The impact of asking intention or self-prediction questions on subsequent behavior: a meta-analysis

The current meta-analysis estimated the magnitude of the impact of asking intention and self-prediction questions on rates of subsequent behavior, and examined mediators and moderators of this question–behavior effect (QBE). Random-effects meta-analysis on 116 published tests of the effect indicated that intention/prediction questions have a small positive effect on behavior (d+ = 0.24). Little support was observed for attitude accessibility, cognitive dissonance, behavioral simulation, or processing fluency explanations of the QBE. Multivariate analyses indicated significant effects of social desirability of behavior/behavior domain (larger effects for more desirable and less risky behaviors), difficulty of behavior (larger effects for easy-to-perform behaviors), and sample type (larger effects among student samples). Although this review controls for co-occurrence of moderators in multivariate analyses, future primary research should systematically vary moderators in fully factorial designs. Further primary research is also needed to unravel the mechanisms underlying different variants of the QBE

Genre analysis of the literature review section in hospitality and management research articles

Writing an effective literature review is not an easy task for novice writers of research articles, who are oftentimes unaware of the exact functions and purpose of this section; they are often unsuccessful in establishing the necessary connection between what has already been reviewed and the proposed research. This paper discusses the rhetorical patterns of the literature review (LR) section of Hospitality and Management (HM) research articles (RAs) from the perspective of genre analysis using the move structures as posited by Swales (2004). Twenty literature reviews from research articles in the Hospitality and Management discipline were analyzed to determine the move structure of the LR section. A moves analysis was carried out to identify the main moves and steps in the LR section. The analysis indicates that the LR sections display cyclical move patterns that show the presence of the 3 moves and their respective steps as postulated in Swales (2004) revised CARS model, but with some variations. The findings show that the LR section has Move 1 as an obligatory step and that HM RA writers favour making general statements about current situations as a beginning strategy. The findings further show that Move 2 Step 1B, ‘Adding to what is known’, is prevalent in the LR section because the writers will go on to contribute to the existing field of research by adding other research findings that are deemed necessary. Another outcome is that only Move 3-Step 1 is prevalent while the other 6 steps are either not found at all or are present in only a few of the samples

Innovation attributes and managers' decisions about the adoption of innovations in organizations: A meta-analytical review

The adop­tion of in­no­va­tions has emerged as a dom­i­nant re­search topic in the man­age­ment of in­no­va­tion in or­ga­ni­za­tions, al­though in­ves­ti­ga­tions of­ten yield mixed re­sults. To help man­agers and re­searchers im­prove their ef­fec­tive­ness, the au­thors em­ployed a meta-analy­sis in­te­grated with struc­tural equa­tion mod­el­ing to an­a­lyze the as­so­ci­a­tions be­tween the at­trib­utes of in­no­va­tions, man­agers' be­hav­ioral pref­er­ences, and or­ga­ni­za­tions' in­no­va­tion adop­tion de­ci­sions in a me­di­ated-mod­er­ated frame­work. Our find­ings of­fer ev­i­dence that at­trib­utes of in­no­va­tions in­flu­ence man­agers' be­hav­ioral pref­er­ences and, con­se­quently, adop­tion de­ci­sions in or­ga­ni­za­tions. We also ob­serve the sig­nif­i­cance of the con­text in which the adop­tion de­ci­sion oc­curs as well as the re­search set­tings em­ployed by schol­ars. Fi­nally, we dis­cuss the the­o­ret­i­cal con­tri­bu­tion and prac­ti­cal im­pli­ca­tions of our meta-an­a­lyt­i­cal re­sults

Essays on the Influence of Review and Reviewer Attributes on Online Review Helpfulness: Attribution Theory Perspective

With the emergence of digital technology and the increasing availability of information on the internet, customers rely heavily on online reviews to inform their purchasing decisions. However, not all online reviews are helpful, and the factors that contribute to their helpfulness are complex and multifaceted. This dissertation addresses this gap in the literature by examining the antecedents that determine online review helpfulness using attribution theory. The dissertation consists of three essays. The first essay examines the impact of authenticity (review attribute) on review helpfulness, showing that the expressive authenticity of a review enhances its helpfulness. The second essay investigates the relationship between the reviewer attributes i.e., motivation, activity, and goals in online reviews. The study employs various machine learning techniques to investigate the influence of these factors on reviewers\u27 goal attainment. The third essay explores how the reviewer attributes are related to the helpfulness of online reviews. The dissertation offers significant theoretical and practical implications. Theoretically, the dissertation provides new insights into novel review and reviewer attributes. The study proposes a taxonomy of online reviews using means-ends fusion theory offering a framework for understanding the relationships between different components of online reviewer attributes and their contribution to the attainment of specific goals, such as emotional satisfaction. The study also highlights the importance of understanding the motivations and activities of online reviewers in predicting emotional satisfaction and the conditional effects of complaining behavior on emotional satisfaction. The findings inform review platform owners, business owners, reviewers, and prospective consumers in decision-making through helpful reviews. To review platform owners, the findings help segregate helpful reviews from the humongous number of reviews by determining the authenticity of the review. To business owners, the findings can help in understanding consumer behavior and taking necessary actions to provide better service to their customers. To reviewers, this dissertation can act as a guideline to write helpful reviews and to determine their helpfulness. Finally, to consumers or review readers, this dissertation provides an understanding of helpful reviews, thus allowing them to take product or service purchase decisions

IDENTIFYING A CUSTOMER CENTERED APPROACH FOR URBAN PLANNING: DEFINING A FRAMEWORK AND EVALUATING POTENTIAL IN A LIVABILITY CONTEXT

In transportation planning, public engagement is an essential requirement forinformed decision-making. This is especially true for assessing abstract concepts such aslivability, where it is challenging to define objective measures and to obtain input that canbe used to gauge performance of communities. This dissertation focuses on advancing adata-driven decision-making approach for the transportation planning domain in thecontext of livability. First, a conceptual model for a customer-centric framework fortransportation planning is designed integrating insight from multiple disciplines (chapter1), then a data-mining approach to extracting features important for defining customersatisfaction in a livability context is described (chapter 2), and finally an appraisal of thepotential of social media review mining for enhancing understanding of livability measuresand increasing engagement in the planning process is undertaken (chapter 3). The resultsof this work also include a sentiment analysis and visualization package for interpreting anautomated user-defined translation of qualitative measures of livability. The packageevaluates users satisfaction of neighborhoods through social media and enhances thetraditional approaches to defining livability planning measures. This approach has thepotential to capitalize on residents interests in social media outlets and to increase publicengagement in the planning process by encouraging users to participate in onlineneighborhood satisfaction reporting. The results inform future work for deploying acomprehensive approach to planning that draws the marketing structure of transportationnetwork products with residential nodes as the center of the structure

Exploring Natural Language Processing and Sentence Embeddings for Sentiment Analysis of Online Restaurant Reviews

This paper explores the application of Natural Language Processing (NLP) methods in sentiment analysis of restaurant reviews available online, for a sample of restaurants in the Algarve region. The primary objective was to develop an automated method that could efficiently extract and categorize relevant sentiments relating to five key attributes of customer satisfaction, namely food quality, service, ambient, price and restaurant’s location. Using the F1 Score the proposed method was compared against human classification benchmarks. The results showed that Universal Sentence Encoding (USE) was a suitable method for implementation due to its acceptable F1 score performance, ease of accessibility and reduced cost. The use of semantic embeddings can provide valuable insights from online reviews that could benefit the restaurant management and in general the data-driven decision-making processes businesses in the gastronomic sector

The impact of digital therapeutics on the pharmaceutical industry in the treatment of mental health disorders

Digital alternatives to traditional treatment methods for mental health disorders are increasing. These digital therapeutics pose a threat to the traditional pharmaceutical company, having the ability to potentially replace some medications in the treatment. While the digital therapeutics sector is growing, the economic implications of the technology for pharmaceutical companies is rarely discussed in academic literature. This dissertation aims to close the knowledge gap by providing ex-ante predictions of the disruption potential of digital therapeutics in the treatment of mental health disorders. A mixed research approach consisting of both expert interviews and a survey was used to collect market insights from both digital therapeutic and pharmaceutical industries. In combination with knowledge gathered from current literature, predictions about the disruption potential of digital therapeutics in the mental health care market were made. The findings indicated a high disruption potential for digital therapeutics within the mental health care market. A complete displacement of pharmaceuticals is unlikely. For future research, additional medical specialties or competitive capabilities of pharmaceutical companies can be examined as the market environment constantly changes.As alternativas digitais aos métodos tradicionais de tratamento das perturbações da saúde mental estão a aumentar. Estas terapêuticas digitais representam uma ameaça para a empresa farmacêutica tradicional, tendo a capacidade de potencialmente substituir alguns medicamentos no tratamento. Enquanto o sector da terapêutica digital está a crescer, o tema é raramente discutido na literatura académica sobre as implicações económicas da tecnologia para as empresas farmacêuticas. Esta dissertação visa colmatar a lacuna de conhecimentos, fornecendo previsões ex-ante do potencial de perturbação da terapêutica digital no tratamento de distúrbios da saúde mental. Foi utilizada uma abordagem de investigação mista que consiste em entrevistas a peritos e num inquérito para recolher conhecimentos de mercado tanto da indústria terapêutica digital como da indústria farmacêutica. Em combinação com o conhecimento recolhido da literatura actual, foram feitas previsões sobre o potencial de perturbação da terapêutica digital no mercado dos cuidados de saúde mental. Os resultados indicaram um elevado potencial de perturbação da terapêutica digital no mercado dos cuidados de saúde mental. É improvável uma deslocação completa dos produtos farmacêuticos. Para investigações futuras, especialidades médicas adicionais ou capacidades competitivas das empresas farmacêuticas podem ser examinadas à medida que o ambiente do mercado muda constantemente