Inflexible Capacity Research Articles

Competition under demand uncertainty: The roles of technology and capacity strategy

To uncover the secrets of creating competitive advantage for firms under demand uncertainty, we study the roles of technology level and capacity investment strategies. Specifically, we analyze the Nash equilibrium of two competing firms at different technology levels under two capacity investment strategies, namely flexible or inflexible. We examine both symmetrical competition where the two firms adopt a same capacity type (flexible or inflexible), and asymmetrical competition where the two firms invest different capacity types. We find that an advanced technology level incentivises capacity expansion regardless of the capacity strategy adopted. In addition, the technology-capacity relationship significantly depends on demand distribution when both firms adopt inflexible capacity investment, but is independent of demand distribution when both firms invest in flexible capacity. No overwhelming superiority is observed from either side when both firms adopt the same capacity investment, and firms always co-exist in a profitable market, despite significant differences in technology. However, overwhelming superiority emerges from one side when both firms have different capacity investments. A firm can squeeze out its competitor and capture the entire market by upgrading its technology. When the two firms adopt the same capacity strategy, each firm may increase or decrease its technology level and capacity volume proportionally in equilibrium, regardless of the competition scenarios. We further explore the endogenous capacity investment type and technology flexibility in competition. We show that the competition effect plays an important role when the flexible capacity cost is moderate.

Green flexible vs. inflexible capacity strategies for duopoly

This paper investigates green capacity strategies and production volume portfolio for two homogenous firms under emission constraint and demand uncertainty. Each firm utilizes either inflexible capacity or flexible capacity which can postpone production after demand is observed. Results indicate that as the green product becomes more advantaged, flexible capacity advantage weakens and firms prefer inflexible capacity. Firms choose different capacity types when capacity investment costs are close; otherwise, they adopt the cost-advantaged type. A prisoner’s dilemma arises when inflexible capacity is relatively cost-advantaged, which is mitigated by Nash negotiation.

Multi-item single-source ordering with detailed consideration of transportation capacities

We consider multi-item single-source ordering with detailed consideration of transportation capacities. Such problems are characteristic for companies which operate direct links as part of their supply chain to transport loads with heterogeneous physical dimensions and fluctuating demands. Given knowledge on transportation demands, companies can eliminate future transports by shifting the load to fill the inflexible capacity of prior transports. While reducing transportation costs, doing so will ceteris paribus imply inventory. The problem is to coordinate orders across multiple items such that transport costs are minimized at minimal increase in inventory. The approach is distinct from prior works in that it considers detailed loading restrictions. We therefore interpret the problem as a multi-period version of the container loading problem. A wall building approach is used and incorporated into a heuristic rolling horizon procedure. We test the proposed procedure on some random problems which resemble a real inbound case from the automotive industry. As compared to period-by-period planning and two benchmarks with aggregated capacity models from the literature and practice, cost savings are possible under a wide range of operating conditions and mostly independent of the shipping volume. The largest potential exists for mid- to long-distance transports. There is a relevant potential to improve short-distance transports as well, however, only if inventory cost rates are moderate.

Flexible capacity strategy in an asymmetric oligopoly market with competition and demand uncertainty

AbstractThis article studies flexible capacity strategy (FCS) under oligopoly competition with uncertain demand. Each firm utilizes either the FCS or inflexible capacity strategy (IFCS). Flexible firms can postpone their productions until observing the actual demand, whereas inflexible firms cannot. We formulate a new asymmetrical oligopoly model for the problem, and obtain capacity and production decisions of the firms at Nash equilibrium. It is interesting to verify that cross‐group competition determines the capacity allocation between the two groups of firms, while intergroup competition determines the market share within each group. Moreover, we show that the two strategies coexist among firms only when cost differentiation is medium. Counterintuitively, flexible firms benefit from increasing production cost when the inflexible competition intensity is sufficiently high. This is because of retreat of inflexible firms, flexibility effect, and the corresponding high price. We identify conditions under which FCS is superior than IFCS. We also demonstrate that flexible firms benefit from increasing demand uncertainty. However, when demand variance is not very large, flexible firms may be disadvantaged. We further investigate the effects of cross‐group and intergroup competition on individual performance of the firms. We show that as flexible competition intensity increases, inflexible firms are mainly affected by the cross‐group competition first and then by the intergroup competition, whereas flexible firms are mainly affected by the intergroup competition. Finally, we examine endogenous flexibility and identify its three drivers: cost parameters, cross‐group competition, and intergroup competition. © 2017 Wiley Periodicals, Inc. Naval Research Logistics 64: 117–138, 2017

CR2M—an approach for capacity control considering long-term effects on the value of a customer for the company

In the last years, customer centricity has turned out to be a promising paradigm for maximizing corporate value by increasing value contributions from customers. In this context, the discipline of revenue management provides plenty of methods to optimize (predominantly short-term) cash-inflows from customers. However, the paradigm of a value-oriented management requires the integration of perspectives from revenue management and customer relationship management: When controlling scarce, inflexible capacity, the effects of the acceptance or denial of a customer request on the value of a customer for the enterprise have to be considered. Hence, this paper proposes a model for a customer lifetime value-oriented capacity control by allocating scarce resources to products for different customer segments combining methods from both revenue management and customer relationship management—termed CR2M. The model presented in this paper at the same time allows a transparent calculation of opportunity costs caused by a short-term oriented control mechanism. In order to illustrate the applicability of the model, a company of the semiconductor industry serves as example.

Designing replenishment rules in a two-echelon supply chain with a flexible or an inflexible capacity strategy

We consider a two-echelon supply chain where a single retailer holds an inventory of finished goods to satisfy an i.i.d. customer demand, and a single manufacturer produces the retailer's replenishment orders on a make-to-order basis. The objective of this paper is to analyse the impact of the retailer's replenishment policy on total supply chain performance. We consider two strategies with regard to the production capacity. In a flexible capacity strategy, the manufacturer invests in excess capacity to guarantee constant lead times in order to keep inventories low. The amount of investment depends on the retailer's order pattern. In an inflexible capacity strategy, the capacity is limited and independent of the retailer's replenishment decision. This results in stochastic lead times, thereby inflating the retailer's inventory requirements. We treat the variability of the order rate of the retailer as the primary decision variable to minimise total supply chain costs. The objective is to find the value of the replenishment parameter β (parameter to tune the order variability) that minimises total supply chain costs in a flexible and inflexible capacity scenario.

Do humans have two systems to track beliefs and belief-like states?

The lack of consensus on how to characterize humans' capacity for belief reasoning has been brought into sharp focus by recent research. Children fail critical tests of belief reasoning before 3 to 4 years of age (H. Wellman, D. Cross, & J. Watson, 2001; H. Wimmer & J. Perner, 1983), yet infants apparently pass false-belief tasks at 13 or 15 months (K. H. Onishi & R. Baillargeon, 2005; L. Surian, S. Caldi, & D. Sperber, 2007). Nonhuman animals also fail critical tests of belief reasoning but can show very complex social behavior (e.g., J. Call & M. Tomasello, 2005). Fluent social interaction in adult humans implies efficient processing of beliefs, yet direct tests suggest that belief reasoning is cognitively demanding, even for adults (e.g., I. A. Apperly, D. Samson, & G. W. Humphreys, 2009). The authors interpret these findings by drawing an analogy with the domain of number cognition, where similarly contrasting results have been observed. They propose that the success of infants and nonhuman animals on some belief reasoning tasks may be best explained by a cognitively efficient but inflexible capacity for tracking belief-like states. In humans, this capacity persists in parallel with a later-developing, more flexible but more cognitively demanding theory-of-mind abilities.

Dynamic pricing for project-oriented production: A comparison to current pricing techniques

Previous research on dynamic pricing has concentrated primarily on small projects using inflexible capacity. In this paper, we discuss the differences between this work and dynamic pricing for project-oriented production (POP). POP is formally defined and limitations of current dynamic pricing and revenue management techniques for this industry are demonstrated through empirical results. A new heuristic that exploits the flexible capacity of POP industries is developed for such industries and computational results are presented for its performance over a range of dynamic pricing environments. We test the heuristic on a variety of job sizes and rates, and our numerical results indicate that the heuristic significantly outperforms other heuristics in the literature for jobs that fall into the POP category.

Delivery‐date and capacity management in a decentralized internal market

AbstractWe study competitive due‐date and capacity management between the marketing and engineering divisions within an engineer‐to‐order (ETO) firm. Marketing interacts directly with the customers and quotes due‐dates for their orders. Engineering is primarily concerned with the efficient utilization of resources and is willing to increase capacity if the cost is compensated. The two divisions share the responsibility for timely delivery of the jobs. We model the interaction between marketing and engineering as a Nash game and investigate the effect of internal competition on the equilibrium decisions. We observe that the internal competition not only degrades the firm's overall profitability but also the serviceability. Finally, we extend our analysis to multiple‐job settings that consider both flexible and inflexible capacity. © 2008 Wiley Periodicals, Inc. Naval Research Logistics, 2008