Search

As subsidy is a popular form of stimulating consumption, not only for home appliances market, the effectiveness of selling promotion subsidies need to be analyzed. In this paper, we check the role of promotion subsidies in the offline channel layout by establishing three models, i.e., no subsidy, customer rebate and retailer subsidy. Two kinds of online-to-offline strategies are considered, which are retailer's opening separate and sharing offline stores. It is gotten that: both customer rebate and retailer subsidy increase the possibility of opening offline channels by sharing offline store strategy, but customer rebate takes high price than no subsidy while retailer subsidy is on the contrary. With the growing subsidy, both customer rebate and retailer subsidy could make offline channels opened by separate or sharing offline store strategy, but the customer rebate brings more possibilities. Both customer rebate and retailer subsidy require less social welfare to open offline channel, but the customer rebate brings more consumer surplus of opening offline channels than retailer subsidy for a given market area. Therefore, government should give the subsidy to customer, not to retailer, even if it brings the increasing of product' price. [ABSTRACT FROM AUTHOR]

• Biform games can coordinate supply chains with competition and cooperation relation. • Carbon complementary is a beneficial way to organize the internal carbon trading. • The pareto improvement can be achieved under hybrid carbon trading schemes. • We incorporate the Minimax and Maximin principle and Shapley value into biform game. Cap-and-trade, Certified Emission Reductions (CERs) and Renewable Energy Consumption Obligation (RECO) are three regulatory instruments used by governments to decarbonize supply chains. Integrating these mechanisms creates a Carbon Complementary Supply Chain (CCSC), in which traditional energy manufacturers (TMs) with high emissions can offset their carbon footprint by trading CERs with renewable energy manufacturers (RMs) who develop the CER projects, and compete with RMs. In the downstream, retailers are incentivized to procure more renewable energy products to avoid RECO penalties. Given that all the CCSC members tend to cooperatively invest in the CER project, this paper proposes a novel biform game-based coordination mechanism combining noncooperative and cooperative games to promote CCSC's synergy. The findings show that this mechanism can induce CCSC members to cooperate, achieving Pareto improvement in social welfare, economic performance, and individual profits under specific regulatory intensity thresholds compared to the noncooperative scenario. Our findings contribute to the ongoing debate on the role of carbon regulations in enhancing supply chain performance by providing insights into the contractual relationships among supply chain members and the economic forces at play. [ABSTRACT FROM AUTHOR]

The purpose of this article is to present a novel biobjective biform game framework for optimizing strategy selection of nodes (agents) in bilateral link network formation under dual objectives of profit and link security. First, in the first part of the noncooperative game, we construct various possible strategy combinations (situations) of all players (nodes) in the network, which define the competitive environment in the second part of the cooperative game. Second, in the second part, we derive coalitions’ payoffs under the two objectives of profit and link security and propose the biobjective Banzhaf values to allocate the corresponding cooperative games in all strategy situations. Then, a biobjective noncooperative game is formed on the basis of the obtained biobjective Banzhaf values. Third, we redefine Pareto–Nash equilibriums (in the sense of pure strategies) and obtain the Pareto–Nash equilibriums of the biobjective noncooperative game in the first part. Subsequently, the choice of the obtained Pareto–Nash equilibriums is regarded as a biobjective group decision-making problem, which is solved by employing the redefined Borda choice function method with objective weights. Hence, we can obtain the optimal strategy choices of all the nodes (players) for the entire bilateral link network formation. Finally, numerical examples and comparative analysis are given to verify the validity and applicability of the proposed models and methods. [ABSTRACT FROM AUTHOR]

This paper uses a biform game model to study firms’ trade-offs between corporate social responsibility (CSR) and competitive advantage. We focus on the context in which a competitive advantage may lead to a non-profitable scenario. It is possible that the first mover’s investment in competitive strength may deter itself from the market, which encourages firms’ investment in CSR over competitive strength. As a result, in some circumstances, firms may actively choose a CSR strategy over a competitive strategy. Our results show that (1) technological characteristics, (2) industrial structure, and (3) institutional environments are factors that influence the rational equilibrium of our model and the balance between competitive advantage and CSR. The mechanism and boundary on how firms make trade-offs between CSR activities and competitive strength are exhibited by our model, which provides a framework for decision-making and adds new insights into the strategic balance between market and non-market strategies. [ABSTRACT FROM AUTHOR]

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In proof-of-work (PoW)-based blockchain network, the blockchain miners publish blocks by contributing computing power to solve crypto-puzzles. Due to the weak computing power of single miner, miners tend to join a mining pool and share the profits from the mining pool according to the contribution proportions of the miners. However, some miners may initiate block withholding attack which may result in wasting computing power, even threatening the efficiency of the blockchain network. To address this problem, in this paper, we use the biform game model to optimize the miners' strategy choices. We firstly formulate the mining process as a non-cooperative–cooperative biform game model. We use the model to exhibit miners' strategy choices (non-cooperation stage) and the cooperation mining process (cooperation stage). Then we set the conditions to maintain the voluntary honest behavior of miners. After that, we employ the semi-CIS (semi-the center of imputation set value) value to compute the solutions of the cooperative games in the cooperation stage, and optimize miners' strategy choices to prevent the block withholding attack. Hence we can ensure the blockchain network is secure. Finally, the validity and applicability of the proposed model and method are verified by a numerical example.

Structureless communications such as Device-to-Device (D2D) relaying are undeniably of paramount importance to improving the performance of today’s mobile networks. Such a communication paradigm requires a certain level of intelligence at the device level, thereby allowing it to interact with the environment and make proper decisions. However, decentralizing decision-making may induce paradoxical outcomes, resulting in a drop in performance, which sustains the design of self-organizing yet efficient systems. We propose that each device decides either to directly connect to the eNodeB or get access via another device through a D2D link. In the first part of this article, we describe a biform game framework to analyze the proposed self-organized system’s performance, under pure and mixed strategies. We use two reinforcement learning (RL) algorithms, enabling devices to self-organize and learn their pure/mixed equilibrium strategies in a fully distributed fashion. Decentralized RL algorithms are shown to play an important role in allowing devices to be self-organized and reach satisfactory performance with incomplete information or even under uncertainties. We point out through a simulation the importance of D2D relaying and assess how our learning schemes perform under slow/fast channel fading.

Structureless communications such as Device-to-Device (D2D) relaying are undeniably of paramount importance to improving the performance of today’s mobile networks. Such a communication paradigm requires implementing a certain level of intelligence at device level, allowing to interact with the environment and select proper decisions. However, decentralizing decision making sometimes may induce some paradoxical outcomes resulting, therefore, in a performance drop, which sustains the design of self-organizing, yet efficient systems. Here, each device decides either to directly connect to the eNodeB or get access via another device through a D2D link. Given the set of active devices and the channel model, we derive the outage probability for both cellular link and D2D link, and compute the system throughput. We capture the device behavior using a biform game perspective. In the first part of this article, we analyze the pure and mixed Nash equilibria of the induced game where each device seeks to maximize its own throughput. Our framework allows us to analyse and predict the system’s performance. The second part of this article is devoted to implement two Reinforcement Learning (RL) algorithms enabling devices to self-organize themselves and learn their equilibrium pure/mixed strategies, in a fully distributed fashion. Simulation results show that offloading the network by means of D2D-relaying improves per device throughput. Moreover, detailed analysis on how the network parameters affect the global performance is provided.

• New construction approach of exponential entropy measures for HFLTSs is derived. • Confidence level based on hesitant fuzzy linguistic comprehensive entropy is given. • Biform game with hesitant fuzzy linguistic Shapley value is defined. Profit allocation is a decision-making process, and noncooperative-cooperative biform game can effectively depict the real competitive-cooperative relationship. This paper aims to construct an effective Shapley function of biform game in hesitant fuzzy linguistic environment, which can reasonably analyze the formation and the distribution of profits by taking into account the individual hesitation and information fuzziness. Firstly, we propose a new construction method of an entropy for hesitant fuzzy linguistic term sets (HFLTSs). This entropy measure can describe the linguistic information from the aspects of fuzziness and hesitation, which improves the flaws of the existing entropy for HFLTSs. After that, a function for calculating confidence level is defined based on comprehensive entropy. Then in order to study the profit allocation in a competitive-cooperative environment, we define hesitant fuzzy linguistic biform game and its characteristic function, and the effectiveness of the proposed Shapley value function according to an axiomatic system is proved. Finally, the feasibility of this approach is indicated by an example of profit allocation of cooperation in watershed management considering information asymmetry. [ABSTRACT FROM AUTHOR]

This article focuses on the question how optimal decisions in a two-firm supply chain can be determined and influenced when the lot size planning of the two firms is expanded to include investment decisions and to coordinate the just-in-time-delivery with the lot size planning on the basis of the Harris- or the Wagner/Whitin-approach. The link between these planning aspects is new. As an approach to a solution of the investment problem we examine a biform game, and consider the solution concept of the core and the cooperative Nash solution in resolving the cooperative game on the second stage of the biform game. We discuss on what terms the two strategic players make their investments. The lot size planning of the supplier (firm 1) is firstly coordinated with his just-in-time-delivery on the basis of the Harris-approach. Then, in a second step, we check to what extent the coordination can be improved if we apply the Wagner/Whitin-approach instead of the Harris-approach because of the dynamic demand structure of firm 1. For all of these decision cases we specify the payoffs of the biform game and look for optimal solutions of the two players. As a special result of the methodological consideration turns out that disposition benefits by Wagner/Whitin will lead to dominant solutions. [ABSTRACT FROM AUTHOR]

This paper analyzes innovation in perspective of system and network and offers a full-scale view of innovation holistically and connectedly. Fundamental elements, conditions and steps of innovation are discussed according to system organization theory. The function of innovation is to help solve the demanders’ problem and the value of it is the rate between function and expense. The optimal price is derived by a competitive game deduced from system analysis. And then biform game is introduced to describe cooperation and competition relations among innovation network. This paper provides a qualitative and quantitative analysis framework to analyze innovation process and offers pondering frame of enterprises’ innovation strategy decision. [ABSTRACT FROM AUTHOR]

This paper uses biform games to examine the endogenous decision to invest in relationship-specific assets. It addresses the questions of how competition affects suppliers' decisions to produce a general-purpose product or a relationship-specific product for a buyer and under what circumstances a governance arrangement designed to share investment costs between the transacting parties increases the investment in relationship-specific assets. We offer a balanced perspective that emphasizes both the superior transaction value of relationship-specific products and their high transaction costs while considering the competition effects generated by alternative investment plans. The model and its extensions generate new insights into investment decisions regarding relationship-specific assets. Copyright © 2013 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

This paper provides a model of the competitive newsvendor problem in which there is price competition following the inventory decisions. Using the biform game formalism of Brandenburger and Stuart (2004), the price competition is modeled by considering the core of the induced cooperative game. Such an analysis allows price competition to be modeled without a priori assumptions about price-setting power or pricing procedures. The paper shows that with no uncertainty, the inventory decision is equivalent to the capacity decision in Cournot competition. With uncertainty, the analysis again reduces to Cournot competition if the demand uncertainty is characterized by an appropriately constructed, expected demand curve. The results highlight the critical role of the fixed-price assumption in newsvendor models. [ABSTRACT FROM AUTHOR]

Structureless communications such as Device-to-Device (D2D) relaying are undeniably of paramount importance to improving the performance of today's mobile networks. Such a communication paradigm requires a certain level of intelligence at the device level, thereby allowing it to interact with the environment and make proper decisions. However, decentralizing decision-making may induce paradoxical outcomes, resulting in a drop in performance, which sustains the design of self-organizing yet efficient systems. We propose that each device decides either to directly connect to the eNodeB or get access via another device through a D2D link. In the first part of this article, we describe a biform game framework to analyze the proposed self-organized system's performance, under pure and mixed strategies. We use two reinforcement learning (RL) algorithms, enabling devices to self-organize and learn their pure/mixed equilibrium strategies in a fully distributed fashion. Decentralized RL algorithms are shown to play an important role in allowing devices to be self-organized and reach satisfactory performance with incomplete information or even under uncertainties. We point out through a simulation the importance of D2D relaying and assess how our learning schemes perform under slow/fast channel fading. [ABSTRACT FROM AUTHOR]

Structureless communications such as Device-to-Device (D2D) relaying are undeniably of paramount importance to improving the performance of today's mobile networks. Such a communication paradigm requires implementing a certain level of intelligence at device level, allowing to interact with the environment and select proper decisions. However, decentralizing decision making sometimes may induce some paradoxical outcomes resulting, therefore, in a performance drop, which sustains the design of self-organizing, yet efficient systems. Here, each device decides either to directly connect to the eNodeB or get access via another device through a D2D link. Given the set of active devices and the channel model, we derive the outage probability for both cellular link and D2D link, and compute the system throughput. We capture the device behavior using a biform game perspective. In the first part of this article, we analyze the pure and mixed Nash equilibria of the induced game where each device seeks to maximize its own throughput. Our framework allows us to analyse and predict the system's performance. The second part of this article is devoted to implement two Reinforcement Learning (RL) algorithms enabling devices to self-organize themselves and learn their equilibrium pure/mixed strategies, in a fully distributed fashion. Simulation results show that offloading the network by means of D2D-relaying improves per device throughput. Moreover, detailed analysis on how the network parameters affect the global performance is provided. [ABSTRACT FROM AUTHOR]