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This paper aims to study the impacts of groundwater seepage on artificial freezing process of gravel strata, the temperature field characteristics of the strata, and the strata process, closure time and thickness evolution mechanism of the frozen wall.

In this paper several laboratory model tests were conducted, considering different groundwater seepage rate.

The results show that there is a significant coupling effect between the cold diffusion of artificial freezing pipes and groundwater seepage; when there is no seepage, temperature fields upstream and downstream of the gravel strata are symmetrically distributed, and the thickness of the frozen soil column/frozen wall is consistent during artificial freezing; groundwater seepage causes significant asymmetry in the temperature fields upstream and downstream of the gravel strata, and the greater the seepage rate, the more obvious the asymmetry; the frozen wall closure time increases linearly with the increase in the groundwater seepage rate, and specifically, the time length under seepage rate of 5.00 m d⁻¹ is 3.2 times longer than that under no seepage; due to the erosion from groundwater seepage, the thickness of the upstream frozen wall decreases linearly with the seepage velocity, while that of the downstream frozen wall increases linearly, resulting in a saddle-shaped frozen wall.

The research results are beneficial to the optimum design and risk control of artificial freezing process in gravel strata.

The purpose of this paper is to design a unified operational design domain (ODD) monitoring framework for mitigating Safety of the Intended Functionality (SOTIF) risks triggered by vehicles exceeding ODD boundaries in complex traffic scenarios.

A unified model of ODD monitoring is constructed, which consists of three modules: weather condition monitoring for unusual weather conditions, such as rain, snow and fog; vehicle behavior monitoring for abnormal vehicle behavior, such as traffic rule violations; and road condition monitoring for abnormal road conditions, such as road defects, unexpected obstacles and slippery roads. Additionally, the applications of the proposed unified ODD monitoring framework are demonstrated. The practicability and effectiveness of the proposed unified ODD monitoring framework for mitigating SOTIF risk are verified in the applications.

First, the application of weather condition monitoring demonstrates that the autonomous vehicle can make a safe decision based on the performance degradation of Lidar on rainy days using the proposed monitoring framework. Second, the application of vehicle behavior monitoring demonstrates that the autonomous vehicle can properly adhere to traffic rules using the proposed monitoring framework. Third, the application of road condition monitoring demonstrates that the proposed unified ODD monitoring framework enables the ego vehicle to successfully monitor and avoid road defects.

The value of this paper is that the proposed unified ODD monitoring framework establishes a new foundation for monitoring and mitigating SOTIF risks in complex traffic environments.

The purpose of this paper is to examine the role of founding team experience (industry and venturing) in new venture creation. This paper posits the following questions: How does founding team experience influence the likelihood of new venture creation, in the nascent stage? How does industry context moderate this relationship? The study aims to fill an important gap in the literature by unpacking the impact of different types of founding team experiences on venture outcome, and by focusing on the influence of founding team in the venture creation process, specifically at the nascent stage.

The paper utilizes data from the Second Panel Study of Entrepreneurial Dynamics, a longitudinal data set of 1,214 nascent entrepreneurs in the USA. Logistics regression was employed to analyze the effect of founding team experience on new venture creation. Post hoc analysis was conducted to ensure the confidence of the findings.

The paper provides empirical insights about how founding team experience influences the likelihood of new venture creation in the nascent stage. At the nascent stage, founding team industry experience positively affects new venture creation while founding team venturing experience does not. However, in the high-technology industry environment, the influence of the founding team’s venturing experience on new venture creation is stronger than that in the low-technology industry environment.

Due to the design of the data set, there is a risk of “right-censoring” problem. Also, because the study used archival data on founding teams, the methodology did not allow for uncovering the underlying team processes and dynamics during the venture creation process based on learning from experience. Future studies are encouraged to examine other types of founding team experience and the underlying process-level factors on venture creation.

The paper provides important practical implications for nascent entrepreneurs/entrepreneurial teams on team assembling and composition. In general, a team with higher-level industry experience is critical for venturing success. A team with higher-level venturing experience is more desired in the high-technology industry.

This paper fulfills an important gap in the entrepreneurial team literature by highlighting the complex and nuanced ways in which founding team experience influences the likelihood of venture creation in the nascent stage of the firm, especially after incorporating the additional impact of the industry context.

This editorial establishes the broader context for debating the great global convergence of world economic systems and the role of Belt and Road Initiative in shaping the reconfiguration of key global transport nodes and trade corridors. The interwoven relationships between various aspects of technological transformation, supply chain integration and demographic restructuring in shaping the global value chain and integrated production networks are theoretically and empirically probed in this special issue. The importance of technological innovation, and structural reforms are highlighted to help businesses to sustainably manage the growing supply chain complexity and the likely disruptions during the fourth industrial revolution.

This paper analyzes the effect of circular economy practices on firm performance for a circular supply chain and explores the moderating role that big-data-driven supply chain plays within these relationships.

This study uses data collected through an online survey distributed to managers of 378 Italian firms that have adopted circular economy principles. The data are processed using multiple regression analysis.

The results indicate that the three categories of circular economy practices investigated – namely circular economy supply chain management design, circular economy supply chain relationship management and circular economy HR management – play a crucial role in enhancing firm performance from a circular economy perspective. A big-data-driven supply chain acts as a moderator of the relationship between circular economy HR management and firm performance for a circular economy supply chain.

This study makes a number of original contributions to research on circular economy practices in a big-data-driven supply chain and provides useful insights for practitioners. First, it answers the call to capture digital transformation trends and to extend research on sustainability in supply chain management. Second, it enhances the literature by investigating the relationships between three different kinds of circular economy supply chain practices and firm performance. Finally, it clarifies the moderating role of big data in making decisions and implementing circular supply chain solutions to achieve better environmental, social and economic benefits.

This study aims to elucidate the process and internal mechanism of place identity construction in traditional villages under the impact of tourism by taking Cuandixia village as a case. The research methods comprise participatory observation and in-depth interviews with the residents. The main results are as follows: the impact of tourism on traditional villages is mainly reflected in space reconstruction, livelihood change, social relations restructuring and culture change; under the impact of tourism, the representation of residents’ identity construction shows complexity, with positive and negative effects; and the place identity construction of residents affects their perception of and attitudes toward tourism. Moreover, self-esteem and self-efficacy principles play a key role in their perception of tourism. This study provides some reference for further investigation of the tourism development model and the mental mechanism of residents in traditional villages.

This paper summarizes the severity of global warming, collaboration and endeavor within international government and the trend of international development for “energy-saving and emission reduction.” The Chinese government is enduring high pressure under the environment of “global warming” and “energy-saving and emission reduction” and it has made a policy for “energy-saving and emission reduction.” Based on this, we analyzed the possibility and feasibility for our logistics to “energy-saving and emission reduction,” then propose some solutions for our logistics industry to development and “energy-saving and emission reduction.”

Objectively evaluating the fairness of the algorithm, exploring in specific scenarios combined with scenario characteristics and constructing the algorithm fairness evaluation index system in specific scenarios.

This paper selects marketing scenarios, and in accordance with the idea of “theory construction-scene feature extraction-enterprise practice,” summarizes the definition and standard of fairness, combs the application link process of marketing algorithms and establishes the fairness evaluation index system of marketing equity allocation algorithms. Taking simulated marketing data as an example, the fairness performance of marketing algorithms in some feature areas is measured, and the effectiveness of the evaluation system proposed in this paper is verified.

The study reached the following conclusions: (1) Different fairness evaluation criteria have different emphases, and may produce different results. Therefore, different fairness definitions and standards should be selected in different fields according to the characteristics of the scene. (2) The fairness of the marketing equity distribution algorithm can be measured from three aspects: marketing coverage, marketing intensity and marketing frequency. Specifically, for the fairness of coverage, two standards of equal opportunity and different misjudgment rates are selected, and the standard of group fairness is selected for intensity and frequency. (3) For different characteristic fields, different degrees of fairness restrictions should be imposed, and the interpretation of their calculation results and the means of subsequent intervention should also be different according to the marketing objectives and industry characteristics.

First of all, the fairness sensitivity of different feature fields is different, but this paper does not classify the importance of feature fields. In the future, we can build a classification table of sensitive attributes according to the importance of sensitive attributes to give different evaluation and protection priorities. Second, in this paper, only one set of marketing data simulation data is selected to measure the overall algorithm fairness, after which multiple sets of marketing campaigns can be measured and compared to reflect the long-term performance of marketing algorithm fairness. Third, this paper does not continue to explore interventions and measures to improve algorithmic fairness. Different feature fields should be subject to different degrees of fairness constraints, and therefore their subsequent interventions should be different, which needs to be continued to be explored in future research.

This paper combines the specific features of marketing scenarios and selects appropriate fairness evaluation criteria to build an index system for fairness evaluation of marketing algorithms, which provides a reference for assessing and managing the fairness of marketing algorithms.

Algorithm governance and algorithmic fairness are very important issues in the era of artificial intelligence, and the construction of the algorithmic fairness evaluation index system in marketing scenarios in this paper lays a safe foundation for the application of AI algorithms and technologies in marketing scenarios, provides tools and means of algorithm governance and empowers the promotion of safe, efficient and orderly development of algorithms.

In this paper, firstly, the standards of fairness are comprehensively sorted out, and the difference between different standards and evaluation focuses is clarified, and secondly, focusing on the marketing scenario, combined with its characteristics, key fairness evaluation links are put forward, and different standards are innovatively selected to evaluate the fairness in the process of applying marketing algorithms and to build the corresponding index system, which forms the systematic fairness evaluation tool of marketing algorithms.

Circular economy (CE) initiatives are taking hold across both developed and developing nations. Central to these initiatives is the reconfiguration of core supply chain management (SCM) processes that underlie current production and consumption patterns. This conceptual article provides a detailed discussion of how supply chain processes can support the successful implementation of CE. The article highlights areas of convergence in hopes of sparking collaboration among scholars and practitioners in SCM, CE, and related fields.

This article adopts a theory extension approach to conceptual development that uses CE as a “method” for exploring core processes within the domain of SCM. The article offers a discussion of the ways in which the five principles of CE (closing, slowing, intensifying, narrowing, dematerialising loops) intersect with eight core SCM processes (customer relationship management, supplier relationship management, customer service management, demand management, order fulfilment, manufacturing flow management, product development and commercialization, returns management).

This article identifies specific ways in which core SCM processes can support the transition from traditional linear approaches to production and consumption to a more circular approach. This paper results in a conceptual framework and research agenda for researchers and practitioners working to adapt current supply chain processes to support the implementation of CE.

This article highlights key areas of convergence among scholars and practitioners through a systematic extension of CE principles into the domain of SCM. In so doing, the paper lays out a potential agenda for collaboration among these groups.