Search

Co-opetition plays an important role in decision-making of the supply chain. This paper investigates an electric vehicle battery (EV battery) supply chain containing one manufacturer and two competing retailers. We construct three retailer co-opetition models and characterize equilibrium results using differential game theory and Bellman's optimality principle. By comparing and analyzing the wholesale price, retail prices, technology investment and quality level of batteries, we explore the influence of retailer co-opetition on supply chain dynamic decisions. The results show that: (1) the enhancement of the technology investment will lead to the improvement of each decision; (2) the cooperation between one retailer and the manufacturer benefits the supply chain extremely; (3) the cooperation between two retailers is detrimental to the consumer utility. [ABSTRACT FROM AUTHOR]

As high-speed rail (HSR) and air transportation developed rapidly in the last decade, their coopetition and interactional relationship has reshaped China's urban networks. Based on HSR and flight schedule data from 2009 to 2019, this paper constructs a weighted network to compare China's urban networks and their evolution, and employs machine learning to investigate the potential determinants. The results indicated that both networks tend toward polarization in the overall distribution and that the structure of urban networks under HSR networks is more hierarchical. That of HSR networks gradually forms a corridor structure along the trunk lines, while that of airline networks mainly shows a diamond spatial structure with Beijing, Shanghai, Guangzhou, and Chengdu as the cores. As for the evolution of urban networks, geographical factors, per capita GDP, and the tourism function of cities have more important impacts on that of HSR networks, while the network's topological structure and education resources have a greater impact on that of airline networks. Some socioeconomic attributes, such as urban administrative level, population, and the proportion of tertiary industry, have similar and limited influences on the two networks. • The paper constructed a comparative analysis on the evolution of China's urban networks during the last decade. • Employing machine learning to investigate the potential determinants. • The study examined the distinct attributes of the evolution and structure of high-speed rail and airline networks. • The study contrasts the determinants influencing the evolution of high-speed rail and airline networks at the city level. [ABSTRACT FROM AUTHOR]

Energy trade has been a hot topic in countries participating in the Belt and Road Initiative (BRI), while cooperation and competition are two elementary modes of international trade. This study examines the coopetition relations in terms of renewable energy trade among BRI countries by constructing a two-layer network model for 1996–2018. We examined 65 BRI countries and indicated that the interplay between intrinsic and network dynamics features either cooperation or competition. First, the evolutionary patterns between cooperation network and competition network are different but with a declining gap. Besides, the BRI policy promotes cooperation more effectively than competition. Second, competitiveness and cooperativeness are heterogeneously distributed across countries and influential cooperators are not necessarily top competitors. Notably, BRI has reinforced China's competitive position. Third, the intralayer and interlayer network dissimilarity are integrated to provide insights that numerous countries play dual roles of competitor and collaborator, while cooperation-oriented competition is more conducive. Finally, policy recommendations are proposed so that sustainable renewable energy supply can be attained. [ABSTRACT FROM AUTHOR]

We propose the rule engine of expert system consists of quantum algorithm in two folds: quantum mechanics and quantum computation. The simulation of quantum computation-based coopetition leads to explain the external economics scale (EES) and disruptive innovations of coopetition by the use of Brynjolfsson–Hitt computing productivity function as a real context of the proposed expert system. We show the quantum coopetition computation of Brynjolfsson–Hitt system on a global polyadic coopetition of globotics upheaval. The Schrödinger and Heisenberg pictures are discussed: the Schrödinger picture results the energy of coopetition environment, while the Heisenberg picture provides production function transformation due to quantum effect of production variables. The Composite Production Function is constructed through quantum algorithm, and the energy of member coopetition depends on quadratic of elasticity and production variables. It is shown that the composite production function of a coopetition depth is ≈ O ( (n + δ) ∑ i β i ) , where it depends on the number of production function variables (n), the number of perturbation variables (δ), and the output elasticities of production function variables ( ∑ i β i > 1). Our findings suggest that the model has potential implementation for the expert system of coopetition on globotics upheaval era. • Quantum based-rule engine of expert system. • Quantum game of Adam and Barry coopetition game. • Quantum circuit of coopetition. • Schrödinger and Heisenberg pictures of coopetition environment. [ABSTRACT FROM AUTHOR]

• Developed a model for Mobility-as-a-Service platform equilibrium. • Captures on-demand mobility, coopetition between operators, user equilibrium. • Algorithm converges to global optimum when outcomes are non-empty. • Stability guarantee is ensured in algorithmic design that may introduce subsidy. • Tests on 748-link network can output firm market entry, inequities, and congestion. Mobility-as-a-Service (MaaS) systems are two-sided markets, with two mutually exclusive sets of agents, i.e., travelers/users and operators, forming a mobility ecosystem in which multiple operators compete or cooperate to serve customers under a governing platform provider. This study proposes a MaaS platform equilibrium model based on many-to-many assignment games incorporating both fixed-route transit services and mobility-on-demand (MOD) services. The matching problem is formulated as a convex multicommodity flow network design problem under congestion that captures the cost of accessing MOD services. The local stability conditions reflect a generalization of Wardrop's principles that include operators' decisions. Due to the presence of congestion, the problem may result in non-stable designs, and a subsidy mechanism from the platform is proposed to guarantee local stability. A new exact solution algorithm to the matching problem is proposed based on a branch and bound framework with a Frank-Wolfe algorithm integrated with Lagrangian relaxation and subgradient optimization, which guarantees the optimality of the matching problem but not stability. A heuristic which integrates stability conditions and subsidy design is proposed, which reaches either an optimal MaaS platform equilibrium solution with global stability, or a feasible locally stable solution that may require subsidy. For the heuristic, a worst-case bound and condition for obtaining an exact solution are both identified. Two sets of reproducible numerical experiments are conducted. The first, on a toy network, verifies the model and algorithm, and illustrates the differences local and global stability. The second, on an expanded Sioux Falls network with 82 nodes and 748 links, derives generalizable insights about the model for coopetitive interdependencies between operators sharing the platform, handling congestion effects in MOD services, effects of local stability on investment impacts, and illustrating inequities that may arise under heterogeneous populations. [ABSTRACT FROM AUTHOR]

The phenomenon of transportation service providers (TSPs) engaging in both competition and cooperation, commonly referred to as coopetition, has become increasingly prevalent in the transportation market. This is driven by the rapid advancements in information technology and sharing economy. In practice, competitive TSPs can engage in a resource exchange scheme to share their resources to improve their service quality. However, such a resource exchange scheme may not be sustained since the service prices and profits will be further changed due to the competition in the end market. This study proposes a two-stage sequential-move game to characterize the coopetition problem between TSPs, wherein the first-stage resource exchange problem is modeled with a Nash bargaining game, and the second-stage pricing problem is modeled with a non-cooperative Nash game. Different from prior studies, our model incorporates the supply–demand congestion effects and the asymmetric bargaining power of TSPs. The subsequent impacts on social welfare, TSPs, and end users are investigated. Analytical results show that only when the unit price of the exchanged resources decreases in the exchanged resource quantity will the resource-exchange scheme succeed. Furthermore, we find that TSPs prefer to leave some "buffer zone" in between to avoid fierce competition with price wars. • Integrate non- and cooperative game-theoretic methods to characterize the strategic coopetition among TSPs. • Quantify the system-wide impact of congestion effects and asymmetric bargaining power. • The end market is partially covered. • The resource price decreases in the transaction volume to sustain the resource exchange scheme. [ABSTRACT FROM AUTHOR]

• Competition and coopetition of airline, intercity bus, and entrant HSR operators. • The main driver for the operators' pricing competition is identified. • Non-pricing strategies may be necessary for the incumbent operators' survival. • Short-term government policies may not guarantee the passengers' full satisfaction. We investigate pricing competition between passenger transportation modes in a transportation market by using a game-theoretic approach. Airplane and intercity bus operators are considered as incumbent; while a High-Speed Rail (HSR) operator decides on whether or not to enter the market. If the incumbent operators evaluate the entrance threat of HSR as serious, they have two alternatives: a barrier pricing strategy (BPS) to deter its entrance, and an accommodation pricing strategy (APS). Their interaction involves two competitive and cooperative aspects, called the coopetition interaction. Moreover, we extend the analysis to a real-world situation in which a government, as a social welfare maximizer, intends to certify and support one operator out of two candidate HSR operators. Our analyses reveal that: (a) the passengers' heterogeneity (with respect to their perceptions on the operators' quality of services) is the main driver for pricing competition between the three operators. (b) Under certain conditions, implementing a BPS is not only precluded for the incumbent operators, but also their pricing strategies cannot even guarantee their survival in the market. To address this issue, we suggest the incumbent operators adopt non-pricing strategies. Nevertheless, an incumbent operator may freely ride on the other ones' non-pricing strategy. (c) Under a short-term (long-term) planning horizon, the government should specifically concentrate on compensating for the HSR operating cost (procurement cost of rolling stock). (d) In contrast to the short run, government expenses and the HSR's profit exploitation provide a strong foundation for the passengers' full satisfaction in the long run. [ABSTRACT FROM AUTHOR]

• Studied data sharing within a transit market with externality effects. • Data availability modeled with Bayesian game with noncooperative frequency setting. • Data sharing decisions modeled as partitions in a coalitional structure. • Test results on competitive services, complementary services, Nguyen-Dupuis network. • Results suggest voluntary data-sharing or require cooperation in market-wide sharing. In this study, various forms of data sharing are axiomatized. A new way of studying coopetition, especially data-sharing coopetition, is proposed. The problem of the Bayesian game with signal dependence on actions is observed; and a method to handle such dependence is proposed. We focus on fixed-route transit service markets. A discrete model is first presented to analyze the data-sharing coopetition of an oligopolistic transit market when an externality effect exists. Given a fixed data sharing structure, a Bayesian game is used to capture the competition under uncertainty while a coalition formation model is used to determine the stable data-sharing decisions. A new method of composite coalition is proposed to study efficient markets. An alternative continuous model is proposed to handle large networks using simulation. We apply these models to various types of networks. Test results show that perfect information may lead to perfect selfishness. Sharing more data does not necessarily improve transit service for all groups, at least if transit operators remain noncooperative. Service complementarity does not necessarily guarantee a grand data-sharing coalition. These results can provide insights on policy-making, like whether city authorities should enforce compulsory data-sharing along with cooperation between operators or setup a voluntary data-sharing platform. [ABSTRACT FROM AUTHOR]

• Novel devices must meet rigorous thresholds for clinical efficacy and safety. Some innovations succeed more than others. • Variations in the success trajectory of innovations cannot be easily explained by device efficacy alone. • The key to successful device development lies in 2 concepts of business theory: disruptive innovation and co-opetition. • We propose that initial randomized clinical trials of newer devices be conducted on these 2 building blocks. • Our construct places interventions in a Venn diagram depicting disruptive innovation, co-opetition and randomized trials. • Our construct has significant implications for industry, regulatory bodies and clinical trialists. [ABSTRACT FROM AUTHOR]

In large-scale group decision-making (LSGDM), the complexity of the decision-making environment highlights the significance of co-opetition in reaching a consensus among decision-makers (DMs) with diverse knowledge. Thus, this paper proposes an ordinal–cardinal consensus model for three-way LSGDM that considers co-opetition relationships among DMs. Specifically, we first improve the ordinal consensus measure and propose the ordinal–cardinal consensus measure by analyzing the co-opetition relationships. Then, utilizing the constructed trust consensus network, DMs are categorized into subgroups, and spokespersons are selected from each subgroup. Further, we establish the consensus identification rule using the three-way decision (TWD) theory and design a personalized feedback regulation mechanism for distinct relationships among subgroup representatives based on ordinal consensus. Also, an example of economic revitalization is employed to illustrate the feasibility of the proposed approach. Finally, the benefits and values of the proposed method are highlighted by simulation and comparative analysis. • Propose an ordinal–cardinal consensus measure considering co-opetition relations. • Construct a trust consensus network for clustering. • Present a consensus identification mechanism based on three-way decision. • Design a bidirectional regulatory mechanism covering co-opetition relations. • Provide a new framework for large-scale group decision making. [ABSTRACT FROM AUTHOR]

This study explores whether coopetition enhances scale determinants for SMEs, focusing on a case study in the Portuguese Ornamental Stone sector. The findings show that transitioning to coopetition networks positively impacts scale determinants in this sector. These improvements highlight coopetition's potential to drive operational efficiency, resource optimization, and market responsiveness, aligning with Sustainable Development Goals (SDGs) 8, 9, and 12. However, the study's limitations include a specific focus on Portuguese SMEs and a limited data collection period, indicating the need for broader and longer-term research. Future research should extend to different sectors and regions, incorporate a broader range of KPIs, and consider external factors affecting coopetition outcomes. This would provide a more comprehensive understanding of coopetition's role in fostering sustainable growth and innovation in SMEs. This research contributes to theory by leveraging S-D Logic and open innovation to enhance coopetition, showcasing their practical application in SMEs. [ABSTRACT FROM AUTHOR]

At its November 2018 annual meeting, the Roundtable on Sustainable Palm Oil (RSPO) approved a new version of its foundational rules that advocates argued made it a zero-deforestation standard. Using a combination of over 160 key informant interviews and archival analysis, we argue that actors in the RSPO orbit made the High Carbon Stock Approach - a new method for defining forest boundaries that features heavy use of satellite data - attractive by blending cooperative and competitive strategies in a pattern known as coopetition. Critical stakeholders pushed leading companies into a competition for legitimacy that spurred innovations outside of the Roundtable setting. In turn, however, these firms also used relationships established through the RSPO Roundtable - cooperating - to elaborate guidelines and tools for defining forest areas, pursuing supply chain traceability and engaging in supplier transformation. This cooperation helped zero-deforestation strategies to emerge outside the organization. In response, stakeholders with sunk investments in RSPO membership reincorporated those external tools into the standard by framing them as consistent with the institution's fundamental logics. This case provides a compelling example of how coopetition can lead to norm emergence in a contentious governance arena, allowing a combination of internal and external actors to steer institutional development. We argue that this strategy could be employed to stimulate increased rigor in environmental standards. [ABSTRACT FROM AUTHOR]

The relationship between innovation and economic development has been extensively analyzed, highlighting how the national environment influences business innovation dynamics. In this context, the concept of the Triple Helix is introduced, identifying universities, firms, and governments as the main drivers of innovation development. The main objective of this paper is to deepen the understanding of the impact that cooperation and coopetition between these actors have on innovation dynamics. To achieve this, we compare two EU countries, focusing on product innovation following the Schumpeterian idea that economic development is driven by the introduction of new products. Data from 31,105 Spanish and 8224 Portuguese firms from the Community Innovation Survey (CIS) 2018 were analyzed. The results confirm that these collaborative dynamics have a positive impact on product innovation. Furthermore, human resource management is shown to be a fundamental aspect in driving innovation processes within an organization. The national context has positioned itself as a determining factor in innovation dynamics. In particular, in this study, Portuguese companies demonstrate a greater positive impact of innovation in human resources on product innovation compared to Spanish companies. The strength of this research lies in the comparative framework established between the two countries, allowing for the detection of the influence of governments, universities, and other agents in the collaborative processes that drive innovation dynamics in companies. The model proposed in this research could be extended to compare other countries, helping to explain the relationship between innovation levels and the influence of the country effect on their economic development. • This research suggests that collaborative R&D improves HRM and product innovation, crucial aspects for company success. • The study compares Spain and Portugal, showing geographic location affects innovation differently in each country, • The article highlights the crucial role of universities and governments in innovation , following the Triple Helix model. • The concept of coopetition is key to fostering innovation and the efficient use of resources. • The study advocates for open, collaborative innovation models over traditional, isolated internal processes. [ABSTRACT FROM AUTHOR]

Dynamic tensile (micro-spallation) fracture and subsequent recompression in a molten state is the key physical process for metallic materials undergoing multiple intense dynamic loadings. However, there still lacks in-depth analysis of the complete evolution process from damage accumulation to recompression, as well as the influence of damage history on subsequent deformation and fracture. In the present work, the mechanism of cooperative competition evolution between the melt-phase and voids has been proposed as a new perspective to investigate damage evolution. Various important physical phenomena discovered in larger-scale MD simulations of molten aluminum can be self-consistently explained according to the proposed mechanism, such as the rate-dependence of spall strength and the pressure oscillation. The recompression-after-damage and second fracture process are discussed in detail to analyze the damage history effect. Under the present framework, two theoretical models have been proposed from the perspective of void and melt-phase evolution, respectively. The proposed models agree well with the simulation results and provide a comprehensive understanding of the damage evolutionary characteristics. [Display omitted] • The cooperative competition evolution mechanism between melt-phase and voids during micro-spallation and recompression is revealed. • The influence of damage history on subsequent deformation and fracture processes is analyzed via MD. • A theoretical framework is proposed for damage description including two models from the view of void and melt-phase evolution, respectively. [ABSTRACT FROM AUTHOR]

The efficient collection of spent batteries is important for the recycling of power batteries and the sustainable advancement of electric vehicles (EVs). This study introduces and evaluates 14 power battery collection models, encompassing single-channel, dual-channel, and triple-channel scenarios, which encapsulate the dynamics of competition, cooperation, and co-opetition among key stakeholders. Employing Stackelberg game theory and simulation analysis, this study assesses the economic and environmental benefits of these models, with particular attention to the impact of consumer environmental awareness and competition intensity. Findings indicate that the collaborative collection model involving battery manufacturers, EV companies, and third-party recyclers (Model MVTP) delivers superior economic outcomes, with benefits ranging from 20.3 to 20.31 billion RMB. Meanwhile, the competitive three-party collection model (Model M-V-TP) stands out for its environmental benefits, achieving collection rates between 14.95 % and 25.65 %. Intriguingly, while competition intensity does not influence the outcomes of single-channel models, it diminishes both economic and environmental benefits in dual- and triple-channel scenarios. Moreover, enhanced consumer environmental awareness consistently elevates the economic benefits of all models, though its effect on environmental benefits varies—enhancing collection rates in single- and dual-channel models but detrimentally impacting the triple-channel model. • Construct 14 battery collection models covering single, dual, and triple channels. • Examine potential competition, cooperation, and co-opetition among participants. • Compare the economic and environmental benefits of different collection models. • Explore the impact of consumer environmental awareness and competition. [ABSTRACT FROM AUTHOR]

In an attempt to find the key factors influencing the co-opetition relationship between China and "Belt and Road" countries, we firstly analyzed the status quo of the renewable energy trade between the two parties. Then, we constructed a dynamic game model, taking China and the "Belt and Road" countries as two players of the game. Next, we estimated the influence of different strategies to be adopted by China and the "Belt and Road" countries based on the model evolution results under different scenarios. Results show that: (1) The strategies to be adopted by both sides (players) for renewable energy product trade in the dynamic game process depend on the differences between their trade costs and additional benefits; (2) Whether China and the "Belt and Road" countries can achieve a win-win situation in their trade cooperation depends on the additional benefits obtained by the two sides (players) due to the additional benefits from cooperation and external benefits of the "Belt and Road" countries through technology spillovers, trade costs and the losses brought by the game strategies of both players, i.e., when one player adopts a cooperation strategy while the other takes a competition strategy; and (3) There is an extra income distribution coefficient in the co-opetition relationship between the two parties in the renewable energy trade, which will maximize the probability of "cooperation strategy" to be adopted by both sides. Finally, we put forward policy implications based on the above findings. [ABSTRACT FROM AUTHOR]

The development of dry ports has reshaped the international freight shipping market, introducing both competition pressure (i.e., the common hinterland) and cooperation opportunities (sea-rail intermodal) for seaports. This is more evident in China with the development of the China Railway Express. Unlike dry ports, seaports are more vulnerable to climate change-related disasters, calling for investment in adaptation measures. This paper examines how co-opetition with the dry port affects seaport adaptation investment using a two-stage game-theoretical economic model. Results indicate that cooperation leads to more seaport adaptation investment, while competition results in reduced investment. When compared to the social optimal level of adaptation investment, the seaport tends to under-invest (over-invest) when the cooperation (competition) market size is larger. We also analyze how government subsidies in the seaport's adaptation help achieve optimal social adaptation and how the Knightian uncertainty of the disaster occurrence affects seaport adaptation investments. The relevant policy implications are also discussed. [ABSTRACT FROM AUTHOR]

In a competitive e-hailing market, each participating platform can only utilize a portion of the total demand (passengers) and supply (drivers), in which this fragmentation leads to market inefficiencies. Therefore in this study, we propose a decentralized dynamic cooperation mechanism, inspired by capacity-sharing strategies, between two platforms to mitigate market fragmentation. With the proposed mechanism, the platforms can offer to (i) refer their passengers and (ii) temporarily (for a single trip) lease idle vehicles to the other platform, at varying optimized prices. In its essence, whenever a platform is under-supplied while the other platform is over-supplied in a localized area, the proposed mechanism could help the platforms bridge their supply and demand. The proposed mechanism is constructed as an optimization problem incorporated in the batch-matching algorithm. We test the proposed cooperation mechanism in a disaggregated dynamic model. We consider multiple scenarios, which include symmetrical and asymmetrical duopolies. The performance of the proposed cooperation mechanism is compared to equivalent non-cooperative duopolies and equivalent monopolies. We show that the proposed cooperation mechanism leads to simultaneous improvements in all performance indicators for all stakeholders (passenger pickup time, passenger cancellations, driver income, and platform profitability) compared to equivalent non-cooperative duopolies. Additionally, the proposed cooperation mechanism is shown to be especially effective as the asymmetry between the duopoly increases. • A decentralized dynamic cooperation mechanism for capacity-sharing in e-hailing duopoly markets. • The platforms can refer their passengers and lease idle vehicles (for a single trip) to the other platform at varying optimized prices. • The proposed mechanism is formulated as an optimization problem incorporated in the batch-matching algorithm. • The cooperation mechanism leads to improvements in all performance indicators for all stakeholders compared to non-cooperative duopolies. • The mechanism is effective as the asymmetry between the duopoly increases. [ABSTRACT FROM AUTHOR]

We explored the problem about function approximation error and complex mission adaptability in multi-agent deep reinforcement learning. This paper proposes a new multi-agent deep reinforcement learning algorithm framework named multi-agent time delayed deep deterministic policy gradient. Our work reduces the overestimation error of neural network approximation and variance of estimation result using dual-centered critic, group target network smoothing and delayed policy updating. According to experiment results, it improves the ability to adapt complex missions eventually. Then, we discuss that there is an inevitable overestimation issue about existing multi-agent algorithms about approximating real action-value equations with neural network. We also explain the approximate error of equations in the multi-agent deep deterministic policy gradient algorithm mathematically and experimentally. Finally, the application of our algorithm in the mixed cooperative competition experimental environment further demonstrates the effectiveness and generalization of our algorithm, especially improving the group's ability of adapting complex missions and completing more difficult missions. [ABSTRACT FROM AUTHOR]

This paper concentrates on the adaptive neural finite-time bipartite consensus tracking of nonstrict feedback nonlinear coopetition multi-agent systems with input saturation. A novel consensus tracking method combined the adaptive neural control with the finite-time command filtered backstepping is proposed. During each backstepping process, the Radical Basis Function Neural Network (RBF NN) is used to approximate the unknown nonlinear dynamics and the finite-time sliding mode differentiator (FTSMD) is used to obtain intermediate signals and their derivative. Moreover, the filtering errors are eliminated by using error compensation signals. By using the finite-time Lyapunov stability theory, it can be proved that the bipartite consensus tracking errors can converge to a sufficient small region of the origin in finite-time and all signals in the closed-loop systems are bounded in finite-time although there exists the input saturation. The effectiveness of the proposed method is shown by simulation results. [ABSTRACT FROM AUTHOR]

• We study work-related advice networks among competitors in three high-tech clusters. • Specifically, we explore social mechanisms under perceived competitive conditions. • We analyze various network patterns of coopetition by taking a multi-level approach. • Managers actively seek out advice with direct competitors within clusters. • There are tendencies towards reciprocal advice-seeking among competitors. Collaboration with direct competitors is a valuable, yet risky, strategy that might pave the way for competitive advantages. Thus far, we have lacked a detailed understanding of how competitive relations between firms shape collaborative relations between their managers, and consequently the structural interdependencies at both levels. The primary objective of this study is to understand the multi-level structure underlying the ambiguous relationship of coopetition, a state of simultaneous collaboration and competition. Hence, we investigate the influence of perceived inter-firm competition on interpersonal knowledge flows among managers within three high-tech clusters by applying multi-level exponential random graph models to network data. Our results reveal that the interpersonal exchange of advice and information depends strongly on the inter-firm competitive structure and that competitive structures shape these interpersonal exchanges in different ways. Thereby, our research demonstrates that managers utilize asymmetries by means of perceived competitive relations to seek work-related advice and information from their competitors and that stronger forms of competition are significant, but not insuperable, obstacles to the exchange of knowledge. [ABSTRACT FROM AUTHOR]

This paper addresses the bipartite synchronization problem of coupled inertia memristor-based neural networks with both cooperative and competitive interactions. Generally, coopetition interaction networks are modeled by a signed graph, and the corresponding Laplacian matrix is different from the nonnegative graph. The coopetition networks with structural balance can reach a final state with identical magnitude but opposite sign, which is called bipartite synchronization. Additionally, an inertia system is a second-order differential system. In this paper, firstly, by using suitable variable substitutions, the inertia memristor-based neural networks (IMNNs) are transformed into the first-order differential equations. Secondly, by designing suitable discontinuous controllers, the bipartite synchronization criteria for IMNNs with or without a leader node on coopetition networks are obtained. Finally, two illustrative examples with simulations are provided to validate the effectiveness of the proposed discontinuous control strategies for achieving bipartite synchronization. [ABSTRACT FROM AUTHOR]

This paper discusses the effects of the cooperation among terminal operators in a single port as a part of their coopetition strategy in order to increase overall port competitiveness by minimizing vessel traffic congestion and berthing delays at terminals. A mixed-integer programming model is formulated incorporating game-theoretical decision-making, and then tested with the Port of Colombo, Sri Lanka. The results show that depending on the terminals' objectives, namely "minimizing total penalty cost" and "maximizing total profit," cooperation among terminals in the operation stage reduces berthing delays and increases terminal utilization than in the status quo, where terminals do not cooperate in the operation stages. This paper discusses policy recommendations to increase the effectiveness of vessel transfers, while also considering the port authority's policies toward enforcing penalty charges for berthing delays and collecting terminal fees from concession terminals. • Proposes coopetition to increase port competitiveness by minimizing berthing delays. • Analyzes the effect of cooperation among terminals with a vessel transfer policy. • Formulates a mixed-integer programming model with game-theoretical decision-making. • Different results are based on terminal fee collection policy for transfer vessels. • Vessel transfers and berthing delays are changed when terminal objective changes. [ABSTRACT FROM AUTHOR]

This study uses the lens of competitive dynamics to examine the coopetition process, which combines both cooperation and competition, employed by Qualcomm within the SoC (System on a Chip) design market related to smart devices. Qualcomm succeeded in developing the first SoC, which integrated GPS (Global Positioning System) and other software, and during the process of developing mobile chips has simultaneously cooperated and competed with competitors. In particular, Samsung, which began as a customer of the firm, has since become its competitor. By conducting descriptive case analysis, this study shows a coopetition process in the SoC industry and supplemented a coopetition study with the actual exemplary coopetition case. [ABSTRACT FROM AUTHOR]

This paper studies how technology suppliers can optimally design licensing contracts when there is incomplete information on the licensee's demand potential for the product in a high-technology supply chain. A licensing contract typically contains an up-front payment and royalties on product sales. The licensor decides to license one technology to a licensee, which designs products based on the supplier's technology and outsources the product manufacturing to a competitive downstream manufacturer. We apply principal-agent models to formulate the licensor's contracting problem while considering the transparency of the licensing royalty and find that under demand information asymmetry, the optimal contract structure changes with the demand potential. More specifically, both the separating and pooling strategies can be the optimal strategies for the licensor under the observable contract case. Conversely, under the unobservable case, only the separating strategy is the optimal licensing strategy. And the licensor can always charge zero royalty to a high-type design firm regardless of the menu strategy or the single contract. Furthermore, we examine the effect of licensing royalty transparency on licensing decisions and firms' profits and highlight the effect of downstream competition on the licensor's profit. Our results show that the licensor can be better off in the observable contract case. By contrast, the design firm may be better off in the unobservable contract case. We provide a rationale for the licensing contract design under demand information asymmetry and further shed light on the choice between public and secret licensing terms. [ABSTRACT FROM AUTHOR]

With the implementation of the renewable energy quota system and the development of the green certificate market, the diversification of cross-region trading subjects has brought about the problem of complicating the competition and cooperative relationship between multiple subjects. This problem makes it difficult to balance the conflict of interests of multiple participating subjects in green certificate transactions, and reduces the enthusiasm for trading. To this end, this paper proposes a multi-participant decision model of cross-regional green certificate trading behavior that takes into account the uncertainty of renewable energy generation. In the model, in order to explore the potential full set of strategies of the participating subjects, the cooperative game theory is utilized to analyze the complex interaction between multiple participating subjects in the cross-regional transaction, and the cooperative game model based on green certificates is established. As the participating subjects' information about other participants and their knowledge of the game environment are limited, the decision-making behavior is uncertain. In order to more reasonably portray the subject's game behavior in the actual decision-making scenario and to solve the defect that the traditional evolutionary game model can not reflect the influence of uncertain factors, we use the stochastic evolutionary game theory to dynamically deduce the cooperative strategies of the participating subjects under the limited rationality, and at the same time, introduce the strategy influencing factors to explore the dependence relationship between strategies. In addition, in order to cope with the impact of power generation uncertainty on cross-regional trading and to solve the defects of distributionally robust fuzzy set construction which is subjective and only for the analysis of uncertainty in a single time section, it is proposed to use Bayesian multivariate nonlinear model and mixed-effects model to construct probability distribution fuzzy sets of wind and light power generation uncertainty on the basis of distributionally robust theory. Finally, based on the arithmetic example, the cooperative strategy of multi-participants in cross-regional transactions under finite rationality is deduced, and the impact of uncertainty factors on the cooperative strategy is analyzed. • Bayesian theory-based distributed robust method solves the defects of fuzzy set construction. • Deducing the cooperative behavior of the subject under the environment of limited rationality. • Extending a deterministic game system to a stochastic game system by introducing Gaussian white noise. • Introducing strategy influence factors to explore the interaction effects between strategies. [ABSTRACT FROM AUTHOR]

• Terminal operators in one port cooperate to defeat competition from external ports. • Terminal operators in one port compete with each other to enhance individual terminal performance. • Coopetition allows overcoming the trade-off between cooperation and competition. • In coopetition, operator incentives change depending on the mix of ownership types. • If authorities support coopetition, terminal operators achieve a win-win strategy. An intra-port coopetition model is proposed, which simultaneously characterizes both competition and cooperation among terminal operators in a port when competing with operators from external ports. Terminal operators make cooperative efforts to increase port competitiveness, while simultaneously making competitive efforts for price adjustment, cost and/or time reduction at individual terminals. Numerical analysis is performed considering private and public terminals characterized by different profit and social surplus maximization objectives. The results show that operator incentives change depending on the combinations of terminal ownership, and the private terminal tends to behave as a free rider in a public-private combination. [ABSTRACT FROM AUTHOR]

Graphical abstract Highlights • Cu-SAPO-34 with 2 wt% of copper is effective in SCR in quasi -real conditions. • Cu-CHA model catalyst with copper inside the framework is hydrothermal stable. • NH 3 oxidation and nitrate decomposition are hindered under H 2 O + CO 2 atmosphere. • Hydrated-carbonated copper species are responsible for SCR activity improvement. Abstract Cu-SAPO-34 materials with 2 wt% of copper synthesized in one pot with all the copper inside the framework are hydrothermally stable. Copper oxide species were not detected by XRD after thermal and hydrothermal aging at 750 °C. CO 2 and H 2 O molecules are retained on Cu-SAPO catalyst and are related to CO 2 adsorption aided by water involving the Cu-species. Copper species coordination is modified by the reaction atmosphere and the species are directly involved in the SCR-process. A decrease in the ammonia storage capacity in the presence of water has been justified due to the cooperative competition between the ammonia and water adsorption and/or CO 2 carbonation over the same sites. Higher coordinated Cu species localized inside of CHA-framework, up to a loading close to 4% with this methodology, are highly efficient in the removal of NO x by reaction with ammonia, in the presence of oxygen, water (1.5%) and CO 2 (0.3%) as reaction atmosphere. The SCR mechanism is essentially the same as in dry conditions because the Cu2+/Cu+ ions, in equilibrium with H 2 O + CO 2 , are the active species in the SCR-reaction. Hydrated-carbonated Cu(II) and hydrated-carbonated Cu(I) species are associated with the redox-chemistry of NO x abatement as responsible for the improvement in the standard SCR; favoring the hindering of ammonia oxidation and nitrate decomposition. In the SCR temperature range, the conversion values registered for this catalyst are higher than 80% with total selectivity to N 2. [ABSTRACT FROM AUTHOR]

Highlights • We investigate decision-makers' behavior for highway infrastructure protection. • Algorithms for co-opetitive games among multiple players are developed. • Findings are applied to a real-world network in California for 0.5 m sea level rise. • Budget constraints, hydrodynamic effects, and traffic interactions are considered. • Cooperation is beneficial in most budget cases compared to competitive actions. Abstract This research investigates the influence of decision-maker behavior on policies that may be adopted for the protection of highway infrastructure against inundations resulting from sea-level rise. We develop an integrated game-theoretical decision-making framework to represent multiple co-opetitive decision-makers' behavior and use the San Francisco Bay Area shoreline with a scenario of a 0.5 m sea-level rise as a numerical simulation study. The decision-makers' objective is to minimize the traffic delay caused by inundations in the transportation network that lies within their geographical boundaries. Each decision-maker should determine where to build levees either only along their shoreline without cooperation or along a shared shoreline within a coalition. In this framework, each competitive decision-maker can consider cooperation to minimize its traffic delay, so its behavior can be defined as co-opetitive. We define necessary conditions for forming coalitions for multiple co-opetitive decision-makers, as well as cost-distributing rules and incentive negotiation processes within each coalition. Our model considers the effects of hydrodynamic interactions, traffic flow patterns changes as a result of inundations, and budget constraints on the costs of seashore protection. The hydrodynamics in the Bay Area are affected by the shoreline protection strategy, and closure of a highway link in one county affects traffic delays in other counties due to traffic re-routing. Thus, protection decisions made by a county have potential impacts on several other counties, and therefore counties must consider other counties' actions. In the numerical study, we investigate the results of co-opetitive games for a range of funding scenarios. It is shown, through examples, that cooperation among counties decreases the additional delay for all participants in most cases compared to competition-only cases. In some cases, cooperation also reduces protection costs. [ABSTRACT FROM AUTHOR]

Highlights • Promised delivery time (PDT) sensitive demand is considered in air cargo operational decisions. • Incentives of carriers' big data investment and demand signal sharing are explored. • A carrier does not prefer other carriers' big data investment under tense PDT competition. • A carrier may be willing to share its demand signal only when under PDT competition. Abstract We study two competing air cargo carriers' incentives of cooperation with promised-delivery-time (PDT) sensitive demand, where Carrier 1 may invest in big data and share demand signal with Carrier 2. When the carriers focus on demand competition, Carrier 1's big data investment may benefit itself and the rival, while Carrier 1 never shares its updated demand signal. When the carriers focus on PDT competition, Carrier 2 does not prefer Carrier 1's big data investment when the PDT competition is fierce. Interestingly, Carrier 1 may be willing to share its updated demand signal and a "win-win" situation occurs. [ABSTRACT FROM AUTHOR]

Abstract In light of the transition towards a low-carbon economy and growing social demands for sustainable energy consumption, alternative powertrain systems, such as battery electric vehicles (BEVs), hybrid electric vehicles (HEVs) and fuel cell electric vehicles (FCEVs), have gained significance as a viable solution to revolutionize the dominant design logic of internal combustion engines (ICE) in automotive applications. By assuming that technological innovations emerge from the ability to recombine existing technologies, tracking and forecasting the technological knowledge interaction trajectory could assist experts and decision-makers in guiding their future R&D activities. To this end, a patent-based analysis framework is introduced to study the technological knowledge ecosystem of BEVs, HEVs and FCEVs in terms of technological knowledge flow (TKF). In this study, the principles of social network analysis are firstly used to quantify and visualize the connections among interacting technological knowledge areas. Secondly, link prediction technique is applied to predict the newly emerging and decaying links from a forward-looking perspective as well as the changing interrelationships among different technological knowledge areas. The findings show that the alternative powertrain systems form a cohesive technological knowledge ecosystem, pushing the underlying technological knowledge ecosystem to adopt a coopetition-based growth strategy. This study can provide valuable information for stakeholders interested in evaluating the evolving characteristics of alternative powertrain system technologies and offer an enhanced understanding on the technological competition in the automotive industry with regard to developing cleaner and more efficient mobility solutions. Highlights • Alternative powertrain systems form a cohesive technological knowledge ecosystem. • The innovation paths of alternative powertrain systems seem to be blurring. • Battery-based vehicle design will play a dominant role in the future. • The study offers an enhanced data-driven means to study technological landscapes. [ABSTRACT FROM AUTHOR]

Many governments in different countries and regions incentivize enterprises to recycle and remanufacture through subsidies to improve resource recovery efficiency. This article establishes a supply chain consisting of retailer R, manufacturer M, and third-party supplier N based on government regulations. Firstly, This paper discussed whether retailer R should establish its brand. Secondly, whether manufacturer M chooses internal recycling and whether to cooperate with competitive or non-competitive suppliers was discussed. Finally, the issue of incentive consistency was discussed from the government's perspective. This paper has established four typical scenarios: basic Scenario, cooperative competition, complete competition scenario, and tripartite Scenario. Our research results indicate that Recycling subsidies and remanufacturing subsidies have a promoting effect on retailer R's establishment of independent brands and manufacturer M's participation in internal recycling, with recycling subsidies having a more significant promoting effect on manufacturer M's participation in internal recycling. The government should control the recycling subsidy not to be too high to ensure that both manufacturer M and retailer R prefer the CO scenario and enhance the stability of the supply chain. At the same time, remanufacturing subsidies should be appropriately increased to increase social welfare. • Manufacturer M's brand, subsidies & sales costs influence strategic decisions. • High subsidies allow retailer R to establish & benefit from its own brand. • Manufacturer M can offset sales costs with high recycling subsidies. • Government seeks stable production, prioritizing CO cooperation scenario. • For optimal social welfare, government should regulate subsidy amounts. [ABSTRACT FROM AUTHOR]

Under the background of carbon neutrality, the solar PV will usher in a rapid development stage. The international co-opetition for solar PV critical mineral resources is getting unprecedentedly intense especially among the world's major powers. Based on the niche theory and a panel dataset of chromium, gallium, copper and platinum in 2008–2020, this research has created an evaluation system for the ecological co-opetition in solar PV critical mineral resources, then analyzed the dynamic evolution trends of China, United States, Japan and European Union using eco-niche models. The results demonstrate that: (1) Distinct differences exist in the overall competitive advantages for solar PV critical minerals between these four countries. The competitive advantage rankings from strong to weak are USA, China, Japan and the EU; However, the EU possesses most available critical mineral resources, followed by the USA and Japan, whereas China has the least, revealing a complex competition pattern among the four major powers; (2) The competition for solar PV critical mineral resources between these nations has intensified since 2017. The competition between the United States and Japan is the most intense; in terms of the competition China is faced with, the United States is the most competitive, followed by Japan and the EU; and (3) The technological innovation in solar PV critical minerals has a significant impact on the ecological niche of these countries with a great heterogeneity. Finally, this research puts forward corresponding policy recommendations. [Display omitted] • Investigated co-opetition relationships for solar PV critical mineral resources. • Constructed an evaluation index system for the ecological co-opetition relationships. • Built a tech-innovation index, and verified its impact on the ecological niche. • Competition between the four major powers has intensified since 2017. [ABSTRACT FROM AUTHOR]

• Given that the government gives a certain percentage of research and development subsidies to the supplier who carries out technological innovation, the cost pressure is eased. • We construct two different co-opetition models, namely wholesale co-opetition and patent licensing co-opetition. • The optimal model selection of supply chain members is discussed from the perspective of profit. • Under certain conditions, the patent licensing model can enable the supplier and manufacturer to achieve a win–win situation. We study the co-opetition model selection problem for a new energy vehicle (NEV) supply chain comprising a dominant manufacturer and a subordinate supplier. Given the impact of R&D subsidies on suppliers' technological innovation, we consider two co-opetition models, namely wholesale co-opetition and patent licensing co-opetition, derive the optimal decisions of the models, and analyze the optimal selections for supply chain members. We also conduct extensive numerical studies to verify the research findings and generate practical insights. We find that patent licensing co-opetition is not necessarily beneficial to supply chain members. However, under certain conditions, patent licensing co-opetition can create a "win-win" situation for the supply chain. Furthermore, as the degree of product substitution increases under patent licensing co-opetition, the optimal retail prices of the manufacturer and supplier both decrease first and then increase, but their thresholds are different. In addition, the R&D cost coefficient positively affects the fixed cost of patent usage, but it does not affect the unit patent licensing fee. This study provides theoretical guidance for supply chain members to choose the optimal co-opetition models and has important practical significance for promoting the sustainable development of the NEV industry. [ABSTRACT FROM AUTHOR]

Today, blockchain is a very critical technology for many industrial operations. In this study, we aim to study the applications of blockchain in the industry. We reveal the latest blockchain-supported solutions developed by companies, identify the key challenges and discuss the long-term benefits of blockchain adoption. To be specific, this study adopts a multi-methodological approach by systematically reviewing the literature, and conducting exploratory case studies and a semi-structured interview. Based on the findings, we establish a "SMARTER" framework to illustrate the "SMART" challenges that companies may face and discuss the "ER" long-term benefits that can be generated to the business enterprises. We further propose some important future research areas, such as the impacts of blockchain technology to support corporate social responsibility, the co-opetition effect when the companies form partnership in the blockchain development, the feasibility of integration between blockchain technology and other disruptive technologies, and the values of blockchain adoption in the industry. • Establish the "SMARTER" framework • Study the applications of blockchain in the real-world • Reveal the latest blockchain-supported solutions developed by companies • Explore key challenges and long-term benefits of blockchain adoption • Propose future research areas [ABSTRACT FROM AUTHOR]

The shipping industry has witnessed fiercer competition and more volatility. As a new source to increase profits, more and more liner companies are beginning to encroach on the downstream market, forming a co-opetition relationship between liner companies and freight forwarders. Insufficient (globally or regionally) capacity is also becoming a common problem to liner companies. This paper uses a game-theoretical model to study how can resilience be improved through capacity allocation and pricing in a shipping supply chain with insufficient capacity. We solve the model analytically and find that: The establishment of a direct selling platform (encroachment) helps the liner company to expand his competitive advantages, the price and profit of the liner company are higher than the counterparts of the freight forwarder. Moreover, with the spot market, deliberate capacity allocation and pricing strategy can help to enhance supply chain resilience in case of capacity shortage. • We consider a theoretical game model with a liner company and a freight forwarder. • We discuss the liner company's optimal capacity allocation decision, and what is the pricing equilibrium between the liner company and the freight forwarder. • With the spot market, deliberate capacity allocation and pricing strategy can help to enhance supply chain resilience in case of capacity shortage. [ABSTRACT FROM AUTHOR]

Abstract In terms of the research content, previous studies did not analyze influences of interactions among different knowledge behaviors on collaborative innovation in the knowledge-intensive competitive alliance. Meanwhile, they overlooked exploring the external control mechanism together with internal interaction mechanism. In terms of the research method, previous studies failed to deal with challenges brought by collaborative innovation complexity. In order to address these gaps, different knowledge behaviors that influence collaborative innovation are identified as knowledge creation, knowledge transaction and knowledge application. The theory and method of synergetics, which is capable of explaining collaborative innovation complexity, is introduced to establish a dynamic collaborative innovation evolution model. Taking high-end medical device knowledge-intensive competitive alliances in China, Korea and Germany as empirical research subjects, we reveal the collaborative innovation principles in the knowledge-intensive competitive alliance by analyzing external control mechanism (resource input mechanism) and internal interaction mechanism (interactions among different knowledge behaviors). Results showed that: I) resource input mechanism, the most important external control mechanism, is able to alter collaborative innovation period. II) in the process of collaborative innovation, there is a highly non-linear positive correlation between knowledge creation and knowledge application, but the collaborative innovation does not depend on knowledge transaction. III) no matter what the role of resource input mechanism is, the collaborative innovation in knowledge-intensive competitive alliance is able to enter into a new stability spontaneously under interactions among different knowledge behaviors. With this research, this study can promote studies on collaborative innovation in the knowledge-intensive competitive alliance, provide new perspectives and methods for researchers, and offer important implications for managers to set strategies. Highlights • Identified the different knowledge behaviors which effect co-innovation • Analyzed effects of resource input mechanism on co-innovation • Explained the effects of knowledge behaviors' interactions on co-innovation • Revealed the complexity mechanism of co-innovation [ABSTRACT FROM AUTHOR]

The main purpose of the present paper is to analyze the feasibility of managing coopetition among two given agents in a firm, under a Markovian structure, where the transition probabilities are defined by the incentive schemes for cooperation and competition and the personality-tradeoffs between the two agents. Furthermore, the asymptotic behavior of the model is considered and analyzed through a numerical estimation of the different possibilities. The behavior of the steady state probabilities as a function of the incentive scheme is shown for different possibilities of personality-tradeoffs between the agents. The existence of a dominant coopetitive range, wherein the steady state probability of the coopetition state is higher than the similar probabilities of the cooperation and competition state, is shown to exist for some types of personality-tradeoffs. The state dominance mapping is found, and it is shown that the locus of the types of personality-tradeoffs in which coopetition is prevalent is quite narrow. Lastly, the probabilities of remaining in a specific state of cooperation, competition, and no coopetition are found, for the coopetition locus. Our results indicate that the possibilities for managing coopetition through incentive schemes are quite narrow and that an active management of interpersonal relationships in the firm is required. The paper also aims to introduce a general framework for the analysis of coopetition at the micro level, by explicitly considering coopetition and not merely a treatment of alternating behavior between pure cooperation and pure competition. [ABSTRACT FROM AUTHOR]

Abstract An important ingredient of the Swedish railway system is the increased involvement of public actors in the provision of local and regional railway services. The local and regional railway services show the strongest growth of all market segments in the Swedish passenger railway market. The strong growth is due both to changes in travel patterns and improved subsidized railway services. One important factor in the success of the regional public transport authorities' (PTA) railway services is the redefinition of the scope of these railway services by interconnecting regional railway networks into bigger entities. In 2017, nearly all local and regional railway services in Sweden's most populated region, Mälardalen, became part of a network of railway services subsidized by the PTAs in the greater region. We analyse the cooperative and competitive interactions between the stakeholders in the greater region using the key concepts in the theory of hybrid organizations. We find that despite moving towards a unified public transport market covering many counties the hybrid organizations use different governance structures and have different principles for sharing value creation. The closer cooperation paradoxically enhances competition in the regional railway market, both between subsidized travel cards and between subsidized and commercial railway services. [ABSTRACT FROM AUTHOR]

Drawing on the concept of institutional logics, this study advances the coopetition research on tourism destinations. An inductive multi-case study approach is adopted to explore the evolution of coopetitive practices of four tour operators in Macau over the last decade. The findings indicate that actors in a tourism destination respond to the changes of institutional factors by adopting an institutional logic of coopetition, which include five key processes: exploiting, exploring, bridging, sharing and boundary spanning. This paper contributes to the nascent literature on coopetition in tourism destination studies by analyzing the dynamics of co-evolution between the multi-stakeholders’ changing logics of practice and the surrounding institutional environment. The implications of institutional logics and coopetition from a managerial perspective are also discussed. [ABSTRACT FROM AUTHOR]

Tourism loyalty is a key topic that has been covered in literature mainly from a very homogenous perspective. This study analyses horizontal loyalty (consumer's loyalty divided among several destinations), and explains the background factors that affect this behaviour (cognitive, affective and overall destination image; information sources; motivations; socio-demographic characteristics; previous behaviour; conative loyalty). The paper also identifies the differences between the explanatory factors of horizontal loyalty and one-single-destination loyalty. Applying a comprehensive analysis with 6964 tourists from 17 European countries in the context of Canary Islands (Spain), the study provides interesting recommendations for destinations with a view to better designing marketing activities and improving their coopetition strategies and competitiveness. [ABSTRACT FROM AUTHOR]

In this paper, a fully distributed output regulation problem is investigated for a linear multi-agent system with both cooperative and competitive interactions. The interaction network associated with the multi-agent system is conveniently modeled by an undirected signed graph and called coopetition network for simplicity. In most literatures on cooperative output regulation problems, it is commonly assumed that the state matrix of the exogenous system is available to all agents. In this paper, a distributed adaptive observer is developed for each agent to estimate the state and the state matrix of the exogenous system to relax the constraint. Furthermore, a reduced-order observer based controller is proposed for each agent by using an internal model approach to guarantee bipartite consensus. Finally, simulation results are provided to demonstrate the proposed control strategy. [ABSTRACT FROM AUTHOR]

Ports are key elements of global supply chains, providing connection between land- and maritime-based transportation modes. They operate in cooperative, but competitive, co-opetitive , environments wherein individual port throughput is linked through an underlying transshipment network. Short-term port performance and long-term market share can be significantly impacted by a disaster event; thus, ports plan to invest in capacity expansion and protective measures to increase their reliability or resiliency in times of disruption. To account for the co-opetition among ports, a bi-level multiplayer game theoretic approach is used, wherein each individual port takes protective investment decisions while anticipating the response of the common market-clearing shipping assignment problem in the impacted network. This lower-level assignment is modeled as a cost minimization problem, which allows for consideration of gains and losses from other ports decisions through changes in port and service capacities and port cargo handling times. Linear properties of the lower-level formulation permit reformulation of the individual port bi-level optimization problems as single-level problems by replacing the common lower-level by its equivalent Karush Kuhn Tucker (KKT) conditions. Simultaneous consideration of individual port optimization problems creates a multi-leader, common-follower problem, i.e. an unrestricted game, that is modeled as an Equilibrium Problem with Equilibrium Constraints (EPEC). Equilibria solutions are sought by use of a diagonalization technique. Solutions of unrestricted, semi-restricted and restricted games are analyzed and compared for a hypothetical application from the literature involving ports in East Asia and Europe. The proposed co-opetitive approach was found to lead to increased served total demand, significantly increased market share for many ports and improved services for shippers. [ABSTRACT FROM AUTHOR]

Port relationships have received continuous attention from the academic community. However, the existing studies do not provide a science map for promoting the sustainable transition of port relationships. This study combined quantitative analysis and qualitative discussion on the previous research of port relationships from 1999 to 2022. A total of 339 articles were quantitatively analyzed and visualized the knowledge body of existing studies. The main key research topics and evolution path of these 339 articles were quantitatively analyzed and qualitatively discussed for constructing a science map of port relationships. The results indicate that the academic community of port relationships does not show a significant Matthew effect. Existing research on port relationships is supported by 16 classical references with higher co-citation frequency, and the knowledge foundation of port relationships is divided into three significant co-citation clusters. The main research topics of port relationships show evolutionary trends during different research periods and mainly focus on competition, cooperation, and co-opetition. Finally, three future research directions are predicted based on the science map for guiding the future research of port relationships: (1) integration mechanism and strategy of dry ports and multimodal transportation; (2) comprehensive competitiveness evaluation index system; (3) port adaptation investment assessment method and optimization strategy. This study provides a comprehensive science map for promoting the sustainable transition of e academic collaborations and management practices on port relationships. [ABSTRACT FROM AUTHOR]

This study aims to examine the mediating role of open innovation and the moderating effect of digitalization capabilities in the relationship between coopetition strategy and sustainable performance in the Belt and Road Initiative (BRI), which offers a coopetitive climate and is the most widely recognized business ecosystem. We conducted an empirical analysis using the partial least squares (PLS) structural equation model (SEM) based on 520 firm datasets from multiple hubs of BRI. The results show that open innovation partially mediates the relationship between coopetition strategy and sustainable performance. The results also indicate that digitalization capability significantly moderates the relationship between coopetition strategy and open innovation. However, there was insignificant moderating effect between coopetition strategy and sustainable performance of digitization capability. We believe that our research, which is based on the dynamic capability perspective, provides a structured perspective and understanding of how and why coopetition strategy, open innovation, and digitalization capabilities can be leveraged to achieve a firm's sustainable performance in the BRI. [ABSTRACT FROM AUTHOR]