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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.

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.

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

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.

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.

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.

Presents a review on implementing finite element methods on supercomputers, workstations and PCs and gives main trends in hardware and software developments. An appendix included at the end of the paper presents a bibliography on the subjects retrospectively to 1985 and approximately 1,100 references are listed.

This paper gives a review of the finite element techniques (FE) applied in the area of material processing. The latest trends in metal forming, non‐metal forming and powder metallurgy are briefly discussed. The range of applications of finite elements on the subjects is extremely wide and cannot be presented in a single paper; therefore the aim of the paper is to give FE users only an encyclopaedic view of the different possibilities that exist today in the various fields mentioned above. An appendix included at the end of the paper presents a bibliography on finite element applications in material processing for the last five years, and more than 1100 references are listed.

A growing body of research outlines how to best facilitate and ensure methodological rigor when using dictionary-based computerized text analyses (DBCTA) in organizational research. However, these best practices are currently scattered across several methodological and empirical manuscripts, making it difficult for scholars new to the technique to implement DBCTA in their own research. To better equip researchers looking to leverage this technique, this methodological report consolidates current best practices for applying DBCTA into a single, practical guide. In doing so, we provide direction regarding how to make key design decisions and identify valuable resources to help researchers from the beginning of the research process through final publication. Consequently, we advance DBCTA methods research by providing a one-stop reference for novices and experts alike concerning current best practices and available resources.

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.

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.

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.

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.

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.

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).

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.

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.

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.

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.

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.

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

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

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.

Several implications concerning destination marketing are outlined.

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.

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。

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。

本论文只研究了单一市场群, 分析样本量较小。

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。

本论文结构指出了多个旅游目的地营销的相关启示

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

Research on artificial intelligence (AI) and its potential effects on the workplace is increasing. How AI and the futures of work are framed in traditional media has been examined in prior studies, but current research has not gone far enough in examining how AI is framed on social media. This paper aims to fill this gap by examining how people frame the futures of work and intelligent machines when they post on social media.

We investigate public interpretations, assumptions and expectations, referring to framing expressed in social media conversations. We also coded the emotions and attitudes expressed in the text data. A corpus consisting of 998 unique Reddit post titles and their corresponding 16,611 comments was analyzed using computer-aided textual analysis comprising a BERTopic model and two BERT text classification models, one for emotion and the other for sentiment analysis, supported by human judgment.

Different interpretations, assumptions and expectations were found in the conversations. Three subframes were analyzed in detail under the overarching frame of the New World of Work: (1) general impacts of intelligent machines on society, (2) undertaking of tasks (augmentation and substitution) and (3) loss of jobs. The general attitude observed in conversations was slightly positive, and the most common emotion category was curiosity.

Findings from this research can uncover public needs and expectations regarding the future of work with intelligent machines. The findings may also help shape research directions about futures of work. Furthermore, firms, organizations or industries may employ framing methods to analyze customers’ or workers’ responses or even influence the responses. Another contribution of this work is the application of framing theory to interpreting how people conceptualize the future of work with intelligent machines.

The purpose of this special issue is to extend the Economic and Social Sciences Research Council (ESRC)-funded UK seminar series–Challenging Gendered Media (Mis)Representations of Women Professionals and Leaders; and to highlight research into the gendered media constructions of women managers and leaders and outline effective methods and methodologies into diverse media.

Gendered analysis of television, autobiographies (of Sheryl Sandberg, Karren Brady, Hillary Clinton and Julia Gillard), broadcast news media and media press through critical discourse analysis, thematic analysis, metaphor and computer-aided text analysis software following the format of the Gender Media Monitoring Project (2015) and [critical] ecological framework for advancing social change.

The papers surface the gendered nature of media constructions of women managers and leaders and offer methods and methodologies for others to follow to interrogate gendered media. Further, the papers discuss – how women’s leadership is glamourized, fetishized and sexualized; the embodiment of leadership for women; how popular culture can subvert the dominant gaze; how women use agency and how powerful gendered norms shape perceptions, discourses and norms and how these are resisted, repudiated and represented.

The papers focus upon how the media constructs women managers and leaders and offer implications of how media influences and is influenced by practice. There are recommendations provided as to how the media could itself be organized differently to reflect diverse audiences, and what can be done to challenge gendered media.

Challenging gendered media representations of women managers and leaders is critical to social justice and equality for women in management and leadership.

This is an invited Special Issue comprising inaugural collection of research through which we get to “see” women and leaders and the gendered media gaze and to learn from research into popular culture through analysis of television, autobiographies and media press.