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With the increasing number of Web services, correct and efficient classification of Web services is crucial to improve the efficiency of service discovery. However, existing Web service classification approaches ignore the class overlap in Web services, resulting in poor accuracy of classification in practice. This paper aims to provide an approach to address this issue.

This paper proposes a label confusion and priori correction-based Web service classification approach. First, functional semantic representations of Web services descriptions are obtained based on BERT. Then, the ability of the model is enhanced to recognize and classify overlapping instances by using label confusion learning techniques; Finally, the predictive results are corrected based on the label prior distribution to further improve service classification effectiveness.

Experiments based on the ProgrammableWeb data set show that the proposed model demonstrates 4.3%, 3.2% and 1% improvement in Macro-F1 value compared to the ServeNet-BERT, BERT-DPCNN and CARL-NET, respectively.

This paper proposes a Web service classification approach for the overlapping categories of Web services and improve the accuracy of Web services classification.

The paper attempts to discuss the optimal pricing decisions under the decentralized and centralized decision and analyze the influence of online reviews and in-sale service on dual-channel supply chain. Finally, the authors design a two-part tariff coordination mechanism.

To deal with this pricing conflict problems of dual-channel supply chain consisting of dominant manufacturer and a retailer, considering the fact that online reviews and in-sale service are important factors on consumers’ purchase decisions, the authors establish some basic models and exploit them to discuss the optimal pricing decisions under the decentralized and centralized decision and analyze the influence of online reviews and in-sale service on dual-channel supply chain. Finally, the authors design a profit-sharing coordination mechanism.

The results show that the optimal online direct selling price is positively correlated with product perceived quality obtained from online reviews and negatively correlated with the in-sale service. The traditional retail price is positively correlated with the in-sale service and weakly correlated with online reviews. For the manufacturer and retailer, whether decentralized decision or coordination contract, their profits increase with the increase of the in-sale service in a certain range and quality perceived from spontaneous online reviews. Online reviews and in-sale service are important factors on consumers’ purchase decisions. Positive in-sale services and online reviews can provide consumers with a better shopping experience, thereby promoting their enthusiasm for shopping and improving their quality of life. The two-part tariff coordination mechanism improves the profits of the manufacturer and the traditional retailer, respectively, through the transfer fee.

The proposed approach can well analyze the channel conflicts and pricing problems between retailers and manufacturers with respect to product offline price and online price. The analysis and results can inform decision-making for manufacturers and retailers.

Evaluating project success within the construction industry presents challenges due to the unique characteristics of the sector, the complexity of projects, and the involvement of diverse stakeholders. Conducting a bibliometric analysis, this paper aims to unravel the major research themes and methodologies utilised by researchers in studying the critical success criteria for construction projects, as well as extracting these success criteria.

The researchers systematically searched and screened 95 papers from Scopus and Web of Science (WoS) databases. This study conducted research focus parallelship network (RFPN) analysis and keywords co-occurrence network (KCON) analysis using BibExcel and Gephi to cluster the papers, illuminate the relationships among keywords within each cluster, and identify the primary research directions.

Using the RFPN analysis, this study classified the papers into three distinct clusters: infrastructure and public projects success, risk and knowledge management, and contractors and procurement management. Statistical techniques such as structural equation modelling (SEM) and multi-criteria decision-making methods such as analytic hierarchy process (AHP) have been used to analyse project success in the construction industry.

Considering the intensified demand for streamlined digital interactions and the increasing emphasis on sustainability and safety performance, construction companies are recommended to allocate greater investments toward the automation and digitisation of their products and processes. Prioritising modular construction and embracing transformative technologies alongside data science is crucial for enabling well-informed decision-making, and enhancing project success.

This study contributes to the existing body of knowledge by conducting a quantitative and systematic evaluation of the literature on project success criteria in the construction industry and uncovering key research areas. It addresses the pressing need to understand the complexities of construction projects amidst evolving industry dynamics and emerging disruptions. Moreover, by highlighting the implications of digital innovations and modular construction, this study urges deeper exploration into their impact on project performance and stakeholder satisfaction. This research sets a comprehensive framework for investigating the interplay between project complexity, technological advancements, and sustainable practices in the construction sector, paving the way for strategic advancements in the field.

The purpose of this paper is to provide a critical historical analysis of the business (mis)behaviors and influencing factors that discourage enduring cooperation between principals and agents, to introduce strategies that embrace the social values, economic motivation and institutional designs historically adopted to curtail dishonest acts in international business and to inform an improved principal–agent theory that reflects principal–agent reciprocity as shaped by social, political, cultural, economic, strategic and ideological forces

The critical historical research method is used to analyze Chinese compradors and the foreign companies they served in pre-1949 China.

Business practitioners can extend orthodox principal–agent theory by scrutinizing the complex interactions between local agents and foreign companies. Instead of agents pursuing their economic interests exclusively, as posited by principal–agent theory, they also may pursue principal-shared interests (as suggested by stewardship theory) because of social norms and cultural values that can affect business-related choices and the social bonds built between principals and agents.

The behaviors of compradors and foreign companies in pre-1949 China suggest international business practices for shaping social bonds between principals and agents and foreign principals’ creative efforts to enhance shared interests with local agents.

Understanding principal–agent theory’s limitations can help international management scholars and practitioners mitigate transaction partners’ dishonest acts.

A critical historical analysis of intermediary businesspeople’s (mis)behavior in pre-1949 (1840–1949) China can inform the generalizability of principal–agent theory and contemporary business strategies for minimizing agents’ dishonest acts.

This paper aims to examine employees’ online learning continuation intentions (OLCI), exploring factors such as performance expectancy (PE), effort expectancy (EE), social influence (SI), perceived benefits (PB) and management support (MS) influencing their commitment to online learning engagement.

The Unified Theory of Acceptance and Use of Technology (UTAUT) model was expanded to include PB and MS constructs. This study used a quantitative research approach using purposive sampling techniques. Three hundred and eighty-six responses from Indian information technology (IT) professionals at various levels were analysed using Statistical Package for the Social Sciences-Analysis of Moments Structures tool.

This study found a strong positive influence of PE, EE, PB and MS on OLCI in the context of post-pandemic. Workplace learning rapidly generates outcomes if employees associate it with their career growth. However, the authors found that SI does not significantly affect OLCI.

This research is unique work in the area of workplace learning by evaluating the OLCI of IT professionals using the extended UTAUT model in a new normal. Moreover, this study contributes to online learning literature with a combined study of technology usage, continuance intention and organization learning and development.

In tourism live streaming (TLS), streamers strive to capture viewers’ attention by responding quickly to viewers’ requests and providing tourism-related knowledge. However, the effectiveness of such practices in the TLS context remains unclear. Accordingly, based on flow theory, this study aims to uncover the effects of responsiveness and knowledge spillover on viewers’ travelling intentions.

The authors collected 319 valid questionnaires to examine the proposed model. Followingly, the authors used a partial least squares structural equation modelling approach using SmartPLS 4 to analyse the survey data.

The authors found that responsiveness could enhance viewers’ flow experience and destination attachment, fostering travelling intentions. The authors further found that knowledge spillover strengthened the relationship between responsiveness and travelling intentions and responsiveness and flow experience.

This study broadens the scope of extant tourism research by juxtaposing the effects of responsiveness and knowledge spillover on viewers’ travelling intentions in the TLS context. Practically, the findings provide valuable insights for streamers to conduct appropriate viewer–streamer interaction strategies by providing instant responses and tourism-related knowledge to viewers.

在旅游直播中, 主播常常通过快速响应观众并提供目的地知识, 以吸引观众注意。然而这种策略是否有效地提升了观众的旅游意愿仍需进一步验证。因此, 本研究基于心流理论验证了响应性及知识溢出效应对观众旅游意愿的影响。

我们通过评估319份有效问卷来检验所提出的模型, 采用了SmartPLS软件构建偏最小二乘结构方程模型（PLS-SEM）分析问卷数据。

我们发现, 响应性将增强观众的心流体验和目的地依恋感, 从而促进旅游意愿。此外, 知识溢出效应强化了响应性和旅游意愿及响应性和心流体验之间的关系。

本研究同时关注响应性及知识溢出在旅游直播情境下对观众旅游意愿的影响机制。从实践层面, 本研究为旅游主播提供了高效互动及目的地推广的策略。

En las retransmisiones turísticas en directo (TLS), los organizadores se esfuerzan por captar la atención de los espectadores respondiendo de forma rápida a sus peticiones y aportando conocimientos relacionados con el turismo. Sin embargo, la eficacia de estas prácticas en el contexto de la retransmisión turística en directo sigue sin estar clara. Por consiguiente, este estudio, basado en la teoría del flujo, trata de descubrir los efectos de la capacidad de respuesta y la difusión de conocimientos en la intención de viajar de los espectadores.

Se recogieron 319 cuestionarios válidos para examinar el modelo propuesto. Seguidamente, se aplicó la técnica de ecuaciones estructurales con mínimos cuadrados parciales (PLS-SEM) mediante el software SmartPLS para analizar los datos de la encuesta.

Se concluye que la capacidad de respuesta mejoraría la experiencia de flujo de los espectadores y el apego al destino, fomentando su intención de viajar. Además, se comprueba que la difusión de conocimientos fortalece la relación entre (1) la capacidad de respuesta y la intención de viajar y (2) la capacidad de respuesta y la experiencia de flujo.

La presente investigación amplía el enfoque de los estudios existentes en la investigación turística al aproximar los efectos de la capacidad de respuesta y la difusión de conocimientos sobre la intención de viajar de los espectadores en el contexto de retransmisiones turísticas en directo. Desde el punto de vista práctico, los resultados aportan ideas para que los streamers empleen estrategias de interacción apropiadas con los espectadores, proporcionándoles respuestas instantáneas y transmitiéndoles conocimientos relacionados con el turismo.

The detrimental effects of air pollution on the continuity of corporations attract more and more attention in the economic and financial studies. Prior literature investigates the impact of air pollution on corporate financial performance. This study aims to extend this research area by exploring the role of corporate innovation and happiness as factors that mitigate the adverse effects of air pollution and moderate the relationship between air pollution and financial performance.

This study uses two-step system generalized method of moments models to analyze the data of 200 firms listed on Istanbul Stock Exchange over the period 2009–2022.

The results show that firms located in regions with higher air pollution are more likely to invest in innovation. In addition, firms that are more exposed to air pollution and have investments in research and development (R&D) have less ability to improve their financial performance compared to firms that have no investments in R&D. In a similar vein, although R&D has positive effect on financial performance, this effect diminishes in the presence of higher air pollution. The results also show that happiness has no significant moderating effect on the relationship between air pollution and financial performance.

The findings of this study related to the role of corporate innovation in determining the effect of air pollution on financial performance indicate that the costs of investment in R&D weaken the firm’s ability to mitigate the adverse impact of air pollution on financial performance, which provides important signals to policymakers to concentrate more on supporting investment in corporate innovation by providing the necessary facilities for firms to improve their innovative performance and decrease the costs of investment in innovation.

To the author’s knowledge, this research is the first to explore the influence of happiness on the air pollution–financial performance relationship. In addition, this study differs from most prior ones by examining how responding to air pollution through investment in innovation can moderate the association between air pollution and financial performance.

This study aims to construct a “contractual–relational–governmental” 3D governance framework for new infrastructure projects (NIPs) within China’s distinct institutional context. The primary objective is to explore the impact of multiple governance mechanisms on the NIP performance, thus identifying the key governance mechanisms and proposing targeted performance improvement strategies.

The research design follows a sequential mixed methodology of integrating qualitative and quantitative data collection and analysis. Firstly, project governance and performance indicators were collected from relevant literature and expert interviews. Secondly, a questionnaire was developed, and data were collected through on-site and online means. Finally, the partial least square structural equation model (PLS-SEM) was utilized to examine and analyze the relationships between governance mechanisms and NIP performance.

Contractual, relational and governmental governance all have a certain role in promoting the NIP performance. Specifically, contract stringency, trust and governmental decision are the core elements of contractual, relational and governmental governance, respectively, while commitment does not significantly affect NIP performance. Generally, relational and governmental governance exert a more substantial influence compared to contractual governance, with governmental decision and trust being the most effective.

This paper contributes to the field by introducing PLS-SEM as a measurement tool for exploring the impact of multiple governance mechanisms on governance performance in NIPs. The results offer valuable insights for project managers, enabling them to concentrate on core factors while refining and optimizing governance mechanisms and strategies.

Artificial intelligence (AI) applications pose a potential threat to users' data security and privacy due to their high data-dependence nature. This paper aims to investigate an understudied issue in the literature, namely, how users perceive the threat of and decide to use a threatening AI application. In particular, it examines the influencing factors and the mechanisms that affect an individual’s behavioral intention to use facial recognition, a threatening AI.

The authors develop a research model with trust as the key mediating variable by integrating technology threat avoidance theory, the theory of planned behavior and contextual factors related to facial recognition. Then, it is tested through a sequential mixed-methods investigation, including a qualitative study (for model development) of online comments from various platforms and a quantitative study (for model validation) using field survey data.

Perceived threat (triggered by perceived susceptibility and severity) and perceived avoidability (promoted by perceived effectiveness, perceived cost and self-efficacy) have negative and positive relationships, respectively, with an individual’s attitude toward facial recognition applications; these relationships are partially mediated by trust. In addition, perceived avoidability is positively related to perceived behavioral control, which along with attitude and subjective norm is positively related to individuals' intentions to use facial recognition applications.

This paper is among the first to examine the factors that affect the acceptance of threatening AI applications and how. The research findings extend the current literature by providing rich and novel insights into the important roles of perceived threat, perceived avoidability, and trust in affecting an individual’s attitude and intention regarding using threatening AI applications.

The integration of women higher education leaders into the ideal discourse of educational leadership is a significant issue, as the discourses on women and leadership are continually reshaped in a changing social background, with their compatibility directly influencing women leaders’ construction, understanding and presentation of their leadership identities. In recent years, the Ministry of Education in China has issued a series of documents encouraging the promotion of academic and innovative development in higher education. In response, local governments and higher education institutions (HEIs) have introduced policies that directly link the achievements of university teachers and leaders to evaluations, promotions and performance assessments. The concept of ‘academic and innovative’ encompasses both research and innovation – the ideal educational leader is expected to demonstrate stable research outcomes while actively promoting educational reforms. This chapter focuses on the narratives of women higher education leaders. In particular, the study explores the structural challenges faced by women leaders within the higher education system in integrating this seemingly non-conflicting new ideal leadership discourse with their identities. The research is derived from narrative interviews with eight women leaders in HEIs in China, focusing on their understanding, construction and presentation of their leadership identities. The study suggests that the discourse surrounding the ideal ‘academic and innovative’ higher education leader, while not directly opposing traditional notions of ‘feminine traits’, brings a set of performance management-like evaluation criteria for leaders. However, due to structural challenges within higher education, women face significant hurdles in attempting to integrate into the emerging ideal leadership discourse.