Radio frequency identification (RFID) technology has been used to collect information for use in information systems that support knowledge-based business decisions. Most applications involve using the technology for automatic identification and tracking within facilities and supply chains....

Radio frequency identification (RFID) technology has been used to collect information for use in information systems that support knowledge-based business decisions. Most applications involve using the technology for automatic identification and tracking within facilities and supply chains....

In this paper, we study a supply chain comprising one manufacturer and one retailer. Customers can make purchases either from the retailer or directly from the manufacturer via an e-tail channel. From the manufacturer's perspective of managing the two channels, we study three different inventory...

This research first conceptualizes, develops, and validates four constructs for studying RFID in health care, including Drivers (Internal and External), Implementation Level (Clinical Focus and Administrative Focus), Barriers (Cost Issues, Lack of Understanding, Technical Issues, and Privacy and...

In this paper, we consider an inventory–routing problem (IRP) in a large petroleum and petrochemical enterprise group. Compared to many other IRPs, the problem in this paper includes some special aspects due to the operational constraints, such as hours-of-service regulations of the company...

This paper considers the maximum likelihood estimation of the panel data models with interactive effects. Motivated in economics and other social sciences, a notable feature of the model is that the explanatory variables are correlated with the unobserved effects. The usual within-group...

The factor-augmented vector autoregressive (FAVAR) model, first proposed by Bernanke, Bovin, and Eliasz (2005, QJE), is now widely used in macroeconomics and finance. In this model, observable and unobservable factors jointly follow a vector autoregressive process, which further drives the...

An approximate factor model of high dimension has two key features. First, the idiosyncratic errors are correlated and heteroskedastic over both the cross-section and time dimensions; the correlations and heteroskedasticities are of unknown forms. Second, the number of variables is comparable or...

Spatial effects and common-shocks effects are of increasing empirical importance. Each type of effect has been analyzed separately in a growing literature. This paper considers a joint modeling of both types. Joint modeling allows one to determine whether one or both of these effects are...