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In acoustic detection technology, optical microcavities offer higher detection bandwidth and sensitivity than traditional acoustic sensors. However, research on acoustic detection technologies involving optical microcavities has not yet been reported. Therefore, this paper aims to design and construct an underwater acoustic detection system based on optical microcavities and study its acoustic detection technology to improve its performance.

Based on the principles of optical microcavity acoustic sensors, a signal-detection circuit was designed to form a detection system in conjunction with a laser, an optical waveguide resonator and an oscilloscope. This circuit consists of two modules: a photodetection module and a filter amplification module.

The photodetection module features a baseline noise of −106.499 dBm and can detect device spectral line depths of up to 2410 mV. The gain stability of the filter amplification module was 58 dB ± 1 dB with a noise gain of −107.626 dBm. This design allows the acoustic detection system to detect signals with high sensitivity within the 10 Hz−1.2 MHz frequency band, achieving a maximum sensitivity of −126 dB re 1 V/µPa at 800 Hz and a minimum detectable pressure (MDP) of 0.37 mPa/Hz^1/2, corresponding to a noise equivalent pressure (NEP) of 51.36 dB re 1 V/µPa.

This study designs and constructs a broadband underwater acoustic detection system specifically for optical waveguide resonators based on the sensing principles of silicon dioxide optical waveguide resonators. Experiments demonstrated that the signal detection module improves the sensitivity of underwater acoustic detection based on optical waveguides.

Online reviews have become increasingly important and numerous studies have noted the effect of social factors on the review provision of users. The purpose of this study is to investigate how hometowner contributions, which are defined as prior reviews posted by users from the same city, affect the quality of reviews by focal users.

Based on the theories of competitive altruism, pure altruism and reciprocity, as well as several social influence theories, a conceptual framework is constructed to explain user contribution behavior. In addition, empirical models are established based on 831,737 reviews of 919 hotels on Tripadvisor.

The quality of reviews by hometowners can significantly motivate subsequent users to contribute high-quality reviews. This positive effect is stronger than the effect of previous contributions by non-hometowners. The effect of hometowner contribution is amplified in users with limited review-posting experience and/or in those from countries with a considerable cultural distance from the target destination.

This study provides the hospitality literature with new insights into the effect of social factors on the review provision of users in the context of online hotel review websites. The results also present numerous practical implications for online travel communities.

This study is an early attempt to analyze the effect of prior hometowner contributions on the subsequent contribution decisions of focal users. Thus, this study provides a satisfactory starting point for determining whether the review provision of focal users can be affected differently by prior contributions from their peers from different categories.

Effectively evaluating the efficiency of individual e-markets for better understanding the efficiency-oriented critical drivers for individual e-markets is of great significance to the development of electronic business. The purpose of this paper is to develop an approach through adequately integrating data envelopment analysis (DEA) and bootstrapped Tobit regression analysis for identifying the efficiency-oriented critical drivers on the development of e-market in electronic business.

A review of the related literature is conducted for adequately formulating the e-market evaluation problem. DEA is appropriately used for assessing the efficiency of available e-markets, leading to the identification of the efficient e-market. Tobit regression analysis is then employed to examine the outcome of the DEA analysis for identifying the efficiency-oriented critical drivers in the development of e-markets in electronic business.

A better understanding of the operations of individual e-markets with respect to their overall efficiency in electronic business can be achieved with the use of the developed approach. Such understanding is built on the identification of the efficiency-oriented critical drivers on the development of e-market in electronic business.

This paper develops a novel approach for better understanding of the operations of individual e-markets with respect to their overall efficiency in electronic business. The adoption of this approach helps existing e-markets improve their efficiency by focussing on the efficiency-oriented critical drivers and provide new players in e-markets with guidelines for developing their efficient e-markets.

There are a large number of interdependent risk factors in complex project. Risk response strategy without considering risk correlation cannot achieve good risk response. Therefore, the purpose of this paper is to propose a risk response strategy selection model considering risk correlation based on the grey K-shell algorithm.

This paper mainly focuses on the measurement of two aspects of risk factors. One is the ability of the risk factors to influence other risk factors, another is the degree affected by other risk factors. Both of the above are measured by the grey K-shell algorithm improved in this paper, and the weights of these are used for the constructing of risk response strategy selection model.

The risk response strategy considering risk relevance is more effective than the risk response strategy without considering risk relevance. Also, results indicate that as the risk response budget increases the risk response effect also increases, and the increasing trend is weakens. The relative gap between the effect of response strategies considering risk relevance and the strategy without considering risk relevance increases first and, then, decreases with the increase of budget.

The results of this paper demonstrate that the risk response strategy considering risk relevance is more effective than not considering risk relevance. The approach presented in this paper can guide project managers’ risk decisions and may also help to find the best risk response budget.

Information technology has been recognized as one of the keys to improved productivity in organizations. Yet, existing research has not paid sufficient attention to how information systems (ISs) influence the creative performance of individual users. The paper aims to discuss this issue.

This study draws on the theories of flow and cognitive load to establish a model of the predicted influences. The authors hypothesize that the information technology supports creativity by engaging individuals in a creative process and by lowering their cognitive load related to the process. To test these hypotheses, the authors employ a meta-analytical structural equation modeling approach using 24 previous studies on creativity and ISs use.

The results suggest that factors that help the user to maintain an interest in the performed task, immerse the user in a state of flow, and lower a person’s cognitive load during IS use can affect the user’s creative performance.

The findings imply that a combination of the theories of flow and cognitive load complements the understanding of how ISs influence creativity.

This paper proposes an explanation on why ISs affect creativity, which can be used by scholars to position further research, and by practitioners to implement creativity support systems.

Universities face challenges due to the absence of artificial intelligence (AI) integration in entrepreneurship education (EE) and its incubation centers for young startups. Making a business plan for their innovative enterprises, which includes market analysis, financial projections, marketing strategy and an operations plan, are a few of the toughest tasks they may face. Aspiring students can make it simple to launch their dream business by integrating AI tools. Hence, this study aims to conduct a systematic literature review (SLR) to examine the global trend of the transformation of EE with AI and determine the necessity of integrating AI in university incubation centers as a potential future research direction.

In this study, the authors conducted an SLR method to investigate the transformation of EE with AI. This review employed a bibliometric analysis covering the period of 1993–2023 and utilized articles published in scientific journals available in the SCOPUS database as our data source.

There is an enormous potential for research on EE using cutting-edge AI in developed and developing nations. There is a lack of studies exploring AI integration into university incubation centers. Hence, there are possible future directions for research into integrating AI into university incubation centers using cutting-edge tools like chatbots, ChatGPT, ChatGen and other AI that will help to develop a comprehensive business plan for students aspiring entrepreneurial venture startups.

The study’s research was limited using the Scopus database’s core collection, which may ignore other significant research articles. Therefore, the study’s scope can be constrained due to the narrow search parameters. The study, however, tries to establish the importance of its research by offering a thorough review and evaluation of AI in EE.

There is significance of incorporating AI into EE to foster an EE culture and realize its potential benefits. To transform incubation centers and promote aspirant entrepreneurs in the fourth industrial revolution (4IR), higher education institutions (HEIs) should strategically adopt AI.

This study presents a novel viewpoint by investigating the distinction in AI perception and usage among educators, advocating the incorporation of AI in university incubation centers to help entrepreneurial students. It contributes uniqueness and innovative approaches to early startup issues in EE.

This study aims to expand tourism knowledge by analysing literature review articles published in English Web of Science (WOS) and Chinese China National Knowledge Infrastructure (CNKI) language journals and reviewing their influence, interconnection and trends.

A three-stage method was designed to understand the tourism research progress. Performance analysis identified the publication timeline, high-yielding journals and authors that published tourism literature reviews and frequently cited papers. Science mapping visualisation examined the intrinsic connections between co-authorship and co-institution. Finally, emerging trend analysis explored the topic modelling and evolution through Latent Dirichlet allocation (LDA) and regression.

The key statistics and collaborations relationships of tourism literature reviews were traced. LDA identified 45 and 22 topics, which narrowed the barriers in tourism studies. The regression analysis divided these topics into “hot”, “fresh”, “bell-shaped” and “stable” patterns. These modes represent the progress of tourism studies. The topic “new emerging technologies and the internet” is the focus of tourism literature reviews published in both databases. Future research could pay more attention to the topics in the “hot” and “fresh” patterns. The results enrich the progress of tourism literature reviews and provide a direction for future research.

To the best of the authors’ knowledge, this study is the first literature analysis for tourism literature reviews published in WOS versus CNKI journals. The proposed three-stage systematic method is used for the first time for the literature review and can guide future research.

本研究旨在通过分析英文WOS和中文CNKI语言期刊上发表的文献综述文章, 回顾其影响、相互联系和趋势, 来扩大旅游知识体系。

本研究设计了一个三阶段方法来了解旅游研究进展。绩效分析确定了出版时间线、发表的旅游文献综述的高产期刊和作者以及经常被引用的文章。科学地图可视化审视了合作作者和合作机构之间的内在联系。最后, 新兴趋势分析通过潜在狄利克雷分配和回归探讨了主题建模和演变。

本文追踪了旅游文献综述的关键统计数据和合作情况。潜在狄利克雷分配确定了45个和22个主题, 这缩小了旅游研究中的研究缺口。回归分析将这些主题分为“热门”、“新鲜”、“钟形”和“稳定”模式。这些模式代表了旅游研究的进展。主题“新兴技术和互联网”是不同数据库中发表的旅游文献综述的焦点。未来的研究可以更多地关注“热门”和“新鲜”模式中的主题。研究结果丰富了旅游文献综述的进展, 为今后的研究提供了方向。

这项研究是首次对WOS与CNKI期刊上发表的旅游文献评论进行文献分析。所提出的三阶段系统方法首次用于文献综述, 可以指导未来的研究。

El objetivo de este estudio es ampliar el conocimiento turístico analizando los artículos de revisión documental publicados en revistas, tanto en la versión WOS en inglés cómo en CNKI China, y revisando sus efectos, interconexiones y tendencias.

Se ha diseñado el método de tres etapas para comprender el progreso de la investigación turística. El análisis del desempeño determinó la línea de tiempo de publicación, las revistas de alto rendimiento y los comentarios de la literatura turística publicados por los autores, así como los artículos citados con frecuencia. La visualización de los mapas científicos, examina los vínculos intrínsecos entre los autores colaboradores y las instituciones colaboradoras. Finalmente, el análisis de tendencias emergentes explora el modelado temático y la evolución a través de posibles asignaciones y regresiones de dilick-ray.

Se han analizado las estadísticas clave y las relaciones de cooperación de la revisión de la literatura turística. La asignación potencial de dilich-ray identifica 45 y 22 temas, lo que reduce las barreras en la investigación turística. El análisis de regresión divide estos temas en patrones “populares”, “novedosos”, “en forma de campana” y “estables”. Estos modelos representan el avance de la investigación turística. El tema “tecnologías emergentes e internet” es el foco de la revisión de la literatura turística publicada en diferentes bases de datos. La investigación futura puede centrarse más en temas en modelos “populares” y “novedosos”. Los resultados de la investigación enriquecen el progreso de la revisión de la literatura turística y proporcionan una dirección para futuras investigaciones.

El estudio es el primer análisis documental de los comentarios de la literatura turística publicados en las revistas WOS y CNKI. El método sistemático de tres etapas propuesto se utiliza por primera vez en la revisión documental y puede guiar futuras investigaciones.

This study aims to utilize DMAIC methodology along with value stream mapping and other Lean Six Sigma tools in a major automobile light manufacturing industry to reduce defect rates and increase production capacity in their manufacturing line. The study also proposes a modified framework based on lean principles and FlexSim to identify and reduce waste in the selected industry.

A Lean Six Sigma modified framework has been deployed with DMAIC to reduce the defect rate and increase the production rate. Various tools like value stream mapping, brainstorming, Pareto charts, 5S, kanban, etc. have been used at different phases of DMAIC targeting wastes and inventory in the production line. Also, a simulation model has been utilized for the automobile light manufacturing industry to improve the machine utilization time with varying batch sizes.

The results of the study indicated a 53% reduction in defect rates. Thus, there would be an expected improvement in sigma value from 3.78 to 3.89 and a reduction in defects per million opportunities (DPMO) from 11,244 to 8,493. Additionally, simulation model using FlexSim was developed, and the optimum ordering batch size of raw material was obtained. It was also analyzed that idle time for various stations could be reduced by up to 30%.

The utilized framework helps identify defects for managers to increase production efficiency. The workers, operators and supervisors on the production line also need to be trained regularly for identifying the areas of improvement.

The modified Lean Six Sigma framework used in this study includes FlexSim simulation to make the framework robust, which has not been used with LSS tools in the literature studied. Also, the LSS finds very less application in the manufacturing domain, considering which this study tends to add value in existing literature taking a case of an automobile light manufacturing industry.