Projected Destination Image of Beijing on Instagram: A Sequential Research Design

Abstract

Using a sequential research design combining image analytics and Qualitative Comparative Analysis (QCA), this research examines Beijing’s projected destination image and its impacts on social media engagement on Instagram. Deep learning algorithms and convolutional neural networks were used to analyze the images. The image analytic findings show that Beijing’s projected destination image includes: (1) multiple urban and country landscapes; (2) a mixture of modernity and tradition; (3) a range of activities in a dynamic city and (4) cuisine—a variety of traditional Chinese food. QCA identified three paths that lead to high engagement, including “building” and “sky,” “building” and “event,” “sky,” and “event.” This research advances the destination image literature by empirically establishing the relationship between destination image labels and social media engagement. Further, it offers a new configurational perspective for constructing projected destination image by delineating how DMOs effectively increase social media engagement through image semantic content configurations.