Evaluating and Ranking Factors Promoting Green Consumer Behavior on C2C E-Commerce Websites Using the PARETO – FUZZY – AHP – TOPSIS Model

This work is licensed under a Creative Commons Attribution 4.0 International License. The license permits unrestricted use, distribution, and reproduction in any medium, on the condition that users give exact credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if they made any changes. Evaluating and Ranking Factors Promoting Green Consumer Behavior on C2C E-Commerce Websites Using the PARETO – FUZZY – AHP – TOPSIS Model Tran Trung Dung  Hanoi University of Natural Resources and Environment, Viet Nam Abstract In the context of strong digital transformation, online shopping has become the preferred choice of many consumers. Peer-to-peer (C2C) e-commerce models are developing rapidly, creating a flexible and diverse trading environment with products and prices. However, the rich amount of information and large number of sellers on these platforms make the product selection process complicated, leading interested consumers to get lost in the shopping matrix. In order to help consumers shop smarter, the study proposes applying the integrated model set PARETO - FUZZY - AHP - TOPSIS to evaluate and rank factors affecting green consumer behavior in the context of online shopping on C2C websites. Keywords: E-commerce, green consumer behavior, C2C e-commerce model, Pareto principle, Fuzzy - AHP model, TOPSIS model, Fuzzy - AHP - TOPSIS model, C2C website ranking. JEL Classification codes: E21, P64. Suggested citation: Dung, T.T. (2025). Evaluating and Ranking Factors Promoting Green Consumer Behavior on C2C E-Commerce Websites Using the PARETO – FUZZY – AHP – TOPSIS Model. European Journal of Management, Economics and Business, 2(6), 273-279. DOI: 10.59324/ejmeb.2025.2(6).20 Introduction The rapid development of e-commerce in the digital economy era has changed the way consumers approach and make shopping decisions. In particular, the green consumption trend is emerging as an important factor affecting online shopping behavior on C2C e-commerce platforms. However, the factors that shape green consumption behavior are often qualitative in nature, difficult to define clear boundaries, and are influenced by consumers' emotional perceptions. To overcome this limitation, the study proposes the use of the integrated model PARETO - FUZZY - AHP - TOPSIS as a multi-criteria approach, allowing for a more objective assessment of priority levels. Through this model, six typical C2C websites are evaluated and ranked according to the level of consumer choice in the context of green consumption. The research results are expected to provide empirical evidence to support the proposal of solutions to promote e-commerce development towards green consumption. EJMEB (ISSN 3041-2102) | VOLUME 2 | NUMBER 6 | 2025 274 Literature Review and Previous Research Studies The Pareto principle, also known as the 80/20 rule, was proposed by Vilfredo Pareto (1897) after observing the distribution of wealth in society. Over time, this rule is not only limited to economics but has become an important tool in management analysis. In management science research, Pareto is used as an initial screening step that allows researchers to eliminate secondary factors to focus on the key group of factors that create the majority of the impact, thereby making the analysis more concise and accurate. Fuzzy Logic was introduced by Zadeh (1965) as one of the important foundations of modern artificial intelligence science. Unlike traditional binary logic models (0-1), Fuzzy Logic describes intermediate states with true-false levels in a “fuzzy” form, reflecting more accurately how people think and evaluate in reality. In consumer behavior research, Fuzzy Logic helps quantify emotional assessments into fuzzy numbers, allowing for the handling of ambiguity in consumer choices, levels of agreement, or feelings. When combined with AHP, fuzzy-AHP increases reliability and reduces bias due to subjective feelings to create a solid foundation for the TOPSIS ranking step. AHP is a multi-criteria decision-making method developed by Professor Thomas L. Saaty in the 1970s. This method helps determine the priority of each factor influencing green purchasing decisions on C2C websites. TOPSIS is a multi-criteria decision-making method proposed by Hwang and Yoon (1981), based on the principle: The optimal solution is the solution that has the closest distance to the positive ideal solution and the farthest distance to the negative ideal solution. In this study, it is used to rank the priority order for C2C websites. Methodology and Proposed Model The study was conducted over 5 months to survey 1,050 consumers and 8 experts from various positions in the field of e-commerce, including 4 lecturers who research and teach e-commerce, 1 e-commerce business operator, 1 digital marketing specialist, 1 marketing manager and 1 website programmer. Step 1: Survey and collect data Step 2: Apply Pareto to identify key factors. Step 3: Identify a set of evaluation criteria based on core factors. Step 4: Build a research model Step 5: Create an evaluation matrix according to Fuzzy AHP Step 6: Evaluate the impact of criteria on green consumer behavior Step 7: Rank criteria that influence online shopping decisions Step 8: Rank C2C websites in order of priority Research model (Figure 1). EJMEB (ISSN 3041-2102) | VOLUME 2 | NUMBER 6 | 2025 275 Figure 1. Hierarchical Structure Diagram Source: Author's own proposed research model Other domestic websites such as Tiki.vn (30.3%), Lazada.vn (18.7%), Chotot.com (12.4%), Sendo.vn (10.2%), and Taobao.vn (23.6%) are selected at an average level, reflecting the differentiation in consumer behavior depending on product type, pricing policy, and transaction experience. Although Tiki and Lazada previously operated under the B2C model, their expansion into the individual seller model has helped these two platforms to some extent participate in the C2C market. Meanwhile, Cho Tot and Sendo still maintain their role as old classifieds and sales platforms - suitable for the consumer group that prefers direct transactions and low prices. In addition, the “Other” group (20%) includes emerging platforms such as Facebook Marketplace, Zalo, or small classifieds websites, demonstrating the flexible expansion of C2C consumer behavior to social media channels and mobile applications. Based on the results of a survey of 1,050 consumers and interviews with 8 experts, 18 criteria were proposed to be included in the evaluation model. After using the Pareto 80/20 principle, 13 key factors were identified to be included in the evaluation model as shown in Table 1. Table 1. Table of Criteria Used in Evaluating C2C E-Commerce Websites No. Survey element Proposed criteria in the model Criteria code 1 Product brand Green product brand TC1 2 Selling price Green selling price TC2 3 Product quality Green product quality TC3 4 Product images Green product images TC4 5 Product information Green product information TC5 6 Online brand reputation Green online brand reputation TC6 7 Product catalog Green product catalog TC7 8 Shipping costs Green shipping costs TC8 9 Promotional program Green Promotion Program TC9 10 Payment method Green payment method TC10 11 Delivery time Green delivery time TC11 12 Return policy Green return policy TC12 13 Delivery unit Green delivery unit TC13 Source: Author's suggestion The selected criteria for evaluation are the criteria that have a high level of influence on consumers' purchasing behavior when choosing to buy online on C2C websites. EJMEB (ISSN 3041-2102) | VOLUME 2 | NUMBER 6 | 2025 276 Table 2. Table of Linguistic Variables and Corresponding Fuzzy Numbers Language variables Variable symbol Language variable code The corresponding triangular fuzzy numbers Inverse of triangular fuzzy numbers Equally important BN 1 (1, 1, 3) (1/3, 1/1, 1/1) More importantly TH 3 (1, 3, 5) (1/5, 1/3, 1/1) More important NH 5 (3, 5, 7) (1/7, 1/5, 1/3) Very important RT 7 (5, 7, 9) (1/9, 1/7, 1/5) Extremely important CT 9 (7, 9, 9) (1/9, 1/9, 1/7) Source: Author's suggestion In this study, this author will use the scale from 1 to 9 (Sodhi & Prabhakar, 2012) to convert the linguistic variable into Fuzzy number in Table 2. In which the selected conversions include 5 ranges to perform pairwise comparisons between fuzzy parameters. The linguistic variable will be converted to suit the survey and evaluation content. Typical websites used in the research model for evaluation are Shopee, Tiki, Lazada, Sendo, Chotot, Taobao will be denoted as W1, W2, W3, W4, W5, W6 respectively for convenience of calculation. The results of constructing the standardized matrix are as Table 3. Table 3. Ranking of Influencing Factors According to the Standardized Matrix and Ideal Solution Criteria MT normalized weights A+ ATC Ranking W1 W2 W3 W4 W5 W6 TC1 0.194 0.228 0.143 0.139 0.143 0.186 0.228 0.139 6 TC2 0.157 0.183 0.132 0.151 0.170 0.151 0.132 0.183 12 TC3 0.205 0.149 0.136 0.149 0.111 0.136 0.205 0.111 4 TC4 0.206 0.225 0.159 0.168 0.178 0.234 0.234 0.159 8 TC5 0.217 0.235 0.181 0.163 0.163 0.254 0.254 0.163 7 TC6 0.213 0.190 0.167 0.144 0.190 0.213 0.213 0.144 9 TC7 0.269 0.192 0.154 0.154 0.173 0.250 0.269 0.154 5 TC8 0,200 0.154 0.154 0.162 0.177 0.177 0.154 0.200 11 TC9 0.214 0.182 0.190 0.127 0.111 0.174 0.214 0.111 3 TC10 0,200 0.166 0.146 0.133 0.113 0.139 0.200 0.113 2 TC11 0.216 0.216 0.164 0.138 0.138 0.198 0.138 0.216 13 TC12 0.233 0.183 0.166 0.133 0.124 0.183 0.233 0.124 1 TC13 0.188 0.204 0.157 0.141 0.141 0.173 0.204 0.141 10 Source: Author's suggestion The most important criterion is the green return policy (TC12) with the highest CC value, the green return policy is identified as the factor that most strongly influences consumers' decision to choose a C2C platform. This shows that green shoppers are not only interested in the product itself but also pay attention to after-sales commitment, transparency and the "green" level of the return process. The next group of criteria with the highest priority: Green payment method (TC10) ranked second, showing that consumers highly appreciate electronic payment methods to reduce paperwork and be environmentally friendly. Green promotion program (TC9) also has a significant influence, thereby reflecting the trend of consumers paying attention to incentives associated with environmental messages. Green product quality (TC3) continues to be a basic factor for consumers to evaluate the true value of environmentally friendly products. Green product categories (TC7) EJMEB (ISSN 3041-2102) | VOLUME 2 | NUMBER 6 | 2025 277 are ranked in the important group, showing that the diversity of green products increases choice and promotes consumer purchasing behavior. Medium-influence criteria group: Criteria such as green product brand (TC1), green product image (TC4), green product information (TC5), green online brand reputation (TC6) and green delivery unit (TC13) have a medium CC score, showing that consumers are still interested but do not consider this the most decisive factor. Least-influence criteria group: Green selling price (TC2) is near the bottom, showing that consumers who buy green products do not consider price as the most important factor; they are willing to pay more for environmentally friendly products. Green shipping costs (TC8) have a low priority, possibly because platforms often have policies to support shipping costs or consumers consider this an additional cost, not a strong decision. Green delivery time (TC11) ranked last, showing that consumers are willing to accept slower delivery if it helps reduce carbon emissions or use environmentally friendly delivery methods. The results emphasize that green consumer behavior on C2C platforms is not only dependent on the product itself but is also strongly influenced by: “Green” support service policies or transparency commitments and core quality of green products. In contrast, price and delivery speed are no longer the most important factors as in traditional shopping, showing that green consumers are willing to trade short-term benefits for more sustainable consumption. Table 4. Table of Distance between Options and Closeness Index Distance Option options W1 W2 W3 W4 W5 W6 𝑑𝑖 + 0.012 0.023 0.049 0.068 0.073 0.041 𝑑𝑖 − 0.067 0.039 0.018 0.010 0.009 0.041 𝑑𝑖 ++ 𝑑𝑖 − 0,079 0.062 0.067 0.078 0.082 0.082 CCi 0.848 0.629 0.268 0.128 0.109 0.500 Ranking 1 2 4 5 6 3 Conclusion Research results show that Shopee.vn is considered the most optimal C2C website for green online shopping behavior in Vietnam thanks to its ability to combine economic benefits and sustainable values, in line with modern consumer trends. Based on the research results, it is hoped that websites will be able to build their own competitive strategies in accordance with customer needs. Proposing Optimal Solutions to Promote Green Consumer Behavior on C2C E-Commerce Websites Green product quality: C2C needs to establish a seller verification system. Green selling price: C2C needs to apply optimal selling price strategies. Green product information: C2C needs to establish a dynamic information system for products. Green product catalog: C2C needs to expand the green product catalog in 3 dimensions. Green product image: C2C needs to build realistic illustrations. Green product brand: C2C needs to strengthen public relations activities. Green shipping cost: C2C needs to apply green cost and green delivery unit. Green delivery time: C2C needs to establish a green scheduling system. EJMEB (ISSN 3041-2102) | VOLUME 2 | NUMBER 6 | 2025 278 Green delivery unit: C2C needs to cooperate with units according to green standards. Green return policy: C2C needs to establish a flexible return policy. Green payment method: C2C needs to provide a variety of electronic payments. Green promotion program: C2C needs to design in the direction of increasing social benefits. Green website interface: C2C needs to design a friendly and easy-to-use interface. Green online brand reputation: C2C needs to increase promotional activities through green brand ambassadors. Acknowledgements This article is the research result of the topic "Research on the application of Pareto - Fuzzy - AHP - TOPSIS model in analyzing consumer behavior on C2C e-commerce websites aiming at green consumption" (Topic code: HUNRE.2025.06.20), sponsored by Hanoi University of Natural Resources and Environment. References Gefen, D. (2000). E-commerce: The role of familiarity and trust. Omega, 28(6), 725–737. https://doi.org/10.1016/S0305-0483(00)00021-9 Hwang, C. L., & Yoon, K. (1981). Multiple attribute decision making: Methods and applications. Springer-Verlag. https://doi.org/10.1007/978-3-642-48318-9 Laudon, K. C., & Traver, C. G. (2022). E-commerce 2021–2022: Business, technology, society (17th ed.). Pearson. Li, R., & Sun, T. (2020). Assessing factors for designing a successful B2C e-commerce website using fuzzy AHP and TOPSIS-Grey methodology. Symmetry, 12(3), 363. https://doi.org/10.3390/sym12030363 Pareto, V. (1897). Cours d’économie politique. Lausanne: F. Rouge. Pourjavad, E., & Shahin, A. (2020). Green supplier development programmes selection: A hybrid fuzzy multi-criteria decision-making approach. International Journal of Sustainable Engineering, 13(6), 463–472. https://doi.org/10.1080/19397038.2020.1773569 Saaty, T. L. (1980). The analytic hierarchy process: Planning, priority setting, resource allocation. McGraw-Hill. Sequeira, M., Adlemo, A., & Hilletofth, P. (2023). A hybrid fuzzy-AHP-TOPSIS model for evaluation of manufacturing relocation decisions. Operations Management Research, 16(1), 164– 191. https://doi.org/10.1007/s12063-022-00284-6 Sıcakyüz, Ç., & Erdebilli, B. (2023). Is e-trust a driver of sustainability? An assessment of Turkish e-commerce sector with an extended intuitionistic fuzzy ORESTE approach. Sustainability, 15(13), 10693. https://doi.org/10.3390/su151310693 Smith, M. D., & Brynjolfsson, E. (2001). Consumer decision-making at an Internet shopbot: Brand still matters. Journal of Industrial Economics, 49(4), 541–558. https://doi.org/10.1111/14676451.00162 EJMEB (ISSN 3041-2102) | VOLUME 2 | NUMBER 6 | 2025 279 Sodhi, M. S., & Prabhakar, A. (2012). AHP–fuzzy approach for evaluating service quality in academic libraries. International Journal of Productivity and Quality Management, 10(4), 519–540. Turban, E., Outland, J., King, D., Lee, J. K., Liang, T.-P., & Turban, D. (2018). Electronic commerce 2018: A managerial and social networks perspective (9th ed.). Springer. https://doi.org/10.1007/978-3-319-58715-8 Wijayanti, W. R., Dewi, W. R., & Ardi, F. (2018). The integration of fuzzy AHP and TOPSIS methods to evaluate the service quality of e-commerce websites. Journal of Theoretical and Applied Information Technology, 96(13), 4065–4073.