A study on the assessment of risk management performance in maritime start-ups: evidence from China

Due to the COVID-19 pandemic, the international shipping market has been highly volatile, posing a serious threat to the survival and development of many maritime start-ups. With the development of the digital economy, digital transformation is affecting the evolution and upgrading of many traditional enterprises, including maritime enterprises. In the post-COVID-19 era, start-up small and medium-sized enterprises will need to consider the importance of enterprise risk management to achieve transformation and upgrading. The purpose of this study is to provide guidance for the establishment and upgrading of risk management systems for start-ups based on the identification of risk management strategies of maritime enterprises and the evaluation of their performance. The fuzzy analytic hierarchy process and importance-performance analysis methods were used to rank the operational risk, financial risk, market risk, innovation risk, and disaster risk according to sub-items and screen out the risk management schemes for priority improvements. Through empirical research, it was found that the financial risk and market risk response schemes have the lowest performance and need to be prioritised for improvement. This study argues that start-ups can appropriately challenge their risk management strategies to meet potential risk management needs based on their own circumstances.

Supplier selection framework to evade pseudo-resilience and to achieve sustainability in supply chains

PurposeDue to increasing uncertainty in the global business scenario, research on supply chain resilience is gaining significance. The outbreak of the COVID-19 pandemic has accelerated and magnified the issues already pertaining in the supply chain thereby increasing the vulnerabilities in the network. This study attempts to build the concept of pseudo-resilience in supplier selection and evaluation for supply chain sustainability.Design/methodology/approachA combination of multi-criteria decision-making methods AHP and R is adopted, and an integrated method called Combined AHP–R method is used to identify and include the property of pseudo-resilience into supplier selection processes.FindingsThe authors identified various factors contributing to pseudo-resilience considering supplier selection process and found the most important attribute. Using the combined AHP–R method, the suppliers were evaluated, considering the attributes contributing to the pseudo-resilience of supply chains and best supplier was selected.Originality/valueTo the best of our knowledge, this is the first study addressing a supplier selection problem for sustainable supply chains, considering pseudo-resilience. Also, this is the first study to apply the AHP–R method for supplier selection in the resilience or sustainability context.

Optimization of message communication during COVID-19 epidemic using fuzzy AHP & goal programming

This paper determines the optimal communication by the policymakers in the wake of the Covid-19 crisis. The authors have developed a conceptual framework for optimal communication from the available literature and the opinion of the experts. Further, a hybrid methodology based on Fuzzy AHP and Goal programming has been used for the analysis. Using the conceptual framework it was revealed that there are 72 configurations from which optimal one has to be chosen by the policymakers for communicating optimally during pandemic emergencies like the Covid-19 outbreak. The analysis using hybrid methodology highlighted that FRTD is the optimal configuration out of the 72 possibilities. Considering this option would minimize the effect of the Covid-19 crisis by helping policymakers communicate to the maximum people at the minimum delay.

Application of Multi-Criteria Assessment in Banking Risk Management

Banks face a number of business risks on a daily basis. Today, operational risk is dominant. The aim of this paper is to develop a decision-making system when choosing a method of operational risk management by using the Analytical Hierarchy Process (the AHP method) and the Fuzzy Analytic Hierarchy Process (the FAHP method). Analytical hierarchical process is a simple efficient process in solving decision-making problems. The final decision depends on the assessment of a set of alternatives and the decision criteria. The main purpose of the process is to find appropriate solutions for defined user factors in the current competitive environment. The results obtained by the classical AHP method, as well as the FAHP method, show that external factors are the dominant criterion, especially during the financial crisis or the Covid19 pandemic, and that solutions should be sought in international standards, using control tools created by the banks themselves.

Developing a resilient healthcare supply chain to prevent disruption in the wake of emergency health crisis

PurposeThe study aims to identify and analyse the drivers of resilient healthcare supply chain (HCSC) preparedness in emergency health outbreaks to prevent disruption in healthcare services delivery in the context of India.Design/methodology/approachThe present study has opted for the grey clustering method to identify and analyse the drivers of resilient HCSC preparedness during health outbreaks into high, moderate and low important grey classes based on Grey-Delphi, analytic hierarchy process (AHP) and Shannon's information entropy (IE) theory.FindingsThe drivers of the resilient HCSC are scrutinised using the Grey-Delphi technique. By implementing AHP and Shannon's IE theory and depending upon structure, process and outcome measures of HCSC, eleven drivers of a resilient HCSC preparedness are clustered as highly important, three drivers into moderately important, and two drivers into a low important group.Originality/valueThe analysis and insights developed in the present study would help to plan and execute a viable, resilient emergency HCSC preparedness during the emergence of any health outbreak along with the stakeholders' coordination. The results of the study offer information, rationality, constructiveness, and universality that enable the wider application of AHP-IE/Grey clustering analysis to HCSC resilience in the wake of pandemics.

Integration of RFID strategic value attributes mechanism decision in apparel supply chain: fuzzy AHP-TOPSIS approach

PurposeThe purpose of this paper is to identify the radio frequency identification (RFID) strategic value attributes (RFIDSVAs) mechanism selections preferences and also integration of RFID tags with technology coordination tools (IRTWTCTs) alternatives ranking performance decisions in supply chain management (SCM). RFID-enabled techno-economic feasibility decisions are enhancing the SC visibility in apparel supply chains (ASCs). The RFIDSVAs mechanism selections have performed significant agility to strategic competitive advantages, namely, inventory visibility, multi-tags ownership transfer within trusted third party, etc.Design/methodology/approachFuzzy analytical hierarchy process (FAHP) and FAHP-fuzzy Technique for Order of Preference by Similarity to Ideal Solution (FTOPSIS) approaches have been used to evaluate the quantitative assessment of RFIDSVA mechanisms selection decision based on weight priority orders and IRTWTCTs alternatives selection in ASC networks. The comparison of FAHP and FAHP-FTOPSIS approaches to evaluate the integrated framework develop in RFIDSVAs mechanisms and IRTWTCTs alternatives selection decisions in Indian multi-tier ASC networks.FindingsThe result found that the FAHP-FTOPSIS approaches have used to prioritizing the RFIDSVA mechanism selection weights and also identify the IRTWTCTs alternatives ranking preferences order in apparel SCM. The comparison between the FAHP and FAHP-FTOPSIS approach to quantitative assessments from RFIDSVA mechanisms and IRTWTCTs alternatives selection decisions, which enable them SC agility potential across multi-tier visibility in ASC networks. ASC stakeholders can be benefited by techno-economic feasibility decisions, RFID-enabled shop floor activities, multi-tags ownerships transfer in SCs and knowledge-based cryptography tags/items separation in SCs.Research limitations/implicationsThe research work has considered only five RFIDSVA mechanisms and also three integration of RFIDTWTCTs alternatives in multi-tier ASC. The strategic competitive advantages are achieved by RFID-enabled break-even tags price decisions and also techno-economic feasibility decision by contractual design multi-tier SC stakeholder's involvements.Practical implicationsThe pilot project study explores that the quantitative assessment decision has based on RFID-enable techno-economic feasibility in ASCs. Stakeholders can be benefited by inventory control of the financial losses, reducing the inventory inaccuracies and multi-tags ownership transfer within trusted third-party traceability in ASC networks.Originality/valueThis study explores the RFID-enabled apparel SC process and activities visibility (natural fibre's fibre producer, fibre dyeing producer, yarn spinning producer, knitting and finishing producer).

Identifying Optimal Approaches for Sustainable Maritime Education and Training: Addressing Technological, Environmental, and Epidemiological Challenges

Maritime education and training (MET) for seafarers who operate ships has struggled to flexibly adapt to technological and environmental changes. In particular, as social demand for online MET arose due to COVID-19, the need for sustainable MET beyond traditional teaching methods grew exponentially. In order to identify the most optimal MET methods among face-to-face and online methods, this study reviewed the concepts and applications of existing MET methods, grouped them using a fuzzy analytic hierarchy process, and supplemented this structure through a designed survey. The results showed that the online methods had the greatest weight, and the "XR (extended reality) within the metaverse" teaching method had the highest priority. This study identified which MET methods should be prepared for the post-COVID era through quantitative analysis. We confirmed the need for attention to XR within the metaverse as a field of online methods in the future. Furthermore, our findings reveal that online education platforms via metaverse-based "expansion" and "connection" are needed, and pave the way for future research to expand empirical studies on MET satisfaction regarding existing International Maritime Organization model courses.

Integration AHP and MOORA for Sustainable Supplier Selection During the COVID-19 Pandemic Era: A Case Study

The global COVID-19 pandemic had a complex impact on the supply chain system. Manufacturing companies always strive to be able to face corporate competition and become superior with one of them through selecting the right supplier. Suppliers have the highest risk in a company, especially during the COVID-19 pandemic era, but with the correct selection of suppliers, the company can provide strength in global competition. The purpose of this research is to be able to solve the problem of sustainable supplier selection in a garment industry in Indonesia during the COVID-19 pandemic through the integration method between AHP and MOORA. AHP as a method that has been proven in many studies, in this study is used to determine the weight of each criterion. Furthermore, MOORA as a method that has good selectivity in choosing the best alternative will be used in the selection process. 12 criteria with 5 alternatives are used to determine the best supplier. The contribution of this research is the integration of the AHP and MOORA methods and the determination of important criteria in the era of the COVID-19 Pandemic. The results show that the criteria for the area with the level impact of COVID-19 (C12) have the greatest weight and supplier 3 becomes the first ranked supplier or the best supplier. The integration method between AHP and MOORA is easy to use and can choose the right sustainable supplier during the COVID-19 pandemic. © 2023 American Institute of Physics Inc.. All rights reserved.

Tourism in India: The reasons of tourist gathering after 2ndwave

In today's Era,various industries are settling up in India and tourism is one of them. Tourism being one of the leading industries in India has set up the benchmark within last few years. Talking about today's scenario, the tourism industry is facing a huge loss because of the deadly humanitarian disease "COVID-19"that came at the end of 2019. It had led to the LOCKDOWN nationwide, leading towards the downfall of the hotel and tourism industry. Global covid-19 pandemic has challenged this sensitive industry with unprecedented circumstances and repercussions. Although, after the second wave, the situation is becoming better day by day, the tourist visits at famous stations have increased rapidly that may be harmful for the country and virus may further spread to the country and there are several reasons for increase in the tourist visit at different parts of the globe. These reasons have been considered as criteria for the study. The main objective of this work is to find out the main reasons why people are getting attracted towards tourism. In this work an AHP approach been proposed to solve the above discussed problem. Total seven criteria's have been taken from expert opinions which have been considered for study. It has been found that the reason "Upcoming 3rd Wave"has the maximum impact than other reasons for increment of people at tourist places. © 2023 Author(s).

Micro-depots site selection for last-mile delivery, considering the needs of post-pandemic parcel recipients

The pandemic has changed consumer habits, leading to an increase in parcel delivery and changing consumer requirements. Last-mile delivery has become more important than ever. Parcel delivery providers face a major challenge, as research shows that many consumers will maintain the same shopping habits as during the pandemic. It is, therefore, necessary to find sustainable and not just short-term solutions for the last-mile delivery. Identifying suitable locations for micro-depots in urban areas and delivery with e-cargo bicycles can be one of them. This article has two objectives: (1) to determine whether the changes brought by Covid-19 affect the selection of the appropriate micro-depot site and to what extent;and (2) whether the extension of the Analytical Hierarchy Process (AHP) by evaluating the technical efficiency of micro-depo sites locations changes the ranking of most favourable locations and to what extent. We first gathered existing criteria for selecting a suitable micro-depot location through a literature review. Then, a qualitative and quantitative analysis were performed to check suitability of criteria and complement the current set of criteria with potential new criteria resulting from Covid-19. A real numerical example of one of the past researches was selected to perform Delphi and super-efficiency Data Envelopment Analysis (DEA) analysis. Results of Delphi analysis, where the AHP was applied, revealed that Covid-19 had not affected the type of stakeholders' demands (city administration, citizens and logistics companies) taken into account, but their importance. However, upgrading the AHP with a super-efficient DEA model has completely changed the order of the most relevant micro-depot locations. © 2023 The Authors. Published by ELSEVIER B.V.

The Utility of Decision Tree and Analytics Hierarchy Process in Prioritizing of Social Aid Distribution due to Covid-19 Pandemic in Indonesia

The Indonesian government provided various social assistance programs to local governments during Covid-19. One of the difficulties for the local governments in determining candidates for social aid is ensuring that the number of candidates is in balance with the available quota. Therefore, the local governments must select the most eligible candidates. This study proposes a priority model that can provide recommendations for candidates who meet the criteria for social assistance. The six parameters used in this study were: number of dependents, occupation, income, age, Covid status, and citizen status. The model operates in two stages, namely classification followed by ranking. The classification stage is conducted using a decision tree, while the ranking stage is performed conducted using the Analytical Hierarchy Process (AHP) algorithm. The decision tree separates two classes, namely, eligible and non-eligible. In addition, the classification process is also used to determine the dominant attributes and played a role in the modeling. The proposed model generates a list of the most eligible candidates based on our research. These are sorted by weight from greatest to most eligible using five dominant parameters: number of dependents, income, age, Covid status, and citizen status.

A novel fuzzy group decision making approach for buying a house in pandemic process

After the detection of the first official case diagnosed with COVID-19 on March 2020, the new package called as "Economic Stability Shield” have been implemented in Turkey to minimize the effects of the pandemic. As in all sectors, the epidemic caused various changes in the real estate sector. The demands of citizens who stayed in homes for a long time during the epidemic period have also changed when buying a house. This study aims to investigate the importance of selection criteria for buying a house criterion in the real estate sector and to determine the most suitable house of via a Multi-Criteria Decision Making (MCDM) approach. By integrating Fuzzy Analytic Hierarchy Process (FAHP) and Multi-Attribute Ideal Real Comparative Analysis (FMAIRCA), the assessment criteria of buying house and suitable houses are evaluated. While making this evaluation, the weights of the criteria are obtained by pairwise comparisons under fuzzy environment through collected from five households living in Konya. Next, the FMAIRCA method is used to rank the candidate houses according to the views of the households. As a result of the study, it has been determined that the criteria of eligibility for credit are the most important criteria. For the case study, we perform a comparative analysis on the performance of fuzzy TOPSIS and fuzzy VIKOR in buying a house. Our comparative analysis for this case study shows that the three fuzzy MCDM methods achieve the identical rankings. © 2023 Gazi Universitesi Muhendislik-Mimarlik. All rights reserved.

Micro-depots site selection for last-mile delivery, considering the needs of post-pandemic parcel recipients

The pandemic has changed consumer habits, leading to an increase in parcel delivery and changing consumer requirements. Last-mile delivery has become more important than ever. Parcel delivery providers face a major challenge, as research shows that many consumers will maintain the same shopping habits as during the pandemic. It is, therefore, necessary to find sustainable and not just short-term solutions for the last-mile delivery. Identifying suitable locations for micro-depots in urban areas and delivery with e-cargo bicycles can be one of them. This article has two objectives: (1) to determine whether the changes brought by Covid-19 affect the selection of the appropriate micro-depot site and to what extent;and (2) whether the extension of the Analytical Hierarchy Process (AHP) by evaluating the technical efficiency of micro-depo sites locations changes the ranking of most favourable locations and to what extent. We first gathered existing criteria for selecting a suitable micro-depot location through a literature review. Then, a qualitative and quantitative analysis were performed to check suitability of criteria and complement the current set of criteria with potential new criteria resulting from Covid-19. A real numerical example of one of the past researches was selected to perform Delphi and super-efficiency Data Envelopment Analysis (DEA) analysis. Results of Delphi analysis, where the AHP was applied, revealed that Covid-19 had not affected the type of stakeholders' demands (city administration, citizens and logistics companies) taken into account, but their importance. However, upgrading the AHP with a super-efficient DEA model has completely changed the order of the most relevant micro-depot locations. © 2023 The Authors. Published by ELSEVIER B.V.

Exploring the Determinants of Digital Transformation Adoption for SMEs in an Emerging Economy

In the fourth industrial revolution age, digital transformation is crucial to the sustainable development of small- and medium-sized businesses (SMEs). This study suggests a hierarchical model based on the Technology–Organization–Environment (TOE) model with three main dimensions and nine sub-dimensions for SMEs that implemented digital transformation in the emerging economy. The fuzzy analytic hierarchical process methodology (Fuzzy AHP) was used to explore and rank determinants of the digital transformation adoption for SMEs. Data were collected by the questionnaires from 72 respondents, who were the leaders of SMEs in Vietnam. The results revealed that the environmental factor was ranked the most important factor in the pairwise comparisons of the hierarchical structure, and the sub-dimension of the customer experience was at the highest ranking of the relative pairwise comparisons of the digital transformation adoption for SMEs, followed by technological compatibility, government support, organizational support, and human resources. This research makes contributions to the topic of digital transformation from both theoretical and practical implications. The result stresses the critical significance of environmental factors in the successful adoption of digital technologies in SMEs, which adds to the perspective in the context of a growing nation.

Analysis of Factors Affecting the Sustainable Success of Airlines During the COVID-19 Pandemic

The COVID-19 pandemic increased the risk of financial distress, bankruptcy, or both, in the airline industry. Whether airlines can survive or not during and/or after the pandemic is closely related to their decisions and actions which will enable their success by increasing their resilience. In crisis periods such as COVID-19, the decisions taken by airlines are strategically important for achieving sustainable success. Thus, it is critical to understand which factors are more important for airlines to shape their actions and make correct decisions. This paper investigates the sustainable success factors on which airlines should focus to provide resilience during the COVID-19 pandemic crisis. It provides a robust model using the interval type-2 fuzzy analytic hierarchy process (IT2FAHP) and interval type-2 fuzzy Decision Making Trial and Evaluation Laboratory (IT2FDEMATEL) to identify and rank success factors. The findings indicate that financial and operational factors are extremely important to ensure resilience for airlines. In addition, the results of the study reveal that operational factors and information sharing factors have an impact on financial factors and customer satisfaction. © National Academy of Sciences: Transportation Research Board 2021.

Comparative analysis among doctors working in private and government hospitals in identifying and prioritizing essential stress factors during COVID-19- an AHP-TOPSIS approach

The spread of COVID-19 across the world, triggered multiple stresses among doctors working tirelessly round the clock to attend sick patients. Doctors had to cope with new environment thereby developing anxiety and fear. The current paper identifies and explores the stress intensity developed among doctors with the aid of multi-criteria decision analysis in doctors working in private and government hospitals of India during COVID-19. After identification of numerous stresses through questionnaire, weights are assigned to common most stress factors by employing AHP method. Furthermore, comparative analysis and prioritization of stress factors is performed with the aid of TOPSIS. The current combined system is a quantitative analysis furnished to establish the feasibility of the methods in weighing and MCDM in stress assessment. This study identifies and predicts the foremost stress factor which needs to be addressed by hospital management to keep doctors with a stable and fresh mindset. This research further establishes a proper MCDM technique which need to be applied in all hospital to regulate and distribute doctors work load without overloading them. Psychological stress is the foremost type of stress reported by multiple doctors. Results showed that lack of balance among personal and professional life followed by lack of communication is highly related problem in doctors in such adverse events.

Aligning the Goals Hybrid Model for the Diagnosis of Mental Health Quality

The social distancing imposed by the COVID-19 pandemic has been described as the "greatest psychological experiment in the world”. It has tested the human capacity to extract meaning from suffering and challenged individuals and society in Brazil and abroad to promote cohesion that cushions the impact of borderline experiences on mental life. In this context, a survey was conducted with teachers, administrative technicians, and outsourced employees at the Federal Institute of Piauí (IFPI). This educational institution offers professional and technological education in Piauí, Brazil. This study proposes a system for the early diagnosis of health quality during social distancing in the years 2020 and 2021, over the COVID-19 pandemic, combining multi-criteria decision support methodology, the Analytic Hierarchy Process (AHP) with machine learning algorithms (Random Forest, logistic regression, and Naïve Bayes). The hybrid approach of the machine learning algorithm with the AHP multi-criteria decision method with geometric mean accurately obtained a classification that stood out the most in the characteristics' performance concerning emotions and feelings. In 2020, the situation was reported as the SAME AS BEFORE, in which the hybrid AHP with Geographical Average with the machine learning Random Forest algorithm stands out, highlighting the atypical situation in the quality of life of the interviewees and the timely manner in which they realized that their mental health remained unchanged. After that, in 2021, the situation was reported as WORSE THAN BEFORE, in which the hybrid AHP with geometric mean with the machine learning Random Forest algorithm provided an absolute result. © 2023 by the authors.

Evaluating Software Quality in E-Learning System by Using the Analytical Hierarchy Process (AHP) Approach: Case Study: Mu'tah University

This study defines and analyzes essential quality characteristics that should be addressed in the creation and implementation of an E-learning system in institutes, as well as its System Content's Quality, Characterizes, and Attributes. The model was empirically validated by fitting it to data from 302 students who participated in an E-learning AHP. All of the evaluated end-users were compared using the pairwise comparison technique in one of Jordan's colleges. Student Oriented Domain, Online Services, and Content Quality are the three sub characteristics of System Content Quality;each sub characteristic has its own set of traits that are used to determine the evaluation's outcome. The Analytical Hierarchy Process (AHP) has been widely employed in multi-criteria decision-making for a variety of practical decision-making situations. The AHP model was used to collect pairwise comparison judgments from all evaluated end users. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Application of GIS-Based AHP Model for the Impact Assessment of COVID-19 Lockdown on Environment Quality: The Case of Kabul City, Afghanistan

The COVID-19 pandemic has negatively impacted the industrial, financial, and social aspects of our daily life due to the implementation of lockdown to protect against the spread of the virus. In addition, the lockdown deduced by COVID-19 has promising positive impacts on air quality and environmental pollution. This study aims to monitor the effects of lockdown on environmental degradation during the pandemic in Kabul city, the capital of Afghanistan, using geospatial data and a statistical model of the Analytical Hierarchy Process (AHP). To achieve the purpose of the study, the most essential influencing factors on air quality were generated from different sources using Google Earth Engine (GEE) and GIS environment;Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI), Normalized Difference Moisture Index NDMI) were calculated using Sentinel-2MSI, Carbon Monoxide (CO) was obtained from Sentinel-5P TROPOMI, and land surface temperature was retrieved from MODIS data. The generated thematic layers (before COVID-19, and during a lockdown of COVID-19) were weighted and rated using the AHP analysis. The weighted layers were spatially overlayed to obtain the final output. Consequently, the environmental quality degradation maps before and during COVID-19 were generated to assess the differences over the 22 districts of Kabul city. The findings of the study show that Kabul city is covered by the very low, low, moderate, high, and very high degradation of the environment by 3.17%, 5.33%, 20.54%, 26.63%, 44.32% before COVID-19 in 201,9 respectively, while the percentages are changed to 4.37%, 8.99%. 16.55%, 37.47%, and 32.62% during the lockdown caused by COVID-19 in 2020. The changes in the percentage of environmental degradation in Kabul city particularly in high and very high zones confirm the positive impact of the lockdown of COVID-19.

The role of e-learning in higher education during COVID 19 pandemic

Over 60 per cent of pupils in the COVID 19 epidemic created significant disruption in the educational system, and educational institutions across the globe were closed. Essential elements of e-learning during COVID-19 have been technology management, management support, improved student knowledge about the usage of e-learning systems and the need for a high standard of information technology from instructors, students, and institutions. This article aims to find key success elements for E-learning during COVID-19 by utilising the MSP and TOPSIS methods to improve the educational process. The objective of the paper was to identify crucial success factors for e-learning during COVID-19. In COVID-19, 69 E-learning managers were interviewed based on specified evaluation and e-learning methods across various channels. Mixed learning was the best appropriate training method for practical use among the five learning systems. These findings showed the readiness of E-learning to carry out instruction throughout the COVID-19 epidemic, regardless of how exceptional the technology was at a school. © 2023 Author(s).