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The industrial revolution 4.0 (IR4.0) signifies technological advancements and digitalization. The fragmented and labour-intensive nature of the construction industry inherently possesses difficulties for IR4.0 adoption compared to other industries. This paper aims to investigate the perspectives of quantity surveying students on the challenges of IR4.0 implementation in the construction industry.

A questionnaire survey were distributed to a population of 191 quantity surveying students, with 96 valid responses returned. Descriptive statistics and factor analysis were employed to analyse the collected data.

Factor analysis revealed eight components as the key challenges for IR4.0 implementation, which revolved around resistance to change, data security issues, etc.

The findings could provide a guideline to higher education institutions on certain IR4.0-related areas to be incorporated into the syllabus, in ensuring that the students are equipped with such skills and knowledge, in meeting market demands. The construction stakeholders' could look into the identified challenges for strategizing the organizations in moving towards IR4.0 adoption.

To the best of the authors’ knowledge, this is the first study to investigate quantity surveying students' perspectives on the challenges of IR4.0 implementation in the construction industry by employing factor analysis method. The findings contribute to the body of knowledge in relation to the opinions of a younger generation who has more exposure towards technology on the hindrance of IR4.0 adoption.

This study aims to explore the effects of responsible international investment in a least developed country (LDC) on ethics and corruption in the local industry. While investment growth in least developed countries (LDCs) is essential to meet the United Nations Sustainable Development Goals, international investment in LDCs poses challenges, including corruption. The authors explore perspectives from relevant stakeholders on the influence, if any, on an LDC’s banking sector, of investment in the LDC by a multinational bank with an environmental, social and governance focus – using a case study of Standard Chartered Bank (SCB) in Nepal.

The authors conducted thematic analysis on: focus groups with current and former SCB Nepal management; semi-structured interviews with Nepal banking regulator representatives; senior staff from SCB global divisions; and management of other commercial banks in Nepal.

Knowledge transfer, organisational enablers and constructive international competition contributed to the dissemination of best practices within the Nepal banking sector, supporting the notion of beneficial spill-over effects of multinationals on LDC host countries.

Practical insights will aid LDC governments, international businesses, investment funds and donor organisations seeking to invest in/assist LDCs with economic development.

To the best of the authors’ knowledge, this may be the first case study on ethics and anti-corruption practices of a multinational bank in a LDC. Through a practice-driven focus, the authors provide “on-the-ground” insights to better understand the complex nature of corruption.

Considering the frequency of extreme events, enhancing the global financial system's stability has become crucial. This study aims to investigate the contagion effects of extreme risk events in the international commodity market on China's financial industry. It highlights the significance of comprehending the origins, severity and potential impacts of extreme risks within China's financial market.

This study uses the tail-event driven network risk (TENET) model to construct a tail risk spillover network between China's financial market and the international commodity market. Combining with the characteristics of the network, this study employs an autoregressive distributed lag (ARDL) model to examine the factors influencing systemic risks in China's financial market and to explore the early identification of indicators for systemic risks in China's financial market.

The research reveals a strong tail risk contagion effect between China's financial market and the international commodity market, with a more pronounced impact from the latter to the former. Industrial raw materials, food, metals, oils, livestock and textiles notably influence China's currency market. The systemic risk in China's financial market is driven by systemic risks in the international commodity market and network centrality and can be accurately predicted with the ARDL-error correction model (ECM) model. Based on these, Chinese regulatory authorities can establish a monitoring and early warning mechanism to promptly identify contagion signs, issue timely warnings and adjust regulatory measures.

This study provides new insights into predicting systemic risk in China's financial market by revealing the tail risk spillover network structure between China's financial and international commodity markets.

The growing availability of naturalistic driving datasets (NDDs) presents a valuable opportunity to develop various models for autonomous driving. However, while current NDDs include data on vehicles with and without intended driving behavior changes, they do not explicitly demonstrate a type of data on vehicles that intend to change their driving behavior but do not execute the behaviors because of safety, efficiency, or other factors. This missing data is essential for autonomous driving decisions. This study aims to extract the driving data with implicit intentions to support the development of decision-making models.

According to Bayesian inference, drivers who have the same intended changes likely share similar influencing factors and states. Building on this principle, this study proposes an approach to extract data on vehicles that intended to execute specific behaviors but failed to do so. This is achieved by computing driving similarities between the candidate vehicles and benchmark vehicles with incorporation of the standard similarity metrics, which takes into account information on the surrounding vehicles' location topology and individual vehicle motion states. By doing so, the method enables a more comprehensive analysis of driving behavior and intention.

The proposed method is verified on the Next Generation SIMulation dataset (NGSim), which confirms its ability to reveal similarities between vehicles executing similar behaviors during the decision-making process in nature. The approach is also validated using simulated data, achieving an accuracy of 96.3 per cent in recognizing vehicles with specific driving behavior intentions that are not executed.

This study provides an innovative approach to extract driving data with implicit intentions and offers strong support to develop data-driven decision-making models for autonomous driving. With the support of this approach, the development of autonomous vehicles can capture more real driving experience from human drivers moving towards a safer and more efficient future.

This paper aims to elucidate how humorous prompts affect tourists’ heritage responsible behaviors (THRBs).

Three scenario-based experiments were conducted through Credamo (an online survey platform). Studies 1 and 2 used a single-factor (language style: humorous vs serious) between-subject design to test the direct and indirect effects of humorous prompts. Study 3 used a 2 (environmental quality: high vs low) × 2 (language style: humorous vs serious) between-subject design to further reveal the boundary condition (environmental quality) of the humor effect.

The results revealed that humorous (vs serious) prompts better persuade tourists to engage in heritage responsible behaviors (HRBs). Content liking mediates the relationship between humorous prompts and THRBs. Moreover, environmental quality significantly moderates the effect of humorous prompts on THRBs, whereby the persuasive effect of humorous prompts is greater in high environmental quality conditions than in low environmental quality conditions.

Destination management organizations can use humor to reduce tourists’ reactance against prompts for behavioral persuasion. Moreover, it is also important to adapt humorous prompts to changes in environmental quality in a timely manner.

Based on psychological reactance theory, the research confirmed the dominant effect of humorous prompts by using content liking as a mediating variable, providing a new research perspective for research on the regulation of THRBs. Moreover, the authors clarified a boundary condition for the persuasiveness of humorous prompts, which helps reinforce the comprehension of humor persuasion.

本研究旨在厘清幽默提示语如何影响游客遗产责任行为的差异效应与过程机制。

本研究利用见数平台开展了三个情景实验。实验1与实验2采用单因素（语言风格：幽默 vs. 严肃）组间实验设计, 验证了幽默提示语对遗产责任行为的直接与间接效应。实验3采用2（语言风格：幽默 vs. 严肃）×2（环境质量：高 vs. 低）组间实验设计进一步揭示环境质量对幽默提示语效果的调节效应。

相较于严肃提示语, 幽默提示语可更好地说服游客产生遗产责任行为。内容喜爱在幽默提示语与遗产责任行为过程中发挥完全中介作用。此外, 环境质量调节了幽默提示语对遗产责任行为的影响, 即幽默提示语（较严肃提示语）仅在环境质量较高的遗产地中具备优势。

遗产地管理组织可使用幽默来降低游客对提示语的心理逆反程度, 从而达到行为说服的目的。与此同时, 管理者也要根据目的地环境质量及时调整幽默提示语的使用策略。

基于心理逆反理论, 本研究以内容喜爱为中介变量, 证实了幽默提示语的优势说服作用, 为游客遗产责任行为管理的相关研究提供了一个新的理论视角。同时, 本研究厘清了幽默提示语在遗产旅游地中的应用边界, 并强化了对幽默说服的理解。

Esta investigación pretende aclarar cómo afecta el humor al efecto persuasivo de la señalización sobre el comportamiento responsable de los turistas respecto al patrimonio.

Se realizaron tres experimentos basados en escenarios a través de Credamo (una plataforma de encuestas en línea). En los estudios 1 y 2 se utilizó un diseño entre sujetos de un solo factor (estilo de lenguaje: humorístico frente a serio) para comprobar los efectos directos e indirectos de los señalización humorísticos. El estudio 3 utilizó un diseño entre sujetos de 2 (calidad del entorno: alta frente a baja) × 2 (estilo lingüístico: humorístico frente a serio) para revelar con más detalle la condición límite (calidad del entorno) del efecto del humor.

Los resultados revelaron que las señalización humorísticas (frente a las serias) persuaden mejor a los turistas a participar en las HRB. El gusto por el contenido influye en la relación entre los señalización humorísticos y las HRB. Además, la calidad del entorno modera de forma significativa el efecto de los señalización humorísticos sobre los THRB, de modo que el efecto persuasivo de los señalización humorísticos es mayor en condiciones de alta calidad del entorno que en condiciones de baja calidad del entorno.

Las organizaciones de gestión de destinos pueden utilizar el humor para reducir la reacción de los turistas ante las señalización a la persuasión conductual. Además, también es importante adaptar oportunamente las señalización humorísticas a los cambios en la calidad del entorno.

Basándonos en la teoría de la reactancia psicológica, nuestra investigación confirmó el efecto dominante de las señalización humorísticas empleando el gusto por el contenido como variable mediadora, proporcionando una nueva perspectiva para la investigación sobre la regulación de las THRB. Además, aclaramos una condición límite para la persuasión de los señalización humorísticos, lo que ayuda a reforzar la comprensión de la persuasión humorística.

This study aims to study the thermal identification issue by harvesting both solar energy and atmospheric thermal updraft for a solar-powered unmanned aerial vehicle (SUAV) and its electric energy performance under continuous soaring conditions.

The authors develop a specific dynamic model for SUAVs in both soaring and cruise modes. The support vector machine regression (SVMR) is adopted to estimate the thermal position, and it is combined with feedback control to implement the SUAV soaring in the updraft. Then, the optimal path model is built based on the graph theory considering the existence of several thermals distributed in the environment. The procedure is proposed to estimate the electricity cost of SUAV during flight as well as soaring, and making use of dynamic programming to maximize electric energy.

The simulation results present the integrated control method could allow SUAV to soar with the updraft. In addition, the proposed approach allows the SUAV to fly to the destination using distributed thermals while reducing the electric energy use.

Two simplified dynamic models are constructed for simulation considering there are different flight mode. Besides, the data-driven-based SVMR method is proposed to support SUAV soaring. Furthermore, instead of using length, the energy cost coefficient in optimization problem is set as electric power, which is more suitable for SUAV because its advantage is to transfer the three-dimensional path planning problem into the two-dimensional.

The aim of this paper is to provide a narrative review of previous research on tourism demand modelling and forecasting and potential future developments.

A narrative approach is taken in this review of the current body of knowledge.

Significant methodological advancements in tourism demand modelling and forecasting over the past two decades are identified.

The distinct characteristics of the various methods applied in the field are summarised and a research agenda for future investigations is proposed.

本文旨在对先前关于旅游需求建模和预测的研究进行叙述性回顾并对未来潜在发展进行展望。

本文采用叙述性回顾方法对当前知识体系进行了评论。

本文确认了过去二十年旅游需求建模和预测方法论方面的重要进展。

本文总结了该领域应用的各种方法的独特特征, 并对未来研究提出了建议。

El objetivo de este documento es ofrecer una revisión narrativa de la investigación previa sobre modelización y previsión de la demanda turística y los posibles desarrollos futuros.

En esta revisión del marco actual de conocimientos sobre modelización y previsión de la demanda turística y los posibles desarrollos futuros,se adopta un enfoque narrativo.

Se identifican avances metodológicos significativos en la modelización y previsión de la demanda turística en las dos últimas décadas.

Se resumen las características propias de los diversos métodos aplicados en este campo y se propone una agenda de investigación para futuros trabajos.

This study aims to examine the reaction of anchor investors (AIs) to pre-IPO earnings management (EM). The authors use the unique detailed bid data from the Indian anchor experiment. The authors also study the reputed AIs’ EM detection ability and pricing behavior in response to pre-IPO EM.

The authors use unique AI bid data for 169 Indian IPO firms. Utilizing the logistic regression and Tobit regression models with industry and year-fixed effects, the authors examine the relationship between various measures of AI participation and proxies of short-term and long-term discretionary accruals.

The authors document that pre-IPO EM is positively associated with the likelihood of anchor backing but negatively related to the likelihood of reputed anchor backing. The findings indicate that AIs are misled by pre-IPO EM, but reputed AIs are not. The authors also observe that reputed AIs, compared to the non-reputed, pay less than the upper band with increasing EM. The findings are robust to using various AI measures and EM proxies.

The findings have significant implications for regulators in the implementation of AI concept in non-anchor markets and better implementation of policies in existing anchor settings. Findings can also be relevant for non-institutional investors in the IPO domain.

This is one of the few studies on institutional investors' IPO bidding behavior in response to pre-IPO EM. However, this is the first study to analyze AIs' IPO bidding behavior in response to pre-IPO EM.

This study aims to examine the impact of China's “Manufacturing and Internet Integration Development Pilot Demonstration Project” (MIP) policy on the digital transformation (DT) and labor structure optimization (LSU) of manufacturing enterprises, reveal the relationship between DT and LSU at the micro level and investigate the mechanism between them.

This study employs MIP as a quasi-natural experiment and develops a time-varying difference-in-difference (DID) model based on a sample of 2,445 Chinese A-share listed manufacturing enterprises in the Shanghai and Shenzhen markets from 2013 to 2021.

The implementation of MIP significantly increases DT by 0.4366 and optimizes LSU by 0.0507. By enhancing the two mediated variables of organizational learning inputs (SI) and employees' personal digital cognition (PDC), DT can optimize the LSU of pilot enterprises by 0.035 and 0.034, according to the results of the mechanism analysis. The study also reveals that the impact of MIP on LSU is highly heterogeneous. With effects of 0.0691 and 0.0632, the optimization effect is more pronounced in state-owned firms and firms with low ownership concentration, respectively.

This study demonstrates the dual effects of the MIP pilot on DT and LSU. In addition, this study pioneers research on the significance of optimizing the labor structure through SI and PDC on the basis of DT, which provides an empirical foundation for the Chinese Government to expand the scope of MIP pilots and revise policy content, as well as for manufacturing enterprises to upgrade the labor structure.

The aggregate index and per capita index have different meanings for some countries or regions. CO₂ emissions per capita matters for China because of its huge population. Therefore, this study aims to deepen the understanding of Kuznets curve from the perspective of CO₂ emissions per capita. In this study, mathematical formulas will be derived and verified.

First, this study verified the existing problems with the environmental Kuznets curve (EKC) through multiple regression. Second, this study developed a theoretical derivation with the Solow model and balanced growth and explained the underlying principles of the EKC’s shape. Finally, this study quantitatively analyzed the influencing factors.

The CO₂ emission per capita is related to the per capita GDP, nonfossil energy and total factor productivity (TFP). Empirical results support the EKC hypothesis. When the proportion of nonfossil and TFP increase by 1%, the per capita CO₂ decrease by 0.041 t and 1.79 t, respectively. The growth rate of CO₂ emissions per capita is determined by the difference between the growth rate of output per capita and the sum of efficiency and structural growth rates. To achieve the CO₂ emission intensity target and economic growth target, the growth rate of per capita CO₂ emissions must fall within the range of [−0.92%, 6.1%].

Inspired by the EKC and balanced growth, this study investigated the relationships between China’s environmental variables (empirical analysis) and developed a theoretical background (macro-theoretical derivation) through formula-based derivation, the results of which are universally valuable and provide policymakers with a newly integrated view of emission reduction and balanced development to address the challenges associated with climate change caused by energy.