不透明销售的顾客退货政策选择

本文探讨从事不透明销售的零售商对顾客退货政策的选择问题。分别针对零售商垄断和竞争两种市场情况,建立不透明零售商与其它供应链成员(制造商或普通零售商)之间的博弈模型,获得唯一均衡解;对均衡结果进行结构化分析,给出不透明销售方式下采用全额退款政策的判别条件;针对均衡结果,分析零售商垄断情况下产品不透明参数的最优设计,以及零售商竞争情况下的市场分化情况;鉴于净残值参数在退货政策选择中的决定性作用,本文进一步探讨了净残值为正时全额退款政策对各参与方利润及产品需求和价格的影响,分析了净残值在其中的作用机理。本研究能够为不透明零售商制定退货政策和价格以及其它供应链成员制定相关决策提供支持。     

Network analysis: Understanding consumers' choice in the film industry and predicting pre‐released weekly box‐office revenue

Predicting weekly box‐office demand is an important yet challenging question. For theater exhibitors, such information will enhance negotiation options with distributers, and assist in planning weekly movie portfolio mix. Existing literature focuses on forecasts of pre‐released total gross revenue or on weekly predictions based on first‐weeks observations. This work adds to the literature in modeling the entire demand structure forecasts by utilizing information on movie similarity network. Specifically, we draw upon the assumption that aggregated consumers' choice in the film industry is the main key in understanding movies' demand. Therefore, similar movies, in terms of audience appeal, should yield similar demand structure. In this work, we propose an automated technique that derives measurements of demand structure. We demonstrate that our technique enables to analyze different aspects of demand structure, namely, decay rate, time of first demand peak, per‐screen gross value at peak time, existence of second demand wave, and time on screens. We deploy ideas from variable selection procedures, to investigate the prediction power of similarity network on demand dynamics. We show that not only our models perform significantly better than models that discard the similarity network but are also robust to new sets of box‐office movies. Copyright © 2016 John Wiley & Sons, Ltd.     

The effect of gossip on social networks

In this article, we develop a simple model for the effect of gossip spread on social network structure. We define gossip as information passed between two individuals A and B about a third individual C which affects the strengths of all three relationships: it strengthens A‐B and weakens both B‐C and A‐C. We find, in both an analytic derivation and model simulations, that if gossip does not spread beyond simple triads, it destroys them but if gossip propagates through large dense clusters, it strengthens them. Additionally, our simulations show that the effect of gossip on network metrics (clustering coefficient, average‐path‐length, and sum‐of‐strengths) varies with network structure and average‐node‐degree. © 2010 Wiley Periodicals, Inc. Complexity 16: 39‐47, 2011     

Information processing,memories, and synchronization in chaotic neural network with the time delay

Information processing and two types of memory in an analog neural network model with time delay that produces chaos similar to the human and animal EEGs are considered. There are two levels of information processing in this neural network: the level of individual neurons and the level of the neural network. Similar to the state of brain, the state of chaotic neural network is defined. It is characterized by two types of memories (memory I and memory II) and correlation structure between the neurons. In normal (unperturbed) state, the neural network generates chaotic patterns of averaged neuronal activities (memory I) and patterns of oscillation amplitudes (memory II). In the presence of external stimulation, the activity patterns change, showing changes in both types of memory. As in experiments on stimulation of the brain, the neural network model shows synchronization of neuronal activities due to stimulus measured by Pearson's correlation coefficient. An increase in neural network asymmetry (increase of the neural network excitability) leads to the phenomenon similar to the epilepsy. Modeling of brain injury, Parkinson's disease, and dementia is performed by removing and weakening interneuron connections. In all cases, the chaotic neural network shows a decrease of the degree of chaos and changes in both types of memory similar to those observed in experiments with healthy human subjects and patients with Parkinson's disease and dementia. © 2005 Wiley Periodicals, Inc. Complexity 11:39–52, 2005     

The impact of network structure on innovation efficiency: An agent‐based study in the context of innovation networks

This article investigates the impact of network structure on innovation efficiency by establishing a simulation model of innovation process in the context of innovation networks. The results indicate that short path lengths between vertices are conductive to high efficiency of explorative innovations, dense clusters are conductive to high efficiency of exploitative innovations, and high small‐worldness is conductive to high efficiency of the hybrid of these two innovations. Moreover, we discussed the reason of the results and give some suggestions to innovators and innovation policy makers. © 2014 Wiley Periodicals, Inc. Complexity 21: 111–122, 2015     

带有网络外部性的动态寡头垄断定价

给出了带有网络外部性的两阶段寡头垄断定价模型,并用博弈论方法求解.通过与带有网络外部性的完全垄断定价模型的比较,得出重要结论:在网络外部性足够大的情况下,①寡头竞争情况下与完全垄断下情况一样,“科斯假设”将得到克服,均衡定价将呈现先低后高的情况.②对于完全垄断厂商来说,网络外部性k的增加能够增加其利润,但对于寡头竞争的企业来说,正好相反,k的增加将导致其利润的下降.     

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     

Individual irrationality,network structure,and collective intelligence: An agent‐based simulation approach

An agent‐based model is constructed to study the effects of individual irrationality and network structure on collective performance. We find that individual irrationality and network density are the most influential factors. Moderate degree of irrationality results in moderate knowledge unity and superior quality of knowledge; increasing network connections or decreasing average path length (APL) can promote quality of knowledge integration and knowledge unity. Furthermore, APL is more influential than clustering coefficient and centralization (CE). Less clustering may contribute to higher quality of knowledge integration, while higher CE may contribute to higher knowledge unity. © 2015 Wiley Periodicals, Inc. Complexity 21: 44–54, 2016     

Exploring express delivery networks in China based on complex network theory

Based on the complex network theory, we explore an express delivery system in China, which consists of two delivery networks, namely, the air delivery network (ADN) and the ground delivery network (GDN). Systematic structural analysis indicates that both delivery networks exhibit small‐world phenomenon, disassortative mixing behavior, and rich‐club phenomenon. However, there are significant differences between ADN and GDN in terms of degree distribution property and community structure. On the basis of the Barabási‐Albert model, we have proposed a network model incorporating the structural features of the two delivery networks to reveal their evolutionary mechanisms. Lastly, the parcel strength and the distance strength are analyzed, which, respectively, reflect the number of parcels and the long‐haul delivery distance handled by a node city. The strengths are highly heterogeneous in both delivery networks and have intense correlations with topological structures. These works are beneficial for express enterprises to construct or extend their express delivery networks, and provide some useful insights on improving parcel delivery service. © 2014 Wiley Periodicals, Inc. Complexity 21: 166–179, 2015     

A MICRO‐LEVEL ‘CONSUMER APPROACH’ TO SPECIES POPULATION DYNAMICS

ABSTRACT. In this paper we develop a micro ecosystem model whose basic entities are representative organisms which behave as if maximizing their net offspring under constraints. Net offspring is increasing in prey biomass intake, declining in the loss of own biomass to predators and Allee's law applies. The organism's constraint reflects its perception of how scarce its own biomass and the biomass of its prey is. In the short‐run periods prices (scarcity indicators) coordinate and determine all biomass transactions and net offspring which directly translates into population growth functions. We are able to explicitly determine these growth functions for a simple food web when specific parametric net offspring functions are chosen in the micro‐level ecosystem model. For the case of a single species our model is shown to yield the well‐known Verhulst‐Pearl logistic growth function. With two species in predator‐prey relationship, we derive differential equations whose dynamics are completely characterized and turn out to be similar to the predator‐prey model with Michaelis‐Menten type functional response. With two species competing for a single resource we find that coexistence is a knife‐edge feature confirming Tschirhart's [2002] result in a different but related model.     

A cellular automata model can quickly approximate UDP and TCP network traffic

Brooks and Orr [R.R. Brooks and N. Orr, A model for mobile code using interacting automata. IEEE Trans Mobile Computing 2002, 1(4)] present a model for analysis and simulation of mobile code systems based on cellular automata (CA) abstractions. One flaw with that article was a lack of experimental support showing that CA can model IP networks. This article presents CA models, consistent with those in the work of Brooks and Orr, that model the transport layer of IP networks. We show how these models may be generalized for more complicated network topologies. We provide quantitative results comparing the quality of our CA implementation versus the standard network modeling tool ns‐2. The results from the CA model are qualitatively similar to ns‐2, but the CA simulation runs significantly faster and scales better. © 2004 Wiley Periodicals, Inc. Complexity 9:32–40, 2004     

Distributed subgradient method for multi‐agent optimization with quantized communication

This paper focuses on a distributed optimization problem associated with a time‐varying multi‐agent network with quantized communication, where each agent has local access to its convex objective function, and cooperatively minimizes a sum of convex objective functions of the agents over the network. Based on subgradient methods, we propose a distributed algorithm to solve this problem under the additional constraint that agents can only communicate quantized information through the network. We consider two kinds of quantizers and analyze the quantization effects on the convergence of the algorithm. Furthermore, we provide explicit error bounds on the convergence rates that highlight the dependence on the quantization levels. Finally, some simulation results on a l₁‐regression problem are presented to demonstrate the performance of the algorithm. Copyright © 2016 John Wiley & Sons, Ltd.     

Simplicial complexes: Spectrum,homology and random walks

This paper studies the dynamical and asymptotic aspects of high‐dimensional expanders. We define a stochastic process on simplicial complexes of arbitrary dimension, which detects the existence of homology in the same way that a random walk on a finite graph reflects its connectedness. Through this, we obtain high‐dimensional analogues of graph properties such as bipartiteness, return probability, amenability and transience/recurrence. In the second part of the paper we generalize Kesten's result on the spectrum of regular trees, and of the connection between return probabilities and spectral radius. We study the analogue of the Alon‐Boppana theorem on spectral gaps, and exhibit a counterexample for its high‐dimensional counterpart. We show, however, that under some assumptions the theorem does hold ‐ for example, if the codimension‐one skeletons of the complexes in question form a family of expanders. © 2016 Wiley Periodicals, Inc. Random Struct. Alg., 50, 225–261, 2017     

The Hungarian insurance market structure: an empirical analysis

This paper analyzes the market structure of the Hungarian insurance market, which operated as a monopoly market until 1986. After the regime change this sector started to develop rapidly. But the Hungarian insurance market has a strong oligopolistic character, and thus raises an interesting question as to how close the market is to a state of perfect competition. Based on the Panzar and Rosse (J Ind Econ 35:443–456, 1987) methodology we estimate the elasticity of total revenues with respect to changes in input prices, so that we can determine the market structure. The estimation of input price elasticity is made with a static and a dynamic panel model. According to research the structure of the Hungarian insurance market significantly differs from the perfect competition case between 2010 and 2019. The market is in long-run equilibrium, and the hypothesis of the monopoly case cannot be rejected. The market structure of a sector is important for modelling phenomena and new regulations effectively, which is relevant for insurance and competition supervision in the protection of customers.

     

Patterning by genetic networks

We consider here the morphogenesis (pattern formation) problem for some genetic network models. First, we show that any given spatio‐temporal pattern can be generated by a genetic network involving a sufficiently large number of genes. Moreover, patterning process can be performed by an effective algorithm. We also show that Turing's or Meinhardt's type reaction–diffusion models can be approximated by genetic networks. These results exploit the fundamental fact that the genes form functional units and are organized in blocks. Due to this modular organization, the genes always are capable to construct any new patterns and even any time sequences of new patterns from old patterns. Computer simulations illustrate some analytical results. Copyright © 2005 John Wiley & Sons, Ltd.     

企业研发组织沟通网络实证及优化策略研究

鉴于企业研发组织内部沟通网络对研发组织中高效、低成本地实现技术信息共享的重要性,本文首先介绍了结构洞的测度方法,并对中间中心性方法进行改进;其次分析了某企业研发组织沟通网络的结构洞情况,指出非正式沟通网络和专业沟通网络的相关性;然后通过比较改进的中心度算法、传统的中心度算法与限制度指标的相似性,验证了该算法的有效性;最后提出一种削弱沟通网络中“核心人物”垄断地位的“搭桥”策略。结果发现:改进的中心度算法适用于带权值沟通网络结构洞的测定,验证了该算法加权方法的有效性,并给出通过非正式组织促进技术信息共享的对策     

BML revisited: Statistical physics,computer simulation,and probability

Statistical physics, computer simulation, and discrete mathematics are intimately related through the study of shared lattice models. These models lie at the foundation of all three fields, are studied extensively, and can be highly influential. Yet new computational and mathematical tools may challenge even well‐established beliefs. Consider the BML model, which is a paradigm for modeling self‐organized patterns of traffic flow and first‐order jamming transitions. Recent findings, on the existence of intermediate states, bring into question the standard understanding of the jamming transition. We review the results and show that the onset of full‐jamming can be considerably delayed based on the geometry of the system. We also introduce an asynchronous version of BML, which lacks the self‐organizing properties of BML, has none of the puzzling intermediate states, but has a sharp, discontinuous, transition to full jamming. We believe this asynchronous version will be more amenable to rigorous mathematical analysis than standard BML. We discuss additional models, such as bootstrap percolation, the honey‐comb dimer model and the rotor‐router, all of which exemplify the interplay between the three fields, while also providing cautionary tales. Finally, we synthesize implications for how results from one field may relate to the other, and also implications specific to computer implementations. © 2006 Wiley Periodicals, Inc. Complexity, 12, 30–39, 2006     

Estimation of nonstrict Archimedean copulas and its application to quantum networks

Bivariate nonstrict Archimedean copulas form a subclass of Archimedean copulas and are able to model the dependence structure of random variables that do not take on low quantiles simultaneously; i.e. their domain includes a set, the so‐called zero set, with positive Lebesgue measure but zero probability mass. Standard methods to fit a parametric Archimedean copula, e.g. classical maximum likelihood estimation, are either getting computationally more involved or even fail when dealing with this subclass. We propose an alternative method for estimating the parameter of a nonstrict Archimedean copula that is based on the zero set and the functional form of its boundary curve. This estimator is fast to compute and can be applied to absolutely continuous copulas but also allows singular components. In a simulation study, we compare its performance to that of the standard estimators. Finally, the estimator is applied when modeling the dependence structure of quantities describing the quality of transmission in a quantum network, and it is shown how this model can be used effectively to detect potential intruders in this network. Copyright © 2014 John Wiley & Sons, Ltd.     

TIMBER SUPPLY UNDER DEMAND UNCERTAINTY: WELFARE GAINS FROM PERFECT COMPETITION WITH RATIONAL EXPECTATIONS

ABSTRACT. This paper presents a noneconometric approach to estimating the short‐run timber supply function based on optimal harvest decisions. Determination of optimal harvest levels and estimation of supply function coefficients are integrated into one step by incorporating a parametric short‐run timber supply function into the harvest decision model. In this manner we convert the original harvest decision model into a new optimization problem with the supply function coefficients functioning as “decision variables.” Optimal solution to the new decision model gives the coefficients of the short‐run supply function and, indirectly, the optimal harvest levels. This approach enables us to develop stochastic models of the timber market that are particularly useful for forest sector analysis involving comparison of alternative institutional regimes or policy proposals and when the timber market is affected by stochastic variables. For demonstration purposes, we apply this method to compare the performances of two timber market regimes (perfect competition and monopoly) under demand uncertainty, using the Swedish data. The results show that the expected timber price is 22 percent lower and the expected annual timber supply is 43 percent higher in the competitive market than in the monopoly market. This confirms the theoretical result that monopoly reduces supply and increases price. The expected social welfare gain from perfect competition over monopoly is about 24 percent.     

A methodology for analyzing decision networks, based on information theory

This paper assumes the organization as a distributed decision network. It proposes an approach based on application and extension of information theory concepts, in order to analyze informational complexity in a decision network, due to interdependence between decision centers.Based on this approach, new quantitative concepts and definitions are proposed in order to measure the information in a decision center, based on Shannon entropy and its complement in possibility theory, U uncertainty. This approach also measures the quantity of interdependence between decision centers and informational complexity of decision networks.The paper presents an agent-based model of organization as a graph composed of decision centers. The application of the proposed approach is in analyzing and assessing a measure to the organization structure efficiency, based on informational communication view. The structure improvement, analysis of information flow in organization and grouping algorithms are investigated in this paper. The results obtained from this model in different systems as distributed decision networks, clarifies the importance of structure and information distribution sources effect’s on network efficiency.