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The purpose of the study is to quickly identify significant heterogeneity of surrounding rock of tunnel face that generally occurs during the construction of large-section rock tunnels of high-speed railways.

Relying on the support vector machine (SVM)-based classification model, the nominal classification of blastholes and nominal zoning and classification terms were used to demonstrate the heterogeneity identification method for the surrounding rock of tunnel face, and the identification calculation was carried out for the five test tunnels. Then, the suggestions for local optimization of the support structures of large-section rock tunnels were put forward.

The results show that compared with the two classification models based on neural networks, the SVM-based classification model has a higher classification accuracy when the sample size is small, and the average accuracy can reach 87.9%. After the samples are replaced, the SVM-based classification model can still reach the same accuracy, whose generalization ability is stronger.

By applying the identification method described in this paper, the significant heterogeneity characteristics of the surrounding rock in the process of two times of blasting were identified, and the identification results are basically consistent with the actual situation of the tunnel face at the end of blasting, and can provide a basis for local optimization of support parameters.

Innovation ecosystems (IEs) have attracted the attention of policymakers and researchers because of their potential to positively affect territories, creating shared value. However, due to the fragmentation of IEs, how this happens in different IEs has been explored only partially. This research aims to bridge this gap, aiming to support policymakers in understanding how to foster shared value in diverse IEs.

The paper identifies, based on the literature, two “drivers of aggregation” of IE's actors as key dimensions characterizing shared value in IEs, namely physical proximity and dominant issue. If these are combined, three archetypes emerge: Hub- and Chain-Driven, Place-Driven, Competence- and Issue-Driven IEs.Then, elements useful for understanding shared value creation in these archetypes are framed and studied in real cases.

Results reveal that aggregation drivers affect shared value creation, which differ among archetypes: in Competence- and Issue-Driven IEs alignment is challenged by the low physical proximity, which in Place-Driven IEs is high, but not enough to grant shared value; in Hub- and Chain-Driven IEs, the hub is the orchestrator, representing both a driver and a risk.

Differences in shared value creation processes relate to the set-up of the IE, which has relevant implications for policy definition. In Competence- and Issue-Driven IEs, policies at diverse levels align in funding and promoting the IE; in Place-Driven IEs, policies support anchors' development on-site; in Hub- and Chain-Driven IEs, policies, sometimes absent, should foster partnerships for projects for the territory, IE's enlargement and resilience.

The purpose is to increase knowledge of rent negotiations by investigating differences in beliefs held by property landlords and retailers on factors that they deem important in rent negotiation.

This study investigates differences in subjective beliefs held by landlords and retail trade tenants on factors that affect rent levels during the rent negotiation process using a factor analysis approach. Semi-structured interviews were made with seven large real estate owners/landlords and retailers and eight experts in negotiating retail rent to elicit variables that have an impact on retail rent. Thereafter, a web-based survey was sent to 421 respondents who had experience in rent negotiation. Several factors were extracted using factor analysis. The data collection was made in Sweden during the coronavirus disease 2019 (COVID-19) pandemic in late spring 2021

Significant differences are found in beliefs held by landlords and retail trade tenants in four out of seven-factor: regional growth, e-commerce, customer focus and trust. Landlords rate these factors higher than retailers do. There are also systematic differences between landlords and retailers depending on their education levels on the following factors: rent and vacancies, e-commerce and customer focus. The number of years of experience did not prove to be significant instead differences are found to exist in factors

Not only do traditional factors of importance, such as lease structure, the effect of location, size and anchor or non-anchor tenants, have an effect on negotiated rent levels. Differences in other factors also exist, such as regional growth, e-commerce, customer focus and trust factors that may play an important role in the negation of retail rent.

The findings provide new insights into the different views on factors that affect rent negotiations between landlords and retail tenants. Knowledge of such differences may increase the overall transparency in the negotiation process. Transparency may be increased by putting forward information on these factors before a negotiation takes place, in order to smooth differences in their beliefs.

If transparency in the negotiation process of retail rent increases, time to reach an agreement, stress and anxiety can be reduced by putting forward information on factors where differences exist between landlords and retailers

New insights on retail rent negotiation have been put forward in this research paper. Not only do traditional factors such as lease structure matters, but subjective beliefs on factors such as regional growth and the level of education are also important, as this study has shown using a factors analysis approach.

Sustainability is regarded as a core value that the coworking movement aspires to. However, most sustainability efforts focus on the providers’ perspective while neglecting the coworking members’ role. Therefore, this paper aims to explore sustainable coworking from the members perspective by focusing on sustainable behaviors.

This study uses a flexible pattern matching approach. Theoretical patterns are identified using literature on coworking space and sustainable behavior while matching them with the empirical data. Data were collected from three different coworking spaces in Sweden through interviews and observations.

Based on the theoretical patterns, three constructs for sustainable coworking were identified, namely, productive behavior, prosocial behavior and responsible space sharing behavior. Through the empirical data, the constructs were further concretized to understand their different aspects. The findings uncovered a new layer of complexity where members can show the same behavior and be perceived differently.

This study offers a more holistic understanding of sustainable coworking by highlighting the members’ role and identifying different member perceptions on sustainable coworking behaviors.

The microseismic monitoring technique has great advantages on identifying the location, extent and the mechanism of damage process occurring in rock mass. This study aims to analyze distribution characteristics and the evolution law of excavation damage zone of surrounding rock based on microseismic monitoring data.

In situ test using microseismic monitoring technique is carried out in the large-span transition tunnel of Badaling Great Wall Station of Beijing-Zhangjiakou high-speed railway. An intelligent microseismic monitoring system is built with symmetry monitoring point layout both on the mountain surface and inside the tunnel to achieve three-dimensional and all-round monitoring results.

Microseismic events can be divided into high density area, medium density area and low density area according to the density distribution of microseismic events. The positions where the cumulative distribution frequencies of microseismic events are 60 and 80% are identified as the boundaries between high and medium density areas and between medium and low density areas, respectively. The high density area of microseismic events is regarded as the high excavation damage zone of surrounding rock, which is affected by the grade of surrounding rock and the span of tunnel. The prediction formulas for the depth of high excavation damage zone of surrounding rock at different tunnel positions are given considering these two parameters. The scale of the average moment magnitude parameters of microseismic events is adopted to describe the damage degree of surrounding rock. The strong positive correlation and multistage characteristics between the depth of excavation damage zone and deformation of surrounding rock are revealed. Based on the depth of high excavation damage zone of surrounding rock, the prestressed anchor cable (rod) is designed, and the safety of anchor cable (rod) design parameters is verified by the deformation results of surrounding rock.

The research provides a new method to predict the surrounding rock damage zone of large-span tunnel and also provides a reference basis for design parameters of prestressed anchor cable (rod).