Promised Delivery Time and Capacity Games in Time-Based Competition

Abstract

We investigate firms' competitive behaviors in industries where customers are sensitive to both promised delivery time (PDT) and quality of service (QoS) measured by the on-time delivery rate. To study the competition in PDT at the marketing level, we construct an oligopoly game with an external QoS requirement. We show that there exists a unique Nash equilibrium, and the equilibrium QoS exhibits a switching surface structure with respect to capacities. To study the competition in capacity at the strategic level, we construct a two-stage game in which the firms compete in terms of their capacities in stage 1 and in terms of PDT in stage 2. We show the existence of two different types of pure strategy equilibria and characterize them. This study provides the following insights: an index of time-based competitive advantage (ITCA) and the first-mover advantage determine the positions of the firms in time-based competition; either the well-known prisoner's dilemma or off-equilibrium behaviors due to different preferences for equilibria (when multiple equilibria exist) may lead the firms to overinvest in capacity, but no one may gain a competitive advantage; a uniform improvement in internal efficiency (i.e., a uniform capacity cost reduction) may harm everyone; quality differentiation (i.e., going beyond the QoS benchmark) plays a dual role in time-based competition, either helping a firm with a larger ITCA to compete more effectively, or helping a firm possibly with a smaller ITCA to preempt competitors and protect its market advantage. This paper was accepted by Paul H. Zipkin, operations and supply chain management.time-based competition, consumer choice model, Nash equilibrium, switching surface, quality differentiation, capacity competition, marketing-operations interface

Toward a Chance Management View of Organizational Change

“…With the increasing uncertainty of the business environment, researchers have begun to pay more attention to studies of timing effects in organizational contexts. In addition, timing strategy has been increasingly regarded as an important source for firms to formulate a competitive advantage (Huy, 2001), as with time-based competition (Shang & Liu, 2011), justin-time production (Sakakibara, Flynn, Schroeder, & Morris, 1997) or first-mover advantage (Lieberman & Montgomery, 1998). As Orlikowski and Yates (2002) noted in their review of research on organizational time, most prior studies have taken an objective perspective toward time, assuming time to be objective and independent of human actions.…”

A dynamic pricing strategy for a 3PL provider with heterogeneous customers

“…So and Song (1998) and Ata and Olsen (2009) studied leadtime pricing with leadtime guarantees, but did not consider the heterogeneity of customer orders. Liu et al (2007) and Shang and Liu (2011) assume customers sensitivity in price and leadtime, but they also do not consider customers heterogeneity and the leadtime and price quotes are static regardless of the system congestion. Plambeck (2004), Zhang et al (2012) and Ata and Olsen (2013) studied the pricing for different leadtime options when the firm faces customers that are heterogeneous both in price sensitivity and leadtime sensitivity.…”

Pricing and promised delivery lead time decisions with a risk-averse agent

“…As a result, delivery lead time, in addition to price, has become a dominant factor in determining a firm's competitive advantage. That is, delivery lead time is not only becoming the order winner, but also the order qualifier (Shang and Liu 2011).…”

“…If a firm sets a short promised delivery lead time to capture more demand, fulfilling all the orders on time is harder given the increased customer demand, uncertainties in production and delivery processes, or other uncontrollable factors. This situation will lead to poor on-time delivery performance and higher tardiness cost, and thereby cause a firm to lose more customers and damage the firm's long-term competitive advantage in the future (Shang and Liu 2011). If a firm sets a long promised delivery lead time, the demands will decrease, which will then decrease the firm's market share and profit (Wu et al 2012).…”

“…Jha and Shanker (2009) proposed a model to find the optimal order quantity, lead time and the number of shipment from the vendor to the buyer in order to minimise the total expected cost of the integrated system. Shang and Liu (2011) took both promised delivery time and quality of service into consideration in an oligopoly market. Zhao, Stecke, and Prasad (2012) compared a single lead time and price quotation with a selection of lead times and prices to determine which and when is better for a firm.…”