ABSTRACT
The adaptation of halal food to Chinese food culture was investigated in a meta-analysis of this China e-commerce study. Indoctrination is a sociocultural transformation in the Coronavirus pandemic in which a community of people or an in-dividual integrates into a different culture or country by adopting the host culture's linguistic skills, social features, nutritional pat-terns, and the current growth of e-commerce consumption. We ap-ply a data-driven marketing approach and modify the STP model in marketing to analyze the product differentiation parameters ac-cording to the research. Consuming halal food prepared following Islamic standards is a religious dietary obligation imposed on all Muslims, regardless of where they reside or travel. In Arabic, the term 'halal food' refers to food that is legal and allowed to ingest. Among many other dietary requirements, Islamic tenets ban the consumption of porcine food items, dead animal meat, animal blood, and any quantity of alcohol. Islam and halal eating prac-tices were introduced to China in the early seventh century by Cen-tral Asians and Muslim missionaries traveling through the peri-lous ancient desert. Throughout its history, China has been a non-Muslim country, but halal food practice has been successfully assimilated and even flourished as a key component of contemporary Chinese cuisine culture. This paper addresses the two most significant variables that have contributed to the successful cultural as-similation of halal food into the new Chinese food culture in the digital era through key Chinese e-commerce sites. © 2022 IEEE.
ABSTRACT
This study aimed to design and test a COVID-19 surveillance system model for community-industry population. A prospective cohort study was conducted from May to December, 2020. Researchers designed a COVID-19 surveillance system and presented it to stakeholders from the community-industry setting in Lamphun and Chiang Mai provinces, Thailand. The model was adjusted following feedback and tested. The model was an Active surveillance for early Alert and rapid Action using Big data and mobile phone application technology for a Community-industry setting (3ABC model). The major components were active surveillance, community-based surveillance, event-based surveillance, and early warning and rapid response. A drive-thru testing unit was operated to enable early detection. Alerts and recommended action on individual and administrative levels were sent via an application and networks. In the testing of the model, risk assessment was initially conducted with regard to COVID-19 transmission in the factories. Researchers provided recommendations based on findings. The improvements included human resource management, systems, and structure. The 3ABC model work well as designed. The participants actively reported events daily including prevention and control activities, animal diseases (foot-and-mouth disease in buffalos and hog cholera), human diseases (dengue and chikungunya), and absent of COVID-19 outbreak. Only five quarantined COVID-19 cases whom were monitored. Daily reports of no abnormal event was also high (70.2% to 71.1%). It is practical and feasible to implement the 3ABC model in a community-industry setting. A further study for a longer period to verify its level of effectiveness should be done. © 2021. Author (s). This is an open access article distributed under the term of the Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution, and reproduction in any medium or format, as long as you give appropriate credit to the original author (s) and the source.