A significant part of supply chain management research has been devoted to understanding the role of information sharing in achieving the best performance. The modern technology, especially the internet, is creating new channels that facilitate interactions and communications between different parties in supply chains. Motivated by various companies that share information with their buyer and suppliers, we study the value of information sharing in supply chains.;The dissertation consists of three self-contained papers. Motivated by our interaction with a leading consumer packaged goods company in the beverage industry, in Chapter 1, we provide an empirical and theoretical assessment of the value of information sharing in a two-stage supply chain. The value of downstream sales information to the upstream firm stems from improving upstream order fulfillment forecast accuracy. Such an improvement can lead to lower safety stock and better service. Based on the data collected from the CPG company, we empirically show that, if the company includes the downstream sales data to forecast orders, the improvement in the mean squared forecast error ranges from 7.1% to 81.1% across all studied products. Theoretical models in the literature, however, suggest that the value of information sharing should be zero for over half of our studied products. To reconcile the gap between the literature and the empirical observations, we develop a new theoretical model. While the literature assumes that the decision maker strictly adheres to a given inventory policy, our model allows him to deviate, accounting for private information held by the decision maker, yet unobservable to the econometrician. This turns out to reconcile our empirical findings with the literature. These "decision deviations" lead to information losses in the order process, resulting in a strictly positive value of downstream information sharing. Furthermore, we empirically quantify and show the significance of the value of knowing the downstream replenishment policy.;Sellers could use operations information disclosure to affect consumer behavior and benefit the sellers. Chapter 2 studies the inventory information sharing behavior of a firm that sells vertically differentiated products. The seller credibly and discretionarily discloses inventory information to customers either fully or partially, i.e., disclosing only the aggregate inventory level. In the disclosure literature, discretion usually leads to the unraveling results: full disclosure is the equilibrium even when it is not optimal for the seller. Instead, this paper shows that aggregate inventory disclosure can sustain as an ex post equilibrium, which is also ex ante optimal for the seller. We explore when and why it is optimal to do so.;Chapter 3 studies an inventory replenishment policy that attempts to keep a constant amount of days of inventory, which we refer to as ConDOI policy. This practice is widely used in practice, including the CPG company that we worked with and from which we receive the data set in our first paper. This policy is easy to implement and free from heavy computational burdens, because it requires only one parameter (targeted days of inventory) to manage inventory. While its performance is equivalent to that of a constant base stock policy under stationary demand, its most attractive feature is the adaptability to a non-stationary (e.g. seasonal) environment. In this paper, we consider a dynamic forecast-inventory model with forecast updates under the MMFE demand.;Customers participate in the discussions of companies' products and services. Customers' voice is embedded in the social media content. Chapter 4 empirically explores how much social media information helps improve sales forecasting. Using (1) daily sales data from an online apparel startup company that primarily advertises on Facebook, and (2) publicly available Facebook posts and the users' comments and likes data, we find a statistically significant improvement in sales forecast accuracy. We analyze the underlying mechanism---the endorsement effect and the attention effect. We show that sales from new customers are driven by the endorsement effect and sales from repeated customers are driven by the attention effect. Since new customers have never purchased the product before, they are less familiar with the products and thus have difficulties evaluating the quality of products. Attention might not be enough to drive sales. A purchasing decision of a new customer might rely on the endorsement from established social relationships. On the other hand, repeated customers who already have purchasing experience are less likely to learn the product quality from others. A reminder of the brand's promotions or simply the brand's name might lead to a potential purchase from repeated customers. (Abstract shortened by UMI.).
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