ABSTRACT
The COVID-19 outbreak has heavily influenced the way many businesses operate across all sectors linked to both changes in the consumer behavior, social-distancing restrictions and also the availability of resources and services (inc. public services) for businesses. These restrictions have influenced also the work of enterprises in the sector of bioeconomy – producers, processors and distributors of manufactured goods like food, clothing or home goods and other bio-based sectors both in the stages of primary production and processing and distribution. This study aims to assess the digitalisation process of the enterprises in the bioeconomy sector, the enterprise`s motivation for digitalisation and the impact of COVID-19 to the digitalisation of enterprises. It analyses the results of a survey carried out in Latvia in 2 phases – in 2020 and 2021 of entrepreneurs and employees of the enterprises working in the sector of bioeconomy, which allows to identify the digitalisation tools used by these enterprises and their motivation in moving towards the digital transformation. © 2022 International Multidisciplinary Scientific Geoconference. All rights reserved.
ABSTRACT
After the occurrence of the COVID-19, preventing cross infection has become a top priority. Therefore, it is proposed to use robots to replace people to distribute anti epidemic materials, so as to reduce human contact. By planning the trajectory of the robot in advance, and using mechanical arms and claws to achieve accurate grasp and delivery of anti epidemic materials, it can carry out material distribution in the isolated inpatient department, and can independently locate and deliver products, goods, etc. in a complex environment. It has strong cargo carrying capacity, and has the dual functions of traditional delivery robots and indoor delivery services. Its use can greatly reduce the infection rate in the epidemic and deliver materials in time. © 2022 IEEE.
ABSTRACT
Emergencies, such as pandemics (e.g., COVID-19), warrant urgent production and distribution of goods under disrupted supply chain conditions. An innovative logistics solution to meet the urgent demand during emergencies could be the factory-in-a-box manufacturing concept. The factory-in-a-box manufacturing concept deploys vehicles to transport containers that are used to install production modules (i.e., factories). The vehicles travel to customer locations and perform on-site production. Factory-in-a-box supply chain optimization is associated with a wide array of decisions. This study focuses on selection of vehicles for factory-in-a-box manufacturing and decisions regarding the optimal routes within the supply chain consisting of a depot, suppliers, manufacturers, and customers. Moreover, in order to contrast the options of factory-in-a-box manufacturing with those of conventional manufacturing, the location of the final production is determined for each customer (i.e., factory-in-a-box manufacturing with production at the customer location or conventional manufacturing with production at the manufacturer locations). A novel multi-objective optimization model is presented for the vehicle routing problem with a factory-in-a-box that aims to minimize the total cost associated with traversing the edges of the network and the total cost associated with visiting the nodes of the network. A customized multi-objective hybrid metaheuristic solution algorithm that directly considers problem-specific properties is designed as a solution approach. A case study is performed for a vaccination project involving factory-in-a-box manufacturing along with conventional manufacturing. The case study reveals that the developed solution method outperforms the ε-constraint method, which is a classical exact optimization method for multi-objective optimization problems, and several well-known metaheuristics. © 2022 Elsevier Ltd
ABSTRACT
The distributed accounting method of blockchain, together with its decentralized and tamper proof characteristics, can solve the problem of lack of food safety traceability data and low credibility, which enable the traceability requirements of food chain traceability, problem food recall, food circulation information query. It also improves the food flow mode, and establishes a new food safety ecosystem. This paper innovatively integrates the principle of blockchain into the traceability and circulation process of Hebei cold chain food. In order to find the proportion and distribution of various types of commodities in the circulation of imported and domestic cold chain food in Hebei Province, the combination of qualitative and quantitative analysis methods, chi square test, association rules and other analysis methods are used. The results show that the demand for cold chain food in Hebei Province is mainly domestic food and supplemented by imported food. Cold chain poultry is the main need and other cold chain food is supplement. The flow of imported cold chain food is mainly from the surrounding provinces and cities. Furthermore, in the process of tracing the positive commodities, it is found that there are four main modes of commodity circulation in Hebei Province, namely, family model from farmer, wholesale market, new retail and multi-level sales model. The new retail and multi-level sales model fill the gap in the distribution and circulation of cold chain goods in Hebei Province. © 2021 ACM.
ABSTRACT
The Covid-19 pandemic has caused the domestic and global economic sectors to experience turmoil. The impact of the pandemic has been most pronounced in the Small Medium Enterprise (SMEs) sector. Most SMEs experienced a decline in sales turnover, difficulties in obtaining financing/credit, problems in the distribution of goods, and difficulties in obtaining raw materials. The purpose of this research is to determine the selection of Decision Support System (DSS) SMEs Batik Madura Indonesian, in the face of the Covid-19 pandemic based on influential indicators. The method used is interval value fuzzy type-2 Technique for Others Reference by Similarity to Ideal Solution (TOPSIS) based on Group Decision Support System (GDSS). The method for processing expert data is interval value fuzzy type-2 Geometric Mean Aggregation (GMA). The research findings are the most influential indicator weights in the selection are a variety of batik motifs and online market places. The contribution of the research is to develop the fuzzy interval type-2 method to support SMEs selection decisions by modifying the midpoint on triangular Fuzzy Number interval based on GRUP (GDSS). Based on expert data, the comparison of accuracy between fuzzy type-2 with one point, and two points, the highest accuracy result is using fuzzy type-2 with two points. © 2021 IEEE.