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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.

This study aims to explore a new restaurant category’s development from birth to maturity, thereby explaining the rationale for category innovation strategies.

The authors conducted a qualitative case study analysis of the New Chinese-style Fusion Restaurant category’s development from birth to maturity. Thematic analysis was conducted on data collected from semi-structured interviews and textual information.

A new restaurant category’s maturation is determined by the formation of society’s shared knowledge about the category’s crucial attributes, which is an outcome of market participants’ category-related social practices. The authors develop a novel, four-stage framework for the socialized construction of this shared knowledge: a knowledge creation (KC), knowledge diffusion (KD), knowledge integration (KI) and knowledge structuralization (KS). This knowledge evolution along this KC–KD–KI–KS sequence can holistically describe the category maturation process. This framework can help understand the rationale for a restaurant category’s maturation by analyzing the interrelationships among market participants’ social practices, knowledge-related activities and market development.

This study explains how market participants’ knowledge-related activities facilitate a new restaurant category’s maturation. This can help restaurant managers cope with increasingly homogeneous competition by applying a category-innovation strategy.

This study extends product categorization research on restaurants by articulating a product category’s maturation process from a knowledge perspective.

This study aims to address the global food waste problem in restaurants by analyzing customer sales information provided by restaurant tickets to gain valuable insights into directing sales of perishable products and optimizing product purchases according to customer demand.

A system based on unsupervised machine learning (ML) data models was created to provide a simple and interpretable management tool. This system performs analysis based on two elements: first, it consolidates and visualizes mutual and nontrivial relationships between information features extracted from tickets using multicomponent analysis, bootstrap resampling and ML domain description. Second, it presents statistically relevant relationships in color-coded tables that provide food waste-related recommendations to restaurant managers.

The study identified relationships between products and customer sales in specific months. Other ticket elements have been related, such as products with days, hours or functional areas and products with products (cross-selling). Big data (BD) technology helped analyze restaurant tickets and obtain information on product sales behavior.

This study addresses food waste in restaurants using BD and unsupervised ML models. Despite limitations in ticket information and lack of product detail, it opens up research opportunities in relationship analysis, cross-selling, productivity and deep learning applications.

The value and originality of this work lie in the application of BD and unsupervised ML technologies to analyze restaurant tickets and obtain information on product sales behavior. Better sales projection can adjust product purchases to customer demand, reducing food waste and optimizing profits.

The case tracks Dineout's evolution into a full-scale tech solution provider for restaurants. In 2020, the COVID-19 pandemic struck the world. Several countries, including India, implemented complete lockdowns to control the spread of the virus. Stringent measures to ensure social distancing, night curfews and restrictions on social gatherings continued, which were a severe blow to the restaurant industry. The restaurants' revenue streams dried up as the diners avoided dining out and preferred food deliveries, which was against Dineout's core business model. The case ends with the questions on how Dineout should wade through the pandemic when its entire business model was being challenged.

Amidst pressing environmental concerns, the service industry has increased its focus on sustainable production and consumption patterns. This study aims to explore whether Generation Z’s perceived value of plant-based food influences feelings of guilt as a result of consuming meat instead of plant-based food and/or pride from consuming plant-based foods, which might then lead to decisions to purchase alternative plant-based products at restaurants.

A survey was conducted measuring a range of variables and their relationships. The hypothesized model was tested using covariance-based structural equation modeling.

Results showed that perceived social value significantly influenced guilt and pride with perceived emotional value only influencing pride. Both guilt and pride significantly influenced the decision to switch eating patterns from conventional meat to plant-based protein at restaurants. And, finally, environmental concern significantly moderated the effect of emotional value on guilt.

To achieve sustainable goals, food producers should promote plant-based menu items by increasing the awareness of social approval through marketing communications.

This study bridges a gap in the literature by investigating how consumers’ perceived value affects their anticipated emotional feelings of guilt and pride leading to the switch from meat-based to plant-based diets at restaurants.

This study proposes a model that influences customer citizenship behavior during COVID-19, and empirically tests the effects of fast-food restaurant customers' perceptions of justice (price and procedural justice) on trust; trust on satisfaction and loyalty; and trust, satisfaction and loyalty on customer citizenship behavior. Furthermore, it was questioned whether there was a disparity between customer expectations based on the restaurant's image and consumption experience.

The data were gathered from customers of fast-food restaurants in the shopping centers in Turkey. The data set, which included 437 valid questionnaires, was subjected to CFA for validity and reliability, SEM analysis for hypothesis and paired sample t-Tests for the research questions.

The findings of the study indicate that perceived justice affects customer trust, which, consequently, affects customer loyalty and satisfaction during the COVID-19 period. Findings also demonstrate that, while customer loyalty and trust increase customer citizenship behavior, customer satisfaction alone is insufficient to increase customer citizenship behavior. The study also shows that during the COVID-19 period, fast-food restaurants should have raised awareness of employees’ fair behaviors toward the customers and provided additional services to differentiate themselves in the market. Also, it indicates that customer expectations related to price, cleanliness and professional appearance of staff are not met after taking service.

No research has been found in the literature focusing on the expectations, justice, trust, satisfaction, loyalty and citizenship behaviors of fast-food restaurant customers in the COVID-19 pandemic process. Therefore, the results can fill the gap in relevant literature by testing the relationships between justice, trust, satisfaction, loyalty and citizenship during the pandemic and provide inferences for fast-food business owners.

This study attempts to ascertain how behavioral intention and word-of-mouth communication is affected by belonging, attitude toward behavior and subjective norm found in the theory of reasoned action. The research universe consists of customers visiting local restaurants operating in Afyonkarahisar.

The survey technique was used to collect data from customers visiting local restaurants between 05 September and 05 November 2022, using the convenience sampling method. The acquired data (n = 385) were analyzed using the structural equation model and the SmartPLS statistical tool.

The study findings indicate that behavioral intention is positively and significantly influenced by behavioral attitude, subjective norm and behavioral norm, but not by belonging. However, behavioral intention significantly and favorably influences word-of-mouth. When the indirect effect of study findings was analyzed, it was showcased that behavioral intention and attitude indirectly influence subjective norm and word-of-mouth communication, but belonging has no such effect.

The results suggest that businesses should focus on using local products as customers have a positive attitude toward them and provide customers with a sense of belonging to increase word-of-mouth communication. Additionally, the study highlights the importance of subjective norms in shaping customers' intentions and behavior toward local products.

The contribution of this article is valuable in terms of meeting this quest of visitors who have the motivation to introduce and experience the local culture, especially the Reasoned Action Theory of Word-of-Mouth communication approach of the customers, who play an essential role in the promotion and marketing of local restaurants selling local products, and to make a difference in their travels. Findings indicate that businesses should use local products, and customers need a sense of belonging. However, there is a subjective norm and attitude toward local products, and they should provide the necessary tendencies to gain a sense of belonging.

This study evaluates the impact of online menus and perceived convenience of online food ordering on consumer purchase intention and shows how a desire for food creates a relationship between an online menu and a customer's purchase intention. Suggestions for management are proposed to design an effective menu to improve business performance in the competitive market in Vietnam.

The paper follows a quantitative method. Quantitative research aims to analyze and critically evaluate the research question(s) to discover new factors.

Findings indicate a positive relationship between menu visual appeal (MV), menu informativeness (MI), desire for food (DF), the perceived convenience (PC) of ordering food online and intention to purchase (PI). The attractiveness of images and information is a significant factor affecting diners’ desire to eat, while the demand for food and the convenience of ordering food online are also factors affecting purchase intention.

The study confirms the importance of online menus to purchase intention. Economically, when supply and demand are reasonable, the market is stable and technology develops. In terms of social, hygiene, attractiveness and price factors, it is helpful to have an overview. Research is the premise for further studies with factors from menu to customer trust.

The study provides a solid foundation for further studies on restaurant menu elements as well as a new perspective on how restaurants improve their dishes.

This study aims to examine consumers’ responses to crowdsourcing campaigns in the request initiation stage using the signaling theory from economics. The purpose of the research is threefold. First, it provides a comprehensive classification of various task types within crowdsourcing. Second, it conceptualizes crowdsourcing announcements as signals of customer orientation and empirically tests the differential effects of the two most common crowdsourcing task types (product- and communication-related) on customer orientation perceptions. Third, it illuminates the downstream behavioral consequences of crowdsourcing campaign announcements.

The authors conducted secondary data analysis of 883 crowdsourcing campaigns (pilot study) to provide evidence on the differential effects of crowdsourcing task types. In addition, four laboratory experiments were conducted to test the theoretical arguments. To test the main effect of crowdsourcing task types, Study 1A (N = 252 MTurk workers) used a one-factor (product- vs communication-related crowdsourcing vs control) between-subject design, whereas Study 1B (N = 171 undergraduate students) used a 2 (task type: product- vs communication-related) by 2 (product category: restaurant vs fashion) between-subject design. Study 2 (N = 93 MTurk workers) explored the underlying mechanism using a one-factor (product- vs communication-related) between-subject design. Study 3 (N = 375 MTurk workers) investigated the boundary condition for the effect of task type with a 2 (task type: product- vs communication-related) by 3 (company credibility: low vs neutral vs high) between-subject design.

The pilot study provides evidence for the conceptualized typology and the differential effects of crowdsourcing task types. Study 1A reveals that product-related crowdsourcing tends to have a more substantial impact than communication-related crowdsourcing on how customer-oriented consumers perceive a company. Study 1B validates the results of Study 1A in a different product category and population sample. Study 2 shows that the differential customer-orientation effect is mediated by the perceived cost of implementing the crowdsourcing outcome and unravels the differences in consumers’ purchase and campaign participation intentions depending on task type. Study 3 highlights that the customer-orientation effect attenuates as company credibility increases.

This research contributes to the crowdsourcing literature by categorizing the various types of crowdsourcing campaigns companies undertake and revealing the differential impact of the different types of crowdsourcing campaigns on consumers’ perceptions and behavioral intentions. In doing so, this research converges two lines of consumer research on crowdsourcing, i.e. product- and communication-related crowdsourcing. The findings add to the debate over the returns from research and development (R&D) versus advertising and extend it from marketing strategy to crowdsourcing literature.

The findings highlight the importance of choosing specific task types for crowdsourcing and lead to practical recommendations on designing crowdsourcing campaigns to maximize their benefits to crowdsourcing brands.

To the best of the authors’ knowledge, this is the first study that differentiates crowdsourcing task types and compares their effectiveness from a consumer perspective.

This paper aims to illustrate the application and effectiveness of a marketing programme co-designed by supply- and demand-side stakeholders to reduce consumer food waste in restaurants.

This stakeholder-based marketing pilot study adopted the co-create, build and engage framework for programme design and implementation. Major stakeholders, interacting at the point-of-sale, participated in a series of focus groups, interviews and co-design. The research process informed the marketing mix, which aimed to provide value for all parties. The four-week pilot programme was delivered in a non-buffet-style commercial restaurant chain for 10 months. The amount of consumer food leftovers was measured and compared with pre-programme baseline data to evaluate programme effectiveness.

The results show that the marketing mix co-designed by restaurant stakeholders and consumers effectively reduced food waste by almost half in the pilot period. The profitability of the pilot restaurant increased as food costs decreased.

This research demonstrates how working with stakeholders from both the supply and demand sides can identify motivations and barriers. Insights gained in the research phase can inform the delivery of a marketing mix that reduces consumer food waste. This study demonstrates the marketing research, design, implementation and evaluation process for a marketing programme that reduced consumer food waste.

To effectively reduce consumer food waste, practitioners should not only focus on changing consumers’ behaviour. Co-designing solutions with food service stakeholders to address business and operation challenges is crucial to the attainment of a positive impact at the point-of-sale.

This research shows how marketing changes behaviour in individuals and business entities, contributing to positive environmental impact through waste reduction in the commercial food service sector.