Production and Sales Planning in Capacitated New Product Introductions

How should a firm with limited capacity introduce a new product? Should it introduce the product as soon as possible or delay introduction to build up inventory? How do the product and market characteristics affect the firm's decisions? To answer such questions, we analyze new product introductions under capacity restrictions using a two‐period model with diffusion‐type demand. Combining marketing and operations management decisions in a stylized model, we optimize the production and sales plans of the firm for a single product. We identify four different introduction policies and show that when the holding cost is low and the capacity is low to moderate, a (partial) build‐up policy is indeed optimal if consumers are sensitive to delay. Under such a policy, the firm (partially) delays the introduction of its product and incurs short‐term backlog costs to manage its future demand and total costs more effectively. However, as either the holding cost or the capacity increases, or consumer sensitivity to delay decreases, the build‐up policy starts to lose its appeal, and instead, the firm prefers an immediate product introduction. We extend our analysis by studying the optimal capacity decision of the firm and show that capacity shortages may be intentional.     

Energy Performance Contracting in a Competitive Environment*

Energy Performance Contracting (EPC) is an important and effective energy conservation mechanism, under which an energy service company (ESCO) provides an energy‐saving service to its client and shares the resulting energy cost savings. Using a game‐theoretic model, we investigate the impacts of EPC on two competing manufacturers, of which one is more energy‐efficient in production than the other. The less energy‐efficient firm first proposes an energy‐saving sharing contract to the more energy‐efficient firm, who, if accepting the contract, acts as an ESCO that decides the energy‐saving target and helps realize it for the client. Then the firms engage in Cournot competition by producing/selling substitutable products. By solving the equilibrium solutions, we show that under an EPC project, the total production quantity of both firms increases (so the market price of the product decreases) with the ESCO producing less while its client producing more, which also leads to a higher consumer surplus. Meanwhile, both manufactures are better off under EPC and would obtain strictly higher profits when the service cost rate is high. Nevertheless, EPC may not result in a better environmental performance in that the total energy consumption of both firms may be higher under EPC, which happens when the market size is small and the ESCO has not much energy‐efficiency advantage over its client. We also study four extensions: When the energy saving service and production decisions are made separately, we find the more energy‐efficient firm is worse off when implementing EPC; when the energy‐saving sharing ratio is determined by the ESCO instead of the client, the ESCO extracts all the surplus derived from the EPC project while the total energy consumption of both firms is always reduced; when the energy‐saving sharing ratio is determined via Nash bargaining, the main insights from the base model remain valid; finally, when the client sets the target of overall cost reduction, it extracts all the surplus derived from the EPC project.     

Outsourcing Competition and Information Sharing with Asymmetrically Informed Suppliers

This paper studies an outsourcing problem where two service providers (suppliers) compete for the service contract from a client. The suppliers face uncertain cost for providing the service because they do not have perfect information about the client's type. The suppliers receive differential private signals about the client type and thus compete under asymmetric information. We first characterize the equilibrium of the supplier competition. Then we investigate two of the client's information sharing decisions. It is shown that less information asymmetry between the suppliers may dampen their competition. Therefore, the client does not necessarily have the incentive to reduce information asymmetry between the suppliers. We characterize the conditions under which leveling the informational ground is beneficial to the client. We also find that under the presence of information asymmetry (e.g., when the suppliers have different learning abilities), sharing more information with both suppliers may enhance the advantage of one supplier over the other and at the same time increase the upper bound of the suppliers' quotes in equilibrium. Consequently, the suppliers compete less aggressively and the client's payoff decreases in the amount of shared information. The findings from this study provide useful managerial implications on information management for outsourcing firms.     

How Costs and Heterogeneous Consumer Price Sensitivity Interact with Add‐On Pricing

Firms often cite cost savings as a reason why they charge separately for add‐ons. Firms also often face situations where consumers' price sensitivity is correlated with their valuation of add‐ons. While cost savings may directly translate into profit gains in some scenarios, this study examines the strategic implications of add‐on pricing and is the first to suggest that cost savings from add‐on pricing may in fact result in profit loss for firms when consumers are heterogeneous in price sensitivity. This is because add‐on pricing can trigger a revenue loss that exceeds any cost savings, thus leading to a negative net profit change for competing firms. Even if firms have the capability to pre‐commit to not adopting add‐on pricing, we show that competing firms can be locked in a prisoner's dilemma where all choose to adopt add‐on pricing and lose profits (as compared to none adopting add‐on pricing). We further show the possibility that the greater the cost of providing the add‐on (and the greater the cost savings generated from add‐on pricing), the worse this profit loss gets.     

The Impact of Outsourced Manufacturing on Timing of Entry in Uncertain Markets

Several firms are interested in manufacturing and selling new products based on a new process technology. Before manufacturing can begin, either these Original Equipment Manufacturers (OEMs), or a Contract Manufacturer (CM) needs to adopt the process technology, i. e., make a capacity investment in it. Due to market uncertainty, the timing of capacity investment is crucial. In such a setting, we investigate how the timing of process adoption, an important determinant of time‐to‐market, is impacted by the make/buy decision. We first characterize the optimal time for process adoption and show that this delay depends on competitive intensity, cost structure and the rate of forecast improvement. Due to differing cost structures, incentives and risks, an OEM and a CM may invest in a new process technology at different times. We show that while there are conditions where outsourced manufacturing can be advantageous for the OEM from a time‐to‐market perspective, there are also cases where the OEM would be disadvantaged. In these cases, the OEM can accelerate process adoption by risk sharing through joint investment. Finally, the right choice of CM is extremely important for an OEM that faces a short time window for product introduction: An efficient CM not only provides low costs but also rapid access to new process technologies, and therefore higher revenues.     

INVENTORY RATIONING AND SHIPMENT FLEXIBILITY ALTERNATIVES FOR DIRECT MARKET FIRMS

This paper investigates inventory‐rationing policies of interest to firms operating in a direct market channel. We model a single product with two demand classes, where one class requests a lower order fulfillment lead time but pays a higher price. Demand for each class follows a Poisson process. Inventory is fed by a production system with exponentially distributed build times. We study rationing policies in which the firm either blocks or backlogs orders for the lower priority customers when inventory drops below a certain level. We compare the performance of these rationing policies with a pure first‐come, first‐serve policy under various scenarios for customer response to delay: lost sales, backlog, and a combination of lost sales and backlog.     

Social Optimal Location of Facilities with Fixed Servers,Stochastic Demand,and Congestion

We consider two capacity choice scenarios for the optimal location of facilities with fixed servers, stochastic demand, and congestion. Motivating applications include virtual call centers, consisting of geographically dispersed centers, walk‐in health clinics, motor vehicle inspection stations, automobile emissions testing stations, and internal service systems. The choice of locations for such facilities influences both the travel cost and waiting times of users. In contrast to most previous research, we explicitly embed both customer travel/connection and delay costs in the objective function and solve the location–allocation problem and choose facility capacities simultaneously. The choice of capacity for a facility that is viewed as a queueing system with Poisson arrivals and exponential service times could mean choosing a service rate for the servers (Scenario 1) or choosing the number of servers (Scenario 2). We express the optimal service rate in closed form in Scenario 1 and the (asymptotically) optimal number of servers in closed form in Scenario 2. This allows us to eliminate both the number of servers and the service rates from the optimization problems, leading to tractable mixed‐integer nonlinear programs. Our computational results show that both problems can be solved efficiently using a Lagrangian relaxation optimization procedure.     

Investing in a Shared Supplier in a Competitive Market: Stochastic Capacity Case

When firms invest in a shared supplier, one key concern is whether the invested capacity will be used for a competitor. In practice, this concern is addressed by restricting the use of the capacity. We consider what happens when two competing firms invest in a shared supplier. We consider two scenarios that differ in how capacity is used: exclusive capacity and first‐priority capacity. We model firms' investment and production decisions, and analyze the equilibrium outcomes in terms of the number of investing firms and capacity levels for each scenario; realized capacity is a stochastic function of investment levels. We also identify conditions under which the spillover effect occurs, where one firm taps into the other firm's invested capacity. Although the spillover supposedly intensifies competition, it actually discourages firms' investment. We also characterize the firms' and supplier's preference about the capacity type. While the non‐investing firm always prefers spillovers from the first‐priority capacity, the investing firm does not always want to shut off the other firm's access to its leftover capacity, especially when allowing spillover induces the other firm not to invest. The supplier's preference depends on the trade‐off between over‐investment and flexibility.     

Technology Choice and Capacity Portfolios under Emissions Regulation

We study the impact of emissions tax and emissions cap‐and‐trade regulation on a firm's technology choice and capacity decisions. We show that emissions price uncertainty under cap‐and‐trade results in greater expected profit than a constant emissions price under an emissions tax, which contradicts popular arguments that the greater uncertainty under cap‐and‐trade will erode value. We further show that two operational drivers underlie this result: (i) the firm's option not to operate, which effectively right‐censors the uncertain emissions price; and (ii) dispatch flexibility, which is the firm's ability to first deploy its most profitable capacity given the realized emissions price. In addition to these managerial insights, we also explore policy implications: the effect of emissions price level, and the effect of investment and production subsidies. Through an illustrative example, we show that production subsidies of higher investment and production cost technologies (such as carbon capture and storage technologies) have no effect on the firm's optimal total capacity when firms own a portfolio of both clean and dirty technologies, but that investment subsidies of these technologies increase the firm's total capacity, conditionally increasing expected emissions. A subsidy of a lower production cost technology, on the other hand, has no effect on the firm's optimal total capacity in multi‐technology portfolios, regardless of whether the subsidy is a production or investment subsidy.     

Equilibrium Joining Strategies and Optimal Control of a Make‐to‐Stock Queue

We consider a make‐to‐stock, finite‐capacity production system with setup cost and delay‐sensitive customers. To balance the setup and inventory related costs, the production manager adopts a two‐critical‐number control policy, where the production starts when the number of waiting customers reaches a certain level and shuts down when a certain quantity of inventory has accumulated. Once the production is set up, the unit production time follows an exponential distribution. Potential customers arrive according to a Poisson process. Customers are strategic, i.e., they make decisions on whether to stay for the product or to leave without purchase based on their utility values, which depend on the production manager's control decisions. We formulate the problem as a Stackelberg game between the production manager and the customers, where the former is the game leader. We first derive the equilibrium customer purchasing strategy and system performance. We then formulate the expected cost rate function for the production system and present a search algorithm for obtaining the optimal values of the two control variables. We further analyze the characteristics of the optimal solution numerically and compare them with the situation where the customers are non‐strategic.     

Collusion With Persistent Cost Shocks

We consider a dynamic Bertrand game in which prices are publicly observed and each firm receives a privately observed cost shock in each period. Although cost shocks are independent across firms, within a firm costs follow a first‐order Markov process. We analyze the set of collusive equilibria available to firms, emphasizing the best collusive scheme for the firms at the start of the game. In general, there is a trade‐off between productive efficiency, whereby the low‐cost firm serves the market in a given period, and high prices. We show that when costs are perfectly correlated over time within a firm, if the distribution of costs is log‐concave and firms are sufficiently patient, then the optimal collusive scheme entails price rigidity: firms set the same price and share the market equally, regardless of their respective costs. When serial correlation of costs is imperfect, partial productive efficiency is optimal. For the case of two cost types, first‐best collusion is possible if the firms are patient relative to the persistence of cost shocks, but not otherwise. We present numerical examples of first‐best collusive schemes.     

Pricing in a Transportation Station with Strategic Customers

We consider a transportation station, where customers arrive according to a Poisson process, observe the delay information and the fee imposed by the administrator and decide whether to use the facility or not. A transportation facility visits the station according to a renewal process and serves all present customers at each visit. We assume that every customer maximizes her individual expected utility and the administrator is a profit maximizer. We model this situation as a two‐stage game among the customers and the administrator, where customer strategies depend on the level of delay information provided by the administrator. We consider three cases distinguished by the level of delay information: observable (the exact waiting time is announced), unobservable (no information is provided) and partially observable (the number of waiting customers is announced). In each case, we explore how the customer reward for service, the unit waiting cost, and the intervisit time distribution parameters affect the customer behavior and the fee imposed by the administrator. We then compare the three cases and show that the customers almost always prefer to know their exact waiting times whereas the administrator prefers to provide either no information or the exact waiting time depending on system parameters.     

The Timing of Capacity Investment with Lead Times: When Do Firms Act in Unison?

We study competitive capacity investment for the emergence of a new market. Firms may invest either in capacity leading demand or in capacity lagging demand at different costs. We show how the lead time and other operational factors including volume flexibility, existing capacity, and demand uncertainty impact equilibrium outcomes. Our results indicate that a type of bandwagon behavior is the most likely equilibrium outcome: if both firms are going to invest, then they are most likely to act in unison. Contrary to much received wisdom, we show that leader–follower behavior is very uncommon in equilibrium where firms do not have volume flexibility, and will not occur at all if lead times are sufficiently short. On the other hand, if there is volume flexibility in production, then the likelihood of this sequential investment behavior increases. Our findings underscore the importance of operational characteristics in determining the competitive dynamics of capacity investment timing.     

Real‐Time Revision of Order Quantities with Capacity Constraint: A Single Period Model

Manufacturing firms would like to maximize customer satisfaction by providing them with what they need when they need it. This, however, would mean continual variations in production quantities, and component orders from suppliers. A flexible manufacturing system can help alleviate costs related to modification of production quantities. The capacity of such a system, however, has to be limited because of high investment cost. Further, unless there is a long‐term relationship, suppliers may levy a high surcharge for last minute changes in order size. We model a hybrid control policy comprising an advance (pre‐production) order size agreed upon with suppliers, and a provision for real‐time order revision at a given rate of surcharge. We show that a rank‐order of products can be used for real‐time revisions, and that a strong buyer‐supplier relationship that keeps these surcharges low can actually help increase profits for both parties. We study issues such as compatibility between JIT and flexibility, and the impact of market conditions on overall profitability.     

Demand Forecast Sharing in Supply Chains

This paper examines the incentives of a manufacturer and a retailer to share their demand forecasts. The demand at the retailer is a linearly decreasing function of price. The manufacturer sets the wholesale price first, and the retailer sets the retail price after observing the wholesale price. Both players set their prices based on their forecasts of demand. In the make‐to‐order scenario, the manufacturer sets the production quantity after observing the actual demand; in the make‐to‐stock scenario, the manufacturer sets the production quantity before the demand is realized. In the make‐to‐order scenario, we show that sharing the forecast unconditionally by the retailer with the manufacturer benefits the manufacturer but hurts the retailer. We also demonstrate that a side payment contract cannot induce Pareto‐optimal information sharing equilibrium, but a discount based wholesale price contract can. The social welfare as well as consumer surplus is higher under the discount contract, compared with under no information sharing. In the make‐to‐stock scenario, the manufacturer realizes additional benefits in the form of savings in inventory holding and shortage costs when forecasts are shared. If the savings from inventory holding and shortage costs because of information sharing are sufficiently high, then a side payment contract that induces Pareto‐optimal information sharing is feasible in the make‐to‐stock scenario. We also provide additional managerial insights with the help of a computational study.     

The Use of Flexible Manufacturing Capacity in Pharmaceutical Product Introductions*

This work considers the value of the flexibility offered by production facilities that can easily be configured to produce new products. We focus on technical uncertainty as the driver of this value, while prior works focused only on demand uncertainty. Specifically, we evaluate the use of process flexibility in the context of risky new product development in the pharmaceutical industry. Flexibility has value in this setting due to the time required to build dedicated capacity, the finite duration of patent protection, and the probability that the new product will not reach the market due to technical or regulatory reasons. Having flexible capacity generates real options, which enables firms to delay the decision about constructing product‐specific capacity until the technical uncertainty is resolved. In addition, initiating production in a flexible facility can enable the firm to optimize production processes in dedicated facilities. The stochastic dynamic optimization problem is formulated to analyze the optimal capacity and allocation decisions for a flexible facility, using data from existing literature. A solution to this problem is obtained using linear programming. The result of this analysis shows both the value of flexible capacity and the optimal capacity allocation. Due to the substantial costs involved with flexibility in this context, the optimal level of flexible capacity is relatively small, suggesting products be produced for only short periods before initiating construction of dedicated facilities.     

Capacity Investment and Product Line Decisions of a Multiproduct Leader and a Focus Strategy Entrant

In this article, I investigate the capacity investment cost conditions where a multiproduct market leader may respond to a focus strategy entrant by using different strategies such as changing the product mix, production volumes, quality levels, and/or by investing in more capacity. The products offered in the market are quality differentiated and customers are heterogeneous in their willingness to pay for quality. The capacity investment costs of the two firms (i.e., the leader and the entrant) may also be different. The classical Stackelberg model predicts that an incumbent does not change its position in response to entry. However, when heterogeneous customer base, product differentiation, and capacity costs are taken into consideration, I find that the leader with a low capacity cost may choose to expand its product line and increase its production. The leader with low capacity cost may introduce a product that it was holding back when the entrant has to bear the high‐capacity cost and cannibalization threat is relatively small. Nevertheless, the extent of production volume strategies reduces as the capacity cost increases for the leader. I also find that when the leader has the power to set the industry standards by deciding the quality levels, as a response to a high‐quality focused entrant, the leader increases both levels of quality and production of the low‐quality product. Moreover, when the capacity investment cost is high for both the entrant and the leader, I find that market prices may increase with entry.     

Optimal Workforce Mix in Service Systems with Two Types of Customers

We consider a service system with two types of customers. In such an environment, the servers can either be specialists (or dedicated) who serve a specific customer type, or generalists (or flexible) who serve either type of customers. Cross‐trained workers are more flexible and help reduce system delay, but also contribute to increased service costs and reduced service efficiency. Our objective is to provide insights into the choice of an optimal workforce mix of flexible and dedicated servers. We assume Poisson arrivals and exponential service times, and use matrix‐analytic methods to investigate the impact of various system parameters such as the number of servers, server utilization, and server efficiency on the choice of server mix. We develop guidelines for managers that would help them to decide whether they should be either at one of the extremes, i.e., total flexibility or total specialization, or some combination. If it is the latter, we offer an analytical tool to optimize the server mix.     

Capacity rationing in rental systems with two customer classes and batch arrivals

Service differentiation is an emerging method to improve profit and to better serve high-priority customers. Such an approach has recently been introduced by one of Europe's leading rail cargo companies. Under this approach, customers can choose between classic and premium services. Premium service is priced above classic service and premium customers receive a service guarantee which classic customers do not receive. The company has to decide under which conditions it should ration its fleet capacity to classic customers in order to increase service of premium customers. We model such a situation as a batch-arrival queuing loss system. We describe the model, solve it optimally, and derive quantities of interest such as service probabilities. We further analyze it by performing numerical experiments based on the data from the company that motivated our research. We show that the potential of capacity rationing can be substantial in situations like the one we analyzed. We also derive conditions under which rationing is especially beneficial, such as under high unit fleet holding costs or in the presence of batch arrivals compared to single arrivals.     

Do third-party certifications work in a weak institutional environment?

We investigate whether third-party certification may negatively affect firm performance in a weak institutional environment. Firms in weak institutional environments often obtain certifications to appeal to foreign audiences. But these audiences hold negative evaluations of firms from weak institutional settings, judging them as being of poor quality due to their geographic origin. We argue that these negative evaluations greatly diminish the informational value of certifications, such that the costs of certification exceed revenue gains causing performance decline. We also examine whether industry-level evaluations can challenge country-level ones. Focusing on industry legitimation, we argue that this increases the salience of the industry over the institutional context. Audiences see the industry first, not the weak institutional environment. Thus, third-party certifications can become a basis for differentiating among firms and thereby help improve firm performance as industry legitimation increases. We use the first decade post-liberalization of the Indian software industry, 1992–2003, to test our hypotheses. Based on a sample of 792 firms, we find support for our arguments suggesting that in weak institutional environments certification alone is not enough for firms targeting foreign audiences to overcome the stigma of their origins; it needs to be accompanied by positive industry-level processes.