A novel advertising media selection framework for online games in an intuitionistic fuzzy environment

• Authors: Jalil Heidary Dahooie , Mehrdad Estiri , Mahshid Janmohammadi , Edmundas Kazimieras Zavadskas , Zenonas Turskis

Abstracts

EN

Research background: The critical role of online games in e-commerce and the great competition among providers to enhance market share has significantly increased the need to use effective advertising patterns, techniques, and tools to attract users. There are two significant challenges to planning online media game selection. The first challenge is that there is no agreement on media selection criteria for online game advertising. The second challenge relates to the complexity of choosing advertising media. Purpose of the article: Given the multidimensionality and uncertainty in evaluating and selecting advertising media, especially in the case of online games, the need to provide a systematic framework for evaluating and selecting media is critical. Methods: The present study aims to provide a systematic framework based on multi-attribute decision-making (MADM) methods to evaluate and select the appropriate media for online game advertising. For this purpose, first, by reviewing the literature, a relatively comprehensive list of media selection criteria for online game advertising was extracted and then provided to experts in online game marketing and advertising in the fuzzy Delphi questionnaire. Then, based on their opinions, a localized decision model was obtained. Also, the Step-wise Weight Assessment Ratio Analysis (SWARA) method helped to determine the criteria' importance. In the next step, a preliminary list of online game advertising media was prepared and evaluated by experts based on the criteria obtained in the previous step. Finally, the media was ranked using the Additive Ratio ASsessment (ARAS) method. Findings & value added: Awareness of the criteria affecting the selection of online game advertising media and having a systematic framework for applying these criteria in advertising media selection decisions play a vital role in practical decisions. This research addresses one of the main gaps in the field of study by proposing a quantitative methodology for integrating information based on the knowledge of experts in the decision-making processes select advertising media for online games. Most traditional media selection processes are based solely on experience and estimation, and in practice, they are unable to systematically prioritize the alternatives due to the multiplicity of media available and the complexity of the decision-making process Interval-valued triangular fuzzy numbers (IVTFNs) can address the shortcomings of previous research while considering the uncertainties in this decision-making process. The findings of this framework can be good support for e-commerce managers and online game advertising practitioners.

Keywords

EN

online game; advertising media; multi-attribute decision-making; SWARA-IVTFN; ARAS-IVTFN

• Publisher: Instytut Badań Gospodarczych
• Journal: Oeconomia Copernicana
• Year: 2022
• Volume: 13
• Issue: 1
• Pages: 109-150

Dates

published

2022

Contributors

author

Jalil Heidary Dahooie

• University of Tehran

• https://orcid.org/0000000340376670

author

Mehrdad Estiri

• University of Tehran

• https://orcid.org/0000000318920852

author

Mahshid Janmohammadi

• University of Tehran

• https://orcid.org/0000000163157310

author

Edmundas Kazimieras Zavadskas

• Vilnius Gediminas Technical University

• https://orcid.org/000000023201949X

author

Zenonas Turskis

• Vilnius Gediminas Technical University

• https://orcid.org/0000000258359388

References

• Aashirwad Kumar, G. (2020). An analytical study of search engine optimization (SEO) techniques: to maximize number of travelers on an e-content material website. International Journal of Management (IJM), 11(1), 114?119. doi: 10.34218/IJM.11.1.2020.012.
• Aggarwal, S., Kaul, A., Gupta, A., & Jha, P. C. (2014). Multi period advertising media selection in a segmented market. In Proceedings of the third international conference on soft computing for problem solving . New Delhi: Springer, 905?928. doi: 10.1007/978-81-322-1768-8_76.
• Aghey, C. (2020). Integration of eSports in the structure of Ifs: disruption or continuity? International Sports Law Journal, 20(3), 120?125. doi: 10.1007/s40318-020-00175-7.
• Ahmady, N., Saen, R. F., Ahmady, E., & Sadeghi, A. H. (2015). Developing a fuzzy enhanced Russell measure for media selection. International Journal of Business Innovation and Research, 9(4), 470?485. doi: 10.1504/IJBIR.2015.07 0179.
• Alavijeh, M. R. K., Foroozan, A., & Afrashteh, A. A. (2019). Identification and prioritisation of effective criteria in the selection of outdoor advertising using the AHP technique. International Journal of Internet Marketing and Advertising, 13(4), 359?373. doi: 10.1504/IJIMA.2019.103464.
• Ashtiani, B., Haghighirad, F., Makui, A., & Ali Montazer, G. (2009). Extension of fuzzy TOPSIS method based on interval-valued fuzzy sets. Applied Soft Computing, 9(2), 457?461. doi: 10.1016/j.asoc.2008.05.005.
• Baradari, I., Shoar, M., Nezafati, N., & Motadel, M. (2021). A new approach for KPI ranking and selection in ITIL processes: using simultaneous evaluation of criteria and alternatives (SECA). Journal of Industrial Engineering and Management Studies, 8(1), 152?179.doi: 10.22116/JIEMS.2020.228519.1356.
• Calantone, R. J., & de Brentani-Todorovic, U. (1981). The maturation of the science of media selection. Journal of the Academy of Marketing Science, 9(4), 490?524.
• Calli, L. (2016). Selection of social media sites for advertising: literature review and a model proposal. In Proceedings of MAC-MME 2016. Prague: MAC Prague consulting Ltd, 253?261.
• Chaney, I., Hosany, S., Wu, M. S. S., Chen, C. H. S., & Nguyen, B. (2018). Size does matter: effects of in-game advertising stimuli on brand recall and brand recognition. Computers in Human Behavior, 86, 311?318. doi: 10.1016/j.chb.2 018.05.007.
• Chen, H. J., & Sun, T. H. (2014). Clarifying the impact of product scarcity and perceived uniqueness in buyers' purchase behavior of games of limited-amount version. Asia Pacific Journal of Marketing and Logistics, 26(2), 232?249. doi: 10.1108/APJML-07-2013-0084.
• Chess, S., Evans, N. J., & Baines, J. J. (2016). What does a gamer look like? Video games, advertising, and diversity. Television & New Media, 18(1), 37?57. doi: 10.1177/1527476416643765.
• Cicchirillo, V. J. (2019). Digital game advertising (IGA and advergames): not all fun and games. Journal of Interactive Advertising, 19(3), 202?203. doi: 10.1080/15252019.2019.1697126.
• Consalvo, M. (2003). Zelda 64 and video game fans: a walkthrough of games, intertextuality, and narrative. Television & New Media, 4(3), 321?334. doi: 10.1177/1527476403253993.
• Coulter, K., & Sarkis, J. (2005). Development of a media selection model using the Analytic Network Process. International Journal of Advertising, 24(2), 193?215. doi: 10.1080/02650487.2005.11072914.
• Coulter, K., & Sarkis, J. (2006). An application of the Analytic Network Process to the advertising media budget allocation decision. International Journal on Media Management, 8(4), 164?172. doi: 10.1207/s14241250ijmm0804_2.
• Dahooie, J. H., Meidute-Kavaliauskiene, I., Vanaki, A. S., Podviezko, A., & Abadi, E. B. J. (2020). Development of a firm export performance measurement model using a hybrid multi-attribute decision-making method. Management Decision, 58(11), 2349?2385. doi: 10.1108/MD-09-2019-1156.
• Dahooie, J. H., Zavadskas, E. K., Abolhasani, M., Vanaki, A., & Turskis, Z. (2018). A novel approach for evaluation of projects using an interval?valued fuzzy additive ratio assessment (ARAS) method: a case study of oil and gas well drilling projects. Symmetry, 10(2), 45. doi: 10.3390/sym10020045.
• Dörnyei, K. R. (2020). Marketing professionals? views on online advertising fraud. Journal of Current Issues & Research in Advertising, 43(3), 1?19. doi: 10.1080/10641734.2020.1737276.
• Dyer, R. F., Forman, E. H., & Mustafa, M. A. (1992). Decision support for media selection using the Analytic Hierarchy Process. Journal of Advertising, 21(1), 59?72. doi: 10.1080/00913367.1992.10673360.
• Farzipoor Saen, R. (2011). Media selection in the presence of flexible factors and imprecise data. Journal of the Operational Research Society, 62(9), 1695?1703. doi: 10.1057/jors.2010.115.
• Gong, X., Chen, C., & Lee, M. K. (2020). What drives problematic online gaming? The role of IT identity, maladaptive cognitions, and maladaptive emotions. Computers in Human Behavior, 110, 106386. doi: 10.1016/j.chb.2020. 106386.
• Gorzałczany, M. B. (1987). A method of inference in approximate reasoning based on interval-valued fuzzy sets. Fuzzy Sets and Systems, 21(1), 1?17. doi: 10.101 6/0165-0114(87)90148-5.
• Grigorovici, D. M., & Constantin, C. D. (2004). Experiencing interactive advertising beyond rich media: impacts of Ad type and presence on brand effectiveness in 3D gaming immersive virtual environments. Journal of Interactive Advertising, 5(1), 22?36. doi: 10.1080/15252019.2004.10722091.
• Grimes, S. M., & Feenberg, A. (2009). Rationalizing play: a critical theory of digital gaming. Information Society, 25(2), 105?118. doi: 10.1080/0197224080270 1643.
• Hamari, J., Keronen, L., & Alha, K. (2015). Why do people play games? A review of studies on adoption and use. In Proceedings of the 48th annual Hawaii international conference on system sciences (HICSS), Hawaii, USA, January 5-8, 2015. IEEE, 3559?3568. doi: 10.1109/HICSS.2015.428.
• Harris, N., Hollett, K. B., & Remedios, J. (2020). Facets of competitiveness as predictors of problem video gaming among players of massively multiplayer online first-person shooter games. Current Psychology. Advance online publication. doi: 10.1007/s12144-020-00886-y.
• Hashemkhani Zolfani, S., Zavadskas, E. K., & Turskis, Z. (2013). Design of products with both international and local perspectives based on Yin-Yang balance theory and SWARA method. Economic Research-Ekonomska Istraživanja, 26(2), 153?166. doi: 10.1080/1331677X.2013.11517613.
• Heidary Dahooie, J., Estiri, M., Zavadskas, E. K., & Xu, Z. (2021). A novel hybrid Fuzzy DEA-Fuzzy ARAS method for prioritizing high-performance innovation-oriented human resource practices in high tech SME?s. International Journal of Fuzzy Systems. Advance online publication. doi: 10.1007/s40815-021-01162-2.
• Heidary Dahooie, J., Zavadskas, E. K., Vanaki, A. S., Firoozfar, H. R., Lari, M., & Turskis, Z. (2019). A new evaluation model for corporate financial performance using integrated CCSD and FCM-ARAS approach. Economic Research-Ekonomska Istraživanja, 32(1), 1088?1113. doi: 10.1080/1331677X.2019.1613 250.
• Herrewijn, L., & Poels, K. (2015). The impact of social setting on the recall and recognition of in-game advertising. Computers in Human Behavior, 53, 544?555. doi: 10.1016/j.chb.2014.06.012.
• Iran Computer and Video Games Foundation (2018). Landscape report 2017: the most significant information of digital games consumption in Iran. Retrieved from http://direc.ir/wp-content/uploads/2018/07/ EnglishLandscape.2017.pdf.
• Javan, H. T., Khanlari, A., Motamedi, O., & Mokhtari, H. (2018). A hybrid advertising media selection model using AHP and fuzzy-based GA decision making. Neural Computing and Applications, 29(4), 1153?1167. doi: 10.1007/s00 521-016-2517-z.
• Jeong, E. J., & Biocca, F. A. (2012). Are there optimal levels of arousal to memory? Effects of arousal, centrality and familiarity on brand memory in video games. Computers in Human Behavior, 28(2), 285?291. doi: 10.1016/j.chb .2011.09.011.
• Jha, P. C., Aggarwal, R., Gupta, A., & Aggarwal, S. (2012). An optimal advertising media selection model for promotion of multiproducts in segmented market. Journal of Statistics and Management Systems, 15(1), 61?80. doi: 10.1080/ 09720510.2012.10701613.
• Karabasevic, D., Zavadskas, E. K., Turskis, Z., & Stanujkic, D. (2016). The framework for the selection of personnel based on the SWARA and ARAS methods under uncertainties. Informatica, 27(1), 49?65. doi: 10.15388/Informa tica.2016.76.
• Kassaye, W. W. (1999). Sorting out the practical concerns in World Wide Web advertising. International Journal of Advertising, 18(3), 339?361. doi: 10.1080 /02650487.1999.11104765.
• Keršulienė, V., Zavadskas, E. K., & Turskis, Z. (2010). Selection of rational dispute resolution method by applying new Step?wise Weight Assessment Ratio Analysis (SWARA). Journal of Business Economics and Management, 11(2), 243?258. doi: 10.3846/jbem.2010.12.
• Keshavarz-Ghorabaee, M., Amiri, M., Zavadskas, E. K., Turskis, Z., & Antucheviciene, J. (2021). Determination of objective weights using a new method based on the removal effects of criteria (MEREC). Symmetry, 13(4), 525. doi: 10.3390/sym13040525.
• Khoshsaligheh, M., & Ameri, S. (2020). Video game localisation in Iran: a survey of users? profile, gaming habits and preferences. Translator, 26(2), 190?208. doi: 10.1080/13556509.2020.1724046.
• Krueger, K., & Soley, L. (2010). Advertising media selection. In Wiley international encyclopedia of marketing. Part 4. Advertising and integrated communication. John Wiley & Sons Ltd. doi: 10.1002/9781444316568.wiem04010.
• Labrador, F. J., Bernaldo-de-Quirós, M., Sánchez-Iglesias, I., Labrador, M., Vallejo-Achón, M., Fernández-Arias, I., & Estupi?á, F. J. (2020). Advertising games of chance in adolescents and young adults in Spain. Journal of Gambling Studies, 37(3), 1?14. doi: 10.1007/s10899-020-09988-5.
• Lewis, B., & Porter, L. (2010). In-game advertising effects: examining player perceptions of advertising schema congruity in a massively multiplayer online role-playing game. Journal of Interactive Advertising, 10(2), 46?60. doi: 10.10 80/15252019.2010.10722169.
• Li, Y. M., & Shiu, Y. L. (2012). A diffusion mechanism for social advertising over microblogs. Decision Support Systems, 54(1), 9?22.
• Mardani, A., Nilashi, M., Zakuan, N., Loganathan, N., Soheilirad, S., Saman, M. Z. M., & Ibrahim, O. (2017). A systematic review and meta-analysis of SWARA and WASPAS methods: theory and applications with recent fuzzy developments. Applied Soft Computing, 57, 265?292. doi: 10.1016/j.asoc.2017.03.045.
• Merhi, M. I. (2016). Towards a framework for online game adoption. Computers in Human Behavior, 60, 253?263. doi: 10.1016/j.chb.2016.02.072.
• Mishra, S., & Malhotra, G. (2020). The gamification of in-game advertising: examining the role of psychological ownership and advertisement intrusiveness. International Journal of Information Management, 61, 102245. doi: 10.1016/j.ijinfomgt.2020.102245.
• Moorman, M., Neijens, P. C., & Smit, E. G. (2010). Advertising media selection and planning. In Wiley international encyclopedia of marketing. Part 4. Advertising and integrated communication. John Wiley & Sons Ltd. doi: 10.1002/97 81444316568.wiem04010.
• Nanda, S., & Warms, R. L. (2010). Cultural anthropology. Cengage Learning.
• Nawi, N. C., Mamun, A. A., Nasir, N. A. M., & Muniady, R. (2019). Factors affecting the adoption of social media as a business platform: a study among student entrepreneurs in Malaysia. Vision, 23(1), 1?11. doi: 10.1177/09722629188 21200.
• Newzoo (2018). 2018 games market: key numbers. Retrieved form https://newzoo.com/key-numbers.
• Newzoo (2019). Newzoo's 2018 report: insights into the $137.9 billion global games market. Retrieved form https://newzoo.com/insights/articles/newzoos-2018-report-insights-into-the-137-9-billion-global-games-market.
• Newzoo (2021). 2021 games market: key numbers. Retrieved form https://newzoo.com/key-numbers.
• Ngai, E. W. T. (2003). Selection of web sites for online advertising using the AHP. Information & Management, 40(4), 233?242. doi: 10.1016/s0378-7206(02)000 04-6.
• Paulson, C., Luo, L., & James, G. M. (2018). Efficient large-scale internet media selection optimization for online display advertising. Journal of Marketing Research, 55(4), 489?506. doi: 10.1509/jmr.15.0307.
• Pitt, H., Thomas, S. L., Bestman, A., Daube, M., & Derevensky, J. (2017). Factors that influence children?s gambling attitudes and consumption intentions: lessons for gambling harm prevention research, policies and advocacy strategies. Harm Reduction Journal, 14(1), 11. doi: 10.1186/s12954-017-0136-3.
• Plantin, J. C., & Punathambekar, A. (2019). Digital media infrastructures: pipes, platforms, and politics. Media, Culture & Society, 41(2), 163?174. doi: 10.1177 /0163443718818376.
• Reddick, C., & Anthopoulos, L. (2014). Interactions with e-government, new digital media and traditional channel choices: citizen-initiated factors. Transforming Government: People, Process and Policy, 8(3), 398?419. doi: 10.1108/TG-01-2014-0001.
• Ramírez-Correa, P., Rondán-Cataluña, F. J., Arenas-Gaitán, J., & Martín-Velicia, F. (2019). Analysing the acceptation of online games in mobile devices: an application of UTAUT2. Journal of Retailing and Consumer Services, 50, 85?93. doi: 10.1016/j.jretconser.2019.04.018.
• Ruzgys, A., Volvačiovas, R., Ignatavičius, Č., & Turskis, Z. (2014). Integrated evaluation of external wall insulation in residential buildings using SWARA-TODIM MCDM method. Journal of Civil Engineering and Management, 20(1), 103?110. doi: 10.3846/13923730.2013.843585.
• Sari, D. K., Suziana, S., & Games, D. (2020). An evaluation of social media advertising for Muslim millennial parents. Journal of Islamic Marketing. Advance online publication. doi: 10.1108/jima-02-2020-0055.
• Skvarciany, V., Lapinskaitė, I., & Volskytė, G. (2021). Circular economy as assistance for sustainable development in OECD countries. Oeconomia Copernicana, 12(1), 11?34. doi: 10.24136/oc.2021.001.
• Scharrer, E. (2004). Virtual violence: Gender and aggression in video game advertisements. Mass Communication and Society, 7(4), 393?412. doi: 10.1207/s15 327825mcs0704_2.
• Schouten, A. P., Janssen, L., & Verspaget, M. (2020). Celebrity vs. influencer endorsements in advertising: the role of identification, credibility, and product-endorser fit. International Journal of Advertising, 39(2), 258?281. doi: 10.1080 /02650487.2019.1634898.
• Shi, J., Potenza, M. N., & Turner, N. E. (2020). Commentary on: ?The future of gaming disorder research and player protection: what role should the video gaming industry and researchers play??. International Journal of Mental Health and Addiction, 18, 791?799. doi: 10.1007/s11469-019-00153-7.
• Shieber, J. (2019). Video game revenue tops $43 billion in 2018, an 18% jump from 2017. Tech crunch. Retrieved from https://techcrunch.com/2019/01/22/video-game-revenue-tops-43-billion-in-2018-an-18-jump-from-2017/?ren derMode=ie (11.10.2019).
• Siksnelyte-Butkiene, I., Streimikiene, D., Balezentis, T., & Skulskis, V. (2021). A systematic literature review of multi-criteria decision-making methods for sustainable selection of insulation materials in buildings. Sustainability, 13(2), 737. doi: 10.3390/su13020737.
• Smith, R., Kelly, B., Yeatman, H., Moore, C., Baur, L., King, L., Boyland, E., Chapman, K., Hughes, C., & Bauman, A. (2020). Advertising placement in digital game design influences children?s choices of advertised snacks: a randomized trial. Journal of the Academy of Nutrition and Dietetics, 120(3), 404?413. doi: 10.1016/j.jand.2019.07.017.
• Stanujkic, D. (2016). An extension of the ratio system approach of MOORA method for group decision-making based on interval-valued triangular fuzzy numbers. Technological and Economic Development of Economy, 22(1), 122?141. doi: 10.3846/20294913.2015.1070771.
• Stanujkic, D., Zavadskas, E. K., Brauers, W. K., & Karabasevic, D. (2015). An extension of the MULTIMOORA method for solving complex decision-making problems based on the use of interval-valued triangular fuzzy numbers. Transformations in Business & Economics, 14(2B), 355?375.
• Statista (2019). Unit sales of the best selling PC games of all time worldwide as of January 2018 (in Million Units). Retrieved form https://www.statista.com/stat istics/275226/best-selling-pc-games-of-all-time-worldwide/ (12.02.2019).
• Sudipa, I. G. I., Astria, C., Irnanda, K. F., Windarto, A. P., Daulay, N. K., Suharso, W., & Wijaya, H. O. L. (2020). Application of MCDM using PROMETHEE II technique in the case of social media selection for online businesses. IOP Conference Series: Materials Science and Engineering, 835(1), 012059.
• Tafreshi, P. F., Aghdaie, M. H., Behzadian, M., & Abadi, M. G. (2016). Developing a group decision support system for advertising media evaluation: a case in the Middle East. Group Decision and Negotiation, 25(5), 1021?1048. doi: 10.1007/s10726-015-9464-4.
• Tavana, M., Momeni, E., Rezaeiniya, N., Mirhedayatian, S. M., & Rezaeiniya, H. (2013). A novel hybrid social media platform selection model using fuzzy ANP and COPRAS-G. Expert Systems with Applications, 40(14), 5694?5702. doi: 10.1016/j.eswa.2013.05.015.
• Terlutter, R., & Capella, M. L. (2013). The gamification of advertising: analysis and research directions of in-game advertising, advergames, and advertising in social network games. Journal of Advertising, 42(2-3), 95?112. doi: 10.1080/00 913367.2013.774610.
• Till, B. D., & Busler, M. (2000). The match-up hypothesis: physical attractiveness, expertise, and the role of fit on brand attitude, purchase intent and brand beliefs. Journal of Advertising, 29(3), 1?13. doi: 10.1080/00913367.2000.10673 613.
• Turskis, Z., Dzitac, S., Stankiuviene, A., & Šukys, R. (2019). A fuzzy group decision-making model for determining the most influential persons in the sustainable prevention of accidents in the construction SMEs. International Journal of Computers Communications & Control, 14(1), 90?106. doi:10.15837/ijccc.20 19.1.3364.
• Turskis, Z., Lazauskas, M., & Zavadskas, E. K. (2012). Fuzzy multiple criteria assessment of construction site alternatives for non-hazardous waste incineration plant in Vilnius city, applying ARAS-F and AHP methods. Journal of Environmental Engineering and Landscape Management, 20(2), 110?120. doi: 10.3846/16486897.2011.645827.
• Turskis, Z., Zavadskas, E. K., & Kutut, V. (2013). A model based on ARAS-G and AHP methods for multiple criteria prioritizing of heritage value. International Journal of Information Technology & Decision Making, 12(01), 45?73. doi: 10.1142/S021962201350003X.
• Turskis, Z., & Zavadskas, E. K. (2010a). A new fuzzy additive ratio assessment method (ARAS?F). Case study: the analysis of fuzzy multiple criteria in order to select the logistic centers location. Transport, 25(4), 423?432. ? doi: 10.3846/ transport.2010.52.
• Turskis, Z., & Zavadskas, E. K. (2010b). A novel method for multiple criteria analysis: grey additive ratio assessment (ARAS-G) method. Informatica, 21(4), 597?610.
• Vahdani, B., Mousavi, S. M., Tavakkoli-Moghaddam, R., Ghodratnama, A., & Mohammadi, M. (2014). Robot selection by a multiple criteria complex proportional assessment method under an interval-valued fuzzy environment. International Journal of Advanced Manufacturing Technology, 73(5-8), 687?697. doi: 10.1007/s00170-014-5849-9.
• Valaei, N., Bressolles, G., Nikhashemi, S. R., & Khan, H. (2019). In-game advertising and gamers? behavior in app environment: an abstract. In Academy of Marketing Science Annual Conference. Springer, Cham. 387?388. doi: 10.1007/978-3-030-39165-2152.
• Wang, H., & Sparks, C. (2019). Marketing credibility: Chinese newspapers? responses to revenue losses from falling circulation and advertising decline. Journalism Studies, 20(9), 1301?1318. doi: 10.1080/1461670X.2018.151 3815.
• Wijman, T. (2020). The world's 2.7 billion gamers will spend $159.3 billion on games in 2020; the market will surpass $200 billion by 2023. Dipetik dari. Retrieved form https://newzoo.com/insights/articles/newzoo-games-market-numb ers-revenues-and-audience-2020-2023/pada, 8.
• Wilbur, K. C., & Zhu, Y. (2009). Click fraud. Marketing Science, 28(2), 293?308. doi: 10.1287/mksc.1080.0397.
• Yao, J. S., & Lin, F. T. (2002). Constructing a fuzzy flow-shop sequencing model based on statistical data. International Journal of Approximate Reasoning, 29(3), 215?234. doi: 10.1016/S0888-613X(01)00064-0.
• Zadeh, L. A. (1975). The concept of a linguistic variable and its application to approximate reasoning?I. Information Sciences, 8(3), 199?249. doi: 10.1016 /0020-0255(75)90036-5.
• Zavadskas, E. K., & Turskis, Z. (2010). A new additive ratio assessment (ARAS) method in multicriteria decision?making. Technological and Economic Development of Economy, 16(2), 159?172. doi: 10.3846/tede.2010.10.
• Zavadskas, E. K., Turskis, Z., Šliogerienė, J., & Vilutien?, T. (2021). An integrated assessment of the municipal buildings? use including sustainability criteria. Sustainable Cities and Society, 67, 102708. doi: 10.1016/j.scs.2021.102708.
• Zavadskas, E. K., Turskis, Z., Vilutienė, T., & Lepkova, N. (2017). Integrated group fuzzy multi-criteria model: case of facilities management strategy selection. Expert Systems with Applications, 82, 317?331. doi: 10.1016/j.eswa.2017. 03.072.
• Zha, X., Li, J., & Yan, Y. (2015). Advertising value and credibility transfer: attitude towards web advertising and online information acquisition. Behaviour and Information Technology, 34(5), 520?532. doi: 10.1080/0144929X.2014.9 78380.
• Zemlickienė, V., Bublienė, R., & Jakubavičius, A. (2018). A model for assessing the commercial potential of high technologies. Oeconomia Copernicana, 9(1) 29?54. doi: 10.24136/oc.2018.002.
• Zolfani, S. H., Torkayesh, A. E., Ecer, F., Turskis, Z., & Šaparauskas, J. (2021). International market selection: a MABA based EDAS analysis framework. Oeconomia Copernicana, 12(1), 99?124. doi: 10.24136/oc.2021.005.

Identifiers

DOI

10.24136/oc.2022.004

Biblioteka Nauki

19322479