sustainability

Article Wildlife Conservation through Economically Responsible Ecotourist: The Mediator Roles of Attitude between Anticipated Emotion and Intention to Stay in Local Homestays

Hayati Ibrahim 1,2 , Manohar Mariapan 1,*, Evelyn Lim Ai Lin 1 and Sheena Bidin 1

1 Faculty Forestry and Environment, University Putra Malaysia, Seri Kembangan 43400, Malaysia; [email protected] (H.I.); [email protected] (E.L.A.L.); [email protected] (S.B.) 2 Department of and Hospitality, Polytechnic Sultan Idris Shah, Sungai Ayer Tawar 45100, Malaysia * Correspondence: [email protected]

Abstract: If responsible ecotourists stay in a local , this will benefit local people economically and lead to improved wildlife conservation. This study aims to examine the mediator roles of attitudes between anticipated emotion and intention. It was conducted in Penang National Park, Malaysia, and a stratified sampling method was used for collecting the data. In all, 320 sets of questionnaires were analysed using the SPSS Amos 24.0 Statistical Software Package to test the Structural Equation Modelling. The findings show that economically responsible ecotourist attitudes to staying in local homestays for wildlife conservation partially mediate the relationship between anticipated emotion and intention to stay in a local homestay for wildlife conservation. This study suggests that players   in the industry should incorporate emotional elements in their marketing strategies to promote local homestays to responsible ecotourists, which would benefit local economies. Citation: Ibrahim, H.; Mariapan, M.; Lin, E.L.A.; Bidin, S. Wildlife Keywords: wildlife conservation; economically responsible ecotourists; anticipated emotion; attitude; Conservation through Economically intention; mediator Responsible Ecotourist: The Mediator Roles of Attitude between Anticipated Emotion and Intention to Stay in Local Homestays. Sustainability 2021, 13, 9273. 1. Introduction https://doi.org/10.3390/su13169273 According to a 2020 World Wildlife Fund (WWF) report [1], wildlife populations have declined by 68% since 1970 due to their over-consumption by poor local people living in Academic Editor: Reuven Yosef or near national parks. According to Duffy, St John, Büscher and Brockington [2], poverty is the main reason for illegal wildlife hunting by locals, who then sell the hunted wildlife Received: 16 July 2021 at high prices as a source of income. CITES, the of International Trade in Accepted: 12 August 2021 Endangered Species of Wild Fauna and Flora, reports that international wildlife trade is Published: 18 August 2021 estimated to be worth billions of dollars per year, affecting hundreds of millions of animal and plant specimens [3,4]. It is important to alleviate poverty among local people to save Publisher’s Note: MDPI stays neutral wildlife. Increased incomes will reduce the local dependence on wildlife. Ecotourism is with regard to jurisdictional claims in defined by the International Ecotourism Society (TIES) as “responsible to natural published maps and institutional affil- settings that conserves the environment and enhances the well-being of local people” [5]. iations. TIES is an example of a non-profit organisation devoted to aiding businesses by imple- menting ecotourism practices and fostering long-term community development. Poverty is the main cause of illegal wildlife hunting among local communities, causing widespread wildlife extinction, so ecotourist groups have introduced local ecotourism plans [6,7] to Copyright: © 2021 by the authors. develop the local economy to eliminate the local over-dependence on wildlife. Through Licensee MDPI, Basel, Switzerland. local ecotourism, communities have been given opportunities to run homestay businesses This article is an open access article to obtain economic benefits from the resulting profits [8]. Many homestays have been distributed under the terms and established by locals in or near national parks to provide accommodation facilities and conditions of the Creative Commons experiences to ecotourists [9]. However, it was found that tourists prefer [8] to stay in Attribution (CC BY) license (https:// or located in cities [10,11] rather than choosing local homestays as their creativecommons.org/licenses/by/ accommodation [12–15]. As a result, local homestay businesses are unprofitable 4.0/).

Sustainability 2021, 13, 9273. https://doi.org/10.3390/su13169273 https://www.mdpi.com/journal/sustainability Sustainability 2021, 13, 9273 2 of 16

and this sector is stagnant [16,17]. Staying in a local homestay for wildlife conservation is deemed as responsible behaviour in this study. Ecotourists are those who travel in a natural area and spend a predetermined number of days developing the local economy [18,19]. They are responsible people who care about maintaining and protecting the natural envi- ronment [20,21]. Ecotourists display responsible economic behaviour as they are willing to do everything that others expect them to do, even when confronted with challenging situations [22]. They will stay in a local homestay for the purposes of wildlife conservation. However, to what extent do they intend to stay in local homestays for wildlife conservation during their visits to a national park? To answer this question, it is vital to understand ecotourists’ responsible economic behaviour in relation to wildlife conservation so an effective marketing strategy for staying in local homestays can be implemented. As tourists and wildlife have a strong emotional connection, the present research study focuses on the relationship between anticipated emotion, attitude and intention.

2. Literature Review and Research Hypotheses Ecotourism is an economic tool for wildlife conservation [23,24]. Previous studies involving wildlife conservation through ecotourism highlighted conservation learning that focused on captive wildlife, such as in zoos or aquariums [25–28], and conservation interpretation [29–34]. According to Myers [35], tourists are agents in wildlife conservation. They are responsible people who care about maintaining and protecting wildlife [20,21]. Responsible behaviour is the act of doing what should be done in any given situation, even if it is difficult, unpleasant or unclear [36]. There are three main types of responsible behaviour, namely environmentally responsible behaviour, socially responsible behaviour and economically responsible behaviour [37]. However, scholars of tourist responsible behavioural research tend to study environmentally responsible behaviour [38–40] and socially responsible behaviour [41,42]. For example, Xu, Kim, Liang and Ryu [43] conducted a case study of Nansha Wetland Park in China to examine the links between tourist involvement, experience and environmentally responsible behaviour. He, Hu, Swanson, Su and Chen [44] conducted a study of tourists’ environmentally responsible tourism behaviour and perceptions of destinations and quality. Su and Swanson [41] analysed the effect of destination social responsibility on tourist behaviour. Luo, Tang, Jiang and Su [42] investigated socially responsible tourists’ awareness of environmentally responsible behaviour. In tourism economics research, studies have proven that tourists are willing to pay for wildlife conservation [45–52]; however, no studies have been undertaken on tourists’ economically responsible behaviour. In the present research, ecotourists staying in local homestays for wildlife conservation is referred to as responsible economic behaviour. The Theory of Planned Behaviour (TPB) was developed by Ajzen in 1991 for studying the human decision-making process [53] and it is widely used in conservation behavioural research [54–59]. It consists of three important components, namely attitude, subjective norm and perceived behavioural control, which are used as important determinants in understanding human behaviours [53]. In psychological terms, attitude refers to a person’s mental and emotional state [60]. It can enable a better understanding of how humans perceive the world and how they behave [61]. It involves an overall evaluation of attitude objects, e.g., favour or disfavour, or like or dislike [62,63]. In wildlife value orientation [64], a beneficial interaction between humans and wildlife exists when humans have a posi- tive attitude towards wildlife conservation [65,66]. Previous studies indicate that local communities [67–70], stakeholders [71–75] and teachers [76] have positive attitudes to- wards wildlife conservation. However, ecotourist attitudes towards wildlife conservation remain unclear. According to Newhouse [77], ecotourist attitudes have major implications for wildlife conservation. Based on Ajzen [53] in the TPB, attitudes are antecedents of intention. Intention is the individual willingness to undertake a particular behaviour, so it has a direct relationship with behaviour [53]. The TPB explains that the more an attitude relates to a behaviour, the greater the intention to perform the behaviour [53]. In tourism research, several studies have confirmed that ecotourist attitudes have a direct effect on Sustainability 2021, 13, 9273 3 of 16

intention, as shown by research conducted by Clark Mulgrew, Kannis–Dymand, Schaffer and Hoberg [78]; Phu, Hai, Yen and Son [79]; Meng and Choi [80]; and Gstaettner, Rodger and Lee [81]. Based on the arguments above, the present study proposed the first research hypothesis as follows:

Hypothesis 1 (H1). Attitude to staying in a local homestay for wildlife conservation has a significant direct effect on intention to stay at a local homestay for wildlife conservation.

The importance of emotions in the decision-making process is often overlooked by scholars because they believe rational thinking is more meaningful. They regard emo- tions as irrational phenomena that can lead to incorrect thinking. However, current ideas emphasise the significance of emotions in decision making. Loewenstein and Lerner [82] distinguish between two sorts of emotions encountered during decision-making: antici- pated emotions and immediate emotions. Emotions that are anticipated (or predicted) are not experienced immediately, but are anticipated as a result of the rewards or losses arising from a decision. The two effects that exist in anticipated emotion are self-consistency (e.g., pride and guilt) and basic hedonic (e.g., pleasure and frustration). Self-consistency shows a long-term emotional effect while basic hedonic is more short-term [83]. Bagozzi, Belanche, Casaló and Flavián [84] mentioned that anticipated emotion plays an important role in purchasing decision making. Emotion is widely used by major companies and organisations in marketing strategies to influence buyers’ emotions by placing emotional taglines in their marketing adverts. Some examples are the ‘Choose Happiness’ tagline, used in Coca Cola ads; the ‘Stop Climate Changes Before It Changes You’ tagline by the World Wildlife Fund, which adds the element of fear; the ‘30+ Years’ Experience Success- fully Representing Accident Victims’ tagline by John Rapillo, a law office that uses the element of trust; the ‘Help Me Read This’ tagline by Children Of The World, which features a sad element; or ‘You’re Not You When You’re Hungry’ for the Snickers bar (Mars), which uses an element of humour by displaying an awesome picture of Godzilla, except when he is hungry. Surprisingly, adverts that include emotional elements are generally successful in influencing users/customers to buy products or services. In tourism research, studies also show that tourists have a strong emotional connection with wildlife through their wildlife view experience [85–87]. This research assesses how tourists’ anticipated emotions in relation to wildlife affect their decisions to stay in local homestays for wildlife conservation. In the TPB, scholars tend to relate environmental research to norms [88–92]. However, in their study, Onwezen, Antonides and Bartels [93] suggest that exploring anticipated emo- tion in environmental research is critical. Moreover, a meta-analysis conducted by Rivis, Sheeran, and Armitage [94] mentioned that anticipated emotion can increase the variance in explaining attitude and intention in the TPB. In TPB research, previous studies by Kim, Njite and Hancer [95] and Londono, Davies and Elms [96] have shown that anticipated emotion has a significant direct effect on attitudes to behaviour and intention. Based on the arguments above, the present study proposed further research hypotheses as follows:

Hypothesis 2 (H2). Anticipated emotion has a significant direct effect on attitude to staying in a local homestay for wildlife conservation.

Hypothesis 3 (H3). Anticipated emotion has a significant direct effect on intention to stay in a local homestay for wildlife conservation.

Mediation analyses are often used in social psychology [97] to investigate the underly- ing mechanism or process by which one variable influences another via a mediator variable in order to better understand a known relationship. When no evident direct relationship ex- ists between an independent variable and a dependent variable, mediation analysis might enable a better understanding of the relationship [98]. In tourism behavioural research, attitude has been identified as functioning in a mediator role [99]. Studies by Rahman, Rana, Hoque and Rahman [100] showed that tourists’ attitude has the effect of mediating Sustainability 2021, 13, x FOR PEER REVIEW 4 of 16

Mediation analyses are often used in social psychology [97] to investigate the under- lying mechanism or process by which one variable influences another via a mediator var- iable in order to better understand a known relationship. When no evident direct relation- ship exists between an independent variable and a dependent variable, mediation analy- Sustainability 2021, 13, 9273 sis might enable a better understanding of the relationship [98]. In tourism behavioural4 of 16 research, attitude has been identified as functioning in a mediator role [99]. Studies by Rahman, Rana, Hoque and Rahman [100] showed that tourists’ attitude has the effect of mediating between service and satisfaction. Mehmood, Liang and Gu [101] determined thatbetween attitudes service mediate and satisfaction. the relationship Mehmood, between Liang user-generated and Gu [101] content determined and thattravel attitudes inten- tions.mediate Studies the relationshipconducted by between Gilchrist, user-generated Masser, Horsley content and Ditto and travel [102]; intentions.and Taylor, Studies Ishida andconducted Donovan by [103], Gilchrist, indicate Masser, that attitude Horsley mediates and Ditto the [102 relationship]; and Taylor, between Ishida anticipated and Dono- emotionvan [103 ],and indicate intention. that attitudeThe proposed mediates research the relationship framework, between illustrating anticipated the relationship emotion and betweenintention. attitude, The proposed anticipated research emotion framework, and intent illustratingion, is shown the relationship in Figure between 1. Based attitude, on the argumentsanticipated above, emotion the andpresent intention, study isproposed shown ina further Figure1 research. Based onhypothesis the arguments as follows: above, the present study proposed a further research hypothesis as follows: Hypothesis 4 (H4). Attitude to staying at a local homestay for wildlife conservation mediates the relationshipHypothesis between 4 (H4). anticipatedAttitude toem stayingotion and at intention a local homestay to stay at for a local wildlife homestay conservation for wildlife mediates con- servation.the relationship between anticipated emotion and intention to stay at a local homestay for wildlife conservation.

Figure 1. The proposed research framework. Figure 1. The proposed research framework. 3. Research Methodology 3.3.1. Research Target Area Methodology 3.1. TargetIn terms Area of richness of biodiversity, Malaysia is one of the top 17 countries, with an estimatedIn terms of 12,500 richness plant ofspecies, biodiversity, 306 mammal Malaysia species, is one of 742 the bird top species 17 countries, and 547 with reptile an estimatedspecies [104 12,500]. As plant a protected species, area 306 gazettedmammal under species, Malaysia 742 bird National species and Parks 547 [105 reptile], Penang spe- ciesNational [104]. ParkAs a (PNP)protected functions area gazetted to protect under and conserve Malaysia wildlife. National PNP Parks is home [105], to Penang 417 species Na- tionalof flora Park and (PNP) 143 species functions of fauna, to protect including and co numerousnserve wildlife. rare and PNP endangered is home to species.417 species It is ◦ 0 00 ◦ 0 00 oflocated flora and at 5 14326 53 speciesN 100 of 11fauna,36 Eincluding in Peninsular numerous Malaysia rare and and has endangered an area of 2563species. hectares It is located(9.9 sq mi).at 5°26 In this′53″N study, 100°11 PNP′36″ wasE in selected Peninsular as the Malaysia target area and to has conduct an area the of research, 2,563 hectares as it is (9.9a developed sq mi). In eco-tourismthis study, PNP area was that selected receives as high the numbers target area of domesticto conduct and the foreign research, tourists. as it isAmong a developed the tourism eco-tourism activities areaat that PNP receives are visiting high numbers the interpretation of domestic centre, and foreign camping tour- at ists.Keranchut AmongBeach the tourism and Teluk activities Kampi; at PNP wildlife are observation,visiting the interpretation e.g., squirrels, centre, beavers, camping moles, atants Keranchut and pythons; Beach andand variousTeluk Kampi; bird species wildlife such observation, as eagles; walkinge.g., squirrels, at the beavers, Canopy moles, Bridge; antsdoing and water pythons; activities; and various picnicking; bird fishing; species jungle such as trekking; eagles; mountainwalking at climbing; the Canopy and Bridge; visiting the lighthouse, the Turtle Conservation Centre and Lake Meromiktik. As with national parks in other countries, PNP also faces its own challenges in reviving the local community economy for wildlife conservation [106,107]. Figure2 depicts a map of Penang National Park, the study area for this research. Sustainability 2021, 13, x FOR PEER REVIEW 5 of 16

doing water activities; picnicking; fishing; jungle trekking; mountain climbing; and visit- ing the lighthouse, the Turtle Conservation Centre and Lake Meromiktik. As with national Sustainability 2021, 13, 9273 parks in other countries, PNP also faces its own challenges in reviving the local commu-5 of 16 nity economy for wildlife conservation [106,107]. Figure 2 depicts a map of Penang Na- tional Park, the study area for this research.

FigureFigure 2.2. MapMap ofof PenangPenang NationalNational Park,Park, Malaysia.Malaysia.

3.2.3.2. MethodMethod InIn thisthis study,study, thethe non-experimentalnon-experimental quantitativequantitative researchresearch methodmethod waswas usedused [[108].108]. AlthoughAlthough this this method method appears appears highly highly flexible, flexible the, the results results obtained obtained through through the the quantitative quantita- researchtive research procedure procedure are extremely are extremely reliable reliable because because data is collected, data is collected, processed processed and presented and inpresented numbers, in which numbers, are not which deceptive. are not Moreover,deceptive. inMoreover, non-experimental in non-experimental research, a predictor research, variablea predictor or subjects variable cannot or subjects be manipulated, cannot be mani provingpulated, that proving this method that this is highly method systematic. is highly Non-experimentalsystematic. Non-experimental quantitative researchquantitative is often rese usedarch becauseis often it used allows because researchers it allows to gain re- asearchers better understanding to gain a better of socialunderstanding science through of social questionnaires, science through polls questionnaires, and survey datapolls analysis.and survey Where data the analysis. data is Where easily communicated the data is easily using communicated statistics and using figures, statistics this method and fig- is performedures, this method to study is theperformed relationships to study between the re variableslationships in between an existing variables phenomenon in an existing [109]. phenomenon [109]. 3.3. Sampling 3.3. SamplingTourists formed the sample in this study, and they were selected using the stratified sampling method [110]. Initially, tourists who came to Penang National Park were asked Tourists formed the sample in this study, and they were selected using the stratified whether they had checked in to local accommodation or were staying overnight during their sampling method [110]. Initially, tourists who came to Penang National Park were asked visit to Penang National Park. Only tourists who had checked in to local accommodation or whether they had checked in to local accommodation or were staying overnight during were staying overnight were selected for the sample in this study. Secondly, only a tourist their visit to Penang National Park. Only tourists who had checked in to local accommo- who agreed to be a respondent received a set of questionnaires from the research team. The datadation collection or were was staying conducted overnight carefully were face selected to face for with the tourists sample inin Penang this study. National Secondly, Park andonly they a tourist were givenwho agreed a token to of be appreciation a respondent after received the questionnaire a set of questionnaires had been completed. from the A summaryresearch team. of the The sample data background collection was is shown conducte in Tabled carefully1. face to face with tourists in Penang National Park and they were given a token of appreciation after the questionnaire had been completed. A summary of the sample background is shown in Table 1. Sustainability 2021, 13, 9273 6 of 16

Table 1. Sample description.

Item Classification Sample Amounts Percentage (%) Age 18–23 127 39.7 24–29 72 22.5 30–35 60 18.8 36–41 47 14.7 Above 41 14 4.4 Gender Male 134 41.9 Female 186 58.1 Nationality Malaysian 263 82.2 Non-Malaysian 57 17.8 Status Employed 229 71.6 Unemployed 11 3.4 Pensioner 5 1.6 Student 75 23.4 Purpose Visiting Business 29 9.1 Leisure 237 74.1 Others 54 16.9

Table1 shows that tourists aged 18 to 23 years old formed the largest group of respondents, 39.7% of the total, followed by respondents aged from 24 to 29 (22.5%) and 30 to 35 (18.8%). However, the smallest group was tourists aged above 41, which was only 4.4% of the total. Table1 also shows that females comprised the largest group of respondents in terms of gender, with a total of 58.1%, while the rest were male. Respondents from the Malaysian group were found to be the largest in terms of nationality, with 82.2% of the total; the rest were from the non-Malaysian group. The table shows that tourists with employed status were the largest group of respondents in this field, at 71.6%, while the smallest group comprised pensioners, with 1.6% of the total. Tourists visiting for leisure comprised the largest group of respondents in terms of the purpose of visiting, with 74.1% of the total; followed by the ‘other purposes’ group, with 16.9%; and business purposes, with 9.1% of the total.

3.4. Measurement Since this study aimed to predict tourist intention to stay in a local homestay for wildlife conservation, the survey method was deemed to be the most suitable. The most appropriate instrument used to survey tourist intentions is a questionnaire form [111]. The questionnaire consisted of two parts. The first part related to the tourist background, and respondents were required to answer questions regarding their age, gender, nationality, working status and their purpose of visiting PNP. The second part of the questionnaire contained three measurements, namely anticipated emotion (four items), attitude (four items) and intention (three items). All the items were measured using a five-point Likert- type scale, from 5-strongly agree to 1-strongly disagree. All items were adapted from the literature research. The items used to measure anticipated emotion were based on Bagozzi et al. [84], such as ‘If I visit Penang National Park next time, it would be a real pleasure if I stay at a local homestay that contributes to wildlife conservation’. The items used to measure attitude and intention were based on Ajzen [112], such as ‘I would like very much to stay at a local homestay if this contributes to wildlife conservation in Penang National Park’ and ‘I intend to stay at a local homestay when visiting Penang National Park this year for wildlife conservation’. AppendixA shows the items used in the questionnaire. Two steps were involved in conducting this research. The first step was the pilot study. At this stage, 80 tourists had been selected as respondents. The internal consistency shows that the questionnaire had very high reliability, with Cronbach’s Alpha values between 0.89 and 0.94. The questionnaire had also gone through the validation process before the pilot study was conducted. The questionnaire had been checked by the supervisors to Sustainability 2021, 13, x FOR PEER REVIEW 7 of 16

Sustainability 2021, 13, 9273 7 of 16 between 0.89 and 0.94. The questionnaire had also gone through the validation process before the pilot study was conducted. The questionnaire had been checked by the super- visors to determine whether the items would achieve the appropriate measurement of the constructs.determine whetherThe second the itemsstep in would this research achieve the process appropriate was conducting measurement the ofactual the constructs. research. TheThe data second collection step in process this research took place process over was four conducting weeks from the 19 actualDecember research. 2020 to The 10 dataJan- uarycollection 2021and process was tookconducted place over during four the weeks weeken fromd. 19 Since December 20 sets 2020 were to not 10 January answered 2021and com- pletelywas conducted by the respondents, during the only weekend. 320 sets Since of questionnaires 20 sets were not were answered used for completely data analysis by out the ofrespondents, the 340 set questionnaires only 320 sets of that questionnaires had been returned were used to the for research data analysis team. out of the 340 set questionnaires that had been returned to the research team. 4. Data Analysis and Results 4. Data Analysis and Results 4.1. Measurement Modelling 4.1. Measurement Modelling In this study, the data was analysed using the SPSS Amos 24.0 Statistical Software In this study, the data was analysed using the SPSS Amos 24.0 Statistical Software Package to test the Structural Equation Modelling (SEM) [113]. SEM is widely used in so- Package to test the Structural Equation Modelling (SEM) [113]. SEM is widely used in cial science research [114] because it provides a flexible framework for constructing and social science research [114] because it provides a flexible framework for constructing analysing complicated interactions across different variables, allowing researchers to ver- and analysing complicated interactions across different variables, allowing researchers ify the validity of a theory using empirical models [115]. Its capacity to manage measure- to verify the validity of a theory using empirical models [115]. Its capacity to manage ment error, one of the most significant constraints of most studies, is perhaps its greatest measurement error, one of the most significant constraints of most studies, is perhaps its advantage [116]. SEM is a combination of factor analysis and multiple regression analysis, greatest advantage [116]. SEM is a combination of factor analysis and multiple regression and it is used to analyse the structural relationship between measured variables and latent analysis, and it is used to analyse the structural relationship between measured variables constructs [117]. Conducting SEM in data analysis involves two steps [117]. The first step and latent constructs [117]. Conducting SEM in data analysis involves two steps [117]. The is conducting a measurement of the model and the second step is conducting a structural first step is conducting a measurement of the model and the second step is conducting a equation of the model. In a measurement model, a confirmatory factor analysis (CFA) structural equation of the model. In a measurement model, a confirmatory factor analysis process(CFA) process needs needsto be conducted to be conducted initially. initially. CFA is CFA a validation is a validation process process and it and is used it is used to de- to terminedetermine thethe validity validity and and reliability reliability of a of latent a latent construct construct [117]. [117 There]. There are arethree three types types of va- of lidity:validity: construct construct validity, validity, convergent convergent validity validity and and discriminant discriminant validity. validity. The The former former is achievedachieved when when the Fitness Fitness Index Model has reached its standard. Four indicators [113] [113] are suitablesuitable for testing thethe FitnessFitness Index Index Model; Model; the the Root Root Means Means Square Square of of Error Error Approximation Approxima- tion(RMSEA) (RMSEA) (good (good if RMSEA if RMSEA < 0.08); < 0.08); the Comparativethe Comparative Fit Index Fit Index (CFI) (CFI) (good (good if CFI if CFI > 0.9); > 0.9); the theTucker- Tucker- Lewis Lewis Index Index (TLI) (good(TLI) if(good TLI> if 0.9) TLI and > 0.9) Chi Square/degreeand Chi Square/degree of freedom of (Chisq/df) freedom (Chisq/df)(good if Chisq/df (good if < Chisq/df 3.0). Figure < 3.0).3 indicates Figure that3 indicates the Fitness that Indexthe Fitness Model Index standard Model had stand- been ardachieved. had been The achieved. results of The the indicatorsresults of the show indicators that RMSEA show = that 0.05, RMSEA CFI = 0.99, = 0.05, TLI CFI = 0.99 = 0.99, and TLIChi/df = 0.99 = 1.7.and Chi/df = 1.7.

Figure 3. Result of Fitness Index Model. Figure 3. Result of Fitness Index Model. Convergent validity of a model is achieved if the Average Variance Extracted (AVE) value of the latent construct is above 0.5, the Composite Reliability (CR) value of the latent construct is above 0.6 and the factor loading of the item is above 0.6 [113]. Table2 shows that the model had a high internal consistency and reliability. The results indicate that the Sustainability 2021, 13, 9273 8 of 16

AVE of all the latent constructs are between 0.81 and 0.84. The CR values of all the latent constructs are between 0.93 and 0.95. Meanwhile, all 11 items had a high factor loading of between 0.88 and 0.94.

Table 2. Result of Convergent Validity and Composite Reliability.

Construct Item Factor Loading CR AVE AE_1 0.9 Anticipated AE_2 0.92 0.95 0.83 Emotion AE_3 0.9 AE_4 0.91 ATT_1 0.88 ATT_2 0.93 Attitude 0.95 0.84 ATT_3 0.92 ATT_4 0.94 INT_1 0.91 Intention INT_2 0.92 0.93 0.81 INT_3 0.88

When a model is free from redundant items, it means the discriminant validity is achieved. The discriminant validity is assessed by comparing the square root of AVE and the correlation coefficient of the latent constructs. It is achieved if the diagonal value with bold (the square root of AVE) is larger than the value in its row and column (correlation coefficient) [113]. Table3 shows that the discriminant validity of all the latent constructs was achieved, since the results indicate that all the square root AVE values were larger than the correlation coefficient values.

Table 3. Discriminant Validity Index Summary of the Construct.

Construct Anticipated Emotion Attitude Intention Anticipated Emotion 0.91 Attitude 0.85 0.92 Intention 0.8 0.81 0.9

In the study, the data distribution analysis was also conducted to evaluate whether the data was normally distributed. Table4 presents the results of the analysis. The results indicate that the data was normally distributed. The values of the skewness item are lower than 1.0, indicating the data was normally distributed.

Table 4. The assessment of normality distribution for items of the constructs.

Variable Min Max Skew c.r. Kurtosis c.r. INT_1 1.000 5.000 −0.001 −0.006 −0.318 −1.161 INT_2 1.000 5.000 −0.037 −0.268 −0.182 −0.666 INT_3 1.000 5.000 0.017 0.127 −0.383 −1.399 AE_1 1.000 5.000 −0.297 −2.173 −0.470 −1.717 AE_2 1.000 5.000 −0.078 −0.569 −0.679 −2.478 AE_3 1.000 5.000 −0.049 −0.361 −0.526 −1.921 AE_4 1.000 5.000 −0.108 −0.787 −0.545 −1.990 ATT_4 1.000 5.000 −0.163 −1.190 −0.603 −2.201 ATT_3 1.000 5.000 −0.073 −0.533 −0.625 −2.282 ATT_2 1.000 5.000 −0.146 −1.069 −0.622 −2.271 ATT_1 1.000 5.000 −0.046 −0.333 −0.593 −2.167

4.2. Structural Equation Modelling After the measurement modelling had been conducted, the final step implemented the structural equation modelling. In this step, the Fitness Index Model also needed to be run Sustainability 2021, 13, x FOR PEER REVIEW 9 of 16

ATT_3 1.000 5.000 −0.073 −0.533 −0.625 −2.282 ATT_2 1.000 5.000 −0.146 −1.069 −0.622 −2.271 ATT_1 1.000 5.000 −0.046 −0.333 −0.593 −2.167

4.2. Structural Equation Modelling Sustainability 2021, 13, 9273 After the measurement modelling had been conducted, the final step implemented9 of 16 the structural equation modelling. In this step, the Fitness Index Model also needed to be run structurally [117]. Figure 4 shows that the Fitness Index Model for SEM was achieved, sincestructurally the results [ 117were]. Figureas follows:4 shows RMSEA that the = 0.047, Fitness CFI Index = 0.993, Model TLI for = SEM0.991 was and achieved, ChiSq/df since = 1.692the. results were as follows: RMSEA = 0.047, CFI = 0.993, TLI = 0.991 and ChiSq/df = 1.692.

Figure 4. Fitness Index for SEM. Figure 4. Fitness Index for SEM. The direct effect results shown in Table5 indicate that the path coefficient of attitude toThe staying direct at effect a local results homestay shown for in Table wildlife 5 indicate conservation that the in path terms coefficient of intention of attitude to stay at to stayinga local at homestay a local homestay for wildlife for conservationwildlife conservation is 0.47, so in it terms is statistically of intention significant. to stay at Thus, a localHypothesis homestay H1for iswildlife supported conservation by the results. is 0.47, The so pathit is statistically coefficient ofsignificant. anticipated Thus, emotion hy- to pothesisattitude H1 to is staying supported at a localby the homestay results. forThe wildlife path coefficient conservation of anticipated is 0.85, which emotion shows thatto it attitudeis statistically to staying significant. at a local homestay Thus, Hypothesis for wildlife H2 isconservation also supported is 0.85, by the which results. shows Finally, that the it ispath statistically coefficient significant. of anticipated Thus, emotionhypothesis on intentionH2 is also to supported stay at a local by the homestay results. forFinally, wildlife conservation is 0.4 and the p-value result indicates that it is statistically significant. Thus, the path coefficient of anticipated emotion on intention to stay at a local homestay for Hypothesis H3 is also supported by the results. wildlife conservation is 0.4 and the p-value result indicates that it is statistically significant. Thus, hypothesis H3 is also supported by the results. Table 5. Path Coefficient and Its Significance.

Standardized PathTable 5. Path Coefficient Coefficient and Its Significance. Estimate p-Value Hypothesis Result StandardizedIntention Path <— Coefficient Attitude Estimate 0.47 P-Value 0.001Hypothesis Supported Result IntentionAttitude <--- <— AttitudeAnticipated_Emotion 0.47 0.85 0.001 0.001 Supported Supported Intention <— Anticipated_Emotion 0.4 0.001 Supported Attitude <--- Anticipated_Emotion 0.85 0.001 Supported Intention <--- Anticipated_Emotion 0.4 0.001 Supported Mediation analysis is prominent in psychological theory and research [118]. This studyMediation was conducted analysis is in prominent part to quantify in psychological the extent to theory which and attitude research to staying [118]. at This a local studyhomestay was conducted for wildlife in part conservation to quantify was the a extent mediating to which variable. attitude A mediating to staying variable at a local isone homestaythat illustrates for wildlife a relationship conservation between was a mediating dependent variable. and independent A mediating variables variable [118 is]. one There thatare illustrates two ways a relationship to analyse thebetween mediating dependent effect, and which independent are to determine variables the [118]. direct There and the are indirecttwo ways effects. to analyse Based the on mediating Baron and effect, Kenny, which several are stepsto determine are needed the direct to determine and the the existence of a mediator variable using the direct effect. First, there should be a correlation between an independent variable and a mediator variable; second, there should be a correlation between the mediator variable and the dependent variable; and third, if the relationship between the independent variable and the dependent variable is significant, this means the existence of a partial mediator. The results reveal a partial mediating effect of attitude to staying at a local homestay for wildlife conservation on the relationship between anticipated emotion and intention to stay at a local homestay for wildlife conservation, which is supported by the findings for Hypothesis H4. The indirect effect tests also show that there is a mediating effect of attitude to staying at a local homestay for wildlife Sustainability 2021, 13, x FOR PEER REVIEW 10 of 16

indirect effects. Based on Baron and Kenny, several steps are needed to determine the existence of a mediator variable using the direct effect. First, there should be a correlation between an independent variable and a mediator variable; second, there should be a cor- relation between the mediator variable and the dependent variable; and third, if the rela- tionship between the independent variable and the dependent variable is significant, this means the existence of a partial mediator. The results reveal a partial mediating effect of attitude to staying at a local homestay for wildlife conservation on the relationship be- Sustainability 2021, 13, 9273 tween anticipated emotion and intention to stay at a local homestay for wildlife conserva-10 of 16 tion, which is supported by the findings for hypothesis H4. The indirect effect tests also show that there is a mediating effect of attitude to staying at a local homestay for wildlife conservation between the relationship of anticipated emotion and intention to stay at a localconservation homestay for between wildlife the conservation. relationship These of anticipated results are emotion presented and intentionin Figure to 5. stayBased at aon local Baronhomestay and Kenny, for wildlife if the conservation.indirect effect These of axb

Figure 5. Indirect Effect Result. Figure 5. Indirect Effect Result. Recently, scholars have tended to confirm the result of a mediator using bootstrap- Recently, scholars have tended to confirm the result of a mediator using bootstrap- ping analysis. Bootstrapping is a non-parametric test based on resampling, with many ping analysis. Bootstrapping is a non-parametric test based on resampling, with many in- instances of replacement, e.g., 1000. Based on the bootstrapping results in Table6, the stancessignificant of replacement, results for e.g., both 1000. the directBased and on the indirect bootstrapping effects in this result studys in haveTable confirmed 6, the sig- that nificantattitude results to stayingfor both at the a localdirect homestay and indire forct wildlifeeffects in conservation this study have partially confirmed mediates that the attituderelationship to staying between at a local anticipated homestay emotionfor wildlife and conservation intention to partially stay at a mediates local homestay the re- for lationshipwildlife between conservation. anticipated emotion and intention to stay at a local homestay for wild- life conservation. Table 6. Bootstrapping Result of Mediation Analysis. Table 6. Bootstrapping Result of Mediation Analysis. Indirect Effect Direct Effect Indirect Effect Direct Effect Bootstraping result 0.394 0.42 BootstrapingBootsraping resultp-value 0.001 0.394 (significant) 0.003 0.42 (significant) BootsrapingResults P-value 0.001 (significant) Partial mediation since direct 0.003 is also(significant) significant Results Partial mediation since direct is also significant 5. Discussion and Conclusions This research examined the mediator roles of attitude towards staying in a local homestay for wildlife conservation between the relationship of anticipated emotion and intention to understand ecotourist responsible economic behaviour. The study revealed that attitude towards staying in a local homestay for wildlife conservation has a significant direct effect on intention to stay in local homestays for wildlife conservation. This result is in line with studies conducted by Clark Mulgrew, Kannis–Dymand, Schaffer and Hoberg [78]; Phu, Hai, Yen and Son [79]; Meng and Choi [80]; and Gstaettner, Rodger and Lee [81]. The study also proves that anticipated emotion can influence attitude since the results indicate that anticipated emotion has a significant direct effect on attitude towards staying in a local homestay for wildlife conservation. These results support those of previous studies by Kim, Njite and Hancer [95] and Londono, Davies and Elms [96]. The study also Sustainability 2021, 13, 9273 11 of 16

shows that anticipated emotion can highly influence intention since the results indicate that anticipated emotion has a significant direct effect on intention to stay in a local homestay for wildlife conservation, which is in line with previous studies [95,96]. The study also confirmed that attitude is a mediator between anticipated emotion and intention, since the study revealed the mediating effect of attitude to staying in a local homestay for wildlife conservation between anticipated emotion and intention to stay in a local homestay for wildlife conservation. This result is also supported by the findings of previous studies by Gilchrist, Masser, Horsley and Ditto [102] and Taylor, Ishida, and Donovan [103]. The high variance in explaining attitude and intention shows that anticipated emotion plays an important role in understanding economically responsible ecotourists’ attitudes and intentions to stay in local homestays for wildlife conservation. In practical terms, the current study has proven that a responsible ecotourist’s attitudes and intentions are influenced by his/her anticipated emotions. Therefore, it is suggested that an emotional element is considered in advertising that promotes a local homestay. This would resemble the actions of major companies and organisations, e.g., Mars, Coca Cola, and the World Wildlife Fund, which have promoted their products and services in this way. For example, players in the ecotourism industry can use narratives and storytelling strategies to market a local homestay by creating an emotional connection between tourists and wildlife. Since colours have a scientifically proven association with human emotions, stakeholders could also practise this technique in their marketing strategies. Although the influences of colours vary according to gender, stakeholders could consider the power of colour itself to influence others. For example, black and purple are related to being strong, powerful and masterful; red is arousing; blue is soft. The colour Facebook uses is blue and that of Coca-Cola is red; this is no coincidence. Word-of-mouth techniques (through testimonials, customer reviews, logos, or real customer stories) are also important in instilling trust in a tourist. Trust will eventually produce a positive emotional reaction, such as ‘If other people trust them, I should too’. Airbnb is well-known for using the simple yet strong word-of-mouth method. Since this study has determined that attitude mediates the relationship between anticipated emotion and intention, it is also suggested that players in the ecotourism industry conduct strategic planning on how to improve the attitudes of responsible ecotourists to wildlife conservation. The more positive the attitude to wildlife conservation is, the higher the chance that a responsible ecotourist will stay in a local homestay to help the local economy. An effective marketing strategy would induce responsible ecotourists to choose a local homestay rather than other accommodation. To summarize, ecotourists are particularly responsible for wildlife conservation when they are willing to stay in local homestays and pay for their accommodations to aid the local economy through changes in their attitudes and emotions. This study has some limitations due to time constraints. Although this study found that attitude and anticipated emotion greatly influence behavioural intentions, the study did not consider the effect of behavioural intentions on the actual behaviour of responsible ecotourists. According to Ajzen [53], not all intentions have a significant effect on actual behaviour. It is recommended that future researchers conduct a study of economically responsible ecotourist behaviour using the Theory of Planned Behaviour.

Author Contributions: Writing—original draft preparation, H.I.; data curation, M.M.; writing— review and editing, E.L.A.L.; and validation, S.B. All authors have read and agreed to the published version of the manuscript. Funding: This research was partially funded by University Putra Malaysia (UPM) under UPM Journal Publication Fund. Institutional Review Board Statement: Not applicable. Informed Consent Statement: Informed consent was obtained from all subjects involved in the study. Conflicts of Interest: The authors declare no conflict of interest. Sustainability 2021, 13, 9273 12 of 16

Appendix A

Table A1. Items in the questionnaire.

Construct Indicators Source Anticipated Emotion If I visit Penang National Park next time, it would be extremely AE_1 pleasureable if I stay at local homestay that contributes to wildlife conservation. If I visit Penang National Park next time, I would be extremely AE_2 frustrated if I didn’t join a local homestay that contributes to wildlife conservation. [84] If I visit Penang National Park next time, I would always be proud AE_3 to stay at a local homestay that contributes to wildlife conservation. If I visit Penang National Parksnext time, I would feel guilty not AE_4 paying for a local homestay that contributes to wildlife conservation. Attitude I would very much like to stay at local homestay if it would ATT_1 contribute to the wildlife conservation in Penang National Park. I would very much like to join local homestay programmes if it ATT_2 contributes to the wildlife conservation in Penang National Park. [112] I would very much like to promote local homestays if it contributes ATT_3 to the wildlife conservation in Penang National Park. I would very much like to pay for staying at a local homestay if it ATT_4 contributes to the wildlife conservation in Penang National Park. Intention I intend to stay at a local homestay when visiting Penang National INT_1 Park this year for wildlife conservation. I intend to join local homestay programmes when visiting Penang INT_2 [112] National Park this year for wildlife conservation. I will pay for staying at a local homestay when visiting Penang INT_3 National Park this year for wildlife conservation.

References 1. Almond, R.E.A.; Grooten, M.; Petersen, T. (Eds.) Living Planet Report 2020. Bending the Curve of Biodiversity Loss: A Deep Dive into Freshwater; WWF: Gland, Switzerland, 2020. 2. Duffy, R.; John, F.S.; Büscher, B.; Brockington, D. Toward a new understanding of the links between poverty and illegal wildlife hunting. Conserv. Biol. 2015, 30, 14–22. [CrossRef] 3. Symes, W.S.; McGrath, F.L.; Rao, M.; Carrasco, L.R. The gravity of wildlife trade. Biol. Conserv. 2018, 218, 268–276. [CrossRef] 4. UNODC. World Wildlife Crime Report 2020; United Nations Office on Drug and Crime: Vienna, Austria, 2020. 5. Bricker, K. The International Ecotourism Society Travel and Tourism Research Association: Advancing Tourism Research Globally. 2017. Available online: https://scholarworks.umass.edu/ttra/2013marketing/White_Papers/11 (accessed on 30 May 2021). 6. McLoughlin, E.; Hanrahan, J. Local authority tourism planning in Ireland: An environmental perspective. J. Policy Res. Tour. Leis. Events 2015, 8, 33–52. [CrossRef] 7. Hussin, R. Ecotourism and Community Participation in the Homestay Programme of Sukau Village: Long-term or Limited Benefits? SARJANA 2008, 23, 72–86. 8. Yusof, Y.; Muda, M.S.; Amin, W.A.; Ibrahim, Y. in Malaysia: A homestay program. China-USA Bus. Rev. 2013, 12, 300–306. 9. Andriotis, K.; Agiomirgianakis, G.; Mihiotis, A. Tourist Preferences: The Case of Mass Tourists to Crete. Tour. Anal. 2007, 12, 51–63. [CrossRef] 10. Shoval, N.; McKercher, B.; Ng, E.; Birenboim, A. location and tourist activity in cities. Ann. Tour. Res. 2011, 38, 1594–1612. [CrossRef] Sustainability 2021, 13, 9273 13 of 16

11. Lee, W.H.; Moscardo, G. Understanding the Impact of Ecotourism Experiences on Tourists’ Environmental Attitudes and Behavioural Intentions. J. Sustain. Tour. 2005, 13, 546–565. [CrossRef] 12. Jamal, S.A.; Othman, N.; Muhammad, N.M.N. Tourist perceived value in a community-based homestay visit: An investigation into the functional and experiential aspect of value. J. Vacat. Mark. 2011, 17, 5–15. [CrossRef] 13. Mura, P. Perceptions of authenticity in a Malaysian homestay—A narrative analysis. Tour. Manag. 2015, 51, 225–233. [CrossRef] 14. Kasuma, J.; Esmado, M.I.; Yacob, Y.; Kanyan, A.; Nahar, H. Tourist perception towards homestay businesses: Sabah experience. J. Sci. Res. Dev. 2016, 3, 7–12. 15. Karki, K.; Chhetri, B.B.K.; Chaudhary, B.; Khanal, G. Assessment of Socio-economic and Environmental Outcomes of the Homestay Program at Amaltari Village of Nawalparasi, Nepal. J. For. Nat. Resour. Manag. 2019, 1, 77–87. [CrossRef] 16. Kc, B. Ecotourism for wildlife conservation and sustainable livelihood via community-based homestay: A formula to success or a quagmire? Curr. Issues Tour. 2020, 24, 1227–1243. [CrossRef] 17. Ballantine, J.L.; Eagles, P.F.J. Defining Canadian ecotourists. J. Sustain. Tour. 1994, 2, 210–214. [CrossRef] 18. Sharpley, R. Ecotourism: A Consumption Perspective. J. Ecotour. 2006, 5, 7–22. [CrossRef] 19. Chiu, Y.-T.H.; Lee, W.-I.; Chen, T.-H. Environmentally responsible behavior in ecotourism: Antecedents and implications. Tour. Manag. 2014, 40, 321–329. [CrossRef] 20. Dolnicar, S.; Crouch, G.I.; Long, P. Environment-friendly Tourists: What Do We Really Know About Them? J. Sustain. Tour. 2008, 16, 197–210. [CrossRef] 21. Weeden, C. Responsible Tourist Behaviour, 1st ed.; Routledge: London, UK, 2013. [CrossRef] 22. Stronza, A. The Economic Promise of Ecotourism for Conservation. J. Ecotour. 2007, 6, 210–230. [CrossRef] 23. Stronza, A.L.; Hunt, C.; Fitzgerald, L.A. Ecotourism for Conservation? Annu. Rev. Environ. Resour. 2019, 44, 229–253. [CrossRef] 24. Ballantyne, R.; Packer, J.; Falk, J. Visitors’ learning for environmental sustainability: Testing short- and long-term impacts of experiences using structural equation modelling. Tour. Manag. 2011, 32, 1243–1252. [CrossRef] 25. Ballantyne, R.; Packer, J.; Hughes, K.; Dierking, L. Conservation learning in wildlife tourism settings: Lessons from research in zoos and aquariums. Environ. Educ. Res. 2007, 13, 367–383. [CrossRef] 26. Hughes, K.; Packer, J.; Ballantyne, R. Using post-visit action resources to support family conservation learning following a wildlife tourism experience. Environ. Educ. Res. 2011, 17, 307–328. [CrossRef] 27. Orams, M.B. A conceptual model of tourist-wildlife interaction: The case for education as a management strategy. Aust. Geogr. 1996, 27, 39–51. [CrossRef] 28. Ham, S.H.; Weiler, B. Interpretation as the centrepiece of sustainable wildlife tourism. Sustain. Tour. Butterworth-Heinemann Oxf. 2002, 35–44. [CrossRef] 29. Hughes, K. Measuring the impact of viewing wildlife: Do positive intentions equate to long-term changes in conservation behaviour? J. Sustain. Tour. 2013, 21, 42–59. [CrossRef] 30. Jacobs, M.H.; Harms, M. Influence of interpretation on conservation intentions of whale tourists. Tour. Manag. 2014, 42, 123–131. [CrossRef] 31. Marschall, S.; Granquist, S.M.; Burns, G.L. Interpretation in wildlife tourism: Assessing the effectiveness of signage on visitor behaviour at a seal watching site in Iceland. J. Outdoor Recreat. Tour. 2017, 17, 11–19. [CrossRef] 32. Moscardo, G.; Woods, B.; Saltzer, R. The role of interpretation in wildlife tourism. In Wildlife Tourism: Impacts, Management and Planning; Higginbottom, K., Ed.; Common Ground/ CRC: Altona, VIC, Australia, 2004; pp. 231–251. 33. Zeppel, H.; Muloin, S. Conservation Benefits of Interpretation on Marine Wildlife Tours. Hum. Dimens. Wildl. 2008, 13, 280–294. [CrossRef] 34. Myers, N. The Tourist as an Agent for Development and Wildlife Conservation: The Case of Kenya. Int. J. Soc. Econ. 1975, 2, 26–42. [CrossRef] 35. Gong, J.; Detchkhajornjaroensri, P.; Knight, D.W. Responsible tourism in Bangkok, Thailand: Resident perceptions of Chinese tourist behaviour. Int. J. Tour. Res. 2018, 21, 221–233. [CrossRef] 36. Zgolli, S.; Zaiem, I. The responsible behavior of tourist: The role of personnel factors and public power and effect on the choice of destination. Arab. Econ. Bus. J. 2018, 13, 168–178. [CrossRef] 37. Chiu, Y.-T.H.; Lee, W.-I.; Chen, T.-H. Environmentally Responsible Behavior in Ecotourism: Exploring the Role of Destination Image and Value Perception. Asia Pac. J. Tour. Res. 2013, 19, 876–889. [CrossRef] 38. Han, J.H.; Lee, M.J.; Hwang, Y.-S. Tourists’ Environmentally Responsible Behavior in Response to Climate Change and Tourist Experiences in Nature-Based Tourism. Sustainability 2016, 8, 644. [CrossRef] 39. Kiatkawsin, K.; Sutherland, I.; Lee, S.K. Determinants of Smart Tourist Environmentally Responsible Behavior Using an Extended Norm-Activation Model. Sustainability 2020, 12, 4934. [CrossRef] 40. Su, L.; Swanson, S.R. The effect of destination social responsibility on tourist environmentally responsible behavior: Compared analysis of first-time and repeat tourists. Tour. Manag. 2017, 60, 308–321. [CrossRef] 41. Luo, W.; Tang, P.; Jiang, L.; Su, M.M. Influencing mechanism of tourist social responsibility awareness on environmentally responsible behavior. J. Clean. Prod. 2020, 271, 122565. [CrossRef] 42. Xu, S.; Kim, H.J.; Liang, M.; Ryu, K. Interrelationships between tourist involvement, tourist experience, and environmentally responsible behavior: A case study of Nansha Wetland Park, China. J. Travel Tour. Mark. 2018, 35, 856–868. [CrossRef] Sustainability 2021, 13, 9273 14 of 16

43. He, X.; Hu, D.; Swanson, S.R.; Su, L.; Chen, X. Destination perceptions, relationship quality, and tourist environmentally responsible behavior. Tour. Manag. Perspect. 2018, 28, 93–104. [CrossRef] 44. Aseres, S.A.; Sira, R.K. Estimating visitors’ willingness to pay for a conservation fund: Sustainable financing approach in protected areas in Ethiopia. Heliyon 2020, 6, e04500. [CrossRef][PubMed] 45. Barnes, J.I.; Schier, C.; Van Rooy, G. Tourists’ willingness to pay for wildlife viewing and wildlife conservation in Namibia. S. Afr. J. Wildl. Res. 24-Mon. Delayed Open Access 1999, 29, 101–111. 46. Davis, D.; Tisdell, C.A. Tourist Levies and Willingness to Pay for a Whale Shark Experience. Tour. Econ. 1999, 5, 161–174. [CrossRef] 47. Kaffashi, S.; Yacob, M.R.; Clark, M.S.; Radam, A.; Mamat, M.F. Exploring visitors’ willingness to pay to generate revenues for managing the National Elephant Conservation Center in Malaysia. For. Policy Econ. 2015, 56, 9–19. [CrossRef] 48. Mmopelwa, G.; Kgathi, D.; Molefhe, L. Tourists’ perceptions and their willingness to pay for park fees: A case study of self-drive tourists and clients for mobile tour operators in Moremi Game Reserve, Botswana. Tour. Manag. 2007, 28, 1044–1056. [CrossRef] 49. Murphy, S.E.; Campbell, I.; Drew, J.A. Examination of tourists’ willingness to pay under different conservation scenarios; Evidence from reef manta ray snorkeling in Fiji. PLoS ONE 2018, 13, e0198279. [CrossRef][PubMed] 50. Tisdell, C.; Wilson, C. Wildlife-Based Tourism and Increased Support for Nature Conservation Financially and otherwise: Evidence from Sea Turtle Ecotourism at Mon Repos. Tour. Econ. 2001, 7, 233–249. [CrossRef] 51. Hultman, K.G.M.; Kazeminia, A.; Ghasemi, V. Intention to visit and willingness to pay premium for ecotourism: The impact of attitude, materialism, and motivation. J. Bus. Res. 2015, 68, 1854–1861. [CrossRef] 52. Ajzen, I. The theory of planned behavior. Organ. Behav. Hum. Decis. Process. 1991, 50, 179–211. [CrossRef] 53. Lam, S.-P. Predicting Intentions to Conserve Water from the Theory of Planned Behavior, Perceived Moral Obligation, and Perceived Water Right. J. Appl. Soc. Psychol. 1999, 29, 1058–1071. [CrossRef] 54. Trumbo, G.J.O.C.W. Intention to Conserve Water: Environmental Values, Planned Behavior, and Information Effects. A Compari- son of Three Communities Sharing a Watershed. Soc. Nat. Resour. 2001, 14, 889–899. [CrossRef] 55. Tonglet, M.; Phillips, P.S.; Read, A.D. Using the Theory of Planned Behaviour to investigate the determinants of recycling behaviour: A case study from Brixworth, UK. Resour. Conserv. Recycl. 2004, 41, 191–214. [CrossRef] 56. Nie, H.; Vasseur, V.; Fan, Y.; Xu, J. Exploring reasons behind careful-use, energy-saving behaviours in residential sector based on the theory of planned behaviour: Evidence from Changchun, China. J. Clean. Prod. 2019, 230, 29–37. [CrossRef] 57. Yuriev, A.; Dahmen, M.; Paillé, P.; Boiral, O.; Guillaumie, L. Pro-environmental behaviors through the lens of the theory of planned behavior: A scoping review. Resour. Conserv. Recycl. 2020, 155, 104660. [CrossRef] 58. Wang, Q.-C.; Chang, R.; Xu, Q.; Liu, X.; Jian, I.Y.; Ma, Y.-T.; Wang, Y.-X. The impact of personality traits on household energy conservation behavioral intentions—An empirical study based on theory of planned behavior in Xi’an. Sustain. Energy Technol. Assess. 2020, 43, 100949. [CrossRef] 59. Eagly, A.H.; Chaiken, S. The Psychology of Attitudes; Harcourt Brace Jovanovich College Publishers: Orlando, FL, USA, 1993. 60. Ajzen, I. Nature and Operation of Attitudes. Annu. Rev. Psychol. 2001, 52, 27–58. [CrossRef][PubMed] 61. Haddock, G.; Maio, G.R. Attitudes: Content, structure and functions. In Introduction to Social Psychology: A European Perspective, 4th ed.; BPS Textbooks in Psychology; Blackwell: Oxford, UK, 2008; pp. 112–133. 62. Ajzen, I. Attitude structure and behavior. In Attitude Structure and Function; Breckler, S.J., Greenwald, A.G., Eds.; American Psychiatric Association: Washington, DC, USA, 1989; pp. 241–274. 63. King, N. Determining the wildlife value orientation (WVO): A case study of lower Kinabatangan, Sabah. Worldw. Hosp. Tour. Themes 2013, 5, 377–387. [CrossRef] 64. Soulsbury, C.D.; White, P.C.L. Human–wildlife interactions in urban areas: A review of conflicts, benefits and opportunities. Wildl. Res. 2015, 42, 541–553. [CrossRef] 65. Lischka, S.A.; Teel, T.L.; Johnson, H.E.; Reed, S.E.; Breck, S.; Carlos, A.D.; Crooks, K.R. A conceptual model for the integration of social and ecological information to understand human-wildlife interactions. Biol. Conserv. 2018, 225, 80–87. [CrossRef] 66. Hemson, G.; Maclennan, S.; Mills, G.; Johnson, P.; Macdonald, D. Community, lions, livestock and money: A spatial and social analysis of attitudes to wildlife and the conservation value of tourism in a human–carnivore conflict in Botswana. Biol. Conserv. 2009, 142, 2718–2725. [CrossRef] 67. Shrestha, R.K.; Alavalapati, J.R.R. Linking Conservation and Development: An Analysis of Local People’s Attitude Towards Koshi Tappu Wildlife Reserve, Nepal. Environ. Dev. Sustain. 2006, 8, 69–84. [CrossRef] 68. Sekhar, N.U. Local people’s attitudes towards conservation and wildlife tourism around Sariska Tiger Reserve, India. J. Environ. Manag. 2003, 69, 339–347. [CrossRef] 69. Hariohay, K.; Fyumagwa, R.D.; Kideghesho, J.R.; Røskaft, E. Awareness and attitudes of local people toward wildlife conservation in the Rungwa Game Reserve in Central Tanzania. Hum. Dimens. Wildl. 2018, 23, 503–514. [CrossRef] 70. Holsman, R.H.; Ben Peyton, R. Stakeholder attitudes toward ecosystem management in southern Michigan. Wildl. Soc. Bull. 2003, 349–361. [CrossRef] 71. Marshall, K.; White, R.; Fischer, A. Conflicts between humans over wildlife management: On the diversity of stakeholder attitudes and implications for conflict management. Biodivers. Conserv. 2007, 16, 3129–3146. [CrossRef] 72. van der Meer, E.; Dullemont, H. Human-carnivore coexistence: Factors influencing stakeholder attitudes towards large carnivores and conservation in Zimbabwe. Environ. Conserv. 2020, 48, 48–57. [CrossRef] Sustainability 2021, 13, 9273 15 of 16

73. Weladji, R.B.; Moe, S.R.; Vedeld, P. Stakeholder attitudes towards wildlife policy and the Bénoué Wildlife Conservation Area, North Cameroon. Environ. Conserv. 2003, 30, 334–343. [CrossRef] 74. West, B.C.; Parkhurst, J.A. Interactions between deer damage, deer density, and stakeholder attitudes in Virginia. Wildl. Soc. Bull. 2002, 30, 139–147. 75. Barthwal, S.C.; Mathur, V.B. Teachers’ Knowledge of and Attitude toward Wildlife and Conservation. Mt. Res. Dev. 2012, 32, 169–175. [CrossRef] 76. Newhouse, N. Implications of Attitude and Behavior Research for Environmental Conservation. J. Environ. Educ. 1990, 22, 26–32. [CrossRef] 77. Clark, E.; Mulgrew, K.; Kannis-Dymand, L.; Schaffer, V.; Hoberg, R. Theory of planned behaviour: Predicting tourists’ pro- environmental intentions after a humpback whale encounter. J. Sustain. Tour. 2019, 27, 649–667. [CrossRef] 78. Phu, N.H.; Hai, P.T.; Yen, H.T.P.; Son, P.X. Applying theory of planned behaviour in researching tourists’ behaviour: The case of Hoi An World Cultural Heritage site, Vietnam. Afr. J. Hosp. Tour. Leis. 2019. Available online: https://www.semanticscholar.org/ paper/Applying-theory-of-planned-behaviour-in-researching-Toan/ebf27aa61ee05008794d4c06a3ba49be1150f2d8 (accessed on 11 August 2021). 79. Meng, B.; Choi, K. Extending the theory of planned behaviour: Testing the effects of authentic perception and environmental concerns on the slow-tourist decision-making process. Curr. Issues Tour. 2016, 19, 528–544. [CrossRef] 80. Gstaettner, A.M.; Rodger, K.; Lee, D. Visitor perspectives of risk management in a natural tourism setting: An application of the Theory of Planned Behaviour. J. Outdoor Recreat. Tour. 2017, 19, 1–10. [CrossRef] 81. Lowenstein, G.; Lerner, J.S. The role of affect in decision making. In Handbook of Affective Science; Davidson, R., Scherer, K., Goldsmith, H., Eds.; Oxford University Press: New York, NY, USA, 2003; pp. 619–642. 82. Mellers, B.; Schwartz, A.; Ritov, I. Emotion-based choice. J. Exp. Psychol. Gen. 1999, 128, 332–345. [CrossRef] 83. Bagozzi, R.P.; Belanche, D.; Casaló, L.V.; Flavián, C. The Role of Anticipated Emotions in Purchase Intentions. Psychol. Mark. 2016, 33, 629–645. [CrossRef] 84. Malone, S.; McKechnie, S.; Tynan, C. Tourists’ emotions as a resource for customer value creation, cocreation, and destruction: A customer-grounded understanding. J. Travel Res. 2018, 57, 843–855. [CrossRef] 85. Apps, K.; Dimmock, K.; Huveneers, C. Turning wildlife experiences into conservation action: Can white shark cage-dive tourism influence conservation behaviour? Mar. Policy 2018, 88, 108–115. [CrossRef] 86. McIntosh, D.; Wright, P.A. Emotional processing as an important part of the wildlife viewing experience. J. Outdoor Recreat. Tour. 2017, 18, 1–9. [CrossRef] 87. Harland, P.; Staats, H.; Wilke, H.A.M. Explaining Proenvironmental Intention and Behavior by Personal Norms and the Theory of Planned Behavior. J. Appl. Soc. Psychol. 1999, 29, 2505–2528. [CrossRef] 88. Parker, D.; Manstead, A.S.R.; Stradling, S.G. Extending the theory of planned behaviour: The role of personal norm. Br. J. Soc. Psychol. 1995, 34, 127–138. [CrossRef] 89. Kaiser, F.G.; Hübner, G.G.; Bogner, F.X. Contrasting the Theory of Planned Behavior with the Value-Belief-Norm Model in Explaining Conservation Behavior. J. Appl. Soc. Psychol. 2005, 35, 2150–2170. [CrossRef] 90. Ate¸s,H. Merging Theory of Planned Behavior and Value Identity Personal norm model to explain pro-environmental behaviors. Sustain. Prod. Consum. 2020, 24, 169–180. [CrossRef] 91. Oteng-Peprah, M.; de Vries, N.; Acheampong, M. Households’ willingness to adopt greywater treatment technologies in a developing country—Exploring a modified theory of planned behaviour (TPB) model including personal norm. J. Environ. Manag. 2019, 254, 109807. [CrossRef] 92. Onwezen, M.C.; Antonides, G.; Bartels, J. The Norm Activation Model: An exploration of the functions of anticipated pride and guilt in pro-environmental behaviour. J. Econ. Psychol. 2013, 39, 141–153. [CrossRef] 93. Rivis, A.; Sheeran, P.; Armitage, C. Expanding the Affective and Normative Components of the Theory of Planned Behavior: A Meta-Analysis of Anticipated Affect and Moral Norms. J. Appl. Soc. Psychol. 2009, 39, 2985–3019. [CrossRef] 94. Kim, Y.J.; Njite, D.; Hancer, M. Anticipated emotion in consumers’ intentions to select eco-friendly : Augmenting the theory of planned behavior. Int. J. Hosp. Manag. 2013, 34, 255–262. [CrossRef] 95. Londono, J.C.; Davies, K.; Elms, J. Extending the Theory of Planned Behavior to examine the role of anticipated negative emotions on channel intention: The case of an embarrassing product. J. Retail. Consum. Serv. 2017, 36, 8–20. [CrossRef] 96. Shrout, P.E.; Bolger, N. Mediation in experimental and nonexperimental studies: New procedures and recommendations. Psychol. Methods 2002, 7, 422–445. [CrossRef] 97. Cohen, P.; West, S.G.; Aiken, L.S. Applied Multiple Regression/Correlation Analysis for the Behavioral Sciences, 3rd ed.; Routledge: London, UK, 2013. [CrossRef] 98. Zhang, Y.; Wang, L. Influence of Sustainable Development by Tourists’ Place Emotion: Analysis of the Multiply Mediating Effect of Attitude. Sustainability 2019, 11, 1384. [CrossRef] 99. Rahman, M.; Rana, S.; Hoque, M.N.; Rahman, M.K. Brand perception of services and satisfaction: The mediating role of tourists’ attitudes. Int. J. Tour. Sci. 2019, 19, 18–37. [CrossRef] 100. Mehmood, S.; Liang, C.; Gu, D. Heritage Image and Attitudes toward a Heritage Site: Do They Really Mediate the Relationship between User-Generated Content and Travel Intentions toward a Heritage Site? Sustainability 2018, 10, 4403. [CrossRef] Sustainability 2021, 13, 9273 16 of 16

101. Gilchrist, P.T.; Masser, B.M.; Horsley, K.; Ditto, B. Predicting blood donation intention: The importance of fear. Transfusion 2019, 59, 3666–3673. [CrossRef] 102. Taylor, S.A.; Ishida, C.; Donovan, L.A.N. Considering the Role of Affect and Anticipated Emotions in the Formation of Consumer Loyalty Intentions. Psychol. Mark. 2016, 33, 814–829. [CrossRef] 103. Tan, S.G. Biodiversity characterization in Malaysia through biology and genetics. Genetik 2009, 14, 3–7. 104. Law of Malaysia: Act 226 National Parks Act; The Commissioner of Law Revision: Malaysia, 1980. 105. Kaffashi, S.; Radam, A.; Shamsudin, M.N.; Yacob, M.R.; Nordin, N.H. Ecological Conservation 1980, Ecotourism, and Sustainable Management: The Case of Penang National Park. Forests 2015, 6, 2345–2370. [CrossRef] 106. Hong, C.W.; Chan, N.W. The potentials, threats and challenges in sustainable development of Penang National Park. Malays. J. Environ. Manag. 2010, 11, 95–109. 107. Sekaran, U.; Bougie, R. Research Methods for Business: A Skill Building Approach; John Wiley & Sons: Hoboken, NJ, USA, 2019. 108. Burns, R.P.; Burns, R. Business Research Methods and Statistics Using SPSS; Sage: Thousand Oaks, CA, USA, 2008. 109. Taherdoost, H. Sampling methods in research methodology. How to choose a sampling technique for research. Int. J. Acad. Res. Manag. (IJARM) 2016, 5, 18–27. [CrossRef] 110. Taherdoost, H. Validity and Reliability of the Research Instrument; How to Test the Validation of a Questionnaire/Survey in a Research. Int. J. Acad. Res. Manag. 2016, 5, 28–36. [CrossRef] 111. Ajzen, I. Theory of Planned Behaviour Questionnaire. Available online: https://www.midss.org/content/theory-planned- behaviour-questionnaire (accessed on 22 February 2021). 112. Awang, Z. SEM Made Simple; MPWS: Bandar Baru Bangi, Malaysia, 2015. 113. Gefen, D.; Rigdon, E.; Straub, D. Editor’s Comments: An Update and Extension to SEM Guidelines for Administrative and Social Science Research. MIS Q. 2011, 35.[CrossRef] 114. Ibrahim, H.; Mariapan, M.; Lin, E.; Bidin, S. Environmental Concern, Attitude and Intention in Understanding Student’s Anti-Littering Behavior Using Structural Equation Modeling. Sustainability 2021, 13, 4301. [CrossRef] 115. Fornell, C.; Larcker, D.F. Evaluating Structural Equation Models with Unobservable Variables and Measurement Error. J. Mark. Res. 1981, 18, 39. [CrossRef] 116. Kline, R.B. Response to Leslie Hayduk’s Review of Principles and Practice of Structural Equation Modeling; The Guilford Press: New York, NY, USA, 1998. 117. MacKinnon, D.P.; Fairchild, A.J.; Fritz, M.S. Mediation analysis. Annu. Rev. Psychol. 2007, 58, 593–614. [CrossRef][PubMed] 118. Baron, R.M.; Kenny, D.A. The moderator-mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. J. Personal. Soc. Psychol. 1986, 51, 1173–1182. [CrossRef]