پیوندهای مفید
اخبار و اعلانات
آمار
| تعداد نشریات | 161 |
| تعداد شماره‌ها | 6,532 |
| تعداد مقالات | 70,504 |
| تعداد مشاهده مقاله | 124,121,912 |
| تعداد دریافت فایل اصل مقاله | 97,229,623 |
بخشبندی مصرف‌کنندگان در شبکههای اجتماعی بر اساس انگیزههای اجتماعی مشارکت در ارتباطات دهانبهدهان الکترونیک | ||
| مدیریت بازرگانی | ||
| مقاله 12، دوره 11، شماره 1، 1398، صفحه 201-218 اصل مقاله (1.15 M) | ||
| نوع مقاله: مقاله علمی پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22059/jibm.2018.259484.3084 | ||
| نویسندگان | ||
| حمید ایزدی1؛ منیژه بحرینی زاد* 2؛ مجید اسماعیل پور3 | ||
| 1کارشناسی ارشد، گروه مدیریت بازرگانی، دانشکده ادبیات و علوم انسانی، دانشگاه خلیج فارس، بوشهر، ایران | ||
| 2دانشیار، گروه مدیریت بازرگانی، دانشکده ادبیات و علوم انسانی، دانشگاه خلیج فارس، بوشهر، ایران | ||
| 3استادیار، گروه مدیریت بازرگانی، دانشکده ادبیات و علوم انسانی، دانشگاه خلیج فارس، بوشهر، ایران | ||
| چکیده | ||
| هدف: کارکرد مهم شبکههای اجتماعی در بازاریابی، تولید محتوا و تبلیغات رایگان، بدون دخالت شرکت‌ها و توسط کاربران است که به آن ارتباطات دهانبهدهان الکترونیک میگویند. هدف از اجرای این پژوهش شناسایی انگیزههای اجتماعی مؤثر بر رفتارهای دهانبهدهان در شبکههای اجتماعی و بخشبندی کاربران بر اساس انگیزههای شناسایی شده است. روش: این پژوهش از نظر هدف کاربردی و از نظر روش اجرا در دسته پژوهشهای توصیفی ـ پیمایشی قرار میگیرد. دادههای این پژوهش از طریق توزیع لینک پرسشنامه به بیش از 385 نفر از کاربران شبکههای اجتماعی و با روش نمونهگیری در دسترس، جمعآوری شده است. به‌منظور تحلیل دادهها و بخشبندی کاربران شبکههای اجتماعی نیز از رویکرد نقشههای خودسازمان‌ده مبتنی بر شبکههای عصبی مصنوعی استفاده شده است. یافتهها: بر اساس یافتهها، کاربران شبکههای اجتماعی در سه بخش با ویژگیهای مختلف جمعیتشناختی، رفتاری و همچنین انگیزههای اجتماعی مؤثر بر رفتارهای دهان به دهان، قرار گرفتند. این سه بخش کمانگیزههای اجتماعی فعال، باانگیزههای اجتماعی فعال و باانگیزههای اجتماعی غیرفعال نامگذاری شدند. نتیجهگیری: بخش اول کاربرانی هستند که زمان نسبتاً زیادی را در شبکههای اجتماعی صرف میکنند، ولی برای مشارکت در رفتارهای دهانبهدهان انگیزههای اجتماعی کمتری دارند. بخش دوم، کاربران جوانی هستند که بیشترین زمان را به فعالیت در شبکههای اجتماعی اختصاص میدهند و بسیار با انگیزهاند و بخش سوم کسانی هستند که از انگیزه کافی برخوردارند ولی زمان بسیار کمی را به فعالیت در شبکههای اجتماعی اختصاص میدهند. در پایان، پیشنهادهای کاربردی متناسب با هر یک از بخشهای شناسایی‌شده ارائه شد. | ||
| کلیدواژه‌ها | ||
| ارتباطات دهانبهدهان الکترونیک؛ انگیزه؛ بخشبندی؛ شبکههای عصبی مصنوعی؛ نقشههای خودسازمان‌ده | ||
| عنوان مقاله [English] | ||
| Segmenting Consumers in Social Networks Based on Social Motivations of Engagement in Electronic Word of Mouth Relationships | ||
| نویسندگان [English] | ||
| Hamid Izadi1؛ Manije Bahrinizad2؛ Majid Esmaeilpour3 | ||
| 1MSc. Student, Department of Business Management, Faculty of Literature and Humanities Sciences, Persian Gulf University, Bushehr, Iran | ||
| 2Associated Prof., Department of Business Management, Faculty of Literature and Humanities Sciences, Persian Gulf University, Bushehr, Iran | ||
| 3Assistant Prof., Department of Business Management, Faculty of Literature and Humanities Sciences, Persian Gulf University, Bushehr, Iran | ||
| چکیده [English] | ||
| Objective All kinds of word-of-mouth (WOM) communication are not created in the same way, and their effects vary depending on several factors, such as resource, recipient, message, and status features. Accordingly, for the purpose of effective use of social networks, it is not enough to create a positive WOM relationship but it is important to take into account the conditions and factors through which the users of such communications accept and communicate it with others. Although researchers have been studying WPM communication in various online platforms, including online consumer surveys as well as from a variety of perspectives including marketing and psychology, there is little research on word of mouth communication in the field of social networking. The investigation in the present study shows that there is no research (local and international) investigating social network users based on social incentives affecting participation in WOM communication so far. This research can be considered as the first to deal with the partitioning of social network users based on the motivations of participation in oral communication. The main objective of this research is to identify the social motivations affecting the participation of consumers in advertising campaigns on social networks, the segmentation of users from this perspective, and ultimately providing marketing strategies tailored to each sector. Methodology This research is applied in terms of purpose and descriptive-exploratory in terms of implementation. The data were collected distributing the on-line link to the questionnaire to more than 385 social network users selected based on available sampling method. In order to analyze the data and to partition social network users, self-organizing maps based on artificial neural networks have been used. Findings Based on the findings, social network users were divided into three sections with different demographic, behavioral and social motivations affecting WOM behaviors. These three sections were titled "Low Active Social Stimulus", "Active Social Stimulus" and "Social Inactivity Stimulus". The first section is applied to users who spend a fair amount of time on social networks, but have less social motivation to engage in word of mouth behaviors. The second section is applied to young people who devote most of their time to social networking activities and are highly motivated. And the third category is applied to those who are motivated enough but devote very little time to working on social networks. Conclusion Managers and advertising activists in social networks should consider word of mouth communication as an important part of social interactions. Although the content of WOM messages is often related to brands, the fact is that these types of communications are more likely to be influenced and published by the various incentives of consumer. This kind of behavior suggests that communication strategies should develop to the point where consumers' incentives to engage in oral communication in social networks can be identified and thereby their likelihood of purchasing can be increased. In the first group, it is recommended that marketers take into consideration the incentives that affect this sector and activate them based on the relative great magnitude of this sector compared to other sectors. In the second group, marketers are advised to consider this sector as a motivated sector for communication and encouraging them to have WOM communication. Hence, those who want to advertise their products on social networks should know that this section of social networking users are willing to receive oral messages and that they should provide the product information in a comprehensive and detailed manner so that they can further explore them by sharing it with experts. In the third group, marketers should invite them to engage in oral communication through communicating with individuals with similar beliefs, behaviors and intellectual flow. The members of this section are buying the products that others have verified. Hence, using well-known individuals to advertise their products can be used as one of the appropriate ways to promote products and brands for this section. | ||
| کلیدواژه‌ها [English] | ||
| Artificial Neural Networks, Electronic word of mouth, Motivation, Segmentation, Self-organized map | ||
| مراجع | ||
|
امیری، شیما؛ مصدق، محمدجواد؛ ثنایی، محمدرضا (1396). رفتار خرید بدون برنامهریزی برخط مصرف‌کنندگان در تجارت اجتماعی: نقش تعاملات شبهاجتماعی کاربران (مطالعه موردی: کاربران شبکه اینستاگرام).مدیریت بازرگانی، 9(3)، 463-484. سولومون، م. آ.؛ توتن، جان (1395). بازاریابی در شبکههای اجتماعی؛ رویکردی نوین به بازاریابی الکترونیکی پیشرفته (ترجمه: کامبیز حیدرزاده و علی مریخ نژاد اصل). تهران: نشرعلم. شائمی، علی؛ براری، مجتبی (1390). کانون کنترل و ارتباط دهانبهدهان الکترونیک در میان مصرف کنندگان. فصلنامه مدیریت بازرگانی، 3(8)، 101-114. عربلوی مقدم، سعید؛ اسفیدانی، محمدرحیم؛ آقازاده، هاشم؛ زندیپور، هاشم (1397). شناسایی و بررسی انواع روابط مصرف‌کنندگان با اجتماعات برند در اینستاگرام. فصلنامه مدیریت بازرگانی. 10 (3)، 529-546. معینی، حسین؛ جامیپور، مونا؛ ابراهیمی دلاور، فاطمه (1396). تأثیر قابلیت‌های تجارت اجتماعی بر نگرش مشتریان به خرید به واسطه اعتماد. فصلنامه مدیریت بازرگانی، 9 (1)، 173-192.
References Alexandrov, A., Lilly, B., & Babakus, E. (2013). The effects of social-and self-motives on the intentions to share positive and negative word of mouth. Journal of the Academy of Marketing Science, 41(5), 531-546. Amiry,Sh. Mosadegh, M.J & Sanaei, M.R. (2017). The Unplanned Online Buying Behavior in Social Commerce: The Role of Users’ Pseudo-social Interactions (Case: Users of Instagram Network). Journal of Business Management,10(3), 529-546. (in Persian) Arablooye Moghaddam, S., Rahim Esfidani, M., Aghazade, H. & Zandipou, T. (2018). Identifying and Investigating Types of Consumer Relationships with Brand Communities on Instagram. Journal of Business Management, 9(3), 463-484. (in Persian) Azar, S. L., Machado, J. C., Vacas-de-Carvalho, L., & Mendes, A. (2016). Motivations to interact with brands on Facebook – Towards a typology of consumer–brand interactions. Journal of Brand Management, 23(2), 153-178. Baber, A., Thurasamy, R., Malik, M. I., Sadiq, B., Islam, S., & Sajjad, M. (2016). Online word-of-mouth antecedents, attitude and intention-to-purchase electronic products in Pakistan. Telematics and Informatics, 33(2), 388-400. Bataineh, A. Q., & Al-Smadi, H. M. (2015). Factors impact customers engagement in eWOM on SNSs of non-profit organizations: the moderating role of habit. International Journal of Business and Management, 10(6), 178-187. Baumeister, R. & Leary, M. (1995). The need to belong: desire for interpersonal attachments as a fundamental human motivation. Psychol Bull, 117(3), 497-529. Chan, Y. Y., & Ngai, E. W. (2011). Conceptualising electronic word of mouth activity: An input-process-output perspective. Marketing Intelligence & Planning, 29(5), 488-516. Chang, C.C., Hung, S.W., Cheng, M.J., & Wu, C.Y. (2015). Exploring the intention to continue using social networking sites: The case of Facebook. Technological Forecasting and Social Change, 95, 48-56. Cheung, C. M. K., & Lee, M. K. O. (2012). What drives consumers to spread electronic word of mouth in online consumer-opinion platforms. Decision support systems, 53(1), 218-225. Chu, S.C., & Choi, S. M. (2011). Electronic word-of-mouth in social networking sites: A cross-cultural study of the United States and China. Journal of Global Marketing, 24(3), 263-281. Chu, S.C., & Kim, Y. (2011). Determinants of consumer engagement in electronic word-of-mouth (eWOM) in social networking sites. International Journal of Advertising, 30(1), 47-75. Doma, S., Elaref, N., & Elnaga, M. A. (2015). Factors Affecting Electronic Word-of-Mouth on Social Networking Websites in Egypt–An Application of the Technology Acceptance Model. Journal of Internet Social Networking & Virtual Communities, 2015, 1-31. Festinger, L. (1957). A Theory of Cognitive Dissonance. Oxford, uK: Stanford university Press. Godes, D., Mayzlin, D., Chen, Y., Das, S., Dellarocas, C., Pfeiffer, B., . . . Verlegh, P. (2005). The firm's management of social interactions. Marketing letters, 16(3), 415-428. Hennig-Thurau, T., Gwinner, K. P., Walsh, G., & Gremler, D. D. (2004). Electronic word-of-mouth via consumer-opinion platforms: what motivates consumers to articulate themselves on the internet? Journal of interactive marketing, 18(1), 38-52. Ho, J. Y., & Dempsey, M. (2010). Viral marketing: Motivations to forward online content. Journal of Business research, 63(9), 1000-1006. Hochanadel, C. E. (2014). Motivations for engaging in electronic word of mouth in a social networking setting. TUI University. Ismagilova, E., Dwivedi, Y. K., Slade, E., & Williams, M. D. (2017). Electronic Word-of-Mouth (eWOM). In E. Ismagilova, Y. K. Dwivedi, E. Slade, & M. D. Williams (Eds.), Electronic Word of Mouth (eWOM) in the Marketing Context: A State of the Art Analysis and Future Directions (pp. 17-30). Cham: Springer International Publishing. Kim, S., Park, J., & Lee, Y. (2013). The E-Word-of-Mouth effect on consumers’ Internet shopping behaviour: focus on apparel products. International Journal of Fashion Design, Technology and Education, 6(3), 160-172. Koo, D.-M. (2016). Impact of tie strength and experience on the effectiveness of online service recommendations. Electronic Commerce Research and Applications, 15, 38-51.
Moeini, H., Jamipour, M., & Ebrahimidelavar, F. (2017). The Effect of Social Commerce Capabilities on Customers' Attitude to Ward Buying by the Mediator Role of Trust (Case Study: Instagram Users). Journal of Business Management, 9(1), 173-192. (in Persian) Moorman, C., Deshpande, R. & Zaltman, G. (1993) Factors affecting trust in market research relationships. Journal of Marketing, 57(21), 81–102. Naumann, K., Lay-Hwa Bowden, J., & Gabbott, M. (2017). Exploring Customer Engagement Valences in the Social Services. Asia Pacific Journal of Marketing and Logistics, 29(4), 890-912. Park, N., Jin, B., & Jin, S.-A. A. (2011). Effects of self-disclosure on relational intimacy in Facebook. Computers in Human Behavior, 27(5), 1974-1983. Pigg, K.E. & Crank, L.D. (2004) Building community social capital: the potential and promise of information and communications technologies. Journal of Community Informatics, 1(1), 58–73. Pookulangara, S., & Koesler, K. (2011). Cultural influence on consumers' usage of social networks and its' impact on online purchase intentions. Journal of Retailing and Consumer Services, 18(4), 348-354. Ridings, C.M., Gefen, D. & Arinze, B. (2002) Some antecedents and effects of trust in virtual communities. Journal of Strategic Information Systems,11(3 & 4), pp.271–295. Rogers, E.M. & Bhowmik, D.K. (1970) Homophily–heterophily: relational concepts for communication research. Public Opinion Quarterly, 34(4), 523–538. Shaemi, A. & Barari, M. (2011). Locus of Control and Word of Mouth Communication among Consumer. Journal of Business Management, 8(3), 101-114. (in Persian) Shan, Y., & King, K. W. (2015). The Effects of Interpersonal Tie Strength and Subjective Norms on Consumers' Brand-Related eWOM Referral Intentions. Journal of Interactive Advertising, 15(1), 16-27. Shin, D., Song, J. H., & Biswas, A. (2014). Electronic word-of-mouth (eWOM) generation in new media platforms: The role of regulatory focus and collective dissonance. Marketing letters, 25(2), 153-165. Shirkhodaie, M., & Rezaee, S. (2014). Identification of Advertisement Message Delivery Motivations in Virus Marketing (Case Study: University of Mazandaran). Commercial Strategies, 2(3), 83-92. Solomun, M. A. & Toten, T. A. (2016). Marketing in social network: A new approach in advanced electronic marketing. Translated by K. Hidarzadeh & A. Merikhiy Asl. Tehran. Elm publication. (in Persian) Sukhu, A., Zhang, T., & Bilgihan, A. (2015). Factors Influencing Information-Sharing Behaviors in Social Networking Sites. Services Marketing Quarterly, 36(4), 317-334. Suki, N. M., Suki, N. M., Mokhtar, A. H. A., & Ahmad, R. (2016). Assessing Normative and Informational Influences on Students’ Opinion in Engaging Electronic Word of Mouth via Social Networking Sites. Procedia Economics and Finance, 37, 190-195. Terblanche, N. S. (2016). Measuring word-of-mouth activity after a service encounter: are we measuring what customers communicate? Service Business, 10(2), 283-299. Vogel, E., Rose, J., Roberts, L., & Eckles, K. (2014). Social comparison, social media, and self-esteem (Vol. 3).
Wang, T., Yeh, R. K.-J., Chen, C., & Tsydypov, Z. (2016). What drives electronic word-of-mouth on social networking sites? Perspectives of social capital and self-determination. Telematics and Informatics, 33(4), 1034-1047. Yap, K. B., Soetarto, B., & Sweeney, J. C. (2013). The relationship between electronic word-of-mouth motivations and message characteristics: The sender’s perspective. Australasian Marketing Journal (AMJ), 21(1), 66-74. Yen, C.-L. A., & Tang, C.-H. H. (2015). Hotel attribute performance, eWOM motivations, and media choice. International Journal of Hospitality Management, 46, 79-88. Zhao, Y., Liu, Y., Lai, I. K., Zhang, H., & Zhang, Y. (2016). The Impacts of Attitudes and Engagement on Electronic Word of Mouth (eWOM) of Mobile Sensor Computing Applications. Sensors, 16(3), 391. | ||
|
آمار تعداد مشاهده مقاله: 2,033 تعداد دریافت فایل اصل مقاله: 1,621 |
||