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This paper aims to elucidate the pivotal role of Digital Twin (DT) technology in addressing the adverse impacts of Urban Heat Island (UHI) and consolidate the fragmented knowledge of DT technology in urban environments by identifying applied actions, proposing an approach and revealing challenges for tackling UHI effects.

Using a systematic literature review, 24 materials were retrieved from scholarly databases to provide a comprehensive understanding of DT technology and propose a conceptual framework for mitigating UHI effects.

The results revealed three major study categories within the DT and UHI domains: (1) DT-enabled actions for urban greenery optimisation, (2) DT implementation for enhancing resilience in urban planning and (3) increasing the fidelity level of DT for addressing UHI effects. Additionally, this paper introduces REFLECT, a conceptual DT-enabled framework consisting of seven layers: Retrieve, Establish, Facilitate, Lump, Examine, Cognition and Take. The framework proposes developing a systems-based model with identifiable scopes, strategies and factors through a multilayered platform, specifying model input, process and output towards mitigating UHI effects.

This paper contributes to the discourse on sustainable urban development by highlighting the challenges associated with DT technology in mitigating UHI. It introduces a conceptual framework to demonstrate applications and directions for developing innovative solutions to unlock the full potential of DT technology in mitigating UHI effects.

The theme park industry has attracted wide attention and visitors’ perceptions are key to improving theme park management. Applying the cognitive-affective theory, this study aims to explore various cognitive attributes and affective attitudes and how they affect the overall theme park image.

A mixed research method was used to analyze tourists’ cognitive, affective and overall evaluations of theme parks through text mining and logistic regression and to verify their internal relationships.

Study 1 confirms the impact of six features of theme parks, including food and beverage consumption, merchandising, spatiality, immersive technologies, interactive performances and thematization. Study 2 reveals that finer-grained emotions such as goodness, sadness, disgust, surprise, fear, joy and anger are present in visitor reviews. Study 3 confirms the significant influence of cognitive characteristics and emotions related to theme parks on the overall image through regression analysis. The findings carry meaningful implications for theme park managers, offering guidance on customer needs, perceived negative attributes and how to improve visitor experiences.

This study explores the attribute characteristics of cognitive and affective images of theme parks and their influence on the overall image, thereby enriching the research on the connotations of cognitive-affective theory. In particular, this study introduces and quantitatively analyses the concept of theme parks for the first time through a large-scale data analysis, which empirically reconciles the contradictions of previous reviews of different definitions of theme parks.

主题公园评论：文本挖掘的认知特征和情感如何决定主题公园形象

摘要

主题公园行业备受关注, 而游客的看法是改进主题公园管理的关键所在。本研究运用认知-情感理论, 旨在探索游客评论的认知属性与情感态度, 以及它们如何影响主题公园的整体形象。

采用混合研究方法, 通过文本挖掘和逻辑回归分析游客对主题公园的认知、情感及总体评价, 并验证它们之间的内在关系。

研究1证实了主题公园的六个特征所产生的影响, 包括餐饮消费、商品销售、空间性、沉浸式技术、互动表演和主题化。研究2表明, 游客评价中存在更细化的情感, 如好感、悲伤、厌恶、惊讶、恐惧、喜悦和愤怒。研究3通过回归分析证实了与主题公园相关的认知和情感特征对整体形象具有显著影响。这些研究结果对主题公园管理者具有重要意义, 为了解客户需求、识别负面属性以及如何改善游客体验提供了指导。

本研究对主题公园认知和情感形象的属性特征及其对整体形象的影响进行了探索, 从而丰富了认知-情感理论内涵。特别是本研究首次通过引入大规模数据并量化分析了主题公园的概念, 从实证角度调和了以往针对主题公园不同定义的相关评论中存在的矛盾。

Reseñas de parques temáticos: cómo la minería de textos de las características cognitivas y las emociones pueden determinar la imagen del parque temático

Resumen

El sector de los parques temáticos ha atraído una gran atención y las percepciones de los visitantes son clave para mejorar su gestión. Aplicando la teoría cognitivo-afectiva, este estudio pretende explorar diversos atributos cognitivos y actitudes afectivas, y cómo afectan a la imagen global del parque temático.

Se adoptó un enfoque de investigación de métodos mixtos para analizar las evaluaciones cognitivas, afectivas y globales de los turistas sobre los parques temáticos mediante minería de textos y regresión logística, y para validar la relación intrínseca entre ellas.

El estudio 1 confirmó el impacto de seis características de los parques temáticos, como el consumo de alimentos y bebidas, el merchandising, la espacialidad, las tecnologías inmersivas, los espectáculos interactivos y la tematización. El estudio 2 reveló la presencia de emociones más sutiles en las evaluaciones de los visitantes, como la bondad, la tristeza, el asco, la sorpresa, el miedo, la alegría y la ira. El estudio 3 confirmó, mediante un análisis de regresión, que las características cognitivas y las emociones asociadas a los parques temáticos tienen un efecto significativo en la imagen global. Estas conclusiones tienen importantes implicaciones para los gestores de los parques temáticos, ya que proporcionan orientación para comprender las necesidades de los clientes, identificar los atributos negativos percibidos y saber cómo mejorar las experiencias de los visitantes.

Este estudio explora las características de los atributos de las imágenes cognitivas y afectivas de los parques temáticos y su impacto en la imagen global, enriqueciendo así la investigación sobre las connotaciones de la teoría cognitivo-afectiva. En particular, este estudio introduce y analiza cuantitativamente por primera vez el concepto de parque temático mediante un análisis de datos a gran escala, que concilia empíricamente las contradicciones que existían en revisiones anteriores de las distintas definiciones de parque temático.

The study aims to pioneer an innovative approach for the evaluation of government portal websites (GPWs) by introducing an eye-tracking-based method. The research meticulously pinpoints and analyses the distinct usability issues and challenges that users encounter while navigating and interacting with GPWs.

This study devises an eye-tracking-based GPW usability evaluation approach, which focuses on the major functions (i.e. government information disclosure, government services and interactive responses) of GPWs. An Entropy Weighted Technique for Order Preference by Similarity to an Ideal Solution (EW-TOPSIS) method is employed to process eye-tracking indicator results for deriving GPW usability results.

The proposed approach is demonstrated to assess the usability of 12 GPWs in pilot smart cities in China, and it is found that most GPWs have lower-than-average usability. GPWs with low usability require more cognitive load that exhibit increased fixation and saccade. The comparisons among the GPW usability results from (1) the eye-tracking experiment, (2) questionnaire surveys and (3) the ready-made performance evaluation report validate the effectiveness of eye-tracking-based GPW usability evaluation.

The work contributes to shifting the GPW usability evaluation approach from a subjective judgment paradigm to an objective paradigm, as well as provides implications for enhancing GPW usability, including improving search function, reducing website complexity and prioritizing user needs.

This paper provides a thorough examination of the advancements and impacts of artificial intelligence (AI) on construction management (CM) over the past five years, particularly focusing on its role in mitigating prevalent challenges such as inefficiency and ensuring quality. By methodically reviewing and synthesizing the body of research conducted in this period, it underscores key contributions and breakthroughs in the application of AI within construction management (AICM). Additionally, the study aims to shed light on emerging trends and forecast future directions for technological innovation in the construction management sector.

Guided by the preferred reporting items for systematic reviews and meta-analyses (PRISMA) framework, this research conducts a bibliometric analysis of 176 relevant publications from the past five years. The analysis focuses on the adoption of AICM across three critical areas: construction equipment management, improvement of construction safety and construction cost optimization. Additionally, the study systematically identifies and examines 14 emerging themes within this domain, ensuring a comprehensive exploration aligned with PRISMA guidelines.

This manuscript summarizes recent research from the past five years in three key areas: construction equipment management, construction safety management and construction cost management within the realm of AICM. It identifies key gaps and outlines future research directions, including enhancing AI-driven equipment integration, developing sophisticated AI-based safety systems and optimizing cost management with advanced data analytics. These findings and directions are essential for steering the field toward greater digital innovation and sustainability.

This research provides a detailed analysis of the literature within the AICM domain, thoughtfully compiling significant findings and highlighting the importance of addressing user needs. The insights and recommendations shared aim to be beneficial for both academic researchers and industry professionals, contributing to the ongoing development of AICM as it moves toward a future characterized by digital innovation and sustainability.

The combination of improved PSO (IPSO) algorithm and artificial neural network (ANN) model for intelligent monitoring of the bearing performance of the hydrostatic turntable.

This paper proposes an artificial neural network model based on IPSO algorithm for intelligent monitoring of hydrostatic turntables.

The theoretical model proposed in this paper improves the accuracy of the working performance of the static pressure turntable and provides a new direction for intelligent monitoring of the static pressure turntable. Therefore, the theoretical research in this paper is novel.

Theoretical novelties: an ANN model based on the IPSO algorithm is designed to monitor the load-bearing performance of a static pressure turntable intelligently; this study show that the convergence accuracy and convergence speed of the IPSO-NN model have been improved by 52.55% and 10%, respectively, compared to traditional training models; and the proposed model could be used to solve the multidimensional nonlinear problem in the intelligent monitoring of hydrostatic turntables.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-03-2024-0081/

This study expanded the model of technology acceptance and investigated how the relationship between usefulness, ease of use, efficiency, personalization, safety and security and behavioural intention differ on Gen Z and silver tourists toward smart hotel. This study further applies multiple group analysis to examine whether there are substantial differences among these two groups of respondents.

Using an online survey, this study was undertaken with Gen Z and silver tourists in mainland China who had stayed in smart hotel over the past 12 months. A total of 474 valid responses were collected. Structural equation modelling and multigroup analysis were employed to test the proposed relationships.

This study revealed that personalization did not affect the behavioural intention among Gen Z tourists, meanwhile, there is no positive relationship between usefulness, efficiency and behavioural intention on silver group. Additionally, the findings revealed that there are no substantial differences among Gen Z (digital natives) and silver customers (digital immigrants) regarding smart hotel behavioural intentions.

This study offers strategic guidance for hotel managers to design and reposition smart hotel based on different customer sectors. Further, important implications for smart devices manufacturers are also provided to improve the functioning of hotel service robots.

This is the first study to compare the drivers and outcomes of behavioural intentions among different age groups of tourists toward smart hotels.

The concept of cost stickiness has emerged as a crucial factor affecting organizational resilience. While prior literature has mainly focused on the short-term performance implications of cost stickiness, this study aims to investigate its influence on organizational resilience over the long term.

Using data from Chinese A-share listed companies spanning from 2010 to 2019, we examine how cost stickiness impacts organizational resilience and explore the underlying mechanisms. This study contributes to the theoretical understanding of cost stickiness and organizational resilience and offers practical insights for businesses aiming to strengthen their resilience amid economic uncertainties.

Our findings suggest that cost stickiness not only promotes sustained performance growth and stabilizes financial outcomes but also enhances organizational resilience. Moreover, we find that macroeconomic policy uncertainty and micro-level corporate governance positively moderate the relationship between cost stickiness and organizational resilience. Additionally, our analysis reveals that organizational slack plays a partial mediating role in this relationship.

It is essential to clarify the concepts of cost and cost stickiness. Enterprises should scientifically implement the policy concept of “cutting overcapacity and reducing costs” while maintaining a reasonable cost stickiness.

Shareholders and institutional investors of enterprises should pay close attention to the behavior of managers to reduce the possibility of “inferior” stickiness due to agency problems. Both external institutional investors and inner shareholders play essential roles in supervising managers.

Enterprises should focus on cultivating organizational resilience. Resilience is vital for an enterprise to adapt quickly to external changes, overcome adversity, and make progress. Enterprises should reduce the excessive emphasis on short-term performance, focus on long-term development, cultivate strategic thinking, and establish a corporate culture.

The results show that cost stickiness can enhance organizational resilience. Economic policy uncertainty, the shareholding ratio of institutional investors, and the shareholding ratio of the largest shareholder can inhibit the opportunistic behavior of management, thereby positively regulating the relationship between cost stickiness and organizational resilience.

Ensuring the safety of structures is important. However, when a structure possesses both an implicit performance function and an extremely small failure probability, traditional methods struggle to conduct a reliability analysis. Therefore, this paper proposes a reliability analysis method aimed at enhancing the efficiency of rare event analysis, using the widely recognized Relevant Vector Machine (RVM).

Drawing from the principles of importance sampling (IS), this paper employs Harris Hawks Optimization (HHO) to ascertain the optimal design point. This approach not only guarantees precision but also facilitates the RVM in approximating the limit state surface. When the U learning function, designed for Kriging, is applied to RVM, it results in sample clustering in the design of experiment (DoE). Therefore, this paper proposes a FU learning function, which is more suitable for RVM.

Three numerical examples and two engineering problem demonstrate the effectiveness of the proposed method.

By employing the HHO algorithm, this paper innovatively applies RVM in IS reliability analysis, proposing a novel method termed RVM-HIS. The RVM-HIS demonstrates exceptional computational efficiency, making it eminently suitable for rare events reliability analysis with implicit performance function. Moreover, the computational efficiency of RVM-HIS has been significantly enhanced through the improvement of the U learning function.

This study investigates the causal relationship and mechanisms between the development of digital finance and household carbon emissions. Its objective is to explore how digital finance can influence the carbon footprint at the household level, aiming to contribute to the broader understanding of financial innovations' environmental impacts.

The research combines macro and micro data, employing input-output analysis to utilize data from the China Household Finance Survey (CHFS) for the years 2013, 2015, 2017, and 2019, national input-output tables, and Energy Statistical Yearbooks. This approach calculated CO2 emissions at the household level, including the growth rate of household carbon emissions and per capita emissions. It further integrates the Peking University Digital Financial Inclusion Index of China (PKU-DFIIC) for 2012–2018 and corresponding urban economic data, resulting in panel data for 7,191 households across 151 cities over four years. A fixed effects model was employed to examine the impact of digital finance development on household carbon emissions.

The findings reveal that digital finance significantly lowers household carbon emissions. Further investigation shows that digital transformation, consumption structure upgrades, and improved household financial literacy enhance the restraining effect of digital finance on carbon emissions. Heterogeneity analysis indicates that this mitigating effect is more pronounced in households during the nurturing phase, those using convenient payment methods, small-scale, and urban households. Sub-index tests suggest that the broadening coverage and deepening usage of digital finance primarily drive its impact on reducing household carbon emissions.

The paper recommends that China should continue to strengthen the layout of digital infrastructure, leverage the advantages of digital finance, promote digital financial education, and facilitate household-level carbon emission management to support the achievement of China's dual carbon goals.

The originality of this paper lies in its detailed examination of the carbon reduction effects of digital finance at the micro (household) level. Unlike previous studies on carbon emissions that focused on absolute emissions, this research investigates the marginal impact of digital finance on relative increases in emissions. This method provides a robust assessment of the net effects of digital finance and offers a novel perspective for examining household carbon reduction measures. The study underscores the importance of considering heterogeneity when formulating targeted policies for households with different characteristics.

We attempt to construct a grey three-way conflict analysis model with constraints to deal with correlated conflict problems with uncertain information.

In order to address these correlated conflict problems with uncertain information, considering the interactive influence and mutual restraints among agents and portraying their attitudes toward the conflict issues, we utilize grey numbers and three-way decisions to propose a grey three-way conflict analysis model with constraints. Firstly, based on the collected information, we introduced grey theory, calculated the degree of conflict between agents and then analyzed the conflict alliance based on the three-way decision theory. Finally, we designed a feedback mechanism to identify key agents and key conflict issues. A case verifies the effectiveness and practicability of the proposed model.

The results show that the proposed model can portray their attitudes toward conflict issues and effectively extract conflict-related information.

By employing this approach, we can provide the answers to Deja’s fundamental questions regarding Pawlak’s conflict analysis: “what are the underlying causes of conflict?” and “how can a viable consensus strategy be identified?”