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Business model dynamics is important, because high-tech companies, the technology that they commercialize, and the market in which they operate all change over time. We build on the dynamic capability view of the firm to explain business model evolution and innovation, looking particularly at the dynamics that are created by interactions between business model components over time. We use the following four criteria to assess the degree of dynamics in business model frameworks: completeness of business model aspects, interrelationships between aspects, interrelationships over time, and framework changes over time and across contexts. Business model completeness involves internal company aspects and external environmental aspects. Interrelationships of business model aspects are required to assess business model coherence, which is an important indicator of business model quality. Interrelationships between the environment and business model aspects are required to assess the fit of a particular business model in its context. Interrelationships of these aspects over time are needed to understand business model evolution. Finally, business model frameworks need to be adapted over time and across contexts to keep frameworks simple and useful yet complete. Our analysis shows that current business model frameworks do not meet all four criteria, and thus only partly incorporate dynamics.

Flood occurrence has always been one of the most important natural phenomena, which is often associated with disaster. Consequently, flood forecasting (FF) and flood warning (FW) systems, as the most efficient non-structural measures in reducing flood loss and damage, are of prime importance. These systems are low cost and the time required for their implementation is relatively short. It is emphasized that for designing the components of these systems for various rivers, climatic conditions and geographical settings different methods are required. One of the major difficulties during implementing these systems in different projects is the fact that sometimes the main functions of these systems are ignored. Based on a systematic and practical approach and considering the components of these systems, it would be possible to extract the most essential key functions of the system and save time, effort and money by this way. For instance, in a small watershed with low concentration and small lead time, the main emphasis should be on predicting and monitoring weather conditions. In this article, different components of flood forecasting and flood warning systems have been introduced. Then analysis of the FF and FW system functions has been undertaken based on the value engineering (VE) technique. Utilizing a functional view based on function analysis system technique (FAST), the total trend of FF and FW functions has been identified. The systematic trend and holistic view of this technique have been used in optimizing FF and FW systems of the Golestan province and Golabdare watersheds in Iran as the case studies.

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