Strategic Behavior Research Articles

Policies for Selecting the Advance Selling Mode in a Supply Chain Considering Network Externalities

ABSTRACTThe marketing strategy of advance selling new products through e‐commerce channels is becoming increasingly popular among merchants and users. In advance selling on e‐commerce platforms, network externalities and the probability of consumer satisfaction with products are important factors affecting consumers' strategic behavior. This study considers network externalities and the probability of consumer satisfaction with products in the advance selling decision‐making problem in the supply chain. Using game theory and prospect theory, three scenario models—advance selling considering network externalities, advance selling without considering network externalities, and nonadvance selling—are designed to construct theoretical models for supply chain decision‐making. The optimal decision‐making problem of supply chain members is discussed. Furthermore, through a comparison of pricing, demand and profits, the impacts of advance selling with or without considering network externalities on the decisions of retailers and manufacturers are analyzed. By comparing the differences in decision‐making between manufacturers and retailers, the feasible area for advance selling under network externalities is obtained. Furthermore, through numerical experiments, the impacts of the strength of network externalities, and the probability of consumer satisfaction with products on the decision‐making of supply chains are analyzed.

Alternative Pharmaceutical Innovation Models in Competitive Markets: A Collaborative Approach to Develop a Novel Drug for Hepatitis C.

Alternative innovation models have emerged to address failures of the traditional pharmaceutical system, particularly for diseases where market incentives do not attract sufficient research and development efforts. However, the feasibility of such models for diseases with significant markets is not well-established. This article analyses the development of a novel drug (ravidasvir) for the treatment of hepatitis C, a highly profitable market. Data from qualitative research methods, including literature reviews and semi-structured interviews, was analyzed using a novel conceptual framework focusing on actors, resources, organizational practices, and outcomes. Dissimilar to other projects, ravidasvir did not involve any major pharmaceutical companies. Rather, it leveraged the capacities of actors less traditionally involved in the development of novel medicines by constructing a collaborative network of private and public partners from low- and middle-income countries with a shared goal. The collaboration was successful in developing a highly effective, easy-to-use, and affordable medicine and contributed significantly to capacity-strengthening. However, the case also highlighted that strategic behavior by competing for-profit firms could pose significant challenges and that changing external conditions reduced the potential public health impact of the drug. Lessons from ravidasvir can inform future efforts to develop alternative innovation models for therapeutic areas with significant commercial interest.

Strategic behavior in multi-criteria sorting with trust relationships-based consensus mechanism: Application in supply chain risk management

Strategic behavior is common in multi-criteria sorting, where manipulated alternatives are allocated to the target category to achieve the intended goal. Engaging in such strategic behavior in sorting consensus often comes at a cost, which is closely tied to the degree of preference adjustments and the level of trust relationships among decision makers. This study investigates strategic behavior using piecewise cost-based consensus mechanism in social trust network. Firstly, the trust relationship dependent piecewise cost is formally defined and formulated by considering the impact of trust relationship on the preference adjustments willingness to achieve sorting consensus. Then, based on the trust relationship dependent piecewise cost, a preference strategic manipulation model is proposed to achieve strategic behavior in sorting consensus, which is implemented by minimizing the cost of strategically guiding decision makers in adjusting their preferences. Considering that social trust network affects strategic manipulation, a preference-network collaborative strategic manipulation model is further proposed, which is designed to strategically guide decision makers in adjusting both their preferences and social trust networks. Moreover, the practicality of proposed strategic manipulation models is exemplified through a case study on supply chain risk management and their performance is validated via simulation analysis.

Nature-inspired design principles promote supply network resilience

The dynamic, interconnected nature of modern supply chains makes it important to understand how firm-level decision-making will impact the robustness of supply chains to disruption. The behavior of naturally evolved distribution systems offers a useful starting point to identify potential design features that can promote robustness without compromising the viability of individual firms. Drawing inspiration from how ant food-sharing networks respond to supply shortages, we developed an agent-based model of a generalized supply network and evaluated how different local strategies influenced the ability of firms to acquire sufficient resources to meet their demand. Our simulations reveal that differences among firms in strategic behavior can reduce variation in outcomes across firms while maintaining mean performance, thereby buffering system-level robustness. In addition, the ability to expand one’s supplier network bolstered performance when firms experienced difficulty in meeting their demand. Conversely, under the assumptions of our model, overly relying on distributors to gain access to additional suppliers or to gain competitive advantages was ineffective in helping firms to meet their consumptive demand. Our nature-inspired modeling framework provides a potentially useful approach for evaluating how different participant decision-making strategies may impact the robustness and resilience of global supply chains that are increasingly likely to face frequent and unpredictable disruptions.

Strategic behavior in one-to-one matching markets without outside options

In two-sided one-to-one matching markets, each side of the market has a single stable mechanism that is strategy-proof for its members (Alcalde and Barberà, 1994). When agents may not declare potential partners inadmissible, this uniqueness result only holds for the short side, if there is one. Furthermore, among the stable mechanisms that are strategy-proof for the long side of the market, there is one that is less manipulable by coalitions of its members than the long-side optimal deferred acceptance mechanism. In general, Alcalde and Barberà's uniqueness result holds for one side of the market if and only if either at most one of its members may not declare inadmissibilities or there are fewer agents on that side than individuals without outside options on the other side of the market.

Behavioral strategy in evolution: A review and conceptual framework

Behavioral strategy integrates psychology with strategic management theory and practice, offering realistic insights into human cognition, emotions, and social behavior in strategic management. Yet behavioral strategy's antecedents, mechanisms, consequences, and moderators and their interconnectedness and future directions remain unclear. We explore this field's development and current state based on a systematic literature review of 241 articles. We develop a conceptual framework using a coevolutionary perspective and a socially situated cognition approach, which captures essential behavioral strategy elements and dynamics. We advance the field by emphasizing multilevel coevolving dynamics and the interplay of cognition and emotions in shaping strategic behavior. Furthermore, our framework situates cognition within social contexts. We propose an expanded research agenda for the field that highlights artificial intelligence's potential role in enhancing behavioral strategy and the connection between heuristics and nudge frameworks.

Financing urban land development in underdeveloped small cities in western China: The role of earmarked funds

Previous studies suggest that market forces and the strategic behavior of local governments regarding land development jointly contribute to rapid urban expansion in China. In underdeveloped small cities in Western China, the market is weak, and local governments lack the conditions required to promote land-centered urbanization. Surprisingly, these cities have experienced an expansion of urban space faster than the national average. This study presents a significant funding model of urban land development within the framework of the project system. Within this model, central and provincial governments are key providers of land development funds. Local governments design, apply for, package, and implement land development projects. Private developers cooperate with local governments rather than functioning as real initiators of and investors in land development projects. The findings provide new and supplementary evidence about how rapid urban expansion occurs in China, particularly in underdeveloped areas.

OPTIMIZING PROCESSOR WORKLOADS AND SYSTEM EFFICIENCY THROUGH GAME-THEORETIC MODELS IN DISTRIBUTED SYSTEMS

The primary goal of this research is to examine how different strategic behaviors adopted by processors affect the workload management and overall efficiency of the system. Specifically, the study focuses on the attainment of a pure strategy Nash Equilibrium and explores its implications on system performance. In this context, Nash Equilibrium is considered as a state where no player has anything to gain by changing only their own strategy unilaterally, suggesting a stable, yet not necessarily optimal, configuration under strategic interactions. The paper rigorously develops a formal mathematical model and employs extensive simulations to validate the theoretical findings, thus ensuring the reliability of the proposed model. Additionally, adaptive algorithms for dynamic task allocation are proposed, aimed at enhancing system flexibility and efficiency in real-time processing environments. Key results from this study highlight that while Nash Equilibrium fosters stability within the system, the adoption of optimal cooperative strategies significantly improves operational efficiency and minimizes transaction costs. These findings are illustrated through detailed 3D plots and tabulated results, which provide a detailed examination of how strategic decisions influence system performance under varying conditions, such as fluctuating system loads and migration costs. The analysis also examines the balance between individual processor job satisfaction and overall system performance, highlighting the effect of rigid task reallocation frameworks. Through this study, the paper not only improves our understanding of strategic interactions within computational systems but also provides key ideas that could guide the development of more efficient computational frameworks for various applications.

A multi-commodity partial equilibrium model of imperfect competition in future global hydrogen markets

Techno-economic studies are investigating procurement costs of hydrogen and related derivatives across various international trade routes. However, the strategic behavior of exporters is rarely considered in this context, despite similar behavior frequently observed in the fossil fuel world and market characteristics indicating some potential. This work introduces a novel techno-economic model of oligopolistic trade tailored around the value chain of potential future global hydrogen markets. It is formulated as a mixed complementarity problem with a convex reformulation, allowing to solve both competitive and oligopolistic equilibria much beyond the capabilities of traditional complementarity models. Illustrative results show that assuming perfectly competitive price formation in early phases of future global hydrogen markets may lead to overly optimistic hydrogen price projections. This is especially the case within Europe, Japan, and South Korea. In contrast, strategically withholding quantities in export may decrease prices for some domestic markets.

Resistance is futile: Unveiling the self-presentational arsenal of the left-wing authoritarian

ABSTRACT Although right-wing authoritarianism is among the most well-studied constructs in the social sciences, left-wing authoritarianism (LWA) has only recently gathered attention. To expand on this burgeoning area, this study investigated LWA’s associations with an encompassing list of tactical self-presentation behaviors that are designed to gain power. A sample of US adults (N = 446; M age = 46.10; 51% female) completed self-report measures of LWA and their use of 12 self-presentation tactics. LWA was related to a protean overreliance on all self-presentation tactics except apologies, which could not be attributed to liberalism or demographics (e.g. age; sex; race) and were consistent across LWA’s facets. Our findings suggest the utility of conceptualizing LWA as based in strategic self-presentation behavior that can secure social power.

Flag of convenience and the tragedy of the commons in maritime transportation

Flag of convenience (FOC) refers to the practice of registering ships in foreign countries to benefit from lax regulations. While FOC offers several short-term cost advantages to ship owners and FOC countries, it poses significant threats to critical international interests, including environmental protection and marine habitat preservation. Despite global outrage and concerns over FOC's environmental impact, the number of FOC ships have continued to rise. Using game theory, we illustrate how individual rationality – opting for FOC to maximize economic benefits – leads to adverse outcomes for the common good, resulting in increased marine pollution, that we refer to as the tragedy of the commons. Our findings have implications for understanding the strategic behaviour of key players in the maritime transportation, revealing the dark side of globalization and stressing the need for stronger international cooperation to shift these behaviours.

GPT-3.5 altruistic advice is sensitive to reciprocal concerns but not to strategic risk.

Pre-trained large language models (LLMs) have garnered significant attention for their ability to generate human-like textand responses across various domains. This study delves into examines the social and strategic behavior of the commonly used LLM GPT-3.5 by investigating its suggestions in well-established behavioral economics paradigms. Specifically, we focus on socialpreferences, including altruism, reciprocity, and fairness, in the context of two classic economic games: the Dictator Game(DG) and the Ultimatum Game (UG). Our research aims to answer three overarching questions: (1) To what extent do GPT-3.5suggestions reflect human social preferences? (2) How do socio-demographic features of the advisee and (3) technicalparameters of the model influence the suggestions of GPT-3.5? We present detailed empirical evidence from extensiveexperiments with GPT-3.5, analyzing its responses to various game scenarios while manipulating the demographics of theadvisee and the model temperature. Our findings reveal that, in the DG Dictator Game, model suggestions are more altruistic than in humans.We further show that it also picks up on more subtle aspects of human social preferences: fairness and reciprocity. Thisresearch contributes to the ongoing exploration of AI-driven systems' alignment with human behavior and social norms,providing valuable insights into the behavior of pre-trained LLMs and their implications for human-AI interactions.Additionally, our study offers a methodological benchmark for future research examining human-like characteristics andbehaviors in language models.

Strategic behavior and entry deterrence by branded drug firms: the case of authorized generic drugs.

Pharmaceutical firms that market brand-name drugs lose substantial market share to generic manufacturers after patent expiration. As a response to the threat of generic competition, branded manufacturers pursue defensive strategies. One such strategy is the launch of authorized generic drugs. Authorized generic drugs are produced by branded manufacturers to compete against other generic drug entrants. Such competition may lower the expected profits of generic drug manufacturers and hence deter future generic drug entry. This paper models and empirically examines whether the introduction of authorized generic drugs changes the independent generic firms' decisions on entering the market. We use an instrumental variable approach to evaluate the effect of authorized generic drugs on the responses of generic manufacturers. The results show that the entry of authorized generic drugs deters and delays the entry of generic drugs.

Rethinking the low profile: The evolving stance of China’s strategic culture

In recent decades, the concept of strategic culture has emerged as the core focus of cultural approach theories to explain a state’s strategic behavior, given that existing theories have failed to convey deviations from the universal principles of rational state behavior. Relying on the conceptual framework of strategic culture, complemented by Barry Buzan’s “revisionist” approach, this article strives to fill the existing gap in the literature by presenting motives and evidence of revisionism in China’s culture-based conduct. By investigating China’s revisionist behavior vis-à-vis its strategic culture, we conclude that both are correlated. China’s territorial claims, its rapid military modernization, the launch of the Belt and Road Initiative, and its ambiguous alignment with Russia, emphasize the evolution of China’s strategic culture from a defensive to a more resolute stance.

PRIORITY DIRECTIONS OF ENTERPRISES DEVELOPMENT IN THE WAR CONDITIONS BASED ON THE IMPLEMENTATION OF INFORMATION TECHNOLOGIES AND DIGITAL TOOLS

The article examines the modern challenges faced by Ukrainian enterprises in war conditions and the strategic approaches to adapting to these challenges. As business leaders, policymakers, and analysts, your understanding and support are crucial. The current stage of Ukraine's economic development, characterized by high instability due to the full-scale invasion of Russia, dictates new conditions for the functioning of domestic enterprises. In these conditions, implementing information technologies and digital tools becomes critically important for ensuring sustainable development and adaptation of enterprises to new realities. The influence of the war on the strategic behavior of enterprises is considered in detail, emphasizing the need to adapt to rapid changes in the external environment. In constant uncertainty and risks, enterprises are forced to look for new development opportunities, actively implement information technologies, and diversify their activities. The main challenges and barriers faced by enterprises during the war are also analyzed. Among them are the lack of sufficient capital, limited access to credit funds, the unpredictability of the situation in Ukraine, the negative impact of government decisions on business, and others. To overcome these problems, enterprises must look for development directions and develop appropriate development strategies that consider internal opportunities and external threats. Digitization and the use of information technologies are becoming critical tools for achieving these goals, allowing enterprises to adapt to changes in the external environment quickly, increase the efficiency of their activities, and maintain competitiveness. Special attention is paid to such promising development directions as DefenseTech, FinTech and cyber security. These directions, with their significant potential for development in wartime, provide the necessary technological solutions to improve the security and efficiency of enterprises, offering a beacon of hope for the future. Thus, the article provides a comprehensive analysis of the priority directions of enterprise development in wartime conditions, with an emphasis on implementing information technologies and digital tools.

Effects of Core Competitiveness on Strategic Alliance and Alliance Performance in Medical Device Industry

Along with the progress of economic development, the enhancement of national income, and the trend of population ageing in past years, people are annually increasing the medical expenses and enhancing the demands for medical devices. Being a part of healthcare, the requirements for the product safety and quality of medical devices are rather high. Manufacturers in the world therefore have to work hard to promote the competitiveness, attempting to achieve corporate goals and supply the best products to medical profession. Core competition combined resources are the sign of competitive advantage. Firms would build excellent competitive advantage through important resource combinations. A company tending to create competitiveness as well as build and lead new markets has to make investment earlier and continuously, apply the imagination to predict, develop, and investigate markets which have not been existed. The research focused on supervisors and employees in the medical device industry. The results reveal notable and positive effects of core competitiveness on strategic alliance and alliance performance, the understanding of how medical device firms apply strategic behavior in the competitive strategic means to reinforce the resource acquisition capability, and the reference for building the competitive advantage after strategic alliance and drafting appropriate competitive strategies for the business management of a domestic firm in medical device industry. It is expected to propose more specific suggestions for firms in medical device industry using core competitiveness in strategic alliance and dedicating to the promotion of competitive advantage.

The Impact of Strategic Entrepreneurship Behaviors on Business Performance in Turkish SMES: The Role of Business Model Innovation and Competitive Intensity

The Impact of Strategic Entrepreneurship Behaviors on Business Performance in Turkish SMES: The Role of Business Model Innovation and Competitive Intensity

Walking the Walk: How Genuine Organizational Transformation Can Enhance DEI Initiatives

This article discusses how genuine organizational transformation can enhance diversity, equity, and inclusion (DEI) initiatives to deliver meaningful results. The article suggest that standalone DEI programs are generally insufficient for driving sustainable cultural change. Instead, DEI needs to be embedded throughout an organization through systemic shifts in mindsets, processes, policies, and practices. The article outlines recommendations for advancing DEI through reimagining strategic vision and leadership behaviors, restructuring human resources systems and resource allocation, cultivating an inclusive culture, and demonstrating continued commitment through action, progress measurement, and issue response. Case examples from various industries are provided. The article argues that holistic organizational transformation integrating DEI into the fabric of the organization is key to authentically advancing diversity and inclusion.

Evolutionary Dynamics of Population Games With an Aspiration-Based Learning Rule.

Agents usually adjust their strategic behaviors based on their own payoff and aspiration in gaming environments. Hence, aspiration-based learning rules play an important role in the evolutionary dynamics in a population of competing agents. However, there exist different options for how to use the aspiration information for specifying the microscopic learning rules. It is also interesting to investigate under what conditions the aspiration-based learning rules can favor the emergence of cooperative behavior in population games. A new learning rule, called as "Satisfied-Cooperate, Unsatisfied-Defect", is proposed here, which is based on aspiration. Under this learning rule, agents prefer to cooperate when their income is satisfied; otherwise, they prefer the strategy of defection. We introduce this learning rule to a population of agents playing a generalized two-person game. We, respectively, obtain the mathematical conditions in which cooperation is more abundant in finite well-mixed, infinite well-mixed, and structured populations under weak selection. Interestingly, we find that these conditions are identical, no matter whether the aspiration levels for cooperators and defectors are the same or not. Furthermore, we consider the prisoner's dilemma game (PDG) as an example and perform numerical calculations and computer simulations. Our numerical and simulation results agree well and both support our theoretical predictions in the three different types of populations. We further find that our aspiration-based learning rule can promote cooperation more effectively than alternative aspiration-based learning rules in the PDG.

Contextual Dynamic Pricing with Strategic Buyers

Personalized pricing, which involves tailoring prices based on individual characteristics, is commonly used by firms to implement a consumer-specific pricing policy. In this process, buyers can also strategically manipulate their feature data to obtain a lower price, incurring certain manipulation costs. Such strategic behavior can hinder firms from maximizing their profits. In this article, we study the contextual dynamic pricing problem with strategic buyers. The seller does not observe the buyer’s true feature, but a manipulated feature according to buyers’ strategic behavior. In addition, the seller does not observe the buyers’ valuation of the product, but only a binary response indicating whether a sale happens or not. Recognizing these challenges, we propose a strategic dynamic pricing policy that incorporates the buyers’ strategic behavior into the online learning to maximize the seller’s cumulative revenue. We first prove that existing nonstrategic pricing policies that neglect the buyers’ strategic behavior result in a linear Ω ( T ) regret with T the total time horizon, indicating that these policies are not better than a random pricing policy. We then establish an O ( T ) regret upper bound of our proposed policy and an Ω ( T ) regret lower bound for any pricing policy within our problem setting. This underscores the rate optimality of our policy. Importantly, our policy is not a mere amalgamation of existing dynamic pricing policies and strategic behavior handling algorithms. Our policy can also accommodate the scenario when the marginal cost of manipulation is unknown in advance. To account for it, we simultaneously estimate the valuation parameter and the cost parameter in the online pricing policy, which is shown to also achieve an O ( T ) regret bound. Extensive experiments support our theoretical developments and demonstrate the superior performance of our policy compared to other pricing policies that are unaware of the strategic behaviors. Supplementary materials for this article are available online, including a standardized description of the materials available for reproducing the work.