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International Journal of Contemporary Hospitality Management

ISSN : 0959-6119

Article publication date: 10 April 2017

The purpose of this paper is to present a review of the foodservice and restaurant literature that has been published over the past 10 years in the top hospitality and tourism journals. This information will be used to identify the key trends and topics studied over the past decade, and help to identify the gaps that appear in the research to identify opportunities for advancing future research in the area of foodservice and restaurant management.

Design/methodology/approach

This paper takes the form of a critical review of the extant literature that has been done in the foodservice and restaurant industries. Literature from the past 10 years will be qualitatively assessed to determine trends and gaps in the research to help guide the direction for future research.

The findings show that the past 10 years have seen an increase in the number of and the quality of foodservice and restaurant management research articles. The topics have been diverse and the findings have explored the changing and evolving segments of the foodservice industry, restaurant operations, service quality in foodservice, restaurant finance, foodservice marketing, food safety and healthfulness and the increased role of technology in the industry.

Research limitations/implications

Given the number of research papers done over the past 10 years in the area of foodservice, it is possible that some research has been missed and that some specific topics within the breadth and depth of the foodservice industry could have lacked sufficient coverage in this one paper. The implications from this paper are that it can be used to inform academics and practitioners where there is room for more research, it could provide ideas for more in-depth discussion of a specific topic and it is a detailed start into assessing the research done of late.

Originality/value

This paper helps foodservice researchers in determining where past research has gone and gives future direction for meaningful research to be done in the foodservice area moving forward to inform academicians and practitioners in the industry.

• Hospitality management
• Restaurants
• Food and beverage
• Foodservice research

DiPietro, R. (2017), "Restaurant and foodservice research: A critical reflection behind and an optimistic look ahead", International Journal of Contemporary Hospitality Management , Vol. 29 No. 4, pp. 1203-1234. https://doi.org/10.1108/IJCHM-01-2016-0046

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Restaurant Quality Analysis: A Machine Learning Approach

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• Rohit B. Diwane 12 ,
• Kavita S. Oza 12 &
• Varsha P. Desai 13  

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 672))

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Managing customer’s happiness has emerged as a significant business trend, particularly in the restaurant industry. The purpose of this study is to determine how K-Means algorithms can be used to measure customer satisfaction at a family restaurant in Kolhapur. A survey is carried out related to services and ambiguous at the restaurant. What makes restaurants popular is the main focus of the survey. Data collected through online survey are clustered using the elbow method as well as the K-Means clustering. This study presents the results of the customer satisfaction measurement and offers improvement and recommendations to the concerned restaurant.

• K-Means algorithms
• Elbow method
• Principal Component Analysis

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Claypo N, Jaiyen S (2015) Opinion mining for Thai restaurant reviews using K-means clustering and MRF feature selection, 978-1-4799-6049-1

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Department of Computer Science, Shivaji University, Kolhapur, Maharashtra, India

Rohit B. Diwane & Kavita S. Oza

Computer Science & Engineering Department, D. Y. Patil Agriculture and Technical University, Talsande, Kolhapur, Maharashtra, India

Varsha P. Desai

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Diwane, R.B., Oza, K.S., Desai, V.P. (2023). Restaurant Quality Analysis: A Machine Learning Approach. In: Suma, V., Lorenz, P., Baig, Z. (eds) Inventive Systems and Control. Lecture Notes in Networks and Systems, vol 672. Springer, Singapore. https://doi.org/10.1007/978-981-99-1624-5_10

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Satisfaction and revisit intentions at fast food restaurants

• Amer Rajput 1 &
• Raja Zohaib Gahfoor 2  

Future Business Journal volume  6 , Article number:  13 ( 2020 ) Cite this article

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This study is to identify the positive association of food quality, restaurant service quality, physical environment quality, and customer satisfaction with revisit intention of customers at fast food restaurants. Additionally, word of mouth is investigated as moderator on the relationship of customer satisfaction with revisit intentions of customers at fast food restaurants. Data were collected through a questionnaire survey from 433 customers of fast food restaurants through convenience sampling. Hypotheses of proposed model were tested using structural equation modeling with partial least squares SEM-PLS in SMART PLS 3. The results confirmed the positive association of food quality, restaurant service quality, physical environment quality, and customer satisfaction with revisit intentions of customers at fast food restaurants. However, word of mouth does not positively moderate the relationship of customer satisfaction with revisit intentions of customers at fast food restaurants. This study emphasizes the importance of revisit intention as a vital behavioral reaction in fast food restaurants. This study reveals revisit intention’s positive association with food quality, restaurant service quality, physical environment quality, and customer satisfaction based on stimulus-organism-response (S-O-R) theory. Furthermore, it is identified that social conformity theory does not hold its assumption when consumers experience quality and they are satisfied because word of mouth does not moderate the relationship of customer satisfaction with revisit intention of customer.

Introduction

Background of the study.

Hospitality industry is observing diversified changes in highly competitive environment for restaurants [ 1 ]. Consumers are becoming conscious of food quality (FQ), restaurant service quality (RSQ), and physical environment quality (PEQ) of the fast food restaurants. Consumers switch easily in case of just one evasive experience [ 2 , 3 ]. Fast food restaurants must attract new customers and retain the existing customers. There is a growing trend in Pakistani culture to dine out at fast food restaurants with family, friends, and colleagues [ 4 ]. Restaurants focus to provide a dining experience by combining tangible and intangible essentials [ 5 ]. Decisive objective is to achieve customer satisfaction (CS), word of mouth (WOM), and future revisit intention (RVI) at fast food restaurant.

Restaurants differ in offerings, appearance, service models, and cuisines; this classifies restaurants as downscale and upscale [ 6 , 7 ]. Revisit intention is the willingness of a consumer to revisit a place due to satisfactory experience. Customer satisfaction generates a probability to revisit in presence or absence of an affirmative attitude toward the restaurant [ 8 ]. Revisit intention is a substantial topic in hospitality research [ 8 , 9 , 10 ]. To date there has been little agreement on that word of mouth can affect revisit intention after experience of customer satisfaction. For instance, when a customer is satisfied at a fast food restaurant experience, however, the customer’s family and friends do not share the same satisfying experience. Will this word of mouth affect the customer’s revisit intention? Food quality is acknowledged as a basic component of the restaurant’s overall experience to affect consumer revisit intention. Fast food quality is substantially associated with customer satisfaction and it is an important predictor of behavioral intention [ 11 ]. Service quality is an essential factor to produce consumers’ revisit intentions [ 12 ]. Furthermore, physical environment quality affects behavior of consumers at restaurants, hotels, hospitals, retail stores, and banks [ 13 ]. Physical environment quality is a precursor of customer satisfaction [ 9 ]. This suggests that customer satisfaction is associated with fast food quality, restaurant service quality, physical environment quality, and revisit intention.

Aims of the study

This study is to investigate the association of fast food quality, restaurant service quality, physical environment quality with customer’s revisit intention through mediation of customer satisfaction using S-O-R theory and moderation of word of mouth on the relationship of customer satisfaction with revisit intention based on social conformity theory. This study empirically tests a conceptual research framework based on S-O-R and social conformity theory adding value to the knowledge. Objectives of the study are given below.

To investigate the association of fast food quality, restaurant service quality, and physical environment quality with revisit intention through customer satisfaction based on S-O-R theory in the context of Pakistani fast food restaurants.

To investigate moderation of WOM on relationship of customer satisfaction with revisit intention based on social conformity theory in the context of Pakistani fast food restaurants.

Furthermore, little empirical evidence is present about customer satisfaction with respect to fast food restaurant service quality [ 14 ]. Customer satisfaction is a post-consumption assessment in service industry. Customer satisfaction acts as the feedback mechanism to boost consumer experience [ 15 ]. Customer satisfaction brings competitive advantage to the firm and produces positive behavioral revisit intention [ 16 ]. Marketing literature emphasizes customer satisfaction in anticipation of positive word of mouth, revisit intention, and revisit behavior [ 5 ]. Behavioral intention is assessed through positive WOM, and it is important in service industry [ 15 ], whereas social influence in shape of WOM affects the behavior of individuals toward conformity leading to a driving effect based on social conformity theory [ 17 ].

• Food quality

Food quality plays a central role in the restaurant industry. Food quality is essential to satisfy consumer needs. Food quality is a substantial condition to fulfill the needs and expectations of the consumer [ 18 ]. Food quality is acknowledged as a basic component of the restaurant’s overall experience. Food quality is a restaurant selection’s most important factor, and it is considerably related to customer satisfaction [ 11 ]. Food quality affects customer loyalty, and customer assesses the restaurant on the basis of food quality [ 19 ]. Food quality entails food taste, presentation, temperature, freshness, nutrition, and menu variety. Food quality influences customers’ decisions to revisit the restaurant [ 20 ]. Academic curiosity is increasing in the restaurant’s menus, as variety of menu items is considered the critical characteristic of food quality [ 11 ]. Taste is sensual characteristic of food. Taste is assessed after consumption. Nonetheless, customers foresee taste before consumption through price, quality, food labels, and brand name. Taste of food is important to accomplish customer satisfaction. Presentation of food enhances dining customer satisfaction [ 21 , 22 ]. Customer’s concerns of healthy food substantially affect customer’s expectations and choice of a restaurant [ 23 ]. Freshness is assessed with the aroma, juiciness, crispness, and fresh posture of the food. Food quality enhances customer satisfaction [ 24 ].

• Restaurant service quality

Quality as a construct is projected by Juran and Deming [ 25 , 26 ]. Service quality is comparatively a contemporary concept. Service quality assesses the excellence of brands in industry of travel, retail, hotel, airline, and restaurant [ 27 ]. Restaurant service quality affects dining experiences of customers. Service quality creates first impression on consumers and affects consumers’ perception of quality [ 28 ]. Service industry provides good service quality to the customers to attain sustainable competitive advantage. Customer satisfaction depends on quality of service at the restaurant [ 29 ]. Service quality entails price, friendliness, cleanliness, care, diversity, speed of service, and food consistency according to menu. Customer satisfaction also depends on communication between restaurant’s personnel and the customers [ 30 ]. Consumer’s evaluation of service quality is affected by level of friendliness and care. Service quality leads to positive word of mouth, customer satisfaction, better corporate image, attraction for the new customers, increase revisits, and amplified business performance. Service quality increases revisits and behavioral intentions of customers in hospitality industry [ 12 ].

• Physical environment quality

PEQ is a setting to provide products and services in a restaurant. Physical environment quality contains artifacts, decor, spatial layout, and ambient conditions in a restaurant. Customers desire dining experience to be pleasing; thus, they look for a physical environment quality [ 31 ]. Physical environment quality satisfies and attracts new customers. PEQ increases financial performance, and it creates memorable experience for the customers [ 9 ]. Consumers perceive the quality of a restaurant based on cleanliness, quirky, comfortable welcoming, physical environment quality, and other amenities that create the ambiance [ 32 ]. Effect of physical environment quality on behaviors is visible in service businesses such as restaurants, hotels, hospitals, retail stores, and banks [ 33 ]. Physical environment quality is an antecedent of customer satisfaction [ 34 ]. Thus, restaurants need to create attractive and distinctive physical environment quality.

• Customer satisfaction

Customer satisfaction contains the feelings of pleasure and well-being. Customer satisfaction develops from gaining what customer expects from the service. Customer satisfaction is broadly investigated in consumer behavior and social psychology. Customer satisfaction is described “as the customer’s subjective assessment of the consumption experience, grounded on certain associations between the perceptions of customer and objective characteristics of the product” [ 35 ]. Customer satisfaction is the extent to which an experience of consumption brings good feelings. Customer satisfaction is stated as “a comparison of the level of product or service performance, quality, or other outcomes perceived by the consumer with an evaluative standard” [ 36 ]. Customer satisfaction constructs as a customer’s wholesome evaluation of an experience. Customer satisfaction is a reaction of fulfilling customer’s needs.

Customer satisfaction brings escalated repeat purchase behavior and intention to refer [ 37 ]. Dissatisfied consumers are uncertain to return to the place [ 38 ]. Satisfactory restaurant experience can enhance revisit intention of the consumer. Positive WOM is generated when customers are not only satisfied with the brand but they demand superior core offering and high level of service [ 15 ].

• Word of mouth

Word of mouth is described as “person-to-person, oral communication between a communicator and receiver which is perceived as a non-commercial message” [ 39 ]. WOM is also defined as “the informal positive or negative communication by customers on the objectively existing and/or subjectively perceived characteristics of the products or services” [ 40 ]. Moreover, [ 41 ] defines it as “an informal person to person communication between a perceived non-commercial communicator and a receiver regarding a brand, a product, an organization or a service”. WOM is described as a positive or negative statement made by probable, actual or former customers about a product or a company, which is made available through offline or online channels [ 42 , 43 ]. WOM is an important and frequent sensation; it is known for long time that people habitually exchange their experiences of consumptions with others. Consumers complain about bad hotel stays, talk about new shoes, share info about the finest way of getting out tough stains, spread word about experience of products, services, companies, restaurants, and stores. Social talks made more than 3.3 billion of brand impressions per day [ 44 ].

WOM has substantial impact on consumer’s purchasing decision; therefore, a vital marketing strategy is to initiate positive WOM [ 45 ]. However, negative WOM is more informative and diagnostic where customers express their dissatisfaction [ 38 ]. Word of mouth communications are more informative than traditional marketing communications in service sector. WOM is more credible than advertisement when it is from friends and family [ 46 ]. WOM is a vital influencer in purchase intention. WOM escalates affection that enhances commitment of consumer purchase intention. WOM is generated before or after the purchase. WOM helps the consumers to acquire more knowledge for the product and to reduce the perceived risk [ 47 ]. WOM in the dining experience is very important. People tend to follow their peers’ opinions when they are to dine out.

• Revisit intention

To predicting and to explain human behavior is the key determination of consumer behavior research. Consumer needs differ and emerge frequently with diverse outlooks. Revisit intention is to endorse “visitors being willing to revisit the similar place, for satisfactory experiences, and suggest the place to friends to develop the loyalty” [ 48 ]. Consumer forms an attitude toward the service provider based on the experience of service. This attitude can be steady dislike or like of the service. This is linked to the consumer’s intention to re-patronize the service and to start WOM. Repurchase intention is at the core of customer loyalty and commitment. Repurchase intention is a significant part of behavioral and attitudinal constructs. Revisit intention is described as optimistic probability to revisit the restaurant. Revisit intention is the willingness of a consumer to visit the restaurant again. Furthermore, the ease of visitors, transportation in destination, entertainment, hospitability, and service satisfaction influence visitor’s revisit intention.

Consumer behavior encircles the upcoming behavioral intention and post-visit evaluation. Post-visit evaluation covers perceived quality, experience, value, and the satisfaction. Restaurant managers are interested to understand the factors of consumer revisit intention, as it is cost effective to retain the existing customers in comparison with attract new customers [ 49 ]. Substantial consideration is prevailing in literature for the relationship among quality attributes, customer satisfaction, and revisit intention. There is a positive association between customer satisfaction and revisit intention. Indifferent consumer, accessibility of competitive alternatives and low switching cost can end up in a state where satisfied consumers defect to other options [ 2 ]. Consumer behavior varies for choice of place to visit, assessments, and behavioral intentions [ 50 ]. The assessments are about the significance perceived by regular customers’ satisfactions. Whereas, future behavioral intentions point to the consumer’s willingness to revisit the similar place and suggest it to the others [ 51 ].

S-O-R model is primarily established on the traditional stimulus–response theory. This theory explicates individual’s behavior as learned response to external stimuli. The theory is questioned for oversimplifying ancestries of the behaviors and ignoring one’s mental state. [ 52 ] extended the S-O-R model through integrating the notion of organism between stimulus and response. S-O-R concept is embraced to reveal individual’s affective and cognitive conditions before the response behavior [ 53 ]. S-O-R framework considers that environment comprises stimuli (S) leading changes to the individual’s internal conditions called organism (O), further leading to responses (R) [ 52 ]. In S-O-R model, the stimuli comprise of various components of physical environment quality, organism indicates to internal structures and processes bridging between stimuli and final responses or actions of a consumer [ 9 ]. Behavioral responses of an individual in a physical environment quality are directly influenced by the physical environment quality stimulus [ 54 ]. S-O-R framework is implemented in diverse service contexts to examine how physical environment quality affects customer’s emotion and behavior [ 55 ]. The effect of stimulation in an online shopping environment on impulsive purchase is investigated through S-O-R framework [ 56 ]. The effects of background music, on consumers’ affect and cognition, and psychological responses influence behavioral intentions [ 57 ]. Perceived flow and website quality toward customer satisfaction affect purchase intention in hotel website based on S-O-R framework [ 58 ]. Therefore, this study conceptualizes food quality, restaurant service quality, and physical environment quality as stimuli; customer satisfaction as organism; and revisit intention as response.

Moreover, social conformity theory (SCT) is to support the logical presence of WOM in the conceptual framework as a moderator on the relationship of customer satisfaction and revisit intention. Social conformity influences individual’s attitudes, beliefs and behaviors leading to a herding effect [ 17 , 59 ]. Thus, social influence (WOM) moderates the relationship of customer satisfaction and revisit intention. Following hypotheses are postulated, see Fig.  1 .

Conceptual research framework

Food quality is positively associated with customer satisfaction in fast food restaurant.

Restaurant service quality is positively associated with customer satisfaction in fast food restaurant.

Physical environment quality is positively associated with customer satisfaction in fast food restaurant.

Customer satisfaction is positively associated with revisit intention of customer in fast food restaurant.

Customer satisfaction mediates between food quality and revisit intention of customer in fast food restaurant.

Customer satisfaction mediates between restaurant service quality and revisit intention of customer in fast food restaurant.

Customer satisfaction mediates between physical environment quality and revisit intention of customer in fast food restaurant.

WOM positively moderates the relationship between customer satisfaction and revisit intention of customer in fast food restaurant.

There are two research approaches such as deductive (quantitative) and inductive (qualitative). This study utilized the quantitative research approach as it aligns with the research design and philosophy. Quantitative research approach mostly relies on deductive logic. Researcher begins with hypotheses development and then collects data. Data are used to determine whether empirical evidence supports the hypotheses [ 60 ]. The questionnaires survey is used. This study chose the mono-method with cross-sectional time horizon of 6 months. Deductive approach is utilized in this study. Cross-sectional time horizon also known as “snapshot” is used when investigation is related with the study of a specific phenomenon at a particular time [ 61 ]. Questionnaire survey is mostly used technique for data collection in marketing research due to its effectiveness and low cost [ 62 ]. Data are collected through self-administered questionnaires. Following the footsteps of Lai and Chen [ 63 ] and Widianti et al. [ 64 ] convenience sampling is applied. Famous fast food restaurants in twin cities (Rawalpindi and Islamabad) of Pakistan were chosen randomly. Furthermore, 650 questionnaires (with consideration of low response rate) were distributed to the customers at famous fast food restaurants. Moreover, researchers faced difficulty in obtaining fast food restaurant’s consumers data.

It yielded a response rate of 68.92% with 448 returned questionnaires. Fifteen incomplete questionnaires are not included; thus, 433 responses are employed for data analysis from fast food restaurant customers. The obtained number of usable responses was suitable to apply structural equation modeling [ 65 , 66 , 67 , 68 ].

Sample characteristics describe that there are 39.7% females and 60.3% males. There are 31.4% respondents of age group 15–25 years, 48.3% of age group 26–35, 12.2% of age ranges between 36 and 45, 6.7% of age ranges between 46 and 55, and 1.4% of age group is above 56 years. The educational level of the respondents indicates that mostly respondents are undergraduate and graduate. Occupation of respondents reflects that 28.6% work in private organizations and 24.9% belong to student category. Monthly income of 29.3% respondents ranges between Rupees 20,000 and 30,000 and 25.6% have monthly income of Rupees 41,000–50,000. Average monthly spending in fast food restaurants is about Rupees 3000–6000, see Table  1 .

Measures of the constructs

Food quality is adopted from measures developed by [ 69 ]. Food quality contains six items such as: food presentation is visually attractive, the restaurant offers a variety of menu items, and the restaurant offers healthy options. Restaurant service quality is adopted with six items [ 70 ]. This construct contains items such as: efficient and effective process in the welcoming and ushering of the customers, efficient and effective explanation of the menu, efficient and effective process in delivery of food. Physical environment quality is adopted with four items [ 71 ], and one item is adopted from measures developed by [ 70 ]. The items are such as: the restaurant has visually striking building exteriors and parking space, the restaurant has visually eye-catching dining space that is comfortable and easy to move around and within, and the restaurant has suitable music and/or illumination in accordance with its ambience. Revisit intention is measured through four adapted items [ 8 ]; such as: I would visit again in the near future and I am interested in revisiting again. Customer satisfaction is measured by three adopted items [ 29 ]; such as: I am satisfied with the service at this restaurant, and the restaurant always comes up to my expectations. Word of mouth is measured with four adopted items such as: my family/friends mentioned positive things I had not considered about this restaurant, my family/friends provided me with positive ideas about this restaurant [ 72 ]. Each item is measured on 5-point Likert scale, where 1 = strongly disagree, 3 = uncertain, and 5 = strongly agree.

Results and discussion

Validity and reliability.

Validity taps the ability of the scale to measure the construct; in other words, it means that the representative items measure the concept adequately [ 73 ]. The content validity is executed in two steps; firstly, the items are presented to the experts for further modifications; secondly, the constructive feedback about understanding of it was acquired by few respondents who filled the questionnaires. Each set of items is a valid indicator of the construct as within-scale factor analysis is conducted.

The factor analyses allotted the items to their respective factor. Fornell and Lacker’s [ 74 ] composite reliability p is calculated for each construct using partial least squares (PLS) structural equation modeling and Cronbach’s coefficient α [ 75 ]. Cronbach’s α is used to evaluate the reliability of all items that indicates how well the items in a set are positively related to one another. Each Cronbach’s α of the instrument is higher than .7 (ranging from .74 to .91); see Table  2 .

Common method bias

Same measures are used to collect data for all respondents; thus, there can be common method bias [ 76 ]. Firstly, questionnaire is systematically constructed with consideration of study design. Secondly, respondents were assured for the responses to be kept anonymous [ 77 ]. Common method bias possibility is assessed through Harman’s single factor test [ 78 , 79 , 80 , 81 , 82 , 83 ]. Principal axis factor analysis on measurement items is exercised. The single factor did not account for most of the bias and it accounted for 43.82% variance that is less than 50%. Thus, common method bias is not an issue [ 80 , 81 ].

SEM-PLS model assessment

Survey research faces a challenge to select an appropriate statistical model to analyze data. Partial least squares grounded structural equation modeling (SEM-PLS) and covariance-based structural equation modeling (CB-SEM) are generally used multivariate data analysis methods. CB-SEM is based on factor analysis that uses maximum likelihood estimation. PLS-SEM is based on the principal component concept; it uses the partial least squares estimator [ 84 ]. PLS-SEM is considered appropriate to examine complex cause–effect relationship models. PLS-SEM is a nonparametric approach with low reservations on data distribution and sample size [ 84 ].

Measurement model assessment

To evaluate convergent validity measurement model (outer model) is assessed that includes composite reliability (CR) to evaluate internal consistency, individual indicator reliability, and average variance extracted (AVE) [ 85 ]. Indicator reliability explains the variation in the items by a variable. Outer loadings assess indicator reliability; a higher value (an item with a loading of .70) on a variable indicates that the associated measure has considerable mutual commonality [ 85 ]. Two items RSQ 14 and PEQ 24 are dropped due to lower value less than .60 [ 86 ]. Composite reliability is assessed through internal consistency reliability. CR values of all the latent variables have higher values than .80 to establish internal consistency [ 85 ]; see Table  2 .

Convergent validity is the extent to which a measure correlates positively with alternative measures of the same variable. Convergent validity is ensured through higher values than .50 of AVE [ 74 ], see Table  2 . Discriminant validity is the degree to which a variable is truly distinct from other variables. Square root of AVE is higher than the inter-construct correlations except customer satisfaction to hold discriminant validity [ 74 ]. Additional evidence for discriminant validity is that indicators’ individual loadings are found to be higher than the respective cross-loadings, see Table  3 .

Structural model assessment

Structural model is assessed after establishing the validity and reliability of the variables. Structural model assessment includes path coefficients to calculate the importance and relevance of structural model associations. Model’s predictive accuracy is calculated through R 2 value. Model’s predictive relevance is assessed with Q 2 , and value of f 2 indicates substantial impact of the exogenous variable on an endogenous variable in PLS-SEM [ 85 ]. SEM is rigueur in validating instruments and testing linkages between constructs [ 87 ]. SMART-PLS produces reports of latent constructs correlations, path coefficients with t test values. The relationships between six constructs of food quality, restaurant service quality, physical environment quality, customer satisfaction, word-of-mouth, and revisit intention are displayed in Fig.  2 after bootstrapping. Bootstrapping is a re-sampling approach that draws random samples (with replacements) from the data and uses these samples to estimate the path model multiple times under slightly changed data constellations [ 88 ]. Purpose of bootstrapping is to compute the standard error of coefficient estimates in order to examine the coefficient’s statistical significance [ 89 ].

Bootstrapping and path coefficients

Food quality is positively associated to customer satisfaction in fast food restaurant; H 1 is supported as path coefficient = .487, T value = 8.349, P value = .000. Restaurant service quality is positively associated with customer satisfaction; H 2 is supported as path coefficient = .253, T value = 4.521, P value = .000. Physical environment quality is positively associated with customer satisfaction in fast food restaurant; H 3 is supported as path coefficient = .149, T value = 3.518, P value = .000. Customer satisfaction is positively associated with revisit intention of customer in fast food restaurant; H 4 is supported as path coefficient = .528, T value = 11.966, P value = .000. WOM positively moderates the relationship between customer satisfaction and revisit intention of customer in fast food restaurant; H 8 is not supported as path coefficient = − .060, T value = 2.972, P value = .003; see Table  4 .

Assessing R 2 and Q 2

Coefficient of determination R 2 value is used to evaluate the structural model. This coefficient estimates the predictive precision of the model and is deliberated as the squared correlation between actual and predictive values of the endogenous construct. R 2 values represent the exogenous variables’ mutual effects on the endogenous variables. This signifies the amount of variance in endogenous constructs explained by total number of exogenous constructs associated to it [ 88 ]. The endogenous variables customer satisfaction and revisit intention have R 2  = .645 and .671, respectively, that assures the predictive relevance of structural model. Further the examination of the endogenous variables’ predictive power has good R 2 values.

Blindfolding is to cross-validate the model’s predictive relevance for each of the individual endogenous variables with value of Stone–Geisser Q 2 [ 90 , 91 ]. By performing the blindfolding test with an omission distance of 7 yielded cross-validated redundancy Q 2 values of all the endogenous variables [ 88 ]. Customer satisfaction’s Q 2  = .457 and RVI’s Q 2  = .501; this indicates large effect sizes. PLS structural model has predictive relevance because values of Q 2 are greater than 0, see Table  5 .

Assessing f 2

Effect size f 2 is the measure to estimate the change in R 2 value when an exogenous variable is omitted from the model. f 2 size effect illustrates the influence of a specific predictor latent variable on an endogenous variable. Effect size f 2 varies from small to medium for all the exogenous variables in explaining CS and RVI as shown Table  6 .

Additionally, H 5 : CS mediates between food quality and RVI is supported as CS partially mediates between FQ and RVI. Variation accounted for (VAF) value indicates that 70% of the total effect of an exogenous variable FQ on RVI is explained by indirect effect. Therefore, the effect of FQ on RVI is partially mediated through CS. Similarly, the VAF value indicates that 70% of the total effect of an exogenous variable RSQ and 35% VAF of PEQ on RVI is explained by indirect effect. Therefore, the effects of RSQ and PEQ on RVI are also partially mediated through CS. H 6 is supported as the effect of CS is partially mediated between RSQ and RVI of customer in fast food restaurant. H 7 is supported as the effect of CS is partially mediated between PEQ and RVI of customer in fast food restaurant, see Table  7 . This clearly indicates that customer satisfaction mediates between all of our exogenous variables (food quality, restaurant service quality and physical environment quality) and dependent variable revisit intention of customer in fast food restaurant [ 88 , 92 ] (Additional files 1 , 2 and 3 ).

This is interesting to note that food quality, restaurant service quality, physical environment quality, and customer satisfaction are important triggers of revisit intention at fast food restaurants. However, surprisingly, word of mouth does not moderate the relationship of customer satisfaction with revisit intention of customer at fast food restaurant. The results of the study correspond with some previous findings [ 15 , 29 , 32 , 69 , 93 ]. Positive relationship between customer satisfaction and revisit intention is consistent with the findings of the previous studies [ 5 , 8 , 94 , 95 , 96 ]. Food quality is positively associated with revisit intention; this result as well corresponds to a previous study [ 24 ]. Furthermore, interior and amusing physical environment is an important antecedent of revisit intention at a fast food restaurant; this finding is congruent with previous findings [ 29 , 70 , 97 , 98 ] and contrary to some previous studies [ 9 , 15 ].

Intensified competition, industry’s volatile nature, and maturity of the business are some challenges that fast food restaurants face [ 5 ]. Amid economic crunch, competition becomes even more evident, driving fast food restaurants to look for unconventional ways to appeal the customers. In fact, these findings somehow show that significance of physical environment quality in creating revisit intention is probably lower in comparison with food quality and restaurant service quality. Nonetheless, fast food restaurant’s management should not underrate the fact that physical environment quality considerably affects the revisit intention. Due to this, the importance of physical environment quality must not be overlooked when formulating strategies for improving customer satisfaction, revisit intention and creating long-term relationships with customers.

Managerial implications

The results imply that restaurant management should pay attention to customer satisfaction because it directly affects revisit intention. Assessing customer satisfaction has become vital to successfully contest in the modern fast food restaurant business. From a managerial point of view, the results of this study will help restaurant managers to better understand the important role of food quality, restaurant service quality and physical environment quality as marketing tool to retain and satisfy customers.

Limitations

There are certain limitations with this study. This study is cross sectional, and it can be generalized to only two cities of Pakistan. Scope of research was limited as the data were collected from two cities of Pakistan (Islamabad and Rawalpindi) using convenience sampling.

Future research

A longitudinal study with probability sampling will help the researchers to comprehensively investigate the relationships among the constructs. Moreover, it would be useful for future research models to add information overload as an explanatory variable and brand image as moderating variable in the research framework. Additionally, moderation of WOM can be investigated in other relationships of conceptual model.

The study encircles the key triggers of customer satisfaction and revisit intention in fast food restaurants. It also offers a model that defines relationships between three factors of restaurant offer (food quality, restaurant service quality, and physical environment quality), customer satisfaction, word of mouth, and revisit intention at fast food restaurants. The model specially focuses the revisit intention as dependent variable of conceptual model despite behavior intentions. The findings suggest the revisit intention is positively associated with customer satisfaction, food quality, restaurant service quality, and physical environment quality in a fast food restaurant.

However, contrary to the findings of a previous study [ 99 ], WOM do not positively moderate between the relationship of customer satisfaction and revisit intention. The empirical findings confirm the significant impact of food quality, restaurant service quality, physical environment quality, and customer satisfaction which are important antecedents of revisit intention at fast food restaurant through mediation of customer satisfaction. Moreover, findings of the research support the assumptions of SOR theory strengthening our conceptual model which states the external stimuli (FQ, RSQ, PEQ) produced internal organism (CS) which led to the response (RVI). However; assumption of social conformity theory failed to influence the satisfied customer. In other words, customer satisfaction plays dominating role over social influence (i.e. WOM) in making revisit intention. Therefore, WOM was not able to influence the strength of relationship of CS and RVI.

Availability of data and materials

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Abbreviations

Social conformity theory

Stimulus-organism-response

Structural equation modeling with partial least squares

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The authors gratefully acknowledge the conducive research environment support provided by Department of Management Sciences at COMSATS University Islamabad, Wah Campus and Higher Education Commission Pakistan for provision of free access to digital library.

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Rajput, A., Gahfoor, R.Z. Satisfaction and revisit intentions at fast food restaurants. Futur Bus J 6 , 13 (2020). https://doi.org/10.1186/s43093-020-00021-0

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Customer Restaurant Choice: An Empirical Analysis of Restaurant Types and Eating-Out Occasions

Bee-lia chua.

1 Department of Food Service and Management, Faculty of Food Science and Technology, Universiti Putra Malaysia, Serdang 43400, Malaysia; ym.ude.mpu@aileebauhc (B.-L.C.); ym.ude.mpu@mirhahs (S.K.)

Shahrim Karim

Sanghyeop lee.

2 Major in Tourism Management, College of Business Administration, Keimyung University, Daegu 42601, Korea; rk.ca.umk@poeyhgnaseel

3 College of Hospitality and Tourism Management, Sejong University, Seoul 143-747, Korea

This study investigated restaurant customers’ perceived importance of key factors in accordance with dining occasions and restaurant segments. Our investigation into restaurant selection and situational factors present two types of empirical evidence regarding customers’ choice of restaurant. First, menu price was customers’ top priority in restaurant selections for full-service, quick-casual, and quick-service restaurants. Second, restaurant customers rated the importance level of restaurant selection criteria differently according to eating-out occasions. The importance of menu price was greatest for both quick meal/convenience and social occasion, brand reputation was the most important factor for business necessity, and word-of-mouth recommendation was greatest for celebration.

1. Introduction

In today’s competitive restaurant business, an increase in restaurant business competition implies that customers nowadays have more dining choices to choose from than ever before, ranging from fast food to fine dining restaurants [ 1 , 2 ]. As a result, customer expectations of restaurant offerings are ever-increasing, and they are now more demanding in choosing better restaurant choices based on what they can get from their decision [ 3 ]. In view of the growing phenomenon toward eating-out, knowledge of the criteria used by customers in the selection of a restaurant is strategic in understanding food consumption trends [ 4 ]. In fact, as digital technology continues to advance, it is becoming increasingly challenging to please restaurant customers as their eating-out behavior is now more sophistically evolved, and they are cognizant of the customer value [ 5 , 6 , 7 ]. Thus, it is particularly important that restauranteurs stay on top of consumer behavior in the restaurant industry so that they can cater to the needs and wants of customers appropriately. This present study overcame this challenge by addressing the following research questions: (1) What is the relative importance of a restaurant selection factor in relation to other factors? (2) How do key factors in restaurant selection differ across eating-out occasions? (3) How do key factors in restaurant selection differ across restaurant segments?

A restaurant customer’s decision-making process begins when he/she recognizes a need that can be fulfilled by consuming the products/services offered by a restaurant [ 8 ]. The need for restaurant consumption may be driven by various factors, such as having quick meals, celebrating special occasions, entertaining business clients, etc. Customers will search for relevant information about restaurants, compare restaurant options, and make the final purchase decision of which restaurant to dine at [ 9 ]. The theory of information integration [ 10 ] posits an individual’s overall attitude toward a product/service is mutually shaped by the perceived actual performance and the perceived importance of the product/service. In hospitality business, it is essential that service firms understand how important each product/service’s key factor is in customers’ decision making. While service firms can operationally control a product/service’s performance, customers, the direct receivers of a product or service, primarily determine the importance of a product/service’s decisive factors [ 11 , 12 , 13 ]. Hence, several marketing scholars have investigated the importance of key factors in customer decision making across hospitality and tourism backgrounds, such as hotel [ 14 ], cruise [ 15 ], and destination [ 16 ].

A review of past research on restaurant management reveals that the factors driving customers’ choice of restaurant are price, food, variety, reputation, promotion, location, and information sources [ 8 , 17 , 18 , 19 , 20 , 21 ]. In this regard, the key factors in restaurant selection have relevance only if they are being perceived as significantly important from the viewpoints of customers. Restaurateurs often make costly expenditures on marketing activities to attract customers by utilizing various marketing techniques from menu development to sales promotion. However, any change in marketing activities meant to expand the customer base and increase sales requires concrete and sound evidence to evaluate whether such efforts payoff. Despite substantial interest in consumer behavior and restaurant marketing research among hospitality scholars [ 22 , 23 , 24 , 25 ], evidence of customers’ perceived importance of restaurant selection factors and how they vary across situational factors (i.e., dining occasions and restaurant segments) are surprisingly scant. Restauranteurs are left with little evidence on how restaurant choice factors influence customers’ eating-out decision making. When making an eating-out decision, customers often view a restaurant in terms of a set of characteristics that make it desirable, assigning an importance score to each factor [ 26 ]. Restauranteurs thus need to be mindful of whether a decisive factor is perceived by customers as generally important, or important depending on the context and situation, or if the factor is perceived to be trivial no matter what the context and situation. The effectiveness of restaurant marketing strategy can possibly be strengthened by discerning customer perception of important factors when making an eating-out decision. Of special relevance to this study, we theorized that the factors driving customers’ choice of restaurant vary with the occasion of eating-out as well as with the type of restaurant. Restaurant reputation, for example, may appeal to those who are planning for special occasions, such as a birthday or a wedding anniversary, rather than for those who want to eat-out simply to satisfy hunger. On the other hand, location may be perceived to be more important for quick-service restaurants than full-service restaurants. More accurate evidence, however, is needed.

Understanding how key factors driving customers’ choice of restaurant differ is critical to the continued advancement of customer decision-making knowledge and effective restaurant marketing strategies. First, while numerous studies in hospitality literature have explored the factors and attributes affecting restaurant customers’ decision to choose a restaurant, they have particularly focused on a restaurant segment, omitting the moderating variables when examining the attributes. Furthermore, previous studies have reported that there is a gap in the hospitality literature with respect to the understanding of drivers in customers’ eating-out decision making, and this situation has called for further investigation into the topic [ 3 , 27 ]. The present study attempted to bridge the literature gap by incorporating dining occasions and restaurant segments to better explain the underlying reason behind customers’ decision-making in the restaurant industry, and hence complement past research findings. We provided a picture regarding restaurant customers’ perceived importance of key factors in accordance with dining occasions and restaurant segments, which is the theoretical contribution of this study. Therefore, we expect that this present study would extend the customer decision-making literature. Second, from a practical viewpoint, an investigation of key factors driving customers’ restaurant choice in eating-out decision making not only can help restaurateurs understand restaurant customer perception of key factors when selecting a restaurant, but also form appropriate marketing strategies to attract existing and potential customers and outperform competitors.

This study aimed to conduct an empirical research associated with critical factors for customers’ restaurant choice in the current restaurant industry using a descriptive analysis. The specific research objectives are as follows:

• The first objective was to rank the factors that are important for the selection of restaurants (i.e., (a) word-of-mouth recommendations from people I know, (b) online reviews from customers, (c) brand reputation, (d) brand popularity, (e) personal or past experience with the restaurant, (f) variety of menu items, (g) menu price, (h) sales promotion, and (i) location).
• The second objective was to uncover the order of importance among the factors for customers to consider when choosing a restaurant by eating-out occasions ((a) quick meal/convenience, (b) social occasion, (c) business necessity, and (d) celebration).
• The third objective was to identify the relative importance among the restaurant selection factors by restaurant types ((a) full-service restaurants, (b) quick-casual/convenience restaurants, and (c) quick-service restaurants).

2. Literature Review

2.1. critical restaurant selection factors.

Attribute importance is the significance of an attribute for a product/service [ 28 , 29 ]. Customers typically evaluate product/service attributes that are perceived to be important in the purchase decision by assigning weight to each attribute in the product/service evaluation [ 30 ]. This relative importance of the attributes is decisive criteria often used by customers in comparing the product/service options, thus leading to purchase behavior [ 11 , 31 ]. In a similar vein, the importance of restaurant selection factors plays a crucial role in affecting customers’ restaurant choice. Based on the existing empirical studies, this study derived nine restaurant selection factors that are likely to affect customers’ decision in choosing a restaurant: word-of-mouth, online customer review, brand reputation, brand popularity, personal (past) experience, menu variety, menu price, sales promotion, and location. It is important to note that we did not include the core elements of restaurant operations: food quality (e.g., taste), service quality, and restaurant physical environment as they have been consistently and intuitively demonstrated to be highly important for restaurant survival [ 32 ]. The nine restaurant selection factors in our study, on the other hand, represent the value-added elements that can positively contribute restaurant business growth. The following sub-sections describe the determinants of customers’ restaurant choice.

2.1.1. Word-of-Mouth Recommendations from People I Know

In the marketing literature, word-of-mouth refers to person-to-person communication about a product, a service, or a brand between a non-commercial communicator and a message receiver [ 28 , 33 ]. Word-of-mouth communication has been well-recognized as an influential drive in attracting new consumers and shaping customer behavior [ 33 , 34 ]. It is a communication process that allows people to share information about an offering which could either encourage or discourage potential customers to make a purchase. In fact, personal sources of information, including recommendations from family and friends, are perceived to be more reliable than commercial advertising media, and thus are more likely to induce customer’s positive/negative attitude towards a brand [ 35 , 36 ]. Sundaram, Mitra, and Webster [ 37 ] identified in their study that people involved in positive word-of-mouth for altruistic, product involvement, and self-enhancement reasons and in negative word-of-mouth for altruistic, anxiety reduction, vengeance, and advice-seeking reasons. In the service industries, such as restaurants and hotels, because consumers lack objective means of evaluating services, they typically depend upon subjective evaluations from family, friends, or acquaintances [ 35 ]. Because consumers may not know a restaurant (e.g., the food quality, service, environment, price) before actual consumption, they may seek referrals from an experienced source. For example, when seeking a nice restaurant for a celebration occasion, consumers will often ask friends for recommendations. Consistent with Stokes and Lomax [ 38 ], this present study viewed word-of-mouth as an informal and interpersonal communication of a restaurant between a customer and his/her acquaintance(s), of which such communication is independent of commercial influence.

2.1.2. Online Review from Customers

The ever-increasing growth of Internet applications in hospitality has contributed to a great number of consumer-generated online reviews on different interactive forums. The importance of online reviews has been widely recognized in the hospitality marketing literature [ 39 ]. The customer decision-making process is strongly affected by online customer reviews posted on online review websites [ 40 ]. Put simply, online customer review websites are Internet channels that connect customers with many other customers. Online consumer reviews serve two functions [ 41 ]. First, it delivers information about a product/service. Second, it serves as a recommendation. As communication technology evolves, the role and significance of online reviews have been further heightened as people can make their opinion about and give feedback on a product/service easily available to other consumers [ 42 ]. Online review is particularly relevant for service-oriented products, such as hospitality products. Given the absence of tangibles, people often look to the tangible clues of the service to assist them in making a decision [ 35 ]. Online reviews primarily derive from many users who discuss and give insight into specific products/services to others [ 43 ]. Online reviews made by other customers about product and service performance appear to provide a clue as to whether the target brand can be trusted [ 44 ]. It also has been found to reduce consumers’ perceived risk and uncertainty prior to actual consumption [ 45 ]. Undeniably, consumers are increasingly relying on online search and review engines when making purchase decisions [ 46 ]. These online reviews are likely to encourage or detract potential customers from using a brand [ 40 ]. While some studies demonstrated that online reviews could reduce cognitive loads of consumers and thus are likely to result in increased sales [ 47 ], some studies reported that online reviews are perceived as having lower trustworthiness than traditional word-of-mouth due to the absence of source cues on the Internet [ 48 ]. Examining the relative importance of online reviews in restaurant customers’ decision-making would be useful for restauranteurs to better understand the significance of online reviews on their business.

2.1.3. Brand Reputation of Restaurant

Brand reputation reflects a mixture of reliability, admiration, benevolence, respect, and confidence of a brand [ 49 ]. It is a signal for the underlying quality of a company’s product or service offerings to customers [ 50 ]. A well-known reputation is psychologically easier for customers to choose a brand over another [ 51 ]. A reputable brand conveys a psychological assurance of the brand quality, thus creating customer trust [ 52 ]. Consumers typically have more trust in a brand if the brand has a favorable reputation as a result of consistently excellent performance [ 53 ]. Another stream of logic that lends support to the role of brand reputation is its influence on customers’ confidence in assessing a brand quality [ 54 ]. Stated differently, customers’ level of uncertainty can be reduced by choosing a reputable brand. In addition, brand reputation serves as a precursor of customer loyalty [ 55 , 56 ]. The influence of brand reputation on customer loyalty is in accordance with signal theory where consumers tend to associate themselves with brands of high reputation as part of self-enhancement [ 57 ]. In tandem with the positive correlation between brand reputation and brand quality, a restaurant’s reputation could be a critical consideration for customers when choosing a restaurant [ 58 ]. Recognizing the fact that consumers are likely to rely on reputation to infer restaurant quality, restaurant operators tend to devote efforts and utilize resources to develop a brand reputation [ 59 ]. Drawing upon this discussion, we suggest that brand reputation can add value to a restaurant’s brand equity [ 60 ], which is likely to influence customers’ decision-making.

2.1.4. Brand Popularity

In general, brand popularity measures the extent to which a brand is broadly consumed by customers. This decisional tool has an information processing advantage by which a consumer can lessen his/her cognitive efforts in making purchase decision by selecting what most customers choose [ 54 ]. In marketing, brand popularity has been utilized as an advertising cue in order to stimulate consumer behavior positively [ 61 ]. The influence of popularity cues on behavior can be explained by social norm theory which attempts to understand social influences on an individual’s behavioral change [ 62 ]. How most people behave in a situation motivates an individual’s behavioral change by inducing a consumer to choose a particular brand that most consumers choose [ 54 ]. This supports the view that to determine what is right is to seek the approval of others [ 63 ] and justifies why consumers consciously look to other consumers when making a purchase decision [ 64 ]. In marketing research, it has been established that consumers being exposed to an advertisement using a popularity cue are more likely to have higher perceived quality, lower perceived risk [ 65 ], and higher intention to purchase the brand [ 61 ] compared to those being exposed to an advertisement without a popularity cue. Based on the theoretical and empirical foundations, this present study measures the extent to which brand popularity influences customers’ choice of restaurant.

2.1.5. Personal or Past Experience with a Restaurant

Past experience has been regarded as a key factor in customers’ post-consumption evaluations [ 66 , 67 ]. It is an important variable in understanding how consumer behavior is formed. The choice of brand does not affect repeat customers in the same way as first-time customers as there is an influence of previous experience in customers’ subsequent response to the purchase [ 68 ]. Common sense suggests that there is a high tendency of repeat patronage for repeat customers because they have visited the restaurant before and know what to expect on the next visit [ 69 ]. Furthermore, these two segments vary in their motives to consume products or services [ 70 ]. First-time customers may visit the restaurant for a new experience; repeat customers, on the other hand, revisit the restaurant to enjoy meals at a familiar place. Given this basis, we posit that personal (past) experience with the restaurant can be one of the most powerful situational factors that affect customers’ choice of restaurant.

2.1.6. Variety of Menu Items

Restaurant consumers’ variety seeking behavior refers to the tendency to seek variety in their dining experiences [ 71 ]. The need for variety is based on individual’s prior purchase experiences which affect his/her choice in next purchase decision [ 72 ]. According to the theory of optimal stimulation level, consumers’ variety seeking behavior is triggered to reduce boredom from repeat purchases as well as to increase stimulation to the desired level [ 73 ]. Past studies suggested that the level of satiation or boredom varies depending on product/service attributes [ 74 , 75 ]. Consumers are likely to satiate on a product/service attribute if they relate the attribute to the primary feature being consumed [ 76 ]. For example, if cake is thought of as a food per se, then consumers tend to satiate on specific attributes (e.g., flavor, color, shape) and seek variety among the cakes. The attribute satiation model, proposed by McAlister [ 75 ], explains consumer choice behavior. It predicts choice behavior at a point in time; as product items decrease and are refilled, consumer’s product preference ranking, however, will likely change. To put it simply, boredom with certain product/service attributes (e.g., taste, color) may lead to variety seeking. Customers cognitively evaluate what they experience when eating-out at a restaurant [ 77 ]. Higher perceived variety leads to greater consumption [ 78 ]. In restaurant consumption, consumers’ need for variety can be satisfied in the offering of a variety of menu items. When choosing restaurants, consumers may choose one that offers a variety of menu options (although all the menu options are not eventually purchased). In these respects, we suggested that a variety of menu items is likely to be a crucial factor for those seeking variety in their dining experiences.

2.1.7. Menu Price

Price is a crucial marketing element in predicting consumer behavior in the restaurant industry [ 79 ]. It has been established as one of the highest-ranked factors for restaurant selections [ 80 ]. Consumers usually remember an objective or actual price to a certain extent that is meaningful to them, also known as perceived price [ 81 ]. Perceived price refers to what is given up, including monetary and non-monetary costs (e.g., money, time, and/or effort) to obtain a product or service [ 81 ]. The effect of price on consumer decision-making can be explained by the difference between reference price and actual price in product/service selection [ 82 ]. Reference price is compared against the actual price of a product/service in deciding whether or not to choose the product/service. An internal reference price (i.e., generated from past purchase experience) is a more important variable than an external reference price (i.e., generated from advertisement) in affecting consumers’ purchase behavior for regularly purchased product/service categories, such as meals in restaurants [ 83 ]. In restaurant settings, perceived price is commonly operationalized as meal price for which a customer transacts during his/her dining at a restaurant [ 84 ]. It has been established that consumers use price to evaluate the service quality as it partially acts as a clue for the quality [ 85 ]. Consequently, we measure the extent to which menu price influences customers’ choice of restaurant.

2.1.8. Sales Promotion

Sales promotion creates a monetary incentive to purchase by reducing price for a certain quantity or increasing quantity for the same price [ 85 ]. It is a strategy that marketers offer to customers to satisfy their financial needs [ 86 ]. Marketers often employ sales promotion to encourage repeat purchase, induce product trials, or promote brand switching behavior [ 87 ]. Sales promotion provides customers with immediate financial incentives [ 88 ], but it may put a brand at risk by moving customers’ attention away from quality to a temporary financial incentive [ 89 ]. In fact, sales promotion appeals to price sensitive consumers who are willing to sacrifice quality for price or see all products in a certain product category as being equal [ 90 ]. Given that sales promotion is a common promotional strategy for attracting customers and generating revenue immediately in the foodservice industry [ 91 ], such as in restaurants, it is important to measure how it is likely to affect customers’ selection of restaurant.

2.1.9. Location

Location has been well-identified as a strategic success factor for a restaurant business to stay competitive in the industry [ 92 , 93 ]. A strategic restaurant location can attract more customers to the restaurant, provide convenience to customers, and has a positive effect on customer loyalty [ 94 ]. Restaurants use location strategy to cater to target market/s and enhance the restaurant visibility [ 95 ]. For consumers, restaurant selection is dependent not only on location but also restaurant characteristics such as type of food served, facilities, size, etc. [ 69 ]. Nevertheless, given that location determines customer access to particular products or services, it remains fundamental to the decision-making of customers and is paramount to the success of a restaurant operation [ 96 , 97 ]. Consequently, this study determines the degree to which location shapes the restaurant customer decision-making process.

2.2. Eating-out Occasions (Quick Meal/Convenience, Social Occasion, Business Necessity, and Celebration) and Customer Behaviors

Customers seek dining consumption experiences for different reasons [ 25 ]. As dining consumption occasions drive customer behavior, it is reasonable to assume that customers’ choice of restaurant is influenced by dining-out occasions. Past research has indicated that dining occasions influence customer choice in the restaurant selection process. One example of this can be found in a study by Kivela [ 98 ] which examined dining occasions (i.e., celebration, business, social, and convenience/quick meal) in understanding customers’ restaurant choice. The findings revealed that location was most related to convenience/quick meal occasion; food quality was perceived to be important for celebration and business occasions; and cleanliness seemed to be one of the important factors in customer choice of restaurant. In a similar vein, Ponnam and Balaji [ 25 ] investigated visitation motives (in place of dining occasions) and restaurant attributes in casual dining restaurants. Customers were found to have different motives (i.e., dine out, celebration, hang out, take-away, and date) for patronizing a casual dining restaurant. More specifically, dine out and take-away motives were found to be highly related to gourmet taste, celebration motive was strongly associated with hospitality service, hang-out motive was related to staff responsiveness, and date motive was highly correlated with ambiance and staff responsiveness. Overall, restaurant customers have specific reasons for patronizing specific types of restaurants.

2.3. Restaurant Types (Full-Service, Quick-Casual, and Quick-Service) and Customer Behaviors

Every restaurant provides three basic attributes (i.e., food, service, and physical environment) to customers. Each type of restaurant has its distinct attributes to differentiate the restaurant’s characteristics from the other restaurant types and to appeal to its target market [ 3 , 77 ]. Customers expect a certain level of quality according to the attributes provided by restaurants [ 99 ]. In the present study, restaurant services are categorized into three types: full-service, quick-casual, and quick-service [ 100 ]. A quick-service restaurant accentuates convenience and efficiency, such as low food price, quick service, convenient location, long hours of operation, and drive-through service [ 101 ]. Food is prepared in a standardized process that can be distributed immediately for ordering and consumption [ 100 ]. Customers visiting fast food restaurants are predominantly concerned about convenience when eating-out [ 3 ]. Quick-casual dining restaurant, a limited-service dining style, serves moderately-priced food in a casual dining atmosphere [ 100 ]. It is less expensive than a full-service restaurant but serves more high-quality food than a quick-service restaurant. Food is made-to-order and innovative food may be served to cater for sophisticated tastes. Quick-casual restaurants attract customers by serving good quality food at a reasonable price in a relaxed atmosphere [ 102 ]. A full-service restaurant provides meal courses and professional services by well-trained staff in an upscale or midscale dining atmosphere [ 98 ]. Full-service restaurants appeal to customers who consider emotional value to be an important factor when dining-out [ 3 ].

3. Methodology

3.1. measures.

A self-administered questionnaire was designed to measure the key factors importance, dining occasions, restaurant segments, and demographics. The first section of the questionnaire measured respondent’s eating-out information: type of restaurant and eating-out occasion. The second section comprised of key factors in restaurant selection: word-of-mouth recommendations from people I know, online reviews from customers (e.g., through Facebook, Twitter, blogs, TripAdvisor, etc.), brand reputation, brand popularity, personal (or past) experience with the restaurant, variety of menu items, price, sales promotion, and location. The respondent was asked to rank the factors from 1 (the most important) to 9 (the least important) when he/she chooses a restaurant. The factors were identified from an extensive review of past studies pertaining to restaurant management [ 4 , 5 , 8 , 25 , 69 , 103 , 104 ]. Then, we refined the factors through formal discussions with three academic professionals in restaurant management. Based on the discussions, “word-of-mouth recommendations”, “online reviews”, and “sales promotion” were further detailed. “Word-of-mouth recommendations” was specified as “word-of-mouth recommendations from people I know”; “online reviews” was rephrased as “online reviews from customers (e.g., through Facebook, Twitter, blogs, TripAdvisor, etc.)”; and “sales promotion” was specified with examples—“sales promotion (e.g., discounts, happy hours)”. The third section contained questions about basic demographics, such as gender, age, occupation, personal monthly net income, and level of education attainment.

3.2. Sample and Data Collection

We employed a descriptive survey research design to achieve the research purpose. A pencil-and-paper survey was conducted in 2017. Individuals were approached at six shopping centers in Klang Valley, Malaysia. Klang Valley is home to a number of popular and major shopping centers located in the urban cities, which include Kuala Lumpur and Petaling Jaya [ 105 ]. Every one of the shopping centers has a collection of stores, including local and international restaurant brands. Our trained research enumerators selected individuals through a convenience sampling method. Potential participants were politely approached in public seating areas at the shopping centers. To ensure that the individuals were qualified to participate in this survey, three screening questions were asked:

• Do you regularly eat-out at restaurants on weekends?
• What is your age?
• Are you currently employed/working?

The individuals who regularly eat-out on weekends, aged 25 years and older, and were currently working were invited to participate in this anonymous survey. This group of individuals was selected because we believed that this group of respondents was capable of earning a disposable income and making decisions in restaurant selection. It has been reported that employed and educated consumers seem to seek variety in product/service decision-making [ 106 ]. Furthermore, eating-out has become prevalent among urban consumers in Malaysia [ 107 ]. We did not consider weekdays as eating-out on weekdays might not be a volitional behavior given that people are usually occupied with their daily work routine, and thus restricting their decision in choosing a restaurant. Every respondent was presented with a short statement recalling the experience of eating-out. The statement was described as follows: “ Think of your most recent visit to a restaurant in the past three months. It is a different kind of restaurant (that may have a distinctive feature such as menu, restaurant ambiance, or service style) from the ones that you commonly patronize. You made the decision to go to the restaurant ”. Respondents then indicated the type of restaurant and the dining occasion for the restaurant visit. They were also asked to provide rankings of the key factors in the restaurant selection decision. Lastly, respondents were asked to fill out the demographics section in the questionnaire.

The survey questionnaires were distributed to a total of 617 restaurant customers. After eliminating unusable responses among the completed responses, 539 responses were coded for data analysis. More than half of the respondents were females (54.6%). The majority of the respondents were in the age range of 25 to 44 years old (80.9%), had a personal monthly net income of MYR 2000 to MYR 5999 (68.4%), and obtained a tertiary education (50.7%). This reflects Malaysia’s population which was relatively young and educated [ 107 ]. With regards to occupation, about 27.3% held executive/managerial/administrative position and about 22.4% were self-employed.

4.1. General Order of Importance for Restaurant Choice

The order of criticality among the factors that are vital for patrons’ restaurant selection (i.e., word-of-mouth recommendations from people I know, online reviews from customers, reputation, popularity, personal (or past) experience with the restaurant, variety of menu items, price, sales promotion, and location) was examined. Using IBM SPSS Statistics 20 (IBM, New York, NY, USA), a descriptive analysis was conducted based on the rank that the survey participants indicated. Table 1 and Figure 1 present the results of the analysis. As noted, the value “1” indicates the most important criteria to consider when choosing a restaurant, and the value “9” indicates the least important criteria. Thus, the results show that “price” which is closer to “1” as compared to other variables is ranked the most critical thing that patrons consider when choosing a restaurant.

Overall ranking. The most/least important factor when choosing a restaurant. The value “1” indicates the most important criteria to consider when choosing a restaurant, and the value “9” indicates the least important criteria. Thus, the figure shows that “price” which is closer to “1” as compared to other variables is ranked the most important factor that patrons consider when selecting a restaurant.

Overall ranking of restaurant choice factors.

1: “The most important criteria to consider when choosing a restaurant”; 9: “The least important criteria to consider when choosing a restaurant”. Std. Deviation refers to Standard Deviation.

This finding implies that when making a decision to select a restaurant, patrons consider price as the most important factor, word-of-mouth from people they know as the second most important factor, personal/past experience as the third most important factor, variety of menu items as the fourth important factor, popularity as the fifth important factor, reputation as the sixth important factor, location as the seventh important factor, sales promotion as the eighth important factor, and online reviews from customers as the least important factor in sequence. In addition, about 25% of the participants ranked price as “1”. About 17.3%, 14.5%, 8.3%, 9.3%, 9.1%, 8.9%, 3.3%, and 4.3% ranked word-of-mouth, personal experience, variety of menu items, popularity, reputation, location, sales promotion, and online reviews from customers as “1”, respectively. Meanwhile, about 6.3% of the participants ranked price as “9”. In addition, about 8.3%, 8.5%, 9.5%, 6.7%, 6.5%, 13.0%, 17.6%, and 23.7% ranked word-of-mouth, personal experience, variety of menu items, popularity, reputation, location, sales promotion, and online reviews from customers as “9”, respectively. Table 2 further displays the significance of the restaurant choice factors ranking. The t -test results demonstrated that in general, price was significantly more important than word-of-mouth, and that location was significantly more important than sales promotion. This result contributed to achieving the first research objective of the present study.

Significance of restaurant choice factors ranking.

1: “The most important criteria to consider when choosing a restaurant”; 9: “The least important criteria to consider when choosing a restaurant”. *** p < 0.001.

4.2. Ranking by Eating-out Occasions

The order of importance among restaurant choice factors by customers’ eating-out occasions (i.e., quick meal/convenience, social occasion, business necessity, and celebration) was examined by using a descriptive analysis. The details are shown in Figure 2 . The top three restaurant choice factors in the occasion of quick meal/convenience were price (mean = 3.508, SD = 2.476), personal/past experience (mean = 4.571, SD = 2.610), and variety of menu items (mean = 4.631, SD = 2.427). In the case of social occasion, price (mean = 3.784, SD = 2.531), popularity (mean = 4.506, SD = 2.420), and word-of-mouth (mean = 4.543, SD = 2.659) were ranked as the three major choice factors. In the occasion of business necessity, unlike the previous two occasions, reputation (mean = 3.483, SD = 2.064) was ranked in the first place, followed by popularity (mean = 3.828, SD = 2.019), and word-of-mouth (mean = 4.103, SD = 2.440). Lastly, in the occasion of celebration, the top three restaurant selection factors were word-of-mouth (mean = 3.927, SD = 2.580), price (mean = 4.240, SD = 2.615), and reputation (mean = 4.500, SD = 2.362).

Ranking by eating-out occasions. 1: “The most important criteria to consider when choosing a restaurant”; 9: “The least important criteria to consider when choosing a restaurant”. Quick meal/convenience ( n = 252), Social occasion ( n = 162), Business necessity ( n = 29), Celebration ( n = 96).

Table 3 discloses the differences in importance of restaurant choice factors across eating-out occasions. The one-way ANOVA findings indicated that while variety of menu items was not statistically significant, the importance of word-of-mouth, online review from customers, reputation, popularity, personal experience, price, sales promotion, and location were statistically significant across eating-out occasions. The non-significant difference in variety of menu items across eating-out occasions suggests that the attribute is equally important for all the occasions. This is consistent with Kivela et al. [ 69 ] where variety of menu was a crucial attribute determining customer evaluation of restaurant experience. A closer examination of the ranking by eating-out occasions further indicated that word-of-mouth was particularly crucial in celebration, followed by business necessity, social occasion, and quick meal/convenience. In addition, online reviews from customers were critical in the order of business necessity, celebration, social occasion, and quick meal/convenience. Reputation was especially important in business necessity, followed by celebration, social occasion, and quick meal/convenience. Popularity was particularly critical in business necessity, followed by social occasion, quick meal/convenience, and celebration. Moreover, personal experience was important in the order of quick meal/convenience, business necessity, social occasion, and celebration. Price was crucial in quick meal/convenience, social occasion, celebration, and business necessity in sequence. Sales promotion was important in the order of celebration, quick meal/convenience, social occasion, and business necessity. Further, location was particularly critical in the occasion of quick meal/convenience, followed by celebration, social, and business necessity. This result contributed to achieving the second research objective of this study.

Differences in restaurant choice factors across eating-out occasions.

* p < 0.05, ** p < 0.01.

4.3. Ranking by Restaurant Types

Ranking by restaurant types (i.e., full-service restaurants, quick-casual/convenience restaurants, and quick-service restaurants) was investigated by using a descriptive analysis. First, the order of criticality among the nine choice factors for full-service restaurants was examined. The results are exhibited in Figure 3 . Our finding indicated that price (mean = 3.866, SD = 2.436) was ranked in first place, followed by word-of-mouth (mean = 4.496, SD = 2.632), personal experience (mean = 4.594, SD = 2.654), variety of menu items (mean = 4.612, SD = 2.415), popularity (mean = 4.775, SD = 2.415), reputation (mean = 4.891, SD = 2.384), location (mean = 5.232, SD = 2.576), online reviews from customers (mean = 6.022, SD = 2.401), and sales promotion (mean = 6.467, SD = 2.325). This finding implies that when choosing a full-service restaurant for eating out, customers consider the above order in sequence.

Ranking by restaurant types. 1: “The most important criteria to consider when choosing a restaurant”; 7: “The least important criteria to consider when choosing a restaurant”. Full-service restaurants ( n = 276), Quick-casual restaurants ( n = 132), Quick-service restaurants ( n = 125).

Second, the order of importance among the choice factors for quick-casual restaurants was examined. While price (mean = 3.886, SD = 2.811) was found as the most critical factor, the order of the rest of the factors in quick-casual restaurants was little different from that of the full-service restaurants. Our results revealed that personal experience (mean = 4.530, SD = 2.260), reputation (mean = 4.780, SD = 2.590), variety of menu items (mean = 4.796, SD = 2.291), popularity (mean = 4.833, SD = 2.282), word-of-mouth (mean = 4.886, SD = 2.754), location (mean = 5.091, SD = 2.593), sales promotion (mean = 5.977, SD = 2.352), and online reviews from customers (mean = 6.242, SD = 2.542) were the second, third, fourth, fifth, sixth, seventh, eighth, and ninth important factors in sequence when customers select a quick-casual restaurant.

Lastly, we examined the rank indicated by customers when making a decision for selecting a quick-service restaurant. In the case of quick-service restaurant choice, participants ranked price (mean = 3.576, SD = 2.547) as the most crucial thing that they consider among the nine factors driving restaurant selection, followed by word-of-mouth (mean = 4.440, SD = 2.775), popularity (mean = 4.840, SD = 2.329), reputation (mean = 4.848, SD = 2.279), location (mean = 5.192, SD = 2.678), variety of menu items (mean = 5.264, SD = 2.609), personal experience (mean = 5.352, SD = 2.515), sales promotion (mean = 5.384, SD = 2.327), and online reviews from customers (mean = 6.152, SD = 2.393). The results pertinent to the ranking among important restaurant choice factors by restaurant types contributed to achieving the third research objective of the present study.

Table 4 further illustrates the differences in importance of restaurant choice factors across restaurant types. The one-way ANOVA findings revealed that the importance of personal experience, variety of menu items, and sales promotion were statistically different across restaurant types. Personal experience was important in the order of quick-casual, full-service, and quick-service. Variety of menu items was crucial in full-service, quick-casual, and quick-service in sequence. Sales promotion was important in the order of quick-service, quick-casual, and full-service. The insignificant difference in price implies that price is the most critical factor for all the three types of restaurant, which supports the aforementioned discussion.

Differences in restaurant choice factors across restaurant types.

* p < 0.05, *** p < 0.001.

5. Discussion

Faced with the complex phenomenon of eating-out, our study extends the body of knowledge on the relative importance of restaurant selection criteria. Our investigation into customers’ perceived importance of restaurant selection factors and how they vary across situational factors, namely dining occasions and restaurant segments, presents empirical evidence regarding customers’ choice of restaurant. Our study provides three insights. First, menu price was perceived as the most important criterion in all nine criteria when consumers choose a restaurant to eat-out. This is not surprising as since the Malaysian government imposes the implementation of a 6% Goods and Service Tax (GST) in 2015, consumers are becoming more price-sensitive and cautious about spending on eating-out [ 108 ]. Another plausible reason is that, consistent with past research advocating the salient role of price as a clue of consumers’ expectation and evaluation of product or service performance [ 109 , 110 ], our findings suggest that menu price has the overall greatest importance for restaurant customers. The role of price in influencing restaurant customers’ decision-making could be attributed by the common belief that price has been used as a reference in making quality inference [ 84 ].

Second, our study ranked the level of importance among the factors for customers to consider when choosing a restaurant by eating-out occasions. The importance level of menu price was greatest for both quick meal/convenience and social occasion; brand reputation was the most important for business necessity; and word-of-mouth recommendation (from the people I know) was greatest for celebration. On the other hand, online reviews carried the least importance for quick meal/convenience, and sales promotion was ranked being the least important for social occasion, business necessity, and celebration. Our findings provide empirical evidence that eating-out occasion is the key determinant of restaurant selection criteria. This supports the assertion that restaurant customers have distinctive reasons when patronizing restaurants [ 25 , 27 , 98 ]. The findings of this study allow restaurant selection criteria to be segmented in relation to their primary use occasion.

Third, our study investigated the relative importance among the restaurant selection factors by restaurant types. Menu price was perceived as being the most important criterion and sales promotion was the least important criterion for full-service restaurants. Menu price was also ranked highest on quick-casual restaurant selection criteria and online review was perceived to be the least important. The nature of our sample might shed light on the prevalence of quick-casual units in Malaysia. The majority of the respondents in this study were young working adults and middle-income consumers. This group of consumers prefer an informal and comfortable environment as well as reasonably-priced menu items [ 108 ]. Similarly, menu price was ranked highest and online review was ranked lowest on quick-service restaurant selection criteria. The substantial growth of the restaurant market in Malaysia and the homogeneity of offerings across restaurants within one segment might shed light on the importance of menu price in customers’ choice of restaurant. Customers have too many choices of restaurant when it comes to eating-out. Our study suggests that when there is a huge number of restaurant options with similar product or service offerings, there is a greater tendency for customers to rely on the prices when making decision. Thus, it is not surprising that customers are relatively mindful of prices when making eating-out decisions. This is consistent with Lewis’s [ 111 ] argument that price is a key factor in differentiating within a set of product class.

6. Implications

The restaurant industry is highly competitive. The understanding about restaurant customer behavior is vital for restaurants to achieve a sustainable restaurant business growth. Several managerial implications emerge from our study. First, restauranteurs should be alert to the comparative importance of factors in customer decision making. Such importance levels may trigger restauranteurs to consider marketing strategies for their restaurant that they may not have otherwise considered. For example, considering our finding that menu price is customers’ top priority in restaurant selections for full-service, quick-casual, and quick-service restaurants, when food is priced appropriately, it can positively influence customers’ decision. Customers encode menu price as a synopsis of dining experience. The price perception is influential in assisting customers make a choice, suggesting the need to adopt effective pricing strategies. Restauranteurs should utilize the principle of integrated marketing communication strategies and grasp every opportunity to manage customer perception of price. Rather than leaving customer perception of price to chance, restauranteurs can take a proactive role in setting up value-based pricing strategies. For example, quick-service restauranteurs should consider implementing the practice of several international fast-food chains who regularly remind customers of their meal savings. When creating a pricing strategy, quick-casual restauranteurs should keep in mind that their customers value good quality food at a reasonable price in a comfortable dining atmosphere. The pricing strategies of full-service restauranteurs should appeal to customers who appreciate emotions in dining experiences as they typically seek a dining experience beyond eating, therefore strengthening competitive price perception. Quick-service and full-service restauranteurs must get customers to recognize the eating-out benefits they receive for the price they pay. In other words, the advertising messages should highlight the benefits of eating in the restaurants relative to the prices.

Second, word-of-mouth recommendation (from the people I know), which was ranked second in the important factors list, can strengthen customers’ decision to choose a restaurant. In the restaurant industry, word-of-mouth recommendation is influential, and most importantly, it costs a restaurant nothing to promote its products/services to potential customers. Thus, we suggest that restaurateurs consistently provide high-quality products and services to trigger positive word-of-mouth. Achieving customer satisfaction stimulates positive communications in a customer’s direct contacts and immediate surroundings [ 112 ]. Third, personal experience, which was ranked third in the important factors list, can affect restaurant customer decision-making. Most Malaysian consumers are well-informed and sophisticated, and they appreciate quality in dining experience [ 108 ]. If a restaurant receives favorable evaluations of their dining experience in the restaurant from existing customers, the positive evaluations can have a considerable impact on customer satisfaction and, consequently, on their behavioral intentions, such as revisit intentions [ 113 ].

Forth, a closer look into the relative important of restaurant selection criteria across eating-out occasions shows that restaurant customers rated the importance level of restaurant selection criteria differently according to eating-out occasions. As the restaurant selection criteria are influenced by the eating-out occasions, we suggest that decisions relating to personalizing the promotional strategies should be undertaken. Because customers attach different levels of importance to restaurant selection criteria, it is essential to tailor distinctive efforts for optimal effects on restaurant customer behavior. Promotional tactics should reflect the consistency between purpose of eating-out and restaurant selection factors. Menu prices are critically important when customers patronize a restaurant for quick meal/convenience and social occasion. In Malaysia, with growing urbanization and changing lifestyles, an increasingly great number of consumers seek convenience through eating-out. Financial incentives (such as value meals and set meals) and psychological pricing (such as 9-ending prices) are thus recommended for customers visiting a restaurant for quick meal/convenience or social occasions. Restaurant reputation is vital when customers choose a restaurant for business necessity. Customers may expect to have good food and drink in a comfortable physical environment to entertain their business clients. Restauranteurs should maintain the standards of these attributes to meet the needs and wants of their customers. Word-of-mouth is essential when customers select a restaurant for celebration occasion. Considering that customers visiting a restaurant to celebrate a special occasion (e.g., birthday, wedding anniversary), it is important for customers to choose the right restaurant where they can happily cherish the special moment. Accordingly, restauranteurs should increase their competitive advantage by creating customer engagement opportunities, such as sharing dining experiences on social media networks and facilitating customer-to-customer interactions.

7. Limitations and Recommendations for Future Research

There are several limitations to this study that should be addressed for future research. First, we conducted data collection in only one area in Malaysia (i.e., Klang Valley), thus limiting the generalizability of the conclusions. Other metropolitan cities across countries may be studied to obtain comparative results. Second, how respondents evaluate the difference in important ranking was not examined. In other words, the variables, such as values associated with eating-out, that may have a significant influence on important factor ratings should be further examined. More theoretical and practical implications regarding customers’ perceived importance of restaurant selection factors could be drawn when the underlying variables explaining the outcomes are investigated. Third, this study identified the nine factors based on the existing empirical studies on consumer behavior in the restaurant industry. The importance of certain restaurant choice factors, which included word-of-mouth, online reviews, reputation, popularity, price, and location were not statistically different between full-service, quick-casual, and quick-service restaurants ( Table 4 ). This suggests that these factors are equally important for all the three types of restaurant. Given the fact that consumer decision-making in restaurant selection is dynamic and may be driven by emerging factors or reasons, future research is suggested to delve into this topic by utilizing qualitative methods. Fourth, this study was descriptive in nature, thus failing to include delicate statistical techniques and to suggest a causal model of the antecedents and consequence of customers’ decision. The contribution of this study could be strengthened through more robust quantitative research approach efforts. Fifth, the subgroups (i.e., quick meal, social occasion, business, celebration) have different number of sample size. Future research should balance the sample size for these subgroups. In addition, future research should increase the sample size to effectively compare the constituents of eating-out occasions.

8. Conclusions

Customer expectations of restaurant offerings are ever-increasing, and they are now more demanding in choosing better restaurant choices based on what they can get from their decision. An investigation of key factors driving customers’ restaurant choice in eating-out decision making not only can help restaurateurs understand restaurant customer perception of key factors when selecting a restaurant, but also form appropriate marketing strategies to attract existing and potential customers and outperform competitors. Faced with the complex phenomenon of eating-out, our study extends the body of knowledge on the relative importance of restaurant selection criteria. Our investigation into customers’ perceived importance of restaurant selection factors and how they vary across situational factors, namely dining occasions and restaurant segments, presents empirical evidence regarding customers’ choice of restaurant. Our study has three important findings. First, menu price is perceived as the most important criterion in all nine criteria (i.e., word-of-mouth, online customer review, brand reputation, brand popularity, personal (past) experience, menu variety, menu price, sales promotion, and location) when consumers choose a restaurant to eat-out. Second, eating-out occasion is the key determinant of restaurant selection criteria. More specifically, the importance level of menu price is greatest for both quick meal/convenience and social occasion; brand reputation is the most important for business necessity; and word-of-mouth recommendation (from the people I know) is greatest for celebration. Third, menu price was perceived as being the most important criterion for full-service restaurants, quick-casual restaurants, and quick-service restaurants, respectively. This suggests that when there are a huge number of restaurant options with similar product or service offerings within a restaurant segment, there is a greater tendency for customers to rely on the prices when making decision. Overall, the findings of this study add to the restaurant management literature that customers’ restaurant choice is markedly affected by situational factors [ 69 , 98 ]. It is concluded that customers’ perceived importance of restaurant selection factors are important considerations in the occasion for which a restaurant is patronized and in the choice of restaurant type. The findings are valuable to restauranteurs in developing occasion-based and restaurant type-based segmentations based on restaurant selection factor priorities.

Author Contributions

Conceptualization, B.-L.C. and H.H.; methodology, B.-L.C. and H.H.; writing—original draft preparation, B.-L.C.; writing—review and editing, H.H. and S.L.; visualization, H.H. and S.L.; supervision, H.H.; project administration, B.-L.C. and S.K.; funding acquisition, B.-L.C. and S.K. All authors have read and agreed to the published version of the manuscript.

This study was supported by GP-IPM research fund, Universiti Putra Malaysia, Malaysia.

Conflicts of Interest

The authors declare no conflict of interest.

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This paper is in the following e-collection/theme issue:

Published on 3.4.2024 in Vol 26 (2024)

Public Discourse, User Reactions, and Conspiracy Theories on the X Platform About HIV Vaccines: Data Mining and Content Analysis

Authors of this article:

Original Paper

• Jueman M Zhang 1 , PhD   ; 
• Yi Wang 2 , PhD   ; 
• Magali Mouton 3   ; 
• Jixuan Zhang 4   ; 
• Molu Shi 5 , PhD  

1 Harrington School of Communication and Media, University of Rhode Island, Kingston, RI, United States

2 Department of Communication, University of Louisville, Louisville, KY, United States

3 School of Rehabilitation Sciences, University of Ottawa, Ottawa, ON, Canada

4 Polk School of Communications, Long Island University, Brooklyn, NY, United States

5 College of Business, University of Louisville, Louisville, KY, United States

Corresponding Author:

Jueman M Zhang, PhD

Harrington School of Communication and Media

University of Rhode Island

10 Ranger Road

Kingston, RI, 02881

United States

Phone: 1 401 874 2110

Email: [email protected]

Background: The initiation of clinical trials for messenger RNA (mRNA) HIV vaccines in early 2022 revived public discussion on HIV vaccines after 3 decades of unsuccessful research. These trials followed the success of mRNA technology in COVID-19 vaccines but unfolded amid intense vaccine debates during the COVID-19 pandemic. It is crucial to gain insights into public discourse and reactions about potential new vaccines, and social media platforms such as X (formerly known as Twitter) provide important channels.

Objective: Drawing from infodemiology and infoveillance research, this study investigated the patterns of public discourse and message-level drivers of user reactions on X regarding HIV vaccines by analyzing posts using machine learning algorithms. We examined how users used different post types to contribute to topics and valence and how these topics and valence influenced like and repost counts. In addition, the study identified salient aspects of HIV vaccines related to COVID-19 and prominent anti–HIV vaccine conspiracy theories through manual coding.

Methods: We collected 36,424 English-language original posts about HIV vaccines on the X platform from January 1, 2022, to December 31, 2022. We used topic modeling and sentiment analysis to uncover latent topics and valence, which were subsequently analyzed across post types in cross-tabulation analyses and integrated into linear regression models to predict user reactions, specifically likes and reposts. Furthermore, we manually coded the 1000 most engaged posts about HIV and COVID-19 to uncover salient aspects of HIV vaccines related to COVID-19 and the 1000 most engaged negative posts to identify prominent anti–HIV vaccine conspiracy theories.

Results: Topic modeling revealed 3 topics: HIV and COVID-19, mRNA HIV vaccine trials, and HIV vaccine and immunity. HIV and COVID-19 underscored the connections between HIV vaccines and COVID-19 vaccines, as evidenced by subtopics about their reciprocal impact on development and various comparisons. The overall valence of the posts was marginally positive. Compared to self-composed posts initiating new conversations, there was a higher proportion of HIV and COVID-19–related and negative posts among quote posts and replies, which contribute to existing conversations. The topic of mRNA HIV vaccine trials, most evident in self-composed posts, increased repost counts. Positive valence increased like and repost counts. Prominent anti–HIV vaccine conspiracy theories often falsely linked HIV vaccines to concurrent COVID-19 and other HIV-related events.

Conclusions: The results highlight COVID-19 as a significant context for public discourse and reactions regarding HIV vaccines from both positive and negative perspectives. The success of mRNA COVID-19 vaccines shed a positive light on HIV vaccines. However, COVID-19 also situated HIV vaccines in a negative context, as observed in some anti–HIV vaccine conspiracy theories misleadingly connecting HIV vaccines with COVID-19. These findings have implications for public health communication strategies concerning HIV vaccines.

Introduction

Vaccination has long been recognized as a crucial preventive measure against diseases and infections, but opposition to vaccines has endured [ 1 ]. HIV vaccination has been regarded as a potential preventive measure to help combat the HIV epidemic in the United States, with research and progress dating back to the mid-1980s but without success thus far [ 2 ]. An estimated 1.2 million people were living with HIV in the United States by the end of 2021, with 36,136 new HIV diagnoses reported in 2021 [ 3 ].

On January 27, 2022, the biotechnology company Moderna announced the initiation of clinical trials for an HIV vaccine using messenger RNA (mRNA) technology [ 4 ]. In March 2022, the National Institutes of Health announced the start of clinical trials for 3 mRNA HIV vaccines [ 5 ]. The mRNA technology had previously been used in the Pfizer-BioNTech and Moderna COVID-19 vaccines, which protected individuals against severe symptoms and fatalities during the pandemic [ 6 ]. Following the successes of mRNA COVID-19 vaccines, which led to the Nobel Prize in Physiology or Medicine being awarded to 2 scientists in October 2023 [ 7 ], researchers have been investigating the potential of mRNA vaccines for various other diseases, including HIV [ 8 , 9 ]. The announcements of clinical trials for mRNA HIV vaccines revived public discussion on the prospect of vaccines to combat HIV [ 9 ] despite >3 decades of unsuccessful research [ 2 ]. Meanwhile, these announcements were made against the backdrop of intense vaccine debates during the COVID-19 pandemic, with misinformation and conspiracy theories fueling vaccine hesitancy [ 10 - 12 ].

The X platform, formerly known as Twitter, has been a significant social media platform and a vital source for text-based public discourse. Posts on X have been studied to understand public discourse about vaccines in general [ 13 - 15 ] and about specific vaccines, such as COVID-19 vaccines in recent years [ 12 , 16 , 17 ]. However, there is a dearth of research about public discourse on HIV vaccines on social media. Given the advancement in mRNA technology in COVID-19 vaccines and heated vaccine debates, it has become especially important to gain insights into public discourse and reactions regarding potential new vaccines.

This study is grounded in the growing field of infodemiology and infoveillance, which investigates the “distribution and determinants of information in an electronic medium,” specifically on the web, by analyzing unstructured text with the aim of informing public health practices or serving surveillance objectives [ 18 ]. In recent infodemiology and infoveillance studies, machine learning algorithms have been increasingly used to examine substantial amounts of social media content, such as posts on X related to COVID-19 vaccines [ 12 , 16 , 17 ] and HIV prevention [ 19 ], to extract insights into public discourse and reactions. These algorithms automatically analyze extensive volumes of posts and capture latent textual information such as topics and sentiments. This study aimed to investigate how users used different post types to contribute original content to topics and valence identified through machine learning algorithms and how these topics and valence affected user reactions on X regarding HIV vaccines. In addition, by manually coding the most engaged posts, similar to an approach used in previous infodemiology and infoveillance research [ 20 ], the study intended to identify salient aspects of HIV vaccines related to COVID-19 as well as prominent anti–HIV vaccine conspiracy theories. Analyzing posts on X about HIV vaccines can shed light on public discourse and information diffusion. These findings have implications for shaping public health communication strategies about HIV vaccines [ 18 ]. Furthermore, the findings may help in understanding the acceptability of the HIV vaccine upon its successful development in comparison with adherence to existing HIV prevention measures. Previous infodemiology and infoveillance research effectively increased the forecast accuracy of COVID-19 vaccine uptake by leveraging insights derived from posts on X [ 21 ].

Literature Review

Public discourse about hiv prevention on x.

Social media platforms have become important channels for HIV communication, enabling the dissemination of and engagement with content encompassing a wide array of issues related to HIV prevention, treatment, coping, and available resources [ 22 , 23 ]. An earlier infodemiology study examined 69,197 posts on the X platform containing the hashtag #HIVPrevention between 2014 and 2019 and categorized these posts into 10 identified topics concerning HIV prevention [ 19 ]. Among them, pre-exposure prophylaxis had the highest representation with 13,895 posts, followed by HIV testing; condoms; harm reduction; gender equity and violence against women; voluntary medical male circumcision; sex work; postexposure prophylaxis; elimination of mother-to-child transmission of HIV; and abstinence, which had the lowest representation with 180 posts. Furthermore, that study suggested a consistency between the volume of posts related to specific HIV prevention measures on X over time and the temporal trends in the uptake of those measures [ 19 ]. It is noteworthy that the topic of HIV vaccines was absent, which suggested minimal public discourse on the topic during these years. This may be associated with the extensive history of unsuccessful research in this area [ 2 ].

Despite the availability of current HIV prevention measures, efforts have been made to develop HIV vaccines, which are considered necessary to bridge the gap between the challenges in adhering to existing HIV prevention measures and the ambitious goal set by United Nations member states to end the HIV epidemic by 2030 [ 24 , 25 ]. The surge in public discussion about HIV vaccines, possibly elicited by the clinical trials for mRNA HIV vaccines [ 9 ], presented an optimal opportunity to investigate public discourse and reactions regarding HIV vaccines. To the best of our knowledge, this is the first study to analyze posts on X about HIV vaccines.

Public Discourse and Post Types on X

On the X platform, public discourse featuring original content can be observed through 3 post types: self-composed posts, quote posts, and replies [ 26 ]. X users can compose a post. They can also create a quote post, which entails reposting a post while adding their comments. In addition, they can reply to a post to share their comments [ 26 ]. While self-composed posts initiate new conversations, quote posts and replies enable users to join existing conversations by contributing their own comments [ 27 ]. The Pew Research Center’s analysis of survey respondents’ posts on X from October 2022 to April 2023 revealed the composition of different types of posts. Regarding the 3 types of posts containing original content, replies accounted for the highest proportion at 40%, followed by self-composed posts at 15% and quote posts at 9%. The remaining 35% were reposts [ 28 ].

Machine learning algorithms have been increasingly used in recent years to identify latent message features, including textual topics and sentiment valence, among vast numbers of social media posts, as exemplified by previous research analyzing posts on X about COVID-19 vaccines [ 12 , 16 , 17 ] and HIV prevention [ 19 ]. However, the patterns of public discourse in social media conversations are unclear. Specifically, there is a scarcity of research on how people contribute their original content to topics and valence related to a public health issue. This study aimed to address this gap by examining the relationship between post types and message features, specifically topics and valence uncovered using machine learning algorithms, with a focus on HIV vaccines as the subject matter. The findings will advance our knowledge of user contributions to social media conversations about HIV vaccines.

Message Features Influencing User Reactions on X

Examining message diffusion on social media has been a multifaceted challenge, especially with vaccines being a contentious issue debated fervently during the COVID-19 pandemic [ 16 ]. Another contribution of this study is to advance this research area by using machine learning to investigate the synergistic impact of content and account features on user reactions regarding a potential new vaccine amid the context of intense vaccine debates.

The extent to which a message results in optimal diffusion on social media can be gauged by user reactions [ 16 , 29 - 31 ]. On X, a user can engage with posts—be it a self-composed post, quote post, or reply—in 2 primary 1-click reactions: liking and reposting [ 26 ]. An X user can like a post to show appreciation for it or repost it to share it publicly. Compared to liking, reposting is a more social behavior [ 16 , 32 ]. Unlike X’s old timeline, which mostly displayed posts from accounts that a user followed, its current “For you” timeline also shows posts that those accounts have engaged with along with other posts recommended based on user reactions [ 33 ]. The nature of promoting posts based on user reactions makes it more important to investigate the factors that influence user reactions.

This study investigated 2 categories of message-level features that, according to previous research, can drive user interactions: content features in terms of topics and valence and account features in terms of user verification and follower count. Post topics affect likes and reposts on X [ 16 , 30 , 34 ]. Previous research on COVID-19 vaccine posts on X has indicated that posts containing useful information garner more likes and reposts [ 16 ]. This is likely because information utility fills people’s knowledge gaps and serves their utilitarian needs in the face of health risks [ 16 , 32 , 34 - 36 ]. In addition, previous studies have suggested that the novelty of useful information further facilitates sharing of digital health information [ 32 , 36 ], such as updates about COVID-19 vaccine development [ 12 ]. Given the initial success of mRNA technology in COVID-19 vaccines, mRNA HIV vaccine candidates may possess the inherent features of prospective usefulness and ongoing novelty. As a result, posts presenting pertinent information have the potential to generate more likes and reposts. Meanwhile, the announcements of clinical trials for mRNA HIV vaccines were made amidst intense vaccine debates during the COVID-19 pandemic [ 12 ]. Previous research has shown that perceived controversiality in health information increases viewership but not sharing on social media [ 32 ]. In the context of the heated controversy surrounding vaccines, it is crucial to understand user reactions to new potential vaccines.

In addition to post topics, post valence can play a role in user reactions [ 34 ]. Past research has generally revealed that there are more positive than negative posts on X about vaccines in general [ 13 - 15 ] and, more recently, about COVID-19 vaccines in particular [ 12 , 16 , 17 ]. However, the influence of post valence on user reactions remains unclear. One study on COVID-19 vaccines showed that positive posts on X received more likes but not more reposts [ 16 ]. Another study on vaccines regardless of their type revealed that antivaccine posts garnered more reposts than provaccine posts on X [ 13 ]. A psychological rationale supporting the social transmission of positive content is the motivation of individuals to present themselves positively and shape their self-identity [ 35 , 37 ]. In comparison, social transmission of negative content can be attributed to the idea that certain negative content triggers activation, which drives user reactions [ 35 ].

Furthermore, previous research has shown that account features such as verification status and follower count affect user reactions on social media [ 13 , 16 , 34 ]. Given the vast amounts of information available in the digital age, the authenticity of user accounts becomes crucial in the diffusion of health information. One study revealed that account verification enhanced the number of likes and reposts for posts about COVID-19 vaccines on X [ 16 ]. Another study indicated that follower counts increased the number of reposts for posts about vaccines on X regardless of vaccine type [ 13 ].

Conspiracy Theories

A conspiracy theory refers to the belief that a coalition of powerholders forms secret agreements with malevolent intentions [ 38 , 39 ]. It differs from other types of misinformation by hypothesizing a pattern in which people, objects, or events are interconnected in a causal manner [ 39 ]. Previous research has revealed conspiracy theories as a salient theme in antivaccine discourse on social media, along with other themes such as side effects and inefficacy [ 40 , 41 ]. For HIV vaccines, conspiracy theories are crucial in understanding public discourse against them given the limited information about side effects and inefficacy until future success. An additional contribution of this study is the identification of prominent anti–HIV vaccine conspiracy theories through manual coding of the most engaged with negative posts.

Antivaccine conspiracy theories contribute to vaccine hesitancy [ 42 - 44 ], as observed recently with COVID-19 vaccines [ 10 , 11 ]. Understanding the themes and reasoning behind antivaccine conspiracy theories will provide vital implications for deploying evidence-based and logic-driven strategies to counter them [ 45 - 47 ]. A systematic review of antivaccine discourse on social media from 2015 to 2019 revealed pre–COVID-19 conspiracy theories [ 41 ]. These theories claimed that powerholders promoted vaccines for self-serving interests, including hiding vaccine side effects for financial gain and controlling society and the population [ 40 , 41 ]. During the COVID-19 pandemic, antivaccine conspiracy theories thrived on social media. Some theories claimed that the pandemic was invented for pharmaceutical companies’ profit from vaccines [ 44 ], whereas others linked mRNA COVID-19 vaccines to infertility and population control [ 10 , 11 , 44 , 48 , 49 ]. Another conspiracy theory claimed that Bill Gates and the US government aimed to implant trackable microchips into people through mass vaccination [ 11 , 27 , 49 ]. This aligns with conspiracy theories from earlier years. In particular, the Big Pharma conspiracy theory claims that pharmaceutical companies, together with politicians and other powerholders, conspire against the public interest [ 50 ]. The New World Order conspiracy theory alleges that a power elite with a globalization agenda colludes to rule the world [ 51 ]. Conspiracy theories have also linked other vaccines, such as poliovirus vaccines in the past [ 52 , 53 ] and COVID-19 vaccines in recent years, to HIV infection [ 54 , 55 ]. These conspiracy theories were based on the claims that alleged vaccines contained HIV.

Research Questions

To understand public discourse and reactions surrounding HIV vaccines on the X platform, we put forward the following research questions (RQs):

• What are the topics of the posts about HIV vaccines? (RQ 1)
• What is the valence of the posts about HIV vaccines? (RQ 2)
• How do topics and valence vary across different types of posts? (RQ 3)
• How do content features (topics and valence) and account features (verification status and follower count) affect 1-click reactions in terms of likes and reposts, respectively? (RQ 4)
• What are the prominent anti–HIV vaccine conspiracy theories that receive the most reactions? (RQ 5)

Data Source

We collected English-language original posts about HIV vaccines on the X platform from January 1, 2022, to December 31, 2022, using Netlytic [ 56 ]. The selected time frame began in January 2022 with the initiation of mRNA HIV vaccine clinical trials fueling public discussion and concluded in December 2022, a significant month for HIV and AIDS awareness marked by World AIDS Day on the first day of the month. Posts, excluding reposts, that contained both keywords (case insensitive)—“HIV” and “vaccine”—were extracted, resulting in a total of 36,424 posts across 365 days. Posts were collected weekly. Posts published from the last ending time point to at least 24 hours before each collection time point were included in the data set, allowing for a substantial reaction time.

The unit of analysis was a post. For each post, automated extraction produced data for user reactions (the number of likes and reposts) as well as account features (account verification status and follower count). All 36,424 posts underwent topic modeling using latent Dirichlet allocation (LDA) to identify latent topics, as well as sentiment analysis using Valence Aware Dictionary and Sentiment Reasoner (VADER) to access valence. LDA generated topic-specific loadings and identified the dominant topic for each post. VADER generated a valence compound score for each post, which was also categorized as positive, neutral, or negative based on standard VADER classification values.

LDA revealed 3 topics. As the topic of HIV and COVID-19 dominated in a large proportion of posts, we manually coded the 1000 most engaged posts containing the words “HIV” and “COVID” to uncover the salient aspects of HIV vaccines related to COVID-19. To develop coding for subtopics, 2 researchers initially reviewed and coded the top 200 posts with the most reactions. Subtopics were categorized by adapting existing categories from the literature [ 16 , 34 ] and integrating newly identified subtopics from the posts. The Scott π was 0.80 for categorizing subtopics. Subsequently, each researcher independently coded half of the remaining 800 posts.

We then conducted cross-tabulation analyses among all posts to examine the distribution of topics and valence among different types of posts. Furthermore, we conducted linear regression analyses among all posts to assess the influence of content and account features on these 1-click reactions. Of all 36,424 posts, 19,284 (52.94%) received ≥1 like, and 9155 (25.13%) received ≥1 repost. We added a constant value of 1 to all data points for likes and reposts before applying the natural logarithm. This was done to include posts with 0 likes or reposts and to mitigate the skewness of the data distribution.

Of the 28,439 posts that received likes or reposts, 6176 (21.72%) were negative. We manually coded the top 1000 negative posts with the most reactions to uncover prominent anti–HIV vaccine conspiracy theories. To develop coding for conspiracy theories, 2 researchers initially reviewed and coded the top 200 negative posts that received the most reactions. Posts containing conspiracy theories were identified based on expressions of postulated causal connections between people, objects, or events with malevolent intent [ 38 , 39 ]. Conspiracy theories were then classified based on the existing ones from the literature [ 50 , 51 ] and the emerging ones observed in the posts. Coding discrepancies were resolved through a further review of questionable posts and refinement of the conspiracy theories following the approach used in previous social media content analyses [ 40 , 57 ]. The procedure identified conspiracy theories and established intercoder reliability. The Scott π was 0.83 for identifying conspiracy theories and 0.81 for categorizing them. Each researcher then independently coded half of the remaining 800 negative posts.

User Reactions

One-click reactions were measured by the number of likes and reposts, which were automatically extracted. Because a small number of posts garnered significant 1-click reactions, the distribution of likes and reposts was right skewed. To reduce right skewness, we used the natural logarithm of the number of likes and reposts in linear regression analyses, as done in previous research [ 16 , 30 , 34 ].

Post Topics

All posts underwent topic modeling using LDA [ 58 ]. Topic modeling is a commonly used unsupervised learning method that generates a probabilistic model for a corpus of text data [ 59 ]. As a widely used topic model [ 59 ], LDA has been applied to discover topics within rich sources of digital health information, such as electronic health records [ 60 ], reviews on the web [ 61 ], and posts on X [ 16 , 34 ].

LDA relies on 2 matrices to define the underlying topical structure: the word-topic matrix and the document-topic matrix [ 62 ]. In this study, a post was considered a document. The general idea is that a post is represented by a Dirichlet distribution of latent topics, with each latent topic being represented by a Dirichlet distribution of words [ 59 ]. In the word-topic matrix, where the rows represent words and the columns represent topics, each element reveals the conditional probability of a word appearing within a topic [ 62 ]. A topic can be interpreted by examining a list of the most probable words ranked by their frequencies within a given topic using 3 to 30 words [ 63 ]. In the document-topic matrix, where rows represent posts and columns represent topics, each element reveals the conditional probability of a topic underlying a post [ 62 ]. In other words, it reveals the topic-specific loadings for each post.

When interpreting each topic, we reviewed the word-topic matrix as well as sample posts with high topic-specific loadings and significant reactions. LDA generated topic-specific loadings for each post ranging from 0 to 1, with values closer to 1 indicating a higher probability of a topic being associated with a post. Furthermore, LDA determined the dominant topic for each post by selecting the topic with the highest topic-specific loading among all topics. In the cross-tabulation analysis examining the distribution of topics across post types, the dominant topic for each post was entered for analysis. In the linear regression models assessing message-level drivers of user reactions, topic-specific loadings for each post were entered as topic values following previous research [ 16 , 34 ].

Post Valence

We used VADER to analyze the sentiment valence of each post. VADER is a rule-based model specifically attuned for assessing sentiments expressed in social media text [ 64 ]. VADER generated a compound valence score for each post ranging from –1 to 1, with a value of –1 indicating the most negative sentiment and a value of 1 indicating the most positive sentiment [ 65 ]. The standard VADER compound value thresholds for classifying valence categories are as follows: 0.05 to 1 for positive, −0.05 to 0.05 for neutral, and −0.05 to −1 for negative [ 65 ]. In the cross-tabulation analysis examining the distribution of valence among post types, the valence category for each post was entered for analysis. In the linear regression models assessing message-level drivers of user reactions, the VADER compound valence score for each post was used.

This study collected original posts excluding reposts. For each original post, it was automatically extracted whether it was a self-composed post, a quote post with comments, or a reply.

In total, 2 researchers manually coded the top 1000 out of 6176 negative posts with the highest total number of likes and reposts to uncover highly engaged conspiracy theories. They distinguished conspiracy theories from other types of negative information, particularly other types of misinformation, by recognizing the presence of a hypothesized pattern of causal connections between people, objects, or events for malicious intent [ 38 , 39 ]. Conspiracy theories were then categorized based on the existing ones from the literature and the emerging ones observed in the posts.

As an example, consider a post paraphrased as follows:

Image using condoms consistently, only to contract HIV from a COVID vaccine.

It was posted on February 9, 2022, and received 783 likes and 296 reposts. This post was not coded as displaying a conspiracy theory as it only presented misinformation suggesting that COVID-19 vaccines caused HIV. In comparison, another post was paraphrased as follows:

The COVID vaccine contained a spike protein derived from HIV. I was banned from saying this and ridiculed for months. Also, pharmacies stock up HIV self-tests.

It was posted on February 8, 2022, with 147 likes and 48 reposts. This post was coded as displaying a conspiracy theory. It was further classified within the category of conspiracy theories linked to COVID-19 vaccines containing, causing, or increasing HIV. This post suggested a hypothesized pattern of maliciously intended causal connections between the claim that the COVID-19 vaccine contained HIV and the stocking of HIV self-tests in pharmacies. As another example, a post was paraphrased as follows:

Scientists uncover a “highly virulent” strain of HIV in the Netherlands.

It was posted on February 12, 2022, and received 11 likes and 11 reposts. This post conveyed negative information but did not present a conspiracy theory. In comparison, another post was paraphrased as follows:

By coincidence again, the development of a new mRNA HIV vaccine began just before the emergence of the new HIV strain.

It was posted on February 8, 2022, and received 102 likes and 4 reposts. This post was coded as presenting a conspiracy theory and further classified into the category of conspiracy theories linked to the identification of a new highly virulent HIV strain. This post emphasized the speculative timing of the discovery of the new highly virulent HIV strain occurring shortly after the announcement of the development of a new mRNA HIV vaccine.

Account Features

For each post, the posting account’s verification status and follower count were automatically extracted.

Data Analysis

We used cross-tabulation analyses to investigate the distribution of topics and valence across different post types, in which the dominant topic and valence category for each post were entered, respectively, alongside the post type. We used linear regression models to examine the message-level drivers of user reactions among posts that received likes or reposts. In the linear regression models, a constant value of 1 was added to all data points of like and repost counts. The natural log-transformed values for each post were then regressed on 3 topic-specific loadings generated from LDA, the valence compound score generated from VADER, and 2 autoextracted account features—account verification status and follower count. The “plus one” technique was used to include posts that received 0 likes or reposts and to address the skewness of the data distribution.

Ethical Considerations

Following Long Island University’s institutional review board determination process, an institutional review board review was deemed unnecessary for this study, which collected and analyzed publicly available social media data. All referenced posts were paraphrased to avoid association with any particular user on the X platform.

RQ 1 asked about the topics present in all the posts. We trained a topic model using LDA exploring topic numbers ranging from 2 to 20. The optimal number of topics ( k ) was selected considering both the coherence score ( C v ) and the topic model visualization in a Python library called pyLDAvis , as done in previous research [ 16 , 66 ]. C v is a metric that reflects the semantic coherence of topics by evaluating the word co-occurrence likelihood within topics [ 67 ]. A higher C v indicates a better classification achieved by the topic model. In this study, the model with 2 topics ( k =2) yielded the highest C v (0.42), whereas the model with 3 topics ( k =3) yielded the second highest C v (0.35). The pyLDAvis chart depicts each topic as a circle. Overlapping areas between circles suggest similarities in topics. Thus, a chart without overlapping circles is preferable for k . The pyLDAvis chart for this study showed that, when the value of k was 2 or 3, the circles did not overlap. However, when k reached 4, the circles began to overlap, and overlapping circles persisted for values of k ranging from 4 to 20. Between the k values of 2 and 3, we opted for a model comprising 3 topics ( k =3) considering that a smaller number of topics tends to result in overly broad meanings for each topic [ 68 ].

Table 1 summarizes the 3 topics and lists their representative posts. Each topic was interpreted by examining the top 10 probable words ranked by frequency, along with sample posts exhibiting high topic-specific loadings and 1-click reactions. Topic 1 was HIV and COVID-19, covering 78% of the tokens [ 69 ] and dominating in 92.46% (33,678/36,424) of the posts. Topic 2 was mRNA HIV vaccine trials, covering 14% of the tokens and dominating in 5.91% (2151/36,424) of the posts. Topic 3 was HIV vaccine and immunity, covering 8% of the tokens and dominating in 1.63% (595/36,424) of the posts.

Figure 1 illustrates the daily numbers of original posts about HIV vaccines throughout 2022, in total and categorized into 3 topics. Moderna’s announcement of clinical trials for its first mRNA HIV vaccine on January 27, 2022, likely triggered the initial surge, culminating in a daily peak when the number of posts reached 805 on January 29, 2022. The daily number of posts about mRNA HIV vaccine trials (topic 2) in the week following Moderna’s announcement was higher than on other days throughout the year. Nevertheless, even during that week, there were higher daily numbers of posts about HIV and COVID-19 (topic 1), which remained dominant among the 3 topics during the entire year. The year’s second and highest daily peak occurred on February 8, 2022, recording a total of 1603 posts, most of which focused on HIV and COVID-19 (topic 1). This could be attributed to the emergence of new HIV-related events in early February 2022, including the promotion of HIV tests by public figures [ 64 ] and the discovery of a new highly virulent HIV strain [ 65 ]. The third highest daily peak, comprising 1085 posts, occurred on May 18, 2022, which has marked HIV Vaccine Awareness Day since 1998. Most of the posts centered on HIV and COVID-19 (topic 1). The remainder of the year did not reach such high peaks, with the largest daily volume of 205 posts occurring on December 2, 2022, the day following World AIDS Day, observed since 1988. Similar to previous daily peaks, most of the posts revolved around HIV and COVID-19 (topic 1).

The results revealed the dominance of HIV and COVID-19 (topic 1) in 92.46% (33,678/36,424) of the posts, with HIV as the most frequent word and COVID as the fourth most frequent word. To gain a deeper understanding of salient aspects of HIV vaccines related to COVID-19, we manually coded the top 1000 posts with the highest total number of likes and reposts that contained both HIV and COVID . Table 2 summarizes the subtopics and their representative posts with like and repost counts.

The first major subtopic, comprising 24% (240/1000) of the posts, focused on the reciprocal influence of HIV vaccines and COVID-19 vaccines on each other’s development. Years of HIV vaccine research facilitated the rapid development of mRNA COVID-19 vaccines, and the success of COVID-19 vaccines might accelerate the development of mRNA HIV vaccines. The second major subtopic, comprising 17.6% (176/1000) of the posts, involved comparisons between HIV and COVID-19 in various aspects. Specifically, the development speed of HIV vaccines compared to COVID-19 vaccines was a major point of comparison. In addition, some posts questioned whether potential HIV vaccines could be comparable to COVID-19 vaccines in terms of cost and accessibility during rollout. Others raised concerns about efficacy, safety, and inequality for both vaccines. The third major subtopic, comprising 26.5% (265/1000) of the posts, connected COVID-19 vaccines with HIV. One issue discussed was whether COVID-19 vaccines contained, caused, or increased HIV. Another issue raised was distinguishing between HIV symptoms and COVID-19 vaccine side effects, such as a fabricated condition called VAIDS , short for vaccine-acquired immunodeficiency syndrome. The fourth major subtopic, comprising 13.6% (136/1000) of the posts, featured conspiracy theories that presented hypothesized patterns linking COVID-19, HIV, and their vaccines with malicious intent. Prominent conspiracy theories in this subtopic included connecting misinformation that COVID-19 vaccines contain, cause, or increase HIV with the ongoing development of HIV vaccines; associating HIV and AIDS symptoms with side effects of COVID-19 vaccines; and claiming that COVID-19 originated from unsuccessful HIV vaccine research. As this study also manually coded the 1000 most engaged negative posts to identify prominent conspiracy theories, additional results pertaining to conspiracy theories will be discussed further in another subsection. The remaining posts related to HIV and COVID-19 included those that generally mentioned research on them or made connections without specifying details.

a mRNA: messenger RNA.

a The reaction count is the total number of likes and reposts.

b PrEP: pre-exposure prophylaxis.

c VAIDS: vaccine-acquired immunodeficiency syndrome.

d The categories labeled as “other” contain various topics. Thus, no representative post is displayed.

RQ 2 asked about the sentiment valence present in all the posts. According to the standard VADER classification values, valence is categorized by compound scores as follows: positive (0.05 to 1), neutral (−0.05 to 0.05), and negative (−0.05 to −1) [ 65 ]. On average, all posts had a marginally positive score of 0.053. HIV and COVID-19 (topic 1) had a slightly positive average score of 0.055. The mRNA HIV vaccine trials (topic 2) had a neutral average score of 0.040, leaning toward the positive side. HIV vaccine and immunity (topic 3) had a more neutral average score of −0.0008. Moreover, 42.78% (15,584/36,424) of the posts were positive, 25.64% (9338/36,424) of the posts were neutral, and 31.58% (11,502/36,424) of the posts were negative.

Topics and Valence Across Post Types

Of the 36,424 posts, 18,580 (51.01%) were replies, making up over half of the overall count. Self-composed posts totaled 41.6% (15,151/36,424), whereas the remaining 7.39% (2693/36,424) were quote posts. RQ 3 asked about the distribution of topics and valence among the 3 post types. As Table 3 shows, the distribution of topics varied by post type (N=36,424, χ 2 4 =2511.4, P <.001). Of the self-composed posts, 85.36% (12,933/15,151) focused on HIV and COVID-19 (topic 1) and 13.21% (2001/15,151) focused on mRNA HIV vaccine trials (topic 2). In comparison, quote posts and replies exhibited a different pattern, in each case >97% of posts centering on HIV and COVID-19 (topic 1; 2616/2693, 97.14% and 18,129/18,580, 97.57%, respectively).

As Table 4 shows, the distribution of valence also varied by post type (N=36,424, χ 2 4 =911.7, P <.001). The proportion of positive posts was slightly higher among self-composed posts at 44.95% (6810/15,151) compared to replies at 41.09% (7634/18,580) and quote posts at 42.33% (1140/2693). Self-composed posts had a smaller proportion of negative posts at 23.56% (3570/15,151) compared to replies at 37.64% (6994/18,580) and quote posts at 34.83% (938/2693). The proportion of neutral posts was larger for self-composed posts at 31.49% (4771/15,151) compared to quote posts at 22.84% (615/2693) and replies at 21.27% (3952/18,580).

Regarding the distribution of topics and valence among the 3 types of posts, quote posts and replies displayed similarities, whereas self-composed posts diverged. Compared to self-composed posts, which initiate new conversations, there was a higher proportion of HIV and COVID-19-related posts (topic 1) and a greater proportion of negative posts among quote posts and replies, which contribute to existing conversations.

a N=36,424, χ 2 4 =2511.4, P <.001.

b mRNA: messenger RNA.

a N=36,424, X 2 4 =911.7, P <.001.

Content and Account Features Influencing User Reactions

RQ 4 asked about the influence of content and account features on likes and reposts.

Liking is more common than reposting. While 52.94% (19,284/36,424) of posts received an average of 24.83 likes, ranging from 1 to 102,843, a total of 25.13% (9155/36,424) posts received an average of 11.38 reposts, ranging from 1 to 10,572. Table 5 reveals the influence of content features (topics and valence) and account features (verification status and follower count) on the natural log-transformed number of likes and reposts. Both linear regression models were significant at P <.001. The adjusted  R 2 was 0.072 for the like model and 0.090 for the repost model.

Among the 3 topics identified using LDA, HIV and COVID-19 (topic 1) did not affect like counts but decreased repost counts. In comparison, mRNA HIV vaccine trials (topic 2) decreased like counts while increasing repost counts. Positive valence increased like and repost counts. Account verification status and follower count increased like and repost counts.

a The natural logarithm, ln (Y i +1), was calculated on like and repost counts. This transformation was conducted to include posts receiving 0 likes and reposts, as well as to account for the skewness of the data distribution.

b F (model significance): P <.001; adjusted R 2 =0.072.

c F (model significance): P <.001; adjusted R 2 =0.090.

d mRNA: messenger RNA.

e The models excluded topic 3 on HIV vaccine and immunity to address multicollinearity issues arising from its correlations with topics 1 and 2. The reported standard β for topic 3 represents a possible β value if it had been included in the models.

Posts With Most Reactions

Table 6 summarizes posts ranked within the top 5 for the number of likes and reposts presented in chronological order. It is worth noting that all posts in the top 5 for likes and reposts were self-composed. One particular post, which garnered the most likes (n=102,843) and reposts (n=10,572), expressed the incredible feeling of witnessing the development of an HIV vaccine within our lifetimes. It was posted by an unverified account on January 28, 2022, the day after Moderna’s announcement of clinical trials for its first mRNA HIV vaccine.

a Ranks beyond the fifth were not indicated.

Anti–HIV Vaccine Conspiracy Theories

RQ 5 asked about prominent anti–HIV vaccine conspiracy theories. Of the 1000 negative posts that received the most reactions, 227 (22.7%) contained conspiracy theories. As Table 7 shows, we classified these prominent anti–HIV vaccine conspiracy theories into 4 categories and presented their representative posts and the number of reactions.

The first category, comprising 44.9% (102/227) of the posts, formulated conspiracy theories by connecting COVID-19, COVID-19 vaccines, HIV, and HIV vaccines. For instance, 52.9% (54/102) of these posts connected the misinformation regarding COVID-19 vaccines containing, causing, or increasing HIV with the ongoing efforts to develop HIV vaccines. This misinformation may have arisen from past occurrences resurfacing following Moderna’s initiation of its mRNA HIV vaccine trials. One incident occurred at the end of 2020, when an Australian COVID-19 vaccine, which used a small fragment of protein from HIV to clamp SARS-CoV-2’s spike proteins, was abandoned due to false HIV-positive results [ 70 ]. Another incident occurred in October 2020, when 4 researchers sent a letter to a medical journal expressing concerns about the potential increased risk of HIV acquisition among men receiving COVID-19 vaccines using adenovirus type-5 vectors without supporting data from COVID-19 vaccines [ 71 ]. The misinformation typically interpreted the incidents out of context and generally suggested that COVID-19 vaccines contained, caused, or increased HIV without specifying details. In addition, there were conspiracy theories linking HIV and AIDS to COVID-19 vaccine side effects, including a fabricated condition known as VAIDS. VAIDS falsely suggests that COVID-19 vaccines caused immune deficiency [ 72 ]. Furthermore, there were claims that COVID-19 originated from unsuccessful HIV vaccine research.

The second category, comprising 38.3% (87/227) of the posts, suggested that the alignment of concurrent events with Moderna’s start of mRNA HIV vaccine trials in late January 2022 was intentional to manipulate the market for HIV vaccines. These events included the rising HIV discussion and fear; promotion of HIV tests by public figures [ 73 ]; the discovery of a new highly virulent HIV strain [ 74 ]; and the passing away of HIV researchers, including Luc Montagnier, codiscoverer of HIV with an antivaccine stance during the COVID-19 pandemic [ 75 ], all occurring in early February 2022.

The third category, with 11.5% (26/227) of the posts, revealed conspiracy theories based on the distrust of powerholders [ 76 ]. Some posts extended existing conspiracy theories, such as the Big Pharma conspiracy theory [ 50 ] and the New World Order conspiracy theory [ 51 ], into the context of HIV vaccines, emphasizing the intent of powerholders, including major pharmaceutical companies and governments, behind vaccine promotion for financial profits and society control. Other posts created conspiracy theories about the government’s research on HIV vaccines. The remaining posts generally stated that HIV vaccines were a scam. The final category comprised the remaining 5.3% (12/227) of the posts with other conspiracy theories.

It is worth noting that, of the 227 posts containing conspiracy theories, 39 (17.2%) were posted by accounts that had already been suspended at the time of manual coding. For these posts, the X platform displays the following message—“This post is from a suspended account”—and the content of the post is not visible. The X platform suspends accounts that violate its rules [ 77 ]. However, specific details of the violations are not accessible on the platform. The invisibility of these posts halted their spread when the suspension was enacted. For our manual coding of these posts, we used the text obtained during the data collection process.

b The posts were from suspended accounts.

d The categories labeled as “other” contain various conspiracy theories. Thus, no representative post is displayed.

Principal Findings

This study investigated the patterns of public discourse and the message-level drivers of user reactions on the X platform regarding HIV vaccines through the analysis of posts using machine learning algorithms. We examined the distribution of topics and valence across different post types and assessed the influence of content features (topics and valence) and account features (account verification status and follower count) on like and repost counts. In addition, we manually coded the 1000 most engaged posts about HIV and COVID-19 to understand the salient aspects of HIV vaccines related to COVID-19 and the 1000 most engaged negative posts to identify prominent anti–HIV vaccine conspiracy theories.

The results revealed that COVID-19 plays a substantial role as a context for public discourse and reactions regarding HIV vaccines. Of the 3 topics identified using LDA, the leading topic was HIV and COVID-19, covering 78% of tokens and dominating in 92.46% (33,678/36,424) of the posts. Furthermore, on each of the top 4 days with the highest post counts, most of the posts were about HIV and COVID-19. This comprehensive topic included important subtopics that linked HIV vaccines with COVID-19 vaccines, as demonstrated through the manual coding of the 1000 most engaged posts about HIV and COVID-19. These subtopics encompassed the reciprocal influence of HIV vaccines and COVID-19 vaccines in advancing each other’s development; comparisons in their development speed; inquiries about the possible alignment of HIV vaccines with COVID-19 vaccines in terms of cost and accessibility during distribution; and concerns about efficacy, safety, and equality for both vaccines.

COVID-19 positioned HIV vaccines in both a positive and negative context. On the one hand, the success of mRNA technology in COVID-19 vaccines [ 6 ] potentially cast mRNA HIV vaccines in a positive light. The topic of HIV and COVID-19 had a marginally positive valence score of 0.055. Moreover, 3 (60%) out of the 5 most liked posts and 2 (40%) out of the 5 most reposted posts expressed excitement about advancements in HIV vaccines that were based on the experience with COVID-19 vaccines. On the other hand, antivaccine discourse, including conspiracy theories, heated up during the COVID-19 pandemic [ 10 , 11 , 27 , 44 , 48 , 49 ], which posed challenges to HIV vaccines. Of the 1000 most engaged posts about HIV and COVID-19, a total of 136 (13.6%) featured conspiracy theories. Of the 1000 most engaged negative posts, 227 (22.7%) contained conspiracy theories, with 102 (44.9%) of them revolving around HIV and COVID-19. For instance, a prominent conspiracy theory connected the misinformation about COVID-19 vaccines containing, causing, or increasing HIV infection [ 55 ] with the initiation of clinical trials for mRNA HIV vaccines [ 4 , 5 ], implying a malevolent intent behind the deliberate connection. The results indicate that conspiracy theories tend to elicit an approach-oriented response, as evidenced by people engaging in liking and reposting, as opposed to an avoidance-oriented approach [ 39 ]. This underscores the need to intensify efforts to counter conspiracy theories in public health communication about HIV vaccines.

According to a study conducted by the Pew Research Center, irrespective of the subject matter, replies constituted the largest portion of original posts on X, followed by self-composed and quote posts [ 28 ]. Specifically, the number of replies was 3 times greater than that of self-composed posts. In this study, although replies constituted slightly more than half (18,580/36,424, 51.01%) of the posts, it is worth noting that the subject of HIV vaccines elicited a higher proportion of self-composed posts at 41.6% (15,151/36,424). Specifically, the number of replies was 23% higher than that of self-composed posts. Moreover, the topic of mRNA vaccine trials was most evident in self-composed posts compared to replies and quote posts. In comparison, there was a higher proportion of focus on the topic of HIV and COVID-19 and a greater proportion of negative posts among quote posts and replies, which contribute to existing conversations. This suggests that users were more likely to initiate new conversations rather than joining existing conversations about mRNA HIV vaccines. In contrast, they were more likely to join existing conversations rather than starting new conversations about HIV and COVID-19. In addition, users were less likely to initiate new conversations negatively but more likely to contribute negatively to existing ones.

As the primary topic, HIV and COVID-19 had no impact on like counts but had a negative impact on repost counts. In comparison, the topic of mRNA HIV vaccine trials had a negative impact on like counts and a positive impact on repost counts. The results should be interpreted while considering that, as revealed in previous research [ 16 , 34 ] and this study, most posts on the X platform are unlikely to receive likes and even less likely to receive reposts. In this study, among the total of 36,424 posts, approximately half (n=19,284, 52.94%) received likes, and approximately one-quarter (n=9155, 25.13%) received reposts. To include all posts and mitigate the data distribution skewness in the linear regression analysis, we applied the “plus one” technique. This involved adding a constant value of 1 to all like and repost data points before taking the natural logarithm. Although most posts were not liked or reposted, it is noteworthy that the topic of mRNA HIV vaccines led to an increase in repost counts, highlighting its positive influence on social sharing. In addition, 2 (40%) out of the 5 most reposted posts were about mRNA HIV vaccine trials. These results correspond to the findings of previous research that suggested the diffusion of novel useful information [ 12 , 16 , 32 , 36 ].

The overall valence of the posts about HIV vaccines was marginally positive. The positivity aligns with the positive sentiment found in posts on X about vaccines in general [ 13 - 15 ] and COVID-19 vaccines in particular [ 12 , 16 , 17 ]. However, the positivity about HIV vaccines was not apparent as the average score of 0.053 placed it on the edge of the neutral range, which goes from −0.05 to 0.05 according to the standard VADER classification values. Positive sentiment had a favorable impact on like and repost counts, partially consistent with findings of previous research on COVID-19 vaccines [ 16 ]. The post that achieved the most likes conveyed the incredible feeling of witnessing the development of an HIV vaccine in our lifetimes. This could be attributed to the psychological rationale that social transmission of positive content fulfills people’s motivation to present a positive image [ 35 , 37 ]. In alignment with the findings of previous research [ 13 , 16 , 34 ], account verification status and follower count increased like and repost counts.

This study has implications for public health communication related to HIV vaccines and potentially other vaccines. Given the massive scale of the COVID-19 vaccination campaign, it is understandable that people will draw comparisons with other vaccines. Topic modeling identified HIV and COVID-19 as the primary topic, and manual coding revealed various intertwined aspects. Leveraging the advantages observed in the COVID-19 vaccine campaign, such as its widespread accessibility, could be valuable. Furthermore, addressing common concerns such as efficacy, safety, and inequality could also prove beneficial.

In the case of HIV vaccines, it is essential to tackle concerns associated with COVID-19 vaccines, especially those related to HIV vaccines. A major subtopic of HIV and COVID-19 involved suspicions about COVID-19 vaccines containing, causing, or increasing HIV. Another major subtopic was the confusion between HIV symptoms and the alleged side effects of COVID-19 vaccines, such as VAIDS. Misinformation concerning both subtopics has been woven into conspiracy theories, further complicating this situation. To combat misinformation and conspiracies that have these elements, efforts could focus on promoting evidence-based factual information [ 45 - 47 ].

Another notable technique in the conspiracy theories was linking concurrent COVID-19 and other HIV-related events in unsubstantiated relationships to create false perceptions, suggesting that these events were intentional to manipulate the market for HIV vaccines. These HIV-related events included rising HIV discussion and fear, promotion of HIV tests by public figures [ 73 ], the discovery of a new highly virulent HIV strain [ 74 ], and the passing away of HIV researchers, all occurring in early February 2022. These findings suggest that refuting false connections among such concurrent events can be an effective strategy to counter these conspiracy theories [ 45 - 47 ]. These occurrences, frequently entwined within conspiracy theories, could be specifically addressed in public health communication efforts.

Limitations

This study has several limitations. Because we used autoidentified content features (topics and valence) and autoextracted account features (verification status and follower count) in the regression models to predict the autoextracted number of user reactions (likes and reposts), the results were mostly limited to the examined autoidentified and autoextracted factors. For instance, political polarization, which manifested in a wide range of issues, including response to vaccines [ 78 ], could be a factor worth investigating in future studies. Furthermore, manual coding of conspiracy theories revealed a prevalent technique of twisting concurrent events into false relationships. This underscores the significance of refuting unfounded associations among these incidents to counter such conspiracy theories. It will be interesting for future research to assess the impact of this technique on user reactions to conspiracy theories. These findings could provide further insights into public health communication strategies to combat conspiracy theories.

Conclusions

The results highlight COVID-19 as a significant backdrop for public discourse and reactions on the X platform regarding HIV vaccines. COVID-19 situated HIV vaccines in both a positive and negative context. The success of mRNA COVID-19 vaccines shed a positive light on HIV vaccines. However, COVID-19 also situated HIV vaccines in a negative context, as evident in anti–HIV vaccine conspiracy theories falsely linking HIV vaccines to COVID-19. The findings provide implications for public health communication strategies concerning HIV vaccines.

Acknowledgments

This study was supported in part by the College of Arts and Sciences and the Harrington School of Communication and Media at the University of Rhode Island. The authors express their appreciation for the support. The funders had no role in study design, data collection, data analysis, data interpretation, or writing of the report.

Data Availability

The data sets collected and analyzed during this study are available from the corresponding author upon request.

Conflicts of Interest

None declared.

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Abbreviations

Edited by G Eysenbach; submitted 04.10.23; peer-reviewed by X Ma, J Zhang; comments to author 18.10.23; revised version received 08.11.23; accepted 28.02.24; published 03.04.24.

©Jueman M Zhang, Yi Wang, Magali Mouton, Jixuan Zhang, Molu Shi. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 03.04.2024.

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