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Recycling and reuse of the electric vehicle (EV) batteries are ways to extend their limited lives. If batteries can be traced from production to recycling, it is beneficial for battery recycling and reuse. Using blockchain technology to build a smart EV battery reverse supply chain can solve the difficulties of lack of trust and data. The purpose of this study is to discuss the behavioural evolution of a smart EV battery reverse supply chain under government supervision.

This study adopts evolutionary game theory to examine the decision-making behaviours of the government, EV manufacturers with recycled used batteries and third-party EV battery recyclers lacking professional recycling qualification.

On the smart reverse supply chain integrated by blockchain technology, a cooperative recycling strategy of the third-party EV battery recycler is the optimal choice when the government tends to actively regulate. The probability of the EV manufacturer choosing the blockchain adoption strategy exceeds (below) the threshold, and the government prefers negative (positive) supervision. According to numerical analysis, in the mature stage in the EV battery recycling industry, when the investment cost of applying blockchain is high, EV manufacturers' willingness to apply blockchain slows down, the government accelerates adopting a negative supervision strategy and third-party EV battery recyclers prefer cooperative recycling.

The results of this study provide opinions on the strength of government supervision and the conditions under which EV manufacturers and third-party EV battery recyclers should apply blockchain and cooperate. On the other hand, this study provides theoretical analysis for promoting the application of blockchain technology in smart reverse supply chain.

Compared with previous research, this study reveals the relevance of government supervision, blockchain application and cooperation strategy in smart EV battery reverse supply chain. In the initial stage, even if the subsidy (subsidy reduction rate) and penalty are high and the penalty reduction rate is low, the EV manufacturer should rather give up the application of blockchain technology. In the middle stage in the EV battery recycling industry, the government can set a lower subsidy (subsidy reduction rate) combined with a penalty or a higher penalty (penalty reduction rate) combined with a subsidy to supervise it. The third-party EV battery recycler is advised to cooperate with the EV manufacturer when the subsidy is low or the penalty is high.

This paper examines the different features of China's economic development in different stages of economic globalization. The study finds that the investment- and export-based growth model drove China's high-speed economic growth between 2000 and 2007, which came into existence around 2000 when China plugged into the global production network.

This paper also finds that China slowed down to the New Normal because of the disruption to the socio-economic underpinnings of this growth model. As China adapts to and steers the New Normal, supply-side structural reforms can channel excess capacity to the construction of underground pipe networks in rural areas of central China and fix capital while advance rural revitalization.

At the same time, enterprises must strive to build a key component development platform for key component innovation and the standard-setting power in global manufacturing.

The establishment of a domestic production network integrating the integrated innovation-driven core enterprises and modular producers at different levels can satisfy the dynamic demand structure of China in which standardized demands and personalized demands coexist.

The purpose of this paper is to investigate market segmentation of affluent Chinese consumers and develop profiles of identified segments for potential target markets for luxury fashion goods.

The data are from the 2006 edition of an annual survey called the “China's New Rich Study”. The respondents form a representative sample of affluent consumers, 18 to 45 years old, residing in China's 12 largest cities. A psychographic segmentation approach is employed to classify these consumers.

Five distinct market segments of affluent Chinese consumers are identified and profiled. Of these segments, three seem the most promising target markets for luxury fashion goods.

When companies understand the similarities and differences between consumer segments as well as the unique characteristics of segments, they have a meaningful basis for selecting receptive target markets and formulating and implementing effective marketing strategies. The findings of this study can be useful not only to companies that offer luxury fashion goods, but also to those targeting the upscale market with a plethora of products and services like yachts, luxury cars, high‐end electronics, resort vacations, and credit cards and other financial services.

This is the first study on segmentation of Chinese consumers for potential target markets for luxury fashion goods. Results reveal heterogeneity among affluent urban Chinese consumers. Strategies for marketing luxury fashion goods to promising target markets in China are outlined on the basis of segment profiles and culturally based motivations for purchasing such goods.

The building sector is one of the main contributors to carbon dioxide emissions in Singapore. Over 90 per cent of life-cycle carbon emissions are due to the operations phase of buildings, and 90 to 98 per cent of the building cost is associated with operation, maintenance and personnel costs. Hence, occupants have a major role in achieving environmental sustainability objectives. This study aims to understand the awareness level of potential homeowners and real estate agents concerning environmental sustainability issues in the built environment, to identify the types of green features required by potential homeowners and to understand real estate agents’ perceptions of the types of green features required by the homeowners in a green condominium.

The features of the Green Mark (GM)-awarded buildings, as well as the benefits derived by homeowners were identified from the literature. A survey of a group of potential homeowners and real estate agents was carried out in Singapore to analyse the gap, if any, between the potential homeowners’ needs and expectations and real estate agents’ perceptions of these needs and expectations with respect to the green features in the homes.

The results indicate that potential homeowners are more aware of environmental sustainability issues in the built environment than are real estate agents; potential homeowners seem to be more supportive of environmentally sustainable development than the real estate agents are aware of, despite the fact that the price of the apartment remains an important deciding factor; and potential homeowners are more concerned about the ease of maintaining green homes and paying greater attention to green features in the areas most heavily promoted by the government. However, green features do not constitute the main considerations of potential homeowners when making the decision to buy a green home.

To close the gaps identified in the analysis, recommendations are suggested, including having public education and awareness campaigns to emphasize the long-term energy savings of green homes, conducting GM courses for real estate agents and involving real estate agents in the developers’ project consultancy team.

As there has been no prior research in this area, this study serves to provide fresh perspectives on how developers can better select the types of green features to be included in the green homes, so as to meet the potential homeowners’ needs and expectations and, at the same time, balance mandatory GM requirements with such demands. Choosing the right type of green features to incorporate in a residential development for homeowners to utilize increases the owners’ satisfaction level and allows them to reap the intended benefits of green features.

Much research on knowledge discovery in database (KDD) merely pays attention to data mining, one of many interacting steps in the process of discovering previously unknown and potentially interesting patterns in large databases, but little to the whole process. However, such approaches cannot satisfy the need of real applications of KDD. The purpose of this work is to extend a process model of KDD in practice at large.

A new model based on research experiences of the knowledge discovery process is formalized as an extension of the model by Fayyad et al. A case study by a reduct method from rough set theory is to illustrate why the process model is proposed and in what situation it can be used in practice.

This model incorporates data collection in the KDD process to supply a sound framework to better support KDD applications.

This model reflects the native of KDD in some tested cases. It may need further research to be used in all other situations.

It can be used in the area of information security, medical treatment and other information management.

Using this model, one can directly collect data that are essential and useful for the mining results. It also offers practical help to those KDD researchers both from industry and academia.

The purpose of this paper is to discuss the Schur D‐stability and the vertex stability of interval matrices (including point matrix obviously). Some new sufficient conditions (criteria) are proposed which guarantee the interval matrix is Schur D‐stable. This results are shown to be less conservative than those in recent literatures. In addition, two equivalence relations between the Schur D‐stability and the vertex stability of interval matrices will be proposed and a new Schur D‐stability range of an interval matrix presented.

Matrix eigenvalues theory and matrix measure approach.

Several simple sufficient conditions (criteria) for guaranteeing the Schur D‐stability of interval matrices are derived, two equivalence relations between the Schur D‐stability and the vertex stability of interval matrices are proposed, and a new Schur D‐stability range of an interval matrix is presented.

Control theory or stability theory. These stability criterion possess simple forms and provide useful tools to check Schur D‐stability of interval matrices (including point matrix) at first stage.

The paper provides useful tools to check Schur D‐stability of interval matrices (including point matrix) at first stage.

Two equivalence relations between the Schur D‐stability and the vertex stability for general interval matrices (including point matrix) are proposed, such that the conditional limitations for tridiagonal matrix in recent papers are broken. A new Schur D‐stability range of an interval matrix is presented, and several simple sufficient conditions are obtained which guarantee the Schur D‐stability of interval matrices (including point matrix).

Purpose: Risk is a multifaceted concept, and its identification requires complex approaches that are often misunderstood. The consequence is that decisions are based on limited perception rather than the full value and meaning of what risk is, as a result, the way it is being tackled is incorrect. The individuals are often limited in their perceptions and ideas and do not embrace the full multifaceted nature of risk. Regulators and individuals want to follow norms and checklists or overuse models, simulations, and templates, thereby reducing responsibility for decision-making. At the same time, the wider use of technology and rules reduces the critical thinking of individuals. We advance the automation process by building robots that follow protocols and forget about the part of risk assessment that cannot be programed. Therefore, with this study, the objective of this study was to discover how people define risk, the influencing factors of risk perception and how they behave toward this perception. The authors also determine how the perception differed with age, gender, marital status, education level and region. The novelty of the research is related to individual risk perception during COVID-19, as this is a new and unknown phenomenon. Methodology: The research is based on the analysis of the self-administered purposely designed questionnaires we distributed across different social media platforms between February and June 2020 in Europe and in some cases was carried out as a interview over communication platforms such as “Skype,” “Zoom” and “Microsoft Teams.” The questionnaire was divided into four parts: Section 1 was designed to collect demographic information from the participants; Section 2 included risk definition statements obtained from literature and a preliminary discussion with peers; Section 3 included risk behavior statements; and Section 4 included statements on risk perception experiences. A five-point Likert Scale was provided, and participants were required to answer along a scale of “1” for “Strongly Agree” to “5” for “Strongly Disagree.” Participants also had the option to elaborate further and provide additional comments in an open-ended box provided at the end of the section. 466 valid responses were received. Thematic analysis was carried out to analyze the interviews and the open-ended questions, while the questionnaire responses were analyzed using various quantitative methods on IBM SPSS (version 23). Findings: The results of the analysis indicate that individuals evaluate the risk before making a decision and view risk as both a loss and opportunity. The study identifies nine factors influencing risk perception. Nevertheless, it must be emphasized that we can continue to develop models and rules, but as long as the risk is not understood, we will never achieve anything.

Olfaction plays a very important role in daily life. The olfactory system has the ability to recognize, discriminate and identify thousands of odorant compounds with extremely high sensitivity and specificity. The research on olfactory system has very important values in exploring the mechanisms of information processing in the other sensory nervous systems and brain. Recently, with the development of molecular biological and microelectronics technology research, the study of olfactory cell-based sensors has made great progress. The purpose of this paper is to provide details of recent developments in olfactory cell-based sensors.

Following an introduction, this paper first discusses some olfactory cell-based biosensors, which focus on the light-addressable potentiometric sensors and the microelectrode arrays. Second, surface modification, microfabrication and microfluidic technology which can improve the efficiency of cell immobilization will be summarized. The research trends of olfactory cell-based sensor in future will be proposed.

This paper shows that the biosensors’ performance is expected to be greatly improved due to the fast development of nanotechnology, optical technology and microelectronics. More and more emerging intelligent olfactory sensors will have a promising prospect in many application fields, including food quality and safety assessment, environmental monitor and human diseases detection.

This paper provides a detailed and timely review of the rapidly growing research in the olfactory cell-based sensors.

Grey modeling technique is an important element of grey system theory, and academic articles applied to agricultural science research have been published since 1985, proving the broad applicability and effectiveness of the technique from different aspects and providing a new means to solve agricultural science problems. The analysis of the connotation and trend of the application of grey modeling technique in agricultural science research contributes to the enrichment of grey technique and the development of agricultural science in multiple dimensions.

Based on the relevant literature selected from China National Knowledge Infrastructure, the Web of Science, SpiScholar and other databases in the past 37 years (1985–2021), this paper firstly applied the bibliometric method to quantitatively visualize and systematically analyze the trend of publication, productive author, productive institution, and highly cited literature. Then, the literature is combed by the application of different grey modeling techniques in agricultural science research, and the literature research progress is systematically analyzed.

The results show that grey model technology has broad prospects in the field of agricultural science research. Agricultural universities and research institutes are the main research forces in the application of grey model technology in agricultural science research, and have certain inheritance. The application of grey model technology in agricultural science research has wide applicability and precise practicability.

By analyzing and summarizing the application trend of grey model technology in agricultural science research, the research hotspot, research frontier and valuable research directions of grey model technology in agricultural science research can be more clearly grasped.

With the explosive growth of the Internet, online travel agents (OTAs) have gained an increasing market share in the online booking market. However, OTAs are facing fierce competition from hotels' direct booking channels, as well as competition among themselves. Therefore, there is a need for an understanding of the evolution of the OTA market from a dynamic perspective. The purpose of this study is to investigate the long-term effect of OTAs on the hospitality industry and to find whether an equilibrium of this effect exists in the context of e-commerce.

To gain a better understanding of the OTA market process, a mathematical framework is constructed on the basis of four assumptions. NetLogo 5.1.0 is used to perform a series of numerical simulations.

The results indicate the following: (1) the development of the OTA market helps to improve net social welfare, but hotels (especially economy hotels) have suffered as a result; (2) clever exploitation of both online and offline channels that are based on hotels' historical data may improve hotels' performance; (3) a scale-priority strategy can be more helpful than a profit-priority strategy for enabling OTAs to maintain their long-term competitiveness; (4) the timing of participation in online-channel competition is a crucial factor in determining whether OTAs can achieve business success.

In this study, it is shown how consumer habits have changed since the development of OTAs. The online channels provided by OTAs create a convenient, low-cost user experience, and they consequently improve the net welfare of customers. OTAs should be encouraged appropriately, although some economy hotels may suffer from the rise of OTAs.

In this empirical study, a mathematical framework is developed to describe the process of evolution in the OTA market, and it uses simulations as a means to validate prior research findings. Unlike previous studies, a dynamic perspective is used in this investigation to interpret the emergence of OTAs and to analyze their enormous impact on the hospitality industry. Thus, the findings of this study capture the competitive characteristics of online and offline channels in a network context and indicate potential strategies for the development of OTAs and which hotels may use OTAs to achieve better performance. In addition, the study findings could be easily extended to explain many of the classical economic phenomena regarding firms with intangible products.