Integrating the BWM and TOPSIS algorithm to evaluate the optimal token exchanges platform in Taiwan

    Wei-Yuan Wang Affiliation
    ; Yeh-Cheng Yang Affiliation
    ; Chun-Yueh Lin Affiliation


This research presents procedures for determining the optimal solution of token exchanges platform for investors in Taiwan via integrating the best-worst method (BWM) and the technique for ordering preference by similarity to the ideal solution (TOPSIS). Firstly, this research applies the modified Delphi method to develop the perspectives and factors via literature review and experts opinion. Secondly, the BWM is implemented to obtain weights of perspectives and factors on the linear programming concept. Thirdly, the TOPSIS model is used to rank the optimal solution of the token exchange for investors or corporations. Finally, the proposed model BWMTOPSIS-based procedures will list the optimal token exchanges platform on the three token exchange platforms to investors or corporations in Taiwan on the basis of their rankings in the architecture. The proposed combination framework is able to provide academic and commerce support to investors or corporations in implementing the token into their portfolio as a valuable objective guide to determine the optimal token exchange platform.

First published online 09 December 2021

Keyword : bitcoin, token exchange platform, decision-making, Delphi method, Best-Worst Method (BWM), TOPSIS

How to Cite
Wang, W.-Y., Yang, Y.-C., & Lin, C.-Y. (2022). Integrating the BWM and TOPSIS algorithm to evaluate the optimal token exchanges platform in Taiwan . Technological and Economic Development of Economy, 28(2), 358–380.
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Feb 23, 2022
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Achu, A. L., Thomas, J., & Reghunath, R. (2020). Multi-criteria decision analysis for delineation of groundwater potential zones in a tropical river basin using remote sensing, GIS and analytical hierarchy process (AHP). Groundwater for Sustainable Development, 10, 100365.

Ahluwalia, S., Mahto, R. V., & Guerrero, M. (2020). Blockchain technology and startup financing: A transaction cost economics perspective. Technological Forecasting and Social Change, 151, 119854.

Alexander, C., Choi, J., Massie, H. R., & Sohn, S. (2020). Price discovery and microstructure in ether spot and derivative markets. International Review of Financial Analysis, 71, 101506.

Ali-Yrkko, J., Rouvinen, P., Seppala, T., & Yla-Anttila, P. (2011). Who captures value in global supply chains? Case Nokia N95 Smartphone. Journal of Industry, Competition and Trade, 11(3), 263–278.

Andrada-Félix, J., Fernandez-Perez, A., & Sosvilla-Rivero, S. (2020). Distant or close cousins: Connectedness between cryptocurrencies and tradi-tional currencies volatilities. Journal of International Financial Markets, Institutions and Money, 67, 101219.

Arslanian, H., & Fischer, F. (2019). The crypto-asset ecosystem. In The future of finance (pp. 157–163). Palgrave Macmillan, Cham.

Aziz, A. T. I. F. (2019). Cryptocurrency: Evolution & legal dimension. International Journal of Business, Economics and Law, 18(4), 31–33.

Baidya, R., Dey, P. K., Ghosh, S. K., & Petridis, K. (2018). Strategic maintenance technique selection using combined quality function deployment, the analytic hierarchy process and the benefit of doubt approach. The International Journal of Advanced Manufacturing Technology, 94(1–4), 31–44.

Bentov, I., Ji, Y., Zhang, F., Breidenbach, L., Daian, P., & Juels, A. (2019, November). Tesseract: Real-time cryptocurrency exchange using trust-ed hardware. In Proceedings of the 2019 ACM SIGSAC Conference on Computer and Communications Security (pp. 1521–1538).

Bouri, E., Lau, C. K. M., Lucey, B., & Roubaud, D. (2019). Trading volume and the predictability of return and volatility in the cryptocurrency market. Finance Research Letters, 29, 340–346.

Brauneis, A., & Mestel, R. (2019). Cryptocurrency-portfolios in a mean-variance framework. Finance Research Letters, 28, 259–264.

Bunjaku, F., Gorgieva-Trajkovska, O., & Miteva-Kacarski, E. (2017). Cryptocurrencies – advantages and disadvantages. Journal of Economics, 2(1), 31–39.

Chen, Y., & Bellavitis, C. (2020). Blockchain disruption and decentralized finance: The rise of decentralized business models. Journal of Business Venturing Insights, 13, e00151.

Chuen, D. L. K., Guo, L., & Wang, Y. (2018). Cryptocurrency: A new investment opportunity? The Journal of Alternative Investments, 20(3), 16–40.

Coin Market Cap. (2020). Cryptocurrencies by market capitalization. Retrieved August 25, 2020, from

CoinGecko. (2020a). NEXO market capitals. Retrieved July 09, 2020, from

CoinGecko. (2020b). Celsius network market capitals. Retrieved July 09, 2020, from

Conrad, C., Custovic, A., & Ghysels, E. (2018). Long-and short-term cryptocurrency volatility components: A GARCH-MIDAS analysis. Journal of Risk and Financial Management, 11(2), 23.

Corbet, S., Larkin, C., Lucey, B., Meegan, A., & Yarovaya, L. (2020). Cryptocurrency reaction to FOMC Announcements: Evidence of heteroge-neity based on blockchain stack position. Journal of Financial Stability, 46, 100706.

DeFi Market Cap. (2020). Top 100 Defi Tokens by market capitalization. Retrieved January 09, 2010, from

Easley, D., O’Hara, M., & Basu, S. (2019). From mining to markets: The evolution of bitcoin transaction fees. Journal of Financial Economics, 134(1), 91–109.

Enoksen, F. A., Landsnes, C. J., Lučivjanská, K., & Molnár, P. (2020). Understanding risk of bubbles in cryptocurrencies. Journal of Economic Behavior & Organization, 176, 129–144.

Ghosh, A., Gupta, S., Dua, A., & Kumar, N. (2020). Security of Cryptocurrencies in blockchain technology: State-of-art, challenges and future prospects. Journal of Network and Computer Applications, 163, 102635.

Hamdan, S., & Cheaitou, A. (2017). Supplier selection and order allocation with green criteria: An MCDM and multi-objective optimization ap-proach. Computers & Operations Research, 81, 282–304.

Hasson, F., & Keeney, S. (2011). Enhancing rigour in the Delphi technique research. Technological Forecasting and Social Change, 78(9), 1695–1704.

Ho, W., & Ma, X. (2018). The state-of-the-art integrations and applications of the analytic hierarchy process. European Journal of Operational Research, 267(2), 399–414.

Hwang, C., & Yoon, K. (1981). Multiple attribute decision making: Methods and application. Springer Publications.

Issaoui, Y., Khiat, A., Bahnasse, A., & Ouajji, H. (2019). Smart logistics: Study of the application of blockchain technology. Procedia Computer Science, 160, 266–271.

Ivaniuk, V. (2020). Cryptocurrency exchange regulation – An international review. Studia Prawnoustrojowe, 48, 67–77.

Kamaruzzaman, S. N., Lou, E. C. W., Wong, P. F., Wood, R., & Che-Ani, A. I. (2018). Developing weighting system for refurbishment building assessment scheme in Malaysia through analytic hierarchy process (AHP) approach. Energy Policy, 112, 280–290.

Kheybari, S., Kazemi, M., & Rezaei, J. (2019). Bioethanol facility location selection using best-worst method. Applied energy, 242, 612–623.

Kilic, B., & Ucler, C. (2019). Stress among ab-initio pilots: A model of contributing factors by AHP. Journal of Air Transport Management, 80, 101706.

Kimani, D., Adams, K., Attah-Boakye, R., Ullah, S., Frecknall-Hughes, J., & Kim, J. (2020). Blockchain, business and the fourth industrial revolu-tion: Whence, whither, wherefore and how? Technological Forecasting and Social Change, 161, 120254.

Kumar, G., Saha, R., Buchanan, W. J., Geetha, G., Thomas, R., Rai, M. K., Kim, T.-H. & Alazab, M. (2020). Decentralized accessibility of e-commerce products through blockchain technology. Sustainable Cities and Society, 62, 102361.

Libra Association. (2019). Libra White Paper. Retrieved August 26, 2020, from

Lin, C. Y. (2020). Optimal core operation in supply chain finance ecosystem by integrating the fuzzy algorithm and hierarchical framework. Inter-national Journal of Computational Intelligence Systems, 13(1), 259–274.

Lin, S. W. (2017). Identifying the critical success factors and an optimal solution for mobile technology adoption in travel agencies. International Journal of Tourism Research, 19(2), 127–144.

Lee, J. Y. (2019). A decentralized token economy: How blockchain and cryptocurrency can revolutionize business. Business Horizons, 62(6), 773–784.

Lee, S., Kim, B. S., Kim, Y., Kim, W., & Ahn, W. (2018). The framework for factors affecting technology transfer for suppliers and buyers of technology in Korea. Technology Analysis & Strategic Management, 30(2), 172–185.

Liang, F., Brunelli, M., & Rezaei, J. (2020). Consistency issues in the best worst method: Measurements and thresholds. Omega, 96, 102175.

Linden, G., Kraemer, K. L., & Dedrick, J. (2009). Who captures value in a global innovation network? The case of Apple’s iPod. Communications of the ACM, 52(3), 140–144.

Liu, W., Semeyutin, A., Lau, C. K. M., & Gozgor, G. (2020). Forecasting Value-at-Risk of Cryptocurrencies with RiskMetrics type models. Re-search in International Business and Finance, 54, 101259.

Luo, X. (2019). Application and evaluation of payment channel in hybrid decentralized Ethereum token exchange [Doctoral dissertation]. Univer-sity of British Columbia.

Luo, X., Cai, W., Wang, Z., Li, X., & Leung, C. V. (2019, May). A payment channel based hybrid decentralized ethereum token exchange. In 2019 IEEE International Conference on Blockchain and Cryptocurrency (ICBC) (pp. 48–49). IEEE.

Ma, F., Liang, C., Ma, Y., & Wahab, M. I. M. (2020). Cryptocurrency volatility forecasting: A Markov regime‐switching MIDAS approach. Journal of Forecasting, 39(8), 1277–1290.

Malek, J., & Desai, T. N. (2019). Prioritization of sustainable manufacturing barriers using Best Worst Method. Journal of Cleaner Production, 226, 589–600.

Martino, P., Wang, K. J., Bellavitis, C., & DaSilva, C. M. (2019). An introduction to blockchain, cryptocurrency and initial coin offerings. In New frontiers in entrepreneurial finance research (pp. 181–206). World Scientific Publishing.

Matkovskyy, R. (2019). Centralized and decentralized bitcoin markets: Euro vs USD vs GBP. The Quarterly Review of Economics and Finance, 71, 270–279.

Moin, A., Sirer, E. G., & Sekniqi, K. (2019). A classification framework for stablecoin designs. arXiv preprint arXiv:1910.10098

Nabilou, H. (2019). How to regulate bitcoin? Decentralized regulation for a decentralized cryptocurrency. International Journal of Law and Infor-mation Technology, 27(3), 266–291.

Nizamuddin, N., Salah, K., Azad, M. A., Arshad, J., & Rehman, M. H. (2019). Decentralized document version control using ethereum blockchain and IPFS. Computers & Electrical Engineering, 76, 183–197.

Nourmohamadi Shalke, P., Paydar, M. M., & Hajiaghaei-Keshteli, M. (2018). Sustainable supplier selection and order allocation through quantity discounts. International Journal of Management Science and Engineering Management, 13(1), 20–32.

Omrani, H., Amini, M., & Alizadeh, A. (2020). An integrated group best-worst method – Data envelopment analysis approach for evaluating road safety: A case of Iran. Measurement, 152, 107330.

Pamučar, D., Ecer, F., Cirovic, G., & Arlasheedi, M. A. (2020). Application of improved Best Worst Method (BWM) in Real-World Problems. Mathematics, 8(8), 1342.

Patel, M. M., Tanwar, S., Gupta, R., & Kumar, N. (2020). A deep learning-based cryptocurrency price prediction scheme for financial institutions. Journal of Information Security and Applications, 55, 102583.

Pereira, J., Tavalaei, M. M., & Ozalp, H. (2019). Blockchain-based platforms: Decentralized infrastructures and its boundary conditions. Techno-logical Forecasting and Social Change, 146, 94–102.

Peters, G. W., Chapelle, A., & Panayi, E. (2016). Opening discussion on banking sector risk exposures and vulnerabilities from Virtual currencies: An Operational Risk perspective. Journal of Banking Regulation, 17(4), 239–272.

Poongodi, M., Sharma, A., Vijayakumar, V., Bhardwaj, V., Sharma, A. P., Iqbal, R., & Kumar, R. (2020). Prediction of the price of Ethereum blockchain cryptocurrency in an industrial finance system. Computers & Electrical Engineering, 81, 106527.

Rehman, M. H. u., Salah, K., Damiani, E., & Svetinovic, D. (2019). Trust in blockchain cryptocurrency ecosystem. IEEE Transactions on Engi-neering Management, 67(4), 1196–1212.

Rezaei, J. (2015). Best-worst multi-criteria decision-making method. Omega, 53, 49–57.

Rezaei, J. (2016). Best-worst multi-criteria decision-making method: Some properties and a linear model. Omega, 64, 126–130.

Rezaei, J., van Roekel, W. S., & Tavasszy, L. (2018). Measuring the relative importance of the logistics performance index indicators using Best Worst Method. Transport Policy, 68, 158–169.

Ricci, S., Ferreira, E., Menasche, D. S., Ziviani, A., Souza, J. E., & Vieira, A. B. (2018). Learning blockchain delays: A queueing theory approach. ACM SIGMETRICS Performance Evaluation Review, 46(3), 122–125.

Roberti, F., Oberegger, U. F., Lucchi, E., & Troi, A. (2017). Energy retrofit and conservation of a historic building using multi-objective optimiza-tion and an analytic hierarchy process. Energy and Buildings, 138, 1–10.

Schär, F. (2020). Decentralized finance: On blockchain- and smart contract-based financial markets.

Shapiro, D. C. (2018). Taxation and regulation in decentralized exchanges. Journal of Taxation of Investments, 36(1), 3–13.

Silfversten, E., Favaro, M., Slapakova, L., Ishikawa, S., Liu, J., & Salas, A. (2020). Exploring the use of Zcash cryptocurrency for illicit or crimi-nal purposes. Retrieved August 13, 2020, from

Singh, A., Click, K., Parizi, R. M., Zhang, Q., Dehghantanha, A., & Choo, K. K. R. (2020). Sidechain technologies in blockchain networks: An examination and state-of-the-art review. Journal of Network and Computer Applications, 149, 102471.

Söylemez, Y. (2019). Cryptocurrency derivatives: The case of Bitcoin. In U. Hacioglu (Ed.), Blockchain economics and financial market innova-tion (pp. 515–530). Springer, Cham.

Sung, W. C. (2001). Application of Delphi method, a qualitative and quantitative analysis, to the healthcare management. Journal of Healthcare Management, 2(2), 11–19.

Tapscott, A., & Tapscott, D. (2017). How blockchain is changing finance. Harvard Business Review, 1(9), 2–5.

Tian, H., Xue, K., Li, S., Xu, J., Liu, J., & Zhao, J. (2020). Enabling cross-chain transactions: A decentralized cryptocurrency exchange protocol. arXiv preprint arXiv:2005.03199

van de Kaa, G., Kamp, L., & Rezaei, J. (2017). Selection of biomass thermochemical conversion technology in the Netherlands: A best worst method approach. Journal of Cleaner Production, 166, 32–39.

Veisi, H., Liaghati, H., & Alipour, A. (2016). Developing an ethics-based approach to indicators of sustainable agriculture using analytic hierarchy process (AHP). Ecological Indicators, 60, 644–654.

Vora, G. (2015). Cryptocurrencies: Are disruptive financial innovations here? Modern Economy, 6(7), 816.

Walther, T., Klein, T., & Bouri, E. (2019). Exogenous drivers of Bitcoin and Cryptocurrency volatility – A mixed data sampling approach to fore-casting. Journal of International Financial Markets, Institutions and Money, 63, 101133.

Wu, C. R., Lin, C. T., & Chen, H. C. (2007). Evaluating competitive advantage of the location for Taiwanese hospitals. Journal of Information and Optimization Sciences, 28(5), 841–868.

Xia, P., Wang, H., Zhang, B., Ji, R., Gao, B., Wu, L., Luo, X., & Xu, G. (2020). Characterizing cryptocurrency exchange scams. Computers & Security, 98, 101993.

Xu, Q., Zhang, Y., & Zhang, Z. (2021). Tail-risk spillovers in cryptocurrency markets. Finance Research Letters, 38, 101453.

You, P., Guo, S., Zhao, H., & Zhao, H. (2017). Operation performance evaluation of power grid enterprise using a hybrid BWM-TOPSIS method. Sustainability, 9(12), 2329.

Zhang, L., Xie, Y., Zheng, Y., Xue, W., Zheng, X., & Xu, X. (2020). The challenges and countermeasures of blockchain in finance and economics. Systems Research and Behavioral Science, 37(4), 691–698.