مشخصات مقاله | |
ترجمه عنوان مقاله | شکست های شدید خدمات و تبلیغات شفاهی انتقام جویانه آنلاین: تأثیر استراتژی های مقابله |
عنوان انگلیسی مقاله | Searching for word of mouth in the digital age: Determinants of consumers’ uses of face-to-face information, internet opinion sites, and social media |
انتشار | مقاله سال 2022 |
تعداد صفحات مقاله انگلیسی | 17 صفحه |
هزینه | دانلود مقاله انگلیسی رایگان میباشد. |
پایگاه داده | نشریه الزویر |
نوع نگارش مقاله |
مقاله پژوهشی (Research Article) |
مقاله بیس | این مقاله بیس میباشد |
نمایه (index) | Scopus – Master Journals List – JCR |
نوع مقاله | ISI |
فرمت مقاله انگلیسی | |
ایمپکت فاکتور(IF) |
7.550 در سال 2020 |
شاخص H_index | 195 در سال 2020 |
شاخص SJR | 2.049 در سال 2020 |
شناسه ISSN | 0148-2963 |
شاخص Quartile (چارک) | Q1 در سال 2020 |
فرضیه | دارد |
مدل مفهومی | دارد |
پرسشنامه | ندارد |
متغیر | دارد |
رفرنس | ندارد |
رشته های مرتبط | مدیریت |
گرایش های مرتبط | مدیریت کسب و کار، مدیریت بازرگانی، بازاریابی، تجارت الکترونیک |
نوع ارائه مقاله |
ژورنال |
مجله | مجله تحقیقات بازرگانی – Journal of Business Research |
دانشگاه | Marketing Center Münster, University of Münster, Germany |
کلمات کلیدی | بازاریابی دهان به دهان الکترونیکی، دهان به دهان، رفتار جستجوی اطلاعات، رسانه های اجتماعی، رگرسیون کسری |
کلمات کلیدی انگلیسی | Privacy, Internet of Things (IoT); Smart Devices; User-Centric; GDPR; Explicit Consent; Anonymity; Transparency; Simplicity; Privacy Scorecard |
شناسه دیجیتال – doi |
https://doi.org/10.1016/j.jbusres.2021.11.035 |
کد محصول | E15940 |
وضعیت ترجمه مقاله | ترجمه آماده این مقاله موجود نمیباشد. میتوانید از طریق دکمه پایین سفارش دهید. |
دانلود رایگان مقاله | دانلود رایگان مقاله انگلیسی |
سفارش ترجمه این مقاله | سفارش ترجمه این مقاله |
فهرست مطالب مقاله: |
Abstract Keywords Introduction What we know (and don’t) about different wom types Conceptual framework and hypotheses Hypotheses testing Discussion Declaration of Competing Interest Appendix A. Quota sampling by the market research company Appendix B. Social network–specific regression results Appendix C:. Results of separate fractional regression analyses Appendix D:. Results of ordinary least squares regression analyses Appendix E. Multinomial logistic regressions for WOM types ranks References |
بخشی از متن مقاله: |
ABSTRACT In the digital era, consumers choose among various types of word of mouth (WOM) when searching for product information. This research investigates how consumers allocate their search efforts across three key WOM types: face-to-face (e.g., offline communication among consumers), Internet opinion sites (e.g., product reviews), and social media platforms (e.g., recommendations on Facebook). The authors develop a conceptual framework of WOM types and derive hypotheses about the determinants of WOM search behaviors, which they test against representative data from more than 2,000 consumers. Several product and consumer characteristics have systematic effects on search effort allocation, as do WOM type–specific resources. A process-related analysis also suggests different roles of WOM types during customers’ search journeys, such that face-to-face conversations and Internet opinion sites tend to be consulted early, whereas social media mostly serve as final information sources. Overall, the results caution against assuming that the different WOM types are arbitrary or random substitutes. Introduction Word of mouth (WOM) is one of the most influential information sources for consumers (Brown & Reingen, 1987; Katz & Lazarsfeld, 1955). In addition to receiving information through face-to-face interactions with others, consumers in the digital age can learn from product reviews on Internet opinion sites (e.g., Amazon, Yelp, Trustpilot) or social media (e.g., Facebook, Twitter). Because these platforms and the forms of WOM they produce differ vastly, in terms of personal connections, synchronicity, and feedback options, a deeper understanding of the functions of various types of WOM for consumers is demanded, beyond imposing a simple online–offline dichotomy (Berger & Iyengar, 2013; Hennig-Thurau et al., 2015; Lovett et al., 2013). While research has shed light on each WOM type individually (e.g., face-to-face, de Matos & Rossi, 2008; Internet opinion sites, You et al., 2015; social media, Hennig-Thurau et al., 2015), limited insights exists into how the differences manifested by various WOM types influence consumers’ WOM usage, particularly over the course of their search process (cf. Berger & Iyengar, 2013; Rosario et al., 2020) |