Kevin K. Byon, Juha Yoon, Alex Gang, Juho Park and Paul M. Pedersen
The current study applied the concept of country image to a context of bilateral relations for two post-Soviet states to examine the impact of a mega sport event on the image of…
Abstract
Purpose
The current study applied the concept of country image to a context of bilateral relations for two post-Soviet states to examine the impact of a mega sport event on the image of the host country Russia.
Design/methodology/approach
Surveys were collected before and after the World Cup to assess any changes among Georgians with regard to their views on Russia and intentions to visit.
Findings
The results showed a significant change in Russia’s pre-perceived cognitive image related to reputation, respect and development, as well as the emotional aspect and overall country image after the mega sport event. Interestingly, the affective image of Russia carried more weight in shaping the overall country image compared to the cognitive aspects, suggesting the increasing importance of emotional perceptions over beliefs. However, despite these changes, the study found that mega sport events did not significantly moderate the association between country image and behavior intentions in the context of Russo-Georgian hostile bilateral relations.
Originality/value
This study is one of the first examinations of the impact of hosting mega sport events in countries with hostile bilateral ties. The findings support that mega sport events can be an effective mechanism to gain soft power in that such events can arouse changes in people’s emotions and feelings towards the host country, even for those living in a country with a hostile relationship with the host country. The scope of applicability of these findings can be extended to other contexts, including future hosts of mega sport events in their geo-political contexts.
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Juho Park, Junghwan Cho, Alex C. Gang, Hyun-Woo Lee and Paul M. Pedersen
This study aims to identify an automated machine learning algorithm with high accuracy that sport practitioners can use to identify the specific factors for predicting Major…
Abstract
Purpose
This study aims to identify an automated machine learning algorithm with high accuracy that sport practitioners can use to identify the specific factors for predicting Major League Baseball (MLB) attendance. Furthermore, by predicting spectators for each league (American League and National League) and division in MLB, the authors will identify the specific factors that increase accuracy, discuss them and provide implications for marketing strategies for academics and practitioners in sport.
Design/methodology/approach
This study used six years of daily MLB game data (2014–2019). All data were collected as predictors, such as game performance, weather and unemployment rate. Also, the attendance rate was obtained as an observation variable. The Random Forest, Lasso regression models and XGBoost were used to build the prediction model, and the analysis was conducted using Python 3.7.
Findings
The RMSE value was 0.14, and the R2 was 0.62 as a consequence of fine-tuning the tuning parameters of the XGBoost model, which had the best performance in forecasting the attendance rate. The most influential variables in the model are “Rank” of 0.247 and “Day of the week”, “Home team” and “Day/Night game” were shown as influential variables in order. The result was shown that the “Unemployment rate”, as a macroeconomic factor, has a value of 0.06 and weather factors were a total value of 0.147.
Originality/value
This research highlights unemployment rate as a determinant affecting MLB game attendance rates. Beyond contextual elements such as climate, the findings of this study underscore the significance of economic factors, particularly unemployment rates, necessitating further investigation into these factors to gain a more comprehensive understanding of game attendance.
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Jere Jokelainen, Brian Garrod, Erose Sthapit and Juho Pesonen
This study aims to examine the role of experiential familiarity in determining the competitiveness of hotel chains. It does so by comparing the attribute-performance perceptions…
Abstract
Purpose
This study aims to examine the role of experiential familiarity in determining the competitiveness of hotel chains. It does so by comparing the attribute-performance perceptions of guests who had and had not previously stayed at a property belonging to a specific hotel chain. It also examines how far such perceptions shape word-of-mouth and future purchase intentions.
Design/methodology/approach
Data were collected from 1,016 Finnish leisure tourists in 2021 using an online questionnaire, providing a representative sample of Finnish domestic leisure tourists.
Findings
The results indicate that the competitiveness of different hotel chains depends on a small number of key attributes. Differentiation between hotel chains can be seen from the results. Previous guests rate hotel chain attributes more highly than non-previous guests. Behavioral intentions do not differ between previous and non-previous guests, but how many times a person has stayed in the hotel chain significantly influences behavioral intentions. The results provide strategic levers that hotel chains can use to enhance their competitiveness.
Practical implications
Hotels should invest in attributes that have the biggest positive impact on customer behavior. These will be different for different hotel chains. By understanding these differences, it is possible to communicate relevant attributes to customers through marketing and develop hotel features that will drive revisit intention and word-of-mouth marketing.
Originality/value
This study found that while certain hotel attributes had a significant shaping effect on guests’ performance ratings, there were no decisive differences between those with or without experiential familiarity with the hotel chain.
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Nannan Xi, Juan Chen, Filipe Gama, Henry Korkeila and Juho Hamari
In recent years, there has been significant interest in adopting XR (extended reality) technologies such as VR (virtual reality) and AR (augmented reality), particularly in…
Abstract
Purpose
In recent years, there has been significant interest in adopting XR (extended reality) technologies such as VR (virtual reality) and AR (augmented reality), particularly in retail. However, extending activities through reality-mediation is still mostly believed to offer an inferior experience due to their shortcomings in usability, wearability, graphical fidelity, etc. This study aims to address the research gap by experimentally examining the acceptance of metaverse shopping.
Design/methodology/approach
This study conducts a 2 (VR: with vs. without) × 2 (AR: with vs. without) between-subjects laboratory experiment involving 157 participants in simulated daily shopping environments. This study builds a physical brick-and-mortar store at the campus and stocked it with approximately 600 products with accompanying product information and pricing. The XR devices and a 3D laser scanner were used in constructing the three XR shopping conditions.
Findings
Results indicate that XR can offer an experience comparable to, or even surpassing, traditional shopping in terms of its instrumental and hedonic aspects, regardless of a slightly reduced perception of usability. AR negatively affected perceived ease of use, while VR significantly increased perceived enjoyment. It is surprising that the lower perceived ease of use appeared to be disconnected from the attitude toward metaverse shopping.
Originality/value
This study provides important experimental evidence on the acceptance of XR shopping, and the finding that low perceived ease of use may not always be detrimental adds to the theory of technology adoption as a whole. Additionally, it provides an important reference point for future randomized controlled studies exploring the effects of technology on adoption.
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Henriikka Vartiainen, Teemu Valtonen, Juho Kahila and Matti Tedre
In 2022 generative AI took the Internet world by storm. Free access to tools that can generate text and images that pass for human creations triggered fiery debates about the…
Abstract
Purpose
In 2022 generative AI took the Internet world by storm. Free access to tools that can generate text and images that pass for human creations triggered fiery debates about the potential uses and misuses of generative AI in education. There has risen a need to check the popular utopian and dystopian narratives about AI against the diversity of hopes, concerns and future imaginaries that educators themselves associate with generative AI. The purpose of this study is to investigate the perspectives of Finnish teacher educators on the use of AI in education.
Design/methodology/approach
This article reports findings from a hands-on workshop in teacher training, where participants learned about how generative AI works, collaboratively explored generative AI and then reflected on its potential and challenges.
Findings
The results reveal nuanced, calm and thoughtful imaginaries rooted in deep understanding of educational policy, evaluation and the sociocultural context of education. The results cover teachers’ views on the impact of AI on learners’ agency, metacognition, self-regulation and more.
Originality/value
This article offers a unique exploration into the perceptions and imaginaries of educators regarding generative AI in specific (instead of “monolithic AI”), moving beyond dystopian views and instead focusing on the potential of AI to align with existing pedagogical practices. The educators contrasted the common techno-deterministic narratives and perceived AI as an avenue to support formative assessment practices and development of metacognition, self-regulation, responsibility and well-being. The novel insights also include the need for AI education that critically incorporates social and ethical viewpoints and fosters visions for a future with culturally, socially and environmentally sustainable AI.
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Xiao-Yu Xu, Syed Muhammad Usman Tayyab, Qingdan Jia and Albert H. Huang
Video game streaming (VGS) is emerging as an extremely popular, highly interactive, inordinately subscribed and very dynamic form of digital media. Incorporated environmental…
Abstract
Purpose
Video game streaming (VGS) is emerging as an extremely popular, highly interactive, inordinately subscribed and very dynamic form of digital media. Incorporated environmental elements, gratifications and user pre-existing attitudes in VGS, this paper presents the development of an extended model of uses and gratification theory (EUGT) for predicting users' behavior in novel technological context.
Design/methodology/approach
The proposed model was empirically tested in VGS context due to its popularity, interactivity and relevance. Data collected from 308 VGS users and structural equation modeling (SEM) was employed to assess the hypotheses. Multi-model comparison technique was used to assess the explanatory power of EUGT.
Findings
The findings confirmed three significant types elements in determining VGS viewers' engagement, including gratifications (e.g. involvement), environmental cues (e.g. medium appeal) and user predispositions (e.g. pre-existing attitudes). The results revealed that emerging technologies provide potential opportunities for new motives and gratifications, and highlighted the significant of pre-existing attitudes as a mediator in the gratification-uses link.
Originality/value
This study is one of its kind in tackling the criticism on UGT of considering media users too rational or active. The study achieved this objective by considering environmental impacts on user behavior which is largely ignored in recent UGT studies. Also, by incorporating users pre-existing attitudes into UGT framework, this study conceptualized and empirically verified the higher explanatory power of EUGT through a novel multi-modal approach in VGS. Compared to other rival models, EUGS provides a more robust explanation of users' behavior. The findings contribute to the literature of UGT, VGS and users' engagement.