Analytic Hierarchy Process Weight Research Articles

Health assessment of The Upper Citarum Watershed, West Java, Indonesia

Citarum watershed is one of the national priority watersheds. Watershed health assessment activities are used as a reference in efforts to restore watershed conditions and improve watershed management planning. The watershed health was assessed for the Upper Citarum watershed in West Java, Indonesia. Three indicators, including hydrology and land cover were used to assess the watershed health. Hydrology indicators include the Annual Flow Coefficient (KAT) and River Regime Coefficient (KRA). Watershed health level assessment was conducted using Analytical Hierarchy Process (AHP) scoring method. Watershed health levels such as very unhealthy, unhealthy, moderately unhealthy, healthy, and very healthy were obtained by calculating each indicator total number of scores. From the health assessment result of The Upper Citarum watershed, the Annual Flow Coefficient indicator shows an unhealthy level, and River Regime Coefficient indicator shows very unhealthy level. In addition, the land cover indicator shows unhealthy level. Thus, because of a decreased vegetation cover over ten years. Based on the AHP weighting, it was found that The Upper Citarum watershed is at a very unhealthy level. Therefore, according to government regulations about proper watershed management, land cover vegetation must be managed to increase conservation and water quantity to maintain the Citarum watershed’s sustainability.

Model Evaluasi Penerapan Aspek Pakan dan Air Minum dalam Good Farming Practice Peternakan Domba di UP3J Bogor

Good Farming Practice applied as agovernment-based guideline for good and precise cultivation in raising livestock. The main objective of good farming practice is to increase livestock population, meat production and livestock productivity. Published guidance contained how to apply good farming practices in goats and sheep cultivation, but priority of each aspect is not available. Based on that guidance, 5 main aspects were determined which include aspects of facilities, feed and drinking water, production processes. Unit Pendidikan dan Peternakan Jonggol (Jonggol Animal Husbandry Education and Research Unit), which was established since 1984, has a sheep farm unit with semi-intensive rearing methods, but the current production is less than optimal. This study aimed to examines Good Farming Practice (GFP) appliance at Jonggol Animal Husbandry Education and Research Unit using the Analytical Hierarchy Process (AHP) method to find priority vectors that will be apploed as the basis for the priority weights for each aspect, and then conduct an evaluation model to assess and improve the performance of livestock units in UP3J. The results showed priority aspects of GFP with the highest AHP weight, namely feed and drinking water (weight 0.548). This study shows that the combined value ofobservation and priority vector of the aspects of feed and drinking water is 42.7%. The value represents the implementation of thus aspects of good farming practice categorized as LESS.

Quantitative identification of Q-markers of Euphorbiae Humifusae Herba based on AHP-CRITIC comprehensive weighting method

This study investigated the quality markers(Q-markers) of Euphorbiae Humifusae Herba based on the analytic hierarchy process(AHP)-criteria importance through intercriteria correlation(CRITIC) comprehensive weighting method. The Q-markers evaluation system was constructed based on the AHP-CRITIC comprehensive weighting method with quantitative identification of Q-markers of Euphorbiae Humifusae Herba as the target layer. The index weights of the factor layer and the control layer were integrated based on the weights of three indicators(effectiveness, testability, and specificity) in the factor layer calculated by the AHP method and weights of eight indicators(anti-inflammatory inhibitory rate, coagulation shortening rate, anti-cancer inhibition rate, component degree value, component test batch, component average content, content variation coefficient, and number of medicinal materials retrieved according to components) in the control layer calculated by the CRITIC method. The comprehensive score of the chemical components of Euphorbiae Humifusae Herba was weighted and ranked to identify the Q-markers of Euphorbiae Humifusae Herba. In terms of comprehensive scores, top 10 potential Q-markers of Euphorbiae Humifusae Herba were ranked as cynaroside > quercetin > gallic acid > apigenin > luteolin > apigenin-7-O-glucoside > quercetin-7-O-glucoside > ellagic acid > astragalin > ethyl gallate. This study provides a reference for the quality control of Euphorbiae Humifusae Herba and a methodological reference for the quantitative identification of Q-markers of Chinese medicine.

Hazardous waste management system for Thailand’s local administrative organization via route and location selection

ABSTRACT This study proposed a decision support system (DSS) for optimizing transportation routing and disposal hub location for Thailand’s local administrative organizations’ hazardous waste management. The first step is to choose the origin and destination, as well as to collect data for each route. Each route’s decision criteria were based on traffic quality and risk measures from the perspective of users. An analytic hierarchy process (AHP) was used to compute effective weights for decision criteria. To achieve optimal routing, AHP weights were combined with a zero-one goal programming technique. The DSS operates systematically and successfully, taking into account both transportation risk and socioeconomic factors, and provides appropriate routes. Overall, this waste management system may provide useful information to decision-makers for prioritizing disposal site alternatives and implementing feasible waste management actions. The zero-one location design was then used to determine the best hub location. Based on two scenarios of six and fifteen CoG hubs, the results revealed that the best model for managing a case company’s hazardous waste was to establish 15 hubs scattered throughout the country for collecting points and then transporting them to the waste disposal plant in Phitsanulok province. Locating the hub near sink points would reduce transportation costs and backhaul issues, reducing the environmental impact of GHG emissions and increasing system efficiency. Implications: The problem of waste pollution has become increasingly serious all over the world, particularly in developing countries that face significant pollution control challenges. End-of-life wastes cause economic, health, and environmental problems if they are not properly managed. As the world’s population and living standards rise, so does the amount of waste produced. The environmental impact is significant, with massive amounts of waste generated each year with only basic or minimal treatment to mitigate its impact. As a result, there is an urgent need for a method that can precisely optimize transportation routing and disposal hub location for Thailand’s local administrative organizations’ hazardous waste management (LAOs). The proposed decision support system (DSS) may provide useful information to decision-makers in prioritizing disposal site alternatives and implementing feasible waste management actions.

The Construction of an Evaluation System of Corporate Social Responsibility to Employees: An Empirical Study in the Chinese Clothing Industry

Recently, with the intensification of employee suicides in well-known international companies such as Facebook and Pinduoduo, people are paying more and more attention to the violation of employee rights and interests. As an important embodiment of safeguarding the legitimate rights and interests of employees, the corporate social responsibility to employees has become one of the focuses of academic discussions. The aim of this article is to build a corporate social responsibility evaluation system for employees for Chinese clothing companies. As a representative of labor-intensive enterprises, enterprises in the cloth industry often need to rely on the strength of their employees to create value more than ordinary enterprises. Therefore, it is of practical significance to study the corporate social responsibility of employees in the cloth industry. In addition, China is an important exporting country of clothing in the world, and its market environment is different from that of developed countries. Research with Chinese enterprises as samples may lead to different conclusions. Finally, unlike general CSR, the evaluation of employee CSR needs to consider the importance of subjective and objective factors. At this time, the use of the catastrophe progression method can more accurately evaluate the weight of each factor. The result of our research on 100 Chinese clothing companies shows that enterprises with higher rankings in clothing industry will fulfill social responsibility to employees better. The use of the catastrophe progression method to evaluate corporate social responsibility to employees can reduce errors caused by subjective steps such as assigning weights in Analytic Hierarchy Process (AHP) and improve the accuracy of evaluation.

Supply Chain Management Performance Analysis Using SCOR (Supply Chain Operation Reference), and AHP (Analytical Hierarchy Process) Methods at PT YCH Indonesia Medan Branch

This research was conducted to find out how the supply rate performance occurred at PT YCH Cab. Medan, Develop a supply chain performance preparation model so that it can be used as a basis for evaluating company performance. This research aims to find out and analyze supply chain performance at PT YCH Cab. Medan, to find out and analyze performance measurement comprehensively using SCOR and AHP methods. The method used in this study is quantitative with a population of 18 people, data collection techniques used are interviews, questionnaires and documentation. Data processing methods by performing normalization, AHP weighting, Calculation of the final weight of the supply chain process, Traffic Light System and Calculation of the overall performance of the supply chain. The results of this study obtained the red category on symbols S1.2, S2.2, S3.2, M1.3, D1.1, R2.1, R3.1 and R3.2. The company's performance is 74.2 in the Good Performance category. From these results, it can be concluded that the performance of PT YCH is good. Companies that are advanced and want to continue to grow will not be satisfied with good criteria, continue to improve existing conditions by continuing to innovate according to customer needs and requests to make a company with the Great Performance category. Keywords: SCOR, AHP, Performance.

Impact assessment on the economy, society, resource, and environment in the water-receiving cities of the Middle Route Project of South-to-North Water Diversion.

The Middle Route Project of South-to-North Water Diversion (MRPSNWD) is a major strategic project to alleviate the serious shortage of water resources in northern China, and it benefited 14 large- and medium-sized cities in Henan, Hebei, Beijing, and Tianjin. Most of the predecessors used qualitative analysis to study the impact of the MRPSNWD on the water-receiving cities (WRCs), and they only considered one aspect of economy, society, resources, and environment, which could not fully reflect the impact of the MRPSNWD on the water-receiving cities. Therefore, based on the data of economic and social resources and environment of the water-receiving cities in the MRPSNWD from 2010 to 2019, an evaluation model based on entropy weight-analytic hierarchy process (AHP) fuzzy comprehensive evaluation method was constructed to account for the impacts on the economy-society-resources-environment of the water-receiving cities after the operation of the MRPSNWD and scientifically evaluated the comprehensive benefits of the MRPSNWD. The evaluation results revealed that the economic and environmental impacts of the MRPSNWD on the water-receiving cities were more obvious than those on society and resources. As far as water-receiving cities were concerned, the impact of the Middle Route Project of South-to-North Water Diversion on Zhengzhou, Shijiazhuang, Tianjin, and Beijing was generally higher than that of other cities. As far as the Middle Route Project of South-to-North Water Diversion was concerned, its overall impact on water-receiving cities was relatively slow.

Application of Entropy Hierarchy Analysis and Deep Neural Network Algorithm Combination in Enterprise Economic Management

The efficiency and effect of enterprise economic management activities depend on whether the performance evaluation can be implemented and the evaluation results can effectively feedback and improve the enterprise knowledge management process. Allocate enterprise resources to create more value. The evaluation of enterprise economic management activities depends heavily on the weights of different evaluation indicators of enterprises. In order to solve this problem, this paper proposes an evaluation method that integrates entropy weight analytic hierarchy process and deep neural network algorithm. Through objective entropy weight and imitation, the deep neural network fusion of subjective judgment of experts combines the subjective and objective factors of the evaluation index, then uses the AHP method as the evaluation index of performance evaluation according to the index weight, and finally realizes the accurate evaluation of enterprise economic management.

Modeling crop suitability under micro irrigation using a hybrid AHP-GIS approach

Crop suitability analysis using novel models is a pillar for sustainable land-use planning. In this work, the analytical hierarchy process (AHP) was integrated with GIS to produce suitability maps for wheat and maize under sprinkler irrigation and broad bean under drip irrigation. The study was conducted in an arid area, west Nile Delta of Egypt. The characteristics of local climate, landscape, and groundwater quality were matched with crop requirements and assigned scores. A GIS-based model was implemented to integrate scores and AHP weights and generate crop suitability maps. The climate conditions fitted optimum crop requirements; however, slight slope limitations affected wheat and maize. The electrical conductivity (EC), exchangeable sodium percentage, and CaCO3 were the most important soil factors affecting broad bean, and these factors besides coarse fragments affected wheat and maize. The EC, Na+, and Cl– were the most influential factors for wheat and maize irrigation, while EC and sodium adsorption ratio had the greatest priority for broad bean irrigation. Irrigation water quality had the highest specific weight (0.38) followed by soil (0.36), slope (0.15), and climate (0.10). The final suitability maps showed that 97 and 3% of the total area were suitable (S2) and moderately suitable (S3) for wheat, respectively. Moreover, 85 and 15% of the total area fitted the S2 and S3 classes for broad bean. For maize, 36 and 64% of the total area fitted the S2 and S3 classes. Integrating AHP and GIS would provide effective land-use planning and also suggest proper management practices in arid areas.

Use of Multi-Criteria Decision Analysis (MCDA) for Mapping Erosion Potential in Gulf of Mexico Watersheds

The evaluation of soil erosion is often assessed using traditional soil-loss models such as the Revised Universal Soil-Loss Equation (RUSLE) and the Soil and Water Assessment Tool (SWAT). These models provide quantitative outputs for sediment yield and are often integrated with geographic information systems (GIS). The work described here is focused on transitioning towards a qualitative assessment of erosion potential using Multi-Criteria Decision Analysis (MCDA), for improved decision-support and watershed-management prioritization in a northern Gulf of Mexico coastal watershed. The foundation of this work conceptually defined watershed erosion potential based on terrain slope, geomorphology, land cover, and soil erodibility (as defined by the soil K-factor) with precipitation as a driver. These criteria were evaluated using a weighted linear combination (WLC) model to map generalized erosion potential. The sensitivity of individual criteria was accessed with the one-at-a-time (OAT) method, which simply removed one criterion and re-evaluated erosion potential. The soil erodibility and slope were found to have the most influence on erosion-potential modeling. Expert input was added through MCDA using the Analytical Hierarchy Process (AHP). The AHP allows for experts to rank criteria, providing a quantitative metric (weight) for the qualitative data. The individual AHP weights were altered in one-percent increments to help identify areas of alignment or commonality in erosion potential across the drainage basin. These areas were used to identify outliers and to develop an analysis mask for watershed management area prioritization. A comparison of the WLC, AHP, ensembled model (average of WLC and AHP models), and SWAT output data resulted in visual geographic alignment between the WLC and AHP erosion-potential output with the SWAT sediment-yield output. These observations yielded similar results between the qualitative and quantitative erosion-potential assessment approaches, with alignment in the upper and lower ranks of the mapped erosion potentials and sediment yields. The MCDA, using the AHP and ensembled modeling for mapping watershed potential, provided the advantage of more quickly mapping erosion potential in coastal watersheds for improved management of the environmental resources linked to erosion.

City-wide greenhouse gas emissions of communities nearby the world heritage site of Ayutthaya, Thailand

Climate change has emerged one of the greatest threats to sustainable development. Cities are a major contributor to high carbon dioxide levels. This research aimed to quantify city-wide GHG emissions and investigate the potential for climate change mitigation in communities near the World Heritage Site (WHS) of Ayutthaya, Thailand via the multi-criteria analytical hierarchy process (AHP). The total city-wide GHG emission of Ayutthaya Municipality in 2018 was 99,137.04 tCO2eq (1.93 tCO2eq per capita). Energy and waste sectors were the two largest emitters. Pratuchai, the most populated subdistrict and the WHS location, was the largest source of GHGs. However, the cultural heritage site emitted only 0.2% of total GHGs. Based on the IPCC2013 LCA method, residential sector accounted for the largest share (74%), while the WHS contributed only < 1% of total energy-related CO2 emissions. If all the Thailand’s Nationally Determined Contribution (NDC) Roadmap are fully implemented in the residential sector, total GHGs would be reduced by 9735.47% tCO2eq and 6846.86 tCO2eq in 2030. Based on expert interviews, AHP pairwise comparison showed that energy-saving strategies were more preferable than renewable energy technologies. For climate policy initiative, ‘feasibility of implementation’ had the highest AHP weight (0.45) followed by ‘policy feasibility’ (0.39), and ‘environmental performance’ (0.16).

Fuzzy AHP-TOPSIS approaches to prioritize teaching solutions for Intellect Errors

Abstract: The teaching fraternity and intellects play an important role in students’ careers as they make students industry-ready. During their teaching, they make different types of errors. One of the neglected aspects during teaching is intellect errors and these directly or indirectly impact students learning capabilities. The scattered literature shows that there are twelve types of intellect errors like ‘error of coincidence’, ‘senses error’, ‘analogy error’, ‘subjectivity error’, etc. To minimize these errors, six solutions have been identified like ‘selection of right instruments’, ‘developmeand least rated intellect errors respectively. Thent of critical thinking in the students’, ‘aware about knowledge engineering development’ etc. This study aims to identify and prioritize the solutions to overcome the errors of the intellect that has been the ignored aspect of the teaching till now. A hybrid approach of fuzzy AHP (Analytical Hierarchy Process) and Fuzzy TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) has been proposed to rank the solutions that minimize the intellect errors. Fuzzy AHP is used to compute the weights for intellect errors by doing the pairwise comparison and fuzzy TOPSIS is used to rank the identified solutions with the help of generated weights of fuzzy AHP. The results show that “error of proximity” and “senses error” are the highest topmost rated solution to handle errors of the intellect is “development of critical thinking in the students”. Keywords: Intellect errors, fuzzy AHP, fuzzy TOPSIS, industry-ready

Developing Robust Flood Susceptibility Model with Small Numbers of Parameters in Highly Fertile Regions of Northwest Bangladesh for Sustainable Flood and Agriculture Management

The present study intends to improve the robustness of a flood susceptibility (FS) model with a small number of parameters in data-scarce areas, such as northwest Bangladesh, by employing machine learning-based sensitivity analysis and an analytical hierarchy process (AHP). In this study, the nine most relevant flood elements (such as distance from the river, rainfall, and drainage density) were chosen as flood conditioning variables for modeling. The FS model was produced using AHP technique. We used an empirical and binormal receiver operating characteristic (ROC) curves for validating the models. We performed Sensitivity analyses using a random forest (RF)-based mean Gini decline (MGD), mean decrease accuracy (MDA), and information gain ratio to find out the sensitive flood conditioning variables. After performing sensitivity analysis, the least sensitivity variables were eliminated. We re-ran the model with the rest of the parameters to enhance the model’s performance. Based on previous studies and the AHP weighting approach, the general soil type, rainfall, distance from river/canal (Dr), and land use/land cover (LULC) had higher factor weights of 0.22, 0.21, 0.19, and 0.15, respectively. The FS model without sensitivity and with sensitivity performed well in the present study. According to the RF-based sensitivity and information gain ratio, the most sensitive factors were rainfall, soil type, slope, and elevation, while curvature and drainage density were less sensitive parameters, which were excluded in re-running the FS model with just vital parameters. Using empirical and binormal ROC curves, the new FS model yields higher AUCs of 0.835 and 0.822, respectively. It is discovered that the predicted model’s robustness may be maintained or increased by removing less relevant factors. This study will aid decision-makers in developing flood management plans for the examined region.

A comparative analysis of weight-based machine learning methods for landslide susceptibility mapping in Ha Giang area

ABSTRACT Landslide susceptibility maps (LSMs) are very crucial for planning policies in hazardous areas. However, the accuracy and reliability of LSMs depend on available data and the selection of suitable methods. This study is conducted to produce LSMs by combinations of machine learning methods and weighting techniques for Ha Giang province, Vietnam, where has limited data. In study area, we gather 11 landslide conditioning factors and establish a landslide inventory map. Computing the weights of classes (or factors) is very important to prepare data for machine learning methods to generate LSMs. We first use frequency ratio (FR) and analytic hierarchy process (AHP) techniques to generate the weights. Then, random forest (RF), support vector machine (SVM), logistic regression (LR), and AHP methods are combined with FR and AHP weights to yield accurate and reliable LSMs. Finally, the performance of these methods is evaluated by five statistical metrics, ROC and R-index. The empirical results have shown that RF is the best method in terms of R-index and the five metrics, i.e. TP rate (0.9661), FP rate (0.0), ACC (0.9835), MAE (0.0046), and RMSE (0.0350) for this study area. This study opens the perspective of weight-based machine learning methods for landslide susceptibility mapping.

Multi-Criteria Prediction Framework for the Prioritization of Council Candidates based on Integrated AHP-Consensus and TOPSIS Methods

Predicting the council candidate becomes difficult due to the large number of criteria that must be known and identified. The best candidate should be chosen from among the candidates because he or she will play an important role in the organization or institution. It is critical to find the right and best candidate these days because people see and judge the outcome from the candidate in a short time with the help of social media. Perhaps the organization and institution require the best candidate criteria because they will manage and organize the community around them. This study focuses on how to prioritize council candidates using Analytic Hierarchy Process (AHP) for determine the criteria and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) for prioritize the student council candidate. This proposed framework based on Multi-Criteria Decision Making (MCDM) will be used to recommend and assist students in selecting the best candidate for student council. The three criteria chosen were grade point average (GPA), Age, and Semester. Based on the results of the questionnaire and a review of the literature, these criteria were developed. The three criteria were then used to determine the most important criterion for selecting the student council. The AHP weight is used to determine and prioritize the most important criteria. TOPSIS was used to select the most qualified student council candidate. The findings show that GPA is the most important criteria in selecting the best candidate, and the TOPSIS findings support the AHP findings.

Using RS/GIS for spatiotemporal ecological vulnerability analysis based on DPSIR framework in the Republic of Tatarstan, Russia

The republic of Tatarstan is one of the most growing state in Russia in terms of industrialization and modernization with various natural disasters and intense human activities which brought dramatic changes in the ecological process and then led to serious ecological vulnerability. Therefore this research work proposed an analytical framework based on remote sensing (RS), geographical information system (GIS), and analytical hierarchy process (AHP) for spatiotemporal ecological vulnerability analysis at pixel level from 2010 to 2020 and developed a driver-pressure-state-impact-response (DPSIR) framework based on 23 indicators by the AHP weight method to compute ecological vulnerability index (EVI). Further, EVI was classified into five levels based on natural breaks in ArcGIS software as potential, slight, light, moderate, and heavy levels. All 23 indicators were generated from different remote sensing and socio-economic data, processed through digital image processing techniques in terms of removing errors, projection, standardization, and results were saved in GIS format. Results indicate that from 2010 to 2020, EVI was continuously increased from 0.419 to 0.429, and its changes associated with regional vulnerability events and their impact in the region. The moderate level EVI was covering the highest area in all three years with very few changes and continuously increasing. Results also indicate that higher human-socio-economic activities and pressure on natural resources increased ecological vulnerability. This research work is useful to identify main causes and responsible indicators for ecological vulnerability as well as suitable for real-time EVI mapping, monitoring at any scale and region.

A measurement model of occupant well-being for Malaysian office building

The condition of indoor environment is becoming progressively crucial because inadequate indoor conditions in office building can create risks to occupant well-being such as adverse health effects, productivity loss and higher rate of absenteeism. This has led to the development of various assessment tools dealing with this issue. However, most of existing assessment tools focused on the environmental protection and economic growth of building, while the importance of social aspect such as occupant well-being has been scarcely emphasized. This study aims to develop a measurement model of occupant well-being for Malaysian office building. Analytical hierarchy process (AHP) is utilized to assign the weight of four criteria of occupant well-being and fifteen associated indoor environmental parameters for computing the measurement model of occupant well-being for Malaysian office building. The measurement model, which have been driven from an AHP weighting process found that Occupant Health scores the highest priority (35.5%) in computing the measurement model of occupant well-being for Malaysian office building, followed by Occupant Comfort, Occupant Safety and Occupant Adaptation respectively. This study makes a methodological contribution by developing a novel approach that is applicable to monitor the performance of indoor environment in Malaysian office building context to improve occupant well-being.

Mineralisation potential assessment using analytical hierarchy process (AHP) modeling technique: A case study of Ilesha schist belt, southwestern Nigeria

A mineralisation potential assessment in part of Ilesha Schist belt of southwestern Nigeria was carried out using multi criteria decision analysis (MCDA) in the context of analytical hierarchy process (AHP). Three parameters sourced from aeromagnetic, electrical resistivity and geological data were identified to favour gold mineralisation in the study area. These parameters include lineament density (Ld), lithology (Lt), and electrically derived coefficient of anisotropy (An). The application of data enhancement techniques such as total horizontal derivative, 3-D Euler deconvolution and source edge detection were employed in the production of lineament map of the study area. Two hundred and sixty-five (265) vertical electrical sounding (VES) points were investigated using Schlumberger configuration. Coefficient of anisotropy derived from the Dar-Zarouk parameters was obtained from the synthesized VES data. The lithologic information was obtained from the existing geological map of the area. The orientations of lineaments displayed on the aeromagnetic results suggest predominantly NE-SW trending structures, which are characteristic of the Pan African orogenic events in the area. However, few of the E-W trending lineaments are imprints of secondary structural alteration. Furthermore, the Euler deconvolution solutions revealed that the area is characterised by geological contacts with estimated depth of 94–600 m. The coefficient of anisotropy results obtained from the geo-electric parameters vary from 1.00–2.87. AHP weighting and ranking technique was used to develop a reliable mineralisation potential model (MPM). In line with the recommended lower limit of 10 %, the consistency ratio of the developed model is 9.61 %. The produced MPM was classified into low, moderate and high mineralisation potential zones. Preliminary validation of the MPM using the existing pits in the area showed 79 % success rate. The validation of the model using the existing geochemical information from the previous studies indicated 85 % agreement with the conceptual model; thus, confirming the reliability of the produced MPM. The developed model is therefore believed to serve as a future reference in the resource management of the study area.

Empirical Investigation of Lean Six Sigma Enablers and Barriers in Indian MSMEs by Using Multi-Criteria Decision Making Approach

Lean Six Sigma (LSS) is an inclusive approach based on the concept of waste and variation reduction to achieve quality and sustainability. The successful adoption of any approach depends upon the awareness and readiness measures of a particular one. This paper contributes toward Micro-Small and Medium Enterprises (MSMEs) to adopt a comprehensive LSS approach in their existing system through the identification, analysis, and prioritization of LSS enablers and barriers. In the present study, 25 enablers and 21 barriers of LSS adoption are identified through literature review and are validated by using questionnaire-based survey. The screened enablers and barriers are further formulated into logical groups using factor analysis. These formulated groups are prioritized through Analytical Hierarchy Process (AHP) and compared the obtained results with the fuzzy decision-making trial and evaluation laboratory (Fuzzy-DEMATEL). The result reveals that among the main group of enablers, “management-based factor” is the top-ranked followed by “training- and education-based factor” and “technology-based factor” with AHP weights 0.4008, 0.2742, and 0.1465 respectively. On the other hand, among the main groups of barriers, “training and education based factor” is at first rank trailed by “management-based factor” with AHP weights 0.4780 and 0.2915 respectively. The outcomes of current research will facilitate the MSMEs to make a favorable environment toward the LSS approach for increasing productivity and profitability dynamics. An engineering manager can use this paper to enhance social sustainability through the incorporation of LSS approach in the communities where they work. Moreover, this study provides a guiding reference for practitioners and academicians to undertake similar nature of problems into other industrial sectors.

Selecting Freight Transportation Modes in Last-Mile Urban Distribution in Pamplona (Spain): An Option for Drone Delivery in Smart Cities

Urban distribution in medium-sized cities faces a major challenge, mainly when deliveries are difficult in the city center due to: an increase of e-commerce, weak public transportation system, and the promotion of urban sustainability plans. As a result, private cars, public transportation, and freight transportation compete for the same space. This paper analyses the current state for freight logistics in the city center of Pamplona (Spain) and proposes alternative transportation routes and transportation modes in the last-mile city center distribution according to different criteria evaluated by residents. An analytic hierarchy process (AHP) was developed. A number of alternatives have been assessed considering routes and transportation modes: the shortest route criterion and avoiding some city center area policies are combined with traditional van-based, bike, and aerial (drone) distribution protocols for delivering parcels and bar/restaurant supplies. These alternatives have been evaluated within a multicriteria framework in which economic, environmental, and social objectives are considered at the same time. The point in this multicriteria framework is that the criteria/alternative AHP weights and priorities have been set according to a survey deployed in the city of Pamplona (Navarre, Spain). The survey and AHP results show the preference for the use of drone or bike distribution in city center in order to reduce social and environmental issues.