10 research outputs found

    Temporal variations of phosphorus uptake by soil microbial biomass and young beech trees in two forest soils with contrasting phosphorus stocks.

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    The objective of this study was to determine temporal variations of phosphorus (P) uptake by young beech trees (Fagus sylvatica L.) and soil microorganisms in two forests with contrasting P stocks with the aim to better understand P dynamics in forest ecosystems. For this purpose, we conducted a mesocosm experiment and determined P uptake by F. sylvatica, total soil microbial biomass (SMB) and ectomycorrhizal fungi (EMF) at the root tip based on P-33 labeling at five times during the year. Furthermore, we measured EMF community composition, potential acid phosphatase activity (APA), and abundance of bacterial acid phosphatase (phoN) genes. The results showed that plant P uptake was elevated in summer and autumn in the mesocosms from the P-poor site, while it was elevated only in autumn in the mesocosms from the P-rich site. P uptake by SMB was higher in the organic layer at the P-poor site than in the organic layer at the P-rich site throughout the year, underlining the importance of the microbial P pool in the organic layer of P-poor forests. The finding shows that the SMB was able to compensate for the lower P availability in the soil of the P-poor site. The EMF community composition was very variable over the year, and plant P uptake seemed to be independent of EMF community composition. Despite the high species turnover in the EMF community, the potential APA was high throughout the year, indicating functional redundancy of the microbial community with respect to P mineralization. Taken together, our results show important differences in temporal patterns of P uptake by F. sylvatica and the SMB as well as in the total partitioning of P between the SMB and F. sylvatica across the sites. Moreover, decreasing P availability in forests would not only change the size of P stocks and of P cycling rates, but would also affect temporal dynamics of P uptake and the overall partitioning of P between different biotic compartments

    Online users' attitudes toward fake news: Implications for brand management

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    [EN] This study examines brands' vulnerability to fake news. The rapid spread of online misinformation poses challenges to brand managers, whose brands are cocreated online, sometimes to the detriment of the brand. There is a need to identify the information sources that are likely to be trustworthy and to promote positive consumer attitudes toward brands. The data for this study were taken from a Flash Eurobarometer of 26,576 respondents across 28 European countries. Cluster analysis and partial least squares structural equation modeling were used to analyze the data and unveil users' attitudes toward fake news. The findings show that users' attitudes toward fake news differ among European countries. Younger and tech-savvy users are more likely to recognize fake news and are consequently able to evaluate digital information sources without relying on policy interventions to limit the impact of fake news. Brand managers can use the findings of this study to better understand different kinds of users' susceptibility to fake news and reshape their social media branding strategies accordingly. It is hoped that this paper will encourage further research on brand management in relation to fake news and promote the widespread adoption of best practices in social media communication.Fundação Ciência e Tecnologia, Portugal, Grant/Award Numbers: IDB/00685/2020 CEEAplA, UIDB/04521/2020 Advance/CSGBorges-Tiago, T.; Tiago, F.; Silva, O.; Guaita Martínez, JM.; Botella-Carrubi, D. (2020). Online users' attitudes toward fake news: Implications for brand management. Psychology and Marketing. 37(9):1171-1184. https://doi.org/10.1002/mar.2134911711184379Allcott, H., & Gentzkow, M. (2017). Social Media and Fake News in the 2016 Election. Journal of Economic Perspectives, 31(2), 211-236. doi:10.1257/jep.31.2.211ASSAEL, H. (2005). A Demographic and Psychographic Profile of Heavy Internet Users and Users by Type of Internet Usage. Journal of Advertising Research, 45(01), 93. doi:10.1017/s0021849905050014Berthon, P. R., & Pitt, L. F. (2018). Brands, Truthiness and Post-Fact. Journal of Macromarketing, 38(2), 218-227. doi:10.1177/0276146718755869Bhandari, M., & Rodgers, S. (2017). What does the brand say? Effects of brand feedback to negative eWOM on brand trust and purchase intentions. International Journal of Advertising, 37(1), 125-141. doi:10.1080/02650487.2017.1349030Bluemle, S. R. (2018). Post-Facts: Information Literacy and Authority after the 2016 Election. portal: Libraries and the Academy, 18(2), 265-282. doi:10.1353/pla.2018.0015Borges-Tiago, M. T., Tiago, F., Veríssimo, J. M., & Silva, T. (2019). A brand-new world: brand-endorsers-users fit on social media. Academia Revista Latinoamericana de Administración, 32(4), 472-486. doi:10.1108/arla-02-2019-0047Brandtzæg, P. B., Heim, J., & Karahasanović, A. (2011). Understanding the new digital divide—A typology of Internet users in Europe. International Journal of Human-Computer Studies, 69(3), 123-138. doi:10.1016/j.ijhcs.2010.11.004Campan, A., Cuzzocrea, A., & Truta, T. M. (2017). Fighting fake news spread in online social networks: Actual trends and future research directions. 2017 IEEE International Conference on Big Data (Big Data). doi:10.1109/bigdata.2017.8258484Casado-Díaz, A. B., Pérez-Naranjo, L. M., & Sellers-Rubio, R. (2016). Aggregate consumer ratings and booking intention: the role of brand image. Service Business, 11(3), 543-562. doi:10.1007/s11628-016-0319-0Chakraborty, C., & Chakraborty, D. (2007). Fuzzy rule base for consumer trustworthiness in Internet marketing: An interactive fuzzy rule classification approach. Intelligent Data Analysis, 11(4), 339-353. doi:10.3233/ida-2007-11403Chen, Y., Fay, S., & Wang, Q. (2011). The Role of Marketing in Social Media: How Online Consumer Reviews Evolve. Journal of Interactive Marketing, 25(2), 85-94. doi:10.1016/j.intmar.2011.01.003Chen, Z. F., & Cheng, Y. (2019). Consumer response to fake news about brands on social media: the effects of self-efficacy, media trust, and persuasion knowledge on brand trust. Journal of Product & Brand Management, 29(2), 188-198. doi:10.1108/jpbm-12-2018-2145Cheung, C. M. K., & Thadani, D. R. (2012). The impact of electronic word-of-mouth communication: A literature analysis and integrative model. Decision Support Systems, 54(1), 461-470. doi:10.1016/j.dss.2012.06.008Commission E.(2018).Fake news and disinformation online. Flash Eurobarometer 464. Retrieved fromhttp://ec.europa.eu/commfrontoffice/publicopinion/index.cfm/ResultDoc/download/DocumentKy/82308Constantinides, E., & Fountain, S. J. (2008). Web 2.0: Conceptual foundations and marketing issues. Journal of Direct, Data and Digital Marketing Practice, 9(3), 231-244. doi:10.1057/palgrave.dddmp.4350098Dinev, T., Goo, J., Hu, Q., & Nam, K. (2009). User behaviour towards protective information technologies: the role of national cultural differences. Information Systems Journal, 19(4), 391-412. doi:10.1111/j.1365-2575.2007.00289.xFarzin, M., & Fattahi, M. (2018). eWOM through social networking sites and impact on purchase intention and brand image in Iran. Journal of Advances in Management Research, 15(2), 161-183. doi:10.1108/jamr-05-2017-0062Fletcher R. Cornia A. Graves L. &Nielsen R. K.(2018).Measuring the reach of “fake news” and online disinformation in Europe. Retrieved from Reuters Institute Factsheet.Guess A. Nyhan B. &Reifler J.(2018).Selective exposure to misinformation: Evidence from the consumption of fake news during the 2016 US presidential campaign. European Research Council (Working Paper). Retrieved fromhttp://www.dartmouth.edu/~nyhan/fake‐news‐2016.pdfHennig-Thurau, T., Hofacker, C. F., & Bloching, B. (2013). Marketing the Pinball Way: Understanding How Social Media Change the Generation of Value for Consumers and Companies. Journal of Interactive Marketing, 27(4), 237-241. doi:10.1016/j.intmar.2013.09.005Hsu, M.-H., Tien, S.-W., Lin, H.-C., & Chang, C.-M. (2015). Understanding the roles of cultural differences and socio-economic status in social media continuance intention. Information Technology & People, 28(1), 224-241. doi:10.1108/itp-01-2014-0007Ind, N., Iglesias, O., & Schultz, M. (2013). Building Brands Together: Emergence and Outcomes of Co-Creation. California Management Review, 55(3), 5-26. doi:10.1525/cmr.2013.55.3.5Kamis, Koufaris, & Stern. (2008). Using an Attribute-Based Decision Support System for User-Customized Products Online: An Experimental Investigation. MIS Quarterly, 32(1), 159. doi:10.2307/25148832Keenan, M., & Dillenburger, K. (2018). How ‘Fake News’ Affects Autism Policy. Societies, 8(2), 29. doi:10.3390/soc8020029Lis, B. (2013). In eWOM We Trust. Business & Information Systems Engineering, 5(3), 129-140. doi:10.1007/s12599-013-0261-9Litvin, S. W., Goldsmith, R. E., & Pan, B. (2008). Electronic word-of-mouth in hospitality and tourism management. Tourism Management, 29(3), 458-468. doi:10.1016/j.tourman.2007.05.011Liu, L., Lee, M. K. O., Liu, R., & Chen, J. (2018). Trust transfer in social media brand communities: The role of consumer engagement. International Journal of Information Management, 41, 1-13. doi:10.1016/j.ijinfomgt.2018.02.006Love, P. E. D., & Ahiaga-Dagbui, D. D. (2018). Debunking fake news in a post-truth era: The plausible untruths of cost underestimation in transport infrastructure projects. Transportation Research Part A: Policy and Practice, 113, 357-368. doi:10.1016/j.tra.2018.04.019Marchi, R. (2012). With Facebook, Blogs, and Fake News, Teens Reject Journalistic «Objectivity». Journal of Communication Inquiry, 36(3), 246-262. doi:10.1177/0196859912458700Mills, A. J., & Robson, K. (2019). Brand management in the era of fake news: narrative response as a strategy to insulate brand value. Journal of Product & Brand Management, 29(2), 159-167. doi:10.1108/jpbm-12-2018-2150Pariser, E. (2012). FILTER BUBBLE. doi:10.3139/9783446431164Quan-Haase, A., Williams, C., Kicevski, M., Elueze, I., & Wellman, B. (2018). Dividing the Grey Divide: Deconstructing Myths About Older Adults’ Online Activities, Skills, and Attitudes. American Behavioral Scientist, 62(9), 1207-1228. doi:10.1177/0002764218777572Rizvi, W. H., & Oney, E. (2018). The influence of emotional confidence on brand attitude: using brand belief as mediating variable. Economic Research-Ekonomska Istraživanja, 31(1), 158-170. doi:10.1080/1331677x.2017.1421993Schapals, A. K. (2018). Fake News. Journalism Practice, 12(8), 976-985. doi:10.1080/17512786.2018.1511822Schranz, M., Schneider, J., & Eisenegger, M. (2018). Media Trust and Media Use. Trust in Media and Journalism, 73-91. doi:10.1007/978-3-658-20765-6_5So, K. K. F., Wu, L., Xiong, L., & King, C. (2017). Brand Management in the Era of Social Media: Social Visibility of Consumption and Customer Brand Identification. Journal of Travel Research, 57(6), 727-742. doi:10.1177/0047287517718354Sultan, P., Wong, H. Y., & Sigala, M. (2018). Segmenting the Australian organic food consumer market. Asia Pacific Journal of Marketing and Logistics, 30(1), 163-181. doi:10.1108/apjml-10-2016-0211Tajvidi, M., Richard, M.-O., Wang, Y., & Hajli, N. (2020). Brand co-creation through social commerce information sharing: The role of social media. Journal of Business Research, 121, 476-486. doi:10.1016/j.jbusres.2018.06.008Tandoc, E. C., Lim, Z. W., & Ling, R. (2017). Defining «Fake News». Digital Journalism, 6(2), 137-153. doi:10.1080/21670811.2017.1360143Tiago, F., Couto, J., Faria, S., & Borges-Tiago, T. (2018). Cruise tourism: social media content and network structures. Tourism Review, 73(4), 433-447. doi:10.1108/tr-10-2017-0155Torres, R., Gerhart, N., & Negahban, A. (2018). Epistemology in the Era of Fake News. ACM SIGMIS Database: the DATABASE for Advances in Information Systems, 49(3), 78-97. doi:10.1145/3242734.3242740Trusov, M., Bucklin, R. E., & Pauwels, K. (2009). Effects of Word-of-Mouth versus Traditional Marketing: Findings from an Internet Social Networking Site. Journal of Marketing, 73(5), 90-102. doi:10.1509/jmkg.73.5.90Tsfati, Y. (2010). Online News Exposure and Trust in the Mainstream Media: Exploring Possible Associations. American Behavioral Scientist, 54(1), 22-42. doi:10.1177/0002764210376309Turcotte, J., York, C., Irving, J., Scholl, R. M., & Pingree, R. J. (2015). News Recommendations from Social Media Opinion Leaders: Effects on Media Trust and Information Seeking. Journal of Computer-Mediated Communication, 20(5), 520-535. doi:10.1111/jcc4.12127Vafeiadis, M., Bortree, D. S., Buckley, C., Diddi, P., & Xiao, A. (2019). Refuting fake news on social media: nonprofits, crisis response strategies and issue involvement. Journal of Product & Brand Management, 29(2), 209-222. doi:10.1108/jpbm-12-2018-2146Vargo, C. J., Guo, L., & Amazeen, M. A. (2017). The agenda-setting power of fake news: A big data analysis of the online media landscape from 2014 to 2016. New Media & Society, 20(5), 2028-2049. doi:10.1177/1461444817712086Varkaris, E., & Neuhofer, B. (2017). The influence of social media on the consumers’ hotel decision journey. Journal of Hospitality and Tourism Technology, 8(1), 101-118. doi:10.1108/jhtt-09-2016-0058Visentin, M., Pizzi, G., & Pichierri, M. (2019). Fake News, Real Problems for Brands: The Impact of Content Truthfulness and Source Credibility on consumers’ Behavioral Intentions toward the Advertised Brands. Journal of Interactive Marketing, 45, 99-112. doi:10.1016/j.intmar.2018.09.001De Vries, L., Gensler, S., & Leeflang, P. S. H. (2012). Popularity of Brand Posts on Brand Fan Pages: An Investigation of the Effects of Social Media Marketing. Journal of Interactive Marketing, 26(2), 83-91. doi:10.1016/j.intmar.2012.01.003De Vries, L., Peluso, A. M., Romani, S., Leeflang, P. S. H., & Marcati, A. (2017). Explaining consumer brand-related activities on social media: An investigation of the different roles of self-expression and socializing motivations. Computers in Human Behavior, 75, 272-282. doi:10.1016/j.chb.2017.05.016Wang, C.-Y., Lee, H.-C., Wu, L.-W., & Liu, C.-C. (2017). Quality dimensions in online communities influence purchase intentions. Management Decision, 55(9), 1984-1998. doi:10.1108/md-11-2016-0822Wang, Y., Min, Q., & Han, S. (2016). Understanding the effects of trust and risk on individual behavior toward social media platforms: A meta-analysis of the empirical evidence. Computers in Human Behavior, 56, 34-44. doi:10.1016/j.chb.2015.11.011Warner-Søderholm, G., Bertsch, A., Sawe, E., Lee, D., Wolfe, T., Meyer, J., … Fatilua, U. N. (2018). Who trusts social media? Computers in Human Behavior, 81, 303-315. doi:10.1016/j.chb.2017.12.026Yu, T.-K., Lin, M.-L., & Liao, Y.-K. (2017). Understanding factors influencing information communication technology adoption behavior: The moderators of information literacy and digital skills. Computers in Human Behavior, 71, 196-208. doi:10.1016/j.chb.2017.02.005Zhang, X., & Ghorbani, A. A. (2020). An overview of online fake news: Characterization, detection, and discussion. Information Processing & Management, 57(2), 102025. doi:10.1016/j.ipm.2019.03.00
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