Can we sense shift in consumer behaviour in Portuguese retail companies due to the pandemic?

The 2019 coronavirus pandemic (COVID-19) has effects in the most diverse fields of our society, from mental health and lifestyle to commerce and education. A huge adaptation by the population and restructuring of habits was necessary to make progress in this new reality, leading several companies to reinvent the way they conducted their businesses and a complete metamorphosis of their business plans. As such, there was an interest in conducting this research to understand how consumer behaviour in Portuguese retail companies was affected by the lockdown in the country, aiming to identify the change in the purchase intention of consumers living in Portugal and what motivated this same change, allowing extracting information to help organizations in the decision making. Thus, 15,000 comments were collected from the social network Facebook referring to the pre-lockdown, lockdown, and post-lockdown period in Portugal. Then, data mining techniques and processes were used to clean the set of collected data and extract knowledge. Furthermore, an Intention Mining analysis was carried out to assess the collected comments and draw conclusions. Finally, the results of this study indicate a negative evolution in the purchase intention of consumers, verifying that the relationship with the company deteriorated and problems in the supply chain increased, indicating that it is necessary to redirect strategies to improve the service of customer support and distribution channels to meet customer satisfaction and may apply to other countries in similar contexts.A pandemia do coronavírus 2019 (COVID-19) tem efeitos nos mais diversos campos da sociedade, desde a saúde mental e estilo de vida, ao comércio e educação. Foi necessária uma enorme adaptação da população e reestruturação de hábitos para conseguir avançar nesta nova realidade, levando várias empresas a reinventar a forma como conduziam os seus negócios e a uma completa metamorfose dos respetivos planos de negócio. Como tal, surgiu o interesse em realizar esta investigação para compreender como o comportamento do consumidor nas empresas de retalho portuguesas foi afetado pelo confinamento no país, tendo como objetivo identificar a mudança na intenção de compra dos consumidores a viver em Portugal e o que motivou essa mesma mudança, permitindo extrair informações que permitam auxiliar na tomada de decisão das organizações. Assim, recolheram-se 15,000 comentários da rede social Facebook referentes ao período pré-confinamento, confinamento e pós-confinamento em Portugal. Em seguida, foram utilizados técnicas e processos de mineração de dados para limpeza do conjunto de dados recolhidos e extração de conhecimento. Ainda, realizou-se uma análise de mineração de intenções para avaliar os comentários recolhidos e extrair conclusões. Por fim, os resultados deste estudo indicam uma evolução negativa na intenção de compra dos consumidores, verificando-se que a relação com a empresa deteriorou-se e problemas ao nível da supply chain aumentaram, indicando ser necessário redirecionar as estratégias para melhorar o serviço de apoio ao cliente e os canais de distribuição para ir ao encontro da satisfação dos clientes, podendo ser aplicável a outros países em contextos semelhantes

Dynamic Characteristic of Consumer Attention in Online Reviews —Empirical Research Based on Mobile Store Reviews

Nowadays consumer online reviews are becoming more and more important for enterprise decision-making. While the existing research seldom discussed review data from a dynamic perspective, especially ignored consumers\u27 attention change during the product life cycle. To study whether there are dynamic changes and the characteristics of changes in the attention degree of consumers in each phase of the product life cycle, this paper coded a specific node program to collect the online reviews data of the four mobile phones in the entire product life cycle and used python\u27s Chinese automatic word segmentation tool library to segment each word and count word frequency, and then a stepwise regression method was used to analyze the dynamic changes of consumer attention. The paper finds that consumers’ attention on logistics and products presented in online reviews show a downward trend, and the attention on brands shows an upward trend; There is no obvious change in the attention degree on services, prices, and promotion; On the different dimensions of products, there is a significant difference in the attention degree. The research results broad the research ideas of online reviews, provide decision-making basis for enterprises to grasp the characteristics of consumers at different stages and to formulate production and marketing strategies

The applications of social media in sports marketing

n the era of big data, sports consumer's activities in social media become valuable assets to sports marketers. In this paper, the authors review extant literature regarding how to effectively use social media to promote sports as well as how to effectively analyze social media data to support business decisions. Methods: The literature review method. Results: Our findings suggest that sports marketers can use social media to achieve the following goals, such as facilitating marketing communication campaigns, adding values to sports products and services, creating a two-way communication between sports brands and consumers, supporting sports sponsorship program, and forging brand communities. As to how to effectively analyze social media data to support business decisions, extent literature suggests that sports marketers to undertake traffic and engagement analysis on their social media sites as well as to conduct sentiment analysis to probe customer's opinions. These insights can support various aspects of business decisions, such as marketing communication management, consumer's voice probing, and sales predictions. Conclusion: Social media are ubiquitous in the sports marketing and consumption practices. In the era of big data, these ＂footprints＂ can now be effectively analyzed to generate insights to support business decisions. Recommendations to both the sports marketing practices and research are also addressed

Research on Image Perception of Luxury Hotels in Dalian Based on Text Analysis

In recent years, with the development of mobile Internet and smartphones, more and more consumers will share their feelings and thoughts after staying in the hotel on the website, thus forming many online comments. These online comments reflect consumers\u27 perception of the hotel image to a certain extent. This paper uses Python to collect 35977 online comment data of luxury hotels in Dalian. Through the analysis of high-frequency words, characteristic words, and comment emotion, it is found that the main factors affecting the perception of hotel image are: hotel location, room condition, environmental sanitation, service attitude, and professional ability of receptionist and other service personnel. Finally, according to the research conclusions, provide personalized suggestions for the hotel to improve its image

Sentiment Mining of Consumer Reviews: Evidence from Guangxi Fresh Fruit Supply on China's JD.com E-commerce Platform

This study identifies the product supply chain management issues based on significant data analysis methods by considering user evaluation data from JD.com e-commerce platform, a central e-commerce platform in China. Fresh fruit contributes to substantial sales in e-commerce platforms due to the particular characteristics of freshness. The quality perception of fresh fruits directly affects consumers' trust and willingness to repurchase. Therefore, studying the perceived value of online shopping for fresh fruit consumers in Guangxi, China, is significant to the operation and marketing of fresh fruit e-commerce. In view of these perspectives, we developed a user portrait model for fresh fruits in the Guangxi province based on three key dimensions: user information, fruit category details, and user evaluation information. Utilizing Rost CM software to analyze the content of user comments, including keyword word frequency analysis, semantic network analysis and consumers' shopping sentiment mining, so as to find out the existing problems, and provide decision-making reference for the improvement of the supply chain system of fresh fruits in Guangxi

Path Analysis of Perceived Value Influence on Shopping Satisfaction of Online Customers in the View of Mental Accounting

As a kind of psychological activity in the individuals, families or organizations, mental accounting focuses on economic activity, coding and evaluation. It is of practical significance to explore customer behavior patterns and psychological changes, and improve customer satisfaction through reasonable marketing. Online enterprises need to pay attention to the perceived value of consumers and enhance overall consumer satisfaction so as to achieve long-term and stable development under the background of economic globalization. Enterprises and organizations obtain complete and accurate personalized demand information of consumers in order to achieve a win-win situation for both consumers and enterprises. This study focuses on the influencing factors of online shopping satisfaction of consumers in the new environment of online and offline integration, and explores the path dependence and influence of online consumer perceived value and the website features of consumer satisfaction. Based on the theory of mental accounting and consumer behavior, this study combines the Howard-Sheth model with the consumer perception value theory to construct a theoretical framework. This study extends prior work by using structural equation model to test the effect of perceived value on website features, trust and customer satisfaction from the perspective of mental accounting. It is hoped that this study can provide data reference and theoretical guidance for online enterprises in marketing and knowledge management, in a bid to develop accurate marketing strategies, customer segmentation and differentiated services, improve the operation mechanism of network market and promote online services

Designing a Customer Relationship Management System in Online Business

With the advancement of online shopping technology, it has become the first choice for most consumers. The activity of online stores in this competitive business space should be in line with the expectations of their customers. Understanding, collecting, maintaining and organize data in online stores makes it easier for managers to decide. So, in this research, we examine the textual and non-textual of user opinions and reviews. We use rapid miner software and text mining. In this research, the processes are aimed at finding active users, analyze the user type and their suggestions, analyzing the strengths and weaknesses of the products, and categorizing them with the K-NN and Naïve Bayes algorithms.  Finally, suggestions were made to increase loyalty and improve business using the results obtained from the processes

The relationship between brand coolness, brand love, loyalty and e-WOM: A text mining and sentiment analysis approach focused on a tech brand (Apple)

Brand coolness is a multidimensional construct that encompasses different characteristics consumers perceive in a brand they think is cool. More research has been dedicated to the theme in recent years, been recognized as being of great importance for companies and marketeers alike. Brand love is another construct, which encompasses many kinds of positive emotions a customer can have regarding a brand. Previous research has been mostly based on prompted, pre-formatted surveys. Concurrently, the new wealth of data available online has brought along new technology able to extract and analyze said data, its value being widely recognized for many marketing and managerial purposes. This dissertation contributed to existing research by proposing a different method to gather and analyze consumer online feedback regarding a tech brand, using text mining and sentiment analysis techniques. More than 2000 consumer reviews were extracted, cleaned, processed and analyzed and a model was tested using linear regression models, for the relationship between brand coolness, brand love, loyalty and e-WOM (measured in its volume). Results showed brand coolness is rather present in consumer online feedback regarding a tech brand, and that of all the brand coolness subdimensions, useful/reliable, usability and aesthetic were the most represented; extraordinary, energetic, and original/innovative were the most positively evaluated. In addition, results also showed there is in fact a causation effect of brand coolness on brand love and of those two on loyalty. The causal relationship between brand love and loyalty with e-WOM, measured in its volume, was not statistically significant.Brand coolness é um construto multidimensional que abrange diferentes características que os consumidores podem percecionar numa marca que consideram cool. Vários estudos têm sido dedicados ao tema nos últimos anos, que tem sido reconhecido como de grande importância para empresas e profissionais de marketing. Brand love é outro constructo que abrange vários tipos de emoções positivas que um consumidor pode ter em relação a uma marca. Estudos anteriores basearam-se principalmente em questionários pré-formatados. Ao mesmo tempo, a riqueza dos dados online trouxe novas tecnologias para extrair e analisar esses dados, sendo o seu valor reconhecido para muitos fins de marketing e de gestão. Esta tese contribui para a literatura, propondo um método diferente para recolher e analisar o feedback online do consumidor em relação a uma marca de tecnologia, utilizando técnicas de mineração de texto e análise de sentimento. Mais de 2000 críticas de consumidores foram extraídas, limpas, processadas e analisadas e as hipoteses foram testadas usando modelos de regressão linear, para a relação entre brand coolness, brand love, loyalty e e-WOM. Os resultados mostraram que o brand coolness está presente no feedback online do consumidor, e que, de todas as subdimensões do brand coolness, útil/confiável, usabilidade e estética foram as mais representadas; extraordinário, enérgico e original/inovador foram avaliadas mais positivamente. Além disso, os resultados mostraram que existe um efeito causal de brand coolness no brand love e de ambos em loyalty. A relação causal entre brand love e loyalty com e-WOM, medido em volume, não foi significativa estatisticamente

Importance of Social Network Structures in Influencer Marketing

As collaborations between brands and influencers become increasingly popular, predicting the capacity of an influencer to generate engagement has garnered increasing attention from researchers. Traditionally, managers have been relying on follower-based statistics to identify individuals with potential to reach a vast number of users on social-media. However, this approach may often direct managers to accounts with millions of followers accompanied with high recruiting costs. In this paper, we argue that the network structure of influencers is a useful measure for capturing an influencer’s ability to generate engagement. Using Instagram data, we perform a deep-learning analysis on the social network of influencers and show that the network structure explains a large share of the variations in user engagement, even outperforming traditionally used variables such as the number of followers in the case of comments. This study contributes to the emergent literature on the importance of social ties in the digital environmen

Research on the Construction Mechanism of Consumers’ Trust Intentions and Behaviors in the Context of Live Streaming Shopping

As a new-type media form integrating text, image, video, and audio, live streaming itself is an excellent way of informationcarrying and interaction. And the development of information technology makes the use of live streaming shopping easier and more convenient. At the same time, with the popularity of live streaming marketing, there are also some consumption traps, which not only harm the rights and interests of consumers but also affect its own development. Thus, how to build trust and improve the credit evaluation mechanism has become a common concern of academic and industrial circles. Anchored in the theory of planned behavior (TPB) and other research results, this paper expounds on the definition and connotation of trust intention in live streaming shopping in detail. From the perspective of consumers, the trust model of live streaming shopping is constructed based on the comprehensive consideration of social presence, consumers\u27 personal attitude, and structural assurance. It adopts partial least squares (PLS) structural equation modeling (SEM) to evaluate the research model and hypothesis. On the basis of 259 samples, the result shows that consumers\u27 trust behavior in live streaming shopping is mainly affected by live streamers\u27 personalities, comment information, social presence, platform characteristics, usefulness, and structural assurance. The research result of this paper will play a positive role in building a more credible environment, improving the trust relationship with consumers, and promoting potential transactions. Meanwhile, it also lays a foundation for understanding consumers\u27 trust behavior and related theories in the context of China