نوع مقاله : مقاله پژوهشی
نویسندگان
1 دانشجوی دوره دکترای مهندسی مالی ، واحد یزد ، دانشگاه آزاد اسلامی ، یزد ، ایران .
2 گروه مدیریت مالی، واحد یزد، دانشگاه آزاد اسلامی، یزد، ایران
3 گروه مدیریت بازرگانی، واحد یزد، دانشگاه آزاد اسلامی، یزد، ایران
چکیده
کلیدواژه‌ها
عنوان مقاله [English]
نویسندگان [English]
The present article content in the Big Data Analysis of volatility spillovers of user generated content in the Tehran Stock Exchange. In this research, the variables of stock return rate of each product, positive and negative comments, Google searches about the product, new product announcement, business development, executive amendments and legal issues for Iran Khodro and Saipa stocks have been used to estimate the models. The data of Iran Khodro shares from 1397 to 1400 and Saipa shares from 1400 to 1400 were collected from the stock exchange website. The random sampling method is simple. The results of the research showed that there is a significant and direct relationship between legal issues in Iran Khodro shares and positive comment fluctuations, there is a significant and direct relationship between legal issues in Iran Khodro shares and negative comment fluctuations, between legal issues in Iran Khodro shares and There is a significant and direct relationship between Google fluctuations, there is a significant and direct relationship between legal issues in Saipa shares and positive comment fluctuations, and there is a significant and direct relationship between legal issues in Iran Khodro shares and negative comment
کلیدواژه‌ها [English]
2-امروی،مجید (1394) ، بررسی اثر سرایت پذیری تلاطم در شرکتهای درمانده مالی واقع در زنجیره. تأمین: شواهدی از شرکتهای پذیرفته شده در بورس اوراق بهادار تهران، پایان نامه کارشناسی ارشد، دانشگاه علوم اقتصادی،دانشکده علوم مالی.
3- تقی‌لو. محمد، (1396)- بررسی تاثیر محتوای تولید شده توسط کاربر درباره برند در شبکه اجتماعی بر روی رفتار مصرف کننده(مطالعه موردی: صنعت خودرو)، پایان نامه کارشناسی ارشد - دانشگاه پیام نور استان البرز، مرکز پیام نور کرج .
4- جهانگرد، اسفندیار، )1389)، صنعت خودروسازی و جایگاه آن در اقتصاد ایران. پژوهشنامه اقتصادی, 6(23), 183-206.
5- صالحی، اعظم، (1398) ، تحلیل نقش ابعاد بازاریابی محتوا بر خرید و ارزش آفرینی برند محصولات گیاهان دارویی با نقش میانجی اعتماد، پسندیدن و اشتراک گذاری محتوا در شبکه های اجتماعی ،پایان نامه کارشناسی ارشد، دانشگاه شهید اشرفی اصفهانی، دانشکده علوم اداری و اقتصاد .
6- علومی دودران ، مینا ،(1381 ) ، تحلیل محتوا و ساختار تبلیغات بازرگانی بانک مسکن و بررسی تاثیرات آن بر نگرش و رفتار مشتریان ، پایان نامه کارشناسی ارشد، دانشگاه آزاد اسلامی واحد تهران مرکزی.
7- مرادی،سروش(1397)، آزمون تأثیر کمپین های شبکه اجتماعی بر واکنش مشتریان،پایان نامه کارشناسی ارشد،دانشگاه گیلان ،دانشکده ادبیات وعلوم انسانی.
1.Asur, S., & Huberman, B. A. Predicting the future with social media. Working paper: (2010).arXiv:1003.5699v1
2.. Bloom, N., Bond, S., & Van Reenen, J. Uncertainty and investment dynamics.Review of Economic Studies, (2007), 74, 391–415.
3.Bloom, N. The impact of uncertainty shocks. Econometrica ,(2009), 77(3), 623–685.
4..Bloom, N., Bond, S., & Van Reenen, J. Uncertainty and investment dynamics.Review of Economic Studies, (2007),74, 391–415.
5.. Bollen, J., Mao, H., & Zeng, X. J. Twitter mood predicts the stock market. Journal of Computational Science, 2, (2011), 1–8.
6.. Bollerslev, T., Chou, R., & Kroner, K. ARCH modelling in finance: A review of the theory and empirical evidence. Journal of Econometrics, (1992), 52, 5–59.
7..Bollerslev, T., & Wooldridge, J. M. Quasi-maximum likelihood estimation and inference in dynamic models with time-varying covariances. Econometric Reviews, (2010),11(2), 143–172.
8.. Chintagunta, P. K., Gonipath, S., & Venkataraman, S. The effects of online user reviews on movie box office performance: Accounting for sequential rollout and aggregation across local markets. Marketing Science, (2010), 29(5), 944–957.
9.. Chevalier, J. A., & Mayzlin, D. The effect of word-of-mouth on sales: Online bookreviews. Journal of Marketing Research, (2006), 43, 345–354.
10..Dellarocas, C., Zhang, X., & Awad, N. F. Exploring the value of online product reviews in forecasting sales: The case of motion pictures. Journal of InteractiveMarketing, (2007), 21(4), 23–45.
11.Feng Hu, Rohit H. Trivedi, Mapping hotel brand positioning and competitive landscapes by text-mining user-generated content, International Journal of Hospitality Management , (2020) , 84, 102317.
12..Franses, P. H., & Van Dijk, D. (2000). Nonlinear time series models in empirical finance.Cambridge University Press.
13..Gopinath, S., Thomas, J. S., & Krishnamurthi, L. Investigating the relationship between the content of online word of mouth, advertising, and brand performance.Marketing Science, (2014), 33(2), 241–258.
14..Hennig-Thurau, T., Wiertz, C., & Feldhaus, F. Does Twitter matter? The impact of microblogging word of mouth on consumers' adoption of new movies. Journal of the Academy of Marketing Science, (2014)., 43(3), 375–394.
15.Huaxia Rui , Yizao Liu , Andrew Whinston, Whose and what chatter matters? The effect of tweets on movie sales, Decision Support Systems, (2013) ,55 ,863–870.
16..Liu, Y. Word of mouth for movies: Its dynamics and impact on box office revenue.Journal of Marketing, (2006), 70(3), 75–88.
17..Luo, X. Consumer negative voice and firm-idiosyncratic stock returns. Journal of Marketing, (2007), 71(3), 75–88.
18... Luo, X. Quantifying the long-term impact of negative word-of-mouth on cash flows and stock prices. Marketing Science, (2009), 28(1), 148–165.
19..Luo, X., Zhang, J., & Duan, W. Social media and firm equity value. Information Systems Research, (2013), 24(1), 146–163.
20..McAlister, L., Sonnier, G., & Shively, T. The relationship between online chatter and firm value. Marketing Letters, (2012), 23(1), 1–12.
21..Moe, W. W., & Trusov, M. The value of social dynamics in online product ratings18. forums. Journal of Marketing Research, (2011), 48(June), 444–456.
22..Nam, H., & Kannan, P. K. The informational value of social tagging networks.Journal of Marketing, (2014), 78(4), 21–40.
23..Nga N. Ho-Dac, The value of online user generated content in product development, Journal of Business Research (2020), 112,136–146.
24..Rajasree K. Rajamma, User-generated content (UGC) misclassification and its effects, Journal of Consumer Marketing (2020) , 37/2 , 125–138
25..Rui, H., Liu, Y., & Whinston, A. Whose and what chatter matters? The effect of tweets on movie sales. Decision Support Systems,(2013), 55, 863–870.
26..Seshadri Tirunillai, Gerard J. Tellis,Does Chatter Really Matter? Dynamics of User-Generated Content and Stock Performance, Published Online:24 Jan 2012https://doi.org/10.1287/mksc.1110.0682
27.Shyam Gopinath, Jacquelyn S. Thomas, Lakshman Krishnamurthi, Investigating the Relationship Between the Content of Online Word of Mouth,Advertising, and Brand Performance, 2014https://doi.org/10.1287/mksc.2013.0820
28..Sonnier, G. P., McAlister, L., & Rutz, O. J. A dynamic model of the effect of online communications on firm sales. Marketing Science, (2011),30(4), 702–716.
29..Tirunillai, S., & Tellis, G. J. Does chatter really matter? Dynamics of UGC and stock performance. Marketing Science, (2012), 31(2), 198–215.
30..Trusov, M., Bucklin, R. E., & Pauwels, K. Effects of word-of-mouth versus traditional marketing: Findings from an internet social networking site. Journal ofMarketing, (2009), 73(5), 90–102.
31.Wendy W. Moe, Michael Trusov, The Value of Social Dynamics in Online Product Ratings Forums , Journal of Marketing Research,(2011),
32.Xia Liu, Analyzing the impact of user-generated content on B2B Firms' stock performance: Big data analysis with machine learning methods, journal Industrial Marketing Management, (2020), 86,30-39.
33..Xueming Luo,Quantifying the Long-Term Impact of Negative Word of Mouth on Cash Flows and StockPrices, ( 2009), 28, 148–165.
)