ERIM: Business Processes最新文献

{"title":"Towards Profitable Growth in E-Grocery Retailing - the Role of Store and Household Density","authors":"Joydeep Paul, Niels A. H. Agatz, J. Fransoo","doi":"10.2139/ssrn.3924272","DOIUrl":"https://doi.org/10.2139/ssrn.3924272","url":null,"abstract":"Despite the continued growth of e-grocery sales, few companies actually make any profits in this retail segment. Increasing market shares and associated drop densities may render profitable operations possible, but higher delivery fees seem essential to achieving profitability. Yet such higher fees may put e-groceries at a disadvantage as compared with the traditional store channel, which remains highly competitive. This study models customer choice between the e-grocery channel and the store channel as well as the effects of that choice on those channels’ operational costs and market shares. We identify conditions under which e-grocery retail can be profitable, and we estimate our model’s parameters using secondary industry data. Our results indicate that e-grocery is profitable when household density is high and store density is low. When customer valuation of the e-grocery channel increases substantially, the result may be cannibalization of the store channel’s sales to the extent that stores encounter losses. Thus there are three paths to e-grocery profitability:(i) a substantial increase in the relative consumer valuation of the online channel; (ii) a focus on areas with high household density and low store density; (iii) a long-term subsidy of the online channel until stores begin to close.","PeriodicalId":416965,"journal":{"name":"ERIM: Business Processes","volume":"111 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126902663","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":"Modeling and Solving Line Planning with Integrated Mode Choice","authors":"Johann Hartleb, M. Schmidt, D. Huisman, Markus Friedrich","doi":"10.2139/ssrn.3849985","DOIUrl":"https://doi.org/10.2139/ssrn.3849985","url":null,"abstract":"We present a mixed-integer linear program (MILP) for line planning with integrated mode and route choice. In contrast to existing approaches, the mode and route decisions are modeled according to the passengers' preferences while commercial solvers can be applied to solve the corresponding MILP. The model aims at finding line plans that maximize the profit for the public transport operator while estimating the corresponding passenger demand with choice models. Both components of profit, revenue and cost, are influenced by the line plan. Hence, the resulting line plans are not only profitable for operators but also attractive to passengers. By suitable preprocessing of the passengers' utilities, we are able to apply any choice model for mode choices using linear constraints. We provide and test means to improve the computational performance. In experiments on the Intercity network of the Randstad, a metropolitan area in the Netherlands, we show the benefits of our model compared to a standard line planning model with fixed passenger demand. Furthermore, we demonstrate with the help of our model the possibilities and limitations for operators when reacting to changes in demand in an optimal way. The results suggest that operators should regularly update their line plan in response to changes in travel demand and estimate the passenger demand during optimization.","PeriodicalId":416965,"journal":{"name":"ERIM: Business Processes","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132508196","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":"Timetabling for Strategic Passenger Railway Planning","authors":"G. Polinder, M. Schmidt, D. Huisman","doi":"10.2139/ssrn.3526757","DOIUrl":"https://doi.org/10.2139/ssrn.3526757","url":null,"abstract":"In research and practice, public transportation planning is executed in a series of steps, which are often divided into the strategic, the tactical, and the operational planning phase. Timetables are normally designed in the tactical phase, taking into account a given line plan, safety restrictions arising from infrastructural constraints, as well as regularity requirements and bounds on transfer times. In this paper, however, we propose a timetabling approach that is aimed at decision making in the strategic phase of public transportation planning and to determine an outline of a timetable that is good from the passengers’ perspective. Instead of including explicit synchronization constraints between train runs (as most timetabling models do), we include the adaption time (waiting time at the origin station) in the objective function to ensure regular connections between passengers’ origins and destinations. We model the problem as a mixed integer quadratic program and linearise it. Furthermore we propose a heuristic to generate starting solutions. We illustrate the type of solutions found by our approach on two case studies based on the Dutch railway network and analyse trade-offs that are made to balance dwell times and regularity of trains.","PeriodicalId":416965,"journal":{"name":"ERIM: Business Processes","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125466444","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":"Enhancing Urban Mobility: Integrating Ride-Sharing and Public Transit","authors":"Mitja Stiglic, Niels A. H. Agatz, M. Savelsbergh, M. Gradisar","doi":"10.2139/ssrn.2805342","DOIUrl":"https://doi.org/10.2139/ssrn.2805342","url":null,"abstract":"Seamless integration of ride-sharing and public transit may offer fast, reliable, and affordable transfer to and from transit stations in suburban areas thereby enhancing mobility of residents. We investigate the potential benefits of such a system, as well as the ride-matching technology required to support it, by means of an extensive computational study.","PeriodicalId":416965,"journal":{"name":"ERIM: Business Processes","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124876538","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":"Maintenance Appointments in Railway Rolling Stock Rescheduling","authors":"J. Wagenaar, L. Kroon, M. Schmidt","doi":"10.2139/ssrn.2712465","DOIUrl":"https://doi.org/10.2139/ssrn.2712465","url":null,"abstract":"This paper addresses the Rolling Stock Rescheduling Problem (RSRP), while taking maintenance appointments into account. After a disruption, the rolling stock of the disrupted passenger trains has to be rescheduled in order to restore a feasible rolling stock circulation. Usually, a number of train units have a scheduled maintenance appointment during the day: these appointments must be taken into account while rescheduling the rolling stock. In this paper we propose three Mixed Integer Programming (MIP) models for this purpose. All models are extensions of the Composition model from literature, which does not distinguish individual train units. The Extra Unit Type model adds an additional rolling stock type for each train unit that requires maintenance. The Shadow-Account model keeps track of a shadow account for each train unit that requires maintenance. The Job-Composition model creates a path for each train unit such that the train units that require maintenance are on time for their maintenance appointments. All models are tested on instances of Netherlands Railways (NS). The results show that especially the Shadow-Account model and the Job-Composition model are effectively able to take maintenance appointments into account during real-time rescheduling. It depends on the characteristics of an instance whether the Shadow-Account model or the Job-Composition model performs best.","PeriodicalId":416965,"journal":{"name":"ERIM: Business Processes","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130527071","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 2016 Power Trading Agent Competition","authors":"W. Ketter, John Collins, P. P. Reddy, M. D. Weerdt","doi":"10.2139/ssrn.2714236","DOIUrl":"https://doi.org/10.2139/ssrn.2714236","url":null,"abstract":"This is the specification for the Power Trading Agent Competition for 2012 (Power TAC 2012). Power TAC is a competitive simulation that models a “liberalized” retail electrical energy market, where competing business entities or “brokers” offer energy services to customers through tariff contracts, and must then serve those customers by trading in a wholesale market. Brokers are challenged to maximize their profits by buying and selling energy in the wholesale and retail markets, subject to fixed costs and constraints. Costs include fees for publication and withdrawal of tariffs, and distribution fees for transporting energy to their contracted customers. Costs are also incurred whenever there is an imbalance between a broker’s total contracted energy supply and demand within a given time slot. The simulation environment models a wholesale market, a regulated distribution utility, and a population of energy customers, situated in a real location on Earth during a specific period for which weather data is available. The wholesale market is a relatively simple call market, similar to many existing wholesale electric power markets, such as Nord Pool in Scandinavia or FERC markets in North America, but unlike the FERC markets we are modeling a single region, and therefore we do not model location-marginal pricing. Customer models include households and a variety of commercial and industrial entities, many of which have production capacity (such as solar panels or wind turbines) as well as electric vehicles. All have “real-time” metering to support allocation of their hourly supply and demand to their subscribed brokers, and all are approximate utility maximizers with respect to tariff selection, although the factors making up their utility functions may include aversion to change and complexity that can retard uptake of marginally better tariff offers. The distribution utility models the regulated natural monopoly that owns the regional distribution network, and is responsible for maintenance of its infrastructure and for real-time balancing of supply and demand. The balancing process is a market-based mechanism that uses economic incentives to encourage brokers to achieve balance within their portfolios of tariff subscribers and wholesale market positions, in the face of stochastic customer behaviors and weather-dependent renewable energy sources. The broker with the highest bank balance at the end of the simulation wins.","PeriodicalId":416965,"journal":{"name":"ERIM: Business Processes","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131309754","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":"Does Chatter Really Matter? Dynamics of User-Generated Content and Stock Performance","authors":"Seshadri Tirunillai, G. Tellis","doi":"10.2139/ssrn.1856482","DOIUrl":"https://doi.org/10.2139/ssrn.1856482","url":null,"abstract":"This study examines whether user-generated content (UGC) is related to stock market performance, which metric of UGC has the strongest relationship, and what the dynamics of the relationship are. We aggregate UGC from multiple websites over a four-year period across 6 markets and 15 firms. We derive multiple metrics of UGC and use multivariate time-series models to assess the relationship between UGC and stock market performance. \u0000 \u0000Volume of chatter significantly leads abnormal returns by a few days (supported by Granger causality tests). Of all the metrics of UGC, volume of chatter has the strongest positive effect on abnormal returns and trading volume. The effect of negative and positive metrics of UGC on abnormal returns is asymmetric. Whereas negative UGC has a significant negative effect on abnormal returns with a short “wear-in” and long “wear-out,” positive UGC has no significant effect on these metrics. The volume of chatter and negative chatter have a significant positive effect on trading volume. Idiosyncratic risk increases significantly with negative information in UGC. Positive information does not have much influence on the risk of the firm. An increase in off-line advertising significantly increases the volume of chatter and decreases negative chatter. These results have important implications for managers and investors.","PeriodicalId":416965,"journal":{"name":"ERIM: Business Processes","volume":"AES-23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114117599","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}