Abstract
Purpose: Aesthetic clinics have expanded dramatically in recent years due to social media trends. This study aims to examine the antecedents of patient experience: product quality, service encounter, servicescape, outcome quality, electronic word of mouth (EWOM) on cognitive experience (CE) and affective experience (AE), and its influence on revisit intention (RI) moderated by social media engagement (SME).
Methodology: This study used a quantitative survey with a cross-sectional approach. Data is collected by purposive sampling using a self-report questionnaire from 280 patients who attended Youthology Aesthetic Clinic®, South Jakarta minimum of twice between July to August 2022 and followed the clinic’s social media account. Partial least square-structural equation modeling (PLS-SEM) was deployed for data analysis.
Results: Electronic word of mouth is the most prominent antecedent influencing AE and CE, with more effect in CE than AE. Servicescape was found not significant to influence CE. Finally, AE has a slightly more substantial influence on RI than CE, but the moderating impact of SME was found insignificant.
Practical implications: The findings of this study suggested that management should pay attention to all the mentioned antecedents, especially EWOM. The administration should develop a strategy to give the best experience to the patients visiting the clinic. This experience should prioritise the patient’s emotional response by patient-centric approach.
Originality/value: This study used cognitive and affective mediation from the patient’s perspective, where these two variables mediate their antecedents to RI. Therefore, this study offers a more comprehensive functional service model such as service encounter and technical approach
Keywords: antecedents; cognitive experience; affective experience; revisit intention; aesthetic clinic.
Introduction
Over recent years, there has been a shift in consumer attitudes about wellness, beauty, and healthy ageing awareness and acceptance, generating high demands in the market from new patient segments. The beauty industry was documented to grow by more than 10% a year, also by widening its accessibility primarily via aesthetic clinic chains (Leclerc et al., 2021). Innovative aesthetic equipment developed by manufacturers as well as the broadening variety of options in this industry raised the demand for aesthetic treatments, contributing to profitable expansion (Leclerc et al., 2021).
The skincare industry is expected to rise at an 8.9% compound annual growth rate (CAGR) from $1.7 billion in 2021 to $2.5 billion by 2026 (Globaldata, 2022). Consequently, customer perception should be prioritised. The term embraces the overall assessment of the client’s impression of service to the client’s attitude towards the service (Chahal & Kumari, 2010; Parasuraman et al., 1985; Shie et al., 2022).
This leads to the emphasis of the importance of patient-centric marketing (Bellio & Buccoliero, 2021; Giraldo et al., 2014). Patient centricity means incorporating and prioritising patients’ views and needs to ensure optimum patient’s experience journey (Wolf et al., 2014). Thus, the patient experience becomes pivotal to assessing quality of service delivered by the aesthetic clinic.
Efforts to increase customer experience are inseparable from factors influencing it. An earlier study by Schmitt (1999) pointed out that customer experience is a multidimensional construct that consists of sensory, affective, cognitive and active. However, previous studies (Molinillo et al., 2020; Palací et al., 2019) argued that cognitive and affective dimensions are the most important and distinctive of experience. Another study (Ahn & Picard, 2014) demonstrated that affective experience (AE) and cognitive experience (CE) could predict marketing success. In that sense, this study uses these two kinds of dimensions.
One of the most crucial outcomes of marketing objectives is to keep loyal customers and evaluate through their revisit intention (RI) (Park et al., 2021). It is also worth noting that revisiting intention has become one of the most critical aspects of the healthcare industry (Bellio & Buccoliero, 2021; Woo & Choi, 2021). The dependent variable in this study is the patient’s desire to visit a specific cosmetic clinic as frequently as possible within a given time frame, as specified in aesthetic clinics.
A study on an aesthetic clinic in Thailand identified these preceding factors, such as image, trust, brand loyalty and social media marketing activities; however, the results showed limited predictive capability influencing this outcome (Nurittamont, 2022). A study done in Taiwan (Wu, 2011) showed that satisfaction in aesthetic clinics did not always result in customer loyalty, and dissatisfaction did not necessarily result in a different outcome. Another study by Giraldo et al. (2014) on aesthetic medicine patients found a strong influence from relationship quality to loyalty but less from satisfaction. Aside from the undesired results, more previous studies on customer experience are too general and might not apply to the aesthetic industry. Consequently, further research in aesthetic clinics is required, particularly using patient experience.
According to Endeshaw (2021), many studies on healthcare service quality have been done by a service quality evaluation (SERVQUAL) that mainly referred to Parasuraman et al. (1985). However, that approach puts more emphasis on functional quality and neglects technical and other quality dimensions, such as outcome quality (OQ) that explain the result of the healthcare (Chahal & Kumari, 2010; Swain & Kar, 2018). Therefore, both are equally important and are associated with patient satisfaction.
Currently, the aesthetic industry utilises visual media as the primary tool for the target audience, and because patients these days are more influenced by digital platforms, social media engagement that is rich with visual content becomes an effective channel to engage with the patient (Trunfio & Rossi, 2021). Social media activity in the healthcare industry could affect patients’ motivation to return by luring in new clients while keeping hold of old ones. The most potent element of social media activity is provided through electronic word of mouth (EWOM, or EW). Electronic word of mouth is one method of using online customer communities to effectively promote one’s brand or cause, and also includes basic advice for website and forum moderators on how to make such presentations helpful to the users of their respective online communities. Studies have found that EWOM and RI have a positive association (Abubakar et al., 2017). Unfortunately, few studies are done to explore this phenomenon in the aesthetic clinic.
Based on the aforementioned consideration, three research questions were raised as follows:
What are the antecedents of patient experience in aesthetic clinic services? Do these antecedents have a different way of influencing patient experience, either cognitively or affectively? To what extent can these two dimensions of patient experience predict RI with social media engagement as a moderator?
To answer those three research questions, this study attempts to integrate functional and technical quality measurement in healthcare services and how patient experience, in turn, affects RI with the moderation of social media engagement. In this study, the influence of product quality (PQ), service encounters (SE), servicescape (SS), OQ and EWOM towards patient experience was explored through the affective and cognitive dimensions. This study has two benefits. Firstly, it helps to analyse and identify the factors that might lead to a profound patient experience, particularly at the aesthetic clinic. Secondly, it helps to determine how these experiences are perceived through the differential subjective process. This empirical study deployed a new model on what actionable factors might be effective in enhancing patient return intention in the aesthetic clinic, which, hence, will result in managerial implications for supporting a more effective business growth strategy.
Literature review
Theoretical framework and hypotheses development
The conceptual framework of this study is taken from the service quality (SERVQUAL) theory which also can imply the quality of care in health services (Parasuraman et al., 1985). The SERVQUAL framework is associated with overall quality management. Service quality evaluation consists of five dimensions that are used by customers when evaluating service quality (Parasuraman et al., 1988), which include (1) tangible the appearance of physical facilities, equipment and personnel; (2) reliability the ability to perform the promised service dependably and accurately; (3) responsiveness the willingness to help customers and provide prompt service; (4) assurance the knowledge and courtesy of employees and their ability to inspire trust and confidence and (5) empathy providing the caring and individualised attention to customers. According to this theory, there were disparities between the levels of service provided and the levels of care expected. Identifying such differences may help to eliminate dissonance between the level of a customer’s expectations and patient perceptions of the service provided, which may lead to higher customer satisfaction and hence enhance service quality (Endeshaw, 2021; Gronroos, 1990). In health services, patient expectations are more shaped by aspects of their affection because consumers are limited in medical knowledge.
In connection with that matter, studies have concluded that the previously established SERVQUAL was insufficient (Endeshaw, 2021; Gronroos, 1990; Swain & Kar, 2018). One of the reasons was because patients use their feelings more in evaluating and do not see the results of the treatment as a whole. Another study in consumer behaviour stated that the complexity of the process leading to experience and satisfaction is multidimensional (Brakus et al., 2009) and therefore needs to be evaluated also by cognitive aspect. Hence, a theory by Gentile et al. (2007) is adopted, where it is said that experience comprises multiple cognitive and affective aspects. In line with this, according to a prior study’s conceptual analysis of brand experience, the fundamental characteristics of brand experience are affection, connection, passion and other domains in various professions such as marketing, philosophy, cognitive science and management practice. Philosophical research defined experiences as intellectual experiences arising from knowing and experiences by experiencing through senses, feeling or acting. This classification then becomes the fundamental principle of what we know now as CE and AEs. Cognitive assessment component is the outcome of a cognitive process in which the patient evaluates various components of a service, either by assessing the perceived result alone or by comparing it to a standard. According to this view, happiness with a healthcare experience is the consequence of the independent assessments of several elements, such as medical personnel, atmosphere, service, among others. And then emotional aspect analyses subjective components by capturing sentiments or emotions created in the patient–provider connection that are beyond the conscious control of the patient. This framework is further supported by other articles which stated that experience is enough to be divided into two, namely cognitive and affective (Alnawas & Hemsley-Brown, 2018; Molinillo et al., 2020; Palací et al., 2019).
Both CE and AE were further characterised as heavily influenced by various factors, including sensory perception, sentiments and emotions, creativity, logic and social interactions. Affective and CEs can be categorised as aesthetic elements (including visual, auditory, olfactory and tactile components), instructional, entertaining and escapist experiences when marketing and managing retail locations or events. Following this paradigm, brand-related stimuli such as colours, forms, fonts, designs, slogans, mascots and brand characters elicited emotions or intellectual experiences (Klaus & Maklan, 2013; Schmitt, 1999).
In addition to these direct impacts, brand experience will likely lead to further processing, indirectly influencing satisfaction and loyalty. Brand personality, defined as ‘the collection of human traits connected with the brand’, has been offered as one construct to explain this behaviour. Both brand experiences and personality judgements occur in reaction to brand engagement and entail a classification procedure. This phenomenon is expected to eventually affect customers’ sensory, affective, intellectual and behavioural experiences, finally leading to RI (Klaus & Maklan, 2013; Schmitt, 1999).
Derived from research models from hypotheses generated by past research, this study’s conceptual framework aims to evaluate the correlation of PQ, SE, SS, OQ and EWOM with patient experience about their future visit intention.
Antecedents of patient experience
As explained in the previous section, CE and AE are heavily influenced by numerous factors, ranging from aesthetic elements to brand personality. From these domains, we broke down main components to further clarify the antecedents of patient experience.
The degree to which a product satisfies patient needs, performs its function and complies with industry standards is referred to as its quality. The performance of the business and the building of the company’s reputation in the markets it serves make PQ essential. Service encounter is similar to this and is defined as a face-to-face interaction between a service provider and a recipient during service consumption. It is a fundamental component of outstanding patient service (Voorhees et al., 2017). The third influencing aspect is the atmosphere or environment, which is a patient’s first impression of the service when they enter a specific location. Patients are likely to form opinions about the service quality they will receive now, highlighting its significance to their overall experience. Affective experience is then concluded to correlate with SS strongly. Environmental psychologists have investigated how physical environments affect consumer behaviours, and their findings suggest that a person’s emotional state influences how they respond to their surroundings (Bitner, 1992). Pleasure, arousal and dominance are the three primary emotional reactions elicited by environmental stimuli. Providing impressive experiences in the aesthetic industry is proposed to significantly impact outcome variables such as patient satisfaction and loyalty. Experiences are valuable if they are stored in an individual’s memory. The cumulative encounters between patients and the service providers will create a strong bond, ultimately affecting how patients perceive the experience they have been anticipating, generating higher RI. Patients are anticipated to generate AE through these induced emotions, which is the expected outcome of the variables examined in this article.
The term EWOM refers to consumer information sharing and exchange about a company or brand using the internet, social media and many other platforms (Cheung et al., 2008). Academic study on the influence of EWOM on patient behaviour has been recorded in areas such as advertising, marketing, communication, management and electronic commerce (Hennig-Thurau et al., 2004). Recurring visitors who are pleased are more likely to advocate a destination through good EWOM (Abubakar et al., 2017; Güçer & Arici, 2018). Social media and EWOM are essential for consumer engagement. Patient engagement is made possible by building enduring connections and loyal relationships with patients. It focuses on the cognitive, emotive and behavioural facets of customer-brand connections and is a multifaceted notion. Numerous researches have revealed that patient engagement frequently serves as a brand’s desire to relate to and connect with its target audience. Patients have reportedly developed positive sentiments about the brand when they are present (Lim & Rasul, 2022). This variable, together with CE and AE, is hypothesised to influence overall patient experience and hence the RI positively.
Cognitive and affective experiences
Brakus et al. (2009) stated that there are three fundamental systems that make up patient experience: sensation, cognition and emotion. Cognitive experience is a type of representation (i.e., how a person perceives, understands and interprets what is occurring in the surrounding world) and a precursor to a person’s intellectual existence. Meanwhile, AE is one in which the things are balanced positively or negatively. In terms of marketing, AE has emerged as a crucial factor for enhancing the whole customer journey and boosting customer loyalty and retention by emphasising the creation of an emotional connection. Affective experiences, such as sentiments of attraction and repulsion, become the motivating force for customers to perceive the experience of delivered service. Many academics also believe that one of the most effective methods to achieve peak customer experience is to put much greater attention on the client. In conjunction with this, some of the antecedents are related to CE and AE, namely PQ, SE, SS, OQ and EWOM (Alnawas & Hemsley-Brown, 2018; Gentile et al., 2007; LaSalle & Britton, 2003; Schmitt, 1999).
Quality is always the top concern, a critical strategy for product competitiveness and customer happiness. Product functioning, comprising overall product, reliability, accuracy, simplicity of use and maintenance, and other attributes, directly affect PQ. Product quality encompasses all consumer benefits. Even if the categories are similar, commercial organisations’ products must be distinct from their competitors. Several fields, including aesthetics, have investigated cognitive processes connected to PQ (Braun-LaTour & Latour, 2020). Cognitive experience is both the psychological foundation of intellectual capability and a depiction of how a customer perceives, understands and interprets their contractual services. Similarly, AE translates to customers’ attitudes or emotions elicited by an external stimulus, PQ (Smithies & Weiss, 2019). From these aforementioned statements, our first two hypotheses were drawn as such:
H1: Product quality has a positive connection with CE.
H2: Product quality has a positive connection with AE.
Customers assess the firm’s quality throughout this sequence, and each encounter enhances their happiness and willingness to do business with the company (Chandon et al., 1997; Voorhees et al., 2017). Any discrete engagement between the customer and the service provider related to a core service offering constitutes an SE, including the interaction that occurs when the core service offering is provided. Good SE will lead to overall reasonable customer satisfaction, imprinting good experiences on customers, both cognitive and affective (Slåtten, 2011). From these statements, other hypotheses can be drawn as such:
H3: Service encounter has a positive connection with CE.
H4: Service encounter has a positive connection with AE.
Customers’ initial impression of a service or retail outlet is the service environment in the form of physical consequences of a service process’s surroundings (Bitner, 1992). Servicescape is also interrelated to experiential satisfaction (Bellio & Buccoliero, 2021). Environment, emotions and two opposing reactions make up a person’s response to external stimuli (i.e. approach or avoidance) (Easterby, 1976; Kim & Moon, 2009). As a result, the following hypotheses might be put up:
H5: Servicescape has a positive connection with CE.
H6: Servicescape has a positive connection with AE.
A recent study shows that service quality comprises field outcome and process quality (Parasuraman et al., 1985). Moreover, there is an outcome dimension to how well a service is regarded by clients. The OQ dimension is concerned with how the service transaction turned out (Gronroos, 1990; Swain & Kar, 2018). The treatment’s OQ may affect how treatment outcomes are perceived because true treatment effects involve not just therapeutic results but also psychological factors like rapport and the placebo effect. These hypotheses can be derived from the theories:
H7: Outcome quality has a positive connection with CE.
H8: Outcome quality has a positive connection with AE.
Electronic word of mouth is the online and social media sharing of customer information about a firm or organisation. Social media is excellent for EWOM, according to research. This is made feasible by the quick conveyance of information without having to convince or influence the targeted audiences face to face, making the material available everywhere. Previous research employed the service provider’s ability, compassion and honesty to build confidence. An emotional trust may increase buying intention (Wang et al., 2019). A conclusion can be drawn that EWOM significantly relates to overall customers’ experiences. As such, these hypotheses might be put up:
H9: EWOM has a positive connection with CE.
H10: EWOM quality has a positive connection with AE.
Customer experience is a moment of truth strategy. This lengthy period affects their long-term decisions to revisit or repurchase (Lemon & Verhoef, 2016). Revisit intention is the likelihood of consumers returning. Schmitt (1999) stated that experiential marketing emphasises customers’ emotions and rationality. Thus, a company may tailor experiential marketing to clients’ experiences (Rathee & Rajain, 2020). In this study, all prior assumptions can produce this emotional attachment. Product quality, SE, SS, OQ and EWOM contribute to customers’ CE and AE. All these factors create a subjective experience through processed information when a customer visits a particular place for the first time (Smithies & Weiss, 2019). Thus, when consumers like a place, they are more likely to return, boosting RI. From these statements, the following hypotheses can then be drawn:
H11: Cognitive experience has a positive connection with RI.
H12: Affective experience has a positive connection with RI.
Social media engagement and revisit intention
Social media networks enable brand-consumer marketing interactions. Social media affects consumer trust and repurchase beyond communication. Social media marketing boosts customer awareness, repurchase intentions and brand loyalty (Khan, 2022). Few research has examined how social media engagement (SME) affects beauty clinics’ luxury service RI. Research found social media engagement benefited aesthetic clinics (Jatiyananda et al., 2021). No study has studied how SME moderators affect brand image, trust, loyalty and intention to revisit. Social media engagement also mediated patient loyalty in one research (Heriyanto & Antonio, 2021). This hospital-based study measured satisfaction rather than experience. As a result, this study will evaluate the impacts of SME as a moderator in an aesthetic clinic, unlike earlier research that focused on social media marketing activities. Hypotheses may include:
H13: Social media engagement has a positive connection with CE and RI.
H14: Social media engagement has a positive connection with AE and RI.
Research framework
The conceptual frameworks are developed from previous studies by Zeithaml (1988), Shie et al. (2022), Bitner (1992), Kim et al. (2017), Hennig-Thurau et al. (2004), Alnawas and Hemsley-Brown (2018), Bustamante and Rubio (2017), Gentile et al. (2007) and Palací et al. (2019). Figure 1 illustrates the framework’s assumptions and the relationships between the variables. The objects in this study are all variables included in this research model. The dependent variable is RI, while PQ, SE, SS, OQ and EWOM are the independent variables. There are three additional variables of concern to this model, namely two mediating variables consisting of CE and AE, and one moderating variable which in this case is SME. The definition of each construct can be seen in Table 1.
Methods
This quantitative analysis employed cross-sectional data. Targeted population are patients who visited Youthology Aesthetic Clinic® minimum twice. It is a new, well-established aesthetic clinic with potential of expansion. This study used purposive sampling to collect data from preset objectives or groups (Bougie & Sekaran, 2020). Structured questionnaire indicators examined the conceptual framework’s aspects. This study used a questionnaire modified from previous research, such as PQ from Swain & Kar (2018), SE from Chandon et al. (1997), SS from Bitner (1992), OQ from Kim et al. (2017), EWOM from Hennig-Thurau et al. (2004), CE and AE from Brakus et al. (2009), SME from Choi and Kim (2013) and RI from Khan (2022). Respondents used the Likert scale to rate their agreement with the statements from ‘strongly disagree (1)’ to ‘strongly agree (5)’ (Bougie & Sekaran, 2020).
The conceptual framework, a complex research paradigm, has 14 parts. PLS-SEM was recommended for exploratory research because it could evaluate complex models (Sarstedt et al., 2022). The PLS-SEM analysis was carried out to assess significance using SmartPLS® Version 3.3, which was selected as it provides a bootstrapping menu to test significance (Memon et al., 2021).
The PLS-SEM analysis began with outer loading from the reflective model to assess indicator reliability. Twenty-one research model indicators satisfied outer loading requirements. Outer and inner models serve as the foundation for the primary method. Outer model is used to assess the validity and reliability of relationships between indicators and corresponding model components. The inner model is used to investigate if there is a meaningful connection between each component in the study model (Sarstedt et al., 2022).
Ethical considerations
The Research Ethical Committee of Universitas Pelita Harapan assessed the survey questionnaire. Interested entrepreneurs approved its dissemination. This essay follows research ethics without human or animal subjects. Permission for the research location was obtained from Youthology Aesthetic Clinic® (No. 11/HRD/Eks-Mng/KUD/XI/2022).
Results
The study had 280 eligible participants. Table 2 shows the study participants’ profiles. Female reactions predominate. Most responders lived in West and South Jakarta. Most respondents are upper-middle class, independent contractors with high purchasing power. They also had skin and face contouring consultations.
| TABLE 2: Respondents’ demographic profile. |
Analysing the outer model is the first step in the PLS-SEM model analysis process (Sarstedt et al., 2022). We excluded a few indicators that could not match the threshold value of 0.5, as required in the outer loading results in Table 3 (Hair et al., 2019).
All remaining indicators are reliable in measuring their respective constructs according to the model. The construct validity test was applied by analysing the average variance extracted (AVE). It can be deduced from the result that all indicators in this study model are considered valid to measure their respective constructs collectively (Hair et al., 2019). Heterotrait-monotrait (HT-MT) ratio is then applied to evaluate the discriminant validity. This method was chosen because it is reputed to provide a more accurate value (Hair et al., 2019). As all of the HT-MT values in Table 4 fall considerably below the 0.9 cutoff, it can be said that all of the indicators in this study model have achieved sufficient discrimination in measuring their respective constructs (Sarstedt et al., 2022). As a result, it can be concluded that every indicator in this study model is valid and dependable for measuring each construct explicitly.
| TABLE 4: Construct reliability, validity and discriminant validity (Heterotrait-monotrait). |
Variable inflation factor (VIF) is then used to determine multicollinearity issues. The findings showed all the constructs had inner VIF values below 5 as suggested (Hair et al., 2019); thus, it can be said that there is no multicollinearity issue found in this model (Table 5). The coefficient of determination or R2 of CE is 0.421, categorised as weak to moderate predictive accuracy (Table 5), as well as AE (0.462) and RI (0.428). Cognitive experience has a small effect size on RI with an f2 value of 0.108, as well as AE on RI (0.116), as seen in Table 7. The value of the construct Q2 predict of CE (0.398) and AE (0.454) shows medium predictive relevance, as well as RI (0.429), as shown in Table 6. Based on these results, it can be said that this model has consistency in its predictive ability.
| TABLE 5: Inner variable inflation factor values. |
| TABLE 6: Coefficient of determination and predictive relevance. |
The significance and coefficients of the variables in the structural model were evaluated to see whether or not the hypothesis could be supported. Based on the results shown in Table 8, all of the supported hypotheses have T-statistics greater than 1.645 (one-tailed with alpha 0.05) with p-value equal to or less than 0.05 and confidence interval (CI) 5% and CI 95% follow the direction of the hypotheses and there is no zero value between the ranges of CI 5% and CI 95%. As a result, we conclude that the analysis of the empirical data supports the 11 hypotheses that were created in this study.
Figure 2a and b shows that the moderation of SME to the link between AE and RI is consistent with the moderation of SME to the association between CE and RI. This means that when emotional intention rises, so will RI. Furthermore, as subjective experiences rise, so does the inclination to return.
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FIGURE 2: Simple slope analysis of (a) cognitive experience, and (b) affective experience on revisit intention. |
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It can be observed that the difference between +1 SD and −1 SD grows larger below 0 and that the meeting point between the +1 SD line and the −1 SD line is where the value of CE and RI grows. This also applies to AE and RI. The wider the difference between +1 SD and −1 SD, the stronger the influence of the moderating variable. The graph depicts a straight connection, indicating that the more the CE and AE, the greater the patient’s inclination to return.
These findings have management implications for the aesthetic clinic, as the clinic should improve the patient’s CE and AE by either expanding the content of social media to be more instructive and informative or by incorporating a sense of emotion into the material.
From the path linking the independent variables to the dependent variables (Table 9), four pathways are showing significant mediation (T-statistics > 1.645) of CE to RI and four have significant mediation of AE to RI. Thus, the eight pathways are shown to be interconnected and show a link between the antecedents and RI.
| TABLE 9: Specific indirect effect test results. |
In the context of cognitive and experience constructs, the variables must be maintained and continuously improved to achieve desirable OQ. It is worth noting down that the variables that must be a concern for management to be improved and cultivated are EWOM and SS. In cognitive construct indicators, the indicators that must be maintained are EW1 and OQ1. Meanwhile, PQ2, PQ4, SE6 and SE7 have run well but are not considered necessary by the clinic. EW1 and OQ1 are running very well and need to be maintained. Moreover, OQ3, EW4, SS3, EW3 and SS1 are considered essential but are still not performing well. Figure 3 shows importance-performance map analysis (IPMA) analysis results in indicators in estimating AE, which has the most prominent correlation towards RI. In the AE construct, SE is a variable that must be kept constant and enhanced. The factors of EWOM must also be considered for the management to be improved and nurtured. The affective construct indicator, EW1, must be kept up because it serves the clinic effectively, while SS1, SS3, EW3 and EW4 require much attention because they are underperforming but are important for the clinic.
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FIGURE 3: The importance-performance map analysis (IPMA) analysis of (a) cognitive experience (indicator), and (b) affective experience (indicator). |
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Discussion
This study examined how patient experience antecedents impact behaviour intention. This research defined patient experience as several encounters across time and emphasised cognitive and emotional consumer reactions (Molinillo et al., 2020; Palací et al., 2019). This study’s conclusion was drawn to illustrate the significance of the structural relationship depicted in Figure 4.
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FIGURE 4: Empirical model (hypothesis) R2 and Q2_predict. |
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Product quality, SS, OQ and EWOM positively influenced patient experience. Service encounter influenced AE but not CE. Patients judge SE more on the clinic’s medical staff’s empathy, warmth and friendliness. Thus, service emotions matter more. Service interactions may not always result in a favourable experience because consumers may need more than one visit to the facility to build a solid opinion (Voorhees et al., 2017). In contrast to other studies which focus on the promotion (Nurittamont, 2022), this study shows that patient experience of services at the clinic can adequately predict RI directly. It is true that patients remember the clinical services through brands, but the fundamental thing is the deep impression obtained from their experience at the clinic. Thus, it is recommended for clinic managers to routinely conduct patient experience surveys.
Electronic word of mouth, SS, PQ and OQ influenced CE the most. This finding supports the latest research from Hsu (2021) on a beauty enterprise, which shows that EWOM positively influences customer attitudes. The finding regarding EWOM is also in line with the study by Koay et al. (2020), where EWOM from social media marketing activity can influence brand experience and loyalty. Thus, clinic management must prioritise EWOM with strategic digital marketing. Positive online conversations about the clinic should be monitored and encouraged to become positive EWOM material that promotes clinic services.
This finding elucidates the notion from Bitner (1992) about the importance of SS in superior service. Patients who come to the clinic will evaluate the service based on its utility, such as complete facilities in the waiting room. This study is in line with Jeloudarlou et al. (2022), which showed a favourable correlation between SS and customer experience. Patient cognition also affected clinic PQ and treatment outcomes. Patient knowledge determines PQ. This study verifies patient evaluation-based OQ (Swain & Kar, 2018) in the healthcare service. Thus, the patient or consumer may evaluate the treatment’s success based on pre- and post-treatment findings. This finding is also in line with a study from Kim et al. (2017), which shows that the treatment results significantly affect RI. This OQ variable must account for the duration between treatment and ideal outcomes, as cosmetic clinic treatments frequently take time to show effects.
Parallel to PQ, EWOM, OQ, SS and SE were major AE antecedents. This result is in line with a study by Paulssen and Guru (2020). This reveals that customers’ evaluations of PQ and overall excellence or superiority over alternatives affect how enthusiastically they would use the same thing in the future. Thus, a clinic manager must work to maintain beauty PQ. This also becomes a concern because many unauthorised or counterfeit products are used in beauty clinics, which might harm the patient’s overall health and welfare. It is recommended for clinic managers to always inform consumers the quality certification of the product and the authenticity of the drugs or devices used before starting the treatment. This kind of communication should be the standard procedure before treatment.
This study shows that EWOM is crucial to emotional experiences. Short video storytelling and testimony are emotive. Thus, seeing or hearing EWOM might evoke pleasant feelings like enthusiasm (Fredrickson & Branigan, 2005). The finding of OQ to AE is also in line with a study by Klaus and Maklan (2013), which found that OQ positively influences customer experience and loyalty. Another study by Alnawas and Hemsley-Brown (2018) further supported this result, where it was emphasised that any positive or negative statement made by potential, actual or former customers about a product or company will eventually shape any decisions by information-seeking, specifically in the online marketplace and any reputations involved, hence implying consequences on customer AE. From these findings, it can be suggested that clinic managers may develop their promotional content, with pictures, videos and listening stories that can trigger positive emotions in the patients. This content can amplify the patient experience that has been formed, thereby strengthening their intention to continue using the clinic’s services.
The R2 value for CE in the research model assessment is found to be 0.421. This value represents that percentage of CE is 42.1% estimated by PQ, SS, OQ and EWOM. Particularly EWOM serves as the construct with the most prominent ability to estimate the CE. On another side, the R2 value for AE is 0.462. This value represents that percentage of CE is 46.2% estimated by all the antecedents, with PQ contributing as the most prominent relationship. These two results are only slightly different where R2 is found more in AEs. Furthermore, AE also has a slightly stronger influence on RI than CE (0.334 vs. 0.319). This result confirms previous research findings that AE has a more substantial influence on satisfaction than the CE (Ahn & Picard, 2014; Molinillo et al., 2020) and that the two dimensions can be independent at one time. Moreover, this overall experience reflected that customers have accomplished higher order of specific goals that represent a mix of utilitarian and emotional factors.
Overall, the two characteristics of experience have an equally beneficial impact on RI and align with earlier research that predicts customer loyalty (Choi & Kim, 2013; Giraldo et al., 2014; Jatiyananda et al., 2021; Woo & Choi, 2021). Thus, analysing cosmetic clinic customer experience must include cognitive and emotive elements, different from previous studies that focused on patient satisfaction to evaluate service by beauty clinics (Giraldo et al., 2014). This study shows that both experience dimensions may be used together to analyse antecedents in a new way. Thus, multimodal client experience should be evaluated (Schmitt, 1999). In an aesthetic clinic, the AE and CE can considerably predict client intentions to return.
Unexpectedly, SME moderation was not significant in the research findings. In another study, social media increased beauty clinic RI (Jatiyananda et al., 2021). Even if the coefficient value is low, an interesting phenomenon is discovered where AE strengthens RI while CE weakens it. Social networking weakened loyalty in a healthcare research (Heriyanto & Antonio, 2021). This is also mentioned in a prior study (Dolan et al., 2015) that social media consumer contact may have negative influence. The clinic’s social media material may not meet the client category. Another study indicated that brand experience regulated by social media marketing is stronger in the millennial subgroup than the non-millennial subgroup, suggesting that social media can influence certain target audiences more than others (Khan, 2022).
It is crucial to underline that social media is always public, searchable, shareable, volatile and dynamic. This may elicit various responses from target audiences, some of which may be negative. Patients may be influenced by third-party comments or overexpectations. Further studies are needed to investigate this finding.
This research model identified R2 value during the analysis of empirical data, which is classified as medium predictive accuracy, despite when viewed from f2 it categorised has a large effect size (f2 > 0.35) to RI respectively. When using out-of-sample examination from Q2 predict value, that is considered more advanced in assessing predictive power (Sarstedt et al., 2022). This research model classified has a medium predictive relevance. Therefore, this research model can be considered adequate to predict RI as a consequence of patient experience at the aesthetic clinic. Likewise, the R2 values for both experience dimensions were classified as moderate. Thus, the antecedents in this study can be considered satisfactory in predicting patient experience.
Through this research model, new insight can be contributed, namely integrating technical quality such as treatment OQ, infrastructural quality such as SS and social support quality such as EWOM. This is following the relevant proposition in the science of healthcare management that service quality in healthcare is broader than just functional quality (Swain & Kar, 2018). Also, the conventional SERVQUAL model with five dimensions is no longer sufficient to assess patient experience (Chahal & Kumari, 2010; Swain & Kar, 2018). This study fulfilled the previous research suggestions that it is necessary to measure the quality of service specifically for different types of health services (Endeshaw, 2021), such as the services provided by the aesthetic clinic. Apart from some limitations, this study which is deliberately done in aesthetic clinic services has proposed a model that can be developed in further research.
Conclusion
The identified antecedents of this study – PQ, EWOM, SS, OQ, and SE – are likely to affect patient experience. Parallel cognitive and affective experiences processed the antecedents differently. For instance, EWOM mostly affects CE and PQ affects AE.
This study improves patient experience multidimensional assessment for academics and managers. The experiential marketing theory showed that the two elements of patient experience might predict cosmetic clinic service RI. The model’s predictive power makes it suitable for a similar healthcare industry. This empirical study can help managers design a patient-centric company plan to ensure that existing clients will return to the aesthetic clinic.
Limitations and future research
This study has some limitations such that the data are based on patients from a single clinic in a single country, although it was done at one top aesthetic clinic, which has many clients yet may have diverse resources that impact service. Thus, random sample studies of clinics in the same category are needed to increase this study’s generalisability. This study did not classify respondents by therapy type, such as body or face contour and derma care. Aesthetic treatments may affect patient experience and treatment complexity. Laser and injectable filler clients have varied treatment times and results. Thus, future study must categorise responders by cosmetic clinic therapy.
The model measurement should also include patient experience scores for pre-, during and post-clinic treatment. Finally, the following research tests dimensionality through reflective first-order and second-order modelling of the patient experience construct and their structural linkages with other targeted constructs.
Acknowledgements
The authors would like to thank the staff of Youthology Aesthetic Clinic®, South Jakarta, Indonesia for their support during the period of the data collection.
Competing interests
The authors declare that they have no financial or personal relationships that may have inappropriately influenced them in writing this article.
Authors’ contributions
S.O. conceived the research. F.A. and A.A. planned the research. S.O., F.A., and A.A. wrote the manuscript. S.O. and A.A. conducted the data analysis, while F.A. read the final manuscript after putting down the implication and limitation of the research.
Funding information
The authors received no financial support for the research, authorship, and/or publication of this article.
Data availability
The data that support the findings of this study are available from the corresponding author, S.O., upon reasonable request.
Disclaimer
The views and opinions expressed in this article are those of the authors and do not necessarily reflect the official policy or position of any affiliated agency of the authors.
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