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    SUNY Canton

    院校EST. 1906
    146论文总数
    1,176引用总数

    The State University of New York at Canton (SUNY Canton) is a public college in Canton, New York. It is part of the State University of New York. The college offers 31 bachelor's degrees, 20 associate degrees, three one-year certificate programs, and 23 online degrees.

    论文量&引用量时间轴

    机构学者

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    Ali Shehzad Zaidi
    Ali Shehzad Zaidi
    STATE UNIVERSITY of New York
    论文:12引用:0H-index:0
    Cori Wilhelm
    Cori Wilhelm
    Coll Tech Lib, SUNY Canton
    论文:7引用:0H-index:0
    Bradley Fowler
    Bradley Fowler
    SUNY Canton
    论文:7引用:0H-index:0
    richard m manazir
    richard m manazir
    SUNY Canton
    论文:6引用:0H-index:0
    kenneth scarola
    kenneth scarola
    Windsor Dermatology
    论文:6引用:0H-index:0
    robert l rescorl
    robert l rescorl
    Vernon College
    论文:6引用:0H-index:0
    david s jamison
    david s jamison
    Windsor Dermatology
    论文:6引用:0H-index:0
    janet mcclellan
    janet mcclellan
    Criminal Invest Dept, State Univ New York Canton
    论文:5引用:0H-index:0
    Laini Kavaloski
    Laini Kavaloski
    Univ Wisconsin Madison, Dept English, Madison, WI USA
    论文:5引用:0H-index:0

    论文(146)

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    1The Implicated Subject and World War II Identity in the Twenty-First Century
    Laini Kavaloski
    2026GRAPHIC WAR Jewish Women Drawing Contested Spaces(2026)
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    2Militarized Bodies and Contested Homelands in the Works of Miriam Libicki and Sarah Glidden
    Laini Kavaloski
    2026GRAPHIC WAR Jewish Women Drawing Contested Spaces(2026)
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    3A Simple SUR-based Approach to Handling Missing Data
    Sima Fortsch,Jeong Hoon Choi, Chia-Hung Chuang, Elena Khapalova

    PurposeThis study aims to explore practical strategies for addressing missing competitor data to support data-driven decision-making in the North American automotive industry.Design/methodology/approachThe authors analyze 11 years of monthly sales data from GM, Ford, Honda, Toyota and Nissan to develop an approach for data-driven decisions in the presence of missing competitor information. The authors use autoregressive time series regressions to model four scenarios: full access to competitor information, substituting competitors' missing data using historical marginal rates of substitution (MRS), a direct variable replacement without MRS and ignoring missing data entirely.FindingsResults indicate that both the MRS-based approach (Method 2) and direct variable replacement (Method 3) offer predictive accuracy comparable to using full data, with minimal loss in explanatory power. While both methods are likely sufficient, due to the simplicity and time savings associated with direct variable replacement, the authors suggest using Method 3. In contrast, ignoring missing data significantly degrades model performance. These findings suggest that managers can maintain decision quality even with partial data by using simple substitution strategies.Practical implicationsWhile the proposed framework is validated using data from the North American automotive industry, the findings suggest its applicability to other competitive sectors.Originality/valueBy evaluating the above four distinct scenarios, we offer the novel application of marginal rates of substitution and the direct variable replacement strategy for replacing missing data, proving that decision-making could remain feasible even in the absence of complete information.

    2026JOURNAL OF MODELLING IN MANAGEMENT(2026)
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    4"The Drug of H" Holocaust Addiction, Pulp Horror, and Jewish Identity
    Laini Kavaloski
    2026GRAPHIC WAR Jewish Women Drawing Contested Spaces(2026)
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    5"Work for the Future, Not Only for Memory" Agency, Activism, and Joy in the Works of Leela Corman and Julia Alekseyeva
    Laini Kavaloski
    2026GRAPHIC WAR Jewish Women Drawing Contested Spaces(2026)
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    合作机构(99)

    克拉克森大学合作论文 8
    Vernon College合作论文 6
    Windsor Dermatology合作论文 6
    田纳西大学诺克斯维尔分校合作论文 4
    University of Northwestern合作论文 4
    埃默里大学合作论文 4
    纽约州立大学合作论文 4
    伊利诺伊大学芝加哥分校合作论文 3
    比萨大学合作论文 3
    John Brown University合作论文 3

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