Knowledge that Transforms

We use a real‐options approach to analyze investments in process improvement. We develop a simple, stochastic model of a firm making investment decisions in process improvement. Our analysis offers several interesting insights into investments in process improvement. First, early investment in process improvement results in valuable knowledge, which helps increase the value of the option to invest in process improvement in future periods. This may motivate a firm to invest in process improvements as early as possible. Second, it may be optimal for a firm to stop investing when such investments do not create enough value in the later stages of the investment horizon. Third, although one would expect the state of a firm's process relative to that of other firms to impact a firm's decision to invest in process improvement, this study finds that the impetus is conditional and identifies these conditions. Finally, in such an environment, the delay of investment in process improvement incurs an opportunity cost for a firm, and we show that the traditional net present value rule must incorporate this opportunity cost and the knowledge‐induced change in future option values to lead to a correct investment decision.

Should service capacities (such as agent groups in call centers) be pooled or not? This paper will show that there is no single answer. For the simple but generic situation of two (strictly pooled or unpooled) server groups, it will provide (1) insights and approximate formulae, (2) numerical support, and (3) general conclusions for the waiting‐time effect of pooling. For a single call type, this effect is clearly positive, as represented by a pooling factor. With multiple job types, however, the effect is determined by both a pooling and a mix factor. Due to the mix factor, this effect might even be negative. In this case, it is also numerically illustrated that an improvement of both the unpooled and the strictly pooled scenario can be achieved by simple overflow or threshold scenarios. The results are of both practical and theoretical interest: practical for awareness of this negative effect, the numerical orders, and practical scenarios in call centers, and theoretical for further research in more complex situations.

The process of introducing new and phasing out old products is called product rollover. This paper considers a periodic‐review inventory system consisting of a manufacturer and a retailer, where the manufacturer introduces new and improved products over an infinite planning horizon using the solo‐roll strategy. We consider two scenarios: (1) the manufacturer does not share the upstream information about new‐product introduction with the retailer and (2) the manufacturer shares the information. For each scenario, we first derive the decentralized ordering policy and the system‐optimal ordering policy with given cost parameters. We then devise an optimal supply chain contract that coordinates the inventory system. We demonstrate that when the inventory system is coordinated, information sharing improves the performance of both supply chain entities. However, this may not be true if the inventory system is not coordinated. We also show that under the optimal contract, the manufacturer has no incentive to mislead the retailer about new‐product information in the information‐sharing model. When demand variability increases, information sharing adds more benefits to the coordinated supply chain. Our research provides insights about coordinating product, financial, and information flows in supply chains with product rollover.

We model strategic behavior of two types of suppliers in B2B spot markets: a supplier that has forward contracts and uses the spot market only for inventory liquidation, and a supplier that uses the spot market as its sole selling channel. We find that when the spot market demand is small, the supplier that has forward contracts has a higher incentive to invest in expanding the spot market. When the spot market demand exceeds a threshold size, this situation is reversed, and the supplier with no contracts benefits more from making the spot market more prevalent. We show that a supplier with forward contracts benefits from the existence of the spot market more than a supplier with no contracts and that this result holds with both negative and positive correlation between spot market demand and contracted demand. We find that suppliers producing only for the spot market gain from working in industries where contracted demand and spot market demand are positively correlated, whereas suppliers that have forward contracts benefit from working in industries with a negative correlation between demands, since it allows them to better manage risk. In addition, both total industry supply and spot market supply are higher in industries where demands are negatively correlated.

A significant portion of the services industry is focused on providing services (medical, legal, financial, personal, and travel) to individuals. However, studies have shown that a less visible but rapidly growing segment of the service sector comprises firms that provide business functions to other businesses. The sector covers tasks such as payroll processing, procurement, and information systems management, as well as business consulting, technical support, call center operations, and software development. Firms may choose to purchase, rather than perform, these business functions to reduce costs, to mitigate risk, or simply to focus on their processes that provide marketplace differentiation. Transferring a business function from within a firm to an outside supplier is often called “outsourcing”; when the supplier provides the service from a lower‐cost country, it is called “offshoring.” The risks and benefits of outsourcing to the firm purchasing a business service have been studied in some detail by both academics and consultants. In this paper, we outline revenue management issues faced by business service providers and describe some new opportunities for the use of analytic methods in the service science sector.

Motivated by the proliferation of multifunction products, we investigate product portfolio decisions of a single firm by analyzing the impact of three major factors. First, because multifunction products provide complete or partial functionalities of single‐function products, we incorporate substitution or cannibalization effects between the potential products. Second, we explicitly model the variable costs of manufacturing the single‐function and multifunction products. Third, we examine the firm's pricing decisions because of their impact on the degree of cannibalization between the multifunction product and one or more single‐function products. Using an economic model, we first characterize the firm's optimal product portfolio (through a quantity‐based decision), which in turn determines the market equilibrium prices for each product in its portfolio. Some of the unique insights stemming from our analysis are: (a) the optimal product portfolio choice is driven primarily by maximum profit margins for the single‐function products weighted by the demand substitution effects; and (b) from a product design perspective, the complete functionality of the base single‐function product is always included in the optimal product offering, but this is not necessarily the case with the complete functionality of the nonbase single‐function product.

Multiple‐skill call centers propagate rapidly with the development of telecommunications. An abundance of literature has already been published on call centers. Here, we want to focus on centers that would typically occur in business‐to‐business environments; these are call centers that handle many types of calls but where the arrival rate for each type is low. To find an optimal configuration, the integrality of the decision variables is a much more important issue than for larger call centers. The present paper proposes an approach that uses elements of combinatorial optimization to find optimal configurations. We develop an approximation method for the evaluation of the service performance. Next, we search for the minimum‐cost configuration subject to service‐level constraints using a branch‐and‐bound algorithm. What is at stake is to find the right balance between gains resulting from the economies of scale of pooling and the higher cost or cross‐trained agents. The article shows that in most cases this method significantly decreases the staffing cost compared with configurations with only cross‐trained or dedicated operators.

The celebrated model of Gallego and van Ryzin is specialized to the case of constant elasticity of demand. A closed form is developed, which has an even simpler form than that arising with exponential demand and which possesses an excellent approximation. In this environment, monopoly is efficient, which means that all the behavior usually attributed to monopoly pricing is actually a consequence of efficient pricing and would arise even in a perfectly competitive environment. If the initial supply is not too large, consumers have no incentive to delay their purchases to get a lower price at the average inventory prevailing at any time.

It is well known that maximizing revenue from a fixed stock of perishable goods may require discounting prices rather than allowing unsold inventory to perish. This behavior is seen in industries ranging from fashion retail to tour packages and baked goods. A number of authors have addressed the markdown management problem in which a seller seeks to determine the optimal sequence of discounts to maximize the revenue from a fixed stock of perishable goods. However, merchants who consistently use markdown policies risk training customers to “wait for the sale.” We investigate models in which the decision to sell inventory at a discount will change the future expectations of customers and hence their buying behavior. We show that, in equilibrium, a single‐price policy is optimal if all consumers are strategic and demand is known to the seller. Relaxing any of these conditions can lead to a situation in which a two‐price markdown policy is optimal. We show using numerical simulation that if customers update their expectations of availability over time, then optimal sales limit policies can evolve in a complex fashion.