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The demand for the cold chain logistics of agricultural products was investigated through demand forecasting; targeted suggestions and countermeasures are provided. This paper aims to discuss the aforementioned statement.

A Markov-optimised mean GM (1, 1) model is proposed to forecast the demand for the cold chain logistics of agricultural products. The mean GM (1, 1) model was used to forecast the demand trend, and the Markov chain model was used for optimisation. Considering Guangxi province as an example, the feasibility and effectiveness of the proposed method were verified, and relevant suggestions are made.

Compared with other models, the Markov-optimised mean GM (1, 1) model can more effectively forecast the demand for the cold chain logistics of agricultural products, is closer to the actual value and has better accuracy and minor error. It shows that the demand forecast can provide specific suggestions and theoretical support for the development of cold chain logistics.

This study evaluated the development trend of the cold chain logistics of agricultural products based on the research horizon of demand forecasting for cold chain logistics. A Markov-optimised mean GM (1, 1) model is proposed to overcome the problem of poor prediction for series with considerable fluctuation in the modelling process, and improve the prediction accuracy. It finds a breakthrough to promote the development of cold chain logistics through empirical analysis, and give relevant suggestions based on the obtained results.

Smart senior care industry in China currently faces a series of practical difficulties such as an imbalance in the demand and supply structure, service products unable to cater to the actual needs of the elderly and a low degree of marketization. This study therefore proposes using grey relational analysis and the Fuzzy-quality function development (QFD) quality improvement method to help solve these problems.

The proposed method converts the fuzzy requirements of the elderly into the technical characteristics of technologically augmented senior care service products. It then, uses the QFD relationship matrix, combined with grey relational analysis, to analyze the relationship between the needs of elderly and the converted technical characteristics, and subsequently identifies key technical characteristics.

Results show that an improvement in the smart senior care service platform according to the differences of the elderly's preferences can significantly improve users' satisfaction with the service in addition to enhancing market competitiveness of the technologically assisted senior care service products.

A novel method to improve the need of smart senior care is proposed by considering age difference. The proposed grey relational analysis and Fuzzy-QFD quality improvement method can help improve the service quality of the smart senior care service platform.

This paper aims to explore the critical factors which affect the quality of preschool education service so that targeted and effective measures to improve service quality can be put forward.

Evidential theory is applied to aggregate experts’ knowledge, and a fuzzy cognitive map (FCM) model of preschool education service quality is established to further carry out a simulation for inference, thus figuring out the critical factors to improve service quality.

The simulation results show that the main body of supervision and environment of governments and policies are two critical factors affecting the quality of preschool education service. More emphasis should be put on these two aspects, and corresponding measures can be put forward so as to ensure the quality of preschool education service.

This paper proposes a new model based on FCM and evidential theory to study the factors affecting preschool education service quality.

This study establishes a risk management system for medical and health care integration projects to address the problem of high-risk potential and a strong correlation between risk factors.

A new fuzzy WINGS-G1 model for identifying key risk factors in medical and health care integration projects is proposed by introducing the fuzzy theory and the concept of risk incidence into the Weighted Influence Non-linear Gauge System (WINGS) method.

The authors analyze the fluidity of project risk factors through complex networks to control direct risks and cut off risk transmission paths to provide a reference for risk control and prevention of medical and health care integration projects.

(1) The integration of fuzzy theory into the WINGS method solves the problem of strong subjectivity of expert scoring in the traditional WINGS method; (2) By the different probabilities of risk factors, the concept of risk incidence is introduced in the WINGS model, which is more conducive to the identification of the critical risk factors and the rational allocation and utilization of organizational resources; (3) The use of the complex network for risk interactivity analysis fully reflects the dynamic nature of risk factors in medical and health care integration projects.

The purpose of this study is to establish a grey-entropy-catastrophe progression method (CPM) model to assess the photovoltaic (PV) industry chain resilience of Jiangsu Province in China.

First, we designed the resilience evaluation index system of such a chain from two aspects: the external environment and internal conditions. We then constructed a PV industry chain resilience evaluation model based on the grey-entropy-CPM. Finally, the feasibility and applicability of the proposed model were verified via an empirical case study analysis of Jiangsu Province in China.

As of the end of 2022, the resilience level of its PV industry chain is medium-high resilience, which indicates a high degree of adaptability to the current unpredictable and competitive market, and can respond to the uncertain impact of changes in conditions effectively and in a timely manner.

The construction of this model can provide reference ideas for related enterprises in the PV industry to analyze the resilience level of the industrial chain and solve the problem of industrial chain resilience.

Firstly, an analysis of the entire industrial chain structure of the PV industry, combined with its unique characteristics is needed to design a PV industry chain resilience evaluation index system. Second, grey relational analysis (GRA) and the entropy method were adopted to improve the importance of ranking the indicators in the evaluation of the CPM, and a resilience evaluation model based on grey-entropy-CPM was constructed.

Augmented reality (AR), an innovative interactive technology that can realize the synchronization and integration of virtual and reality, has been widely used in commodity displays and museum exhibitions. However, few studies have examined the effectiveness of AR-based product display in the context of historically cultural and creative product (HCCP) marketing. This study aims to focus on whether and how the application of AR technology to the HCCP display will influence consumers’ product evaluation.

This study uses three experiments to examine the impact of an AR-based product display on consumers’ evaluation of HCCPs. In experiments 1 and 2, the researchers compared the consumer’s evaluation of HCCPs under the AR-based product display condition and two other display conditions (i.e. 3D model display and photographic display) and examined the mediating role of perceived authenticity in the evaluation process. Experiment 3 tested the moderating effect of the availability of artistic detail information on weakening the negative impact of AR-based product display on the evaluation of HCCPs.

This study found that using AR-based displays harms consumers’ evaluation of HCCPs by impairing perceived authenticity. The spatial-temporal cues of real-time circumstances impede consumers’ processing of the historical attributes of the product. The dynamic AR-based display makes it hard for consumers to build the product’s connection with historical prototypes. Thus, consumers’ perception of the authenticity of HCCP is reduced. Providing artistic details during the presentation makes artistic attributes more prominent than historical attributes, allowing consumers to pay more attention to the sensory experience caused by the artistic design instead of the spatial-temporal cues of the product. At this point, the negative impact of AR-based product display on the evaluation of HCCPs will be attenuated.

First, this study shows the adverse effects of AR-based product displays in the field of HCCP marketing. AR-based product display degrades product evaluations when the displayed product has historical attributes. Second, this study extends the perceived authenticity theory to the technological experience context and establishes a theoretical connection with the AR literature. Third, this study explores the multiple characteristics of HCCPs. The historical attributes are the central attribute of HCCPs, leading consumers to perceive lower sense of authenticity due to the conflict with real-time spatiotemporal cues risen from the AR-based display. However, the artistic attributes, which are beyond the limitation of time and space, will attenuate this conflict when they become prominent.

This study aims to explore the influencing factors of online tourism service quality to clarify the relationship between such factors and the degree of influence so that targeted and effective measures to improve service quality can be suggested.

A questionnaire is used to obtain original data, establish the fuzzy cognitive map (FCM) structure chart model and modify the model.

The results reveal that comprehensive service types, comprehensive information provided, true and accurate, upgrade and update, payment security, data and information security, customer rights and interests protection, service friendliness and evaluation processing are the key influencing factors in online tourism service quality. In addition, the FCM can also predict the improvement of service quality.

To establish an FCM model, this study establishes the evaluation framework of influencing factors of online tourism service quality and identifies the cause and effect of 26 indicators. The mechanism of influencing factors of online tourism service quality is explored through the iteration of the model.

Currently, China’s manufacturing industry chain still faces the danger of chain breakage due to the persistent “lack of technology” issue. The definition and detection of key nodes in the industry chain are significant to the enhancement of the stability of the industry chain. Therefore, detecting the key nodes in the manufacturing industry chain is necessary.

A complex network based on the links amongst listed manufacturing enterprises is built, and the authors analyse the network’s basic characteristics and vulnerability, taking into account the impact of scientific and technological innovation on the stability of the industry chain.

It is found that the high structural characteristic of midstream nodes in the naval architecture and marine engineering equipment industry chain determines their importance to stability, and the key status of upstream nodes is reflected in the weakness of technological innovation. The upstream nodes should focus on improving their independent innovation and R&D capability, whilst the midstream nodes should maintain a close supply–demand cooperation relationship.

The key node detection model for industry chain stability is constructed by considering various factors from the perspective of network and technological innovation. Empirical study is conducted to verify effectiveness of proposed method.

This study aims to investigate the vulnerability of cold chain logistics through a comprehensive assessment and provide targeted control measures.

The index system of the cold chain vulnerability assessment was established with knowledge obtained from three different dimensions, namely, exposure, sensitivity and adaptability. The final index weight was determined through combination of the intuitionistic fuzzy (IF) entropy and compromise ratio approaches, followed by the comprehensive vulnerability assessment through the two-stage grey comprehensive measurement model. The feasibility and effectiveness of the proposed method were verified by evaluation with SF, HNA, China Merchants and COFCO as target examples.

The results revealed that the most influential factors in the cold chain vulnerability problem were the temperature reaching the standard, as well as the storage and preservation levels; through their analysis combined with the overall cold chain vulnerability assessment, the targeted control measures were obtained.

Based on the research perspective of cold chain vulnerability assessment, a novel assessment model of cold chain logistics vulnerability was proposed, which is based on IF entropy two-stage grey comprehensive measurement. It provides more powerful theoretical support to improve the quality management of cold chain products.

The purpose of this paper is to show that research on policy diffusion mechanism of Government Procurement of Public Services (GPPS) is beneficial to improve the efficiency of policy formulation and implementation.

In view of the four dimensions which are internal demand, external pressure, policy innovation environment and service characteristic, a system of factors affecting policy diffusion is established. On this basis, a Multilayer Fuzzy Cognitive Map (MFCM) model for policy diffusion of GPPS is constructed. Nonlinear Hebbian Learning algorithm and genetic algorithm are applied to optimize the two components of the MFCM model, which are relationship between nodes at the same layer and influence weights between nodes at different layers, respectively. Taking Nanjing municipal government purchasing elderly-care services in China as the empirical object, simulation of policy diffusion based on the MFCM model is carried out, aiming to obtain the key factors influencing policy diffusion and the dynamic diffusion mechanism of GPPS policy.

Research results show that, compared with monolayer Fuzzy Cognitive Map, the MFCM model converges faster. In addition, simulation results of policy diffusion indicate that economic development level of jurisdiction, superior pressure, administrative level and operability of services are key influencing factors which are under four dimensions correspondingly. And the dynamic influencing mechanism of key factors has also been learned.

This paper constructs the MFCM model, which is a new approach based on several monolayer FCMs, to study the policy diffusion mechanism.