Service-dominant logic for exploring modular business service system

Investigating the management of the three dimensions of modular business service system from the perspective of the service-dominant (S-D) logic. An integrated approach with an abductive research process in theory building was conducted through case study. The results show that ten foundational premises of S-D logic, especially service -focused, customer-oriented, and rational views can be applied in defining and managing the modular business service system constructed by service modularization

Continuity of the Value Function for Deterministic Optimal Impulse Control with Terminal State Constraint

Deterministic optimal impulse control problem with terminal state constraint is considered. Due to the appearance of the terminal state constraint, the value function might be discontinuous in general. The main contribution of this paper is the introduction of an intrinsic condition under which the value function is continuous. Then by a Bellman dynamic programming method, the corresponding Hamilton-Jacobi-Bellman type quasi-variational inequality (QVI, for short) is derived for which the value function is a viscosity solution. The issue of whether the value function is characterized as the unique viscosity solution to this QVI is carefully addressed and the answer is left open challengingly.Comment: 29 page

Empirical properties of inter-cancellation durations in the Chinese stock market

Order cancellation process plays a crucial role in the dynamics of price formation in order-driven stock markets and is important in the construction and validation of computational finance models. Based on the order flow data of 18 liquid stocks traded on the Shenzhen Stock Exchange in 2003, we investigate the empirical statistical properties of inter-cancellation durations in units of events defined as the waiting times between two consecutive cancellations. The inter-cancellation durations for both buy and sell orders of all the stocks favor a $q$-exponential distribution when the maximum likelihood estimation method is adopted; In contrast, both cancelled buy orders of 6 stocks and cancelled sell orders of 3 stocks prefer Weibull distribution when the nonlinear least-square estimation is used. Applying detrended fluctuation analysis (DFA), centered detrending moving average (CDMA) and multifractal detrended fluctuation analysis (MF-DFA) methods, we unveil that the inter-cancellation duration time series process long memory and multifractal nature for both buy and sell cancellations of all the stocks. Our findings show that order cancellation processes exhibit long-range correlated bursty behaviors and are thus not Poissonian.Comment: 14 pages, 7 figures and 5 table

DDAC-SpAM: A Distributed Algorithm for Fitting High-dimensional Sparse Additive Models with Feature Division and Decorrelation

Distributed statistical learning has become a popular technique for large-scale data analysis. Most existing work in this area focuses on dividing the observations, but we propose a new algorithm, DDAC-SpAM, which divides the features under a high-dimensional sparse additive model. Our approach involves three steps: divide, decorrelate, and conquer. The decorrelation operation enables each local estimator to recover the sparsity pattern for each additive component without imposing strict constraints on the correlation structure among variables. The effectiveness and efficiency of the proposed algorithm are demonstrated through theoretical analysis and empirical results on both synthetic and real data. The theoretical results include both the consistent sparsity pattern recovery as well as statistical inference for each additive functional component. Our approach provides a practical solution for fitting sparse additive models, with promising applications in a wide range of domains.Comment: 52 pages, 3 figure

Disordered and Multiple Destinations Path Planning Methods for Mobile Robot in Dynamic Environment

In the smart home environment, aiming at the disordered and multiple destinations path planning, the sequencing rule is proposed to determine the order of destinations. Within each branching process, the initial feasible path set is generated according to the law of attractive destination. A sinusoidal adaptive genetic algorithm is adopted. It can calculate the crossover probability and mutation probability adaptively changing with environment at any time. According to the cultural-genetic algorithm, it introduces the concept of reducing turns by parallelogram and reducing length by triangle in the belief space, which can improve the quality of population. And the fallback strategy can help to jump out of the “U” trap effectively. The algorithm analyses the virtual collision in dynamic environment with obstacles. According to the different collision types, different strategies are executed to avoid obstacles. The experimental results show that cultural-genetic algorithm can overcome the problems of premature and convergence of original algorithm effectively. It can avoid getting into the local optimum. And it is more effective for mobile robot path planning. Even in complex environment with static and dynamic obstacles, it can avoid collision safely and plan an optimal path rapidly at the same time