Cooperation Willingness Research Articles

Ecological compensation for cross-regional domestic waste treatment: A stochastic differential game perspective.

The implementation of ecological compensation for cross-regional domestic waste treatment is beneficial for balancing the interests of waste generation districts and waste treatment districts. This paper introduces dynamic differential games to capture the temporal evolution and adjustment of strategies, examining dynamic game strategies under different compensation scenarios (non-horizontal ecological compensation, horizontal ecological compensation and fully shared ecological compensation). A new interest distribution model is proposed, with empirical analysis conducted using Shanghai as a case study to validate the reliability and feasibility of the model. The findings indicate: (1) Government intervention combined with horizontal ecological compensation significantly improves waste management efficiency and urban welfare. The compensation mechanism fosters regional cooperation, optimizes resource allocation, reduces decision-making conflicts and enhances overall processing effectiveness. (2) Without a compensation mechanism, high costs in export regions and low benefits in import regions result in low cooperation willingness. The ecological compensation mechanism enhances willingness to cooperate by fairly distributing costs and benefits, optimizing long-term cooperation and overall gains. (3) Complete shared ecological compensation is optimal, though partial shared mechanisms are also effective in practice. Proper interest and ecological compensation ratios can significantly improve waste management efficiency and urban environment, strengthening long-term cooperation. The study theoretically expands the dynamic optimization and cooperation mechanism analysis in waste management, provides solutions for environmental policy formulation in cross-regional waste handling and offers new perspectives and tools for addressing complex issues in cross-regional environmental governance, including targeted policy recommendations with practical significance for enhancing cross-regional waste management.

Do climate disasters make farmers more willing to cooperate? Evidence from rural communities in southern China

PurposeThis article aims to explore the impact of climate disasters on small-scale farmers’ willingness to cooperate and explore the mediating effect of social capital.Design/methodology/approachThe study investigates farmers’ willingness to cooperate through a framed field approach and surveys the information of individuals and villages, including climate disasters and social capital, using a structured questionnaire from rural communities in Jiangxi and Sichuan, China.FindingsThe results show that climate disasters and social capital are significant and positive determinants of farmers’ willingness to cooperate. In specific types of climate disasters, drought is positively associated with farmers’ cooperation willingness. Moreover, the mediation effect of drought on farmers’ willingness to cooperate through social capital has been demonstrated to be significant although negative, whereas the mediation effect of flood on farmers’ willingness to cooperate through social capital is significant and positive.Originality/valueFirst, given the limited studies focusing on the impact of climate disasters on small-scale farmers’ willingness to cooperate, the authors complement the existing literature through a framed field experiment approach by designing a scenario that every farmer may encounter in their production activities. Second, the study figures out the roles of drought and flood as different kinds of climate disasters in farmers’ decision-making of cooperation and sheds light on the positive impact of climate disasters on small-scale farmers. Finally, this paper provides empirical evidence of social capital as a potential channel through which climate disasters could possibly affect farmers’ willingness to cooperate.

Green Supplier Assessment and Selection for Sea Cucumber (Apostichopus japonicus) Processing Enterprise: Case Study in China

Green supply chain management is a crucial way to balance economic benefits and environmental impacts. As an important economic aquatic product in China, sea cucumber (Apostichopus japonicus) is facing the dual challenges of economic benefits (profit) and environmental sustainability (material input and emission output). Currently, the sea cucumber industry in China lacks a green supplier screening system, resulting in a fragmented pattern of cooperation among enterprises. Core enterprises in the supply chain cannot assume social responsibility to help and guide upstream and downstream enterprises to jointly improve environmental performance. This study focuses on the selection and evaluation of green suppliers for sea cucumber processing enterprises. Firstly, a green supplier assessment indicator system for sea cucumber processing enterprises was established, and the indicator weights were determined by the analytic hierarchy process (AHP) method. Next taking a large sea cucumber processing enterprise in Dalian, China, as an example, the importance level of each index was evaluated by fuzzy comprehensive evaluation (FCE), and the score and ranking of existing suppliers were determined. The validity and practicality of the method were verified. The results show that Supplier 1 (S1) has the highest score, and the price of sea cucumber farming, the cleaner production level of sea cucumber farming, environmental awareness, and long-term cooperation willingness were the most important factors in the selection of green suppliers for sea cucumber processing enterprises, which provides useful clues on the best practice of making sustainable development decisions. With an in-depth understanding of the key factors, suppliers can formulate different prices according to the differences in sales channels to improve the economic deficiencies. Environmental pollution can also be reduced by using clean energy, establishing a recirculating aquaculture system, and using micro-ecological preparations. The conclusions of this study can provide technical support and decision-making suggestions for the application of green supply chain management in China’s aquaculture industry.

A Multiplatform-Cooperation-Based Task Assignment Mechanism for Mobile Crowdsensing

Mobile crowdsensing (MCS) has been an effective sensing paradigm by utilizing the smart devices carried by mobile users to complete sensing tasks at different locations. An important problem in MCS is how to achieve effective task assignment in the context of opportunistic sensing, where mobile users are selectively recruited to perform tasks in an opportunistic way. However, most existing work in this aspect suppose there are only one service platform and further the sensing qualities of users are known apriori. In this paper, we study the task assignment when there are multiple service platforms and further the sensing qualities of users are unknown apriori. The design objective is to maximize the overall sensing qualities of finished tasks at all platforms. For this purpose, we build a multi-platform cooperation framework and formulate the task quality maximization problem in this case as a 0-1 integer linear programming (ILP) problem. We propose a Multi-platform Cooperation based Task Assignment mechanism (MCTA). MCTA includes two phases. The first phase establishes stable cooperation relationship among platforms while respecting their respective cooperation willingness, and for this phase, we propose a cross-platform cooperation relationship construction algorithm. The second phase performs effective online task assignment, and for this phase, we propose two online Multi-Armed Bandit (MAB) with sleeping arms based user selection algorithms using local and global learning, respectively, based on whether cross-platform user-sensing-quality learning is allowed. We derive the regrets of the proposed algorithms and prove that MCTA has the properties of cooperation stability and computation efficiency. Extensive simulation results show the high performance of our proposed MCTA mechanism as compared with existing work.

A Large Group Emergency Decision-Making Method Based on Uncertain Linguistic Cloud Similarity Method

In recent years, the consensus-reaching process of large group decision making has attracted much attention in the research society, especially in emergency environment area. However, the decision information is always limited and inaccurate. The trust relationship among decision makers has been proven to exert important impacts on group consensus. In this study, we proposed a novel uncertain linguistic cloud similarity method based on trust update and the opinion interaction mechanism. Firstly, we transformed the linguistic preferences into clouds and used cloud similarity to divide large-scale decision makers into several groups. Secondly, an improved PageRank algorithm based on the trust relationship was developed to calculate the weights of decision makers. A combined weighting method considering the similarity and group size was also presented to calculate the weights of groups. Thirdly, a trust updating mechanism based on cloud similarity, consensus level, and cooperation willingness was developed to speed up the consensus-reaching process, and an opinion interaction mechanism was constructed to measure the consensus level of decision makers. Finally, a numerical experiment effectively illustrated the feasibility of the proposed method. The proposed method was proven to maximally retain the randomness and fuzziness of the decision information during a consensus-reaching process with fast convergent speed and good practicality.

Modeling Isotropic Traffic Flow Under Vehicle-to-Vehicle Communication: A Kinetic Approach

Vehicle-to-vehicle communication enables inter-vehicle interactions by sending a message or exchanging data. So a vehicle is affected not only by the ones in front but also by the ones behind. The mutual influence changes the feature of traffic flow from the anisotropy to the isotropy. In this paper, I model vehicle interactions by a stochastic game and formulate the isotropic flow in lane-based traffic by a kinetic approach. Specifically, a scalar variable, called the cooperation willingness, is introduced, which may evolve as time passes. Also, I formulate a mapping between the cooperation willingness and the cooperation probability. I embed the cooperation probability into the stochastic game. Also, a general expression of the evolution equation of cooperation willingness is derived. The equilibrium solutions for a given choice of five and seven discrete classes of the cooperation willingness are solved. Finally, the proposed kinetic model of the isotropic lane-based traffic flow is used to simulate the merging of two clusters of vehicles. The results show that the nudging of vehicles ahead can improve the efficiency of traffic flow. It also confirms the theoretical analysis results.

Influencing factors of and multiple paths to high performance in multidisciplinary scientific research cooperation in colleges in China: a fuzzy-set qualitative comparative analysis.

BackgroundIn the context of globalization of science and technology, multidisciplinary cooperation plays an important role in enhancing national scientific research strength. Many countries issue policies and reports to promote the implementation of interdisciplinary research. Colleges play a central role in knowledge generation and scientific inquiry and thus frequently contain a variety of scientific research organizations. With rapid advances in science, large-scale scientific research cooperation across disciplines and institutions is increasingly common. Many factors can affect the performance of research collaboration, and the implementation paths of some key factors remain unclear. In addition, no standardized collaboration system has been established in relevant research. Further studies on interdisciplinary scientific research cooperation will be particularly valuable for improving the efficiency of resource allocation and increasing the level of academic research. Here we explored the “joint effect” of various influencing factors on interdisciplinary collaborative research in colleges and the “interactions” among these factors.MethodsWith stratified-cluster random sampling, 358 researchers from 181 research teams at 6 colleges across China were surveyed using a self-administered questionnaire. We used fuzzy-set qualitative comparative analysis (fsQCA) to analyze data to obtain more insight into the status quo of interdisciplinary cooperation among colleges.ResultsThe results showed that initiation and organization by an institution was a necessary condition for achieving high-performance scientific research collaboration. The performance incentive method of high-tech collaboration could be divided into four main paths: configuration organized by an institution; configuration organized by an institution, with high policy-based guarantees (PG); configuration organized by an institution, with high cooperation willingness (CW) and high cooperation ability (CA); and configuration organized by an institution, with high CW, abilities, and outputs. The drive mechanism of high performance in scientific cooperation could be divided into two types: organization-led and ability/willingness-driven.ConclusionsOnly the integration of internal changes with the support of the external environment can ensure the stable development of multidisciplinary scientific research cooperation among colleges.

Customer relationships, corporate social responsibility, and stock price reaction: Lessons from China during health crisis times

This paper studies the effect of corporate social responsibility (CSR) and customer relationships on the stock price during the COVID-19 pandemic. The empirical results show that CSR practices improve firms’ resilience to the negative health crisis shocks. The functional principal component analysis helps display the relationship between CSR and cumulative abnormal returns (CAR). It shows that CSR practices improve customers’ cooperation willingness. Customers of high-CSR firms pay invoices faster during the crisis, which results in less increment of accounts receivable. Hence, high-CSR firms gain more cash support from their customers to overcome the COVID-19 pandemic, resulting in higher cumulative abnormal returns.

Research on Cooperative Behavior of Green Technology Innovation in Construction Enterprises Based on Evolutionary Game

The dynamic evolution game model is built by using evolutionary game theory, and the evolutionarily stable strategy is analyzed by matlab2018b software in this paper. The cooperation willingness, sharing level, income distribution, and punishment mechanism are comprehensively considered in this model, and numerical simulations of the influence of various influencing factors on the cooperation strategy selection of green technology innovation for construction enterprises are carried out. Then, countermeasures and suggestions are put forward. The results of evolutionary game analysis show that the cooperation willingness, sharing level, income distribution, and punishment mechanism have a significant impact on the cooperative evolution direction of green technology innovation for construction enterprises, separately. Stronger cooperation willingness or higher relative value of positive spillover, or reasonable income distribution can promote partners to adopt active cooperative strategies, while appropriately increasing punishment intensity can prevent opportunistic behaviors and improve the probability of success of cooperative innovation.

How to escape the dilemma of charging infrastructure construction? A multi-sectorial stochastic evolutionary game model

Providing effective charging infrastructure is an essential step in popularizing electric vehicles, which is conductive to improving pollution induced by traditional fuel vehicles and thus improving the environmental sustainability. The most crucial factor in escaping the dilemma of charging infrastructure construction lies in the synergies of multi-sectorial. This paper develops a stochastic evolutionary game model grounded on the strategy adoption of charging infrastructure construction involving governments (public), companies (private), and consumers (civil). We collect the data of Shanghai for simulation to compare the influence of strategy adoption. Our findings suggest that ⅰ) unlike the public and civil sector, in the current situation, the private sector will adopt the defector strategy quickly and lock in the defection state as time goes on; ⅱ) the additional cost effect caused by public-civil co-construction scenario is significant positive to the public sector but almost no impact on the civil sector; ⅲ) civil's strategy adoption has directional differences under two cost sharing scenarios (private-civil and public-civil) of charging infrastructures construction. In the private-civil scenario, if the cost of charging infrastructures construction is transferred to the civil sector, not only will it not change the private-sectorial defection state, but it will also cause civil sector to shift from cooperation to defection. However, at the same sharing ratio of the public-civil scenario, the civil sector is still willing to cooperate. ⅳ) reducing incentives of electric vehicles or increasing costs of internal combustion engine vehicles is necessary, which will not change the lock-in cooperation state of civil sector, and it can improve the cooperation willingness of publicsector.

System dynamics mechanism of cross-regional collaborative dispatch of emergency supplies based on multi-agent game

The cross-regional coordinated dispatch of emergency supplies is a complex issue involving multiple topics, which covers multiple relationships and is affected by multiple variables. In the face of severe emergencies, relief supplies inside a specific area are far from meeting the explosive demand for emergency supplies. Besides, the supply of emergency materials and the disaster areas often have a spatial mismatch. Considering the attributes of externalities and public goods of emergency rescue, there are many obstacles for Local administration of emergency (LAE) and emergency logistics enterprises (ELE) spontaneously carrying out emergency supplies across regions. To solve this complexity problem, this research abstracts higher-level administration of emergency (HAE), LAE and ELE as the main stakeholders, with which a tripartite evolutionary game (ETG) model and a system dynamic (SD) model are constructed to analyze the dynamic mechanism of the complex system and to carry out the numerical simulation of the three-party game process. All the analyses and tests in this study have proved that the strong supervision of HAE has a decisive impact on the realization of cross-regional coordinated dispatch of emergency supplies, and the financial rewards and punishments imposed by HAE on other entities can accelerate or delay the achievement of the equilibrium strategy. However, when HAE chooses not to regulate, the cooperation willingness of LAE affects a lot that all the stakeholders will eventually reach equilibrium at (1,1,1) only if LAE chooses to actively carry out cross-regional coordinated dispatch of emergency supplies.

Critical creativity: managing creativity as a strategic resource in media organisations

ABSTRACT This article addresses the critical role of creativity as a core resource in media work. Drawing on an empirical analysis, the study produces a new understanding about the significance of creativity in media organisations and their management. It identifies three critical aspects of creativity, i.e. co-operation willingness, experimental atmosphere and supportive practices, and discusses three corresponding managerial focus areas. Thus, this article offers both theoretical contributions in relation to critical creativity in media work and practical implications for managing creativity as a strategic resource in media organisations.

The Formation Mechanism of Green Dairy Industry Chain from the Perspective of Green Sustainable Development

By constructing an evolutionary game model of green dairy industry chain from the perspective of green sustainable development, this paper analyzed the evolution process of strategy selection of dairy farmers and dairy enterprises under the supervision of the government. The study found the following. (1) In the absence of supervision, even if the initial cooperation willingness of dairy farmers and dairy enterprises is strong, once the additional cost of their input of “green production” is less than the additional benefit, they will eventually choose noncooperative strategy. (2) In the case of government supervision, when the government punishment or subsidy is not strong enough, the strategic choice of dairy farmers and dairy enterprises will fluctuate repeatedly, and the game equilibrium cannot be reached. However, when the government punishments and subsidies are strong enough, dairy farmers and dairy enterprises will choose to cooperate in their own interests. At this time, government subsidies have a greater impact on the evolution of bilateral cooperation than government punishments. (3) The reduction of green production cost can promote the formation of the green dairy industry chain, which is conducive to the green dairy industry chain system to achieve an ideal equilibrium state.

Providing secure and reliable communication for next generation networks in smart cities

Finding a framework that provides continuous, reliable, secure and sustainable diversified smart city services proves to be challenging in today’s traditional cloud centralized solutions. This article envisions a Mobile Edge Computing (MEC) solution that enables node collaboration among IoT devices to provide reliable and secure communication between devices and the fog layer on one hand, and the fog layer and the cloud layer on the other hand. The solution assumes that collaboration is determined based on nodes’ resource capabilities and cooperation willingness. Resource capabilities are defined using ontologies, while willingness to cooperate is described using a three-factor node criteria, namely: nature, attitude and awareness. A learning method is adopted to identify candidates for the service composition and delivery process. We show that the system does not require extensive training for services to be delivered correct and accurate. The proposed solution reduces the amount of unnecessary traffic flow to and from the edge, by relying on node-to-node communication protocols. Communication to the fog and cloud layers is used for more data and computing-extensive applications, hence, ensuring secure communication protocols to the cloud. Preliminary simulations are conducted to showcase the effectiveness of adapting the proposed framework to achieve smart city sustainability through service reliability and security. Results show that the proposed solution outperforms other semi-cooperative and non-cooperative service composition techniques in terms of efficient service delivery and composition delay, service hit ratio, and suspicious node identification.

Channel Coordination under Predictive and Corrective Maintenance Outsourcing

With respect to Industry 4.0, predictive maintenance plays an important role in production systems. A better predictive maintenance strategy is absolutely essential to an efficient, reliable and safe production process. This study considers a supply chain that consists of a manufacturer and an external contractor wherein the manufacturer is willing to outsource the predictive maintenance activities provided by the contractor. In order to achieve channel coordination, we introduce three incentive contracts: 1) maintenance cost subsidisation contract; 2) uptime target and bonus contract; 3) uptime reward contract, which enhance the cooperation willingness of the contractor and increases profit for both parties, thereby leading to a win-win situation. We also discuss the feasibility of the contracts given improvements in the failure rate and maintenance capability. Theoretical results show that the uptime target and bonus and uptime reward contracts can achieve channel coordination under specific conditions given increases in the failures rate and maintenance capacity. Numerical results are further presented to reveal the managerial insights.

GroupCast: Preference-Aware Cooperative Video Streaming With Scalable Video Coding

In this paper, we propose a preference-aware cooperative video streaming system for videos encoded using scalable video coding (SVC). In the proposed system, the collaborating users are interested in watching a video together on a shared screen. However, the willingness of each user to cooperate is subject to her own constraints such as user data plans. Using SVC, videos are segmented into chunks and each chunk is encoded using layers, where each layer can be fetched through any of the collaborating users. We formulate the problem of finding the optimal quality decisions and fetching policy of the SVC layers of video chunks subject to the available bandwidth, chunk deadlines, and cooperation willingness of the different users as an optimization problem. The objective is to optimize a QoE metric that maintains a trade-off between maximizing the playback rate of every chunk and ensuring fairness among all chunks to achieve the minimum skip (stall) duration without violating any of the imposed constraints. We propose an offline algorithm to solve the non-convex optimization problem when the bandwidth prediction is non-causally known. This algorithm has a run-time complexity that is polynomial in the video length and the number of collaborating users. Furthermore, we propose an online version of the algorithm for practical scenarios, where erroneous bandwidth prediction for a short window is used. Real implementation with android devices using SVC encoded video and a public dataset of bandwidth traces reveals the robustness and performance of the proposed algorithm and shows that the algorithm significantly outperforms round robin-based mechanisms in terms of avoiding skips/stalls and fetching video chunks at their highest quality possible.

SRSM-Based Adaptive Relay Selection for D2D Communications

This paper proposes an adaptive relay selection method that exploits the social network and establishes a physical domain and social domain-based model named the Social-based device-to-device (D2D) relay selection model to address relay selection failure caused by the diversity of users cooperation willingness and the instability of communication links due to human mobility. Under the premise of tolerable interference caused to cellular users, the proposed approach synthetically considers the desired physical-relation factor and the social-interaction factor for the relay user. In particular, the reliability of the D2D link is obtained by considering the transmission stability of the link, assessed by the user encounter history and cooperation willingness characterized by user social distance, which is set as the criterion of relay selection, combined with the physical channel condition. Simulation results show that compared with the traditional socially blind method, the proposed method can increase the probability of relay selection success and reduce the burden of the cellular network to improve the system performance.

Cooperative Innovation Evolutionary Game Analysis of Industrialized Building Supply Chain

Great changes have taken place in construction methods of industrial building relative to traditional construction. The cooperation between construction contractors, prefabricated parts suppliers and other materials and equipment suppliers in the supply chain of the industrial building can not be ignored. The evolutionary game theory can be used to explain the dynamic trend of the relationship until it is stable. The evolutionary game theory is applied to study the process and method of cooperative innovation between construction contractor and many subcontractors. Based on evolutionary game theory, the paper discusses the process and method of cooperative innovation between the construction contractors and numerous subcontractors. It focuses on the analysis of the influence of cooperative profit distribution, spillover effect, innovation subsidies and cooperation risk sharing for evolutionary stable strategy. The evolutionary game model of cooperation parties is constructed. The key indexes such as profit, risk loss, distribution of excess income and innovation cost are considered comprehensively. The results show that with the increasing of the spillover effect, innovation cooperation, suppliers’ innovation income and excess returns of cooperation innovation, the system will tend to the stability of cooperation. And with the increasing of the contractor's subsidy coefficient, the innovation cost, cooperation innovation risk cost, the system will tend to uncooperative. There exists an optimal distribution coefficient of excess income, which can strengthen the cooperation willingness of both sides. This study provides a guidance for the cooperative innovation of the supply chain participating parties.

A capabilities-based service development process for industrial manufacturers

Despite years of research regarding service innovation, there is no generally recognised model for the process of new service development (NSD). Focusing on industrial manufacturers, we create a new approach based on the participating actors' resources and capabilities. After determining general characteristics of the NSD process, we deduce corresponding requirements conducting a literature review. We find that during NSD, the supplier has to develop, next to the service elements the client receives afterwards, resources and capabilities which are required for the later delivery and hence closely linked. To learn about its necessary resources and capabilities and to match them with those of the customer the firm needs to consider organisational antecedents, communicative and collaborative skills as well as the processing and integration of new knowledge during all innovation stages. Besides, it has to assess the clients' cooperation willingness to gain knowledge about the customers' resources and capabilities from the beginning.

A capabilities-based service development process for industrial manufacturers

Despite years of research regarding service innovation, there is no generally recognised model for the process of new service development (NSD). Focusing on industrial manufacturers, we create a new approach based on the participating actors' resources and capabilities. After determining general characteristics of the NSD process, we deduce corresponding requirements conducting a literature review. We find that during NSD, the supplier has to develop, next to the service elements the client receives afterwards, resources and capabilities which are required for the later delivery and hence closely linked. To learn about its necessary resources and capabilities and to match them with those of the customer the firm needs to consider organisational antecedents, communicative and collaborative skills as well as the processing and integration of new knowledge during all innovation stages. Besides, it has to assess the clients' cooperation willingness to gain knowledge about the customers' resources and capabilities from the beginning.