Does RFID improve firms’ financial performance? an empirical analysis

Radio frequency identification (RFID) is viewed as a technology that improves supply chain efficiency by enhancing inventory efficiency, optimizing logistics, and coordinating the flow of materials. Although RFID has gained great attention in many business applications, the financial gain that accrues over time from RFID adoption is not well understood. We examine the effects of RFID on firm profits while adjusting for self-selection of adoption choice. We find that firms self-select into a certain adoption mode on the basis of their organizational characteristics. Our results also show that RFID confers significant benefits for firms that have adopted RFID. Interestingly, improved inventory ratio and sales efficiency begin to play a greater role in shaping higher profitability over time for firms that have adopted RFID possibly due to time-consuming processes for them to reap the benefits from RFID. However, we find that the values of RFID that accrue to firms are not universal across firm. That is, our results suggest that RFID confers a significant value for certain firms while it does not for other firms with unobservable disadvantages. In sum, our study sheds new light on what drives firms to adopt RFID and on which firms achieve higher financial performance in a post-adoption period as a result of RFID adoption.     

Higher-order schemes for the Laplace transformation method for parabolic problems

In this paper we solve linear parabolic problems using the three stage noble algorithms. First, the time discretization is approximated using the Laplace transformation method, which is both parallel in time (and can be in space, too) and extremely high order convergent. Second, higher-order compact schemes of order four and six are used for the the spatial discretization. Finally, the discretized linear algebraic systems are solved using multigrid to show the actual convergence rate for numerical examples, which are compared to other numerical solution methods.     

Performance assessment in an interactive call center workforce simulation

In this paper, a new performance assessment methodology for human-in-the-loop call center systems at the level of customer-agent interactions (CAI) is proposed. We develop a team-in-the-loop simulation test bed, to analyze CAI-level performance of a service system using a temporal performance measure with time windows. The proposed framework should allow researchers to collect and analyze individual as well as team performance at a finer granularity than current call center efforts which focus on queue-centered analysis. The software framework is object-oriented and has been designed to be configurable. A sample simulation study in different scenarios is illustrated to provide the usages and advantages of the proposed method with index of Interactive Service Performance.     

Improving responsiveness of soft aperiodic tasks using proportional slack time

In a real-time system with both hard real-time periodic jobs and soft real-time aperiodic jobs, it is important to guarantee that the deadline of each periodic job is met, as well as to provide a fast response time for each aperiodic job. We propose an algorithm, called Proportional Slack Reserve (PSR), that produces an efficient schedule for such an environment. For every execution unit of a periodic job, the PSR algorithm reserves time which can be used for execution of aperiodic jobs. If reserved time is not available, the algorithm assigns a deadline to an aperiodic job for achieving better responsiveness of aperiodic jobs. The proposed algorithm can fully utilize processing power while meeting all deadlines of periodic jobs. It can also easily reclaim the time unused by the periodic job. We analytically show that for each aperiodic job, the response time in a PSR schedule is no longer than that in a TBS schedule, which is known to be efficient for servicing aperiodic jobs. We also present simulation results in which the response time of PSR is significantly improved over that of TBS, and moreover the performance of PSR compares favorably with TB(N) considering scheduling overhead.     

Multiple change-point detection of multivariate mean vectors with the Bayesian approach

Bayesian multiple change-point models are proposed for multivariate means. The models require that the data be from a multivariate normal distribution with a truncated Poisson prior for the number of change-points and conjugate priors for the distributional parameters. We apply the stochastic approximation Monte Carlo (SAMC) algorithm to the multiple change-point detection problems. Numerical results show that SAMC makes a significant improvement over RJMCMC for complex Bayesian model selection problems in change-point estimation.     

Credible sets for risk ratios in over-reported two-sample binomial data using the double-sampling scheme

We consider point and interval estimation for risk ratios based on two independent samples of binomial data subject to false positive misclassification. For such data it is well known that the model is unidentifiable. We consider incorporating training data obtained by using a double-sampling scheme to make the model identifiable. In this identifiable model, we propose a Bayesian method to make statistical inferences. In particular, we derive an easy-to-implement closed-form algorithm for drawing from the posterior distributions. The algorithm is illustrated using a real data example and further examined via Monte Carlo simulation studies.     

Hybrid Simulation of Miscible Mixing with Viscous Fingering

By modeling mass transfer phenomena, we simulate solids and liquids dissolving or changing to other substances. We also deal with the very small‐scale phenomena that occur when a fluid spreads out at the interface of another fluid. We model the pressure at the interfaces between fluids with Darcy's Law and represent the viscous fingering phenomenon in which a fluid interface spreads out with a fractal‐like shape. We use hybrid grid‐based simulation and smoothed particle hydrodynamics (SPH) to simulate intermolecular diffusion and attraction using particles at a computable scale. We have produced animations showing fluids mixing and objects dissolving.     

Effectiveness of MMORPG‐based instruction in elementary English education in Korea

This study investigated the effectiveness of massive multiplayer online role‐playing game (MMORPG)‐based (massive multiplayer online role‐playing game) instruction in elementary English education. The effectiveness of the MMORPG program was compared with face‐to‐face instruction and the independent variables (gender, prior knowledge, motivation for learning, self‐directed learning skills, computer skills, game skills, computer capacity, network speed, and computer accessibility) were examined to see how accurately achievement was predicted in MMORPG instruction. The results indicated that students studying English utilizing online role‐playing games showed higher scores in areas of listening, reading, and writing than those who attended face‐to‐face instruction classes. It was also found that prior knowledge, motivation for learning, and network speed were factors affecting achievement in English learning. These findings suggest that MMORPGs can play an important role in improving English communicative skills.