Search Results (279)

The rapid growth of live e-commerce, a sector valued at over USD 100 billion worldwide, demonstrates its transformative impact on the retail industry, especially in markets like China, where platforms such as Taobao Live and TikTok Shop have markedly altered consumer interaction. This transition is further expedited by Netflix-like entertainment marketing methods, which have demonstrated the capacity to enhance consumer retention by as much as 40%. As organizations adjust to this evolving landscape, it is essential to optimize supply chain strategies to align with these dynamic, consumer-centric environments. This paper examines the complexity of decision-making in live e-commerce supply chains, specifically regarding Netflix-inspired marketing strategies. The primary aim of this study is to design a game-theoretic framework that examines the interactions between producers and online celebrity retailers (OCRs) across different power dynamics. As live commerce integrates digital retail with immersive experiences, businesses must optimize pricing, quality, and marketing strategies in real-time. We present engagement-driven marketing as a strategic variable and incorporate consumer regret and switching costs into the demand function. To illustrate practical trade-offs in strategy, we incorporate a multi-criteria decision-making (MCDM) layer with AHP-TOPSIS, assessing profit, consumer surplus, engagement score, and channel efficiency. The experiment results indicate that Netflix-style marketing markedly increases demand and profit in retailer-led frameworks, whereas centralized tactics enhance overall channel performance. TOPSIS analysis prioritizes high-effort, high-engagement methods, whereas the Stackelberg experiment underscores the influence of power dynamics on profit distribution. This study presents an innovative integrative decision-making methodology for enhancing live-streaming commerce tactics in data-driven and consumer-focused markets. Full article

This paper investigates sustainable decision systems within green E-business models by analyzing how different O2O (online-to-offline) fulfillment structures affect emission-reduction efforts and pricing strategies in a two-tier supply chain consisting of a manufacturer and a new retailer. Three practical sales formats—package self-pickup, nearby delivery, and hybrid—are modeled using Stackelberg game frameworks that incorporate key factors such as inconvenience cost, logistics cost, processing fees, and emission-reduction coefficients. Results show that the manufacturer’s emission-reduction decisions and both parties’ pricing strategies are highly sensitive to cost conditions and consumer preferences. Specifically, higher inconvenience and abatement costs consistently reduce profitability and emission efforts; the hybrid model exhibits threshold-dependent advantages over single-mode strategies in terms of carbon efficiency and economic returns; and consumer green preference and distance sensitivity jointly shape optimal channel configurations. Robustness analysis confirms the model’s stability under varying parameter conditions. These insights provide theoretical and practical guidance for firms seeking to develop adaptive, low-carbon fulfillment strategies that align with sustainability goals and market demands. Full article

With the rapid development of the Financial Internet of Things (FIoT), many intelligent devices have been deployed in various business scenarios. Due to the unique characteristics of these devices, they are highly vulnerable to malicious attacks, posing significant threats to the system’s stability and security. Moreover, the limited resources available in the FIoT, combined with the extensive deployment of AI algorithms, can significantly reduce overall system availability. To address the challenge of resisting malicious behaviors and attacks in the FIoT, this paper proposes a trust-based collaborative smart device selection algorithm that integrates both subjective and objective trust mechanisms with dynamic blacklists and whitelists, leveraging domain knowledge and game theory. It is essential to evaluate real-time dynamic trust levels during system execution to accurately assess device trustworthiness. A dynamic blacklist and whitelist transformation mechanism is also proposed to capture the evolving behavior of collaborative service devices and update the lists accordingly. The proposed algorithm enhances the anti-attack capabilities of smart devices in the FIoT by combining adaptive trust evaluation with blacklist and whitelist strategies. It maintains a high task success rate in both single and complex attack scenarios. Furthermore, to address the challenge of resource allocation for trusted smart devices under constrained edge resources, a coalition game-based algorithm is proposed that considers both device activity and trust levels. Experimental results demonstrate that the proposed method significantly improves task success rates and resource allocation performance compared to existing approaches. Full article

Background: The concept of evidence-based practice (EBP) is globally relevant in current healthcare climates. However, nursing students and teachers often struggle with integrating EBP effectively into a curriculum. This has implications for the way students learn to use evidence for their nursing practice. A new undergraduate EBP module was co-designed with current nursing students and university staff throughout 2023. Underpinning the module was a UDL (universal design for learning) pedagogy consisting of flexible approaches to learning for nursing students which included co-developed videos, co-developed audio podcasts, and co-developed serious games to complement traditional flipped classroom learning. The module commenced in September 2023, running in Year 1 one of a 3-year undergraduate nursing program, and was co-taught by staff and senior students. Methods: A pre/post-test design was used to collect data on student attitude, knowledge, and utilization of EBP. A total of 430 students completed two validated questionnaires, the EBP Beliefs Scale© and EBP Implementation Scale©, before and after the module. Following the post-test, six focus group interviews were also conducted with 58 students to explore how the module informed student nursing practice whilst attending clinical placement during Year 1. A convergent mixed-methods design was employed. Sample attrition occurred (~25%). Effect sizes and 95% confidence intervals were calculated for primary outcomes. Results: Quantitative data was analyzed using paired t-tests and this highlighted statistically significant improvements in attitude, knowledge and utilization of evidence-based practice after learning (p < 0.001). Qualitative data was transcribed verbatim, thematically analyzed, and highlighted three main findings; EBP is my business, EBP positively influenced the care of my patients and EBP has positively impacted my professional development. Conclusions: Partnership with current nursing students in the co-design and implementation of a module about EBP was associated with improvements in student knowledge, attitude and utilization of evidence in practice. These factors are likely to also improve professional competence and ultimately patient care. Full article

In distribution networks, energy storage serves as a crucial means to mitigate power fluctuations from renewable energy sources. However, due to its high cost, energy storage remains a resource whose large-scale adoption in power systems faces significant challenges. In recent years, the emergence of shared energy storage business models has provided new opportunities for the efficient operation of multi-distribution networks. Nevertheless, distribution network operators and shared energy storage operators belong to different stakeholders, and traditional centralized scheduling strategies suffer from issues such as privacy leakage and overly conservative decision-making. To address these challenges, this paper proposes a Nash bargaining game-based optimal energy management and trading strategy for multi-distribution networks with shared energy storage. First, we establish optimal scheduling models for active distribution networks (ADNs) and shared energy storage operators, respectively, and then develop a cooperative scheduling model aimed at maximizing collaborative benefits. The interactive variables—power exchange and electricity prices between distribution networks and shared energy storage operators—are iteratively solved using the Alternating Direction Method of Multipliers (ADMM). Finally, case studies based on modified IEEE-33 test systems validate the effectiveness and feasibility of the proposed method. The results demonstrate that the presented approach significantly outperforms conventional centralized optimization and distributed robust techniques, achieving a maximum improvement of 3.6% in renewable energy utilization efficiency and an 11.2% reduction in operational expenses. While maintaining computational performance on par with centralized methods, it effectively addresses data privacy concerns. Furthermore, the proposed strategy enables a substantial decrease in load curtailment, with reductions reaching as high as 63.7%. Full article

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

This study investigated the social and behavioural impacts of employing a card game designed to support the teaching of business metrics through active peer-to-peer engagement, contrasting with traditional passive lectures. Grounded in Bandura’s Social Learning Theory (SLT), the study used a multiple-methods approach including student feedback, a focus group, and an interview. A novel card game, Metrics Masters©, was played by 390 students across a range of educational levels and settings. The research found that the game effectively introduced and reinforced their understanding of key business metrics, while simultaneously enhancing social interaction, teamwork, and problem-solving among Millennial and Generation Z students. The findings underline the efficacy of game-based learning and its close alignment with the SLT principles of observation, imitation, and social interaction. The theoretical contribution of this paper lies in its explicit application and extension of SLT within the context of business education, illustrating empirically how social interactions facilitated by game-based activities significantly enhance learning outcomes. Furthermore, this paper contributes to educational practice by providing robust evidence that game-based learning methods can effectively address educational challenges heightened by the COVID-19 pandemic, offering actionable strategies for educators aiming to foster both academic and social development among students. Full article

Diversified application scenarios and business models are effective ways to improve the utilization and economic benefits of energy storage systems. In response to the current problems of single application scenarios, high idle rates, and imperfect price formation mechanisms faced by energy storage on the power generation side, a robust two-stage optimization operation strategy for shared energy storage is proposed, taking into account leasing demand and multiple uncertainties, from the perspective of the sharing concept. A multi-scenario application framework for shared energy storage is established to provide leasing services for wind farm clusters, as well as auxiliary services for participating in the electric energy markets and frequency regulation markets, and the participation sequence is streamlined. Based on the operating and opportunity costs of shared energy storage, a pricing mechanism for leasing services is designed to explore the driving forces of wind farm clusters participating in leasing services from the perspective of cost assessment. Considering the uncertainty of wind power output and market electric prices, as well as the market operational characteristics, an optimized operation model for shared energy storage in the day-ahead and real-time stages is constructed. In the day-ahead stage, a Stackelberg game model is introduced to depict the energy sharing between wind farm clusters and shared energy storage, forming leasing prices, leasing capacities, and energy storage pre-scheduling plans at different time periods. In the real-time stage, the real-time prediction results of wind power output and electric prices are integrated with scheduling decisions, and an improved robust optimization model is used to dynamically regulate the pre-scheduling plan for leasing capacity and shared energy storage. Based on actual data from the electricity market in Guangdong Province, effectiveness verification is conducted, and the results showed that diversified application scenarios improve the utilization rate of shared energy storage in the power generation side by 52.87%, increasing economic benefits by CNY 188,700. The proposed optimized operation strategy has high engineering application value. Full article

This study investigates the relationship between diversification and profitability in Macau’s gaming firms, offering quantitative evidence from the world’s largest gambling market. Compared to other major gambling hubs such as Las Vegas, Macau’s gaming companies generate higher revenues but exhibit significantly lower levels of diversification, highlighting an urgent need for strategic expansion beyond gaming. Drawing on governmental data and company financial reports issued from 2010 to 2019, this research employs a combination of case study analysis, linear regression modeling, and bootstrapping techniques. The findings reveal that an increased share of non-gaming business significantly enhances profitability metrics, including net profit margin, return on assets, and a firm’s profit share within the overall gaming market. These results offer valuable implications for the development of corporate strategies, regulatory frameworks, and future academic research. Full article

Diversification and business expansion have become key strategies for modern business development, prompting many large companies to move from singular service models to diversified service strategies, ultimately evolving into comprehensive service ecosystems. Therefore, an in-depth understanding of the evolutionary patterns of service ecosystems is crucial for formulating efficient and effective management strategies and helping enterprises to make informed decisions during the service innovation process. At present, research on the evolution of service ecosystems largely lacks sufficient theoretical underpinning and focuses on the supply–demand relationship relationship, which reduces the credibility of research conclusions and ignores the influence of multiple factors. In this paper, the Lotka–Volterra (LV) model is introduced to service ecosystems and the model as a ternary framework that captures competition–cooperation dynamics among atomic and composite services. In addition, an agent-based computational experiment is designed to integrate adversarial games for decision-making and genetic algorithms for service evolution. Furthermore, the results indicate that moderate competition $\alpha \approx 0.5$ among atomic services maximizes composite service innovation and excessive cooperation $\alpha \to 0$ stifles it. Full article

The shipping industry employs various strategies for outsourcing between freight forwarders and ocean shipping (OS) companies, including consignment and turnkey strategies. Freight forwarders often have a competitive edge in cargo canvassing, but many OS companies still engage in this practice. With China’s new policy liberalizing coastal shipping rights, OS companies are presented with two coastal shipping tactics: coastal transition and coastal piggyback (CPB). The interaction between OS companies and freight forwarders in the context of this policy change raises important strategic questions. This study examines the coastal piggyback business model within a three-tier shipping supply chain, involving a freight forwarder and two competing OS companies (OS1, which does not qualify for the coastal piggyback policy, and OS2, which does) using game theory. Through game analysis, we find that CPB may represent a myopic equilibrium. Specifically, when the freight forwarder’s cargo-canvassing capability is higher than a certain threshold, CPB is not advantageous for OS2’s market entry. Conversely, if the freight forwarder’s capability is relatively low, both OS companies can benefit from CPB. Additionally, OS companies enter the market when entry costs are low and avoid it when costs are high. With moderate costs, their strategy depends on the other OS company’s actions. Interestingly, the forwarder can deter market entry by enhancing cargo canvassing and adjusting outsourcing tactics. Notably, OS companies’ market entry may boost the forwarder’s payoffs in a horizontally competitive supply chain. Furthermore, this research examines the economic sustainability of coastal piggyback policy by analyzing its impacts on the profitability of all supply chain members. Full article

As a carbon reduction tool that discloses the green quality information of products, a unified standard for the evaluation and identification of carbon labeling has not yet been established. Given the diverse market environments and the different types of carbon labels, selecting an appropriate carbon label can create greater value for both the businesses and the society. This paper constructs a game model involving green and non-green firms to explore the heterogeneous firms’ carbon label choices and green decisions under two market structures. Using a numerical comparative analysis, it examines the social value of carbon labeling schemes in various scenarios. The study finds that (1) enhancing consumer environmental awareness (CEA) and competition intensity contributes to economic and social benefits, while an increased ambiguity in carbon labeling may suppress system efficiency; (2) carbon labeling schemes always generate profits for green firms but do not necessarily benefit non-green firms; (3) in a monopolistic competition market, self-certified labeling (SCL) is more beneficial for improving social welfare, whereas the opposite holds in an oligopolistic competition setting, but in both market structures, third-party certified labeling (TCL) maximizes environmental benefits; and that (4) for the same type of carbon label, environmental improvements vary significantly across market structures, whereas firms’ carbon label choices have a relatively minor impact on environmental benefits. This research provides valuable managerial insights for firms’ green decision-making and carbon label standard selection in different markets. Full article

Shore power represents one of the principal solutions for the green transformation within the port industry. It significantly aids in the reduction in carbon emissions from vessels while they are berthed in port, yet often necessitates an effective promotional strategy to foster its installation and utilization. Stakeholders including port authorities, ship operators, and local governments all play a crucial role in achieving this objective. This paper employs a tripartite evolutionary game model in conjunction with a system dynamics model to investigate the evolutionary responses of stakeholders when policy tools are applied, and consequently, to elucidate the dynamics of strategy effectiveness. In this context, six business scenarios are developed to ascertain the potential impacts of implementing subsidies and carbon taxes. The findings demonstrate that any singular strategy, whether a subsidy or a carbon tax, is inadequate for the successful advancement of shore power; on the contrary, a government-led, integrated, and dynamic reward–punishment strategy aids in stabilizing the inherent fluctuations within this game process. Moreover, the initial willingness of ship operators exerts a considerably greater influence than that of the other two stakeholders. 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

In the context of globalized and complex supply chains, supply uncertainty occurs frequently. To reduce dependence on suppliers, retailers often consider holding strategic inventory and introducing private brands. To explore the relationship between private brands and strategic inventory strategies, and to determine the optimal strategic decisions, this paper constructs a two-stage supply chain model. Using game theory methods, we calculate the equilibrium outcomes of the supply chain under two scenarios: one with only national brands and the other with the introduction of private brands. The main findings are as follows. First, we identify the optimal decisions for both suppliers and retailers in each scenario. The influencing factors include perceived quality, inventory costs, and supply stability. Second, we find that there are constraints for retailers to activate strategic inventory, but these constraints are less restrictive when private brands are introduced. Finally, introducing private brands benefits retailers in implementing strategic inventory, although the extent of this impact depends on the conditions under which the strategic stockpile is implemented. These findings fill the gap in the existing literature on the impact of private brand introductions on strategic inventory under supply uncertainty and highlight valuable implications for business decision-makers. Full article