Negative brand meaning co‐creation in social media brand communities: A laddering approach using NVivo

Social media brand communities (SMBCs) have been heralded for their co‐creative, participatory potential whereby consumers actively contribute to the proliferation of meaningful brand avenues in a virtuously circular relationship with brands. Elevated loyalty and enhanced brand equity have been posited repeatedly as likely outcomes of a positively engaged community of brand aficionados. However, evidence to the contrary as negative brand co‐creation or brand co‐destruction has been progressively piling up in the extant literature. This paper contributes to the meaning co‐creation in SMBCs literature primarily on two grounds: first, by offering a methodological framework for adapting the laddering research technique in a mixed methods vein to SMBCs data in a thread‐specific context, by leveraging the analytical capabilities of NVivo CAQDAS software; second, by addressing bottlenecks in the applicability of the proposed methodology in light of negative brand co‐creation.     

基于NVivo软件的互联网旅游文本的质性研究——以贵州黔东南肇兴的旅游者文本为例

现有的国内研究对互联网上的旅游者文本关注很少,也缺乏对质性研究的重视．运用质性分析软件NViv07.0对一个典型的民族旅游目的地的旅游者在互联网上传播的旅游者文本进行质性分析研究。研究通过搜索引擎选取最具代表性的15篇文本,通过NVivo对其进行信息编码,最终筛选得到3个概念范畴的议题。研究发现,旅游者对该目的地的总体感知倾向于正面评价;旅游者的旅游体验质量总体较高,但对旅游服务设施抱怨明显。此外,从人类学角度探讨了“想象”、“现代性”和“传统”的议题。研究认为对互联网旅游者文本的分析有助于旅游体验和满意度的研究,并试探性地分析认为民族旅游地居民在旅游发展中缺乏足够的话语权,并以此解释旅游者“想象”破灭的抱怨。     

Analysing customers' reviews and ratings for online food deliveries: A text mining approach

The purpose of this study was to explore the relationship between online reviews and ratings through text mining and empirical techniques. An Indian food delivery portal ( Zomato.com ) was used, where 50 restaurants on Presence Across Nation (PAN) basis were selected through stratified random sampling. A total of 2530 reviews were collected, scrutinized, and analysed. Using the NVivo software for qualitative analysis, seven themes were identified from collected reviews, out of which, the ‘delivery’ theme was explored further for identifying sub-themes. Linear regression modelling was used to identify the variables affecting delivery ratings and sentiment analysis was also performed on the identified sub-themes. Regression results revealed that hygiene and pricing (delivery subthemes) demonstrated lower delivery ratings. These variables can be established as indicators for restaurants and related online food delivery services to build their business model around them. Similarly, negative sentiments were observed in pricing and hygiene sub-themes. Restaurants and online food services can enhance hygiene levels of their food delivery process in order to receive higher delivery ratings. Similarly, pricing of food items can be modified such that customers are not deterred from ordering the items—food and ordering service do not become cost-prohibitive. This study devised a standardized methodology for analysing vast amounts of online user-generated content (UGC). Findings from this study can be extrapolated to other sectors and service industries such as, tourism, cleaning, transportation, hospitals and engineering especially during the pandemic.