That’s So Instagrammable! Understanding How Environments Generate Indirect Advertising by Cueing Consumer-Generated Content

TY - JOUR

T1 - That’s So Instagrammable! Understanding How Environments Generate Indirect Advertising by Cueing Consumer-Generated Content

AU - Campbell, Colin L.

AU - Sands, Sean

AU - Montecchi, Matteo

AU - Jensen Schau, Hope

PY - 2022/4/26

Y1 - 2022/4/26

N2 - This article explores how firms, through characteristics of physical environments, can inspire consumers to engage in creating and posting environment-cued indirect advertising, or what is commonly known as “Instagramming.” The first study is used to qualitatively understand what makes an environment “Instagrammable” from the designer perspective. Emergent themes are used to inform a second study, a quantitative analysis of 43,004 instances of indirect advertising gathered by scraping Instagram postings from 97 environments in four prominent pop culture museums. After manually sorting the data, both artificial intelligence (AI)-enabled computer vision and manual coding are used to quantify multiple environment characteristics. Analysis reveals how different environment characteristics affect the creation of indirect advertising. Environments that use more interactive props, color, and brightness are associated with greater indirect advertising. Except in limited cases, most design themes have no effects—or negative effects—on indirect advertising. This article also contributes to the emerging literature on computer vision by showcasing how AI can offer insight for better understanding shared digital content.

AB - This article explores how firms, through characteristics of physical environments, can inspire consumers to engage in creating and posting environment-cued indirect advertising, or what is commonly known as “Instagramming.” The first study is used to qualitatively understand what makes an environment “Instagrammable” from the designer perspective. Emergent themes are used to inform a second study, a quantitative analysis of 43,004 instances of indirect advertising gathered by scraping Instagram postings from 97 environments in four prominent pop culture museums. After manually sorting the data, both artificial intelligence (AI)-enabled computer vision and manual coding are used to quantify multiple environment characteristics. Analysis reveals how different environment characteristics affect the creation of indirect advertising. Environments that use more interactive props, color, and brightness are associated with greater indirect advertising. Except in limited cases, most design themes have no effects—or negative effects—on indirect advertising. This article also contributes to the emerging literature on computer vision by showcasing how AI can offer insight for better understanding shared digital content.

UR - http://www.scopus.com/inward/record.url?scp=85130049895&partnerID=8YFLogxK

U2 - https://doi.org/10.1080/00913367.2022.2053901

DO - https://doi.org/10.1080/00913367.2022.2053901

M3 - Article

SN - 0091-3367

VL - 51

SP - 411

EP - 429

JO - JOURNAL OF ADVERTISING

JF - JOURNAL OF ADVERTISING

IS - 4

ER -