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Article
Publication date: 25 February 2020

Linda W. Lee, Amir Dabirian, Ian P. McCarthy and Jan Kietzmann

The purpose of this paper is to introduce, apply and compare how artificial intelligence (AI), and specifically the IBM Watson system, can be used for content analysis in…

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Abstract

Purpose

The purpose of this paper is to introduce, apply and compare how artificial intelligence (AI), and specifically the IBM Watson system, can be used for content analysis in marketing research relative to manual and computer-aided (non-AI) approaches to content analysis.

Design/methodology/approach

To illustrate the use of AI-enabled content analysis, this paper examines the text of leadership speeches, content related to organizational brand. The process and results of using AI are compared to manual and computer-aided approaches by using three performance factors for content analysis: reliability, validity and efficiency.

Findings

Relative to manual and computer-aided approaches, AI-enabled content analysis provides clear advantages with high reliability, high validity and moderate efficiency.

Research limitations/implications

This paper offers three contributions. First, it highlights the continued importance of the content analysis research method, particularly with the explosive growth of natural language-based user-generated content. Second, it provides a road map of how to use AI-enabled content analysis. Third, it applies and compares AI-enabled content analysis to manual and computer-aided, using leadership speeches.

Practical implications

For each of the three approaches, nine steps are outlined and described to allow for replicability of this study. The advantages and disadvantages of using AI for content analysis are discussed. Together these are intended to motivate and guide researchers to apply and develop AI-enabled content analysis for research in marketing and other disciplines.

Originality/value

To the best of the authors’ knowledge, this paper is among the first to introduce, apply and compare how AI can be used for content analysis.

Details

European Journal of Marketing, vol. 54 no. 3
Type: Research Article
ISSN: 0309-0566

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Book part
Publication date: 31 July 2014

Aaron H. Anglin, Thomas H. Allison, Aaron F. McKenny and Lowell W. Busenitz

Social entrepreneurs often make public appeals for funding to investors who are motivated by nonfinancial considerations. This emerging research context is an opportunity…

Abstract

Purpose

Social entrepreneurs often make public appeals for funding to investors who are motivated by nonfinancial considerations. This emerging research context is an opportunity for researchers to expand the bounds of entrepreneurship theory. To do so, we require appropriate research tools. In this chapter, we show how computer-aided text analysis (CATA) can be applied to advance social entrepreneurship research. We demonstrate how CATA is well suited to analyze the public appeals for resources made by entrepreneurs, provide insight into the rationale of social lenders, and overcome challenges associated with traditional survey methods.

Method

We illustrate the advantages of CATA by examining how charismatic language in 13,000 entrepreneurial narratives provided by entrepreneurs in developing countries influences funding speed from social lenders. CATA is used to assess the eight dimensions of charismatic rhetoric.

Findings

We find that four of the dimensions of charismatic rhetoric examined were important in predicting funding outcomes for entrepreneurs.

Implications

Data collection and sample size are important challenges facing social entrepreneurship research. This chapter demonstrates how CATA techniques can be used to collect valuable data and increase sample size. This chapter also examines how the rhetoric used by entrepreneurs impacts their fundraising efforts.

Details

Social Entrepreneurship and Research Methods
Type: Book
ISBN: 978-1-78441-141-1

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Book part
Publication date: 27 November 2018

Esther Biehl, Kerstin Fehre and Marco Tietze

This study updates the discussion on demand-pull attention as a source of radical product innovation. Demand-pull attention shows an ex ante alignment with market…

Abstract

This study updates the discussion on demand-pull attention as a source of radical product innovation. Demand-pull attention shows an ex ante alignment with market characteristics and needs as opposed to pushing resources toward markets. The authors suggest a holistic framework and specify three dimensions of demand-pull attention: anticipated or revealed market demand, market environment, and external economic environment. Based on a large German longitudinal panel consisting of 941 firm-year observations from 2003 to 2013, the authors conceptualized the measurement of demand-pull dimensions’ attention and radical product innovation using computer-aided text analysis of annual reports. The authors analyzed the relationship between the attention that a firm pays to different demand-pull dimensions and the firm’s strategic intention to radically innovate; thus, the authors actually focused on the cognitive sources of radical product innovations. This chapter suggests that radical product innovation activities are positively driven by attention toward the market environment and market demand orientation. However, the hypothesis, which assumed a negative relationship between attention toward the external economic environment and radical innovation, could not be significantly confirmed. This demands a closer look into the underlying decision processes of firms when deciding on radical product innovations. With the theoretical grounding on the attention-based view of the firm, the authors contribute to a better understanding of the role that organizational cognition plays in innovation processes.

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Book part
Publication date: 24 July 2020

Emily D. Campion and Michael A. Campion

This literature review is on advanced computer analytics, which is a major trend in the field of Human Resource Management (HRM). The authors focus specifically on…

Abstract

This literature review is on advanced computer analytics, which is a major trend in the field of Human Resource Management (HRM). The authors focus specifically on computer-assisted text analysis (CATA) because text data are a prevalent yet vastly underutilized data source in organizations. The authors gathered 341 articles that use, review, or promote CATA in the management literature. This review complements existing reviews in several ways including an emphasis on CATA in the management literature, a description of the types of software and their advantages, and a unique emphasis on findings in employment. This examination of CATA relative to employment is based on 66 studies (of the 341) that bear on measuring constructs potentially relevant to hiring decisions. The authors also briefly consider the broader machine learning literature using CATA outside management (e.g., data science) to derive relevant insights for management scholars. Finally, the authors discuss the main challenges when using CATA for employment, and provide recommendations on how to manage such challenges. In all, the authors hope to demystify and encourage the use of CATA in HRM scholarship.

Details

Research in Personnel and Human Resources Management
Type: Book
ISBN: 978-1-80043-076-1

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Article
Publication date: 12 January 2021

Sean Bradley Power and Niamh M. Brennan

A royal charter of incorporation imposing public benefit/social responsibilities established the privately owned British South Africa Company (BSAC), in return for power…

Abstract

Purpose

A royal charter of incorporation imposing public benefit/social responsibilities established the privately owned British South Africa Company (BSAC), in return for power to exploit a huge territory using low-cost local labour. This study explores the dual principal–agent problem of how the BSAC used annual report narratives to report on its conflicting economic responsibilities to investors versus its public benefit charter responsibilities to the British Crown.

Design/methodology/approach

Having digitised the dataset, the research analyses narratives from 29 BSAC annual reports spanning a continuous 35-year royal charter period, using computer-aided keyword content analysis to identify economic-orientated versus public benefit-orientated annual report narratives. The research analyses how the annual report narratives shifted according to four key contextual periods by reference to the changing influence of private investors versus the British Crown.

Findings

There are two key findings. First, economic primacy. At no point do public benefit disclosures outweigh economic disclosures. Second, the BSAC's meso-corporate context and macro-social/political context can explain patterns in public benefit disclosures. The motivation for producing public benefit information is not altruism. Rather, commercial interests motivate disclosure. The BSAC used its annual reports to sustain what proved ultimately unsustainable – royal charter-style colonialism.

Originality/value

This accounting history study contributes to an understanding of corporate narrative reporting using one of the earliest known cases of such analysis and shows how accounting plays a central role in facilitating a company in sustaining its interests. This 100-year lookback may be a portend of the future for modern-day annual report corporate social responsibility narratives in, say, mining and oil and gas company corporate reports, especially if these natural resources run out.

Details

Accounting, Auditing & Accountability Journal, vol. 34 no. 4
Type: Research Article
ISSN: 0951-3574

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Book part
Publication date: 31 December 2003

Robert P Gephart

This comment provides a discovery-oriented reading of grounded theory which supplements the verification-oriented approach to level specification. I address how grounded…

Abstract

This comment provides a discovery-oriented reading of grounded theory which supplements the verification-oriented approach to level specification. I address how grounded theory can be used to discover new constructs, to surface properties of constructs, to validate constructs, and to enhance understanding of levels of analysis of constructs. Two approaches to the integration of qualitative and quantitative data in grounded theory are discussed: the linking approach and computer-aided interpretive textual analysis. The comment shows how multi-level constructs can be developed from real life interaction using discovery oriented grounded theory.

Details

Multi-Level Issues in Organizational Behavior and Strategy
Type: Book
ISBN: 978-0-76231-039-5

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Article
Publication date: 1 August 2016

Yanto Chandra

This paper aims to extend the understanding of the ways in which social entrepreneurs give sense to and legitimize their work by introducing a rhetoric-orientation view of…

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1087

Abstract

Purpose

This paper aims to extend the understanding of the ways in which social entrepreneurs give sense to and legitimize their work by introducing a rhetoric-orientation view of social entrepreneurship (SE).

Design/methodology/approach

This study uses computer-aided text analysis and computational linguistics to study 191 interviews of social and business entrepreneurs. It offers validation and exploration of new concepts pertaining to the rhetoric orientations of SE.

Findings

This study confirms prior untested assumptions that the rhetoric of social entrepreneurs is more other, stakeholder engagement and justification-oriented and less self-oriented than the rhetoric of business entrepreneurs. It also confirms that the rhetoric of both types of entrepreneurs is equally economically oriented.

Originality/value

This research makes new contribution to the SE literature by introducing three new orientations, namely, solution, impact and geographical, which reflect distinctive rhetorical themes used by social entrepreneurs, and by revealing that social entrepreneurs use terms associated with other, stakeholder engagement, justification, economic, solution, impact and geographical orientations differently than business entrepreneurs.

Details

Social Enterprise Journal, vol. 12 no. 2
Type: Research Article
ISSN: 1750-8614

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Article
Publication date: 13 May 2014

Caryn Conley and Jennifer Tosti-Kharas

The purpose of this paper is to evaluate the effectiveness of a novel method for performing content analysis in managerial research – crowdsourcing, a system where…

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2206

Abstract

Purpose

The purpose of this paper is to evaluate the effectiveness of a novel method for performing content analysis in managerial research – crowdsourcing, a system where geographically distributed workers complete small, discrete tasks via the internet for a small amount of money.

Design/methodology/approach

The authors examined whether workers from one popular crowdsourcing marketplace, Amazon's Mechanical Turk, could perform subjective content analytic tasks involving the application of inductively generated codes to unstructured, personally written textual passages.

Findings

The findings suggest that anonymous, self-selected, non-expert crowdsourced workers were applied content codes efficiently and at low cost, and that their reliability and accuracy compared to that of trained researchers.

Research limitations/implications

The authors provide recommendations for management researchers interested in using crowdsourcing most effectively for content analysis, including a discussion of the limitations and ethical issues involved in using this method. Future research could extend the findings by considering alternative data sources and coding schemes of interest to management researchers.

Originality/value

Scholars have begun to explore whether crowdsourcing can assist in academic research; however, this is the first study to examine how crowdsourcing might facilitate content analysis. Crowdsourcing offers several advantages over existing content analytic approaches by combining the efficiency of computer-aided text analysis with the interpretive ability of traditional human coding.

Details

Management Decision, vol. 52 no. 4
Type: Research Article
ISSN: 0025-1747

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Article
Publication date: 22 June 2010

Ken Crofts and Jayne Bisman

The paper has a dual purpose, being to report on an interrogation of concepts and contexts of accountability used in the accounting literature and to illustrate the…

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2698

Abstract

Purpose

The paper has a dual purpose, being to report on an interrogation of concepts and contexts of accountability used in the accounting literature and to illustrate the application of a qualitative data analysis software tool in this interrogation.

Design/methodology/approach

A content analysis was undertaken of 114 journal articles related to accountability and published in highly ranked accounting journals from 2000 to 2007.

Findings

Accountability is a concept used in a variety of contexts, particularly in connection with public accountabilities and accountability in the public sector, as well as within social contexts. The emphasis appears to be on accountability reporting in these settings, with less concern for the management perspective. The variety of contextual usage and categorisations of the term “accountability” indicate it has not become more precise over the period in question.

Research limitations/implications

Since only 21 accounting journals are sampled, there is scope for investigating accountability concepts across a broader base of publication outlets. The findings suggest that greater effort should be devoted to developing frameworks of accountability, researching accountability in relatively under‐explored contexts and settings, and considerable scope for researchers to more frequently utilise computer‐assisted qualitative data analysis in content analysis studies concerning accounting and accountability.

Originality/value

While there is anecdotal evidence of the elusive nature of accountability, this paper provides a window on conceptions of accountability employed by accounting scholars and the contexts in which accountability is discussed and researched. Further, the use of the Leximancer software tool in qualitative content analysis is demonstrated, noting that the accounting literature is currently devoid of examples of applications of this software.

Details

Qualitative Research in Accounting & Management, vol. 7 no. 2
Type: Research Article
ISSN: 1176-6093

Keywords

Open Access
Article
Publication date: 10 June 2021

Vanesa F. Guzman-Parra, Juan Trespalacios Gutierrez and José Roberto Vila-Oblitas

This study aims to demonstrate the application of computer-aided text analysis (CATA) software in identifying primary associations and impressions of a specified tourist…

Abstract

Purpose

This study aims to demonstrate the application of computer-aided text analysis (CATA) software in identifying primary associations and impressions of a specified tourist destination.

Design/methodology/approach

The Leximancer software is applied on primary information to analyze the concepts evoked by a destination. Because no specific planning has been done for destination image marketing strategies for rural tourism in Andalusia, this study visualizes and determines clusters of the main attributes associated with this destination.

Findings

The analysis identifies the main clusters among associations and impressions of the destination that can be useful in developing strategies.

Research limitations/implications

Only a target segment is studied, with a relatively small sample size.

Practical implications

Leximancer can not only be applied to online user-generated content, but primary information can also be mapped to generate a holistic destination image. Furthermore, identification of the relevant attributes and impressions can serve to identify unique assets to help tourism organizations develop a destination.

Social implications

Several implications concerning destination marketing are outlined.

Originality/value

Although previous studies have applied Leximancer and other CATA software, the present research uses a new approach. Deriving the primary information on destination image using an unstructured methodology, the concepts evoked by a destination are mapped. Because there is a lack of research on rural tourism in Andalusia and its destination image, its associated attributes are studied.

研究目的

本论文展示如何使用CATA分析软件来确定一个具体旅游目的地的主要关系和印象。

研究设计/方法/途径

Leximancer软件主要用于分析一个目的地引发的相关概念。因为安达卢西亚至今未有确定的乡村旅游目的地形象营销策略, 本论文视觉化和决定与此目的地相关的主要因素群。

研究结果

研究结果指出了此安达卢西亚目的地的主要相关群和印象群, 这些对于指定战略计划有很大帮助。

研究理论限制

本论文只研究了单一市场群, 分析样本量较小。

研究实际启示

Leximancer不仅可以用来分析用户生成内容, 还可以分析主要信息, 以展示整体旅游目的地形象。此外, 分析指出的相关因素和印象群可以用来确立独特的资源组合, 帮助旅游机构开发旅游目的地。

研究社会启示

本论文结构指出了多个旅游目的地营销的相关启示

研究原创性/价值

尽管文献中有关Leximancer和其他CATA软件的使用文章, 本论文创立了新的使用方法。基于对旅游目的地形象的主要信息进行非结构性研究, 本论文对于旅游目的地的概念进行展开论述。由于至今未有针对安达卢西亚的乡村旅游研究以及旅游目的地形象研究, 本研究论述了其相关因素。

关键词 安达卢西亚、旅游目的地形象、旅游目的地因素、CATA软件、Leximancer

Details

Journal of Hospitality and Tourism Technology, vol. 12 no. 2
Type: Research Article
ISSN: 1757-9880

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