We introduce and empirically test the creation-dispersion model of supply chain organizational learning to align learning orientations in a supply chain context. Our paper seeks to advance the knowledge on supply chain organizational learning by showing that four distinct supply chain learning orientations (team, learning, memory, and systems), previously studied only as a collective, can be parsed strategically. We parse these four learning orientations into creation capacity (team and learning orientations) and dispersion capacity (memory and system orientations). The creation and dispersion capacity can enhance exploration (long-term) and exploitation (short-term) practices respectively in supply chain organizations. We used a survey questionnaire to collect data from 128 respondents belonging to firms of various sizes and different industries. We find that creation capacity is positively associated with exploration and indirectly associated with exploitation through exploration. Dispersion capacity is associated with exploitation and indirectly influences market share and profitability through exploitation. The findings demonstrate that creation and dispersion-based combinations of supply chain learning orientations coalesce to influence exploration and exploitation practices. We discuss the implications for supply chain organizational learning literature.

INTRODUCTION

As a vital operating system, the supply chain of an organization is responsible for up to 90 percent of an organization’s cost base (O’Byrne, 2016). Supply chain function is undergirded in nearly every aspect of an organization’s operations and requires coordination and cooperation within the organization and with entities external to the organization, including the critical connection to the customer (Marchese and Lam, 2015). Jim Owens, a former Caterpillar CEO, feels that “the competitor that’s best at managing the supply chain is probably going to be the most successful competitor over time” (Malik et al., 2011, p. 2). The challenge of simultaneous management of exploration and exploitation practices is pronounced in the supply chains (Lauer, 2014; Gualandris et al., 2018; Turner et al., 2018). Supply chain functions have the unique challenge to minimize inventory levels, drive down costs, and deliver flawless customer service (exploitative practices), while looking towards new technologies and practices that will allow operational innovation and flexibility (explorative practices) (Marchese and Dollar, 2015; PwC, 2015). Cultivation of skills important for supply chain efficiency and effectiveness, such as, agility, complex problem-solving, and adoption of new technology and business models, require supply chain organizations to become focused on organizational learning that fosters both exploration and exploitation practices (Malik et al., 2011; Marchese and Dollar, 2015; PwC, 2015). The need to simultaneously manage exploration and exploitation efforts is rooted in March (1991), who was the first to characterize the need to explore and exploit in the context of a learning organization. Though there is a general consensus that firms are required to simultaneously explore and exploit for short-term performance and long-term survival (Birkinshaw and Gupta, 2013; Long, 2016; O’Rielly and Tushman, 2013), there is little consensus on the nature of orientations and how they drive exploration and exploitation. Since March’s seminal article, there has been only limited advancement in the knowledge and understanding of how firms manage exploration and exploitation (Birkinshaw and Gupta, 2013; Levinthal and March, 1993; O’Reilly and Tushman, 2013). There is also a limited understanding of how organizations manage trade-offs to create different structures that offset organizational routines necessary for exploration and exploitation, to allocate variegated resources and attention necessary for exploration and exploitation pursuits in a supply chain, and to develop processes, capabilities, skills, and cultures to enable each dimension (Birkinshaw and Gupta, 2013; Jensen and Clausen, 2017; Lavie and Rosenkopf, 2006).