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  • Institute for Operations Research and the Management Sciences (INFORMS)  (117)
  • Economics  (117)
  • QA 10000  (117)
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  • Institute for Operations Research and the Management Sciences (INFORMS)  (117)
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RVK
  • QA 10000  (117)
  • 1
    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
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  • 2
    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
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  • 3
    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
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  • 4
    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
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  • 5
    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
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  • 6
    Online Resource
    Online Resource
    Managing Competition from Within and Outside: Using Strategic Inventory and Network Externality to Combat Copycats
    Institute for Operations Research and the Management Sciences (INFORMS) ; 2023
    In:  Manufacturing & Service Operations Management Vol. 25, No. 5 ( 2023-09), p. 1814-1834
    Details
    In: Manufacturing & Service Operations Management, Institute for Operations Research and the Management Sciences (INFORMS), Vol. 25, No. 5 ( 2023-09), p. 1814-1834
    Abstract: Problem definition: Prior studies have identified the role of downstream retailers’ strategic inventory in mitigating double marginalization within decentralized supply chains. Our work adds to this literature by introducing two relevant features that naturally appear in a dynamic environment: network externality and copycatting. We demonstrate how strategic inventory and network externality can be used to manage competition from within and outside the supply chain. Methodology/results: We develop a game-theoretical model to capture the strategic interaction within a brand-name supply chain, which enjoys positive externalities from early-period sales but faces competition from copycats in later periods. We show that copycats, on the one hand, deter the retailer’s strategic inventory by exerting external competition and on the other hand, can amplify the benefit of the retailer’s strategic inventory in allaying internal double marginalization and enhancing the supply chain’s external competitiveness. We further show that network externality, on the one hand, brings immediate gains to the supply chain’s external battle with copycats and on the other hand, creates internal inefficiency in the form of cross-period double marginalization best exhibited under the supplier’s dynamic contract. When network externality and strategic inventory are optimized jointly, we find that they are always complementary in increasing the supplier’s payoff but can be substitutive to the retailer under a large inventory cost and weak network externality. Managerial implications: Our work provides firms ways of managing decentralized supply chains in the face of copycats. We propose strategic inventory and network externality to combat copycats and provide normative guidance on their operating mechanisms. Funding: C. Jin received financial support from the Singapore Ministry of Education Academic Research Fund [Tier 1 Grant 251RES2101]. Y.-J. Chen received financial support from Hong Kong RGC [Grants GRF 16500821 and HKUST C6020-21GF] . Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2021.0182 .
    Type of Medium: Online Resource
    ISSN: 1523-4614 , 1526-5498
    URL: Article
    DOI: 10.1287/msom.2021.0182
    RVK:
    QA 10000
    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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  • 7
    Online Resource
    Online Resource
    Sales-Force Incentives and Inventory Management
    Institute for Operations Research and the Management Sciences (INFORMS) ; 2000
    In:  Manufacturing & Service Operations Management Vol. 2, No. 2 ( 2000-04), p. 186-202
    Details
    In: Manufacturing & Service Operations Management, Institute for Operations Research and the Management Sciences (INFORMS), Vol. 2, No. 2 ( 2000-04), p. 186-202
    Abstract: This article studies the problem of sales-force compensation by considering the impact of sales-force behavior on a firm's production and inventory system. The sales force's compensation package affects how the salespeople are going to exert their effort, which in turn determines the sales pattern for the firm's product and ultimately drives the performance of the firm's production and inventory system. In general, a smooth demand process facilitates production/inventory planning. Therefore, it is beneficial for a firm to induce its salespeople to exert effort in a way that actually smoothes the demand process. The article proposes a compensation package to induce such behavior. It evaluates and compensates the sales force on a moving-time-window basis, where the length of the time window is determined by the production lead time. Numerical examples show that the proposed package is beneficial to the firm relative to a widely used compensation plan based on annual quotas.
    Type of Medium: Online Resource
    ISSN: 1523-4614 , 1526-5498
    URL: Article
    DOI: 10.1287/msom.2.2.186.12351
    RVK:
    QA 10000
    Language: English
    Publisher: Institute for Operations Research and the Management Sciences (INFORMS)
    Publication Date: 2000
    detail.hit.zdb_id: 2023273-1
    SSG: 3,2
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  • 8
    Online Resource
    Online Resource
    Maximum Profit Scheduling
    Institute for Operations Research and the Management Sciences (INFORMS) ; 2008
    In:  Manufacturing & Service Operations Management Vol. 10, No. 1 ( 2008-01), p. 84-107
    Details
    In: Manufacturing & Service Operations Management, Institute for Operations Research and the Management Sciences (INFORMS), Vol. 10, No. 1 ( 2008-01), p. 84-107
    Abstract: The classical scheduling literature considers many problems where a given set of jobs must be processed at minimum cost, subject to various resource constraints. The literature only considers the issue of revenue generation in a very limited way, by allowing a job to remain unprocessed and its revenue contribution to be lost. By contrast, we consider three diverse practical situations where efficient scheduling affects revenue in much more general and realistic ways. First, we study two make-to-order environments where efficient scheduling increases customer goodwill, thus stimulating demand in different ways. Second, we study two make-to-stock environments where efficient scheduling creates inventory, thus also stimulating demand in different ways. Third, we study new product markets where efficient scheduling leads to a company becoming the first mover, and thus acquiring a larger market share. In each case, we provide both a computationally efficient algorithm for scheduling and a proof that a much more efficient algorithm is unlikely to exist. For both the make-to-stock and make-to-order problems, we also describe heuristic approaches that are easy to implement, and we study their average performance. The results show that substantial benefits arise from considering the implications of efficient scheduling for revenue and net profit. The practical impact of our work is to demonstrate the importance of efficient scheduling, not only in controlling cost, but also in increasing revenue and net profit.
    Type of Medium: Online Resource
    ISSN: 1523-4614 , 1526-5498
    URL: Article
    DOI: 10.1287/msom.1060.0144
    RVK:
    QA 10000
    Language: English
    Publisher: Institute for Operations Research and the Management Sciences (INFORMS)
    Publication Date: 2008
    detail.hit.zdb_id: 2023273-1
    SSG: 3,2
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  • 9
    Online Resource
    Online Resource
    Coordinating Supply and Demand on an On-Demand Service Platform with Impatient Customers
    Institute for Operations Research and the Management Sciences (INFORMS) ; 2019
    In:  Manufacturing & Service Operations Management Vol. 21, No. 3 ( 2019-07), p. 556-570
    Details
    In: Manufacturing & Service Operations Management, Institute for Operations Research and the Management Sciences (INFORMS), Vol. 21, No. 3 ( 2019-07), p. 556-570
    Abstract: We consider an on-demand service platform using earning-sensitive independent providers with heterogeneous reservation price (for work participation) to serve its time and price-sensitive customers with heterogeneous valuation of the service. As such, the supply and demand are “endogenously” dependent on the price the platform charges its customers and the wage the platform pays its independent providers. We present an analytical model with endogenous supply (number of participating agents) and endogenous demand (customer request rate) to study this on-demand service platform. To coordinate endogenous demand with endogenous supply, we include the steady-state waiting time performance based on a queueing model in the customer utility function to characterize the optimal price and wage rates that maximize the profit of the platform. We first analyze a base model that uses a fixed payout ratio (i.e., the ratio of wage over price), and then extend our model to allow the platform to adopt a time-based payout ratio. We find that it is optimal for the platform to charge a higher price when demand increases; however, the optimal price is not necessarily monotonic when the provider capacity or the waiting cost increases. Furthermore, the platform should offer a higher payout ratio as demand increases, capacity decreases or customers become more sensitive to waiting time. We also find that the platform should lower its payout ratio as it grows with the number of providers and customer demand increasing at about the same rate. We use a set of actual data from a large on-demand ride-hailing platform to calibrate our model parameters in numerical experiments to illustrate some of our main insights.
    Type of Medium: Online Resource
    ISSN: 1523-4614 , 1526-5498
    URL: Article
    DOI: 10.1287/msom.2018.0707
    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
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  • 10
    Online Resource
    Online Resource
    Retailer-Direct Financing Contracts Under Consignment
    Institute for Operations Research and the Management Sciences (INFORMS) ; 2020
    In:  Manufacturing & Service Operations Management Vol. 22, No. 3 ( 2020-05), p. 528-544
    Details
    In: Manufacturing & Service Operations Management, Institute for Operations Research and the Management Sciences (INFORMS), Vol. 22, No. 3 ( 2020-05), p. 528-544
    Abstract: Problem definition: Many small businesses (suppliers) use web platforms (retailers) to sell their products on a consignment basis. Suppliers are often financially constrained, which affects their profits. Academic/practical relevance: We derive the equilibrium terms of the loan that a retailer will offer to a supplier in a consignment selling environment and their implications for supply chain efficiency. Our model is inspired by the lending program initiated by a major web platform owner. Methodology: We formulate and solve a Stackelberg game. The retailer sets loan terms that may include a debt seniority requirement. The supplier may either accept the retailer’s offer or borrow only from the bank or rely solely on its own capital. A competitively priced bank loan is the supplier’s default option. Results: There exist parameter values for which the on-equilibrium loan terms include retailer debt seniority as well as parameter values that do not. In the latter case, the supplier makes the bank the senior lender. The retailer’s debt seniority choice depends on the supplier’s working capital. When the retailer chooses to be the senior lender, its loan terms may induce the supplier to produce more than the first-best quantity. Managerial implications: Direct financing under equilibrium loan terms weakly improves the expected profits of both the retailer and the supplier. However, it may induce the supplier to produce less than or equal to or greater than the first-best production quantity. Loan limits serve to reduce overproduction.
    Type of Medium: Online Resource
    ISSN: 1523-4614 , 1526-5498
    URL: Article
    DOI: 10.1287/msom.2018.0754
    RVK:
    QA 10000
    Language: English
    Publisher: Institute for Operations Research and the Management Sciences (INFORMS)
    Publication Date: 2020
    detail.hit.zdb_id: 2023273-1
    SSG: 3,2
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