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As artificial intelligence (AI) continues to influence sports league and team operations, the brands providing these services are sponsoring sports properties to demonstrate and communicate their performance capabilities. This article examines Amazon Web Services (AWS) sponsorship with the National Football League (NFL). This sponsorship features functional congruence, which is when a sponsor has a participatory role in performing services for the property.

The AWS sponsorship with the NFL is captured by examining specially created websites, in-game sponsored elements, and television commercials aired during the broadcast of NFL games. The AWS website focuses on the services profiled in this article.

AWS provides the NFL with performance-based (on-the-field) and business-based (off-the-field) services. Of particular note, AWS capabilities help the NFL create the game schedule and address the issue of player health and safety. Demonstrating functional congruence appears to be especially valuable in business-to-business marketing where purchase decisions are more focused on brand reliability. AWS television commercials feature the tagline, “if AWS can do this for the NFL, imagine what it can do for your business.”

With the role of AI in sports in its relative infancy, it is imperative to document what services AI brands are performing for a professional sports league. Examining AWS sponsorship with the NFL provides a timely, practical example of how an AI brand communicates and positions itself using sponsorship as a marketing strategy.

This paper aims to review the latest management developments across the globe and pinpoint practical implications from cutting-edge research and case studies.

This briefing is prepared by an independent writer who adds their own impartial comments and places the articles in context.

This paper identified that artificial intelligence (AI) can be incorporated into the National Football League (NFL) to produce valuable data and information for decision making. It also explored the wider applications that AI has to offer.

The briefing saves busy executives, strategists and researchers hours of reading time by selecting only the very best, most pertinent information and presenting it in a condensed and easy-to-digest format.

Following the triple helix (TH) model and the way knowledge is transferred into the industry domain, this chapter aims to define features interface that should be implemented in order to facilitate the University–Industry (UI) relationship and thus encourage the spin-off creation.

In order to support this relationship, a new business model configuration of an entrepreneurial ecosystem is proposed, aiming at creating a sustainable environment, where business entities can grow. The field of the Governance of Entrepreneurial Ecosystems is also investigated in order to define a framework for launching, developing, and sustaining a company over time.

This chapter presents a case study developed within the University of Salento (Italy). It capitalizes results from three different research analyses, based on questionnaires and interviews with actors of the spin-off network (professors and researchers, graduating students, admin-tech staff of the Technology Transfer Office, spin-offs’ CEOs/Associates, and R&D managers of external companies) and on results coming from scientific publications and regional/national reports in the innovation context.

A research methodology based on semantic network analysis and sentiment analysis has been applied in order to identify which features an interface should implement in order to facilitate the UI relationship and encourage the spin-off creation.

To support the start-up overcoming the “death valley,” the creation of a link between the strategy used to transfer value to the market and the phase of innovation is proposed inside the business model configuration. Some aspects of a governance model of an entrepreneurial ecosystem were also presented in order to support the business evolution of a single business entity and assuring sustainability over time.

Intellectual capital disclosure (ICD) in universities is gaining increasing attention, especially through the adoption of innovative technologies. Online media, as a relevant source of Big Data, is shifting ICD. The purpose of this paper is to explore how Big Data generated through online media, such as websites and platforms like Facebook, can be used as rich sources of data and viable disclosure channels for ICD in a university.

This is an exploratory case study, following the methodology in Yin (2014), that examines how online media data contributes to closing the ICD gap. The IC disclosed through different online media channels by a private university in Albania is analysed using Secundo et al.’s (2016) collective intelligence framework. The online data sources include the university’s website, Facebook page, periodic reports and statements outlining future goals.

What the authors discover in this research is that IC is an important part of how universities operate, and IC is communicated through social media, although unintentionally. However, this only serves to highlight the importance of IC, and if researchers want to discover IC and understand how it works in an organisation, they need to include social media and a prime resource for developing that understanding.

Most importantly, the findings add to a growing consensus that ICD researchers, and researchers in other management and accounting disciplines, who traditionally rely on annual corporate social responsibility and other periodic reports, they need to change their medium of analysis because these reports no longer can be relied on to understand IC and its impact on an organisation.

Online media tools and the advent of Big Data have created new opportunities for universities to disclose their IC information to stakeholders in a timely manner and to gain relevant insights into their impact on the society. The originality of the paper resides in the contribution of Big Data to the ICD research stream.

A persistent theme throughout the history of the Communication, Information Technologies, and Media Section of the American Sociological Association (CITAMS, formerly CITASA) has been that the work of section members has been underrepresented in sociology’s leading journals. This chapter empirically examines that claim, using data from the newly created American Sociological Review (ASR) Digital Archive, a collection of all manuscripts, published and unpublished, submitted to ASR between 1990 and 2010, along with all reviews of these manuscripts. Analyses in the chapter focus on a comparison of CITAMS and Methodology Section members’ participation in the ASR process as a manuscript author or reviewer. The findings of this chapter show that controlling for differences in the gender and age composition of the two sections, CITAMS members are significantly less likely than Methodology Section members to participate in the ASR publication process. This pattern is evident not only in the degree to which CITAMS members are asked to review papers, but also in the frequency with which they submit to ASR. Further analyses in the chapter look at membership in multiple sections and the possibilities for innovative collaboration. Increasing CITAMS involvement in the ASR publication process and amplifying the section’s voice in the discipline’s flagship journal may begin with more CITAMS members submitting manuscripts to ASR and collaborating with sociologists affiliated with other ASA sections.

This paper aims to investigate the evolution, roots and influence of the rural entrepreneurship literature.

Using a bibliometric exercise, the analysis starts with investigation of studies on entrepreneurship and gathering all (772) articles on rural entrepreneurship (from 1981 to 2020) found in both Scopus and Web of Science up to 15 August 2020. Citation analysis of the references/citations of 755 articles are listed in the abstract database, generating a citation database involving 46,432 references/citations. This paper considers 635 (out of the 772) articles on rural entrepreneurship (i.e. articles cited in one or more studies), generating a database of 10,767 studies influenced by the rural entrepreneurship literature.

This study discovers that the relative importance of rural entrepreneurship within the entrepreneurship literature has increased in the last few years, but rural entrepreneurship remains a European concern; the most frequently addressed topics include growth and development, institutional frameworks and governance and rurality, with theory building being rather understudied. Most of the studies on rural entrepreneurship are empirical, involving mainly qualitative analyses and targeting high income countries; rural entrepreneurship is rooted in the fields of economics and entrepreneurship and is relatively self-referential.

This study provides a comprehensive and updated investigation of evolution of the rural entrepreneurship literature. The assessment of the literature’s scientific roots of rural entrepreneurship had not yet been tackled before. To the best of the author’s knowledge this study can be considered as the first effort for identifying the scientific influence of the rural entrepreneurship literature.

Online social networks are increasingly important venues for businesses to promote their products and image. However, information propagation in online social networks is significantly more complicated compared to traditional transmission media such as newspaper, radio, and television. In this chapter, we will discuss research on modeling and forecasting diffusion of virally marketed content in social networks. Important aspects include the content and its presentation, the network topology, and transmission dynamics. Theoretical models, algorithms, and case studies of viral marketing will be explored.