Suchergebnisse

AbstractIn this article, we address two network design problems for a responsive supply chain that consists of make‐to‐order (make‐to‐assemble) facilities facing stochastic demand and service time. The response time to customer orders, critical to the success of the supply chain, is the sum of the flow time in the facility and the delivery time to the customers. The response time performance in our models is measured by the probability that the response time is shorter than a constant. This nonlinear performance measure makes the models less or not tractable. The objective of both problems is to minimize the expected network cost that consists of the cost of delivery to customers as a function of the time of delivery (or the mode of transportation), the fixed cost of locating facilities and the capacity cost as a linear function of the processing capacity. The main decision variables are the number and locations of facilities, the resources allocated to them and the delivery mode selected between facilities and demand. In the first problem, a constraint is imposed to ensure an acceptable response time level. In the second problem, a penalty is charged on the number of days that each unit is delivered later than the targeted response time and is incorporated into the objective function. In the first problem, the probabilistic constraint on the flow time can be linearized and the problem can be formulated as an integer linear programming model. In the second problem, we propose an approximation approach to linearize the objective function and an iterative search and cut algorithm to combine linear approximation with neighborhood search. A multi‐start meta‐heuristic is also suggested. Computational experiments are conducted to evaluate the performance of these solution procedures. Recommendations are made on the basis of the computational results. This appears to be the first study in the area of locating capacitated facilities with stochastic demand to incorporate the delivery mode choice decision and to evaluate the expected congestion cost as a function of the actual flow time in the facilities, instead of the average one. The models developed enable the decision maker to investigate the effect of a combination of facility location, capacity allocation, and delivery mode decisions on the expected network cost and the response time. In addition, the findings of the computational experiments shed light on tuning parameters of approximation algorithms.

In this paper, we study the relation between order imbalances (buyer versus seller-initiated trades measured by a buy ratio) at an early trading hour and intraday price discovery in the Chinese stock markets. We find that the volatility of order imbalances is the highest around the open. There is strong evidence that order imbalances in the early trading hours have significant predictive power to intraday price discovery. The intraday returns of the high buy-ratio quintiles are significantly higher than those of the low buy-ratio ones. The evidence indicates that the information incorporated in early trading signals the intraday price discovery, and the information around the open dominates that revealed over the rest of the trading day.

AbstractThis article empirically examines how political connections (PCs) affect a firm's media reaction after corporate fraud. Using data for Chinese listed companies from 2008 to 2021, we find that the media reports more positively for firms with PCs than for others that do not possess such advantages after the enforcement against fraud. The results are robust to a series of robustness checks and endogeneity corrections. When decomposing media reports, we find that PCs only facilitate positive media coverage but do not impede negative media coverage, which is more pronounced in state‐controlled media. This suggests that PCs protect firms' branding by facilitating positive media reports rather than withholding bad news. Moreover, we find this protective effect is more pronounced in firms with stronger PCs, weaker anti‐corruption regulation, lighter punishment for fraud, private ownership, and more donations. Further, the consequences analysis shows that this kind of protective effect significantly increases the probability of future fraud and stock price crashes. Our findings present a new perspective on the role of PCs and provide evidence for political bias in media coverage.

This paper examines opening and closing return patterns on the Chinese stock markets. We find that open-to-open returns are significantly more volatile than close-to-close returns. In addition, the correlation of the overnight return with the following daytime return is significantly negative, while the correlation of the daytime return with the following overnight return is strongly positive. The results show strong price continuation around the close and strong price reversal at the open, and the findings are not sensitive to trading volume. The findings are less likely to be caused by price limits. Our results are inconsistent with previous findings from the Tokyo Stock Exchange, yet similar to those from the New York Stock Exchange, albeit under a different market structure.