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The creative process through which the territorial resources, knowledge and culture are used, exploited and configured to match needs and to achieve congruence with the changing business environment has become a crucial process for competitiveness. This is even more relevant for economies of developing countries which are continuously struggling to reap the benefits of globalisation, as well as to grasp the new opportunities for competitiveness. As such, this paper aims to try to concentrate on the dynamic perspectives of the creative economy of countries by distinguishing between the potentialities and performance. The paper tackles the influence that creativity capacities might have on performance of countries.

The methodology consists in identifying creative economy indicators from a diverse data set of the World Economic Forum and distinguish them between potential and performance indicators.

Data reveal as good progress and emphasis is being devoted to increasing the level of creativity; however, the Balkan countries still holdup in their capacity to boost innovation.

The paper provide a new focus of research on creativity measurement that is significant for understanding what creative capacities territories possess and the ability to make proficient use for growth and innovation.

This paper proposes a new operational framework for measuring and interpreting the creative economy indicators by identifying not only indicators that gauge the potentialities of a country, but also indicators that are linked with the performance dimension, as well as the relationship amongst them.

The purpose of this paper is to review and critique the knowledge management (KM) literature within Entrepreneurial universities, providing an overview of the state of research and outlining a future research agenda.

In a systematic literature review, 1106 articles indexed at Scopus were initially submitted to a bibliometric analysis. Finally, 150 papers published in a variety of academic journals specializing in the field of Entrepreneurship, KM and Higher Education were analyzed through a content and a bibliometric analysis to minimize mistakes in interpreting findings of collected studies.

KM within entrepreneurial university is a research area of growing importance. Findings show that literature on KM models and tools in the entrepreneurial university is fragmented and dominated by unrelated research. Content analysis shows heterogeneous literature, but four major research streams emerge: knowledge transfer in university–industry collaboration; knowledge creation in entrepreneurship education; KM processes for university spin-offs; entrepreneurial university to support knowledge-based regional development. The results show a failure to address the implications of findings for policy makers, which risks making KM in entrepreneurial universities research irrelevant.

Although different structured literature reviews (SLRs) exist separately in the field of KM and entrepreneurial universities, to the authors’ best knowledge, no studies exist in the intersection between the two fields.

The paper presents the first attempt to provide a comprehensive SLR of the articles dealing with models and processes of KM in the entrepreneurial university. Despite the increasing literature, this research area is still fragmented and undertheorized, thus requiring more systematic and holistic studies, considering both the economic and the social aspects of KM within universities. The paper’s findings can offer insights into future research avenues.

This paper aims to highlight how big social data (BSD) and analytics exploitation may help destination management organisations (DMOs) to understand tourist behaviours and destination experiences and images. Gathering data from two different sources, Flickr and Twitter, textual and visual contents are used to perform different analytics tasks to generate insights on tourist behaviour and the affective aspects of the destination image.

This work adopts a method based on a multimodal approach on BSD and analytics, considering multiple BSD sources, different analytics techniques on heterogeneous data types, to obtain complementary results on the Salento region (Italy) case study.

Results show that the generated insights allow DMOs to acquire new knowledge about discovery of unknown clusters of points of interest, identify trends and seasonal patterns of tourist demand, monitor topic and sentiment and identify attractive places. DMOs can exploit insights to address its needs in terms of decision support for the management and development of the destination, the enhancement of destination attractiveness, the shaping of new marketing and communication strategies and the planning of tourist demand within the destination.

The originality of this work is in the use of BSD and analytics techniques for giving DMOs specific insights on a destination in a deep and wide fashion. Collected data are used with a multimodal analytic approach to build tourist characteristics, images, attitudes and preferred destination attributes, which represent for DMOs a unique mean for problem-solving, decision-making, innovation and prediction.

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.

Recent figures show that users are discontinuing their usage of TripAdvisor, the leading user-generated content (UGC) platform in the tourism sector. Hence, it is relevant to study the factors that influence travelers’ continued use of TripAdvisor.

The authors have integrated constructs from the technology acceptance model, information systems (IS) continuance model and electronic word of mouth literature. They used PLS-SEM (smartPLS V.3.2.8) to test the hypotheses using data from 297 users of TripAdvisor recruited through Prolific.

Findings reveal that perceived ease of use, online consumer review (OCR) credibility and OCR usefulness have a positive impact on customer satisfaction, which ultimately leads to continuance intention of UGC platforms. Customer satisfaction mediates the effect of the independent variables on continuance intention.

Managers of UGC platforms (i.e. TripAdvisor) can benefit from the findings of this study. Specifically, they should improve the ease of use of their platforms by facilitating travelers’ information searches. Moreover, they should use signals to make credible and helpful content stand out from the crowd of reviews.

This is the first study that adopts the IS continuance model in the travel and tourism literature to research the factors influencing consumers’ continued use of travel-based UGC platforms. Moreover, the authors have extended this model by including new constructs that are particularly relevant to UGC platforms, such as performance heuristics and OCR credibility.

The wide development of digital platforms permitted the birth of new financing modalities, namely, crowdfunding, where the crowd of individuals and investors can supply the necessary financial resources for venture creation and growth. While the extant literature has focused on analyzing the dynamics and features of crowdfunding campaigns, few studies have focused on understanding how crowd investors decide which ventures to invest in and which factors influence their decision-making process. Due to this gap, the purpose of this paper is to analyze the factors influencing the choice to invest in an equity crowdfunding campaign, by defining a set of indicators useful to evaluate the risk of the campaign.

An empirical research study of Italian equity crowdfunding campaigns has been conducted to identify quantitative indicators useful for evaluating the risk in a crowdfunding campaign.

Findings demonstrate that the risk indicators proposed to represent important gauges that investors can usefully consider ex ante to assess the degree of riskiness of the investment in the equity crowdfunding campaign.

The limitations of the study regarding the size of the sample that is small due to the necessity to extract enough information in pre and post-equity campaigns. Also, the lack of historical data is another limitation.

The originality of the studies relies on the proposal of quantitative indicators for the evaluation of the risk in equity crowdfunding campaigns for “crowd” investors to reduce information asymmetries.

In the current scenario, cybersecurity issues have emerged to be a major challenge for firms to deal with. The increased use of technologies has increased radically the volume and typology of information produced, exchanged, and managed by firms thus creating conditions for cybersecurity incidents or information breaches. In this situation, it becomes paramount for firms to recognize cybersecurity risks and be prepared to prevent them through the implementation of approaches and technologies able to ensure a high level of protection.

In this chapter, we provide a framework for analyzing and managing cybersecurity risks. We employed a case study strategy to understand how the risk analysis process is carried out within an Information Security company. The study and observations obtained from this case study have permitted to define a framework useful for SME to deal with cybersecurity issues.

This study aims to examine the factors influencing tourists to share their travel experiences on social media (SM).

An online questionnaire was administered to 1,280 American travelers, and the data were analyzed using partial least squares structural equation modeling (PLS-SEM).

The PLS-SEM results indicated that non-participant sharing had a direct and positive effect on tourists’ tendencies to share their travel experiences on SM. Environmental, relational and security concerns had direct and negative effects on actual travel-experience sharing, whereas altruism, personal fulfillment and self-actualization had direct and positive effects on actual travel-experience sharing.

Travelers were found to attach importance to content shared on SM when they believed the content to be objective and reliable and were more likely to share such content on their own SM accounts. This finding suggests that tourist-created content is crucial. Tourism businesses, therefore, should reduce or eliminate inhibitory factors to increase content sharing. This research provides guidance for tourism businesses’ SM initiatives.

The study, first, contributes to an understanding of the factors affecting the sharing of travel experiences on SM. Second, this study develops a holistic approach that integrates the factors that might affect tourists’ SM content-sharing behavior into a single model.