An Exploratory Attitude and Belief Analysis of Ecotourists’ Destination Image Assessments and Behavioral Intentions

1. Introduction

While COVID-19 and post-COVID restrictions continue to affect all forms of tourism some forms of tourism such as ecotourism are poised to rebound due pent-up demand (especially domestic), as well as participation models falling within accepted pandemic norms such as social distancing. Demographically, birdwatchers reflect an economically resilient tourism segment with a high levels of education and high annual incomes thus surviving the pandemic induced economic downtown with ample discretionary income (Rutter, et al., 2021). On the demand side, birdwatching features some economic inelasticity as many birdwatchers consider the activity to be a lifestyle rather than a hobby with a high degree of knowledge and interest (Kim, Scott, & Crompton, 1997).

Although birdwatching can be a solitary pursuit, it does exhibit characteristics of being a tight-knit community, even referring to one another as “birders” rather than “birdwatchers” (Scott & McMahan, 2017) and a high interest in social media with positive and negative effects on birdwatching behavior (Ma, Ng, Cheung, & Lam, 2021). On the supply side, however, social and economic impact of the pandemic has placed millions of livelihoods at risk and threatens to roll back progress in advancing sustainable development goals (United Nations, 2021). Despite the near dependence of many communities around the world on birdwatching as the only ecotourism offering, the literature on birdwatching as a tourism activity remains scarce.

Colombia was one of those countries that pre-pandemic was poised to be a breakout destination for birdwatching, with over 1,900 avian species and 79 endemic to the country. In general, however, Colombian tourism is still at a stage where ecotourism operations such as birdwatching are highly dependent on the local community for everything from guides to lodging, to transportation and food and beverage. Without the economic benefit of tourists such as birdwatchers, many of these communities unfortunately regress toward consumptive environmental practices, such as unsustainably harvesting and hunting local flora and fauna (United Nations, 2021). Thus, post-Covid, ecotourism activities such as birdwatching must be considered within the context of destination marketing and management.

As destination management strategy, the proper allocation of destination investments is difficult to estimate because of subjective nature of the destination image construct, including cognitive (beliefs) and affective (feelings) variables. The study here contributes an empirical analysis useful for assisting local businesses to identify the most important issues influencing tourists’ perception of the destination and its behavioral intentions. In addition to traditional measurement items for destination image, the study proposes 15 additional items that are specific to birdwatching as an ecotourism activity.

A destination image assessment may be a complex construct based on a mental imagery immersion on the expectations, mixed with emotional and cognitive engagements, as predictors of e motions, experiences and outcomes of traveling into the destination (Xiaghong & Ivan, 2021). Based on the above image implicates physiological arousal, on the cognitive side information source can influence knowledge and beliefs of destination but not neccesarly implies changing the affective assesments positively or negatively (Li, Pan, Zhang & Smith, 2009). Acording to the idea of a dominant attraction, the greater the sense of obligation to visit, which means destination image should develop the attributes of the destinations, tourists’ perceptions of what the destination offers enhance the expectations of having their needs met and the probability of having a satisfying visit. Traditionally, destination image was mainly thought for marketing and branding. In this framework, tourists were considered as passive consumers who process some information, however, Web 2.0 revolutionized communication and information flows in many sectors, including tourism, tourists became active consumers in physical and online platforms (Arabadzhyan, Figini & Vici, 2021). Perceived destination image remains a critical factor in promoting the behavioral intention. Contemporary tourists seek different experiences during the trip, which means repetitive characteristics of a destination would be less valuable. This is even more relevant in post-COVID as tourists might be too familiar with their nearby regions (Arefieva, Egger & Yu, 2021).

2. Materials and Methods

Case Background

Valle Del Cauca, a Department of Colombia, is an emerging birdwatching destination. This region of western Colombia is home to about 50% of the country's species; as for municipalities according to SITUR (2018), Cali is the one with the greatest diversity recorded with 561 species, followed by Ibague (537), Medellin (445), Manizales (439), Popayan (338), Bogotá (269), and Pereira (203). Every year thousands of tourists come especially from the United States and Europe to enjoy this immense natural wealth. To meet this demand, Valle del Cauca created a Bird Watching Tourism Club—an initiative for the conservation of these species, led by the Ministry of Commerce, Industry and Tourism, through the Productive Transformation Program PTP, in partnership with the National Audubon Society, one of the most important ONGs in the world in the field of bird conservation.

Likewise, it represents a great opportunity for economic activity for tourism after a complex time with the global Covid pandemic, representing an outlet for specialized segments, a tourist aware of the environment and the impact it generates, in addition to currently representing a profitable segment for participating companies in this sector.

Characteristics of the Sample

This study utilizes both qualitative and quantitative methods. The first part presents an interview process with experts on the field and the second part a questionnaire for tourists. A sample of 64 tourists were compiled in the study. A questionnaire was administrated to the respondents in public areas selected (rural areas around the city of Cali, where birdwatching can be enjoyed from different locations).

Table 2. Respondents Characteristics.

Gender	Total	%	Birds Knowledge Level	Total	%
Woman	21	33%	High	15	23%
Man	43	67%	Medium	30	47%
Total	64	100%	Low	19	30%
Age	Total	%	Total general	64	100%
18-24	6	9%	Education level	Total	%
25-34	18	28%	Postgraduate	38	59%
35-44	17	27%	Graduated	20	31%
45-54	19	30%	High School	2	3%
55-64	2	3%	Technician	4	6%
65 or more	2	3%	Total	64	100%
Total	64	100%

*Demogrhapic characteristics of sample.

Table 2. Respondents Characteristics.

Gender	Total	%	Birds Knowledge Level	Total	%
Woman	21	33%	High	15	23%
Man	43	67%	Medium	30	47%
Total	64	100%	Low	19	30%
Age	Total	%	Total general	64	100%
18-24	6	9%	Education level	Total	%
25-34	18	28%	Postgraduate	38	59%
35-44	17	27%	Graduated	20	31%
45-54	19	30%	High School	2	3%
55-64	2	3%	Technician	4	6%
65 or more	2	3%	Total	64	100%
Total	64	100%

*Demogrhapic characteristics of sample.

Scale Development

This research makes an important contribution of the questionnaire as a survey research tool for collecting information on the destination’s image focused on the tourist activity of birdwatching, from the perspective of tourists and visitors. For this study, a new scale of measurement was built for the specific activity of birdwatching. The process was developed using the in-depth interview as a qualitative tool. The selection of the interviewees is given through the level of experience of the expert. The following criteria are established: Expert bird watchers and experts in tourist development in birdwatching. The participation of the interviewees is given through their availability, and the purpose is to be able to develop specific items for this activity from experience in the field.

In-depth interviews were conducted with the main representatives of bird watching associations and groups in the southwestern part of the country, to identify the main aspects of bird watching activity that is related to the image of a destination from their experience. After the analysis of the interviews, three new items were determined for Factor 1 (Natural/environmental characteristics) relating to the diversity of birds and contamination conditions of the territory. Nine new items for Factor 2 (Tourist facilities/infrastructure) related, among other things, to specialized guidance, bilingualism (in this case, Spanish-English) and access to technology. Finally, three new items for Factor 5 (Social environment/travel environment) related to access to clean water and the capacity to respond to emergencies. The following table present the new scale development:

Table 3. Scale proposal for birders destinations in beliefs assessments.

Cognitive Image
Factor	Statement
Factor 1: Natural/environmental characteristics	The destination has a variety of bird species
	The destination has uncontaminated natural environments
	The destination has conditions for bird watching
Factor 2: Tourist facilities/Infrastructure	The destination has expanded financial services (ATMs, banks and currency exchanges)
	You have access to minimal shops for supplies (food and implements for sighting)
	It is easily accessible to pharmacies (24 hours)
	The destination has bilingual guides on sighting trails
	The destination has tourist informants
	It is a destination with virtual connectivity (Internet, operators and satellite telephony)
	The destination has connectivity to energy sources to load implements (e.g., cell phones and cameras)
	The destination has adequate logistics to access sighting points or tourist areas.
	The destination has a natural food offer
Factor 3: Social environment/ travel environment	The destination has accessibility to the provision of clean water
	The destination is prepared to attend the occurrence of natural events
	It is a destination that has a proper attention to health issues

*The scale proposal is a result of in-depth interviews with experts.

Table 3. Scale proposal for birders destinations in beliefs assessments.

Cognitive Image
Factor	Statement
Factor 1: Natural/environmental characteristics	The destination has a variety of bird species
	The destination has uncontaminated natural environments
	The destination has conditions for bird watching
Factor 2: Tourist facilities/Infrastructure	The destination has expanded financial services (ATMs, banks and currency exchanges)
	You have access to minimal shops for supplies (food and implements for sighting)
	It is easily accessible to pharmacies (24 hours)
	The destination has bilingual guides on sighting trails
	The destination has tourist informants
	It is a destination with virtual connectivity (Internet, operators and satellite telephony)
	The destination has connectivity to energy sources to load implements (e.g., cell phones and cameras)
	The destination has adequate logistics to access sighting points or tourist areas.
	The destination has a natural food offer
Factor 3: Social environment/ travel environment	The destination has accessibility to the provision of clean water
	The destination is prepared to attend the occurrence of natural events
	It is a destination that has a proper attention to health issues

*The scale proposal is a result of in-depth interviews with experts.

3. Results

The research model was analyzed using Partial Least Square (PLS) approach and SmartPLS software. PLS was used because the study represent the measurement of the construct of image based on a small segment of tourism as birders, allowing a reflective second order model. Incorporating Cognitive image as a reflective second-order construct requires special treatment (Duarte and Amaro 2018; Hair et al. 2017). In this analysis, Cognitive image was presented as a ‘phantom’ variable. We obtained indicators representing each dimension after running the PLS algorithm and estimating the latent variable values for each observation.

The first step to validate the measurement model is to analyze the reliability for each of the factors. This study presents reflective constructs that are expected to contain a factor load equal to or > 0.5 (Hair, et al., 1998). In the estimation of the initial model, the authors decide to eliminate the item IV4 (Cali could be my next place of vacation), the outer loading is inferior to 0.5. The evaluation of the reflective model is analyzed through (a) Cronbach's alpha, (b) composite reliability index (CRI), and (c) the mean variance extracted (AVE). Nunnally and Bernstein (1994) suggest a minimum value of 0.70 for Cronbach's alpha. Fornell and Larcker (1981) suggest values greater than 0.70 and 0.5 for CRI and AVE, respectively (see Table 4). The findings show reliability of the scale.

Table 4. Construct Reliability.

Construct	Item	Loadings	Cronbach	CRI	AVE
Affective Image	AF1	0.983	0.965	0.983	0.966
	AF2	0.983
Cognitive image	MED	0.577	0.830	0.879	0.597
	INFR	0.813
	ATR	0.728
	ACC	0.843
	ENT	0.866
Intention to visit	IV1	0.948	0.928	0.954	0.874
	IV2	0.947
	IV3	0.910

*The project has a good level of reliability for all constructs.

Table 4. Construct Reliability.

Construct	Item	Loadings	Cronbach	CRI	AVE
Affective Image	AF1	0.983	0.965	0.983	0.966
	AF2	0.983
Cognitive image	MED	0.577	0.830	0.879	0.597
	INFR	0.813
	ATR	0.728
	ACC	0.843
	ENT	0.866
Intention to visit	IV1	0.948	0.928	0.954	0.874
	IV2	0.947
	IV3	0.910

*The project has a good level of reliability for all constructs.

Discriminant validity indicates that a given construct is significantly different from another construct. To assess this type of validity, the Fornell and Larcker (1981) criteria and the HTMT matrix (Henseler, et al., 2016) are used. According to Fornell and Larcker (1981), a construct has discriminant validity if its AVE is greater than the squared correlations between this construct and the others (see Table 5). Fornell and Larcker criteria confirmed discriminant validity.

Table 5. Fornell and Larcker Criteria.

Constructs	Affective Image	Cognitive Image	Intention to Recommend	Total Image	Intention to Visit
Affective image	0.983
Cognitive image	0.030	0.773
Intention to recommend	0.258	0.291	1.000
Total image	0.656	0.336	0.639	1.000
Intention to visit	0.099	0.158	0.650	0.337	0.935

* Fornell and Larcker criteria confirmed discriminant validity.

Table 5. Fornell and Larcker Criteria.

Constructs	Affective Image	Cognitive Image	Intention to Recommend	Total Image	Intention to Visit
Affective image	0.983
Cognitive image	0.030	0.773
Intention to recommend	0.258	0.291	1.000
Total image	0.656	0.336	0.639	1.000
Intention to visit	0.099	0.158	0.650	0.337	0.935

* Fornell and Larcker criteria confirmed discriminant validity.

Once the validity and reliability of the reflective model has been demonstrated, the structural model is evaluated. For measuring relationships between variables, the beta coefficient (β), represents the strength. For the level of significance, the T-Student test is obtained from a bootstrapping process in the same statistical system. The following table (see Table 7 and Table 8) showing the findings obtained for the structural model (direct and indirect effects).

Table 7. Structural Model (Direct effects).

Direct Effects	Original Sample	Mean (M)	Standard Deviation (STDEV)	T Statistics	P Values	2.5%	97.5%	Supported /Non Supported
Affective I-> Total image	0.647	0.649	0.071	9.147***	0.000	0.509	0.778	S
Cognitive-> Total image	0.316	0.318	0.106	2.989**	0.003	0.103	0.503	S
Total image -> Intention to visit	0.475	0.476	0.195	2.441**	0.015	0.102	0.873	S
Total image -> Intention to recommend	0.811	0.803	0.165	4.932***	0.000	0.480	1.126	S

*R2= (Overall image: 0.531 (adjusted 0.515); Intention of recommend: 0.456 (adjusted 0.428); Intention of revisit: 0.140 (adjusted: 0.097)) *T-value > 1.96 ⁎ p < .05. ⁎⁎ p < .01. ⁎⁎⁎ p < .001.

Table 7. Structural Model (Direct effects).

Direct Effects	Original Sample	Mean (M)	Standard Deviation (STDEV)	T Statistics	P Values	2.5%	97.5%	Supported /Non Supported
Affective I-> Total image	0.647	0.649	0.071	9.147***	0.000	0.509	0.778	S
Cognitive-> Total image	0.316	0.318	0.106	2.989**	0.003	0.103	0.503	S
Total image -> Intention to visit	0.475	0.476	0.195	2.441**	0.015	0.102	0.873	S
Total image -> Intention to recommend	0.811	0.803	0.165	4.932***	0.000	0.480	1.126	S

*R2= (Overall image: 0.531 (adjusted 0.515); Intention of recommend: 0.456 (adjusted 0.428); Intention of revisit: 0.140 (adjusted: 0.097)) *T-value > 1.96 ⁎ p < .05. ⁎⁎ p < .01. ⁎⁎⁎ p < .001.

Table 8. Structural Model (Indirect effects).

	Original Sample (O)	Mean (M)	Standard Deviation	T Statistics	P Values	2.5%	97.5%	S/NS
Affective -> Total Image -> Intention to visit	0.307	0.314	0.141	2.175**	0.030	0.057	0.597	S
Cognitive -> Total image -> Intention to visit	0.150	0.151	0.086	1.757**	0.079	0.027	0.353	NS
Affective ->Total image -> I. Recommend	0.525	0.525	0.139	3.770***	0.000	0.276	0.801	S
Cognitive -> Total Image ->I. recommend	0.257	0.257	0.108	2.369**	0.018	0.075	0.493	S

*T-value > 1.96 ⁎ p < .05. ⁎⁎ p < .01. ⁎⁎⁎ p < .001

Table 8. Structural Model (Indirect effects).

	Original Sample (O)	Mean (M)	Standard Deviation	T Statistics	P Values	2.5%	97.5%	S/NS
Affective -> Total Image -> Intention to visit	0.307	0.314	0.141	2.175**	0.030	0.057	0.597	S
Cognitive -> Total image -> Intention to visit	0.150	0.151	0.086	1.757**	0.079	0.027	0.353	NS
Affective ->Total image -> I. Recommend	0.525	0.525	0.139	3.770***	0.000	0.276	0.801	S
Cognitive -> Total Image ->I. recommend	0.257	0.257	0.108	2.369**	0.018	0.075	0.493	S

*T-value > 1.96 ⁎ p < .05. ⁎⁎ p < .01. ⁎⁎⁎ p < .001

Affective Image has a positive and direct effect in overall image and is verified in the study with a beta of 0.647 (high), with a significant T-Value. Cognitive Image has a positive effect in overall image, has also been verified in the study, demonstrating a direct and positive relationship in the development of overall image with a beta of 0.316 (Low-medium).

Overall Image has a positive effect to the intention to recommend the tourism destination, presents a strong influence with a beta of 0.811 (high) and a significant T-value, and a medium influence to revisit intention with a beta of 0.475 and a significant T-value, corroborated both in this study. Likewise, it is identified that the Total Image is explained in 53.1% (R2: 0.531), the Intention to Recommend in 45.6% (R2: 0.456) and the Intention to Revisit the destination in 14% (R2: 0.140).

Additionally, the study identifies that affective image relates positively related to the intention to recommend and revisit the tourism destination with an indirect relationship; it is mediated through the Total Image of the destination, presenting an indirect beta of 0.525 (average-high) and 0,307 (medium-low), respectively with a significant T-Value. Also, and indirect effect of Cognitive Image over Intention to Recommend with a beta of 0.257. Cognitive Image impacts positively to intention to visit has not being validated in the present study, the relationship is not statistically significant.

4. Discussion

In this study, new empirical evidence is provided by proposing new items for a scale focused on the measurement of destination image, specifically for birdwatching. The findings allow us to analyze the customer experience from the cognitive image. The model includes two dimensions: the affective image associated with the emotions generated from the interaction with the destination through different channels and the cognitive image associated with the beliefs and knowledge of the same. In this case, the tourist manages to obtain a more holistic construction that includes the total image of the destination, reaffirming a direct and positive effect on the behavioral intentions of the birdwatching tourist—specifically the intention of visiting and recommending the destination.

For this study of birdwatching in Colombia, it should be noted that both cognitive and affective image result in a positive total image. However, it is identified that the greater weight within the formation of that total image can be attributed to the generation of emotions, because birdwatching tourists seek to have more emotional experiences when they practice this type of tourism activity. These findings support a cognitive experience that allows the accompaniment of services provided by local practitioners and operators, including combining knowledge and experience about Colombian flora and fauna—including microclimates and rare indigenous species—with provided a context for an emotional experience, that may include private tours or limited group tours among tourists that have the same emotional attachments in serene or obtrusive environments. In this way, participation might take place in the form of volunteerism in which the tourist makes a direct emotional investment in the experience.

While the success of a birdwatching destination can be attributed more to the development of a positive overall image, by having a direct and strong influence on behavioral intentions, indirect effects such as affective image can also be identified such as intention to visit and intention to recommend. These findings have implications that the emotions and feelings that the destination generates is quite important for the birdwatching tourist. The level of emotional experience before, during, and after the trip can be promoted to indirectly influence tourist behavior, obtaining a favorable recommendation for the destination through a tourist’s social network and the intention to visit from potential tourists in this network.

The cognitive image as an indirect effect on the intention to recommend is also identified—the association of beliefs and positive knowledge about the destination’s attributes can influence the tourist’s intention to recommend as a destination for a potentially rewarding birdwatching experience. Likewise, this study has identified that within the cognitive image the factors with the greatest influence are the environment, accessibility to the destination, and destination infrastructure. For practitioners in emerging or post-war destinations like Colombia that may otherwise provide excellent birdwatching locations, it is recommended that they focus on such factors as security, cleanliness, access to potable water, health services and good value for the money. In addition, for these high-affective/high-cognition tourists in emerging or post-war destinations, it is important to have accessible infrastructure with comfortable and convenient transportation. Finally, the infrastructure highlights the importance of basic services, such as food and accommodations, ease to access birdwatching locations, support services, quality services, tourism information, tourist guides and connectivity in remote locations, meaning electrical outlets for phone and phone-held photography and videography and Internet as these images can be readily posted on social media and other media outlets.

5. Conclusions

The findings show a greater interest of the respondents to recommend destinations with respect to their intention to revisit; therefore future research may consider a detailed study on the main factors that influence the intention to revisit of tourists. From a practical perspective, this information is useful for a destination to create and sustain emotional bonds with tourists. In addition, the findings of this study provide an enhanced understanding of the relationship between the affective image and the intention to recommend and revisit the tourism destination in future research, where the cultural factors of the host community are also considered and their collective relationship with an affective image can also be studied.

However, this study presents limitations, including the number of tourists sampled. Because the research was undertaken during the pandemic and the level of visiting tourists was low. Future research could provide a larger tourist sample and make comparisons between the development of the image before and after the destination visit, especially a post-hoc analysis of behavior once the destination has been visited. In addition, future research should address image formation during different stages as pre-travel, during trip and post-trip for significant changes in image formation based on trip stages. Finally, Colombia itself might be seen as somewhat as an outlier destination, given the strength of its biodiversity in a country emerging from decades of internal conflict.

Managing the destination image for the promotion of certain types of tourists can generate positive effects for the region. In this case, Valle del Cauca is a department that has a high level of potential for the promotion and development of birdwatching tourism, attracting tourists who value the development of a natural environment that allows the maintenance of biodiversity, the visualization of different species, and the care of tourist spaces for the development of this activity. The study seeks to contribute to measurement of the destination image, to understand the most relevant aspects for tourists. At the same time to be able to propose strategies that, allow the development of tourist activity based on birdwatching in a sustainable way.

This study also considers, first, the conative image in the model, through the hypotheses. Cognitive image has a positive effect in overall image. Conative image relates positively to the intention to recommend the tourism destination. Conative image relates positively to the intention to revisit intention, according to the tri-partite definition of destination, proposed by authors such as Gartner (1993 y 1994), Chen, Ji and Funk (2014), Stylos, Vassiliadis, Bellou and Andronikidis (2016), Stylos, Bellou, Andronikidis and Vassiliadis (2017), but in this case, the present study does not support this paradigm.