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Streaming media companies have changed how contents are consumed, produced, and delivered. This research develops a theoretical model on optimal content policies for streaming media companies in order to maximize customer engagement. We have the following interesting findings. First, in contrast to the results in prior literature that firms produce just enough products without overlapping product coverage intervals, we show that overlapping coverage intervals and placing products closer can be a better policy for engagement-based firms. Second, engagement-based model produces more contents when the value of the contents is large to the customers or the profit margin in selling content is less than a certain threshold. Third, on learning a general customers’ distribution, the media firm will always overlap product coverage intervals and place programs closer when the distribution density is larger. Additionally, in facing the tradeoffs of content quality and quantity, the firm should use a higher-quality and low-variety policy for high density clusters but a lower-quality and high-variety policy for low density clusters. Furthermore, when customers consume multiple shows in a period, a better policy is to film TV shows or series with multiple episodes rather than individual movies. Our research contributes to the literature on digital media, and the results provide interesting and insightful implications for streaming companies.

We study a dual channel supply chain in which a manufacturer sells to a retailer as well as to consumers directly. Consumers choose the purchase channel based on price and service qualities. The manufacturer decides the price of the direct channel and the retailer decides both price and order quantity. We develop conditions under which the manufacturer and the retailer share the market in equilibrium. We show that the difference in marginal costs of the two channels plays an important role in determining the existence of dual channels in equilibrium. We also show that demand variability has a major influence on the equilibrium prices and on the manufacturer’s motivation for opening a direct channel. In the case that the manufacturer and the retailer coordinate and follow a centralized decision maker, we show that adding a direct channel will increase the overall profit. Our numerical results show that an increase in retailer’s service quality may increase the manufacturer’s profit in dual channel and a larger range of consumer service sensitivity may benefit both parties in the dual channel. Our results suggest that the manufacturer is likely to be better off in the dual channel than in the single channel when the retailer’s marginal cost is high and the wholesale price, consumer valuation and the demand variability are low.

We investigate the value of pooling capacity in supply chains that serve product demands of different variabilities. We build and analyze models that integrate production queuing models with base stock inventory systems serving demands with different inter-arrival time distributions. The first model combines hyperexponential and exponential demand inter-arrival time distributions. Exact analysis of the model allows us to develop insights into the impact of the difference in demand variabilities on the value of pooling capacity. Simulation experiments allow us to validate these insights for more general settings. We then find one special case that combines exponential and deterministic demand arrivals with deterministic service, where pooling capacity results in increasing the total cost.