Understanding the Progressive Nature of Inter-Organizational Systems (IOS) Adoption

Introduction

Inter-organizational Systems (IOS) are automated information systems, which are shared by two or more companies (Cash and Konsynski, 1985). Examples of IOS include Electronic Data Interchange (EDI) and Collaborative Planning, Forecasting and Replenishment (CPFR). Many organizations adopt IOS to improve their supply chain management. IOS offer organizations substantial benefits such as reduced inventory costs, elimination of redundant handling of data entries, improved scheduling, processing and distribution of goods and improved information accuracy, to name a few (Premkumar and Ramamurthy, 1995; Mentzer, 2004). IOS have become a strategic weapon for some organizations to obtain competitive advantage and have shifted competition from single firms competing individually to supply chains competing against other supply chains (Birou, Fawcett and Magnan, 1998; Lambert and Cooper, 2000).

Despite these benefits, many companies face difficulties in adopting these systems because such implementations are highly reliant on trading partners’ existing relationships which often are not favorable (Kurnia and Johnston, 2003). IOS adoption requires credible commitment of participating firms to work collaboratively to achieve common objectives and goals. Because of the inherent complexity in IOS adoption, there have been many attempts in the literature to study various aspects of IOS adoption by organisations (Kumar and Van Dissel, 1996; Damsgaard and Lyytinen, 1998; Saeed, Malhotra and Grover, 2005). Some studies (see for example, (Webster, 1992; Meier, 1995; Kumar and Van Dissel, 1996; Saeed et al., 2005; Ham and Johnston, 2007) indicate that unfavourable relationships often exist among trading partners, which makes IOS adoption difficult.

Realizing the importance of relationships in IOS adoption, there have been an increasing number of studies investigating Interorganizational (IO) relationships. For example, some studies examine IO relationship factors or aspects that contribute to adoption failures or success (Hart and Saunders, 1997; Ibrahim and Ribbers, 2006; Nagy, 2006), while others classify relationship types based on relationship intimacy and IOS types based on integration and then match levels of relationship intimacy with the levels of IOS integration (Choudhury, 1997; Shah, Goldstein and Ward, 2002; Redonodo et al, 2009). More recently, researchers do not only examine the interaction between relationship types and IOS types but also investigate how organizations move from lower levels to higher levels of intimacy of relationship and integration of IOS types (Ham and Johnston, 2007).

While there are some studies that shed light on how organizations can move or progress from a less sophisticated to a more sophisticated IOS based on relationships, it is difficult to base an empirical investigation on this work. This is because these studies are not theoretically strong and do not include, or justify the exclusion of, other factors such as organizational capabilities to investigate maturity or progression of IOS adoption.

Over the years, various frameworks have been developed within the IOS adoption field. For example, Damsgaard and Lyttinen (1998) examine IOS using micro, meso and macro level of analysis, Kumar et al. (1998) classify IOS studies as technical, economical or socio-political, Ramanathan and Rose (2003) explain the IOS adoption research in the form of stages. While these frameworks help us obtain a general understanding of the field, they do not emphasise the importance of time in the study of IOS adoption.