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Şirketlerin sosyal medya metriklerini kullanıcıların oluşturduğu içerik odağında değerlendirmeye yönelik bir MCDM yaklaşımı

Year 2022, Volume: 5 Issue: 3, 266 - 285, 09.11.2022

Abstract

Kullanıcıların oluşturduğu içerik (UGC), şirketleri tüketicilerin satın alma niyetlerinden şirketlerin satışlarına kadar etkileyen ana faktörlerden biri haline gelmiştir. Bu çalışma, şirketlerin sosyal medya ölçümlerini UGC'ye dayalı olarak değerlendirmek için bir MCDM yaklaşımı önermektedir. UGC metrikleri, her bir tweet'in duygu türüne (olumlu, olumsuz veya nötr) ve ilgili metriklere (tweet, retweet, favori ve erişim) dayalı oranlar olarak belirlenip hesaplanmıştır. Kozmetik, pazaryeri ve elektronik alanlarında faaliyet gösteren altı şirket hakkında Twitter'dan veri toplanmıştır. MCDM teknikleri, kriter ağırlıklarını elde etmek için CRITIC, şirketleri sıralamak için ARAS ve COPRAS, R programlama dilinde uygulanmıştır. Bu çalışmanın bulguları, UGC aracılığıyla şirketlerin sıralamasının iyileştirilmesine ve konuyla ilgili literatürün genişletilmesine katkıda bulunmaktadır. MCDM yaklaşımı birkaç özelliği bir arada dikkate aldığından dolayı şirketlerin sosyal medya metriklerinin değerlendirilmesinde etkili bir şekilde kullanılması tavsiye edilmiştir. Veri analizi için R kodları ekte verilmiştir. Bu yaklaşım birkaç özelliği bir arada dikkate aldığı için MCDM tekniklerinin, şirketlerin sosyal medya metriklerini değerlendirmek için etkili bir şekilde kullanılması tavsiye edilmiştir. Veri analizi için R kodları da ekte verilmiştir.

References

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  • Capatina, A., Micu, A., Micu, A. E., Bouzaabia, R., & Bouzaabia, O. (2018). Country-based comparison of accommodation brands in social media: An fsQCA approach. Journal of Business Research, 89, 235–242. doi: 10.1016/j.jbusres.2017.11.017
  • Christodoulides, G., Jevon, C., & Bonhomme, J. (2012). Memo to marketers: Quantitative evidence for change: How user-generated content really affects brands. Journal of Advertising Research, 52(1), 53–64. doi: 10.2501/jar-52-1-053-064
  • Chu, S. C., Chen, H. T., & Sung, Y. (2016). Following brands on Twitter: An extension of theory of planned behavior. International Journal of Advertising, 35(3), 421–437. doi: 10.1080/02650487.2015.1037708
  • Cvijikj, I. P., Spiegler, E. D., & Michahelles, F. (2013). Evaluation framework for social media brand presence. Social Network Analysis and Mining, 3(4), 1325–1349. doi: 10.1007/s13278-013-0131-y
  • Diakoulaki, D., Mavrotas, G., & Papayannakis, L. (1995). Determining objective weights in multiple criteria problems: The CRITIC method. Computers & Operations Research, 22(7), 763–770. doi: 10.1016/0305-0548(94)00059-H
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  • Ho-Dac, N. N. (2020). The value of online user generated content in product development. Journal of Business Research, 112, 136–146. doi: 10.1016/j.jbusres.2020.02.030
  • Hoffman, D. L., & Fodor, M. (2010). Can you measure the ROI of your social media marketing?. MIT Sloan Management Review, 52(1), 41–49.
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  • Irfan, A., Rasli, A., Sulaiman, Z., Sami, A., & Qureshi, M. I. (2018). Use of social media sites by Malaysian universities and its impact on university ranking. International Journal of Engineering and Technology, 7(4.28), 67–71. doi: 10.14419/ijet.v7i4.28.22393
  • Kang, D., & Park, Y. (2014). Based measurement of customer satisfaction in mobile service: Sentiment analysis and VIKOR approach. Expert Systems with Applications, 41(4), 1041–1050. doi: 10.1016/j.eswa.2013.07.101
  • Kaplan, A. M., & Haenlein, M. (2010). Users of the world, unite! The challenges and opportunities of social media. Business Horizons, 53(1), 59–68. doi: 10.1016/j.bushor.2009.09.003
  • Kazan, H., & Özdemir, O. (2014). Financial Performance Assessment of Large Scale Conglomerates via TOPSIS and CRITIC Methods. International Journal of Management and Sustainability, 3(4), 203-224.
  • Lee, K., Oh, W. Y., & Kim, N. (2013). Social media for socially responsible firms: Analysis of Fortune 500’s Twitter profiles and their CSR/CSIR ratings. Journal of Business Ethics, 118(4), 791–806. doi: 10.1007/s10551-013-1961-2
  • Liu, X., Burns, A. C., & Hou, Y. (2017). An investigation of brand-related user-generated content on Twitter. Journal of Advertising, 46(2), 236–247. doi: 10.1080/00913367.2017.1297273
  • Malhotra, A., Malhotra, C. K., & See, A. (2012). How to get your messages retweeted. MIT Sloan Management Review, 53(2), 61–66.
  • Malthouse, E. C., Calder, B. J., Kim, S. J., & Vandenbosch, M. (2016). Evidence that user-generated content that produces engagement increases purchase behaviours. Journal of Marketing Management, 32(5-6), 427–444. doi: 10.1080/0267257X.2016.1148066
  • Michopoulou, E., & Moisa, D. G. (2019). Hotel social media metrics: The ROI dilemma. International Journal of Hospitality Management, 76, 308–315. doi: 10.1016/j.ijhm.2018.05.019
  • Mukul, E., Büyüközkan, G., & Güler, M. (2019, April). Evaluation of digital marketing technologies with MCDM methods. Paper presented at 6th International Conference on New Ideas in Management, Economics and Accounting. doi: 10.33422/6th.imea.2019.04.1070
  • Muruganantham, A., & Gandhi, G. M. (2020). Framework for social media analytics based on multi-criteria decision making (MCDM) model. Multimedia Tools and Applications, 79(5), 3913–3927. doi: 10.1007/s11042-019-7470-2
  • Murdough, C. (2009). Social media measurement: It’s not impossible. Journal of Interactive Advertising, 10(1), 94–99. doi: 10.1080/15252019.2009.10722165
  • Nair, M. (2011). Understanding and measuring the value of social media. Journal of Corporate Accounting & Finance, 22(3), 45–51. doi: 10.1002/jcaf.20674
  • Oh, C., Roumani, Y., Nwankpa, J. K., & Hu, H. F. (2017). Beyond likes and tweets: Consumer engagement behavior and movie box office in social media. Information & Management, 54(1), 25–37. doi: 10.1016/j.im.2016.03.004
  • Peters, K., Chen, Y., Kaplan, A. M., Ognibeni, B., & Pauwels, K. (2013). Social media metrics-A framework and guidelines for managing social media. Journal of Interactive Marketing, 27(4), 281–298. doi: 10.1016/j.intmar.2013.09.007
  • Safko, L. (2012). The social media bible: Tactics, tools, and strategies for business success. John Wiley & Sons.
  • Shao, G. (2009). Understanding the appeal of user-generated media: A uses and gratification perspective. Internet Research, 19(1), 7–25. doi: 10.1108/10662240910927795
  • Silva, S. C., Duarte, P. A. O., & Almeida, S. R. (2020). How companies evaluate the ROI of social media marketing programmes: insights from B2B and B2C. Journal of Business & Industrial Marketing, 35(12), 2097–2110. doi: 10.1108/JBIM-06-2019-0291
  • Sterne, J. (2010). Social media metrics: How to measure and optimize your marketing investment. John Wiley & Sons.
  • Stich, V., Emonts-Holley, R., & Senderek, R. (2015). Social media analytics in customer service: A literature overview-an overview of literature and metrics regarding social media analysis in customer service. Valérie B. & Karl-Heinz K. (Eds.), In International Conference on Web Information Systems and Technologies (pp. 335-344). Springer: Switzerland.
  • Stieglitz, S., Dang-Xuan, L., Bruns, A., & Neuberger, C. (2014). Social media analytics: An interdisciplinary approach and its implications for information systems. Business & Information Systems Engineering, 6(2),89–96. doi: 10.1007/s12599-014-0315-7
  • 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. doi: 10.1088/1757-899X/835/1/012059
  • Tajudeen, F. P., Jaafar, N. I., & Ainin, S. (2018). Understanding the impact of social media usage among organizations. Information & Management, 55(3), 308–321. doi: 10.1016/j.im.2017.08.004
  • 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
  • Tirunillai, S., & Tellis, G. J. (2012). Does chatter really matter? Dynamics of user-generated content and stock performance. Marketing Science, 31(2), 198–215. doi: 10.1287/mksc.1110.0682
  • Toloie-Eshlaghy, A., & Homayonfar, M. (2011). MCDM methodologies and applications: A literature review from 1999 to 2009. Research Journal of International Studies, 21, 86–137.
  • Tsai, J. F., Wang, C. P., Chang, K. L., & Hu, Y. C. (2021). Selecting bloggers for hotels via an innovative mixed MCDM model. Mathematics, 9(13), 1555. doi: 10.3390/math9131555
  • Wu, L. C., Chang, K. L., & Liao, S. K. (2020). A hybrid MCDM model to select optimal hosts of variety shows in the social media era. Symmetry, 12(1), 125. doi: 10.3390/sym12010125
  • Zavadskas, E. K., Kaklauskas, A., & Sarka, V. (1994). The new method of multicriteria complex proportional assessment of projects. Technological and Economic Development of Economy, 1(3), 131–139.
  • 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., Kaklauskas, A. K., Banaitis, A., & Kvederyte, N. (2004). Housing credit access model: the case for Lithuania. European Journal of Operational Research, 155, 335–352. doi: 10.1016/S0377-2217(03)00091-2

An MCDM approach to evaluating companies’ social media metrics based on user-generated content

Year 2022, Volume: 5 Issue: 3, 266 - 285, 09.11.2022

Abstract

User-generated content (UGC) has become one of the main factors that impacts companies, from consumers’ purchase intentions to sales. This study proposes an MCDM approach to evaluate companies’ social media metrics based on UGC. UGC metrics were defined and calculated as ratios based on each tweet’s sentiment type (positive, negative, or neutral) and relevant metrics (tweet, retweet, favorite, and reach). Data was gathered from Twitter about six companies operating in cosmetics, marketplace, and electronics. MCDM techniques were conducted in the R programming language, namely CRITIC for obtaining criteria weights and ARAS and COPRAS for ranking the companies. The findings of this study contribute to improving the ranking of companies through UGC and extend the literature on the subject. MCDM techniques are recommended to be used effectively to evaluate companies’ social media metrics since this approach considers several attributes altogether. R codes for data analysis are also provided in the appendix.

References

  • Anderson, S. P., Waldfogel, J., & Strömberg, D. (Ed.) (2015). Handbook of media economics. Oxford: North Holland.
  • Aichner, T., & Jacob, F. (2015). Measuring the degree of corporate social media use. International Journal of Market Research, 57(2), 257–276. doi: 10.2501/ijmr-2015-018 Boomsocial. (2018). Compare Pages-Twitter Statistics. https://www.boomsocial.com. Accessed 20 March 2018
  • Çalık, A. (2020). Evaluation of social media platforms using best-worst method and fuzzy VIKOR methods: A case study of travel agency. Iranian Journal of Management Studies, 13(4), 645–672. doi: 10.22059/ijms.2020.294545.673893
  • Capatina, A., Micu, A., Micu, A. E., Bouzaabia, R., & Bouzaabia, O. (2018). Country-based comparison of accommodation brands in social media: An fsQCA approach. Journal of Business Research, 89, 235–242. doi: 10.1016/j.jbusres.2017.11.017
  • Christodoulides, G., Jevon, C., & Bonhomme, J. (2012). Memo to marketers: Quantitative evidence for change: How user-generated content really affects brands. Journal of Advertising Research, 52(1), 53–64. doi: 10.2501/jar-52-1-053-064
  • Chu, S. C., Chen, H. T., & Sung, Y. (2016). Following brands on Twitter: An extension of theory of planned behavior. International Journal of Advertising, 35(3), 421–437. doi: 10.1080/02650487.2015.1037708
  • Cvijikj, I. P., Spiegler, E. D., & Michahelles, F. (2013). Evaluation framework for social media brand presence. Social Network Analysis and Mining, 3(4), 1325–1349. doi: 10.1007/s13278-013-0131-y
  • Diakoulaki, D., Mavrotas, G., & Papayannakis, L. (1995). Determining objective weights in multiple criteria problems: The CRITIC method. Computers & Operations Research, 22(7), 763–770. doi: 10.1016/0305-0548(94)00059-H
  • Dhar, V., & Chang, E. A. (2009). Does chatter matter? The impact of user-generated content on music sales. Journal of Interactive Marketing, 23(4), 300–307. doi: 10.1016/j.intmar.2009.07.004
  • dos Santos, M. L. B. (2021). The “so-called” UGC: An updated definition of user-generated content in the age of social media. Online Information Review, 1–19. doi: 10.1108/oir-06-2020-0258/v3/review1
  • Ho-Dac, N. N. (2020). The value of online user generated content in product development. Journal of Business Research, 112, 136–146. doi: 10.1016/j.jbusres.2020.02.030
  • Hoffman, D. L., & Fodor, M. (2010). Can you measure the ROI of your social media marketing?. MIT Sloan Management Review, 52(1), 41–49.
  • Hootsuite & We Are Social (2021, October 23). Digital 2021 global digital overview. https://www.hootsuite.com/pages/digital-trends-2021
  • Irfan, A., Rasli, A., Sulaiman, Z., Sami, A., & Qureshi, M. I. (2018). Use of social media sites by Malaysian universities and its impact on university ranking. International Journal of Engineering and Technology, 7(4.28), 67–71. doi: 10.14419/ijet.v7i4.28.22393
  • Kang, D., & Park, Y. (2014). Based measurement of customer satisfaction in mobile service: Sentiment analysis and VIKOR approach. Expert Systems with Applications, 41(4), 1041–1050. doi: 10.1016/j.eswa.2013.07.101
  • Kaplan, A. M., & Haenlein, M. (2010). Users of the world, unite! The challenges and opportunities of social media. Business Horizons, 53(1), 59–68. doi: 10.1016/j.bushor.2009.09.003
  • Kazan, H., & Özdemir, O. (2014). Financial Performance Assessment of Large Scale Conglomerates via TOPSIS and CRITIC Methods. International Journal of Management and Sustainability, 3(4), 203-224.
  • Lee, K., Oh, W. Y., & Kim, N. (2013). Social media for socially responsible firms: Analysis of Fortune 500’s Twitter profiles and their CSR/CSIR ratings. Journal of Business Ethics, 118(4), 791–806. doi: 10.1007/s10551-013-1961-2
  • Liu, X., Burns, A. C., & Hou, Y. (2017). An investigation of brand-related user-generated content on Twitter. Journal of Advertising, 46(2), 236–247. doi: 10.1080/00913367.2017.1297273
  • Malhotra, A., Malhotra, C. K., & See, A. (2012). How to get your messages retweeted. MIT Sloan Management Review, 53(2), 61–66.
  • Malthouse, E. C., Calder, B. J., Kim, S. J., & Vandenbosch, M. (2016). Evidence that user-generated content that produces engagement increases purchase behaviours. Journal of Marketing Management, 32(5-6), 427–444. doi: 10.1080/0267257X.2016.1148066
  • Michopoulou, E., & Moisa, D. G. (2019). Hotel social media metrics: The ROI dilemma. International Journal of Hospitality Management, 76, 308–315. doi: 10.1016/j.ijhm.2018.05.019
  • Mukul, E., Büyüközkan, G., & Güler, M. (2019, April). Evaluation of digital marketing technologies with MCDM methods. Paper presented at 6th International Conference on New Ideas in Management, Economics and Accounting. doi: 10.33422/6th.imea.2019.04.1070
  • Muruganantham, A., & Gandhi, G. M. (2020). Framework for social media analytics based on multi-criteria decision making (MCDM) model. Multimedia Tools and Applications, 79(5), 3913–3927. doi: 10.1007/s11042-019-7470-2
  • Murdough, C. (2009). Social media measurement: It’s not impossible. Journal of Interactive Advertising, 10(1), 94–99. doi: 10.1080/15252019.2009.10722165
  • Nair, M. (2011). Understanding and measuring the value of social media. Journal of Corporate Accounting & Finance, 22(3), 45–51. doi: 10.1002/jcaf.20674
  • Oh, C., Roumani, Y., Nwankpa, J. K., & Hu, H. F. (2017). Beyond likes and tweets: Consumer engagement behavior and movie box office in social media. Information & Management, 54(1), 25–37. doi: 10.1016/j.im.2016.03.004
  • Peters, K., Chen, Y., Kaplan, A. M., Ognibeni, B., & Pauwels, K. (2013). Social media metrics-A framework and guidelines for managing social media. Journal of Interactive Marketing, 27(4), 281–298. doi: 10.1016/j.intmar.2013.09.007
  • Safko, L. (2012). The social media bible: Tactics, tools, and strategies for business success. John Wiley & Sons.
  • Shao, G. (2009). Understanding the appeal of user-generated media: A uses and gratification perspective. Internet Research, 19(1), 7–25. doi: 10.1108/10662240910927795
  • Silva, S. C., Duarte, P. A. O., & Almeida, S. R. (2020). How companies evaluate the ROI of social media marketing programmes: insights from B2B and B2C. Journal of Business & Industrial Marketing, 35(12), 2097–2110. doi: 10.1108/JBIM-06-2019-0291
  • Sterne, J. (2010). Social media metrics: How to measure and optimize your marketing investment. John Wiley & Sons.
  • Stich, V., Emonts-Holley, R., & Senderek, R. (2015). Social media analytics in customer service: A literature overview-an overview of literature and metrics regarding social media analysis in customer service. Valérie B. & Karl-Heinz K. (Eds.), In International Conference on Web Information Systems and Technologies (pp. 335-344). Springer: Switzerland.
  • Stieglitz, S., Dang-Xuan, L., Bruns, A., & Neuberger, C. (2014). Social media analytics: An interdisciplinary approach and its implications for information systems. Business & Information Systems Engineering, 6(2),89–96. doi: 10.1007/s12599-014-0315-7
  • 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. doi: 10.1088/1757-899X/835/1/012059
  • Tajudeen, F. P., Jaafar, N. I., & Ainin, S. (2018). Understanding the impact of social media usage among organizations. Information & Management, 55(3), 308–321. doi: 10.1016/j.im.2017.08.004
  • 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
  • Tirunillai, S., & Tellis, G. J. (2012). Does chatter really matter? Dynamics of user-generated content and stock performance. Marketing Science, 31(2), 198–215. doi: 10.1287/mksc.1110.0682
  • Toloie-Eshlaghy, A., & Homayonfar, M. (2011). MCDM methodologies and applications: A literature review from 1999 to 2009. Research Journal of International Studies, 21, 86–137.
  • Tsai, J. F., Wang, C. P., Chang, K. L., & Hu, Y. C. (2021). Selecting bloggers for hotels via an innovative mixed MCDM model. Mathematics, 9(13), 1555. doi: 10.3390/math9131555
  • Wu, L. C., Chang, K. L., & Liao, S. K. (2020). A hybrid MCDM model to select optimal hosts of variety shows in the social media era. Symmetry, 12(1), 125. doi: 10.3390/sym12010125
  • Zavadskas, E. K., Kaklauskas, A., & Sarka, V. (1994). The new method of multicriteria complex proportional assessment of projects. Technological and Economic Development of Economy, 1(3), 131–139.
  • 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., Kaklauskas, A. K., Banaitis, A., & Kvederyte, N. (2004). Housing credit access model: the case for Lithuania. European Journal of Operational Research, 155, 335–352. doi: 10.1016/S0377-2217(03)00091-2
There are 44 citations in total.

Details

Primary Language English
Subjects Operation
Journal Section Research Article
Authors

Büşra Ayan 0000-0002-5212-2144

Seda Abacıoğlu 0000-0002-3150-2770

Publication Date November 9, 2022
Acceptance Date November 3, 2022
Published in Issue Year 2022 Volume: 5 Issue: 3

Cite

APA Ayan, B., & Abacıoğlu, S. (2022). An MCDM approach to evaluating companies’ social media metrics based on user-generated content. Business Economics and Management Research Journal, 5(3), 266-285.

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