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Adopting efficient marketing strategies is a challenging task in a competitive market place involving complex marketing planning, techniques and mechanisms to identify the best course of action under these circumstances and finding optimal solutions or stable outcomes. Decisions and strategies of competitors in the market influence the selection of the appropriate marketing strategy. The main purpose of this paper is to develop a mathematical methodology based on the game theory approach for planning optimal marketing-mix strategies in dynamic competitive markets, taking into account strategic foresight and interaction effects.

The game theory approach, as a decision-making tool in conflict situations, is suggested for planning and adopting optimal marketing strategy. The main intellectual attraction of the game theory is essentially a question of how to act in gaming situations against highly rational opponents A kind of static, finite and non-cooperative game analytics approach has been developed for this issue, and the proposed model has been implemented to design optimal marketing strategies for two top brands of the automotive parts market in Iran.

The findings of this study show that the optimal marketing-mix strategy for brand A is pricing and for brand B is the product strategy.

Game theory and the Nash equilibrium model can provide a practical approach to find and adopt the right strategy, know competitors' movements and strategies and get more profit.

The integration of the game theory approach into the marketing mix framework has been adopted as a generalized model for marketing strategy planning and analysis as well as to resolve some shortcomings of the marketing mix framework. The Nash equilibrium model has been used to analyze the results. The incorporation of game theory into marketing models has the potential to enrich the scope of marketing modeling.

The purpose of this paper is to investigate the state of the art in static and dynamic games (or inter‐firm relationships). This research area has changed significantly over the last 25 years through the development of phenomena such as the supply chain and the progressive overcoming of monopolistic and oligopolistic frameworks. By exploring the state of the art in inter‐firm relationships, this paper aims to identify the most suitable research methods to be used by future research in this domain and to highlight the major areas under investigation.

This research adopts both qualitative and quantitative approaches. The qualitative approach describes the technical differences between static and dynamic methods and gives evidence of their appropriateness when applied to a game. Quantitative analysis transforms some of the information extracted from the qualitative analysis into categorical variables in order to obtain an indication of the major issues still to be addressed.

The resulting findings identify the extent of the use of static and dynamic modelling in previous research and how their use has changed over time, what resolution methods need to be applied when investigating inter‐firm relationship, what features influence this decision and what research areas still remain unexplored.

The existing literature on the modelling of static and dynamic games lacks an exhaustive review. Several contributions investigate the literature on inter‐firms relationships and review numerous issues, but focus only on static or dynamic modelling. This paper fills this gap by reviewing a number of theoretical papers.

This paper aims to study the impact of existence and lack of discount on the relationships between one manufacturer and one retailer under the cooperative and the non-cooperative games and the members’ profits are compared.

In the first approach, the manufacturer’s price function is constant, and in the second approach, this price function is a decreasing function with respect to lot size. These approaches are modeled through three games structure, including two Stackelberg games and one cooperative game.

Some numerical instances comprising sensitivity analysis are provided, and then the members’ profits in different scenarios are compared. This paper reveals that in the presented models, whether the members are inclined to change their profits.

This paper presents a tool of decision-making for the type of relationships of members in two different circumstances, and an approach is also presented to maximize the members’ profit.

In this paper, the relationships between one manufacturer and one retailer are studied under six different circumstances, where pricing, cooperative advertising and inventory cost are considered simultaneously. Also, a different model is presented to make a balance in individual profits and gain more profit for each member compared to the cooperative and non-cooperative game.

The purpose of this paper is to review the concepts of “fun and play” and propose a preliminary model that suggests potential benefits for quantitatively/qualitatively rating serious games and simulations associated with corporate and university game-based learning (GBL).

A relevant literature review was executed to locate significant references to fun and play, assessment of GBL, and the pattern for integrating those elements with knowledge mobilization (KMb). A repertory grid method (RGM) was used to propose a preliminary model.

The proposed FUNIFICATION Model will be useful as a foundation for further evaluation of GBL environments.

Additional rationalization of the proposed model and applying it to actual games with focus groups as the observers would provide additional validity to the new model.

A threshold for fun involved in serious games and simulations would provide a quantitative/qualitative measure for playability of serious games and simulations. The FUNIFICATION Factor would feed into a KMb model for acquiring, codifying, disseminating, and making knowledge actionable, either within academic, corporate, or public sector environments.

The range of assessment models for GBL is evident from the literature review, and value could be derived in building an evaluation model based upon the RGM to identify a FUNIFICATION Factor for serious games and simulations.

This chapter explores a number of issues connected with the use of game-theoretic models to organize analytic narratives, both generally and specifically. First, a causal explanation of the Rhineland crisis of 1936 is developed within the confines of a game-theoretic model of asymmetric or unilateral deterrence. Then some methodological obstacles that may arise in more complex cases are discussed and suggestions for overcoming them are offered. Finally, the advantages of using game models to more fully understand real world events are highlighted.

The purpose of this paper is to compare the pricing decisions and earning potential of the software supplier and the smart device manufacturer in different software promotion strategies.

Based on game theory, the authors formulate two promotion models, that is, the supplier implements software promotion activities individually (SP model) or outsources the promotion activity to the manufacturer under profit-sharing contract (MP model) when taking different channel power structures into consideration. Besides, in order to test the robustness of the conclusions, the authors also extend the basic model to the following situations: (1) the customers have different price elasticity toward service fee and product price; (2) the revenue sharing contract is employed by the supply chain members; and (3) the manufacturer's product promotion practice is taken into consideration.

The optimal service fee (product price) of the supplier (manufacturer) under SP model is always lower (higher) than that under MP model. Surprisingly, if the supplier is the channel leader and the profit sharing ratio exceeds certain threshold, the manufacturer's profit decreases in profit sharing ratio, which remains robust in three extension models. Moreover, the supply chain's profit in supplier-led game is always lower than that in Nash game irrespective of the promotion strategy in profit sharing context. When revenue sharing contract is adopted, the result holds only when the revenue sharing ratio is relatively low.

The authors originally explore two promotion strategies of the software supplier when taking the channel power structures into considerations, which has not been explored in the literature to the best of the authors' knowledge.

The purpose of this paper is to summarize ways in which game theory has been or could be utilized within the humanitarian sector and to identify future research opportunities in this field. Game theory is a tool for modeling systems in which multiple decision makers act according to their own objectives and where individual choices affect system outcomes. Humanitarian logistics systems are often characterized by the presence of many such decision makers.

The authors synthesize literature from operations research, humanitarian logistics, and the political and management sciences that describes either game theory models or settings in which game theory has the potential to contribute practical insights. Papers are categorized based on the types of decision makers highlighted and the facets of humanitarian operations described.

The review of literature indicates that applications of game theory to humanitarian supply chain systems are limited to date but that many components of humanitarian operations can benefit from such study.

The literature on game theory in humanitarian supply chains is still emerging. The findings imply opportunities for researchers to advance both theoretical and practical understanding in this area.

Current research provides some managerial insights to humanitarian practitioners, but future practice-driven research could increase the impact of game theory models in the humanitarian sector.

This work reviews past research contributions in the area of game theory and humanitarian operations and recommends areas for future research.

This article aims to provide an interactive model for hands on training of malware analysis. Cyberwar games are the highly stylized representation of cyber conflicts in a simulation model. Game models are helpful in understanding the phenomenon of cyber attacks as well as to evolve new techniques of detection. Cyber security trainings are generally very challenging. Cyber test beds make such trainings easy both for trainees and trainers. However, it is not feasible for each organization to build a network for the sole purpose of hands-on training for employees. Therefore, it is desirable to build an interactive environment that is interesting and free of cost as well.

After exploring existing cyberwar games and their techniques, limitation and strengths, this paper presents a design to merge the cyber attacks into a unique model of war game for detection and analysis of malware. This research designs a malware analysis testbed using online free resources. The authors have used the platform of Cyber Defense Technology Experimental Research (DETER). This study proposed model of a testbed that supports malware reverse engineering scenarios, exercise logs and analysis to develop reverse engineering tactics.

The proposed cyber testbed is an automated system that can be used as a platform to train cyber warriors. A few features of the proposed testbed are as follows: testbed provides real or seemingly real malware communication with the real world. It includes automated decisions for the detection of malicious behavior without human intervention. The author gives a design to develop free of cost mechanism for remote learning of highly technical cyber security areas, and this simulation is for malware analysis.

Cyberwar games are built for strengthening offensive and defensive capabilities in cyberspace. For this purpose, many simulations, as well as emulation platforms, can be found. Some are free and open-source, whereas others are commercial and quite expensive. Existing testbeds have limitations in respect of cyberwar games for creating innovative scenarios. Existing literature does not offer any attack and response scenario developed for malware detection through some existing open-source and online simulation or emulation environments. This research includes an analysis of the existing platforms as well as the design of a new model for malware analysis and training.

In the process of group decision-making, there may be multilayer subjects. In other words, members of the decision-making group may come from different layers and there is interest game among decision experts. Therefore, it is an extremely important topic to aggregate the information of decision experts who are involved in hierarchical relations and gaming relations so as to effectively address game conflicts and reach game cooperation.

First, a programming model is established to minimize the difference of expert opinions in hierarchical decision-making, and the method to solve the optimal solution is given. Second, the cooperative game model and its properties are discussed by using cooperative game and Shapley value, and the method to determine the weight vector between layers is also proposed.

This model can quickly aggregate information and achieve game equilibrium among decision-makers with hierarchical relationships. It can be widely used in decision evaluation with hierarchy structure and has certain practical value.

In order to solve the problem that experts at different levels may have conflicts of interest in multilayer grey situation group decision-making process, cooperative game and Shapley value theory are introduced into the study, and a multilayer grey situation group decision-making model based on cooperative game is constructed. The validity and practicability of the model are illustrated by an example.

The purpose of this paper is to attempt the construct of a Centipede Game network model of investment in real estate market based on grey integration and forwards induction.

The investment process of decision making in the real estate market is a multi-agent-stage dynamic process. The behavior of the game are interdependent and the ultimated equilibrium is an outcome of every the game adjust themselves comprehensively in certain conditions. The paper constructs a Centipede Game network model of investment in real estate market based on grey integration and forwards induction, regulars the method framework based on grey integration and forwards induction.

The results verifies that the validity of Centipede Game network model by taking N's real estate market as an example.

Most of the existing real estate market game researches study it from the view of pairwise game or one-to-many game, in fact, the game tend to be developed in the form of a network. And the paper puts forward Centipede Game network model based on the mode of players game in real estate market.

The paper succeeds in providing a new and systematic framework of studying the real estate market game by using game theory.