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This study aims to investigate the integration of blockchain technology into the food supply chain within the restaurant industry. It focuses on how blockchain can be applied to enhance transparency and trust in tracking food sources, ultimately impacting customer satisfaction.

A service design workshop (Study 1) and three between-subjects experiments (Studies 2–4) were conducted.

Results indicate that blockchain adoption significantly improves traceability and trust in the food supply chain. This improvement in turn enhances customer satisfaction through perceived improvements in food safety, quality and naturalness. This study also notes that the effects of blockchain technology vary depending on the type of restaurant (casual or fine dining) and its location (tourist destinations or residential areas).

The findings offer practical insights for restaurant owners, technology developers and policymakers. Emphasizing the benefits of blockchain adoption, this study guides decision-making regarding technology investments for enhancing customer service and satisfaction in the hospitality sector.

This research contributes novel insights to the field of technology innovation in the hospitality industry. It extends the understanding of signaling theory by exploring how blockchain technology can serve as a tool for signal transmission in restaurant food supply chains.

The intense competition among restaurant brands made it difficult to retain and engage customers. Service innovation can play a vital role to serve this purpose, however, restaurant brands' efforts to bringing innovativeness may not yield desired results unless customers perceive them innovative. Therefore, the present study aims to investigate the role of customer perceived innovativeness (CPRI) in enhancing brand love and evangelism among customers. This study compares these effects between fast-food and continental restaurants to offer deeper insights.

Data were collected from 303 customers of fast-food and continental restaurants through self-administered structured questionnaire. The reliability and validity were established through confirmatory factor analysis. The hypotheses were tested using structural equation modeling and multi-group SEM with MPlus.

The findings of this study reveal that menu, experiential and promotional innovativeness dimensions of CPRI positively influence brand love. The effects of CPRI dimensions transcend to brand evangelism dimensions, i.e. brand purchase intension, positive brand referrals and oppositional brand referrals via brand love. The multi-group analysis showed that continental restaurants' menu innovativeness strongly impacts brand love and evangelism while promotional innovativeness matters more in the context of fast-food restaurants.

This study helps restaurant managers in devising tailor made strategies for fast-food and continental restaurants by focusing on the relevant attributes to bring innovation.

This research is one of the pioneering studies to investigate the relationship of CPRI with brand evangelism through the mediating role of brand love. This study also marks an initial attempt to compare fast-food and continental restaurants in the context of CPRI.

This study empirically identifies household demographic and socioeconomic characteristics as well as restaurant characteristics that affect the probability of households choosing an ethnic restaurant (American, Asian, European, Mexican and other) in the USA.

A multinomial logistic regression model is applied using the data derived from the information from the National Household Food Acquisition and Purchase Survey conducted between April 2012 and January 2013.

The empirical findings suggest that such factors as the unit cost on away-from-home food items (i.e. price), region of residence, primary respondent's ethnicity, race, education level, marital status and employment status as well as such restaurant characteristics as availability of loyalty program and presence of coupons significantly affect the probability of households choosing a particular ethnic restaurant in the USA.

The original dataset employed in this study does not permit the quantification of information associated with size, location, and number of years in operation for the ethnic restaurants considered. Also, the dataset does not permit the classification of the ethnic restaurants included in the “other” category.

To the best of the authors' knowledge, there has been no empirical micro-level analysis associated with determining factors impacting households' choice of ethnic restaurants using a polytomous logistic regression model allowing for a wide range of ethnic restaurants and covering the entire USA, based on an extensive set of household demographic and socioeconomic factors and restaurants characteristics. As such, the current study plugs this research gap, with the empirical findings furnished by this study being of importance to ethnic restaurant operators (owners) in the operators' effort to develop effective marketing strategies.

The purpose of this study is to discover what attributes of casino buffet restaurants are the most important for customers’ willingness to pay (WTP).

Choice-based conjoint analysis was used in this study to test seven attributes: food, price/value, real price, service, atmosphere, the number of reviews and user-generated star ratings. Sawtooth Software was used to do the conjoint analysis, and a series of significance t-tests were run to determine the significance of each attribute on WTP with Statistical Package for the Social Sciences (SPSS).

Based on a survey of 483 respondents who had visited a buffet at a casino within the last two years, this study found that food is ranked as the most significant attribute of a casino buffet restaurant, followed by real price and service quality.

Theoretically, this work is the first to the authors’ knowledge to apply the antecedents of behavioral intention to willingness-to-pay for niche restaurants. Practically, the results of this study will help casino buffet operators as they re-open after COVID-19. Future studies could collect data in the post-pandemic environment and examine WTP at casino buffets in different geographic locations.

This study (1) assessed restaurant consumers' perceived importance of better food quality versus larger portion sizes, (2) classified restaurant consumers into different segments based on their perceived importance of seven food quality attributes (taste, texture, aroma, appearance and the use of natural, local and organic ingredients) relative to portion size and (3) compared the identified market segments.

An online survey assessed 613 USA adult participants' perceived importance of seven food quality attributes relative to portion size. A K-means cluster analysis classified participants into different segments based on their perceptions.

Five restaurant consumer segments were identified: sensory-oriented consumers, taste-oriented organic food consumers, local and natural food consumers, quantity-oriented consumers and quality-oriented consumers. In general, quality-oriented consumers were the least likely to visit fast-food restaurants, had the highest average per-meal spending and were the least likely to eat out alone. Local and natural food consumers and taste-oriented organic food consumers had higher total restaurant spending than other groups. Quantity-oriented and sensory-oriented consumers visited fast-food restaurants more often and had lower total restaurant spending and per-meal spending than other groups. Age, sex and income were significantly associated with the segmentation outcomes.

Findings suggest promising opportunities for restaurants to enhance consumer perceptions of value by prioritizing the factors that hold the greatest significance to their target customers.

This study is the first attempt to segment restaurant consumers based on their perceived importance of food quality attributes relative to portion size, effectively identifying five distinct consumer segments.

Built upon customer engagement marketing theory and uses and gratification theory, this study examines the link between individual social media marketing (SMM) performance indicators and restaurant sales performance at the firm level. Moreover, the study investigates the moderating effect of advertising expenditure on this proposed relationship.

Random effect regression models were developed in Stata to examine the associations between SMM performance indicators, advertising expenditure, and restaurant firm revenue. Twelve years of SMM data from brands' Facebook pages were collected with a web scraper built in Python. Natural language processing was used to analyze the sentiment of user-generated content (UGC).

The results suggest that restaurant annual sales revenue increases as the volume of brand posts, “like”s, “share”s and positive comments on restaurants' Facebook pages increase. However, the total number of comments and the number of negative comments show non-significant associations with revenue. Firm advertising expenditure negatively moderates the relationships between sales revenue and the number of “like”s, “share”s, total comments and positive comments.

Restaurants benefit from making frequent posts on SNSs. Promotions that motivate online users to “like”, share, and comment on brand posts should be implemented. Firms with limited advertising budgets are encouraged to actively create buzz on SNSs due to evidenced stronger effects of UGC on sales performance than large advertisers.

This research bridges the gap by studying the effects of individual SMM performance indicators on restaurant financial outcomes. The findings support the effectiveness of SMM; and, for the first time, demonstrate that SMM could generate a more profound impact for firms with low advertising budgets.

While the rise of chain restaurants has attracted increasing research interest, few studies have taken servicescape into consideration to examine its effects on transformative service outcomes. This study aims to assess how social service elements can provide customers with restorative qualities, though social components are considered vital in constituting a dining locale's servicescape (AKA Social Servicescape).

The study fills the void above by undertaking a survey-based quantitative research method. Using online surveys with a sample of 306 diners, the study employed structural equation modeling to explore a proposed moderated mediation model. A post-hoc interview followed to provide qualitative data to complement the findings developed from surveys.

Results first point to a positive relationship between social servicescape and attention restoration. Moreover, the authors unveil that substantive servicescape has a moderating effect on the relationship of interest, suggesting the interplay of social and built servicescape in promoting restorative experiences.

Social and built stimuli can be intertwined to offer restorative qualities for customers. Through such an intertwined network of relationships, one may derive better mental health resources from hospitality settings.

This research presents new nuances to the existing field of inquiry by linking social servicescape and restoration through an intertwined network of attentional recovery.

This study aims to analyze how restaurants' collaboration with mobile food delivery applications (MFDAs) affects product development efficiency and argues that technological capabilities moderate relational ties impact the joint decision-making and development efficiency of restaurant products.

A product development efficiency model was formulated using a resource-based view and real options theory. In all, 472 samples were collected from restaurants collaborating with MFDAs, and partial least squares structural equation modeling was applied to the proposed model.

The findings of this study indicate three factors are critical to the product development efficiency between restaurants and MFDAs; restaurants must develop a strong connection with the latter to ensure meals are consistently served promptly. Developers of MFDAs should use artificial intelligence analysis, such as order records of different genders and ages or various consumption attributes, to collaborate with restaurants.

To the best of the authors’ knowledge, this study is one of the few that considers the role of MFDAs as a product strategy for restaurant operations, and the factors the authors found can enhance restaurants’ product development efficiency. Second, as strategic artificial intelligence adaptation changes, collaborating firms and restaurants use such applications for product development to help consumers identify products.

The existing literature has examined the determinants of post-purchase behavioral intentions. However, less attention has been devoted to the factors that contribute to perceived usefulness of fast-food restaurants attributes. The current study considers the servicescapes and social servicescapes of restaurants as well as their relationship with customers' perceived usefulness, with the moderating role of customer experience. It also explores how perceived usefulness influences choice process satisfaction and subsequent behavioral responses, including revisit intention and negative word-of-mouth.

Data from 485 fast-food restaurant consumers in Pakistan were collected using purposive sampling. The data were analyzed using both structural equation modeling (SEM) through AMOS 24.0 and the PROCESS macro in IBM SPSS 27.0.

The research revealed that perceived usefulness in fast-food restaurant industry is positively influenced by servicescapes and social servicescapes. Similarly, choice process satisfaction is primarily caused by perceived usefulness and affects behavioral responses. It also found that choice process satisfaction is positively associated with revisit intentions and negative word-of-mouth. Customer experience significantly moderates the relationship between ambient condition, facility aesthetic, layout, perceived similarity and perceived usefulness. However, customer experience insignificant moderates the relationships of physical appearance and suitable behavior with perceived usefulness.

The findings provide insightful information for both academic and managerial fields, contributing to the literature on consumer psychology, consumer behavior, servicescapes and the stimulus-organism-response theory. The study also assists restauranteurs in the fast-food restaurant industry in overcoming the challenges posed by a highly competitive environment and developing strategies based on consumer perceptions.

This study, conducted in Pakistan, took a pioneer step in testing and confirming a novel perceived usefulness model that incorporates not only servicescapes but also social servicescapes in consumer behavior. It enhances the knowledge of consumer visit intentions by quantifying the significance of perceived usefulness developed by different servicescapes.

When encountering novel technology, customers often use the term “cool” to express their thoughts; therefore, coolness has become crucial for launching service robots. However, research on the impact mechanism of “coolness” is lacking. This study explored the relationship between delight and behavioral intention regarding the coolness of service robots in the food and beverage industry while discussing the mediating roles of utilitarian and hedonic values.

Questionnaires were distributed online with links to the survey posted on restaurant discussion boards on Facebook and online community platforms such as Dcard. In total, 540 responses were deemed valid. The hypotheses were tested using the partial least squares structural equation modeling method.

The results indicate that coolness positively impacted both utilitarian and hedonic values and that both perceived values positively impacted delight. Moreover, coolness does not directly impact delight but must be mediated by perceived value to be effective.

Increasing customer perceptions of the coolness of service robots is recommended. Moreover, regarding customer revisits, utilitarian value services can delight customers more effectively than hedonic value services.

The stimulus-organism-response model was used to identify the relationships among coolness, perceived value, delight and behavioral intention. Moreover, the authors investigated the impact of coolness on utilitarian and hedonic values. These findings are significant for the development of smart restaurants and provide a critical reference for exploring service robots.