Relevant bibliographies by topics / Similarity with an influencer

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Similarity with an influencer'

Author: Grafiati
Published: 11 September 2021
Last updated: 10 February 2022

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Journal articles on the topic "Similarity with an influencer"

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Adrianto, Rifqi, and Kurnia. "Kredibilitas Influencer dalam Membentuk Kepercayaan Konsumen terhadap Brand." Jurnal Riset Manajemen Komunikasi 1, no. 1 (July 14, 2021): 54–60. http://dx.doi.org/10.29313/jrmk.v1i1.117.

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Abstract. Advertising and promotion campaigns often involve influencers to deliver messages through the media to increase consumer trust in the brand. In addition, influencers have a level of credibility which has an impact on the level of trust in the brand. Zilingo is one of the fashion e-commerce brands on the online platform, which also takes advantage of influencers' credibility in their advertising campaign strategy. However, in entering the eMarket Platform, Zilingo as a new E-commerce platform is required to be able to build brand trust in order to compete with e-commerce brands that have previously existed as market leaders. Establishing trust in a brand is very important because Brand Trust is the main consideration for consumers to buy products. The research has several variables, namely Trustworthiness, Expertise, Similarity, Attractiveness as the independent variable and Brand Trust as the dependent variable. This research uses a quantitative approach and a positivist paradigm based on observations of social realities that occur. The research population is Zilingo consumers. The data collection technique is done by using non probability sampling. Based on the calculation of the sample formula, it is known that the number of samples in this study was 100 respondents. The results showed that Trustworthiness, Expertise, Similarity, Attractiveness had a significant positive effect on Brand Trust. Abstrak. Kampanye periklanan dan promosi seringkali melibatkan influencer untuk mengantarkan pesan melalui media guna meningkatkan kepercayaan konsumen terhadap brand. Selain itu, Influencer memiliki tingkat kredibilitas yang berdampak pada tingkat kepercayaan terhadap brand. Zilingo merupakan salah satu fashion e-comerce brand pada Platform online, yang juga memanfaatkan kredibilitas influencer dalam strategi kampanye iklannya. Namun, dalam memasuki eMarket Platform, Zilingo sebagai new E-comerce dituntut mampu membangun kepercayaan brand agar dapat bersaing dengan e-comerce brand yang telah lebih dahulu ada sebagai market leader. Membentuk kepercayaan terhadap brand merupakan hal yang sangat penting karena Brand Trust menjadi pertimbangan utama konsumen untuk membeli produk. Dalam penelitian memiliki beberapa Variable yaitu Trustworthiness, Expertise, Similarity, Attractiveness sebagai Variable independent dan Brand Trust sebagai Variable dependent. Dalam penelitian ini digunakan pendekatan kuantitatif dan paradigma positivism berdasarkan pengamatan terhadap realitas sosial yang terjadi. Populasi penelitian yaitu konsumen Zilingo. Teknik pengumpulan data dilakukan dengan non probability sampling. Berdasarkan perhitungan rumus sampel diketahui bahwa jumlah sampel penelitian ini adalah 100 responden. Hasil penelitian menunjukkan bahwa Trustworthiness, Expertise, Similarity, Attractiveness memiliki pengaruh positif yang signifikan terhadap Brand Trust.
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Balaban, Delia, and Maria Mustățea. "Users’ Perspective on the Credibility of Social Media Influencers in Romania and Germany." Romanian Journal of Communication and Public Relations 21, no. 1 (April 1, 2019): 31. http://dx.doi.org/10.21018/rjcpr.2019.1.269.

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The present research addresses the issue of source credibility of social media influencers from the perspective of users. Social media influencers are defined as online personalities with a large number of followers, across one or several social media platforms. They have a complex role, being content creators, online opinion leaders, and even entrepreneurs. Influencer marketing is becoming a more and more relevant component of current advertising campaigns worldwide. A consistent body of literature has underlined the importance of source credibility for the effectiveness of advertising. Recent researches on Source Credibility Theory (Teng et al, 2014; Djafarova & Rushworth, 2016; Munnukka et al 2016; Lou &Yuan, 2018) have stressed the influence of trustworthiness, expertise, similarity and attractiveness as elements of source credibility on perceived trust in influencer marketing. In order to gain better insights, we chose to conduct qualitative research that can allow us an in-depth perspective on the phenomenon of source credibility in influencer marketing. We carried out four group discussions in Germany and five in Romania. We explored the differences and similarities regarding the users’ perception of the perceived credibility of social media influencers.
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Taillon, Brian J., Steven M. Mueller, Christine M. Kowalczyk, and Daniel N. Jones. "Understanding the relationships between social media influencers and their followers: the moderating role of closeness." Journal of Product & Brand Management 29, no. 6 (June 27, 2020): 767–82. http://dx.doi.org/10.1108/jpbm-03-2019-2292.

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Purpose The purpose of this paper is to better understand the role of closeness and the relationships between social media influencers and their followers, and, more specifically, how social media influencers can effectively manage their human brands. Design/methodology/approach Two studies were conducted to explore social media influencers. Qualitative content analysis and modeling with path analysis were used to analyze the data. Findings Results found attractiveness and likeability to positively predict attitudes toward the influencer, word-of-mouth and purchase intentions, whereas similarity only predicted word-of-mouth from the follower. Closeness served as a moderator but had different effects. Closeness positively moderated the effect of attractiveness on purchase intentions; however, it had a negative effect with similarity on purchase intentions. Moreover, closeness moderated the effect of likeability on attitude toward the influencer. Research limitations/implications This study was limited by the student sample as well as the students’ self-identification of a social media influencer. Future research should include experimental design manipulating well-known/followed or fictional social media influencers on different social media. Practical implications This paper explores the characteristics of social media influencers as well as the potential outcomes associated with influencers on social media. The implications for marketers and advertisers include a better understanding of how consumers engage with influencers on social media. Originality/value The role of closeness is identified as a moderator of consumers’ behaviors toward social media influencers.
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Tsarashafa, Tsaniya Athaya, and Annisa Rahmani Qastharin. "HOW FASHION INFLUENCER CONTRIBUTES TO CONSUMERS’ PURCHASE INTENTION OF UNIVERSITY STUDENT." Advanced International Journal of Business, Entrepreneurship and SMEs 3, no. 9 (September 2, 2021): 209–27. http://dx.doi.org/10.35631/aijbes.39015.

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Fashion is receiving more attention these days since it has become a continual existence in a person’s everyday life, especially for the younger generation as it represents their identity. On the other hand, the dynamic competitive environment of marketing-led fashion brands to put in the excess effort to achieve effective marketing strategies. As social media grew, one of the most effective ways to do it is using influencers in the marketing campaign. Influencer marketing is becoming increasingly popular throughout the world, prompting marketers to consider it an essential component of their marketing strategy. This research determines the factors of fashion influencers that contribute to influencing purchase intention. The variables constructed include trustworthiness, expertise, similarity, likability, and familiarity. Further, consumer attitude is proposed to mediate between trustworthiness, expertise, similarity, likability, and familiarity to purchase intention. The research was conducted using a quantitative approach and analyzed using a regression method through IBM SPSS Statistics. From 234 qualified respondents, the results presented trustworthiness, similarity, familiarity, and likability significantly contribute to purchase intention, and consumers' attitudes towards influencers are proven to be mediate the relationships between independents variables and purchase intention. The findings of the study assist marketers and advertisers in the fashion industry in understanding the elements influencing consumer attitudes about fashion influencers and, as a result, better choose influencers capable of establishing purchase intentions in existing and potential customers.
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Fensi, Fabianus, and Michael Christian. "DETERMINAN CITRA MEREK PADA IKLAN PRODUK GAWAI “VIVO” BERDASARKAN ASPEK “CELEBRITY ENDORSER”." Bricolage : Jurnal Magister Ilmu Komunikasi 4, no. 02 (September 22, 2018): 163. http://dx.doi.org/10.30813/bricolage.v4i02.1659.

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<p>ABSTRACT<br />The impact of using influencers in a product such as a smartphone that can create stronger advertising effectiveness. This strengthens the understanding of advertising in an effort to tell stories, arouse emotions, create fantasy, and impact to provide strong visuals. This study aims to analyze the effect of VIVO brand image. By using quantitative research and processed with SPSS 25.0, the results of this study explain that brand image is partially influenced by factors such as endorser self quality, similarity, and persuasive power displayed. While factors can be trusted, expertise, physical attractiveness, popularity does not affect. Simultaneously the brand image in the VIVO device is influenced by Trustworthy factors, Expertise, Physical Attraction, Quality Appreciated, Similarity, Popularity, and Persuasive Strength.<br /><strong>Keywords:</strong> brand image, device, endorser, influencer</p><p><br />ABSTRAK<br />Dampak dari penggunaan influencer dalam dalam suatu produk seperti gawai yang dapat menciptakan efektivitas iklan yang lebih kuat. Hal ini menguatkan pemahaman iklan dalam upaya untuk menceritakan kisah, membangkitkan emosi, menciptakan fantasi, dan dampak memberikan visual yang kuat. Penelitian ini bertujuan untuk menganalisis pengaruh citra merek gawai VIVO. Dengan menggunakan penelitian kuantitatif dan diolah dengan SPSS 25.0 hasil penelitian ini menjelaskan citra merek secara parsial dipengaruhi oleh faktor-faktor seperti kualitas diri endorser, kesamaan, dan kekuatan persuasif yang ditampilkan. Sedangkan faktor-faktor dapat dipercaya, keahlian, daya tarik fisik, popularitas tidak berpengaruhi. Secara simultan citra merek pada gawai VIVO dipengaruhi oleh faktor-faktor Dapat Dipercaya, Keahlian, Daya Tarik Fisik, Kualitas Dihargai, Kesamaan, Popularitas, dan Kekuatan Persuasif.<br /><strong>Kata kunci:</strong> citra merek, gawai, endorser, influencer</p>
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Naderer, Brigitte, Jörg Matthes, and Stephanie Schäfer. "Effects of disclosing ads on Instagram: the moderating impact of similarity to the influencer." International Journal of Advertising 40, no. 5 (July 4, 2021): 686–707. http://dx.doi.org/10.1080/02650487.2021.1930939.

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Ait Rai, K., T. Agouti, M. Machkour, and J. Antari. "Identification of Complex Network Influencer using the Technology for Order Preference by Similarity to an Ideal Solution." Journal of Physics: Conference Series 1743 (January 2021): 012004. http://dx.doi.org/10.1088/1742-6596/1743/1/012004.

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CRUZ, LEONARDO DOMINICI, FERNANDA RODRIGUES FERNANDES, and ARÍCIO XAVIER LINHARES. "Similarities among ectoparasite fauna of sigmodontine rodents: phylogenetic and geographical influences." Parasitology 139, no. 13 (August 20, 2012): 1749–56. http://dx.doi.org/10.1017/s0031182012001126.

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SUMMARYPhylogenetic and geographical overlaps in host distributions influence the compositional similarity of ectoparasite fauna in a host–parasite system. In these systems, hosts that are more closely related (phylogenetically) are expected to share more parasitic species than more distantly related hosts. Similarly, hosts sharing a larger geographical distribution overlap are expected to have similar ectoparasites. This study investigated the influence of phylogeny (divergence time) and geographical overlap of some neotropical sigmodontine rodent species on the similarities among their ectoparasite fauna (Mesostigmata and Siphonaptera), using a partial Mantel test. Divergence time was the only significant factor that influenced the similarity among the ectoparasites, when mites and fleas were analysed together. Host species that had diverged more recently displayed ectoparasite fauna that were similar. The similarities of the flea species showed similar results in both separate and joint analyses, but neither phylogenetic nor geographical overlap influenced the similarity in mite species. Fleas were shown to be more host-specific than were mesostigmate mites, probably because of the increased influence of host phylogeny.
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Zainal, Alia Azleen, Norasyikin Yusri, Nurul Malim, and Shereena M. Arif. "The Influence of Similarity Measures and Fusion Rules Toward Turbo Similarity Searching." Procedia Technology 11 (2013): 823–33. http://dx.doi.org/10.1016/j.protcy.2013.12.264.

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Xi chun, Zhang, He Li, Wang Jing yi, and Liu Wei. "The Development Trend of Musicians’ Influence and Music Genres of Big Data." E3S Web of Conferences 253 (2021): 02085. http://dx.doi.org/10.1051/e3sconf/202125302085.

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This paper uses the data crawled from the AllMusic website to establish a directional network of followers and influences of music genre artists, analyzes the music influence influenced by genre. The Beatles had the greatest influence from 1950 to 2010, and promoted the development of Pop/Rock and Country music genres. In addition, it was found that “influencers” would actually influence the music created by followers. Based on the music feature data set of 91719 songs provided by Spotify’s API, drawing the correlation heat map and making the measurement of music similarity, it is found that the songs of artists of the same genre are more similar. For the similarity between different genres, by selecting the representative music in the genre and using the music characteristics to analyze their correlation, it is found that Folk and Avant-Garde, New Age and Stage & Screen all have high similarity, reaching 0.97. In addition, songs can also be classified into genres according to music characteristics. For example, if a genre has high performance in livability, speech and explicit attributes, it can be considered as Comedy/Spoken. Finally, combined with the historical reality, it is found that there may be characteristics and music revolutionaries[1] that mark the great revolution of music development.
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Dissertations / Theses on the topic "Similarity with an influencer"

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Al-Darraji, Zainab, Mansour Zahra Al, and Shilan Rezai. "Similarity, Familiarity, and Credibility in influencers and their impact on purchasing intention." Thesis, Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-48502.

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Egertz, Linnea, Jonathan Almström, and Benny Truong. "Influencer marketing: What if everything revolves around the consumer’s self-esteem : A study about the purchasing behaviour of Swedish women in relation to influencer marketing." Thesis, Högskolan i Jönköping, Internationella Handelshögskolan, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-44077.

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This thesis examines how female consumers’ self-esteem may impact an influencer’s ability to create a purchase through suggesting and testing a developed conceptual model. The Source credibility model, Similarity and Tie-strength were utilized as underlying theoretical frameworks. Five different independent variables were identified; Source- Attractiveness, Trustworthiness, Expertise, Similarity, and Tie-strength, which were evaluated in relation to the dependent variable; Purchase intention. Lastly, Self-esteem was introduced as a moderating variable. The goal with the conceptual model was to gain a deeper understanding of how a consumer’s self-esteem may affect their purchasing behavior, as well as which factors that may influence their purchase intention. A quantitative research method was used, and ten hypotheses were developed from the conceptual model.    To test the hypotheses and answer the research questions, a questionnaire was distributed with the use of snowball sampling. Overall, 1029 Swedish females who followed an influencer on a social media participated in the survey. It was stated in the results and the analysis that all five independent variables had a significant positive relation on the consumer’s purchase intention. However, data shows that a consumer’s self-esteem solely had a relation on two of the five independent variables; Trustworthiness & Tie-strength. Trustworthiness was found to have a negative relation to the purchase intention, while Tie-strength was found to have a positive relation. A content analysis was conducted in order to identify other factors that the participants in the survey felt had a significant impact on why they followed their favorite influencer. The result of the content analysis identified two more factors that may impact the ability of an influencer to create a purchase. These were the Entertainment value and the Core values of the influencer.
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Ervin, Jennifer. "The Impact of Similarity on Influence Attempts during Group Discussions." Thesis, The University of Arizona, 2012. http://hdl.handle.net/10150/238656.

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Two studies were conducted in order to investigate the role of similarity and influence processes in groups. It was proposed that if group members believe they share one or more salient characteristics (i.e., relevant to the evaluation process) with a target it will (a) fundamentally change the way those group members orient themselves towards that target, and (b) subsequently affect the way those members contribute to the group discussion. Findings suggested that group members who were similar to a target were perceived as having contributed more novel arguments to the group discussion than those dissimilar, and high self-reported levels of communication competence significantly predicted a person's ability to generate arguments about a target. Limitations and future directions are discussed.
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Simmons, Sabrina. "The influence of Thematic relations on similarity and difference." Thesis, University of Warwick, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.487834.

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Nelson, Reid A. "Effects of similarity and tourist status on prosocial behavior : a field study in Spain /." Online version, 2009. http://content.wwu.edu/cdm4/item_viewer.php?CISOROOT=/theses&CISOPTR=320&CISOBOX=1&REC=9.

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Goodson, Ann Lesley. "The influence of parent-child behavioural similarity on parental empathetic responding." Thesis, Bangor University, 2004. https://research.bangor.ac.uk/portal/en/theses/the-influence-of-parentchild-behavioural-similarity-on-parental-empathetic-responding(b1337571-0111-4076-be2b-781c4685bfc5).html.

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Wifall, Timothy Curtis. "Reaching into response selection: stimulus and response similarity influence central operations." Diss., University of Iowa, 2014. https://ir.uiowa.edu/etd/1418.

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This dissertation examines the impact of stimulus and response similarity on response selection. Traditional models of response selection invoke a central processor that operates like a look-up table by matching the perceptually classified stimulus (e.g., green square) to the specified response (e.g., right button press). The look-up property of response selection affords the system the ability to map any stimulus onto any response, even if that stimulus-response has never been paired before. Under such an approach, the degree of perceptual similarity or dissimilarity that exists among stimuli in the environment should have little effect on central operations, the similarity or dissimilarity of the motor response executed in response to a stimulus should not influence response selection, and no interaction between stimulus and response features is permitted, given that stimulus features affect the encoding process, and response features affect the output process, but not response selection itself. Eight studies examine the influence of stimulus and response similarity during response selection. The first two experiments establish the interaction across different task demands between stimulus and response similarity. The interaction was not the result of perceptual difficulty (Experiment 3) and was extended to a new set of stimuli (Experiment 4). A consequence of the design in Experiments 1 - 4 was that response condition was confounded with response configuration. In one of the response conditions the target location had three competitors on one side of it compared to the other condition where the target had one competitor on one side and two others on the other side. Experiments 5 and 6 examined the separate roles that response configuration and response metrics had on the interaction between stimulus and response similarity. The mechanism that produced the interaction was the result of competition between partially activated stimulus-response alternatives. Experiments 7 and 8 further explored the role of competition during response selection by turning to traditional response selection methodologies that introduce competition through either the presentation of irrelevant stimulus information or through presenting the stimulus along an irrelevant spatial dimension. These data have broad implications for models of RS. To account for the ability to pair any stimulus modality with any response modality dominant accounts of RS assume that central operations are performed by a generic set of processes that operate over representations that are stripped of metric information (amodal representations). Response selection works as a look-up table that receives a categorized stimulus as an input and returns an abstract response code as output. This type of model cannot produce an interaction between stimulus and response similarity and thus, the present data provide a serious challenge to these types of models. Finally, the data provide evidence that the metric relationship between stimuli and response matter and influence response selection. The co-activation of stimulus-response alternatives are at a level of representation that includes both stimulus and response properties. A framework is presented that captures key aspects of the data.
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Ruys, Kirsten Inger. "The influence of self and similarity on immediate affective impressions of people." [S.l. : Amsterdam : s.n.] ; Universiteit van Amsterdam [Host], 2004. http://dare.uva.nl/document/76549.

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Zhou, Li. "Towards a deeper understanding of store branded lookalikes : similarity judgment and price influence." Thesis, University of East Anglia, 2016. https://ueaeprints.uea.ac.uk/59590/.

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The development of store branded lookalikes (SBLs) imitating established manufacturer national brands has long been a source of friction and dispute between brand manufacturers and retailers. It is evident that retailers often use a close positioning strategy on store brands (SBs) to imitate the look and appearance of leading national brands (NBs) on a wide range of fast moving consumer goods. It is, though, less clear why and how a me-too store brand is perceived to be a lookalike to an imitated national brand. At issue is a fundamental question: What makes a store brand lookalike and imitated national brand look alike? Precisely to what extent do the different packaging features, both in isolation and in tandem, trigger in the consumer’s mind similarity between the two goods? Furthermore, the overall market outcome from the introduction and use of lookalike packaging on store brands is also not clear or evidenced, especially its effect on pricing and more generally how this impacts national brand/store brand competition as well as well as competition between competing retailers each purveying their own store brand. Does offering a closer lookalike allow a retailer to price the store brand higher and close the price gap with the imitated national brand? Does offering a closer lookalike allow a retailer to price higher than rival retailers offering less close lookalike store brands? This thesis seeks to provide some answers to these important questions that have so far received relatively little attention in marketing research. The analysis is based on undertaking different studies of consumers’ perceptions gathered through structured surveys regarding actual national brand and store brand equivalents as well as through experiments in manipulating features of store brands (to control for individual effects) to understand how consumers form judgments over product similarity. Along with additional information provided by respondents on their own backgrounds and their shopping behaviour, this primary data is supplemented with secondary data on market features and outcomes, including market share and sales performance data as well as prices, to allow for consideration of contextual aspects that might influence similarity perceptions and also for analysing how the degree of perceived similarity relates to the price gap between competing products. Collectively, the studies undertaken and iv reported in the thesis provide several new and perhaps counterintuitive insights to improve our understanding of this prevalent marketing phenomenon and its effects on market outcomes as well as the nature of competitive rivalry in positioning and selling FMCG products. On the issue of what makes a brand and a lookalike look alike, the analysis shows that whether consumers perceive a store brand to be a lookalike is initially derived from the physical similarity of its packaging, which is primarily determined by colour, size & shape, and imagery. However, the analysis shows that the context matters. Specifically, the findings show that consumers’ degree of brand loyalty and brand familiarity, as well as their perception of the retailers’ store work together to influence the perception of similarity for a particular pairing of a national brand and the intended equivalent me-too store brand. Accordingly, different consumers will perceive the same product pairings differently based on their experience, tastes and broader perceptions. Regarding the nature of NB and SBL prices, it might be expected that high packaging similarity of SBLs will bring more intense price competition between the SBLs and the targeted NBs they imitate and among competing SBs. There is indeed evidence for this here. However, again, the context is shown to be important. Several marketing context indicators were considered in analysing the price competition between the products. A key finding is that the price gap tends to be wider for NBs that have growing sales (measured by a higher sales turnover compared to the previous year) or have higher market shares in a given category. In contrast, the price gap between an SBL and targeted NB tends to be lower the greater market power of the SBs in a category (measured by store brands share of category sales) and the strength of rival manufacturer brands in the same category (captured by relative brand shares). In terms of cross-retailer rivalry, an SBL tends to be priced more closely to a competing SBL the higher is SB familiarity and the greater the relative strength of the retailer (measured by its retailer market share). In contrast, higher category share held by store brands is found to allow for a wider price gap between competing SBLs. All these effects were tested in numerous FMCG product categories from across the v different leading grocery retailers in the UK, which adds a degree of reassurance about the generality to the studies conducted in this thesis. The findings reported in the thesis add to the existing literature in five significant ways. First, it confirms that colour, when treated in isolation or in tandem with other packaging features, is the most important packaging cue that determines the physical similarity of SBLs. Second, it reveals how various contextual indicators, such as brand loyalty, brand familiarity, and store image, can moderate the similarity perception process. Third, it demonstrates that the close packaging position of an SBL to a targeted NB will intensify the price competition between the NB manufacturer and the retailer. Fourth, it highlights the strategic importance of SBs in assisting retailers with cross-store competition where retailers compete amongst themselves through their SBLs. Fifth, it reveals the necessity of considering the influence of several frequently mentioned marketing performance indicators in this price competing process and these moderate or accentuate the packaging similarity effect, such as the targeted NB manufacturer’s market strength, the general market strength of the SBs, and the competition intensity in the NBs’ market.
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Wenzel, Christoph [Verfasser]. "DNS of compressible turbulent boundary layers: pressure-gradient influence and self-similarity / Christoph Wenzel." München : Verlag Dr. Hut, 2019. http://d-nb.info/1192568362/34.

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Books on the topic "Similarity with an influencer"

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Sturmer, Martin. Corporate Influencer. Wiesbaden: Springer Fachmedien Wiesbaden, 2020. http://dx.doi.org/10.1007/978-3-658-27870-0.

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Schach, Annika, and Timo Lommatzsch, eds. Influencer Relations. Wiesbaden: Springer Fachmedien Wiesbaden, 2018. http://dx.doi.org/10.1007/978-3-658-21188-2.

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Yesiloglu, Sevil, and Joyce Costello, eds. Influencer Marketing. 1 Edition. | New York : Routledge, 2021.: Routledge, 2020. http://dx.doi.org/10.4324/9780429322501.

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Fries, Peter J. Influencer-Marketing. Wiesbaden: Springer Fachmedien Wiesbaden, 2019. http://dx.doi.org/10.1007/978-3-658-25784-2.

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Jahnke, Marlis, ed. Influencer Marketing. Wiesbaden: Springer Fachmedien Wiesbaden, 2018. http://dx.doi.org/10.1007/978-3-658-20854-7.

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Jahnke, Marlis, ed. Influencer Marketing. Wiesbaden: Springer Fachmedien Wiesbaden, 2021. http://dx.doi.org/10.1007/978-3-658-31892-5.

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Kelly, Bernard. Similarity. Alsager: Crewe & Alsager College of Higher Education, Flexible Learning Centre, 1989.

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Laborde, Genie. Influencer avec intégrité. Paris: InterEditions, 1987.

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O'Sullivan, J. Examining similarity. Dublin: Trinity College, Dublin, 1992.

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Deges, Frank. Quick Guide Influencer Marketing. Wiesbaden: Springer Fachmedien Wiesbaden, 2018. http://dx.doi.org/10.1007/978-3-658-22163-8.

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Book chapters on the topic "Similarity with an influencer"

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Porro-Muñoz, Diana, Robert P. W. Duin, Isneri Talavera, and Mauricio Orozco-Alzate. "A Study on the Influence of Shape in Classifying Small Spectral Data Sets." In Similarity-Based Pattern Recognition, 306–20. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-24471-1_22.

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Fuchs, Christoph, and Adamantios Diamantopoulos. "Positioning Bases’ Influence on Product Similarity Perceptions." In Quantitative Marketing and Marketing Management, 325–51. Wiesbaden: Gabler Verlag, 2012. http://dx.doi.org/10.1007/978-3-8349-3722-3_16.

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Pratelli, Cristina. "How does leadership style (dis)similarity influence employees’ attitudes? An empirical study about CEO leadership succession in SMEs." In CEO Succession, Leadership, and (Dis)similarity, 73–111. Wiesbaden: Springer Fachmedien Wiesbaden, 2019. http://dx.doi.org/10.1007/978-3-658-24819-2_4.

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Aci, Samia, Gilles Bisson, Sylvaine Roy, and Samuel Wieczorek. "Clustering of Molecules: Influence of the Similarity Measures." In Selected Contributions in Data Analysis and Classification, 433–44. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-73560-1_40.

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Feldman, Laurie Beth, and Michal Raveh. "10. When degree of semantic similarity influences morphological processing." In Language Processing and Acquisition in Languages of Semitic, Root-Based, Morphology, 187–200. Amsterdam: John Benjamins Publishing Company, 2003. http://dx.doi.org/10.1075/lald.28.10fel.

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Ringbom, Håkan. "Chapter 4. The Importance of Different Types of Similarity in Transfer Studies." In Cross-linguistic Influences in the Second Language Lexicon, edited by Janusz Arabski, 36–45. Bristol, Blue Ridge Summit: Multilingual Matters, 2006. http://dx.doi.org/10.21832/9781853598579-007.

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Li, Songnan, and King Ngi Ngan. "Influence of the Smooth Region on the Structural Similarity Index." In Advances in Multimedia Information Processing - PCM 2009, 836–46. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-10467-1_74.

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Schudel, Kai, and Katharina Maag Merki. "Taking Composition and Similarity Effects into Account: Theoretical and Methodological Suggestions for Analyses of Nested School Data in School Improvement Research." In Accountability and Educational Improvement, 83–106. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-69345-9_6.

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AbstractSchool improvement research is faced with a school teaching staff, which is not a simple homogeneous entity. The compositional attributes of the teaching staff – such as diversity – can have a crucial influence on school processes. Whether the teaching staff is highly fractured, consists of sharply dissociated subgroups, or has shared beliefs, affects the adoption of school improvement programs differently. However, school improvement research has not yet taken into account what different compositions of the teaching staff mean from a methodological viewpoint. It is true that the use of multilevel analysis is standard in school improvement research and that it considers nested school data. However, this method alone only takes averaged measures of teaching staffs into consideration but not their different compositions. In this contribution, we argue that school improvement research has to consider, theoretically and methodologically, how compositional attributes of the teaching staff can be conceptualized. We first discuss some advancements in the conceptualization of group composition from research on small groups and organizations. We then incorporate suggestions for different diversity typologies from small group research to describe the compositional attributes of the teaching staff. Additionally, we address how the composition of the teaching staff influences each teacher differently, depending on the specific position a teacher has within the teaching staff. We further suggest incorporating the Group Actor-Partner Interdependence Model (GAPIM; Kenny, DA, Garcia RL, Small Group Res 43:468–496, 2012) as a methodological approach for assessing these compositional influences. In addition to classic multilevel analysis, the GAPIM also considers the effects of the other teachers on staff and the similarity and dissimilarity of a teacher to the other members of the teaching staff. Finally, we illustrate the possibilities of the theoretical and methodological endorsements discussed by applying the GAPIM to a data set of 37 German upper secondary schools by way of example. We show that a teacher’s job satisfaction is not only influenced by their individual and collective teacher self-efficacy but also by positional effects: The similarity of a teacher to the other teachers on staff and the similarity among the other members of the teaching staff have additional influences on job satisfaction.
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Giannantoni, Patrizia, and Viviana Egidi. "Similarity of Perceived Health Between Household Members: The “Mutual Influences” Hypothesis." In A Demographic Perspective on Gender, Family and Health in Europe, 133–54. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-72356-3_7.

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Lommatzsch, Timo. "Begriffsklärung: Influencer Marketing vs. Influencer Relations." In Influencer Relations, 23–26. Wiesbaden: Springer Fachmedien Wiesbaden, 2018. http://dx.doi.org/10.1007/978-3-658-21188-2_2.

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Conference papers on the topic "Similarity with an influencer"

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Sowmya, V., B. Vishnu Vardhan, and M. S. V. S. Bhadri Raju. "Influence of Token Similarity Measures for Semantic Textual Similarity." In 2016 IEEE 6th International Conference on Advanced Computing (IACC). IEEE, 2016. http://dx.doi.org/10.1109/iacc.2016.18.

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Wang, Guan, Qingbo Hu, and Philip S. Yu. "Influence and similarity on heterogeneous networks." In the 21st ACM international conference. New York, New York, USA: ACM Press, 2012. http://dx.doi.org/10.1145/2396761.2398453.

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Adel, Naeemeh, Keeley Crockett, Joao P. Carvalho, and Valerie Cross. "Fuzzy Influence in Fuzzy Semantic Similarity Measures." In 2021 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2021. http://dx.doi.org/10.1109/fuzz45933.2021.9494535.

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Love, Tamlin, and Ritesh Ajoodha. "Building Undirected Influence Ontologies Using Pairwise Similarity Functions." In 2020 International SAUPEC/RobMech/PRASA Conference. IEEE, 2020. http://dx.doi.org/10.1109/saupec/robmech/prasa48453.2020.9040984.

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Tang, Zeyang, Jie Xing, Hongyan Zhou, Xiaodong Yu, Kan Cao, Xin Shu, Bingke Yan, et al. "Influence Analysis of Voltage Loss on Similarity Calculation." In 2019 IEEE Innovative Smart Grid Technologies - Asia (ISGT Asia). IEEE, 2019. http://dx.doi.org/10.1109/isgt-asia.2019.8881745.

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Dickerson, Kelly, Jeremy R. Gaston, Brandon S. Perelman, Timothy Mermagen, and Ashley N. Foots. "Sound source similarity influences change perception in complex scenes." In 169th Meeting of the Acoustical Society of America. Acoustical Society of America, 2016. http://dx.doi.org/10.1121/2.0000152.

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Zevin, Jason D., and Thomas A. Farmer. "Similarity between vowels influences response execution in word identification." In Interspeech 2008. ISCA: ISCA, 2008. http://dx.doi.org/10.21437/interspeech.2008-532.

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Tang, Zeyang, Kunpeng Zhou, Kan Cao, Defu Cai, Li Wan, Xiaodong Yu, and Wenna Wang. "Influence Analysis of Voltage Stochastic Error on Similarity Calculation." In 2019 IEEE International Conference on Energy Internet (ICEI). IEEE, 2019. http://dx.doi.org/10.1109/icei.2019.00042.

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Rogdakis, E., and G. Dogkas. "Similarity Scaling of Vuilleumier Heat Pumps." In ASME 2015 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/imece2015-53571.

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Previous works on scaling methods for Stirling and regenerative machines, have yielded interesting results about the prediction of the performance of the machine. Information from existing Vuilleumier heat pump is utilized for a scaling correlation. Geometric and dynamic variables are selected for scaling investigation in terms of thermodynamic characteristics such as heat power input or heat power gain. This is accomplished with the aid of a specially developed computer program. In addition, energy dissipation due to pressure drop, losses across the heat exchangers walls and thermally ineffective regenerators are introduced and the performance of the Vuilleumier heat pump is reevaluated. A combination of scaling factors with two or more dynamic variables is derived for a deeper examination of scaling influences.
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Chen, Hui. "The Influences of Compiler Optimization on Binary Files Similarity Detection." In 2013 the International Conference on Education Technology and Information Systems (ICETIS 2013). Paris, France: Atlantis Press, 2013. http://dx.doi.org/10.2991/icetis-13.2013.221.

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Reports on the topic "Similarity with an influencer"

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Tostado, Philip. When You Aren't Who Your Friends Are: The Moderating Influence of Racial Similarity on the Association between Friendships and Mental Well-Being. Portland State University Library, January 2000. http://dx.doi.org/10.15760/etd.5902.

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Kim, Do Yuon, and Hye-Young Kim. An Influencer Like Me: Does Influencer Social Status Matter? Ames (Iowa): Iowa State University. Library, January 2019. http://dx.doi.org/10.31274/itaa.8758.

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Marsh, Sean M., Kara Marsh, Jason Fors, Stacy Emanuel, and Matt Boehmer. Influencer Poll Report and Crosstabulations. Fort Belvoir, VA: Defense Technical Information Center, November 2004. http://dx.doi.org/10.21236/ada431156.

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Sommermeyer, Katherine, and Sanjukta Pookulangara. LIKEtoKNOW.it: The Influencer Economy, An Exploratory Study. Ames (Iowa): Iowa State University. Library, January 2019. http://dx.doi.org/10.31274/itaa.8425.

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Snodgrass, J. G. Stimulus Similarity vs. Process Similarity in Picture Priming. Fort Belvoir, VA: Defense Technical Information Center, April 1997. http://dx.doi.org/10.21236/ada324781.

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Ting, Kai M. Non-Metric Similarity Measures. Fort Belvoir, VA: Defense Technical Information Center, March 2015. http://dx.doi.org/10.21236/ada622081.

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Shum, Heung-Yeung, Martial Hebert, and Katsushi Ikeuchi. On 3D Shape Similarity,. Fort Belvoir, VA: Defense Technical Information Center, November 1995. http://dx.doi.org/10.21236/ada303243.

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Martínez-Sala, AM, J. Monserrat-Gauchi, and J. Segarra-Saavedra. The influencer tourist 2.0: from anonymous tourist to opinion leader. Revista Latina de Comunicación Social, August 2019. http://dx.doi.org/10.4185/rlcs-2019-1388en.

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Boehmer, Matt, Andrea Zucker, Brian Ebarvia, Ray Seghers, and David Snyder. Department of Defense August 2003 Influencer Poll 1 Overview Report. Fort Belvoir, VA: Defense Technical Information Center, March 2004. http://dx.doi.org/10.21236/ada426582.

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Gentner, Dedre, and Mary Jo Rattermann. The Roles of Similarity in Transfer: Determinants of Similarity-Based Reminding and Mapping. Fort Belvoir, VA: Defense Technical Information Center, June 1991. http://dx.doi.org/10.21236/ada237005.

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