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Management Sciences and Quantitative Methods Commons™
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- Keyword
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- Analytical hierarchical process (1)
- Analytical hierarchy process; expert choice; multiple objective decision making; supply chain management software (1)
- CART (1)
- Data (1)
- Data mining software (1)
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- Environmental policy (1)
- Hazardous waste management (1)
- International taxation; the European Commission; worldwide tax system; territorial tax system; domestic-sourced income; foreign-sourced income (1)
- K-means algorithm; data clustering; Kd-tree structure (1)
- Knowledge life cycle model (1)
- Logistics (1)
- Logistics policy evaluation (1)
- SAS (1)
- SPSS (1)
- Search costs; price obfuscation; diamond retail; data mining; pricing; revenue management (1)
- Spatial general equilibrium (1)
- Triple bottom line; B Corporations; COVID-19; social media; communication (1)
Articles 1 - 7 of 7
Full-Text Articles in Management Sciences and Quantitative Methods
B Corps’ Social Media Communications During The Covid-19 Pandemic: Through The Lens Of The Triple Bottom Line, Manveer Mann, Sang-Eun Byun, Whitney Ginder
B Corps’ Social Media Communications During The Covid-19 Pandemic: Through The Lens Of The Triple Bottom Line, Manveer Mann, Sang-Eun Byun, Whitney Ginder
Department of Marketing Faculty Scholarship and Creative Works
The COVID-19 pandemic and rising demand for transparency has heightened the importance of sustainability communications on social media to generate deeper stakeholder engagement. Although B Corporations (B Corps), businesses committed to the triple bottom line (TBL), could serve as a catalyst for sustainable development, little is known about how they communicate on social media during a crisis. Therefore, we examined social media communications of B Corps to (1) identify salient topics and themes, (2) analyze how these themes align with the TBL, and (3) evaluate social media performance against industry benchmarks. We focused on the apparel, footwear, and accessories (AFA) …
Tree-Based Algorithm For Stable And Efficient Data Clustering, Hasan Aljabbouli, Abdullah Albizri, Antoine Harfouche
Tree-Based Algorithm For Stable And Efficient Data Clustering, Hasan Aljabbouli, Abdullah Albizri, Antoine Harfouche
Department of Information Management and Business Analytics Faculty Scholarship and Creative Works
The K-means algorithm is a well-known and widely used clustering algorithm due to its simplicity and convergence properties. However, one of the drawbacks of the algorithm is its instability. This paper presents improvements to the K-means algorithm using a K-dimensional tree (Kd-tree) data structure. The proposed Kd-tree is utilized as a data structure to enhance the choice of initial centers of the clusters and to reduce the number of the nearest neighbor searches required by the algorithm. The developed framework also includes an efficient center insertion technique leading to an incremental operation that overcomes the instability problem of the K-means …
Subjectivity Of Diamond Prices In Online Retail: Insights From A Data Mining Study, Stanislav Mamonov, Tamilla Triantoro
Subjectivity Of Diamond Prices In Online Retail: Insights From A Data Mining Study, Stanislav Mamonov, Tamilla Triantoro
Department of Information Management and Business Analytics Faculty Scholarship and Creative Works
Diamonds belong to a unique product category whose perceived value is largely dependent on socially constructed beliefs. To explore the degree to which the physical properties of a diamond can be used to predict the diamond price, we perform data mining on a large dataset of loose diamonds scraped from an online diamond retailer. We find that diamond weight, color and clarity are the key characteristics that influence diamond prices. The data mining results also suggest a high degree of subjectivity in diamond pricing that may reflect price obfuscation strategies employed by diamond retailers.
The Emerging International Taxation Problems, James G. Yang, Victor N.A. Metallo
The Emerging International Taxation Problems, James G. Yang, Victor N.A. Metallo
Department of Accounting and Finance Faculty Scholarship and Creative Works
The problems of tax evasion and tax avoidance are as old as taxes themselves. Between 2015 and 2016 alone, many U.S. multinational corporations were involved in tax disputes with the European Commission. From a historical perspective, these disputes are unprecedented as they have resulted in tremendous amount of tax penalties. The most notable case was Apple for €13 billion of unpaid tax. This article discusses what tax strategies these corporations used that caused such disputes. It specifically investigates seven corporations: Apple Inc., McDonald’s, Starbucks, Fiat, Amazon, Google, and Ikea, and elaborates on the following tax strategies: high royalties, intercompany transfer …
A Relative Comparison Of Leading Supply Chain Management Software Packages, Zhongxian Wang, Ruiliang Yan, Kimberly Hollister, Ruben Xing
A Relative Comparison Of Leading Supply Chain Management Software Packages, Zhongxian Wang, Ruiliang Yan, Kimberly Hollister, Ruben Xing
Department of Information Management and Business Analytics Faculty Scholarship and Creative Works
Supply Chain Management (SCM) has proven to be an effective tool that aids companies in the development of competitive advantages. SCM Systems are relied on to manage warehouses, transportation, trade logistics and various other issues concerning the coordinated movement of products and services from suppliers to customers. Although in today’s fast paced business environment, numerous supply chain solution tools are readily available to companies, choosing the right SCM software is not an easy task. The complexity of SCM systems creates a multifaceted issue when selecting the right software, particularly in light of the speed at which technology evolves. In this …
Chapter Xii: A Comparison And Scenario Analysis Of Leading Data Mining Software, John Wang, Xiaohua Hu, Kimberly Hollister, Dan Zhu
Chapter Xii: A Comparison And Scenario Analysis Of Leading Data Mining Software, John Wang, Xiaohua Hu, Kimberly Hollister, Dan Zhu
Department of Information Management and Business Analytics Faculty Scholarship and Creative Works
Finding the right software is often hindered by different criteria as well as by technology changes. We performed an analytic hierarchy process (AHP) analysis using Expert Choice to determine which data mining package was best suitable for us. Deliberating a dozen alternatives and objectives led us to a series of pair-wise comparisons. When further synthesizing the results, Expert Choice helped us provide a clear rationale for the decision. The issue is that data mining technology is changing very rapidly. Our article focused only on the major suppliers typically available in the market place. The method and the process that we …
A Risk/Cost Framework For Logistics Policy Evaluation: Hazardous Waste Management, Kimberly Hollister
A Risk/Cost Framework For Logistics Policy Evaluation: Hazardous Waste Management, Kimberly Hollister
Department of Information Management and Business Analytics Faculty Scholarship and Creative Works
The management of hazardous waste disposal operations is extremely complex involving a multitude of environmental, engineering, economic, social and political concerns. This article proposes a framework to assist policy makers in the evaluation of logistic policies. A spatial general equilibrium based policy evaluation model is developed to calculate risk, cost, and risk equity tradeoff curves. This framework provides policy makers a tool with which they can relate resulting logistics patterns and their associated risk, cost, and equity attributes to original policy goals.