Reciprocal Preference Research Articles

Influences of Reciprocal Altruistic Preferences and Reference Low-Carbon-Level Effect on Carbon Emission Transfer Strategies of Supply Chains

Consumers’ low-carbon preferences will affect the decision-making behavior of supply chain members; an understanding of the influence mechanism of reciprocal altruistic preferences and reference low-carbon-level effect on carbon emission transfers in a supply chain is of great significance for optimizing transfer and reducing emissions and enhancing the overall emission reduction effect of the supply chain. By constructing a manufacturer-led differential game model, we analyzed the carbon emission transfer strategy of a supply chain under the influence of the reference low-carbon level effect and reciprocal altruistic preferences in scenarios with and without such preferences. The results showed that the reference low-carbon-level effect had a positive influence on the manufacturer’s transfers but not on the supplier’s acceptance of them. Moreover, reciprocal altruistic preferences increased both the transfer and acceptance of emissions while improving the low-carbon level of products. Under the influence of reciprocal preferences, the difference in the degree of altruism will also affect the carbon emission transfer and acceptance behavior of the manufacturer and supplier. When the supplier’s reciprocal altruism coefficient and the consumer’s memory parameter remain within a certain range, the transfers positively affect cooperation in the supply chain.

A general unified consistency framework of reciprocal preference relations over bipolar Abelian quasi-ordered monoids

Diverse categories of reciprocal preference relations (RPRs) have been put forward and extensively employed to quantify preference information. Consistency frameworks, which are profoundly interrelated with algebraic structures of RPRs, play a critical role in decision-making systems with RPRs. This paper introduces a novel concept of bipolar Abelian quasi-ordered monoids (BAQO-monoids) and regards any kind of RPRs as preference matrices over a given BAQO-monoid. Six BAQO-monoids are established to characterize algebraic structures of six types of imprecision-based RPRs: interval multiplicative RPRs, interval additive RPRs, triangular fuzzy multiplicative RPRs, triangular fuzzy additive RPRs, trapezoidal fuzzy multiplicative RPRs and trapezoidal fuzzy additive RPRs. Based on a general BAQO-monoid, a transitivity equation system with the binary mapping and parametric elements is developed. These parametric elements are then identified to propose a general unified consistency framework for RPRs over the BAQO-monoid. A distance-based computational formula is built to acquire inconsistency indices of RPRs over the general BAQO-monoid. The proposed general unified consistency framework and inconsistency measuring model are applied to set up consistency models and to calculate inconsistency indices for the six types of imprecision-based RPRs. Six numerical examples and important properties are provided to validate the proposed consistency frameworks and inconsistency measuring models.

Pricing and collection decisions of a closed-loop supply chain with remanufacturing under reciprocal preferences

This paper examines the effects of reciprocal preferences on the performances of a closed-loop supply chains (CLSC) with remanufacturing. Specifically, we incorporate reciprocal preferences into a two-echelon CLSC in which the manufacturer collects used products and then remanufactures the other parts except for key components as well as producing new products, and must purchase such key components from the supplier. Using a supplier-led Stackelberg game framework, the models are constructed with and without reciprocity, and then the effects of reciprocity on channel efficiency, consumers, environment and society are examined. We show that, (i) if the supplier reciprocates, the collection rate, the CLSC’s total profit, the channel efficiency and the consumer surplus enhance. Additionally, if only the manufacturer reciprocates, the CLSC’s profit remains constant; (ii) under certain conditions, the reciprocal preferences of both channel members aggravate environmental impact, while benefit social welfare; (iii) Pareto improvement can be achieved if the reciprocity parameters of both channel members are relatively high, and a simple procurement price contract can conditionally coordinate the CLSC. Finally, two extensions are studied by considering consumer heterogeneity and solving a two-period game problem, and the results characterize how reciprocal behaviors drive the performances of channel members.

Evolution game simulation study on Asia–Europe grain trade cooperation network

There has unavoidably been a problem for international grain cooperation in the Asia–Europe region as a result of the Russian–Ukrainian conflict. Analysis of the impact of Russian–Ukrainian conflict on the evolution of grain trade cooperation, identifying key influencing factors and formulating corresponding measures are of practical value for safeguarding grain security in the Asia–Europe region. In this paper, a grain trade network is constructed according to grain trade data from the Asian–European grain trade cooperation countries. A grain trade network game (GTNG) model of grain trade cooperation is established in order to investigate the elements that influence trade cooperation. The reciprocal preference is introduced. Through simulation experiments, the effects of cooperation costs, neighboring countries’ incentives, and punitive pressures, the degree of goodwill perception, the types of game, and the proportion of initial cooperators on trade cooperation are examined. This study may give useful policy recommendations for promoting Asia–Europe grain trade cooperation under the influence of the Russian–Ukrainian conflict.

A Closed-loop Supply Chain Game Model Considering Reciprocal Preferences and Echelon Utilisation

A Closed-loop Supply Chain Game Model Considering Reciprocal Preferences and Echelon Utilisation

Research on Closed-Loop Supply Chain Decision Making for Product Packaging Considering Reciprocal Preferences and Recycling Efforts

Research on Closed-Loop Supply Chain Decision Making for Product Packaging Considering Reciprocal Preferences and Recycling Efforts

On a many-sided matching problem with mixed preferences

Motivated by recent results on lexicographic and cyclic preferences, we present new sufficient conditions for the existence of stable matching in many-sided matching problems. Here, our focus shifted towards integrating the two-sided matching problem, characterized by reciprocal preferences, with the many-sided matching problem, which involves cyclic preferences. In particular, we show that one of the configurations presented recently by Zhang and Zhong for three-sided matching problems can be generalized to more dimensions. In our setting, the preferences are cyclic and, in the case of all but two pairs of consecutive sets of agents, also reciprocal, which generalizes the three-set setting of Zhang and Zhong. Our approach can be also applied to generalize the problems with any system of cyclic preferences for which the existence of a stable matching is guaranteed.

Analysis of the Game Behavior of Real Estate Mortgage Securities Issuers Based on Reciprocal Preferences

In recent years, the Chinese government has gradually begun to pay attention to the development of real estate investment trusts (REITs) and hopes to use REITs to increase the securitization of assets in the real estate market, making it possible to accelerate the circulation of funds in the real estate market. In order to enable issuers to price REITs effectively to form a mutually beneficial transaction model with investors, to increase the willingness and success rate of both parties and to ultimately create a harmonious and efficient REITs market, it is important to study the pricing decisions of issuers when issuing REITs. This study analyzes and investigates the issue of pricing decisions of REITs based on reciprocal preferences and evolutionary game theory. It is found that when the proportion of REITs issuers choosing to construct a reciprocal initial pricing decision is greater than the equilibrium probability of REITs issuers choosing a reciprocal pricing strategy, and when the initial proportion of investors choosing a reciprocal investment decision is greater than the equilibrium probability of investors choosing a reciprocal investment strategy, the overall REITs transaction market tends to be a reciprocal and harmonious transaction market at this time, the overall happiness of the REITs trading market is the highest, and the success rate of trading increases and the capital circulation of the real estate market is accelerated. Therefore, it is recommended that issuers choose reciprocal competitive decisions when pricing REITs in order to increase the success rate of their own REIT holdings; and it is recommended that the government, when regulating the pricing of REITs, pays attention to the psychological factors of reciprocal preferences of issuers and investors and that the government penalizes REIT issuers and investors when they choose self-serving decisions and rewards them when they choose reciprocal decisions.

How to mobilize owner-dynamic capabilities in megaprojects? A tripartite evolutionary game approach

PurposeCurrently, many studies have shown an increasing interest in owner-dynamic capabilities (ODCs). Existing studies mainly focus on the dynamic capability basis and capability development within the owner organization, whereas they rarely analyze the capability mobilization within the network of participants in megaprojects. Therefore, this study aims to explain the interaction and evolution of the mobilization strategies of ODCs and the cooperative strategies of other participants.Design/methodology/approachThis study develops a tripartite evolutionary game model to analyze the evolutionarily stable strategy of the owner, the reciprocal participants and the general participants. Results are numerically simulated with a validation case. The asymptotic stability of multiple group strategies is discussed under the replicator dynamic system.FindingsThis study suggests that resource complementarity significantly reduces the difficulty of mobilization. Moreover, these strategies are only effective with sufficient ODCs. The results indicate that reciprocal participants are more sensitive to the change in resource complementarity.Originality/valueThis study provides strategic guidance for mobilizing ODCs in megaprojects to better embrace uncertainty and stress, contributing to the dynamic capability literature with an evolutionary game approach. And new insight for the study of reciprocity preference in megaprojects is also provided.

Evolution of cooperation in spatial public goods game based on heterogenous social preferences and dynamic punishment

The mechanism of promoting cooperation in the public goods game has always been concerned by scholars. However, most of the existing studies are based on the premise that participants are self-interested. In order to explore why some sellers on e-commerce platforms voluntarily maintain the platform’s reputation, we incorporate heterogeneous social preferences of sellers into the spatial public goods game. We find that heterogeneous social preferences can enhance cooperation by improving collective rationality. Specifically, the altruistic preference of sellers can greatly reduce free-riding behavior, while the inequality aversion preference has a little inhibitory effect. Interestingly, when the benefit of maintaining the platform’s reputation is relatively high, the reciprocal preference can inhibit cooperation, but it can promote cooperation when the benefit is relatively small. This is due to the existence of some loosely connected but stable cooperative or defective clusters of sellers in e-commerce platforms. Furthermore, we propose a dynamic punishment mechanism to punish free riders. We observe that the dynamic punishment mechanism is more effective than the static punishment mechanism in solving the second-order free-riding problem faced by punishers. Increasing the enhancement factor of public goods is identified as a fundamental approach to mitigating this problem.

New Tanino's Additive Consistency Trapezoidal Fuzzy Extension and Optimal Fuzzy Priority Vector Acquisition

Multiplication and division of fuzzy arithmetic have brought out theoretical drawbacks to fuzzy analytic hierarchy process based decision making systems. To cope with the drawbacks, trapezoidal fuzzy additive reciprocal preference matrices (TFARPMs) are utilized to characterize preference information and addition and subtraction of fuzzy arithmetic are applied to fuzzy numbers. This paper introduces formulas to calculate left and right spread indices and imprecision indices of cores and supports for fuzzy elements in a TFARPM. Based on the addition of fuzzy arithmetic, a transitivity equation system with a parameterized trapezoidal fuzzy vector is built and computational formulas are devised to identify values of parameters from imprecision indices of cores and supports of the trapezoidal fuzzy elements in a TFARPM. A fuzzy addition based non-parametric transitivity equation is then established to define additive consistency of TFARPMs. Properties of additively consistent TFARPMs are proposed and an index formula is brought forward to compute additive inconsistency degrees of TFARPMs. A novel approach is presented to generate additively consistent TFARPMs from fuzzy vectors and a new framework is put forward to normalize [0, 1]-valued trapezoidal fuzzy vectors. An absolute deviation based minimization model is developed and converted equivalently into a linear program to acquire normalized trapezoidal fuzzy priority vectors from TFARPMs. A closed-form solution of the minimization model is found to calculate normalized optimal trapezoidal fuzzy priority vectors of additively consistent TFARPMs. Two illustrating examples including a multi-criteria decision making problem are provided to validate the proposed models.

A Local Adjustment Method to Improve Multiplicative Consistency of Fuzzy Reciprocal Preference Relations

Preferences that verify the transitivity property are usually referred to as rational or consistent preferences. Existent methods to improve the consistency of inconsistent fuzzy reciprocal preference relations (FPRs) fail to retain the original preference values because they always derive a new FPR. This article presents a new inconsistency identification and modification (IIM) method to detect and rectify only the most inconsistent elements of an inconsistent FPR. As such, the proposed IIM can be considered a local adjustment method to improve multiplicative consistency (MC) of FPRs. The case of inconsistent FPRs with missing values, i.e., incomplete FPRs, is addressed with the estimation of the missing preferences with a constrained nonlinear optimization model by the application of the IIM method. The implementation process of the proposed algorithms is illustrated with numerical examples. Simulation experiments and comparisons with existent methods are also included to show that the new method requires fewer iterations than existent methods to improve the MC of FPRs and achieves better MC level, while preserving the original preference information as much as possible than the existent methods. Thus, the results presented in this article demonstrate the correctness, effectiveness, and robustness of the proposed method.

Average consistency index based consensus model for a group decision making problem dealing with ELICIT expressions

A group decision making (GDM) problem is often modeled by using a reciprocal preference relation (RPR) structure. Linguistic information is widely used in RPRs to depict its components because it facilitates its understanding and management of uncertainty. Among the existing linguistic representation models, the extended comparative linguistic expressions with symbolic translation (ELICIT) model improves the accuracy of computational processes and maintains the comprehensibility and interpretability of the results. Therefore, we introduce a new linguistic RPR (L-RPR) structure using ELICIT information, denoted as ELICIT-RPR, whose elements are uniformed as 2-tuple linguistic intervals to simplify and facilitate computations between ELICIT expressions. In addition, the average consistency index (ACI) of ELICIT-RPR is proposed together an algorithm for improving the ACI values of ELICIT-RPRs based on their best and worst consistency indices. To avoid conflicts and obtain agreed solutions, consensus reaching processes (CRPs) have been widely used in GDM. Thus, a novel CRP based on ACI values is developed using a new distance between linguistic intervals. Finally, a case study and a comparison analysis are presented to demonstrate the validity and applicability of the proposal.

Two legume fatty acid amide hydrolase isoforms with distinct preferences for microbial- and plant-derived acylamides

Fatty acid amide hydrolase (FAAH) is a widely conserved amidase in eukaryotes, perhaps best known for inactivating N-acylethanolamine lipid mediators. However, FAAH enzymes hydrolyze a wide range of acylamide substrates. Analysis of FAAHs from multiple angiosperm species revealed two conserved phylogenetic groups that differed in key conserved residues in the substrate binding pocket. While the foundation group of plant FAAHs, designated FAAH1, has been studied at the structural and functional level in Arabidopsis thaliana, nothing is known about FAAH2 members. Here, we combined computational and biochemical approaches to compare the structural and enzymatic properties of two FAAH isoforms in the legume Medicago truncatula designated MtFAAH1 and MtFAAH2a. Differences in structural and physicochemical properties of the substrate binding pockets, predicted from homology modeling, molecular docking, and molecular dynamic simulation experiments, suggested that these two FAAH isoforms would exhibit differences in their amidohydrolase activity profiles. Indeed, kinetic studies of purified, recombinant MtFAAHs indicated a reciprocal preference for acylamide substrates with MtFAAH1 more efficiently utilizing long-chain acylamides, and MtFAAH2a more efficiently hydrolyzing short-chain and aromatic acylamides. This first report of the enzymatic behavior of two phylogenetically distinct plant FAAHs will provide a foundation for further investigations regarding FAAH isoforms in legumes and other plant species.

Sorting of trustees: the good and the bad stay in the game

AbstractWe extend the theoretical and experimental analysis of endogenous sorting in social dilemma games to decisions of trustees in trust games. Trustees first decide about the amount they send back if the trustor sends the money and then learn that they can exit the game for a payoff that is identical to the trustor’s endowment. We develop a behavioral model where trustors and trustees have reciprocal preferences, and hence put positive weight on the other player’s payoff if they perceive their behavior as kind. Our model yields two possible constellations: Only trustees with high reciprocity participate, or all types except those with intermediate reciprocity participate. Our data lend strong support for the second pattern, as we observe a U-shaped relation between the trustees’ participation rate and the amount they return. Trustors are hence left with an extreme pool of participants where they are either matched with particularly selfish or generous trustees.

Deriving priorities from the fuzzy best-worst method matrix and its applications: A perspective of incomplete reciprocal preference relation

Preference relation is an effective tool in multi-criteria decision making (MCDM). The fuzzy best-worst method (FBWM), which is an extension of the BWM, is proposed to determine weights for criteria. In the FBWM, the Fuzzy Best-to-others Vector (FBV) and Fuzzy others-to-Worst Vector (FWV) are given. The FBV and FWV can intrinsically formulate one incomplete reciprocal preference relation (IRPR), which we call the FBWM matrix. As the FBWM is designed mainly to determine the weights, and the existing FBWM only uses the min–max problem to derive the weights. Therefore, it is important to develop other effective methods to derive the weights from the FBWM matrix. Deriving the weights from FBWM matrix is converted into deriving the priorities from the corresponding IRPR. In this view, two groups of methods are proposed. One group is for a single FBWM matrix, and the other group is for a group of FBWM matrices. To show the effectiveness and performance of the developed methods, Monte Carlo simulations were implemented. Finally, two examples were used to show how these methods are applied in real decision-making problems. Comparative analyses were performed to show the differences and usefulness of the proposed methods.

Saaty’s consistency trapezoidal fuzzy extension and optimized fuzzy utility vector acquisition

Fuzzy extensions of Saaty’s consistency play an important role in developing fuzzy analytic hierarchy process based decision-making methods. This paper proposes formulas to calculate ratio-based increasing and decreasing spread indices and to obtain ratio-based indeterminacy indices of modal and support intervals for fuzzy judgments of trapezoidal fuzzy reciprocal preference matrices (TFRPMs). A transitivity equation with parametric fuzzy elements is introduced and combined with the existence of parameter values to define consistency of TFRPMs. To cope with the challenge of identifying the existence, computational formulas are developed to directly obtain values of parameters from the fuzzy judgments in a TFRPM, and an equivalent consistency concept is proposed for TFRPMs. Properties of consistent TFRPMs are presented and a logarithmic deviation based formula is provided to compute consistency indices of TFRPMs. A new framework of normalized vectors with trapezoidal fuzzy elements is introduced. A logarithmic goal programming model is established and transformed into a linear program for acquiring normalized trapezoidal fuzzy utility vectors from TFRPMs. An analytical solution is found for optimized trapezoidal fuzzy utility vectors of consistent TFRPMs. The developed models are validated by three numerical illustrations possessing comparative studies.

The Preference for Reciprocity in Congress

AbstractMost researchers assume legislators repay past favors to secure future rewards and avoid future punishments, but a growing literature shows that human beings are intrinsically motivated to reciprocate past favors. However, there is no systematic evidence as to whether legislators bring this preference for reciprocity to Congress. An original survey experiment, an observational study of end‐of‐career behavior, and a matching‐based analysis of responses to committee assignments provide consistent evidence that legislators have a preference for reciprocity.

Reciprocity in Dynamic Employment Relationships

This paper analyzes a dynamic relational contract for employees with reciprocal preferences. A model of a long-term employment relationship is developed that implies that generous upfront wages activate the norm of reciprocity and then are more important when an employee is close to retirement. In earlier stages, direct incentives promising a bonus in exchange for effort are more effective. Hence, direct and reciprocity-based incentives reinforce each other and should be used in combination. Moreover, a more competitive labor market may increase the utilization of reciprocity-based incentives. This paper was accepted by Axel Ockenfels, behavioral economics and decision analysis. Funding: This work was supported by Hardegg’sche Stiftung, the Deutsche Forschungsgemeinschaft [CRC TRR 190], and the Austrian Science Fund [Grant P 33307-G]. Supplemental Material: The online appendices are available at https://doi.org/10.1287/mnsc.2022.4657 .

An improved multiplicative acceptability consistency-driven group decision making with triangular fuzzy reciprocal preference relations

Triangular fuzzy reciprocal preference relation (TFRPR) is one of the most effective tools to express the vague and uncertain preferences of decision makers in group decision making (GDM). Consistency of TFRPRs is a crucial premise for reasonable and reliable decision-making. To do so, this study develops an improved multiplicative acceptability consistency-driven GDM with TFRPRs. By analyzing the composition of TFRPRs, a multiplicative consistency index and the corresponding threshold are defined to measure whether a TFRPR is acceptably consistent. The consistency measurement reflects the essential traits of triangular fuzzy numbers, which fully considers the multiplicative consistency of modal values and the multiplicative consistency of geometric mean based on central tendency. Subsequently, three inconsistent TFRPR cases are analyzed, and the algorithm based on mathematical derivation and a linear programming model is presented to repair the inconsistency of TFRPRs. As per the multiplicative acceptability consistency degree (MACD) of TFRPRs, an MACD-induced ordered weighted averaging (MACD-IOWA) operator is proposed to aggregate individual TFRPRs into group TFRPR. The essence principle is that the larger the MACD value, the higher the decision maker’s weight. Finally, a case study, comparative analysis and discussions are given to verify the feasibility and validity of the proposed methods.