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1 – 10 of over 2000Zsolt Havran, Attila Kajos and Bálint Mazzag
The environmental characteristics of international football can vary significantly from one country to another. As a result, the economic and market possibilities and the…
Abstract
Purpose
The environmental characteristics of international football can vary significantly from one country to another. As a result, the economic and market possibilities and the objectives of each national league are very heterogeneous. This article aims to examine the differences in revenue structures amongst European national football leagues (n = 50) and cluster them based on these structures. It also investigates which revenue structure would be more effective for similar leagues, considering the previously mentioned varying environmental characteristics of international football.
Design/methodology/approach
The study utilises a theoretical framework of business modelling, applied in a unique way to league organisers of national championships. Data on sports and business aspects were collected from sources such as the Union of European Football Associations (UEFA) Financial Benchmarking Reports, transfermarkt.de and related sources for the period 2015 to 2018. K-means cluster analysis, using the Euclidean distance approach, was employed to develop clusters based on revenue sources over a four-year average.
Findings
The paper presents the characteristics and year-to-year changes of nine developed clusters. Throughout the analysis, variables such as average overpayment and inequality between player values amongst leagues were prioritised. The study's practical implications can assist league organisers in enhancing the competitiveness of their leagues, supported by short case studies that provide illustrative examples.
Originality/value
The novelty of the current article lies in introducing innovative variables such as the variance of player value whilst focussing on meso-level analysis, providing a fresh contribution to the existing literature in the field for understanding revenue structures and performance in European national football leagues.
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Xin-Zhou Qi, Eric Ping Hung Li, Zhuangyu Wei and Zhong Ning
This study examines the impact of university science parks’ (USPs) capabilities on revenue generation and introduces regional innovation as a moderating variable. This study aims…
Abstract
Purpose
This study examines the impact of university science parks’ (USPs) capabilities on revenue generation and introduces regional innovation as a moderating variable. This study aims to provide insights into enhancing revenue generation and fully leveraging the role of USPs in promoting revenue generation.
Design/methodology/approach
This study employs system generalized method of moments (GMM) estimation for 116 universities in China from 2008 to 2020, using hierarchical regression analysis to examine the relationships between variables.
Findings
The findings suggest that USPs play a beneficial role in fostering revenue generation. Specifically, the provision of incubation funding demonstrates a positive correlation, while USPs size exhibits an inverted U-shaped pattern, with a threshold at 3.037 and a mean value of 3.712, highlighting the prevalent issue of suboptimal personnel allocation in the majority of USPs. Moreover, the analysis underscores the critical moderating influence of regional innovation, affecting the intricate interplay between USPs size, incubation funding and revenue generation.
Research limitations/implications
The single country (China) analysis relied solely on the use of secondary data. Future studies could expand the scope to include other countries and employ primary data collection. For instance, future research can further examine how regional development and USPs strategic plan impact revenue generation.
Practical implications
The study recommends that USPs managers and policymakers recognize the importance of incubation funding and determine the optimal quantity of USPs size to effectively foster revenue generation in USPs. Policymakers can use regional innovation as a moderating variable to reinforce the relationship between USPs size and incubation funding on revenue generation.
Social implications
The study’s findings can contribute to the strategic industry growth and economic development of nations by promoting revenue generation. Leveraging the role of USPs and implementing the study’s recommendations can strengthen innovation and technology capabilities, driving strategic industry growth and economic development. This can enhance global competitiveness and promote sustainable economic growth.
Originality/value
This study introduces regional innovation as a moderating variable and provides empirical evidence of its influence on the relationship between USPs size and incubation funding on revenue generation. This adds value to research to the existing literature on USPs and revenue generation by showcasing the importance of examining the regional impact in research and innovation.
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Ajid ur Rehman, Asad Yaqub, Tanveer Ahsan and Zia-ur-Rehman Rao
This study aims to investigate earnings management practice of classification shifting of revenues in Chinese-listed firms.
Abstract
Purpose
This study aims to investigate earnings management practice of classification shifting of revenues in Chinese-listed firms.
Design/methodology/approach
The study employs a dataset of 2,920 A-listed firms from Chinese stock exchanges of Shanghai and Shenzhen for the period of 2003–2019. We apply both univariate and panel regression analysis by using fixed effect estimation with robust standard errors.
Findings
Our findings reveal that firms misclassify revenues by taking advantage of the flexibility provided by applicable financial reporting standards. The empirical evidence obtained through regression analysis suggest that managers reclassify non-operating revenues as operating revenue to alter the economic reality while seeking the advantage of financial reports users’ vulnerability for valuing the upper half of income statement items more as compared to lower part. The results further indicate that international financial reporting standards adoption inhibits the earnings management practices using classification shifting of revenues. It is also concluded that firms, which are suffering losses or having low growth, are more persistently involved in misclassification of revenues.
Originality/value
The study is unique from the point of view that it investigates earnings management from the prospective of revenue’s classification in an emerging market characterized by various market imperfections such as lower investor protection and higher information asymmetry.
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Tyler Skinner, Steven Salaga and Matthew Juravich
Using the lens of upper echelons theory, this study examines the degree to which National Collegiate Athletic Association athletic department performance outcomes are associated…
Abstract
Purpose
Using the lens of upper echelons theory, this study examines the degree to which National Collegiate Athletic Association athletic department performance outcomes are associated with the personal characteristics and experiences of the athletic director leading the organization.
Design/methodology/approach
The authors match organizational performance data with athletic director and institutional characteristics to form a robust data set spanning 16 years from the 2003–04 to 2018–19 seasons. The sample contains 811 observations representing 136 unique athletic directors. Fixed effects panel regressions are used to analyze organizational performance and quantile regression is used to analyze organizational revenues.
Findings
The authors fail to uncover statistically significant evidence that athletic director personal characteristics, functional experience and technical experience are associated with organizational performance. Rather, the empirical modeling indicates organizational performance is primarily driven by differentiation in the ability to acquire human capital (i.e. playing talent). The results also indicate that on average, women are more likely to lead lower revenue organizations, however, prior industry-specific technical experience offsets this relationship.
Originality/value
In opposition to upper echelons research in numerous settings, the modeling indicates the personal characteristics and experiences of the organization's lead executive are not an economically relevant determinant of organizational performance. This may indicate college athletics is a boundary condition in the applicability of upper echelons theory.
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Armin Saadatian and Svetlana Olbina
The retail sector has the largest energy consumption among commercial buildings in the U.S. Although previous studies explored benefits, barriers and solutions for implementing…
Abstract
Purpose
The retail sector has the largest energy consumption among commercial buildings in the U.S. Although previous studies explored benefits, barriers and solutions for implementing sustainability in various building sectors, research focused on retail facilities has been very scarce. This study aims to explore U.S. facilities managers’ perceptions of barriers that prevented the implementation of energy-efficiency practices in the retail sector. Their perceptions were compared by facility size and facilities management company’s business revenue.
Design/methodology/approach
An online survey was distributed to the members of the International Facility Management Association and the author's LinkedIn network. The survey responses were analyzed using descriptive statistical analysis and ANOVA.
Findings
Managers from large facilities, as opposed to those from small ones, significantly more agreed that the unavailability of building automation systems, a lack of professional writing skills and a lack of awareness of life cycle cost (LCC) were the barriers. Business revenue did not cause significantly different perceptions of the barriers except for a lack of awareness of LCC and a lack of support from upper management.
Originality/value
This study fills the research gap on energy efficiency in the retail sector by revealing U.S. facilities managers’ perceptions of the barriers to the implementation of energy-efficiency practices in retail stores. This novel study compares perceptions of the facilities managers by facility size and business revenue; this comparison has not been performed before. The study also identified several new barriers to the implementation of energy efficiency in the retail sector.
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Fatemeh Binesh, Amanda Mapel Belarmino, Jean-Pierre van der Rest, Ashok K. Singh and Carola Raab
This study aims to propose a risk-induced game theoretic forecasting model to predict average daily rate (ADR) under COVID-19, using an advanced recurrent neural network.
Abstract
Purpose
This study aims to propose a risk-induced game theoretic forecasting model to predict average daily rate (ADR) under COVID-19, using an advanced recurrent neural network.
Design/methodology/approach
Using three data sets from upper-midscale hotels in three locations (i.e. urban, interstate and suburb), from January 1, 2018, to August 31, 2020, three long-term, short-term memory (LSTM) models were evaluated against five traditional forecasting models.
Findings
The models proposed in this study outperform traditional methods, such that the simplest LSTM model is more accurate than most of the benchmark models in two of the three tested hotels. In particular, the results show that traditional methods are inefficient in hotels with rapid fluctuations of demand and ADR, as observed during the pandemic. In contrast, LSTM models perform more accurately for these hotels.
Research limitations/implications
This study is limited by its use of American data and data from midscale hotels as well as only predicting ADR.
Practical implications
This study produced a reliable, accurate forecasting model considering risk and competitor behavior.
Theoretical implications
This paper extends the application of game theory principles to ADR forecasting and combines it with the concept of risk for forecasting during uncertain times.
Originality/value
This study is the first study, to the best of the authors’ knowledge, to use actual hotel data from the COVID-19 pandemic to determine an appropriate neural network forecasting method for times of uncertainty. The application of Shapley value and operational risk obtained a game-theoretic property-level model, which fits best.
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The purpose of this study was to gather insights from sport marketing professionals and identify key opportunities, challenges and knowledge that sport marketing educators and…
Abstract
Purpose
The purpose of this study was to gather insights from sport marketing professionals and identify key opportunities, challenges and knowledge that sport marketing educators and researchers could utilize in developing curriculum and research agendas.
Design/methodology/approach
A qualitative approach was used, and data were collected through in-depth interviews with 15 sport marketing professionals. Participants were asked questions related to the knowledge, skills and experiences that they believe are important for students to have to be successful in the industry, as well as the types of research that would be most useful in their day-to-day work.
Findings
Industry professionals noted collaboration, transformation in digital marketing, data and analytics and experiential marketing as key trends facing the industry today. The findings suggest that sport marketing curriculum should focus on soft skill development such as communication, relationship building and empathy alongside hard skill development such as data analysis and storytelling. As well, findings show research areas where scholars can aid practitioners with a focus on consumer insights, technology, measuring ROI and experiential marketing.
Originality/value
With these findings, educators and scholars can better prepare students for successful careers in industry and contribute to the ongoing advancement of the scholarly field. This study serves as a starting point for further research in this area, and it is hoped that it will spark continued collaboration between academia and industry.
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Ramya Ravi and Manthan D. Janodia
Protection of intellectual property (IP) is important to leverage its commercial potential. This study aims to examine and comprehend the level of understanding of intellectual…
Abstract
Purpose
Protection of intellectual property (IP) is important to leverage its commercial potential. This study aims to examine and comprehend the level of understanding of intellectual property rights (IPR) among Indian academics. The study covers three main aspects – awareness level of IP among Indian academics, comprehending if the current state of knowledge about IP is useful for commercialization and whether the current knowledge of IP activities among Indian academics is sufficient to support their professional career and generate revenues from their inventions.
Design/methodology/approach
A structured methodology was contemplated and applied. A cross-sectional study with a convenience sampling method was adopted. The duration of the study was six months from March to August 2021. A total of 500 Indian academics were approached, of which 116 responded with a response rate of 23.4%. A structured questionnaire was administered to the participants to understand their level of knowledge about IP. Furthermore, the data analysis was performed based on descriptive analysis.
Findings
The study findings revealed that the awareness among the participants about IP was minimal. The underlying reasons could be academics did not focus on generating IP through novel research, awareness of basic knowledge about IP was considerably low and inadequate to support their professional career, primary focus was on which publications are considered as one of the important criteria for performance management, national policies do not encourage collaborative research between university and industry that may lead to potential IP generation and the Indian academic set-up expects multitasking by its faculty members.
Originality/value
To the best of the authors’ knowledge, this paper is an original contribution, based on the study carried out by the authors to understand the awareness of IP activities among Indian academics.
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XiaoXi Wu, Jinlian Shi and Haitao Xiong
This paper aims to analyze the research highlights, evolutionary process and future research directions in the field of tourism forecasting.
Abstract
Purpose
This paper aims to analyze the research highlights, evolutionary process and future research directions in the field of tourism forecasting.
Design/methodology/approach
This study used CiteSpace to conduct a bibliometric analysis of 1,213 tourism forecasting articles.
Findings
The results show that tourism forecasting research has experienced three stages. The institutional collaboration includes transnational collaboration and domestic institutional collaboration. Collaboration between countries still needs to be strengthened. The authors’ collaboration is mainly based on on-campus collaboration. Articles with high co-citation are primarily published in core tourism journals and other relevant publications. The research content mainly pertains to tourism demand, revenue management, hotel demand and tourist volumes. Ex ante forecasting during the COVID-19 pandemic has broadened existing tourism forecasting research. The future forecasting research focuses on the rational use of big data, improving the accuracy of models and enhancing the credibility of forecasting results.
Originality/value
This paper uses CiteSpace to analyze tourism forecasting articles to obtain future research trends, which supplements existing research and provides directions for future research.
意图
本文旨在分析旅游预测领域的研究重点、演化过程和未来的研究方向。
设计/理论/方法
本研究使用 CiteSpace 软件对 1213 篇旅游预测文章进行了文 献计量学分析。
结果
结果表明, 旅游预测研究经历三个阶段。机构合作包含国际机构合作和 国内机构合作, 需要持续加强国家之间的合作, 作者之间的合作多以校内合作为 主。高引用文章不仅发表在旅游领域的核心期刊还发表在其他专业的核心期刊上。 旅游预测研究的主要内容为旅游需求、收入管理、酒店需求和游客量。新冠疫情 期间的事前预测拓宽了现有的旅游预测研究。未来预测的研究重点在于合理利用 大数据, 提高模型的准确定以及提高预测结果的可信度。
创意/价值
本文使用 CiteSpace 分析旅游预测文章得到未来研究趋势, 既是对 现有研究的补充, 又为今后的研究提供方向。
Objetivo
Este artículo pretende analizar los aspectos más destacados de la investigación, el proceso evolutivo y las futuras orientaciones de la investigación en el campo de la previsión turística.
Diseño/metodología/enfoque
Este estudio utilizó CiteSpace para realizar un análisis bibliométrico de 1213 artículos sobre previsión turística.
Resultados
Los resultados muestran que la investigación sobre previsión turística ha experimentado tres etapas. La colaboración institucional incluye la colaboración transnacional y la colaboración institucional nacional. La colaboración entre países aún debe reforzarse. La colaboración entre autores se basa principalmente en la colaboración dentro del campus. Los artículos con una alta cocitación se publican principalmente en las principales revistas de turismo y en otras publicaciones relevantes. El contenido de la investigación se refiere principalmente a la demanda turística, el revenue management, la demanda hotelera y los volúmenes turísticos. La previsión previa y durante la pandemia de la COVID-19 ha ampliado la investigación existente sobre previsión turística. La futura investigación sobre previsiones se centra en el uso racional de los big data, la mejora de la precisión de los modelos y el aumento de la credibilidad de los resultados de las previsiones.
Originalidad/valor
Este artículo utiliza CiteSpace para analizar artículos de previsión turística con el fin de obtener futuras tendencias de investigación, lo que complementa la investigación existente y proporciona orientaciones para futuras investigaciones.
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Tianyu Pan, Rachel J.C. Fu and James F. Petrick
This study aims to examine consumer perception during COVID-19 and identifies cruise industry marketing strategies to fill a gap in crisis management and product pricing…
Abstract
Purpose
This study aims to examine consumer perception during COVID-19 and identifies cruise industry marketing strategies to fill a gap in crisis management and product pricing literature.
Design/methodology/approach
This study developed and validated two-factor measurement scales (vaccine perception and protective behavior), which predicted cruise intents well. This study revealed how geo-regional factors affect consumer psychology through spatial analysis.
Findings
This study recommended pricing 7-day cruises at $1,464 (the most preferred length). The results also showed that future price hikes would not affect demand and that coastal marketing would help retain customers.
Originality/value
This study contributed to the business, hospitality and tourism literature by identifying two new and unique factors (vaccine perception and protective behaviors), which were found to affect consumers’ intention to travel by cruise significantly. The result provided a better understanding of cruise tourists’ pricing preferences and the methods utilized could easily be applied to other cruise markets or tourism entities.
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