Partner Selection Mechanism Research Articles

An incentive mechanism for partner selection from a collaborative network with private information

Partner selection is critical to the success of a Virtual Enterprise. This paper studies the partner selection problem under the virtual organization breeding environment where candidates have private information about their cost to undertake the tasks. A systematic solution is provided to reveal the true value of the private information and then select the optimal partners. This solution mainly comprises two steps: (1) For each possible cost combination, a multi-objective integer nonlinear programming model and an algorithm are designed to obtain the optimal partners. Then, a social choice correspondence, which indicates the optimal partners for any cost combination, is formulated. (2) An incentive mechanism is constructed to implement the social choice correspondence and ensure that candidates will announce their values of cost truthfully. Furthermore, a numerical study is provided to illustrate the effectiveness of the solution and to investigate the relationship between the construction of the collaborative network and the utility to partners. We find that the number of candidates in each period affects the utility of partners as well as the expected surplus of the leading company significantly.

A Bilateral Multi-Attribute Negotiation-Based Approach for a VE Configuration

In this paper, a specific case faced during the process of a Virtual Enterprise (VE) configuration from the Virtual Breeding Environment (VBE), for a specific Business Opportunity (BO), was studied. The considered case deals with the existence of a unique qualified partner in the VBE with a specific competence required by an activity of the BO at hand. This partner may behave opportunistically, taking advantage of being the only competent VBE member to achieve an activity, influencing, then, the effectiveness of the VE configuration. This paper proposed the integration of a bilateral multi-attribute negotiation process in the partner selection mechanism to improve the unique competent partner proposal and the development of a negotiation process-based concession. During negotiation, automated agents, representing the broker and the unique partner, exchange proposals and counter-proposals to reach a mutual agreement. Then, the accepted proposal is integrated into the Multi-Objective Programming model to complete the partner selection and order allocation mechanism. A real case study from a network in textile sector was presented to prove the contribution of the development and the integration of the negotiation process in the partner selection decision-making mechanism. The performance evaluation shows that integrating negotiation in the decision-making mechanism improves the VE objectives and performances.

Lotus Accessions Possess Multiple Checkpoints Triggered by Different Type III Secretion System Effectors of the Wide-Host-Range Symbiont Bradyrhizobium elkanii USDA61.

Bradyrhizobium elkanii, a rhizobium with a relatively wide host range, possesses a functional type III secretion system (T3SS) that is involved in symbiotic incompatibility against Rj4-genotype soybean (Glycine max) and some accessions of mung bean (Vigna radiata). To expand our knowledge on the T3SS-mediated partner selection mechanism in the symbiotic legume-rhizobia association, we inoculated three Lotus experimental accessions with wild-type and T3SS-mutant strains of B. elkanii USDA61. Different responses were induced by T3SS in a host genotype-dependent manner. Lotus japonicus Gifu inhibited infection; L. burttii allowed infection, but inhibited nodule maturation at the post-infection stage; and L. burttii and L. japonicus MG-20 both displayed a nodule early senescence-like response. By conducting inoculation tests with mutants of previously reported and newly identified effector protein genes of B. elkanii USDA61, we identified NopF as the effector protein triggering the inhibition of infection, and NopM as the effector protein triggering the nodule early senescence–like response. Consistent with these results, the B. elkanii USDA61 gene for NopF introduced into the Lotus symbiont Mesorhizobium japonicum induced infection inhibition in L. japonicus Gifu, but did not induce any response in L. burttii or L. japonicus MG-20. These results suggest that Lotus accessions possess at least three checkpoints to eliminate unfavorable symbionts, including the post-infection stage, by recognizing different T3SS effector proteins at each checkpoint.

Exploring small-world network with an elite-clique: Bringing embeddedness theory into the dynamic evolution of a venture capital network

This paper uses a network dynamics model to explain the formation of a small-world network with an elite-clique. This network is a small-world network with an elite-clique at its center in which elites are also the centers of many small groups. These leaders also act as bridges between different small groups. Network dynamics are an important research topic due to their ability to explain the evolution of network structures. In this paper, a Chinese Venture Capital (VC) network was coded from joint investments between VC firms and then analyzed to uncover its network properties and factors that influence its evolution. We first built a random graph model to control for factors such as network scale, network growth, investment frequency and syndication tendency. Then we added a partner-selection mechanism and used two theories to analyze the formation of network structure: relational embeddedness and structural embeddedness. After that, we ran simulations and compared the three models with the actual Chinese VC network. To do this we computed the elite-clique’s EI index, degree distribution, clustering coefficient distribution and motifs. Results show that adding embeddedness theories significantly improved the network dynamic model’s predictive power, and help us uncover the mechanisms that affect the formation of a small-world industrial network with an elite-clique at its center.

The Partner Selection Modes for Knowledge-Based Innovation Networks: A Multiagent Simulation

With the advent of the knowledge economy, technological innovation has become more and more complex. Firms in innovation system need to cooperate with others to upgrade their knowledge level and market competitiveness. Proper partner selection can increase the efficiency of the entire innovation system. Different partner selection mechanism has a significant impact on the efficiency of knowledge transfer for the enterprises and innovation system. In this study, a multiagent simulation is conducted to explore the effects of four different partner selection modes on knowledge transfer of innovation network: random selection mode, mode of selection based on space, mode of selection based on knowledge capital and mode of selection based on complementary knowledge. The results indicate that: in a period time, (1)the spatial selection mode limits the scope of partner selection and reduces the knowledge transfer path;(2)mode of selection based on the knowledge capital enables the large firms to have more cooperation opportunities;(3)complementary knowledge based selection mode improves the knowledge transfer efficiency of the system.

Enhancing the partner selection process in a Sustainable Partner Network

Purpose: The purpose of this paper is to introduce how to describe in a unified way the business models of different sectors companies based on VAC/EPC notations, and to contribute to the lean based partner selection mechanism for sustainable partner network. Design/methodology/approach: The authors introduce the unified business process modelling approach for collaborative companies modelling, which supports the lean based sustainable partner selection. Where lean correspond to the characteristics of cheap (cost effective), better (lower risk) and fast (less time).Findings: The authors defend that appropriate partner selection is a vital success factor in any collaboration. Existing supplier (partner selection) tools do not include the unified approach for business processes modelling of partners organisations and do not apply the lean principles for sustainable partner selection. Existing collaborative networks such as conventional supply chains spend considerable time and money to search for suitable partners, decrease the number of successful initiation of a project and completed collaborative projects.Research limitations/implications: The authors have designed a unified methodology for the business process modelling of manufacturing and machinery sectors companies applied for the formation of a sustainable partner network. After implementation, the solution applies the lean based approach for partner selection, to decrease the time and cost spend with simultaneous improvement of collaborative project sustainability. Nevertheless, the proposed approach is adaptable to other fields.Practical implications: To evaluate the achieved results the authors have performed the simulation study of Sustainable Partner Network (SPN) formation followed by partner’s selection that supports lean principles. The paper includes a feasibility case study for the approval of findings, where twenty-seven small and medium enterprises (SMEs) from the manufacturing and logistics fields collaborate to achieve a common goal. The time required for collaborative partner selection in the conventional supply chain is compared to the partner selection in Sustainable Partner Network was found to less.Originality/value: The main idea is to collect information about the available resources of SMEs into a new temporary entity and to utilise those resources for the realisation of the tasks of a particularly large project while meeting customer expectations. This work also suggests a methodology for faster business process modelling and evaluation (assessment) based on lean principles for a particular business process. Partners can use the SPN resources with the attributes of fast, cheap and less risk. The suggested solution enables to select the most reliable partners and contributes to the improvement of collaborative networks sustainability.

Mechanism for cooperative partner selection: Dual-factor theory perspective

With global competition and greater components outsourcing, partners play an important role in the supply chain. Previous research on partner selection from the perspective of partner ability has ignored cooperation factors. Ignoring the cooperation factor can lead to a higher chance of failure, even if the partners have a good track record of performance. For this reason, this paper seeks to study the mechanism on cooperative partner selection from a dual-factor theory perspective. We consider two levels: collaborative level and individual level, as well as their measurements. We propose a novel framework for solving the cooperative partner evaluation and selection problem. This framework applies the compatibility degree of the triangular fuzzy soft set (TFSS) to measure the collaborative level, and an extended TODIM based on TFSS to measure the dominance degree for the individual level. A simple example is used to illustrate the potential application of the proposed method. To highlight our method’s practicality and effectiveness, we compare against an established technique.

Guarantee network model and risk contagion

In this paper, we construct a dynamic guarantee network model. Based on the constructed model, the dynamic evolution of risk contagion is researched by means of simulation methods. The risk contagion research is carried out from three aspects:guarantee mechanism, partner selection mechanism, and production parameter. The research shows that: (1) Firm size distribution takes on a power-law tail. (2) Guarantee network provides a channel for risk contagion and aggravates risk contagion among firms. (3) The type of partner selection mechanism has an impact on risk contagion. Risk cognation in the net worth mechanism is more serious in comparison to the random mechanism. (4) Risk contagion among firms is the increasing function of the production parameter φ.

Dynamic partner selection in Cloud Federation for ensuring the quality of service for cloud consumers

Cloud Computing has become the popular paradigm for accessing the various scalable and on-demand computing services over the internet. Nowadays, individual Cloud Service Providers (CSPs) offering specialized services to the customers collaborate to form the Cloud Federation, in order to reap the real benefits of Cloud Computing. By collaboration, the member CSPs of the federation achieve better resource utilization and Quality of Service (QoS), thereby increasing their business prospects. When a CSP runs out of resources in the Cloud Federation, in order to offload the customer requests for resources to other CSP(s), identifying a suitable partner is a challenging task due to the lack of global coordination among them. In this paper, we propose the design and implementation of an efficient partner selection mechanism in the Cloud Federation, using the Analytic Hierarchy Process (AHP) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methods, and also considering the trust values of various CSPs in the federation. The AHP method is used to calculate the weights of the QoS parameters used in the TOPSIS method which is used to rank the various CSPs in the Cloud Federation according to the user requirements. Simulation results show the effectiveness of this approach in order to efficiently select the trustworthy partners in large scale federations to ensure the required QoS to the cloud consumers.

Trust-Oriented Partner Selection in D2D Cooperative Communications

To meet the rapid growing requirement of data services and offload the heavy base station load, device-to-device (D2D) communication is proposed as one of the key technologies for future cellular network, which can enable users to communicate directly and thus effectively improve the bearing capacity of the network. However, when D2D users transmit packets in the manner of cooperative communication, the cooperative users with non-cooperative behavior, such as the selfishness of user, may lead to a sharp decline in network performance. For this reason, in our paper, a trust-oriented partner selection mechanism (TPSM) is proposed to avoid choosing those users with non-cooperative behavior. In particular, the related psychological researches show that the psychology structure of users can be divided into three aspects: cognition, emotion, and behavior. Considering the psychology structure of users, we build multi-dimensional trust relationships between sending users and cooperative users by evaluating the cognition trust, emotion trust, and behavior trust. Furthermore, aiming at the multi-dimensional trust relationships between sending users and cooperative users, we classify the cooperative users into three categories, namely reliable users, observed users, and unreliable users, by combining the decision-theoretic rough sets based on Naive Bayes. Finally, based on different cooperative transmission scenarios, an optimal partner selection mechanism is proposed in this paper. The optimal partner can be chosen from the reliable cooperative users, according to the different scenarios and factors. The numerical results show that the proposed TPSM can effectively identify the selfish users and notably enhance the packet delivery rate.

Evolution of gossip-based indirect reciprocity on a bipartite network.

Cooperation can be supported by indirect reciprocity via reputation. Thanks to gossip, reputations are built and circulated and humans can identify defectors and ostracise them. However, the evolutionary stability of gossip is allegedly undermined by the fact that it is more error-prone that direct observation, whereas ostracism could be ineffective if the partner selection mechanism is not robust. The aim of this work is to investigate the conditions under which the combination of gossip and ostracism might support cooperation in groups of different sizes. We are also interested in exploring the extent to which errors in transmission might undermine the reliability of gossip as a mechanism for identifying defectors. Our results show that a large quantity of gossip is necessary to support cooperation, and that group structure can mitigate the effects of errors in transmission.

An endogenous network model of banking systems

In this article, we propose an endogenous network model for banking systems. Starting from the balance sheets of a banking system and its update algorithms, the interbank credit lending was established based on the partner selection mechanism. Through simulation analysis, we find that the endogenous network model displays a structure with multiple liquidity centers, that the in‐degree distribution exhibits a Pareto tail, and that the bank asset distribution is a lognormal distribution with a Pareto tail. © 2016 Wiley Periodicals, Inc. Complexity 21: 512–520, 2016

Partner selection and incentive mechanism for physical layer security

We study user cooperation to enhance the physical layer security. Specifically, the source cooperates with friendly intermediate nodes to transmit message securely in the presence of multiple eavesdroppers. We propose a cooperative framework, whereby the source selects multiple partners and stimulates them by granting an amount of reward. First, multiple cooperative relays and jammers are selected by the source using greedy or cross-entropy based approaches. Then, the source and the partners negotiate for the payment and transmission power, which is modeled as a two-layer game. At the top layer, a buyer-seller game is utilized, where the source buys the service provided by the partners. At the bottom layer, all the partners share the reward by determining their transmission powers in a distributed way, which is formulated as a non-cooperative power selection game. By analyzing the game, the partners can determine the transmission powers for cooperation, while the source can select the best payment. To further improve the utility of the source, a set of reward allocation coefficients are introduced and optimized using particle swarm optimization approach. Simulation results are provided to demonstrate the performance of the proposed schemes.

BiomeNet: a Bayesian model for inference of metabolic divergence among microbial communities.

Metagenomics yields enormous numbers of microbial sequences that can be assigned a metabolic function. Using such data to infer community-level metabolic divergence is hindered by the lack of a suitable statistical framework. Here, we describe a novel hierarchical Bayesian model, called BiomeNet (Bayesian inference of metabolic networks), for inferring differential prevalence of metabolic subnetworks among microbial communities. To infer the structure of community-level metabolic interactions, BiomeNet applies a mixed-membership modelling framework to enzyme abundance information. The basic idea is that the mixture components of the model (metabolic reactions, subnetworks, and networks) are shared across all groups (microbiome samples), but the mixture proportions vary from group to group. Through this framework, the model can capture nested structures within the data. BiomeNet is unique in modeling each metagenome sample as a mixture of complex metabolic systems (metabosystems). The metabosystems are composed of mixtures of tightly connected metabolic subnetworks. BiomeNet differs from other unsupervised methods by allowing researchers to discriminate groups of samples through the metabolic patterns it discovers in the data, and by providing a framework for interpreting them. We describe a collapsed Gibbs sampler for inference of the mixture weights under BiomeNet, and we use simulation to validate the inference algorithm. Application of BiomeNet to human gut metagenomes revealed a metabosystem with greater prevalence among inflammatory bowel disease (IBD) patients. Based on the discriminatory subnetworks for this metabosystem, we inferred that the community is likely to be closely associated with the human gut epithelium, resistant to dietary interventions, and interfere with human uptake of an antioxidant connected to IBD. Because this metabosystem has a greater capacity to exploit host-associated glycans, we speculate that IBD-associated communities might arise from opportunist growth of bacteria that can circumvent the host's nutrient-based mechanism for bacterial partner selection.

New Synthesis: The Chemistry of Partner Choice in Insect-Microbe Mutualisms

Most insects are associated with mutualistic microorganisms that can confer novel traits and thereby play important roles for the ecology and evolution of host organisms. Although many insects ensure that their offspring are endowed with the beneficial symbionts by transmitting them vertically from parent to offspring, others rely on environmental uptake in every generation. How can these insects choose the best cooperative partner from the diversity of environmental microbes? Proposed means of partner choice - signaling and screening (Archetti et al. 2011)typically are chemically-mediated in cross-kingdom mutualisms. While wellstudied in plant-pollinator and some plant-microbe mutualisms, however, the use of chemical signals (e.g., specific odors, surface attractants) or selective environments (e.g., through nutritional constraints or defensive chemicals) to filter potential partners remains largely unexplored in insect-microbe associations, despite the implications for the ecology and evolution of the host organisms. Ideally, individuals identify beneficial partners in advance of any interaction, thus preventing exploitation of the costly cooperative act. Signaling is a wellknown mechanism for partner selection in animal-animal (e.g. ,c leaner fish), animal-plant (e.g., pollinator and seed dispersal mutualisms), as well as plantmicrobe mutualisms (e.g., legumes and rhizobia, plants and mycorrhizal fungi). Signal honesty is required in order to maintain a mutualism, and thus signals most easily evolve if directly linked to partner quality. In insects, specific long-range signaling and short-distance recognition of mutualistic partners by odors or surface chemicals has been implicated in the establishment of symbiosis in several fungusgrowing insects. Some ambrosia beetle species are attracted to their fungal symbionts, suggesting that signaling by specific microbial volatile organic compounds (MVOCs) mediates the initial stages of partner choice (Hulcr et al. 2011). Long-range beetle attraction by general MVOCs (e.g., short-chain alcohols) is long known, but partner recognition is expected to involve specific secondary compounds (e.g., terpenoids) or blends of general MVOCs. However, since ambrosia beetles usually transmit their symbiotic fungus vertically in specialized pouches (mycangia) and inoculate them into new host trees upon colonization, attraction to the symbiont’s volatiles may direct the beetles to suitable environments for fungus growth rather than providing a signal necessary for symbiosis establishment. By contrast, most fungus-growing termites collect their cultivar’sspores de novo from the environment in each generation, highlighting the need for mechanisms to localize and recognize the symbiotic partner. Currently, it is unknown whether recognition occurs through volatile signals or surface compounds produced by the fungal spores. Given thatspores often are rich in defensive secondary metabolites (e.g., terpenoids, mycotoxins), derivatives of these compounds could be involved in partner choice. Similar to ambrosia beetles and despite vertical transmission of their symbionts, leaf-cutter ants of the genus Acromyrmex chemically recognize their native cultivar fungi (see references in Zhang et al. 2007), as well as discriminate between native and non-native

VE architect-driven partner selection: ontology-based approach

An underlying formation of instant virtual enterprises VE is the matter of flexible and efficient partner selection. In rapidly changing business environment and turbulent market conditions, selecting the partners for reconfiguration of VE must be realised regarding many factors such as skill, cost, resource, availability, goal, etc. However, these attributes primarily are not constant and may not be appropriate for some networks or conditions; hence they should be instantly replaced with some new ones. This imposes a demand that the VE architect selects partners in terms of changing criterion. Thus, we have to establish an adaptable and flexible partner selection mechanism that is driven by the VE architect's requirements. To achieve this, the paper proposes an ontology-based partner selection algorithm to effectively calculate the semantic similarity between VE architect's requirement ontology and partners' ontologies. The algorithm comprises diverse metrics including gravitation of resources GoR, path similarity, path weight, and definition similarity which make it more close to VE architect. The paper also discusses implementation and evaluation of it using different approaches which confirm the quality, efficiency, and generality of algorithm.

Cdc42 Explores the Cell Periphery for Mate Selection in Fission Yeast

How cells polarize in response to external cues is a fundamental biological problem. For mating, yeast cells orient growth toward the source of a pheromone gradient produced by cells of the opposite mating type. Polarized growth depends on the small GTPase Cdc42, a central eukaryotic polarity regulator that controls signaling, cytoskeleton polarization, and vesicle trafficking. However, the mechanisms of polarity establishment and mate selection in complex cellular environments are poorly understood. Here we show that, in fission yeast, low-level pheromone signaling promotes a novel polarization state, where active Cdc42, its GEF Scd1, and scaffold Scd2 form colocalizing dynamic zones that sample the periphery of the cell. Two direct Cdc42 effectors--actin cables marked by myosin V Myo52 and the exocyst complex labeled by Sec6 and Sec8--also dynamically colocalize with active Cdc42. However, these cells do not grow due to a block in the exocytosis of cell wall synthases Bgs1 and Bgs4. High-level pheromone stabilizes active Cdc42 zones and promotes cell wall synthase exocytosis and polarized growth. However, in the absence of prior low-level pheromone signaling, exploration fails, and cells polarize growth at cell poles by default. Consequently, these cells show altered partner choice, mating preferentially with sister rather than nonsister cells. Thus, Cdc42 exploration serves to orient growth for partner selection. This process may also promote genetic diversification.

A Synchrony-Based Perspective for Partner Selection and Attentional Mechanism in Human-Robot Interaction

Abstract Future robots must co-exist and directly interact with human beings. Designing these agents imply solving hard problems linked to human-robot interaction tasks. For instance, how a robot can choose an interacting partner among various agents and how a robot locates regions of interest in its visual field. Studies of neurobiology and psychology collectively named synchrony as an indispensable parameter for social interaction. We assumed that Human-Robot interaction could be initiated by synchrony detection. In this paper, we present a developmental approach for analyzing unintentional synchronization in human-robot interaction. Using our neural network model, the robot learns from a babbling step its inner dynamics by associating its own motor activities (oscillators) with the visual stimulus induced by its own motion. After learning the robot is capable of choosing an interacting agent and of localizing the spatial position of its preferred partner by synchrony detection.

Mixed strategy and coevolution dynamics in social networks

We investigate coevolution dynamics of both individual strategies and social ties as they adapt within the snowdrift game with mixed strategies. We propose a partner selection mechanism based on the concept of trust. Here trust is considered an instrument for an individual both selecting the right partners and being selected amongst other potential partners. Based on her local views of the system, the focal individual dismisses the link from the partner with the lowest trust and rewires to the partner’s partner with the highest trust. It is shown that such a trust-based partner switching mechanism favors the emergence of cooperators. Furthermore, when the number of an individual’s partners is restricted (which is a metaphor of limited capacities and capabilities of an individual in real environments), surprising assortative mixing patterns are formed in the emerging network and change the network’s degree distribution from a power–law distribution to an asymmetrically U-shaped distribution. This plays a leading role in preventing global avalanches triggered by perturbations acting on the state of the highly connected individuals.

An analytic hierarchy process approach with linguistic variables for selection of an R&D strategic alliance partner

This study establishes a mechanism for partner selection that emphasizes the relation of criteria and motivation. Since the motivations for establishing strategic alliances follow different enterprises’ needs, attempting to identify universal criteria weights that enterprises should employ when seeking a proper partner are not productive. Consequently, the weighting process for criteria must consider the intensity of motivations for establishing the alliance. When evaluating companies with closer levels of performance, the approach of pair-wise comparison is more suitable than the direct scoring method. Considering the strategic level, most comparisons may be vague and linguistic variables defined as fuzzy numbers are applied to this situation. The calculation procedure for the weighting and evaluation processes under a vague environment is proposed and validated by using an illustrative example.