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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.

Knowledge sharing has entered the stage of knowledge payment with the typical models of paid Q&A, live session, paid subscription, course column and community service. Numerous knowledge suppliers have begun to pour into the knowledge payment market, and users' willingness to pay for premium content has increased. However, the academic research on knowledge payment has just begun.

In this paper, the authors searched several bibliographic databases using keywords such as “knowledge payment”, “paid Q&A”, “pay for answer”, “social Q&A”, “paywall” and “online health consultation” and selected papers from aspects of research scenes, research topics, etc. Finally, a total of 116 articles were identified for combing studies.

This study found that in the early research, scholars paid attention to the definition of knowledge payment concept and the discrimination of typical models. With the continuous enrichment of research literature, the research direction has gradually been refined into three main branches from the perspective of research objects, i.e. knowledge provider, knowledge demander and knowledge payment platform.

This paper focuses on discussing and sorting out the key research issues from these three research genres. Finally, the authors found out conflicting and contradictory research results and research gaps in the existing research and then put forward the urgent research topics.

Resilience concepts in integrated urban transport refer to the performance of dealing with external shock and the ability to continue to provide transportation services of all modes. A robust transportation resilience is a goal in pursuing transportation sustainability. Under this specified context, while before the perturbations, robustness refers to the degree of the system’s capability of functioning according to its design specifications on integrated modes and routes, redundancy is the degree of duplication of traffic routes and alternative modes to maintain persistency of service in case of perturbations. While after the perturbations, resourcefulness refers to the capacity to identify operational problems in the system, prioritize interventions and mobilize necessary material/ human resources to recover all the routes and modes, rapidity is the speed of complete recovery of all modes and traffic routes in the urban area. These “4R” are the most critical components of urban integrated resilience.

The trends of transportation resilience's connotation, metrics and strategies are summarized from the literature. A framework is introduced on both qualitative characteristics and quantitative metrics of transportation resilience. Using both model-based and mode-free methodologies that measure resilience in attributes, topology and system performance provides a benchmark for evaluating the mechanism of resilience changes during the perturbation. Correspondingly, different pre-perturbation and post-perturbation strategies for enhancing resilience under multi-mode scenarios are reviewed and summarized.

Cyber-physic transportation system (CPS) is a more targeted solution to resilience issues in transportation. A well-designed CPS can be applied to improve transport resilience facing different perturbations. The CPS ensures the independence and integrity of every child element within each functional zone while reacting rapidly.

This paper provides a more comprehensive understanding of transportation resilience in terms of integrated urban transport. The fundamental characteristics and strategies for resilience are summarized and elaborated. As little research has shed light on the resilience concepts in integrated urban transport, the findings from this paper point out the development trend of a resilient transportation system for digital and data-driven management.

Under the background of the overall increase of China's economic policy uncertainty and the urgent need for the transformation and upgrading of the substantial economy, this paper studies the time-varying causality between China's economic policy uncertainty and the growth of the substantial economy through bootstrap rolling window causality test, further refines economic policies and studies the causal differences between different types of economic policies and substantial economic growth, refining the conclusions of previous studies.

This paper first studies the causal relationship between China's economic policy uncertainty and substantial economic growth in the full sample period through bootstrap Granger causality test. Then, the paper tests the short-term and long-term stability of the parameters of the VAR model, and it is found that the model parameters are unstable in both the short and long term, so the results of the Granger causality test of the full sample are not credible. Finally, we conduct a dynamic test of the causal relationship between China's economic policy uncertainty and substantial economic growth by means of rolling window, so as to comprehensively analyze the dynamic characteristics and sudden changes of the relationship between them.

The research shows that economic policy uncertainty in China has a significant inhibiting effect on the growth of substantial economy. Growth in the substantial economy will drive up economic policy uncertainty before 2016 and restrain it after that. In addition, this paper further subdivides economic policy uncertainty to explore the causal differences between different types of economic policy uncertainty and substantial economic growth. The test results show that the relationship between them has obvious policy heterogeneity. The fiscal policy uncertainty and the monetary policy uncertainty, as the main policy means in China, has a significant impact on the growth rate of substantial economy in multiple ranges, but the effect time is short. Although trade policy uncertainty has a significant impact on the growth rate of substantial economy only during the financial crisis, the effect lasts for a long time. The impact of exchange rate and capital account policy uncertainty on the growth rate of substantial economy is mainly reflected after 2020.

The values of this paper are as follows: First, the economic policy uncertainty is combined with the growth of substantial economy, which makes up the gap of previous studies. Second, the economic policy uncertainty is further subdivided. The paper explores the causal differences between different types of economic policy uncertainties and the growth of substantial economy, so as to make the research more detailed. Finally, different from the previous static analysis, this paper uses dynamic model to examine the relationship between China's economic policy uncertainty and the growth of substantial economy from a dynamic perspective, with richer research conclusions.

The research approach is based on the concept that a failure event is rarely random and is often generated by a chain of previous events connected by a sort of domino effect. Thus, the purpose of this study is the optimal selection of the components to predictively maintain on the basis of their failure probability, under budget and time constraints.

Assets maintenance is a major challenge for any process industry. Thanks to the development of Big Data Analytics techniques and tools, data produced by such systems can be analyzed in order to predict their behavior. Considering the asset as a social system composed of several interacting components, in this work, a framework is developed to identify the relationships between component failures and to avoid them through the predictive replacement of critical ones: such relationships are identified through the Association Rule Mining (ARM), while their interaction is studied through the Social Network Analysis (SNA).

A case example of a process industry is presented to explain and test the proposed model and to discuss its applicability. The proposed framework provides an approach to expand upon previous work in the areas of prediction of fault events and monitoring strategy of critical components.

The novel combined adoption of ARM and SNA is proposed to identify the hidden interaction among events and to define the nature of such interactions and communities of nodes in order to analyze local and global paths and define the most influential entities.

The purpose of this paper is to explore the impact of firm-, finance- and country-specific indicators to the performance of companies under the COVID-19 outbreak.

The study uses a regression performance model for enterprises during the COVID-19 crisis. The investigation is based upon a data set of 5,730 firms from 13 countries collected by the World Bank through enterprise surveys. The author combined the analysis of traditional performance measurements with the testing of relatively novel variables.

This study confirms the significance of multiple factors for company performance: sector, size, participation in exports and market demand for firms’ products. Robust financing solutions during the coronavirus pandemic period include equity contributions, followed by firms’ cash balances and debt. Support by a government, however, has not yet been confirmed as a significant source of finance. This paper also suggests the importance of country-specific factors for the performance of enterprises, including the level of economic development and the corporate governance infrastructure.

The research outcomes might assist regulatory bodies, policymakers and companies in their formulation of public and corporate governance strategies concerning future emergency preparedness and responses.

This paper is among the first empirical studies in the management realm that addresses the impact of COVID-19 on company performance, with cross-national empirical data.