Investigating healthcare hotel travelers’ overall image formation: Impact of cognition,affect,and conation

Abstract

Since there has been little empirical research on the phenomenon of healthcare hotels, this study examined them in order to provide a clear understanding of these facilities and international medical/healthcare tourists’ overall perspectives on them. A model was developed and tested that integrated conation into an existing theoretical framework related to image. A field survey was conducted to collect data. A confirmatory factor analysis was used to evaluate measurement quality, and a structural equation modeling was utilized to test research hypotheses and achieve study objectives. A series of modeling comparisons using a structural analysis were conducted. The test results verified the completeness of the proposed model and demonstrated the superiority of the proposed research framework, which comprises conative image factors as the most proximal determinants of overall image, over alternative models. In addition, the results of the structural analysis suggested that cognitive image involving perceived quality and value has a positive impact on affective image; affective image forms conative images involving visit intention and commitment, and conative image exerts a positive impact on overall image. Moreover, an examination of the indirect impact of study variables suggested that affective image and conative image components are necessary mediators in the model. Theoretical implications and the advertising and marketing implications for practitioners are discussed.

Keywords

Healthcare hotel medical tourism overall image medical treatment intention to visit

Introduction

The medical tourism industry is nearly $60 billion-plus annually, primarily involves international travelers, and has experienced growth of approximately 20% each year (Heung et al., 2011; Yu and Ko, 2012). While medical travel is becoming more and more popular, medical/healthcare tourists who engage in it express concerns relating to conveniences (e.g., access to a variety of medical treatment/healthcare clinics from the hotel, language issues), privacy/confidentiality, medical safety (e.g., follow-up care, malpractice), quality of care, quality of accommodations, and food and beverage (F&B) for themselves as well as accompanying family/friends/others (Gan and Frederick, 2011; Reddy et al., 2010). The healthcare hotel, which is also known as a medical hotel or Meditel, can be a great facilitator of international medical tourism (Han, 2013).

Although the phenomenon of the healthcare hotel is not well documented in the academic literature, it has made inroads into the popular press. Accounts in these publications report that this destination is believed to significantly increase patient travelers’ physical and psychological conveniences, feelings of privacy/confidentiality, safety, quality of care, comfort, and services (Han, 2013; Han and Hyun, 2014; Hwang, 2011). The notion of the healthcare hotel is not yet a heavily studied topic in the academic literature and, to the best of our knowledge, little empirical study has appeared in the hospitality and tourism literature.

It is generally believed that a firm’s overall image is one of the vital elements in increasing a firm’s competitiveness and encouraging continuous repurchase (Lee et al., 2010; Lin et al., 2007). Therefore, a number of studies have dealt with customers’ perceptions and images of a product or service. Previous studies have generally indicated that overall image forms through two major stages: cognitive and affective image (Baloglu and McCleary, 1999; Lee et al., 2010; Lin et al., 2007). That is, the perceptual, cognitive, and affective steps taken by customers in evaluating a product or service are essential to shaping their overall beliefs, ideas, and impressions. However, it has been argued that overall image formation ignores individuals’ conative process by mainly involving intention/commitment (Oliver, 1997), which is a vital/valuable concept in consumer behavior, and that conation is occasionally believed to be an outcome rather than a contributor/predictor of conation. In addition, in the hospitality industry, even though the significance of image and conation in explaining customer behaviors is well recognized, few studies have examined overall image formation. For this reason, there are no detailed explications of how conation produces customers’ overall image of a product/service. Further, while previous studies have identified components of cognition and conation, cognition and conation were normally utilized in the hospitality/tourism literature as uni-dimensional constructs in explaining consumer behaviors.

Considering the points outlined above, in the present study, the main purpose was to develop a robust model that provided a deeper understanding of international medical travelers’ overall image formation of a healthcare hotel. In particularly, the present study attempted to: (1) integrate the conative stage into an existing socio-psychological theory about overall image formation, which mainly consists of cognitive and affective stages; (2) compare the proposed model with alternative models only involving the original phases of the existing theory (i.e., cognitive and affective) and theorizing conation as a function of overall image; (3) examine the detailed relationships among components of cognition, affect, and conation, and the impact of such associations on overall image formation; and (4) investigate mediating roles of study variables in generating customers’ overall image of a healthcare hotel.

Overview of the literature

Healthcare hotels

A healthcare hotel refers to a lodging establishment that contains a variety of medical/healthcare/aesthetic facilities and hospitals (Han, 2013). In the increasingly competitive lodging industry, simply changing a hotel’s accommodations to make them more appealing and improving services cannot be the ultimate strategies followed to ensure continued customer attraction and retention. In recent years, the healthcare hotel has emerged as a niche market in the lodging industry, mainly targeting international visitors who want to obtain medical treatment and healthcare/aesthetic services along with traveling opportunities (Han, 2013; Han and Hyun, 2014). Although the perfect healthcare hotel rarely exists, an increasing number of hotels, particularly in developing/less developed countries, are eager to integrate healthcare/medical facilities and services into their operations as well as to improve existing facilities with advanced technology to actively attract more international medical tourists (Han, 2013; Han and Hyun, 2014). A healthcare hotel provides not only diverse types of rooms—just like a conventional hotel—but a variety of medical treatment, healthcare, or aesthetic services for international tourists (KTMA, 2011; Han, 2013; Han and Hyun, 2014).

Overall image formation and its components

Retaining existing customers and attracting new customers are hospitality/tourism marketers’ goals since customer retention and attraction are directly associated with a firm’s profit and success (Lee et al., 2010; Han and Hyun, 2012; Han et al., 2011). Researchers agree that overall image can have a major impact on attaining this goal. The topic of overall image is, therefore, often preferred in many researchers. For example, Baloglu and McCleary (1999) found that, in the tourism context, the perceptual/cognitive stage and affective phase, which are the outcomes of the perceptual/cognitive stage, generate individuals’ overall conception of image. Lin et al. (2007) have consistently shown that cognitive and affective components of image influence travelers’ overall images and their association with a product preference in natural, developed, and theme park destination settings. In a hotel setting, Lee et al. (2010) reported that cognitive factors of image and affective image impact customers’ overall image of a hotel product/service. These studies all centered on previous knowledge/information and pleasurable feelings of fulfillment about a product/service in shaping overall notions of image. Many researchers in diverse fields have agreed that such perceptual/cognition stage mainly comprises the functional and psychological aspects of perceived value and quality (Back, 2005; Han and Hyun, 2012; Han et al., 2011), and affect mainly involves one’s emotional responses that contain feelings or pleasurable fulfillments of a specific product/service (Bagozzi, 1978; Oliver, 1997, 1999).

However, the common agreement among many researchers in diverse fields is that the conative aspect is also critical in shaping individuals’ psychological processes—this includes decision/image formation (Evanschitzky and Wunderlich, 2006; Han and Hyun, 2012; Han et al., 2011; Oliver, 1997, 1999). Conation can be described as “intention or commitment to behave toward a goal in a particular manner” (Oliver, 1997: 393). Such conation contains two major factors (i.e., commitment and intention) (Han et al., 2011; Oliver, 1997, 1999). Researchers have verified that employment of three phases, including cognitive, affective, and conative, is essential to understanding customers’ psychological process/decision/behavior related to various products/services. These researchers have insisted that conation is a direct function of affect in shaping attitudes and individuals’ purchasing-related psychological processes. Specifically, in examining customers’ attitude development structure, Oliver (1997, 1999) theorized that one’s attitude toward a product/service develops through cognitive, affective, and conative manners. This conative phase, which is mainly comprised of intentions/commitment, is a vital element in attitudinal structure along with cognitive and affective phases. His finding was supported by many recent studies. For instance, Evanschitzky and Wunderlich (2006) and Han et al. (2011) stated that considering cognition and affect as well as conation are vital to explicitly comprehending customers’ psychological processes related to a product/service. Their findings implied the conceptual adequacy of comprehensively integrating conation into an existing bi-dimensional image model that involves cognitive and affective components.

Cognitive dimension and its impact

The term, cognition, refers to one’s perceptions/knowledge/beliefs about a particular product, its attributes, and its performances (Baloglu and McCleary, 1999; Oliver, 1997). This cognition mainly comprises such factors as functional and psychological facets of value and perceived quality (Back, 2005; Han et al., 2011). Zeithaml (1988) indicated this value as one’s comprehensive evaluation of the utility of a product/service rooted in the perceptions of what is obtained and given; Bitner and Hubbert (1994) described this perceived quality as one’s overall perception of the relative superiority or inferiority of a product and the performances of its attributes. The criticality of cognition and its constituents in product/service consumers’ psychological process is often stressed by researchers. For instance, Baloglu and McCleary (1999) asserted that cognitive factor and its components are direct drivers of affective image. Lee et al. (2010) also indicated that cognition exerted a significant influence on affective image playing a vital role in generating hotel customers’ eco-friendly purchasing behaviors. Consequently, it was hypothesized that:

H1 : Increases in perceived value lead to increased affective image.

H2 : Increases in perceived quality lead to increased affective image.

Affective factor and its impact

Affect is another crucial construct in one’s image formation. According to Lee et al. (2010) and Lin et al. (2007), affective image is central in building one’s favorable overall image and decision for a firm. Affect comprises individuals’ emotional responses, which include pleasurable fulfillments/feelings when using a specific product/service (Bagozzi, 1978; Oliver, 1999). Lin et al. (2007) demonstrated that affect generates overall image and contributes to better predicting travelers’ choice/preference across natural, developed, and theme-park destinations. In a green lodging sector, Lee et al. (2010) also verified that affect, which is a significant function of cognitive image, has a key role in triggering patrons’ overall image and behavioral intentions. Moreover, in a restaurant sector, Han et al. (2011) demonstrated that affective process exerted a significant influence on patrons’ commitment and revisit intention. These researchers’ general agreement is that conative image constituents (e.g., intention, commitment, choice, and preference) in the overall image (or decision) formation for a product/service are often induced by affect. It was therefore hypothesized that:

H3 : Increases in affective image lead to increased visit intention.

H4 : Increases in affective image lead to increased commitment.

Conative dimension and its impact

The term, conation, is also an essential concept in explaining one’s psychological decision-making process related to consumption (e.g., Han and Hyun, 2012; Oliver, 1999). Oliver (1997) defined conation as one’s commitment or intention to act toward a goal in a specific manner. As this definition indicates, intention and commitment are two core components of conation (Han et al., 2011; Oliver, 1999). While some researchers utilized conation as a uni-dimensional construct (Back and Parks, 2003), a two-dimensional view of conation comprising commitment, and intention is believed to capture the construct more explicitly (Han et al., 2011). The conative process containing both commitment and intention is often found to be influenced by affect (Han et al., 2011). According to Han and Hyun (2012), conation is a significant and positive function of affect in one’s decision-making process related to consumption. Their finding also indicated that cognition also significantly influences conation indirectly through affect. Similarly, in building a theoretical framework explicating tourists’ behavioral intention, Baloglu (1999) identified that cognitive evaluation determines tourists’ affective evaluation (e.g., feelings-related evaluation) about travel destination, and this affective factor increases their intention to travel to the place, which is a vital constituent of conative image. Therefore, it was hypothesized that:

H5 : Increases in visit intention lead to increased overall image.

H6 : Increases in commitment lead to increased overall image.

Conceptual model

According to the view in the literature discussed above, individuals’ psychological decision-making process or thought development process related to consumption proceeds through cognitive stage, affective phase, and conative stage in a sequential manner. Hence, we put forth that the overall image forms through cognitive, affective, and conative processes. The proposed model is exhibited in Figure 1. This model comprises a total of six hypotheses.

Figure 1.

Proposed model.

Methods

Measures and questionnaire development

The initial questionnaire comprised an introductory cover letter, definition of the concept of a healthcare hotel, questions relating to the variables to be studied, and questions for a demographic profile of each participant. The questionnaire was based on the existing literature (e.g., Baloglu and McCleary, 1999; Han et al., 2010; Kim and Han, 2008; Lee et al., 2010; Morgan and Hunt, 1994; Oh, 2000; Varki and Colgate, 2001) and refined to be adequate in a healthcare hotel setting. Multi-item scales were consistently used to measure study variables. In addition, a seven-point Likert-type scale from “Extremely disagree” (1) to “Extremely agree” (7) was used for cognitive components of image, conative image components, and overall image. For affective image, four bipolar scales were used (e.g., “Arousing” – “Sleepy”). The initial questionnaire was altered and perfected through a hospitality and tourism expert review and a pre-test. As a next step, the original English version of the survey questionnaire was translated into Chinese, Japanese, and Korean employing a blind translation-back-translation method (Brislin, 1976) in that a majority of international travelers using an international airport in Busan, Korea spoke one of these languages. The content validity of the translated questionnaires was ensured in a review by hospitality and tourism experts who use one of these as a native language. Measures used in the present study are shown in Appendix 1.

Data collection

The sample population consisted of international travelers who had had previous medical/healthcare tourism experiences abroad. These travelers were expected to provide more pragmatic judgments and opinions on the survey, as their likelihood of international travel for medical treatment/healthcare and staying at a healthcare hotel would be higher than that of traditional tourists. The data were collected at an international airport located in a metropolitan city, South Korea. Potential respondents were initially screened by asking if they had had any previous experience traveling abroad for medical treatment or healthcare/aesthetic services. Only travelers who had experienced medical/healthcare tourism were invited to fill out the questionnaire. Well-trained students provided a brief explanation about the objectives of the study to international travelers who were in the rest areas near the boarding gates. These travelers were approached during their waiting times for flights. The survey questionnaires were collected onsite to enhance return and usable rates. About 700 questionnaires were distributed. Among them, a total of 423 completed and usable questionnaires were returned through this process (the response rate = 60.4%). After removing five extreme multivariate outliers (Mahalanobis’ D (17) > 40.790, p < .001), 418 responses remained for data analysis. A common method bias was checked by using Harmon’s single-factor test (Podsakoff and Organ, 1986). Our results indicated that the total variance explained by common factor was about 40.1%, which was lower than the problematic level of .50.0% (Podsakoff and Organ, 1986). This finding implied that the common method variance was not a critical issue in the present study.

Sample characteristics

Among the 418 survey participants, 59.0% were female. Their mean age, which ranged from 20 to 65, was 31.8 years old. While about 60.5% of the participants reported that their annual household incomes were under $40,000, about 39.5% described their household incomes as being over $40,001. The greatest proportion of the participants (31.9%) reported that their purpose in traveling at this time was pleasure (39.5%), followed by business (20.5%), study (13.7%), medical treatment/healthcare (12.9%), other (12.7%), and conference (.7%). Of the respondents, a total of 74.5% were Asians; 16.9% were Caucasian/White; 3.4% were Polynesian/Pacific Islander; 2.9% were Black; and 2.4% were others. The respondents were from 22 different countries. The largest group was Koreans (29.4%), followed by Japanese (24.9%), Chinese (22.6%), Americans (11.6%), Filipinos (2.8%), Singaporeans (1.5%), Russians (1.3%), etc. The highest frequency of medical/healthcare tourism experiences within the last five years was two times (38.5%), followed by once (34.7%), three times (23.9%), etc. In addition, 43.8% said that their latest medical/healthcare travel was within the last six months, 74.9% reported that it had been within two years. Lastly, about 34.4% of the participants indicated ever having heard of a healthcare hotel, and only 17.2% reported ever having stayed at a healthcare hotel.

Results and findings

Measurement model and validity testing

This study utilized SPSS and AMOS 5 to analyze the data. A measurement model using the confirmatory factor analysis (CFA) was estimated to test the overall fit of the proposed measurement structure and to assess reliability and validity. Table 1 presents the findings from the measurement model. The results demonstrated acceptable overall fit (χ²= 198.657, df = 87, p < .001, RMSEA = .055, CFI = 0.982, NFI = .968, GFI = .944). Composite reliability was evaluated to ascertain the consistency of the multi-items for each construct. All reliability values ranging from .890 to .930 were acceptable. In the next step, construct validity (i.e., convergent and discriminant) was evaluated for all constructs in the measurement model. As shown in Table 1, average variance extracted (AVE) ranging from .734 to .816 exceeded the minimum suggestion of .500 found in the literature (Fornell and Larcker, 1981; Hair et al., 1988). Thus, convergent validity was wholly established. Next, also as seen in Table 1, the squared correlation values between constructs were less than the AVE of each variable, providing evidence for the discriminant validity of the study constructs (Fornell and Larcker, 1981; Hair et al., 1988).

Table 1.

Summary of the confirmatory factor analysis.

Constructs	Perceived value	Perceived quality	Affective image	Intention to visit	Commitment	Overall image about a healthcare hotel
Perceived value	1.00
Perceived quality	.789 (.623)	1.00
Affective image	.579 (.335)	.561 (.315)	1.00
Intention to visit	.651 (.424)	.630 (.397)	.571 (.326)	1.00
Commitment	.737 (.543)	.762 (.581)	.574 (.329)	.634 (.402)	1.00
Overall image about a healthcare hotel	.670 (.449)	.646 (.417)	.624 (.389)	.687 (.472)	.624 (.389)	1.00
Mean	4.061	4.057	4.143	3.865	4.025	4.139
Composite reliability	.892	.890	.928	.904	.895	.930
AVE	.734	.801	.811	.759	.810	.816

Goodness-of-fit statistics:

χ²= 198.657 (df = 87, p < .001), RMSEA = .055, CFI = .982, NFI = .968, GFI = .944.

Note. Squared correlations are in the parentheses.

Structural model and modeling comparisons

Since the utilization of structural equation modeling (SEM) is effective for the simultaneous assessment of the entire theoretical framework (Hair et al., 1998; Tabachnick and Fidell, 2007), our proposed model was estimated using the SEM. In particular, a covariance-based SEM was utilized. The use of the covariance-based SEM is adequate for theory testing (or theoretical framework development) and comparison of alternative models/theories (Hair et al., 2011) like the present study. The results indicated that the model satisfactorily fit the data (χ²= 277.175, df = 94, p < .001, RMSEA = .068, CFI = 0.970, NFI = .966). Prior to testing the hypothesized associations among study variables, this model was compared with two alternative models to determine the best model with the most excellent model fit and predictive ability. As discussed earlier, previous studies indicated that overall image formation is mainly a function of cognition and affect (e.g., Baloglu and McCleary, 1999; Lin et al., 2007). In addition, unlike our proposed framework, some researchers indicated that overall image is a direct predictor of such conative components as behavioral intentions (e.g., Han et al., 2009; Lee et al., 2010). Thus, the first alternative model only involves perceived value, perceived quality, affective image, and overall image, and the second alternative model locates overall image as an antecedent of conative components. These models are presented in Figure 2. The fit of both alternative models was acceptable (Alternative model 1: χ²= 172.502, df = 37, p < .001, RMSEA = .074, CFI = 0.968, NFI = .960; Alternative model 2: χ²= 449.557, df = 95, p < .001, RMSEA = .078, CFI = 0.943, NFI = .929). In comparing three models, the proposed model had better explanatory power for overall image (R²= .630) than alternative models (Model 1: R²= .521; Model 2: R²= .574). In addition, as shown in Table 2, the fit statistics of the proposed model were superior to the alternative models. The Chi-square differences between the proposed model and the alternative model 1 (Δχ² (57) = 104.673, p < .01) and between the proposed model and the alternative model 2 (Δχ² (1) = 172.382, p < .01) were significant. That is, the proposed model, which involves conative components and uses them as direct predictors of overall image, is also statistically and significantly better than the alternative models.

Figure 2.

Results of the proposed and alternative models.

Table 2.

Modeling comparisons and goodness-of-fit statistics.

Fit indices and R²	Suggested value	Proposed model	Alternative model 1	Alternative model 2
χ²		277.175	172.502	449.557
Df		94	37	95
χ²/df	≤ 5	2.949	4.662	4.732
RMSEA	≤ .08	.068	.074	.078
CFI	≥ .90	.970	.968	.943
NFI	≥ .90	.966	.960	.929
Adjusted R²:
Overall Image about a Healthcare Hotel		.630	.521	.574

Note. Suggested values were based on Hair et al. (1998).

As a next step, the proposed relationships were assessed. First, Hypotheses 1 and 2, in which the direct impact of perceived value and quality on affective image were hypothesized, were tested. Both path coefficients were positive and significant (H1: β = .478, p < .01; H2: β = .466, p < .01), thus supporting Hypotheses 1 and 2. Hypotheses 3 and 4 were tested to determine if affective image has a positive influence on conative components. The path coefficients from affective image to visit intention and commitment were positive and significant (H3: β = .803, p < .01; H4: β = .898, p < .01), supporting Hypotheses 3 and 4. Hypotheses 5 and 6 were assessed. As expected, the linkages from visit intention and commitment to overall image about a healthcare hotel were positive and significant (H5: β = .528, p < .01; H6: β = .320, p < .01). Cognitive image components explained about 80.3% of the variance in affective image, and this affective image accounted for 64.4% and 84.2% of the total variance in visit intention and commitment, respectively. The model involving cognitive, affective, and conative image well predicted an overall image of a healthcare hotel (R²= .630).

Lastly, the indirect impacts of study variables were examined. In particular, bootstrapping was utilized to identify the mediating effect of research variables. This method is a widely accepted way to test the mediating role of constructs. As shown in Table 3, our findings from bootstrapping revealed that perceived value and quality had a significant impact on a healthcare hotel’s overall image through affective image and conative image components (p < .01). In addition, affective image had a significant indirect impact on overall image (p < .01). Overall, these results indicated that both affective and conative image components acted as significant mediators in the proposed theoretical model.

Table 3.

Final model – Hypotheses testing and structural model results.

Hypothesis	Independent variable → Dependent variable		Standardized coefficient	t-value
H1	Perceived value → Affective image		.478	3.144**
H2	Perceived quality → Affective image		.466	3.070**
H3	Affective image → Intention to visit		.803	11.594**
H4	Affective image → Commitment		.898	12.913**
H5	Intention to visit → Overall image		.528	8.203**
H6	Commitment → Overall image		.320	5.203**
Goodness-of-fit statistics: χ²= 277.175 (df = 94, p < .001), RMSEA = .068, CFI = .970, NFI = .966
Total variance explained:		Standardized indirect impact of variables:
R² of affective image = .863		β perceived value → affective image → visit intention and commitment → overall image = .343**
R² of intention to visit = .644		β perceived quality → affective image → visit intention and commitment → overall image = .334**
R² of Commitment = .842		β affective image → visit intention & commitment → overall
R² of overall image = .630		image = .417**

**p < .01.

Discussion

According to the existing conceptual frameworks/theories, overall image forms through cognitive and affective evaluation processes. In particular, many image studies focused mainly on cognition and affect as direct indicators of overall image (e.g., Baloglu and McCleary, 1999; Lin et al., 2007). In addition, many theoretical frameworks in the previous literature consider overall image as a predictor of conation mainly involving behavioral intentions (e.g., Lee et al., 2010; Lin et al., 2007). However, researchers from various fields have indicated that customers’ psychological process can be better explicated when the conative phase is involved (e.g., Evanschitzky and Wunderlich, 2006; Han et al., 2011; Oliver, 1997, 1999). Findings of the present research were of great importance since it provided a clue for such theoretical conflict. In particular, our empirical demonstration contributes to the literature by successfully theorizing that conation is essential in explaining consumers’ psychological process, and the effectiveness of this variable is maximized when utilizing it as an outcome of cognition/affect and as a direct predictor of overall image.

The previous approach can be criticized in that the complicated procedure of image formation cannot be solely explained by the use of a single dimensional approach that combines components of cognition/conation into one comprehensive construct (Han et al., 2011; Lee et al., 2010). To avoid such criticism of a single dimensional approach, the present study examined the independent role of each component of the cognitive and conative images. As indicated by the excellent fit of the proposed model (χ²= 277.175, df = 94, p < . 001, RMSEA = .068, CFI = 0.970, NFI = .966) and path coefficients relating components of cognitive and conative images to other study variables, this study verified the adequacy of the utilization of a bi-dimensional model involving cognitive and conative image components in explaining overall image formation. Researchers should consider utilizing a bi-dimensional (or even multi-dimensional) approach in the cognitive and conative phases of overall image formation and using possible associations between the components of these phases and other critical variables when developing a model/theoretical framework for overall image.

In our theoretical framework, a prominent role of affective image was identified. In particular, the impact of affective image on outcome variable(s) was substantial not only in the proposed model but also in alternative models. As demonstrated in this study, affective image significantly triggers such conative image factors as visit intention and commitment, which are most proximal determinants of overall image. On the whole, our result informs industry practitioners that providing favorable affective experiences to patient travelers is an essential process to build strong commitment and intention and to form a positive overall image about a healthcare hotel. Given this, diverse endeavors should be made for the enhancement of healthcare hotel travelers’ affective experiences. According to Han et al. (2015), one of the important benefits that medical travelers are likely to expect from healthcare/medical lodging accommodations is that they can receive medical treatment and healthcare/aesthetic services within a hotel. Offering high quality encounter services and physical environments (décor, music, lighting, colors, plants, quality of furniture, aroma, overall layout, air quality, paintings, etc.) would be an effectual way to elicit travelers’ positive affective experiences, which ultimately contributes to enhancing conative and overall images regarding healthcare hotels.

In the proposed theoretical model, the important role of perceived value and perceived quality was empirically identified. In other words, the enhancement of these constructs is essential to building a positive overall image of a healthcare hotel. From the managerial aspect, it is indispensable to increase and offer diverse benefits or advantages that are not easily available in other healthcare or medical clinics. Providing an inclusive value package containing choices for various healthcare/medical/aesthetic treatments, airline ticket, meals, and hotel room, and meals within one property and offering hotel-style services/products comprising upscale F&Bs and hotel rooms for overseas patient customers and their accompanying friends/family can be the good examples of such benefits or advantages. Moreover, the existing benefits or advantages of a healthcare lodging firm should be extensively advertised for the enhancement of cognitive image of a firm. In particular, such advertising endeavors may help overseas patient travelers believe that experiencing diverse healthcare/aesthetic services and receiving medical treatments at a healthcare hotel facility are valuable, which eventually contributes to improving the firm’s overall image.

The present study identified a significant mediating impact of affective image and conative image components. This result is consistent with previous studies that emphasized the significance of affect and conation as mediators (Evanschitzky and Wunderlich, 2006; Han et al., 2011; Oliver, 1997, 1999). Our findings implied that the enhancement of these variables is essential to magnifying the role of cognitive image components in international travelers’ favorable overall image of a healthcare hotel. Hospitality and tourism researchers should carefully develop a conceptual framework about overall image formation that includes this result. For practitioners in the healthcare hotel industry, a simultaneous effort to increase perceived value and quality as well as to enhance affective image and conative image is recommended for the effective improvement of their hotel’s image.

Conclusion

This study was designed to advance earlier conceptual frameworks related to overall image by developing and testing a theoretical model comprising cognitive, affective, and conative image as these influence healthcare hotel residents’ perceptions of this location. A series of modeling comparisons verified the superior ability of our proposed theoretical model to predict overall image, compared with alternative models. The hypothesized associations were all supported. In particular, cognitive image components (perceived value and quality), affective image, and conative image components (visit intention and commitment) in the formation of overall image for a healthcare hotel were all significantly and highly associated.

Overall, our findings suggested the following sequence of psychological processes in forming overall image: Briefly, international medical/healthcare tourists initially form a cognitive image of a healthcare hotel based on their general perception of its quality and value; this image shapes their emotional states about this hotel; they then form a certain level of behavioral intention and commitment based on these affective states; and lastly, such intention and commitment eventually result in a favorable/unfavorable image of a healthcare hotel as a place to obtain medical treatment, healthcare, or aesthetic services. Although medical tourism is in rapid growth (Heung et al., 2011; Jackson and Barber, 2015), the phenomenon of healthcare hotels is not sufficiently examined in previous studies. The proposed model is theoretically and practically meaningful since the framework provides a new insight to existing theories about overall image formation. In reflecting on study findings relating to the development or extension of a theoretical/conceptual framework, it can be concluded that the employment of the consecutive overall image formation through cognitive, affective, and conative processes is critical and effective when conducting image-related research in a medical tourism sector.

Limitations and future research

This study had several limitations. None of the correlations among constructs exceeded Hair et al.’s (1998) cut-off of .80. However, some correlations were comparatively high (e.g., correlation between value and quality = .789). A thorough study design in future research is necessary to completely avoid the multicollinearity issue. All study variables were assessed using measures designed to be adequate in a healthcare hotel setting. Hospitality and tourism researchers who employ and directly apply our conceptual framework to other situations should do so carefully. As discussed earlier, one of the greatest advantages of a healthcare hotel for customers is conveniences. Identification of the detailed components of conveniences (e.g., physical convenience, time and effort saving, language/communication) through a qualitative approach would be meaningful in future studies. In addition, examining the possible associations between such convenience factors and conceptual variables in the proposed model would be an interesting extension of this study.

Footnotes

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Author Biographies

Heesup Han is a Professor in the College of Hospitality and Tourism Management at Sejong University, Korea. His research interests include airline, medical tourism, green hotels, and hospitality and tourism marketing. His papers have been selected as the most downloaded and read articles in many top-tier hospitality and tourism journals.

Jinsoo Hwang is an assistant professor in the College of Hospitality and Tourism Management at Sejong University, Korea. He received his Ph.D. degree in Hospitality Management from Kansas State University. Dr. Hwang has published in various professional journals in hospitality and tourism. He specializes in hospitality and tourism marketing and research methods.

Appendix 1

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