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The purpose of this paper is to describe a research method successfully used to study intellectual capital (IC) and IC flows through a highly networked marketplace.

The method integrates computer‐assisted content analysis (CA) and multivariate statistics. The CA is performed on a large source of business and analyst reports. The method is successful in enabling the elements of IC to be related to firm performance, using 156 firms in the global information technology market as a testing ground.

Computer‐assisted CA techniques could be successfully used to analyse the larger samples of firms for IC attributes like human capital, internal capital and external or relational capital, than have previously been feasible using manual CA methods.

Several limitations of the method are identified and relate to the computer‐assisted CA method used. First, the method relies on the existence of a large body of content, in this case business reports and articles, to create the indices for the IC attributes. A second limitation is that the IC attributes are constructed from public sources (i.e. they represent the view of external reporters, rather than internal to the organisation reporters). The method presented combines and extends the benefits of both qualitative and quantitative methods. The richer source of IC content for a larger sample of firms is made accessible through computer‐assisted CA. The overall method enables insights to be explored in relating firm IC to firm performance in the market place.

The integrated research method presented is the result of original research. The value to researchers is the opportunity it provides to study the IC/performance relationship across markets, rather than be limited to small sample or limited attribute studies.

This study aims to explore multifaceted corporate social responsibility (CSR) covered in popular English newspapers in the UK, USA, mainland China and Hong Kong from 2000 to 2016 via a computer-assisted analytical approach. This study moves the understanding of CSR away from corporate self-reporting to the mass media and raises interesting questions about the role of the news media in presenting CSR as a multifaceted, socially constructed concept.

Data were retrieved from CSR-related news articles from 2000 to 2016 that were archived in the LexisNexis database. Guided by the theoretical framework of agenda setting, a computer-assisted content analysis (Latent Dirichlet Allocation) was used to analyze 4,487 CSR-related articles from both business and non-business news sources. Analysis of variance was used to compare salient CSR topics in each country/region.

This study identifies newspapers as an alternate to corporations’ attempts to distribute CSR information and construct CSR meaning. The findings revealed that the news communicates a variety of CSR issues that are aligned or beyond what CSR was defined in corporate CSR reporting, as suggested in previous studies. In addition, CSR news coverages differ between the business and nonbusiness news sources. Furthermore, the media tone of CSR coverage significantly differed across the regions and between the business and nonbusiness newspapers.

Emerging topics in CSR news coverage, such as business education, could help companies identify untapped CSR realms in the market.

This study contributes to CSR communication research by adding a non-corporate perspective regarding what CSR means and should be focused on. The news media presents CSR using a heterogeneous approach as they not only provide surface reports on corporations’ CSR activities but also offer in-depth discussions.

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.

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

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.

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.

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.

The purpose of this paper is to summarize the main developments from the early days of manual content analysis to the adoption of computer-assisted content analysis and the emerging artificial intelligence (AI)-supported ways to analyze content (primarily text) in marketing and consumer research. A further aim is to outline the many opportunities these new methods offer to marketing scholars and practitioners facing new types of data.

This conceptual paper maps our methods used for content analysis in marketing and consumer research.

This paper concludes that many new and emerging forms of unstructured data provide a wealth of insight that is neglected by existing content analysis methods. The main findings of this paper support the fact that emerging methods of making sense of such consumer data will take us beyond text and eventually lead to the adoption of AI-supported tools for all types of content and media.

This paper provides a broad summary of nearly five decades of content analysis in consumer and marketing research. It concludes that, much like in the past, today’s research focuses on the producers of the words than the words themselves and urges researchers to use AI and machine learning to extract meaning and value from the oceans of text and other content generated by organizations and their customers.

This study aims to understand how media content and media sentiment in corporate social responsibility (CSR) news coverage affect investment performance, as reflected in the S&P 500 Environmental and Socially Responsible Index from 2010 to 2016.

Computer-assisted content analysis and sentiment analysis are employed to analyze 818 CSR-related newspaper articles from mainstream newspapers. Autoregressive model is used to comprehend socially responsible investment (SRI) performance.

This study reveals the impact of media content and media sentiment of CSR-related news articles on SRI. The authors’ findings indicate that such topics as recognition of a company's CSR contributions in CSR-related news articles are positively associated with SRI performance, whereas topics such as tax avoidance and environmental protection show a negative relationship with SRI performance. In addition, this study contributes to the authors’ understanding of framing bias in investment by confirming a significant positive association between an uncertain or constraining media sentiment and SRI performance, as well as a negative relationship between a litigious sentiment and SRI performance.

There has been limited attention to examining the effect of media coverage of CSR on the financial market. Since SRI is one of the most useful financial indices for SRIs, it is meaningful to explore the relationship between media coverage of CSR and SRI. To fill the research gap, this study specifically examines how media coverage of CSR-related issues is associated with SRI performance.

This study seeks to understand the communication factors associated with effective social media for nonprofit organizations (NPOs). Specifically, the study investigated how interactive and emotional communication strategies influence public engagement in different ways, and how the effects differ by service-oriented and other types of NPOs.

Using computer-assisted textual and emotional analyses, the authors examined the functional interactivity, contingency interactivity and emotion elements of 301,559 tweets from the 100 largest US nonprofits. Negative binomial regression was applied to test the relationships among these elements and public engagement on Twitter (i.e. likes and retweets).

Findings revealed negative effects of functional interactivity on likes, negative effects of contingency interactivity on likes and retweets but a positive effect of functional interactivity on retweets. The findings also showed negative effects of emotion valence on likes and retweets but positive effects of emotion strength on likes and retweets. There were varying effects of interactivity and emotion on public engagement for service-oriented and other types of NPOs.

This study advances the nonprofit social media scholarship in several ways. First, this study suggests a clear yet largely ignored distinction in the effects of functional and contingency interactivity on public engagement. Second, this study is an early attempt to examine the role and impact of emotion elements in nonprofit social media success without downplaying the role of interactivity. Third, this study is one of the earliest attempts to include interaction effects for different types of NPOs. Last, this study contributes to the organizational social media use research by demonstrating the benefits of computer-assisted approaches in processing text data on social media. From a practical perspective, this study provides strategic guidelines for NPOs to design effective communication contents and improve their public engagement on social media.

While morality is ever-present in elections, scholars have yet to merge political public relations and Moral Foundations Theory. It is crucial to assess the complex morality present not only in social deduction, but also in political strategic communication. The current work aims to analyze the issue agendas and their relationships in the 2020 presidential campaign and assesses their moral strategy.

This study used a computer-assisted content analysis (N = 7,888) with each moral intuition coded from the Moral Foundations Dictionary. Datapoints included campaign tweets, Facebook posts, debate performances, remarks, news releases and nomination acceptance speeches. Coverage included articles from including The New York Times, Washington Post, Wall Street Journal, CNN and Fox News to assess both liberal and conservative media.

Candidates' issue and moral agendas were correlated with each other and with the media's agenda. Comparatively, the Biden campaign has stronger correlations when it came to connecting with issues, stakeholders and moral intuitions in the media agenda than the Trump campaign. For issues, the Biden campaign prioritized COVID-19 and the economy, while the Trump campaign prioritized the economy and crime. The candidates also had similar moral strategies.

This study suggests effectively leveraging organizational communications in democracies can support the transfer of object salience, moral attributes and networks to media coverage, public discourse and opponent messaging. It can also help achieve organizational goals by managing public image, reputation and expectations.

This work expands the literature by taking a pluralist moral psychology approach in assessing the salience and correlation of five moral intuitions: harm/care, fairness/reciprocity, ingroup/loyalty, authority/respect and purity/sanctity. This study serves as a springboard for examining morality's impact on political public relations.

Social media is an engaging area of research that is rapidly evolving. The purpose of this paper is to focus on how corporations should effectively utilize this new media as a marketing channel. The key to any successful communication strategy is matching the message to the target audience and achieving customer engagement. Two important target audience variables were identified as crucial when determining an organization’s social media communications strategy: the level of brand relationship, and the level of category involvement.

Depth interviews were initially employed, followed by questionnaires, and then computer assisted content analysis was performed on 723 online media articles relating to social media marketing to identify semantic and conceptual relationships.

Research from both a customer and corporate perspective led to insights into how organizations can develop their social media strategies in order to transform their brand message from being perceived as a commercial source of information to a social source – the social media transformation process.

This research suggests a finer level of segmentation of social media users that will lead to content strategies adapted to fit the current levels of brand and category involvement. This could be used by organization to develop a model of best practice to achieve their social media objectives.

It is crucial for organizations to understand how different groups of users influence, receive, curate, and interact via social media. The greater the depth of this knowledge, the greater the effectiveness of content marketing strategies developed by the corporation. Organizations that utilize social media marketing must carefully analyse the large amount of consumer information available to them, listen to consumer conversations, and determine the needs and segments that will be most receptive to different approaches. They must also accept that in a social media environment user generated content and interactive communication processes should be at the heart of successful strategy.

To date, there has been limited analysis of how relationship and involvement factors drive social media content (Cho et al., 2014; Malthouse et al., 2013). More research is needed to understand how key user characteristics lead to content that fully utilizes the social interaction and message diffusion potential of this media. This paper introduces a hierarchy of content marketing based upon the type of relationship between the user and the organization, as well as their level of product category involvement.

This paper aims to identify potential avenues for innovation in urban hotel management by analyzing self-reported data from visitors regarding their experience with interior design.

A qualitative exploratory computer-assisted content analysis was conducted to identify the impact of interior design on the guest experience. Leximancer 4.0 software analyzed 2,562 reviews from urban hotels collected through a reservation website.

The findings reveal that data reported by guests on interior design play a crucial role in shaping guest experiences, both positively and negatively. The esthetic appeal of interior design is shown to impact resting and comfort, affecting overall performance significantly. The study also highlights how different star categories of hotels and variations in visitors' purposes for their stay lead to distinct guest experiences and different opportunities to innovate.

The study’s results provide evidence for researchers and practitioners of the potential of the guest-reported interior design experience as a valuable source for fostering innovation. In addition, in the hotel industry, innovation may eventually be attained through interior design renovation.

Self-reported data from guests on interior design is an effective tool for innovation. Making interior design a priority throughout the establishment and ongoing management of a hotel is crucial. By integrating interior design, not only can potential negative experiences be avoided, but greater guest satisfaction can also be achieved during their stay, promoting memorable experiences that align with the hotel category and customer expectations.

This research emphasizes the importance of interior design as a catalyst for innovation and improved social experiences in the hospitality industry. Innovation in interior design can improve hotel performance in several dimensions, including attracting more visitors to the hotel and the area, increasing tourism revenue for local businesses and contributing to the broader societal goal of reducing environmental impact and promoting sustainability.

This article adopts a guest-centered methodology to provide valuable insights for hotel managers to leverage interior design as a tool for innovation in the hospitality industry after showing that interior design enhances guests' experiences, comfort and hotel differentiation.

Joint ventures (JVs) are known to create value for their parent firms, in part due to the mutually beneficial sharing of information that occurs at the JV level. Market orientation (MO) is a well-documented strategic orientation that has received little attention in the JV literature, despite considerable research suggesting that MO has a positive effect on performance. This study posits that the MO skills contributed to a new JV by parent firms are likely to play a central role in a shareholder's assessment of the potential for success of a newly announced JV, thereby triggering changes in market value for parent firms.

Computer-Assisted-Text-Analysis (CATA) is used to calculate MO heterogeneity from annual reports, and event-study methodology is used to assess parent firm performance. The authors rely on a US sample of 82 public JV parents involved in 41 new equally-weighted JV formation announcements.

The authors find that heterogeneity on MO's behavioral components (customer orientation, competitor orientation, and coordination) is negatively related to parent performance, while heterogeneity on MO's profitability component is positively related to parent performance. However, the effect of MO's long-term focus heterogeneity on parent performance was not supported.

The results suggest that the benefits of information sharing in partnerships may be of a nuanced nature when it comes to MO. Although heterogeneity in profitability inclination created value for parent firms announcing a new JV; heterogeneity in customer, competitor and coordination market orientations did not appear to be rewarded by shareholders.