ASEAS 17(2) | 187 Invisible Workers in Philippines’ Ghost Kitchens: Trends and Implications Daryl Cornella , Jay-R Manamtama , & Aaron Thamb* aPolytechnic University of the Philippines bUniversity of the Sunshine Coast, Australia *corresponding author: mtham@usc.edu.au Received: 24 February 2024 / Accepted: 21 September 2024 / Published: 28 October 2024 ► Cornell, D., Manamtam, J-R, & Tham, A. (2024). Invisible workers in Philippines’ ghost kitchens: Trends and implications. Advances in Southeast Asian Studies, 17(2), 187-200. This research workshop reports on employee relations within ghost kitchens, which are delivery-only food businesses. Surveys conducted with 125 ‘invisible’ ghost kitchen employees revealed that almost 70% of them had less than one year’s experience working in ghost kitchens. Yet, close to half could see themselves working in such environments for four years or more. Ghost kitchens also featured a small pool of less than four staff and a workforce aged 18-25. More than half of the respondents possessed undergraduate qualifications, and at least two-thirds of those surveyed were female. Overall, favorable working conditions, as evidenced by ghost kitchen employees, contribute to theoretical and managerial implications for existing and future ghost kitchen practices. Keywords: Cloud Kitchen; Digital Disruption; Hospitality Human Resources; Platform Economy; Virtual Kitchen  INTRODUCTION This research workshop focuses on one of the more recent developments in the form of a platform economy, characterized by economic transactions taking place entirely in a digital ecosystem (Farrell & Greig, 2016). Some scholars attach the term ‘gig economy’ to the platform economy, positioning the workforce in a highly precarious frame because they are contractors for service rather than full- time employees of the organizations concerned (Lin et al., 2023; Popan, 2024). In this vein, studies have examined the workforce from perspectives such as Uber and other meal-delivery riders within a hospitality context (Goods et al., 2019; Myhill et al., 2021), though the ‘invisible workers’ of ghost kitchens remain large- ly under-studied (El Hajal & Rowson, 2021). Ghost kitchens have been known in other contexts as cloud/virtual/dark kitchens and refer to delivery-only businesses where kitchen operations are not disclosed to customers (Ashton et al., 2023; Cai et al., 2022; Hakim et al., 2022). Research Workshop w w w .s ea s. at 1 0. 14 76 4/ 10 .A SE A S- 01 13 http://orcid.org/0000-0002-8461-4004 http://orcid.org/0000-0001-5772-3603 mailto:thithimadee.art%40mahidol.ac.th?subject= https://orcid.org/0000-0003-1408-392X mailto:mtham@usc.edu.au 188 | ASEAS 17(2) Invisible Workers in Philippines’ Ghost Kitchens Ghost kitchens operate on mobile applications (apps), whereby customers can select from a range of menus or cuisine brands and are taken by food delivery riders to their intended address (Chen & Hu, 2024; Klouvidaki et al., 2023). According to Howarth (2023), the ghost kitchen industry was reportedly worth US$58 billion and is antici- pated to grow to almost US$90 billion by 2026. Some studies have emerged to explore consumer motivations towards ghost kitchens (Leung et al., 2023; Recuero-Virto & Valilla-Arrospide, 2022; Shapiro, 2023) or why businesses operate such establishments (Fridayani et al., 2021; Kulshreshtha & Sharma, 2022). However, few studies have empirically analyzed ghost kitchen working conditions and employee welfare, with Giousmpasoglou et al. (2024) alleg- ing labor exploitation. Prompted by extant literature (or a lack thereof), the research questions are: • Who are these ghost kitchen employees? • What are these employees’ working environments? Understanding the perspectives of these ghost kitchen employees helps to elu- cidate greater insights into their work conditions and what may account for their loyalty to the business (or lack thereof). This research then addresses the gaps in extant literature that have called for more studies on the viewpoints of ghost kitchen employees (da Cunha et al., 2024; Rosette, 2024). LITERATURE REVIEW The meteoric rise of ghost kitchens can be broadly classified into two main themes – technological advancement and the COVID-19 pandemic. These broad themes provide the necessary backdrop to elucidate employee characteristics within ghost kitchens. Technological Advancement Technological advancement in terms of mobile connectivity has given rise to hospital- ity innovation, including online food delivery (Ardiansyahmiraja et al., 2024; Darekar et al., 2020). Ghost kitchens, in this space, allow for on-demand and a product/pro- cess focus where such establishments deliver items on their menu to their intended audiences and monitor trends and consumer preferences to reconfigure menus of interest (Choudhary, 2019; John, 2023). This mechanism reduces inefficiencies and potential food waste because orders are cooked on demand without significant stor- age requirements (Cai et al., 2022; Shroff et al., 2022). COVID-19 Pandemic The COVID-19 pandemic disrupted hospitality operations as many countries were compelled to halt dining-in opportunities for hospitality establishments (Kaavya & Andal, 2022; Ma et al., 2021). To arrest the financial and operating losses, ghost kitchens became popular in streamlining kitchen operations without having direct customer contact (Gonzalez-Aleu et al., 2022; Othman et al., 2021; Vu et al., 2023). ASEAS 17(2) | 189 Daryl Cornell, Jay-R Manamtam, & Aaron Tham YEAR AUTHOR(S) CONTEXT METHOD FINDINGS FUTURE STUDIES 2020 Upadhye & Sathe Indian ghost kitchen in Pune Case study on Swiggy ghost kitchen The ghost kitchen was located in an area that was conve- nient to service its intended customers Ghost kitchens would benefit from supporting a range of food delivery platforms and ensuring food and hygiene quality The strength of a ghost kitchen is its ability to have staff spe- cialize in tasks 2021 Othman et al. Customer usage of ghost kitchens in Malaysia 200 online surveys More than three in five respon- dents indicated that perceived control, convenience, and service fulfillment made them adopt ghost kitchens 2021 Wankhede et al. Ghost kitchen sustainabil- ity in Mumbai, India 40 online surveys Customers indicate they are likely to continue purchasing from ghost kitchens post- COVID-19 2022 Cai et al. US online food service customers 977 online surveys Personal and societal benefits develop trust in online food delivery, while societal risk reduces trust Customer familiarity with ghost kitchens and level of trust Perspectives from operators Cross-cultural insights 2022 Chatterjee et al. Ethical and sustainable perceptions of ghost kitchens in India Question- naires with 72 customers and 68 stakeholders (managers) Loss of human touch from traditional restaurants to on- demand ghost kitchens Men perceived ghost kitchens as being more cost-effective than women Ghost kitchens generate lower food waste Employee perspectives needed 2022 Deepak et al. Financial vi- ability of ghost kitchens in Hyderabad 12 interviews with ghost kitchen manag- ers Ghost kitchens offer a more at- tractive return on investment than traditional restaurant setups 2022; 2023 Hakim et al. Brazilian con- sumers 623 online questionnaires General public awareness of ghost kitchens is in its infancy Perceived food safety, trust in health systems, quality control, consumer experience, and solidarity with foodservice were positive predictors of consumption Consumer prefer- ences of ghost kitchen brands Food safety and hygiene in ghost kitchens vs full-service restaurants 2022 Kulshreshtha & Sharma Indian Gen Z ghost kitchen users 576 online questionnaires Purchase decisions were influenced by a combination of factors including food quality, marketing, convenience, price, hygiene and speed Sustainability of ghost kitchens Other cultural con- texts Gender and age variables 2022 Nigro et al. Ghost kitchen consumer intentions post COVID-19 596 online surveys with Italian consum- ers Social influence is a key driver of ghost kitchen adoption Hedonic value is not a main element of ghost kitchen adoption Country differences 190 | ASEAS 17(2) Invisible Workers in Philippines’ Ghost Kitchens Employees could also work with specializations of labor – focusing on a specific cuisine type, while delivery drivers took charge of reaching the intended addresses (Chern & Ahmad, 2020; Talamini et al., 2022). Despite these advantages, ghost kitchens are not without their critics. Altenried (2024) alluded to the precariousness of ghost kitchen employment conditions, 2022 Ongkasuwan et al. Ghost kitchen consumers and providers in Thailand, China and the USA 554 surveys with consum- ers and 18 interviews with providers Convergence towards a more efficient food delivery manage- ment system is advantageous Effect of artistic design for meals Use of robots for delivery Compliance with health regulations 2023 Ghazanfar et al. Ghost kitchen stakeholders in Dubai, UAE 7 interviews with executive chefs, restau- rant owners and a ghost kitchen opera- tor Ghost kitchens helped busi- nesses get through COVID-19 to save on rental spaces and overheads However, ghost kitchens are heavily reliant on third party applications and can come at a cost of profit margins Stakeholder analysis Other destinations 2023 Khan et al. Ghost kitchen business model in Dhaka, Bangladesh 168 online surveys with customers, 33 surveys and 6 focus groups with managers, and 3 interviews with industry experts Customers prefer ghost kitchens over traditional establishments as they are cheaper and faster, but food quality was perceived as higher in restaurant settings While ghost kitchens require less overhead costs to setup, they are not as flexible in terms of employee payroll systems, and overall, managers are undecided as to whether the ghost kitchen model will grow in the next few years Engagement with so- cial media and returns on investment with ghost kitchens Longitudinal studies on sustainable ghost kitchen operations 2023 Klouvidaki et al. Ghost kitchen consumers in Greece 1097 consum- ers Ghost kitchens offer a new innovative tool to engage with consumer expectations and demands Other contexts Longitudinal studies 2023 Pookulangara et al. US based ghost kitchen consumers 316 consumers Perceived innovativeness, price and hedonic motivations trig- gered attitudes towards ghost kitchen patronage Experimental studies Other contexts Post pandemic atti- tudes and preferences 2023 Vu et al. Ghost kitchen owners in Vietnam 20 owners and head chefs Ghost kitchens facilitated en- trepreneurial freedom to make decisions and adapt based on market preferences Ghost kitchens enabled the development of customer- centric brands Future developments call for investment into training and development of staff and processes Longitudinal studies Cross-cultural percep- tions 2024 Leung et al. Ghost kitchen consumers in the US 487 consumers External attribution and ethnic cuisine strongly influence consumption patterns Comparison between chain and independent owned ghost kitchens Consumer needs in terms of future dining behavior Table 1. Empirical studies on ghost kitchens (compiled by authors) ASEAS 17(2) | 191 Daryl Cornell, Jay-R Manamtam, & Aaron Tham where exploitation, wage theft, and work contracts are under intense scrutiny. Several scholars (Aiswarya & Ramasundaram, 2024; Ghosh & Reddy, 2021; Wrycza & Maslankowski, 2020) called out how ghost kitchens have shifted socio-cultural prac- tices of home cooking and dining out, which may inadvertently create cultures of convenience. Ashton et al. (2023) and Ghazanfar et al. (2023) further problematize how ghost kitchens can result in business dilemmas of gaining new markets but los- ing control of customer interactions. Amidst this backdrop, 17 empirical studies have emerged to paint a more nuanced picture of ghost kitchens, as depicted in Table 1. Importantly, these papers reveal how ghost kitchens have become more sophisticated and reflect a growing adoption of different business models catering to diverse mar- ket segments (Hakim et al., 2023). However, as Chatterjee et al. (2022) postulated, very little has been empirically revealed about employees in ghost kitchens and their employment conditions and futures in these facilities. This is important to address as very little is known about their plight and circumstances, especially with the global rise of ghost kitchen mod- els. This knowledge gap justifies undertaking research in this space to uncover employee sentiments and experiences in working within ghost kitchen environ- ments to advance theory and practice in this space. METHOD The paper utilized quantitative research approaches to provide a systematic approach to answer the research questions. By employing online surveys and statistical analysis techniques, the researchers collected and analyzed numerical data that offered valu- able insights into the experiences and perspectives of ghost kitchen employees in the Philippines. Qualitative data was not considered feasible due to the data collection undertaken during the pandemic, limiting opportunities to conduct interviews or focus groups with participants working various shifts and unavailable to meet out- side work hours. The survey design was informed by the work of other scholars (Md Fadzil & Che Azmi, 2022; Wu et al., 2019), as well as direct answers to profile these ‘invisible’ workers. The Philippines was chosen as the context for investigation as it was the country that exhibited the fastest-growing food delivery market in Southeast Asia, worth an estimated US$8 billion in 2025 (Abudheen, 2023). As data collection occurred whilst the COVID-19 pandemic was still raging, online surveys were the most realistic and safe option for both the research team and respondents. Following a call for par- ticipation through the researchers’ networks and on social media sites related to the Filipino hospitality workforce, 125 completed surveys were received in October 2022. Statistical software and techniques such as path analysis were adopted in this research using SPSS to investigate patterns of effect within the variables. Moreover, WARP-PLS and AMOS were employed in this study since they looked at how the components directly affected the outcomes. The software's ability to handle complex models with both reflective and formative indicators proved invaluable in assessing these components’ direct and indirect effects on each other. WARP PLS facilitated the examination of path coefficients, the significance of relationships, and the overall model fit, providing a comprehensive understanding of the factors influencing the 192 | ASEAS 17(2) Invisible Workers in Philippines’ Ghost Kitchens experiences and perceptions of ghost kitchen employees. Through the use of WARP PLS, the study established a strong theoretical foundation and contributed valuable insights into ghost kitchens and gig economy research. KMO (Kaiser-Meyer-Olkin) and Bartlett's test of sphericity were employed in this study to assess the suitability of the data for factor analysis. These statistical tests are crucial in determining if the variables under consideration are suitable for dimension reduction techniques like factor analysis. Hypotheses were derived from the current body of work surrounding ghost kitch- ens, particularly from the perspectives of employees. These hypotheses sought to expand on knowledge regarding employee experiences, satisfaction, ghost kitchen loyalty, and outlook on individual likelihood to perceive desirable futures working in this sector. These hypotheses are therefore structured to help address the research questions of interest. RESULTS Table 2 shows the breakdown of the respondents who had completed the survey. 1. Do you work in a cloud/ghost kitchen based on the definition above? f % 20. How many employees usually work with you during each shift? f % Yes 112 89.6 1-4 98 78.4 No 13 10.4 5-9 17 13.6 2. How long have you been working in a cloud/ghost kitchen? 10 or more 10 8 1-6 months 61 48.8 21. How many hours do you work during each shift? 7-12 months 15 12 1-4 47 37.6 More than a year 49 39.2 5-8 62 49.6 3. Before the cloud/ghost kitchen, did you have any prior experience working in a kitchen or hospitality setting? 9 or more 16 12.8 Yes 73 58.4 22. Do you consider your cloud/ghost kitchen accessible (e.g. easy to get to)? No 52 41.6 Yes 114 92.68 4. How many years of kitchen/hospitality experience did you have prior to the cloud/ ghost kitchen? No 9 7.32 Less than a year 87 69.6 23. What is your gender? 1-4 years 24 19.2 Male 42 33.6 5-9 years 9 7.2 Female 82 65.6 10 years or more 5 4 Non-binary 1 0.8 16. How long do you see yourself working in the cloud/ghost kitchen for? 24. What is your income level per month? 1-6 months 23 18.4 Less than 2,500 Pesos 25 20 7-12 months 15 12 Between 2,501 and 5,000 Pesos 33 26.4 1-3 years 29 23.2 Between 5,001 and 7,500 Pesos 27 21.6 4 years or more 58 46.4 7,501 Pesos or others 40 32 17. Would you recommend this cloud/ghost kitchen to others? 25. What is your age group? Yes 120 96.8 18-25 83 66.4 No 4 3.23 26-35 24 19.2 ASEAS 17(2) | 193 Daryl Cornell, Jay-R Manamtam, & Aaron Tham Table 3 includes the correlation matrix of items 6-15 in the cloud/ghost kitchen. The intercorrelations of items 6, 7, 8, and 9 exceed 0.30, while the intercorrelations of items 10, 11, 12, 13, 14, and 15 exceed 0.40. 18. Would you work for another cloud/ghost kitchen? 36-45 15 12 Yes 73 60.8 46-55 3 2.4 No 46 38.3 26. What is your highest qualification? Not Sure 1 0.8 Junior High School 5 4 19. Is your cloud/ghost kitchen part of a wider franchise? Senior High School 26 20.8 Yes 32 25.6 University or College Undergraduate De- gree 70 56 No 67 53.6 University or College Postgraduate Degree 21 16.8 Not Sure 26 20.8 Vocational 3 2.4 Table 2. Profile of respondents (compiled by authors) Item 6 Item 7 Item 8 Item 9 Item 10 Item 11 Item 12 Item 13 Item 14 Item 6 1.00 Item 7 0.55 1.00 Item 8 0.39 0.55 1.00 Item 9 0.40 0.42 0.52 1.00 Item 10 0.34 0.44 0.65 0.56 1.00 Item 11 0.30 0.37 0.49 0.33 0.42 1.00 Item 12 0.22 0.13 0.61 0.40 0.63 0.47 1.00 Item 13 0.17 0.36 0.45 0.36 0.49 0.55 0.47 1.00 Item 14 0.32 0.48 0.49 0.36 0.51 0.44 0.514 0.56 1.00 Item 15 0.29 0.41 0.45 0.29 0.54 0.50 0.592 0.59 0.72 Table 3. Correlation Matrix of 10 items in the cloud/ghost kitchen (compiled by authors) Table 4 revealed the Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy, Bartlett’s test of sphericity, and rotated component matrix. The KMO value of 0.875 indicates that the degree of common variance is meritorious. Bartlett’s test was KMO AND BARTLETT’S TEST ROTATED COMPONENT MATRIX Kaiser-Meyer-Olkin (KMO) 0.879 Items Component Bartlett’s Test of Sphe- ricity Chi-Square 607.941 1 2 Df 45 Item 6 0.835 Sig. Less than 0.001 Item 7 0.739 Item 8 0.549 0.588 Item 9 0.676 Item 10 0.641 Item 11 0.656 Item 12 0.737 Item 13 0.799 Item 14 0.745 Item 15 0.829 Table 4. KMO Test, Bartlett’s Test, and Rotated Component Matrix (compiled by authors) 194 | ASEAS 17(2) Invisible Workers in Philippines’ Ghost Kitchens significant (less than 0.05), suggesting that the correlation matrix is not an identity matrix. Both the KMO and Bartlett’s tests revealed that it is preferable to conduct fac- tor analysis [9]. The rotated component matrix showed that items 6, 7, 8, and 9 have the highest loading from component 2, while items 10, 11, 12, 13, 14, and 15 have the highest loading from component 1. Table 5 shows the indicator loading of all constructs/items, as well as the aver- age variance extracted, composite reliability, and Cronbach alpha measurement. In addition, the AVE of components 2 and 1 are 0.603 and 0.616, respectively. The out- comes are all acceptable, as all the extracted average variances were greater than 0.5. Given that all the composite reliability values are greater than 0.7 for all the items, the instrument has good to excellent consistency in terms of component 2 (CR = 0.858; CA = 0.780) and component 1 (CR = 0.906; CA = 0.874). STATEMENT Mean SD AVE CR CA Component 2 0.603 0.858 0.780 6. To what extent has working at a cloud/ghost kitchen im- proved your income level? 3.73 1.02 7. To what extent has working at a cloud/ghost kitchen im- proved your job security? 3.82 0.94 8. To what extent has working at a cloud/ghost kitchen im- proved your working conditions? 3.98 0.9 9. To what extent has working at a cloud/ghost kitchen been more flexible in terms of working hours? 4.14 0.82 Component 1 0.616 0.906 0.874 10. To what extent has working at a cloud/ghost kitchen improved kitchen efficiency? 4.18 0.77 11. To what extent has working at a cloud/ghost kitchen reduced gender pay gaps? 3.92 0.92 12. To what extent has working at a cloud/ghost kitchen improved kitchen cleanliness? 4.19 0.93 13. To what extent has working at a cloud/ghost kitchen made hospitality work easier (e.g. 2t having to deal with customers)? 4.14 0.87 14. To what extent has working at a cloud/ghost kitchen improved employee morale? 4.1 0.87 15. To what extent has working at a cloud/ghost kitchen enhanced organisational culture? 4.07 0.85 AVE: Average Variances Extracted; CR: Composite Reliability; CA: Cronbach Alpha. Table 5. Reliability and Validity Tests of the Constructs (compiled by authors) Table 6 presents the HTMT ratios. Since the HTMT value is 0.793 (<0.85), which is best, it passes the HTMT ratios. The following findings were drawn from the data after it had been collected, cleaned, and examined. The study used Partial Least Square - Structural Equation Modeling (PLS-SEM) to examine the relationships between the two components. Table 7 represents the model fit and quality indices of the model. It depicts that APC = 0.661 (p < 0.001), ARS = 0.437 (p < 0.001), AARS = 0.432 (p < 0.001). All p-values ASEAS 17(2) | 195 Daryl Cornell, Jay-R Manamtam, & Aaron Tham of the APC, ARS, and AARS should be less than 0.05 to have a good quality fit (Kock, 2015). Thus, the model provides a more comprehensive and explanatory prediction of the latent variables (Kock & Lynn, 2012). The Tenenhaus Good of Fit (GoF) value is 0.516, which is greater than the threshold of ≥ 0.36, hence having a higher explana- tory power. Table 8 shows the direct and indirect effects of the PLS Model. Based on the find- ings, the hypothesis was confirmed. The path coefficient of H1 is 0.661 with an effect size of f 2= 0.076. Based on Cohen’s effect size, the hypothesis falls under a large effect size. Figure 1 shows the PLS path model of components 2 and 1 with path coefficients. It shows that component 2 has a direct effect on component 1 (β = 0.661; p < 0.01). Table 9 shows the regression path coefficient and p-values of component 2. The paths from item 6 to item 9 are significant. COMPONENT 2 COMPONENT 1 Component 2 Component 1 0.793 Note: For HTMT, good if < 0.90, best if < 0.85 Table 6. KMO Test, Bartlett’s Test, and Rotated Component Matrix (compiled by authors) INDEX COEFFICIENT APC 0.661, P<0.001 ARS 0.437, P<0.001 AARS 0.432, P<0.001 AFVIF 1.755, acceptable if ≤ 5, ideally ≤ 3.3 Tenehaus GoF 0.516, small ≥ 0.1, medium ≥ 0.25, large ≥ 0.36 Table 7. Model Fit and Quality (compiled by authors) Hypothesis Path Coefficient p-value Standard Error Effect Size (f 2) Decision Direct Effects H1. Comp2 ► Comp1 0.661 <0.001 0.076 0.437 Supported Note: f 2is the Cohen's (1988) effect size: 0.02=small, 0.15=medium, 0.35=large. Table 8. Direct Effects of the PLS Model (Component 2 to Component 1) (compiled by authors) Figure 1. Conceptual model of components 1 and 2 with parameter estimates (compiled by authors) 196 | ASEAS 17(2) Invisible Workers in Philippines’ Ghost Kitchens Figure 2 shows the PLS path model of component 2 with path coefficients. The critical ratios of H2, H3, H4, H5, and H6 are 4.78, 5.87, 3.02, 5.19, and 4.56 respectively. Table 10 shows the goodness of fit of component 2 and fit indices. The Chi-square value is 0.255 which is less than twice the degrees of freedom. The p-value is 0.614 which is between 0.05 to 1.00. The RMSEA is less than 0.05, the GFI is 0.999 which is between 0.95 and 1.00 and the CFI is 1.00. All values of different fit measures suggest a good fit model. HYPOTHESES PATH COEFFICIENT S.E. C.R. P - VALUE DECISION H2: Item 6 ? Item 9 0.318 0.066 4.783 < 0.001 Supported H3: Item 6 ? Item 7 0.426 0.073 5.870 < 0.001 Supported H4: Item 9 ? Item 7 0.273 0.090 3.023 0.003 Supported H5: Item 7 ? Item 8 0.381 0.073 5.193 < 0.001 Supported H6: Item 9 ? Item 8 0.385 0.084 4.561 < 0.001 Supported Table 9. Regression Path Coefficient of Component 2 (compiled by authors) Figure 2. Cloud Ghost Kitchen model of component 2 with parameter estimates (compiled by authors) GOODNESS OF FIT VALUES REMARKS Chi square 0.255 Good fit p-value 0.614 Good fit Chi square/df 0.255 Good fit RMSEA 0.000 Good fit GFI 0.999 Good fit CFI 1.000 Good fit Table 10. Goodness of fit and fit indices of Component 2 (compiled by authors) DISCUSSION Each of the hypotheses presented in Figure 2 was supported by the data, indicating that working in a ghost kitchen was largely perceived as a positive experience by the participants in the study. Compared to the work of Giousmpasoglou et al. (2024), ASEAS 17(2) | 197 Daryl Cornell, Jay-R Manamtam, & Aaron Tham ghost kitchen work was not perceived to be exploitative but instead as a sound work- ing environment for employees, at least in the case of the Filipino sample in this study. Correspondingly, this resulted in stronger word-of-mouth recommendations for ghost kitchens as employers of choice. The hypothesis of employee loyalty was also supported in this study. The benefits of the study from employee loyalty can lead to higher employee retention rates and reduced labor hiring costs. This may be attributed to the specialization of labor evident in ghost kitchens, thereby reducing employee requirements to handle numerous work tasks, as well as customer inter- actions that would be present in a full-service restaurant (Tayeb, 2021). Contrary to the findings of Giousmpasoglou et al. (2024), this research suggests that employees in developing nations like the Philippines may gravitate toward working in ghost kitchens because they may be afforded higher wages and operating conditions as compared to other kitchens, prompted by the COVID-19 pandemic. Crucially, this outcome triggers further studies to unpack whether such assertions are consistent elsewhere, especially in countries of the Global South. The research findings can inform subsequent management decisions (Deepak et al., 2022; Kulshreshtha & Sharma, 2022). For example, employers may benefit from individualized onboarding and training programs designed to capitalize on the enthu- siasm and new perspectives of this young workforce. Similarly, this may also advocate increased worker rights, unionization efforts, or other forms of worker empowerment as a response to the challenges posed by labor exploitation in platform-based econo- mies. It could discuss ongoing efforts to address gaps in ghost kitchen operations, such as layout, task specialization, cleanliness, and employee health and well-being. CONCLUSION This research workshop highlights employee relations within the context of ghost kitchens. The major findings include the fact that many employees in ghost kitchens are new to this type of employment, with less than a year of experience. However, many stated that they intend to continue working in such situations for at least four years. The study unveils a positive correlation between the adoption of ghost kitch- ens by young employees as hospitality workplaces of choice. This research workshop adds to our understanding of how ghost kitchens work and how they might be efficiently handled within the broader context of the hos- pitality industry. It interprets the experiences and perspectives of ‘invisible’ staff working behind the scenes to prepare food. From a research standpoint, this study enhances current information on ghost kitchens. It is an acknowledged limitation that this research offers insights from 125 employees surveyed solely in the context of the Philippines. Future researchers can use this information to further examine and comprehend the mechanics of ghost kitchen operations elsewhere, especially from a qualitative perspective which could offer more diverse perspectives. Further insights into the demographic and educational backgrounds of employ- ees in this sector are provided. Theoretical contributions in the form of decent work and employee relations in a ghost kitchen setting provide more nuanced insights, addressing gaps in existing literature, which has predominantly focused on questions of business models or customer experiences. From a managerial perspective, current 198 | ASEAS 17(2) Invisible Workers in Philippines’ Ghost Kitchens and future ghost kitchen operations should emphasize the positive attributes and favorable working conditions that can attract a wider pool of potential employees. This study provides a foundation for future research into ghost kitchen employee relations, particularly data about the demographics, perspectives, and experiences of people employed in such establishments, and calls for more empirical investigation in this field. Future studies should explore and analyze ghost kitchens’ staff relations in more detail. 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Labor control in the gig economy: Evidence from Uber in China. Journal of Industrial Relations, 61(4), 574–596. ABOUT THE AUTHORS Dr. Daryl Cornell is currently the Chief of the Center for Research Dissemination and Linkages of the Research Management Office of the Polytechnic University of the Philippines. Dr. Cornell is the Founding President of the Philippine Association of Researchers for Tourism and Hospitality, Inc. the first and only professional organization in the Philippines devoted solely to advocating tourism and hospitality research. ► Contact: darylace.cornell@gmail.com Jay-R Manamtam is a Research Coordinator at the Polytechnic University of the Philip- pines, College of Education Faculty. He has a Master of Arts in Education with a major in Mathematics Education. ► Contact: jamanamtam@pup.edu.ph Dr Aaron Tham is the Subject Component Lead in Tourism, Leisure and Events at the University of the Sunshine Coast. He is a Senior Fellow of the Higher Education Academy and Emerald Publishing’s first Ambassador based in Australia. Aaron is also the Managing Editor of the International Journal of Hospitality and Tourism Administration. ► Contact: mtham@usc.edu.au DISCLOSURE The authors declare no conflict of interest.