Complex Proportional Assessment Of Alternatives Research Articles

Framework for Lean Implementation Through Fuzzy AHP-COPRAS Integrated Approach

Manufacturing industries strive hard to improve their productivity to meet the highly demanding business market. Productivity can be improved by effective use of resources, elimination of wastes, process flow enhancement, and continuous improvement. There are strategies and tools to improve productivity but industries face the problem of selecting appropriate strategies. Lean manufacturing philosophy helps the manufacturing industries to enhance their productivity aspects by identifying and eliminating the wastes using specific tools/techniques. This article presents an integrated framework for the lean implementation process in the steel processing industry. The value stream mapping (VSM) tool is used to identify the wastes at each stage of the production process. Lean tools are identified from literature based on the wastes identified from the current state. For prioritizing the lean tools based on the positive correlation on one another, fuzzy integrated analytic hierarchy process and complex proportional assessment of alternatives are used. A future state value stream map is developed to illustrate the improvements achieved due to the implementation of selected lean tools. Comparison of present and future state VSM shows a great reduction of wastes, such as scale waste (50%), miss roll defects (72.7%), size variation defect (62%), corrosion defect, and improvements in talk time and cleanliness.

Flood vulnerability analysis using different aggregation frameworks across watersheds of Ardabil province, northwestern Iran

Flood-vulnerable-area selection could be interpreted as an intricate multiple-criteria decision-making (MCDM) problem. Lacking systematic flood vulnerability maps in Iran usually leaves the National Disaster Management Organization and provincial authorities to rely on limited knowledge to inform their emergency actions. Therefore, the present study was conducted as pioneer research in flood problematization for solving disaster issues that have not been adequately considered in the country. To obtain a more trustworthy and safer decision, a complex set of multivariate flood vulnerability assessments was done for 26 watersheds of Ardabil province using the novel-ensemble MCDM frameworks. Towards this, the complex proportional assessment of alternatives (COPRAS) and the UK Department for International Development (DFID) approach was integrated with widely used weighting methods of Shannon's entropy (Entropy) and analytical hierarchy process (AHP). Finally, four different aggregation frameworks of COPRAS-Entropy, COPRAS-AHP, DFID-Entropy, and DFID-AHP were developed and compared based on 19 criteria and three factors (exposure, sensitivity, and resilience). The flood vulnerability was obtained as 0.70 ± 0.13, 0.66 ± 0.18, 0.17 ± 0.10, and 0.20 ± 0.15, respectively, based on COPRAS-Entropy, COPRAS-AHP, DFID-Entropy, and DFID-AHP. As can be seen, higher values were estimated according to COPRAS-based frameworks rather than DFID-based frameworks, except for resilience. The top-ranked watersheds in terms of exposure (i.e., Mashiran) and sensitivity (i.e., Samian) produced by aggregation frameworks match entirely. However, the top-ranked watersheds based on resilience and flood vulnerability slightly mismatch among the used aggregation's frameworks. These findings help the responsible authorities for natural disaster risk reduction to promote sustainable development processes and equitable access to financial resources.

Factors influencing the consumers’ behavioural intention to use online food delivery service: Empirical evidence from Taiwan

Understanding consumer preferences is crucial in helping online food delivery services (OFDS) increase operating revenue and competitiveness while achieving sustainable development. Prior studies on OFDS employed qualitative research and methods for statistical analysis, but few researchers have discussed the importance of the primary factors influencing consumers' selection and intention of OFDS from multiple-attribute decision-making (MADM) perspective. Based on a consumer's perspective, the MADM techniques were utilised in this study to build an assessment model for consumers' selection of OFDS. First, to determine the relative weight of each evaluation criterion and dimension, the analytic hierarchy process (AHP) was utilised. Subsequently, the complex proportional assessment of alternatives (COPRAS) was utilised to analyse the feasible solutions. Lastly, the modified VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) was employed to discuss the performance gap between each evaluation dimension and criterion. The three methods helped identify the primary evaluation criteria and determine the rankings of feasible solutions and related performance gaps. The methods were used to conduct an empirical analysis of the data. Several conclusions and suggestions have been provided based on the findings. The findings are anticipated to serve as a reference for OFDS operators to learn from, allowing them to better understand consumers' demands and provide better service. Finally, theoretical and managerial implications are explored.

Optimal selection of sustainable battery supplier for electric vehicle battery swapping station

ABSTRACT The problems faced in the electric vehicle (EV) charging station like time consumption and limited space can be overcome by battery swapping station (BSS), which not only saves time but also reduces the range anxiety problem among the users of EV. Batteries are the backbone of EV as it is power supply and essential to run the vehicle. Total price of EV has a good share in the form of battery, thus impacting a lot in the EV industry. Therefore, this paper presents a methodology for the selection of a sustainable battery supplier for BSS using fuzzy multi-criteria decision-making method. Firstly, four main criteria segregated into 12 supplementary criteria are identified considering several requirements for BSS. To cope with the uncertainty in the decision-making process, triangular fuzzy number (TFN) has been implemented. The TFNs give the relative weights among the considered criterion, and to make this framework more customer-centric, quality function deployment (QFD) is implemented, leading to final weights of the criteria. The obtained results give the hierarchy of the criteria, and top five weights after implementing the QFD methodology are as follows: battery price (0.2313), innovation ability (0.2188), safety assurance (0.12135), financial condition (0.1119), and cost of transportation (0.066). Subsequently, integrating fuzzy with complex-proportional assessment of alternatives (COPRAS) leads to rank the alternatives. As a case study, Kolkata city of India is chosen to demonstrate a viable selection. It was found that supplier based on Kolkata Municipal Corporation is the topmost priority, followed by North 24 Parganas, eastern part of Howrah, and South 24 Parganas, with the relative significance value of 0.3305, 0.2575, 0.2540, and 0.1578, respectively. This paper reveals an approach to the stakeholders for accessing the sustainable battery supplier of BSS choosing the most significant one.

Effect of process parameters on the strength of ABS based FDM prototypes: novel machine learning based hybrid optimization technique

Even though the prototypes built using Fused Deposition Modelling (FDM) process are found to exhibit good mechanical properties, there are ample scopes to improve them by means of selecting suitable process parameters. Since the FDM process involves more number of process parameters, the selection of optimized values becomes more complex and time consuming. Further, the complex correlation among the process parameters makes the selection process more tedious and involves more numerical steps. Hence it has been intended to perform a physical experiment with the known parameters to determine the performance measures of the built prototypes. With this moto, in this work the effect of the 3D printing parameters is studied and the optimal combination of these parameters are determined. The Taguchi L18 orthogonal array based values are assigned for process parameters and the physical prototypes are fabricated. These specimens are tested in the laboratory and the observations are analyzed. It has been found that the process parameters under consideration have a good effect on the strength of the built models. Out of the 18 experiments, better experiments are selected by using a Machine Learning (ML) approach namely decision tree (DT). Finally, the best combination of parameters has been determined by using a novel hybrid multi objective technique which is formulated by integrating Fuzzy Analytical Hierarchy Process (FAHP) and Complex Proportional Assessment of alternatives (COPRAS) techniques. Then a confirmation experiment has also been done to confirm the optimal combination of parameters. The influence of the parameters is also found by using ANOVA (Analysis of Variance) method. The final results show that the raster angle influences the outputs more while the raster to raster gap has the least influence.

A novel hybrid GIS‐based multi‐criteria decision‐making approach for flood susceptibility analysis in large ungauged watersheds

AbstractCharacterizing and identification of flood‐susceptible areas can be a solution to mitigate the damages and fatality rate. This study proposes a novel hybrid MCDM framework to assess flood susceptibility in large ungauged watersheds dealing with data scarcity issues. The proposed method examines the interdependencies and causal relationships between various criteria affecting the flooding procedure using the DEcision‐MAking Trial and Evaluation Laboratory (DEMATEL). Moreover, since experts' opinions contain uncertainty, the fuzzy logic is integrated with DEMATEL to overcome this shortcoming. Then, the local weights of criteria were estimated using the Best–Worst Method (BWM) to enhance the pairwise comparisons process. Final criteria weights were obtained using Fuzzy DEMATEL and BWM results in Analytical Network Process (ANP) super‐matrix. Finally, the criteria were distributed spatially using the Complex Proportional Assessment of Alternatives (COPRAS) method based on obtained weights. The proposed method was compared with different approaches such as Fuzzy‐DEMATEL ANP, BWM, and AHP using several statistical measures. We concluded that the novel hybrid proposed method outperformed other approaches based on our results. Moreover, by overlaying classified maps with the historical flood events locations, it was concluded that 85.96% of flooded areas were classified as “high” and “very high.”

Browser Selection for Android Smartphones Using Novel Fuzzy Hybrid Multi Criteria Decision Making Technique

IT and Telecommunication sector has grown massively over the past few decades. Mobile phones that were initially developed for making calls and now become an essential item and are just not restricted to calling. They have dominated most of the gadgets like computers, cameras etc. Regularly people come across an extensive number of enhanced and better-quality features being inbuilt with them. A variety of mobile phones with different shapes and sizes are manufactured within a wide range of budgets. This is the key motivation behind an exponential growth in the number of users and the arrival of new manufacturers in the field. Along with this growth, there is a fast growth of mobile application software providers also. Apart from calling, many consumers use smartphones for browsing the internet. This puts users into a dilemma to select a better browser for their smartphone to fulfill their requirements. With this aim, an attempt is made in this paper for the evaluation and selection of a better browser. To achieve this, a hybrid Multi Criteria Decision Making (MCDM) approach is proposed by combining COPRAS (Complex Proportional Assessment of alternatives) technique and Fuzzy Analytical Hierarchy Process (FAHP).

Improvement projects with an environmental focus: A novel approach for prioritization

Employment of a systematic approach for prioritization of improvement projects and addressing the voice of the stakeholders are imperative for organizations in the current business circumstances. This study suggests a novel approach that employs multi-criteria decision-making (MCDM) methods for project prioritization. A combination of step-wise weight assessment ratio analysis (SWARA) method and house of quality (HOQ) is used in the calculation of the importance of criteria, followed by utilization of criteria importance in COmplex PRoportional ASsessment of alternatives with grey relations (COPRAS-G) for selection of the final project. It considers environmental effects alongside traditional criteria. Innovation in this study is in the combination of the MCDMs with HOQ and prioritizing projects considering the impact on the environment. The advantages are efficiency and simplicity. The practical focus of the approach is illustrated using a case example. The approach is used for the prioritization of projects that apply the Define–Measure–Analyze–Improve–Control (DMAIC) framework in a Six Sigma organization. The evaluation of three DMAIC projects suggested taking up Project C. The illustration has shown applicability in real-life situations. Thus, the novel approach identifies an environment-friendly project that satisfies the stakeholders the most. The utilization of Grey MCDM method makes the approach suitable for use in an uncertain environment.

Comparative assessment over the selection of lean supply chain practices through fuzzy integrated principal component analysis, gray relational analysis, and complex proportional assessment approaches

Due to the competitive market, the organizations look for performance improvement in their supply chain activities. Lean principles aim to reduce waste, and many research works have explored their effectiveness in the supply chain. Yet, industries face the problem of selecting appropriate lean supply chain management practices for their present environment. The present study performed a detailed literature study to identify majorly adapted lean supply chain management practices and generalize the most important ones with lesser implementation issues. For this purpose, the multi-criteria decision-making approaches, namely, gray relational analysis and complex proportional assessment of alternatives, are used to rank the identified lean supply chain management practices. Principal component analysis was used to generate criteria weights for computations. Out of 28 selected lean supply chain management practices from the literature, seven high-priority lean supply chain management practices are recommended as a generalized list as a result of prioritization by multi-criteria decision-making approaches such as total quality management, just-in-time production, pull system/kanban, 5S, information technology, work standardization, and customer relationship management. This study will benefit the practitioners to quickly identify suitable lean supply chain management practices to enhance their supply chain network, which can result in substantial cost savings.

Materials selection for choosing the best composite blend polymeric membrane for hydrogen/oxygen proton exchange membrane fuel cell

Aromatic sulfonated polymers as a suitable candidate for Nafion membrane in proton exchange membrane fuel cells are the subject of many research activities. It has proved that these polymers need higher ion exchange capacities to reach the same proton conductivities compared to the Nafion membrane, which is a result of their different microstructures. Accordingly, to compensate different microstructures in the Nafion and sulfonated aromatic substitutions, several composite blend membranes of poly(ether sulfone) (PES) and poly(ether ether ketone) (PEEK), including electrospun fibers of highly-sulfonated/non-sulfonated PEEK and PES polymers have prepared. For comparison, two membranes with a routine solution-casting technique also have been made. The membrane-electrode assemblies are tested in H2/O2 single-cell. Before that, characterization measurements have performed for all membranes. To select the best sample between prepared membranes, multi-criteria decision-making (MCDM) have used, and to achieve more reliable results, four techniques of Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE), COmplex PRoportional ASsessment of alternatives (COPRAS), and VIekriterijumsko KOmpromisno Rangiranje (VIKOR) have applied. According to the experiments and MCDM methods, composite blend membrane containing sulfonated electrospun fibers of PEEK in non-sulfonated PES matrix gains the best rank among all membranes.

Planning and establishment of battery swapping station - A support for faster electric vehicle adoption

Establishing Battery Swapping Station (BSS) is categorized as one of the means that can ignite faster adaptability of Electric Vehicles (EVs). For the lucrative performance of BSS, proper selection of an ideal location is crucial. This study uses the concept of the Fuzzy with Multiple Criteria Decision Making (MCDM) method to plan the optimum location of BSS, and is also an innovative type of work done on Indian subcontinent as per the knowledge of authors. With reference from some existing research and literature, an evaluation system is established, and then different criteria from economic, technical, and social aspects are considered for site selection of BSS. The TFN (Triangular Fuzzy Number) has been used to overcome the uncertainty due to insufficient information. Then, using Fuzzy based TFN Method with consideration of the preference within the criteria; weights of the criteria are obtained. Further COPRAS (Complex Proportional Assessment of Alternatives) methodology is applied to rank the selected locations in Kolkata Metropolitan Area (KMA), India. This paper concludes that the cost-related criteria like payback period, land acquisition cost, and machinery purchasing cost dominate other criteria. The area under Kolkata Municipal Corporation and the Western part of North 24 Parganas rank higher than other selected locations; thus, they are suitable for establishing BSS within the KMA, India. The outcome of this paper becomes vital for stakeholders and planners to select the optimum location of BSS. The approached methodology in this paper can be used in any analogous research with the related objective.

Towards sustainable cities: A sustainability assessment study for metropolitan cities in Turkey via a hybridized IT2F-AHP and COPRAS approach

Accelerating trends of urbanization enforce the integration of sustainability principles into urban planning in a local scale to foster prosperity for the next generation of cities. This study incorporates fifty-three indicators on economic, social, environmental, and institutional dimensions to develop a Sustainable Cities Index (SCI) and assess the sustainability performance of thirty metropolitans in Turkey over 2010-2018. Turkish metropolitans constitute an appealing case study due to the rapid urbanization within the same time span. To answer how new metropolitans have been doing and whether they perform better than formerly declared metropolitans in Turkey, we propose a novel methodology with three stages that hybridizes Interval Type-2 Fuzzy Analytical Hierarchy Process (IT2F-AHP) and Complex Proportional Assessment of Alternatives (COPRAS). The former captures a high degree of uncertainty due to the subjective weight assignment by the experts, while the latter calculates aggregate scores for 30 cities. Finally, we conduct posthoc analyses to examine the significance of the urbanization policies in Turkey on the SCI scores. Thus, the study provides valuable insights into urbanization practices and encourages local administrations to spend more effort balancing the benefits and costs of public policies on sustainability.

Strategic supplier selection for renewable energy supply chain under green capabilities (fuzzy BWM-WASPAS-COPRAS approach)

The supplier selection problem (SSP) is a significant issue in renewable supply chain management (RSCM). Selecting a strategic green supplier can not only discover the sustainable development of supply chains but also optimize the consumption rate of resources and decrease the negative environmental effects, which adopts to the green development context. As a multiple criteria group decision-making (MCGDM) problem, choosing a strategic green supplier is important to renewable supply chains. However, how to choose a strategic green supplier for supply chains is a great effort. Hence, In the present work, evaluating a set of strategic suppliers is primarily based on green capabilities by using an integrated fuzzy Best Worst Method (FBWM) with the other two techniques, namely COPRAS (Complex Proportional Assessment of Alternatives) and WASPAS (Weighted Aggregated Sum-Product Assessment). Initially, nine strategic supplier selection criteria have been identified through literature review and a real-world case study of Iran's renewable energy supply chain is deliberated to exhibit the proposed framework's applicability. The applied methodology and its analysis will provide insight to decision-makers of strategic supplier selection. It may aid decision-makers and the procurement department in differentiating the significant strategic green supplier selection criteria and assess the strategic green supplier in the local and global market supply chain. Finally, the strengths and limitation of the framework are discussed by using comparative analysis with other methods.

Use of hybrid MCDM methods for site location of solar-powered hydrogen production plants in Uzbekistan

Uzbekistan is a developing country where energy demand is rising, and it has many problems in the energy supply sector. This issue leads to a mismatch between energy consumption and supply in this country. Most of the country’s energy supply comes from natural gas. A major part of Uzbekistan’s energy demand can be provided by solar power. The purpose of this study is to determine the position of using solar energy to generate hydrogen in 13 provinces of Uzbekistan. This study is performed by using the Stepwise Weight Assessment Ratio Analysis (SWARA) for criteria weighting and using the Weighted Aggregated Sum Product Assessment (WASPAS), the COmplex PRoportional Assessment of alternatives (COPRAS), the Evaluation Based on Distance from Average Solution (EDAS), and the Weight Sum Model (WSM) for ranking locations. The results of criteria weighting with SWARA show that the top three most important criteria are solar radiation, sun hours, and average wind speed with weights of 0.248, 0.2, and 0.154, respectively. All ranking methods identify Bukhara province as the most suitable place in Uzbekistan for solar-powered hydrogen production. It is estimated that 1539.2 MW of solar power and 24.92 tons of hydrogen are produced annually in Bukhara.

Optimization Agricultural Supply Chain: A Case Study of Fertilizer Supplier Selection

The 21st century is associated with the Industrial Revolution 4.0 and the organic agriculture trend, making the utilization of high-quality fertilizers, abundant nutritional content, economical, and no affect to environment pollution. According to the new concept, clean agricultural production and organic agricultural products are not allowed to excessively use synthetic chemicals such as chemical fertilizers, and plant protection drugs, but priority is to use manure, organic fertilizers, and natural mineral fertilizers. Fertilizer must meet the balanced nutritional requirements of crops, maintain, and improve the fertility of the ground, protect the surrounding ecosystem, and leave harmful effects in agricultural products, products with high quality, safe for users and high economic efficiency for producers. To achieve the above goal, the selection of a fertilizer supplier is an important decision, supporting the supply chain's sustainable development, fertilizer supplier selection is a multicriteria decision making model, the decision maker must assess all qualitative and quantitative factors. In this paper, the author proposed an integer decision making model including Fuzzy Analytic Hierarchy Process (FAHP) and Complex Proportional Assessment of Alternatives (COPRAS) for fertilizer supplier selection. The weightings of the criteria are calculated by using FAHP, COPRAS is then applied for ranking some potential fertilizer suppliers. The efficiency of the proposed models is proved by a case study conducted in a farm located in the south of Vietnam. This research is the first fertilizer supplier evaluation and se-lection model in Vietnam by interviewing experts and reviewing the literature. Re-search result is to provide a case study on evaluating supplier in agricultural supply chain utilizing the model proposed by the combination of FAHP and COPRAS models.

An integrated decision making approach for the selection of battery recycling plant location under sustainable environment

Growing economic crisis and strict government policies and regulations regarding the environment have forced the battery industries to practice the recycling process for both economic and environmental benefits. Moreover the consideration of sustainability issues makes the recycling process more significant, successful implementation of recycling activity in the battery industry requires several strategic decisions. Among these decisions, a complex decision faced by the management is to identify the suitable location for the establishment of a formal Battery Recycling Plant (BRP). In this research work, a three-stage hybrid methodology with the combination of ISM (Interpretive Structural Modeling), fuzzy AHP (Analytic Hierarchy Process), and fuzzy COPRAS (Complex Proportional Assessment of Alternatives) methods was proposed to select the best sustainable location from the available options for BRP in India. In this study, a total of eight experts were selected from both academia and industry. Initially in this paper, 4 main sustainable criteria and 20 sustainable sub-criteria were considered from the literature review and field visits along with experts’ opinions for evaluation of alternatives. This work contains three stages. In the first stage, the ISM method was used to filter 18 important sustainable sub-criteria from the primary list of 20 sub-criteria, based on its higher driving power. Then, fuzzy AHP was applied in the second stage to compute the criteria weights. In the last stage, the fuzzy COPRAS was used to rank and choose the best sustainable location for BRP. The findings emphasize that the Environmental protection level, Distance from residential areas, Distance from water source, Capital investment, Government policies, Social acceptance, Availability of scrap batteries, and Availability of utilities were the most significant criteria in the sustainability dimension. Thus, the present work helps the management in the selection of an appropriate sustainable location for BRP.

Fuzzy COmplex PRoportional ASsessment of alternatives‐based Node Cooperation Enforcing Trust Estimation Scheme for enhancing Quality of Service during reliable data dissemination in Mobile Ad hoc Networks

SummaryTrust is considered as the most significant factor that helps in enforcing cooperation among the autonomous nodes of Mobile Ad hoc Network (MANETs). The computation of trust is essential for assessing the level of cooperation rendered by each individual mobile toward the activity of data routing. The calculation of trust in a self‐configuring and infrastructure‐less network is a challenge due to the dynamic movement of mobile nodes. Moreover, the trust of intermediate nodes in the routing path needs to be estimated for preventing the deterioration of network performance. In this paper, a Fuzzy COPRAS‐based Node Cooperation Enforcing Trust Estimation (FCOPRAS‐NCETE) Scheme was proposed for maintaining superior Quality of Service (QoS) in the event of reliable data dissemination. This proposed FCOPRAS‐NCETE Scheme was proposed for comprehensive ranking of mobile nodes acting as intermediate nodes between the source and destination nodes. It incorporated the benefits of fuzzy set theory and COmplex PRoportional ASsessment of alternatives (COPRAS) to determine the trust of intermediate nodes for isolating them from the routing path in the uncertain routing process with the objective to maintain superior QoS in the network. The simulation experiments of the proposed FCOPRAS‐NCETE Scheme conducted using ns‐2 confirmed its predominance in improving the throughput, packet dissemination rate, packet loss rate, energy consumptions and total overhead with different number of mobile nodes, CBR traffic rate and pairs of source and destination nodes in the network.

An integrated and comprehensive fuzzy multicriteria model for supplier selection in digital supply chains

Digital supply chains (DSCs) are collaborative digital systems designed to quickly and efficiently move information, products, and services through global supply chains. The physical flow of products in traditional supply chains is replaced by the digital flow of information in DSCs. This digitalization has changed the conventional supplier selection processes. We propose an integrated and comprehensive fuzzy multicriteria model for supplier selection in DSCs. The proposed model integrates the fuzzy best-worst method (BWM) with the fuzzy multi-objective optimization based on ratio analysis plus full multiplicative form (MULTIMOORA), fuzzy complex proportional assessment of alternatives (COPRAS), and fuzzy technique for order preference by similarity to ideal solution (TOPSIS). The fuzzy BWM approach is used to measure the importance weights of the digital criteria. The fuzzy MULTIMOORA, fuzzy COPRAS, and fuzzy TOPSIS methods are used as prioritization methods to rank the suppliers. The maximize agreement heuristic (MAH) is used to aggregate the supplier rankings obtained from the prioritization methods into a consensus ranking. We present a real-world case study in a manufacturing company to demonstrate the applicability of the proposed method.

Multiobjective Optimization of Fabrication Parameters of Jute Fiber/Polyester Composites with Egg Shell Powder and Nanoclay Filler

In the present study, a model is presented to optimize the fabrication parameters of natural fiber reinforced polyester matrix composites with dual fillers. In particular, jute fiber mat was chosen as reinforcement and eggshell powder (ESP) and montmorillonite nanoclay (NC) were selected as fillers. The weight per square meter (GSM) of the fiber, the weight percentage of ESP and NC have been chosen as independent variables and the influence of these variables on tensile, flexural and impact strength of the composite has been inspected. The permutations of the different combinations of factors are intended to accomplish higher interfacial strength with the lowest possible number of tested specimens. The experiments were designed by the Taguchi strategy and a novel multi-objective optimization technique named COPRAS (COmplex PRoportional ASsessment of alternatives) was used to determine the optimal parameter combinations. Affirmation tests were performed with the optimal parameter settings and the mechanical properties were evaluated and compared. Experimental results show that fiber GSM and eggshell powder content are significant variables that improve mechanical strength, while the nanoclay appears less important.

Analysing the voice of customers by a hybrid fuzzy decision-making approach in a developing country's automotive market

PurposeThis paper analyses the voice of customers (VoCs) using a hybrid clustering multi-criteria decision-making (MCDM) approach. The proposed method serves as an efficient tool for how to approach multiple decision-making involving a large set of countrywide customer complaints in the Iranian automotive sector.Design/methodology/approachThe countrywide data comprising 3,342 customer complaints (VoCs) were gathered. A total of seven determinant complaint criteria were identified in brainstorming sessions with three groups (six each) of experts employing the fuzzy Delphi method. The weights of these criteria were assigned by applying the fuzzy best–worst method (FBWM) to identify the severity of the complaints. Subsequently, the complaints were clustered into five categories with respective customer locations (province), car type and manufacturer using the K-mean method and further prioritised and ranked employing the fuzzy complex proportional assessment of alternatives (FCOPRAS) method.FindingsThe results indicated that the majority of complaints (1,027) from the various regions of the country belonged to one specific model of car made by a particular producer. The analyses revealed that only a few complaints were related to product quality, with the majority related to service and financial processes including delays in automobile delivery, delays in calculating monthly instalments, price variation, failure to provide a registration ( licence) and failure to supply the agreed product. The proposed method is an efficient way to solve large-scale multidimensional problems and provide a robust and reliable set of results.Practical implicationsThe proposed method makes it much easier for management to deal with complaints by significantly reducing their number. The highest-ranked complaints from customers of the car industry in Iran are those related to delivery time, price alternations, customer service support and quality issues. Surveying the list of complaints shows that paying attention to the four most voiced complaints can reduce them more than 54%. Management can make appropriate strategies to improve the production quality as well as business processes, thus producing a significant number of customer complaints.Originality/valueThis paper proposes a comprehensive approach to critically analyse the VoCs by combining qualitative and decision-making approaches including K-mean, FCOPRAS, fuzzy Delphi and FBWM. This is the first paper that analyses the VoCs in the automotive sector in a developing country’s context involving large-scale decision-making problem-solving.