Although the theme of push and pull motivations has received increasing attention in tourist behavior literature, little attention has been devoted to the investigation of the interaction between single push motivations and visitor loyalty and other relevant variables influencing tourist behavior. Given its undoubtable relevance in motivating human behavior, we propose curiosity as a single push motive by examining its causal relationships with destination attributes (evaluated in holistic way), attitude toward destination, and loyalty. In particular, we tested a new research model on a sample of 273 potential Brazilian travelers to Europe by using a structural equation modeling approach. Sample size is in line with the state-of-the-art in literature (Ciasullo et al., 2017). The data moderately well fitted the “curiosity model” and the findings highlighted that curiosity plays a crucial role in shaping attitude and pull motivation, and in influencing tourist loyalty. Consequently, destination managers or European Union institutions should magnify the role of curiosity, attitude towards destination, and pull motivations in terms of marketing policies.
This article presents a methodology to classify the polarity of words from selected Tweets. Usually, social media sentiment (SMS) is lexically determined, manually or by machine learning. However, these methods are either slow or based on a pre-established dictionary, thus not providing a customised analysis. We propose a methodology that, after having mined the topic-related Tweets, filters relevant words based on the mean and standard deviation frequency in positive and negative market days to remove neutral terms. Subsequently, through an ad hoc perceptual mapping, we assign a polarity to the dataset. This method allows the building of a dictionary associated with the investor sentiment customised to that organisation. A practical application was carried out to test the proposed methodology. The results were significant and in line with the behavioural finance theory, confirming that irrational investor feelings—expressed via social media—drive a portion of asset prices. Results also confirm the investor asymmetric behaviour under gain or loss scenarios, with the latter generating more impact than the former because people are risk-averse. The proposed method is expected to identify patterns of behaviour in social media linked to market oscillations, thereby contributing to risk management and optimising decision-making in the stock market. The use of both statistical and perceptual map filters allows a specific asset dictionary to be built; Textual sentiment analysis based on social media; The proposed method efficiently overcomes generic dictionaries and language issues.
Despite the relevant economic and reputational impact of fraud, research in this field remains fragmented. This study aims to create a new framework for accounting fraud, defining its main components from the social media user’s perspective. In terms of research technique, an online data collection using social media platform was used retrieving, through the phyton web crawler procedure, 43,655 tweets containing the phrase “accounting fraud” from July 2006 to December 2019. Individual words were identified and treated within the selected tweets, excluding stop words and, finally, using a sparsity index. The proposed methodology, which overcomes traditional survey inherent bias efficiently, contributes to bridging the divide between academia and society. We find that Twitter users shape the Accounting Fraud Hexagon, composed by (i) The Object and the Tool (of misrepresentation), being the Financials, (ii) The (Guilty) Fraudster, (iii) The Defrauded, (iv) Materiality, (v) The Consequences, and (vi) the Watchdog. Our research has several implications. Our research identifies additional “angles” of vision to the traditional fraud triangle-diamond-pentagon theories compared with the existing top-down conceptual frameworks. Also, since it uses a bottom-up instead of a top-down approach, the study allows a more comprehensive definition of accounting fraud, thus contributing to the debate for a common language in this field. We expect to encourage more research using social media as a tool to test the literature built on in vitro theories empirically.
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