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The purpose of this article is to explore the relationship between the attributes of Olympic mascots and their impact on sponsorship effectiveness. Based on a multiattribute model and the introduction of engagement theory and the meaning transfer model, this article uses the 2022 Beijing Winter Olympics mascot “Bing Dwen Dwen” as the research object to empirically analyze the effects and mechanisms of the mascot's attributes on preference, event engagement, sponsorship enterprise trust and sponsorship enterprise attitude, ultimately constructing a sponsorship effectiveness model.

The survey method was used to examine 238 respondents' emotions and attitudes towards companies participating in sponsoring Olympic mascots.

The study found that the main attributes of the mascot include visual and emotional factors, both of which have a positive impact on preference, with emotional factors having a greater influence than visual factors. Visual and emotional factors indirectly affect engagement through preference. Preference and engagement play a completely mediating role in the effect of mascot attributes on sponsorship enterprise trust and sponsorship enterprise attitude.

This study provides practical recommendations for managers to achieve marketing success in sports sponsorship through mascots.

This paper provides a measurement tool for the study of mascot attributes and important support for subsequent research in sponsorship marketing.

A humanoid intelligent robot (HIR) possessing a human-like appearance can undertake human jobs, interact, communicate and even transmit emotions to human beings. Such robots have gradually been integrated into people's daily life and production scenarios. However, it is unclear whether and by what mechanism HIRs can stimulate people’s risk perception and its impact on consumption attitudes. Based on the risk decision theory, this study aims to take the social value substitution attribute of a HIR as the incentive and analyzes the influence of social value substitution and risk perception on the customers’ consumption attitudes.

Three experiments were conducted to investigate the related questions about the social value substitution attribute of a HIR, its impact on risk perception and the customers’ consumption attitudes.

The results reveal that physical labor, intellectual labor, friendship, kinship and the ego constitute the hierarchical elements of social value substitution. Among them, physical labor and intellectual labor pertain to the dimension of social function value substitution, while friendship, kinship and ego pertain to the dimension of social presence value substitution; social function value substitution and social presence value substitution affect the subjects’ risk perception positively, but the latter arouses a stronger risk perception; the 2 (risk perception of social function value: security/danger) × 2 (risk perception of social presence value: security/danger) condition corresponds to diverse consumption attitudes.

The results enrich the theories of the “cha-xu pattern” and “uncanny valley” and provide reference for the healthy development of the HIR industry.

It is widely known that fast-fashion retailers are struggling to keep up with consumer attention for quick responses within the fashion industry. With the advance of Internet and e-commerce, consumers prefer to purchase online. Online platform information has become an essential source for exploring consumer attention. However, there is often a mismatch between the information provided by retailers and the feedback received from consumers, leading to an imbalance between the supply side and demand side of online information. The purpose of this study is therefore to provide a unified approach to discover consumer attention from the design topic aspect by revealing the information imbalance between supply side and demand side.

To address the issue of online information imbalance and discover consumer attention, this study proposed an approach that focuses on the design topic perspective. The design topic is a collection of design elements that represent a clothing-design feature more comprehensively and accurately compared to a single design element. The proposed approach begins with generating design topics through topic modeling based on online information provided by retailers on e-commerce platforms. Two indicators, influence degree and attention degree, are then used to quantify the intensity of supply information and consumer attention related to design topics. Finally, design topic strategy diagrams are constructed to reveal information imbalance and discover consumer attention.

The experimental case demonstrates the existence of information imbalance, indicating that the intensity of supply information and consumer attention from the perspective of design topics is not uniform, although both follow the Pareto principle. The results of consumer attention distribution with heavy power-law tails are consistent with current research findings. This further demonstrates that the proposed approach is capable of discovering consumer attention in the design topic strategy diagrams.

The issue of information imbalance between retailers and consumers poses a challenge in keeping up with customer attention. The proposed approach offers a practical solution by visually identifying the symptoms of information imbalance and discovering consumer attention through design topic strategy diagrams. This approach provides fast-fashion retailers with a valuable reference to seize market opportunities, improve product design and adjust marketing or management strategies.

This study proposes a novel approach to disclose the issue of information imbalance between supply side and demand side and therefore to discover consumer attention from the perspective of design topics. In addition, guidelines for applying the proposed approach for fast-fashion marketing and management are presented.

With the rapid development of social media, many organizations have begun to attach importance to social media platforms. This research studies the management and the use of social media in academic music libraries, taking the Center for Chinese Music Studies of the Chinese University of Hong Kong (CCMS) as a case study.

We conducted a sentiment analysis of posts on Facebook’s public page to analyze the reaction to the posts with some exploratory analysis, including the communication trend and relevant factors that affect user interaction.

Our results show that the Facebook channel for the library has a good publicity effect and active interaction, but the number of posts and interactions has a downward trend. Therefore, the library needs to pay more attention to the management of the Facebook channel and take adequate measures to improve the quality of posts to increase interaction.

Few studies have analyzed existing data directly collected from social media by programming based on sentiment analysis and natural language processing technology to explore potential methods to promote music libraries, especially in East Asia, and about traditional music.

“Metaverse” has become a buzzword in the Chinese stock market. However, it remains unclear whether a firm's metaverse-related announcements will elicit positive stock market reactions. Whether and how stakeholder reactions are influenced by a firm's metaverse-related readiness also needs to be further explored. This study aims to discuss the aforementioned objective.

The authors derived a set of factors based on readiness theory and business ecosystem literature and extend them into the context of the metaverse. The authors used a sample of 642 Chinese listed firms in 2021 to investigate the hypotheses through the event study.

The study’s findings show that metaverse coverage induces a positive stock market reaction, but it is subject to three moderating effects. The authors introduce the novel concepts of IT readiness, ecosystem readiness and digital infrastructure readiness as the moderators. Stakeholders perceive metaverse announcements as overhyped, and stock prices do not fluctuate significantly after a metaverse announcement when the listed firms are not ready to embrace the metaverse.

This study is one of the first that introduces the event study method into the metaverse research, and it reveals that different levels of readiness influence stakeholders' evaluations and reactions to corporate metaverse coverage. This provides empirical evidence on metaverse development in China from the stock market's perspective.

As foreign direct investment (FDI) plays an important role in economic globalization. This paper examines the structural features of the global FDI network based on FDI flows data and changes in the position of countries within the network.

In order to study the structural characteristics of the global FDI network and the status and changes of countries in the global FDI network, the authors build the investment network and apply the QAP (Quadratic Assignment Procedure) analysis to examine the evolutionary characteristics of the network and its influencing factors.

The global FDI network becomes more interconnected and has a clear “core-periphery” structure. The network connections and volumes have increased dramatically and most countries spread their assets across multiple countries, while only a handful of countries have concentrated investments. The topological structure of the global FDI network has changed noticeably, although this process has been slow and stable and countries in the core position have remained largely intact. The authors find that trade relations between countries, geographic distance and differences in economic size, income levels and institutional environments all have a significant impact on the global FDI network.

Although we find some valuable results, some aspects need further investigation. For example, how a country uses the investment network to boost its economy and how the different industries in the investment network change over time. It is important to get the industry-level details to understand the impact of the global investment network from a government's perspective.

FDI affects the distribution of international capital and contributes to the development of the global economy. Therefore, it is important to study the characteristics of the global FDI network and its development patterns. With more understanding about the network as well as its evolutionary pattern, the government can possibly carry out some policies to promote direct investments as well as economic development.

All countries should actively engage in international direct investments and strengthen their economic ties. At the same time, they can put more emphasis on inward or outward FDI based on their own level of economic development to better establish the circulation channel for domestic and international capital.

This paper examines foreign direct investments through the lens of a global network. In contrast to traditional bilateral studies, this paper focuses on the network structure and evolution, reflecting the dynamics of the entire direct investment system as well as the changing positions of participating countries.

Existing literature demonstrates the important role of information transparency in enterprise development and market surveillance. However, little empirical research has examined the information transparency effect in supply chain management. This study aims to fill this gap by exploring the significant role of information transparency on supply chain financing and its mechanism, taking trade credit as the starting point.

From the data set comprising 3,880 Chinese firms with A-shares listed on the Shenzhen and Shanghai Stock Exchanges from 2011 to 2020, we obtain the basic picture of information transparency and trade credit. Panel fixed effects regression is used to test the hypotheses concerning the antecedents to trade credit.

The empirical results show that: first, information transparency can significantly support corporate access to trade credit and is found to facilitate financing by mitigating perceived risk. Second, among companies with higher levels of financing constraints, weaker market power and more concentration of suppliers, information transparency promotes trade credit more markedly. Third, the outbreak of COVID-19 causes a substantial increase in uncertainty and risk in external circumstances and then the effect of information transparency is weakened. Fourth, the contribution to trade credit is likely to be stronger for disclosures containing management transparency elements compared to single financial transparency.

To the best of our knowledge, this study is one of the first to explore the positive role of information transparency to supply chain financing, which to a certain extent makes up for the lack of information transparency research in the supply chain. It provides new ideas for enterprises to obtain trade credit financing and promote the improvement of supervision departments’ disclosure policies.

This study aims to present a conceptual framework aimed at promoting educational innovation in supply chain management and logistics (SCM&L). The framework can help to design active learning experiences regarding student learning outcomes that tackle current challenges in the discipline. Emphasizing the significance of linking students’ learning to real-world scenarios, the framework enables reflective learning through hands-on engagement in a constructive alignment, overcoming existing pedagogical limitations in the field.

This study presents a qualitative research methodology that relies on the case study method. Three instances are presented to illustrate educational efforts of active learning in countries of Latin America, Bolivia, Mexico and Peru, linking real-world relevant situations to disciplinary teaching and learning.

The innovative learning experiences introduced in this study transform real-world SCM&L operations into distinctive educational opportunities. These experiences facilitate learning not only within traditional classrooms but also in urban areas of the Latin American region, enabling students to interact with educational partners in authentic settings to achieve their intended learning outcomes. These experiences are characterized by their focus on establishing meaningful connections between learning and local communities, businesses or specific contexts.

The study recognizes various limitations of conceptual, methodological, execution-related and research process aspects. First, not all academics in the SCM&L discipline may universally acknowledge the importance of educational innovation and active learning experiences because of limited pedagogical awareness. Moreover, execution-related limitations arise from the demanding nature of incorporating active pedagogical approaches into courses, as they can be resource-intensive and time-consuming. Regarding research process limitations, the case study limits generalizability and broader inferences because of its particular views and locations, which require further investigation with other instances across other disciplines and geographical regions for validation.

The practical implementation of this framework within the MIT SCALE network for Latin America and the Caribbean (LAC) demonstrates its potential in meeting diverse academic and institutional expectations and providing educational benefits to students.

The study makes a valuable contribution to prioritizing and coordinating pedagogical research by investigating the success of learning outcomes achieved through active and experiential implementations in various contexts. It provides inspiring examples of innovative learning experiences that can drive new developments not only within the LAC region but also in other areas, prompting a shift away from traditional educational approaches.

This research presents a conceptual framework, which is developed from the insights obtained in the three learning experiences to guide future efforts in SCM&L education. The findings demonstrate how to structure active learning experiences based on authentic assessment and illustrate the potential for increased cooperation among institutions in Latin America. It also promotes the recognition of novel SCM&L active learning experiences and highlights some of the benefits of this approach.

European rural development programmes are driving multi-actor interactive innovation initiatives and alliances to create an environment in which innovation acts as a tool for accelerating rural development processes. In Europe, where rural areas are facing many challenges, identifying which challenges, difficulties, obstacles or risk factors that interactive innovation projects have had to face in rural areas while being planned and set up would be interesting. The objective of this research work was to, therefore, identify and analyse the risk factors of 200 rural projects and initiatives that were selected as case studies from the whole of Europe.

The employed methodology consisted in conducting interviews to subsequently perform statistical independence analyses of the qualitative variables characterising the found projects and risk factors.

The findings indicated that most of the risks that rural projects and initiatives faced were related to the social domain which was, in turn, the fundamental pillar of interactive innovation. Dependence was found between social risk factors appearing and the innovation type carried out; the risk factors corresponding to the political–legal risks category and the project or initiative coordinating country; and the economic–technical risks category and the initiatives' geographic magnitude.

This paper exposes the main risks identified within various rural innovation initiatives and projects around Europe. For this purpose, a statistical analysis of independence was performed, allowing us to generate reliable and accurate results of the main risks associated with certain descriptive characteristics (coordinating region, domain, innovation type, gender balance and geographic magnitude) of the initiatives studied.

The landscape of search engine usage has evolved since the last known data were used to calculate click-through rate (CTR) values. The objective was to provide a replicable method for accessing data from the Google search engine using programmatic access and calculating CTR values from the retrieved data to show how the CTRs have changed since the last studies were published.

In this study, the authors present the estimated CTR values in organic search results based on actual clicks and impressions data, and establish a protocol for collecting this data using Google programmatic access. For this study, the authors collected data on 416,386 clicks, 31,648,226 impressions and 8,861,416 daily queries.

The results show that CTRs have decreased from previously reported values in both academic research and industry benchmarks. The estimates indicate that the top-ranked result in Google's organic search results features a CTR of 9.28%, followed by 5.82 and 3.11% for positions two and three, respectively. The authors also demonstrate that CTRs vary across various types of devices. On desktop devices, the CTR decreases steadily with each lower ranking position. On smartphones, the CTR starts high but decreases rapidly, with an unprecedented increase from position 13 onwards. Tablets have the lowest and most variable CTR values.

The theoretical implications include the generation of a current dataset on search engine results and user behavior, made available to the research community, creation of a unique methodology for generating new datasets and presenting the updated information on CTR trends. The managerial implications include the establishment of the need for businesses to focus on optimizing other forms of Google search results in addition to organic text results, and the possibility of application of this study's methodology to determine CTRs for their own websites.

This study provides a novel method to access real CTR data and estimates current CTRs for top organic Google search results, categorized by device.