Search Results (50)

Strategic competition in health service markets requires managers to make pricing, marketing, and investment decisions under uncertainty, yet educational programs in healthcare management and dietetics lack experiential tools for teaching these competencies within a game-theoretic framework. This study develops and computationally validates SY142-Game-Theory-1, a computational simulation framework that models strategic competition between two asymmetric healthy living centers as a 36-month repeated Prisoner’s Dilemma, integrating demand decomposition, net present value analysis, employee satisfaction dynamics with burnout thresholds, reputation feedback, and stochastic shock events. The simulation produces a valid and distinctly asymmetric Prisoner’s Dilemma structure in which the established provider faces the classical temptation to defect while the new entrant’s rational incentive aligns with cooperation; Axelrod-style tournaments across 22 strategies (96,800 simulations) identify Forgiving Tit-for-Tat as the top-performing strategy; Monte Carlo validation (n = 1000) confirms a statistically significant cooperation premium of 24.1% over Nash equilibrium; and sensitivity analyses across four parameters demonstrate robustness of all qualitative findings. The open-source framework bridges game theory, simulation-based learning, and health service management education, providing a computationally validated foundation for teaching strategic decision-making in competitive healthcare environments, with empirical evaluation of learning outcomes reserved for future work. Full article

The rapid growth of the sharing economy has improved resource utilization in car-sharing, yet it has also sharpened market competition and diversified user demand. A persistent obstacle is the low coordination efficiency between asset-heavy operating companies and traffic-driven platforms, whose misaligned objectives waste social resources. This paper uses differential game theory to analyze their dynamic coordination strategies and benefit allocation mechanisms. The Nerlove–Arrow model captures the evolution of brand goodwill, while the company’s decisions on station layout, vehicle dispatch, and pricing, together with the platform’s advertising investment, form the core decision variables in a two-party game framework linking the asset side and the traffic side. Compared with the non-cooperative Nash equilibrium, the cooperative mode removes the double marginalization effect, strengthens the investment incentives of both parties, and raises the system’s steady-state goodwill and total profit, achieving a Pareto improvement. To ground the cooperative framework in rigorous theory, we supply a verification theorem confirming that the linear candidate value functions satisfy the Hamilton–Jacobi–Bellman equations over the entire admissible state space. A formal proof of instantaneous rationality ensures that neither party falls into a cooperation trap on the horizon $[0,T]$, and the asymptotic stability of the steady-state goodwill trajectory is established. We further endogenize the revenue-sharing coefficient through a generalized Nash bargaining model that admits asymmetric bargaining structures, and introduce a Stackelberg leadership benchmark as a third comparative regime. Sensitivity analyses with respect to the discount rate and user heterogeneity confirm the robustness of the findings. A dedicated discussion section bridges the gap between idealized parameterization and data-driven calibration, describing practical pathways via A/B testing, user churn metrics, and econometric estimation of demand parameters. The results offer a scientific decision-making reference for strategic cooperation in the car-sharing industry. Full article

The high-value utilization of construction and demolition waste is critical for sustainable development in the building sector. However, in construction and demolition waste (CDW) recycling supply chains, existing studies lack a systematic analysis of pricing mechanisms for such recycled CDW as substrate products, particularly regarding interest coordination and the quantification of green value. To reveal the bargaining mechanism between farmers as recyclers and processors and supermarkets as retailers under an asymmetric bargaining structure, this study applies Nash bargaining theory to construct a dynamic game model. The study revealed that (1) when the green degree of a product reaches a certain level, it can obtain a sustainable market premium and create a stable income space for both parties. (2) The relative strength of the bargaining power between the two sides significantly affects the impact of market base scale changes on profit distribution. When the bargaining power of the supermarket is lower than the threshold and the bargaining power of the farmers is higher than the threshold, the difference in profit between the farmers and the supermarket is negatively correlated with the market base scale of the CDW as a substrate. (3) The green sensitivity level of consumers affects the difference in profit of the main body with the government subsidy to farmers. This level is determined by the value of the green sensitivity coefficient of consumers and presents a differentiated adjustment effect in different value ranges, which in turn affects the transmission direction of government subsidies to profit distribution. (4) When the green sensitivity coefficient and the green communication intensity of farmers and the investment level are lower than the corresponding critical values, the difference in social welfare with or without subsidies is positively correlated with the amount of the subsidy. This study provides decision support for farmers and supermarkets in designing rational bargaining strategies and offers insights for improving coordination and sustainability in construction and demolition waste recycling supply chains. Full article

To address the “greenwashing” trust crisis induced by information asymmetry in sustainable supply chains, this study develops a comprehensive game-theoretic model integrating Stackelberg and evolutionary game theories (EGT). We quantitatively investigate the dynamic interactions among multi-dimensional consumer preferences, blockchain implementation costs, and boundedly rational government interventions. Our analysis yields three core contributions. First, we analytically reveal the “double-edged sword effect” of blockchain adoption. While structural transparency unlocks a trust dividend, exorbitant technological costs trigger a “budget crowding-out effect.” Quantitative results demonstrate that breaching the absolute Feasibility Threshold completely cannibalizes the environmental budget, driving substantive green investments strictly to zero. Second, EGT analysis proves that isolated punitive carbon taxes trap supply chains in a suboptimal “shallow greening” equilibrium. A composite tax-subsidy policy is structurally required to expand the feasible cost space and hedge against technological risks. Finally, we formulate a dynamic policy exit mechanism. As blockchain infrastructure matures and the endogenous green premium effectively offsets implementation costs, regulators must systematically phase out subsidies and converge toward a single-taxation regime to prevent corporate policy arbitrage and alleviate long-term public financial burdens. Full article

Sustainable (ESG) investments have gained significant interest, prompting renewed attention to retail investors’ decision-making processes. ESG investing is motivated by both financial concerns and psychological factors. However, despite growing interest, the motivational underpinnings of sustainable asset allocation remain underexplored. This study bridges economic psychology and sustainable finance to examine drivers of ESG investment intentions and choices in the Italian market. Drawing on the Theory of Planned Behavior, it explores how attitudes, subjective norms, perceived behavioral control, and trust shape ESG investing intentions and choices. Results show that each factor significantly influences investing intentions when considered independently. In particular, the affective dimension of attitudes emerges as especially relevant. These findings challenge traditional views of financial rationality in ESG contexts, suggesting that the motivations of sustainability-oriented investors may differ meaningfully from those of traditional investors. Practical implications are that ESG communication should appeal to emotional and ethical dimensions of decisions, while educational initiatives should enhance investors’ ability to critically assess ESG-related information. Full article

Financial reporting standards aim to increase transparency; however, the expansion in disclosure volume may also create an information overload paradox for investors, an issue that remains underexplored in the context of institutional investors. Excess information beyond mandatory requirements may complicate decision environments and create cognitive burden. When information exceeds cognitive processing capacities, attention may become fragmented, making it more difficult to distinguish signal from noise and potentially leading to analysis paralysis and changes in risk perception. Drawing on bounded rationality and cognitive load theory, this study conceptualizes information overload as a behavioral constraint associated with perceived limitations in decision quality and speed and, accordingly, examines its influence on institutional investors’ decision processes through a phenomenological approach. The study employs thematic analysis based on in-depth interviews with 19 professionals in institutional investment organizations in Türkiye. The findings suggest that information overload is experienced as cognitive strain that may prolong decision processes, may be associated with analysis paralysis and perceived changes in decision quality, and may be associated with increased uncertainty and potential challenges in interpreting risk. These findings provide exploratory insight into how information density may influence risk interpretation and portfolio assessment, and how institutional investors perceive decision-making efficiency. Full article

Technology enterprises are leveraging artificial intelligence (AI) to foster disruptive innovation, aiming to seize first-mover advantages in technological catch-up and strategic transformation. Most existing studies adopt static research methods such as empirical analysis to explore corporate disruptive innovation from the dimensions of technology, market, organization and value creation. However, few scholars dynamically investigate the impacts of multi-stakeholder interactions on the disruptive innovation of AI enterprises from the perspective of innovation ecosystem by employing evolutionary game theory. Against this backdrop, this paper adopts the evolutionary game approach to explore how the bounded rational strategic interactions among AI enterprises, incumbent enterprises and governments in the innovation ecosystem affect the evolutionary dynamics of AI enterprises’ disruptive innovation behaviors. It also examines under what conditions of benefits, costs, risks and policies the system can evolve toward a stable strategic equilibrium. The findings reveal that the sustainable advancement of disruptive innovation by AI enterprises is not merely driven by the unilateral willingness of individual firms. Instead, it is jointly shaped by the innovation investment of AI enterprises, cooperative responses of incumbent enterprises, and regulatory and supportive policies of governments, as well as comprehensively influenced by base benefits, R&D investment pressure, technology spillover effects and niche competition risks. This research provides theoretical references for improving the innovation governance and policy support system of the AI industry. Future research can further analyze the influence of strategic interactions among more heterogeneous stakeholders on the evolutionary process of disruptive innovation of AI enterprises. Full article

The rapid rise in cryptocurrencies has created an investment environment marked by unprecedented levels of information volume, fragmentation, and volatility. While prior research has examined drivers of trust and adoption in crypto markets, far less is known about the psychological consequences of information overload on investor decision-making. This study addresses this gap through nineteen semi-structured interviews with individual cryptocurrency investors, analyzed using an inductive, manually conducted thematic approach. Findings reveal four interconnected dynamics: decision fatigue and paralysis, heuristic reliance on influencers and peers, emotional strain characterized by anxiety and fear of missing out (FOMO), and diverse coping strategies ranging from selective filtering to withdrawal. These results demonstrate that crypto investing is not only a financial process but also a cognitively and emotionally taxing experience. By linking investor narratives to broader theories of decision fatigue, bounded rationality, and consumer vulnerability, the study contributes to interdisciplinary debates in marketing, behavioral finance, and consumer psychology. Practically, the findings highlight the need for clearer communication strategies, supportive platform design, and financial education initiatives that help investors manage cognitive strain and decision fatigue. In a market where credibility is fluid and decisions are often made under conditions of overload, understanding the psychological dimensions of investment behavior is essential. Full article

Early adolescent sport dropout is commonly explained through individual psychological factors such as declining motivation, burnout, or identity conflict. While valuable, these accounts often assume parental logistical and financial support as a stable background condition. This conceptual article introduces the Utilitarian Shift as a novel, family-level structural mechanism that helps explain why sport dropout peaks during early adolescence. Drawing on Social Exchange Theory, sociological perspectives on family investment, and developmental psychology, the framework conceptualizes dropout as emerging from a developmentally timed recalibration of parental investment. During childhood, parental support is largely sustained by custodial and broad developmental incentives; however, as adolescents gain functional independence and perceived developmental returns decline, continued investment becomes conditional rather than assumed. At the same time, sport system demands intensify through specialization pressures, rising costs, and selection mechanisms such as the Relative Age Effect. The convergence of declining perceived returns and escalating costs prompts rational parental withdrawal of logistical and financial support, thereby dismantling the material infrastructure required for sustained participation. Importantly, this withdrawal precedes and reshapes adolescents’ capacity to enact motivation, agency, and resilience, rather than merely responding to disengagement. The article situates early adolescent sport dropout as a relational and structurally mediated process, shifting analytic attention away from athlete-centered deficit models toward dynamic parental decision-making within marketized youth sport systems. Practically, the framework highlights the need for sport organizations and governing bodies to redesign participation pathways and value propositions that sustain parental engagement during early adolescence, even in the absence of elite performance trajectories. Full article

This study investigates the factors associated with niyyah (worshipful intention) of Islamic bankers toward issuing green sukuk (G-sukuk) investment instruments. In particular, it analyses how bankers’ empathy, moral and ethical responsibilities, and self-efficacy are related with environmental awareness, perceived social support, and green tech innovation, respectively. These factors then predicted bankers’ niyyah toward issuing G-sukuk. The present research employed the theory of bounded rational planned behavior as its theoretical foundation. Data were collected from 390 bankers employed in different Islamic banks. Random sampling technique was employed for this cross-sectional study and for analyzing data, this study applied structural equation modeling. Findings indicate that all predictors are statistically significant and positively associated with bankers’ niyyah toward G-sukuk for ensuring sustainable finance. Furthermore, G-sukuk initiatives can help to lower the carbon emissions and other harmful substances, which would improve overall environmental sustainability and ecological contexts related to SDG-13. There is limited empirical evidence available on the G-sukuk perspective in Bangladesh. This study will provide practical insights for the bankers and policymakers. Full article

The rapid rise in cryptocurrency presents both opportunities and challenges for retail investors due to its volatility and technological complexity. Research on investment decisions has primarily focused on behavioural finance, often overlooking how learning and literacy shape investor actions. This study addresses this gap by examining how herding behaviour, financial literacy, and digital literacy impact cryptocurrency investment decisions. Grounded in Social Learning Theory and supported by UTAUT to operationalise digital literacy, this study examines how herding behaviour, financial literacy, and digital literacy shape cryptocurrency investment decisions. We analyse survey data from 138 Indonesian retail investors through PLS-SEM. Key findings show that financial literacy (β = 0.443, t = 5.041) and digital literacy (β = 0.495, t = 4.246) are primary determinants of investment decisions, while herding behaviour (β = 0.016, t = 0.628) does not directly influence them but does so indirectly by enhancing investor literacy. This demonstrates that social observation and learning can convert herd-driven impulses into rational choices when mediated by literacy. By extending Social Learning Theory into digital investment contexts, this study provides insights for investors and policymakers seeking to enhance financial and digital literacy. Full article

Enhancing farmers’ livelihood resilience is a cornerstone of sustainable rural development and poverty alleviation consolidation in developing countries. While tourism has emerged as a prominent rural revitalization strategy, the mediating role of tourism-induced land use transitions in building resilience—and the underlying spatial mechanisms through which these transformations operate—remains inadequately understood. This study integrates Henri Lefebvre’s spatial production theory with land systems analysis to examine how tourism-driven land use transitions influence farmers’ livelihood resilience in rural China. Using provincial panel data and three waves (2018, 2020, 2022) of nationally representative household survey data from the China Family Panel Studies (CFPS), we construct a comprehensive tourism development index emphasizing land transformation dimensions and employ panel regression models with instrumental variables and threshold analysis. The findings reveal that tourism-induced land use transitions significantly enhance farmers’ livelihood resilience through three distinct spatial mechanisms: land-based rural infrastructure investment, industrial land structure rationalization, and cultural facility land development. Importantly, this relationship exhibits a double-threshold effect with diminishing marginal returns, and the positive impact is substantially stronger in heritage-rich regions with comparative policy advantages. By establishing land use transitions as a critical spatial production pathway linking tourism to sustainable livelihood outcomes, this study advances land systems science, offering a novel theoretical framework for integrating people–nature interactions in heritage-rich rural areas and practical guidance for strategic land use planning in support of the Sustainable Development Goals (SDGs). Full article

Investor sentiment has increasingly been recognized as a behavioural factor influencing asset prices beyond traditional rational asset pricing models, yet evidence from South Africa’s property remains limited. This study investigates the short-run and long-run relationship between investor sentiment and FTSE/JSE-listed property indices, to determine the influence of sentiment on property index pricing within the South African context. Using monthly data for selected JSE/FTSE property indices, a composite investor sentiment index was constructed through a principal component analysis (PCA) of multiple market-based sentiment proxies. Consequently, a Vector Error Correction Model (VECM) was estimated to examine both the long-run and short-run relationships, integrated with the VEC Granger causality tests to determine the direction of influence between variables. The findings report a novel relationship between investor sentiment and the FTSE/JSE property indices, as they provide new insights at the disaggregated level, which is overlooked in the literature. In the short run, the findings suggest that market psychology drives short-term property price adjustments. Moreover, in the long run, the relationship remains significant, indicating that this effect persists, underscoring the enduring influence of sentiment on market valuation. Additionally, the Granger causality results indicate uni-directional relationships, where investor sentiment drives listed property pricing and macroeconomic variables, reinforcing its predictive role. The study concludes that investor sentiment is a key determinant of South Africa’s listed property market, consistent with the rationale of behavioural finance theory, and underscores that investment decisions within this market are substantially influenced by investor psychology, contributing to property market volatility. Full article

Regional economic diversity and unevenly allocated space-based resources have created unprecedented difficulties for collaborative and innovative supply chain construction. This paper sets up a tripartite evolutionary model of the government, upstream companies, and downstream companies to explore dynamic processes of regional supply chain collaborative innovation with bounded rationality. Through incorporation of hierarchical space organizations and policy incentive differentiation mechanisms, the model discerns actors’ behavioral evolution and strategic adjustment in a geographically divided structure. Adopting evolutionary game theory and numerical simulation, this paper includes crucial parameters like the conversion efficiency of return conversion, information-sharing coefficient, mutual trust coefficient, and fiscal subsidy coefficient for examining policy and spatial heterogeneity effects on information collaborative innovations. The results reveal that fiscal incentives are the primary driving factor for collaborative evolution across local supply chains. Adaptive profit-sharing and subsidy intensities both stimulate upstream innovation investments and downstream cooperation adoption efficiently, stimulating a shift out of inefficient equilibrium states towards sustainable high-cooperation states. Furthermore, the restructuring of space accelerates hierarchical differentiation—core region companies are able to act like initiators and leaders for collaborative innovations, while periphery companies encounter participatory barriers in terms of elevated coordination costs and incentive shortages. In light of this, it is therefore crucial to have a “core-driven, periphery-subsidized” policy system for eliminating spatial gaps, stimulating cross-regional information exchange, and building systemic robustness. These findings contribute to enhancing the overall efficiency, stability, and innovation capacity of regional supply chain systems. They also provide a theoretical basis for policy decision making and industrial upgrading across regions of varying scales and environments. Full article

In a significant transition from classical theories of efficient markets and perfectly rational investors, the recent literature has increasingly acknowledged the importance of the human element and external market conditions in decision-making. However, the application of adaptive market frameworks in the property sector remains underexplored. This gap is particularly pronounced in the commercial property market, where structural inefficiencies, such as information asymmetry and illiquidity, amplify decision-making complexity. Given that investor rationality tends to diminish as uncertainty and complexity increase, this study explored how private commercial property investors adapt their strategies amid heightened uncertainty. The perspectives of seven experienced property experts were thematically analysed to highlight recurring patterns, which were then integrated into a conceptual mind map. The findings reveal that while economic fundamentals are the constant drivers of capital allocation decisions, investors process these signals through the lens of adaptive behaviour based on intuition, experience, risk perceptions, and herding. This relationship becomes more pronounced under conditions of heightened uncertainty, where investors seek to supplement available information with sentiment due to weaker signals and declining confidence in fundamentals. Sustainable investing and technology integration also emerged as core considerations, but interest among private investors is subdued due to ambiguous value propositions regarding the long-term economic benefits of a green premium. These findings offer practical insights into how external market conditions influence property investment decisions and provide a platform for operational models of investment decision-making that integrate adaptive behaviour. Full article