Restaurant customers\u27 revisit intention and negative word-of-mouth behavior

The purpose of this study is threefold. First, this study intends to determine the factors which affect whether or not customers complain to management when they had problems at a casual table service restaurant. Second, this study seeks to determine the factors which affect the likelihood of returning to the restaurant for customers who complained to management about their problems. Third, this study examines the factors which affect the extent of negative word-of-mouth engaged by customers who complained to management; This study confirms the importance of complaint management in restaurant business. It further suggests how restaurant managers utilize their resources to resolve customers\u27 problems and thereby enhancing customer satisfaction. Thus, management may build a long-term relationship with customers and retain loyal customers

Macroscopic Quantum Tunneling Effect of Z2 Topological Order

In this paper, macroscopic quantum tunneling (MQT) effect of Z2 topological order in the Wen-Plaquette model is studied. This kind of MQT is characterized by quantum tunneling processes of different virtual quasi-particles moving around a torus. By a high-order degenerate perturbation approach, the effective pseudo-spin models of the degenerate ground states are obtained. From these models, we get the energy splitting of the ground states, of which the results are consistent with those from exact diagonalization methodComment: 25 pages, 14 figures, 4 table

Cross-Lingual Cross-Platform Rumor Verification Pivoting on Multimedia Content

With the increasing popularity of smart devices, rumors with multimedia content become more and more common on social networks. The multimedia information usually makes rumors look more convincing. Therefore, finding an automatic approach to verify rumors with multimedia content is a pressing task. Previous rumor verification research only utilizes multimedia as input features. We propose not to use the multimedia content but to find external information in other news platforms pivoting on it. We introduce a new features set, cross-lingual cross-platform features that leverage the semantic similarity between the rumors and the external information. When implemented, machine learning methods utilizing such features achieved the state-of-the-art rumor verification results

A Bayesian measurement error model for two-channel cell-based RNAi data with replicates

RNA interference (RNAi) is an endogenous cellular process in which small double-stranded RNAs lead to the destruction of mRNAs with complementary nucleoside sequence. With the production of RNAi libraries, large-scale RNAi screening in human cells can be conducted to identify unknown genes involved in a biological pathway. One challenge researchers face is how to deal with the multiple testing issue and the related false positive rate (FDR) and false negative rate (FNR). This paper proposes a Bayesian hierarchical measurement error model for the analysis of data from a two-channel RNAi high-throughput experiment with replicates, in which both the activity of a particular biological pathway and cell viability are monitored and the goal is to identify short hair-pin RNAs (shRNAs) that affect the pathway activity without affecting cell activity. Simulation studies demonstrate the flexibility and robustness of the Bayesian method and the benefits of having replicates in the experiment. This method is illustrated through analyzing the data from a RNAi high-throughput screening that searches for cellular factors affecting HCV replication without affecting cell viability; comparisons of the results from this HCV study and some of those reported in the literature are included.Comment: Published in at http://dx.doi.org/10.1214/11-AOAS496 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org