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  • 1
    Online Resource
    Online Resource
    Academy of Management ; 2016
    In:  Academy of Management Perspectives Vol. 30, No. 4 ( 2016-11), p. 349-368
    In: Academy of Management Perspectives, Academy of Management, Vol. 30, No. 4 ( 2016-11), p. 349-368
    Type of Medium: Online Resource
    ISSN: 1558-9080 , 1943-4529
    RVK:
    Language: English
    Publisher: Academy of Management
    Publication Date: 2016
    detail.hit.zdb_id: 2231854-9
    detail.hit.zdb_id: 638493-6
    SSG: 3,2
    Location Call Number Limitation Availability
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  • 2
    Online Resource
    Online Resource
    Institute for Operations Research and the Management Sciences (INFORMS) ; 1973
    In:  Management Science Vol. 20, No. 4-part-ii ( 1973-12), p. 617-628
    In: Management Science, Institute for Operations Research and the Management Sciences (INFORMS), Vol. 20, No. 4-part-ii ( 1973-12), p. 617-628
    Abstract: Empirical data would suggest that forestry managers have been hesitant in their adoption of a management sciences approach to their problems of prevention, detection and suppression of forest fires. A joint program of research has been undertaken between the Alberta Forest Service and the Faculty of Business Administration and Commerce at the University of Alberta in an attempt to develop, test and evaluate state-of-the-art management science approaches to the problems of forest management. This paper outlines the program of research being undertaken and describes a simulation model which has been developed as part of the research program. The model, which can be readily adapted for analysis of any forest, has been used to examine various fire detection strategies for the Footner Forest in Northern Alberta. The results from this examination are presented along with the results from the goodness-of-fit tests used to validate the model. The model is presently being used and evaluated by forestry personnel.
    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: 1973
    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) ; 2023
    In:  Management Science
    In: Management Science, Institute for Operations Research and the Management Sciences (INFORMS)
    Abstract: This paper provides empirical evidence on predictable time variations in out-of-sample bond return predictability. Bond return predictability is associated with periods of high (low) economic activity (uncertainty), which implies that violations of the expectations hypothesis are state dependent and linked to features of the business cycle. These state dependencies in predictability, established by introducing a new multivariate test for equal conditional predictive ability, can be used in real time to improve out-of-sample bond risk premia estimates and investors’ economic utility through a novel dynamic forecast combination scheme that uses predicted forecasting performance to identify the best set of methods to include in the combined forecast. Dynamically combined forecasts exhibit strong countercyclical behavior and peak during recessions. This paper was accepted by Lukas Schmid, finance. Funding: This work was supported by the Danish Council of Independent Research [Grants DFF 7024–00020B and DFF 9033–00003B] and the Danish Finance Institute. Supplemental Material: The data files and online appendices are available at https://doi.org/10.1287/mnsc.2023.4713 .
    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: 2023
    detail.hit.zdb_id: 206345-1
    detail.hit.zdb_id: 2023019-9
    SSG: 3,2
    Location Call Number Limitation Availability
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  • 4
    Online Resource
    Online Resource
    Institute for Operations Research and the Management Sciences (INFORMS) ; 2015
    In:  Management Science Vol. 61, No. 6 ( 2015-06), p. 1217-1236
    In: Management Science, Institute for Operations Research and the Management Sciences (INFORMS), Vol. 61, No. 6 ( 2015-06), p. 1217-1236
    Abstract: Pay what you want (PWYW) can be an attractive marketing strategy to price discriminate between fair-minded and selfish customers, to fully penetrate a market without giving away the product for free, and to undercut competitors that use posted prices. We report on laboratory experiments that identify causal factors determining the willingness of buyers to pay voluntarily under PWYW. Furthermore, to see how competition affects the viability of PWYW, we implement markets in which a PWYW seller competes with a traditional seller. Finally, we endogenize the market structure and let sellers choose their pricing strategy. The experimental results show that outcome-based social preferences and strategic considerations to keep the seller in the market can explain why and how much buyers pay voluntarily to a PWYW seller. We find that PWYW can be viable on a monopolistic market, but it is less successful as a competitive strategy because it does not drive traditional posted-price sellers out of the market. Instead, the existence of a posted-price competitor reduces buyers' payments and prevents the PWYW seller from fully penetrating the market. When given the choice, most sellers opt for setting a posted price rather than a PWYW pricing strategy. We discuss the implications of these results for the use of PWYW as a marketing strategy. Data, as supplemental material, are available at http://dx.doi.org/10.1287/mnsc.2014.1946 . This paper was accepted by Uri Gneezy, behavioral economics.
    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: 2015
    detail.hit.zdb_id: 206345-1
    detail.hit.zdb_id: 2023019-9
    SSG: 3,2
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  • 5
    Online Resource
    Online Resource
    Academy of Management ; 2003
    In:  The Academy of Management Review Vol. 28, No. 3 ( 2003-07-01), p. 514-
    In: The Academy of Management Review, Academy of Management, Vol. 28, No. 3 ( 2003-07-01), p. 514-
    Type of Medium: Online Resource
    ISSN: 0363-7425
    RVK:
    Language: English
    Publisher: Academy of Management
    Publication Date: 2003
    detail.hit.zdb_id: 2064579-X
    detail.hit.zdb_id: 196768-X
    SSG: 3,2
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  • 6
    Online Resource
    Online Resource
    Institute for Operations Research and the Management Sciences (INFORMS) ; 2023
    In:  Management Science
    In: Management Science, Institute for Operations Research and the Management Sciences (INFORMS)
    Abstract: We document that regulatory enforcement actions for financial misrepresentation cluster in industry-specific waves and that wave-related enforcement has information spillovers on industry peer firms. Waves and spillovers have significant effects on share prices. Early-wave target firms have the largest short-run losses in share values and the largest information spillovers on industry peer firms. Late-wave targets’ short-run losses are smaller, but not because they involve less costly instances of misconduct. Rather, late-wave targets are subject to more information spillovers from earlier in the wave. These results indicate that prices incorporate changes in the likelihood that a firm will face wave-related enforcement action for financial misconduct. Short-window share-price losses understate the total share-price impact, particularly for firms whose financial misrepresentation is revealed late in an enforcement wave. This paper was accepted by David Simchi-Levi, finance. Supplemental Material: The internet appendix and data are available at https://doi.org/10.1287/mnsc.2023.4711 .
    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: 2023
    detail.hit.zdb_id: 206345-1
    detail.hit.zdb_id: 2023019-9
    SSG: 3,2
    Location Call Number Limitation Availability
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