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1 – 10 of 888Salam Abdallah and Ashraf Khalil
This study aims to understand and a lay a foundation of how analytics has been used in depression management, this study conducts a systematic literature review using two…
Abstract
Purpose
This study aims to understand and a lay a foundation of how analytics has been used in depression management, this study conducts a systematic literature review using two techniques – text mining and manual review. The proposed methodology would aid researchers in identifying key concepts and research gaps, which in turn, will help them to establish the theoretical background supporting their empirical research objective.
Design/methodology/approach
This paper explores a hybrid methodology for literature review (HMLR), using text mining prior to systematic manual review.
Findings
The proposed rapid methodology is an effective tool to automate and speed up the process required to identify key and emerging concepts and research gaps in any specific research domain while conducting a systematic literature review. It assists in populating a research knowledge graph that does not reach all semantic depths of the examined domain yet provides some science-specific structure.
Originality/value
This study presents a new methodology for conducting a literature review for empirical research articles. This study has explored an “HMLR” that combines text mining and manual systematic literature review. Depending on the purpose of the research, these two techniques can be used in tandem to undertake a comprehensive literature review, by combining pieces of complex textual data together and revealing areas where research might be lacking.
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This study aims to focus on automated text analyses (ATAs) of sustainability and integrated reporting as a recent approach in empirical–quantitative research.
Abstract
Purpose
This study aims to focus on automated text analyses (ATAs) of sustainability and integrated reporting as a recent approach in empirical–quantitative research.
Design/methodology/approach
Based on legitimacy theory, the author conducts a structured literature review and includes 38 quantitative peer-reviewed empirical (archival) studies on specific determinants and consequences of sustainability and integrated reporting. The paper makes a clear distinction between analyses of reports due to readability, tone, similarity and specific topics. In line with prior studies, it is assumed that more readable reports with less tone and similarity relate to increased reporting quality.
Findings
In line with legitimacy theory, there are empirical indications that specific corporate governance variables, other firm characteristics and regulatory issues have a main impact on the quality of sustainability and integrated reporting. Furthermore, increased reporting quality leads to positive market reactions in line with the business case argument.
Research limitations/implications
The author deduces useful recommendations for future research to motivate researchers to include ATA of sustainability and integrated reports. Among others, future research should recognize sustainable and behavioral corporate governance determinants and analyze other stakeholders’ reactions.
Practical implications
As both stakeholders’ demands on sustainability and integrated reporting have increased since the financial crisis of 2008–2009, firms should increase the quality of reporting processes.
Originality/value
This analysis makes major contributions to prior research by including both sustainability and integrated reporting, based on ATA. ATAs play a prominent role in recent empirical research to evaluate possible drivers and consequences of sustainability and integrated reports. ATA may contribute to increased validity of empirical–quantitative research in comparison to classical manual content analyses, especially due to future CSR washing analyses.
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Araceli Galiano-Coronil, Alexander Aguirre Montero, Jose Antonio López Sánchez and Rosario Díaz Ortega
This work aims to examine the communication on Twitter of the most responsible companies in Spain to identify the topics covered on corporate social responsibility (CSR) from the…
Abstract
Purpose
This work aims to examine the communication on Twitter of the most responsible companies in Spain to identify the topics covered on corporate social responsibility (CSR) from the perspective of happiness and social marketing. In addition, the profiles of the messages that show an association with the impact of the messages have been identified.
Design/methodology/approach
An empirical analysis of the Twitter posts of Spain's ten most responsible companies has been carried out. The methodology of this work combines data mining techniques, sentiment analysis and content analysis, both from a quantitative and qualitative approach.
Findings
The results show that most brand tweets do not deal with CSR-related topics. The topics they address the most are those related to sports and the weather. From the perspective of social marketing, conversational-type tweets are the most published and have achieved the most significant reaction from the public. In addition, four messages' profiles have been identified based on the company and the emotional connotation associated with the impact, giving rise to more outstanding promotion of social causes.
Originality/value
Our main contribution to this work has been to value positive communication and social marketing to promote better CSR on Twitter. In this sense, it has been verified that there is a relationship between the public's reaction, the affective connotation and the company that issues the messages.
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S.E. Galaitsi, Krista Rand, Elissa Yeates, Cary Talbot, Arleen O'Donnell, Elizaveta Pinigina and Igor Linkov
Water is a critical and contentious resource in California, hence any changes in reservoir management requires coordination among many basin stakeholders. The Forecast-Informed…
Abstract
Purpose
Water is a critical and contentious resource in California, hence any changes in reservoir management requires coordination among many basin stakeholders. The Forecast-Informed Reservoir Operations (FIRO) pilot project at Lake Mendocino, California explored the viability of using weather forecasts to alter the operations of a United States Army Corps of Engineers (USACE) reservoir. The pilot project demonstrated FIRO's ability to improve water supply reliability, but also revealed the key role of a collaborative Steering Committee. Because Lake Mendocino's Viability Assessment did not explore the features of the Steering Committee, this study aims to examine the relationships and interactions between Steering Committee members that supported FIRO's implementation at Lake Mendocino.
Design/methodology/approach
The project identified 17 key project participants who spoke at a FIRO workshop or emerged through chain-referrals. Using semi-structured interviews with these participants, the project examined the dynamics of human interactions that enabled the successful multi-institutional and multi-criteria innovation as analyzed through text-coding.
Findings
The results reveal the importance for FIRO Steering Committee members to understand the limitations and constraints of stakeholder counterparts at other organizations, the importance of building and safeguarding relationships, and the role of trust and belonging between members. The lessons learned suggest several interventions to support successful group collaboration dynamics for future FIRO projects.
Originality/value
This study identifies features of the Steering Committee that contributed to FIRO's success by supporting collaborative negotiations of infrastructure operations within a multi-institutional and multi-criteria context.
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Aliakbar Marandi, Misagh Tasavori and Manoochehr Najmi
This study aims to use big data analysis and sheds light on key hotel features that play a role in the revisit intention of customers. In addition, this study endeavors to…
Abstract
Purpose
This study aims to use big data analysis and sheds light on key hotel features that play a role in the revisit intention of customers. In addition, this study endeavors to highlight hotel features for different customer segments.
Design/methodology/approach
This study uses a machine learning method and analyzes around 100,000 reviews of customers of 100 selected hotels around the world where they had indicated on Trip Advisor their intention to return to a particular hotel. The important features of the hotels are then extracted in terms of the 7Ps of the marketing mix. This study has then segmented customers intending to revisit hotels, based on the similarities in their reviews.
Findings
In total, 71 important hotel features are extracted using text analysis of comments. The most important features are the room, staff, food and accessibility. Also, customers are segmented into 15 groups, and key hotel features important for each segment are highlighted.
Research limitations/implications
In this research, the number of repetitions of words was used to identify key hotel features, whereas sentence-based analysis or group analysis of adjacent words can be used.
Practical implications
This study highlights key hotel features that are crucial for customers’ revisit intention and identifies related market segments that can support managers in better designing their strategies and allocating their resources.
Originality/value
By using text mining analysis, this study identifies and classifies important hotel features that are crucial for the revisit intention of customers based on the 7Ps. Methodologically, the authors suggest a comprehensive method to describe the revisit intention of hotel customers based on customer reviews.
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Paritosh Pramanik and Rabin K. Jana
This paper aims to discuss the suitability of topic modeling as a review method, identifies and compares the machine learning (ML) research trends in five primary business…
Abstract
Purpose
This paper aims to discuss the suitability of topic modeling as a review method, identifies and compares the machine learning (ML) research trends in five primary business organization verticals.
Design/methodology/approach
This study presents a review framework of published research about adopting ML techniques in a business organization context. It identifies research trends and issues using topic modeling through the Latent Dirichlet allocation technique in conjunction with other text analysis techniques in five primary business verticals – human resources (HR), marketing, operations, strategy and finance.
Findings
The results identify that the ML adoption is maximum in the marketing domain and minimum in the HR domain. The operations domain witnesses the application of ML to the maximum number of distinct research areas. The results also help to identify the potential areas of ML applications in future.
Originality/value
This paper contributes to the existing literature by finding trends of ML applications in the business domain through the review of published research. Although there is a growth of research publications in ML in the business domain, literature review papers are scarce. Therefore, the endeavor of this study is to do a thorough review of the current status of ML applications in business by analyzing research articles published in the past ten years in various journals.
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Ashish S. Galande, Frank Mathmann, Cesar Ariza-Rojas, Benno Torgler and Janina Garbas
Misinformation is notoriously difficult to combat. Although social media firms have focused on combating the publication of misinformation, misinformation accusations, an…
Abstract
Purpose
Misinformation is notoriously difficult to combat. Although social media firms have focused on combating the publication of misinformation, misinformation accusations, an important by-product of the spread of misinformation, have been neglected. The authors offer insights into factors contributing to the spread of misinformation accusations on social media platforms.
Design/methodology/approach
The authors use a corpus of 234,556 tweets about the 2020 US presidential election (Study 1) and 99,032 tweets about the 2022 US midterm elections (Study 2) to show how the sharing of misinformation accusations is explained by locomotion orientation.
Findings
The study findings indicate that the sharing of misinformation accusations is explained by writers' lower locomotion orientation, which is amplified among liberal tweet writers.
Research limitations/implications
Practitioners and policymakers can use the study findings to track and reduce the spread of misinformation accusations by developing algorithms to analyze the language of posts. A limitation of this research is that it focuses on political misinformation accusations. Future research in different contexts, such as vaccines, would be pertinent.
Practical implications
The authors show how social media firms can identify messages containing misinformation accusations with the potential to become viral by considering the tweet writer's locomotion language and geographical data.
Social implications
Early identification of messages containing misinformation accusations can help to improve the quality of the political conversation and electoral decision-making.
Originality/value
Strategies used by social media platforms to identify misinformation lack scale and perform poorly, making it important for social media platforms to manage misinformation accusations in an effort to retain trust. The authors identify linguistic and geographical factors that drive misinformation accusation retweets.
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Ernesto Cardamone, Gaetano Miceli and Maria Antonietta Raimondo
This paper investigates how two characteristics of language, abstractness vs concreteness and narrativity, influence user engagement in communication exercises on innovation…
Abstract
Purpose
This paper investigates how two characteristics of language, abstractness vs concreteness and narrativity, influence user engagement in communication exercises on innovation targeted to the general audience. The proposed conceptual model suggests that innovation fits well with more abstract language because of the association of innovation with imagination and distal construal. Moreover, communication of innovation may benefit from greater adherence to the narrativity arc, that is, early staging, increasing plot progression and climax optimal point. These effects are moderated by content variety and emotional tone, respectively.
Design/methodology/approach
Based on a Latent Dirichlet allocation (LDA) application on a sample of 3225 TED Talks transcripts, the authors identify 287 TED Talks on innovation, and then applied econometric analyses to test the hypotheses on the effects of abstractness vs concreteness and narrativity on engagement, and on the moderation effects of content variety and emotional tone.
Findings
The authors found that abstractness (vs concreteness) and narrativity have positive effects on engagement. These two effects are stronger with higher content variety and more positive emotional tone, respectively.
Research limitations/implications
This paper extends the literature on communication of innovation, linguistics and text analysis by evaluating the roles of abstractness vs concreteness and narrativity in shaping appreciation of innovation.
Originality/value
This paper reports conceptual and empirical analyses on innovation dissemination through a popular medium – TED Talks – and applies modern text analysis algorithms to test hypotheses on the effects of two pivotal dimensions of language on user engagement.
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Joey Lam, Michael S. Mulvey, Karen Robson and Leyland Pitt
This study aims to help uncover corporate culture and values to attract and retain talent by understanding job reviews written by business-to-business (B2B) salespeople.
Abstract
Purpose
This study aims to help uncover corporate culture and values to attract and retain talent by understanding job reviews written by business-to-business (B2B) salespeople.
Design/methodology/approach
Over 40,000 job reviews on Glassdoor.com are analyzed by a dictionary-based content analysis tool, Linguistic Inquiry and Word Count (LIWC2015), to explore the links between corporate culture and linguistics characteristics of reviews as articulated by B2B salespeople. This study adopted a multidimensional scaling approach based on the nine cultural value scores to create a map of corporate profiles. A projection of the LIWC2015 scores on this map uncovers differences in language patterns and emotions expressed across the profiles.
Findings
Findings reveal a map of corporate profiles with two dimensions, namely, product-centricity and customer-centricity, that divide salesforce subculture into a 2 × 2 matrix of four types: Empathic Innovators, Product Pioneers, Customer Champions and Commodity Traders.
Originality/value
This study combined two data sets, scores on CultureX’s nine cultural values (agility, collaboration, customer orientation, diversity, execution, innovation, integrity, performance and respect) and job reviews on Glassdoor.com. This research seeks to develop profiles of the organizational culture and to use a blend of qualitative and quantitative methods. This study adds to the literature on salesforce subculture and showcases a solution to the methodological difficulty in categorizing and measuring culture.
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Radiah Othman and Rashid Ameer
This paper aims to seek accounting graduates' perspectives on the demand for accounting in their workplaces, on the gaps in accounting education (AE), and on the future of the…
Abstract
Purpose
This paper aims to seek accounting graduates' perspectives on the demand for accounting in their workplaces, on the gaps in accounting education (AE), and on the future of the accounting profession, inspired by the new definition of accounting proposed by Carnegie et al. (2021, 2022, 2023a), to adopt a strong focus on sustainable development goals (SDGs) in AE to inculcate tertiary students with the skills that lead them to approach and apply accounting as a multidimensional technical, social and moral (TSM) practice.
Design/methodology/approach
The online qualitative survey was distributed to 100 randomly selected New Zealand accounting graduates in order to gather insights from their workplaces. All responses from the 30 graduates who completed the questionnaire underwent qualitative analysis using Leximancer software, which automatically identifies high-level concepts and insights and offers interactive visualizations without bias.
Findings
The graduates’ experiences underscore the ongoing significance of technical skills in the New Zealand workplace. They emphasized the lack of non-technical skills training, stressed the necessity of diverse business knowledge and highlighted the importance of automation and digital skills.
Practical implications
The implications for transforming AE involve adopting an activist approach to integrate a TSM perspective into teaching and learning and being open to an interdisciplinary approach to expose tertiary students to the impact of accounting on sustainable development, including collaboration with professional bodies for real-world experiences.
Originality/value
The importance of engaging with SDG-related narratives is stressed to stimulate further discussion, debate and research aimed at identifying practical solutions for AE as a facilitator for SDGs in realizing accounting as a TSM practice.