The cost of complexity in system identification: The Output Error case

In this paper we investigate the cost of complexity, which is defined as the minimum amount of input power required to estimate the frequency response of a given linear time invariant system of order n with a prescribed degree of accuracy. In particular we require that the asymptotic (in the data length) variance is less or equal to γ over a prespecified frequency range [0,ω_B]. The models considered here are Output Error models, with an emphasis on fixed denominator and Laguerre models. Several properties of the cost are derived. For instance, we present an expression which shows how the pole of the Laguerre model affects the cost. These results quantify how the cost of the system identification experiment depends on n and on the model structure. Also, they show the relation between the cost and the amount of information we would like to extract from the system (in terms of ω_B and γ). For simplicity we assume that there is no undermodelling.     

Time windows-based team performance measures: a framework to measure team performance in dynamic environments

In this paper, we present a framework for implementing Team Performance Measures based on a temporal accuracy measure called the relative accuracy index (RAI) to evaluate and compare team performance in a command-and-control human-in-the-loop simulation. The framework allows researchers to collect and analyze team outcomes in an unbiased objective manner based on a temporal performance measure known as a Time Window. Our framework provides experimenters and subject matter experts the necessary tools to evaluate performance in terms of task demands. We also provide a sample analysis of individual and team performance using the RAI.     

Competitive strategies for ensuring Fintech platform performance: Evidence from multiple case studies

The emergence of Fintech platforms has revolutionized the way financial services are provided. And yet, in spite of their growing prominence in the global financial sector, there remains a lack of understanding of the competitive strategies that are appropriate for these platform-based businesses, and the implications of those strategies for their performance. Examining four case studies of some of the most successful Fintech platforms in China from the theoretical perspective of the core logics of strategy, we develop a theoretical framework that suggests that the nature of the competitive strategies deployed by a Fintech platform should be contingent on (1) the extent to which their services can be differentiated, as well as (2) the tangibility and physical presence of the platform’s service offerings. More specifically, our framework presents four different combinations of competitive strategies that Fintech platforms can adopt contingent on the nature of their services along these two dimensions. In addition, beyond the two dimensions, our framework suggests that all Fintech platforms should be underpinned by a common strategic core consisting of strategies that align the platform with social pressures. These pressures include those exerted by the government, the market, and society in general. With its findings, it is hoped that our study will provide specific guidance for Fintech practitioners on the appropriate competitive strategies to adopt in order to set their platforms on the path of commercial success.     

Assessing a cross-border logistics policy using a performance measurement system framework: the case of Hong Kong and the Pearl River Delta region

For the most rapidly growing economic entity in the world, China, a new logistics operation called the indirect cross-border supply chain model has recently emerged. The primary idea of this model is to reduce logistics costs by storing goods at a bonded warehouse with low storage cost in certain Chinese regions, such as the Pearl River Delta (PRD). This research proposes a performance measurement system (PMS) framework to assess the direct and indirect cross-border supply chain models. The PMS covers four categories including cost, time, quality and flexibility in the assessment of the performance of direct and indirect models. Furthermore, a survey was conducted to investigate the logistics performance of third party logistics (3PLs) at the PRD regions, including Guangzhou, Shenzhen and Hong Kong. The significance of the proposed PMS framework allows 3PLs accurately pinpoint the weakness and strengths of it current operations policy at four major performance measurement categories. Hence, this helps 3PLs further enhance the competitiveness and operations efficiency through better resources allocation at the area of warehousing and transportation.