in the different location, type of vehicles used, type of accommodation and the kinds of leisure activity in these locations. Notwithstanding, this finding implies that tourism in Benin as a sustainable conservation measure and development tool is not questionable, but there is potential for it to become questionable over years as GHG emissions are increasing and eco-efficiency is becoming less favourable. Hence there is need for more strategic tourism which will cause less adverse effect on the environment; and there is room for improvement and control in Benin tourism as it is still a growing sector in Benin; tourism can be curtailed and tailored to better achieve its aim of generating more revenue and preserving the environment. Therefore it can be seen that this finding counters Weaver’s (2011) suggestion that research into tourism’s negative impact to the environment will hamper the productivity of a sustainable tourism, however the finding is in accordance with Becken (2008) and Scoth (2011) who identified that research in tourism negative impact is for the good of the tourism industry.
Note that this study serves as an estimate; the efficiency and accuracy of the result obtained may have been affected by limited availability of data. For improved analyses of the sustainability of tourism practise in Benin Republic, data and reports are required on tourism activities taking place in Benin Republic, such as in the transport sector, accommodation sector and the activities sector.
4.9 CHAPTER SUMMARY
This chapter has attempted to addressed the aim and objectives outlined for this research (Chapter 1, section 1.7).Stakeholders involved in tourism in Koussoukpa Zogbodomey Benin have been analysed;the likely economic impact of tourism implementation in Koussoukpa Zogbodomey Benin have been evaluated; the amount of GHG emitted into the environment in Benin due to its tourism industry have also been evaluated; and the comparison of the implication of the benefit (income generated) and adverse impact (GHG emissions) has been analysed. The sections (result and discussion) that addressed each study objectives are illustrated in Table 4.5. The next chapter presents recommendation and conclusion of the study.Table 4.5: Sections, tables, figures and the objectives addressed.
| OBJECTIVE | RESULT (figure/table) | DISCUSSION (Section) |
| 1. Analysis of stakeholders roles | Table 4.1 | Section 2.3, 2.3.4 and Section 4.2 |
| 2. Likely Economic benefit from eco-tourism implementation | Figure 4.1, 4.2, 4.3, and 4.4. Table 4.2 | Section 4.3, 4.4, 4.5 and 4.6 |
| 3. Environmental impact of tourism (GHG emitted into the environment) | Figure 4.5 Table 4.4 | Section 4.7 |
| 4. The benefits (income generated) in comparison with the adverse impact (GHG emitted) of eco-tourism | Figure 4.6, and 4.7 | Section 4.8 |
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