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To evacuate passengers arriving at intercity railway stations efficiently, metros and intercity railways usually share the same station or have stations close to each other. When intercity trains arrive intensively, a great number of passengers will burst into the metro station connecting with the intercity railway station within a short period, while the number of passengers will decrease substantially when intercity trains arrive sparsely. The metro timetables with regular headway currently adopted in real-world operations cannot handle the injected passenger demand properly. Timetable optimization of metro lines connecting with intercity railway stations is essential to improve service quality.

Based on arrival times of intercity trains and the entire process for passengers transferring from railway to metro, this paper develops a mathematical model to characterize the time-varying demand of passengers arriving at the platform of a metro station connecting with an intercity railway station. Provided the time-varying passenger demand and capacity of metro trains, a timetable model to optimize train departure time of a bi-direction metro line where an intermediate station connects with an intercity railway station is proposed. The objective is to minimize waiting time of passengers at the connecting station. The proposed timetable model is solved by an adaptive large neighborhood search algorithm.

Real-world case studies show that the prediction accuracy of the proposed model on passenger demand at the connecting station is higher than 90%, and the timetable model can reduce waiting time of passengers at the connecting station by 28.47% which is increased by 5% approximately than the calculation results of the generic algorithm.

This paper puts forward a model to predict the number of passengers arriving at the platform of connection stations via analyzing the entire process for passengers transferring from intercity trains to metros. Also, a timetable optimization model aiming at minimizing passenger waiting time of a metro line where an intermediate station is connected to an intercity railway station is proposed.

Entrepreneurship-related research in management and organizational journals has experienced rapid growth, particularly in the last several years. The purpose of this study is to identify the researchers and universities that have had the greatest influence on entrepreneurship research since the turn of the century. Using a systematic and comprehensive study identification protocol, the authors delve into the individual and institutional actors contributing to scholarship in entrepreneurial studies for the period from 2000 to 2015. Examination of top-tier management and organizational journals revealed that a total of 371 entrepreneurship-related articles were published during this period by 618 authors from 303 different institutions. Rankings for the most prolific individuals as well as institutions, adjusted and unadjusted for journal quality, are presented. The article concludes with a discussion of the limitations and implications of the research undertaken here.

This study aims to construct a double layer heat insulation coating based on hollow glass microspheres (HGMs) and to investigate the effect of particle size on barrier property and heat insulation performance.

The waterborne double layer coating was composed of an anticorrosive epoxy ester primer and an HGM-containing silicone acrylic topcoat. With varied HGM sizes (20 μm, 40 μm, 60 μm and a 1:3 w/w mixture of 20 and 60 μm particles), the coating was immersed in 3.5 wt% NaCl solution for 28 days and was then subjected to a salt spray test for 450 h. The barrier properties of the coating were evaluated through electrochemical impedance spectroscopy. Heat insulation performance was examined using a self-made device.

The addition of HGMs decreased the barrier properties of the coating by creating particle/resin interfaces for water penetration. In the HGMs-containing coatings, the use of larger HGMs showed relatively good barrier properties because of the lower particle density. The coating with smaller particles yielded a higher heat insulating capacity as indicated by lower equilibrium temperatures.

Future work will be focused on improving the barrier properties of the coating. Field exposure tests should also be performed to assess the long-term performance of the coating.

The mechanical properties of the coatings in this study also implied that HGMs can be used to develop scratch-resistant and impact-resistant coatings. Other potential applications for further studies include the uses of HGMs for coatings with improved fire retardancy and electromagnetic interference shielding.

A double layer coating was developed to provide balanced performance on both anticorrosion and heat insulation. The effects of HGM size were particularly highlighted.

The purpose of this paper is to find the optimal environmental quality criteria for a strategic eco-labeling authority with three objectives (i.e. maximizing the aggregate environmental quality, maximizing the industry profit and maximizing the social welfare). Particularly, the authors investigate how the existence of imperfectly informed consumers affects labeling criteria determination and competition among firms.

A game-theoretic modeling approach was adopted in this paper. A three-stage sequential game was modeled and backward induction was used to solve for a subgame perfect Nash equilibrium. To investigate the impacts of the existence of imperfectly informed consumers, the equilibrium, if all consumers are perfectly informed of the eco-label, was studied as a benchmark.

A more strict eco-labeling criterion improves revenues for both the labeled and unlabeled firms. It is interesting to find that the eco-labeling criteria to maximize industry profits are stricter than the criteria to maximize social welfare. Moreover, when the fraction of imperfectly informed consumers increases, the eco-labeling criteria to maximize aggregate environmental quality or industry profits will be more strict, while the criteria to maximize the social welfare will be looser.

The authors analyze the equilibrium strategies for firms against the eco-labeling criteria certified by authority with different objectives. The obtained optimal labeling strategies could provide insightful guidelines for the certifying authority to select the best suitable labeling criteria to achieve its goals.

The purpose of this paper is to obtain the optimal N₂/Ar ratio parameters for preparing Ta (C, N) coating. Three coatings with different N₂/Ar ratios were prepared on the TA15 substrate, and their effects on the wear properties of the coatings were discussed.

Ta(C, N) coatings with three different N₂/Ar ratios were prepared on TA15 substrates using the double cathode glow metallurgical plasma alloying technique (DGMPA) using a step-by-step diffusion method.

With the increase of N₂/Ar flow ratio, the hardness and elastic modulus of the coating first increase and then decrease. Compared with the S1 sample (N₂/Ar gas ratio 25: 75) and the S3 sample (N₂/Ar gas ratio 75: 25), the S2 sample (N₂/Ar gas ratio 50: 50) has better mechanical properties, with hardness increased by 48.45% and 6.8%, respectively, and elastic strain ratio increased by 22.8% and 28.5%, respectively. Moreover, the wear degree of the S2 sample is less than other samples. The wear rate of the S2 sample was 32.4% lower than the S3 sample at 300°C and 14.3% lower than the S3 sample at 500°C. Therefore, the S2 sample has the best mechanical properties and the best high temperature wear resistance.

Ta(C, N) coatings were prepared by DGMPA technology, and the wear mechanism of Ta(C, N) coatings with different N₂/Ar ratios was investigated to reduce the wear rate.

This study aims to the service life of TA15 alloy by solving the problem of the binding force between the matrix and AlTiSiN coating. The effect of a plasma nitriding (PN) interlayer on the magnetron-sputtered AlTiSiN coating was also investigated in detail.

The double-glow plasma alloying (DGPA) and magnetron sputtering (MS) techniques were combined as a new approach to realize a bilayer on TA15 consisting of an AlTiSiN layer with a PN interlayer. A TiN interlayer was formed via co-diffusion during the PN conducted at 1050°C for 3 h.

The PN interlayer can effectively improve the adhesion between coating and matrix; the PN/AlTiSiN coating presented excellent adhesion (80.1 N) and anti-wear property with a nano-hardness of 18.62 GPa. The resulting three-dimensional wear-track morphology exhibited a shallow depth and a narrow width.

The novel combination of the DGPA and MS technologies, using an infiltration layer rather than a coating one as the intermediate layer, can effectively enhance the adhesion between AlTiSiN coating and TA15 matrix. Meanwhile, the gradient layer can effectively improve both surface bearing and wear resistance.

The shape of a product plays a crucial role in shaping consumer behavior. Despite the voluminous research on factors influencing consumers’ shape preferences, there remains a limited understanding of how the busy mindset, a mentality increasingly emphasized by marketing campaigns, works. This study aims to fill this gap by exploring the relationship between a busy mindset and the preference for angular-shaped versus circular-shaped products and brand logos.

This research consists of seven experimental studies using various shape stimuli, distinct manipulations of busy mindset, different assessments of shape preference and samples drawn from multiple countries.

The findings reveal that a busy mindset leads to a preference for angular shapes over circular ones by amplifying the need for uniqueness. In addition, these effects are attenuated when products are scarce.

This research represents one of the pioneering efforts to study the role of a busy mindset on consumers’ aesthetic preferences. Beyond yielding insights for practitioners into visual marketing, this research contributes to the theories on the busy mindset and shape preference.

Synthesizing the unique Confucian cultural values and the common characteristics of emerging markets, the purpose of this paper is to examine how face drives consumers’ attitudes toward global consumer culture positioning (GCCP) as well as the moderating roles of social aggrandizement and susceptibility to normative influence (SNI).

The authors adopt the total effect moderation model to test the hypotheses using data collected from China.

The results show that face positively affects consumers’ attitudes toward GCCP through enhancing their pursuit for global myth. In addition, social aggrandizement positively moderates the influence of face on pursuit for global myth. SNI positively moderates the influence of pursuit for global myth on attitudes toward GCCP.

The findings of this study highlight the need to utilize local powers to promote brands globally and provide guidelines for “Think Globally, Act Locally” in Confucian societies.

This study represents an important step in the global branding literature regarding the advancement of culturally driven attitudes toward GCCP by taking root in the Confucian culture.

Enterprise social media can be the organizational transactive memory in which the knowledge dialogue provides users with the metaknowledge to support knowledge transfer. The purpose of this study is to examine a mediation model to show how perceived critical mass, openness and affiliation climate affect organizational knowledge transfer through the mediation of improving the metaknowledge of who knows what and whom.

To test the mediation model and corresponding hypotheses, this study employs structural equation modeling analysis using 264 valid questionnaires.

The study found the two mediators fully explained the effects of the three preconditions on knowledge transfer.

These results help us to better understand the benefits of enterprise social media and the functions of transactive memory in organizations.

This study aims to examine the ability of Generative Pre-trained Transformer 4 (GPT-4), one of the most powerful large language models, to generate a literature review for peer-reviewed journal publications. The objective is to determine whether business scholars can rely on GPT-4’s assistance with literature reviews and how the nature of human–artificial intelligence (AI) interaction may affect the quality of the reviews generated by GPT-4.

A survey of 30 experienced researchers was conducted to assess the quality of the literature reviews generated by GPT-4 in comparison with a human-authored literature review published in a Social Science Citation Index (SSCI) journal. The data collected were then analyzed with analysis of variance to ascertain whether we may trust GPT-4’s assistance in writing literature reviews.

The statistical analysis reveals that when a highly structured approach being used, GPT-4 can generate a high-quality review comparable to that found in an SSCI journal publication. However, when a less structured approach is used, the generated review lacks comprehensive understating and critical analysis, and is unable to identify literature gaps for future research, although it performed well in adequate synthesis and quality writing. The findings suggest that we may trust GPT-4 to generate literature reviews that align with the publication standards of a peer-reviewed journal when using a structured approach to human–AI interaction.

The findings suggest that we may trust GPT-4 to generate literature reviews that align with the publication standards of a peer-reviewed journal when using a structured approach to human–AI interaction. Nonetheless, cautions should be taken due to the limitations of this study discussed in the text.

By breaking down the specific tasks of a literature review and using a quantitative rather than qualitative assessment method, this study provides robust and more objective findings about the ability of GPT-4 to assist us with a very important research task. The findings of this study should enhance our understanding of how GPT-4 may change our research endeavor and how we may take a full advantage of the advancement in AI technology in the future research.