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Purpose The global business environment combined with increasing societal expectations of sustainable business practices challenges firms with a host of emerging risk factors. As such, firms seek to increase supply chain transparency, enabling them to monitor operational activities and manage supply chain risks. Drawing on organizational information processing theory, the purpose of this paper is to examine how supply chain analytics (SCA) capabilities support operational supply chain transparency. Design/methodology/approach Using data from 477 survey participants, hypotheses are tested using seemingly unrelated regression. Findings The results reveal that: analytics capability in support of planning functions indirectly affects organizational supply chain transparency (OSCT) via SCA capabilities in source, make, and deliver functions; SCA capabilities in source, make, and deliver positively influence OSCT; and supply uncertainty moderates the relationship between SCA capabilities in make and OSCT. Research limitations/implications This research suffers from limitations inherent in all survey-based research. Nonetheless, the authors found convincing evidence that suggests firms can employ SCA capabilities to meet transparency requirements. Practical implications The findings inform design of SCA systems, noting the importance of linking planning tools with tools that support source, make, and deliver functions. The research also shows how transparency can be increased via employing SCA capabilities. Originality/value This is one of first studies to empirically demonstrate that SCA capabilities can be used to increase supply chain transparency. The research also advances organizational information processing theory by illustrating an analytics capability paradox, where increased levels of certain analytics capabilities can become counterproductive in the face of supplier uncertainty.

Research suggests that there are other, more granular factors within the domain of innovation diffusion theory that influence the adoption of technological innovations. In this study, the circumstances that affect a firm's intention to adopt cloud computing technologies in support of its supply chain operations are investigated by considering tenets of classical diffusion theory as framed within the context of the information processing view. We posit that various aspects of an organization and its respective environment represent both information processing requirements and capacity, which influence the firm's desire to adopt certain information technology innovations. We conducted an empirical study using a survey method and regression analysis to examine our theoretical model. The results suggest that business process complexity, entrepreneurial culture and the degree to which existing information systems embody compatibility and application functionality significantly affect a firm's propensity to adopt cloud computing technologies. The findings support our theoretical development and suggest complementarities between innovation diffusion theory and the information processing view. We encourage other scholars to refine our model in future supply chain innovation diffusion research. The findings of this study might also be used by industry professionals to aid in making more informed adoption decisions in regard to cloud computing technologies in support of the supply chain.

PurposeA comprehensive evaluation of the constructs that contribute to the incorporation of a supply chain innovation into an organization is markedly absent in the literature. Even in academic fields where the post‐adoption diffusion stages of acceptance, routinization, and assimilation are often investigated, no study integrates these constructs and their constituent dimensions into a unified framework. In addition, these post‐adoption activities are largely ignored in the supply chain innovation literature. This paper aims to integrate extant literature regarding acceptance, routinization, and assimilation for the purpose of clarifying the definitions and identifying the dimensions of each construct to provide guidance to scholars who are investigating innovation diffusion in the supply chain.Design/methodology/approachThrough the lens of diffusion of innovation theory, a broad base of literature both within and beyond the scope of traditional supply chain management (SCM) journals is considered to develop a unified framework of post‐adoption activities.FindingsThis research effort provides an in‐depth analysis of the post‐adoption stages of the organizational diffusion process and suggests 17 activities that support diffusion. Relationships between and within these stages of the process are inferred to create a unified framework of post‐adoption activities.Research limitations/implicationsThe resultant framework provides a reference point for future research. Although providing motivation for this study, this research is limited by the fact that few studies in the SCM literature consider organizational diffusion beyond adoption. The proposed framework is contingent on generalizing literature from related academic disciplines. Future SCM research can validate these findings and further tailor the framework to be more specific to supply chain applications.Practical implicationsThis article provides insight for supply chain professionals who seek to not just adopt, but also to fully embed a newly acquired innovation into their organization. Managers can use this article's resulting framework as a reference to determine what actions they should take to fully incorporate an innovation.Originality/valueAlthough recognized as an important area of investigation in other literature streams, post‐adoption activities are almost entirely overlooked in SCM research. This study provides both the motivation and a starting point for scholars to consider such activities.