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The rapid growth in volume and value of on-demand restaurant food delivery, accelerated by the COVID-19 pandemic, is causing a paradigm shift in the food service sector. However, there is a lack of hospitality management research into this emerging phenomenon. To address this gap, this paper defines and develops a novel conceptual model and typology and proposes a research agenda for ghost production in the context of food service.

This paper uses the Servuction model to explore, define and model the radical separation between food service production sites, points of sale and consumer interaction from the perspective of on-demand restaurant food delivery. A novel typology is developed and illustrated with eight industry examples from the UK and an accompanying cost benefit analysis. Future research priorities are identified.

In the hospitality literature, little attention has been paid to changes on-demand restaurant food delivery brings to production and business models of food service organisations, resulting in significant gaps between food service practice and theory. The knock-on effects to stakeholders include increased convenience for customers, uncertain employment status of riders and, for restaurants, striking a balance between capturing new markets and losing control of the customer. Additionally, for aggregators, there is a lack of profitability in existing models, despite holding the balance of power (and data).

The concept of “ghost production” and its associated typology is novel and offers a contribution to hospitality management literature by defining the term, scope and scale of this new phenomenon. Practical implications are proposed.

The emergence of dark kitchens in the restaurant industry is a contemporary phenomenon, arising most recently in the context of the so-called gig economy. This new business model flourished during the coronavirus disease 2019 (COVID-19) pandemic on a global scale. Despite dark kitchens' popularity, considerable negative publicity exists in the news related to poor working conditions. To highlight this new phenomenon, this paper explores the existing literature on worker exploitation in dark kitchens in the context of the gig economy.

A systematic literature review of hospitality and tourism databases generated 1,430 articles, of which 18 met the authors' inclusion criteria for the final analysis, and 1,030 anecdotal sources, of which 47 were included. Thematic analysis was used to identify the key themes and summarise the findings to be used for further studies.

The popularity of dark kitchens as a business model is premised on the fact that dark kitchens' dramatically reduces the operational cost and increases productivity. On the other hand, the working conditions and contractual agreements of the gig workers in dark kitchens raise several questions from operational, legal and ethical perspective. These poor working conditions create the conditions for worker exploitation and further damage the sector's image.

This study advocates that companies and managers are responsible for implementing and monitoring fair working conditions in dark kitchens. The existence of poor working conditions increases employee turnover and, overall, affects the industry's reputation.

This explorative study provides insights into the working conditions and contractual agreements in dark kitchens. Currently, there is no other study (empirical or conceptual) to shed light on the working practices. The authors hope this study will trigger further discussion and empirical research in this field.

Online food delivery applications (OFDAs) provide an expedient platform, and consumers’ access to food has been drastically altered, especially during and after the COVID-19 pandemic. This study aimed to completely explore the attributes that influence consumers' purchase intention and how an app's aesthetics can evoke feelings that predict continuous usage intentions for OFDAs. The food industry, especially restaurants, heavily relies on mobile technology to facilitate critical online food delivery during the pandemic crisis.

The data for this study are gathered from 477 food consumers located in the federal capital territory (FCT) of Islamabad, Pakistan, through convenient sampling by developing a self-administrated online survey. SmartPLS is used for structural equation modeling to test the proposed research model and perform bootstrapping and algorithmic analysis.

Our findings revealed that perceived value positively predicted consumers’ purchase intentions. Moreover, perceived value mediates the association of information quality, familiarity, time-saving, usability and reputation with purchase intentions and fear of COVID-19 moderates the relationship between perceived value and purchase intention.

This research work has significant implications for researchers, web developers, app designers, delivery services, restaurants and other enterprises as it demonstrates the importance of aesthetically pleasing OFDAs in eliciting positive emotions and bolstering consumers’ intentions to continue using the app for efficient food delivery services.

This study expanded the application of the technology acceptance model (TAM) and attention, interest, desire and action (AIDA) by examining consumers’ purchase intentions in the context of OFDAs. Further, the successful utilization of TAM enhanced the understanding of consumer perceptions and behavioral intentions about the usage of OFDAs.

The food industry is continuously developing its online services called food delivery applications (FDAs). This study aims to evaluate FDA's importance–performance and identify strategies to maximize its potential gains from a business partner's perspective.

Data are collected from 208 FDA partners in Indonesia. Importance–performance analysis (IPA) is applied to evaluate the FDA feature and extended the theory of potential gain in customer value (PGCV) to achieve potential gains from FDA business partners.

This study provides a clear and measurable direction for future research to develop FDA performance. Owning customer data, revenue sharing and competitive advantage are the most potential gains from joining the FDA from the business partner perspective.

The respondents are restaurants from the micro, small, and medium enterprises levels. Further research should involve middle to upper level restaurants to discover all business partners' perceptions. This will be very helpful for FDA providers interested in improving the best performance for all their partners.

FDA providers must focus on improving and maintaining the features of owning customer data, revenue sharing, competitive advantage, stable terms and conditions, customer interface, building customer loyalty, online presence, user credit rating, promotion and offers, delivery service and sales enhancement to increase consumer satisfaction and meet the expectations desired by business partners.

This research provides a meaningful theoretical foundation for future work. It extends the theory of PGCV using the value of a partner perspective as a substitute for customer value; hence, the authors call it a potential gain in partner value.

This paper investigates the logistics management in the e-grocery sector. It contrasts the key issues faced by practitioners and the topics addressed in the academic literature, to identify potential misalignments between research and practice and propose avenues for future efforts.

This work adopts a twofold methodological approach. From an academic perspective, a systematic literature review (SLR) is performed to define the topics addressed so far by scholars when analysing e-grocery logistics. From a managerial perspective, a Delphi study is accomplished to identify the most significant issues faced by logistics practitioners in the e-grocery context and the associated significance.

The study develops a conceptual framework, identifying and mapping the 9 main logistics challenges for e-grocery along 4 clusters, in the light of a logistics-related revision of the SCOR model: distribution network design (area to be served, infrastructures), order fulfilment process (picking, order storage, consolidation, delivery), logistics-related choices from other domains (product range, stock-out management) and automation. These elements are discussed along three dimensions: criticalities, basic and advanced/automation-based solutions. Finally, the main gaps are identified – in terms of both under-investigated topics (order storage and stock-out management) and investigated topics needing further research (picking and automation) – and research questions and hypotheses are outlined.

This paper provides a threefold contribution, revolving around the developed framework. First, it investigates the state of the art about e-grocery logistics, classifying the addressed themes. Second, it explores the main issues e-grocery introduces for logistics practitioners. Third, it contrasts the two outcomes, identifying the misalignment between research and practice, and accordingly, proposing research directions.

This study aims to establish a comprehensive model integrating variables from the updated unified theory of acceptance and use of technology (UTAUT), expectation-confirmation model (ECM) and trust to determine what factors influence consumers’ decision to continue using food delivery apps (FDA) after the COVID-19 outbreak in Taiwan.

Data was collected from 350 respondents living in Taiwan via Line using a Google Forms link. A total of 333 valid responses were analyzed after 17 invalid questionnaires were eliminated. To test the suggested study paradigm, partial least squares-structural equation modeling was used as the data analysis approach.

The results indicate FDA users’ continuance intention (CI) is directly significantly affected by performance expectancy, satisfaction and habit. All the constructs of the updated UTAUT theory, confirmation and trust significantly influence the satisfaction of FDA, and users’ satisfaction significantly positively impacts users’ CI.

Although consumers’ intentions toward FDA have previously been the topic of research, there is a paucity of literature that discusses the connections between the variables that influence FDA users’ CI after the COVID-19 pandemic in Taiwan. By focusing on the relationships between the multiple antecedents of FDA users’ CI, this study contributes to reducing the existing literature gap. Explanation surrounding the elements influencing FDA users’ CI is provided by examining several aspects of FDA usage, including technological and psychological postadoption issues.

本研究试图建立一个综合模型, 整合了来自统一接受和使用科技理论（UTAUT）、期望-确认模型（ECM）和信任等变量, 以确定影响消费者在COVID-19疫情爆发后继续使用食品外卖应用(FDA)的因素。

本研究针对台湾的居民通过Line平台使用Google Forms链接收集了350份问卷数据, 经过筛选后得到333份有效回复。为了验证所提出的研究范式, 本研究采用了PLS-SEM作为数据分析方法。

结果表明, FDA用户的继续使用意图受到性能预期、满意度和习惯的直接显著影响。UTAUT理论、期望确认和信任显著影响FDA用户的满意度, 而用户的满意度对用户的继续使用意图产生积极影响。

尽管消费者对FDA的意向不是新的研究的主题, 但在讨论COVID-19疫情后影响FDA用户继续使用意图的变量之间的关系方面, 文献中存在不足。通过探索FDA用户继续使用意图的多个前因关系, 本研究有助于弥补现有文献的空白。通过考察FDA使用的技术和心理因素等多个方面, 本研究提供了解释影响FDA用户继续使用意图的论述。

Pay-what-you-want (PWYW) is a pricing strategy implemented in a variety of settings like supermarkets and museums, in which consumers determine the price they are willing to pay for a product or service based on their perceived utility. The authors propose an analytical model to investigate the impact of PWYW delivery pricing on the online food delivery (OFD) platforms.

Using a game-theoretic model, the authors characterize the equilibrium as a function of the platform's average delivery cost and the consumer's social preferences parameters like fairness and reciprocity. The authors derive the parametric conditions under which PWYW generates higher profits for the platform compared to the traditional pay-as-asked delivery pricing.

For the PWYW strategy to be profitable, the average delivery cost to the platform should be low. Therefore, OFD platform managers should focus on reducing delivery costs. The authors also identify the feasible region in which the platform managers need to maintain the consumer's social preferences.

Under PWYW, the authors recommend that the platform managers impose a minimum delivery fee which consumers can use as a benchmark to minimize zero delivery fee payments and consumers' free-riding tendencies simultaneously. This allows OFD platforms to extract online orders from highly price-conscious consumers.

This is one of the first studies to explore the innovative application of PWYW to a particular segment of delivery pricing in OFD platforms. The authors establish that the overall consumer surplus and social welfare are higher under the PWYW strategy, forming a solid ground for its implementation in OFD platforms.

Food service establishments and online food delivery companies use a revenue share model based on a commission rate. Because of the asymmetry of bargaining power, many food service establishments are vulnerable to a high commission rate. What is missing in the ongoing discussion about the revenue share model is the perspective of food consumers, who are the third party in the multi-sided market.

Within a willingness-to-pay (WTP) framework, we study if food consumers have preferences for the commission rate charged by food delivery companies to food service establishments. With 456 random consumers in the United States, we conduct a controlled experiment in which information is used as treatment in two groups. In the first group, the provided information only relates to the revenue share model (i.e. economic). In the second group, participants also received information about price control initiatives (i.e. economic and political).

Based on WTP-space mixed logit model results, there is a significant effect of information on preferences for the commission rate. While participants in the control group exhibited no aversion to the commission rate, participants who received treatment had a significant and negative WTP. The magnitude of the effect is estimated at -$1.08 for participants in the first treatment and -$2.28 for participants in the second treatment.

To date there is no applied research on the preferences of consumers in the online food order and delivery industry with respect to upstream conditions (i.e. commission rates).

From the signaling theory perspective, the current study explores various drivers of brand transparency and its effect on users' interactions with food delivery apps.

First, a set of precursors of brand transparency of food delivery apps from focus group discussions was identified. Next, an integrated model tests the impact of brand transparency, perceived risk and brand trust on users' ordering frequency. Data collected from 522 users were analyzed using the partial least squares structural equation modeling method.

The outcomes showed the effectiveness of brand communications as the strongest indicator of brand transparency. Moreover, brand transparency favorably influences users' brand trust and ordering intention and negatively influences perceived risk. Hygiene rating attenuates the adverse effects of perceived risk.

The current study is a pioneering attempt that offers ways for online food delivery providers to build brand transparency, lessen users' risk perceptions and foster greater use of apps in the post-pandemic scenario.

The COVID-19 pandemic has resulted in a brand-new phenomenon in customer consumption patterns. This resulted from heightened health awareness brought on by the COVID-19 epidemic. There is a dearth of appropriate health psychology perspectives in the existing study examining the effect of COVID-19 on consumers’ use of crowdsourced logistics (CL) platforms. In order to provide unique and thorough insights into how consumer health concerns can affect consumers’ subjective views and their decisions to use CL, this study combines the health belief model and the technology acceptance model.

Five hundred valid responses from an online survey that was created and administered in Singapore were analysed using structural equation modelling.

The findings show that all of the suggested constructs have a favourable influence on consumers’ intentions to use CL. The suggested model also demonstrates high explanatory power, with perceived usefulness serving as the primary driver, followed by perceived ease of use and self-efficacy.

The study advances previous academic research on CL and offers guidance to CL companies and lawmakers for promoting sustainable and secured last-mile delivery.