Niche Theory Analysis of Sustainable Strategic Relationships among MICE Destinations: A Case of New Zealand

This study aimed to analyze the competitive relationship among meetings, incentive, convention and exhibition (MICE) destinations with reference to the notion of niche businesses in New Zealand; and to explore the existence of cooperative strategies between neighboring destinations. The data were collected from Ministry of Business, Innovation and Employment Reports on the Convention Activity Survey (CAS) in New Zealand. The study contributes towards an innovative and better understanding of the dynamics of sustainable destination competitiveness. It broadens the scope of MICE industry research by exploring new insights on the notion of destination competition and makes a theoretical connection between niche theory and the importance of coopetition. By investigating the case of MICE destinations of four northern central islands in New Zealand, this study provides information on the strategic significance of niche marketing for global destinations preparing for entrance into this market.

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.

An Investigation of Conflict Resolution Strategies for the Students of Elementary School Teacher Education Study in Online Learning during the COVID-19 Pandemic

This study aims at identifying various types of conflicts experienced by students of elementary school teacher study program during online learning of elementary social studies learning courses during the COVID-19 pandemic, and determining the strategies they used to resolve conflicts they encountered . This study uses a descriptive research method with a survey design. The research participants were 4th semester students of the PGSD study program in a private university in the West Java region, totaling 243 that consisted of 182 female students and 61 male students. The instruments used in this study were interviews that were used to identify the conflicts experienced by students during online learning, and closed questionnaires that were distributed to determine the strategies used to resolve the conflicts; which were analyzed descriptively. Based on the data obtained from the interviews, it was revealed that the conflicts experienced by students during online learning were completing group assignments, bullying between students, discriminatory attitude, and acknowledging/taking goods/works of others without asking permission. Meanwhile, based on the data obtained from the questionnaires regarding the students' strategies in resolving conflicts, it was found that students used cooperative strategies in resolving these conflicts.

Aglaya Play: Designing a software solution for group compositions in the music classroom

This article details the design for Aglaya Play, a proposed software system that aims to meet three basic needs in the music classroom: the incorporation of creative processes, the adoption of collaborative-cooperative strategies and the reduction of reading–writing- and theory-based learning in the early stages of music education. The text contextualizes the needs that the software intends to meet and describes its phases of construction from a design-based research perspective. Finally, a full description of the system is offered based on its functions, and suggestions for its didactic implementation are provided.

Balancing quality and quantity of social relationships in volatile social environments

Cooperative interactions do not occur in a vacuum, but develop over time in social groups that undergo demographic changes. Intuition suggests that stable social environments might favour individuals that develop few but strong reciprocal relationships (a 'focused' strategy), while volatile social environments do the opposite and favour individuals with more but weaker social relationships (a 'diversifying' strategy). We model reciprocal investments under a tradeoff between quantity and quality of social relationships, and reveal that this intuition is fallible. We find that volatile social environments particularly favour a focused cooperative strategy. This result can be explained by applying the theory of antagonistic pleiotropy, originally developed for senescence, to cooperative strategies. Diversifying social investments benefits late-life individuals that already have their social network built up, but is detrimental early in life when networks must be built from scratch. Under volatile social environments, the age structure of a population remains generally young, and this emphasizes strategies that do well early in life: a focused strategy which makes the individual form its first few social bonds happen quickly. Overall, our model highlights the importance of pleiotropy and population age structure for the evolution of cooperative strategies and other social traits.

Many-Objective Particle Swarm Optimization Algorithm Based on New Fitness Allocation and Multiple Cooperative Strategies

Many-objective optimization problems (MaOPs) refer to those multi-objective problems (MOPs) withmore than three objectives. In order to solve MaOPs, a multi-objective particle swarm optimization algorithm based on new fitness assignment and multi cooperation strategy(FAMSHMPSO) is proposed. Firstly, this paper proposes a new fitness allocation method based on fuzzy information theory to enhance the convergence of the algorithm. Then a new multi criteria mutation strategy is introduced to disturb the population and improve the diversity of the algorithm. Finally, the external files are maintained by the three-point shortest path method, which improves the quality of the solution. The performance of FAMSHMPSO algorithm is evaluated by evaluating the mean value, standard deviation and IGD+ index of the target value on dtlz test function set of different targets of FAMSHMPSO algorithm and other five representative multi-objective evolutionary algorithms. The experimental results show that FAMSHMPSO algorithm has obvious performance advantages in convergence, diversity and robustness.

Many-objective Particle Swarm Optimization Algorithm Based on New Fitness Allocation and Multiply Cooperative Strategies

Many-objective optimization problems (MaOPs) refer to those multi-objective problems (MOPs) withmore than three objectives. In order to solve MaOPs, a multi-objective particle swarm optimization algorithm based on new fitness assignment and multi cooperation strategy(FAMSHMPSO) is proposed. Firstly, this paper proposes a new fitness allocation method based on fuzzy information theory to enhance the convergence of the algorithm. Then a new multi criteria mutation strategy is introduced to disturb the population and improve the diversity of the algorithm. Finally, the external files are maintained by the three-point shortest path method, which improves the quality of the solution. The performance of FAMSHMPSO algorithm is evaluated by evaluating the mean value, standard deviation and IGD+ index of the target value on dtlz test function set of different targets of FAMSHMPSO algorithm and other five representative multi-objective evolutionary algorithms. The experimental results show that FAMSHMPSO algorithm has obvious performance advantages in convergence, diversity and robustness.