Online Food Delivery Platforms Research Articles

Choice architecture promotes sustainable choices in online food-delivery apps

Abstract Greenhouse gas emissions from the food system constitute about one-third of the global total, hence mitigation in this sphere of human activity is a vital goal for research and policy. This study empirically tests the effectiveness of different interventions to reduce the carbon footprint of food choices made on food-delivery apps, using an incentive-compatible online randomised controlled trial with 4,008 participants. The experiment utilized an interactive web platform that mimics popular online food-delivery platforms (such as Just Eat) and included three treatment conditions: a sign-posted meat tax, a carbon-footprint label, and a choice-architecture intervention that changed the order of the menu so that the lowest carbon-impact restaurants and dishes were presented first. Results show that only the choice-architecture nudge significantly reduced the average meal carbon footprint—by 0.3 kg/CO2e per order (12%), driven by a 5.6 percentage point (13%) reduction in high-carbon meal choices. Moreover, we find evidence of significant health and well-being co-benefits. Menu repositioning resulted in the average meal order having greater nutritional value and fewer calories, whilst significantly increasing self-reported satisfaction with the meal choice. Simple back-of-the-envelope calculations suggest that menu repositioning would be a highly cost-effective policy instrument if implemented at scale, with the return on investment expected to be in the range of £1.28 to £3.85 per metric ton of avoided CO2 emissions, depending on implementation costs.

Do calorie labels change energy purchased in a simulated online food delivery platform? A multi-arm randomised controlled trial

BackgroundAs rates of obesity and overweight continue to increase in the UK, calorie labels have been introduced on menus as a policy option to provide information to consumers on the energy content of foods and to enable informed choices. This study tested whether the addition of calorie labels to items in a simulated food delivery platform may reduce the energy content of items selected.MethodsUK adults (n = 8,780) who used food delivery platforms were asked to use the simulated platform as they would in real life to order a meal for themselves. Participants were randomly allocated to a control condition (no calorie labels) or to one of seven intervention groups: (1) large size calorie labels adjacent to the price (LP), (2) large size label adjacent to the product name (LN), (3) small label adjacent to price (SP), (4) small label adjacent to product name (SN), (5) LP with a calorie label switch-off filter (LP + Off), (6) LP with a switch-on filter (LP + On), or, (7) LP with a summary label of the total basket energy content (LP + Sum). Regression analysis assessed the impact of calorie labels on energy content of foods selected compared to the control condition.ResultsThe mean energy selected in the control condition was 1408 kcal (95%CI: 93, 2719). There was a statistically significant reduction in mean energy selected in five of the seven intervention trial arms (LN labels (-60 kcal, 95%CI: -111, -6), SN (-73, 95%CI: -125, -19), LP + Off (-110, 95%CI: -161, -57), LP + On (-109, 95%CI: -159, -57), LP + Sum (-85 kcal, 95%CI: -137, -30). There was no evidence the other two conditions (LP (-33, 95%CI: -88, 24) and SP (-52, 95%CI: -105, 2)) differed from control. There was no evidence of an effect of any intervention when the analysis was restricted to participants who were overweight or obese.ConclusionAdding calorie labels to food items in a simulated online food delivery platform reduced the energy content of foods selected in five out of seven labelling scenarios. This study provides useful information to inform the implementation of these labels in a food delivery platform context.

A study on comparative analysis of zomato and swiggy based on consumer preference in Karaikudi

This study presents a comparative analysis of consumer preferences between two leading online food delivery platforms, Zomato and Swiggy. In an era marked by the rapid expansion of e-commerce and the increasing popularity of online food delivery services, understanding consumer behavior and preferences is crucial for businesses to remain competitive. Through a survey-based approach, data was collected from a diverse sample of consumers, encompassing various demographics and geographic locations. The study investigates user demographics, usage patterns, satisfaction levels, preferences, and factors influencing the choice between Zomato and Swiggy. Statistical analysis techniques, including descriptive statistics and correlation analysis, were employed to analyze the data and identify patterns and trends. The findings reveal insights into user satisfaction with different aspects of the platforms, such as user interface, delivery time, food quality, and customer service. Furthermore, the study examines the factors influencing consumers' decisions, such as pricing, promotions, restaurant selection, delivery reliability, and app features. A comparative analysis between Zomato and Swiggy provides valuable insights into the strengths and weaknesses of each platform, aiding in strategic decision-making and service enhancement. The implications of this study extend to both Zomato and Swiggy, as well as other stakeholders in the online food delivery market, offering actionable insights to improve customer satisfaction and gain a competitive edge.

“Online Cloud Kitchen”: A Virtual Kitchen

Abstract— The food industry has undergone significant transformations in recent years, with the emergence of cloud kitchens presenting a novel approach to food production and delivery. This research paper explores the concept of a cloud kitchen website that facilitates collaboration between various restaurants and offers two distinct modules: a user module for ordering and a comprehensive admin module for managing operations. Through an examination of industry trends, technological advancements, and case studies, this paper elucidates the potential of such a platform to revolutionize the food service sector, enhance customer experience, and streamline business operations. The food industry has witnessed a profound evolution in recent years, driven by technological advancements and shifting consumer preferences. Central to this transformation is the rise of cloud kitchens, innovative culinary hubs designed for efficient food production and delivery. This research paper explores the concept of a cloud kitchen website that not only serves as a platform for ordering food but also fosters collaboration between diverse restaurants, thereby expanding menu offerings and enriching the culinary experience for consumers. The study examines the intersection of cloud kitchen models, online food delivery platforms, and restaurant collaboration strategies to elucidate the potential of such a platform in revolutionizing the food service sector. Through a comprehensive analysis of industry trends, technological frameworks, and case studies, this paper seeks to provide actionable insights for entrepreneurs, food service professionals, and technology enthusiasts interested in harnessing the power of digital innovation to drive growth and innovation in the food industry. Keywords – Cloud kitchen, Ghost kitchen, Remote kitchen, Digital kitchen, Kitchen as a service (KaaS), Delivery-only kitchen, Centralized kitchen

Beyond convenience: exploring the determinants of continuance usage intentions in online food delivery services in Vietnam

This study examines the factors influencing continuance usage intentions in Vietnam’s online food delivery (OFD) market, using the Unified Theory of Acceptance and Use of Technology (UTAUT) with health consciousness as a moderator. The research identifies that performance expectancy, social influence, and facilitating conditions are significant determinants of continuance usage intentions, whereas effort expectancy shows a minor role. The analysis highlights health consciousness’s critical role in moderating the effects of PE and SI on usage intentions, revealing that a higher level of health awareness leads to more stringent evaluations of OFD services. These insights suggest that OFD service adoption in Vietnam is greatly influenced by how well services align with health-centric consumer preferences. The findings advocate for OFD platforms to adapt their strategies to meet the health-oriented demands of the market, emphasizing quality and transparency. This research contributes to understanding technology acceptance by highlighting the complex relationship between traditional service evaluation metrics and individual health values in influencing consumer behavior in a rapidly digitizing economy.

Pricing, channel design, and platform operations with buy-online-and-pick-up-in-store in online food delivery market

Omnichannel selling has gradually become popular in recent years, and the booming online food delivery (OFD) industry is no exception. Buy online and pick up in-store (BOPS) is regarded as the most important omnichannel fulfilment strategy. In this paper, we establish a stylised model to analyse the effects of BOPS on customer purchases and merchant profitability in the OFD market. We also examine merchants’ pricing and channel design strategies and the operational management of OFD platforms. We consider two merchant segments: online-only merchants who sell products only online and omni-merchants who sell products both online and offline. Interestingly, we find that BOPS helps online-only merchants expand market coverage, but does not necessarily increase omni-merchants’ sales depending on the delivery time and delivery service fee. Furthermore, online-only merchants should always implement BOPS, while omni-merchants should be more cautious about implementing BOPS because it may hurt their profits. In addition, the OFD platform charges a higher delivery service fee under certain conditions to react to merchants’ strategic adoption of BOPS. Finally, the adoption of BOPS may benefit merchants, customers, and platforms simultaneously. Therefore, BOPS may alleviate the contradictions among players in the OFD market.

Consumers’ Trust in Sharing Economy Peer-To-Peer Platforms: A Case Study of Online Food Delivery in Hanoi, Vietnam

Purpose: The purpose of this study is to the influence of trust on consumers’ transactional intention within a P2P sharing platform focusing on consumers who used OFD in Hanoi, Vietnam. Design/methodology/approach: A structured questionnaire is developed in a Google Form and distributed mainly through web-based and telephone-based platforms. In total, 240 valid responses were collected from Hanoi. To ensure the study's reliability and representativeness while minimizing bias, a convenience sampling method is employed, considering the demographic distribution of consumers across different age groups, genders, occupations, income levels, and various online food delivery platforms, income, frequency of consumption, and average expense. Analytical techniques included descriptive statistics, Cronbach’s Alpha reliability testing, and multiple regression analysis. Results and discussions: Findings revealed that four of the seven factors examined exerted a significant positive impact on Consumers’ Intention to Transact: "Consumer’s Trust in supplying Peer’s Integrity”, "Consumer's Trust in Products Ability”, "Consumer’s Trust in supplying Peer’s Benevolence”, and "Consumer’s Trust in Platform’s Integrity”. Conversely, while “Consumer’s Trust in supplying Peer’s Ability”, “Consumer’s Trust in Platforms Ability”, and “Consumer’s Trust in Platform’s Benevolence” do influence ‘Customers’ Intention to Transact’, their effect lacks statistical significance. Research Implications: This research sheds light on Vietnam's Sharing Economy, showcasing its transformative impact and governmental support. It focuses on the developing OFD sector, highlighting its rapid growth and significance. By adopting a trust-based research model, the study offers insights into consumer behavior within OFD platforms, contributing to the understanding of trust dynamics. Originality/Value: The research provides a theoretical foundation for understanding trust's role in shaping consumer behavior and transactional intentions, laying the groundwork for empirical research and practical applications. Practically, the study offers actionable insights for policymakers and industry players. It emphasizes the importance of integrity, reliability, and effective communication in building consumer trust.

IJCM_173A: A Cross-Sectional study to determine the role of social media influencers and online food delivery platforms as a risk factor for obesity among adults in Rural Perambalur

Background: Overweight and obesity are defined as abnormal or excessive fat accumulation that presents a risk to health. Around 2.8 million people dying each year as a result of being overweight or obese. The Time spend on social media and other online platforms has remarkably increased and also the prevalence of Noncommunicable disease. The Food related decisions influenced by social media has detrimental effects on the health. Objectives: 1. To assess the role of social media influencers and online food delivery platforms on BMI among adults of Perambalur 2. To determine the association between social media influencers and online food delivery platforms with obesity Methodology: We conducted a cross-sectional study in 399 adults of Perambalur district from March 2023 – May 2023. Consent was obtained. A Semi-structured self-reported questionnaire was used to collect socio-demographic, second section consist of impact of social media influencers on food consumption and third section consist of questions related to food ordering and online food delivery app usage. The collected data were analyzed using SPSS Version 23. Results: There is a significant association between people who use food delivery apps in higher frequency and obesity. 53.3% of people who are obese have higher frequency of usage of food delivery apps. There is a significant association between usage of social media and obesity. 21.7% of people who are obese have higher usage of social media. Conclusion: The increasing usage of social media and online food delivery platforms has lead to easy access to foods and an increase in prevalence of obesity and other medical complications. So proper recommendations should be made to prevent the younger generations from such diseases.

An Empirical Study of The Factors Affecting University Students’ Satisfaction Towards Foodpanda Mobile Application

Foodpanda is a well-known online food delivery platform. Foodpanda has evolved to be a popular option for individuals looking for simple and convenient food delivery services, particularly university students. The objectives of this study are to provide novel insights and investigate what factors influence university students' satisfaction with the Foodpanda mobile application through the proposed research model. Precisely, the objective of this article is to examine the relationship between information quality, system quality, price, perceived convenience, delivery experience, and customer satisfaction. The results of this study aim to guide Foodpanda managers in ensuring a high degree of customer satisfaction and retention, as customer satisfaction is critical to a company's success. This study will use a quantitative method to obtain data from university students by administering a survey. SPSS software will be used to analyze the collected data. Based on the findings, it is anticipated that the five investigated factors will have significant effects on customer satisfaction.

The impact of the collaborative consumption triangle on purchasing intentions within online food delivery platforms

PurposeThis study adopted the collaborative consumption triangle to explore the influence of online food delivery platforms (OFDP) on consumer purchase intentions. It investigates the effects of restaurants' corporate social responsibility (CSR) practices, individuals' food neophilic tendencies (FNT), and platforms' perceived benefits on purchase intention within OFDP. Furthermore, the study analyses differences in consumers' pro-environmental behaviour (PEB) on OFDP.Design/methodology/approachThe 497 participants conducted a web-based self-completion survey, using structural equation modelling to analyse the path structure of consumer purchasing intention. Furthermore, differences in PEB among OFDP consumers were compared through multigroup analysis.FindingsThe findings indicate that CSR influences the perceived value of sustainability and that the perceived value of sustainability influences purchase intention. Additionally, the influence of the perceived value of sustainability on purchase intention is more pronounced among consumers with low PEB compared to those with high PEB.Research limitations/implicationsThe findings may not be generalisable to other countries due to cultural differences, CSR policies, and strategies for promoting sustainable development.Social implicationsThe study provides valuable contributions related to (1) restaurants increasing their revenue and meeting their long-term sustainable development goals; (2) providing reusable containers policy and reusable containers policy and category tags for restaurants within OFDP.Originality/valueThis study is a pioneering work examining factors influencing purchase intentions within OFDP from the tripartite collaborative consumption perspective post-COVID-19 and focuses on the differences in PEB concerning OFDP.

Market Thickness in Online Food Delivery Platforms: The Impact of Food Processing Times

Problem definition: Online food delivery (OFD) platforms have witnessed rapid global expansion, partly driven by shifts in consumer behavior during the COVID-19 pandemic. These platforms enable customers to order food conveniently from a diverse array of restaurants through their mobile phones. A core functionality of these platforms is the algorithmic matching of drivers to food orders, which is the focus of our study as we aim to optimize this driver-order matching process. Methodology/results: We formulate real-time matching algorithms that take into account uncertain food processing times to strategically “delay” the assignment of drivers to orders. This intentional delay is designed to create a “thicker” marketplace, increasing the availability of both drivers and orders. Our algorithms use machine learning techniques to predict food processing times, and the dispatching of drivers is subsequently determined by balancing costs for idle driver waiting and for late deliveries. In scenarios with a single order in isolation, we show that the optimal policy adopts a threshold structure. Building on this insight, we propose a new k-level thickening policy with driving time limits for the general case of multiple orders. This policy postpones the assignment of drivers until a maximum of k suitable matching options are available. We evaluate our policy using a simplified model and identify several analytical properties, including the quasi-convexity of total costs in relation to market thickness, indicating the optimality of an intermediate level of market thickness. Numerical experiments with real data from Meituan show that our policy can yield a 54% reduction in total costs compared with existing policies. Managerial implications: Our study reveals that incorporating food processing times into the dispatch algorithm remarkably improves the efficacy of driver assignment. Our policy enables the platform to control two vital market parameters of real-time matching decisions: the number of drivers available to pick up and deliver an order promptly, and their proximity to the restaurant. Based on these two parameters, our algorithm matches drivers with orders in real time, offering significant managerial implications. Funding: This research is supported by the Ministry of Education, Singapore, under its 2019 Academic Research Fund Tier 3 grant call [Award ref: MOE-2019-T3-1-010]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2021.0354 .

The effect of short-form video content, speed, and proportion on visual attention and subjective perception in online food delivery menu interfaces

Given the rising popularity of utilizing short-form videos as visual cues, employing short-form videos to showcase food visual information in online food delivery menu interfaces could be a promising approach. However, it remains unclear about the effect of short-form video attributes on visual attention and perception of online food delivery consumers. In an experimental study with 36 participants, we combined eye-tracking technology and a perceived quality scale to assess consumers’ visual attention and subjective perception while they performed simulated ordering tasks on designed menu interfaces featuring different video contents, speeds, and proportions. Our results indicated that videos showcasing food tasting and food plating garnered more frequent visual attention and better ordering experience, respectively. Conversely, videos showcasing food cooking led to higher cognitive effort and received worse assessment. Furthermore, we found no significant evidence linking faster video speeds to increased cognitive effort, despite a slightly longer fixation duration in fast-speed videos. Besides, large video formats attracted more visual attention and created better user experiences compared to small formats, with medium formats also performing well in terms of subjective perception. These insights shed light on the optimal strategies for implementing short-form video presentations on online food delivery platforms, thus contributing to the development of user-friendly online menu interfaces for consumers.

Algorithmic control and gig workers’ facades of conformity: A work stress perspective

I examined the relationship between algorithmic control and gig workers’ facades of conformity by investigating the underlying mechanism. Drawing on the challenge???hindrance stress model, I explored the mediating role of challenge stress and hindrance stress in this relationship. Then, by using data collected from an online food delivery platform in China, I demonstrated that hindrance stress positively mediated the relationship between algorithmic control and facades of conformity, but the mediating effect of challenge stress was not significant. This study contributes to the emerging research field of algorithmic control by not only empirically examining its effect on gig workers’ psychological and behavioral outcomes, but also exploring the underlying mechanisms between algorithmic control and gig workers’ facades of conformity. It offers a reference point and guidance for managers of gig economy enterprises.

Online food delivery – easy access to food/meal order vs. limited access to food information

Online food delivery (OFD) platforms are very popular. More and more consumers use them to order meals. The market of OFD is growing very fast. It is a very comfortable way of ordering food and offers access to many restaurants at the same time. However, important disadvantages were identified about the access to food information. Five most popular OFD platforms in Poland were chosen and three most popular meals. Then the access to basic food information was revised (firstly allergens as it is a legal requirement and also ingredients or nutritional value). Lack of information was indicated for each platform and meal. On the basis of the legal requirements of food labelling and the revision of the OFD platforms offers of the most popular meals in Poland, it was shown that there is a big gap in the full access to food information. OFD platforms inform only about the food allergens or do not include any information about them. Consumer also do not have access to the full list of ingredients or the nutritional value. It shows the lack of equal access to food information to consumers who order meals in this way, and also may cause some health problems. These health problems may by caused by the consumption of food containing allergens without knowing about it and also by the highest than accepted fat or salt daily intake.

Fairness, profits and social welfare: the implications of pay-what-you-want in online food delivery

PurposePay-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.Design/methodology/approachUsing 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.FindingsFor 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.Practical implicationsUnder 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.Originality/valueThis 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.

Investigating the consumption behavior of young adults using online food delivery platforms during the COVID-19 pandemic

PurposeOnline food delivery has been prevalent in recent years worldwide, especially during the COVID-19 pandemic, and people's consumption behaviors have changed significantly. This study aims to investigate the consumption behavior of young adults using online food delivery platforms during the COVID-19 pandemic and focuses on the dominant factors influencing their decision to use online food delivery platforms.Design/methodology/approachSemi-structured interviews including 14 young adults aged 18–25 living in Hong Kong were conducted to collect data about their perspectives on online food delivery platforms in five areas. This research adopted the stimulus-organism-response model (S-O-R model) to analyze how the factors influence young adult users' loyalty and satisfaction with online food delivery platforms.FindingsThematic analyses revealed that young adults were attracted to online food delivery platforms for their numerous benefits. They had a high frequency of usage and significant spending. Usability, usefulness, satisfaction and loyalty influenced young adults' behaviors on online food delivery platforms. Participants were overall satisfied with their experiences, but platforms still had room for improvement.Originality/valueFew prior studies investigated the factors affecting the consumer experience and behavioral intention of online food delivery for young adults in Asia. This study contributes to understanding young adults' experiences and problems with online food delivery platforms. It provides practical insights for system engineers and designers to improve the current services and for the governments to enhance the existing regulatory loopholes.

An analysis of the factors influencing sustainable online food delivery

ABSTRACT There is a need to incorporate Sustainability in Online Food Delivery (OFD) as the industry has witnessed a boom due to increased bandwidth and network capabilities. The COVID-19 pandemic also has contributed immensely to the acceleration of the growth of this industry. The OFD players move in unsustainable directions to extract maximum profits. This research aims to identify the factors that act as barriers across Triple Bottom Line (TBL) dimensions viz. Economic, Environmental, and Social, influencing Sustainability and mitigating them. The tools used in this research are the Analytical Hierarchy Process (AHP), Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), Interpretive Structural Modelling (ISM) followed by Confirmatory Factor Analysis (CFA). AHP and TOPSIS were used to identify each factor’s criteria weights and rank the OFD platforms in terms of the pillars of Sustainability. ISM helped to find the contextual relationship between the factors and identify the most dominant ones. The data validation based on loadings of factors, convergent and discriminant validities were done. The rise of OFD platforms is inevitable; thus, inculcating sustainable practices in this industry is pivotal. However, a few research works focus on all the pillars of Sustainability, i.e. the TBL dimensions, for the OFD platforms. The results of this study can be used by various cloud kitchens and potential startups in the field to successfully understand the factors that either help maintain or disrupt Sustainability in the OFD industry.

Enhance understandings of Online Food Delivery's service quality with online reviews

This research presents an integrative approach, leveraging large-scale user-generated content (online reviews) to decipher consumers' quality perceptions in the burgeoning Online Food Delivery (OFD) sector. Utilizing the advanced BERTopic machine learning algorithm, we first qualitatively identify key service topics (qualities) pertaining to consumers’ OFD experience. Different from prior studies that overlook the synergies between cutting-edge machine learning and traditional methods, our findings are reflected against current scales established with traditional methods such as interviews and surveys. This practice allows us to highlight several topics overlooked by existing framework, such as corporate social responsibility, and identify low-importance service dimensions like personalization experience. Following the narrative analysis, an importance-performance analysis is undertaken to discern the priority of quality improvement for OFD platforms. Collectively, our insights offer pivotal theoretical and practical implications for practitioners and researchers in the OFD domain. Besides, our integrative approach balances theoretical development and practical applicability and can be readily extended to wider service scenarios.

Dinner at Your Doorstep: Service Innovation via the Gig Economy on Food Delivery Platforms

Despite the rapid growth of online food delivery (OFD) market, the impact of its three-sided nature—encompassing consumers, restaurants, and gig drivers—on incentives and payoffs remains unclear compared to the traditional two-sided model. This study examines how OFD platforms make optimal choices in a competitive environment involving pricing and service quality. The analysis reveals that insights from two-sided platforms don’t seamlessly translate to OFD markets. The triad nature of OFD can either dampen or heighten price competition in the buyer-seller market, altering subsidization dynamics for platforms. While conventional platforms suffer from negative network effects due to participation pressure, OFD platforms can adapt service strategies to mitigate this. However, introducing gig labor might not always benefit OFD platforms as it could trigger a prisoner’s dilemma situation by empowering competing platforms. The study underscores the dependence of platform strategies on network effects’ strength. As the gig economy rises, the employment status of gig workers garners controversy. The study demonstrates that implementing minimum wage regulations, while benefiting gig drivers, might diminish societal welfare. These findings offer guidance to policymakers aiming to balance gig workers’ interests with overall societal concerns.

SU-ISU BERKAITAN EKONOMI GIG DI JEPUN: ANALISIS LAPORAN AKHBAR

The global COVID-19 pandemic has transformed the media landscape in Japan, as news coverage that previously focused on the preparation for the Tokyo 2020 Olympics has shifted towards pandemic-related issues. Increased news reports on current pandemic-related issues, including those related to gig economy workers, have emerged. Social restrictions and the rise in online activities have driven the growth of the gig economy in Japan, which was initially needed to address the imbalance in talent supply and demand, along with a declining young population. However, a lack of legal oversight has led to various issues, ultimately resulting in the formation of labor unions demanding job justice for gig workers. Previous studies have been conducted on gig workers, such as labor injustices and proposals for regulating labor standards like collective bargaining, but there is still a lack of research exploring media reporting on the gig economy in Japan. Therefore, this study aims to identify current issues related to the gig economy in Japan, focusing on online food delivery platform workers through media coverage analysis. Data was collected from the online news archive of Asahi Shimbun from February 2021 to December 2022 using the search terms "gig economy" and "uber eats." The research findings were obtained through content analysis conducted with the assistance of Leximancer software. It was found that Asahi Shimbun's news reporting on the gig economy during the COVID-19 pandemic tended to be more negative in sentiment than positive. Negative sentiment emerged due to prominent reports of dissatisfaction among gig workers with the Uber Eats Japan food delivery service company, primarily stemming from changes in the delivery compensation system. This study is expected to contribute to the understanding of gig economy issues as portrayed in the media, serving as a guide for policymakers, industry stakeholders, and labor unions to improve the quality of gig work in Japan and globally.