ERN: Statistical Decision Theory; Operations Research (Topic)最新文献

{"title":"Multi-criterion and Multi-period Performance Benchmarking of Products and Services: Discovering Hidden Performance Gaps","authors":"Henry H. Bi","doi":"10.1108/BIJ-10-2015-0100","DOIUrl":"https://doi.org/10.1108/BIJ-10-2015-0100","url":null,"abstract":"Purpose: A product or service usually has multiple measurable characteristics, and its performance on different measures may vary and may change over time. Multi-criterion and multi-period performance benchmarking presents a challenge for management to determine performance gaps among comparable products or services. In this paper, we propose a new performance benchmarking method to address this challenge.Design/methodology/approach: We develop this method by formulating two benchmarking functions: A differentiation function based on Shewhart average and standard deviation charts to distinguish the performance of products or services on a single measure, and a categorization function to classify each product’s or service’s overall performance across all measures. By systematically removing the lowest-performing products or services from comparison, we use these functions iteratively to detect performance gaps. Findings: Using this method, we find performance gaps in each of three benchmarking applications of airports, hotels, and minivans, although a number of performance gaps are not obvious from the raw data. Research limitations/implications: Our benchmarking study focuses on the quantifiable outcome performance of products and services. Practical implications: This benchmarking method is generic and applicable to most products and services. It is robust not only for discovering performance gaps, but also for providing useful insights for managers to prioritize improvement efforts on individual performance measures.Originality/value: The novelty of this benchmarking method lies in that it can not only find the “best overall” products or services for all performance measures, but can also pinpoint the “best-in-class” products or services as well as performance gaps for each performance measure. In addition, this paper presents several original ideas for performance benchmarking, including: (1) using the control limits of Shewhart control charts to categorize performance gaps, (2) systematically removing the lowest-performing products or services from comparison for the purpose of detecting hidden performance gaps, and (3) using symbolic expressions to integrate benchmarking results from all measures and to show all performance gaps intuitively.","PeriodicalId":200007,"journal":{"name":"ERN: Statistical Decision Theory; Operations Research (Topic)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126342215","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"PSO-Based Tuning of Murame Parameters for Creditworthiness Evaluation of Italian SMEs","authors":"M. Corazza, G. Fasano, S. Funari, R. Gusso","doi":"10.2139/ssrn.2934929","DOIUrl":"https://doi.org/10.2139/ssrn.2934929","url":null,"abstract":"In this work we use a MultiCriteria Decision Analysis (MCDA) model to evalu- ate the creditworthiness of a sample of Italian Small and Medium-sized Enterprises (SMEs), on the basis of their balance sheet data provided by the AIDA database. Our methodology is able to consider simultaneously different factors affecting the firmsO solvency level, and can produce results in terms of scoring, classification into homogeneous rating classes and migration probabilities. In this contribution we compare the results obtained considering two scenarios. On one hand, we experience an exogenous specification of the parameters that describe the preference structure implicit in the used MCDA model. On the other hand, we consider the results obtained using a preference disaggregation method to endogenously determine some of the model parameters. Because of the complexity of the obtained math- ematical programming problem, we use an heuristic methodology, namely Particle Swarm Optimization (PSO), which provides a reasonable compromise between the quality of the solution and the computational burden.","PeriodicalId":200007,"journal":{"name":"ERN: Statistical Decision Theory; Operations Research (Topic)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121242529","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimal Supply Planning for Commercial Seeds","authors":"Utku Serhatli, A. Calmon, E. Yucesan","doi":"10.2139/ssrn.2925095","DOIUrl":"https://doi.org/10.2139/ssrn.2925095","url":null,"abstract":"We analyze the optimal production and inventory decisions of a global corn seed manufacturer. Due to naturally long supply lead times and short selling seasons in agriculture, we propose a newsvendor model, which includes not only supply and demand uncertainty, but also product returns and perishability. First, we present the general model for a single variety and derive structural results. Second, we characterize the optimal production and inventory management in multi-period case model for a single end product. Third, we solve the single-product, single-period case and analyze via Monte Carlo simulations using market data. Long lead supply lead time also causes demand forecasts to be notoriously unreliable. Thus, we model and solve various special cases, including scenarios with salvaging and postponement, as well as comparing across these different settings to assess the value of operational agility. Our analysis shows that while salvaging protects the firm against yield uncertainty, postponement is an effective defense against demand uncertainty.","PeriodicalId":200007,"journal":{"name":"ERN: Statistical Decision Theory; Operations Research (Topic)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121144554","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Proactive and Reactive Resource-Constrained Project Scheduling Problem: The Crucial Role of Buffer-Based Reactions","authors":"Morteza Davari, E. Demeulemeester","doi":"10.2139/ssrn.2976350","DOIUrl":"https://doi.org/10.2139/ssrn.2976350","url":null,"abstract":"The proactive and reactive resource-constrained project scheduling problem (PR-RCPSP), that has been introduced recently (Davari and Demeulemeester, 2016a), deals with activity duration uncertainty in a very unique way. The optimal solution to an instance of the PR-RCPSP is a proactive and reactive policy (PR-policy) that is a combination of a baseline schedule and a set of required transitions (reactions). In this research, we introduce two interesting classes of reactions, namely the class of selection-based reactions and the class of buffer-based reactions. We also discuss the theoretical relevance of these two classes of reactions. We run some computational results and report the contributions of the selection-based reactions and the buffer-based reactions in the optimal solution. The results suggest that although both selection-based reactions and buffer-based reactions contribute largely in the construction of the optimal PR-policy, the contribution of the buffer-based reactions is of much greater importance.","PeriodicalId":200007,"journal":{"name":"ERN: Statistical Decision Theory; Operations Research (Topic)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125986554","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Latent Class Analysis - A Variational Approach","authors":"Puneet Tiwari","doi":"10.2139/ssrn.2907840","DOIUrl":"https://doi.org/10.2139/ssrn.2907840","url":null,"abstract":"Choosing number of classes is a major modeling decision in latent class analysis. This is most often carried out by fitting a number of models with increasing number of classes. In the frequentist methodology, one records a number of fit criteria for comparison, while in Bayesian methodology, this exercise is more difficult, as incremental fitting is computationally burdensome, more so when number of manifest variables is large and/or dataset is big. A methodology that can provide good approximation to number of classes with little user intervention, enjoys benefits of Bayesian methodology and can circumvent incremental fitting of latent classes will be a valuable tool. In this article, we bring to the attention of latent class modelers the methodology of variational Bayes for latent class modeling and extend it to the case of polychotomous manifest variables.","PeriodicalId":200007,"journal":{"name":"ERN: Statistical Decision Theory; Operations Research (Topic)","volume":"17 10","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113979824","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Value of 'Bespoke': Demand Learning, Preference Learning, and Customer Behavior","authors":"Tingliang Huang, Chao Liang, Jingqi Wang","doi":"10.1287/mnsc.2017.2771","DOIUrl":"https://doi.org/10.1287/mnsc.2017.2771","url":null,"abstract":"“Bespoke,” or mass customization strategy, combines demand learning and preference learning. We develop an analytical framework to study the economic value of bespoke systems and investigate the interaction between demand learning and preference learning. We find that it is possible for demand learning and preference learning to be either complements or substitutes, depending on the customization cost and the demand uncertainty profile. They are generally complements when the personalization cost is low and the probability of having high demand is large. Contrary to usual belief, we show that higher demand uncertainty does not necessarily yield more complementarity benefits. Our numerical study shows that the complementarity benefit becomes weaker when customers are more strategic. Interestingly, the substitute loss can occur when the personalization cost is small and the probability of having high demand is large, when customers are strategic. The online supplement is available at https://doi.org/10.1287...","PeriodicalId":200007,"journal":{"name":"ERN: Statistical Decision Theory; Operations Research (Topic)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134119430","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Expected Utility with Uncertain Probabilities Theory","authors":"Yehuda Izhakian","doi":"10.2139/ssrn.2017944","DOIUrl":"https://doi.org/10.2139/ssrn.2017944","url":null,"abstract":"This paper introduces a model of decision making under ambiguity by extending the Bayesian approach to uncertain probabilities. In this model, preferences for ambiguity pertain directly to probabilities such that attitude toward ambiguity is defined as attitude toward mean-preserving spreads in probabilities—analogous to the Rothschild–Stiglitz risk attitude toward mean-preserving spreads in outcomes. The model refines the separations between tastes and beliefs, and between risk and ambiguity. These separations are crucial for the measurement of the degree of ambiguity and for the elicitation and characterization of attitudes toward ambiguity, thereby providing an empirically and experimentally applicable framework.","PeriodicalId":200007,"journal":{"name":"ERN: Statistical Decision Theory; Operations Research (Topic)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124580726","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Selecting Healthcare Providers for Bundled Payments in Healthcare Services","authors":"Seokjun Youn, A. Agrawal, Subodha Kumar, C. Sriskandarajah","doi":"10.2139/ssrn.2886066","DOIUrl":"https://doi.org/10.2139/ssrn.2886066","url":null,"abstract":"Identification of competitive healthcare providers is an important issue for successful operation of a bundled payment reimbursement program. We develop a healthcare provider selection framework via data envelopment analysis (DEA) and combinatorial auction (CA). Our goal is to cover target regions with adequate numbers of healthcare providers so as to optimally deploy a bundled payment program across these regions. Our methodology balances bid prices and performance of applicants to cover the entire regions in an equitable manner, allows for provider preferences in selecting the bundle of services, and determines winners taking into account service quality, efficiency and the price of the bundles. Our work provides a practical and systematic selection procedure for payers compared to the extant subjective selection methods.","PeriodicalId":200007,"journal":{"name":"ERN: Statistical Decision Theory; Operations Research (Topic)","volume":"153 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121401591","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Multivariate Bullwhip Effect","authors":"Chaitra H. Nagaraja, T. McElroy","doi":"10.2139/ssrn.2865975","DOIUrl":"https://doi.org/10.2139/ssrn.2865975","url":null,"abstract":"A multivariate bullwhip expression for m products with an order-up-to inventory policy is developed. The demand models under consideration are differenced stationary vector time series with a Wold representation for which general forecasting formulas are available, resulting in a large class of possible models (including nonstationary ones). Examples are provided for common demand models and implemented on sales data. It is found that the multivariate approach gives rise to mechanisms for understanding and reducing the bullwhip effect through horizontal information sharing, particularly for the nonstationary demand case. In the stationary setting, a more nuanced approach to bullwhip reduction can be achieved by managing the relationship between cross-correlations and lead-times. A method of determining whether a multivariate or univariate approach generates a lower bullwhip effect is proposed.","PeriodicalId":200007,"journal":{"name":"ERN: Statistical Decision Theory; Operations Research (Topic)","volume":"102 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115439214","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Decision on Logistics Transportation System of Thai Automotive Service Parts Industry","authors":"Napolpong Sorsomboon, Sittiporn Intuwonges","doi":"10.2139/ssrn.2861342","DOIUrl":"https://doi.org/10.2139/ssrn.2861342","url":null,"abstract":"The purpose of this paper is to study factors that affecting decision to choose logistics transportation system in Thai Automotive Service Parts Industry. The study identified contexts where sourcing is made based on transaction cost economics theory (TCE), the resource-based view (RBV), core competency (CC), and customer requirement (CR). Sampling data of 174 respondents of the suppliers in Thai Automotive Service Parts Industry were collected and analyzed by using multivariable analysis. Generalized Linear Model (GLM) reveals that transaction cost characteristics factor is the significant factor in determining on Transportation Cost. Ordered Probit model was also employed in analyzing different levels of decision in choosing logistics transportation system in Thai Automotive Service Parts Industry. The estimated results indicate that Transportation Cost, Capability, and Customer Requirement are major factors in determining decision on to logistics transportation system while core competency has insignificant impact. This finding implies that core competency theory cannot be applied in this case.","PeriodicalId":200007,"journal":{"name":"ERN: Statistical Decision Theory; Operations Research (Topic)","volume":"96 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127993601","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}