A budgeting resource allocation model for capacity expansion
Authors: Senay Solak, Zhuoxin Li, Mehmet Gumus and Yueran Zhuo
Managing Channel Profits with Positive Demand Externalities
础耻迟丑辞谤蝉:听Long Gao, Dawei Jian, Mehmet Gumus and Barry Mishra
Publication:聽Management Science, Forthcoming 2024.
Inventory Control and Learning for One-Warehouse Multistore system with Censored Demand
Authors: Recep Yusuf Bekci, Mehmet Gumus and Sentao Miao.
Publication: Operations Research, Forthcoming. Article in advance, published online: August 2, 2023.
Desautels鈥� event highlights innovative research and recognizes scholars
On Friday, May 13, members of the Desautels Faculty of Management gathered to celebrate the innovative and impactful research conducted by its scholars.聽
Fifteen professors were on hand to deliver two-minute presentations of their most interesting and research.
Online-Exclusive or Hybrid? Channel Merchandising Strategies for Ship-to-Store Implementation
Authors: N. Ertekin, Mehmet Gumus, and M.E. Nikoofal
Publication: Management Science, Forthcoming
Abstract:
An Empirical Analysis of Intra-Firm Product Substitutability in Fashion Retailing
Authors: E. Ergin, Mehmet Gumus, and N. Yang
Publication: Production and Operations Management, Forthcoming
Abstract:
Desautels professors awarded IVADO research funding
Four Desautels professors have been awarded research grants by the Institute for Data Valorization (IVADO), a Montreal-based scientific and economic data science hub. The grants will fund three two-year research projects led by Desautels professors as part of IVADO鈥檚 Fundamental Research Funding Program.
Value of Audit for Supply Chains with Hidden Action and Information
础耻迟丑辞谤蝉:听Mohammad Nikoofal, Mehmet Gumus
Publication: European Journal of Operational Research, Forthcoming
Abstract:
Supply Competition under Quality Scores: Motivations, Information Sharing and Credibility
础耻迟丑辞谤蝉:听Hedayat Alibeiki, Mehmet Gumus
Publication: International Journal of Production Economics, Forthcoming
Abstract:
Professor Mehmet Gumus awarded 2019 NSERC Discovery Grant
Mehmet Gumus, Associate Professor in Operations Management was recently awarded a 2019 NSERC Discovery Grant.
Optimizing Foreclosed Housing Acquisitions in Societal Response to Foreclosures
础耻迟丑辞谤蝉:听Senay Solak, Armagan Bayram, Mehmet Gumus,聽Yueran Zhuo
Publication: Operations Research, Forthcoming
Abstract:
A dramatic increase in U.S. mortgage foreclosures during and after the great economic recession of 2007-2009 had devastating impacts on the society and the economy. In response to such negative impacts, non-profit community development corporations (CDCs) throughout the U.S. utilize various resources, such as grants and lines of credit, in acquiring and redeveloping foreclosed housing units to support neighborhood stabilization and revitalization. Given that the cost of all such acquisitions far exceeds the resources accessible by these non-profit organizations, we identify socially optimal policies for CDCs in dynamically selecting foreclosed properties to target for potential acquisition as they become available over time. We evaluate our analytical results in a numerical study involving a CDC serving a major city in the U.S, and specify social return based thresholds defining selection decisions at different funding levels. We also find that for most foreclosed properties CDCs should not offer more than the asking price, and should typically consider overbidding only when the total available budget is low. Overall, comparisons of optimal policies with historical acquisition data suggest a potential improvement of around 20% in expected total impacts of the acquisitions on nearby property values. Considering a CDC with annual fund availability of $4 million for investment, this corresponds to an estimated additional value of around $280,000 for the society.
Designing Risk鈥怉djusted Therapy for Patients with Hypertension
础耻迟丑辞谤蝉:听Manaf Zargoush, Mehmet Gumus, Vedat Verter,聽Stella S. Daskalopoulou
Publication: Production and Operations Management, Forthcoming
Abstract:
Limited guidance is available for providing patient鈥恠pecific care to hypertensive patients, although this chronic condition is the leading risk factor for cardiovascular diseases. To address this issue, we develop an analytical model that takes into account the most relevant risk factors including age, sex, blood pressure, diabetes status, smoking habits, and blood cholesterol. Using the Markov Decision Process framework, we develop a model to maximize expected quality鈥恆djusted life years, as well as characterize the optimal sequence and combination of antihypertensive medications. Assuming the physician uses the standard medication dose for each drug, and the patient fully adheres to the prescribed treatment regimen, we prove that optimal treatment policies exhibit a threshold structure. Our findings indicate that our recommended thresholds vary by age and other patient characteristics, for example (1) the optimal thresholds for all medication prescription are nonincreasing in age, and (2) the medications need to be prescribed at lower thresholds for males who smoke than for males who have diabetes. The improvements in quality鈥恆djusted life years associated with our model compare favorably with those obtained by following the British Hypertension Society's guideline, and the gains increase with the severity of risk factors. For instance, in both genders (although at different rates), diabetic patients gain more than non鈥恉iabetic patients. Our sensitivity analysis results indicate that the optimal thresholds decrease if the medications have lower side鈥恊ffects and vice versa.
Quality at the Source or at the End? Managing Supplier Quality Under Information Asymmetry
础耻迟丑辞谤蝉:听Mohammad E. Nikoofal, Mehmet Gumus
Publication: Manufacturing & Service Operations Management, Vol. 20, No. 3, Summer 2018
Abstract:
Supply Diagnostic Incentives under Endogenous Information Asymmetry
础耻迟丑辞谤蝉:听Mohammad E. Nikoofal,聽Mehmet Gumus
Publication: Production and Operations Management, Forthcoming
Abstract:
This paper develops a dyadic supply chain model with one buyer who contracts the manufacturing of a new product to a supplier. Due to the lack of experience in manufacturing, the extent of supply risk is unknown to both the buyer and supplier before the time of contract. However, after the contract is accepted, the supplier may invest in a diagnostic test to acquire information about his true reliability, and use this information when deciding on a process improvement effort. Using this setting, we identify both operational and strategic benefits and costs of diagnostic test. Operationally, it helps the supplier to take the first-best level of improvement effort, which would increase efficiency of the total supply chain. Strategically, it enables the buyer to reduce the agency costs associated with implementing process improvement on the supplier. Besides these benefits, diagnostic test increases the degree of information asymmetry along the supply chain. This in turn provides the supplier with proprietary information, whose rent would be demanded from the buyer in equilibrium. Benefit-cost analysis reveals two key factors in determining the value of diagnostic test: (i) degree of endogenous information asymmetry between supply chain firms, and (ii) the relative cost of diagnostic test with respect to process improvement cost. Our results indicate that when both are high, the mere presence of diagnostic test can result in less reliable supply chain. This implies that when incentives are not properly aligned, information asymmetry amplified due to diagnostic test neutralizes all its benefits.
Designing Risk-Adjusted Therapy for Patients with Hypertension
Authors: Manaf Zargoush, Mehmet Gumus, Vedat Verter, Stella Daskalopoulou
Journal Name: Production and Operations Management, Forthcoming
Abstract:
Hypertension has not been well studied by operations researchers from a clinical decision support perspective. Moreover, little personalized (i.e. patient-centric) guidance is available regarding the number and combination of antihypertensive medications. To fill this gap, we develop a Markov Decision Process (MDP) to characterize the optimal sequence (and combination) of antihypertensive medications under the standard medication dose. Our model is patient-centric as it takes into account a set of relevant patient characteristics such as age, gender, blood pressure level, smoking habits, diabetes status, and cholesterol level. Based on a set of intuitive assumptions, we prove that our model yields a series of structured optimal policies. Having calibrated our model based on real data and medical literature, we analyze these optimal policies and discuss their insights to the real practice. We also compare the benefits, in terms of quality adjusted life expectancy, QALE, obtained from our results with those obtained from British Hypertension Society (BHS) guideline.
