Resident Perceptions of Environment and Economic Impacts of Tourism in Fiji

Abstract

Knowledge of the negative impacts of tourism is an essential prerequisite for sustainability. This study explores the resident perceptions of an educated population on the environment and economic impacts of tourism in Fiji. Using a sample of 298 respondents based on the triple bottom line framework, we construct a model for sustainable tourism planning for Fiji. The structural equation modelling (SEM) approach indicates that awareness of the adverse effects of tourism is vital for the sustainable expansion of the sector and economic development. The current level and type of awareness are nonspecific. The study implies adaptation of sustainability into the education curriculum, enacting uncompromising sustainable acts and policies and forming an independent sustainability national council to vet all tourism developments.

1. Introduction

The tourism industry has evolved as a major contributor to economic development and employment creation globally [1]. Over the past seven decades, the tourism industry has experienced growth in both developed and developing countries [2]. Although tourism has significant economic benefits, it often compromises environmental quality [3]. Thus, tourism sustainability becomes an important element in managing the industry. Tourism sustainability has emerged as a leading policy paradigm and is important because tourism is a significant contributor to carbon emissions worldwide [3,4,5]. The World Tourism Organization (UNWTO) reported that transport-related emissions from tourism would contribute 5.3 percent of all human-made CO₂ emissions by 2030, up from 5 percent in 2016 [6]. Therefore, tourism sustainability becomes imperative for small island developing states (SIDS) because of their vulnerability to the negative impacts of tourism. SIDS have limited resources, are prone to natural disasters and climate change, and rely heavily on tourism for economic growth [7,8].

Literature indicates that residents are the main stakeholders in tourism development and their support plays a key role in the sustainability of the tourism industry [9,10,11]. Literature also suggests that resident perceptions towards the impact of tourism is essential for the development of tourism [12,13]. The tourism industry is unique in the sense that it involves tourists visiting places where local residents live and, for a destination such as Fiji, where most residents are employed. Therefore, the inflow of tourists increases both the increased chances of friction between tourists and residents and the impact of tourism on the environment and the economy. Hence, it is essential that resident perceptions on the impact of tourism are researched. This will assist in tourism development planning, minimize the negative impacts, and contribute to sustainable tourism.

The investigation of the resident perceptions towards tourism impact would address a number of gaps in resident perception literature. Firstly, most of the studies on perceptions of tourism impact have been conducted in developed countries such as the USA [14,15], Greece [16], China [17], Japan [18], and Egypt [19]. Although only a few studies have been reported in developing countries [20], resident perceptions towards tourism impacts on SIDS have been conducted in Mauritius [21,22], and the Cape Verde Islands [23] and are still underexplored. Secondly, only a few studies in SIDS have focused on SIDS, which largely depend on tourism for foreign exchange earnings and employment. Thirdly, few studies have used the triple bottom line model to investigate the sustainable model of a SID. Fourthly, previous studies have not focused on the awareness levels of residents towards their perceptions of tourism impacts. Lastly and most importantly, previous studies have not focused on the perceptions of an educated population.

According to the aforementioned research gap, this research addresses the following research questions: (1) What are the resident perceptions on the environment and economic impacts of tourism in Fiji? (2) What are the relationships between the latent variables of the study? Therefore, the purpose of this study is to understand the perceptions of residents with at least a secondary level education towards tourism impacts, namely, the environmental and economic impacts of tourism in Fiji. Structural equation modelling (SEM) is used in this study to measure these relationships. The sustainable tourism planning model [24,25] and the social exchange theory [26] developed this study’s model.This study seeks to understand the residents’ perceptions of sustainability and provide policy recommendations. The notion behind the awareness of negative impacts is that if residents are aware of the negative impacts, they may address them. If they are unaware, destinations will not be able to address sustainability holistically. As Puczkó and Rátz [27] stated, while locals may identify unfavourable impacts of tourism, they strongly support the expansion of the tourism industry. Therefore, destinations should manage both the impacts of tourism as well as change the perceptions of locals. The implications of this study are the adaptation of sustainability into the education curriculum, providing awareness on specific behaviors required to reduce carbon footprints, enacting stringent sustainable policies and acts, and forming an independent sustainability council that vets all tourism developments.

1.1. Sustainable Tourism

Sustainable tourism has gained widespread acceptance to reconcile and balance various aspects of heritage tourism, tourism management, social pressures, and economic development [28]. Noting the link between tourism development and environmental quality [29,30], Adriana [31] found that public pressures can promote green supply chains, but organizational factors and strategic myopia hinders the implementation of sustainable tourism. Chan et al. [32] found that environmental knowledge, environmental awareness, and environmental concern are positively associated with tourists’ ecological behaviour in a survey of 438 hotel employees in Hong Kong. Chen and Tung [33], Dunk et al. [34], and Suriñach and Wöber [35] indicated that the tourism industry uses many disposable products, which may lead to soil and water pollution.

In a study by Movono et al. [36], respondents of a Fijian village revealed that the first 20 years of tourism brought much social and economic change in the community that was both good and bad. The women of Votualailai village in Fiji were the first to receive full-time employment when the Naviti resort opened. More people left farming and fishing to focus on paid work which changed livelihood activities [37]. Movono et al. [38] also found that tourism involvement has driven a wedge between traditional human-ecology relationships. Villages now recognise these changes and find ways to rescue what all has been lost and adapt to challenges. The effects on stakeholders need to be considered in sustainable tourism planning [39].

1.2. Sustainability in SIDS

SIDS perceive tourism as an invaluable tool that helps them realize their national and development aspirations [40,41,42,43]. Perceptions of the various social impacts of tourism have been extensively studied since the 1970s [44]. Tosun [44] stated that studies have focused on how segments of the host communities react to tourism impacts. However, further investigations in other geographical locations are required to help develop theories on the perceptions of the social impacts of tourism [44]. Various models of perceptions of the impacts of tourism have been developed [45,46,47].

SIDS depend on tourism for exports and contribution to GDP [48]. SIDS depend on imports of food, water, and raw materials [49]. This dependence can cause island destinations to focus on economic gains and ignore social and environmental issues that tourism can potentially have [50,51,52,53]. Negative issues facing SIDS include habitat destruction, natural resource depletion, erosion, inflation, increasing crime, and loss of local identity [49,50,54]. In addition to these, the growing population of SIDS put pressure on limited resources, and sustainable alternatives are difficult to implement due to cost, location, lack of technical expertise, and infrastructure issues. Due to these reasons and limited size, marginalization, and resource limitations, SIDS will face significant challenges in the sustainable development of tourism [55].

Indigenous communities have taken advantage of the socio-economic and environmental potential. They have created new businesses, created natural protected areas, gained formal employment, and adapted to tourism as a means of creating a living [36,56]. Studies on the perceptions of sustainability in tourism are essential to small island economies because they rely extensively on tourism for growth and development [57] and are vulnerable to environmental degradation, exploitation, and rising sea levels. Mainstream tourism has been found to entail unsustainable practices relating to environmental and societal impacts [28].

1.3. Residents Perceptions towards Tourism Impacts

Nunkoo and Ramkissoon [21] used a sample of 230 residents to examine the resident attitudes towards tourism in Port Louis, Mauritius. The authors found that while residents recognize the positive impact of tourism, they are also concerned with some negative influences of the industry. Rughoobur-Seetah [22] also conducted a similar study in Mauritius with a sample of 178 residents. The results of this study indicated that residents agree that tourism has economic value to the island while they also believe that the environment should not be harmed, and more community participation should be initiated. Ribeiro et al. [23] studied a sample of 418 residents from Cape Verde. They found that economic factors had a direct influence on the pro-tourism development behaviour. The study also found that both attitudes to positive impacts and negative impacts have a direct influence on residents’ pro-tourism development behaviour. The authors also recommended that it is important for policymakers to guarantee that tourism developments will have more benefits than costs. In SIDS, residents’ perspectives are not considered and frequently excluded from decision making related to tourism. Therefore, there is a need to include residents in the process of development as it allows for greater transparency, equity, and sustainability of tourism resources [54].

Rahman and Reynolds [58] established a comprehensive model of consumers’ behavior decisions and examined the interaction among consumers’ biospheric value, willingness to sacrifice for the environment, and behavioural intentions. They conclude that the biospheric value influences consumers’ willingness to sacrifice for the environment. Torres-Delgado and Saarinen [59] and Blancas et al. [60] introduced composite indicators to measure and quantify socio-economic dimensions of sustainable tourism for decision making. Sustainable tourism can defend environmental protection, improve community’s health and education, and reduce poverty in destinations [48,61].

1.4. Sustainable Tourism Planning Model

Padin [24,25] proposed a sustainable tourism planning model based on the triple bottom line (TBL) dimensions, viz., ecological, social, and economic planning. “Triangle Nijkamp” initiated the model of this study which arises in Hall [62]. Padin’s TBL approach has been applied by numerous scholars such as Svensson and Wagner [63,64], Hunter [65], Høgevold [66], Cambra-Fierro and Ruiz-Benı’tez [67], Dos Santos [68], Høgevold and Svensson [69], Pilgram [70], Padin et al. [25], Ferro et al. [71], and Grah et al. [72]. The TBL approach asserts that stakeholders show concern towards tourism activities’ economic, ecological, and social aspects. These conflicting relationships are referred to as the TBL approach [73].

The literature treats the three dimensions as independent and uncoordinated. Thus, it is crucial to ascertain relationships between these dimensions. The stakeholders or the so-called social capital are of utmost importance to the model since it represents the same population for whom and why this process exists. Many authors have stated the importance of participation of the stakeholders in any sustainable process or planning in tourism [74,75,76,77,78,79,80,81,82]. However, this is problematic in practice [83]. Studies that have tested the TBL elements separately include those by van Beurden and Gössling [84], Dixon-Fowler et al. [85], Albertini [86], Javed et al. [87], Esteban-Sanchez et al. [88], Liao et al. [89], Wang and Sarkis [90], and Theodoulidis et al. [91].

References to sustainability in TBL is based on theory [63,64,65,70] and in case studies [63,64,66,67,68,69]. These works raise three dimensions, socio-cultural, economic, and environmental, and finding the right balance between them ensures long-term sustainability [24]. Sustainable tourism is a balance between tourism development and the sustainability of the environment. Public pressures ensure that sustainability happens while organizational factors hinder it. For sustainable tourism to occur, all stakeholders of the tourism industry must work together. The TBL model suggests that there needs to be a balance between economic, social, and environmental factors for sustainability to occur. Researchers have also studied the TBL elements separately. It is vital to understand whether the relevant populace is aware of the negative impacts of tourism. An absence of awareness of the negative issues will not lead to any public pressure to resolve the issues.

1.5. Model Conceptualization

We developed a conceptual model that summarizes the entire study incorporated within the SEM framework. Figure 1 represents the conceptual model. The study seeks to find the relationship between resident perceptions on tourism impacts on the environment and economic pillars. Therefore, the dependent variables of this study are the environment and economic pillars. The latent variables for the environment pillar are local environmental impact awareness (LEI) and global environmental impact awareness (GEI). The latent variables for the economic pillar are tourism impact awareness (TIA), reducing impact awareness (RIA), and sustainable future (SF). There are 22 observable variables for LEI, 23 for GEI, 10 for TIA, 18 for RIA, and 6 for SF. Thus, there are a total of 79 observable variables in this study.

The hypotheses of this study are derived using the triple bottom line (TBL) sustainability model created by Padin [24,25] by focusing on the environmental and economic elements. We test five latent variables: two latent variables for the environment pillar and three latent variables for the economic pillar. We derive ten hypotheses, which are the relationships between the five latent variables (Figure 1). Each path represents a hypothesized positive relationship. Subsequently, a tourism sustainability model is constructed using survey level data and estimated using the structural equation modelling technique.

Social exchange theory (SET) has been used previously [26,92,93] to explain the attitudes of residents towards tourism. SET is a sociological theory concerned with understanding the exchange of resources between groups and individuals. The theory proposes that residents will participate in the exchange if the perceived benefit outweighs the costs.

2. Materials and Methods

2.1. Study Site

Tourism contributes about 34 percent towards GDP and 26.3 percent of total employment to Fiji and is an essential driver of economic activity [94] (Figure 2), which is higher than the average of 33 percent in other pacific island countries. There is a growing demand from tourists for multiple pit-stop vacations [95]. Fiji can benefit from island hopping by developing holiday packages for multiple destinations for long haul tourists through its cruise ship, airline, and rental networks [96]. Flying to smaller island destinations provides tourists with a great aerial view of Fiji and showcases unique features such as reefs and atolls. Resorts and excursion sites link through land and air transport [96].

Fiji has the largest tourism industry in the South Pacific, employing about 26.3 percent of the total workforce [94]. COVID-19 had a massive impact on the tourism industry as the economy was expected to contract by 21.7 percent due to insufficient tourism activity and its effects on the economy. The impact also increased unemployment and further pushed households below the poverty line [97]. This is explained by the fact that 27 percent of staff from tourism businesses are on reduced hours and days, 25 percent are on leave without pay, and 8 percent have been made redundant. Additionally, 50 percent of tourism businesses are hibernating or closed with anticipation that if the COVID-19 situation did not change by November of 2020, around 500 tourism and non-tourism businesses anticipate bankruptcy [98].

The primary sources of tourists to Fiji are from Australia, New Zealand, and the United States, each contributing about 44 percent, 18 percent, 10 percent of arrivals, respectively (Figure 3).

Tourism Fiji is the marketing arm of the Fijian government that promotes Fiji as a tourism destination throughout the world. Tourism Fiji has international offices in Sydney, Auckland, Los Angeles, London, Germany, and China, with representatives in India, Singapore, and Japan. Fiji has a good network of transport services, including buses, ferries, and taxis, and has two domestic airlines, Fiji Link and Northern Air, which operate between the outer islands. Yachts, cruises, and car rentals are also great ways of exploring Fiji [99]. Growing tourist numbers indicate Fiji’s popularity as a tourism destination. From the year 2000, tourist arrivals have grown by about 187 percent to reach about 900,000 in 2018. Tourism earnings were FJ $2.08 billion in 2018, which brings Fiji close to achieving its 2021 targets [100].

Major tourism infrastructures in Fiji, such as hotels, are typically in the form of greenfield investments. This results in significant long-term leakages and repatriation of profits [101,102], which further complicates attempts to develop linkages between tourism facilities and local economies [101,103,104,105,106]. This leads to unequal spatial and geographic development [105]. Narayan and Prasad [104] stated that 94% of the 132 tourism projects implemented between 1988 and 2000 were foreign-owned, with just 6% local ownership. Farrelly [107] argued that there may be a need to reform Fiji’s local traditional decision-making systems for local ownership ventures in the future.

Lastly, tourism is affected by political instability and pandemics [108]. Fiji has gone through four coups since 1987 and numerous changes in government [56]. At present, Fiji’s tourism sector is at a halt due to the coronavirus pandemic. Border closures meant job losses to 40 percent of the Fijian workforce and a ripple effect on businesses indirectly related to the tourism industry. The Reserve Bank of Fiji Economic Review of April 2020 indicated that the economy was expected to contract more sharply than the initial −4.3% estimated for 2020 due to a significant decrease in tourism activity and the ripple effect on the rest of the economy. The report also stated that 65,800 members had withdrawn from the Fiji National Provident Fund from a scheme targeted to individuals affected by the COVID-19 pandemic [109].

2.2. Procedure

This study utilized SPSS and Amos software for analysis of the data. A two-stage data analysis was performed. In the first stage, reliability analysis and descriptive statistics were performed using SPSS. Reliability analysis was performed to evaluate the stability and consistency of the measured items. In stage two, structural equation modeling (SEM) was performed using Amos. We test our model of 5 latent variables and 79 observable variables using SEM. Schermelleh-Engel et al. [110] stated that there is consensus that one should avoid reporting all fit indices since the first days of SEM. Hu and Bentler [111] recommended the use of standardized root mean square residual (SRMR) and supplemented by non-normed fit index (NNFI), comparative fit index (CFI), or root mean square error of approximation (RMSEA) (NNFI and RMSEA are less preferable at small sample sizes).

A total of 500 questionnaires (Supplementary Materials) were distributed to a proportional stratified random sample in the three most densely divisions in Fiji. A 60% response resulted from 298 usable questionnaires returned. The 298-sample size of this study meets the recommended sample size for SEM by Garver and Mentzer [112], and Hoelter [113], who proposed a critical sample size of 200. Questionnaires were utilized to gather responses using various forms of scales such as Likert scales, multiple choice, ranking, and open-ended questions. Questionnaires were distributed to respondents and given one week to complete. All questionnaires were completed after one week. Questionnaires were only given to respondents if they agreed to be surveyed. Respondents were explained during questionnaire distribution that their responses would be confidential and only used for research purposes. The targeted sample for this study was the residents of Fiji with at least a secondary level education. We distributed questionnaires in Fiji’s three densely populated divisions, namely the Northern, Central, and Western divisions. These three divisions consist of about 96% of Fiji’s total population. The Eastern division mainly consists of small islands, which are hard to reach, and it is also inadequate to no internet coverage. Therefore, this division was not taken into account. The study ensured that an equal number of people were chosen from the three divisions. The authors identified their key contacts in the three divisions, who then distributed questionnaires to their contacts who had at least a secondary level education. Such a selection criterion was chosen to minimize the cost of data collection. Therefore, purposive sampling was used where the questionnaire distribution ensured that all respondents had at least a secondary school education and that respondents were equally represented from the three most populous divisions in Fiji. Purposive sampling was used as we needed to include people who had at least a secondary level education and those from the three divisions [114].

3. Results

3.1. Respondent Characteristics

The study aimed to ensure that the data set represented respondents of at least a secondary school education.

Table 1. Descriptive Statistics for Education Level of Respondents.

Education Level	Frequency	Percent
None	3	1.0
Primary	1	0.3
Secondary	83	27.2
Certificate	25	8.2
Diploma	61	20.0
Degree	112	36.7
Master’s	17	5.6
Total	302	99.0
No response	3	1
Total	305	100
Usable Responses	298

The authors filtered 7 responses who either did not indicate their level of education (3) and who indicated their education level as less than Primary level (4).

describes the education level of all respondents of this study.

Most respondents of the study had a minimum education level of a degree, this being 36.7% of all respondents. A total of 27.2% had a secondary level education, 20% had a diploma, 8.2% had a certificate, and 5.6% had a master’s degree. An amount of 97.7% of all respondents had secondary level education and above. In total 55% of respondents were females, while 39% were males.

3.2. Descriptive Statistics

Table 2. Descriptive Statistics of the Study.

	N	Mean	Std. Deviation
Gender	285	1.59	0.493
Education	298	4.85	1.336
EnvImp1	290	1.97	0.174
EnvImp2	296	3.56	0.983
EnvImp3	296	3.50	1.173
EnvImp4	298	3.74	0.993
EnvImp5	298	3.10	1.163
EnvImp6	298	4.08	0.956
EnvImp7	298	3.35	1.094
EnvImp8	298	2.70	1.159
EnvImp9	298	2.71	1.278
EnvImp10	297	3.22	1.181
EnvImp11	297	2.77	1.349
EnvImp12	296	3.77	1.123
EnvImp13	296	3.47	1.015
EnvImp14	297	3.75	1.048
EnvImp15	297	3.74	0.953
EnvImp16	296	3.31	1.101
EnvImp17	297	3.58	1.082
EnvImp18	297	3.84	1.012
EnvImp19	297	3.73	1.083
EnvImp20	297	3.76	1.077
EnvImp21	295	3.64	1.130
EnvImp22	295	2.57	1.116
EIG1	294	4.16	0.985
EIG2	295	4.01	0.933
EIG3	295	4.03	0.976
EIG4	295	3.97	0.947
EIG5	295	3.75	1.068
EIG6	295	3.86	1.142
EIG7	295	3.54	1.277
EIG8	294	3.56	1.002
EIG9	295	3.15	1.542
EIG10	295	3.81	1.189
EIG11	294	3.94	1.064
EIG12	294	3.05	1.226
EIG13	295	3.99	1.103
EIG14	295	4.07	1.018
EIG15	295	3.66	1.044
EIG16	295	3.95	0.952
EIG17	295	3.65	1.227
EIG18	294	3.92	1.132
EIG19	295	3.96	1.033
EIG20	295	3.77	1.119
EIG21	295	3.95	1.066
EIG22	295	4.01	1.058
EIG23	295	3.15	1.329
IMPU1	287	1.72	0.590
IMPU2	297	1.71	0.454
IMPU3	297	1.58	0.495
IMPU4	297	1.76	0.429
IMPU5	297	1.65	0.478
IMPU6	297	1.70	0.460
IMPU7	297	1.67	0.470
IMPU8	297	1.52	0.501
IMPU9	297	1.49	0.501
IMPU10	297	1.71	0.456
RIA1	282	1.83	0.380
RIA2	295	1.65	0.478
RIA3	295	1.92	0.279
RIA4	295	1.88	0.320
RIA5	295	1.53	0.500
RIA6	295	1.39	0.489
RIA7	295	1.31	0.463
RIA8	295	1.45	0.499
RIA9	295	1.63	0.483
RIA10	295	1.69	0.464
RIA11	294	1.52	0.500
RIA12	295	1.84	0.363
RIA13	295	1.53	0.500
RIA14	295	1.45	0.498
RIA15	295	1.36	0.481
RIA16	295	1.51	0.501
RIA17	295	1.78	0.413
RIA18	295	1.82	0.387
Eco1	278	1.68	0.510
Eco2	286	1.89	0.311
Eco3	286	1.88	0.320
Eco4	273	1.56	0.497
SusFut1	286	1.95	0.223
SusFut2	285	1.35	0.477

describes the descriptive statistics of this study. Mean and standard deviation was computed for all the 79 observable variables as well as the demographic variables, education and gender. The first question of tourism impact awareness enquired respondents to indicate whether they felt that the tourism industry impacted the environment in Fiji (TIA 1). After this question, respondents were provided with nine negative impacts of tourism on the environment (Supplementary Materials). The respondents were re-questioned whether they felt that there are negative impacts on the environment caused by tourism.

Table 3. Frequency Table for TIA 1.

		Frequency	Valid Percent
Valid	No	101	35.2
	Yes	165	57.5
	No than Yes	21	7.3
	Total	287	100.0
Missing	999	11
Total		298

describes these responses.

An amount of 33.9 percent of respondents indicated that they did not feel that the tourism industry had any negative impacts on the environment. A total of 55.4 percent agreed and 7 percent of respondents agreed after reading the nine major environmental impacts of tourism. The stat to note here is that 33.9 percent of respondents did not feel that there were any negative impacts of tourism. This is slightly above one-third of the respondents.

Table 4. Frequency Table for TIA 8.

		Frequency	Valid Percent
Valid	No	144	48.5
	Yes	153	51.5
	Total	297	100.0
Missing	999	1
Total		298

describes the frequency table for “visual pollution” as a negative impact of tourism (TIA 8).

Table 4 shows that almost half the respondents (48.3%) do not believe that visual pollution is a negative impact on tourism.

Table 5. Frequency Table for TIA 9.

		Frequency	Valid Percent
Valid	No	151	50.8
	Yes	146	49.2
	Total	297	100.0
Missing	999	1
Total		298

shows the frequency table for “trampling” as a negative impact of tourism (TIA 9).

Table 5 shows that about 51% of the respondents did not believe that trampling negatively affects tourism. Around 68% of the respondents agreed with the other seven negative impacts while approximately 32% disagreed. This stat validates the 33.9% (Table 3) of the respondents who felt that there are no negative environmental impacts of tourism.

Table 6. Frequency Table for RIA 1.

		Frequency	Valid Percent
Valid	No	49	17.4
	Yes	233	82.6
	Total	282	100.0
Missing	No response	16
Total		298

shows the frequency table for respondents who agreed that there was a lack of awareness of the negative impacts of tourism in Fiji (RIA 1).

Table 6 shows that 78.2% of respondents believe that there is a lack of awareness of the negative impacts of tourism in Fiji.

Table 7. Frequency Table for SF2.

		Frequency	Valid Percent
Valid	No	186	65.3
	Yes	99	34.7
	Total	285	100.0
Missing	No Response	13
Total		298

shows the frequency table for respondents who indicate that the economic benefits of tourism outweighs its negative impact on the environment (SF2).

Table 7 shows that 62.4% of respondents do not believe that the economic benefits of tourism outweigh its negative impacts on the environment. However, it is important to note that 33.2% believe that the economic benefits of tourism outweigh its negative impact on the environment.

3.3. SEM Results

Covariance in structural equation modeling provides the strength of correlations between the observed and latent variables. In this study, we seek to investigate the relationship between the environmental and economic pillars of tourism sustainability. Many variables are related to these two pillars, but it has been narrowed down using prior research. Local environment impact (LEI), global environment impact (GEI) are latent variables for the environment pillar of the sustainability model, while tourism impact awareness (TIA), reducing impact awareness (RIA), and sustainable future (SF) are recognized as the latent variables for the economic pillar. The goodness of fit for the model meets all the standards set by Bagozzi and Yi [115] and Steiger [116]. Covariance has been performed to observe the relationship between the five latent variables (LEI, GEI, TIA, RIA, and SF).

Figure 4 displays the initial model which had 22 observable variables for local environment impact (LEI), 23 observable variables for global environment impact (GEI), 18 observable variables reducing impact awareness (RIA), 10 observable variables for tourism impact awareness (IMPU), and 6 observable variables for sustainable future (SF).

Figure 5 depicts the final model of the study. The final model indicates that only one variable describes the LEI latent variable (carbon dioxide emissions (CO₂ emissions)). The final model also indicates that eight variables describe the GEI latent variable: pollution (unspecified), climate change, species extinction and loss of biodiversity, carbon dioxide emissions (CO₂ emissions), overuse and depletion of natural resources, extreme weather, habitat destruction, and emissions from cars, trucks, and other land transport. One observable variable describes the RIA latent variable (buy and use fewer plastic bottles). One variable also describes the SF latent variable (government and resort and hotel owners should do more to reduce the impact of tourism on the environment). Therefore, from the 79 observable variables and five latent variables tested, ten observable variables describe only four latent variables. As Padin’s TBL sustainable tourism planning model suggests, there should be an interdependent relationship between all pillars. For this study, there is no relationship between the latent variables of the environment and economic pillars. These results address our first research question, which is that residents are unaware of tourism impacts and there are no relationships between the latent variables of environment and economic pillars which indicate an absence of sustainability. Correlations between the latent variables indicate a moderate negative relationship between TIA and SF and RIA and SF. A moderate positive correlation exists between LEI and GEI. The study confirms just one hypothesis out of ten. The only moderately positive relationship we find is between the LEI and GEI latent variables. These correlations indicate that the more the residents are aware of the negative impacts of tourism, the less they believe that there will be a sustainable future, and the more the residents are aware of reducing their impact, the less they believe in a sustainable future. These findings are contrary to the findings of King et al. [117], where results suggested that residents from Fiji who were dependent on the tourism industry could make a clear distinction between the negative and positive impacts of tourism, and their awareness of the negative impacts do not lead to opposition of the industry. Lepp [118] found that the less economically developed the country, the more positive opportunities by tourism are perceived. Fiji also needs to move away from its generic form of awareness to specific issue awareness to create a real positive change in the behavior of its people. These results address the second research question of this study, which was to determine the relationships between the latent variables of the environment and economic pillars.

The fit indices of the model indicate SRMR of 0.075 (0.05 < SRMR ≤ 0.10), NNFI of 0.91 (0.95 ≤ NNFI < 0.97), CFI of 0.91 (0.95 ≤ CFI < 0.97), and RMSEA of 0.063 (0.05 < RMSEA ≤ 0.08. All these fit indices meet the requirements stated by Schermelleh-Engel et al. [110] except NNFI, which is very close to the minimum requirement. The fit indices indicate that this model is an acceptable fit. The reliability test reveals Cronbach’s Alpha of 0.933, which suggests that data is internally consistent and reliable.

Table 8. Average Variance Extracted for Latent Variables.

Latent Variables	Average Variance Extracted (AVE)
Local Environment Impact (LEI)	0.57
Global Environment Impact (GEI)	0.52
Reducing Impact Awareness (RIA)	0.54
Sustainable Future (SF)	0.55

Source: Authors Calculation.

and

Table 9. Discriminant Validity.

Latent Variables	Local Environment Impact	Global Environment Impact	Reducing Impact Awareness	Sustainable Future
Local Environment Impact	0.76
Global Environment Impact	0.64	0.72
Reducing Impact Awareness	0.10	0.02	0.73
Sustainable Future	−0.01	−0.07	−0.31	0.74

describe the convergent validity and discriminant validity, respectively.

The average variance extracted (AVE) is 0.58 for LEI, 0.53 for GEI, 0.54 for RIA, and 0.55 for SF. The AVE for the three latent variables is above 0.5, meaning that the latent variables have convergent validity.

Table 9 describes the square root of AVE and the correlations between the latent variables. The square root of AVE is higher than the correlations of the latent variables, indicating that discriminant validity exists.

4. Discussion

Residents are one of the main stakeholders in tourism development and their support plays a key role in the sustainability of the industry [9,10,11]. Resident perceptions of the impact of tourism are also important in tourism development [12,13]. In this study, we use the social exchange theory [26] to interpret the results to understand the resident perceptions of the economic and environmental impacts of tourism.

The final SEM model indicates a massive gap in awareness of the negative impacts of tourism in Fiji. This is supported by the descriptive statistics where 33.9% of respondents did not believe that tourism has any negative impacts on our environment. This addresses our first research question concluding that knowledge among Fijians about the negative impacts of tourism and those that lead to sustainability is limited. This finding is supported by the research conducted by Graci and Vliet [55] in Savusavu, Fiji on tourism stakeholders. This finding is, however, inconsistent with other similar studies conducted in SIDS such as Mauritius [21,22] and Cape Verde [23], where residents recognised both the positive and negative impacts of tourism. The final SEM Model also indicates that there are no relationships between the latent variables of the environment and economic pillars. In fact, interdependency is vital for sustainable tourism planning, as per Padin [24]. The TBL model asserts that stakeholders, including residents, show concern for the tourism industry’s ecological economics and social aspects. However, this is not the case for Fiji, and therefore, the focus should be on socio-ecological and ecological-economic planning efficiency. Awareness will act as the stepping stone for socio-ecological and ecological-economic planning efficiencies. There are three relationships between the observable variables but they are all with the respective economic and environmental pillars. The first relationship is a moderate positive relationship between LEI and GEI. This relationship is understandable as the local environmental impacts are perceived as global impacts and vice-versa. The second relationship is a moderate negative relationship between TIA and SF. This relationship means that the more the residents are aware of the negative impacts of tourism, the less they perceive a sustainable future. This can also be phrased as residents perceive a sustainable future because they are not fully aware of the negative impacts of tourism. This relationship further sheds light on the need for awareness to residents in Fiji. The third relationship is a moderate negative relationship between RIA and SF. This relationship indicates that the less the residents are aware of how to reduce tourism impacts, the more they perceive a sustainable future. This once again validates the notion of lack of awareness. When residents are unaware of the negative impacts of tourism, they will not realise the need to reduce that impact and therefore will perceive that there is a sustainable future. Observable variables indicate that existing awareness, despite the lack of it, is generic and should be specific in nature in order for residents to change behavior. These relationships address our second research question.

There are two key findings for this study. Firstly, for a destination reliant on the tourism industry, the negative impacts of the very industry are limited in residents. Secondly, the correlation of latent variables also indicates that with greater awareness of the negative effects of tourism and greater awareness in reducing individual impact, residents are less likely to believe that they have a sustainable future. This means that the only reason why residents currently perceive a sustainable future is because of their limited and lack of awareness of the negative impacts of tourism and subsequently on how to reduce tourism impacts. Thus, extensive awareness is vital for Fiji, with awareness campaigns that focus on the negative impacts of tourism and specific behaviors for mitigating them. This is also indicated in the descriptive statistics where 78.2% of respondents agree that there is a lack of awareness of the negative impacts of tourism. The reasoning for such a neglected outlook on the environment can be attributed to the over-reliance and dependence on tourism for economic benefits as suggested by Puczkó and Rátz [27], Emilsson and Hjelm [119], Luck [50], Lewis-Cameron and Roberts [51], Littau et al. [120], Niles and Baldacchino [53], Bruzzi et al. [121], and Boukas and Ziakas [52].

The study contributes to the literature on resident perceptions of tourism impacts by demonstrating that there is a general lack of awareness of the negative impacts of tourism in Fiji. The results of this study on the lack of awareness extend to the educated population of Fiji. Notably, similar findings were reported earlier by Graci and Vliet [55] on the lack of awareness of the negative impacts of tourism by tourism stakeholders in Savusavu, Fiji. As stated in the above paragraph, the reason for the lack of awareness may be the dependence on tourism for economic benefits [18,27,50,51,52,53,120]. This raises questions on how tourism is presented in the entire educational system in Fiji.

5. Conclusions

There are several studies that explore residents’ perceptions towards the negative impacts of tourism, tourism development, and related topics; however, this is the first study that studies an educated population. The results of the study indicate a lack of awareness of the negative impacts of tourism and allow policymakers to address the specific issues identified. The 2017–2021 National Development Plan for Fiji includes a policy to mainstream sustainable tourism operations and strategizes strengthening enforcement of the Environment Act and Environment Impact Assessment, while also focusing on strengthening conservation of biodiversity for sustainable tourism. The results of our study, however, indicate a lack of awareness of the negative impacts of tourism and this may be due to the economic benefits of the industry. However, it is vital for residents to be aware of the negative impacts associated with tourism for holistic sustainable development of the industry. It is vital for residents to act as watch dogs, question and raise issues where developments create environmental issues. This is only possible if residents acknowledge and are aware of the negative issues of the industry. Thus, this study recommends the following based on the need for awareness and the lack of independence between the environment and economic pillars of the TBL model using social exchange theory [26].

• Thorough Adaption of Sustainability in Education:

As shown by the educated residents’ lack of awareness of the negative impacts of tourism, this study recommends that sustainability should be incorporated into the education system from primary and secondary to tertiary education. There is a need for the syllabus to project the implications of tourism, especially on the environment, as recommended by Graci and Vliet [55], to increase stakeholder education and participation in tourism-related decisions.

2.

Awareness Campaigns Targeting Specific Issues:

As indicated by the final model of the study where most LEI and GEI variables were generic in nature, there is a need for awareness to be specific. As recommended by Graci and Vliet [55] on stakeholder education, awareness campaigns in Fiji should focus on the negative impacts of tourism as almost all Fijians do not deem tourism as having any impact on the environment. That being said, campaigns should focus on specific issues rather than generic ones as it is found that most people chose generic issues over specific issues, which creates the issue that Fijians tend to know what to do but not how to do. The final model of the study shows more generic observable variables rather than those specified.

3.

Establishment of Uncompromising Sustainable Policies and Acts:

This is recommended by the final model of the study, where residents believe that the government and hotels and resorts should do more to reduce the impact of tourism on the environment. Old policies and acts towards sustainability become redundant when tourist numbers are significantly increasing. Therefore, uncompromising sustainable policies and acts should be enacted in the face of growing tourist numbers as it creates greater pressure on the Fijian environment. The inclusion of eco-costs in the financial statements of tourism stakeholders such as hotels, resorts, tour operators, etc., could be the dream start towards a sustainable future for Fiji.

4.

Sustainable Advisory Council (SDC):

This resident view also recommends that the government and hotels and resorts should do more to reduce the impact of tourism on the environment. Therefore, this study proposes an advisory council for Fiji that oversees development plans whose primary objective is sustainability in tourism developments. Such councils usually comprise of scholars and persons with extensive experience in sustainability, economics, accounting, environment, biology, and other relevant areas. Graci and Vliet [55] suggest similarly and recommend appointing an environment coordinator. The government should also scrap government policies such as applying for jobs in government departments in hard copies.

5.

Ecotourism

Ecotourism is a small growing segment in Fiji but is largely unknown by Fiji residents. The promotion of this segment locally and even providing funding for ecotourism attractions will create awareness to residents and provide them with opportunities to offer unique experiences to tourists.

There are several limitations to this study. Firstly, such research is limited to Fiji and the theoretical framework was based on research that has been conducted in other countries. Therefore, further research in this area should be conducted in Fiji. Secondly, this research used a non-random sample as it was practical because of the study on the educated residents. However, this may not have been an accurate representation of the Fiji population and therefore a random sampling study may enhance this issue in future research. The contributions of this study also present areas for future research where SIDS reliant on tourism can be studied to ascertain whether the findings are consistent with them or whether it is only specific to Fiji. An extension of this study could also be to study the social impact perceptions of tourism in Fiji and other SIDS.