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  • 1
    Online Resource
    Online Resource
    Institute for Operations Research and the Management Sciences (INFORMS) ; 2023
    In:  Manufacturing & Service Operations Management Vol. 25, No. 2 ( 2023-03), p. 468-488
    In: Manufacturing & Service Operations Management, Institute for Operations Research and the Management Sciences (INFORMS), Vol. 25, No. 2 ( 2023-03), p. 468-488
    Abstract: Problem definition: In brick-and-mortar fashion retail stores, inventory stockouts are frequent. When a specific size of a fashion product is out of stock, the unmet demand might not be completely lost because of spillovers to adjacent sizes of the same style or to other styles. Little research has been done to study consumer response to stockouts of fashion products because researchers had limited access to proprietary data of fashion retailers and because it is challenging to estimate stockout-based demand spillover patterns using existing approaches due to the enormous number of stockkeeping units (SKUs) and frequent stockouts in fashion retail stores. To fill this void in the literature, we empirically estimate the stockout-based demand spillover effect in a fashion retail setting. Methodology/results: We obtain a large-scale data set from a fashion retail chain selling world-renowned sportswear brands. The retail stores in the sample are dedicated to products of a single brand. Using around 1.5 million granular and real-time sales and inventory records of 217 stores, 503 men’s footwear products, and 4,024 SKUs over a two-year period, we develop a difference-in-differences framework to estimate the stockout-based cross-size demand spillover effect. We demonstrate the validity of this framework by conducting a pretrend test and a placebo test. We find that roughly 51.7% of the unmet demand of an out-of-stock SKU spills over to adjacent sizes of the same style when they are in stock: 25.1% to the adjacent-larger size and 26.6% to the adjacent-smaller size. The cross-size demand spillover effect is larger in regular stores than in flagship stores, larger for casual sports shoes than for specialized sports shoes, and larger for low-price products than for high-price products. Adapting an existing attribute-based demand model to our setting, we estimate that roughly 20.2% of the unmet demand of an out-of-stock SKU spills over to different styles when they are in stock. Taken together, these estimations suggest that about 28.1% of the unmet demand of an out-of-stock SKU becomes lost sales. We further find that when stockouts are widespread among SKUs, stockout-based demand spillovers are significantly reduced, resulting in much increased lost sales. Managerial implications: First, we empirically quantify the stockout-based cross-size demand spillover effect and its impact on lost sales in a brick-and-mortar fashion retail setting. Second, our simulation analysis shows that incorporating the cross-size demand spillover effect into the sportswear retail chain’s proactive transshipment decision can substantially reduce its transshipment cost and improve its profitability. Funding: S. Li and S. Huang were supported by the National Natural Science Foundation of China [Grant 72188101] and the Center for Data Centric Management in the Department of Industrial Engineering at Tsinghua University. Supplemental Material: The online appendices are available at https://doi.org/10.1287/msom.2022.1135 .
    Type of Medium: Online Resource
    ISSN: 1523-4614 , 1526-5498
    RVK:
    Language: English
    Publisher: Institute for Operations Research and the Management Sciences (INFORMS)
    Publication Date: 2023
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  • 2
    Online Resource
    Online Resource
    Institute for Operations Research and the Management Sciences (INFORMS) ; 2022
    In:  Management Science Vol. 68, No. 7 ( 2022-07), p. 5127-5145
    In: Management Science, Institute for Operations Research and the Management Sciences (INFORMS), Vol. 68, No. 7 ( 2022-07), p. 5127-5145
    Abstract: In the past two decades, many nursing homes converted their ownership status from nonprofit to for-profit (NP-to-FP). These conversions have drawn public scrutiny and triggered a debate about the implications of ownership conversions on nursing home performance. Exploring a nationwide panel data set of U.S. nursing homes from 2006 to 2017, we observe that nursing homes with higher financial distress are associated with higher likelihood of NP-to-FP conversions. The postconversion operating margins increased significantly. Converted nursing homes improved their financial performance by reducing operating costs while keeping net resident revenues unchanged. Both cutting registered nurse staffing and cutting overhead staffing contributed to reductions in operating costs; however, only the former cost-reduction measure had a negative impact on quality. On average, the postconversion quality of care declined. The effects of NP-to-FP conversions on nursing homes were moderated by preconversion financial distress: High-distress nursing homes aggressively cut registered nurse staffing and experienced severe quality decline, whereas low-distress ones kept registered nurse staffing unchanged and largely avoided quality decline. These findings lead to both policy and managerial insights. To nursing home regulators, we recommend increased oversight on NP-to-FP conversions of nursing homes with high preconversion financial distress. To managers of nursing homes undergoing NP-to-FP conversions, our findings suggest that although cost reduction is an effective strategy to improve financial performance, they need to avoid the pitfall of cutting registered nurse staffing and instead focus on streamlining overhead operations in order to increase operating efficiency without compromising quality. This paper was accepted by Stefan Scholtes, healthcare management.
    Type of Medium: Online Resource
    ISSN: 0025-1909 , 1526-5501
    RVK:
    Language: English
    Publisher: Institute for Operations Research and the Management Sciences (INFORMS)
    Publication Date: 2022
    detail.hit.zdb_id: 206345-1
    detail.hit.zdb_id: 2023019-9
    SSG: 3,2
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  • 3
    Online Resource
    Online Resource
    Institute for Operations Research and the Management Sciences (INFORMS) ; 2017
    In:  Management Science Vol. 63, No. 11 ( 2017-11), p. 3566-3585
    In: Management Science, Institute for Operations Research and the Management Sciences (INFORMS), Vol. 63, No. 11 ( 2017-11), p. 3566-3585
    Abstract: During the 2000s, over a dozen U.S. states passed laws that prohibit healthcare employers from mandating overtime for nurses. Using a nationwide panel data set from 2004 to 2012, we find that these mandatory overtime laws reduced the service quality of nursing homes, as measured by an increase in deficiency citations. This outcome can be explained by two undesirable changes in the staffing hours of registered nurses: decreased hours of permanent nurses and increased hours of contract nurses per resident day. We observe that the increase in deficiency citations concentrates in the domains of administration and quality of care rather than quality of life, and the severity levels of the increased citations tend to be minor rather than major. We also find that the laws’ negative effect on quality is more severe in nursing homes with higher percentages of Medicare-covered residents. These observations are consistent with the predictions of a stochastic staffing model that incorporates demand uncertainty and operational flexibility. Furthermore, we rule out an alternative hypothesis that the quality decline is induced by an increase in nurse wages. This paper was accepted by Gad Allon, operations management.
    Type of Medium: Online Resource
    ISSN: 0025-1909 , 1526-5501
    RVK:
    Language: English
    Publisher: Institute for Operations Research and the Management Sciences (INFORMS)
    Publication Date: 2017
    detail.hit.zdb_id: 206345-1
    detail.hit.zdb_id: 2023019-9
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  • 4
    Online Resource
    Online Resource
    Institute for Operations Research and the Management Sciences (INFORMS) ; 2022
    In:  Manufacturing & Service Operations Management Vol. 24, No. 2 ( 2022-03), p. 827-845
    In: Manufacturing & Service Operations Management, Institute for Operations Research and the Management Sciences (INFORMS), Vol. 24, No. 2 ( 2022-03), p. 827-845
    Abstract: Problem definition: Health information technology (HIT) interoperability refers to the ability of different electronic health record systems and software applications to communicate, exchange data, and use the information that has been exchanged. The U.S. Government has invested heavily to promote HIT interoperability in recent years in an attempt to improve patient outcomes and control healthcare expenditure. This study empirically assesses the value of HIT interoperability in the interhospital transfer process of heart attack patients. Academic/practical relevance: HIT interoperability is supposed to enable health information exchange between disparate providers. However, there exists little evidence about how it affects care delivery processes across providers. Methodology: Using transfer records of heart attack patients and HIT interoperability adoption records of hospitals in New York State between 2013 and 2015, we estimate the effect of HIT interoperability on care delivery process measures and patient outcome measures. We demonstrate the robustness of the results with alternative samples and model specifications, including the instrumental variable method, the propensity score matching method, the difference-in-differences method, and a falsification test. Results: We show that HIT interoperability shortens the throughput time of interhospital transfer by 45.6 minutes on average or 12.0%. Surprisingly, we find that HIT interoperability has little effect in reducing duplicate electrocardiogram (EKG) testing for transferred patients at receiving hospitals. When HIT interoperability is enabled through a common software vendor, it yields 15.6% more reduction in the throughput time than when it is enabled through different vendors, but it still has no significant effect on duplicate EKG testing. Furthermore, we find that HIT interoperability leads to a 3.0-percentage point decrease in the 30-day readmission rate of transferred patients, which can be explained by the reduction in the throughput time. Managerial implications: Our findings demonstrate the value of incentivizing HIT adoption and promoting widespread exchange of health information because HIT interoperability indeed improves the efficiency of healthcare delivery across providers, which ultimately translates to improved patient outcomes. Given the lack of reduction in duplicate testing in our study, we call for more provider effort toward realizing the full potential of HIT interoperability by minimizing the gap between technology adoption and utilization.
    Type of Medium: Online Resource
    ISSN: 1523-4614 , 1526-5498
    RVK:
    Language: English
    Publisher: Institute for Operations Research and the Management Sciences (INFORMS)
    Publication Date: 2022
    detail.hit.zdb_id: 2023273-1
    SSG: 3,2
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  • 5
    Online Resource
    Online Resource
    Institute for Operations Research and the Management Sciences (INFORMS) ; 2023
    In:  Manufacturing & Service Operations Management
    In: Manufacturing & Service Operations Management, Institute for Operations Research and the Management Sciences (INFORMS)
    Abstract: Problem definition: Social media has become an indispensable platform for disseminating quality information to consumers across various service sectors. Recently, it has extended its influence to healthcare services, which traditionally relied on government report cards to disclose standardized quality information to the public. This article explores the impact of social media on consumer demand for healthcare services and compares its effectiveness with government report cards. Methodology/results: We analyze quality ratings of U.S. nursing homes collected from two information channels: (1) consumer ratings on Yelp and (2) government ratings on Nursing Home Compare, both of which adopt a five-star quality rating scale and are accessible on the Internet. We employ the method of difference-in-differences with continuous treatment intensity and instrumental variables to analyze the data. Using nursing home resident admissions as a proxy for consumer demand, we find that higher Yelp ratings led to higher consumer demand, particularly among Medicare-covered consumers. Furthermore, the effect of Yelp ratings was primarily driven by extreme ratings (one-star or five-star), as opposed to neutral ratings. We also find that Yelp ratings exerted a stronger effect on consumer demand than government ratings. This dominance of Yelp ratings over government ratings was observed primarily in markets with high Yelp penetration or markets with low and medium consumer education levels. Although higher Yelp ratings were associated with increased net incomes, we find little evidence that nursing homes made quality improvement in response to their Yelp ratings. Managerial implications: We recommend that the Centers for Medicare and Medicaid Services recognize social media platforms as valuable sources of information and collaborate with reputable platforms, such as Yelp, to promote public awareness of government report cards like Nursing Home Compare. Moreover, we advise nursing home operators to proactively manage their reputation on social media by promptly addressing consumer complaints and implementing quality improvement measures. Funding: Y. Li was supported by the Shanghai Sailing Program [Grant 22YF1451000] and the Fundamental Research Funds for the Central Universities. S. F. Lu was supported by the Gerald Lyles rising star fund. Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2021.0303 .
    Type of Medium: Online Resource
    ISSN: 1523-4614 , 1526-5498
    RVK:
    Language: English
    Publisher: Institute for Operations Research and the Management Sciences (INFORMS)
    Publication Date: 2023
    detail.hit.zdb_id: 2023273-1
    SSG: 3,2
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  • 6
    Online Resource
    Online Resource
    Wiley ; 2018
    In:  Production and Operations Management Vol. 27, No. 12 ( 2018-12), p. 2251-2269
    In: Production and Operations Management, Wiley, Vol. 27, No. 12 ( 2018-12), p. 2251-2269
    Abstract: We empirically investigate the pattern of where heart attack patients are transferred between hospitals. Using 2011 Florida State Emergency Department and Inpatient Databases, we demonstrate the relative importance of three key factors in determining transfer destinations: (1) the distance between sending and receiving hospitals, (2) publicly reported quality measures of receiving hospitals, and (3) the relationship between sending and receiving hospitals as indicated by whether they are affiliated with the same multihospital system. Our conditional logit analysis shows that hospital relationship plays a more dominant role in determining transfer destinations than distance and quality. This result is robust to three alternative specifications of choice sets using distance ranking, radius circles, and Hospital Referral Regions, and also robust to alternative measures of distance and quality. Using 30‐day readmission rate to evaluate the health outcome of transferred patients, we find that relationship‐based transfers led to worse outcome than distance‐based and quality‐based transfers. We also find that nonprofit hospitals are more likely to conduct quality‐based transfers and less likely to conduct relationship‐based transfers than their for‐profit counterparts. Our study calls for reevaluating the current practice of relationship‐driven routing of heart attack patients—selecting transfer destinations based on quality or distance can potentially decrease hospital readmission rate.
    Type of Medium: Online Resource
    ISSN: 1059-1478 , 1937-5956
    URL: Issue
    RVK:
    Language: English
    Publisher: Wiley
    Publication Date: 2018
    detail.hit.zdb_id: 2151364-8
    detail.hit.zdb_id: 1108460-1
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  • 7
    Online Resource
    Online Resource
    Elsevier BV ; 2021
    In:  Research in International Business and Finance Vol. 57 ( 2021-10), p. 101408-
    In: Research in International Business and Finance, Elsevier BV, Vol. 57 ( 2021-10), p. 101408-
    Type of Medium: Online Resource
    ISSN: 0275-5319
    RVK:
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2021
    detail.hit.zdb_id: 2165501-7
    detail.hit.zdb_id: 424514-3
    SSG: 3,2
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  • 8
    Online Resource
    Online Resource
    Wiley ; 2012
    In:  Journal of Economics & Management Strategy Vol. 21, No. 3 ( 2012-09), p. 673-705
    In: Journal of Economics & Management Strategy, Wiley, Vol. 21, No. 3 ( 2012-09), p. 673-705
    Type of Medium: Online Resource
    ISSN: 1058-6407
    URL: Issue
    RVK:
    Language: English
    Publisher: Wiley
    Publication Date: 2012
    detail.hit.zdb_id: 1481233-2
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  • 9
    Online Resource
    Online Resource
    Institute for Operations Research and the Management Sciences (INFORMS) ; 2023
    In:  Manufacturing & Service Operations Management Vol. 25, No. 3 ( 2023-05), p. 939-957
    In: Manufacturing & Service Operations Management, Institute for Operations Research and the Management Sciences (INFORMS), Vol. 25, No. 3 ( 2023-05), p. 939-957
    Abstract: Problem definition: We ask whether and how a charitable organization’s front-line staff members can be effectively positioned to encourage donors to donate more (in compliance with the eligibility rules) during their in-person interactions. Academic/practical relevance: Specifically, we consider how charitable organizations can use microlevel data on worker-donor interactions to improve donation outcomes, via understanding of workers’ experiences and donors’ characteristics. Methodology: Using a unique data set at the worker-donor interaction level, we analyze the role of nurses’ experiences in driving charitable productivity and explore the downstream effects of the donation volume outcome. Results: We find that the effect of the charitable worker on charitable productivity strongly depends on the worker’s experiences that entail sharing knowledge about a donor’s donation options, rather than the worker’s experiences that are primarily focused on collecting donations. Moreover, worker experience can encourage donors that have lower self-efficacy over performing their donation to choose higher donation volumes. A worker’s experience with donors with lower self-efficacy furthermore benefits charitable productivity when interacting with those donors. Higher donations induced by an experienced worker from the previous session are correlated with higher donation volumes in the focal session if the donor returns to donate. Managerial implications: When taking the insights on staff-donor interactions into account, improved matching between workers and donors can provide economically significant benefits for the blood bank. Understanding worker experience in the staff-donor interactions and leveraging big data in staffing decisions can help charitable organizations improve their productivity simply from the personnel end. Funding: W. Lin acknowledges the support of the Marshall Fellowship at the USC Marshall School of Business. S. F. Lu acknowledges the support of the Gerald Lyles Rising Star fund at Purdue. T. Sun acknowledges the support of an Adobe Data Science Award and an iORB grant at the USC Marshall School of Business. Supplemental Material: The online appendices are available at https://doi.org/10.1287/msom.2023.1198 .
    Type of Medium: Online Resource
    ISSN: 1523-4614 , 1526-5498
    RVK:
    Language: English
    Publisher: Institute for Operations Research and the Management Sciences (INFORMS)
    Publication Date: 2023
    detail.hit.zdb_id: 2023273-1
    SSG: 3,2
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  • 10
    In: Mobile Information Systems, Hindawi Limited, Vol. 2022 ( 2022-4-25), p. 1-10
    Abstract: Credit card fraud is a major problem in today’s financial world. It induces severe damage to financial institutions and individuals. There has been an exponential increase in the losses due to fraud in recent years. Hence, effectively detecting fraudulent behavior is of vital importance for either financial institutions or individuals. Since credit fraud events account for a small proportion of all transaction events in real life, the datasets about credit fraud are usually imbalanced. Some common classifiers, such as decision tree and naïve Bayes, are unable to detect fraud. Furthermore, in some cases, traditional strategies for dealing with an imbalanced problem, such as the synthetic minority oversampling technique (SMOTE), are not effective for the fraud detection datasets. To accurately detect fraud behavior, this study uses anomaly detection on imbalanced data, as well as Isolation Forest (IForest) with kernel principal component analysis. A one-class support vector machine (OCSVM) with AdaBoost is used as two models to detect outliers which significantly improves detection accuracy and efficiency. The model achieved 96% accuracy, 100% precision, 96% recall, and 98% F 1 score, respectively. The proposed model is expected to become a helpful tool for finding credit card fraud detection, and the analysis presented in this study will provides useful insights into credit card fraud detection mechanisms.
    Type of Medium: Online Resource
    ISSN: 1875-905X , 1574-017X
    RVK:
    Language: English
    Publisher: Hindawi Limited
    Publication Date: 2022
    detail.hit.zdb_id: 2187808-0
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