Research on an innovative design and evaluation method of Chinese tea sets based on GT-AHP-FCE.

AIMS: In order to explore new consumer demands for Chinese tea set products, propose an innovative tea set product design and evaluation method to improve the user experience and satisfaction of the produced tea sets, thereby promoting the development of the tea set market and the promotion of tea culture. METHODS: Firstly, grounded theory (GT) was used to analyze interview data to extract consumer demand indicators and construct a design evaluation hierarchical model. Secondly, the Analytical Hierarchy Process (AHP) was used to calculate the weights of the indicators, determine their priority of importance, and obtain several indicators that have a greater impact on the tea set design to guide innovative design practice. Lastly, the tea set design schemes were evaluated using the fuzzy comprehensive evaluation method to select the optimal design scheme and also to act as a guideline for further design optimization. CONCLUSION: This study explores the innovative design and evaluation method for tea set products based on GT-AHP-FCE and validates the feasibility of this approach through a practical example of tea set design inspired by "The Classic of Mountains and Seas.". It provides innovative theoretical and practical guidance for designers of subsequent tea set products and also provides a new path for the inheritance and innovation of traditional culture.

Constructing a student development model for undergraduate vocational universities in China using the Fuzzy Delphi Method and Analytic Hierarchy Process.

As the industrial structure changes, the severe shortage of high-quality technical and skilled talent in China is one of the most significant factors affecting the high-quality development of China's economy. Bridging the gap between cultivating talent from new undergraduate vocational universities and the demand for industrial talent is regarded as an efficient strategy to address the talent shortage. In addressing the gap, China is hindered by a lack of clarity regarding student development goals and effective assessment instruments. Thus, this study aimed to use the Fuzzy Delphi Method (FDM) and the Analytical Hierarchy Process (AHP) to overcome the above challenges. Specifically, we used the FDM to establish a five-level undergraduate vocational education student development model with two 2nd-level indicators, three 3rd-level indicators, eight 4th-level indicators, and 33 5th-level indicators to clarify student development goals. Then, the AHP was applied to determine the indicator weights, and a student development assessment instrument was developed to help universities acquire student development data and improve the matching degree between talent supply and demand. This study could help undergraduate vocational universities cultivate high-quality technical and skilled talent quickly to meet the demand for China's new economic system and to promote industry independence and global competitiveness.

Spatial assessment of flood vulnerability and waterlogging extent in agricultural lands using RS-GIS and AHP technique-a case study of Patan district Gujarat, India.

Assessing and mapping flood risks are fundamental tools that significantly contribute to the enhancement of flood management strategies. Identifying areas that are susceptible to floods and devising strategies to reduce the risk of waterlogging is of utmost importance. In the present study, an integrated approach, combining advanced remote sensing technologies, Geographic Information Systems (GIS), and analytic hierarchy process (AHP), was adopted in the Patan district of Gujarat, India, with a coastline spanning over 1600 km, to evaluate the numerous variables that contribute to the risk of flooding and waterlogging. After evaluating the flood conditioning factors and their respective weights using the analytic hierarchy process (AHP), the results were processed in GIS to accurately delineate areas that are prone to flooding. The results highlighted exceptional precision in identifying vulnerable areas, allowing for a thorough evaluation of the impact severity. The integrated approach yields valuable insights for multi-criteria assessments. The findings indicate that a significant portion of the district's land, precisely 8.94%, was susceptible to very high- risk of flooding, while 27.76% were classified as high-risk areas. Notably, 35.17% of the region was identified as having a moderate level of risk. Additionally, 20.96% and 7.15% were categorized as low-risk and very low-risk areas, respectively. Overall, the study highlights the need for proactive measures to mitigate the impact of floods on vulnerable communities. The research findings were verified by conducting ground truth and visual assessments using microwave satellite imagery (Sentinel-1). The aim of this validation was to test the accuracy of the study in identifying waterlogged agricultural areas and their extent based on AHP analysis. The ground verification and analysis of satellite images confirmed that the model accurately identified approximately 74% of the area categorized under high and very high flood vulnerability to be waterlogged and flooded. This research can provide valuable assistance to policymakers and authorities responsible for flood management by gathering necessary information about floods, including their intensity and the regions that are most susceptible to their impact. Additionally, it is crucial to implement corrective measures to improve soil drainage in vulnerable areas during heavy rainfall events. Prioritizing the adoption of sustainable agricultural practices and improving land use are also crucial for environmental conservation.

Identifying high-vulnerable garbage accumulation areas in Coimbatore City, India: an AHP-GIS approach for effective waste management.

Urbanization has resulted in a surge in municipal solid waste (MSW) generation, posing critical waste management challenges in urban areas. To tackle this issue, we introduce a novel approach for mapping garbage vulnerability zones (GVZ) in Coimbatore City, India, combining the analytic hierarchy process (AHP) and Geographic Information System (GIS). Seven criteria, including per capita waste generation, open dumping, land use land cover, road/railway networks, and population, were integrated and analyzed in GIS. AHP pairwise comparison method assigned weights to each criterion and principal component analysis (PCA) further validated the interconnectedness of the criteria and their impact on the GVZs. The results indicated that open dumping locations and population density are the most influential factors contributing to the risk of garbage accumulation, making up 23.7% and 21.2% of the total weight, respectively. The GVZ map reveals that 94.6% of Coimbatore City is at risk of MSW accumulation, with 20.2% highly and 74.4% moderately vulnerable. Eleven high GVZ clusters were identified, with Saravanampatti, located in the northeastern part of Coimbatore City, being the most vulnerable area. The H3 hexagon format of the GVZ map enhances its usability for monitoring and mitigation capabilities. In conclusion, our comprehensive AHP-GIS approach facilitates effective waste management practices, sustainable resource utilization, and better environmental and public health outcomes in urban areas. The demonstrated methodology has the potential for application in similar developing urban areas in South Asia and the Global South, serving as a valuable tool to address the challenges posed by increasing MSW generation.

An assessment of factors for the cruise port of call selection: The modified fuzzy Analytic Hierarchy Process.

Improving cruise ports of call is essential for enhancing the overall cruise experience for passengers, promoting tourism, and supporting the economic development of the regions served by these ports. Therefore, this article aims to assess selection factors (SFs) for the cruise port of call from the perspective of cruise operators (COs) and port operators (POs). In doing so, this paper first identifies SFs for the cruise port of call and establishes their hierarchical structure thanks to the extensive literature and expert brainstorming. Afterwards, The Modified Fuzzy Analytic Hierarchy Process (MFAHP) is developed to gauge the discrepancy in SFs between COs and POs. Empirical results from MFAHP pinpoint two significant SFs for POs to improve and attract their customers: customs, immigration control and quarantine (CIQ), and incentive measures. Besides, theoretical and managerial implications, and potential limitations for the next research are discussed.

Convenient Site Selection of a Floating PV Power Plant in Türkiye by using GIS-Fuzzy Analytical Hierarchy Process.

Floating photovoltaics (FPVs) are appearing as a promising and an alternative renewable energy opinion in which PV panels are mounted on floating platforms in order to produce electricity from renewable energy on water such as seas, dams, rivers, oceans, canals, fish farms, and reservoirs. So far, such studies related to the body knowledge on financial, technical, and environmental aspects of installation of FPV have not been performed in Turkey while expanding steadily in other countries. In this study, suitable site selection for installation of FPV power plants on three lakes in Turkey was studied by performing geographic information system (GIS) and the fuzzy analytic hierarchy process (FAHP) as multi-criteria decision-making (MCDM) method. This detailed study revealed that the criterion of global horizontal irradiance (GHI) was determined as the most crucial criterion for the installation of FPV on Beysehir Lake, Lake of Tuz, and Van Lake. Additionally, it was clearly seen that the Beysehir Lake had the highest value approximately 52% among other lakes for installation, that is why Beysehir Lake is selected as the best option for installation of an FPV system with this multi-criteria approach.

Integrated analytical hierarchy process-grey relational analysis approach for mechanical recycling scenarios of plastics waste in India.

Mechanical recycling is an indispensable tool for plastic waste (PW) recycling and has the highest share in the PW recycling sector in India. The transition to the circular economy of plastics (CEoP) needs a systemic perspective on the mechanical recycling processes. Nevertheless, the assessment of multiple parameters influencing the mechanical recycling of PW is a complex decision-making problem for the development of triple-bottom-line mechanical recycling. A systemic perspective of various mechanical recycling scenarios was performed by employing a multi-criteria decision-making approach to examine the complexity of interlinked factors in the present investigation. Analytical hierarchy process (AHP) integrated with grey relational analysis (GRA) was used to evaluate the criteria that directly influence quality-oriented mechanical recycling. Data were collected by conducting semi-structured interviews using a framed questionnaire in stakeholder engagement with mechanical recyclers of PW. The first level hierarchy included economy, technical, resource consumption and environmental criteria. These criteria were further categorized into various significant indices such as quality of recyclate, recyclability, water and energy consumption during recycling. The results of the integrated grey relational analysis indicated that the technical parameters including quality of recyclate, resource efficiency, PW processing rate and recyclability have a significant influence on mechanical recycling. Based on AHP-GRA, scenario MR6, i.e. manufacturing of PET strap from recycled PET flakes, was ranked the optimal mechanical process amongst the various scenarios. MR6 was followed by Straps and Films at the second and third rank. The lowest ranking was observed for polymer blend recycling. These processes with higher ranks produced good quality recyclate with better efficiency and recyclability. Moreover, these processes consumed optimal resources during manufacturing. These processes also exhibited less maintenance cost, high production rate, low chemical consumption and waste generation as well as implemented pollution control practices.

Prioritization of sub-watersheds and subsequent site identification for soil water and conservation practices using the SWAT-AHP integrated model in the Lower Sutlej Sub-basin, India.

Prioritization of watersheds is a crucial step in integrated river basin management. It guides resource allocation, planning, decision-making, stakeholder engagement, targeted interventions, and monitoring and evaluation efforts. By identifying and addressing priority watersheds, comprehensive and sustainable management of water resources can be achieved within a river basin. The aim of the current study is to prioritize watersheds using the Soil and Water Assessment Tool (SWAT) and site suitability analysis for the implementation of soil and water conservation structures (SWCS) in the prioritized watersheds by using an analytical hierarchy process (AHP) of the Lower Sutlej Sub-basin, India. The model was calibrated with observed data from 2017 to 2019 with the first 2 years (2015-16) as a warm-up period. Furthermore, validation of the model was done using 2-year data from 2020 to 2021. The model showed successful performance in terms of the R2 range from 0.72 to 0.89, the NSE range from 0.67 to 0.73, the PBIAS range from - 26.70 to 11.30, and the RSR range from 0.51 to 0.57 for stream flow and sediment yield during calibration and validation period. The basin's average annual soil loss ranged from 3.08 to 21.63 t/ha/year, a watershed with the WS2 index seeing the highest rate of soil erosion (21.63 t/ha/year). Hence, WS2 was found to be a top priority. In addition, the site suitability analysis of the prioritized watershed (WS2) reveals that about 1.42% of the area is extremely suitable, 16.14% is highly suitable, and 35.58% is moderately suitable for SWCS. According to the site suitability map validation, both dam locations were found in highly suitable areas, so the developed site suitability map is accurate. This research will help sustainability planners and managers make more informed decisions when building SWCS at suitable sites for better land and water conservation.

Investigation of port intervention to coastal and nearshore dynamics: a GIS and AHP approach.

The goal of the study was attempted to understand the impact of selected ports on the coastal and nearshore dynamics. Dwelling activities along the coastal zone were particularly high in the last two decades. Hence, ports constructed between 2000 and 2022 such as Mundra, Hazira, Karaikal, Krishnapatnam, Gangavaram, and Gopalpur were considered for the study. The land and shore dynamics were assessed prior and after their construction. The landward impact was identified by the changes in LULC, and the dynamics of coastal sediments were assessed from numerical model before and after the ports' construction. The highly impacted land and shore features were used in analytical hierarchy process (AHP) to assess the extent of their impact due to port construction. The extent of impacts was indicated as "criteria weight (CW)" expressed as percentage. Village-wise local sensitivity analysis (LSA) of the port environs due to port activities was also assessed with six parameters such as changes in LULC, cyclone, population, road network, cultural heritage site and shore stability based on their influence on the coast on case-by-case basis using AHP. The obtained influence of the impact of these parameters was used to determine the category of local sensitivity of the adjacent villages around the ports. For effective management planning, the LSA was classified into five classes, namely, very low, low, moderate, high, and very high. Villages categorized with different sensitivities can be attempted for suitable management plans and similar studies can be attempted for all villages impacted by port interventions.

[Application of Delphi method and analytic hierarchy process to construct the evaluation index system of healthy enterprises].

Objective: Explore the application of Delphi method and analytic hierarchy process to explore the construction of scientific, objective and comprehensive evaluation index system for healthy enterprise construction and promote the construction of healthy enterprises. Methods: In October 2022, through Delphi expert consultation and analytic hierarchy process, the indexes were screened and the weights of the indexes were determined, and the evaluation index system of healthy enterprises was established. Results: The positive coefficients of experts in the two rounds were all 100.00%, the authority coefficient of experts was 0.82, the coefficients of variation of the indexes in the two rounds were all less than 0.30. The coordination coefficients of experts in the first and second rounds were 0.64 and 0.77, respectively (P<0.001) . After two rounds of Delphi method expert consultation, a healthy enterprise evaluation index system including 4 first-level indexes, 14 second-level indexes, and 63 third-level indexes was constructed. Conclusion: The constructed health enterprise evaluation index system is highly scientific and reliable, covering the main factors of healthy enterprise construction, and providing a reliable and quantifiable basis and self-assessment basis for the establishment of healthy enterprises.

Development strategy of early childhood music education industry: An IFS-AHP-SWOT analysis based on dynamic social network.

Early childhood music education has garnered recognition for its unique contribution to cognitive, emotional, and social development in children. Nevertheless, the industry grapples with numerous challenges, including a struggle to adapt traditional educational paradigms to new curriculum reforms, and an excessive emphasis on skill training at the expense of nurturing a love for music and aesthetics in children. To navigate these challenges and explore growth strategies for the early childhood music education industry, we initiated a comprehensive approach that involved distributing surveys to practitioners and parents and engaging experts for insightful discussions. Consequently, we proposed an analytical method based on dynamic social networks in conjunction with Intuitionistic Fuzzy Sets (IFS), Analytic Hierarchy Process (AHP), and Strengths, Weaknesses, Opportunities, and Threats (SWOT) analysis, collectively referred to as IFS-AHP-SWOT. This integrated methodology synergizes the capabilities of dynamic social networks, IFS, AHP, and SWOT analysis to offer a nuanced perspective on industry development strategies. The findings underscore that institutions within the early childhood music education industry need to adopt a development strategy that leverages their strengths and opportunities to foster sustainable growth. Ultimately, this research aims to provide critical decision-making support for industry practitioners, policymakers, and researchers, contributing significantly to the ongoing discourse on strategic development in the early childhood music education industry.

IoT-based data and analytic hierarchy process to map groundwater recharge with stormwater.

The sustainable management of groundwater resources in developing countries is often challenging due to limited measurement and monitoring infrastructure to collect data necessary for decision support. To make a contribution towards addressing these challenges, this study investigated the use of Internet of Things (IoT) technology and low-cost sensors to collect the required groundwater-level data and develop a model to map the recharge potential with stormwater. The study focused on two stormwater ponds located in a highly urbanised area in Cape Town, South Africa. A combination of Geographic Information System and analytic hierarchy process was integrated to generate a groundwater recharge potential zone map of the study area. The IoT-based data were used to develop and calibrate a numerical groundwater model in MODFLOW. The study determined that retrofitted stormwater ponds are potential groundwater augmentation zones and can provide opportunity for stormwater recharge in urban areas. Overall, this study highlights the potential of IoT to collect hydrogeological data with low-cost sensors. Data can be collected at high temporal resolution, and the spatial scale can be increased due to availability of low-cost sensors.

Construction and application of a composite model for acid mine drainage quality evaluation based on analytic hierarchy process, factor analysis and fuzzy comprehensive evaluation: Guizhou Province, China, as a case.

The process of mining activities often causes the formation of acid mine drainage (AMD). Through rock fractures and underground rivers, AMD can easily enter the groundwater environment near mines and cause serious pollution to water quality. In order to effectively evaluate the quality of polluted mine water and to understand its threat to the ecosystem around the mine. In this study, four AMD pollution distribution areas, Guiyang City, Bijie City, Qianxinan Prefecture, and Qiandongnan Prefecture in Guizhou Province, were used as the study area. A composite model for mine water quality evaluation was constructed using factor analysis (FA), analytic hierarchy process (AHP), and fuzzy comprehensive evaluation (FCE). Furthermore, by introducing the weighted average method and the level characteristic value (J), the water quality type and the water body environmental quality were evaluated comprehensively, respectively. Compared with the traditional evaluation model, the AHP-FA-FCE model has obvious advantages in the selection of evaluation indicators, the determination of indicator weights, and the comprehensive evaluation of water quality types, and the evaluation results obtained are more reasonable and accurate. Three common factors mainly controlled by mineral oxidation factor, human activity factor, and mineral dissolution factor were extracted by dimension reduction of the original hydrochemical data by FA. The water quality of the mine water samples was evaluated using SO4 2- , Fe, Al, Mn, Na, and F- as evaluation indicators, and the results showed that the mine water samples in the study area as a whole were dominated by class V water, which accounted for 77.78% of the total. Based on the statistical analysis of the original data, it was found that influenced by the water-rock interactions in the study area and the AMD pollution components, the hydrochemical type of the mine water is mainly SO4 2- -Ca-Mg type. The water body environmental quality of mine water in four areas, Guiyang City, Qianxinan Prefecture, Bijie City, and Qiandongnan Prefecture, is from excellent to poor. The average level characteristic value of all the areas is more than 3, and the overall environmental quality of the water body is poor. The strong water-rock interaction and mining activities in the study area may be the main cause of AMD pollution. The results of this study may provide some theoretical reference for the water quality evaluation of AMD-polluted areas. PRACTITIONER POINTS: A composite model for mine water quality evaluation was constructed. A factor analysis-based evaluation indicator selection method is proposed. This study improved the weighting process of the traditional fuzzy comprehensive evaluation. A water quality discriminant based on the weighted average method is proposed. The water environmental quality of various types of mine water was evaluated.

Construction and application of the "Internet + public health service" supply evaluation index system.

To construct an index system for evaluating the supply of Internet+ public health services, and to provide a practical tool for assessing the supply of Internet+ public health services in an objective and scientific manner. The research team drafted the index system framework by combing the literature. The Delphi method was used to determine the content and weight of the index through two rounds of expert consultations. At the same time, the Cronbach coefficient and factor analysis were adopted to test the reliability and validity. What's more, the analytic hierarchy process and the TOPSIS method were applied to analyze the empirical data of 15 counties and cities in the eastern, central, and western regions of China. The constructed indicator system includes 3 first-level indicators, 6 second-level indicators and 29 third-level indicators. Through reliability and validity tests, the stability and practicability of the index system are demonstrated in empirical research. The evaluation index system constructed in this article can be applied to the performance evaluation of Internet + public health service.

Analyzing the effectiveness of environmental impact assessment in Paraná, Brazil and California, United States with fuzzy-set qualitative comparative analysis and the analytical hierarchy process.

Environmental impact assessment (EIA) has become one of the most widespread environmental management instruments. Despite this, EIA is routinely criticized for being ineffective at impacting decision-making. This study compared the EIA systems of Paraná, Brazil and California, United States using the effectiveness dimensions from the EIA literature. This study formats the cases into contextual conditions using the fuzzy-set qualitative comparative analysis (fsQCA) to identify the necessary or sufficient conditions that cause effective outcomes. These effectiveness outcomes are then ranked by EIA stakeholders via the analytical hierarchy process (AHP) to identify stakeholder priorities and to improve stakeholder management. The results show that in Paraná stakeholders identified normative effectiveness as the most important dimension, while stakeholders in California identified this dimension as the second-most important following substantive effectiveness. Public participation was found to be a necessary condition for both substantive and normative effectiveness to occur. Early project definition was found to be sufficient for substantive effectiveness and necessary for normative effectiveness, for which stakeholder coordination was a sufficient condition. This suggests that in order for EIA to influence decision-making and foster sustainable development, greater care needs to be taken to actively engage stakeholders in public participation, with clear roles and project design communicated early on, and a clear role for regulatory authority to promote stakeholder coordination for acceptable outcomes. These findings suggest that some effectiveness dimensions are caused by similar conditions, which could help focus stakeholder management efforts and point to new avenues for future EIA effectiveness research.

Developing a risk assessment tool for cancer-related venous thrombosis in China: a modified Delphi-analytic hierarchy process study.

OBJECTIVE: To develop a Risk Assessment Tool for Cancer-related Venous Thrombosis in China. METHODS: A modified two-round Delphi method was employed to establish consensus within a field to reach an agreement via a questionnaire or by interviewing a multidisciplinary panel of experts by collecting their feedback to inform the next round, exchanging their knowledge, experience, and opinions anonymously, and resolving uncertainties. Furthermore, The AHP (Analytic Hierarchy Process) was used to determine the final quality indicators' relative importance. RESULTS: The expert's positive coefficient was 85.19% in the first round and 82.61% in the second round, with authoritative coefficients of 0.89 and 0.92 in the respective surveys. The P-value of Kendall's W test was all less than 0.001 for each round, and the W-value for concordance at the end of the two rounds was 0.115. The final Risk Assessment Tool for Cancer-related Venous Thrombosis consisted of three domains, ten subdomains, and 39 indicators, with patient factors weighing 0.1976, disease factors weighing 0.4905, and therapeutic factors weighing 0.3119. CONCLUSION: The tool is significantly valid and reliable with a strong authority and coordination degree, and it can be used to assess the risk of cancer-related VTE and initiate appropriate thrombophylactic interventions in China.

The analytic hierarchy process method to design applicable decision making for the effective removal of 2-MIB and geosmin in water sources.

Numerous utilities encounter issues with taste and odor that alter the public's impression of the safety of drinking water. The creation of certain components in water naturally due to global climate change is another source of taste and odor components, in addition to industrial emissions. Geosmin and 2-methylisoborneol (2-MIB), both of which are generated by blue-green algae and actinomycetes, are two substances that contribute to the musty and earthy smells in drinking water sources. Unfortunately, current conventional treatment plants only partially remove 2-MIB and geosmin. Therefore, to protect the environment and public health, more up-to-date or optimized treatment methods should be applied to outdated treatment facilities. Best treatment practices, evaluation standards, and decision-making approaches, however, are still shrouded in mystery. The goal of this study was to identify the most effective treatment options for 2-MIB and geosmin. By using the analytical hierarchy process (AHP), a total of 22 assessment criteria were found and prioritized. A thorough literature search led to the identification of potential treatment options, and their effectiveness was evaluated. These options and priority rankings were decided upon using AHP in the decision-making process. Advanced oxidation techniques came out on top in the final priority ranking, followed by membrane filtering, adsorption, oxidation, hybrid processes, and traditional treatment methods. The applied analytical decision techniques may also be used to choose the optimal treatment options, even though the results are particular to 2-MIB and geosmin.

Modeling climate change adaptation for sustainable coastal zones using GIS and AHP.

The world is currently confronting one of its biggest environmental challenges: combating climate change. Coastal zones are one of the areas thought to be most sensitive to current and future climate change threats. The paper integrates Remote Sensing (RS), Geographic Information System (GIS) techniques, and Multi-Criteria Decision Analysis (MCDA) to detect vulnerable areas from climate change impacts in coastal zones in order to recommend adaptation systems in new coastal zones that can withstand various climatic changes. The proposed decision-making framework was developed in three phases: 1) climate data collection and processing; 2) Coastal Climate Impact Assessment (CCIA) model development; and 3) implementation and adaptation system selection. The climate data collection and processing phase involves determining the most significant climate change parameters and their indicators that affect coastal zone stability, extracting climatic data indicators from different climate database sources, and prioritizing the selected indicators. The indicators' weights were estimated using the Analytical Hierarchy Process (AHP) through a questionnaire survey shared with experts in climate change impacts. A CCIA model development phase involves the formulation of the proposed model using GIS technique to discover the vulnerable areas according to the most dominant impact. The implementation and adaptation system selection phase involves the application of the framework to Al-Alamein New City in Egypt. A sensitivity analysis was conducted to measure the behavior of several climate change parameters to identify the most critical parameter for climate change in Al-Alamein New City. The results showed that the geology of the region is the most crucial component influenced by climate change. It is capable of producing a very sensitive area in the coastal zone while also taking other factors into account. When creating new urban neighborhoods, the erosion of the shoreline is the least important factor to consider. This is because coastal deterioration is caused by both the influence of metrological data on the region and the impact of human activity. Shoreline deterioration will be reduced if climate conditions are maintained while limiting the impact of human activities. To adapt to the long-term effects of climate change on coastal zones, a combination of soft and hard protection systems should be considered.

Index construction and application of digital transformation in the insurance industry: Evidence from China.

In the context of digitization, the insurance industry's value chain is undergoing significant shifts. However, the existing research on its comprehension and measurement remains relatively limited. This study constructs an index system for digital transformation in the insurance industry (DTII) on three components: digital infrastructure, digital platform, and digital applications. Utilizing data from 31 provinces in China, this study employs the entropy weight method, analytic hierarchy process method and minimum relative entropy method to measure the weights of indicators, empirically applying this index system. The results show that DTII in China experiences rapid advancement with an average annual growth rate of 20.46% from 2014 to 2020 and there exists strong regional convergence. In addition, the spatial agglomeration and spatial effects of DTII are mainly concentrated in the life insurance industry and the eastern region. This study provides an index system and empirical evidence for evaluating the DTII, providing policy insights for exploring the sustainable development path of the insurance industry in the digital era.

Groundwater spring potential zonation using AHP and fuzzy-AHP in Eastern Himalayan region: Papum Pare district, Arunachal Pradesh, India.

In the present study, the groundwater spring potential zone (GSPZ) was identified using an integrated approach of remote sensing (RS) and geographic information system (GIS), analytic hierarchy process (AHP), and fuzzy-AHP based on multicriteria decision-making (MCDM). Thus, ten associated factors with groundwater springs have been considered: slope, drainage density, lineament density, geomorphology, lithology, soil texture, land use and land cover, rainfall, groundwater level, and spring discharge. The analysis output was categorized into low, moderate, and high. The result of the AHP model shows the area under the high potential zone (16.61%), the moderate potential zone (60.42%), and the low potential zone (22.61%). The result of the fuzzy-AHP model shows that the area falls under the high potential zone (30.40%), moderate potential zone (41.29%), and low potential zone (22.61%). The validation results showed fuzzy-AHP with the area under the curve 0.806, which is slightly better than 0.779 of AHP. So, the resulting GSPZ map confirms that the thematic layers used in the study have a significant role in groundwater spring occurrence and distribution. It was recommended that any groundwater spring rejuvenation or protection activities must be implemented in medium to very high potential zones.