Optimal Pricing and Order-Up-To S Inventory Policy with Expected Utility of the Present Value Criterion

The article determines pricing and order-up-to level S inventory decisions over an infinite planning horizon from the point of view of a risk-averse decision maker. The demand is assumed to be stochastic but influenced by the selling price which is a decision variable. Shortages are allowed and backordered partially. We calculate the present value of the cash flow over the entire planning horizon and incorporate the notion of risk aversion into the model using a concave utility function. We numerically demonstrate the model and investigate the impact of different model-parameters on the optimal decisions. It is observed that the optimal selling price for a risk-averse decision maker is not less than the optimal selling price of a risk-neutral decision maker while the optimal order level for the risk-averse decision maker is always less than that of the risk-neutral decision maker.     

Managing inventory with two suppliers under yield uncertainty and risk aversion

In this paper, we consider a single-product single-period inventory model in which the retailer can source from two suppliers. The primary supplier is cheaper but unreliable in the sense that it generates supply yield uncertainty, whereas the secondary supplier is perfectly reliable but more expensive. The reliable supplier's capacity is fixed and the retailer cannot order more than the quantity reserved in advance. We study the problem in the context of a risk-averse retailer who has to determine the optimal order quantity from the primary supplier and the optimal reserved quantity from the secondary supplier. We develop the model in the perspective of a low risk averse retailer and quantify the risk via an exponential utility function. We show by numerical experiments how the resulting dual sourcing strategies differ from those obtained in the risk-neutral analysis. We also examine the sensitivity of some model-parameters on the optimal decisions.     

Personality,organization-specific attitude,and socioeconomic correlates of charity giving behavior

It should be noted that due to the composition of the sample, the specific findings of this study are not intended to be generalized to the population. The results of the discriminant analysis, nevertheless, provide some evidence that socioeconomic variables are more efficient than both organization-specific attitudes and personality variables in discriminating donors and nondonors. The analyses also show that personality variables used in this study do not contribute to a separation of nondonor/donor groups. Ford Motor Company The authors gratefully acknowledge the research support of University Research Committee, Ball State University in this study.     

Human Capital,Organizational Orientations and Performance: Evidence From the Restaurant Industry

ABSTRACT

The study examines how human capital combines with and influences organizational orientations to determine performance. Specifically, this study investigates small restaurant businesses’ ability to effectively exploit intangible resources and capabilities, rather than tangible resources, in order to produce sustainable competitive advantage. A structured questionnaire was used to survey owners/managers of small independent restaurants in the United States. The results demonstrate that human capital, market orientation and entrepreneurial orientation serve as intangible resources and capabilities that can augment the competitive position of independent restaurants, and thereby improve performance. Human capital also combines with and influences the adoption of market orientation and subsequent performance.     

Biogeography based optimization for mining rules to assess credit risk

Financial institutions, by and large, rely on the use of machine learning techniques to improve the classic credit risk assessment model for reduction of costs, delivery of faster decisions, guaranteed credit collections, and risk mitigations. As such, several data mining and machine learning approaches have been developed for computation of credit scores over the last few decades. Moreover, the existing rule-based classification algorithms tend to generate a number of rules with a large number of conditions in the antecedent part. However, these algorithms fail to demonstrate high predictive accuracy while balancing coverage and simplicity. Thus, it becomes quite a challenging task for the researchers to generate an optimal rule set with high predictive accuracy. In this paper, we present an effective rule based classification technique for the prediction of credit risk using a novel Biogeography Based Optimization (BBO) method. The novel BBO in the context of rule mining is named as locally and globally tuned biogeography based rule-miner (LGBBO-RuleMiner). This is applied for discovering optimal rule set with high predictive accuracy from the dataset containing both the categorical and continuous attributes. The performance of the proposed algorithm is compared against a variety of rule-miners such as OneR (1R), PART, JRip, Decision Table, Conjunctive Rule, J48, and Random Tree, along with some meta-heuristic based rule mining techniques by considering two credit risk datasets obtained from University of California, Irvine (UCI) repository. It is found from the comparative study that the proposed rule miner in ten independent runs of ten-fold cross validation outperforms all of the aforesaid algorithms in terms of predictive accuracy, coverage, and simplicity.     

Local costs of distribution,international trade costs and micro evidence on the law of one price

This paper connects trade flows to deviations from the law of one price (LOOP) in a structural model of trade and retailing. It accounts for the observed cross-country dispersion in prices of goods, based on retail price survey data, by focusing on two sources of goods market segmentation — (i) international trade costs, and (ii) non-traded input costs of distribution. I find that a multi-sector Ricardian trade model, ala Eaton–Kortum, augmented with a distribution sector, can account for the average price dispersion for a basket of goods fully and generates 70% of the variation in price dispersion across goods within the basket. While tradability of goods is important in explaining the average price dispersion for the basket of goods, distribution costs are important in explaining why, within the basket, some goods show more price dispersion than others.     

Locally minimax test of independence in elliptically symmetrical distributions with additional observations

Summary LetX=(X _ij )=(X ₁, ...,X _n )’,X’ _i =(X _i1, ...,X _ip )’,i=1,2, ...,n be a matrix having a multivariate elliptical distribution depending on a convex functionq with parameters, 0,σ. Let ϱ²=ϱ ₂ ^-2 be the squared multiple correlation coefficient between the first and the remainingp ₂+p ₃=p−1 components of eachX _i . We have considered here the problem of testingH ₀:ϱ²=0 against the alternativesH ₁:ϱ ₁ ^-2 =0, ϱ ₂ ^-2 >0 on the basis ofX andn ₁ additional observationsY ₁ (n ₁×1) on the first component,n ₂ observationsY ₂(n ₂×p ₂) on the followingp ₂ components andn ₃ additional observationsY ₃(n ₃×p ₃) on the lastp ₃ components and we have derived here the locally minimax test ofH ₀ againstH ₁ when ϱ ₂ ^-2 →0 for a givenq. This test, in general, depends on the choice ofq of the familyQ of elliptically symmetrical distributions and it is not optimality robust forQ.     

Locally minimax tests for a multinormal data problem

LetX be ap-normal random vector with unknown mean and unknown covariance matrix and letX be partitioned asX=(X ₍₁₎ ,X ₍₂₎ , ...,X _(r) ) whereX _(j) is a subvector of dimensionp _j such that _j=1 ^r p _j =p. We show that the tests, obtained by Dahel (1988), are locally minimax. These tests have been derived to confront H_o: =0 versusH ₁: 0 on the basis of sample of sizeN, X ₁, ..., X_N, drawn fromX andr additional samples of sizeN _j, U _i ^(j) , i=1, ..., N_j, drawn fromX ₍₁₎, ...X _(r) respectively. We assume that the (r+1) samples are independent and thatN _j>p _j forj=0, 1, ..., r (N _oN andp _op). Whenr=2 andp=2, a Monte Carlo study is performed to compare these tests with the likelihood ratio test (LRT) given by Srivastava (1985). We also show that no locally most powerful invariant test exists for this problem.     

The impact of financial development,economic growth,income inequality on poverty: evidence from India

This paper examines the impact of financial development, economic growth and income inequality on poverty in India from 1970 to 2015 by employing the autoregressive distributed lag (ARDL) bounds testing procedure. The findings reveal a robust long-run relationship between financial development, economic growth, inequality and poverty. Results show that financial development and economic growth help in poverty reduction in India, whereas income inequality and inflation aggravate poverty. Empirical evidence of the Granger-causality test supports the presence of unidirectional causality from financial development and economic growth to poverty. Moreover, bidirectional causality exists between inequality and poverty. The present study provides evidence on which the policymakers may proceed with detailed investigation of how specific financial sector policies and interventions can be deployed as effective instruments for achieving favorable economic growth and income distribution. The study recommends that policies geared toward increasing financial development and economic growth should be adopted to reduce the high level of poverty and inequality currently prevailing in India.     

Healthcare resource utilization with ixazomib or placebo plus lenalidomide-dexamethasone in the randomized,double-blind,phase 3 TOURMALINE-MM1 study in relapsed/refractory multiple myeloma

Aims: The aim of this analysis was to assess healthcare resource utilization in the pivotal phase 3 TOURMALINE-MM1 study of the oral proteasome inhibitor ixazomib or placebo plus lenalidomide and dexamethasone (Rd) in relapsed and/or refractory multiple myeloma (RRMM).

Methods: In this double-blind, placebo-controlled, randomized study (NCT01564537), 722 patients with RRMM following 1–3 prior lines of therapy received Rd plus ixazomib (ixazomib-Rd; n?=?360) or matching placebo (placebo-Rd; n?=?362) until disease progression or unacceptable toxicity. Healthcare resource utilization data were captured on Day 1 of each 28-day cycle, every 4 weeks during follow-up for progression-free survival, and every 12 weeks during subsequent follow-up, and included medical encounters (length of stay, inpatient, outpatient, and reason) and number of missing days from work or other activities for patients and caregivers.

Results: Exposure-adjusted rates of hospitalization were similar between the ixazomib-Rd and placebo-Rd arms, at 0.530 and 0.564 per patient year (ppy), respectively, as were outpatient visit rates (3.305 and 3.355 ppy). Mean length of hospitalization per patient was 10.0 and 10.8 days, respectively. In both arms, hospitalization and outpatient visit rates were higher in patients with two or three prior lines of treatment (ixazomib-Rd: 0.632 and 3.909 ppy; placebo-Rd: 0.774 and 3.539 ppy) compared with patients with one prior line (ixazomib-Rd: 0.460 and 2.888 ppy; placebo-Rd: 0.436 and 3.243 ppy). Patients and their caregivers who missed any work or other activity missed a median of 7 and 5 days in the ixazomib-Rd arm, respectively, vs 8 and 4 days with placebo-Rd.

Limitations: The study was not powered for a statistical comparison of healthcare resource utilization between treatment arms, nor did it capture costs associated with utilization of the identified healthcare resources.

Conclusions: This pre-specified analysis demonstrated that the all-oral triplet regimen of ixazomib added to Rd did not increase healthcare resource utilization compared with placebo-Rd.