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In the age of nine-figure transfer fees and football stars building their own brands and follower base, a shift in fan identification in football appears to be taking place as athletes can build strong connections with their followers. This paper examines the level of identification shown by football fans towards both their favourite team and their favourite player, in connection with the concept of fan loyalty.

A total of 4,707 international respondents participated in an online survey to examine the relationship between fan identification and fan loyalty, and to measure the impact of variables like country, player, club, on fan identification using multi-regression analyses.

The results underline the strong presence of team identification compared to identification of single players. Results have also revealed that the relationship between a fan's favourite team and player has a significant impact on identification levels towards both actors. Fans supporting a foreign club were found to show significantly stronger team identification than those who support a club from their own country or region.

This research contributes to the growing body of publications in the field of sports consumer research and underlines the importance of understanding the quality of relationships and thus the identification of fans with clubs and individual players for the stakeholders involved. International sports marketing is becoming increasingly important and an understanding of fan interests is essential for effective marketing, as information on trends in fan interests enables a more tailored strategy for clubs and sponsors.

Although businesses continue to take up artificial intelligence (AI), concerns remain that companies are not realising the full value of their investments. The study aims to provide insights into how AI creates business value by investigating the mediating role of Business Process Management (BPM) capabilities.

The integrative model of IT Business Value was contextualised, and structural equation modelling was applied to validate the proposed serial multiple mediation model using a sample of 448 organisations based in the EU.

The results validate the proposed serial multiple mediation model according to which AI adoption increases organisational performance through decision-making and business process performance. Process automation, organisational learning and process innovation are significant complementary partial mediators, thereby shedding light on how AI creates business value.

In pursuing a complex nomological framework, multiple perspectives on realising business value from AI investments were incorporated. Several moderators presenting complementary organisational resources (e.g. culture, digital maturity, BPM maturity) could be included to identify behaviour in more complex relationships. The ethical and moral issues surrounding AI and its use could also be examined.

The provided insights can help guide organisations towards the most promising AI activities of process automation with AI-enabled decision-making, organisational learning and process innovation to yield business value.

While previous research assumed a moderated relationship, this study extends the growing literature on AI business value by empirically investigating a comprehensive nomological network that links AI adoption to organisational performance in a BPM setting.

The purpose of this study is to address United Nations’ sustainable development goals (SDGs) 8 and 9 from a service perspective. SDG 8 is a call to improve the dignity of service work by enhancing wages, working conditions and development opportunities while SDG 9 calls upon nations to construct resilient infrastructures, promote inclusivity and sustainability and foster innovation.

This study uses a bibliometric review to extract important themes from a variety of scholarly journals.

Researchers tend to investigate policy-level topics, such as national and international standards related to working conditions, while ignoring the experiences or well-being of workers occupying marginalized and low-opportunity roles in service organizations. Service researchers, educators and practitioners must collaborate to improve the state of service industries by conducting participatory action research, promoting grassroots organizing/advocacy, implementing digitized customer service and addressing workforce soft skills deficiencies.

The authors consider how service work can be transformed into respectable employment and present four specific ways nations can enhance their service industries.

Economic planners can view SDGs 8 and 9 as a framework for understanding and promoting the well-being of service employees and accelerating the productivity and innovation levels of the service sector.

The United Nations’ SDGs are examined from a services perspective, which increases their significance in service-dominated economies.

This study aims to analyze the factors affecting tea-producing farmers' intention to use e-commerce exchanges (ECEs) to sell their products, combining the technology acceptance model (TAM) theory and barrier factors.

The authors use the generalized structural equation modeling (GSEM) to analyze the intermediate model that is built on TAM.

Research results show that perceived usefulness (PU) and perceived ease of use (PEU) significantly influence farmers' intention to use ECEs to sell their products. However, knowledge and information barriers hinder farmers' intention to use such ECEs.

Encouraging farmers to use ECEs is the most helpful solution for agricultural economic development in the context of the Covid-19 pandemic.

From an academic perspective, this is the first study that combines the TAM theory of Davis (1989) and barrier factors to analyze farmers' intention to use ECEs. The findings are valuable references for policymakers to propose strategies for agricultural economic development during the current pandemic. At the same time, the empirical results obtained from this study provide good orientations for agricultural economic development 4.0 in the future.