Strategic Interaction Research Articles

Intranasal oxytocin interacts with testosterone reactivity to modulate parochial altruism

The neuropeptide hormone oxytocin and the steroid hormone testosterone have received attention as modulators of behavior in the context of intergroup conflict. However, to date, their interactive effect has yet to be tested. Here, in a double-blind placebo-control design, 204 participants (102 female participants) self-administrated oxytocin or placebo and completed an experimental economic game modeling intergroup conflict. Salivary testosterone (n = 192) was measured throughout the task to assess endogenous reactivity. As a caveat, even at this sample size, our derived power to detect small effects for 2- and 3-way interactions was relatively low. For male participants, changes in testosterone predicted willingness to sacrifice investments for the betterment of the group. Intranasal administration of oxytocin strongly diminished this effect. In female participants, we found no credible evidence for association between changes in testosterone and investments, rather, oxytocin effects were independent of testosterone. This 3-way interaction was of medium to large effect size (Odds Ratio 5.11). Behavior was also affected by social cues such as signaling of ingroup and outgroup members. Our findings provide insights as to the biological processes underpinning parochial altruism and suggest an additional path for the dual influence of oxytocin and testosterone on human social behavior.

Firm Formalization Strategy: The Interaction of Entrepreneurs and Government Officials in the Enforcement of Regulation

This research investigates how entrepreneurs in an early-stage market economy decide their level of compliance with formal rules and finds the manner in which they interact with government officials to operate on a continuum of formality. Focusing on the nonmarket strategy approaches entrepreneurs employ to establish relationships with government officials, we build a model that shows how entrepreneurs adopt strategies aligned with their firm’s level of formality, spanning low to high formality practices. We draw on qualitative interview data from entrepreneurs who exhibit varying levels of compliance with state-provided rules and guidelines. We inductively theorize that deciding the firms’ level of formality involves strategic interaction approaches with government officials responsible for rule enforcement. Our findings highlight that the interaction strategies entrepreneurs use hinge on the political capital they possess, eliciting the desired response from government officials, and dissuading the officials from enforcing formal rules or imposing sanctions for informality. We offer theoretical and policy implications for future work on the nuances of firm formality and the interaction between entrepreneurs and government officials.

Pacem in Terris: Are Papal Visits Good News for Human Rights?

We analyze the effect of state visits by the Catholic pope on human rights in the host country to understand how a small theocracy like the Vatican can exert disproportionate political influence in international politics. Our theory of the strategic interaction between the Catholic Church and host governments describes how the pope’s use of conditional approval and criticism incentivizes governments to refrain from human rights violations. Drawing on a new dataset of papal state visits outside Italy and a novel identification strategy, we test for the first time whether governments react in anticipation of a papal visit by improving their human rights protection. Our empirical analysis offers robust evidence for this causal effect, which is supported by qualitative evidence.

Platform business models and strategic price interaction

Business platforms delivering Mobility-as-a-Service (MaaS), alongside providing additional user services, have been shown to bring important price strategic interaction impacts which can be welfare improving. We show that the Integrator platform, whose structure alleviates harmful price externalities with two operators, such that it everywhere welfare dominates the Free-Market, can also limit beneficial competitive forces with more operators, reversing this welfare ordering. This is important since MaaS envisages platforms bringing together multiple operators and services in practice. However, calibrations show that where the Integrator platform fails to outperform the Free-Market (with higher operator numbers and lower substitutability), a new platform-based model that we introduce, is optimal. Furthermore, the Integrator is promoted in welfare terms in the presence of non-trivial marginal costs and mid- to high-end market demand elasticities, conditions both consistent with the inclusion in the MaaS journey mix of taxi cabs and other on-demand services which are common-place in MaaS offerings. We also introduce a number of extensions to the modelling framework incorporating additional real network characteristics. Though this can result in the welfare supremacy of the Integrator relative to the Free-Market being undermined, it again tends to be restored under mid- to high-range market elasticity calibrations. Finally, profit incentives tend to neither align across platform providers and operators, nor promote the welfare-best regime, indicating potential for regulatory oversight.

Recovering farming supply chains from animal epidemics via government subsidies

In recent years, animal epidemics – such as African swine fever and bird flu – break out more frequently in both developed and developing economies, causing serious economic losses and animal product shortages. To restore animal product supply, many governments offer two agricultural subsidies to farms: (i) the culling compensating subsidy (CCS), which guarantees a floor price for culled animals, and (ii) the scaled construction subsidy (SCS), which supports large-scale farms to enhance their production capacities. We develop a three-stage Stackelberg game framework to capture the strategic interactions among the government, large- and small-scale farms. In particular, the two types of farms differ in their epidemic prevention and control capabilities and must operate under yield uncertainty. We study two cases regarding whether the government requires a minimum BS for the SCS. In each case, we analyze the equilibrium decisions of the profit-seeking farms and characterize the structure of the government’s optimal subsidy programs with an earmarked budget to maximize social welfare. Moreover, we identify the conditions under which the government should adopt the “SCS only strategy”, “CCS only strategy”, or offer the two subsidies simultaneously. Furthermore, we examine the effectiveness of the subsidy programs in terms of consumer surplus, farms payoffs, and social welfare. We show that in both cases, these programs can make the three stakeholders achieve a win–win–win situation by prioritizing a reasonable CCS according to the subsidy budget. We leverage our analyses to offer insights that can help generate policy recommendations for stakeholders in countries suffering from animal epidemics.

Language-based game theory in the age of artificial intelligence.

Understanding human behaviour in decision problems and strategic interactions has wide-ranging applications in economics, psychology and artificial intelligence. Game theory offers a robust foundation for this understanding, based on the idea that individuals aim to maximize a utility function. However, the exact factors influencing strategy choices remain elusive. While traditional models try to explain human behaviour as a function of the outcomes of available actions, recent experimental research reveals that linguistic content significantly impacts decision-making, thus prompting a paradigm shift from outcome-based to language-based utility functions. This shift is more urgent than ever, given the advancement of generative AI, which has the potential to support humans in making critical decisions through language-based interactions. We propose sentiment analysis as a fundamental tool for this shift and take an initial step by analysing 61 experimental instructions from the dictator game, an economic game capturing the balance between self-interest and the interest of others, which is at the core of many social interactions. Our meta-analysis shows that sentiment analysis can explain human behaviour beyond economic outcomes. We discuss future research directions. We hope this work sets the stage for a novel game-theoretical approach that emphasizes the importance of language in human decisions.

Cooperation among unequal players with aspiration-driven learning.

Direct reciprocity promotes the evolution of cooperation when players are sufficiently equal, such that they have similar influence on each other. In the light of ubiquitous inequality, this raises the question of how reciprocity evolves among unequal players. Existing studies on inequality mainly focus on payoff-driven learning rules, which rely on the knowledge of others' strategies. However, inferring one's strategy is a difficult task even if the whole interaction history is known. Here, we consider aspiration-driven learning rules, where players seek strategies that satisfy their aspirations based on their own information. Under aspiration-driven learning rules, we explore the evolutionary dynamics among players with inequality in endowments and productivity. We model the interactions among unequal players with asymmetric games and characterize the condition where cooperation is feasible. Remarkably, we find that aspiration-driven learning rules lead to a higher level of cooperation than payoff-driven ones over a wide range of inequality. Moreover, our results show that high aspiration levels are conducive to the evolution of cooperation when more productive players are equipped with higher endowments. Our work highlights the advantages of aspiration-driven learning for promoting cooperation among unequal players and suggests that aspiration-based decision-making may be more beneficial for the collective.

Modulating the activity of right temporoparietal junction increased belief-based learning in an economic game.

Modulating the activity of right temporoparietal junction increased belief-based learning in an economic game.

Replicator-mutator dynamics of the rock-paper-scissors game: Learning through mistakes.

We generalize the Bush-Mosteller learning, the Roth-Erev learning, and the social learning to include mistakes, such that the nonlinear replicator-mutator equationwith either additive or multiplicative mutation is generated in an asymptotic limit. Subsequently, we exhaustively investigate the ubiquitous rock-paper-scissors game for some analytically tractable motifs of mutation pattern for which the replicator-mutator flow is seen to exhibit rich dynamics that include limit cycles and chaotic orbits. The main result of this paper is that in both symmetric and asymmetric game interactions, mistakes can sometimes help the players learn; in fact, mistakes can even control chaos to lead to rational Nash-equilibrium outcomes. Furthermore, we report a hitherto-unknown Hamiltonian structure of the replicator-mutator equation.

Nash equilibria for relative investors with (non)linear price impact

We consider the strategic interaction of n investors who are able to influence a stock price process and at the same time measure their utilities relative to the other investors. Our main aim is to find Nash equilibrium investment strategies in this setting in a financial market driven by a Brownian motion and investigate the influence the price impact has on the equilibrium. We consider both CRRA and CARA utility functions. Our findings show that the problem is well-posed as long as the price impact is at most linear. Moreover, numerical results reveal that the investors behave very aggressively when the price impact is close to a critical parameter.

Public Health in Private

ABSTRACT Elite women seized the public health campaign during the 1900 plague outbreak to assert political influence and advocate for sanitation reform grounded in their domestic experiences. These women advocated for their inclusion in the political sphere by valuing their domestic experiences as knowledge relevant for public health initiatives. This reframing of experience positioned them as viable citizens in the imminent Federation. Applying Laura Zanotti's concept of relational ontology, this analysis frames their actions as not simply a battle against institutional authority but as careful and strategic interactions with their era's political context, exploiting aspects of it that were beneficial to them. Their ambivalent involvement in the public health campaign illustrates a complex chapter in Australian medical history. Women used the opportunity of plague to reevaluate their experience of the home as a form of knowledge relevant to public health. At the same time, they leveraged their growing status as political subjects to oppress others.

Last Time Buys during Product Rollovers: Manufacturer & Supplier Equilibria

Durable goods customers expect long-term availability of spare parts to maintain their product. This puts a strain on supply chains. Part suppliers want to obsolete older generations of parts with declining demand and reassign resources to new, growing generations. Meanwhile, durable goods manufacturers that purchase and sell spare parts to customers want suppliers to keep producing old parts. When suppliers offer a “last time buy” opportunity for legacy parts in anticipation of their retirement, manufacturers push back. We study the strategic interaction and equilibria of a supplier and a manufacturer during the rollover between a legacy part and its successor in a durable good supply chain. Evidence from our interviews shows that manufacturers attempt to use the future business of the new part to delay a supplier’s last time buy of the old part. However, this tactic is often ineffective in practice. We propose a two-stage noncooperative game that reproduces the behaviors observed in interviews. Our analysis of this game distills the conditions under which a manufacturer can leverage the future business to delay a last time buy. There exist only six strategies that achieve this delay. We present a necessary and sufficient condition for these six strategies to be subgame perfect Nash equilibria. The condition reduces to a closed-form threshold on the new part volume. We conclude with practical insights that can guide managers during a rollover discussion.

Third‐party logistics firm's technology investment and financing options in platform‐based supply chain with 4PL service

AbstractIn practice, capital‐constrained third‐party logistics (3PL) firms usually obtain bank financing (BF) to invest in logistics technology to enhance the consumer shopping experience. The emergence of financial innovation has prompted the adoption of alternative financing modes by 3PLs, including e‐commerce platform financing (EPF) and fourth‐party logistics financing (4PF). To clarify the differences among the three financing modes at the operational management level, we develop a Stackelberg game model to capture the strategic interactions between the 3PL and creditors. We examine a platform‐based supply chain where a manufacturer sells products through an e‐commerce platform to consumers, with the logistics services for the supply chain provided by the 3PL and fourth‐party logistics (4PL) firms. The analysis results reveal that the equilibrium interest rates under EPF and 4PF share a similar pattern regarding the logistics service cost coefficient, the commission rate, and the 4PL service fee. The difference is that under EPF (4PF), the logistics service level increases in the commission rate (4PL service fee) but decreases under the other financing strategy. Furthermore, the 3PL is inclined to invest in logistics technology only when the fixed investment cost is low, and these financing modes are complementary rather than alternative. The 3PL and manufacturer can benefit from 4PF (BF) when the logistics service cost coefficient is large and the market size is small (large); otherwise, EPF can enhance their profits. We also find that when the opportunity costs of capital are homogeneous, both the 4PL and the platform are consistently willing to act as financiers themselves. However, when considering heterogeneity in the opportunity costs of capital, they may be reluctant to provide financing. Each financing mode may achieve Pareto improvements under specific conditions. Finally, we also analyze the impact of technology R&D risks and endogenous 4PL service fee, yielding some valuable insights.

Evaluating SoJump.com as a tool for online behavioral research in China

SoJump.com (wjx.cn; in short: SoJump) is a survey company that allows researchers to build and deploy inexpensive online surveys in China. Here we evaluate SoJump’s data quality and similarity to the national benchmark. In the first study, we compare SoJump’s performance in China to MTurk’s performance against national benchmarks in the United States and India. In the second study, we compare three Chinese platforms in two-wave panel studies. We conducted the panels on SoJump, Credamo (SoJump’s major competitor), and Cint (national benchmark). We included attention and comprehension checks, economic games, cognitive tasks, and a framing experiment. We find that SoJump’s sample is younger, better educated, more urban, higher-income, and more female than Cint, similar to MTurk in the U.S. and India. Compared to Credamo, SoJump is more similar to Cint both for data quality and behavior. We conclude that SoJump is appropriate to inexpensively access nationally diverse samples in China.

Building a reputation for trustworthiness: Experimental evidence on the role of the feedback rate

In 25 years, research on reputation-based online markets has produced robust evidence on the existence of the so-called reputation effect, that is the positive relation between online traders’ reputations and these traders’ market success in terms of sales and prices. However, there is an ongoing debate on what the size of the reputation effect means. We argue that the rate of truthful feedback that traders leave after completed transactions is negatively related to the size of the reputation effect. The higher the rate of truthful feedback, the quicker will untrustworthy traders be screened and disincentivized to enter the market. With mostly trustworthy traders entering the market, buyers will demand smaller price discounts from market entrants without a good reputation. We test this mechanism empirically in two laboratory experiments. In both experiments, we systematically vary the probability with which information about sellers’ behavior in an economic trust game is recorded and shown to future interaction partners of these sellers. In the second experiment, we introduce competition among sellers by allowing buyers to choose one of two sellers in each interaction. We find that sellers give discounts to buyers to build or repair their reputation and that sellers who give discounts or have a good reputation are trusted more. However, we do not find support for our hypothesis that a higher feedback rate significantly decreases sellers’ propensity to give discounts. We argue and show in exploratory analyses that this is likely due to the high level of unconditional trust buyers exhibit towards sellers without a reputation. Yet, seller competition increases the propensity to offer discounts among sellers without a reputation the most.

The effects of awe on interpersonal forgiveness: the mediating role of small-self.

Awe could increase prosocial behavior, but little is known about its effects on interpersonal forgiveness. This study aims to explore the potential impact of awe on interpersonal forgiveness and the underlying mechanism of this process, using a combination of questionnaires, economic game and computational modeling. In Study 1, we utilized Trait Awe Scale (TAS) and Forgiveness Trait Scale (FTS) to examine the association between trait awe and trait forgiveness. In Study 2, we employed pre-screened video to induce awe, happy and neutral emotions, then evaluated the effects of induced awe on small-self and interpersonal forgiveness in hypothetical interpersonal offensive situations (Study 2a) and two economic interaction situations (Study 2b). Results from Study 1 indicate that there is a positive correlation between trait awe and trait forgiveness. Study 2 reveal that awe can enhance interpersonal forgiveness in both interpersonal conflict situations and economic interaction situations, and this effect is mediated by the sense of small-self elicited by awe. Overall, these findings contribute to our understanding of the potential impact of awe on interpersonal forgiveness and provide valuable insights into the mechanisms through which awe may influence forgiveness. Further research in this area could help to elucidate the potential applications of awe-based interventions in promoting forgiveness and positive social interactions.

Is there a nexus between pro-social behavior and well-being? Correlational evidence

AbstractIs there a connection between pro-social behavior and well-being? This question has long been of interest, with Aristotle famously suggesting a nexus between virtues and well-being. To delve into this relationship, I conducted an extensive study encompassing multiple classical economic games and nearly 100 well-being questions. My findings confirm that different patterns of pro-sociality are robustly correlated with each other. On top, I find reliable correlations between well-being and pro-social behavior, as well as certain forms of punishment. In terms of underlying explanations, I observe that pro-sociality is particularly associated with a form of long-term well-being known as eudaimonia, suggesting that pro-social behavior plays a fundamental role in people perceiving their life as meaningful.

Sino-Russian cooperation under US and European sanctions: Chinese car brands flood into the Russian market

This article uses a realist theoretical framework to thoroughly investigate the motives, processes, and multifaceted impacts of Chinese automobile brands entering the Russian market. The research findings reveal that the transnational market strategy of Chinese brands is based not only on the pursuit of national interests and economic independence but also on a flexible response to changes in the international political and economic structure. Amid the economic sanctions imposed by Western countries on Russia, a power vacuum has emerged in the Russian automotive market. Chinese automobile brands accurately identified and swiftly seized this opportunity, successfully entering and expanding their market share in Russia. This move has not only increased China’s influence in the global automotive industry but also further strengthened the strategic partnership between China and Russia. From a geopolitical perspective, this economic activity has also bolstered political and economic cooperation between China and Russia to resist the pressure from Western governments. This study enriches the application of realism theory in the field of international political economy and provides new perspectives and insights into understanding the motives and strategic choices of national behavior in a complex and changing international environment. By examining the case of Chinese automobile brands in Russia, this research contributes to the broader discourse on the strategic interactions between major global powers and their implications for the international political and economic order. The analysis highlights the importance of adaptive market strategies in achieving national objectives and underscores the interplay between economic strategies and geopolitical dynamics. The insights from this study are valuable for policymakers, scholars, and practitioners interested in international trade, political economy, and strategic studies, offering lessons for navigating the complexities of global market dynamics and international relations.

Complex pathways to cooperation emergent from asymmetry in heterogeneous populations.

Cooperation within asymmetric populations has garnered significant attention in evolutionary games. This paper explores cooperation evolution in populations with weak and strong players, using a game model where players choose between cooperation and defection. Asymmetry stems from different benefits for strong and weak cooperators, with their benefit ratio indicating the degree of asymmetry. Varied rankings of parameters including the asymmetry degree, cooperation costs, and benefits brought by weak players give rise to scenarios including the prisoner's dilemma (PDG) for both player types, the snowdrift game (SDG), and mixed PDG-SDG interactions. Our results indicate that in an infinite well-mixed population, defection remains the dominant strategy when strong players engage in the prisoner's dilemma game. However, if strong players play snowdrift games, global cooperation increases with the proportion of strong players. In this scenario, strong cooperators can prevail over strong defectors when the proportion of strong players is low, but the prevalence of cooperation among strong players decreases as their proportion increases. In contrast, within a square lattice, the optimum global cooperation emerges at intermediate proportions of strong players with moderate degrees of asymmetry. Additionally, weak players protect cooperative clusters from exploitation by strong defectors. This study highlights the complex dynamics of cooperation in asymmetric interactions, contributing to the theory of cooperation in asymmetric games.

Optimizing passenger vehicle travel time with Model Predictive Control in multi-region traffic networks

Abstract This study investigates the impact of truck traffic on passenger vehicles in an urban network. Utilizing the Macroscopic Fundamental Diagram (MFD), a methodology to calculate the travel time spent (TTS) by passenger vehicles has been developed. To address this issue, an optimal control problem was formulated and solved using a Model Predictive Control (MPC) approach. The MPC framework has been applied in a centralized manner, to manage accumulation for various modes. To explore different traffic management strategies, the centralized MPC technique was implemented in two distinct configurations: region-based and vehicle-based approaches. It has been tested for various vehicle mixes and multiple control scenarios to assess the effectiveness in reducing passenger travel time spent (PTTS) and vehicle accumulation. The results demonstrate that the vehicle-based MPC approach tends to minimize the number of vehicles more effectively compared to the region-based approach. However, in terms of reducing passenger travel time, the region-based approach outperforms the vehicle-based strategy. This is attributed to enhanced coordination among traffic flow controllers, highlighting the importance of strategic controller interactions in urban traffic management systems. This research enhances both the theoretical framework for optimizing traffic flow and provides valuable practical insights for city planners and engineers aiming to deploy advanced traffic management strategies. Future studies could explore the scalability of these control systems and their capability to integrate real-time traffic data.