Vossen, "Pricing approaches for data markets," in Proc. Int. Workshop Bus. Intell. Real-Time Enterprise. Berlin, Germany: Springer, 2012, pp. 129-144.Pricing approaches for data markets. MUSCHALLE A,STAHL F,LSER A,et al. Workshop business intelligence for the real time enterprise . ...
although advances in computer-mediated relationships combined with data mining permits more in-depth knowledge of key aspects of customer behavior, the opportunity for using such insights to develop personalized participative pricing has not been widely exploited and there is a lack of approaches that ...
Economy pricingentails setting the lowest price in the market with the intention of attracting bargain hunters. It places little emphasis on product quality and instead markets to the subset of buyers who are willing to abandon quality for a lower price. 9 Pricing Models Following is an overview ...
This pricing model is common for architects. When a client approaches an architecture firm with a request to design and construct a building, the firm will assess the project's scale, complexity, materials, and other specific requirements to provide a project-based quote. Obviously, the process ...
With our discussion of the identification and estimation of network effects completed, we can now turn to approaches to study pricing in these markets and their results, which more closely connects with the earlier sections in the chapter. We distinguish between two approaches, which loosely correspo...
To maximize profits, producers and retailers analyzesupply and demand dynamicsin their particular markets, ingesting many data points from competitors and market surveys. They use methods including break-even analysis, in which they tabulate fixed and variable costs to determine how much inventory must...
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To position the contributions of this paper in the existing literature, we briefly review the main approaches to pricing and hedging in incomplete markets. First, there is a large literature on developing methods for economic hedging based on mean-variance utility (Balduzzi and Kallal (1997); Bree...
This indicates that only earthquakes with financial losses and extreme magnitudes are considered in the data selection. Apart from these two methods, some articles used other approaches to model the loss and magnitude of the 𝑖i-th earthquake. Romaniuk [40] and Kang et al. [46] used ...
Meanwhile, ML algorithms can process vast amounts of data to identify pricing patterns that may deviate from the binomial model's assumptions. These technologies often require more dynamic, data-driven approaches to option pricing. Nevertheless, the binomial model's fundamental insights remain valuable...