Understanding fine dining restaurant dynamics in south Asia: A systematic review

2.1 Review design

The review and the protocol for this review was developed in accordance with Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) (Page et al., 2021) and PRISMA – P (Shamseer et al., 2015) guidelines. This framework is widely used when examining the studies from a methodological, theoretical, and contextual point of view.

2.2 Review questions

2.3 Eligibility criteria

Population included adults (above 18 years of age) and they have been to fine dining restaurants. As authors, we have not followed any specific definition for “fine dining” restaurant. We have included all studies where the customers have been to “fine dine” or “upscale” or “up-market” restaurants where full table service was offered. While all types of study designs—quantitative, qualitative, and mixed methods—were eligible for inclusion, studies that utilize secondary data were excluded from the scope of this study. For this systematic review, reviews, conference papers, letters to the editor, pre-prints, editorials, thesis, commentaries, viewpoints, and perspectives were excluded.

Also, studies conducted in the context of quick service restaurants, fast food outlets, casual dining, family-style, and counter-service restaurants were not included in this review. Lastly, research articles published between January 2011 and October 2024, in English language, and conducted in South Asian countries were eligible for inclusion in this review. According to a regional inter-governmental association, Afghanistan, Bangladesh, Bhutan, India, Maldives, Nepal, Pakistan, and Sri Lanka are considered as South Asian countries (South Asian Association for Regional Cooperation, 2020).

We have narrowed down the scope of this review to focus exclusively on this region as the regional countries have significant similarities in their cuisine and culture. Furthermore, research conducted in other regions or countries may not accurately reflect the true situation or could potentially exaggerate certain aspects that are not usually endemic to this region.

2.4 Information sources and search strategy

Studies were identified by conducting a search on Medline (PubMed), Web of Science, Scopus, and Google Scholar with appropriate filters (language and period). The keywords used for building the search strategy were "fine dining" OR "restaurant dining" OR "upscale restaurant" OR "high-end restaurants" OR "five-star restaurant" OR "full service restaurant” AND “customer satisfaction" OR "customer loyalty" OR "return intention" OR "revisit intention" OR "customer fulfilment" AND “barriers” OR “factors” OR “facilitators” OR "motivating factors" OR "service quality" OR "physical environment" OR "food quality" OR “ambience” OR “menu” OR “pricing”. The search was customized for all other databases. The search strategy is provided in supplementary file 1.

2.5 Selection of eligible studies

Rayyan software (https://www.rayyan.ai/) was used for de-duplication and screening the articles after the database searches (Ouzzani et al., 2016). After de-duplication, in the first stage, the remaining records were screened by title and abstract and then, in the second stage, full-text articles were screened against the eligibility criteria. In each stage, two reviewers (PD and VSD) independently screened articles. Disagreement between the reviewers was settled by consulting a senior reviewer (SKP and KSN). Search results and two-stage screening process is depicted using PRISMA 2020 flowchart (Page et al., 2021).

2.6 Data extraction and charting

After a detailed discussion between the authors, a data extraction form was designed and pilot-tested to extract data in adequate detail. Modifications proposed by the authors were discussed and then incorporated in the final form. This final version of the form included various categories to capture the data relevant to our review such as data on the study citations, methodological details, fine dining, and the outcomes such as factors affecting fine dining selection, customer satisfaction, return intention, servicescape, customer loyalty. Data extraction was done independently by two reviewers and inconsistencies between the reviewers were discussed with a senior reviewer to reach consensus.

2.7 Quality assessment

Qualitative assessment of the included studies was done using Hawker's tool (Hawker et al., 2002). This tool is widely used in systematic reviews to evaluate studies by scoring them under nine criteria—1 point for each criteria that the study meets—such as title, abstract, introduction, method, sampling etc. The total score for each study ranges from a minimum of 9 to a maximum of 36. Subsequently, the studies, based on the total score, were categorised into three: first category corresponding to 30–36 score, second category for score ranging from 24 to 29, and for third category a score less than 24.

2.8 Data synthesis and reporting

The data were summarized narratively with key methodological attributes and results of the included studies presented in tabular format. A descriptive summary of the research methods such as research design, sampling strategy, analysis methods employed and the different aspects of fine dining are presented based on factors affecting customers’ choice, satisfaction, willingness to pay. This systematic review is reported in accordance with PRISMA guidelines (Page et al., 2021) and is provided in supplementary file 2.

3.1 Search results and study selection

Database search resulted in a total of 1180 records: 291 in Medline (through PubMed), 644 in Scopus, 245 in Web of Science. Review of the results yielded 113 duplicates and they were removed. A total of 1067 records were retained for title and abstract screening. After screening titles and abstracts, 979 articles were excluded. Another 200 citations were searched on Google Scholar. A total of 88 full text articles from database search and 30 from Google Scholar were taken forward for full-text screening. Studies at full text stage were excluded based on following reasons: not conducted in South Asia (n=59), fine dining restaurants not included in the study (n=16), population other than customers of fine dining restaurants (n=10), publication type(n=12), secondary data analysis using online reviews (n=03), and full text unavailable (n = 04). After full-text screening, fourteen studies met the eligibility criteria and were included in this review. Study selection procedure at different stages is depicted in PRISMA flow chart (Extended data).

3.2 Characteristics of included studies

The characteristics of the included studies on different aspects of fine dining restaurants are presented in table 1.

3.2.1 Location

Out of the fourteen studies, one was from Bangladesh (Tinne, 2012), ten studies were from India (Biswas & Verma, 2023; Dutta et al., 2014; Gharpure et al., 2021; Gupta et al., 2022; Lim et al., 2022; Nath & Agarwal, 2022; Rai & Anirvinna, 2019; Sahni & Mohsin, 2017; Shashikala & Suresh, 2018; Zeba et al., 2022), two studies were from Pakistan (Shahzadi et al., 2018; Tahir et al., 2022) and one study from Nepal (Upreti & Sherpa, 2018).

3.2.2 Study setting

A total of eleven studies were conducted in the context of upscale of fine dining restaurants (Biswas & Verma, 2023; Gharpure et al., 2021; Gupta et al., 2022; Lim et al., 2022; Rai & Anirvinna, 2019; Sahni & Mohsin, 2017; Shahzadi et al., 2018; Shashikala & Suresh, 2018; Tinne, 2012; Upreti & Sherpa, 2018; Zeba et al., 2022). Three studies considered multiple sectors such as fine dining, casual-dining, quick-service, independent, and chain restaurants (Dutta et al., 2014; Nath & Agarwal, 2022; Tahir et al., 2022). In three studies, the selection of restaurants was done on the basis of average price of a meal for two—between INR 1000 to 1500—(Shashikala & Suresh, 2018), Conde Nast Traveler Magazine List of 2019 (Biswas & Verma, 2023), and Tripadvisor rankings (Gupta et al., 2022). Other studies did not contain details about this aspect. The study by Nath & Agarwal, (2022) examined restaurants that were located within another building (such as malls). As regards the period of data collection, three studies specified the period during which data were collected (Lim et al., 2022; Sahni & Mohsin, 2017; Tahir et al., 2022).

3.2.3 Study design

Majority of the studies (Biswas & Verma, 2023; Gupta et al., 2022; Nath & Agarwal, 2022; Rai & Anirvinna, 2019; Sahni & Mohsin, 2017; Shashikala & Suresh, 2018; Tahir et al., 2022; Tinne, 2012; Upreti & Sherpa, 2018) used survey method. However, one study employed both survey and scenario-based factorial experimental design (Dutta et al., 2014) and two studies did not specify any study design (Gharpure et al., 2021; Shahzadi et al., 2018).

3.2.4 Population

Most of the studies described the study population was indicated as individuals those who have visited any upscale or fine dining restaurant (Biswas & Verma, 2023; Gharpure et al., 2021; Gupta et al., 2022; Lim et al., 2022; Rai & Anirvinna, 2019; Shahzadi et al., 2018; Shashikala & Suresh, 2018; Tinne, 2012; Upreti & Sherpa, 2018; Zeba et al., 2022). While Dutta et al. (2014) and Tahir et al. (2022) surveyed individuals who had been to either a fine dine or a casual restaurant, Nath & Agarwal (2022), surveyed individuals who have patronised any restaurant—casual, quick service or fine dining. Local residents or tourists were participants in one study (Sahni & Mohsin, 2017). Informed consent to participate was explicitly obtained for one study (Tinne, 2012). Only in one study, discount coupons were offered as a reward to respondents of the survey (Zeba et al., 2022).

3.2.5 Sampling

Non-probability sampling was employed by two studies (Shahzadi et al., 2018; Tinne, 2012) where the sampling method was judgemental i.e., based on the researcher’s personal judgement. Convenience/purposive sampling was used in seven studies (Biswas & Verma, 2023; Gharpure et al., 2021; Gupta et al., 2022; Lim et al., 2022; Rai & Anirvinna, 2019; Sahni & Mohsin, 2017; Zeba et al., 2022). The included studies used snowball sampling (Nath & Agarwal, 2022), systematic sampling (Shashikala & Suresh, 2018), random sampling (Dutta et al., 2014; Upreti & Sherpa, 2018), and stratified random sampling (Tahir et al., 2022) as well. There was considerable variation in the sample size of the studies with sample size ranging from 75 in one study to 693 in another study.

3.2.6 Theories, Research instrument and data collection

There are several theories that have been used in the included studies. The Stimulus-Organism-Response (S-O-R) model was used in four studies (Lim et al., 2022; Nath & Agarwal, 2022; Rai & Anirvinna, 2019; Shashikala & Suresh, 2018;). SERVQUAL model was used in three studies (Biswas & Verma, 2023; Dutta et al., 2014; Shahzadi et al., 2018). One study each utilised cognitive dissonance theory (Lim et al., 2022), DINESERV model (Upreti & Sherpa, 2018), theory of planned behaviour (Tahir et al., 2022) and theory of Reasoned Action (Zeba et al., 2022).

Survey tools consisted of questionnaires and Likert scale (Rai & Anirvinna, 2019; Tahir et al., 2022; Tinne, 2012; Upreti & Sherpa, 2018), self-administered questionnaire with close-ended questions (Biswas & Verma, 2023; Gharpure et al., 2021; Gupta et al., 2022; Lim et al., 2022; Nath & Agarwal, 2022; Sahni & Mohsin, 2017; Shahzadi et al., 2018; Shashikala & Suresh, 2018; Zeba et al., 2022), and open-ended questionnaire (Dutta et al., 2014). Two studies (Biswas & Verma, 2023; Gupta et al., 2022), used location intercept method to collect responses.

3.2.7 Data analysis methods

The analyses used were chi-square test (Sahni & Mohsin, 2017), gap analysis (Shahzadi et al., 2018), factor analysis (Biswas & Verma, 2023; Gupta et al., 2022; Lim et al., 2022; Shashikala & Suresh, 2018; Tinne, 2012), and factorial design by analysis of variance (ANOVA) (Dutta et al., 2014; Gharpure et al., 2021; Zeba et al., 2022). Correlation analysis was used in four studies (Gharpure et al., 2021; Rai & Anirvinna, 2019; Shahzadi et al., 2018; Upreti & Sherpa, 2018) and regression analysis were used in four studies (Rai & Anirvinna, 2019; Shashikala & Suresh, 2018; Upreti & Sherpa, 2018; Zeba et al., 2022). Descriptive statistics (frequency and percentages) were used by Nath & Agarwal (2022) and Upreti & Sherpa (2018) in their study. Structural equation modelling was used in four studies (Biswas & Verma, 2023; Gupta et al., 2022; Lim et al., 2022; Tahir et al., 2022).

3.2.8 Frequency of fine dining

Three studies reported the frequency of dining. While in one study it ranged from once a week to once a year (Shahzadi et al., 2018), Gupta et al. (2022) reported that approximately 70% of the respondents had dined at fine dining restaurant on multiple occasions. However, the specific timeframe for these visits was not specified. Lim et al. (2022) reported that around 80% of the respondents were dining for the first time at a fine dining restaurant.

In Pakistan, the choice of food mostly varied between traditional food on one hand and Chinese or Thai food on the other (Shahzadi et al., 2018). In Bangladesh, the preference was for local cuisine even when dining at an upscale restaurant (Tinne, 2012).

The findings of one study indicated that while majority of the respondents preferred visiting fine dining restaurant mostly with friends and family, around 10% preferred visiting with colleagues and very few preferred to visit alone (Shahzadi et al., 2018). This is consistent with results obtained by Lim et al. (2022). In an Indian study, dining companions were mostly friends followed by family.

3.2.9 Outcomes

The selected studies examined a variety of outcomes. In four studies (Nath & Agarwal, 2022; Sahni & Mohsin, 2017; Shahzadi et al., 2018; Tinne, 2012), factors influencing choice of fine dine restaurants were studied. Customer patronage and willingness to pay were examined by Dutta et al. (2014) and Gupta et al. (2022). Customer satisfaction was investigated in most of the studies (Biswas & Verma, 2023; Gharpure et al., 2021; Lim et al., 2022; Nath & Agarwal, 2022; Rai & Anirvinna, 2019; Shahzadi et al., 2018; Shashikala & Suresh, 2018; Upreti & Sherpa, 2018; Zeba et al., 2022). Behavioural intentions were measured in two studies (Gharpure et al., 2021; Shahzadi et al., 2018) and customer loyalty towards fine dine restaurants was examined in two studies (Rai & Anirvinna, 2019; Zeba et al., 2022). Lim et al. (2022) examined the connection between customer satisfaction and the word-of-mouth endorsement. Sustainable behaviour of restaurants and wastage reduction practices were investigated by one study (Tahir et al., 2022).

Factors affecting selection of fine dining restaurants

In the Bangladeshi study a comprehensive assessment was conducted, and fifteen factors were studied that impact customers’ choices when considering dining at upscale establishments. The study’s results indicated that the choice of upscale restaurants is primarily influenced by the promotional aspects, restaurants’ internal attributes, situational circumstances, pricing considerations, restaurant’s image, and the overall deluxe dining experience (Tinne, 2012). The same study indicated that many upscale restaurants go beyond merely offering exceptional cuisine; they also offer supplementary services such as dedicated children’s areas, celebrity appearances, and live performances to attract and engage consumers (Tinne, 2012).

In the study from Pakistan, Shahzadi et al. (2018) suggested the primary factors that influenced the choice of restaurant were: taste of the food, its safety, freshness, environmental cleanliness, and pricing. Among these, taste of food stood out as the most important factor when selecting a fine dining establishment, whereas music was accorded the least significance.

Sahni & Mohsin (2017) identified service quality as the only statistically significant factor that influences the choice of fine dine restaurants. Furthermore, their study indicates that across religions, the variety of food offered by the restaurant played a role in influencing the choice of fine dining establishments.

Nath & Agarwal (2022) found that servicescape ranks as the third most influential factor—after primary product offering and price consideration—when selecting a restaurant.

Customer satisfaction and associated factors

Four studies examined the impact of three quality attributes: food, service, and atmospherics (Dutta et al., 2014; Gharpure et al., 2021; Sahni & Mohsin, 2017; Shahzadi et al., 2018). In their study Gharpure et al. (2021) found overall customer satisfaction was significantly correlated with service quality—0.672 ** for helpfulness and politeness of staff, .669** for timeliness of service, and .531** for adequacy of staff and their grooming—and ambience— .545** for comfortable and welcoming feeling, .491** for availability and cleanliness of washrooms, and.516** upscale restaurant reputation. This was higher than correlation between overall customer satisfaction and food and beverage quality attributes such as portion size (.373**) and availability of the alcoholic beverages (.284**).

The same study indicated that among food quality attributes (portion size, temperature and taste, availability of alcoholic beverages and menu variety), highest correlation was found to be with temperature and taste of the food (.584**) and menu variety (.566**). The findings of two studies (Biswas & Verma, 2023; Upreti & Sherpa, 2018) indicate that satisfaction of diners in a fine dining establishment is notably influenced by various elements of dining services including tangibility, reliability, assurance, and empathy. Upreti & Sherpa (2018) report a robust and positive correlation, ranging from 0.761 (tangibility) to 0.892 reliability), with diner satisfaction. However, Biswas & Verma (2023) reported that the food quality (β = 0.448, p< .01) as the most crucial factor influencing customer satisfaction following closely, tangibility (β = 0.328, p< .01) was ranked second, succeeded by assurance, reliability, restaurant image, and responsiveness.

The results of another study—conducted during COVID-19 pandemic—indicate that customers give importance to factors such as food quality (including sensory experience, satiety value, and menu selection), hygiene, and pricing with the fine dining experience amid the pandemic (Lim et al., 2022). The authors present evidence to suggest that customer satisfaction mediated the relationship between various factors and word-of-mouth recommendation.

Zeba et al. (2022) report that each of the six attributes of perceived value—efficiency, service quality, social experience, enjoyment, aesthetics, and altruism—demonstrated a significant correlation with both customer delight and customer satisfaction. Additionally, the results suggest that in terms of ensuring customer satisfaction, utilitarian values exhibited higher regression coefficients than hedonic values. Conversely, when considering customer delight, the situation was reversed. When compared to customer satisfaction, customer delight exerts a more robust impact on customer loyalty and serves as a more accurate predictor of the same (Zeba et al., 2022).

Behavioural intentions and customer satisfaction

Association between behavioural intentions and customer satisfaction was studied in two studies (Gharpure et al., 2021; Shahzadi et al., 2018). Behavioural intentions such as recommending to others (r= .605, p <. 001) and being a frequent visitor (r= .608, p <. 001) were found to be positively correlated with overall satisfaction post visiting the fine dining restaurant (Gharpure et al., 2021). However, the other study (Shahzadi et al., 2018) reported that the relationship between restaurant attributes (food, service and atmospherics) and behavioural intentions was moderated by customer satisfaction.

Servicescape and customer’s loyalty

Servicescape and its relationship with different aspects of fine dining restaurants was examined in three studies (Nath & Agarwal, 2022; Rai & Anirvinna, 2019; Shashikala & Suresh, 2018). Correlation (0.769) was found between servicescape and customers’ loyalty towards dining at a fine dine restaurant (Rai & Anirvinna, 2019). The authors estimate that 59% of the variation in customer loyalty could be attributed to servicescape.

It was found that fine dining establishments experience higher levels of food wastage. This was attributed to the formal ambiance and frequent change of dinnerware. Additionally, the wastage has an impact on the sustainable dining practices and loyalty of patrons towards the foodservice business (Tahir et al., 2022).

Willingness to pay

Dutta et al. (2014) reported that for fine dining restaurants, willingness to pay increases with a corresponding increase in quality attributes (food, service, and atmospherics). This is supported by the findings of the study by Nath & Agarwal (2022) that indicated consumers were inclined to pay more for a pleasant dining atmosphere and forego the comfort of food delivered at home. Gupta et al. (2022) report that in contrast to other factors, higher correlation was observed between a strong interest in gastronomy and the willingness to pay a higher price for the experience of luxury while dining at fine dining restaurants.

3.3 Quality assessment of the included studies

Out of fourteen studies, six had scores between 30-36 (Dutta et al., 2014; Biswas & Verma, 2023; Tahir et al., 2022; Gupta et al., 2022; Lim et al., 2022; Zeba et al., 2022), four had scores between 24-29 (Tinne, 2012; Sahni & Mohsin, 2017; Shashikala & Suresh, 2018; Shahzadi et al., 2018) and four studies had scores less than 24 (Upreti & Sherpa, 2018; Rai & Anirvinna, 2019; Gharpure et al., 2021; Nath & Agarwal, 2022). Ethics and bias were reported in very few studies. Most of the studies scored between fair to good on items with respect to abstract, introduction and methods. Studies scoring less than 24 are generally regarded as poor to very poor on items such as transferability or generalisability, implications and usefulness, ethics and bias. The result of this quality assessment is presented in table 2.

Strengths and limitations

The review adhered to the PRISMA reporting guideline, ensuring a methodologically robust approach. The use of transparent methods and a structured, systematic approach further enhances the credibility of this review. The studies that were included, provide a valuable insight into the factors influencing customers’ choices and behaviours, customer satisfaction and willingness to pay in a fine dine restaurants; limited to the region of South Asia. The review aimed at synthesising the literature studies employing a systematic review methodology, offering a diverse perspective on the extent of subject matter in one of the most populated regions in the world.

The authors were able to delineate several points for future research. First, the limited number of studies meeting the eligibility criteria (fourteen), indicate a potential gap in literature on this topic. This indicates limited evidence: fourteen studies from four South Asian countries—India, Pakistan, Nepal and Bangladesh. No studies from Afghanistan, Bhutan, Maldives, or Sri Lanka met the inclusion criteria. This scarcity of studies limits the generalizability of the findings. Secondly, the studies incorporated in the analysis shared a commonality in focusing predominantly on quantitative surveys, with a notable absence of qualitative studies. This limitation posed a challenge in obtaining a varied perspective. Also, the lack of an operational definition of "fine dining" in studies may introduce ambiguity and hinder the synthesis of results.