ABSTRACT
The virus that arises from Wuhan, popularly called as “coronavirus” has been spread all over the world in a short period. India has also taken preventive measures to control this threatening virus. In addition to precautions, it is necessary to analyze the risk factors of COVID-19 in overpopulated countries to reduce the impact of the virus. As India is the second-populated country, analyzing the risk factor of COVID-19 helps in categorizing the likely and non-likely people affect by the virus. The work manages the fuzziness through intuitionistic fuzzy sets combine with the VIKOR decision-making process to find the most influencing risk factors of COVID-19. The objective weights of the criteria are evaluated by entropy as it measures the randomness in discrete distribution. Moreover, sensitivity analysis is conducted to verify the robustness of the results of the proposed method.
ABSTRACT
In order to avoid the huge hidden dangers caused by emergencies, it is particularly vital to make a reasonable pre-location and layout of emergency logistics facilities. A multi-objective pre-location model of temporary distribution station for emergency materials was built, which considered the problems of information shortage and uncertain demand after the incident with minimum time, maximum time satisfaction, minimum delivery cost and psychological trauma to the masses. The priority of candidate points was solved by comprehensive evaluation methods, the nominal demand of served points was estimated by triangular fuzzy number theory (TFN), and the location model was solved by non-dominated sorting genetic algorithm. In addition, the optimal schemes without priority and considering it were compared and analyzed, the practicability of the model is verified by concrete examples. The results show the time and cost reduction of 7.754% and 25.651%, an increment of total satisfaction value of the scheme considering location priority. Therefore, the model and algorithm provide theoretical support and practical ideas for solving the location problem, which can better complete the task of the location problem for temporary distribution stations of urban emergency materials.
ABSTRACT
How to improve employees' satisfaction in the remote office mode while working together has become a challenge for enterprises to deal with the new office management mode. The concept of service design touch point is introduced into the remote office management system to improve employees' office experience and help enterprises complete the remote office service design. From the perspective of virtuous circle, the cost of failure analysis and preventive measures for service design touch point in the process of service design is lower than that of dealing with failure after service failure. Therefore, this paper made a risk assessment on the failure mode of service design touch point loss analysis method based on the triangular fuzzy number evaluation method. In the failure risk assessment, the fuzzy failure mode and effect analysis theory and the failure mode of service design touch point are analyzed first, and the expert scoring method is used to evaluate and determine the fuzzy level of severity, occurrence and detection of each failure mode;Then, aiming at the ability difference of different experts in evaluating different objects, the expert importance matrix, which is based on attribute difference, is determined;On this basis, the risk priority value of each failure mode is analyzed and determined by fuzzy calculation method. The risk evaluation ranking results of touch point failure modes are obtained according to the risk priority value. Finally, taking the failure analysis of Y company's remote collaborative office service as an example, the feasibility of the method is verified by the case of protection during COVID-19.
ABSTRACT
In this trying time for the world battling different variants of the COVID'19 pandemic, different intervention strategies are being taken by government, to limit the spread of infection. Closing educational institutes, stay at home orders, campaigns for emphasis on vaccination, usage of medical mask and frequently sanitizing hands, etc. are the endeavors made by the authorities to decrease the number of cases in the country. In this regard, the contribution aims to help the decision-makers to identify a potential prevention strategy, based on public acceptance and intervention effectiveness. To achieve this objective, feasible judgments of professionals from three different sectors are brought together through meetings. Opinions, based on ten criteria, are recorded in linguistic form for prioritizing six alternatives. The linguistic terms are then evaluated and manipulated by entailing triangular fuzzy numbers and a group multi-criteria decision making (GMCDM) approach. After using the fuzzy analytical hierarchy process (F-AHP) for the complex decisions, the fuzzy VIsekriterijumsko KOmpromisno Rangiranje method (F-VIKOR) is utilized to attain the closest ideal stratagem. Consequently, through the ranking orders of defuzzified scores, intuitive preference of compromise solutions is suggested. The tactic gaining more priority with respect to the group utility to the majority and F-VIKOR index is complete lockdown for the short term. Furthermore, a comparison analysis is also added in the discussion to verify the attained prioritized outcomes. This comparative study is carried out through the technique for order of preference by similarity to ideal solution (TOPSIS), which evidently produces the same preference of alternatives. In addition, this strategy can be apparently discovered to be an effective strategy adopted by different countries in successfully decreasing the number of cases.
ABSTRACT
The outbreak of COVID-19 had already shown its harmful impact on mankind, especially on health sectors, global economy, education systems, cultures, politics, and other important fields. Like most of the affected countries in the globe, India is now facing serious crisis due to COVID-19 in the recent times. The evaluation of the present status of the provinces affected by COVID-19 is very much essential to the government authorities to impose preventive strategies in controlling the spread of COVID-19 and to take necessary measures. In this article, a computational methodology is developed to estimate the present status of states and provinces which are affected due to COVID-19 using a fuzzy inference system. The factors such as population density, number of COVID-19 tests, confirmed cases of COVID-19, recovery rate, and mortality rate are considered as the input parameters of the proposed methodology. Considering positive and negative factors of the input parameters, the rule base is developed using triangular fuzzy numbers to capture uncertainties associated with the model. The application potentiality is validated by evaluating Pearson's correlation coefficient. A sensitivity analysis is also performed to observe the changes of final output by varying the tolerance ranges of the inputs. The results of the proposed method show that some of the provinces have very poor performance in controlling the spread of COVID-19 in India. So, the government needs to take serious attention to deal with the pandemic situation of COVID-19 in those provinces.
ABSTRACT
The aim of this study is to find out the most critical service quality priorities in cargo transportation before the Covid-19 and during the Covid-19 outbreak by applying the Fuzzy Importance-Performance-Impact Analysis (FIPIA) method. At the same time, it is also aimed to decide the best resource allocation in cargo services and to show the differences between both periods. This is the first study using the FIPIA method in determining the service quality priorities of consumers using cargo service. A total of 723 participants responded to the questionnaire consisting of 341 participants before the Covid-19 and 382 participants during the Covid-19 period. This study also examined whether there is a relationship between the sectors most frequently used in cargo service in both periods and service quality priorities and found the differences in consumers' sectors most frequently. According to data found in the study, the application of promotion and courteousness, and politeness of the personnel had the highest value in all service quality priorities before the Covid-19 outbreak. According to results, "evaluation of customer complaints in a short time" and "fast delivery" had the highest value in all service quality priorities after the Covid-19 outbreak. Evaluation of customer complaints in a short time and fast delivery had high importance values while performance and impact had relatively low importance, presenting a need to concentrate on these three-service qualities.