Food Delivery Research Articles

Understanding food delivery service customers’ switching behavior

Purpose Prompted by intense competition among providers of food delivery services, this study examines the behavior of customers using mobile applications. Specifically, based on a push-pull-mooring framework, this study aims to identify the key factors affecting customers’ switching intentions in the food delivery context. A push factor is assumed to drive customers away from an existing service provider due to dissatisfaction, while a pull element lures them to an alternative provider by supplying enhanced levels of enjoyment, usefulness and/or informativeness and mooring factors (i.e. affective commitment and perceived herd) help make these switching decisions. Design/methodology/approach Partial least squares structural equation modeling with SmartPLS was used because it is suited to predictive models and produces stringent assessments of measurement models using a variance-based approach. Data was collected through an online survey. Participants were 350 food delivery application (FDA) customers in the USA. Findings The results highlight the importance of a push factor (dissatisfaction with the present FDA) and a mooring factor (perceived herd) as determinants of customers’ perceptions of risk that can induce a decision to switch to another FDA. However, the pull factors of usefulness, enjoyment and information quality did not significantly influence switching behavior. Originality/value Many food delivery service providers now use mobile application technologies to provide their services. Such companies can use the factors that influence customer switching intentions identified in this study to control customers’ churn behavior by managing dissatisfied customers in the mobile context.

Integrated food delivery problem considering both single-order and multiple order deliveries

The global food delivery market is rapidly growing, and leading companies in Korea have recently introduced a single-order delivery service, wherein a courier picks up customers’ food and delivers it immediately without visiting other places. Although this delivery service is associated with a high delivery fee, it is popular among customers who prefer fresh and fast delivery, unlike multiple-order delivery services, which handle orders from several customers simultaneously. Nevertheless, the coexistence of both delivery services has led couriers to prefer single-order deliveries because they are more profitable, resulting in intensified competition among couriers. Furthermore, there are cases where the courier visits other restaurants or customers without immediately delivering food to customers who use the single-order delivery service, making it a multiple-order delivery service, which leads to customer dissatisfaction. To address these issues, this study proposes a mixed-integer linear programming model for optimizing order assignment and routing in an environment where both single-order and multiple-order deliveries coexist. The tabu search was used to solve medium-sized and large-sized problems, and several food delivery models were configured by referencing the operating methods of the platforms. Through experiments, we demonstrate that the proposed model is more efficient in properly delivering food to customers for both single and multiple orders than other food delivery models. We also analyzed the impact of various variables through a sensitivity analysis, providing insights into the platform.

Quantifying consumers’ cost-value trade-offs on on-demand food delivery services: Value-of-time framework and partitioned pricing

PurposeThis study aims to quantitatively characterize consumers' value-cost trade-offs in on-demand food delivery (ODFD) services. On the value side, the study endeavors to monetize the convenience value of ODFD with a Value-of-Time (VOT) framework, while on the cost side, this study investigates the implication of ODFD's partitioned pricing structure with the theoretical tenet of Attribution Theory. Design/methodology/approachA stated choice experiment is developed and distributed to an online panel in Singapore with 580 valid responses collected. The data is then analyzed with a mixed logit model. FindingsThe results show that cost, time, and health-related factors significantly influence consumers' dining channel choices. In terms of time, consumers' differentiated time sensitivities are revealed. Specifically, consumers are most sensitive to walking time, followed by waiting time at food establishments and at their own places. Also, the food type and dining locations affect consumers’ time perceptions. Regarding cost, consumers exhibit an inflated price sensitivity toward food premiums compared to delivery fees. Originality/valueThis study addresses the lack of quantitative investigations into the value-cost tradeoffs in ODFD services. ODFD's convenience values are quantified and monetized with a novel VOT-based framework. Besides, the study sheds light on the underexplored partitioner pricing scheme with the theoretical tenet of the Attribution Theory. Overall, the research provides behavioral insights to support practitioners' operational decision-making.

To Deliver or Not to Deliver: The Case For and Against Restaurant Delivery

Since the start of the COVID-19 pandemic, online food delivery has experienced significant growth. As consumer preferences continue to shift toward this new platform, it is crucial for restaurants to assess the benefits and risks associated with engaging in the delivery market. By synthesizing academic research and industry reports, this case highlights the associated benefits for restaurants including the extension of service capacity constraints, market growth, and ease of implementation. Additionally, risks are introduced including food quality control, profitability, production capacity constraints, and cannibalization. The topics are discussed and contrasted under the examples of a large service provider (Shake Shack) and smaller independent restaurant (EL Ideas). The case provides valuable insights regarding the opportunities and challenges of partnering with food delivery providers, enabling future restaurant managers to make informed decisions in this evolving market.

Degradation of paper-based boxes for food delivery in composting and anaerobic digestion tests

This study evaluated the fate of food delivery boxes when subjected to biological treatments, reproducing at the lab-scale the conditions of full-scale plants. Four paper-based boxes were composted: two made of paper only, one coupled with polylactic acid (PLA), and one with a barrier coating. One paper only box and the box with PLA were also investigated for their anaerobic degradability with biochemical methane potential (BMP) and semi-continuous tests. During composting, the boxes were not recognisable inside the compost after four (paper only boxes), eight (box with PLA), and twelve (box with barrier coating) weeks. In BMP tests, the paper only box showed a degradability similar to that of food waste (92 %), while the box with PLA degraded only at 76 %. Furthermore, undigested pieces of PLA were found in semi-continuous tests. Accordingly, paper resulted suitable for biological treatments, while the presence of PLA or other barrier coatings can be critical.

Online food delivery services and unceasing behavioural intention: An assessment for integrating expectation-confirmation and technology acceptance models

The coronavirus disease (COVID-19) quarantine restrictions led to significant changes in the food industry's delivery methods, with a notable rise in online food delivery services (OFDS). This increase necessitates a deeper understanding of the factors influencing the continued use of these services. This study investigates the relationships between perceived ease of use, perceived usefulness, satisfaction, confidence, trust, and continuous intention to use OFDS applications among young consumers in Kazakhstan. An integrated model based on expectation-confirmation and technology acceptance models, incorporating the habit of online shopping as a moderator, was used. Data was collected from 433 respondents with prior OFDS experience and analyzed using Smart PLS 4.0. The results show positive correlations between perceived ease of use, perceived usefulness, satisfaction, confidence, trust, and the continuous intention to use OFDS among young Kazakhstani consumers. Additionally, the study confirms the moderating role of online shopping habits in the relationship between satisfaction and trust and the continuous intention to use OFDS. These findings offer valuable insights for companies in the online food delivery sector, highlighting key factors that can enhance managerial and IT strategies to boost revenues and foster sustained use of OFDS applications.

Pengaruh Modal dan Penggunaan Online Food Delivery terhadap Pendapatan di CV. Fada Food

This study aims to evaluate how capital and utilization of online food delivery services affect CV Fada Food's revenue. This study applies a quantitative method using multiple linear regression analysis with the help of SPSS version 27 for Windows. The data analyzed came from CV Fada Food's financial transactions in the period 2021 to 2023. The results of the study show that capital has a positive and significant effect on CV Fada Food's revenue. The greater the amount of capital invested, the higher the income generated by the company. In addition, the use of online food delivery services also has a significant positive impact on revenue. By utilizing the food delivery application platform, CV Fada Food can increase customer reach and effectively increase their income.

A proximal policy optimization approach for food delivery problem with reassignment due to order cancellation

Unexpected cancellation of food delivery orders poses significant challenges to resource allocation planning and could lead to reduced revenue for service providers. This paper addresses this issue by developing an optimization framework that can reassign canceled orders to alternative customers to maximize net revenue and minimize resource wastage. The problem is formulated as a route-based Markov decision process, named the Dynamic Routing and Pricing Problem with Cancellation (DRPPC). A solution approach based on the proximal policy optimization strategy is introduced as a computationally effective way of solving the optimization problem using reinforcement learning techniques. Experimental results demonstrate that the proposed computational method outperforms selected benchmark approaches with higher revenue from various kinds of scenarios with uncertainties. This research advances the intersection of urban logistics and reinforcement learning, offering actionable strategies for enhanced operational resilience in food delivery service providers.

Characterizing the packaging waste generation patterns and carbon emissions of university delivery service

As the main consumer group for online shopping and ordering fast food, young people—particularly university students—have contributed to a substantial amount of packaging waste. In the present study, the material flow method was employed to quantify the generation and end-of-life flows of packaging waste from both the express delivery and food delivery sectors at universities in China. Moreover, this study takes reusable packaging materials for food delivery services as a case study to evaluate their environmental benefits through a simplified life cycle assessment approach. The results show that approximately 1.7 (±0.3) million metric tons and 123 (±1.0) kilo metric tons of packaging waste were generated from express delivery and food delivery services, respectively, for university students in 2021. Although reusable food packaging is more complex and costly than regular disposable food packaging is, our modeling results show that reusable food packaging has significant emission reduction benefits under the current practice of 63 cycles per year of actual operation at a specific university. The reusable packaging mode in universities is feasible from an environmental perspective; however, it faces significant challenges due to a few concerns among stakeholders, such as high costs and inadequate recycling supply systems.

“We are Like Little Elves who Never get Their Own Name”– Identity in Food Delivery Platform Work

“We are Like Little Elves who Never get Their Own Name”– Identity in Food Delivery Platform Work

Crafting Identities in Platform Work:Interactions and (Dis) Identification Among Food Delivery Riders

Crafting Identities in Platform Work:Interactions and (Dis) Identification Among Food Delivery Riders

‘Most Favored Nation’ Clauses in the Online Food Delivery Platform Market: Beyond Booking.com Cases

The COVID-19 pandemic catalyzed a transformative shift in the European food service industry, with local restaurants increasingly turning to online food delivery platforms (OFDPs) to sustain their operations during lockdowns. However, this symbiotic relationship has raised concerns regarding the prevalence of Most Favoured Nation clauses (MFNs) within contractual agreements between local restaurants and OFDPs These clauses, designed to ensure price parity across different sales channels, have sparked debates over their impact on competition and consumer welfare. This is due to their potential effect of hindering local restaurants’ ability to compete effectively, thus, consumers may face reduced price options and higher food costs. The Bundeskartellamt’s landmark decisions regarding MFNs in the online accommodation sector concerning Booking.com have provided initial guidance, but the application of this approach to OFDP markets remains complex. Against this backdrop, and following the reasoning laid down in a more recent approach from the Bundeskartellamt, we propose a systematic methodology for evaluating the effects of MFNs, taking as a starting point of analysis OFDP market conditions and business models. Ultimately, we aim to address the balance between positive and negative effects of usingMFNs byOFDPs to incentivize platform investment and protect the efficiencies passed on to consumers and local restaurants.

Customers’ emotional impact on star rating and thumbs-up behavior towards food delivery service Apps

This study explores the intricate relationship between emotional cues present in food delivery app reviews, normative ratings, and reader engagement. Utilizing lexicon-based unsupervised machine learning, our aim is to identify eight distinct emotional states within user reviews sourced from the Google Play Store. Our primary goal is to understand how reviewer star ratings impact reader engagement, particularly through thumbs-up reactions. By analyzing the influence of emotional expressions in user-generated content on review scores and subsequent reader engagement, we seek to provide insights into their complex interplay. Our methodology employs advanced machine learning techniques to uncover subtle emotional nuances within user-generated content, offering novel insights into their relationship. The findings reveal an inverse correlation between review length and positive sentiment, emphasizing the importance of concise feedback. Additionally, the study highlights the differential impact of emotional tones on review scores and reader engagement metrics. Surprisingly, user-assigned ratings negatively affect reader engagement, suggesting potential disparities between perceived quality and reader preferences. In summary, this study pioneers the use of advanced machine learning techniques to unravel the complex relationship between emotional cues in customer evaluations, normative ratings, and subsequent reader engagement within the food delivery app context.

Carbon emissions from urban takeaway delivery in China

Online food delivery has become a popular mode of urban food consumption in China as its underlying business mechanism, Online To Offline (O2O), gaining popularity. However, the environmental impacts of a rapidly expanding online food delivery industry and its potential to mitigate environmental burdens remained unexplored in China. Our research found that Chinese cities generated 1.67 MtCO2-equivalent (CO2e) from 13.07 billion times of deliveries in 2019, including transport and packaging. The transportation-related GHG emissions were 745 KtCO2e in 2019, with an average of 0.057 kg CO2e per order and an average of 0.011 kg CO2e per capita. These emissions have surged from 0.31 MtCO2e in 2014 to 2.74 MtCO2e in 2021. We predict that this figure will increase further to 5.94 MtCO2e by 2035. However, with a range of policies such as replacing motorcycles with electric bikes and optimizing traffic routes, it is possible to mitigate such GHG emissions by 4.39–10.97 MtCO2e between 2023 and 2035. These findings highlight the need for further research into the environmental impact of online food delivery and the potential for mitigating it.

Intention to use Online Food Delivery Services during the Covid-19 Pandemic in Malaysia

Intention to use Online Food Delivery Services during the Covid-19 Pandemic in Malaysia

Intention to use Online Food Delivery Services during the Covid-19 Pandemic in Malaysia

This paper aims to determine the behavioural intention of public use of online food delivery (OFD) services in Malaysia. A quantitative study was done through an online survey where respondents are within Malaysia with 526 respondents. Results revealed various push and pull factors affect the decisions of consumers' intention to use online food delivery services at an exploding rate. Therefore, this research is vital in providing the essential elements to food businesses in identifying the factors that lure consumers to order food through the online system. OFD services act as another source of revenue and a long-term marketing strategy for food businesses. This system moving forward also eases the life of busy city dwellers [20].

UNIVERSITY STUDENTS’ ONLINE FOOD DELIVERY (OFD) USAGE INTENTION: INVESTIGATING THE ROLE OF SENSORY MARKETING AND PERCEIVED BENEFITS

Background and Purpose: The increase of mobile phone usage in Malaysia had contributed to the increasing habit of purchasing food through online food delivery (OFD) service platforms. Sensory marketing is a conceptual strategy that helps to appeal to human five senses. It is utilized as promotion made on social media using ads or attractive photos in order to attract customers to order food through the social media platform. This study aims to investigate the role of sensory marketing (sight and touch) and perceived benefits (convenience and product variety) to predict university students’ online food delivery (OFD) usage intention. Methodology: Structural equation modelling is used to accomplish the objectives of this study with the analyses of 400 university students who were surveyed through Google form application. Findings: The findings concluded that both sensory marketing and perceived benefits influence university students’ OFD usage intention. The strongest predictor of OFD usage intention among students is ‘touch’ element representing sensory marketing followed by convenience (perceived benefits), product variety (perceived benefits) and sight (sensory marketing). Contributions: The findings contribute to the relevant literature by improving the knowledge of online food delivery (OFD) usage intention and it may be beneficial to the foodservice providers for continuous improvement of their business. Keywords: Sensory marketing, perceived benefits, online food delivery app. Cite as: Shun Han, K., Abdul Rais, A. R., Tamby Chik, C., & Jaafar, S. N. (2024). University students’ online food delivery (OFD) usage intention: Investigating the role of sensory marketing and perceived benefits. Journal of Nusantara Studies, 9(2), 297-317. http://dx.doi.org/10.24200/jonus.vol9iss2p297-317

Exploring the Influence of Social Media Marketing on Brand Trust, Brand Image, and Brand Loyalty for Fore Coffee

Indonesia's utilization of digital services such as mobile payments, paid digital content, online transportation, and food delivery has been amplified due to the rise in internet and smartphone usage. The digitalization of the food and beverage (F&B) industry has experienced significant growth since 2015, particularly accelerated by the COVID-19 pandemic. According to McKinsey's research conducted in 2020, there was a significant 34% surge in the number of individuals using food delivery services during the pandemic. Fore Coffee, a coffee startup established in 2018, employs digital marketing strategies to enhance sales and promote brand recognition. Fore Coffee has successfully pleased customers using social media and mobile applications. This study utilizes the concept of brand trust to investigate the impact of social media marketing on brand image and customer loyalty. Research utilizes PLS-SEM. A digital survey was distributed to a total of 301 individuals who are customers of Fore Coffee within the previous six-month period. Studies indicate that social media marketing has a positive and significant influence on brand trust, leading to a positive impact on brand image and customer loyalty. A well-executed digital marketing strategy has the potential to enhance brand trust, image, and loyalty Keywords: Brand Image; Brand Loyalty; Brand Trust; Social Media Marketing

Pengaruh Promosi dan Harga terhadap Keputusan Pembelian Ayam Penyet Nasi Tutug Oncom Setu Melalui Aplikasi Gofood

Tutug Oncom is a small restaurant that sells Tutug Oncom rice in the Bekasi area. This research aims to influence promotions and prices on purchasing decisions for Ayam Penyet Nasi Tutug Oncom via the Gofood application. Using the research method using the Partial Least Square (PLS) quantitative approach via SmartPLS 4.0, data from 100 respondents was analyzed to test the proposed hypothesis. The analysis results show that Gofood promotions, especially through advertising and price discounts, significantly influence purchasing decisions. This shows that effective promotional strategies can increase consumer interest in choosing Ayam Penyet Nasi Tutug Oncom via the Gofood platform. Furthermore, price factors also proved to be important, with price advantages and competitive pricing positively affecting purchase decisions. The managerial implications suggest that companies should consider relevant promotional strategies and competitive pricing to maximize product appeal in the online market. The study also reveals the dominant consumer profile, with the majority of respondents aged 21-25 years, mostly female, and predominantly students. These findings indicate that the younger generation, especially those actively using technology, are the primary target in digital marketing strategies employed by Gofood. This research not only provides insights into the factors influencing purchase decisions in the context of food delivery applications but also offers a foundation for further studies to explore other variables that may affect consumer preferences online.

Migrant workers within the platform assemblage: entwined temporalities of gig work and the border regime

ABSTRACT The temporal structuring of migrant gig workers’ work and lives has been insufficiently addressed in research. Drawing on multi-sited onlineoffline methodologies, including interviews with migrants working via location-based work platforms (cleaning, food delivery) in Finland, we propose the term platform assemblage to analyse the temporal entanglements of living labour, work platforms and the border regime. We argue that migrant gig workers’ entanglement in the platform assemblage engenders experiences of constraint, not only via formally weak labour market positions but also through the specific temporalities arising in the complex entwinement of algorithms, the varying digital platforms used, ratings, urban interferences, migratory status and the personal resources required to navigate these constraints. Discerning the relationship between migrants’ encounters with the temporal border regime, the temporal organisation of platform work, and migrants’ contestations over the dynamics of work, the article contributes to the emerging literature on migrant gig workers.