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Article
Publication date: 13 March 2009

Ranjit Bose

Advanced analytics‐driven data analyses allow enterprises to have a complete or “360 degrees” view of their operations and customers. The insight that they gain from such…

Abstract

Purpose

Advanced analytics‐driven data analyses allow enterprises to have a complete or “360 degrees” view of their operations and customers. The insight that they gain from such analyses is then used to direct, optimize, and automate their decision making to successfully achieve their organizational goals. Data, text, and web mining technologies are some of the key contributors to making advanced analytics possible. This paper aims to investigate these three mining technologies in terms of how they are used and the issues that are related to their effective implementation and management within the broader context of predictive or advanced analytics.

Design/methodology/approach

A range of recently published research literature on business intelligence (BI); predictive analytics; and data, text and web mining is reviewed to explore their current state, issues and challenges learned from their practice.

Findings

The findings are reported in two parts. The first part discusses a framework for BI using the data, text, and web mining technologies for advanced analytics; and the second part identifies and discusses the opportunities and challenges the business managers dealing with these technologies face for gaining competitive advantages for their businesses.

Originality/value

The study findings are intended to assist business managers to effectively understand the issues and emerging technologies behind advanced analytics implementation.

Details

Industrial Management & Data Systems, vol. 109 no. 2
Type: Research Article
ISSN: 0263-5577

Keywords

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Article
Publication date: 4 May 2010

Qingyu Zhang and Richard S. Segall

The purpose of this paper is to review and compare selected software for data mining, text mining (TM), and web mining that are not available as free open‐source software.

Abstract

Purpose

The purpose of this paper is to review and compare selected software for data mining, text mining (TM), and web mining that are not available as free open‐source software.

Design/methodology/approach

Selected softwares are compared with their common and unique features. The software for data mining are SAS® Enterprise Miner™, Megaputer PolyAnalyst® 5.0, NeuralWare Predict®, and BioDiscovery GeneSight®. The software for TM are CompareSuite, SAS® Text Miner, TextAnalyst, VisualText, Megaputer PolyAnalyst® 5.0, and WordStat. The software for web mining are Megaputer PolyAnalyst®, SPSS Clementine®, ClickTracks, and QL2.

Findings

This paper discusses and compares the existing features, characteristics, and algorithms of selected software for data mining, TM, and web mining, respectively. These softwares are also applied to available data sets.

Research limitations/implications

The limitations are the inclusion of selected software and datasets rather than considering the entire realm of these. This review could be used as a framework for comparing other data, text, and web mining software.

Practical implications

This paper can be helpful for an organization or individual when choosing proper software to meet their mining needs.

Originality/value

Each of the software selected for this research has its own unique characteristics, properties, and algorithms. No other paper compares these selected softwares both visually and descriptively for all the three types of data, text, and web mining.

Details

Kybernetes, vol. 39 no. 4
Type: Research Article
ISSN: 0368-492X

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Article
Publication date: 14 May 2018

Saurav Snehvrat, Amit Kumar, Rahul Kumar and Swarup Dutta

The academic discipline of ambidexterity is recognized as an established field within strategic management and organization theory. Extant works in the field recognize the…

Abstract

Purpose

The academic discipline of ambidexterity is recognized as an established field within strategic management and organization theory. Extant works in the field recognize the recent burgeoning academic emphasis on ambidexterity and suggest either an impending focus or a decline of the field. Although there have been attempts to review the field of ambidexterity, most of these reviews have not followed a systematic and scientific approach for extricating the key themes emerging within. The purpose of the study is to inductively and systematically capture the main elements constituting the current boundary of the field.

Design/methodology/approach

To achieve the stated purpose, this study uses data/text mining to analyze abstracts of scholarly ambidexterity papers published over the past two decades (1997-2016) in academic journals. Using text-mining, lexical analysis is performed to compute the frequency distribution of words. The frequently occurring words are studied in detail and their association with ambidexterity is also studied by means of co-relation. This analysis (used for generation of first order themes) is then complemented by a manual analysis of each first order theme to come up with trends and sub-themes lying within.

Findings

The analysis extracts eight distinct themes that indicate the current boundary of ambidexterity research. The findings highlight the potential areas for future academic attention such as networks, business models, leadership, dynamic capability and their inter-linkages with the field of ambidexterity. Overall, the field of ambidexterity is receiving heightened academic interest coupled with a dynamic proliferation across a host of related management fields. Apart from the required future consolidation, the field also needs new insights to enhance its explanatory power.

Research limitations/implications

This study analyzes abstracts of 504 works on ambidexterity (in the last two decades) to inductively indicate the current boundaries of the field using a data/text mining approach. Papers that do not explicitly mention ambidexterity in their abstracts, title or keywords are not included in the analysis.

Practical implications

The insights of the analysis will not only help researchers but also offer practitioners a good view point about the myriad of paths (not restricted to contextual, structural and temporal) through which ambidexterity can be promoted within and at the organization level.

Originality/value

The three-fold contribution of this study is a systematic and scientific approach adopted to define the current boundary of the field of ambidexterity, followed by an exploration of a set of eight distinct themes and finally the identification of ongoing debates, research gaps and future research questions in light of the analysis performed.

Details

International Journal of Organizational Analysis, vol. 26 no. 2
Type: Research Article
ISSN: 1934-8835

Keywords

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Article
Publication date: 20 April 2020

Mehmet Ali Köseoglu, Fuad Mehraliyev, Mehmet Altin and Fevzi Okumus

This study aims to propose a competitor intelligence and analysis (CIA) model that can be used for the analysis of a firm’s competitors. Empirically, it investigates the…

Abstract

Purpose

This study aims to propose a competitor intelligence and analysis (CIA) model that can be used for the analysis of a firm’s competitors. Empirically, it investigates the application of the CIA model on online reviews. This proposed model clarifies the confusion between terms such as competitive intelligence, competitor intelligence and competitor analysis and provides a more efficient process for managers.

Design/methodology/approach

The approach of the model integrates text mining techniques as a big data method with network analysis to form a competitor analysis. This study has considered two centrality metrics – degree centrality and betweenness centrality – to identify the functional associations among the resources elaborated by the customers of the hotels.

Findings

Findings show online reviews may be used as a solid source of intelligence. The intelligence maps visualized through the text-net technique is an efficient representation of tourist satisfaction and dissatisfaction with a tourism company and its competitors.

Practical implications

The proposed approach can be used in the hotel industry along with many others. The implications for scholars and managers and the possible directions for future research are also discussed in the study.

Originality/value

This study develops a new approach for competitive intelligence practices in the hotel industry and tests a new method for competitor analysis as a part of the competitive intelligence and analysis approach developed in this study.

Purpose

本研究提出了一个竞争对手情报与分析(CIA)模型, 可用于分析企业的竞争对手。对CIA模型在网络评论中的进行了实证研究。该模型厘清了竞争情报、竞争对手情报和竞争对手分析等术语之间的概念混淆, 为管理者提供了一个更有效的流程。

Design/methodology/approach

该模型将文本挖掘技术作为大数据方法与网络分析相结合, 来进行竞争对手分析。本研究考虑了两个中心性指标——度中心性和中介中心性——来识别酒店客户精心设计的资源之间的功能关联。

Findings

结果表明, 在线评论可被用作可靠的情报来源。情报地图通过文本网络技术可视化有效地展示了游客对旅游公司及其竞争对手的满意度和不满意度。

Practical implications

本文所提出的方法可用于酒店行业及许多其他行业。同时, 本文也探讨了本研究对学者与管理者的启示, 以及未来可能的研究方向。

Originality/value

本文提出了一种新的酒店行业竞争情报的实践方法, 并测试了一种新的竞争对手分析法, 作为竞争情报和分析方法的一部分。

Keywords

关键词 竞争情报, 竞争对手情报, 文本挖掘, 网络分析, 在线评论, 酒店

Objetivo

Este estudio propone un modelo de análisis de la inteligencia competitiva (CIA) que puede utilizarse para el análisis de los competidores de la empresa. Empíricamente, investiga la aplicación del modelo de la CIA a las reseñas on line. El modelo propuesto aclara la confusión entre términos como inteligencia competitiva, inteligencia de la competencia y análisis de la competencia y proporciona un procedimiento más eficiente para los gerentes.

Diseño/metodología/enfoque

El enfoque del modelo integra las técnicas de minería de textos, como método de Big Data, con el análisis de redes para realizar el análisis de la competencia. En este estudio se han considerado dos métricas de centralidad -centralidad de grado e intermediación- para identificar las asociaciones funcionales entre los recursos elaborados por los clientes de los hoteles.

Resultados

Los hallazgos muestran que las reseñas on line pueden ser utilizadas como una fuente sólida de inteligencia. Los mapas de inteligencia visualizados mediante la técnica de redes de texto son una representación eficiente de la satisfacción e insatisfacción de los turistas con la empresa turística y sus competidores.

Implicaciones prácticas

El enfoque propuesto puede utilizarse en la industria hotelera junto con otros muchos. En el estudio también se analizan las implicaciones para los investigadores y los gerentes y las posibles directrices para investigaciones futuras.

Originalidad/interés

Este artículo desarrolla un nuevo enfoque para la aplicación de la inteligencia competitiva en la industria hotelera y prueba un método nuevo para el análisis de la competencia como parte del enfoque del Análisis de la Inteligencia Competitiva desarrollado en este estudio.

Palabras clave Inteligencia competitiva, Inteligencia del competidor, Minería de textos, Análisis de redes, Reseñas on line, hoteles

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Article
Publication date: 20 September 2018

Casey Daniel Hoeve

Despite its growing popularity, there is a noticeable absence of references to the inclusion of genealogy and family history studies within the field of digital…

Abstract

Purpose

Despite its growing popularity, there is a noticeable absence of references to the inclusion of genealogy and family history studies within the field of digital humanities. New forms of inclusiveness, particularly in production-coding and cultural analysis, closely align genealogy and family history with the core tenants practiced among humanities computing and digital humanities. This paper aims to prove that genealogy as family history should be formally recognized within this cohort, as it can serve as a valuable and innovative partner for advocacy and technological advancement of the field.

Design/methodology/approach

By examining the literature, genealogy will be defined according to its use in the digital humanities, as well as its use in family history studies. The core tenants of humanities computing and digital humanities will be identified and compared against the research methodology and technological tools used in genealogy and family history research. The comparison will determine how closely the fields align, and if genealogy defined as family history should be used, and included within the field of digital humanities.

Findings

The progression of genealogy and family history from production to cultural analysis corresponds with the transition of production and coding (influenced by humanities computing) to the inclusion of experimental cultural research adopted by the digital humanities. Genealogy’s use of technological tools, such as databases, text encoding, data-text mining, graphic information systems and DNA mapping, demonstrates the use of coding and production. Cultural analysis through demographic study, crowdsourcing and establishing cultural connections illustrates new methods of scholarship, and connects coding and cultural criticism, serving as a bridge between digital humanities and the humanities at large. As genealogy continues to create new partnerships of a collaborative nature, it can, and will, continue to contribute to new areas of study within the field. As these practices continue to converge with the digital humanities, genealogy should be recognized as a partner and member in the digital humanities cohort.

Originality/value

Despite its growing popularity, there is a noticeable absence of references to the inclusion of genealogy and family history studies within the field of the digital humanities. The term genealogy resonates differently within the digital humanities, primarily articulating the history of the field over the study and research of family lineage. This study seeks to demonstrate how genealogy and family history can fit within the digital humanities, providing a new perspective that has not yet been articulated in the scholarly literature.

Details

Digital Library Perspectives, vol. 34 no. 3
Type: Research Article
ISSN: 2059-5816

Keywords

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Article
Publication date: 12 September 2016

Asil Oztekin

The prediction of graduation rates of college students has become increasingly important to colleges and universities across the USA and the world. Graduation rates, also…

Abstract

Purpose

The prediction of graduation rates of college students has become increasingly important to colleges and universities across the USA and the world. Graduation rates, also referred to as completion rates, directly impact university rankings and represent a measurement of institutional performance and student success. In recent years, there has been a concerted effort by federal and state governments to increase the transparency and accountability of institutions, making “graduation rates” an important and challenging university goal. In line with this, the main purpose of this paper is to propose a hybrid data analytic approach which can be flexibly implemented not only in the USA but also at various colleges across the world which would help predict the graduation status of undergraduate students due to its generic nature. It is also aimed at providing a means of determining and ranking the critical factors of graduation status.

Design/methodology/approach

This study focuses on developing a novel hybrid data analytic approach to predict the degree completion of undergraduate students at a four-year public university in the USA. Via the deployment of the proposed methodology, the data were analyzed using three popular data mining classifications methods (i.e. decision trees, artificial neural networks, and support vector machines) to develop predictive degree completion models. Finally, a sensitivity analysis is performed to identify the relative importance of each predictor factor driving the graduation.

Findings

The sensitivity analysis of the most critical factors in predicting graduation rates is determined to be fall-term grade-point average, housing status (on campus or commuter), and which high school the student attended. The least influential factors of graduation status are ethnicity, whether or not a student had work study, and whether or not a student applied for financial aid. All three data analytic models yielded high accuracies ranging from 71.56 to 77.61 percent, which validates the proposed model.

Originality/value

This study presents uniqueness in that it presents an unbiased means of determining the driving factors of college graduation status with a flexible and powerful hybrid methodology to be implemented at other similar decision-making settings.

Details

Industrial Management & Data Systems, vol. 116 no. 8
Type: Research Article
ISSN: 0263-5577

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Article
Publication date: 9 May 2016

Oguz Cimenler, Kingsley A. Reeves, John Skvoretz and Asil Oztekin

The purpose of this paper is to provide a model that tests to what extent researchers’ interactions in the early stage of their collaborative network activities affect the…

Abstract

Purpose

The purpose of this paper is to provide a model that tests to what extent researchers’ interactions in the early stage of their collaborative network activities affect the number of collaborative outputs (COs) produced (e.g. joint publications, joint grant proposals and joint patents).

Design/methodology/approach

Using self-reports from 100 tenured/tenure-track faculty at a US-based university, partial least squares (PLS) path models are run to test the extent to which researchers’ individual innovativeness (Iinnov) affects the number of COs they produced taking into account the tie strength (TS) of a researcher to other conversational partners. Iinnov is determined by the specific indicators obtained from researchers’ interactions in the early stage of their collaborative network activities.

Findings

The results indicate that researchers’ Iinnov positively affects the volume of their COs. Furthermore, TS negatively affects the relationship between researchers’ Iinnov and the volume of their COs, which is consistent with the famous “Strength of Weak Ties” theory.

Practical implications

By investigating the degree of impact of researchers’ Iinnov on their CO, college administration could be informed regarding the extent that the social cohesion formed by interpersonal ties affects or drives the collaboration activity that results in COs. When this paper is extended to the entire university, university administration would know the capability of the different colleges, or even the university as a whole, in transforming the ideas embedded in researchers’ networks into a productive work in a collaborative manner.

Originality/value

It is one of the foremost attempts to investigate the relationship between researchers’ Iinnov during ideation phase and their CO. Moreover, this paper contributes to the literature regarding the transformation of tacit knowledge into explicit knowledge at a university context.

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Book part
Publication date: 4 January 2019

William D. Brink and M. Dale Stoel

The purpose of this study is to identify the specific skills and abilities within the broad category of data analytics that current business professionals believe are most…

Abstract

The purpose of this study is to identify the specific skills and abilities within the broad category of data analytics that current business professionals believe are most important for accounting graduates. Data analytics knowledge is clearly important, but this category is broad. Therefore, this study identifies the specific skills and abilities that are most important for accounting graduates so that faculty can create classroom materials most beneficial for the future accounting graduates. In 2013, the Association to Advance Collegiate Schools of Business developed new standards for accounting programs, including standard A7, related to information technology and analytics. The intent of the standard clearly focuses on increasing the level of technology and analytics studied within the accounting curriculum. However, the specific details and methods for achieving the intent of A7 remain an open question. This chapter uses prior research focused on business analytics education to identify potential analytic skills, tools, techniques, and management issues of concern within the accounting profession. A survey of 342 accounting professionals identifies suggested areas of analytic competencies for accounting graduates. Specifically, the authors find preferences for skills related to data interpretation and communication over any individual technical skills or statistical knowledge. These skills suggest a role for accountants as intermediaries who may need to translate analytic activities into business language. Post hoc, the authors examine the survey results for differences based on respondent characteristics. Interestingly, female respondents report lower beliefs about the importance of analytic skills. The authors also find some differences when examining different demographics within the respondents.

Details

Advances in Accounting Education: Teaching and Curriculum Innovations
Type: Book
ISBN: 978-1-78756-540-1

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Article
Publication date: 17 October 2016

Jieun Kim, Sungjoo Lee and Yongtae Park

The purpose of this paper is to propose the use of a user-centric service map to facilitate the visual exploration and monitoring of user context information for proactive…

Abstract

Purpose

The purpose of this paper is to propose the use of a user-centric service map to facilitate the visual exploration and monitoring of user context information for proactive market analysis.

Design/methodology/approach

The paper supports a context-based market analysis by developing a user-centric service map which comprehensively visualizes a variety of contexts, users, and services. Empirical data were gathered from service descriptions and reviews of 100 mobile application services in the Apple App Store’s lifestyle and healthcare and fitness categories.

Findings

The user-centric service map supports the analysis of the context information from using various mobile app services, and can therefore be effectively applied for market-segment analysis and user-value analysis.

Practical implications

The user-centric service map involves implications in terms of multi-disciplinary proactive market orientation and data-driven strategy development, allowing firms to respond to changing market conditions in the mobile business promptly and even preemptively.

Originality/value

The initiative uncovering of latent needs through examining context of use have been an important focus of prior work, but little attempt has been presented in the way of frameworks for converting abundant context data into strategic information. The paper provides new methods and procedures to establish and interpret service maps using flexible visual features.

Details

Management Decision, vol. 54 no. 9
Type: Research Article
ISSN: 0025-1747

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Article
Publication date: 31 May 2018

Antonio Usai, Marco Pironti, Monika Mital and Chiraz Aouina Mejri

The aim of this work is to increase awareness of the potential of the technique of text mining to discover knowledge and further promote research collaboration between…

Abstract

Purpose

The aim of this work is to increase awareness of the potential of the technique of text mining to discover knowledge and further promote research collaboration between knowledge management and the information technology communities. Since its emergence, text mining has involved multidisciplinary studies, focused primarily on database technology, Web-based collaborative writing, text analysis, machine learning and knowledge discovery. However, owing to the large amount of research in this field, it is becoming increasingly difficult to identify existing studies and therefore suggest new topics.

Design/methodology/approach

This article offers a systematic review of 85 academic outputs (articles and books) focused on knowledge discovery derived from the text mining technique. The systematic review is conducted by applying “text mining at the term level, in which knowledge discovery takes place on a more focused collection of words and phrases that are extracted from and label each document” (Feldman et al., 1998, p. 1).

Findings

The results revealed that the keywords extracted to be associated with the main labels, id est, knowledge discovery and text mining, can be categorized in two periods: from 1998 to 2009, the term knowledge and text were always used. From 2010 to 2017 in addition to these terms, sentiment analysis, review manipulation, microblogging data and knowledgeable users were the other terms frequently used. Besides this, it is possible to notice the technical, engineering nature of each term present in the first decade. Whereas, a diverse range of fields such as business, marketing and finance emerged from 2010 to 2017 owing to a greater interest in the online environment.

Originality/value

This is a first comprehensive systematic review on knowledge discovery and text mining through the use of a text mining technique at term level, which offers to reduce redundant research and to avoid the possibility of missing relevant publications.

Details

Journal of Knowledge Management, vol. 22 no. 7
Type: Research Article
ISSN: 1367-3270

Keywords

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