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• v.6(9); 2020 Sep

Modeling domestic tourism: motivations, satisfaction and tourist behavioral intentions

Berhanu esubalew bayih.

a Department of Tourism Management, College of Business and Economics, Madda Walabu University, Bale Robe, Ethiopia

b School of Management Studies,Punjabi University, Patiala, India

Investigating the antecedents of tourist behavioral intentions and its relations with the preceding factors has become an interest of researchers very recently. However, domestic tourism is one of the neglected forms of tourism among academics and policymakers in developing countries in general. This study, therefore, has tried to simultaneously analyze (i) the relationships among motivations (push and pull), satisfaction and behavioral intentions (intention to revisit and willingness to recommend), and (ii) the direct and indirect effects of motivations on the behavioural intentions of domestic tourists in the formation of domestic tourism behavioural model. The relationships were structurally analyzed with Maximum Likelihood Estimation (MLE) method of Structural Equation Modeling (SEM) using data collected from 386 domestic tourists from four destination sites in Ethiopia. The results revealed that both pull and push travel motivations were found to be significant predictors of overall satisfaction. Moreover, the direct effects of pull travel motivation on revisit intention as well as willingness to recommend were observed. On the other hand, overall satisfaction influenced revisit intention more significantly than the willingness to recommend. Overall satisfaction also partially mediated the relationships between travel motivations and revisit intention. Furthermore, the direct and indirect effects of push travel motivation were assessed in this study. The results of this study hold important implications for destination managers and researchers to consider the influences of motivations factors on satisfaction and behavioral intentions in their attempt to develop domestic tourism.

Domestic tourism, Motivation, Satisfaction, Tourist behavioural intention, Push, Pull, Intention to revisit, Willingness to recommend; Tourism; Tourism industry; Tourism management; Business management; Marketing; Consumer attitude.

1. Introduction

Tourism is one of the most important economic activities and is considered as a key to development, prosperity, and well-being. According to the United Nations World Tourism Organization (UNWTO), tourism is ‘a key driver of socio-economic progress through the creation of jobs and enterprises, export revenues, and infrastructure development’. Tourism has shown almost uninterrupted growth in the last six and a half decades demonstrating the sector's strength and resilience. Tourism today represents one of the most pivotal components of the world economy. Generating 1.6 trillion USD in 2017, tourism has become the 3rd most important export category after fuels and chemicals, which is about 7% of the world's export. Tourism is also one of the major job creators with a share of 1 in 10 jobs and accounts for about 10% of the global GDP ( UNWTO, 2017 ). Moreover, tourism is the main foreign currency generating sector for many developing countries in the world. Above all, tourism preserves culture, protects the environment, conveys peace and togetherness, and enhances economic growth and overall development that makes the sector imperative for sustainable development.

According to UNWTO (1995) , tourism could be categorized as international and domestic tourism. International tourism involves the activities of resident tourists and non-resident tourists outside their country of residence whereas domestic tourism comprises the activities of resident tourists within their own country of reference. Domestic tourism is most probably the first form of tourism ( Pierret, 2010 ), that was practiced in the earlier period of civilization. Today it continues as a significant form of tourism all over the world accounting for about 5–6 billion estimated tourist arrivals ( UNWTO, 2016 ) which is more than 74%–86% of total tourism arrivals ( Bigano et al., 2007 ; Pierret, 2010 ). This is about 73% of total overnights, 69% of overnights at hotels, and 75% of overnights in none-hotel accommodations ( Pierret, 2010 ).

Although domestic tourism is the largest portion of tourism, it remains unaddressed and overshadowed by international tourism in terms of researches and policies. However, since international tourism is highly sensitive to both internal and external environments to bring triumphant and sustainable tourism development, it should be complemented with domestic tourism. Such ignorance of domestic tourism caused lack of awareness of most tourists, underestimated total tourism numbers, misunderstood the significance of tourism, and distorted image of tourism in general ( Eijgelaar et al., 2008 ). Although tourism in general and predictors of tourist behavioral intentions, in particular, is not new to the scope of research, domestic tourism is surpassed by the interest of academics on international tourism. Consequently, there is a lack of statistics, researches, policies, and strategies on domestic tourism in most developing countries in the world ( Ghimire, 2001 ). Moreover, it is hard to find tourism marketing and management researches that systematically analyzed the interrelationships between domestic tourist motivations, satisfaction, and behavioral intentions. Such gap, in general, made it challenging for policymakers to develop effective policies and strategies on tourism management, marketing, and sustainable development.

Like many developing countries in the world, domestic tourism in Ethiopia is almost forgotten both as an issue of development and a valuable area of research. Some studies have been conducted on domestic tourism ( Ephrem, 2012 ) and on religious tourism ( Bayih, 2018 ; Gedecho, 2014 ). However, domestic tourist motivations, satisfaction, and behavioral intentions, as well as the direct and indirect effects of travel motivations on the post visit behaviour of domestic tourists, remain hardly studied. Thus, this study has tried to fill the gap through developing domestic tourism behavioural model and assessing relationships among constructs using Maximum Likelihood Estimation (MLE) method of Structural Equation Modeling (SEM). Hence, this study focuses on the structural examination of the relationships among travel motivations (push and pull), overall satisfaction, and behavioral intentions of domestic tourists in Ethiopia.

2. Review of literature

2.1. push and pull travel motivations.

Motivation is one of the basic thoughts of human behavior. There are several basic concepts that are integrated into an understanding of human motivation. There is a general idea that human motivation arises from an inconsistency between a desired and an existing condition. Kotler and Make (2014) identified motivation as one of the psychological factors that determine consumers' buying behavior. According to them, motivation is a need that reached its highest intensity, created tension and finally causes a person to act to minimize or avoid the tension.

According to International Genealogical Index (IGI) global , travel motivation is the inner state of a person, or certain needs and wants of the tourists that can be considered as one of the most important psychological influences of tourist behavior ( IGI, 1988 ). On the other hand, Pearce et al. (1998 cited in Malviya, 2005 , p. 48) defined tourist motivation as “the global integrating network of biological and cultural forces which gives value and direction to travel choices, behavior, and experience”. Hence, any motive that causes travel has been thought to fall under the two universally accepted dimensions of motivations that are the highly inter-related push and pull factors. Crompton (1979) perhaps for the first time, grouped tourist motivations in two ends as socio-psychological and cultural motives. Motives namely escape from a perceived mundane environment; exploration and evaluation of self, relaxation, prestige, regression, enhancement of kinship relations, and facilitation of social interaction were fallen under the first group while the second group constitute novelty and education. The earlier group of motives is the pushing factors while the latter category of motives is pulling factors. Hence, traditionally push motives have been used for explaining the desire to travel for vacation while the pull motives have been considered significant for explaining the destination choice of travelers. On the other hand, Dann (1977) explained the integration of both factors as push factors are the antecedents to that of pull factors. The concept regarding push and pull dimension is that people travel due to the internal forces that pushed them and the external factors of the destination attributes, expectations, benefits and travelers' perceptions that pulled them ( Baloglu and Uysal, 1996 ). Thus, push factors are widely understood as internal factors whereas, pull factors are features of the destination that attract travelers to choose a particular destination ( Albughuli, 2011 ). Push and pull factors are two different decisions made by travelers at two separate points focusing on whether to travel or not and where to travel ( Klenosky, 2002 ). Others argue as they should not be viewed as strictly different as they are basically related to each other ( Albughuli, 2011 ).

As motivations are one of the indicators of buyers' behavior and being in one or other ways influence buyers' preference, necessitate the need for researches on the motives of travelers. Different studies conducted on travel motivation suggested that understanding the traveler's motive is fundamental to tourism development. Furthermore, different researchers such as Pearce (2005) and UM & Crompton (1990) widely approved that tourists' visit patterns are the outcomes of a destination choice process which, in turn, is influenced powerfully by tourists' motives and backgrounds. However, only a few studies have been conducted on domestic tourism in general and the relationships between motivations, satisfaction, and tourist behavioral intentions. Some researchers very recently ( Bogari et al., 2003 ; Albughuli, 2011 ; Bui and Jolliffe, 2011 ; Kanagaraj and Bindu, 2013 ; Baniya and Paudel, 2016 ; Canavan, 2016 ; have tried to identify the push and pull motives of domestic tourists in different countries. On the contrary, an extensive studies can be discovered on the push and pull motivations of foreign or international tourists since earlier ( Crompton, 1979 ; Fodness, 1994 ; Mohammad and Som, 2010 ). Push and pull travel motivations as antecedents of tourist overall satisfaction and behavioral intentions have been studied from international tourist perspectives albeit discrepancies among findings have been observed.

2.2. Tourist satisfaction

Tourist satisfaction is a reaction or decision of tourists which follows emotion or cognition ( Bigne et al., 2001 ). In other words, it is the reaction referred to a specific concentration. In general, satisfaction describes the thinking, state, and thoughts emotionally after experiencing an opportunity ( Ranjanthran and Mohammed, 2010 ). On the other hand, as identified by Baker and Crompton (2000) , satisfaction is determined by gap factors such as social and psychological elements of individual tourists like expression, behavior, and needs and external environments such as weather conditions, social group interactions. Simply, satisfaction can be defined as the evaluation of a consumer after using a product or service ( Ranjanthran and Mohammed, 2010 ). Likewise, Chen and Tsai (2007) defined overall satisfaction as the extent of the overall pleasure felt by tourists resulting from the ability of the tour to fulfill the desires, expectations, and needs of the tourists. Beard and Ragheb (1980) expressed tourist satisfaction as a positive perception or that is developed by tourists by engaging in recreational activities and can be measured by a different degree of pleasure. When the destination attribute satisfies visitor needs and wants, tourists will develop a pleasant experience ( Lee, 2009 ).

Overall tourist satisfaction has a positive correlation with the quality tourist experience on the tourist site ( Tribe and Snaith, 1998 ; Lee, 2007 ). Tourist satisfaction is also an important issue for managers of tourism destinations as it influences the destination choice of tourists ( Cole and Crompton, 2003 ; Kozak and Rimmington, 2000 ) and future visitor behaviours ( Bigne et al., 2001 ; Cole et al., 2002 ; Lee, 2007 ; Yoon and Uysal, 2005 ). A number of studies revealed that satisfaction is the outcome of image and service quality ( Ranjanthran and Mohammed, 2010 ; Bigne et al., 2001 ; Chen and Tsai, 2007 ; Ngoc and Trinh, 2015 ). It also seems widely agreed that favorable satisfaction leads to positive future behavior such as increased intention to revisit and a higher willingness to recommend ( Ranjanthran and Mohammed, 2010 ; Chen and Tsai, 2007 ). However, the result of the empirical study by Bigne et al. (2001) discloses that tourist satisfaction determines their willingness to recommend the destination they have experienced to others like friends and relatives but not the other post-visit behavior, intention to revisit. On the other hand, destination attributes in general and the quality of the accommodation, accessibility of the destination, beautifulness of the scenery, the weather condition or climate and the neatness are considered as most important attributes for tourist's overall satisfaction ( Vinh, 2013 ; Som et al., 2012 ; Um et al., 2006 ).

2.3. Tourist behavioral intentions

Behavioral intention or future behavior or post-visit behavior is the judgment of the visitor about the probability of revisiting the same destination or the visitor's willingness to recommend the destination to the others ( Chen and Tsai, 2007 ). Future behavior or post-visit behavior of tourists is reflected in the form of revisit, recommendation and positive word of mouth ( Hsieh, 2012 ; Baker and Crompton, 2000 ). Customer loyalty, which is an essential issue in any business, can be reflected in terms of repeat purchase, recommendations, and releasing the positive word of mouth. Customer loyalty is one of the most important indicators of the success of marketing strategies as agreed by most marketers and the theory also works for tourism products ( Lee, 2009 ). Managers in the tourism industry assess their management strategies based on the willingness of tourists to recommend their product and share a positive word of mouth regarding their experience. Hence, as frequently mentioned by different researchers such as Baker and Crompton (2000) , Bigne et al. (2001) , Cai et al. (2004) , Lee et al. (2007) , Petrick (2004) , the intention of tourists to ‘revisit’ and their willingness to ‘recommend’ reflects behavioural intention of tourists and tourist loyalty. Intention to revisit is the tourists' interest to return to a certain destination ( Szymanski and Henard, 2001 ). Willingness to recommend also known as word-of-mouth communication refers to customers' intention to share their experiences with their friends and relatives ( Maxham III, 2001 ).

Tourist behavioral intention (revisits and recommend) may often be affected by a number of variables ranging from perceived attractiveness of the destination ( Um et al., 2006 ) to the real destination attributes ( Hsieh, 2012 ; Ngoc and Trinh, 2015 ; Mat Som et al., 2012 ). Moreover, the image of the destination, perceived quality, motivation, and visitor satisfaction are possible predictors of future tourist behavior ( Elgammal and Ghanem, 2016 ; Ranjanthran and Mohammed, 2010 ; Lee, 2009 ).

2.4. Relationships between tourist motivations, satisfaction, and behavioral intentions

In the process of reviewing past studies, the researcher has come up with four widely evidenced paths. These paths connect travel motivations directly with overall satisfaction, travel motivations directly with tourist behavioral intentions, overall satisfaction directly with tourist behavioral intentions and travel motivations indirectly with tourist behavioral intentions through overall satisfaction. Tourist motivations in general and push and pull motivations, in particular, have been identified as antecedents of tourist satisfaction and tourism destination loyalty ( Lee, 2009 ; Yoon and Uysal, 2005 ). In other words, tourist behavioral intentions have been predicted by tourist motivations and their overall satisfaction. More specifically, push and pull motivations have a strong positive relationship with both satisfaction and tourist behavioral intentions ( Khuong and Ha, 2014 ). Nevertheless, according to the empirical findings of Lee (2009) ; Battour et al. (2012) the direct relations between motivations and tourist behavioral intentions were left unsupported. In the results of these studies, motivations have a direct effect on satisfaction and an indirect effect on post-visit tourist behaviors. In another study, Yoon and Uysal (2005) , push motivation factors but not pull motivation factors determined destination loyalty. Contrary to this, the direct relation between extrinsic motivation and service loyalty was not supported in the study conducted by Suardana et al. (2014) . Moreover, some empirical findings on motivations and tourist behavioral intentions are highly paradoxical. For instance, a study by Khuong and Ha (2014) revealed that both pull and push motivation factors to have positive direct and indirect relation with return intention. Conversely, the findings of Huang and Hsu (2009) did not exhibit significant relations among motivations and tourist revisit intentions. Therefore, there is no consensus among tourism literature regarding the direct and indirect relationships between motivations, satisfactions, and tourist behavioral intentions. Such inconsistent results of prior studies and the absence of structural investigations on the aforementioned constructs in the perspectives of domestic tourism are the motives of the current research.

Pull factors have a significant relationship with domestic tourists' overall satisfaction.

Push factors have a significant relationship with domestic tourists' overall satisfaction.

Pull factors have a significant relationship with domestic tourists' intention to revisit.

Pull factors have a significant relationship with domestic tourists' willingness to recommend.

Push factors have a significant relationship with domestic tourists' intention to revisit.

Push factors have a significant relationship with domestic tourists' willingness to recommend.

Tourists express their satisfaction with behavioral responses like recommend, say positive things about and revisit the destinations ( Canny, 2012 ). It seems like the satisfaction of tourists undoubtedly determine their behavioral intentions. The direct effects of satisfaction on tourists' behavioral intentions were proven in studies conducted with different environs. A direct positive relation was observed between satisfaction and service loyalty variables among diving tourists in Bali ( Suardana et al., 2014 ). The direct effect of satisfaction on tourists' future behavior has laso been confirmed in nature-based recreational area settings ( Lee, 2009 ); in Island destination ( Ramseook-Munhurrun et al., 2015 ); in the visitors' heritage tourism experiences ( Chen and Chen, 2010 ). A significant positive association between satisfaction and tourist behavioral intentions was also observed across different niche markets. A positive direct relationship between satisfaction and destination loyalty was witnessed among the student pleasure travel market ( Kim, 2008 ); Muslim tourist ( Battour et al., 2012 ); international leisure tourist ( Khuong and Ha, 2014 ); festival attendees ( Lee and Hsu, 2013 ); domestic tourists to local natural tourist settings ( Kwenye and Freimund, 2016 ).

Moreover, a number of studies supported the direct positive effect of satisfaction on tourist behavioral intentions in general or the return and recommend intentions of visitors in particular. The link between satisfaction and tourist behavioral intentions (both intention to suggest and plan to return) was supported in several prior empirical studies ( Prayag and Ryan, 2012 ; Žabkar et al., 2010 ; Do Valle et al., 2006 ). Then again, Huang and Hsu (2009) asserted the influence of satisfaction solely on revisit intention of Chinese visitors to Hong Kong. On the other hand, a study by Lee et al. (2007) on tourists at the Korean demilitarized zone revealed that satisfaction has an effect exclusively on recommendation intention of tourists. According to Do Valle et al. (2006) , satisfaction significantly predicts the revisit likelihood and the willingness to recommend others to visit the same destination of international tourists.

Domestic tourists' overall satisfaction is positively related to their intention to revisit.

Domestic tourists' overall satisfaction is positively associated with their willingness to recommend.

A number of prior researches confirmed that tourists' satisfaction is a successful mediating variable in behavioral models of tourism ( Lee, 2007 , 2009 ; Osman et al., 2006 ). Satisfaction has been identified as a successful mediator in the relationships between destination image and loyalty ( Ramseook-Munhurrun et al., 2015 ; Prayag and Ryan, 2012 ); place attachment and future intentions ( Prayag and Ryan, 2012 ); tourist attitude, motivation and destination image and future behavioral intentions ( Lee, 2009 ); motivations and service loyalty ( Suardana et al., 2014 ).

Literature also claimed satisfaction as a full mediator on the relationship between push and pull motivations; and tourist behavioral intentions in different settings or contexts. Overall tourist satisfaction was evidenced as a full mediator in the relationship between tourism motivations and destination loyalty in the study conducted among international tourists ( Battour et al., 2012 ). The result of a study by Khuong and Ha (2014) also confirms the significance of the mediating effect of destination satisfaction on the relationship between push and pull motivational factors specifically with return intention. The mediating role of satisfaction between motivation and loyalty was also established in the study performed among festival attendees ( Lee and Hsu, 2013 ). Similarly, satisfaction acts as a moderator in the relationship between motivation and future behavior of nature-based recreational area tourists ( Lee, 2009 ). Thus, the literature supports the motivations, satisfaction, and tourist behavioral intentions relationships in different contexts. However, the following research gaps were identified based on a review of prior studies. First, almost all studies were conducted on foreign tourists albeit domestic tourism is one part of tourism which economically contributes the highest. Second, some studies have used either push or pull motivation factors and considered motivation as a single construct which contradicts with the traditional push and pull motivations in their structural examination of relationships. Then, although destination loyalty can be measured by using return and recommend intentions, prior studies didn't consider examining them separately at a construct level considering their conceptual differences. Finally, relationships among the motivations, satisfaction, and tourist behavioral intentions have never been structurally examined though their character and socio-psychological setup are different. The theoretical framework of the study is provided in Figure 1 .

Theoretical model.

The relationship between push factors and domestic tourists' intention to revisit is mediated by tourists' overall satisfaction.

The relationship between push factors and domestic tourists' willingness to recommend is mediated by tourists' overall satisfaction.

The relationship between pull factors and domestic tourists' intention to revisit is mediated by tourists' overall satisfaction.

The relationship between pull factors and domestic tourists' willingness to recommend is mediated by tourists' overall satisfaction.

3. Research methods

3.1. study area description.

This study was conducted in the country which is found in the Horn of Africa called Ethiopia. Ethiopia is a landlocked country in Africa located between the Equator and Tropic of Cancer, between the 3 o N and 15 o N Latitude and 33 o E and 48 o E Longitude geographic coordinates. Relatively the country is located east of Sudan and South Sudan, south and southwest of Eritrea and Djibouti, west and southwest of Somalia and north of Kenya. The country covers a total area of 1,104,300 km 2 and stands 26 th in the world. From the total area, approximately 1,000,000 km 2 is covered by land area and the remaining 104,300km 2 is covered by water bodies ( Bayih and Singh, 2020 ). The country is featured by high plateau terrain with central mountain range divided by Great Rift Valley. The elevation ranges from the lowest point called Danakil Depression (Afar depression) which is 125m (-410ft) below sea level to the highest point called Ras Dejen elevates about 4,550m (14,928ft) above sea level. The survey was specifically conducted in four famous tourist destination sites of the country namely Bale, Gondar, Hawassa and Lalibela. These destination sites were selected due to their unique tourism products. Bale is known for its natural tourism resources and attracts nature-based tourists. The African Camelot, Gondar, on the other hand, is known for its historical castles and colorful festivals. The Lake-town of Hawassa is attractive to leisure tourists and weekenders due to its glamorous resorts and breathtaking lakeshores. The so-called African Petra, Lalibela, is widely known for being the Ethiopian Orthodox-Tewahido Church religious pilgrimage area.

3.2. Research design and approach

This study has adopted a cross-sectional descriptive research design owing to the following reasons. First, the objective of the study is to provide a comprehensive and detailed explanation of the relationships amongst the motivations, satisfactions and tourist behavioral intentions of domestic tourists. Second, the research questions and hypotheses were organized based on theories and empirical findings. Third, the data were collected only once during a specified period of time. Moreover, quantitative approach was applied to examine both direct and indirect relationships between the aforementioned constructs.

3.3. Sampling design and sample size determination

Due to the high mobility of tourists and limited recordings of domestic tourists, it was impossible to draw the sampling frame and apply random sampling. Consequently, the samples were selected using a purposive method of sampling. Regarding the sample size, as proposed by Roscoe (1975 cited in Sekaran and Bougie, 2016 ), the rules of thumb for determining sample size, sample size more than 30 and less than 500 are appropriate. Since the total number of domestic tourists' data was not available, the largest proposed sample 384 plus 10 percent non-return or incomplete or useless rate; the sample size has become 422 domestic tourists. Hence, the questionnaire was disseminated to a total sample of 422 domestic tourists. The formula proposed by Aaker and Day (1986 cited in El-Gohary, 2012 ) also revealed the same figure (n = 384) and the projected domestic tourists, 6 million, of the Ethiopian Ministry of Culture and Tourism in 2017/18.

• z = degree of confidence (95%), S = Sample error (5%),
• P= Ratio of population characteristics in the sample (50%),
• N= Population size, n = Sample size.

However, only 386 valuable questionnaires were gathered and used for the analysis in this research.

3.4. Research instrument development

The questionnaire was the foremost and the only source of the primary data collected from domestic tourists. Domestic tourists' push and pull motivations were measured by questions developed based on different prior studies. Most of the motivation items were designed based on Yoon and Uysal (2005) , Vinh (2013) , Baniya & Paudel (2016) . Moreover, the following literature were also reviewed in the development process of both push and pull motivation items ( Park et al., 2015 ; Yousefi and Marzuki, 2015 ; Sirisack et al., 2014 ; Kanagaraj and Bindu, 2013 ; Som et al., 2012 ; Prayag and Ryan, 2012 ; Mohammad & Som, 2010 ; Kao et al., 2008 ; Kim et al., 2003 ; and Kozak, 2002 ). The items obtained were customized in accordance with the context of this study. Finally, the questionnaire was developed and measured by using a five-point Likert scale of agreement ranging from strongly disagree (1) to strongly agree (5) as applied by most prior studies.

Questions for measuring the satisfaction of domestic tourists with their travel experience were also developed based on previous studies. However, most satisfaction item scales were not directly taken rather some were modified and others were converted to related terms or concepts. The referred past researches for the organization of 24 item questionnaire used to measure satisfaction of domestic tourists include: Herle (2018) , Mohammad (2014) , Vinh (2013) , Naidoo, et al. (2011) , Alegre and Cladera (2009) , Ozdemir et al. (2012) , Hassan and Shahnewaz (2014) , Hassan and Shahnewaz (2014) . Alike reviewed literature, the satisfaction level of tourists was measured by using five-point Likert scales from highly dissatisfied (1) to delighted (5).

The behavioral intentions of domestic tourists were assessed by using multiple item questionnaires with a five-point scale ranging from ‘strongly disagree’ (1) to ‘strongly agree’ (5). The measurement scales of tourist behavioral intentions were designed after referring to a number of previous studies. Tourist behavioral intentions were grouped into two as recommend and revisit intentions. Each of these behavioral intentions had three items and developed based upon preceding studies such as by Muhammad et al. (2016) , Kwenye and Freimund (2016) , Vinh (2013) , Som, et al. (2012) . Items then were utilized for this study after being modified and restructured based on its thematic scope.

Following the development of the research instrument with additional questions to identify the demographic and travel characteristics of domestic tourists, the instrument was converted into the official language of the country, Amharic. Then questionnaires were handed to domestic tourists at the four destination sites using accommodation and destination points.

4. Methods of data analysis

The returned questionnaires were roughly observed and checked for their appropriateness. Then the questionnaire was coded and data entry was conducted by using a statistical software SPSS version 20. Data preparation was conducted before moving to the data analysis process. In this process, the entered data was screened for the availability of missing data, outliers, and erroneously filled data. The data were compiled, summarized and analyzed quantitatively using both descriptive and inferential statistics. Exploratory Factor Analysis (EFA) was conducted to reduce the dimension of each construct. Moreover, a multivariate statistical procedure such as Confirmatory Factor Analysis (CFA) was performed to check how enough the measured variables or factors represent the latent variables. The measurement model validity was conducted to see how the hypothesized model fits to the collected data and measured by using the goodness of fit statistics including Chi-square test, GFI, NFI, RMSEA, and others. Path analysis was employed to analyse the structural relationships between the exogenous or measured variables and endogenous or latent constructs, to test hypotheses, and build domestic tourism behavioral model. SEM was performed by using Analysis of a Moment Structures (AMOS) software version 23. Besides SPSS and AMOS, MS-Excel was used for data tabulation and drawing graphs.

5. Findings

5.1. socio-demographic characteristics of respondents.

Subjects of this study, domestic tourists, had a different socio-demographic background. Out of the total 386 respondents, 261 (67.6%) were male while the remaining 125 (32.4%) were female. Most of the respondents were found between 26 and 35 years of age 180 (46.6%). The ages of the remaining respondents 98 (25.4%), 86 (22.3%), and 22 (5.7%) were found below 25 years, 36–44 years, and 45 years and above respectively. The majority 220 (57%) of the respondent domestic tourists were married followed by unmarried 152 (39.4%) and divorced 14 (3.6%). The family size of the respondents was measured through the number of children in the family. Accordingly, about half of the respondents 177 (45.9%) had no children whereas the remaining 98 (25.4%), 69 (17.9%), 27 (7%) and 15 (3.9%) respondents had 1 child, 2 children, 3 children, and 4 and more children respectively. Regarding the respondents' educational status, the highest 149 (38.6%) number of respondents had a first degree (graduate) followed by the college or university students 100 (25.9%) and postgraduates 99 (25.9%). Among the 386 respondents, 111 (28.8%) were government employees, 108 (28%) were private company employees, 58 (15%) were self employees, 47 (12.2%) were businessmen/woman and 6 (1.6%) had other jobs. The majority of 123 (31.9%) of the respondents had between 3000 and 5999ETB monthly income. The rest 93 (24.1%), 53 (13.7%), and 47 (12.2%) had a monthly income of between 6000-8,999 ETB, 15,000 ETB and above, and 9,000–14,999 ETB respectively.

5.2. Descriptive statistics

A brief view of the descriptive statistic is conducted based on the mean and standard deviation scores provided in Table 1 . As can be seen from this table, ‘the need to relax both physically and mentally’ was the leading (M = 3.49, SD = 1.372) push motive of domestic tourists followed by ‘the desire to acquire knowledge about tourist destinations’ (M = 3.40, SD = 1.477). In terms of constructs, ‘knowledge or curiosity’ (M = 3.29, SD = 1.240) was the dominant push motive factor of domestic tourists followed by family and togetherness (M = 2.76, SD = 0.942). Most domestic tourists (M = 4.25, SD = 0.905) identified ‘weather or climate’ condition and ‘cultural heritage sites’ (M = 4.14, SD = 0.970) as the major destination attributes that pulled them towards destinations. From the three explored pull factors ‘cultural heritages’ (M = 4.19, SD = 0.802) was the most significant pull factor of domestic tourists followed by events and festivals (M = 3.85, SD = 1.025) and ‘natural heritages’ (M = 3.70, SD = 0.903). Domestic tourists were highly (M = 4.09, SD = 1.009) satisfied with the ‘attractiveness of attractions’. Besides, ‘the destination environmental condition’ (M = 4.08, SD = 0.955) and ‘safety and security of the destination’ (M = 4.00, SD = 1.012) were the other attributes of the destination that satisfied a large number of domestic tourists. Comparatively, domestic tourists were more satisfied with attractions or attributes of destinations (M = 3.64, SD = 0.694) next to accessibilities (M = 3.77, SD = 0.979) and amenities (M = 3.72, SD = 1.011). Most domestic tourists were ‘desired to revisit destinations’ (M = 4.24, SD = 0.924), ‘planning to return’ (M = 4.14, SD = 0.983), and promised ‘to release positive information via social media’ (M = 4.14, SD = 0.876). In general, the destination loyalty scores of domestic tourists were high that most tourists were willing to return and suggest the destinations. However, relatively, most tourists were willing to suggest what they have visited (M = 3.99, SD = 0.892) than to return (M = 3.91, SD = 0. 719) to the same destinations.

Table 1

Factor loadings, Descriptive statistics, and normality measures.

Note: FL- Factor Loading, M-mean, SD- Standard deviation, S- Skewness, K- Kurtosis.

5.3. Exploratory factor analysis

An exploratory factor analysis (EFA) was conducted before the assessments of the measurement and structural models with the purpose to reduce dimensions and extract the best possible factors. To measure the hypothesized model, a total of 59 items were developed based on literature. Initially, the row data had 15 push and 14 pull motivations, 24 satisfaction, 3 willingness to recommend and 3 revisit intention items. The analysis was conducted by using SPSS version 20, Principal Component Analysis (PCA) method of factor analysis; the varimax orthogonal rotation technique. The PCA was preferred because of its advantages in increasing interpretability of datasets and minimising information lose through building uncorrelated new variables that successively maximize variance ( Jolliffe and Cadima, 2016 ). The process brought a relatively refined and moderately correlated 10 component model with eigenvalues greater than 1 and with coefficients above 0.4. The model explained 71.142% of the total variance which is above the widely accepted threshold level of 60% for social studies ( Hair et al., 2014 ). Kaiser-Meyer-Olkin (KMO) of the modified ten component model (0.903) was in the ‘superb’ range according to Field (2009) . Moreover, the significant Bartlett's test of Sphericity X 2 (1081) = 11992.647, p < 0.0001 indicated that there are adequate correlations among variables to proceed.

The ten components were labeled after an extensive literature review, item loadings ( Hair et al., 2014 ) and the current study understandings. These components were named as knowledge or pursuit of knowledge, family and togetherness, cultural heritages, events and festivals, natural heritages, amenities, attractions, accessibilities, willingness to recommend, and intention to revisit. The factors namely knowledge; and family and togetherness were the sub-dimensions of the push motivation which contains items that describe the intrinsic or socio-psychological motives ( Crompton, 1979 ) of tourists. The other factors which were identified as cultural heritage, events and festivals and natural heritages were the sub-dimensions of pull motivation with items that were designed to measure the cultural motives ( Crompton, 1979 ) of domestic travelers. The third latent construct in this study was overall satisfaction and represented by factors labeled as amenities, attractions, and accessibilities. The last two constructs that play a significant role in tourist behavior identification were the willingness to recommend and intention to revisit.

These components all together explained 71.142% of the total variances. More specifically, the highest amount of variance was explained by the construct called amenities and explained 26.149% of the total variance with the eigenvalue of 12.290. The second highest variance was explained by knowledge which explained 10.292% of the total variance with eigenvalue of 4.837. The construct which has explained the third-highest amount of variance is cultural heritage and explained 7.581% with 3.563 eigenvalues. The fourth highest variance was explained by the construct called family and togetherness which explained 5.513% of the total variance with Eigenvalue of 2.591. The fifth-highest amount of variance was explained by the willingness to recommend and explained 5.076% of the total variance with eigenvalues of 2.386. The remaining five constructs namely attractions, events, and festivals, accessibilities, intention to revisit, and natural heritages explained 3.847%, 3.651%, 3.358%, 2.940%, and 2.734%, of the total variance respectively. The eigenvalues of these components were 1.808, 1.716, 1.578, 1.382, and 1.285, respectively (see Table 2 ). This exploratory section of the research provides an insight in to the issues of domestic tourists' behavioural intentions, and the next step is checking for the assumptions of SEM and validating the model through confirmatory factor analysis.

Table 2

Mean and standard deviation of components.

Note: M-mean, SD- Standard deviation, EV- Eigenvalues, VE – Variance Explained, α- Cronbach's alpha values.

5.4. Missing values, outliers and normality

Researchers are advised to be more vigilant about its assumptions while conducting SEM ( Kline, 2012 ). Therefore, before moving to the development of the structural model and hypothesis testing, the major distribution assumptions of SEM specifically missing values, tests for outliers or influentials, normality and multicollinearity were assessed. Only 5 missing values were found after a series observation of the entire data with the help of MS Excel and were replaced by the arithmetic mean values as recommended by ( Byrne, 2010 ). Due to the fact that the missing values were very few and occurred at random in the whole data, plus they did not surpass 5% which is suggested by Tabachnick & Fidell (2013), it can be concluded that missing value was not an issue of the data. The availability of outliers or extreme values more specifically multivariate outliers was assessed with the help of both Mahalanobis Distance (D 2 ) as proposed by ( Byrne, 2010 ) and Cook's distance. Then the data was found free from extreme values. According to the widely accepted rule of thumbs for outlier detection, the evaluation of results showed no observations with a Cook's distance of more than 3 times the mean and there was no Cook's distance value greater than 4/n where ‘n’ stands for the number of observations ( Algur and Biradar, 2017 ).

Both univariate and multivariate normality of the data were assessed using skewness and kurtosis values. However, as stated by DeCarlo (1997) kurtosis affects variance and covariance tests like SEM while skewness has an influence on tests which bases on means such as ANOVA. Since SEM is an analysis of variance kurtosis results are used to examine univariate and multivariate normality. Accordingly, the positive kurtosis values range from 0.018 to 1.860 and the negative kurtosis values range from -1.267 to -0.032. Accoutring to West et al. (1995) kurtosis values equal to or greater than 7 is an indicator of departure from normality. Therefore, there is no kurtotic item, and univariate normality is met. Multivariate normality was also assessed using Critical Ratio (CR) value which represents Mardia's (1970) estimate of multivariate kurtosis ( Byrne, 2010 ). The multivariate z-statistic is 28.348, which indicates that there is suspicion of multivariate non-normality as of the suggestion of Bentler (2005) with values greater than 5.00 as an indicator of non-normally distributed data.

On the other hand, the distribution normality of each variable for each value of every other variable (bivariate normality) was assessed using skewness and kurtosis. The result indicated that the maximum values of skewness and kurtosis -1.406 and 2.078 respectively, and these values are within the established benchmark of +/-2 of skewness and +/-8 of kurtosis suggested by Curran et al. (1996) and Henly (1993) . Accourding to Kline (2012) multivariate normality is achieved when the univariate normality and bivariate normality are met and when all bivariate scatterplots are linear and homoscedastic. Furthermore, the attainment of univariate normality and absence of outliers contribute to multivariate normality ( Kline, 2012 ). Therefore, the analysis estimations based on ML-SEM are tenable.

5.5. Multicollinearity

Multicollinearity occurs when there is a very high correlation between two or more variables ( Byrne, 2016 ). A number of attempts were made to check whether the issue of multicollinearity exists in the data set or not. First, pairwise multicollinearity among variables was assessed through correlation analysis and found plausible with the maximum correlation coefficient value of 0.648 which is less than the threshold 0.85 suggested by Kline (2005) . Then, a series of multicollinearity diagnosis analysis were performed and the maximum Variance Inflation Factors (VIF) which represents the ratio of the total standardized variance and tolerance was 2.313. This value is extremely less than 10.1 cut-off values suggested by Kline (2005 , 2016) that there is no issue of multicollinearity amongst the variables. Finally, the other measure of multicollinearity tolerance which indicates the proportion of unique total standard variance was checked. The tolerance results were greater than the recommended threshold 0.10 ( Kline, 2005 , 2016 ) which confirms the absence of multicollinearity problems among variables. Therefore, as confirmed by the three different extreme multicollinearity detection methods, the ten latent variables of the measurement model were distinct variables and the data is admissible for further analysis.

5.6. Confirmatory factor analysis

CFA was conducted with the purpose to assess the links between the latent variables and their measure variables ( Byrne, 2010 ). The CFA was conducted by using SPSS-AMOS 23 version and found supportive of the ten component measurement model. As can be seen in the pattern matrix diagram in Figure 2 , each latent construct has a causal effect with three and more (over-identified) indicator items. In addition since each measured variable loads on only one construct the hypothesized model is a congeneric model ( Hair et al., 2014 ). As shown in Figure 2 , the standardized factor loadings of each factor in the measurement model were greater than 0.69 and all p-values were statistically significant. The CFA model fit indices suggested that the first-order measurement model with ten constructs is admissible with fitness indices of X 2 (389) = 675.214, p = 0.000, CMIN/DF = 1.736, RMSEA = 0.044, SRMR = 0.0401, CFI = 0.960, IFI = 0.960, TLI = 0.952, GFI = 0.901, NFI = 0.911 ( Byrne, 2010 ; Browne and Cudeck, 1993 ; Hu and Bentler, 1999 ; Mulaik et al., 1989 ; Bentler, 1992 ; Wheaton et al., 1977 ; Jöreskog and Sörbom, 1996 ).

First order CFA (Measurement model).

5.7. Unidimensionality, reliability, and validity of the measurement model

Unidimensionality is the concept in which measured variables (indicators) are explained by only one underlying factor ( Hair et al., 2014 ). In this study, the constructs in the measurement model were assessed to check for whether there is a lack of unidimensionality (existence of significant cross-loadings) does affect the discriminant and construct validity. The constructs were found unidimensional, as evident by the absence of major cross-loadings among items.

Reliability evaluates how consistently instruments reflect the construct they are designed to measure ( Field, 2009 ). The internal reliability of the measurement model was examined with the values of Cronbach's Alpha. As shown in Table 2 , all the ten components scored higher than the widely accepted threshold of 0.7 ( Field, 2009 ; Hair et al., 2014 ). The Cronbach's Alpha values of components in this model ranged from 0.818 for attractions to 0.935 for amenities. The second highest inter-item reliability was recorded for the factor called knowledge (α = 0.915) followed by willingness to recommend (α = 0.931), accessibilities (α = 0.890), events and festivals (α = 0.878), natural heritages (α = 0.868), family and togetherness (α = 0.854), intention to revisit (α = 0.853), and cultural heritages (α = 0.826). Finally, the overall reliability of the model (α = 0.935) indicates the strong internal consistency of the scale. The other reliability measure composite reliability (CR) which shows the reliability and internal consistency of latent constructs in the measurement model ( Holmes-Smith, 2001 ) was also assessed. The CR column in Table 3 revealed that the ten construct factors have superior composite reliability which is greater than the standard value 0.7 suggested by Hair et al. (2014) .

Table 3

Convergent validity.

Note: CR-composite reliability, AVE- Average Variance Extracted, MSV- Maximum Shared Variance, MaxR(H)- McDonald Construct Reliability.

The ability of the measurement model instruments to measure what they are intended to measure ( Field, 2009 ) was cheeked through validity tests by using Stats tools Package from MS-Excel. Three types of validity were applied to examine the validity of the measurement model. Convergent validity examines the degrees of correlations among two or more instruments of the same concept ( Hair et al., 2014 ). The measurement model has achieved convergent validity as all item loadings are statistically significant with magnitudes ranging from 0.688 (Pulm2) to 0.910 (FBI2) (see Figure 2 ). Convergent validity could also be asserted by evaluating the Average Variance Extracted (AVE) for each construct. As can be seen in Table 3 , the AVE column is greater than the standard 0.5 suggested by Hair et al. (2014) . Therefore, the measurement model is free from convergent validity issues or all items were adequately converged to their respective latent constructs.

Discriminant validity of the measurement model was assessed to check the extent of difference among two related concepts ( Hair et al., 2014 ). The distinctiveness of each item was assumed by using three different ways. First, as the model is free from any major cross-loadings that as suggested by Hair et al. (2014) the constructs were distinct. Second, the uniqueness of the constructs in the model was examined by the correlation matrixes among the constructs. As shown in Table 4 , the maximum correlation between constructs was 0.648 which is lower than the threshold 0.85 (Ibid). The third way of ascertaining discriminant validity was by using Fornell and Larcker (1981) concept which compares Average Variance Extracted (AVE) with Maximum Shared Variance (MSV) and to proof discriminant validity MSV should be lower than AVE for all constructs. In other words, to satisfy the requirements of Fornell & Larcker, each AVE should be compared with its squared correlations with the other constructs of the model and AVE values should be greater than squared correlation ( Henseler et al., 2015 ). Connected to this concept, as shown in Table 3 , the MSV values are lower than the values of AVE for each construct and all AVE values were greater than squared correlations. Therefore, it can be concluded that the discriminant validity of the measurement model was established.

Table 4

Discriminant validity and factor correlation with squared root of AVE on the diagonal.

The other type of validity of the measurement model checked for is construct validity. Construct validity measures how actually measured variables represent the theoretical latent variables they are proposed to measure ( Hair et al., 2014 ). It was assessed using fitness indexes and achieved since all fitness indexes have fulfilled the required level (see Table 5 ). Thus, the measurement model had adequate construct validity. Moreover, the absence of convergent and discriminant validity issues and high construct reliability assures the construct validity of the measurement model.

Table 5

Fitness indices of the structure model.

Note: RMSEA = Root Mean Square Error of Approximation, SRMR = Standardised Root Mean square Residual, CFI = Comparative Fit Index, TLI = Tucker-Lewis Index, IFI = Incremental Fit Index, PNFI = Parsimony Normed Fit Index, PGFI = Parsimony Goodness-of-Fit Index, CMIN/DF = Normed Chi-square, PCLOSE = Closeness of fit.

5.8. Second-order CFA measurement model

Base on theories, evidence from empirical researches and purposes of the research, components were merged to form second-order confirmatory factor analysis. Hence, the two factors designed to measure push travel motivations namely knowledge and family and togetherness were merged to form a latent construct named push motives. Similarly, the three factors formed to assess the pull travel motivations of domestic tourists that are cultural heritage, natural heritage and events and festivals together formed a new latent variable labeled push motives. Finally, the three factors assigned to evaluate the overall satisfaction of domestic tourists to be exact, amenity satisfaction, accessibility satisfaction, and attraction satisfaction were combined to form a new latent variable called overall satisfaction.

As can be seen in Figure 3 , the second-order CFA also supported the measurement model for the five constructs of tourist behavioral indicators. The standardized regression weights were ranged from 0.472 for Push motives -→Knowledge to 0.762 for Overall Satisfaction --→AttractionS (satisfaction on attractions) and all p-values were statistically significant. Moreover, according to the fit indices the minimum requirement of the model was achieved with X2 (416) = 742.341, P < 0.0001, CMIN/DF = 1.784, RMSEA = 0.045, SRMR = 0.0515, CFI = 0.954, TLI = 0.949 ( Byrne, 2010 ; Browne and Cudeck, 1993 ; Hu and Bentler, 1999 ; Bentler, 1992 ; Wheaton et al., 1977 ).

Second-Order CFA measurement model.

5.9. Structural model and hypothesis testing

Following the cleaning of data and assessment of outliers, missing values, multivariate and univariate normality, multicollinearity, construct unidimensionality, measurement model reliability, and validity, and model fitness indices, the proposed relationships among the five constructs of domestic tourist behavioral indicators were examined. The hypothesized relationships were tested using the Maximum Likelihood Estimation (MLE) method of SEM. As shown in Table 5 , different fitness indices including absolute, incremental or comparative, and parsimony fit indices of the measurement model were assessed and found admissible. The structural model was evidently good with the fitness index values of X 2 (416) = 795.690, p < 0.0001, RMSEA = 0.048, SRMR = 0.0816, CFI = 0.947, TLI = 0.942, IFI = 0.948, PNFI = 0.808, PGFI = 0.746, PCLOSE = 0.714 ( Byrne, 2006 , 2010 ; Browne and Cudeck, 1993 ; Hu and Bentler, 1999 ; Bentler, 1992 ; Wheaton et al., 1977 ; Mulaik et al., 1989 ; Jöreskog and Sörbom, 1996 ).

5.10. Direct, indirect and total effects

After successfully performing the validation process of the overall structural model, the next crucial move was investigating relations among constructs or testing established hypotheses. Thus, the path diagram of the structure model depicted in Figure 4 illustrates the direct relationships among travel motivations, tourist overall satisfaction and behavioral intentions of domestic tourists. The results of the path analysis revealed that the push travel motivation of domestic tourists positively and significantly affected their overall satisfaction (β = 0.20, t = 2.284, p < 0.05). Thus, the hypothesis (H2) was tested and accepted at a 95% confidence interval. For hypothesis (H1), the pull travel motives of domestic tourists affected overall satisfaction positively and significantly (β = 0.579, t = 7.050, p < 0.01) at 0.01 significance level and the hypothesis was accepted. As shown in Table 6 , the willingness to recommend was positively influenced by pull travel motivations of domestic tourists (β = 0.213, t = 2.255, p < 0.01) and the hypothesis (H4) was accepted. Domestic tourists' intention to revisit a destination was positively influenced by their pull travel motivations (β = 0.245, t = 2.552, p < 0.05) and therefore the proposed hypothesis (H3) was accepted. The overall satisfaction of domestic tourists positively affected their intentions to revisit the destination (β = 0.282, t = 2.978, p < 0.01) and the proposed hypothesis (H7) was accepted.

Structural model.

Table 6

Direct, indirect and total effects of the structural model.

∗∗∗ - p < 0.001; N.A. – Not Available.

However, the hypothesis (H8) with the direct effect of domestic tourists' overall satisfaction on their willingness to recommend was not supported (β = 0.139, t = 1.508, p > 0.05). The other hypothesis (H6), that declares the influence of push travel motivation on tourists' willingness to recommend was not supported (β = 0.124, t = 1.483, p > 0.05) in this behavioral model of domestic tourism. Although not statistically strong, the new and somehow unexpected finding of this research is on the relation between push motivation of domestic tourists and their intention to revisit which was negative and significant (β = -0.148, t = -1.739, p < 0.1) with 90% confidence level and the hypothesis (H5) was not accepted.

The other part of the proposed relations among constructs, the indirect relations, was also assessed. The hypothesized model was tested for mediation of overall satisfaction in the relationships between push and pull motivations (travel motivations) and tourists' willingness to recommend and intention to revisit (tourist behavioral intentions). The most widely recommended ( Preacher and Hayes, 2008 ; Gaskin, 2019 ) bootstrapping method was applied to check the existence of mediation. According to Preacher and Hayes (2004) , if zero lies between the interval range of upper bounds and lower bounds, we do not reject the null hypothesis that claims the absence of significant mediation. On the other hand, if zero does not occur between the lower bounds and upper bounds interval range, there is a significant indirect effect or mediation.

Due to the fact that zero was fallen between the estimated lower (-0.015) and upper (0.117) bounds the indirect effect of push travel motivation on willingness to recommend through overall satisfaction was not statistically significant (β = 0.028, p > 0.05). Therefore, the mediating role of overall satisfaction was not observed in this study and the hypothesis (H10) was not supported. Like the direct and indirect effects, the total effect was also not significant at estimated coefficients of (β = 0.151, p > 0.05). Similarly, overall satisfaction would not mediate the relationship between pull travel motives and willingness to recommend with the occurrence of the null hypothesis zero between the lower (-0.066) and upper (0.229) bounds. Consequently, the indirect effect of pull motives on willingness to recommend was statistically not significant at estimated values (β = 0.080, p > 0.05) and the hypothesis (H12) was not supported. However, the estimated total effect (β = 0.293, p < 0.05) was significant at a 95% confidence level.

On the other hand, following the absence of zero between the lower (0.004) and upper (0.172) bounds overall satisfaction mediated the relationship between push motivation and intention to revisit albeit with a 90% confidence level. Hence, the indirect effect was statistically significant (β = 0.056, p < 0.065) and the proposed hypothesis (H9) were supported. As a result, the total effect remains statistically insignificant (β = -0.092, p > 0.05). The indirect effect of pull travel motives on revisit intention through overall satisfaction was estimated to lie between 0.015 and 0.364 lower and upper bounds respectively. Based on the same theory of the existence or absence of zero between the upper and lower bounds, the indirect effect (β = 0.163, p < 0.05) was statistically significant. Subsequently, the total effect remains significant (β = 0.408, p < 0.05). Thus, the anticipated hypothesis (H11) in this domestic tourism behavioral model was accepted.

Following the existence of statistically significant indirect relations in the model, the type of mediation was detected by comparing the effects of the exogenous variables on endogenous variables after and before mediation is involved. Accordingly, the mediating role of satisfaction in the relationship between pull travel motivations and intentions to revisit and between push travel motives and intention to revisit was found to be partial (see Table 6 ). Therefore, the overall satisfaction in this domestic tourism behavioral model was identified as a partial mediator.

6. Discussions

One of the major findings of this study is the amount of variance in the dependent latent variable explained by predictor variables. The total variance in the latent variable explained by the predictor variables is expressed with Squared Multiple Correlation (SMC equivalent to R 2 ) which is a statistic independent of all units of measurement ( Byrne, 2010 ). As shown in the structural model Figure 4 , with the R 2 value of 0.37, 37% of the variance associated with Overall Satisfaction is accounted for by its two predictors namely Push Motives and Pull Motives. Likewise, the three predictor variables specifically Overall Satisfaction, Push Motives and Pull Motives collectively explained 12% (R 2 = 0.12) of the variance in the variable willingness to recommend. Finally, 22% (R 2 = 0.22) of the variance connected with the intention to revisit is described by its three predictors exclusively Overall Satisfaction, Push Motives, and Pull Motives. This indicates that the hypothesised model explains only limited portions of post-visit behavioural intentions of local visitors. Therefore, future research should incorporate additional predictors of local visitors' behavioural intentions.

The result obtained through MLE method of SEM analysis revealed that the push travel motivation of domestic tourists determines their overall satisfaction in their experiences at destination sites. This result implies that the socio-psychological forces that caused travel to have a significant impact on the overall satisfaction of domestic tourists. This result is in agreement with previous tourism studies that suggested the influence of intrinsic motivations on tourist satisfaction ( Suardana et al., 2014 ; Lee and Hsu, 2013 ; Battour et al., 2012 ; Khuong and Ha, 2014 ). Moreover, the relationship between pull travel motivation of domestic tourists and their overall satisfaction has been confirmed by the structural analysis of the designed behavioral model. This finding strengthens past investigations conducted by Suardana et al. (2014) ; Khuong & Ha (2014) ; Battour et al. (2012) ; Vinh (2013) .

The other major finding in this study was that the direct positive effect of pull motivation of domestic tourists on both indicators of tourist behavioral intentions (i.e., intention to revisit and willingness to recommend). This finding supported the conclusions made in previous studies ( Battour et al., 2012 ; Khuong and Ha, 2014 ; Um et al., 2006 ) which has confirmed the power of destination attributes to influence destination loyalty. However, the direct influence of push travel motivations on both parts of tourist behavioral indicators could not be affirmed in this domestic tourism behavioral model. A similar finding was also witnessed in other empirical studies ( Suardana et al., 2014 ; Huang and Hsu, 2009 ).

The most frequently studied tourist behavioral construct is overall satisfaction and satisfaction as a determinant of destination loyalty or tourist behavioral intentions. The relationship between these variables was also examined in this study and the result revealed that overall satisfaction strongly and positively influenced their revisit intention but not their willingness to suggest destinations. This means the more domestic tourists are satisfied, the better their interest to revisit the same destination. This particular finding corroborated past tourism studies ( Khuong and Ha, 2014 ; Suardana et al., 2014 ; Kim, 2008 ; Battour et al., 2012 ; Prayag and Ryan, 2012 ; Huang and Hsu, 2009 ; Lee and Hsu, 2013 ; Ramseook-Munhurrun et al., 2015 ; Yoon and Uysal, 2005 ; Hui et al., 2007 ). Nevertheless, the relationship between overall satisfaction and recommendation intention remain unsupported in this study and satisfied domestic tourists are more likely to return to the destination than to suggest it to their friends and family. This finding reminds the notion that satisfaction does not always guarantee loyalty ( Mittal and Lassar, 1998 ) as customers' demand may change eventually. Moreover, satisfaction may not be enough ( Oliver, 1999 ) or may not be the only predictor of customer loyalty. Beyond this recommendation intention alone cannot serve as a single predictor of customers' future loyalty behavior ( Keiningham et al., 2007 ). Therefore, since overall satisfaction has a significant influence on the other part of tourist behavioral intention, repeat visitation intention, the general hypothesis about the relationship between overall satisfaction and destination loyalty verified in different studies ( Vinh, 2013 ; Lee, 2009 ; Battour et al., 2012 ; Prayag and Ryan, 2012 ; Yoon and Uysal, 2005 ) was partly accepted in this behavioural model.

The designed domestic tourism behavioral model also assessed the indirect relationship between the independent variables (push and pull motives) and dependent variables (intention to revisit and willingness to recommend) through the mediating variable (overall satisfaction). The mediating role of satisfaction in the relationships between push motivations and revisit intentions of domestic tourists was approved. This finding was in line with the claims of previous studies ( Lee and Hsu, 2013 ; Lee, 2009 ; Khuong and Ha, 2014 ; Suardana et al., 2014 ; Yoon and Uysal, 2005 ). Overall satisfaction has also significantly mediated the relationship between pull motivation of domestic tourists and their revisit intention which strengthened prior study findings ( Khuong and Ha, 2014 ; Battour et al., 2012 ). Nonetheless, overall domestic tourist satisfaction was evidenced as a partial mediator in the relationship between travel motivations and tourist revisit intention. On the other hand, the mediation of overall satisfaction in the relationships between travel motivations (push and pull) and tourists' recommendation intention was not supported in this particular study. This finding contradicts prior studies ( Battour et al., 2012 ; Suardana et al., 2014 ) which claimed the mediating role of satisfaction between motivation and loyalty in general.

To summarise, this study suggests that pull travel motivation factors or cultural motives are the major antecedents of satisfaction, revisit intentions and recommendation readiness of domestic tourists. In this study satisfaction positively significantly predicted revisit intention but not willing to recommend. On the other hand, pull travel motivation strongly and positively influenced willingness to recommend and revisit intentions. Therefore, it can be concluded that the attributes of destinations are the most critical elements that control domestic tourists' satisfaction on their travel experiences and their destination loyalty. It could also be said that domestic tourists' behavioral intentions were strongly influenced by extrinsic motives than their intrinsic motives and overall satisfaction. This empirical finding is in harmony with a prior study ( Um et al., 2006 ) in the cases of international pleasure tourists in Hong Kong (see Table 7 ).

Table 7

Summary of results of the direct relationships among constructs.

∗∗∗p < 0.001, ∗∗p < 0.05, ∗p < 0.1.

6.1. Theoretical implications

The findings of this study confirm the logicality of push and pull travel motivation constructs for predicting satisfaction and post-visit behaviors of tourists as recommended by ( Suardana et al., 2014 ; Kim, 2008 ; Yoon and Uysal, 2005 ; Khuong and Ha, 2014 ; Battour et al., 2012 ). However, in the case of this domestic tourism study, pull travel motivation is the strongest construct influencing overall satisfaction, revisit and recommendation intentions. This is maybe due to the fact that the existence of the destination attributes is the main reason for their travel to the destinations. The other independent variable push travel motivation has a positive relationship with overall satisfaction but not with the tourist behavioral intentions. One of the new findings of this study is the occurrence of a negative relationship between push motivation and intention to revisit domestic tourists albeit not significant and initiates further studies on the interaction among the constructs. Moreover, this study provided empirical support by identifying the push and pull motivation factors of Ethiopians who travel domestically.

The positive relation of overall satisfaction with the intention to revisit is not surprising, as it supports the loyalty theory and empirical findings ( Prayag and Ryan, 2012 ; Battour et al., 2012 ; Khuong and Ha, 2014 ). However, in this study, a weak relationship was observed between overall satisfaction and willingness to recommend the destination constructs. This weak relation may be caused by different reasons 1) poor recommendation habit of domestic tourists via word of mouth or other social media, 2) familiarity of tourist destinations in the country, 3) personal and religious reasons. This satisfaction-recommendation fallacy is the other new finding of this research and initiates further investigations on domestic tourism.

This study also supported the mediating role of overall satisfaction in the relationship between push and pull motivations and future behavioral intentions particularly revisit intention. However, the mediating role of overall satisfaction was limited to partial mediation. This implies that the direct relations are stronger than the indirect relations which may be caused by the strong attachment of domestic tourists with destinations. Since tourists are visiting their own country, their satisfaction level may not be the only determinant of their future behavior. Even some travels such as educational tour, travel for research, conference, and religious fulfillment might probably be independent of their previous satisfaction levels.

The two constructs that represent post-visit behaviour of tourists namely revisit and recommend intentions were considered and measured as a single construct and named as destination loyalty or behavioral intention in previous studies ( Yoon and Uysal, 2005 ; Lee, 2009 ; Suardana et al., 2014 ; Kim, 2008 ; Battour et al., 2012 ). However, in this study, they were examined independently at a construct level after confirming the discriminant validity and multicollinearity issues. The findings further confirm the distinctiveness of these constructs and that a one who is willing to recommend may not be interested to revisit and vies versa. This shows that the two forms of behavioral intentions are distinct and should be assessed separately in order to better understand tourists' post-visit behaviors and predict demands. At last, the empirical findings of this study provide plausible evidence that the structural equation model designed to measure the relationships among domestic tourists' push and pull travel motivations, satisfaction, and tourist behavioral intentions simultaneously was admissible.

6.2. Managerial implications

In the exploratory section of this study, two push and three pull major motivational factors of domestic tourists were identified. Therefore, in order to appeal to the socio-physiological and cultural forces of travel, destination managers and marketers should consider the actual inferences of those motivational components in their decision makings as they can determine the overall satisfaction and post-visit behavior of domestic tourists. Moreover, in the proposed behavioral model, it has been clearly observed that pull travel motivation factors (attractions, accessibilities, and amenities) were the major determinants of domestic tourists' overall satisfaction and behavioral intentions. Therefore, in order to improve the satisfaction of domestic tourists with their visitation experiences and to advance their revisit and recommendation intentions, destination managers must focus on the development and conservation of cultural and natural attractions; improvement of transportation facilities; development of various facilities and activities. Destination marketers should also understand the cultural motivation forces of domestic tourists and carefully produce and deliver promotional packages to potential travelers.

Destination managers should also focus on the internal motivation factors of domestic tourists and consider its positive relationship with satisfaction. Besides, since overall satisfaction is one of the major predictors of domestic visitors revisit intention, destination managers should try to achieve maximum satisfaction through delivering quality services, fulfilling ancillary services, introducing appealing activities, and preserving the originality of heritages. In addition, the relationship between satisfaction and recommendation was found weak and insignificant that destination managers should study the detail characteristics of domestic tourists and find ways to strengthen the connections between the constructs. The results of this study have shown more resemblance to domestic tourism behavioral studies conducted earlier than international tourism. This strengthens the notion that domestic tourism is a distinct niche market with its own unique characteristics. Thus, destination managers are advised to design a typical tourism development policies and strategies to enhance its development and boost its contribution to the economy of the country at large. Lastly, this study asserts the general theory of ‘customer loyalty’ and the plausibility of applying it to the domestic form of tourism. Therefore, destination managers and marketers may estimate the role of push and pull motivation factors on determining their demand, satisfaction and post-visit behavior of domestic tourists. Moreover, it is essential to consider the causal relationship of motivations, satisfaction and tourist behavioral intentions in the development of domestic tourism policies, strategies, and decision makings.

7. Conclusion

Developing domestic tourism is essential for its dynamic economic, socio-cultural and political reimbursement ( Mazimhaka, 2007 ). The stepping stone to the advanced development of domestic tourism lies in distinguishing tourists' motivations, satisfaction, behavioral intentions, and their interrelationships. However, there are very few studies that examined the relationships between the aforementioned constructs structurally in the context of domestic tourists. Moreover, most past studies evaluated travel motivation of tourists through either push or pull motives ( Huang and Hsu, 2009 ; Lee and Hsu, 2013 ) and conclude about destination loyalty based on either of the two tourist behavioral intents ( Khuong and Ha, 2014 ; Huang and Hsu, 2009 ). Hence, in this empirical study, causal relationships among motivations (push and pull), overall satisfaction and behavioral intentions (recommend and revisit) of domestic tourists in Ethiopia were structurally examined after developing and validating domestic tourism behavioural model using MLE method of SEM.

The exploratory section of this study has brought with two major socio-psychological driving forces of domestic travelers namely knowledge and family and togetherness. Moreover, the cultural factors of domestic travelers were identified as natural heritage, cultural heritage and, events and festivals. The CFA supported the adequacy of the data for the hypothesized measurement model with the strong loading of each indicator on its respective latent constructs and acceptable fit indices values. Prior to conducting SEM, all the assumptions particularly, missing values, outliers, normality, multicollinearity, unidimensionality were checked and the data was found feasible for further analysis. Besides, the extent of how items come together under each component and the distinctiveness of components have been confirmed through measures of convergent and discriminant validity respectively. Moreover, both the designed measurement model and the structural model were checked for their fitness and found relatively fitted to the data.

The path analysis of the designed behavioral model indicated that push travel motivation has a direct positive effect on overall satisfaction. In this regard, an improvement in the socio-psychological drives leads to better satisfaction with domestic tourists. However, the influence of push travel motivation on the post-visit behavioral variables couldn't be significantly proved. Based on this behavioral model for domestic tourism the intrinsic forces of tourists that desire them to travel do not assure their future behavioral intentions. On the contrary, pull motivation of domestic tourists has shown a positive direct influence on their overall satisfaction, willingness to recommend and intention to revisit. This implies that in the case of domestic tourism, pull motives but not push motives are the most important predictors of overall satisfaction and future behavioral intentions. Whenever the pull travel motives (destination attributes) get superior, it enhances the overall satisfaction, intentions to return and suggest of domestic tourists. In other words, it could be concluded that the stronger pull travel motivations domestic tourists have, the higher degree of overall satisfaction, recommendation willingness and revisit intention to the destinations.

With regards to the relationships between overall satisfaction and tourist behavioral intentions, only its relationship with the return intention was supported significantly. Its relation with the other indicator of tourists' post-visit behavior, willingness to recommend was still positive but not significant. Therefore, it is possible to draw a conclusion that satisfied domestic tourists are more likely to revisit the destination than recommend it to others. The structural model also supported the indirect effect of push and pull motives on domestic tourists' revisits intention through their overall satisfaction albeit partially. However, in this study, overall satisfaction did not mediate the interaction of push and pull travel motivations with the willingness to recommend. Therefore, overall satisfaction only partly mediated the relationships between travel motivations and tourist behavioral intentions.

Finally, with regards to motivation-→satisfaction -→ tourist behavioral intentions sequential relationships suggested by prior researches, the structural analysis of interrelationships among the constructs as a whole supports the model. However, it is theoretically important to be cautious about the last link and indirect relationships. Following the observed differences between the findings of this study and some prior studies conducted on international tourists, it is probably essential to think about different policies and strategies for domestic tourism.

7.1. Limitations and future studies

Although all the analysis processes were performed serially and the findings are genuine, the study is not free from limitations. This study was conducted based on cross-sectional data collected from randomly sampled 386 domestic visitors from four destinations over a one-year period to examine the behavioural model of domestic tourists. Hence, the model can be rigorously improved through incorporating tourist data for multiple years from vast destination points. The model was fit with all goodness of fit measures; nevertheless the predicting variables did not efficiently explain tourist behavioral intentions. Therefore, extending this behavioral model by including additional predictors such as destination image, perceived quality, place attachment, and perceived value will help to thoroughly understand domestic tourists' behavioral intentions.

Declarations

Author contribution statement.

B.E. Bayih and A. Singh: Conceived and designed the experiments; Performed the experiments; Analyzed and interpreted the data; Contributed reagents, materials, analysis tools or data; Wrote the paper.

Funding statement

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Competing interest statement

The authors declare no conflict of interest.

Additional information

No additional information is available for this paper.

Acknowledgements

The authors would like to express the deepest appreciation to cooperative brothers and sisters who facilitated the data collection process in the four data collection sites.

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Post-visit Tourist Engagement Strategies for DMOs

by Bryan Reynolds | Sep 18, 2023 | Destination Marketing

Destination Marketing Organizations (DMOs) are entities responsible for promoting a town, city, region, or country to attract visitors. The importance of post-visit tourist engagement cannot be overstated as it helps to create lasting relationships with tourists, encouraging them to return and spread positive word-of-mouth. Post-visit engagement helps in building loyalty and encouraging repeat visits. Here are insights and strategies for DMOs to engage tourists effectively after their visit.

Effective Post-Visit Engagement Strategies

Personalized communication is a powerful tool for post-visit engagement. This can be achieved through targeted email marketing campaigns and active social media engagement. Content marketing, such as engaging blog posts and encouraging user-generated content, can keep the destination at the top of tourists’ minds. Implementing loyalty programs and incentives, like discounts and special offers, rewards for loyalty points can also encourage repeat visits.

Step-by-Step Process to Engage Post-Visit Tourists Effectively

Step 1 – collect data.

Gather data about the visitors during their stay, including preferences, activities, and feedback. Use this data to understand their needs, expectations, and areas of interest.

Step 2 – Segment Your Audience

Based on the collected data, segment your tourists into different categories. These categories can be defined by demographic data, interests, or behavior during their visit.

Step 3 – Develop Personalized Communication

Using the insights from the segmentation, develop personalized messages for each group. These messages could be about new attractions, discounts, or events that would likely interest them.

Step 4 – Implement a Communication Channel

Decide on the most effective channel to communicate these messages. This could be through email marketing, social media, or direct mailings.

Step 5 – Create Engaging Content

Develop engaging content that will appeal to the tourists. This could include blog posts about local attractions, features on local businesses, or user-generated content from other tourists.

Step 5 – Launch a Loyalty Program

Encourage repeat visits by offering incentives through a loyalty program. This could include discounts on future visits, special access to events, or rewards based on points accumulated from previous visits.

Step 6 – Request Feedback

After communicating with the tourists, ask for their feedback. This will help you understand their current interests and improve your future engagement strategies.

Step 7 – Analyze and Adjust Your Strategy

Regularly review and analyze the success of your engagement efforts and make adjustments as necessary. This will ensure your strategy remains effective and relevant to your audience’s interests.

The Significance of Post-Visit Engagement

Post-visit engagement enhances visitor experiences by providing personalized content , responses, and offers based on their interests and behaviors. It aids in building long-term relationships with tourists, fostering loyalty, and increasing the likelihood of repeat visits. Moreover, it results in economic benefits for the destination through increased tourist spending and boosted local economy.

• Visitor Retention is effective post-visit engagement and ensures a higher likelihood of tourists returning to the destination, leading to greater profitability and sustainability for the local tourism industry.
• Enhancing reputation-positive experiences and sustained post-visit communication can lead to tourists becoming advocates for the destination, amplifying its reputation through word-of-mouth marketing.
• Post-visit engagement allows for personalized communication based on the visitor’s preferences and behaviors during their visit, which can increase their satisfaction and loyalty levels.
• Data Collection and engagement allow DMOs to gather valuable data for improving future marketing strategies, understanding visitor demographics, and making informed decisions.
• Economic Benefits of repeated visits spurred by successful post-visit engagement can lead to increased spending in the destination, boosting the local economy and supporting businesses.

Understanding Tourist Behavior

To devise effective post-visit engagement strategies, understanding tourist behavior is crucial. This involves tourist journey mapping to identify key touchpoints during their visit.

Personalized Marketing

By understanding tourist behavior, DMOs can create personalized marketing campaigns that resonate with specific segments of tourists, enhancing their post-visit experience and fostering a deeper connection with the destination.

Improved Services and Offers

Insights into tourist behavior can help DMOs refine their services and offers to meet the preferences and expectations of tourists, potentially leading to increased satisfaction and loyalty.

Better Communication

Understanding tourist behavior allows for more effective communication, which can be tailored to resonate with their experiences and interests, furthering post-visit engagement.

Predictive Analytics

Studying tourist behaviors can help DMOs anticipate future trends, allowing them to stay ahead and implement proactive strategies.

Enhanced Visitor Experience

By understanding the needs and wants of tourists, DMOs can enhance the overall visitor experience, increasing the likelihood of return visits and positive word-of-mouth.

Collecting visitor data such as preferences, activities, and feedback can provide valuable insights into their needs and expectations, helping to tailor future marketing and engagement efforts.

Leveraging Technology

Technology plays a key role in post-visit tourist engagement. Customer Relationship Management (CRM) systems can help manage visitor data and personalize communication. Mobile apps and push notifications can provide real-time updates and offers. Chatbots and AI-powered assistance can offer immediate responses to queries, enhancing the visitor experience. Tourism kiosks are also a viable option to get up-to-date information to them where they are. 

The importance of post-visit engagement for DMOs cannot be overstated. It not only enhances visitor experiences but also fosters long-term relationships and boosts the local economy. As DMOs navigate the ever-evolving tourism landscape, adopting effective post-visit engagement strategies and leveraging technology will be critical. The future of tourist engagement promises exciting possibilities with the continuous advancements in technology.

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A progressive nonprofit that has been shelling out cash to anti-Israel protest groups is being sued by Black Lives Matter Global Network Foundation for fraud and withholding more than $33 million in donations, a bombshell lawsuit claims.

Tides Foundation, which has managed hundreds of millions in donations for progressive groups since it was founded in 1976, has “refused to honor its promises and continues to commandeer BLMGNF’s donations,” according to the 285-page lawsuit filed in California Superior Court, Los Angeles County, on Monday.

Instead, Tides doled out an undisclosed amount of donations to a radical BLM breakaway group run by anti-police activist Melina Abdullah — who lost a “frivolous” lawsuit against BLMGNF — according to court papers and an attorney for BLMGNF.

Tides, a Los Angeles- and San Francisco-based nonprofit, acts as a fiscal sponsor — essentially, a clearinghouse that collects donations for groups that may not have 501(c)(3) tax-exempt status.

In addition to BLMGNF and other BLM groups, it manages donations for pro-Palestinian groups that have supported anti-Israel protests across the country.

Billionaire George Soros and his son Alex Soros have funneled nearly $14 million from their Open Society Foundations to Tides , which sponsors activist groups including the pro-Palestinian Adalah Justice Project and others fueling campus protests.

“Tides has engaged in deceptive business practices and has operated in a quasi-banking capacity without appropriate regulatory oversight of licenses,” the BLMGNF lawsuit says. “Tides operates with a level of autonomy and minimal regulatory scrutiny that is starkly at odds with the regulatory framework imposed on traditional financial institutions.”

According to the lawsuit, Tides has more than $1.4 billion in assets and allegedly acts as a bank — only without banking regulations.

BLMGNF, the national organization of the civil rights movement founded in 2017, took in tens of millions in donations after the death of George Floyd in 2020.

At the time, the group did not have tax-exempt status from the IRS, and approached the Tides Foundation to help it manage the flood of cash.

Tides, which takes a percentage of donations to manage a group’s funds, gave verbal assurances that it would return the collected money once BLMGNF received tax-exempt status, the lawsuit claims.

In the meantime, it managed donations in a “collective action fund” that would be accessible to BLMGNF, according to the lawsuit.

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BLMGNF ended its relationship with Tides in 2022, and Tides has refused to hand over the cash, totaling some $33 million, the complaint says.

Instead, Tides, which takes between 3% and 9% of the donations it processes, has sent part of the funds to other BLM groups without the permission of BLMGNF, the lawsuit says.

On June 9, 2022, a Tides official said Tides had transferred $7.4 million from the collective fund back to BLMGNF.

Instead, it sent part of the cash — $4.75 million — to an unaffiliated BLM chapter in Oklahoma City, the lawsuit says.

“It is unclear why such a large amount would have been granted to a single city’s BLM chapter,” the lawsuit says.

In a statement to The Post Wednesday, a spokeswoman for Tides Foundation called the allegations in the complaint “completely false.”

“Resources in the Black Lives Matter [collective action fund] were never intended to be granted to large, well-funded national organizations like Black Lives Matter Global Network Foundation, and were always intended to be granted to local Black Lives Matter chapters,” the Tides statement says. “BLMGNF’s lawsuit seeks to circumvent the intent of the Fund’s donors and deprive grassroots Black Lives Matter chapters critical resources, for its own benefit.”

While Tides’ website mentions that it offers “grant management,” an attorney for BLMGNF said in a statement to The Post that Tides was not authorized to dole out donations earmarked for BLMGNF to offshoot groups or local chapters.

Tides said it had granted $12.6 million from the Support Fund to groups, including BLM Grassroots, a breakaway group helmed by activist Melina Abdullah.

She tried to collect $10 million from BLMGNF in a “frivolous lawsuit” for her breakaway BLM Grassroots. Abdullah — who is running as independent candidate Cornel West’s running mate in the US presidential election — lost the lawsuit last year and was ordered to pay more than $700,000 in BLMGNF legal fees and costs.

An attorney for BLMGNF cited a June ruling by a Los Angeles Superior Court judge who dismissed BLM Grassroots’ claims to any of BLMGNF’s donations.

“This lawsuit against the Tides Foundation is not just about financial discrepancies but the principle of rightful ownership and transparency that should govern partnerships in social justice funding,” attorney Byron McLain said Wednesday.

In a statement to The Post, BLMGNF said it “never expected to become victims of … unscrupulous business practices” in social justice philanthropy.

“There is an expectation for Black Lives Matter to challenge systems, break barriers and uphold the truth, no matter how uncomfortable,” the statement said. “Today, that extends into non-profit operations as we call out Tides Foundation and other so-called ‘fiscal sponsors’ who exploit their role.”

BLMGNF has had its own issues with finances, after raking in $90 million in donations for 2020 alone.

Patrisse Cullors, the group’s co-founder, then went on a multimillion-dollar home-buying spree, purchasing two homes in Los Angeles and a property in the Atlanta suburbs with an airplane hangar and runway, as first revealed by The Post.

Cullors denied that she used donations to buy the properties.

She resigned from BLMGNF a month later, in May 2021.

Cullors also signed off on a $6 million Los Angeles mansion, to be used as an office for BLMGNF, and an $8 million property in Toronto for the group’s Canadian chapter.

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• Case Report
• Open access
• Published: 16 May 2024

Exacerbation of central serous chorioretinopathy during trauma-confronting psychotherapy– a case report

• Eva Schäflein 1 , 2 ,
• Christian Mardin 3 ,
• Eva Morawa 1 ,
• Sophia Rudolf 1 ,
• Yesim Erim 1 &
• Cosima Rhein 1  

BMC Psychiatry volume  24 , Article number:  368 ( 2024 ) Cite this article

Metrics details

Psychotherapy for post-traumatic stress disorder, in particular trauma-confronting psychotherapy, can be associated with increased stress. However, research on the somatic impact and psychosomatic interactions of these psychological stress reactions is lacking. We report on a 43-year old man whose central serous chorioretinopathy exacerbated upon trauma-confronting psychotherapy.

Case presentation

We report on a man with pre-diagnosed, asymptomatic central serous chorioretinopathy who underwent inpatient psychosomatic therapy. He disclosed a history of sexual abuse by a family member and consequently showed intrusions, flashbacks, nightmares, avoidance behavior, and hyperarousal. Thus, we diagnosed post-traumatic stress disorder. After a stabilization phase, he underwent trauma-focused psychotherapy including trauma confrontation. In the course of this treatment, acute vision loss with blurred vision and image distortion of his right eye occurred. An ophthalmologic visit confirmed a relapse of a pre-diagnosed central serous chorioretinopathy. The analysis of stress biomarkers showed a decrease in testosterone levels and a noon peak in diurnal cortisol secretion, which is indicative of a stress reaction.

Central serous chorioretinopathy may exacerbate upon psychotherapeutic treatment. In this case, an exacerbation of chorioretinopathy was observed in direct relation to the therapeutic intervention. Psychotherapists and ophthalmologists should collaborate in the psychotherapeutic treatment of patients with chorioretinopathy. Our case demonstrates the need to consider the possible increased stress levels during psychotherapy and resulting physical side effects, such as exacerbation of an existing condition. It is advisable to adjust the level of generated stress particularly well in the presence of stress-inducible physical diseases. Our case is a good example of the interplay between psychological and physical stress.

Peer Review reports

Central serous chorioretinopathy (CSC) is an eye disorder affecting mainly males with a mean age of 40 years. In its typical appearance, it is characterized by a thick choroid, a serous retinal detachment involving the area of the macula, and retinal pigment epithelium detachment. CSC appears to have a multifactorial pathogenesis, in which venous congestion, inflammation, ischemia, and changes in the hormonal and biochemical milieu seem to play a role [ 1 ]. In particular, increased levels of endogenous or exogenous glucocorticoids are associated with the development of CSC [ 2 , 3 ]. Some studies have shown that the pathogenesis of CSC is strongly related with a dysregulation of the HPA axis, which plays an important role in the stress response and various mental disorders [ 4 ]. Accordingly, psychological stress is one of the most important risk factors [ 5 ]. A study of war veterans showed that post-traumatic stress disorder (PTSD) was strongly associated with the development of CSC [ 6 ].

One central component of PTSD treatment is trauma-confronting/ exposure psychotherapy, which leads to a temporary increase of stress [ 7 ]. Stress again can cause exacerbations of CSC [ 5 ]. Consequently, in patients suffering from PTSD with a history of CSC, stress-inducing trauma-oriented psychotherapeutic treatment including trauma exposure might have an impact on CSC. However, to our knowledge, there is no research reporting on the course of CSC in PTSD patients during a trauma-focused psychotherapeutic treatment.

Patient information

The 43-year old industrial mechanic had been married for three years and coupled with his wife for 16 years in total. He described the relationship as harmonic and supportive. The couple had no children and lived in a rental apartment. The patient had not been working for 1.5 years due to his psychiatric illness. Before that, high workload and limited capacities to perceive own boundaries regarding work and altruism for friends and family members had led to constant excessive demand. He received money from an occupational disability insurance and had applied for a disability pension (procedure ongoing). He did not have any debts or financial problems. He suffered also from a recurrent central serous retinopathy (CSR) which was stable at the timepoint of admission.

At admission, the patient reported intrusions, flashbacks, nightmares, avoidance behavior, and hyperarousal, in addition to sleep disturbances, tremor, and concentration problems. He described depressed mood, low energy, loss of interest, feelings of guilt and insufficiency, and rumination. Additionally, he reported exacerbations of arterial hypertension upon stressful situations.

The patient had received 50 sessions of ambulatory psychotherapy for depression six years before admission. At that time, the patient had not yet been diagnosed with PTSD due to considerable avoidance behavior. One year before admission, he had undergone a psychosomatic rehabilitation inpatient treatment. In the course of this treatment, memories of traumatic events had come up. During the three months before admission, he had received ambulatory psychotherapy. In addition, he received regular ambulatory psychiatric visits. These therapies had led to a temporary relief of depressive symptoms, which recurrently relapsed after a while. As it had been challenging to diagnose PTSD before due to lacking access to traumatic memories and then due to avoidance behavior, the patient had only been diagnosed with PTSD shortly before being recovered in our department.

The patient and his elder brother had grown up in an atmosphere of emotional neglect. Between the age of 10 and 13 years, the patient had been sexually abused by a family member and had no possibility to disclose his experiences to any family member due to a lack of trust. A distantly related family member had given him support and safety.

Clinical findings

Psychopathological assessment.

Patient awake, fully oriented, friendly. Subjective lack of concentration and retentiveness, which cannot be objectified during the visit. Depressed mood, anxious, feelings of guilt and insufficiency. Limited affective vibratory ability, reduced energy. Rumination. No signs of psychosis. No compulsions. Depersonalization. No relevant further dissociative symptoms. Intrusions, flashbacks, avoidance behavior, hyperarousal. Social withdrawal. No self-harming behavior. No signs of suicidality.

Psychometric assessment at admission

The Essen Trauma Inventory (ETI) [ 8 ] supported the diagnosis of a post-traumatic stress disorder (46 points). The Beck Depression Inventory (BDI-II) [ 9 ] suggested severe depressive symptoms in self-report (47 points). When compared to the clinician-rated diagnosis of a medium depressive episode, the higher score in self-report might have been associated with the patient’s feelings of insufficiency.

Physical examination findings

No noticeable problems apart from adiposity grade I WHO and a bursitis of the right shoulder.

Medication at inpatient admission

Sertraline 150 mg 1-0-0, quetiapine retard 25 mg 0-0-1, lercanidipine 10 mg 1-0-1, metamizole 500 mg 1-0-1, ibuprofene 600 mg 1-0-1 (italics: was stopped in the course of the inpatient treatment) .

The patient was not receiving corticosteroid therapy, either systemically or topically, which could impact the course of the disease.

Consultation of the department of ophthalmology (week 9 of inpatient stay)

On appearance, the patient reported reduced visual acuity on his right eye and suspected a recurrence of a known central serous retinopathy. Visual acuity was 20/50. The patient complained about blurred vision and micropsia. Clinical examination revealed a detachment of the central retinal pigment epithelium (RPE) and serous detachment of the central retina without hemorrhage or sign of exsudation on the right eye. OCT revealed a central elevation of neurosensory retina by 600 μm with an underlying detachment of RPE. In the course of follow-up, subretinal fluid was reduced substantially and RPE detachment decreased in height. As with OCT and by the clinical picture, macular neovascularization was ruled out, i.e. acute CSC recurrency was the diagnosis. His history showed already recurring episodes of CSC and there was no further report of other eye diseases or refractive error.

Under supportive therapy with brinzolamide 10 mg/ml eye drops 2x/d and eplerenone 50 mg/d fluid withdraw in two month’s time, visual acuity turned to 20/20 and subretinal fluid resolved in SD-OCT (Fig.  1 ). Our therapy was beyond guidelines for CSC treatment, but was adapted to the individual patient and to clinical experience.

SD-OCT shows on the right eye recurrency of subretinal fluid at the time of presentation and its resolution under therapy. Uninvolved left eye shows normal foveolar depression

Laboratory assessment at admission

No abnormalities in routine parameters apart from pre-diagnosed hypercholesterinemia. Leucocyte count (5400/µl at admission, 5300/µl at dismissal) and C-reactive protein values (1.1 mg/l each at admission and at dismissal) as potential markers of inflammation were in the normal range at the beginning and end of the psychotherapeutic treatment.

Laboratory assessment (week 10 of inpatient stay)

To assess the biological stress reaction, we analyzed several stress marker (Table  1 ).

Testosterone values were decreased in the patient. Other analyzed stress markers were within the reference values.

To get deeper insight into the biological stress reaction, we analyzed the day profile of cortisol secretion using a liquid chromatography-tandem mass spectrometry (LC-MS/MS) assay (Table  2 ).

While morning and evening values were in the normal range, the noon value showed an increased cortisol level. This peak was indicative of a stress reaction [ 10 ].

According to the CARE guidelines [ 11 , 12 , 13 ,], a timeline is provided for an overview of the patient’s course of care (Table  3 ).

Diagnostic assessment

For psychiatric diagnostic assessments, we used clinician-rated self-reported questionnaires (ETI, BDI-II). We analyzed biological stress markers using a liquid chromatography-tandem mass spectrometry (LC-MS/MS) assay.

The patient was diagnosed with a post-traumatic stress disorder, a medium depressive episode in the course of a recurrent depressive disorder, psychological and behavioral factors in the context of arterial hypertension (exacerbations of arterial hypertension upon episodes of psychosocial stress), as well as with bruxism. Furthermore, he received the diagnosis of a central serous retinopathy, obesity grade I WHO, hypercholesterinemia, and bursitis of the right shoulder.

Therapeutic intervention

The patient received 10 weeks of trauma-oriented inpatient psychotherapy at the Psychosomatic Division of the Ebermannstadt Hospital, Hospital Forchheim-Fränkische Schweiz, Ebermannstadt, Germany, which is a cooperation hospital of the Friedrich-Alexander University Erlangen-Nürnberg (FAU), Germany.

At admission, the therapeutic foci were on stabilizing methods: creation of an individual disorder model, psychoeducation, imagination exercises, enhancement of self-perception and self-care, and an overview of traumatic events and resources (lifeline, from Narrative Exposure Therapy (NET), 12,13).

Four weeks after admission and stabilizing treatment, the patient underwent trauma-focused psychotherapy with a modified version of Eye Movement Desensitization and Reprocessing (EMDR; 14): instead of following the moving hand of the therapist, we asked him to look at the fixated hand of the therapist (EFDR, Eyes Fixated Desensitization and Reprocessing;,15). We used this modification in order to prevent retinal detachment, as previous psychotrauma therapists had reported from their clinical experience of cases of retinal detachment upon classic EMDR in patients affected by eye diseases that can cause retinal detachment. Since CSC is a risk factor for retinal detachment, we chose EFDR for safety reasons. EFDR has proven non-inferior to EMDR regarding outcomes of PTSD symptomatology in a previous study by Sack et al. [ 15 ]. The patient preferred EFDR to other ways of bilateral stimulation, e.g. tactile stimulation. We assessed protocol adherence via video recording.

EMDR [ 14 ] is an evidence based treatment for PTSD [ 16 ] that consists of an activation of a traumatic memory with the most disturbing image, negative thought about oneself, emotion and bodily perception which is then reprocessed with phases of eye movements that the patient follows with his/her eyes (in our case: fixated hand which is looked at by the patient, Eyes Fixated Desensitization and Reprocessing EFDR). Usually, symptom distress reduces in the course of several sessions of EMDR therapy.

As the most disturbing memory, the patient chose the sexual abuse in his infancy. Upon EFDR treatment, he had severe bodily reactions such as trembling, high tension, exhaustion, pain in different parts of the body (e.g. headaches, pain in the back and the jaws) and exacerbation of bruxism. Furthermore, self-depreciating thoughts, shame and disgust occurred. Later, emotions like anger came up, which then converted into sadness. After initial deterioration of sleep, he reported an improvement of sleep quality and quantity in the course of the psychotherapeutic treatment. During this treatment, tension and bodily symptoms reduced and the patient reported that he perceived the sessions as very exhausting, but helpful. Apart from EFDR, he used weekly stabilization psychotherapy sessions and body and art therapy sessions to integrate the stressful memories that came up which the patient perceived mostly on the bodily level and to focus on resources and distancing techniques.

After six sessions of EFDR therapy, acute vision loss with blurred vision and image distortion of the right eye occurred. Thus, we presented the patient at the Department of Ophthalmology of Friedrich-Alexander University Erlangen-Nürnberg (FAU), Germany. Our colleagues confirmed an acute episode of the patient’s pre-known CSC of the right eye. Consequently, the colleagues prescribed brinzolamide eye drops and eplerenone.

In order to reduce stress, we stopped EFDR treatment and continued with stabilizing and self-compassion interventions and the activation of resources.

Medication at dismissal

Sertraline 150 mg 1-0-0, quetiapine retard 25 mg 0-0-1, lercanidipine 10 mg 1-0-1, vitamine D 1000 IE 1-0-0, brinzolamide eye drops twice a day (affected eye), eplerenone 50 mg 1-0-0 (italics: new medication).

Follow-up and outcomes

One year after dismissal, the patient reported that depressive and post-traumatic symptoms including lack of motivation, tiredness, flashbacks, sleep problems and pain were still present. After dismissal, he continued outpatient (mainly online due to the pandemic) psychotherapeutic treatment with a focus on everyday problems and being present. About nine months after his dismissal, he managed to be put on the waiting list for a trauma-focused psychotherapy. Furthermore, he continued doing occupational therapy. Sertraline has been stopped and substituted by duloxetine. However, he reported that he did not perceive any benefit neither from sertraline nor from duloxetine. Furthermore, after dismissal, he received an augmentation of his quetiapine dose (from quetiapine retard 25 mg to quetiapine retard 300 mg 0-0-0-1, quetiapine 75 mg 0-0-0-1, and quetiapine on demand 25–50 mg), with no significant effect. He continued to take lercanidipine 10 mg 1-0-1-0 because of his arterial hypertension.

In psychometric diagnostics at a one-year follow-up examination, he exhibited a medium depressive episode with a BDI-II score of 47 points and the symptoms of a post-traumatic stress disorder with 55 points in the ETI, thus similar values as those at dismissal.

Regarding his CSC, the patient described that there had been a significant improvement in vision and that the “bubble” in his eye had disappeared again three months after dismissal. However, he reported that three-dimensional vision was still compromised. He had continued to take eplerenone 50 mg 1-0-0-0 for three months after dismissal, which he tolerated well. Later after dismissal, he was informed that his disability pension had been denied. This caused significant stress and led to another episode of CSC, which again had been treated by eplerenone.

To our knowledge, this is the first case report on a patient with comorbid PTSD and CSC undergoing trauma-confronting psychotherapy. During trauma-focused treatment for PTSD, a relapse of CSC occurred.

The comorbidity of PTSD and CSC in our patient is in line with previous research showing a strong association between PTSD and the development of CSC [ 6 ]. Our observation is in accordance with the assumption that psychological stress might be one of the most important risk factors for exacerbations of CSC [ 5 ]. We also found an increase in cortisol levels after CSC occurred, which is indicative of a stress reaction. In line with this, the use of steroids was earlier shown to be a risk factor for CSC [ 3 ]. PTSD was suggested to be associated with a blunted cortisol secretion [ 17 ]. However, it was shown that responders had increased cortisol levels after therapy compared with non-responders [ 18 ]. Thus, the specific stress situation upon successful trauma-confronting psychotherapy could result in changes in the diurnal cortisol profile and therefore mediate the risk for CSC.

The study of side effects of various psychotherapeutic treatments has long been neglected. Between 5% and 20% of all patients receiving psychotherapeutic treatment experience relevant side effects, with psychological stress and family or marital stress being the most commonly reported [ 19 ]. Other side effects described include symptom exacerbation, emergence of new symptoms, suicidality, impact on professional and social life, stigmatization and undermining of self-efficacy [ 20 ]. Nevertheless, psychological intervention studies usually do not report on potential side effects. For a few years now, efforts have been made to pay more attention to possible side effects [ 21 ]. When comparing different instruments for assessing negative effects of psychotherapy, it became apparent that although there is a large number of possible domains of adverse effects, there is disagreement about a precise definition and conceptualization of adverse effects and their respective relevance [ 22 ].

Since a core idea of medical treatment is ‘primum nil nocere’, i.e. not to harm, offering adequate psychotherapeutic treatment for PTSD with comorbid CSC is challenging. On the one hand, for recovery of PTSD, a trauma-specific psychotherapeutic approach including trauma-confronting elements is crucial. On the other hand, however, trauma-confrontation usually causes a temporary increase of stress symptoms, which then can cause exacerbations of the eye disease when a history of CSC is present. Since there is no evidence on long-term outcomes for both diseases in the course of a longer trauma-focusing treatment, we can only speculate what would be the best therapy options for patients presenting with both disorders.

First, we suggest continuous monitoring for CSC symptoms upon psychotherapeutic treatment, which can always cause stress due to the actualization of stress and problems. Thus, it seems reasonable to adjust the “dosage” of trauma-confronting psychotherapy in individuals affected by both disorders. At admission for psychotherapy, it might be beneficial to administer prophylactic doses of drugs that are usually given for acute exacerbations of CSC in order to prevent from CSC crises upon psychotherapy. It might furthermore be beneficial to screen CSC patients for PTSD, and to inform patients about potential exacerbations of the eye disease upon psychotherapy if patients present with PTSD and comorbid CSC.

A strength of our report is that the findings are partly novel and of clinical relevance. Furthermore, the case report includes several biological stress parameters, e.g. a diurnal cortisol profile. This is helpful to assess the underlying pathophysiology for this case. The findings are limited by a lack of pre-treatment assessment of the ophthalmologic situation and of stress biomarkers. Hence, it is difficult to discern if biomarkers have increased and if CSC has recurred solely due to the psychotherapy sessions or would have recurred anyway. Furthermore, we have not re-measured cortisol levels after the patient’s dismissal and thus have no information about cortisol levels accompanying the second exacerbation once the patient’s disability pension was denied. Another limitation is that we conducted clinical diagnosis and self-report measures instead of structured clinical interview diagnosis. Furthermore, we applied EFDR instead of EMDR including eye movements or other forms of bilateral stimulation due to the contraindication of eye movements in our case and due to patient choice.

Conclusions

CSC may exacerbate upon psychotherapeutic, especially trauma-confronting, treatment. In the future, psychotherapists and ophthalmologists should collaborate and monitor patients presenting with comorbid PTSD and CSC. This includes assessing for trauma and PTSD in CSC, and, vice versa, assessing for chronic stress-related somatic conditions in PTSD before the onset of psychotherapeutic treatment. Consequently, our main conclusion is that psychotherapists should screen for conditions that might exacerbate upon stress and reactualization of traumatic memories in PTSD patients undergoing trauma-confronting psychotherapy.

Patient perspective

We asked the patient to report on his experiences during and after the inpatient stay:

‘The inpatient stay has been quite beneficial to me. However, I always expect too much from myself; nothing has changed about that. The psychotherapeutic sessions have been good; but when many men joined the therapy group, my stress level was again extremely high, and I still do not feel comfortable among men. After the EFDR sessions, stress levels were very high; however, I believe it has helped me to ‘tidy up’ memories.

The stay has helped me to get calmer, even though this has been really challenging in the beginning. However, I am still restless and cannot ‘switch off’. Progressive muscle relaxation has not been relaxing to me at all, but the opposite: rest is my biggest enemy in myself.

Depressive symptoms have slightly reduced, but I wouldn’t call it the life of a ‘normal’ person. If my shoulder is associated with my mental state I do not know; and the eye is the most important to me, ‘cause every day I am afraid that it will get worse again. Sleeping hasn’t been working at all until today, ‘cause I still wake up often even though I’m taking medication and then I begin to ruminate; I force myself to fall asleep, respectively.’

Data availability

All data generated or analysed during this case study are included in this published article.

Abbreviations

Central Serous Chorioretinopathy

Post-Traumatic Stress Disorder

spectral-domain optical coherence tomography

Eye Movement Desensitization and Reprocessing

Eyes Fixated Desensitization and Reprocessing

Beck Depression Inventory II

Essen Trauma Inventory

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Acknowledgements

We thank the patient for giving his informed consent for this case report to be published. Furthermore, we thank the whole team of the Department of Psychosomatic Medicine and Psychotherapy of Hospital Forchheim-Fränkische Schweiz, location Ebermannstadt, for their contribution to the patient’s multimodal psychotherapeutic treatment and their help to organize data collection.

We did not have any kind of financial support.

Open Access funding enabled and organized by Projekt DEAL.

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Department of Psychosomatic Medicine and Psychotherapy, University Hospital of Erlangen, Friedrich- Alexander University Erlangen-Nürnberg (FAU), Erlangen, Germany

Eva Schäflein, Eva Morawa, Sophia Rudolf, Yesim Erim & Cosima Rhein

Department of Psychotherapy and Psychosomatic Medicine, Faculty of Medicine, Technische Universität Dresden, Dresden, Germany

Eva Schäflein

Department of Ophthalmology, University Hospital of Erlangen, Friedrich-Alexander University Erlangen- Nürnberg (FAU), Erlangen, Germany

Christian Mardin

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Contributions

E.S., Y.E. and C.R. planned the case report and assessment of biological parameters. E.S. wrote the first draft of the manuscript. S.R. helped with literature search and writing of the literature background. C.M. added ophthalmologic information and images. C.R., Y.E., E.M. and C.M. critically revised the manuscript. All authors approved the final version to be published.

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Correspondence to Eva Schäflein .

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The study is in accordance with the instructions for the authors and with the ethical and legal principles (according to the Declaration of Helsinki by the World Medical Association). The patient has given his written informed consent to publish his case.

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Written informed consent was obtained from the patient for publication of this case report and any accompanying images.

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The authors declare no competing interests.

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Schäflein, E., Mardin, C., Morawa, E. et al. Exacerbation of central serous chorioretinopathy during trauma-confronting psychotherapy– a case report. BMC Psychiatry 24 , 368 (2024). https://doi.org/10.1186/s12888-024-05756-6

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Received : 20 October 2023

Accepted : 10 April 2024

Published : 16 May 2024

DOI : https://doi.org/10.1186/s12888-024-05756-6

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• Central serous chorioretinopathy
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