How Korean universities portray themselves in the global marketplace: text-mining analysis of university president's messages

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Soo Jeung Lee ◽  
Soowon Park
Keyword(s):  
Text Mining ◽  
Text Analysis ◽  
Design Methodology ◽  
Global Marketplace ◽  
Content Type ◽  
University Websites ◽  
Education Environment ◽  
Word Clouds ◽  
Extract Information ◽  
Korean Universities

PurposeThis study aims to examine university president's messages (PMs) on Korean university websites to analyze how Korean universities present their image and position themselves in the global marketplace.Design/methodology/approachAssuming that visions, missions and strategies might vary depending on the characteristics of a university, the study analyzed PMs according to university type: research, teaching and technology. The authors applied text analysis to 105 Korean universities' PMs to understand the images they project. The authors also used text mining on the PMs to examine the frequencies of keywords, to create word clouds, to investigate the keywords' degrees of centrality and to conduct sentiment analysis.FindingsThe findings show that Korean universities' PMs project hybrid images, simultaneously portraying the universities as public institutes that produce public goods and as globally competitive strategic actors. In addition, while Korean university PMs explicitly position the universities as education-oriented, they nonetheless reveal that the universities pursue both research-oriented and education-oriented goals.Originality/valueThis is the study to examine PMs using text mining with Python to extract information and reveal hidden meanings regarding how universities portray themselves on their websites. Highlighting current challenges faced by universities, this article argues for continued discussion on their societal roles and their strategies for positioning themselves in today's globalized and marketized higher education environment.

When feminism meets social networks

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Gila Prebor
Keyword(s):  
Text Mining ◽  
Violence Against Women ◽  
Text Analysis ◽  
High Frequency ◽  
Research Method ◽  
Design Methodology ◽  
Research Question ◽  
Analysis Tool ◽  
Content Type ◽  
Shed Light

PurposeThe purpose of this study is to examine how different feminist Facebook groups in Israel operate in order to better understand the main issues in their discussions about feminism in Israel. The study will also identify the variances between the different subgroups. A secondary research question examined was whether Voyant Tools can be used as an effective content text analysis tool in general and in Hebrew in particular.Design/methodology/approachThe study's research method analyzes the content of Facebook posts using the Voyant Tools online toolkit to quantitatively analyze and visualize the results of text mining and data visualization. The sample consists of the texts of posts of three groups representing different currents in Israeli feminism, gathered over a period of three months.FindingsThe results show that there are high-frequency words occurring in all groups, each group has its unique words, which distinguish it from the other groups. Feminist and Halachic Feminist groups had few words in common, while the Religious Feminist groups had more words in common with both the Feminist and the Halachic Feminist groups and more so with the latter group. While all groups discussed the issue of violence against women, especially sexual violence, the degree of engagement varied greatly between the groups. In addition, there were clear differences in the prominent issues concerning the various groups. This paper demonstrates the possibility of using Voyant Tools for text mining and analysis.Originality/valueThis paper demonstrates the possibility of using Voyant Tools for text mining and analysis. Voyant Tools shed light on common concepts, their location and prevalence in the text.

Blockchain as supply chain technology: considering transparency and security

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Pei Xu ◽  
Joonghee Lee ◽  
James R. Barth ◽  
Robert Glenn Richey
Keyword(s):  
Supply Chain ◽  
Text Mining ◽  
Information Security ◽  
Design Methodology ◽  
Use Cases ◽  
Future Research ◽  
Content Type ◽  
Blockchain Technology ◽  
Twitter Data ◽  
The Way

PurposeThis paper discusses how the features of blockchain technology impact supply chain transparency through the lens of the information security triad (confidentiality, integrity and availability). Ultimately, propositions are developed to encourage future research in supply chain applications of blockchain technology.Design/methodology/approachPropositions are developed based on a synthesis of the information security and supply chain transparency literature. Findings from text mining of Twitter data and a discussion of three major blockchain use cases support the development of the propositions.FindingsThe authors note that confidentiality limits supply chain transparency, which causes tension between transparency and security. Integrity and availability promote supply chain transparency. Blockchain features can preserve security and increase transparency at the same time, despite the tension between confidentiality and transparency.Research limitations/implicationsThe research was conducted at a time when most blockchain applications were still in pilot stages. The propositions developed should therefore be revisited as blockchain applications become more widely adopted and mature.Originality/valueThis study is among the first to examine the way blockchain technology eases the tension between supply chain transparency and security. Unlike other studies that have suggested only positive impacts of blockchain technology on transparency, this study demonstrates that blockchain features can influence transparency both positively and negatively.

The language of profit warnings: a case of denial, defiance, desperation and defeat

2021 ◽  
Vol 35 (9) ◽  
pp. 28-56
Author(s):  
Victoria C. Edgar ◽  
Niamh M. Brennan ◽  
Sean Bradley Power
Keyword(s):  
Text Analysis ◽  
Design Methodology ◽  
Corporate Communication ◽  
Bad News ◽  
Board Meeting ◽  
Conference Calls ◽  
Content Type ◽  
Three Stages ◽  
Delivering Bad News

PurposeTaking a communication perspective, the paper explores management's rhetoric in profit warnings, whose sole purpose is to disclose unexpected bad news.Design/methodology/approachAdopting a close-reading approach to text analysis, the authors analyse three profit warnings of the now-collapsed Carillion, contrasting the rhetoric with contemporaneous investor conference calls to discuss the profit warnings and board minutes recording boardroom discussions of the case company's precarious financial circumstances. The analysis applies an Aristotelian framework, focussing on logos (appealing to logic and reason), ethos (appealing to authority) and pathos (appealing to emotion) to examine how Carillion's board and management used language to persuade shareholders concerning the company's adverse circumstances.FindingsAs non-routine communications, the language in profit warnings displays and mimics characteristics of routine communications by appealing primarily to logos (logic and reason). The rhetorical profiles of investor conference calls and board meeting minutes differ from profit warnings, suggesting a different version of the story behind the scenes. The authors frame the three profit warnings as representing three stages of communication as follows: denial, defiance and desperation and, for our case company, ultimately, culminating in defeat.Research limitations/implicationsThe research is limited to the study of profit warnings in one case company.Originality/valueThe paper views profit warnings as a communication artefact and examines the rhetoric in these corporate documents to elucidate their key features. The paper provides novel insights into the role of profit warnings as a corporate communication vehicle/genre delivering bad news.

scholarly journals Text mining analysis roadmap (TMAR) for service research

2020 ◽  
Vol 34 (1) ◽  
pp. 30-47 ◽  
Author(s):  
Mohamed Zaki ◽  
Janet R. McColl-Kennedy
Keyword(s):  
Machine Learning ◽  
Text Mining ◽  
Design Methodology ◽  
Data Sources ◽  
Theory Testing ◽  
Service Research ◽  
Data Types ◽  
Content Type ◽  
Research And Practice ◽  
Mining Methods

Purpose The purpose of this paper is to offer a step-by-step text mining analysis roadmap (TMAR) for service researchers. The paper provides guidance on how to choose between alternative tools, using illustrative examples from a range of business contexts. Design/methodology/approach The authors provide a six-stage TMAR on how to use text mining methods in practice. At each stage, the authors provide a guiding question, articulate the aim, identify a range of methods and demonstrate how machine learning and linguistic techniques can be used in practice with illustrative examples drawn from business, from an array of data types, services and contexts. Findings At each of the six stages, this paper demonstrates useful insights that result from the text mining techniques to provide an in-depth understanding of the phenomenon and actionable insights for research and practice. Originality/value There is little research to guide scholars and practitioners on how to gain insights from the extensive “big data” that arises from the different data sources. In a first, this paper addresses this important gap highlighting the advantages of using text mining to gain useful insights for theory testing and practice in different service contexts.

Automatic recommendation of prognosis measures for mechanical components based on massive text mining

2018 ◽  
Vol 14 (4) ◽  
pp. 480-494 ◽  
Author(s):  
Jorge Martinez-Gil ◽  
Bernhard Freudenthaler ◽  
Thomas Natschläger
Keyword(s):  
Fault Diagnosis ◽  
Text Mining ◽  
Design Methodology ◽  
Content Type ◽  
The Past ◽  
Mechanical Component ◽  
The World ◽  
Fault Prognosis ◽  
Mechanical Components ◽  
Unstructured Information

Purpose The purpose of this study is to automatically provide suggestions for predicting the likely status of a mechanical component is a key challenge in a wide variety of industrial domains. Design/methodology/approach Existing solutions based on ontological models have proven to be appropriate for fault diagnosis, but they fail when suggesting activities leading to a successful prognosis of mechanical components. The major reason is that fault prognosis is an activity that, unlike fault diagnosis, involves a lot of uncertainty and it is not always possible to envision a model for predicting possible faults. Findings This work proposes a solution based on massive text mining for automatically suggesting prognosis activities concerning mechanical components. Originality/value The great advantage of text mining is that makes possible to automatically analyze vast amounts of unstructured information to find corrective strategies that have been successfully exploited, and formally or informally documented, in the past in any part of the world.

Identifying the perspectives for sustainability enhancement

2016 ◽  
Vol 13 (3) ◽  
pp. 244-270 ◽  
Author(s):  
Neeraj Bhanot ◽  
P. Venkateswara Rao ◽  
S.G. Deshmukh
Keyword(s):  
Text Mining ◽  
Clustering Algorithm ◽  
Business Processes ◽  
Manufacturing Sector ◽  
Principal Component ◽  
Machining Process ◽  
Machining Processes ◽  
Content Type ◽  
Word Clouds ◽  
Industry Professionals

Purpose Integrating sustainability strategies with business processes is the most challenging task for industry professionals due to the lack of a proper understanding of sustainability concepts. At the same time, a lack of proper guidance restricts them from pursuing such activities. As far as the aspects of implementation are concerned, it is very tough to analyse and pick up key points to start with. The purpose of this paper is to utilize a text mining approach to analyse qualitative data and identify the critical issues for implementing sustainability in the manufacturing sector by focussing on turning processes based on the survey responses of researchers and industry professionals. Design/methodology/approach An integrated method employing principal component analysis (PCA) and the k-means clustering algorithm has been applied to extract useful information from a set of various suggestions provided by both the groups surveyed. The textual data has also been visualized using word clouds and, thus, it has been compared with the results of the text mining approach. Findings The results of the study indicate the importance of the role of government organizations and the need for a skilled workforce, which are crucial for enhancing aspects of sustainability in the manufacturing sector, as supported by both researchers and industry professionals. Besides this, researchers have highlighted the need to focus more on environmentally related issues, whereas industry professionals have raised performance-related issues. Practical implications The findings of the study present the important concerns of both the groups towards sustainability initiatives and, thus, will help to enhance the understanding of the underlying possibilities of negotiating jointly to enhance the performance of machining processes. Originality/value The novelty of this paper lies in its identification of important initiatives that are having a direct impact on the sustainable aspects of the machining process, based on the views of researchers and industry professionals.

Research trends in quality management in years 2000-2019

2020 ◽  
Vol 12 (4) ◽  
pp. 417-433 ◽  
Author(s):  
Sławomir Wawak ◽  
Piotr Rogala ◽  
Su Mi Dahlgaard-Park
Keyword(s):  
Quality Management ◽  
Text Mining ◽  
Design Methodology ◽  
Reliable Data ◽  
Classification Criteria ◽  
Content Type ◽  
Emerging Trends ◽  
Novel Approach ◽  
Computer Aided Analysis ◽  
Practical Implications

Purpose This study aims to demonstrate the suitability of text-mining toolset for the discovery of trends in quality management (QM) literature in 2000-2019. The hypothesis was formulated that as the field of study is mature, the most important trends are related to deepening and broadening of the knowledge. Design/methodology/approach A novel approach to trend discovery was proposed. The computer-aided analysis of full-texts of papers led to increased reliability and level of detail of the achieved results and helped significantly reduce researchers’ bias. Overall, 4,833 papers from 8 journal dedicated to QM were analysed. Findings Trends discovery led to the identification of 45 trends: 17 long-lasting trends, 4 declining trends, 11 emerging trends and 13 ephemeris trends. They were compared to the results of earlier studies. New trends and potential gaps were discussed. Practical implications The results highlight the trends that gain or lose popularity, thus they can be used to focus studies, as well as find new subjects, which are not so popular yet. The knowledge about emerging trends is also important for those quality managers who strive for improvement of their efficiency. Originality/value The research was designed to bypass the limitations of previous studies. The use of text mining methods and analysis of full texts of papers delivered more detailed and reliable data. Resignation from predefinition of classification criteria significantly reduced researchers’ bias and allowed the discovery of new trends, not identified in previous studies.

Estimating numerical scale ratings from text-based service reviews

2020 ◽  
Vol 31 (2) ◽  
pp. 187-202
Author(s):  
Hsiu-Yuan Tsao ◽  
Ming-Yi Chen ◽  
Colin Campbell ◽  
Sean Sands
Keyword(s):  
Language Processing ◽  
Text Analysis ◽  
Design Methodology ◽  
Survey Methods ◽  
Content Type ◽  
Consumer Review ◽  
Numerical Scale ◽  
Analysis Technique ◽  
Textual Data ◽  
Practical Implications

PurposeThis paper develops a generalizable, machine-learning-based method for measuring established marketing constructs using passive analysis of consumer-generated textual data from service reviews. The method is demonstrated using topic and sentiment analysis along dimensions of an existing scale: lodging quality index (LQI).Design/methodology/approachThe method induces numerical scale ratings from text-based data such as consumer reviews. This is accomplished by automatically developing a dictionary from words within a set of existing scale items, rather a more manual process. This dictionary is used to analyze textual consumer review data, inducing topic and sentiment along various dimensions. Data produced is equivalent with Likert scores.FindingsPaired t-tests reveal that the text analysis technique the authors develop produces data that is equivalent to Likert data from the same individual. Results from the authors’ second study apply the method to real-world consumer hotel reviews.Practical implicationsResults demonstrate a novel means of using natural language processing in a way to complement or replace traditional survey methods. The approach the authors outline unlocks the ability to rapidly and efficiently analyze text in terms of any existing scale without the need to first manually develop a dictionary.Originality/valueThe technique makes a methodological contribution by outlining a new means of generating scale-equivalent data from text alone. The method has the potential to both unlock entirely new sources of data and potentially change how service satisfaction is assessed and opens the door for analysis of text in terms of a wider range of constructs.

Evolution of project management studies in the XXI century

2020 ◽  
Vol 13 (4) ◽  
pp. 867-888
Author(s):  
Sławomir Wawak ◽  
Krzysztof Woźniak
Keyword(s):  
Project Management ◽  
Text Mining ◽  
Design Methodology ◽  
Project Managers ◽  
Time Span ◽  
Content Type ◽  
Current Trends ◽  
Scientific Papers ◽  
Expert Analysis ◽  
Number Of Publications

PurposeThe objectives of the study were to demonstrate the suitability of methodology based on a text mining toolset for detecting trends in scientific papers and to find trends that were present in the field of project management during the research time span (2000–2019).Design/methodology/approachAn approach based on text mining tools supported by expert analysis was adopted due to an extensive number of publications in the field of project management. The novelty of the approach lies in the proposed method of trends discovery instead of the commonly used trends predefinition. The use of computer support allowed the full texts of papers, and not only abstracts, to be analysed, which significantly increased the reliability of the achieved results. Overall, 3,544 papers from seven journals were analysed.FindingsAs a result, 43 trends were discovered including seven long-lasting, four declining, 17 emerging and 15 ephemeris trends. Trends were analysed in comparison with the results of previous studies and project management frameworks. New trends and potential gaps were discussed.Originality/valueThe results highlight the topics of research that gain popularity among researchers, and which are related to the current problems that arise in project management. Therefore, the results can help focus studies on the most important areas, as well as find new ones which are not so popular yet. The knowledge of current trends is also important for those project managers who seek to improve the efficiency of their work.

scholarly journals What national governance codes say about corporate culture

2020 ◽  
Vol 20 (5) ◽  
pp. 903-917
Author(s):  
Marie-Fleur Lobrij ◽  
Muel Kaptein ◽  
Mijntje Lückerath-Rovers
Keyword(s):  
Corporate Governance ◽  
Corporate Culture ◽  
Text Analysis ◽  
Design Methodology ◽  
Three Dimensions ◽  
Analysis Program ◽  
Content Type ◽  
Corporate Governance Codes ◽  
Computer Aided ◽  
Insight Into

Purpose This study aims to provide insight into the current incorporation of corporate culture in national corporate governance codes. The authors identify three levels of incorporation for each of the following three dimensions: layers of corporate culture (the “what”), the alignment of corporate culture in the organization (the “for whom”) and the board’s roles regarding corporate culture (the “how”). Design/methodology/approach To assess the extent to which national codes have incorporated corporate culture, the authors used a sample of 88 national corporate governance codes. The authors performed a content analysis of these codes using a computer-aided text analysis program. The first step involved the identification of dimensions of corporate culture per national code. These dimensions were then assessed based on three levels of incorporation. Finally, the authors ranked national codes with similar levels of incorporation per dimension and aggregated the dimensions. Findings The data show that five of the 88 national corporate governance codes that the authors analysed scored the highest level in all three dimensions of corporate culture. Originality/value This is the first study to provide an overview of what national corporate governance codes say about corporate culture. The authors address two gaps in the existing literature. First, the authors develop and use a richer conceptualization of how corporate culture can be addressed in national corporate governance codes. Second, the authors analyse these corporate governance codes worldwide.

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