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With the recent availability of large number of bioinformatics data sources, query from such databases and rigorous annotation of experimental results often use semantic frameworks in the form of an ontology. With the growing access to heterogeneous and independent data repositories, determining the semantic similarity or difference of two ontologies is critical in information retrieval, information integration and semantic web services. The purpose of this paper is to propose a new sense refinement algorithm to construct a refined sense set (RSS) for an ontology so that the senses (synonym words) in this refined sense set represent the semantic meanings of the terms used by this ontology.

A new concept of a semantic set is introduced that combines the refined sense set of ontology with the relationship edges connecting the terms in this ontology to represent the semantics of this ontology. With the semantic sets, measuring the semantic similarity or difference of two ontologies is simplified as comparing the commonality or difference of two sets.

The experimental studies show that the proposed method of measuring the semantic similarity or difference of two ontologies is efficient and accurate; comparisons with existing methods show the efficacy of using the new method.

The concepts introduced in this paper will improve automation of bioinformatics databases to serve queries based on heterogeneous ontologies.

This study explores whether and how financial agglomeration affects enterprise specialization, and whether it weakens the division effects of logistics accessibility.

Using the panel data of A-share listed companies in the Chinese manufacturing industry from 2010 to 2018, the authors test the hypotheses of the research framework by constructing a double fixed effect model.

First, for every 1% increase in financial agglomeration and logistics accessibility, enterprise specialization will increase by 1.8% and 5.6%. Meanwhile, financial agglomeration weakens the division effects of logistics accessibility. After a multiple robustness test, the above conclusions still hold. Second, the mechanism test shows that financial agglomeration can promote enterprise specialization through cost saving effect, scale expansion effect and technological progress effect. Third, financial agglomeration has a stronger positive impact and negative moderating effect on enterprise specialization in periphery areas and small-scale enterprises, but logistics accessibility is more likely to increase enterprise specialization in core regions and small-scale firms.

In the context of the global value chain (GVC) reshaping caused by the transformation of the international situation, exploring the relationship among financial agglomeration, logistics accessibility and enterprise specialization based on China’s experience can be an important insight for other emerging economies to enhance their position in the GVC.

The above findings enrich the literature on the division of labor among firms and contribute to the further improvement of GVC theory and division theory.

Continuous fiber-reinforced thermoplastic composites are a class of materials highly valuable for structural applications and modeling of heat transfer within them is critical to the design of their processing methods. However, the fiber reinforcement leads to highly anisotropic thermal conduction. Among a variety of methods to account for anisotropic thermal conductivity, continuum models with effective media approximation thermal conductivity are computationally efficient and require minimal data to begin modeling a specific composite material. The purpose of this study is to evalute the utility of these models.

In this work, six potential effective media approximation models are evaluated against experimental heating data. Thick (>25 mm) glass fiber-reinforced polyethylene terephthalate glycol (PET-G) specimens with 40% fiber volume fraction were heated with embedded resistance heating to produce validation and testing data sets. A two-dimensional finite-difference solver was implemented using each of the six effective media approximation models. The accuracy of each model is compared.

The model developed by Cheng and Vachon was found to predict the experimental results most accurately. Fit statistics were similar in the testing and validation data sets. This model is recommended for simulation of transient heating in continuous fiber-reinforced thermoplastic composites with low-to-moderate fiber volume fractions.

There are a wide variety of mathematical models for effective media approximation thermal conductivity, though very few have been applied to continuous fiber-reinforced thermoplastic composites. This work shows that the simplest methods based on rules of mixtures are well outperformed by more modern and complex models, and should be incorporated for accurate prediction of heating during thermal processing of fiber-reinforced thermoplastic composites.

This research provides accounting-ethics authors and administrators with a benchmark for accounting-ethics research. While Bernardi and Bean (2010) considered publications in business-ethics and accounting’s top-40 journals this study considers research in eight accounting-ethics and public-interest journals, as well as, 34 business-ethics journals. We analyzed the contents of our 42 journals for the 25-year period between 1991 through 2015. This research documents the continued growth (Bernardi & Bean, 2007) of accounting-ethics research in both accounting-ethics and business-ethics journals. We provide data on the top-10 ethics authors in each doctoral year group, the top-50 ethics authors over the most recent 10, 20, and 25 years, and a distribution among ethics scholars for these periods. For the 25-year timeframe, our data indicate that only 665 (274) of the 5,125 accounting PhDs/DBAs (13.0% and 5.4% respectively) in Canada and the United States had authored or co-authored one (more than one) ethics article.

This paper explores sports consumer interest in virtual environments (VE) and Web3 activations, specifically how the level of psychological involvement, consumers' generational cohorts and previous experience with VE and Web3 activations influence consumer interest in VE and Web3 products and services related to their favorite sports team.

A survey instrument was developed and distributed online resulting in a sample size of n = 526. The survey was designed to measure consumers' psychological involvement with their favorite sports team based on the Psychological Continuum Model, and to determine respondents' interest in potential VE and Web3 activations. Finally, the survey collected demographical information and data regarding respondents' previous experience with VE and Web3 applications. Multiple regression analysis was subsequently conducted to predict the impact of (1) psychological involvement, (2) consumers' generational cohorts and (3) previous experience with VE and Web3 activations on the dependent variable consumer interest in VE and Web3 activations.

The regression model showed a significant impact of the independent variables on consumer interest in VE and Web3 activations with consumer involvement exerting the highest influence. Consumers' previous experience with VE and Web3 applications also seems to trigger interest, in line with the consumption capital theory. This study also suggests that younger generational cohorts are not intrinsically more attracted to VE and Web3 activations but their interest seems to depend on the type of activation.

This study is intended as a first assessment of independent variables that may have an impact on sports consumer interest in VE and Web3 activations. Further research is needed to assess the impact these variables combined with other indicators may have on consumer interest, for instance by employing a Structural Equation Modelling (SEM) approach. This research included selected VE and Web3 applications comprising online games, NFTs and cryptocurrencies, to calculate a VE and Web3 Literacy Score for the purpose of this paper. However, the “umbrella term Web3” (Wang et al., 2022) could indicate a number of additional applications not considered in this research. Future studies could examine sports consumer experience with additional Web3 activations when assessing VE and Web3 Literacy.

The results of this research imply the need for a diversification of the VE and Web3 portfolio offered by sports teams to cater to different consumer segments. Upcoming challenges for sports teams include motivating younger consumers to take an interest in Web3 activations beyond gaming. Additionally, sports teams should encourage loyal supporters in the advanced stages of the PCM who possess limited VE and Web3 experience, to engage in VE and Web3 activations through simplified offers complementing their overall fan experience.

VE and Web3 activations currently offered by sports teams are still in their early stages and data underpinning their success is scarce. This is the first study examining variables that may influence consumer interest in a sports context.

This study aims to examine the influence of reward personalization on financing outcomes in the Industry 5.0 era, where reward-based crowdfunding meets the personalized needs of individuals.

The study utilizes a corpus of 218,822 crowdfunding projects and 1,276,786 reward options on Kickstarter to investigate the effect of reward personalization on investors’ willingness to participate in crowdfunding. The research draws on expectancy theory and employs quantitative and qualitative approaches to measure reward personalization. Quantitatively, the number of reward options is calculated by frequency; whereas text-mining techniques are implemented qualitatively to extract novelty, which serves as a proxy for innovation.

Findings indicate that reward personalization has an inverted U-shaped effect on investors’ willingness to participate, with investors in life-related projects having a stronger need for reward personalization than those interested in art-related projects. The pledge goal and reward text readability have an inverted U-shaped moderating effect on reward personalization from the perspective of reward expectations and reward instrumentality.

This study refines the application of expectancy theory to online financing, providing theoretical insight and practical guidance for crowdfunding platforms and financiers seeking to promote sustainable development through personalized innovation.

Using bibliometric techniques, the author analyzes a dataset of 276 articles on cross-border mergers and acquisitions (CBMAs) published in 13 management and international business journals. The author assesses the scientific impact and visualizes the intellectual landscape of research on CBMAs by analyzing publication and citation data and interconnections between publications. First, the author assesses annual publication trends and identifies highly cited articles and productive journals in the dataset that have significantly contributed to our understanding of CBMAs. Second, the author identifies main themes in recent research on CBMAs by focusing on frequently used keywords in publications. Third, the author identifies clusters of related research and explores their interrelationships to outline emerging trends, new perspectives, and directions for future research on CBMAs. Overall, this chapter contributes to the understanding of CBMAs by documenting the progress made to date and providing important insights for future research.