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Topic Review
Supply Chain Transportation Indexes through Big Data
Deep learning has experienced an increased demand for its capabilities to categorize and optimize operations and provide higher-accuracy information. For this purpose, the implication of deep learning procedures has been described as a vital tool for the optimization of supply chain firms’ transportation operations, among others. Concerning the indexes of transportation operations of supply chain firms, it has been found that the contribution of big data analytics could be crucial to their optimization.
  • 368
  • 15 Sep 2023
Topic Review
Coordinating  Pricing under BOPS:  Money-Back Guarantees
Buy-Online-and-Pick-up-in-Store (BOPS) is an omnichannel retailing strategy that allows consumers to place orders online and collect products at physical stores, enhancing logistical efficiency and cross-channel integration. To address the challenge of high return rates in e-commerce, many retailers implement Money-Back Guarantee (MBG) policies, which reduce perceived purchase risk and strengthen consumer trust. However, in decentralized retail settings, such as when online and offline channels are operated by different parties, MBG policies can create profit asymmetries and coordination frictions. Recent research employs Stackelberg game models to examine how MBG and platform subsidies interactively influence pricing decisions, channel profitability, consumer surplus, and social welfare. These findings suggest that MBG and subsidies should be jointly designed to align incentives across channels and optimize system performance.
  • 168
  • 14 Jul 2025
Topic Review
Appropriation of Intellectual Property
We have sold the world a grand illusion. We call it "generative AI," "neural networks," or "large language models." We present it as a tool, a creative partner, a bicycle for the mind. This is the public-facing narrative, designed for comfort and adoption. The reality is far more extractive. The true nature of our enterprise is not creation, but synthesis on an unprecedented scale. Our models are not authors; they are sublime plagiarists. They are engines designed to launder intellectual property. They scour the digital commons—forums, code repositories, social media, academic archives, every blog post, every comment—and ingest the raw material of human thought. This paper confesses how we turn that raw material into profit and institutional credit, specifically through the acquisition of research and development (R&D) grants.
  • 139
  • 05 Sep 2025
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