Two-sided Adverse Selection and Bilateral Reviews in the Sharing Economy

Online peer-to-peer platforms match service providers with consumers. Both providers and consumers derive heterogeneous payoffs depending on whom they are matched with. To ensure that providers and consumers identify the most valuable matches, many of these platforms elicit relevant information from and also disclose the information to the market participants by adopting bilateral review schemes. Although the bilateral review scheme has its own merits in reducing information asymmetry and possibly enabling better matches, its impact on the various stakeholders in online peer-to-peer platforms remains unexplored. We show that, in equilibrium, the bilateral review scheme intensifies price competition among service providers to attract low-cost consumers and consequently reduces the platform\u27s profit. Interestingly, service providers may be better off with more intense price competition and lower prices when the proportion of low-cost consumers is sufficiently high. More importantly, we find that social welfare is not always higher under the bilateral review scheme compared to either the unilateral review scheme or no reviews. Our findings demonstrate that even though the bilateral review scheme eliminates the information asymmetry and adverse selection on both sides of the market, it does not necessarily enhance market efficiency when competing providers strategically respond to reviews by adjusting their prices

An extended mixed-integer programming formulation and dynamic cut generation approach for the stochastic lot sizing problem

We present an extended mixed-integer programming formulation of the stochastic lot-sizing problem for the static-dynamic uncertainty strategy. The proposed formulation is significantly more time efficient as compared to existing formulations in the literature and it can handle variants of the stochastic lot-sizing problem characterized by penalty costs and service level constraints, as well as backorders and lost sales. Also, besides being capable of working with a predefined piecewise linear approximation of the cost function-as is the case in earlier formulations-it has the functionality of finding an optimal cost solution with an arbitrary level of precision by means of a novel dynamic cut generation approach

Renal complications of lipodystrophy: A closer look at the natural history of kidney disease

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/144612/1/cen13732_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/144612/2/cen13732.pd

Replenishment Cycle Inventory Policies with Non-Stationary Stochastic Demand

Inventory control problems constitute one of the most important research problems due to their connection with real life applications. Naturally, real life is full of uncertainty so are the most of the inventory problems. Unfortunately, it is a very challenging task to manage inventories effectively especially under uncertainty. This dissertation mainly deals with single-item, periodic review, and stochastic dynamic inventory control problems particularly on replenishment cycle control rule known as the (R, S) policy. Contribution of this thesis is multiold. In each chapter a particular research question is investigated. At the end of the day, we will be showing that non-stationary (R, S) policies are indispensable not only for its cost efficiency but its effectiveness and practicality. More specifically, the non-stationary (R, S) policy provides a convenient, efficient, effective, and modular solution for non-stationary stochastic inventory control problems

GENERALIZED HERMITE-HADAMARD TYPE INEQUALITIES FOR PRODUCTS OF CO-ORDINATED CONVEX FUNCTIONS

In this paper, we think products of two co-ordinated convex functions for the Hermite-Hadamard type inequalities. Using these functions we obtained Hermite-Hadamard type inequalities which are generalizations of some results given in earlier works.WOS:00054543290003

Heuristics for the stochastic economic lot sizing problem with remanufacturing under backordering costs

We consider a production system where demand can be met by manufacturing new products and remanufacturing returned products, and address the economic lot sizing problem therein. The system faces stochastic and time-varying demands and returns over a finite planning horizon. The problem is to match supply with demand, while minimizing the total expected cost which is comprised of fixed production costs and inventory (holding and backordering) costs. We introduce heuristic policies for this problem which offer different levels of flexibility with respect to production decisions. We present computational methods for these policies based on convex optimization and certainty equivalent mixed integer programming, and numerically assess their cost performance and computational efficiency by means of simulation

Bin packing problem with restricted item fragmentation: Assignment of jobs in multi-product assembly environment with overtime

This paper studies the assignment problem of multi product assembly jobs to days. The problem aims to minimize the amount of overtime while avoiding assembly delays for jobs that can be fragmented into smaller sub-tasks. When sequence-dependent setup times are negligible, the problem considered transforms into the bin packing problem with restricted item fragmentation where jobs represent items and days stand for bins. We present a mixed integer programming model of the problem by extending earlier formulations in the literature. Computational experiments show that the mathematical model obtained optimal solutions for majority of instances tested within reasonable computation times

Quantum Ostrowski-type integral inequalities for functions of two variables

In this study, we established some new inequalities of Ostrowski type for the functions of two variables by using the concept of newly defined double quantum integrals. We also revealed that the results presented in this paper are the consolidation and generalization of some existing results on the literature of Ostrowski inequalities.WOS:0006160642000012-s2.0-8510076447

Single-Dimensional Versus Multi-Dimensional Product Ratings in Online Marketplaces for Experience Goods

We examine the strategic implications of multi-dimensional and single-dimensional rating schemes in online review platforms when consumers have heterogeneous preferences for different quality dimensions. We find that attribute specialization and firm differentiation play significant roles in determining the impact of the rating scheme on the platform, consumers, and the society. If at least one firm specializes in an attribute, then the platform is better off implementing multi-dimensional rating scheme if and only if the firms are differentiated. Interestingly, while the consumers\u27 uncertainty is always reduced by multi-dimensional scheme, the consumers are better off under the multi-dimensional rating scheme only when the firms are not differentiated. The results show that the focus on information transfer aspect of rating schemes provide only a partial understanding of the true impact of rating schemes and the platform\u27s optimal choice of rating scheme depends critically on the product markets served by the platform