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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 use the game theory combined with Monte Carlo simulation modelling to support the analysis of different retail marketing strategies, in particular, using payoff matrices for modelling the likely outcomes from different retail marketing strategies.

Theoretical research was utilised to develop a practical approach for applying game theory to retail marketing strategies via payoff matrices combined with Monte Carlo simulation modelling.

Game theory combined with Monte Carlo simulation modelling can provide a formal approach to understanding consumer decision making in a retail environment, which can support the development of retail marketing strategies.

Game theory combined with Monte Carlo simulation modelling can support the modelling of the interaction between retail marketing actions and consumer responses in a practical formal probabilistic manner, which can inform marketing strategies used by retail companies in a practical manner.

Game theory combined with Monte Carlo simulation modelling can provide a formalised mechanism for examining how consumers may respond to different retail marketing strategies.

The originality of this research is the practical application of game theory to retail marketing, in particular the use of payoff matrices combined with Monte Carlo simulation modelling to examine likely consumer behaviour in response to different retail marketing approaches.

The purpose of this paper is to illustrate how game theoretic solution concepts inform what classes of problems will be amenable to artificial intelligence and machine learning (AI/ML), and how to evolve the interaction between human and artificial intelligence.

The approach addresses the development of operational gaming to support planning and decision making. It then provides a succinct summary of game theory for those designing and using games, with an emphasis on information conditions and solution concepts. It addresses how experimentation demonstrates where human decisions differ from game theoretic solution concepts and how games have been used to develop AI/ML. It concludes by suggesting what classes of problems will be amenable to AI/ML, and which will not. It goes on to propose a method for evolving human/artificial intelligence.

Game theoretic solution concepts inform classes of problems where AI/ML 'solutions' will be suspect. The complexity of the subject requires a campaign of learning.

Though games have been essential to the development of AI/ML, practitioners have yet to employ game theory to understand its limitations.

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.

Commentators have claimed that business schools encourage unethical behavior by using economic theory as a basis for education. We examine claims that exposure to agency theory acts as a self-fulfilling prophecy, reducing ethical behavior among business students. We experimentally test whether economics coursework or a manipulated competitive vs. cooperative frame affects measured ethical behavior in simulated decision settings. We measure ethical behavior using established tasks. We also measure ethical recognition to test whether agency theory reduces recognition of ethical issues. Exposure to agency theory in either prior classwork or the experiment increased wealth-increasing unethical behavior. We found no effect on unethical behavior that does not affect wealth. We found no effect of exposure to agency theory on ethical recognition. Usual laboratory experiment limitations apply. Future research can examine why agency theory reduces ethical behavior. Educators ought to consider unintended consequences of the language and assumptions of theories that underlie education. Students may assume descriptions of how people behave as prescriptions for how people ought to behave. This study contributes to the literature on economic education and ethics. We found no prior experimental studies of the effect of economics education on ethical behavior.

The purpose of the study is to assess manufacturing firm performance indicators using a reasonably comprehensive integrated BSC-Game model to empirically determine the importance of the perspectives and indicators under evaluation and the best combination of indicators.

After identification of manufacturing indicators of the firm, the Shapley value index is used as the solution of the cooperative game to determine the importance of the perspectives and indicators under evaluation and the best combination of indicators to facilitate the achievement of target goals.

The game theory approach is used as a technique to rank BSC perspectives of the firm's manufacturing performance. The results reveal that the customers' perspective receives the highest ranking. The knowledge sharing, new technology, customer satisfaction and sale profitability are considered as the best combination of BSC indicators.

The integrated BSC-Game framework, approach and outcomes can be beneficial to practitioners and researchers who aim to select the proper indicators’ policy in manufacturing performance field.

Culture is a central concept broadly studied in social anthropology and sociology. It has been gaining increasing attention in economics, appearing in research on labor market discrimination, identity, gender, and social preferences. Most experimental economics research on culture studies cross-national or cross-ethnic differences in economic behavior. In contrast, we explain laboratory behavior using two cultural dimensions adopted from a prominent general cultural framework in contemporary social anthropology: group commitment and grid control. Groupness measures the extent to which individual identity is incorporated into group or collective identity; gridness measures the extent to which social and political prescriptions intrinsically influence individual behavior. Grid-group characteristics are measured for each individual using selected items from the World Values Survey. We hypothesize that these attributes allow us to systematically predict behavior in a way that discriminates among multiple forms of social preferences using a simple, parsimonious deductive model. The theoretical predictions are further tested in the economics laboratory by applying them to the dictator, ultimatum, and trust games. We find that these predictions are confirmed overall for most experimental games, although the strength of empirical support varies across games. We conclude that grid-group cultural theory is a viable predictor of people’s economic behavior, then discuss potential limitations of the current approach and ways to improve it.

One important assumption in the conventional cooperative game theory is that payoffs are assumed to be deterministic. In terms of the players’ cognitive ability of the realistic world, this is a very strict assumption. The classical game theory can find no way out when a particular game circumstance involves uncertainty, such as limited knowledge, small sample, and inadequate information, the payoff values of the game can only be described with interval grey numbers. The paper aims to discuss these issues.

In this study the concept of N-person grey games is proposed in which payoffs are represented with interval grey numbers opposed to the classical game theory. A straight forward solution methodology is submitted compatible to grey numbers. Then, a currency war between anonymous countries is handled and modeled as an N-Person grey game. A generic currency war scenario is developed to follow the proposed solution procedure thoroughly.

Based on the outcomes of this work, the authors can say that N-person grey game is an expansion of the classical N-person game under uncertain grey information and can be applied in more complex and uncertain environments, such as those seen in complicated currency warfare.

This study combines the grey system theory with the classic N-person game theory and sets up the N-person grey game with grey payoff functions. Based on the grey number operating methods, the grey linear programming algorithm is established to calculate and distribute benefits to the players. In this respect this study has the feature of being the pioneer in the N-person grey game area.

Kostova, Roth and Dacin called in 2008 for the advancement of a theoretical conception of the multinational corporation (MNC) that takes into account both power relationships among actors and the structure of its internal institutional field. While micro-political scholars of MNCs have started to answer the former part of the call regarding power, the second part has not been thoroughly addressed yet. Furthermore, the agentic aspects typical of power games and the structural aspects characterizing institutional fields have not been fully combined in a multi-level perspective of MNCs so far. Leaning on Bourdieu, we suggest an answer to the pending call. We theorize the MNC as a playing field of power emerging around the issue of finding a meta-rate of conversion of the actors’ capitals constituted in national fields. We conceive such issue field in a dynamic state due to the constant entry and exit of new players (e.g. through mergers, acquisitions or divestitures). This results in the need to continuously test the validity of exchange rates. The role of the metainstitutional field level of the MNC as a global category is also discussed.