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Digital enabled agility reflects the transformative outset of an organisation to first upgrade its business processes digitally towards facilitating real-time information processing/capabilities. Second, tapping from real-time capabilities, digital enabled agility maximises an agile response's efficacy in enhancing the sophistication of rapidity, flexibility, and sensing involved. In this backdrop, driven by newer IT infrastructure and disruptive technology, this research accentuates on Industry 4.0 digitalisation to understand how a manufacturer can gain digital enabled agility. An empirical survey of manufacturers within the premise of Industry 4.0 is conducted. Drawn from the findings, the capabilities of traceability and visibility can be facilitated by Industry 4.0 that would improve information sharing and information quality in real-time. These capabilities are key propellants to unlock the digital extent of agility. This research however details further how this scope of agility is an extension to that of the scope of typical agility in terms of its ability to handle expansive information processing needs and dynamic coordination/resource orchestration. Insights are weaved under the purviews of (a) organisational information processing view and (b) the manufacturer who is coordinating contemporary dynamic production and allied value chain requirements. [ABSTRACT FROM AUTHOR]

Industry demand for talented analytics professionals has created a significant increase in degree programs (e.g., MS in Analytics) around the globe. Many of these programs incorporate experiential learning in the curriculum to foster a deeper understanding. This article focuses on the value and challenges in implementing experiential learning in an analytics-focused degree program by incorporating and scaffolding multiple organizational analytics projects throughout the curriculum. In addition, this article focuses on the manner in which these organizational analytics projects can create value for scholars, beyond student learning. Scholar-practitioner partnerships have the potential to advance not only the field of academic research but also the rigor of actual practice. We report our experiences and best practices in creating and leveraging scholar-practitioner partnerships in the context of project-based experiential learning in a Master of Science in Business Analytics (MSBA) program. We provide motivation for creating such partnerships for teaching analytics, document student and organizational success, offer illustrations of exemplary experiential learning projects, and discuss the challenges that need to be managed.

The phenomenon of green contagion refers to the diffusion of sustainability practices across multi-tier supply chains. In this research, we propose a model of green contagion, theorising that both collaborative and coercive mechanisms play a role in the propagation of environmental sustainability across supply chains. Hypotheses are tested using a structural equation model with a multinational dataset of 616 manufacturing organisations reporting on their green practices, both internally within the firm and externally with suppliers and customers. From a theoretical perspective, the results lend support to the green contagion effect, with five out of the seven hypotheses being supported. The rejected hypotheses refer to a firm's internal adoption of green practices influencing green collaborative practices with suppliers, and a customer's use of coercive mechanisms towards a firm influencing the adoption of green collaborative practices between the firm and its suppliers. The findings have theoretical and practical implications for production research, as they highlight the challenges that organisations face when trying to influence green practices beyond tier 1 suppliers, and show that collaborative practices may prove more effective than coercive practices. [ABSTRACT FROM AUTHOR]

This study examines how platforms within sharing economy-based service triads (SESTs) can improve their social capital through information processing and knowledge management mechanisms, with the objective to provide better platform services to both service suppliers and end customers. Data were collected through multiple case studies, primarily relying on insight gathered from 32 semi-structured interviews with managers from four sharing economy platform companies in the Chinese ride-sharing (DiDi and Uber China) and logistics-sharing (Huo-che-bang and Yun-man-man) industries. Through our analysis we uncover uncertainties faced by sharing economy platforms in SETSs (including task complexity, over-competition, and task coordination), delineating their information processing requirements. Based on our findings we suggest that these requirements can be addressed by enhanced intra-organizational structures that would contribute to the SESTs' information processing capacity. Accomplishing this fit between a platform's information processing requirements and associated information processing capacity carries great promise to not only affect the platform's knowledge management capability (PKMC) but also the social capital created within SESTs. [ABSTRACT FROM AUTHOR]