The proposed scientific article aims to analyze the application of Lean Six Sigma in the food industry. To this end, a detailed methodology has been designed that ranges from the selection of the works to the synthesis and presentation of the results obtained. The methodology is based on rigorous inclusion criteria to ensure the relevance and quality of the selected sources, including books, academic articles, theses, and other relevant documents. Through extensive searches of academic databases and other reliable sources, key works were identified that specifically address the implementation of Lean Six Sigma in the context of food production. Once the relevant papers were collected, a critical analysis was conducted to identify common themes, trends, and key findings. The works were classified according to their main focus, such as process improvement, waste reduction, supply chain optimization and food safety assurance. This categorization allowed the information to be organized in a coherent way and to facilitate the synthesis of the results. The results obtained were presented in a table that included details about each selected work, such as title, author, year of publication, abstract and links to the original source. This structured and rigorous approach provides a clear and comprehensive view of the topic, contributing to the advancement of knowledge in this area and offering practical guidance for practitioners and researchers interested in the application of Lean Six Sigma in the food industry. The literature on Lean Six Sigma in the food industry highlights its importance in improving efficiency, quality, and safety. Key recommendations include gradual implementation, appropriate training, focus on quality, and continuous improvement.

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.

Online shopping has eliminated the need to visit physical commercial centres. As a result, trips to these centres have shifted from primarily shopping-motives to leisure, companionship, and dining. The shifting in consumer behaviour is implicated in the growing spatial agglomeration of restaurants/cafes within commercial centres in European cities. Conversely, in southern cities, various casual restaurants/cafes also serve as leisure and companionship hubs. However, their spatial patterns are less explained. This article aims to elucidate the spatial pattern of these diverse restaurants/cafes in a typical southern city, Surabaya City. In this study, we employ the term ‘food services’ to encompass the various types of restaurants/cafes found in southern cities. We gather Points of Interest (POIs) data about food services via web scraping on Google Maps, then map out their spatial distribution across 116 spatial units of Surabaya City. Utilising k-means cluster analysis, we classify these 116 spatial units into six distinct clusters based on the composition of food service variants. Our findings show that City Centres and Sub-City Centres are locations for different types of restaurants/cafes. The City Centre is typically a location for fine dining restaurants and cafes, whereas Sub-City Centres are locations for fast casual dining and fast food restaurants. Cafes and fast food restaurants are centralised throughout downtown areas. Casual food service restaurants, such as casual style dining, coffee shops, and food stalls, are dispersed along business, residential zones, and periphery areas without intense domination of any specific variant.

This research aims to solve the research problems regarding the most important value of an object in the form of the wedangan phenomenon. This research objectives to expose the superiority of the communities’ food consumption tradition in the form of wedangan. This research belongs to a qualitative study and uses ethnomethodology as an initial approach. It is because the initial data findings are in the form of an indexical conversation that explicitly refers to the concept of wedangan. The concept refers to wedangan in real life, which is in the form of eating and drinking activities while chatting. The research findings are: 1) the most profound structure of wedangan’s tradition is food provision and food eating; 2) wedangan accommodates three forms (food stall, street food, and restaurant); 3) wedangan also accommodates three food values (delightful, useful, and meritorious); and 4) there is an egalitarian consumption pattern in wedangan, people regardless their social class visiting the same place, eat the same food, being simple and be ordinary (or usually we call it as food marriage). Wedangan is a social activity with advantages from a social, economic, and political perspective. Therefore, this phenomenon requires more serious attention from the government.

The rapid growth of e-commerce in South Africa has increased the demand for efficient last-mile delivery. Motorcycle delivery drivers play a crucial role in the last-mile delivery process to bridge the gap between retailers and consumers. However, these drivers face significant challenges that impact both logistical efficiency and their socio-economic well-being. This study critically analyzes media narratives on the safety and working conditions of motorcycle delivery drivers in the e-commerce sector in South Africa. The thematic analysis of newspaper articles identified recurring themes. This study reveals critical safety and labor vulnerabilities affecting motorcycle delivery drivers in South Africa’s e-commerce sector. Key findings include heightened risks of violence, hijackings, and road accidents, exacerbated by inadequate infrastructure and safety gear. Coupled with low wages, job insecurity, and limited benefits, these conditions expose drivers to significant precarity. Policy interventions are urgently needed for driver safety and sustainable logistics. By integrating insights from multiple disciplines, this study offers a comprehensive understanding of the complex challenges within this rapidly growing sector.

The article highlights Malaysia’s multicultural history, the advancement of Internet technology, and the worldwide appeal of Chinese food, all of which serve as a good basis for the project. This study focuses on Malaysian Chinese takeout systems. The research’s primary goals include developing new business options for the Chinese food sector, as well as enhancing customer happiness and efficiency of takeout systems. As a result, the project intended to create a Web-based system for managing several tasks associated with meal ordering by users. For the system development, an Object-Oriented System Development (OOSD) methodology was used, mostly with the Java programming language. Model-View-Control (MVC) framework was employed throughout development to improve system administration. Redis and HTTP session technologies were included for user login to increase system security. For database operations, MyBatis and MyBatis Plus were also employed to enhance ease and security. The system adheres to design principles and leverages technologies like ElementUI and jQuery to further fulfill this criterion to provide a user-friendly interface. The results of this study demonstrate significant improvements in the overall efficiency of the takeout process, leading to enhanced user experiences and greater customer satisfaction. In addition to streamlining operations, the system opens new avenues for the Malaysian Chinese food industry to capitalize on the growing demand for online food ordering. This research provides a solid foundation for future innovations in takeout systems and serves as a reference point for enhancing the Chinese gastronomy sector in a rapidly digitizing world.