Analysis of Customers’ Reactions to E-Commerce Companies Using Instagram Data

Abstract

The aim of this study is to develop a web application that supports decision-making processes on subjects—such as customer relations management, marketing, and stock management—with data such as posts, comments, and likes from Instagram to four e-commerce companies. In this context, the data obtained from the Instagram accounts of e-commerce companies were recorded in a database after the pre-processing and classification stages. A web application has been developed that can support managers in their decision-making processes at operational, tactical, and strategic decision-making levels by visualizing the data recorded in the database.

Marketing of luxurious gastronomic experiences on social media: The visual storytelling of luxury hotels

“…The content analysis focused on the quantitative categorisations of the Instagram posts by denotative meaning, that is, the direct and rational elements represented (Hunter, 2015; Wegerer & Volo, 2021). The visual representations of the Instagram posts were identified and coded by denotative type as demonstrated in earlier studies (Akkol, 2021; Atiencia et al, 2020; De Perthuis & Findlay, 2019; Yu & Sun, 2019) under (a) hotel (these posts represented hotel related features), (b) people (grouped as staff and customers), (c) gastronomy (the content that represented the direct denotative elements of gastronomy were coded as food, multiple food products, beverages, multiple beverage products, dishes, and multiple dishes), and (d) others (grouped as information and hotel promotion). To minimise bias the second step also involved both researchers in the segmentation of all the posts with gastronomic content; this led to the identification of 447 posts (see Table 2) which were selected for data analysis.…”

“…The visual representations of the Instagram posts were identified and coded by denotative type as demonstrated in earlier studies (Akkol, 2021;Atiencia et al, 2020;De Perthuis & Findlay, 2019;Yu & Sun, 2019) (grouped as information and hotel promotion). To minimise bias the second step also involved both researchers in the segmentation of all the posts with gastronomic content; this led to the identification of 447 posts (see Table 2) which were selected for data analysis.…”

The Algorithm of a Game-Based System in the Relation between an Operator and a Technical Object in Management of E-Commerce Logistics Processes with the Use of Machine Learning

“…Utilising this cognitive gap, the Authors make an attempt to prove that automation and autonomous transportation in e-commerce logistic processes have become practical activities and should be therefore treated as a part of contemporary e-commerce [ 11 ]. As a logic consequence, this type of e-commerce activity should be supported by the properly prepared ML algorithms with control applications (prepared in the field of applied theory) for better use of automated guided vehicles (AGV), including drones within the range of B2C e-commerce delivery processes [ 12 ].…”