Strategic Interaction Research Articles

Strategic interaction between IoT technology openness and adoption considering potential firm entry

Strategic interaction between IoT technology openness and adoption considering potential firm entry

Strategic investment in charging infrastructure: Sharing costs or taking over?

The substantial upfront investment required for the installation of charging infrastructure deters many potential charging station adopters, such as shopping mall operators and real estate owners, from independently undertaking the deployment. Some government agencies (Govs) offer subsidies as a means of encouraging the extensive implementation of charging infrastructure. Nonetheless, this approach is not viable in the long term owing to the constrained public budget. An improper subsidy scheme may induce adopters to become overly reliant on Govs support. To tackle this issue, some local Govs have initiated cost-sharing schemes with adopters who are willing to install chargers. In a typical cost-sharing scheme, the Gov initially assigns the cost-sharing rate to adopters. Subsequently, the adopters determine the quantity they are willing to install through cost-sharing. Despite the potential benefits of the scheme, there are still some challenges: (i) The public budget is limited, (ii) The charging infrastructure penetration goal is uncertain, (iii) Adopters are heterogeneous and their decisions are interdependent, and (iv) Adopters possess dissimilar beliefs regarding the policy of the Gov. These factors could potentially prompt certain adopters, who possess the financial capability to cover the installation expenses, to employ deceptive tactics aimed at persuading the government to assume the entire cost. In consideration of the aforementioned challenges, we propose a sequential-move game model to assess the strategic interactions between the Gov and charging station adopters. We demonstrate that there exists a many-to-one mapping between the optimal cost-sharing rates and the optimal number of installed chargers. Then, we derive the conditions when the Gov withdraws from the market and when it intervenes to share costs with adopters. The results suggest that a reduction in the level of competition intensity leads to an increased probability of adopters engaging in the cost-sharing scheme. This is in contrast to scenarios where policy uncertainty increases or where the correlative effects arise among all adopters’ strategies.

Electrophysiological correlates of why humans deviate from rational decision-making: A registered replication study.

In contrast to rational choice theory predicting humans to optimize expected utilities of choices, humans deviate from rational behavior in decision-making paradigms. Hewig etal. (2011) explored affective correlates of decision-making in the ultimatum game (UG) and the dictator game (DG). They found that feedback-related negativity (FRN), subjective valence ratings, and autonomic nervous system activity predicted rejection of monetary offers. This registered replication aimed to validate and extend these findings. Although behavioral patterns and results of subjective ratings closely matched the original study, not all psychophysiological effects were successfully replicated. Firstly, we could not replicate the reported effects of autonomic nervous system activity. Secondly, a quadratic instead of the originally proposed linear relation between the offer and the FRN emerged, possibly driven by the offer evaluation in economic games and the rewarding anticipation of successful punishment for low offers. Thirdly, P3 amplitudes mirrored the quadratic offer response pattern, generally peaking for the lowest offer. In contrast to the original study, P3 responses were larger in the UG compared with the DG. Finally, our findings indicate that participant-related higher midfrontal theta activation predicted lower acceptance behavior in the UG, with a systematic dampening effect for fairer offers. This highlights cognitive control as a crucial mechanism in economic decision-making to overcome behavioral defaults. Overall, our results conceptually support the original conclusion that decision-making in economic games is non-rational and dependent on the objective situation as well as emotional and neural markers, though not precisely as suggested by Hewig etal. (2011).

Which Measures of Beliefs About Others’ Prosociality Predict Prosocial Behavior in Economic Games?

Prosocial behavior often entails the possibility to be exploited by other people. Correspondingly, situations affording prosocial behavior are often characterized by one’s dependence on others’ unknown behavior. In such situations, actors will arguably assess the risk of being taken advantage of by others before making a decision. Thus, prosocial behavior might be shaped by how prosocial actors generally believe others to be (e.g., trustworthy vs. exploitative). However, a recent investigation found no consistent evidence that perceiver effects, which describe interindividual differences in judging others’ personality in first impressions and thus capture beliefs about others’ prosociality, predict prosocial behavior (Rau et al., 2020). We replicate and extend these findings by pursuing two approaches to examine the influence of beliefs about others’ prosociality on behavior in four behavioral games (public goods game, trust game as trustor and trustee, mind game), two of which involve dependence on others under uncertainty. In our main study (N = 962), perceiver effects failed to predict prosocial behavior. This was confirmed by a meta-analysis of all studies that investigated this relation, providing strong evidence against the predictive validity of perceiver effects for behavior in economic games. In a follow-up analysis, generalized expectations (as measured by generalized trust) predicted prosocial behavior in one of the two relevant games while controlling for honesty-humility, which we interpret as tentative evidence for the role of generalized expectations in prosocial behavior in economic games. We contemplate that the discrepancy between perceiver effects and generalized expectations as measures of beliefs about others’ prosociality might be attributable to their implicit vs. explicit nature and suggest future research to explore whether perceiver effects predict more implicit measures of prosocial behavior.

Quantitative evaluation of a theoretical-conceptual model based on affective and socio-behavioral dimensions to explain the academic performance of mathematics students.

There is evidence that suggests that affective dimensions, personality traits, as well as students' cooperative interpersonal interactions, are an important element in the students learning process. In this work we propose a theoretical model, based on evidence, that shows the direct and indirect relationships between these factors and academic performance in mathematics courses, in undergraduate and school students. To understand the type of relationships between these variables, the PANAS psychometric test of positive and negative affect, the BIG FIVE personality test and the economic decision game DUPLES GAME were applied. The study sample was 130 students between 17 and 22 years of age from undergraduate and school (M ± SD = 20.1 ± 3.99). From a path analysis, statistically significant relationships were found, for example, a direct relationship between neuroticism and positive affect, which in turn is related to academic performance. We also found a direct relationship between neuroticism and negative affect, extraversion and positive affect. This allows us to propose that some of the independent variables of the model directly and indirectly influence the academic performance of students in the subject of mathematics. Positive affect and negative affect directly affect academic performance in mathematics, neuroticism has a direct impact on negative affect and extraversion direct impact on positive affect. Consequently, there are direct and indirect relationships between personality traits and affective dimensions, which affect the academic performance of mathematics students.

Tripartite Evolutionary Game Analysis of Product Quality Supervision in Live-Streaming E-Commerce

With the rapid development of information technology, live-streaming e-commerce has risen rapidly as a new business model. However, product quality problems that exist in the development of live-streaming e-commerce continue to emerge. The influence of strategic interactions between social media influencers, live-streaming e-commerce platforms, and consumers on product quality deserves to be studied. Therefore, this paper constructs a tripartite game model of “social media influencers–the live-streaming e-commerce platform–consumers” and analyzes the dynamic evolution process of the strategy selection among subjects and influencing factors by using evolutionary game theory. This study shows that products with high functional value are more likely to stimulate consumer rights protection behavior, prompting social media influencers to shift from lax to strict quality control. But when the emotional value is high, consumers are more inclined to give up on defending their rights, which leads to the maintenance of lax quality control, and the platform supervision will be weakened accordingly. Moreover, less quality differences motivate social media influencers to choose lax quality control. An increase in quality differences will promote a shift from an equilibrium strategy to strict quality control. However, if the penalty of the platforms is not strong enough, this strategic shift will not happen. In addition, a high percentage of platform commissions can encourage influencers to implement strict quality control, while platforms can maintain weak supervision. This study’s findings provide valuable guidance for understanding and managing product quality issues in live-streaming e-commerce. In the future, the government will be considered a new player in the game in studying the impact of its policies on product quality in live-streaming e-commerce.

Financing and operational strategies for supply chains with yield uncertainty and capital constraints

Facing yield uncertainty is a common phenomenon that corporations encounter in their production and operations processes, especially small and medium-sized enterprises (SMEs). It is a challenge for SMEs that also have capital constraints, and thus financing from supply chain members or commercial banks is the normal way to improve the efficiency of supply chain operations. We consider a supply chain finance system consisting of an SME, a core enterprise (CE), and a bank, in which the SME is capital-constrained and faces productivity yield uncertainty. Therefore, the SME may use two financing sources to support his production: financing or advance payment from the CE. In the presence of bankruptcy risks for the SME, we model their strategic interaction as a Stackelberg game with the CE as the leader. We design the framework for the order penalty contract and derive the optimal strategies that include the planned production quantity decision of the SME and the pricing decisions of the CE under the two financing sources. We find that from the SME’s perspective, he will always prefer advance payments from the CE to bank financing. Furthermore, we propose a framework for partial credit guarantees. When it is difficult for banks to evaluate the credit history of SMEs, CEs provide guarantees to banks for financing SMEs. The analytical methods and numerical results provide decision-making methods and suggestions for production planning of the SME and wholesale prices formulated by CE.

The central bank, the treasury, or the market: Which one determines the price level?

This paper studies a model in which the price level is the outcome of dynamic strategic interactions between fiscal and monetary authorities that pursue distinct objectives. The “unpleasant monetarist arithmetic”, whereby aggressive fiscal expansion forces the monetary authority to chicken out and to lose control of inflation, occurs only if the public sector lacks fiscal space, in the sense that public debt along the optimal fiscal path gets sufficiently close to the threshold above which the fiscal authority would find default optimal. Otherwise, monetary dominance prevails even though the central bank has neither commitment power nor fiscal backing.

Activists’ Strategic Interactions, Collaborative Tactics, and Local Environmental Performance

Activists’ Strategic Interactions, Collaborative Tactics, and Local Environmental Performance

Do fairness concerns matter for ESG decision-making? Strategic interactions in digital twin-enabled sustainable semiconductor supply chain

Spatial-temporal visibility and traceability in the digital twin enable semiconductor supply chain great transparency and efficacy, but also poses challenges to information disclosure. There is growing evidence that investment in digital twin technology is becoming crucial for improving environmental, social, and governance (ESG) ratings and mitigating risks within a sustainable semiconductor supply chain. Nonetheless, how fairness concerns impact the decision-making processes among different stakeholders remains inadequately understood. This paper presents an analytical analysis of the dynamic strategic interplay among semiconductor manufacturers, consumers, and government regulatory agencies (GRAs) utilizing the evolutionary game model. The aim is to investigate how long-term ESG strategies and fairness-oriented behaviors respond to government incentives. The findings imply that substantial investment demands can dissuade semiconductor manufacturers from delivering ESG services, while low tax rates may lead to their complacency and a subsequent lack of investment in ESG initiatives. Meanwhile, semiconductor manufacturers are more inclined to provide ESG services when the order loss ratio is low, and the tax rate is high, with strict regulations further amplifying this probability. Furthermore, consumers valuing fairness and equity tend to give positive feedback for basic services but is critical of ESG services due to issues with transparency in digital twin technologies. Addressing these issues extends beyond the scope of market incentives alone, requiring interventions from third parties such as government regulations, policy incentives, and enhanced data security measures.

A two-sided equilibrium model of Vehicle-to-Vehicle charging platform

A novel mobile charging service utilizing vehicle-to-vehicle (V2V) charging technology has been proposed as a complement to fixed charging infrastructure (CI), enabling electric vehicles (EVs) to exchange electricity. This study develops a two-sided equilibrium model for a V2V charging platform, where the demand-side charging vehicles (CVs) choose between charging piles and the V2V platform, and the supple-side discharging vehicles (DVs) decide whether to provide discharging services. The V2V platform matches CVs with DVs, receiving compensation from CV owners and reimbursing DV owners. To explore the strategic interactions between the V2V platform and fixed CI operators, we construct an analytical bi-level model that examines different operation regimes, including competitive and cooperative scenarios, i.e., non-cooperative game and Nash Bargaining game. The lower-level model is a two-sided equilibrium model that quantifies charging and discharging choices of EV owners, while the upper-level model optimizes the pricing decisions of the V2V platform and fixed CI operator. Numerical results indicate that the introduction of the V2V platform can reduce the overall charging costs, thus encourage the use of public charging services. Furthermore, it is suggested that the V2V platform be managed by independent enterprises, rather than existing fixed CI operators, to promote the EVs at relatively low charging costs.

Public debt stabilization via a stochastic differential game paradigm

In this paper, we examine a public debt stabilization in a country under inflation targeting by arguing that bond yields are sensitive to inflation risks. Endogenously defining the convenience premium function, we focus on fiscal and monetary strategic interactions within an optimal control setting. The level of the debt-to-gross domestic produced (GDP) ratio and current inflation rate of the country are considered as the state variables in the game. We then focus on the convenience risk premium and rate of inflation as market-based disciplining devices, to articulate the Nash noncooperative equilibria, cooperative equilibria and Stackelberg equilibria via a feedback control strategy. We show that the outcome of the game depends on the parameters of the game, the type of equilibrium one considers and the decision horizon. When the current inflation rate follows an uncontrolled Ornstein–Uhlenbeck dynamic process, we highlight its effects on the growth rate of the debt ratio. Hence, our model provides a novel framework in which monetary and fiscal authorities can simultaneously achieve their individual interests, while achieving an optimal debt stabilization policy in the presence of inflation. We also highlight the need for governments to adopt policy-approaches which maintain the debt-to-GDP ratio under an inflation-dependent ceiling.

GAME THEORY AND STRATEGIC DECISION-MAKING: OPTIMIZING BUSINESS STRATEGIES IN THE AGE OF DIGITAL DISRUPTION

The arising digital disruption poses new challenges and opportunities for businesses that, in turn, require new strategic decisions. Game theory, in this respect, offers a very useful mathematical framework for the analysis of strategic interactions and hence valuable insights into the optimal design of business strategies within the changing environment. Accordingly, the paper tries to elaborate on possibilities to apply game theory to strategic decision-making in the digital age concerning competitive strategies, market dynamics, and collaborative opportunities. At the juncture of game theory and digital disruption, it would be the framework through which businesses can improve strategic approaches in competitive moves within the complexities of the modern market landscape.

Ecosystem Approaches in International Business Non-Equity Collaborations and Partnerships in Evolving Global Cities

This qualitative literature review explores ecosystem approaches in international business, focusing on non-equity collaborations and partnerships within evolving global cities. Global cities serve as critical nodes for multinational enterprises (MNEs), facilitating strategic interactions and innovation through diverse collaborations with local firms and stakeholders. The review synthesizes current research to highlight how such collaborations enhance MNEs' competitive advantage by leveraging local knowledge, resources, and market access. Key findings illustrate the role of global city ecosystems in fostering innovation, operational efficiency, and sustainable development for MNEs. However, challenges such as regulatory complexities and institutional misalignments constrain effective collaboration, necessitating adaptive governance and strategic alignment among stakeholders. Future research directions include integrating quantitative analyses to complement qualitative insights, exploring diverse geographic and sectoral contexts, and advancing digital and sustainable strategies within global city ecosystems.

Social norms, political polarization, and vaccination attitudes: Evidence from a survey experiment in Turkey

This paper examines vaccination as a descriptive social norm in the context of the Covid-19 pandemic. Using a large-scale survey experiment in Turkey, we first elicit respondents’ vaccination attitudes and show that political affiliation is a strong predictor of it. We then use economic games to measure the extent of outgroup discrimination induced by respondents’ attitudes towards vaccination. We find that while both pro- and anti-vaxxers discriminate against each other substantially, the pro-vaxxers discriminate more than the anti-vaxxers do. This polarization intensifies when pro- and anti-vaxxers perceive a political difference between them. Using randomized informational treatments, we show that a reminder or priming of external threats, appealing to a broadly shared social identity, might mitigate such outgroup discrimination.

Antisocial Personality Disorder as a Form of Adaptive Strategy

Background: in contemporary domestic psychiatry the evolutionary explanations of antisocial personality disorder are practically lacking. The aim of study: the analysis of the significant concepts of the evolutionary approach to understanding the origins and typology of antisocial, or dissocial, personality disorder. Material and methods: a narrative review of contemporary English-language psychiatric and psychological literature using all available search engines using the keywords “antisocial psychopathy” and “evolutionary psychiatry and psychology”. Discussion and conclusion: in English-language psychiatric and psychological literature the affective component of antisocial traits, emphasized only in ICD-10, is called “primary psychopathy,” while the behavioral component of antisocial traits, associated with “sensation seeking” and “hyperactivation,” is called “secondary” psychopathy. Evolutionary and ecological approaches emphasize the adaptive role of aggressive and antisocial behavior, viewing such behavior as a “high-risk strategy” in social and sexual competition, as “costly” but potentially adaptive (rather than as “behavioral dysfunctions”). The understanding of persistent antisocial behavior as a social “trickster” strategy exploiting the trust and cooperative behavior of others is based on the R. Axelrod-W. Hamilton “iterated” prisoner’s dilemma. In the Prisoner’s Dilemma evolutionary model, the player’s payoff is determined by the effects on “fitness”: survival and fertility. Participating in several interactions with individuals, an antisocial “deceiver” with high mobility is able to exist, manifesting itself with a fairly low frequency in the population. Non-cooperative behavior in both animals and humans reduces the fitness of others and includes aggressive behavior, deception, betrayal, predation and social parasitism. From the point of view of the concept of “economic games,” people with subclinically expressed primary psychopathic traits (emotional coldness, manipulativeness, Machiavellianism) are represented as “strategists” with cooperation partners: they give with reciprocity to those partners whom they consider “highly valuable” (with the potential for great benefits in future), and only “take”, manipulating and deceiving, from those of “low value”. In a broad sense, evolutionary psychologists and psychiatrists find in the characteristics of antisocial individuals a predominance of a set of properties of “fast” life strategies, while the concept of “fast strategies” is also used to explain geographical differences in the prevalence of aggressive behavior.

The Impacts of Centralized Control on Mixed Traffic Network Performance: A Strategic Games Analysis

Cooperative Intelligent Transport Systems (C-ITS) address contemporary transportation challenges, as Connected Vehicles (CVs) can play a pivotal role in enhancing efficiency and safety. The role of central governing authorities in shaping traffic management policies for CVs influences decision-making processes and system performance. In this work, the role of central governing authorities in the traffic management of a mixed traffic network is examined, integrating System Optimum principles with game theory. More specifically, we introduce and develop a framework that models and analyses the strategic interactions between different stakeholders in a mixed traffic environment, considering central governing authorities with varying levels of control. The results indicate how the various levels of control of a central governing authority may have an impact on the network in terms of traffic measures. Through a strategic games analysis, the trade-offs associated with centralized control mechanisms are demonstrated and recommendations are offered for policymakers and practitioners to optimize traffic management strategies.

An Attacker-Defender Game Model with Constrained Strategies.

Recently, research interest in the field of infrastructure attack and defense scenarios has increased. Numerous methods have been proposed for studying strategy interactions that combine complex network theory and game theory. However, the unavoidable effect of constrained strategies in complex situations has not been considered in previous studies. This study introduces a novel approach to analyzing these interactions by including the effects of constrained strategies, a factor often neglected in traditional analyses. First, we introduce the rule of constraints on strategies, which depends on the average distance between selected nodes. As the average distance increases, the probability of choosing the corresponding strategy decreases. Second, we establish an attacker-defender game model with constrained strategies based on the above rule and using information theory to evaluate the uncertainty of these strategies. Finally, we present a method for solving this problem and conduct experiments based on a target network. The results highlight the unique characteristics of the Nash equilibrium when setting constraints, as these constraints influence decision makers' Nash equilibria. When considering the constrained strategies, both the attacker and the defender tend to select strategies with lower average distances. The effect of the constraints on their strategies becomes less apparent as the number of attackable or defendable nodes increases. This research advances the field by introducing a novel framework for examining strategic interactions in infrastructure defense and attack scenarios. By incorporating strategy constraints, our work offers a new perspective on the critical area of infrastructure security.

Industrialization, environmental externality, and climate mitigation strategies

This study proposes a 12-region global modeling framework that integrates industrialization into climate–economy interactions and applies it to explore national strategic interactions and long-term policy outcomes. In this regard, three policy regimes are considered: a non-cooperative Nash equilibrium and two cooperative regimes that maximize the weighted sum of regional welfare. Negishi weights, ensuring uniform carbon price, and equal weights are applied in cooperative setting. Based on the results, global unmitigated emissions will peak around 2040. Given the future industrialization process, developing countries will make greater mitigation efforts under all regimes, whereas the strategies of developed countries will only be affected under the uniform carbon price regime. In the two cooperative regimes, a clear separation of mitigation efforts is observed between developed and developing countries. Moreover, when accounting for industrialization, the global averaged carbon price should grow faster in the first half-century, followed by a period of slower growth. Sensitivity analysis implies that with the support from developed countries, accelerated industrialization in the developing world can help alleviate its environmental strain.

Maneuver Planning for Multiple Pursuit Intelligent Surface Vehicles in a Sequence of Zero-Sum Pursuit–Evasion Games

Unmanned surface pursuit is a complex and challenging engineering problem, especially when conducted by multiple intelligent surface vehicles (ISVs). To enhance the pursuit performance and facilitate strategic interaction during the target pursuit, this paper proposes a novel game theory-based maneuver planning method for pursuit ISVs. Firstly, a specific two-player zero-sum pursuit–evasion game (ZSPEG)-based target-pursuit model is formed. To ensure the vehicles reach a quick consensus, a target-guided relay-pursuit mechanism and the corresponding pursuit payoffs are designed. Meanwhile, under the fictitious play framework, the behavioral pattern and the strategies of the target could be fictitiously learned. Furthermore, mixed-strategy Nash equilibrium (MNE) is employed to determine the motions for the vehicles, the value of which is the best response in the proposed ZSPEG model. Finally, simulations verify the effectiveness of the above methods in multi-ISV surface pursuit.