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Since influencer marketing becomes more sophisticated, it is difficult for brands to manage the strategy and process of this marketing practice. With a practical focus, this study aims at helping marketers cope with the challenge by developing conceptual typologies for influencers and followers and suggesting marketing implications for each type of influencer and follower.

This study subscribes to the perspectives of virtual community and social information processing to develop conceptual typologies for influencers and followers based on their essential characteristics.

Based on levels of expertise and interactivity, influencers can be categorized as broadcasters, leaders, friends and companions. Each type has advantages in certain branding objectives (e.g. increasing awareness, inducing judgments and feelings, building brand and user imagery, encouraging pro-brand behaviors and managing relationships) and is associated with certain marketing limitations (e.g. reach, domain breadth, informational support, brand congruence and relationship management). Based on levels of behavioral engagement and the point of attachment, followers are categorized into spectators, participants, admirers and advocators, with specific marketing communication strategies most effective for each type (e.g. strategies of content, narratives, engagement and co-branding).

The study translates the idea of influencer community into a practically useful framework for practitioners to best leverage influencer marketing and an innovative perspective for scholars to further investigate the phenomenon.

Since the development of the COVID-19 vaccinations, questions surrounding race have been prominent in the literature on vaccine uptake. Early in the vaccine rollout, public health officials were concerned with the relatively lower rates of uptake among certain racial/ethnic minority groups. We suggest that this may also be patterned by racial/ethnic residential segregation, which previous work has demonstrated to be an important factor for both health and access to health care.

In this study, we examine county-level vaccination rates, racial/ethnic composition, and residential segregation across the U.S. We compile data from several sources, including the American Community Survey (ACS) and Centers for Disease Control (CDC) measured at the county level.

We find that just looking at the associations between racial/ethnic composition and vaccination rates, both percent Black and percent White are significant and negative, meaning that higher percentages of these groups in a county are associated with lower vaccination rates, whereas the opposite is the case for percent Latino. When we factor in segregation, as measured by the index of dissimilarity, the patterns change somewhat. Dissimilarity itself was not significant in the models across all groups, but when interacted with race/ethnic composition, it moderates the association. For both percent Black and percent White, the interaction with the Black-White dissimilarity index is significant and negative, meaning that it deepens the negative association between composition and the vaccination rate.

The analysis is only limited to county-level measures of racial/ethnic composition and vaccination rates, so we are unable to see at the individual-level who is getting vaccinated.

We find that segregation moderates the association between racial/ethnic composition and vaccination rates, suggesting that local race relations in a county helps contextualize the compositional effects of race/ethnicity.

The aim of the study is to systematically map the articles published in the area of organic food value chain. Many articles have been published in various domains of organic food value chain, but no significant study has been found related to the systematic mapping of literature.

This study relies on secondary data. Articles from Scopus and Google Scholar databases between January 1, 1990, and July 10, 2021, have been considered. On the basis of inclusion criteria, 56 articles have been analysed in this systematic mapping study.

This study describes the geographical coverage, the methodologies used, sector/industry-specific context of the articles and scope the for future research. Five clusters were identified through co-occurrence analysis: (1) “organic agriculture and sustainable value chain” (2) “organic farming and food value chain,” (3) “organic value chain and sustainable development,” (4) “organic value chain and environmental impact” and (5) organic value chain and profitability.

The study considers only articles published in Scopus and Google Scholar with some specific keywords related to the value chain and organic food industry. Future studies are encouraged by considering a wide range of keywords with a larger data set.

To the best of the author's knowledge, this study is the first to have a systematic mapping of literature on the organic food value chain.