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This paper expands upon existing sports sponsorship 'match-up' research by offering an interview-driven, empirically-grounded, 'thick' description of the decision-making processes of sports organisations in developing athlete-sponsor-team relationships. By focusing on a particular NASCAR (The National Association for Stock Car Auto Racing) organisation (BAM Racing), the study offers an in-depth interpretation of the sometimes 'messy' methods employed by executives in grafting an effective, synergistic match-up. The paper concludes with a discussion on the theoretical and practical implications of these findings.

The purpose of this study was to examine the dimensions of athletic star power associated with Generation Y sports consumption. Multivariate analyses revealed that athletic star power factors (Professional Trustworthiness, Likeable Personality, Athletic Expertise, Social Attractiveness and Characteristic Style) were positively (p < .05) predictive of the sport consumption factors (Event Consumption and Merchandise Consumption).

Despite the use of plagiarism-checking software and current ethical guidelines in sport management journals, raising awareness of ethical concerns and potential risks of artificial intelligence (AI) applications is necessary. This paper discusses how AI affects ethical research and publishing and provides guidelines for sport management scholars to ensure quality and integrity of their research.

A comprehensive review and critical analysis of literature was performed to evaluate research ethics, potential risks, and guiding principles for the use of AI in research.

Ethical research guidelines for quantitative sport management research were proposed. The guidelines encompass seven principles for the proper use of AI and ethical conduct specific to the research methods, data analysis, and results, which would be challenging for AI to accurately replicate.

This study provides an original contribution to the field of sport management because numerous questions concerning ethics and AI have not been addressed until now. The guidelines are suitable for use by sport management scholars, concerning the accuracy, validity, and quality of research while mitigating ethical risks in AI-generated content.

This paper aims to determine if single-item (SI) needs' and values' measures have similar reliability and validity values to multi-item (MI) measures of the same constructs and thus could be substituted by sport marketers to predict internal motivating aspects of sport consumer attitudes and behavior. In addition, the authors wish to determine whether a small subset of needs and values listed in current measures are sufficient to predict sport consumer attitudes and behavior.

In this two-study design, the first study was a national sample (N = 439) comparing reliability and validity of single-item scales to multi-item scales. In the second study the authors collected data from fans and spectators of four different teams (N1 = 583; N2 = 1164; N3 = 213; N4 = 404) to determine the impact of needs and values on sport consumer attitudes and behavior.

The authors determined that in 89% of the scales, single-item measures of needs and values were just as reliable and valid as their associated multi-item measures. The authors also found that a small subset of the needs and values explain a meaningful amount of variance in sport consumer attitudes and behaviors.

The authors determined that in 89% of the scales, single-item measures of needs and values were just as reliable and valid as their associated multi-item measures. The authors also found that a small subset of the needs and values explain a meaningful amount of variance in sport consumer attitudes and behaviors.

The authors show that as motives for sport consumption, single-item measures of personal needs and values are equivalent to multi-item measures and not all needs and values used in previous sport research are necessary because they do not predict a meaningful amount of variance in sport consumer attitudes and behaviors. The authors identified a small number of single-item measures that practitioners can easily use in short surveys that will predict a statistically meaningful amount of variance in sport consumer attitudes and behaviors.

As a fixture in the mainstream media landscape, athletes, coaches, and sport celebrities are regularly used to promote products from sports equipment to high‐end watches. With an intrinsic connection between athlete endorsers and sport‐related products, it is the use of these endorsers to promote non‐sport products that raises questions about their appropriateness as a marketing tool. Therefore, the purpose of this study is to develop an explanatory model that analyzes athlete endorser effectiveness in promoting non‐sport products.

An holistic approach was taken, examining the structural relationships of identification with an athlete and his/her sport to product‐endorser congruency, perceived value, and purchase intentions, providing a preliminary overview of key socio‐psychological factors that may influence the purchase intentions of endorsed products.

This paper provides empirical insights about the effectiveness of athlete endorsers for non‐sport products. The result was a 42‐item, five factor model (i.e. Athlete Identification, Sport Identification, Match‐Up, Perceived Value, and Purchase Intention) that fit the data adequately well.

This model provides academicians with a synthesized review, and application of the various factors that play a role in athlete endorser selection and viability. This model serves as a framework for future analysis.

The paper includes a tactical approach that, when re‐evaluated, can provide a model to adapt and adopt in the selection of product or brand endorsers.

This paper fulfills an identified need to develop a model to test the oft adopted, yet highly risky, method of selecting an athlete to endorse products that do not have an intrinsic link to the sport in which he or she is employed.