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Quantitative and spatial-explicit flood risk information is of great importance for strengthening climate change adaptation and flood resilience. Shanghai is a coastal megacity at large estuary delta with rising flood risks. This study aims to quantify the overall economic-societal risks of storm flooding and their spatial patterns in Shanghai.

Based on multiple storm flood scenarios at different return periods, as well as fine-scale data sets including gridded GDP, gridded population and vector land-use, a probabilistic risk model incorporating geographic information system is used to assess the economic-societal risks of flooding and their spatial distributions.

Our results show that, from 1/200 to 1/5,000-year floods, the exposed assets will increase from USD 85.4bn to USD 657.6bn, and the direct economic losses will increase from USD 3.06bn to USD 52bn. The expected annual damage (EAD) of assets is around USD 84.36m. Hotpots of EAD are mainly distributed in the city center, the depressions along the upper Huangpu River in the southwest, the north coast of Hangzhou Bay, and the confluence of the Huangpu River and Yangtze River in the northeast. From 1/200 to 1/5,000-year floods, the exposed population will rise from 280 thousand to 2,420 thousand, and the estimated casualties will rise from 299 to 1,045. The expected annual casualties (EAC) are around 2.28. Hotspots of casualties are generally consistent with those of EAD.

In contrast to previous studies that focus on a single flood scenario or a particular type of flood exposure/risk in Shanghai, the findings contribute to an understanding of overall flood risks and their spatial patterns, which have significant implications for cost-benefit analysis of flood resilience strategies.

Indoor hallways are the most common and indispensable part of people’s daily life, commercial and industrial activities. This paper aims to achieve high-precision and dense 3D reconstruction of the narrow and long indoor hallway and proposes a 3D, dense 3D reconstruction, indoor hallway, rotating LiDAR reconstruction system based on rotating LiDAR.

This paper develops an orthogonal biaxial rotating LiDAR sensing device for low texture and narrow structures in hallways, which can capture panoramic point clouds containing rich features. A discrete interval scanning method is proposed considering the characteristics of the indoor hallway environment and rotating LiDAR. Considering the error model of LiDAR, this paper proposes a confidence-based point cloud fusion method to improve reconstruction accuracy.

In two different indoor hallway environments, the 3D reconstruction system proposed in this paper can obtain high-precision and dense reconstruction models. Meanwhile, the confidence-based point cloud fusion algorithm has been proven to improve the accuracy of 3D reconstruction.

A 3D reconstruction system was designed to obtain a high-precision and dense indoor hallway environment model. A discrete interval scanning method suitable for rotating LiDAR and hallway environments was proposed. A confidence-based point cloud fusion algorithm was designed to improve the accuracy of LiDAR 3D reconstruction. The entire system showed satisfactory performance in experiments.

In situ 3D reconstruction is the basis for measuring and monitoring large-scale working environments such as construction sites and coal mining surfaces. The purpose of this paper is to address the difficulties of on-site 3D reconstruction in large-scale dynamic environments. Based on panoramic rotating light detection and ranging sensors, a dynamic environment 3D reconstruction method combining occupancy grid and point cloud segmentation is proposed.

The algorithm fully combines the information between point clouds to process the points in the region of interest, improving the processing speed of the occupancy grid method and the accuracy of dynamic object filtering. Furthermore, this paper also proposes an incremental long-short horizon segmentation and reconstruction workflow, which performs different levels of point cloud differential segmentation for various types of dynamic objects.

This paper designs detailed physical and simulation experiments in different environments to verify the advantages and reliability of the algorithm. The entire system showed satisfactory performance in experiments.

The proposed dynamic environment 3D reconstruction method can effectively complete the 3D reconstruction of complex work environments, and the proposed incremental long-short horizon segmentation and reconstruction workflow further improves the accuracy of dynamic object removal.

This study adopts the perspective of dynamic capabilities to investigate influencing factors and proposes improvement strategies of supply chain resilience of prefabricated construction.

The structural equation model (SEM) is used to identify and verify the relationship between factors influencing supply chain resilience of prefabricated construction from the perspective of dynamic capabilities. The system dynamics (SD) model is constructed to dynamically simulate the specific effects of different influencing factors.

Results indicate that: (1) An evaluation index system for supply chain resilience of prefabricated construction containing five first-level indicators and 36 second-level indicators is constructed; (2) Ability to anticipate, ability to respond, ability to adapt, ability to recover and ability to learn are positively correlated with the supply chain resilience of prefabricated construction and (3) ANT3 (information system), RES1 (quick response), ADA3 (buffer stock) and LEA4 (trust) are the most leading factors influencing supply chain resilience of prefabricated construction over time.

This study fulfills the need for an in-depth exploration of the various influencing factors on supply chain resilience of prefabricated construction from the perspective of dynamic capabilities. Furthermore, this study provides improvement strategies to enhance supply chain resilience of prefabricated construction in China.

This paper aims to test the effects of social presence (SP) and other related factors, including trust, self-construal and brand familiarity, in affecting consumers’ purchase intention of live-streaming workout courses.

Three between-subjects, Web-based experimental studies were conducted. There were separately 108, 208 and 284 valid questionnaires collected in the three studies. Moderation and mediation analyses were performed to test the research hypotheses.

Users’ sense of SP when watching live-streaming courses positively affects their willingness to purchase courses, and users’ sense of trust plays a mediating role in the influence of users’ SP on their purchase intention. In addition, when users belong to dependent self-construal rather than independent self-construal, their trust in live-streaming courses plays a stronger mediating role in the influence of users’ SP on their purchase intentions. What is more, when users have high brand familiarity rather than low brand familiarity, their trust in online live-streaming plays a stronger mediating role in the influence of users’ SP on their purchase intentions.

This research delineates the effects of SP on the consumption of live-streaming courses, thus further adding to the understanding of the role of real-time interaction in determining consumer behavior. It also highlights the roles of self-construal and brand familiarity as mediating influences on the relationship between SP and consumer trust.

The purpose of this study is to examine whether and how financial performance feedback influences green innovation performance by drawing on the behavioral theory of the firm (BTOF) and relying on motivation-based logic.

A total of 17,558 firm-year observations from 3,062 publicly traded firms in China are used as the research sample.

The results reveal that low-performing firms are less likely to conduct green innovation activities because managers burden pressure to meet short-term targets. This study further finds that these relations are moderated by institutional ownership.

This study contributes to the BTOF literature by linking performance feedback to green innovation activities. This study applies a motivation-based logic to relate performance below and above aspirations to green innovation activities. This study introduces institutional ownership as a boundary condition.

Some papers have investigated the complex factors impacting building information modeling (BIM) application in prefabricated buildings (PBs), but few paid attention to their interaction relationships. Ignoring the fact that different factors are not isolated may lead to some key factors being overlooked without appropriate improvement strategies being proposed. This paper aims to analyze those factors and their inter-relationships, with the view to identify the critical factors and their interaction relationships so as to derive constructive strategies that would effectively facilitate BIM adoption in Chinese prefabrication.

First, factors influencing BIM application in prefabrication are extracted and collated by literature review, expert interview and analysis of PBs characteristics. Thereafter, an evaluation laboratory (decision-making trial and evaluation laboratory) and interpretive structural modeling are used to explore the relationships and hierarchy among the factors. Based on the degree of cause and centrality, critical factors are extracted and the interaction relationship are investigated.

The results show that BIM policies and standards for PBs are the main causal factors. The maturity of BIM software and BIM data interface for PBs, willingness to share data, the strategic goals of the enterprise, BIM law and BIM input and benefit are the main transitional factors while BIM staff and workflow, enterprise attitude, distribution of BIM liability and cooperation of participants are the main direct factors.

Based on the above findings, corresponding improvement strategies are proposed so as to promote BIM application in prefabrication and the rapid development of China’s PBs efficiently.

This study explores the formation process of cognitive destination image among first-time Chinese millennial tourists visiting Iran.

Employing a comprehensive mixed-method exploratory approach, blending qualitative and quantitative methodologies, we aim to construct a conceptual model explaining the complex process of tourists’ cognitive destination image development. In the qualitative phase, interviews with 15 Chinese millennials unveiled key factors such as perceived behavioral control, perceived product quality, on-site involvement, engagement, and prior destination image as fundamental influencers of tourists’ cognitive destination image. Subsequently, in the quantitative phase, involving a questionnaire survey with 229 first-time Chinese travelers, we proposed a conceptual model to validate our primary findings.

The results highlight the emergence of on-travel cognitive image as a developmental concept originating from tourists' on-site participation and pre-existing perceptions of the destination. Moreover, we identified perceived behavioral control as the primary antecedent of millennials’ image formation, directly affecting the destination’s image development. Furthermore, increased involvement and engagement were found to diminish perceived behavioral control. Additionally, perceived product quality prompted millennials to engage more with cultural attractions and activities, enriching their in-situ image.

The findings offer valuable insights for destination managers, enabling them to construct tailored strategies to augment the cognitive destination image.

This study provides a novel understanding of the cognitive destination image formation process among Chinese millennial tourists, highlighting the crucial role of perceived behavioral control, involvement, engagement, and perceived product quality. These insights can guide destination managers in enhancing the overall tourist experience and destination appeal.