Search Results (63)

Digital transformation is crucial for businesses to thrive in today’s rapidly evolving marketplace. It is a strategic choice that enables organizations to improve customer service, strengthen supplier relationships, and boost sales and business growth, ultimately enhancing their competitive stance. The Internet of Things (IoT) has become a transformative force across various domains, leveraging interconnected devices and sensors to gather and analyse data, thus enhancing decision making, efficiency, and innovation. This paper analyses the strategic competition between two 3PL firms integrating IoT technologies. Based on a game-theoretic model, the study uses Monte Carlo simulation and K-means clustering to identify distinct strategic groups and optimal adoption ranges. The findings highlight risks of over- or under-investments as well as asymmetric outcomes. Also, a set of recommendations and managerial insights are provided for better decision making in a tech-competitive setting. Full article

In the context of managing museums, historical, artistic, and archaeological heritage, an advanced decision support system (DSS) can serve as the engine for a business game platform, optimizing decision paths and management strategies. In complex, multi-parameter scenarios, the final decision is often only part of the process; it is equally essential to follow the decision-making path, that is, the sequence of actions necessary to reach the objective. The DSS presented here simplifies the problem by transforming the initial n-dimensional space, defined by the critical success factors (CSFs) selected by experts, into a two-dimensional space. Indeed, thanks to this approach, the computational complexity is reduced to the point that the technological solution can be used even on standard desktop computers and not only on high-performance computing systems. Moreover, the user does not necessarily need to be an IT expert but rather a specialist in the cultural domain. Through grid-based motion algorithms and a hierarchy of CSF priorities, the system quickly identifies optimal solutions in the 2D plane and then maps them back to the n-dimensional space to maintain consistency with the original context. Since the correspondence between n-dimensional micro-states and two-dimensional macro-states is not one-to-one, the DSS returns the specific micro-state of interest from the optimal macro-state, selecting the most effective path. This research aims to develop algorithms that by minimizing entropy and optimizing the system’s dynamics, build optimal paths in the 2D plane, with algorithms capable of restoring the solution in the initial space. Several use cases in the form of business games have been conducted, demonstrating the value of the proposed solution. The result of this work is a simulation environment useful for museum experts to analyze the impact of their management strategies. Thanks to the ability to assign weights to each of the critical success factors (CSFs), the system can display both qualitative and quantitative simulations of museum dynamics as the weights associated with different CSFs vary. Given the system’s generality, it is applicable to various fields where complex business games are required, such as cultural heritage management, logistics, transportation, healthcare systems, and, more broadly, any context where strategic business analysis is needed for the economic enhancement of resources and their optimization. Full article

As a new business model, cross-border e-commerce has become an important way for countries to meet new foreign trade requirements in the Internet economy. The cross-border logistics industry plays a crucial role in supporting cross-border e-commerce. Compared with domestic e-commerce, cross-border logistics faces more challenges. To address the problems in cross-border logistics, this study takes China as an example and constructs a tripartite evolutionary game model to facilitate information collaboration among cross-border e-commerce platforms, domestic logistics enterprises, and foreign logistics enterprises. The collaboration strategies in this tripartite information system are simulated using MATLAB. The study highlights key factors affecting information cooperation, such as standardization levels, risk and payoff distributions, and their implications on collaboration decisions. Specifically, the results show that higher levels of information collaboration standardization promote cooperative strategies among players; the risk associated with information collaboration is the most sensitive factor influencing decision-making within cross-border logistics alliances; and when the payoff distribution coefficient is too high, other members may resist cooperation. Full article

With more China railway business information systems migrating to the China Railway Cloud Center (CRCC), the attack surface is expanding and there are increasing security threats for the CRCC to deal with. Cyber Mimic Defense (CMD) technology, as an active defense strategy, can counter these threats by constructing a Dynamic Heterogeneous Redundancy (DHR) architecture. However, there are at least two challenges posed to the DHR deployment, namely, the limited number of available schedulable heterogeneous resources and memorization-based attacks. This paper aims to address these two challenges to improve the CRCC-DHR reliability and then facilitate the DHR deployment. By reliability, we mean that the CRCC-DHR with the limited number of available heterogeneous resources can effectively resist memorization-based attacks. We first propose three metrics for assessing the reliability of the CRCC-DHR architecture. Then, we propose an incomplete-information-based game model to capture the relationships between attackers and defenders. Finally, based on the proposed metrics and the captured relationship, we propose a redundant-heterogeneous-resources scheduling algorithm, called the Entropy Weight Scheduling Algorithm (REWS). We evaluate the capability of REWS with the three existing algorithms through simulations. The results show that REWS can achieve a better reliability than the other algorithms. In addition, REWS demonstrates a lower time complexity compared with the existing algorithms. Full article

In the big data era, global business competition focuses on industrial chain coordination. The whole rural e-commerce industry chain, as an advanced system characterized by digital transformation, is experiencing rapid growth. This paper aims to explore the evolutionary mechanism of collaborative behavior in the digital transformation of platform enterprises and participating enterprises across the whole rural e-commerce industry chain. To achieve this, this paper combines prospect theory and evolutionary game theory, introduces the value function and decision weight of prospect theory, and constructs a two-party game model between platform enterprises and participating enterprises. Based on the demonstration of the impact of individual changes in major objective factors, such as the cooperative innovation benefit coefficient, as well as major behavioral characteristic factors, such as decision-makers’ risk attitude coefficients, on enterprises’ strategic choices, we further reveal the influence of the interaction of key factors on the evolutionary results through case simulations. The findings indicate that when the behavior characteristics of the players are introduced, the threshold interval of the cost–benefit ratio of the two sides to reach the optimal state of decision-making is obviously reduced. Under moderate risk attitudes and degrees of loss sensitivity, enhancing the resource absorption capacity of enterprises in the chain and reducing the potential risk loss of platform enterprises to alleviate the influence of subjective behavior characteristics on cooperation willingness are effective measures. Improving innovation ability is the key factor in alleviating the negative impact of uncertainty on the decision-making of both parties. This paper is one of the few studies to integrate prospect theory with evolutionary game analysis in examining the collaborative behaviors between platform enterprises and participating enterprises. Effective strategies are proposed to promote enterprises achieving synergy. Full article

System stability control in resource allocation is a critical issue in group robot systems. Against this backdrop, this study investigates the nonlinear dynamics and chaotic phenomena that arise during pricing games among finitely rational group robots and proposes control strategies to mitigate chaotic behaviors. A system model and a business model for group robots are developed based on market mechanism mapping, and the dynamics of resource allocation are formulated as a second-order discrete nonlinear system using game theory. Numerical simulations reveal that small perturbations in system parameters, such as pricing adjustment speed, product demand coefficients, and resource substitution coefficients, can induce chaotic behaviors. To address these chaotic phenomena, a control method combining state feedback and parameter adjustment is proposed. This approach dynamically tunes the state feedback intensity of the system via a control parameter M, thereby delaying bifurcations and suppressing chaotic behaviors. It ensures that the distribution of system eigenvalues satisfies stability conditions, allowing control over unstable periodic orbits and period-doubling bifurcations. Simulation results demonstrate that the proposed control method effectively delays period-doubling bifurcations and stabilizes unstable periodic orbits in chaotic attractors. The stability of the system’s Nash equilibrium is significantly improved, and the parameter range for equilibrium pricing is expanded. These findings provide essential theoretical foundations and practical guidance for the design and application of group robot systems. Full article

Business simulation games (BSGs) are considered a useful instructional tool to be implemented in the classroom, especially in light of new trends in education. The key components of the paradigm are BSGs and Decision Making (DM), as the latter is often essential to a high-quality education. Thus, over the last 10 years, efforts to find possible methods to enhance BSG learning experiences for the development of DM in higher education have increased. The goals of this article were to examine the effect of BSGs on students’ DM at university, and to identify the elements that can be developed in the BSG learning experience to promote DM. Following PRISMA criteria, a systematic review was carried out using Scopus, Web of Science, and ProQuest. A total of 13 of the 2897 papers that were first discovered underwent a comprehensive review, with all conclusions and findings subjected to analysis. Following implementation, the majority of the BSG learning experiences enhanced DM results. In summary, a few key elements have been highlighted that must be followed to ensure the BSG learning experience helps students foster their DM. Full article

Background and Methods: A primary survey of a multi-national sample of higher institutional educators has been conducted to investigate the determinants of the adoption of management simulation games. The research model is developed based on the technology acceptance model (TAM) and technology–organisation–environment (TOE). Structural equation modelling has been used to test the research model. The paper focuses on the use of management simulation games among educators in higher educational institutions (HEIs). Its purpose is to determine the factors influencing educators’ use of these games from both individual and institutional perspectives. The TAM captures the individual perspective, while the TOE framework addresses the institutional perspective. The structural equation model confirmed most of the TAM hypotheses. Results: However, the model does not support the hypotheses regarding the relationship between perceived ease of use and attitude toward usage or between perceived ease of use and perceived usefulness. The technological factors within the TOE framework did not significantly impact perceived usefulness, only perceived ease of use. Conclusion: The combined TAM-TOE model has demonstrated valid representativeness. Previous research on the usage of management simulation games has primarily focused on students, neglecting the broader perspective of educators in HEIs in business and economics within both the TAM and TOE frameworks. Full article

Clean energy serves as a crucial means to alleviate water resource shortages and ensure power production safety. This study delves into clean energy diffusion and development within the confines of the Yellow River Basin, considering water resource constraints. It examines the dynamic evolution of the strategic choices made by local governments and the expansion of clean energy businesses among power generation groups using an evolutionary game model. Additionally, the study employs the L-V model to elucidate the diffusion and competition dynamics between fossil fuel power generation technology (FFGT) and clean energy generation technology (CEGT). To provide a more scientific elucidation of this process, actual values are utilized for simulation. The findings indicate that: (1) The strategic decisions of power generation groups are influenced not only by local government guidance but also by advancement in clean energy technology and cost reduction efforts; (2) the implementation of water resource tax guidance strategies yields noticeable effects, with higher taxes correlating to increased willingness among power generation groups to expand clean energy businesses; (3) in contrast to diffusion speed, the final state of equilibrium attained by the two technologies is more closely tied to the competition coefficient. A higher competition coefficient leads clean energy generation technology to gain a competitive advantage in the market, potentially dominating it entirely. Based on these conclusions, pertinent policy suggestions are proposed to drive the advancement of clean energy and facilitate energy structure transformation in the Yellow River Basin. Full article

With the increasing global concern for environmental protection and sustainable development, the low-carbon transformation of the manufacturing industries has become a top priority. The rapid development of green digital technology (GDT) provides new opportunities and a strong impetus for the low-carbon transformation of the manufacturing industries. Meanwhile, green credit, as an important financial tool to promote the development of the green economy, plays a key role in guiding resource allocation. In order to respond to the urgent global demand for environmental protection and sustainable development and to accelerate the pace of the low-carbon transformation of manufacturing industries, based on evolutionary game theory, this paper constructs a three-party evolutionary game model of commercial banks (CBs), digital businesses (DBs) and manufacturing industries (MIs); further subdivides the MIs into two categories of non-polluting MIs and polluting Mis; and performs a numerical simulation using Python to analyze the influence of the main parameters on the evolutionary stabilization strategy. The results of the study are as follows: (1) Changes in the interest rate of the green credit have a greater impact on the strategic evolution process of polluting MIs than non-polluting MIs. The green credit model contributes to the introduction of GDT for the low-carbon transformation by non-polluting MIs, although for polluting MIs, the model hinders, to some extent, their introduction of GDT for the low-carbon transformation. (2) Polluting MIs are more sensitive to the investment cost of introducing GDT than non-polluting MIs. When the support benefits of GDT are too low, polluting MIs are more inclined to choose independent innovation to realize the low-carbon transition. (3) Government subsidies to DBs in terms of GDT innovation are crucial to the DBs’ strategy choices. High subsidies can significantly accelerate the cooperation process between DBs and Mis. The findings reveal the challenges and opportunities faced by both non-polluting and polluting manufacturing industries in the process of the low-carbon transformation. In addition, the study provides theoretical references for the behavioral decisions of commercial banks, digital businesses, and manufacturing industries, and proposes corresponding management suggestions to promote the sustainable development of the manufacturing industries. Full article

The carbon quota trading mechanism is considered one of the most effective incentives for carbon reduction to address global climate change. Currently, the EU has adopted this mechanism to intervene in the zero-carbon transition of shipping companies. Unlike other businesses, the shipping market experiences cyclical changes and high uncertainty, with many factors and complex systems involved in the zero-carbon transition process. Research on the impact of dynamic penalty mechanisms combined with government incentive policies on the zero-carbon transition of shipping companies is relatively scarce. To explore this process under such mechanisms, an evolutionary game model of shipping companies’ zero-carbon transition considering dynamic penalties and carbon quota trading was constructed. The model analyzes the effects of factors such as carbon trading prices, emission reductions resulting from zero-carbon transition, government supervision costs, supervision intensity, subsidy values, and penalty caps on the transition process and performs a simulation analysis. The results indicate the following: (1) Under dynamic penalty mechanisms, the evolutionary trajectories of both government and shipping companies spiral towards a unique evolutionary stable strategy, addressing the shortcomings of static penalty mechanisms. (2) Government supervision costs negatively impact the zero-carbon transition of shipping companies, while supervision intensity has a positive effect. Government subsidies positively affect transition strategies but have a minor impact. Increasing the penalty cap benefits the zero-carbon transition of companies. (3) There is a critical point for carbon trading prices corresponding to changes in zero-carbon transition strategies, providing a basis for companies to decide whether to buy or sell carbon emission trading rights. Additionally, government regulatory changes lag behind the changes in companies’ zero-carbon transition behaviors. The results provide significant insights for government strategy formulation and investment in zero-carbon transition under the carbon quota trading mechanism. Full article

Small and medium-scale enterprises (SMEs) need a platform that actively enables collaboration with research institutions and consultants as SMEs lack the financial resources to conduct independent research. Such a platform will require a verifiable manipulation-free system to enable, execute, and record collaboration activities and to track reputations among the organizations and individuals that use the platform. Blockchain provides an opportunity to build such a collaborative platform by enabling the verifiable recording of the results of the collaborations, aggregating the resulting reputation of the collaborating parties, and offering tokenized incentives to reward positive contributions to the platform. Cryptocurrencies from which blockchain tokens are derived are volatile, thereby reducing business organizations’ interest in blockchain applications. Hence, there is a need to design a self-sustaining valuable token model that incentivizes user behaviours that positively contribute to the platform. This paper explores the application of game theory in analyzing token-based economic interactions between various groups of users in an implemented blockchain-based collaboration platform to design and simulate a token distribution system that provides a fair reward mechanism for users while also providing a dynamic pricing model for the utility value provided by platform tokens. To achieve this objective, we adopted the design science research method, a running case of a blockchain collaboration platform that enables research collaboration, and extensive form games in game theory, first to analyze and simulate token outcomes of users of the collaboration platform. Secondly, the research used a logarithmic model to show the dynamic utility pricing property of the developed token model where the self-sustainability of the token is backed by the availability of an internal resource within the platform. Thirdly, we applied a qualitative approach to analyze potential risks in the designed token model and proposed risk mitigation strategies. Thus, the resulting models and their simulations, such as token distribution models and a dynamic token utility model, as well as the identified token risks and their mitigation strategies, represent the main contributions of this work. Full article

With the advent of big data, the swift advancement of diverse algorithmic technologies has enhanced the transaction efficiency of the e-commerce business. Nevertheless, it is crucial to acknowledge that e-commerce platforms might employ algorithmic technology to enforce differential pricing for various consumers with the aim of maximizing profits, thus infringing upon the lawful rights and interests of consumers. This paper focuses on the algorithmic price discrimination commonly observed on e-commerce platforms. To effectively regulate this behavior, the paper utilizes evolutionary game theory (EGT) to analyze the strategies employed by e-commerce platforms, consumers, and market regulators to achieve stability. This research employs a real-life situation and utilizes parametric simulation to visualize and analyze the process and outcomes of the three-party evolutionary game. The results demonstrate the credibility and feasibility of the article’s findings. Based on our research, we have reached the following findings: During the process of evolution, the strategic decisions made by the game participants from the three parties will mutually impact each other, and various elements exert varying degrees of influence on the strategic choices made by the game participants from each party. Collaborative governance can enable consumers and market regulators to regulate the discriminatory pricing behavior of e-commerce platforms effectively. This article offers valuable insights into the governance of violations in the e-commerce sector based on robust data and model research. Full article

This paper explores the significance of digital governance for sustainable rural development in China, emphasizing the collaborative efforts of village administrative organizations, new agricultural business entities, and peasant households. Utilizing an evolutionary game approach, we examine the decision-making behaviors and stability points of these three entities within the context of rural digital governance. Our analysis is grounded in a mechanism of interest linkage among the stakeholders, with numerical simulations used to assess the impact of key variables and parameters on their evolutionary outcomes. The paper reveals that village administrative organizations are highly sensitive to changes in performance gains, special subsidies, penalty losses, and benefit distribution coefficients. Enhancing these variables can significantly motivate these organizations to engage in digital governance. In contrast, new agricultural business entities and peasant households demonstrate a stronger and more consistent willingness to collaborate, minimally affected by variable changes, which suggests a solid economic and social foundation for rural digital governance in China. Our paper underscores the need for positive incentives and a robust fault-tolerance mechanism to foster collaboration among village administrative organizations. It also highlights the importance of integrating new agricultural business entities into the digital governance framework to promote sustainable rural development. These insights provide valuable theoretical and practical implications for policymakers aiming to enhance the efficacy and inclusivity of digital governance in rural China. Full article

The complexity and number of data streams generated by internal processes exceed the capabilities of most current simulation environments. Consequently, there is a need for the development of more advanced solutions that can handle any number of simultaneous simulations. One of the most promising ideas to address these and other challenges is the concept of a Digital Twin (DT), which refers to a digital representation or a virtual model designed to accurately reflect an intended or actual physical product, system, or process (i.e., a physical twin). As a Digital Twin spans the life-cycle of its physical twin, its development and application can bring considerable benefits to organizations seeking to improve existing processes as well as implement new ones. However, few studies have comprehensively examined the value and benefits of Digital Twins. To fill this gap, this study aims to provide a better understanding of this technology by reviewing the contemporary literature, with a particular focus on the documented case studies, as well as reported business and industrial deployments. The results obtained show that Digital Twins have proven beneficial for maintenance, cost reduction, optimization, simulation performance, monitoring, product life-cycle understanding, assessment validation, performance evaluation, product design, and safety and risk mitigation. In addition, when considering the human factor, DTs can facilitate education and training, team collaboration, and decision making. Undeniably, Digital Twins are a game changer for safer, faster, and more sustainable development. Full article