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Smart industry initiatives focus on intelligent and interconnected cyber-physical systems. These initiatives develop complex technical architectures that integrate heterogenous technologies, causing significant organizational complexity. Tapping into the digital capabilities of distant partners while capturing profit from such innovation is demanding. Furthermore, firms often need to establish and orchestrate inter-organizational collaborations without prior relations or established trust. As a result, smart industry initiatives bring together disparate organizational forms and institutional environments, distinctive knowledge bases, and geographically dispersed organizations. We conceptualize this organizational capability as ‘distant capabilities integration’. This research explores the governance mechanisms that support such integration and their relation to value capture. We analyse 11 IoT case studies organized in three categories (process, product and technologies) of smart industry initiatives. Building on existing literature, we consider different ways to describe distance, including knowledge heterogeneity and organizational, geographical, institutional, cultural and cognitive distance. Finally, we describe the governance mode appropriate for upstream (developing foundational technologies) and downstream (leveraging existing distant technologies) smart industry initiatives.

Purpose – The purpose of this study is to analyze and design a virtual collaboration information system of the Jamu supply chain network based on a fair adaptive contract to respond to stability challenges in business with an uncertainty environment condition.

Design/Methodology/Approach – System entity approach is used for the purpose of system analysis and then case, sequence diagram, class diagram, graph data modeling, and business process modeling and Notation verse 2 (BPMN2.0) are also used to design the system concept. Each process of the connecting event and gateways was arranged with relevant multicriteria decision approach, whilst an adaptive quantitative formulation based on prescriptive analytics was embedded to ensure a fair contract implementation during the terms for all sphere roles in supply chain.

Findings – The results and implications of this model emphasizes on the knowledge, competence, trust, and fair (KCTF) for actors’ adoption to improve supply chain stability and implementation.

Practical Implications – This led actors to collaborate their business in a more effective way.

Originality/Value – This model can reach more stability in the uncertainty environment.