21,773 research outputs found
Retail Pricing Behavior for Perishable Produce Products in the US with Implications for Farmer Welfare
The typical model of retail pricing for produce products assumes retailers set price equal to the farm price plus a certain markup. However, observations from scanner data indicate a large degree of price dispersion in the grocery retailing market. In addition to markup pricing behavior, we document three alternative leading pricing patterns: fixed (constant) pricing, periodic sale, and high-low pricing. Retail price variations under these alternative pricing regimes in general have little correlation with the farm price. How do retailers’ alternative pricing behaviors affect farmers’ welfare? Using markup pricing as the baseline case, we parameterize the model to reflect a prototypical fresh produce market and carry out a series of simulations under different pricing regimes. Our study shows that if harvest cost is sufficiently low, retail prices adjusting only partially, or not at all, to supply shocks tends to diminish farm income and exacerbate farm price volatility relative to the baseline case. However, we also find that if harvest cost is sufficiently large and the harvest-cost constraint places a lower bound on the farm price, increased farm price volatility induced by retailers’ alternative pricing strategies may result in higher farm income, compared to markup pricing. Our study is the first to evaluate the welfare implications for producers of the diversified pricing strategies that retailers utilize in practice and the resulting attenuation of the relationship between prices at retail and at the farm gate.Agribusiness, Demand and Price Analysis,
Strong Stationary Duality for M\"obius Monotone Markov Chains: Unreliable Networks
For Markov chains with a partially ordered finite state space we show strong
stationary duality under the condition of M\"obius monotonicity of the chain.
We show relations of M\"obius monotonicity to other definitions of monotone
chains. We give examples of dual chains in this context which have transitions
only upwards. We illustrate general theory by an analysis of nonsymmetric
random walks on the cube with an application to networks of queues
Exploiting Channel Memory for Multi-User Wireless Scheduling without Channel Measurement: Capacity Regions and Algorithms
We study the fundamental network capacity of a multi-user wireless downlink
under two assumptions: (1) Channels are not explicitly measured and thus
instantaneous states are unknown, (2) Channels are modeled as ON/OFF Markov
chains. This is an important network model to explore because channel probing
may be costly or infeasible in some contexts. In this case, we can use channel
memory with ACK/NACK feedback from previous transmissions to improve network
throughput. Computing in closed form the capacity region of this network is
difficult because it involves solving a high dimension partially observed
Markov decision problem. Instead, in this paper we construct an inner and outer
bound on the capacity region, showing that the bound is tight when the number
of users is large and the traffic is symmetric. For the case of heterogeneous
traffic and any number of users, we propose a simple queue-dependent policy
that can stabilize the network with any data rates strictly within the inner
capacity bound. The stability analysis uses a novel frame-based Lyapunov drift
argument. The outer-bound analysis uses stochastic coupling and state
aggregation to bound the performance of a restless bandit problem using a
related multi-armed bandit system. Our results are useful in cognitive radio
networks, opportunistic scheduling with delayed/uncertain channel state
information, and restless bandit problems.Comment: 17 pages, 8 figures. Submitted to IEEE Transactions on Information
Theory. The whole paper is revised and the title is changed for better
clarification
Reversibility in Queueing Models
In stochastic models for queues and their networks, random events evolve in
time. A process for their backward evolution is referred to as a time reversed
process. It is often greatly helpful to view a stochastic model from two
different time directions. In particular, if some property is unchanged under
time reversal, we may better understand that property. A concept of
reversibility is invented for this invariance. Local balance for a stationary
Markov chain has been used for a weaker version of the reversibility. However,
it is still too strong for queueing applications.
We are concerned with a continuous time Markov chain, but dose not assume it
has the stationary distribution. We define reversibility in structure as an
invariant property of a family of the set of models under certain operation.
The member of this set is a pair of transition rate function and its supporting
measure, and each set represents dynamics of queueing systems such as arrivals
and departures. We use a permutation {\Gamma} of the family menmbers, that is,
the sets themselves, to describe the change of the dynamics under time
reversal. This reversibility is is called {\Gamma}-reversibility in structure.
To apply these definitions, we introduce new classes of models, called
reacting systems and self-reacting systems. Using those definitions and models,
we give a unified view for queues and their networks which have reversibility
in structure, and show how their stationary distributions can be obtained. They
include symmetric service, batch movements and state dependent routing.Comment: Submitted for publicatio
Random walks with imperfect trapping in the decoupled-ring approximation
We investigate random walks on a lattice with imperfect traps. In one
dimension, we perturbatively compute the survival probability by reducing the
problem to a particle diffusing on a closed ring containing just one single
trap. Numerical simulations reveal this solution, which is exact in the limit
of perfect traps, to be remarkably robust with respect to a significant
lowering of the trapping probability. We demonstrate that for randomly
distributed traps, the long-time asymptotics of our result recovers the known
stretched exponential decay. We also study an anisotropic three-dimensional
version of our model, where for sufficiently large transverse diffusion the
system is described by the mean-field kinetics. We discuss possible
applications of some of our findings to the decay of excitons in semiconducting
organic polymer materials, and emphasize the crucial influence of the spatial
trap distribution on the kinetics.Comment: 10 page
Axiomatic Construction of Hierarchical Clustering in Asymmetric Networks
This paper considers networks where relationships between nodes are
represented by directed dissimilarities. The goal is to study methods for the
determination of hierarchical clusters, i.e., a family of nested partitions
indexed by a connectivity parameter, induced by the given dissimilarity
structures. Our construction of hierarchical clustering methods is based on
defining admissible methods to be those methods that abide by the axioms of
value - nodes in a network with two nodes are clustered together at the maximum
of the two dissimilarities between them - and transformation - when
dissimilarities are reduced, the network may become more clustered but not
less. Several admissible methods are constructed and two particular methods,
termed reciprocal and nonreciprocal clustering, are shown to provide upper and
lower bounds in the space of admissible methods. Alternative clustering
methodologies and axioms are further considered. Allowing the outcome of
hierarchical clustering to be asymmetric, so that it matches the asymmetry of
the original data, leads to the inception of quasi-clustering methods. The
existence of a unique quasi-clustering method is shown. Allowing clustering in
a two-node network to proceed at the minimum of the two dissimilarities
generates an alternative axiomatic construction. There is a unique clustering
method in this case too. The paper also develops algorithms for the computation
of hierarchical clusters using matrix powers on a min-max dioid algebra and
studies the stability of the methods proposed. We proved that most of the
methods introduced in this paper are such that similar networks yield similar
hierarchical clustering results. Algorithms are exemplified through their
application to networks describing internal migration within states of the
United States (U.S.) and the interrelation between sectors of the U.S. economy.Comment: This is a largely extended version of the previous conference
submission under the same title. The current version contains the material in
the previous version (published in ICASSP 2013) as well as material presented
at the Asilomar Conference on Signal, Systems, and Computers 2013, GlobalSIP
2013, and ICML 2014. Also, unpublished material is included in the current
versio
- …