Contemporary system maturity assessment approaches have failed to provide robust quantitative system evaluations resulting in increased program costs and developmental risks. Standard assessment metrics, such as Technology Readiness Levels (TRL), do not sufficiently evaluate increasingly complex systems. The System Readiness Level (SRL) is a newly developed system development metric that is a mathematical function of TRL and Integration Readiness Level (IRL) values for the components and connections of a particular system. SRL acceptance has been hindered because of concerns over SRL mathematical operations that may lead to inaccurate system readiness assessments. These inaccurate system readiness assessments are called readiness reversals. A new SRL calculation method using incidence matrices is proposed to alleviate these mathematical concerns. The presence of SRL readiness reversal is modeled for four SRL calculation methods across several system configurations. Logistic regression analysis demonstrates that the proposed Incidence Matrix SRL (IMSRL) method has a decreased presence of readiness reversal than other approaches suggested in the literature. Viable SRL methods will foster greater SRL adoption by systems engineering professionals and will support system development risk reduction goals.

The emergence of B2B electronic markets has greatly changed the relative bargaining power of buyers and sellers. We study the equilibrium market structure in a buyer’s market. We find that buyer-controlled B2B markets and neutral B2B markets have different equilibrium structures, and the emergence of B2B markets will increase social welfare, but its effect on buyers and sellers will be different: B2B markets increase the consumer surplus of the end market, but their effects on buyer and seller profits are moderated by the relative bargaining power of buyers and sellers. The profits of the side with much weaker bargaining power will decrease due to the introduction of B2B markets.

Automation systems for buildings interconnect components and technologies from the information technology industry and the telecommunications industry. In these industries, existing platforms and new platforms (that are designed to make building automation systems work) compete for market acceptance and consequently several platform battles among suppliers for building automation networking are being waged. It is unclear what the outcome of these battles will be and also which factors are important in achieving platform dominance. Taking the fuzziness of decision makers’ judgments into account, a fuzzy multi-criteria decision-making methodology called the Fuzzy Analytic Hierarchy Process is applied to investigate the importance of such factors in platform battles for building automation networking. We present the relative importance of the factors for three types of platforms (subsystem platforms, system platforms, and evolved subsystem platforms). The results provide a first indication that the set of important factors differs per type of platform. For example, when focusing on other stakeholders, for subsystem platforms, the previous installed base is of importance; for system platforms, the diversity of the network of stakeholders is essential; and for evolved subsystem platforms, the judiciary is an important factor.

In this paper, we present a new method for finding a fixed local-optimal policy for computing the customer lifetime value. The method is developed for a class of ergodic controllable finite Markov chains. We propose an approach based on a non-converging state-value function that fluctuates (increases and decreases) between states of the dynamic process. We prove that it is possible to represent that function in a recursive format using a one-step-ahead fixed-optimal policy. Then, we provide an analytical formula for the numerical realization of the fixed local-optimal strategy. We also present a second approach based on linear programming, to solve the same problem, that implement the c-variable method for making the problem computationally tractable. At the end, we show that these two approaches are related: after a finite number of iterations our proposed approach converges to same result as the linear programming method. We also present a non-traditional approach for ergodicity verification. The validity of the proposed methods is successfully demonstrated theoretically and, by simulated credit-card marketing experiments computing the customer lifetime value for both an optimization and a game theory approach.

This article introduces a consistency index for measuring the consistency level of an interval fuzzy preference relation (IFPR). An approach is then proposed to construct an additive consistent IFPR from a given inconsistent IFPR. By using a weighted averaging method combining the original IFPR and the constructed consistent IFPR, a formula is put forward to repair an inconsistent IFPR to generate an IFPR with acceptable consistency. An iterative algorithm is subsequently developed to rectify an inconsistent IFPR and derive one with acceptable consistency and weak transitivity. The proposed approaches can not only improve consistency of IFPRs but also preserve the initial interval uncertainty information as much as possible. Numerical examples are presented to illustrate how to apply the proposed approaches.

Increasing popularity of spectrum-based services brings the striking contradictions between the limited spectrum resource and its increasing demands. This paper puts forward an approach to forecast the future spectrum demand and its economic value, so as to offer a scientific basis for spectrum regulators to resolve this contradiction effectively and make a long-term spectrum-use plan. Specifically, this paper analyzes the driving factors of spectrum demand firstly, based on which a forecasting model is constructed to predict the spectrum demand and its deficit/surplus in the next few years. Then, a forecasting model to measure the economic value of spectrum is proposed based on marginal opportunity cost theory, and the indifference curve is introduced to show the economic value generated by additional spectrum. Additionally, an empirical study is conducted to forecast the spectrum demand and its economic value for China in the next 10 years according to the proposed method. The results of this study show that spectrum deficit is a trend in future and releasing additional spectrum will bring China huge economic benefits.