GLORIA

GEOMAR Library Ocean Research Information Access

X

Your email was sent successfully. Check your inbox.

An error occurred while sending the email. Please try again.

Proceed reservation?

Export
Filter
  • Institute for Operations Research and the Management Sciences (INFORMS)  (314)
  • Economics  (314)
Material
Publisher
  • Institute for Operations Research and the Management Sciences (INFORMS)  (314)
Person/Organisation
Language
Years
Subjects(RVK)
  • Economics  (314)
RVK
  • 1
    Online Resource
    Online Resource
    Empirical Investigation of an Equity Pairs Trading Strategy
    Institute for Operations Research and the Management Sciences (INFORMS) ; 2019
    In:  Management Science Vol. 65, No. 1 ( 2019-01), p. 370-389
    Details
    In: Management Science, Institute for Operations Research and the Management Sciences (INFORMS), Vol. 65, No. 1 ( 2019-01), p. 370-389
    Abstract: We show that an equity pairs trading strategy generates large and significant abnormal returns. We find that two components of the trading signal (i.e., short-term reversal and pairs momentum) have different dynamic and cross-sectional properties. The pairs momentum is largely explained by the one-month version of the industry momentum. Therefore, the pairs trading profits are largely explained by the short-term reversal and a version of the industry momentum. The online appendix is available at https://doi.org/10.1287/mnsc.2017.2825 . This paper was accepted by Lauren Cohen, finance.
    Type of Medium: Online Resource
    ISSN: 0025-1909 , 1526-5501
    URL: Article
    DOI: 10.1287/mnsc.2017.2825
    RVK:
    QP 300
    Language: English
    Publisher: Institute for Operations Research and the Management Sciences (INFORMS)
    Publication Date: 2019
    detail.hit.zdb_id: 206345-1
    detail.hit.zdb_id: 2023019-9
    SSG: 3,2
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
    Online Resource
  • 2
    Online Resource
    Online Resource
    Information Provision Policies for Improving Farmer Welfare in Developing Countries: Heterogeneous Farmers and Market Selection
    Institute for Operations Research and the Management Sciences (INFORMS) ; 2019
    In:  Manufacturing & Service Operations Management Vol. 21, No. 2 ( 2019-04), p. 254-270
    Details
    In: Manufacturing & Service Operations Management, Institute for Operations Research and the Management Sciences (INFORMS), Vol. 21, No. 2 ( 2019-04), p. 254-270
    Abstract: We examine the impact of information provision policies on farmer welfare in developing countries where farmers lack relevant and timely information for making informed decisions regarding which crop to grow and which market to sell in. In addition to heterogeneous farmers, we consider the case when farmers are price takers and yet the price of each crop (or the price in each market) is a linearly decreasing function of the total sales quantity. When market information is offered free of charge, we show that (a) providing information is always beneficial to farmers at the individual level and (b) providing information to all farmers may not be welfare maximizing at the aggregate level. To maximize farmer welfare, it is optimal to provide information to a targeted group of farmers who are located far from either markets. However, to overcome perceived unfairness among farmers, we show that the government should provide information to all farmers at a nominal fee so that the farmers will adopt the intended optimal provision policy willingly. We extend our analysis to examine different issues including information leakage, social welfare, precision of market information, and information dissemination via a for-profit company. This paper has been accepted for the Manufacturing & Service Operations Management Special Issue on Value Chain Innovations in Developing Economies.
    Type of Medium: Online Resource
    ISSN: 1523-4614 , 1526-5498
    URL: Article
    DOI: 10.1287/msom.2016.0599
    RVK:
    QA 10000
    Language: English
    Publisher: Institute for Operations Research and the Management Sciences (INFORMS)
    Publication Date: 2019
    detail.hit.zdb_id: 2023273-1
    SSG: 3,2
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
    Online Resource
  • 3
    Online Resource
    Online Resource
    Iterative Prediction-and-Optimization for E-Logistics Distribution Network Design
    Institute for Operations Research and the Management Sciences (INFORMS) ; 2022
    In:  INFORMS Journal on Computing Vol. 34, No. 2 ( 2022-03), p. 769-789
    Details
    In: INFORMS Journal on Computing, Institute for Operations Research and the Management Sciences (INFORMS), Vol. 34, No. 2 ( 2022-03), p. 769-789
    Abstract: The emergence of online retailers has brought new opportunities to the design of their distribution networks. Notably, for online retailers that do not operate offline stores, their target customers are more sensitive to the quality of logistic services, such as delivery speed and reliability. This paper is motivated by a leading online retailer for cosmetic products on Taobao.com that aimed to improve its logistics efficiency by redesigning its centralized distribution network into a multilevel one. The multilevel distribution network consists of a layer of primary facilities to hold stocks from suppliers and transshipment and a layer of secondary facilities to provide last-mile delivery. There are two major challenges of designing such a facility network. First, online customers can respond significantly to the change of logistics efficiency with the redesigned network, thereby rendering the network optimized under the original demand distribution suboptimal. Second, because online retailers have relatively small sales volumes and are very flexible in choosing facility locations, the facility candidate set can be large, causing the facility location optimization challenging to solve. To this end, we propose an iterative prediction-and-optimization strategy for distribution network design. Specifically, we first develop an artificial neural network (ANN) to predict customer demands, factoring in the logistic service quality given the network and the city-level purchasing power based on demographic statistics. Then, a mixed integer linear programming (MILP) model is formulated to choose facility locations with minimum transportation, facility setup, and package processing costs. We further develop an efficient two-stage heuristic for computing high-quality solutions to the MILP model, featuring an agglomerative hierarchical clustering algorithm and an expectation and maximization algorithm. Subsequently, the ANN demand predictor and two-stage heuristic are integrated for iterative network design. Finally, using a real-world data set, we validate the demand prediction accuracy and demonstrate the mutual interdependence between the demand and network design. Summary of Contribution: We propose an iterative prediction-and-optimization algorithm for multilevel distribution network design for e-logistics and evaluate its operational value for online retailers. We address the issue of the interplay between distribution network design and the demand distribution using an iterative framework. Further, combining the idea in operational research and data mining, our paper provides an end-to-end solution that can provide accurate predictions of online sales distribution, subsequently solving large-scale optimization problems for distribution network design problems.
    Type of Medium: Online Resource
    ISSN: 1091-9856 , 1526-5528
    URL: Article
    DOI: 10.1287/ijoc.2021.1107
    RVK:
    QA 10000
    Language: English
    Publisher: Institute for Operations Research and the Management Sciences (INFORMS)
    Publication Date: 2022
    detail.hit.zdb_id: 2070411-2
    detail.hit.zdb_id: 2004082-9
    SSG: 3,2
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
    Online Resource
  • 4
    Online Resource
    Online Resource
    Fast Approximation Algorithm for Maximum Lifetime Aggregation Trees in Wireless Sensor Networks
    Institute for Operations Research and the Management Sciences (INFORMS) ; 2016
    In:  INFORMS Journal on Computing Vol. 28, No. 3 ( 2016-07), p. 417-431
    Details
    In: INFORMS Journal on Computing, Institute for Operations Research and the Management Sciences (INFORMS), Vol. 28, No. 3 ( 2016-07), p. 417-431
    Abstract: One ultimate goal of wireless sensor networks is to collect the sensed data from a set of sensors and transmit them to some sink node via a data gathering tree. In this work, we are interested in data aggregation, where the sink node wants to know the value for a certain function of all sensed data, such as minimum, maximum, average, and summation. Given a data aggregation tree, sensors receive messages from children periodically, merge them with its own packet, and send the new packet to its parent. The problem of finding an aggregation tree with the maximum lifetime has been proved to be NP-hard and can be generalized to finding a spanning tree with the minimum maximum vertex load, where the load of a vertex is a nondecreasing function of its degree in the tree. Although there is a rich body of research in those problems, they either fail to meet a theoretical bound or need high running time. In this paper, we develop a novel algorithm with provable performance bounds for the generalized problem. We show that the running time of our algorithm is in the order of O(mnα(m, n)), where m is the number of edges, n is the number of sensors, and α is the inverse Ackerman function. Though our work is motivated by applications in sensor networks, the proposed algorithm is general enough to handle a wide range of degree-oriented spanning tree problems, including bounded degree spanning tree problem and minimum degree spanning tree problem. When applied to these problems, it incurs a lower computational cost in comparison to existing methods. Simulation results validate our theoretical analysis.
    Type of Medium: Online Resource
    ISSN: 1091-9856 , 1526-5528
    URL: Article
    DOI: 10.1287/ijoc.2015.0688
    RVK:
    QA 10000
    Language: English
    Publisher: Institute for Operations Research and the Management Sciences (INFORMS)
    Publication Date: 2016
    detail.hit.zdb_id: 2070411-2
    detail.hit.zdb_id: 2004082-9
    SSG: 3,2
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
    Online Resource
  • 5
    Online Resource
    Online Resource
    Managing Customer Search via Bundling
    Institute for Operations Research and the Management Sciences (INFORMS) ; 2022
    In:  Manufacturing & Service Operations Management Vol. 24, No. 4 ( 2022-07), p. 1906-1925
    Details
    In: Manufacturing & Service Operations Management, Institute for Operations Research and the Management Sciences (INFORMS), Vol. 24, No. 4 ( 2022-07), p. 1906-1925
    Abstract: Problem definition: Product bundling has been a pervasive marketing strategy, and its success has been largely attributed to its strength in reducing customers’ valuation dispersion. Less is known about the efficacy of bundling in settings where customers are less sure about their valuations for a product, especially when that product is newly launched or has an experience nature, and can conduct costly search to learn the product content and discover their true valuations. In this paper, we investigate the interplay between product bundling and customer search and its implications for a monopolist’s optimal pricing strategy. Academic/practical relevance: The existing search theory has focused on decision making that selects the best among multiple alternatives, with costly search being mandatory for the acquisition of each alternative. In this paper, we introduce a framework of multiproduct demands and nonobligatory search, where customers demanding multiple products strategically decide whether to conduct costly search to resolve valuation uncertainty, while reserving the right to purchase these products without having to search them first. Methodology: We apply a nonobligatory search framework to study two different markets: (1) a market of one mature and one new product, in which valuation uncertainty exists for the new product only; and (2) a market of two new products, in which valuation uncertainty exists for both products. The firm fully anticipates the customers’ search behaviors, determines whether to bundle these products or unbundle them, and optimally sets prices. Results: We show that bundling cultivates search in a market of one mature and one new product, but inhibits search in a market of two new products. This contrast emerges as a result of market structures: Bundling reduces the appeal of search by making the search decisions sequential and path-dependent in the latter market, but is less effective in doing so due to the existing heterogeneity in the former market. Our results thus point to an intricate interplay between customer search, market heterogeneity, and prices and their joint impact on the monopolist’s optimal bundling strategy. We also study mixed bundling and show that its economic benefits only carry through when customers’ search cost is not too large. In this case, mixed bundling can lead to considerable revenue improvement in a market of one mature and one new product, but only tiny revenue improvement in a market of two new products. We also study the joint management of product return and product bundling and show that a positive refund should generally be offered for returned products to stimulate customers’ no-search purchase. Managerial implications: Our paper provides guidance for firms selling multiple experience or new products. We propose product bundling to manage customer search, identifying regimes for its economic benefits and clarifying its implication for customer welfare.
    Type of Medium: Online Resource
    ISSN: 1523-4614 , 1526-5498
    URL: Article
    DOI: 10.1287/msom.2022.1082
    RVK:
    QA 10000
    Language: English
    Publisher: Institute for Operations Research and the Management Sciences (INFORMS)
    Publication Date: 2022
    detail.hit.zdb_id: 2023273-1
    SSG: 3,2
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
    Online Resource
  • 6
    Online Resource
    Online Resource
    Dynamic Pricing of Relocating Resources in Large Networks
    Institute for Operations Research and the Management Sciences (INFORMS) ; 2021
    In:  Management Science Vol. 67, No. 7 ( 2021-07), p. 4075-4094
    Details
    In: Management Science, Institute for Operations Research and the Management Sciences (INFORMS), Vol. 67, No. 7 ( 2021-07), p. 4075-4094
    Abstract: Motivated by applications in shared vehicle systems, we study dynamic pricing of resources that relocate over a network of locations. Customers with private willingness to pay sequentially request to relocate a resource from one location to another, and a revenue-maximizing service provider sets a price for each request. This problem can be formulated as an infinite-horizon stochastic dynamic program, but it is difficult to solve, as optimal pricing policies may depend on the locations of all resources in the network. We first focus on networks with a hub-and-spoke structure, and we develop a dynamic pricing policy and a performance bound based on a Lagrangian relaxation. This relaxation decomposes the problem over spokes and is thus far easier to solve than the original problem. We analyze the performance of the Lagrangian-based policy and focus on a supply-constrained large network regime in which the number of spokes (n) and the number of resources grow at the same rate. We show that the Lagrangian policy loses no more than O(ln n/n) in performance compared with an optimal policy, thus implying asymptotic optimality as n grows large. We also show that no static policy is asymptotically optimal in the large network regime. Finally, we extend the Lagrangian relaxation to provide upper bounds and policies to general networks with multiple interconnected hubs and spoke-to-spoke connections and to incorporate relocation times. We also examine the performance of the Lagrangian policy and the Lagrangian relaxation bound on some numerical examples, including examples based on data from RideAustin. This paper was accepted by David Simchi-Levi, revenue management and market analytics.
    Type of Medium: Online Resource
    ISSN: 0025-1909 , 1526-5501
    URL: Article
    DOI: 10.1287/mnsc.2020.3735
    RVK:
    QP 300
    Language: English
    Publisher: Institute for Operations Research and the Management Sciences (INFORMS)
    Publication Date: 2021
    detail.hit.zdb_id: 206345-1
    detail.hit.zdb_id: 2023019-9
    SSG: 3,2
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
    Online Resource
  • 7
    Online Resource
    Online Resource
    Robust Dynamic Pricing with Two Substitutable Products
    Institute for Operations Research and the Management Sciences (INFORMS) ; 2018
    In:  Manufacturing & Service Operations Management Vol. 20, No. 2 ( 2018-05), p. 249-268
    Details
    In: Manufacturing & Service Operations Management, Institute for Operations Research and the Management Sciences (INFORMS), Vol. 20, No. 2 ( 2018-05), p. 249-268
    Abstract: We consider a practical dynamic pricing problem with two substitutable products involving a number of business rules commonly seen in practice. Demand substitution exists between the two products (interproduct substitution) and may also exist across different time periods (intertemporal substitution). However, there is limited demand information such that the underlying probability distributions of the demand cannot be characterized precisely. We use an interval to represent, respectively, the demand for each individual product in each period, the aggregate demand for the two products in each period, and the total aggregate demand for the two products across multiple time periods. We propose a robust optimization model for this problem to maximize the worst-case total revenue. For the problem with interproduct demand substitution only, we develop a dynamic programming algorithm and show that the search spaces in the DP can be reduced greatly, which enables the algorithm to generate optimal solutions in a reasonable amount of time. For the problem with both interproduct and intertemporal demand substitutions, we develop a more complex dynamic programming algorithm and design a fully polynomial time approximation scheme that guarantees a proven, near optimal solution in a manageable computation time for practically sized problems. Our computational results show that, compared to a risk-neutral approach, our robust optimization approach can decrease the variance of the revenue at a small expense of the average revenue. We also generate a number of managerial insights: (i) none of the key structural properties commonly studied in the pricing literature hold for our problem; (ii) the revenue impact of ignoring intertemporal demand substitution when such substitution exists can be quite significant; and (iii) under- or overestimating the bounds of the demand intervals or imposing moderate business rules leads to relatively small revenue loss, typically less than 3%. The online appendix is available at https://doi.org/10.1287/msom.2017.0639 .
    Type of Medium: Online Resource
    ISSN: 1523-4614 , 1526-5498
    URL: Article
    DOI: 10.1287/msom.2017.0639
    RVK:
    QA 10000
    Language: English
    Publisher: Institute for Operations Research and the Management Sciences (INFORMS)
    Publication Date: 2018
    detail.hit.zdb_id: 2023273-1
    SSG: 3,2
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
    Online Resource
  • 8
    Online Resource
    Online Resource
    Is Price Commitment a Better Solution to Control Carbon Emissions and Promote Technology Investment?
    Institute for Operations Research and the Management Sciences (INFORMS) ; 2023
    In:  Management Science Vol. 69, No. 1 ( 2023-01), p. 325-341
    Details
    In: Management Science, Institute for Operations Research and the Management Sciences (INFORMS), Vol. 69, No. 1 ( 2023-01), p. 325-341
    Abstract: Recent years have seen considerable debate about the practicability of a global quantity/price commitment to control carbon emissions and tackle environmental issues. In this paper, we study the impact of the cap-and-trade policy (quantity commitment) and the carbon tax policy (price commitment) on a firm’s technology investment and production decisions. The main feature captured in our model is that there exist correlated uncertainties between the sales market (demand uncertainty) and the permit trading market (permit price volatility) under the cap-and-trade policy. The correlation relationship stands on the following intuition. The demands for final products affect firms’ production output, which generates the needs of emission permits and influences the permit price. We show that under the cap-and-trade policy, with the uncertainty of the future emission price, the firm could flexibly adjust its production quantity to enhance its profit, resulting in low incentives to invest in clean technology. However, as the (positive) correlation between the sales market and the permit trading market increases, the production flexibility is constrained so that the firm has to increase its technology investment to hedge against the future risk of a high emission price. Making a comparison between the cap-and-trade and carbon tax policies, we find that when the correlation coefficient is moderate, the carbon tax policy generates a multiwin situation (i.e., more technology investment, higher expected profit and consumer surplus, and fewer carbon emissions). Case studies are provided to illustrate the implications and model variants are examined to check the robustness of the main results. Overall, our analysis sheds light on recent debate over carbon pricing and identifies the important role of correlated uncertainties in carbon policy design. This paper was accepted by Charles Corbett, operations management. Funding: This work was supported by the stable support plan program of Shenzhen Natural Science Fund [Program Contract 20200925160533002] and the National Natural Science Foundation of China [Grant 72101105] . Supplemental Material: The data files and online appendix are available at https://doi.org/10.1287/mnsc.2022.4365 .
    Type of Medium: Online Resource
    ISSN: 0025-1909 , 1526-5501
    URL: Article
    DOI: 10.1287/mnsc.2022.4365
    RVK:
    QP 300
    Language: English
    Publisher: Institute for Operations Research and the Management Sciences (INFORMS)
    Publication Date: 2023
    detail.hit.zdb_id: 206345-1
    detail.hit.zdb_id: 2023019-9
    SSG: 3,2
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
    Online Resource
  • 9
    Online Resource
    Online Resource
    An Axiomatic Approach to Systemic Risk
    Institute for Operations Research and the Management Sciences (INFORMS) ; 2013
    In:  Management Science Vol. 59, No. 6 ( 2013-06), p. 1373-1388
    Details
    In: Management Science, Institute for Operations Research and the Management Sciences (INFORMS), Vol. 59, No. 6 ( 2013-06), p. 1373-1388
    Abstract: Systemic risk refers to the risk of collapse of an entire complex system as a result of the actions taken by the individual component entities or agents that comprise the system. Systemic risk is an issue of great concern in modern financial markets as well as, more broadly, in the management of complex business and engineering systems. We propose an axiomatic framework for the measurement and management of systemic risk based on the simultaneous analysis of outcomes across agents in the system and over scenarios of nature. Our framework defines a broad class of systemic risk measures that accomodate a rich set of regulatory preferences. This general class of systemic risk measures captures many specific measures of systemic risk that have recently been proposed as special cases and highlights their implicit assumptions. Moreover, the systemic risk measures that satisfy our conditions yield decentralized decompositions; i.e., the systemic risk can be decomposed into risk due to individual agents. Furthermore, one can associate a shadow price for systemic risk to each agent that correctly accounts for the externalities of the agent's individual decision making on the entire system. This paper was accepted by Gérard P. Cachon, stochastic models and simulation.
    Type of Medium: Online Resource
    ISSN: 0025-1909 , 1526-5501
    URL: Article
    DOI: 10.1287/mnsc.1120.1631
    RVK:
    QP 300
    Language: English
    Publisher: Institute for Operations Research and the Management Sciences (INFORMS)
    Publication Date: 2013
    detail.hit.zdb_id: 206345-1
    detail.hit.zdb_id: 2023019-9
    SSG: 3,2
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
    Online Resource
  • 10
    Online Resource
    Online Resource
    Globalization and U.S. Corporate Tax Policies: Evidence from Import Competition
    Institute for Operations Research and the Management Sciences (INFORMS) ; 2022
    In:  Management Science Vol. 68, No. 8 ( 2022-08), p. 6145-6162
    Details
    In: Management Science, Institute for Operations Research and the Management Sciences (INFORMS), Vol. 68, No. 8 ( 2022-08), p. 6145-6162
    Abstract: This paper studies how globalization affects the corporate tax policies of U.S. manufacturing firms. Using U.S.-granting China Permanent Normal Trade Relations as a quasi-natural experiment, we find a significant increase in tax reduction activities for firms facing higher exposure to Chinese imports. The effect is more pronounced for firms with higher managerial slack. We also find that the effect is stronger for firms in less diversified products market and faster changing industries. We also show that U.S. firms facing higher Chinese import competition are more likely to engage in other tax-motivated activities: acquisition of subsidiaries in low-tax regions and suspected transfer pricing. Furthermore, we explore the 2017 tax cut and the recent U.S.-China trade dispute and find that firms engage less in tax reduction activities after the 2017 tax cut and after the tariff increase for Chinese imports. This paper was accepted by Kay Giesecke, finance.
    Type of Medium: Online Resource
    ISSN: 0025-1909 , 1526-5501
    URL: Article
    DOI: 10.1287/mnsc.2021.4121
    RVK:
    QP 300
    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
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
    Online Resource
Close ⊗
This website uses cookies and the analysis tool Matomo. More information can be found here...