Suchergebnisse

We examined the underlying mechanisms of the association between the coach–athlete relationship and athlete engagement, with an emphasis on the mediating role of athletes??? life satisfaction. We conducted a cross-sectional survey among 272 athletes affiliated with a Chinese local
sports bureau. Participants completed a self-administered questionnaire and we employed structural equation modeling to analyze the data and examine the interrelationships among the coach–athlete relationship, life satisfaction, and athlete engagement. The findings revealed a positive
association between the coach–athlete relationship and athlete engagement, and further demonstrated that life satisfaction partially mediated this relationship. These results contribute to the existing body of knowledge by expanding on previous research and offering novel insights into
the impact of the coach–athlete relationship on athlete engagement.

Purpose
With the rise in wine consumption, accurate wine price forecasts have significantly impacted restaurant and hotel purchasing decisions and inventory management. This study aims to develop a precise and effective wine price point and interval forecasting model.


Design/methodology/approach
The proposed forecast model uses an improved hybrid kernel extreme learning machine with an attention mechanism and a multi-objective swarm intelligent optimization algorithm to produce more accurate price estimates. To the best of the authors' knowledge, this is the first attempt at applying artificial intelligence techniques to improve wine price prediction. Additionally, an effective method for predicting price intervals was constructed by leveraging the characteristics of the error distribution. This approach facilitates quantifying the uncertainty of wine price fluctuations, thus rendering decision-making by relevant practitioners more reliable and controllable.


Findings
The empirical findings indicated that the proposed forecast model provides accurate wine price predictions and reliable uncertainty analysis results. Compared with the benchmark models, the proposed model exhibited superiority in both one-step- and multi-step-ahead forecasts. Meanwhile, the model provides new evidence from artificial intelligence to explain wine prices and understand their driving factors.


Originality/value
This study is a pioneering attempt to evaluate the applicability and effectiveness of advanced artificial intelligence techniques in wine price forecasts. The proposed forecast model not only provides useful options for wine price forecasting but also introduces an innovative addition to existing forecasting research methods and literature.