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1 – 10 of 52Roberto Aprile, Mario Nicoliello and Susanne Durst
This conceptual paper proposes an intellectual capital (IC) framework dedicated to elite athletes (EA) to demonstrate the usefulness of IC on individual persons. Thus, it…
Abstract
Purpose
This conceptual paper proposes an intellectual capital (IC) framework dedicated to elite athletes (EA) to demonstrate the usefulness of IC on individual persons. Thus, it connects EA with the concept of IC.
Design/methodology/approach
The paper is inspired by the classical IC dimensions (human capital, structural capital and relational capital), which are used to develop the IC framework for EA. An exemplary case study is used to validate the framework.
Findings
It is argued that there is a need to adapt the traditional IC framework for EA. Therefore, this paper proposes a specific IC framework consisting of natural capital, sports capital and media capital.
Research limitations/implications
This paper deals with EA and the sports industry, but should be extended to other sectors where aspects such as image and celebrity represent significant intangible resources.
Practical implications
The proposed IC framework can help EA and their managers to better understand how IC value is created.
Originality/value
This paper extends the IC concept to other fields of application, i.e. EA, and thus individual persons.
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Dominik Siemon and Jörn Wessels
The purpose of this paper is to use Twitter data to mine personality traits of basketball players to predict their performance in the National Basketball Association (NBA).
Abstract
Purpose
The purpose of this paper is to use Twitter data to mine personality traits of basketball players to predict their performance in the National Basketball Association (NBA).
Design/methodology/approach
Automated personality mining and robotic process automation were used to gather data (player statistics and big five personality traits) of n = 185 professional basketball players. Correlation analysis and multiple linear regressions were computed to predict the performance of their NBA careers based on previous college performance and personality traits.
Findings
Automated personality mining of Tweets can be used to gather additional information about basketball players. Extraversion, agreeableness and conscientiousness correlate with basketball performance and can be used, in combination with previous game statistics, to predict future performance.
Originality/value
The study presents a novel approach to use automated personality mining of Twitter data as a predictor for future basketball performance. The contribution advances the understanding of the importance of personality for sports performance and the use of cognitive systems (automated personality mining) and the social media data for predictions. Scouts can use our findings to enhance their recruiting criteria in a multi-million dollar business, such as the NBA.
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Although previous studies have examined the influence of celebrity involvement in behavioural intentions, the role of celebrity dimensions such as attraction, self-expression and…
Abstract
Purpose
Although previous studies have examined the influence of celebrity involvement in behavioural intentions, the role of celebrity dimensions such as attraction, self-expression and centrality in influencing tourists’ intention in the context of developing countries such as Tanzania remains largely unaddressed. This study, therefore, examined the relationship between celebrity involvement and domestic tourists' intentions to visit tourist attractions, attitude being the mediating variable.
Design/methodology/approach
A questionnaire was self-administered on a convenient sample of 279 domestic tourists in the Tanzania’s four largest regions, namely, Dar es Salaam, Mbeya, Arusha and Mwanza. Employing a quantitative research approach, structural equation modelling was performed to test the cause-and-effect relationships between celebrity involvement and tourists’ intentions before testing the mediating role of attitude in such a relationship. Confirmatory factor analysis was also performed to test the measurement models.
Findings
Attraction emerged to be the main determinant of the celebrity dimension that significantly influenced domestic tourists’ travel intentions, whereas attitude partially mediates such a relationship. Moreover, Bongo Fleva musicians, particularly Diamond Platnumz, one of the leading celebrities in this genre, were found to influence most of the respondents’ travel intentions – he posted a picture on his Instagram account of him touring the Serengeti National Park.
Research limitations/implications
The study focused on domestic tourists residing in four of the Mainland Tanzania’s largest regions, hence excluding those residing on the islands of Unguja and Pemba. Due to cultural differences, including the islands not only could unleash new perspectives on celebrity involvement dimensions but also could have introduced new determinants of travel intentions.
Practical implications
This study offers guidance to tourism businesses on designing their marketing campaigns that they should harness celebrity’s attractive qualities effectively. The focus should be directed not only towards linking destinations with celebrities but also on stimulating positive perception of those destinations, aligning with the attitudes of their followers.
Social implications
The study has set out a new perspective for researchers, practitioners and tourism businesses to refine their promotional strategies and for academicians to gain a deeper understanding of visitor behavioural intention dynamics.
Originality/value
This study has proposed and verified that attraction is a dominant determinant compared to self-expression and centrality in explaining tourists’ travel intentions and attitudes, which play a significant role in explaining such a relationship. Although the study employed a modified theory of planned behaviour in a celebrity involvement study, the findings have broadened the understanding and its applicability in the context of a developing country.
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David Micallef, Lukas Parker, Linda Brennan, Bruno Schivinski and Michaela Jackson
This paper aims to understand the opportunities and challenges to engage emerging adult gamers (aged 18–25) in adopting healthier diet behaviours through online games and related…
Abstract
Purpose
This paper aims to understand the opportunities and challenges to engage emerging adult gamers (aged 18–25) in adopting healthier diet behaviours through online games and related platforms such as esports and streaming. The study uses a socio-ecological approach to understand influences and suggests approaches to changing behaviours.
Design/methodology/approach
Purposive and convenience sampling were used to identify (n = 13) online gaming industry professionals and emerging adult (EA) gamers for interview. Qualitative thematic analysis of data using NVivo was undertaken.
Findings
Bi-directional influences were found that are potentially impacting EA diet behaviours. Food industry advertising and sponsorships were identified as dominant influences within the behavioural ecology, using microcelebrities and esports events to target EAs. The study identifies a need for social marketers to engage EA gamers in healthful behaviours through interventions across various levels of the behavioural ecology, including those upstream with industry and potential government regulation, to promote better health and balance food marketing. It also identifies future research avenues for engaging gamers in good health.
Originality/value
To the best of the authors’ knowledge, this is the first study to explore the impact of the gaming behavioural ecology on EA diet behaviour. It identifies new channels that social marketers can use to engage EAs, who are difficult to reach through more traditional marketing channels.
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Euodia Vermeulen and Sara Grobbelaar
In this article we aim to understand how the network formed by fitness tracking devices and associated apps as a subset of the broader health-related Internet of things is capable…
Abstract
Purpose
In this article we aim to understand how the network formed by fitness tracking devices and associated apps as a subset of the broader health-related Internet of things is capable of spreading information.
Design/methodology/approach
The authors used a combination of a content analysis, network analysis, community detection and simulation. A sample of 922 health-related apps (including manufacturers' apps and developers) were collected through snowball sampling after an initial content analysis from a Google search for fitness tracking devices.
Findings
The network of fitness apps is disassortative with high-degree nodes connecting to low-degree nodes, follow a power-law degree distribution and present with low community structure. Information spreads faster through the network than an artificial small-world network and fastest when nodes with high degree centrality are the seeds.
Practical implications
This capability to spread information holds implications for both intended and unintended data sharing.
Originality/value
The analysis confirms and supports evidence of widespread mobility of data between fitness and health apps that were initially reported in earlier work and in addition provides evidence for the dynamic diffusion capability of the network based on its structure. The structure of the network enables the duality of the purpose of data sharing.
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