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Modern subway transportation systems need to satisfy increasing safety demands to rapidly evacuate passengers under hazardous emergency circumstances, such as fires, accidents or terrorist attacks, to reduce passenger injuries or life losses. The emergency evacuation capacity (EEC) of a subway station needs to be revised timely, in case passenger demand increases or the evacuation route changes in the future. However, traditional ways of estimating EEC, e.g. fire drills are time- and resource-consuming and are difficult to revise from time to time. The purpose of this study is to establish an intuitive modelling approach to increase the EEC of subway stations in a stepwised manner.

This study develops an approach to combine agent-based evacuation modelling and building information modelling (BIM) technology to estimate the total evacuation time of a subway station.

Evacuation time can be saved (33% in the studied case) from iterative improvements including stopping escalators running against the evacuation flow and modifying the geometry around escalator exits. Such iterative improvements rely on integrating agent-based modelling and BIM.

The agent-based model can provide a more realistic simulation of intelligent individual movements under emergency circumstances and provides precise feedback on locations of evacuation bottlenecks. This study also examined the effectiveness of two rounds of stepwise improvements in terms of operation or design to increase the EEC of the station.

This study aims to construct alternative models to establish the dynamic relationship between exchange rates and housing affordability by estimating both the short- and long-run relationship between exchange rates and housing affordability for 18 OECD countries from 1975Q1 to 2022Q4. After that, this study demonstrates how this nexus behaves during high and low inflation regimes and turbulent times.

This study uses the panel autoregressive distributed lag technique to examine the nexus between housing affordability to capture the distinct characteristics of the sample countries and estimate various short- and long-run dynamics in the relationship between housing affordability and exchange rate.

Exchange rate appreciation improves housing affordability in the short run, whereas this connection tends to dissipate in the long run. Moreover, inflation can worsen housing affordability during turbulent times, such as the global financial crisis, in both the short and long run. Ignoring these changes in the relationship between exchange rates and housing affordability during turbulent times can lead to incorrect conclusions.

To the best of the authors’ knowledge, this study is the first to examine the association between exchange rates and housing affordability by demonstrating how these variables behave in high and low inflation regimes and turbulent times.

The purpose of this study is to design and process the optimal V-shaped microstructure for 7075 aluminum alloy and reveal its wear resistance mechanism and performance.

The hydrodynamic pressure lubrication models of the nontextured, V-shaped, circular and square microtextures are established. The corresponding oil film pressure distributions are explored. The friction and wear experiments are conducted on a rotating device. The effects of the microstructure shapes and sizes on the wear mechanisms are investigated via the friction coefficients and surface morphologies.

In comparison, the V-shaped microtexture has the largest oil film carrying capacity and the lowest friction coefficient. The wear mechanism of the V-shaped microtexture is dominated by abrasive and adhesive wear. The V-shaped microtexture has excellent wear resistance under a side length of 300 µm, an interval of 300 µm and a depth of 20 µm.

This study is conductive to the design of wear-resistant surfaces for friction components.

The interruption event will seriously affect the normal operation of urban rail transit lines,causing a large number of passengers to be stranded in the station and even making the train stranded in the interval between stations. This study aims to reduce the impact of interrupt events and improve service levels.

To address this issue, this paper considers the constraints of train operation safety, capacity and dynamic passenger flow demand. It proposes a method for adjusting small loops during interruption events and constructs a train operation adjustment model with the objective of minimizing the total passenger waiting time. This model enables the rapid development of train operation plans in interruption scenarios, coordinating train scheduling and line resources to minimize passenger travel time and mitigate the impact of interruptions. Regarding the proposed train operation adjustment model, an improved genetic algorithm (GA) is designed to solve it.

The model and algorithm are applied to a case study of interruption events on Beijing Subway Line 5. The results indicate that after solving the constructed model, the train departure intervals can be maintained between 1.5 min and 3 min. This ensures both the safety of train operations on the line and a good match with passengers’ travel demands, effectively reducing the total passenger waiting time and improving the service level of the urban rail transit system during interruptions. Compared to the GA algorithm, the algorithm proposed in this paper demonstrates faster convergence speed and better computational results.

This study explicitly outlines the adjustment method of using short-turn operation during operational interruptions, with train departure times and station stop times as decision variables. It takes into full consideration safety constraints on train operations, train capacity constraints and dynamic passenger demand. It has constructed a train schedule optimization model with the goal of minimizing the total waiting time for all passengers in the system.

This study aims to outline the research field of initial public offerings (IPOs) pricing and performance by combining bibliometric analysis with a systematic literature review process.

The study uses over three decades of IPO publication records (1989–2020) from Scopus and Web of Science databases. An analysis of keyword co-occurrence and bibliometric coupling was used to gain insights into the evolution of IPO literature.

The study categorized the IPO research field into four primary clusters: IPO pricing and short-run behaviour, IPO performance and influence of intermediaries, venture capital financing and top management and political affiliations and litigation risks. The results offer a framework for delineating research advancements at different stages of IPOs and illustrate the growing interest of researchers in IPOs in recent years. The study identified future research potential in the areas of corporate governance, earning management and investor sentiments related to IPO performance. Similarly, the study highlighted the opportunity to test multiple theoretical frameworks on alternative investment platforms (SME IPO platforms) operating under distinct regulatory environments.

To the best of the authors’ knowledge, this paper represents the first instance of using both bibliometric and systematic review to quantitatively and qualitatively review the articles published in the area of IPO pricing and performance from 1989 to 2020.

The author examines the impact these efficient factors have on factor model comparison tests in US returns using the Bayesian model scan approach of Chib et al. (2020), and Chib et al.(2022).

Ehsani and Linnainmaa (2022) show that time-series efficient investment factors in US stock returns span and earn 40% higher Sharpe ratios than the original factors.

The author shows that the optimal asset pricing model is an eight-factor model which contains efficient versions of the market factor, value factor (HML) and long-horizon behavioral factor (FIN). The findings show that efficient factors enhance the performance of US factor model performance. The top performing asset pricing model does not change in recent data.

The author is the only one to examine if the efficient factors developed by Ehsani and Linnainmaa (2022) have an impact on model comparison tests in US stock returns.

This study aims to develop a moderated mediation model to explain the practices of supply base management and how they can achieve innovation performance, and the authors explore the boundary conditions of this implementation mechanism.

The authors used the bootstrap procedure to conduct empirical tests on 328 Chinese manufacturers to verify the proposed model.

The results showed that supplier innovation focus, supply-base structuring and long-term relationship focus have a positive impact on innovation performance through supplier innovativeness, and the mediation performs differently under technology and demand uncertainty.

The authors only focused on innovation performance, and it does not explore the links between supply base management and other performance outcomes. This study involves part of the supply network which is easier to manage, i.e. supply base. The authors ignored the importance of other members in supply network. Finally, the data obtained in this study belong to the cross-sectional data during the same period but it accomplishes the research aim well.

The focal firm needs to improve their supply base composition, establish permeable organizational boundaries, and build long-term strategic partnerships characterized by equality and trust with suppliers to stimulate supply base members to make innovative contributions.

This study complements the implementation path of manufacturers around innovation, emphasizing multidimensional characteristics of supply base management. And this study clarifies the mechanism and boundary conditions between supply base management and innovation performance.

This study aims to clarify why and when digital business strategy (DBS) helps manufacturing firms generate value co-creation (VC) with different stakeholders in the digital context of China. This study considers external network capability (ENC) and internal network capability (INC) as mediation mechanism, and strategic flexibility (SF) as theoretical boundary.

Questionnaires were used and filled out by executives from manufacturing firms. The manufacturing samples from 289 different fields in China were used for hypothesis testing, and the structural equation model was the main analytical method.

This study found that DBS of manufacturing enterprises has a positive impact on VC. Specifically, DBS affects firm-partner VC and firm-consumer VC through the indirect positive effect of ENC, and affects firm-employee VC through INV. The positive effects of ENC on firm-partner VC and firm-consumer VC, as well as INC on firm-employee VC, are weak at high (or low) SF, and are strongest at moderate SF.

This study provides manufacturing firms with practical insights into why and when they can implement DBS to generate VC, with a particular emphasis on the weighted role of SF.

This study spotlights gaps in the literature on why and when manufacturing firms can reap the benefits of DBS, focusing on one important business outcome – VC. The authors clarify the mediating role of differences in ENC and INC, as well as the inverted U-shaped moderating role of SF.

The purpose of this paper is to explore the determinants of entrepreneurs’ subjective social status perception (SSP) on firm international behaviors based on the upper echelons theory and social class theory.

To test the hypotheses, the authors studied a large sample of 10,823 small- and medium-sized private Chinese enterprises from 2006 to 2014.

The results showed that entrepreneurs with higher status perception prefer international activity and firms have higher export intensity and intention. In addition, the social capital of entrepreneurs and institutional environment amplifies the positive relationship between SSP and international behavior.

This paper contributes to research on the upper echelon of management and extends our understanding of how managerial social characteristics influence international strategic decision-making. Besides, it also contributes to the emerging stream of social status research in international expansion studies and expand researchers’ limited understanding of the effects of social status in business settings.

Given the growing preference for internet celebrity restaurants, it is crucial to explore how internet celebrity restaurants can maintain customer loyalty. Therefore, this study aims to examine the connections between brand cognition [emotion value, brand symbol (BS) and brand experience (BE)], brand resonance (BR) and revisit intention.

In this paper, the authors use a theoretical model to test the relationship between cognition and intention. A total of 366 volunteers were recruited to participate in this research. Hypothesis testing and a moderated mediation model were used to measure the results.

BR acts as a mediator in the interaction between emotion value, BS, experience and repurchase intention (RI). Surprisingly, the authors also discover that electronic word-of-mouth (e-WOM) acceptance negatively modifies the relationship between brand cognition and BR. Internet exposure (IE) helps consumers perceive BE and BSs more favorably.

Managers should be aware of how internet celebrity BR is built. Specifically, they can use cultural or emotional elements to maintain relationships with consumers. Furthermore, to lessen the negative consequences of e-WOM, managers should work to maintain positive WOM consistency.

The research advances our knowledge of RI in internet celebrity restaurants settings. This study pioneers an investigation of how brand cognition is related to RI through BR’s mediating effect. It enriches this research perspective of the emerging restaurant literature. By analyzing the boundary impact of internet transmission on resonance, it also advances the literature.