Tourist Environmentally Responsible Behavior and Satisfaction; Study on the World’s Longest Natural Sea Beach, Cox’s Bazar, Bangladesh

Abstract

This research was aimed at investigating the environmentally responsible behavior of tourists and their satisfaction with a tourist destination. Moreover, this study examined the effects of employee service quality, perceived value, environmental commitment and tourist satisfaction with a destination on loyalty and environmentally responsible behavior. We used data from tourists (n = 640) who had previously visited the world’s longest natural sea beach (Cox’s Bazar, Bangladesh). A partial least square structural equation model (PLS-SEM) method was used in this study to evaluate the proposed model and hypotheses. The results suggest that the perceived value of the destination has a significantly positive impact on both tourist satisfaction and environmental commitment. Similarly, employee service quality significantly impacts perceived value, tourist satisfaction and environmental commitment. Thus, both perceived value and employee service quality also substantially affect the environmentally responsible behavior at the Cox’s Bazar tourist destination. The main contribution of this research involved an investigation of the mediating effects of environmental commitment and tourist satisfaction with a destination on loyalty and environmentally responsible behavior using a single model based on relationship quality theory. Tourist satisfaction was found to completely mediate the relationship between the perceived value of a destination and environmentally responsible behavior, as well as loyalty. In addition, the theoretical and managerial implications for the destination were discussed.

1. Introduction

The environmental attitude of tourists is considered one of the most important factors influencing tourist destination’s perception, satisfaction, commitment to the environment, etc. [1,2,3]. Environmental behavior is also referred to as pro-environmental behavior and environmentally responsible behavior (ERB), describing a tourist’s behavior during travel that is beneficial to environmental protection and the wellbeing of tourist areas [4,5,6,7,8]. ERB also impacts a tourist’s quality of life due to social involvement activities [9,10].

When visiting a scenic tourist spot, tourists must protect the natural ecological environment of the scenic area, maintain tangible tourism resources, and be responsible for the humanistic environment of the tourist spot to preserve and inherit the intangible nature of the scenic spot environment. Humanistic behaviors include not eating pre-packaged food, eating local food as much as possible without littering, and other behaviors affecting the environment [1,11,12]. Therefore, this article defines the ERB of tourists as an important factor for the protection of tourism resources, as well as the local natural, cultural, and ecological environment. Although ERB has been a noticeable concern for a more extended period, it has only been emphasized in the literature over the last two decades. ERB is significantly related to sustainable tourism; for example, Li et al. [2] identified ERB as an essential tool for sustainable tourism. Furthermore, ERB has been identified as a strategy to better protect the environment of tourist destinations to achieve destination sustainability [3,13]. In any case, when tourists participate in nature-based travel experiences and come into contact with the natural environment, they are more likely to act in an environmentally friendly manner [14,15]. Nearly 20 years ago, Vaske and Kobrin [16] highlighted environmental education as an important factor in promoting ERB among tourists. This study also highlighted another important issue, i.e., emotional connection with natural resources. This emotional connection also motivates tourists toward environmentally responsible behavior when visiting destinations. Nearly two decades later, Kim and Park [17], Li et al. [2], and Pandža Bajs [18] also emphasized emotional attachment as an important factor underlying ERB toward tourist destinations. However, while the tourism industry is booming, some new problems have also emerged [19,20,21]. The most common problems related to the uncivilized behavior of tourists are littering, spitting, and destroying cultural monuments at tourist destinations. These human behaviors damage the environment of the scenic spot and seriously affect the image of the country. These behaviors are particularly prevalent in overpopulated, underdeveloped and developing countries [19,22]. Specifically, this study focuses on the environment in and tourism perspective of Bangladesh, where various problems are widespread [23,24]. In some cases, the behavior of individual tourists can also impact the environment. Therefore, in order to protect the scenic environment, restore its reputation, and prevent the further deterioration of the situation, analyzing the influencing factors of the ERB of tourists and transforming environmental protection concepts into conscious behavioral choices represent essential issues to be solved urgently. Considering this concept and its significance, this study aimed to investigate the ERB of Bangladeshi tourists and their loyalty to the destination.

Due to the rapid development of the Bangladeshi economy and the continuous improvement of national living standards, tourism is becoming an important part of the general public’s lives, accompanied by increased leisure time and the transformation of social ideology [25,26]. As a result, the number of people choosing to travel around the country has also gradually increased. Therefore, tourism has become an essential component of most people’s lives. As a result, the growth pattern of Bangladesh’s tourism industry has shifted from explosive growth to diversification [21,24].

Due to various challenges, research on the tourism industry in Bangladesh has not been expanded. In this regard, researchers have continued to focus on promoting tourism in Bangladesh. Therefore, this study can significantly contribute to the research and development of the tourism economy in Bangladesh. This improvement will also make a significant contribution to the overall economy of Bangladesh. Considering these circumstances, this study sought to address the following research questions (RQs): RQ1: How do the employee service quality (ESQ) and perceived value (PV) affect environmental commitment (ENC) and ERB? RQ2: How does ENC directly impact ERB? RQ3: How does tourist satisfaction (TS) directly impact ERB and loyalty (TLO)?

Answering these research questions allows us to address the study’s objectives, which involve investigating the impact of the quality perceptions of tourists as a direct consequence of visiting a study area on some outcome variables, including PV, ENC, TS, and ERB. To the best of our knowledge, He et al. [3] were the first to study the influence of ESQ, PV and TS with a destination on ERB using a model. Our research’s main objective was to investigate the effects of ESQ, PV, ENC and TS on ERB using a single model based on relationship quality theory in the context of Cox’s Bazar, the world’s third largest natural sea beach, situated in Bangladesh. Thus, this study sought to identify the factors affecting the satisfaction and environmental commitment of tourists. Furthermore, our study was extended to highlight the impact of tourist satisfaction and tourist loyalty.

This study is structurally presented as follows: The first section focuses on a theoretical perspective with respect to relationship quality, considering the relevant prior literature and hypothesis development. The second section describes the methodology and research setting, while the third section outlines the measurement model and study results. Lastly, discussions on theoretical and managerial implications, as well as future research directions, are presented.

2. Literature Review and Hypothesis Development

2.1. Theoretical Background

Based on the relationship quality theory, this research investigates the behavior and satisfaction of tourists’ responsibility towards the environment to achieve the research goals. According to the relationship quality theory, consumers continue to contribute value throughout their interactions with the company, and vice versa. As a high-level structure, relationship quality can have various unique dimensions to describe the strength of the relationship between consumers and brand or company objects [27,28]. Therefore, He et al. [3] put forward a concept related to brand relationships—tourists actively respond to the relationship efforts of tourist destinations. In addition, people and the environment also have significant relationships [29]. Thus, this research highlights the relationship between tourist pro-environmental behavior and tourist destination. In addition, the satisfaction profit chain (SPC), as described by Anderson [30], is the most widely used method for predicting consumer behavior in consumer relations. The SPC variables impact each other, for example, beginning with product satisfaction and progressing to total consumer satisfaction, with additional effects of consumer commitment, purchase intention/behavior and trust, loyalty intentions and eventually financial profit.

Trust and satisfaction in tourist services are widely regarded as two components of relationship quality [31]. According to Dick and Basu [32], attitude loyalty (described as commitment, trust and satisfaction) can lead to repeated patronage intentions and thus loyal behavior. Studies [3,27,33,34,35,36,37,38,39] have shown that relationship quality helps predict customer behaviors and plays an essential role in consumer decision making and post-purchase processes. Based on the relationship quality theory, we expanded the theory by adding variables such as value perception, tourist satisfaction, environmental commitment and environmental responsibility behavior variables to measure the pro-environmental behavior and quality perception of tourists visiting the world’s largest sea beach destination. The present study examines two dimensions of relationship quality, tourist satisfaction and environmental commitment, and finally considers tourist loyalty. The comprehensive approach of Cronin et al. [40] was also used in this study. It is proposed that employee service quality, customer satisfaction, and perceived value have a direct effect on attitude loyalty. This approach was chosen as numerous industries have successfully tested this model in their industrial practice [3,41,42]. However, this method has not been applied to Bangladesh’s tourism industry. Therefore, this research proposes the relationship among employee service quality, perceived value, environmental commitment, consumer satisfaction, environmental responsible behavior and loyalty, as presented in Figure 1.

2.2. Environmentally Responsible Behavior

Different studies define ERB in various aspects; for example, Poudel and Nyaupane [43] defined ERB as the behavior that deliberately seeks to maximize the positive effects and minimize the adverse impact on the economy, socio-cultural and ecological environment. Lyon et al. [44] describe ERB as an individual’s intentional and unintentional activity to minimize environmental problems. Chiu et al. [1] specified that ecological knowledge and attention are both designated as factors of ERB. The contribution of the tourism industry to the economy is increasingly obvious; at the same time, its adverse effects also affect the natural environment [43]. Thus, the behaviour of human beings responsible for the natural environment is considered as an important force for the responsible party to protect the environment [1,15,45]. ERB has a significant influence on ecotourism and the natural environment [46]. Some factors, such as environmental attitude, perceived behavioural control and subjective norms, are also associated with the ERB of tourist destinations [43]. In addition, ERB is associated with other important factors of sustainable tourism, such as environmental commitment, perceived value and service quality. Since ERB is considered to be one of the most influential forces affecting tourist loyalty, ERB education can encourage tourists to behave positively in the natural environment and revisit tourist destinations.

2.3. Perceived Value

The choice of a successful tourist destination depends on the understanding of the value of the tourist destination and the perception of high-quality tourism. These two factors have caused tourists to revisit tourist attractions many times. Some studies point out that perceptions of tourist quality and destination value affect tourist satisfaction [3,47,48,49,50,51,52,53]. The importance of perceived quality and value also creates a positive intention to revisit the destination. Julaimi and Talib [54] determined that perceived value affects satisfaction and the impact of satisfaction on revisit intention and the environmentally responsible behaviors of tourists. Tourist satisfaction is also highly correlated with the willingness to revisit and travel motivation. Overall, more satisfied tourists are more willing to revisit the destination [55]. Lin [56] found that there is a relationship between perceived value and tourist destinations, and vice versa. The natural environment of the tourist destination is also an important factor that may cause tourists to visit the destination again. In this case, the perceived value will influence positive environmental commitment, tourist satisfaction, and environmentally responsible behavior [3]. Davis et al. [57] specified that perceived value influences behavioral intentions, leading to environmental commitments and ERB. Moliner et al. [58] studied the Spanish tourism industry and determined the relationship between perceived value and environmental commitment. In addition, perceived value has a significant influence on environmental commitment and environmentally responsible behaviour [3]. Based on the above theoretical foundation, Hypothesis 1 is assumed in the following sections.

Hypothesis 1a (H1a).

PV at a destination positively impacts TS.

Hypothesis 1b (H1b).

PV at a destination positively impacts ERB.

Hypothesis 1c (H1c).

PV at a destination positively impacts ENC.

2.4. Employees’ Perceived Service Quality

Employees’ perceived service quality (ESQ) is defined by many researchers, academics and policy makers from different aspects, and has investigated the relationship between ESQ and environmentally responsible behavior, customer satisfaction and environmental commitment [3,47,49,52,53,59,60]. Anastasiei et al. [60] emphasize the intermediate role of information quality, which makes confidence an important factor in perceived service quality. The use of consumer perception of service quality is widely regarded as a good predictive assessments method. Although there are dissimilarities in some aspects, there is still a positive correlation between tourism consumer satisfaction and perceived service quality [3,52]. Poolthong and Mandhachitara [61] pointed out that ESQ has a direct influence on consumer satisfaction.

In most cases, ESQ is considered the antecedent of consumer satisfaction, and vice versa [1,47]. Tsoukatos and Rand [53] also determined the significance of customer satisfaction to route service quality; however, satisfaction differs in tangibility and intangibility. For example, studies have found that the influence of tangibles is not as significant as intangibles. The level of service tangibility positively influences the importance of its tangibility. ESQ is also directly related to environmentally responsible behavior with a significant impact [1,62,63]. He et al. [3] also found that value perceptions positively impact tourists’ environmentally responsible behaviour as well as environmental commitment. In addition, Chiu et al. [1] determined that perceived value helps to promote tourists’ environmentally responsible behaviour. Multiple studies have identified that ESQ positively influences perceived value; based on this concept, Aljarah and Alrawashdeh [62] and Su et al. [28] found that overall ESQ positively influences perceived value. Based on the above theoretical foundation, this study assumed Hypothesis 2 in the following sections.

Hypothesis 2a (H2a).

ESQ of employees at a destination positively impacts TS.

Hypothesis 2b (H2b).

ESQ of employees at a destination positively impacts ERB.

Hypothesis 2c (H2c).

ESQ of employees at a destination positively impacts ENC.

Hypothesis 2d (H2d).

ESQ of employees at a destination positively impacts PV.

2.5. Environmental Commitment

Environmental commitment refers to a friendly approach towards the environment. Lynes and Dredge [64] and Graci and Dodds [65] designated the green concept as an environmental commitment concept. Environmental commitment also means that environmental management practices will lead to more responsible behavior toward the environment [64]. Lokhorst et al. [66] demonstrated that commitments are commonly viewed as an effective way to promote pro-environmental behaviors. The study defined environmental commitment as a commitment to keep the environment’s best interests in mind and strengthen the connection with the environment in the future.

The impact of human behaviour on the environment is one of the major concerns faced by the tourism industry. Due to irresponsible human behaviour towards the environment, tourism is facing a wide range of threats. Many previous studies have focused on human approaches and attachments as an essential indicator of sustainable tourism [67,68,69]. In most cases, tourists will not approach a favourable commitment toward sustainable tourism due to the lack of fundamental knowledge about adverse environmental effects. In addition, the impact of environmental understanding on tourist behavioural intentions as well as environmental responsibilities has also been investigated [4]. Yusliza et al. [70] determined a positive influence of environmental commitment on environmentally responsible behavior to ensure industrial sustainability. Previous studies have also identified that environmental commitments also have a significant impact on the loyalty to tourist destinations. For example, Isa et al. [71] and Lin [56] found that the impact of environmental commitment on tourist destination attachment is that the ultimately leads to loyalty to tourist destinations. Based on the above theoretical foundation, Hypothesis 3 is assumed in the following sections.

Hypothesis 3 (H3).

ENC of tourists positively impacts the TLO of destination.

2.6. Tourists Satisfaction

The concept of destination loyalty is a well-known concept in the tourism industry as well as a marketing strategy [72]. Tourist satisfaction is one of the most significant forces that motivates tourists to revisit the destination. The empirical and theoretical relationship between tourist satisfaction and loyalty is well known and confirmed by many established findings [2,17,70,73,74,75]. Tsoukatos and Rand [53] found that tourist satisfaction positively impacts loyalty to a destination. In general, tourist satisfaction has a significant impact on customer loyalty, and has different degrees of influence on customers’ willingness to revisit and recommend through different dimensions. Customers’ willingness to revisit denotes the amusement perception, shopping perception, tourism environment perception and traffic perception; customer’s willingness to recommend denotes the perception of catering, traffic perception, attitude perception of tourism destinations and environment perception of tourism destinations [17,53,74,76,77]. Satisfaction also impacts the tourists’ responsible environmental behavior in different ways. Wang and Kang [5] specified that tourists’ satisfaction will influence their interest in participating in pro-environmental behavior. Thus, individual tourists’ concern about the environment significantly influences their life satisfaction [1,14]. Based on the above theoretical foundations, this study assumes Hypothesis 4 in the following section.

Hypothesis 4a (H4a).

TS at a destination positively impacts ERB.

Hypothesis 4b (H4b).

TS at a destination positively impacts TLO.

3. Methodology

3.1. Survey of the Research Area

The study area is Cox’s Bazar sea beach, which is the longest natural sea beach in the world with a total length of nearly 93 miles (150 km). The “Longest Sea Beach” has been picked up from some very specific references (https://www.bbc.com/news/av/world-asia-20699989; https://en.wikipedia.org/wiki/Cox%27s_Bazar_Beach; https://www.reuters.com/article/us-bangladesh-tourism-idUSDEL2349420070131, accessed on 22 April 2021). In some other references, this beach is referred as the third-longest beach after Australian Ninety Mile Beach and Praia do Cassino Beach of Brazil (https://0-www-statista-com.brum.beds.ac.uk/statistics/519674/longest-beaches-in-the-world/, accessed on 22 April 2021). However, according to its popularity, this beach is considered the best tourist destination and best research area for tourism in Bangladesh. Since this is the most popular tourist destination in Bangladesh, considering this research, the studies on ERB and TS are highly correlated.

3.2. Questionnaire Design and Scale

In order to collect data from the target respondents, we created a structured questionnaire. Our target respondents were people who had visited Cox’s Bazar sea beach, at least as a tourist destination. According to the criteria for becoming a target respondent, we used social media platforms, especially Facebook, to collect data on the target respondents. We used a Google docs form to distribute the questionnaire through social media. Based on the expected outcome and assumed methods, a questionnaire was compiled, including five demographic questions regarding respondents’ age, gender, education level, monthly income, and respondents’ occupations. The measurement systems of the variables were also structured.

Table 1. Demographic profile of this study.

Variables		Frequency	Percentage
Gender	Male	230	36
	Female	410	64
Age	18–25 years	170	26
	26–30 years	245	38
	31–35 years	87	14
	36–40 years	46	8
	40 years	92	14
Education	Secondary school	40	6
	Higher secondary school	80	13
	Undergraduate	283	44
	Postgraduate	269	42
	PhD	8	3
Job level	Govt. job	65	10
	Private job	200	31
	Students	205	32
	Business	153	24
	Retired	9	2
Income	Below USD 120	142	22
	USD 121-240	117	18
	USD 241-360	162	25
	USD 361-480	131	21
	Above USD 600	88	14

Source: authors’ explanation.

presents the demography profile of tourists. The age of the respondent was measured as an open-ended question to obtain the correct answer. Questions related to the main variables were measured in terms of perceived value [1,3,17,36,63,78,79,80,81,82,83], employee service quality [3,42], tourist satisfaction [3,78,84,85,86], environmental commitment [3,29], environmentally responsible behavior [1,3,87] and tourists loyalty [17,78,80,85,88,89]. Respondents were asked to respond based on a five-point Likert scale for these variables. The details of the variable measurement are provided in Appendix A.

3.3. Data Procurement and Processing

The goal was to collect data on 1000 respondents; thus, we sent the questionnaire to 1132 respondents via social media communication (the questionnaire was sent to everyone, and then we asked whether the respondent visited our target location). We received responses from 688 respondents who visited Cox’s Bazar Beach. The response rate was very high, 61%, as this tourist spot is the most popular tourist destination; most people have experience visiting this place. However, finally, we determined that 640 questionnaires were valid. Another 48 questionnaires were found to be incorrectly answered. Therefore, finally, 93% of the correct answers were used to test the result of this study. In some cases, respondents provided all moderate responses without considering reality.

3.4. Data Analysis

The partial least squares structural equation modeling (PLS-SEM) method was used to measure the proposed model and hypotheses testing. PLS reflects the relationship between existing potential exogenous and endogenous variables and their items. We employed PLS-SEM to evaluate more complicated model structures, while we had small sample sizes, non-normal data and structural indicators [90]. In this study, we used Smart-PLS 3.2.3 software to test the hypothesis. This software is very popular among researchers in the social science field [91]. For analysis assumptions, a bootstrapping of 5000 sub-samples was used with the unsigned change options, bias-corrected and accelerated (BCa) bootstrap confidence interval and two-tailed testing at the 95% confidential level [92,93]. In order to meet the study’s goals of predicting visitor satisfaction and willingness to revisit Cox’s Bazar, PLS-SEM is the most suitable to explain how potential key drivers predict tourist satisfaction and pro-environmentally responsible behavior [94].

4. Result

4.1. Measurement Model

In the measurement model, we observed measures of internal consistency reliability, discriminant validity (HTMT) and the measurement of the convergent construction validity. Reliability and composite reliability were used to test the internal consistency of the constructs. Each latent construct of Cronbach’s alpha and composite reliability surpassed the threshold level of 0.70, indicating satisfactory reliability [95].

Table 2. The measurement model (reliability and validity) analysis.

Constructs	Cronbach’s Alpha	rho_A	Composite Reliability	AVE
PV	0.802	0.813	0.845	0.360
ESQ	0.623	0.626	0.798	0.569
ENC	0.710	0.595	0.784	0.548
ERB	0.724	0.729	0.817	0.473
TS	0.747	0.642	0.810	0.587
TLO	0.715	0.755	0.792	0.562

Source: authors’ experiment ((a) composite reliability = (square of the summation of the factor loadings)/{(square of the summation of the factor loadings) + (square of the summation of the error variances)}. (b) AVE = (summation of the square f the factor loadings)/{(summation of the square of the factor loadings) + (summation of the error variances)}).

shows that, with the exception of employee service quality, all items of Cronbach’s alpha exceeded the reference value, 0.7. The range value of composite reliability was 0.784 to 0.845, which satisfies the 0.70 threshold [90], suggesting that process reliability is very strong and error-free. Except for the two variables PV and ERB, the average variance extracted (AVE) of all latent variables exceeded 0.50. We can accept this AVE score as, according to Fornell and Larcker [95], if AVE is less than 0.50, but composite reliability is higher than 0.6, the convergent validity of the construct is still sufficient. In that study, Fornell and Larcker [95] stated that “the researcher may conclude that the convergent validity of the construct is adequate, even though more than 50% of the variance is due to error”. The AVE value of some studies, such as [96,97,98], is lower than 0.50. In our study, the composite reliabilities of PV and ERB were 0.845 and 0.817, respectively, which are both higher than 0.6. Thus, the present study indicates satisfactory convergent validity.

Table 3. Confirmatory factor analysis results and VIF results.

Constructs and Scale Items	PV	ESQ	ENC	ERB	TS	TLO	Mean	Std.	VIF
PV1	0.632						3.458	1.207	1.421
PV4	0.544						2.93	1.288	1.670
PV5	0.619						3.118	1.276	1.719
PV7	0.669						3.463	1.197	1.301
PV10	0.659						2.837	1.492	1.883
PV11	0.660						3.056	1.365	1.889
PV12	0.710						2.98	1.367	1.760
PV13	0.632						3.458	1.207	1.421
PV15	0.640						3.951	1.207	1.491
PV16	0.619						3.582	1.227	1.456
ESQ1		0.791					3.518	1.131	1.278
ESQ2		0.741					3.433	1.301	1.301
ESQ3		0.729					3.577	1.177	1.161
ENC1			0.741				3.674	1.033	1.126
ENC2			0.689				4.083	0.994	1.243
ENC3			0.788				4.261	0.928	1.327
ERB1				0.703			4.025	0.92	1.320
ERB2				0.718			4.124	1.002	1.397
ERB3				0.650			4.131	0.945	1.374
ERB4				0.654			4.061	0.949	1.406
ERB5				0.709			4.141	0.917	1.395
TS1					0.706		4.007	0.979	1.122
TS2					0.772		3.606	1.201	1.513
TS3					0.818		3.562	1.375	1.603
LO1						0.842	4.107	1.004	1.290
LO2						0.723	4.109	1.005	1.291
LO3						0.674	4.082	1.005	1.144

Source: authors’ experiment.

shows the measures of convergent construction validity. Before measuring the convergent validity, we tested the factor loadings for all items. According to Fornell and Larcker [95], the reliability factor loading of all items should have a minimum cut-off value of 0.50. Therefore, we excluded items in the perceived value construct (PV2, PV3, PV6, PV8, PV9 and PV14), one item in the environmentally responsible behavior construct (ERB6) and one item in the tourist satisfaction construct (TS4) as these factor loadings items did not exceed the value of 0.50.

Moreover, Table 3 also gives the values of the multicollinearity test for independent variables (VIF = variance inflation factor). According to Dospinesc and Dospinescu [99], the VIF value should be less than 2.00, indicating that the data are not collinear. The VIF values for each variable were between 1.122 to 1.889, which is lower than the reference value of 5 [100], indicating that the obtained structural model has no negative effects, and there is no multicollinearity across items or predictor constructs.

Following Hair et al. [100] and Henseler, Ringle and Sarstedt [91], we used the Fornell–Larcker criterion of correlation and Heterotrait–Monotrait ratio (HTMT) to evaluate the effectiveness of discriminant validity. Discriminant validity refers to the degree to which latent variables are different from each other [101]. The square root of the AVE of each construct should be greater than the correlation between each construct and other constructs in the model [101,102].

Table 4. Correlation coefficient and average variance extracted (Fornell–Larcker and HTMT criteria).

Fornell–Larcker Criterion
	ENC	ERB	ESQ	TLO	PV	TS
ENC	0.740
ERB	0.416	0.688
ESQ	0.364	0.267	0.754
TLO	0.425	0.517	0.304	0.749
PV	0.120	0.129	0.444	0.126	0.600
TS	0.409	0.460	0.491	0.463	0.370	0.766
Heterotrait–Monotrait Ratio (HTMT)
	ENC	ERB	ESQ	LO	PV	TS
ENC
ERB	0.630
ESQ	0.595	0.393
TLO	0.670	0.783	0.476
PV	0.245	0.256	0.605	0.270
TS	0.635	0.646	0.772	0.696	0.481

Source: authors’ findings.

shows both the square root of the AVE for the constructs and the correlation among the constructs, where all the diagonal values are greater than the row and column values, indicating appropriate discriminant validity.

Table 4 also shows the HTMT values. In terms of variance-based SEM, the HTMT criterion is superior to both the Fornell and Larcker criterion and the assessment of (partial) cross-loadings [91]. All HTMT ratios were less than 0.85 (HTMT < 0.85) [91]. Each HTMT result was statistically distinct from one result (all confidence intervals did not include 1). As a result, this implies that the measurement model obtained discriminant validity [100].

4.2. Structural Path Model to Examine Hypothesized Relationships

After confirming the reliability of the measurement model and the measurement invariance across the classes, the structural model was evaluated.

Table 5. Evaluation indices and outcomes of hypothesis tests.

Hypotheses	Predicted Relationships	β	Mean	Std.	T Stat.	P-V	2.50%	97.50%	Results
H1	PV → TS	0.207	0.209	0.033	6.337	0.000	0.15	0.272	Accepted
H1a	PV → ERB	−0.03	−0.028	0.031	0.959	0.338	−0.09	0.035	Rejected
H1b	PV → ENC	−0.082	−0.08	0.039	2.098	0.036	−0.163	−0.002	Accepted
H2	ESQ → TS	0.351	0.351	0.034	10.335	0.000	0.287	0.412	Accepted
H2a	ESQ → ERB	0.022	0.018	0.039	0.56	0.576	−0.06	0.096	Rejected
H2b	ESQ → ENC	0.364	0.362	0.03	12.236	0.000	0.303	0.418	Accepted
H2c	ESQ → PV	0.397	0.4	0.028	14.006	0.000	0.345	0.457	Accepted
H3	ENC → ERB	0.302	0.306	0.033	9.1	0.000	0.239	0.372	Accepted
H4	TS → ERB	0.305	0.307	0.037	8.207	0.000	0.235	0.374	Accepted
H4a	TS → LO	0.42	0.424	0.028	14.883	0.000	0.371	0.484	Accepted

Source: authors’ findings.

and Figure 1 illustrate the structural model evaluation and hypothesis testing of Cox’s Bazar tourists’ pro-environmental behavior. The survey results showed that eight out of ten proposed hypotheses were accepted. Except for ESQ → ERB and PV → ERB, all path coefficients are statistically significant. The R² values of revisit intention and tourist satisfaction in Cox’s Bazar scenario are 0.171 and 0.226, respectively, which are considered satisfactory from the perspective of behavioral science [100,103]. The results show a greater R² of satisfaction for the Cox’s Bazar tourist destination and a higher value of revisit intention for the Cox’s Bazar tourist destination. The proposed model has good explanatory power as it has already had a great influence on endogenous variables.

For the hypothesis test, the effect of perceived value on tourist satisfaction (β = 0.207, p < 0.05) and environmental commitment (β = 0.082, t-value = 5.88, p < 0.05) is statistically significant, but the perceived value has insignificant effects on environmentally responsible behavior (β = −0.030, p > 0.05); therefore, hypotheses H1 and H3 are supported, and H2 is not supported. The path coefficients and t value results prove that employee service quality has significant effects on perceived value (β = 0.397, p < 0.05), tourist satisfaction (β = 0.351, p < 0.05) and environmental commitment (β = 0.364, p > 0.05); thus, H4, H6 and H7 are supported. Nevertheless, employee service quality did not significantly impact environmentally responsible behavior (β= 0.022, p > 0.05); therefore, H5 is not supported. Tourist environmental commitment has a significant influence on environmentally responsible behavior (β= 0.302, p < 0.05), which offers support for H8. Finally, the path coefficient shows that Cox’s Bazar tourist satisfaction has a significant positive effect on both environmentally responsible behavior (β = 0.305, p < 0.05) and loyalty on destination (β52 = 0.420, p < 0.05); therefore, H9 and 10 are supported.

4.3. Direct Effects, Indirect Effects, and Total Effect

Table 6. Direct, indirect and total effects.

Relationships between Variables	Direct Effects	Indirect Effects	Total Effects
PV → TS	0.207		0.207
PV → ERB	−0.230	−0.225	0.208
PV → ENC	−0.082		−0.082
PV → LO		0.087	0.087
ESQ → TS	0.351	0.082	0.433
ESQ → ERB	0.022	0.107	0.242
ESQ → ENC	0.364	−0.032	0.331
ESQ → PV	0.397		0.397
ESQ → LO		0.182	0.182
ENC → ERB	0.302		0.302
TS → ERB	0.305		0.305
TS → LO	0.420		0.420

Source: authors’ findings.

shows the effects between the constructs. In terms of direct effects, tourist satisfaction has a greater direct effect on loyalty. Similarly, employee service quality has the greatest direct effect on perceived value and environmental commitment. Perceived value has the least negative direct effect on ERB and ENC. In the context of indirect influence, employee service quality has a significant indirect effect on ERB and ENC. Examining the total effect, it was found that employee service quality has the greatest total effect on tourist satisfaction, and the total effect of tourist satisfaction has the greatest total effect on tourist loyalty. However, the overall impact of perceived value on ERB is minimum.

4.4. Mediating Role of Tourist Satisfaction and Environmental Commitment

Table 7. The result of mediating effects of tourist satisfaction and environmental commitment.

Path	Indirect Effect	T Stat.	p-Values	Results
PV → TS → LO	0.087	5.988	0.000	Accepted
ESQ → TS → ERB	0.107	6.062	0.000	Accepted
PV → TS → ERB	0.063	5.454	0.000	Accepted
ESQ → ENC → ERB	0.110	8.633	0.000	Accepted
PV → ENC → ERB	−0.025	2.069	0.039	Accepted
ESQ → PV → TS → LO	0.034	5.072	0.000	Accepted
ESQ → PV → ENC → ERB	−0.010	2.105	0.036	Accepted

Source: authors’ findings.

exhibits the mediating role of tourist satisfaction and environmental commitment among PV, ESQ, ERB and loyalty. The SEM effect of the mediating role shows that tourist satisfaction is the main mediating variable between PV and LO, ESQ and ERB and PV and ERB, and the p-value is less than 0.05. In addition, the p-value of environmental commitment is less than 0.05, acting as a mediator between PV and ERB, and between ESQ and ERB. As a result, it has an impact on the saliency of the model.

5. Discussion and Conclusions

This study investigates how perceived value and employee service quality influence Cox’s Bazar tourist satisfaction and environmentally responsible behavior. Based on relationship quality theory and the previous literature, our study established an integrated model, which measures tourist satisfaction, loyalty, and environmentally responsible behavior. The SEM results support the hypothetical relationship between variables. Findings suggest that the perceived value has a direct impact on tourist satisfaction and environmental commitment, which is supported by previous studies [3,42]. Tourism researchers have previously considered the perceived value [42]. The perceived value directly affects tourists’ environmentally responsible behavior. However, its influence is mediated by tourist satisfaction and environmental commitment, as supported by a prior study by Chiu et al. [1] in the context of the eco-tourism environment. Thus, the perceived value should be considered as a significant variable for further destination-based research. These findings contribute to the formation of new evidence that tourist satisfaction positively and significantly influences the willingness of travelers to engage in environmentally responsible activity. There is a direct and positive impact of employee service quality on the perceived value, tourist environmental commitment and tourist satisfaction when visiting COX’s Bazar. These findings align with previous studies [3,42,104]. Employee service quality at a destination is a notable antecedent of the value perceived from experience by tourists. In addition, the perceived employee service quality has no direct effect on tourists’ environmentally responsible behavior, which is controversial to a previous study in central China [3]. However, it acts as a mediator between visitor satisfaction and environmentally responsible behavior.

Previous research has indicated that environment commitment can play a significant role in predicting behavior [29,105]. Davis et al. [29,57] introduced environmental commitment as a new psychological construct in the context of environmental psychology, explaining the relationship between people and the environment. Therefore, this study used environmental commitment as a predictor variable of ERB. Recent research supports a significant positive relationship between environmental commitment and environmentally responsible behavior [3]. Environmental commitments have the largest overall impact on environmentally responsible behavior. Tourists are more likely to participate in activities that benefit the natural environment of their destination.

In addition, the findings of the mediating study indicate that environmental commitment completely mediates the impact of the perceived value, employee service quality and tourists’ environmentally responsible behaviors. Finally, our study extended the model to measure tourist destination satisfaction and loyalty, where tourist satisfaction significantly influences environmentally responsible behavior and tourist loyalty. A previous study conducted by He et al. [3] in central China prove that tourist satisfaction significantly affects environmentally responsible behavior. If tourists are satisfied with their destination, they display more responsible environmental behavior. Similarly, Bangladeshi tourists are highly satisfied with Cox’s Bazar as a tourist destination; therefore, they are revisiting it and establishing a loyal relationship.

6. Limitations and Further Research Directions

This study has a particular limitation that can assist researchers in further investigations. First, the comparative literature on Bangladeshi tourism and that of other underdeveloped countries is very limited. A limited number of researchers, for example, He et al. [3], have previously applied the relationship quality theory to the tourist industry. Second, data were collected from tourists who had visited Cox’s Bazar. Therefore, other destinations may provide different outcomes compared to this model. The results of developed countries and developing countries may also be different. Due to the COVID-19 pandemic and social distancing policies, we conducted an online survey. In some cases, physical survey questionnaires can provide a more accurate picture of travelers’ attitudes and environmentally responsible behaviors. In addition, this study was unable to collect a large amount of data from Bangladesh. Therefore, we believe that the data size is also a limitation.

We combined quality theory and conceptual model for a single goal. This model should be applied to various destinations in the context of Bangladesh, such as forests, hills and the sea. Further research will compare the overall scenario of the tourism industry by including more diverse populations and employing random sampling techniques. In addition, future studies may integrate specific theories (e.g., consumption value and planned behavior) with relationship quality theories to test outcomes in various destination contexts.

7. Implications (Managerial, Theoretical and Policy)

The findings of this research have significant theoretical and managerial implications for scholars, destination managers and authorities in Bangladesh aiming to understand how they can motivate tourists to behave in ecologically responsible ways.

Theoretically, the present study supports the relational quality theory by expanding tourist satisfaction and loyalty variables. Tourist satisfaction and environmental commitment have a good relationship with environmentally responsible behaviors. Finally, tourist satisfaction also has a great influence on the loyalty to tourist destinations and services. Through the analysis of multiple mediation effects, we validated the paths of perceived employee service quality → perceived value → tourist satisfaction → tourist loyalty; we also verified the path of perceived employee service quality → perceived value → environmental commitment → environmentally responsible behavior. Our assumptions are in accordance with He et al. [3]. Theoretically, researchers must consider mediating constructs when developing theories or expanding models [3]. The outcomes of this study expand earlier ERB studies and relational quality theory, showing that the acquisition of environmentally responsible tourist behavior is associated with other more general tourism behaviors.

Employees in the tourism sector should provide proper training and information on environmentally friendly services and ecotourism/sustainable tourism. As a result, they will pay more attention to the environment and serve guests in a more environmentally friendly way. Tourists will be more satisfied if they receive a higher net value and fair compensation. Given the critical significance of visitor satisfaction, destination marketers must seek to provide a positive tourism experience and continuously monitor visitor satisfaction levels. Managers need to review the tourism experience and pay attention to the tangible and intangible advantages to visitors, focusing on developing and delivering value, such as upgrading guide duties. The Bangladesh government may also play a role in encouraging visitors to engage in greener behaviors. This requires an assessment of the long-term benefits of behaving in an ecologically friendly manner to maintain natural attractions for the benefit of future generations, rather than a short-term evaluation. Raising awareness of negative environmental impacts will result in a larger sense of responsibility for these effects, leading to more proactive environmental friendly activities [14]. Residents of Bangladesh are not aware of environmentally responsible behavior, and as a result, when they travel, they contribute to overtourism and devastation. Even visitors are unfamiliar with the concepts of eco-tourism and sustainable tourism. Thus, the government should continue to raise awareness and educate visitors on green solutions to motivate visitors to engage in eco-friendly behaviors. The government should support tourism enterprises to design and execute high-quality service standards to guarantee that tourists receive high-quality services. For instance, the government could provide educational resources and training to small- and medium-sized tourism businesses to help their staff to improve their service delivery skills [3,106]. The government should establish adequate environmentally friendly tourism rules, regulations and policies to guarantee the environmentally friendly behaviors of tourism businesses and tourists.