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This study aims to compare online review characteristics, review length and review sentiment score between “organic” and “regular” food products. In addition, variations in the consumer sentiment scores across the review lengths are studied.

This study fits into the descriptive research design. From Amazon’s website, the consumer product reviews are scrapped. Using the text analytical package “sentiment” in R-Studio, we computed the sentiment scores and counted the number of words in each review. The mean sentiment scores and mean review length are compared for regular and organic products using one-way ANOVA. Sentiment score variation across review length and product class is studied through factorial ANOVA. Sample reviews of ghee and honey are used to test the hypotheses.

The review length shows a significant difference between the regular and organic products. The mean number of words in the regular products reviews is significantly lower than the mean number of words in the organic product reviews. The regular products’ mean sentiment score is significantly lower than the mean sentiment score of organic products. The mean sentiment scores are not consistent between ghee and honey. Sentiment scores are better for organic honey and regular ghee products. For regular ghee products, longer reviews result in lower sentiment scores. For regular and organic versions of honey, longer reviews are associated with better sentiment scores.

This study did not include the helpfulness of a review and the demographic data of the reviewers.

Sentiment scores’ variations across the regular and organic and product categories such as ghee and honey give a comprehensive feedback to the firms. It also indirectly communicates a brand’s evaluation by the consumers and the performance feedback for an upward extension like the organic category.

Studies on organic category give feedback for environment-friendly products and consumer attitude shift towards safer products.

Very limited studies have reported the upward line extensions. The authors study the upward line extension organic and associated sentiment scores variation. The role of review length and its systematic influence on the sentiment scores, variations in the review due to the product nature (organic/regular) are unique contributions of this study.

Food companies and consumers are increasingly interested in healthy food and beverages. Coffee is one of the most commonly consumed beverages worldwide. There is increasing consensus that coffee consumption can have beneficial effects on human body. This paper aims at exploring Twitter messages' content and sentiment towards health attributes of coffee.

The research adopted a utilitarian and hedonic consumer behaviour perspective to analyse online community messages. A sample of 13,000 tweets, from around 4,800 users, that mentions keywords coffee and health was collected on a daily basis for a month in mid-2017. The tweets were categorized with a term frequency analysis, keyword-in-context analysis and sentiment analysis.

Results showed that the majority of tweets are neutral or slightly positive towards coffee’s effects on health. Media and consumers are dynamic Twitter users. Findings support that coffee consumption brings favourable emotions, wellness, energy, positive state of mind and an enjoyable and trendy lifestyle. Many tweets have a positive perception of coffee health benefits, especially relating to mental and physical well-being.

The high number of users and tweets analysed compensates the limited amount of time of data collection, Twitter messages' restricted number of characters and quantitative software analysis limitations.

The research provides valuable suggestions for food and beverage industry managers.

This work adds value to the literature by expanding scholars' research on food product attributes perception analysis by using social media as a source of information. Moreover, it provides valuable information on marketable coffee attributes.

Building on tourism crisis studies and behavioral economics, this study describes a national survey conducted among 439 Aruban tourism and nontourism employees.

Regression analysis was subsequently conducted to analyze the relationship between experienced well-being, crisis duration and tourism and nontourism employee sentiments.

The findings indicate that tourism employee sentiments are generally, and significantly, more negative and their concerns about the future are significantly more pessimistic than nontourism employees. The results show that the experienced well-being and expected duration of the COVID-19 crisis have a significant negative effect on tourism employees' sentiments. The paper provides several policies and industry recommendations for strengthening tourism employee well-being and economic resilience. Several avenues for future research are presented.

The current study contributes to this literature by showing that the increased pessimism and negativity of the tourism employees as compared to nontourism employees during the current pandemic influence their thoughts about future income and earnings as well as future purchases.

The purpose of this study is to analyze how sentiment affects economic activity in Brazil.

Based on a nonlinear autoregressive distributed lag (NARDL) model, this study examines in detail the short-term and long-term asymmetric impacts between the variables during the period from January 2007 to December 2020.

There are three main results of this study. First, sentiment is an important factor for economic activity in Brazil, and its effect possibly occurs through the channels of consumption and investment, which are the two main components of economic growth. Second, sentiment affects economic activity in different ways in the short and the long term: in Brazil, although in the short-term, immediate shocks of sentiment may be confusing, the negative shocks from previous periods have a negative impact on economic activity. Third, the effect of shocks of optimism and pessimism on economic activity is asymmetric, and in the long run, only shocks of optimism have a significant and positive impact.

The relationship between sentiment and economic activity is still a controversial issue in the literature and this study seeks to advance its understanding in Brazil.

We examine the relation between investor sentiment proxies and the risk neutral skewness of S&P 500 index option. The risk neutral skewness is estimated by the method of Bakshi, Kapadia and Madan (2003), which is non-parametric method, and the interpolation-extrapolation method and trapezoidal rule is used. We use four sentiment proxies: Michigan Consumer Sentiment Index, non-commercial trader's net position of S&P 500 futures market, Baker and Wurgler (2006)'s sentiment index, and bull-bear survey of American Association of Individual Investors. We firstly conduct the regression to find the general relations of two variables, and then examine the lead-lag relation between investor sentiment proxies and risk neutral skewness through VAR analysis. Contrary to the previous studies, we observe that sentiment proxies show different signs by the economic conditions. Overall, the sentiment proxies explain the three-dimension moment better in the crisis in U.S, and especially non-commercial trader's net position of S&P 500 futures market explains bet among the proxies.

The objective of this paper is to examine the determinants of the Greek house market during the period 2006–2022 using not only economic variables but also behavioral variables, taking advantage of available information on the volume of Google searches. In order to quantify the behavioral variables, we implement a Python code using the Pytrends 4.9.2 library.

In our study, we assert that models relying solely on economic variables, such as GDP growth, mortgage interest rates and inflation, may lack precision compared to those that integrate behavioral indicators. Recognizing the importance of behavioral insights, we incorporate Google Trends data as a key behavioral indicator, aiming to enhance our understanding of market dynamics by capturing online interest in Greek real estate through searches related to house prices, sales and related topics. To quantify our behavioral indicators, we utilize a Python code leveraging Pytrends, enabling us to extract relevant queries for global and local searches. We employ the EGARCH(1,1) model on the Greek house price index, testing several macroeconomic variables alongside our Google Trends indexes to explain housing returns.

Our findings show that in some cases the relationship between economic variables, such as inflation and mortgage rates, and house prices is not always consistent with the theory because we should highlight the special conditions of the examined country. The country of our sample, Greece, presents the special case of a country with severe sovereign debt issues, which at the same time has the privilege to have a strong currency and the support and the obligations of being an EU/EMU member.

The results suggest that Google Trends can be a valuable tool for academics and practitioners in order to understand what drives house prices. However, further research should be carried out on this topic, for example, causality relationships, to gain deeper insight into the possibilities and limitations of using such tools in analyzing housing market trends.

This is the first paper, to the best of our knowledge, that examines the benefits of Google Trends in studying the Greek house market.

Do consumers rate reviews describing other consumers' sensory experience of a product (touch, smell, sight, hear and taste) as helpful or do they rate reviews describing more practical properties (product performance and characteristics/features) as more helpful? What is the effect of review helpfulness on purchase intention? Furthermore, why do consumers perceive sensory and non-sensory reviews differently? This study answers these questions.

The authors analyze 447,792 Amazon reviews and perform a topic modeling analysis to extract the main topics that consumers express in their reviews. Then, the topics were used as regressors to predict the number of consumers who found the review helpful. Finally, a lab experiment was conducted to replicate the results in a more controlled environment to test the serial mediation effect.

Contrary to the overwhelming evidence supporting the positive effects of sensory elicitation in marketing, this study shows that sensory reviews are less likely to be helpful than non-sensory reviews. Moreover, a key reason why sensory reviews are less effective is that they decrease the objective perception of the review, a less objective review then decreases the level of helpfulness, which decreases purchase intention.

This study contributes to the interactive marketing field by investigating customer behavior and interactivity in online shopping sites and to the sensory marketing literature by identifying a boundary condition, the authors’ data suggest that sensory elicitations might not be processed positively by consumers when they are not directly experienced, but instead communicated by another consumer. Moreover, this study indicates how companies can encourage consumers to share more effective and helpful reviews.

The purpose of this paper is to examine the influence of consumers’ perceived corporate social responsibility (CSR). The aim is to provide insight into the effect of perceived CSR on purchase intention (short-term effect) and corporate reputation (long-term effect), whilst considering the role of brand image, satisfaction (affective and cognitive) and brand loyalty.

The sample comprised 429 consumers selected using non-probabilistic sampling with age and gender quotas. Confirmatory factor analysis was used to validate the measurement model. Structural equation modelling was used to validate the research hypotheses.

All direct and mediated influences in the model were significant, except for the effects of perceived CSR on affective satisfaction. Thus, the proposed causal chain is valuable to understand how perceptions of CSR influence purchase intention and perceived reputation.

Perception is considered a dual phenomenon (cognitive and affective). It would be advisable to consider both dimensions in the future. The same is true of affective satisfaction.

Direct and mediated relationships that have previously been studied separately are considered together in a single model. This approach provides a better understanding of how perceived CSR influences purchase intention and reputation.

With the growing popularity of social media, it has become common practice for consumers to write online reviews to share their opinion and experience as well as consider others' reviews to inform purchase decision-making. This study investigated how online review sentiments towards four key aspects (food, service, ambience and price) change after a restaurant is awarded a Michelin Star to shed light on how the award of a Michelin Star affects online reviews as well as what factors contribute to positive online restaurant reviews.

The authors conducted a sentiment analysis of online restaurant reviews on TripAdvisor. A total of 8,871 English-written reviews from 87 restaurants located in Europe were extracted using a web crawler developed by Beautiful Soup, and data were then processed using Semantria.

The study findings revealed that overall sentiments decreased after restaurants were awarded a Michelin Star, in which service sentiment was the most affected aspect, followed by food and ambience. Yet, price sentiment showed a prominent increase. This provides valuable insights for Michelin-starred restaurant operators and owners to create a unique and compelling gastronomic experience that triggers positive online reviews.

The results of this study argue that consumers tend to hold higher expectations for this type of upscale restaurants given its recognition and quality assurance, so they are more likely to have negative feelings when their expectations are disconfirmed. Therefore, restaurants should continuously improve their food and service while paying attention to small details such as ambience, through creativity and innovation. Also, high-end restaurants, especially Michelin-starred restaurants, usually have the edge in premium pricing, yet competitive pricing may backfire considering its perceived luxurious values.

This study analyzed changes in customer sentiments when a restaurant is awarded a Michelin Star through text analytics. Through the lens of online restaurant reviews, the study findings contribute to identifying aspects that are most or least affected by the award of a Michelin Star as well as highlight the role of ambience in customer satisfaction which might have been overlooked in previous studies.

隨著社交媒體日趨普及，消費者出現一種常見的做法，就是在網上書寫評論，分享他們的意見和體驗，他們也會參考其他消費者的評論，以在購物時能作出知情決定。本研究擬探討當餐館獲得米其林星級時，消費者對它們在四個主要方面 (即食物、服務、情調和價格) 的網上評價會如何改變。我們藉此能更容易了解、餐館獲得米其林星級會如何影響其網上評論，以及是哪些因素、會為這些餐館帶來正面的網上評價。

我們對貓途鷹平台上的網上餐館評論進行情感分析。透過BeautifulSoup 研發的網絡爬蟲，我們取出位於歐洲87間餐館、共8,871個以英文書寫的評論，並把這些數據以Semantria加以處理。

研究結果顯示、當餐館獲得米其林星級時，顧客的整體情緒會下降，而其中最受影響的是服務情懷，其次是食物和情調; 但價格情緒卻有明顯的上升。這研究結果給獲得米其林星級餐館的經營者及其東主提供寶貴的啟示，讓他們了解如何為顧客創造一個可帶來正面網上評價的獨特而難忘的美食體驗。

本研究透過文本挖掘、去分析當餐館獲得米其林星級時，顧客情緒會如何改變; 透過網上餐館評論這面透視鏡子，本研究得到的結果、幫助我們確定米其林星級的聲譽所影響最大和最小的是哪些方面，以及讓我們更深入了解餐館的情調在顧客滿意程度上所扮演的角色，而這個角色在過去的研究中似被忽視。

本研究的結果提供了論據、證明由於消費者對擁有相關的認可和品質保證的這類高檔餐館一般予以較高的期望，故當他們發現期望與現實不符時，他們更容易產生負面的情緒; 因此，餐館在關注如情調方面的細節的同時，也應透過創造力和新觀念、去不斷改善他們提供的食物素質和服務水平; 而且，高檔餐館，尤其是獲得米其林星級的餐館，通常在溢價定價方面享有優勢，但當考慮到感知的奢華價值時，具競爭力的價格或會為餐館帶來反效果。