Value Network Design for Innovations: Developing Alternative Value Network Drafts

Customer Lifetime Network Value

Today, people are increasingly connected and extensively interact with each other using technology-enabled media. Hence, customers are more frequently exposed to social influence of other customers when making purchase decisions. However, established approaches for customer valuation most widely neglect network effects based on social influence leading to a misallocation of resources. Therefore...

Value Prediction Network

This paper proposes a novel deep reinforcement learning (RL) architecture, called Value Prediction Network (VPN), which integrates model-free and model-based RL methods into a single neural network. In contrast to typical model-based RL methods, VPN learns a dynamics model whose abstract states are trained to make option-conditional predictions of future values (discounted sum of rewards) rathe...

Two-stage network DEA-R based on value efficiency

It is essential for most organizations and financial institutes to be able to evaluate their decision-making units (DMUs), when there is only a ratio of inputs to outputs (or vice versa) available. In this paper, we will propose our two-stage DEA-R models, which are a combination of data envelopment analysis and ratio data, based on value efficiency. Integrating value efficiency into data envel...

Developing a cross-docking network design model under uncertain environment

Cross-docking is a logistic concept, which plays an important role in supply chain management by decreasing inventory holding, order packing, transportation costs and delivery time. Paying attention to these concerns, and importance of the congestion in cross docks, we present a mixed-integer model to optimize the location and design of cross docks at the same time to minimize the total transpo...

Network Size, Value and Cycles