R P Sundarraj

This book contains contemporary discussions on technology, business models, and the adoption of digital manufacturing systems. The book’s initial chapters cover technological details underpinning the digital manufacturing systems, for example, cyber-physical systems and digital twins. Next, the book discusses how organizations modify their business models using concepts such as servitization and platforms to leverage digital manufacturing. The latter chapters focus on how a country’s unique economic and infrastructural context influences digital manufacturing adoption in terms of technology and business models and frameworks to evaluate readiness for digital manufacturing. With perspectives from different continents, the book appeals to academic researchers and industry alike.

Ever since the industrial revolution, manufacturing has been one of the key drivers of economic growth.

Systems based on information and communication technologies have facilitated the support or automation (partial/complete) of many a task and process, including negotiation. Electronic negotiation systems (ENSs), whose genesis and evolution can be traced to software systems of the 1970s, have grown significantly since the advent of the Internet, in terms of both scope and numbers. Yet, given the complexity of negotiation, there is a need for incorporating behavioral elements into ENSs. This chapter, which concerns a two-party negotiation setting, outlines the behavioral negotiation literature and describes the evolution of ENSs, thus contextualizing the problem of incorporating behavior into negotiation systems. A framework is proposed in this chapter, and it entails a characterization of user preferences, and in turn, the resulting negotiation strategy. Relevant exemplars from the literature are used to illustrate how the tradeoff between the fidelity and tractability of such characterizations can determine the level of automation afforded by an ENS. Research opportunities arising from endowing ENSs with behavioral features are identified.