Demand chain management in the container shipping service industry

As the global service sector continues to grow, service science has evolved as an important academic discipline. Service science is a new interdisciplinary research area that emphasizes quality and productivity improvements in service management (Spohrer and Maglio, 2008). Supply chain management (SCM) is an approach to satisfy customer needs for products and services by integrating the business activities of firms across their entire value chains (Gunasekaran et al., 2008, Wong et al., 2009). In recent years, demand chain management (DCM) has received similar attention as SCM with a focus on strategy development (Francis et al., 2008). DCM is considered broader in scope than SCM because the former emphasizes understanding customer demand, as well as improving organizational ability in product and service development to better meet market needs (Canever et al., 2008). Despite the potential of DCM as a potent strategic management approach, there are still many unanswered questions about its application in practice, particularly in a specific service industry such as shipping (Frohlich and Westbrook, 2002). This omission in the literature is undesirable in view of the fact that container shipping service, which facilitates economic exchange and so international trade, is an important contributor to global economic development. The different shipping-related variables that determine the service capacity of container shipping service providers can affect global economic development. Considering the importance of container shipping as a service science discipline, we empirically develop and test in this paper a container shipping model built on the DCM paradigm.

Container shipping service is a key enabler of international trade and global economic development (Lun et al., 2009, Lun et al., 2011). When demand for shipping capacity is uncertain and significant lead times are required for expanding service capacity, managers of shipping firms need to carefully plan and decide on their firms’ capacity (Lun and Browne, 2009). However, postponing the expansion decision increases the risk of capacity shortage when shipping demand is expected to grow (Ryan, 2004). Such issues of service capacity management have been widely reported in the SCM and operations management literature. For instance, Nickell (1977) establishes a model with uncertain timings of future changes in shipping demand. Smith (1979) develops an algorithm for solving the problem with deterministic exponential demand growth and discrete facilities. Maglaras and Zeevi (2003) examine pricing and capacity sizing for systems with shared resources. Wang et al. (2007) study capacity decisions and supply price games with the flexibility of backward integration. While these service capacity management studies are useful for solving well-structured problems using such approaches as mathematical modeling and optimization techniques, empirical studies that provide managerial insights on issues related to service capacity and pricing in the container shipping industry from the DCM perspective are seriously lacking (Scudder and Hill, 1998).

According to Maglio et al. (2006), service science aims at explaining the origins and growth of service systems, and solving fundamental problems such as how to invest optimally to improve service productivity. Service provision is an economic activity where the buyer does not obtain exclusive ownership of the thing being purchased. With the development of global trade, service depends on customer participation and input through providing information via organizational value chains (Sampson and Froehle, 2006). Maglio and Spohrer (2008) define service systems as “dynamic value co-creation configuration of resources”. Service science is the study of service systems with an aim to “categorize and explain the many types of service systems that exist as well as how service systems interact and evolve to co-create value”. Providing container shipping service means taking an interdisciplinary effort that incorporates the determination of price and shipping service levels to match market demand. In container shipping, the demand for shipping service is derived from trade. Shipping lines provide service to customers by carrying cargoes from ports of loading to ports of discharge. If shippers need more shipping service, price will rise. To meet higher demand, ship owners need to order new ships from ship builders in the new building vessel market. Ship owners can also adjust their shipping capacity by buying and selling ships in the second-hand market. This service system illustrates (1) how customers and service providers must interact to establish a unique service system and (2) how organizations come together to create value across the system (Maglio and Spohrer, 2008). Service science is useful for categorizing and explaining the service systems that exist and how they interact. Another goal of service science is to apply scientific understanding to advance the ability to design, improve, and scale service systems for such business purposes as efficiency, effectiveness, and sustainability enhancements.

This study aims at developing an empirical model for examining the container transport service system, which is a key element of the transport sector. Specifically, this study develops and tests a container shipping service model of the factors that determine the capacity of container transport service. We begin with the DCM paradigm that puts an “emphasis on the importance of the marketplace and designing the chain to satisfy the needs” (Heikkila, 2002). In this research we adopt the demand for container shipping as the starting point for studying the business activities of the container shipping industry on the basis of DCM. We identify the factors that affect the total service capacity in container shipping and develop a container shipping service model to explain the relationships among the factors and assess their effects on the service capacity of the container shipping industry. Using path analysis of the structural equation modeling technique, we test the container shipping model comprising the determinants of shipping capacity based on the DCM paradigm.