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Grey target decision-making serves as a pivotal analytical tool for addressing dynamic multi-attribute group decision-making amidst uncertain information. However, the setting of bull's eye is frequently subjective, and each stage is considered independent of the others. Interference effects between each stage can easily influence one another. To address these challenges effectively, this paper employs quantum probability theory to construct quantum-like Bayesian networks, addressing interference effects in dynamic multi-attribute group decision-making.

Firstly, the bull's eye matrix of the scheme stage is derived based on the principle of group negotiation and maximum satisfaction deviation. Secondly, a nonlinear programming model for stage weight is constructed by using an improved Orness measure constraint to determine the stage weight. Finally, the quantum-like Bayesian network is constructed to explore the interference effect between stages. In this process, the decision of each stage is regarded as a wave function which occurs synchronously, with mutual interference impacting the aggregate result. Finally, the effectiveness and rationality of the model are verified through a public health emergency.

The research shows that there are interference effects between each stage. Both the dynamic grey target group decision model and the dynamic multi-attribute group decision model based on quantum-like Bayesian network proposed in this paper are scientific and effective. They enhance the flexibility and stability of actual decision-making and provide significant practical value.

To address issues like stage interference effects, subjective bull's eye settings and the absence of participative behavior in decision-making groups, this paper develops a grey target decision model grounded in group negotiation and maximum satisfaction deviation. Furthermore, by integrating the quantum-like Bayesian network model, this paper offers a novel perspective for addressing information fusion and subjective cognitive biases during decision-making.

This study aims to obtain the speed and angle during safe and comfortable standing of elderly people. With the advancement of society, it is becoming increasingly difficult for the elderly to sit-to-stand (STS) independently and comfortably in a safe and comfortable manner. Safety is essentially a prerequisite for the elderly to achieve a comfortable STS. The speed, angle and power of the STS process can all affect safe STS. From the standpoint of health-care delivery and administration, comfortable STS can be realized easily by addressing the safety issues during STS.

This paper summarizes the research progress on speed and angle during safe and comfortable standing of older people. The authors analyzed the speed and angle of the STS using the Vicon optical gait acquisition system and plantar pressure sensor to find the appropriate angle and speed thresholds.

The center of gravity movement is a prerequisite for the elderly to achieve a comfortable STS. The authors found that the standing speed during the STS process should not be higher than 103.8 mm/s so that the elderly can stand comfortably and safely (safe and dangerous speeds are 72.8 mm/s and 125.2 mm/s). The limitations of waist angle, waist angle speed and the acceleration are also obtained.

This paper analyzes and summarizes the research status of speed and angle during safe and comfortable standing of elderly people, which is essentially a prerequisite for the elderly to achieve a comfortable STS. These results can lay the foundation for the development of assistive devices and related technologies that meet the needs of older adults.

Studies have indicated that international innovation collaboration has promoted technology transfer and knowledge spillover between countries. The conclusion of various international intellectual property (IP) treaties has played an essential role in optimizing the international innovation and collaboration environment. This study investigates the effect of IP treaties on international innovation collaboration and whether international IP treaties can promote collaboration between a country and other economies in the world.

After collecting and extracting the patent record data from the United States Patent and Trademark Office (USPTO), a final dataset of 3,213,626 cooperative patents and 465,236 pairs of collaborations between two countries or regions is established. Based on the international patent collaboration data of 192 countries during 1976–2017, the changes in patent collaboration indicators after these countries joined 23 IP treaties are analyzed.

International IP treaties have significantly increased the number of patent cooperation countries of a country and its importance in international cooperation networks. The role of IP treaties is more manifested by the increased opportunities for a country's international innovation cooperation than its influence on global innovation; this is of extreme significance for developing countries to introduce advanced technologies.

Ginarte and Park (1997) have confirmed that IP treaties have helped to raise the level of IP protection. In this study, the increase in the degree centrality of the international innovation network is evidence of IP treaties to promote innovation cooperation. For a developing country, joining an intellectual property treaty may strengthen intellectual property protection and optimize its own international innovation cooperation methods.

This paper aims to investigate and prepare the composite polyurea greases with excellent thermal stability and tribological properties.

In this paper, composite Ba-based (Ba, barium) tetra-polyurea lubricating greases were prepared with two different methods: mixing Ba-based gelatinizer and tetra-polyurea gelatinizer by a physical method; and introducing barium carboxylate into tetra-polyurea molecules by a chemical method. The properties of the products, such as heat stability, water resistance and friction performance, were analyzed with thermogravimetry, water-resistance test and four-ball friction test.

The results indicated that the products obtained by chemically introducing barium carboxylate into tetra-urea molecules showed better elevated temperature tribological properties, and the disadvantages of the polyurea greases with high temperature hardening were also obviously improved. The cone penetration rate at 180°C for 24 h is only 3 per cent. The friction coefficient can be decreased to 0.44 and the last non-seizure load value was increased from 560 N to 1,120 N without any other additives.

The research is significant because the prepared composite grease showed excellent performances, such as the outstanding thermal stability, water resistance and excellent extreme pressure and anti-wear properties, which may be widely applied in steel, metallurgy, bearings and other industrial fields.

This paper aims to propose a technique based on cognitive assessments to quantify identified operational risks from the perspective of container shipping or logistics system administrators. The results derived from the risk quantification could be used to prioritize risks as well as support the decision-making process in risk prevention and mitigation.

This paper identified container shipping operational risks (CSORs) from a logistics perspective. A multivariate risk evaluation mechanism by fuzzy rules Bayesian network (FRBN) was established. An improved two-level parameter set based on the failure mode and effects analysis (FMEA) was used to support the input extraction process. By feeding cognitive assessments into the model, the identified risks are evaluated based on their utility values. An illustration example and a sensitivity analysis were carried out to justify and validate the proposed model.

The highest positions in the prioritized list of CSORs in the case study are dominated by risks in the physical flow with the first three are piracy and terrorism, force majeure and port congestion. The results derived from the case study with the satisfaction of all pre-defined axioms proved the feasibility and illustrated the functionality of the proposed risk assessment and prioritization technique.

Controlling risk is irrefutably a significant issue of container shipping and logistics management because of the inconsistency of risk definitions and the involvement of uncertainties. The proposed risk evaluation mechanism and the identified list of CSORs could be beneficial in system management, decision-making and reliability performance.

This paper explores optimal service resource management strategy, a continuous challenge for health information service to enhance service performance, optimise service resource utilisation and deliver interactive health information service.

An adaptive optimal service resource management strategy was developed considering a value co-creation model in health information service with a focus on collaborative and interactive with users. The deep reinforcement learning algorithm was embedded in the Internet of Things (IoT)-based health information service system (I-HISS) to allocate service resources by controlling service provision and service adaptation based on user engagement behaviour. The simulation experiments were conducted to evaluate the significance of the proposed algorithm under different user reactions to the health information service.

The results indicate that the proposed service resource management strategy, considering user co-creation in the service delivery, process improved both the service provider’s business revenue and users' individual benefits.

The findings may facilitate the design and implementation of health information services that can achieve a high user service experience with low service operation costs.

This study is amongst the first to propose a service resource management model in I-HISS, considering the value co-creation of the user in the service-dominant logic. The novel artificial intelligence algorithm is developed using the deep reinforcement learning method to learn the adaptive service resource management strategy. The results emphasise user engagement in the health information service process.

Individuals, organizations, firms, and governments have been making strenuous effort to promote sustainable and green consumption. However, it is noticeable that a large amount of unattractive produce is ruthlessly discarded and wasted around the globe, resulting in unsustainable consumption behavior, harming long-term business development, and breaking the harmonious relationship between humans and nature. Therefore, to increase consumer literacy toward unaesthetic produce, this research investigates the pivotal role of “natural” labeling in increasing purchase intention toward visually unattractive fruits and vegetables.

By recruiting participants from one of the largest online crowdsourcing platforms (the Credamo), this research conducts three online experimental studies (with two pilot studies) to test three hypotheses based on the cue utilization theory and the lay belief theory.

The results show that unattractive produce with the “natural” label could significantly increase consumers' purchase intention compared with those without specific labels. The results also reveal that consumers' lay beliefs that natural foods are perceived to be tastier and healthier mediate the positive effects of “natural” labeling (vs no specific labeling) on willingness to purchase.

This research explores competing lay beliefs about unattractive produce. It identifies the positive effects of lay beliefs “natural = tasty and healthy” through “natural” labeling appeal, thus attenuating the misapplication of lay beliefs “unattractive = tasteless and unhealthy” and broadening the application scope of consumer lay belief theory. The findings also contribute to the cue literature by manifesting the positive consequences of the “natural” label playing as a cognitive cue in priming lay beliefs about naturalness. In addition, it also paves a positive way for business practitioners and marketers to develop the produce industry sustainably.

This study examines the effect of cross-border network ties of returnee entrepreneurs on the foreign market diversity of their ventures. The study further investigates how two cross-cultural competencies (global mindset and cultural intelligence) moderate this effect.

A sample of 135 returnee entrepreneurial ventures from China was used to test the hypotheses.

This study finds that returnee entrepreneurs tend to enter into a wide range of culturally different country groups when returnee entrepreneurs have strong cross-border network ties. Moreover, global mindset and cultural intelligence function as complements in strengthening the effect of the cross-border network ties on foreign market diversity.

The authors contribute to both returnee entrepreneurship and foreign market entry literature in two ways. First, by examining the effect of cross-border network ties on foreign market entry, the authors add new and important insights into the role of social networks in the pre-internationalization phase. This is useful in understanding the internationalization process of new ventures founded by returnees, which have not been fully understood in returnee entrepreneurship literature. Second, by examining the moderating roles of global mindset and cultural intelligence, the authors enhance the understanding of the extent to which cross-border networks can be valuable in foreign market entry.

With the advancement of new-types of urbanization, our country needs to construct reasonable structures of the resource-based central city and sub-central city in the regions, to transform the mode of the development of the city, to achieve the coordinated and the sustainable in resources, to avoid the resources of waste and to build the green, low carbon, agglomeration and sustainable new towns. This paper does the analysis of SWOT by putting forward a specific example which establishes Handan as the central city and Wu’an and Feixiang act as the sub-central cities to explore the advantages of choosing resource-based city as a central city, which gives the support in theory and practice for realizing the winwin situation and maximization of interests in the regions.

The purpose of this paper is to attempt to realize a distribution network optimization in supply chain using grey systems theory for uncertain information.

There is much uncertain information in the distribution network optimization of supply chain, including fuzzy information, stochastic information and grey information, etc. Fuzzy information and stochastic information have been studied in supply chain, however grey information of the supply chain has not been covered. In the distribution problem of supply chain, grey demands are taken into account. Then, a mathematics model with grey demands has been constructed, and it can be transformed into a grey chance‐constrained programming model, grey simulation and a proposed hybrid particle swarm optimization are combined to resolve it. An example is also computed in the last part of the paper.

The results are convincing: not only that grey system theory can be used to deal with grey uncertain information about distribution of supply chain, but grey chance‐constrained programming, grey simulation and particle swarm optimization can be combined to resolve the grey model.

The method exposed in the paper can be used to deal with distribution problems with grey information in the supply chain, and network optimization results with a grey uncertain factor could be helpful for supply chain efficiency and practicability.

The paper succeeds in realising both a constructed model of the distribution of supply chain with grey demands and a solution algorithm of the grey mathematics model by using one of the newest developed theories: grey systems theory.