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This chapter describes how conversational computer agents have been used in collaborative problem-solving environments. These agent-based systems are designed to (a) assess the students’ knowledge, skills, actions, and various other psychological states on the basis of the students’ actions and the conversational interactions, (b) generate discourse moves that are sensitive to the psychological states and the problem states, and (c) advance a solution to the problem. We describe how this was accomplished in the Programme for International Student Assessment (PISA) for Collaborative Problem Solving (CPS) in 2015. In the PISA CPS 2015 assessment, a single human test taker (15-year-old student) interacts with one, two, or three agents that stage a series of assessment episodes. This chapter proposes that this PISA framework could be extended to accommodate more open-ended natural language interaction for those languages that have developed technologies for automated computational linguistics and discourse. Two examples support this suggestion, with associated relevant empirical support. First, there is AutoTutor, an agent that collaboratively helps the student answer difficult questions and solve problems. Second, there is CPS in the context of a multi-party simulation called Land Science in which the system tracks progress and knowledge states of small groups of 3–4 students. Human mentors or computer agents prompt them to perform actions and exchange open-ended chat in a collaborative learning and problem-solving environment.

A collaborative community is an organizational form that is increasingly being used in knowledge-intensive industries to accelerate innovation via collaboration. This study examines key design issues faced by a bilateral broker collaborative community at the point of its formation: (1) whether a critical mass of members is required for community survival, (2) the nature of the match between member skills and community challenges, and (3) how the mix of member skills needs to be adjusted over time to sustain community growth. Findings from our agent-based simulation study indicate that, contrary to suggestions in the literature, a critical mass of members is not necessary for a bilateral broker community to survive early on. The literature also suggests that there should be a match between the skill levels of community members and the skill requirements of the challenges that the community must solve in order for it to grow. We find that a match between skill levels and challenge requirements is necessary but not sufficient: the skill levels of community members must significantly exceed the skill requirements of the challenges. Lastly, we find that the appropriate amount of heterogeneity in member skills is contingent on several factors associated with how the community adapts over time. Implications of these findings for the theory and practice of organization design are discussed.

Organizational cultures that facilitate collaboration are valuable, but little is known about how to create them. The authors investigate the microfoundations of this problem using computational models of dyadic coupled learning. The authors find that merely altering initial beliefs about the consequence of actions (without altering the consequences themselves) can under some conditions create cultures that promote collaboration. The results of this study show why the right initial “framing” of a situation – established for instance through persuasive rhetoric, an inspiring vision, or careful recruitment choices – may under the right conditions be self-reinforcing, instead of becoming empty symbolism.

This research contributes to understanding emotional and political challenges experienced by middle managers as they work with contradictions inherent in leading change from the middle. Focus group data from 27 such middle managers based in the UK indicate that, once they have been assigned roles and tasks for leading change, underlying dynamics and processes influence the degree to which they become capable (or unable) to shape and navigate that change. A proposed conceptual framework, illustrated by a case vignette, provides a base of existing knowledge for understanding and explaining these dynamics. We also construct a model of the key tensions that are integral to middle managers leading change. A further contribution to practice involves elaborating the importance of collaborative effort across hierarchical and vertical boundaries, despite emotional and political tensions that undermine middle managers’ roles as change agents.

Two major trends – demographic shifts in the working-age population, and the proliferation of web technologies – are having a profound and generally unrecognized effect on the nature and characteristics of work, and on opportunities for the mature workforce. Key features of the workplace point to seven broad work trends. These trends have significant implications for organizations and for older workers. Six interdependent organizational changes are central to the far-reaching effects on enterprises and operating approaches. These changing work characteristics require certain essential behaviors for mature workers to be successful in the contemporary work environment. Such a dynamic workplace provides opportunity to introduce new thinking and propose new models. Realigning organizational and workforce interests calls for developing solutions beyond the individual level, reorienting enterprise capabilities, and reframing of the organization development practitioner role as work ecosystem advisor. High-leverage strategies and systemic interventions, such as multiconstituent initiatives and action research, can be used to influence constructively the multifaceted world of work.

Purpose: Technological innovations and frameworks that provide a framework for unification have evolved to improve information exchange across organisational units and information security. These integration technologies share and communicate information using defined protocols and different data. Service-oriented architecture (SOA) is a significant emerging approach that enables modular design solution construction.

Methodology: These designs are beneficial when many apps operating on different architectures and networks need to connect. A well-defined strategy and company-specific guidelines are essential for ensuring the firm’s systematic adoption of such an architecture. The critical components of MASSOASCM ‘(Multi-Agent System Service Oriented Architecture Supply Chain Management’ are a multi-agent system (MAS), a service-oriented structure, and supplier management. The MASSOASCM model has been made, and a production unit has been made to show how it works.

Findings: It has been stated that it saves development costs, and inventory management, all of which are critical concerns in any company. Our goal is to create an inventory control approach that relies on MAS and SOA but also a simulation that demonstrates how it works and may enhance Supply Chain Management (SCM) productivity in a production plant.

Practical Implications: The SCM implementation comprises three different services: SCM, SOA, and MAS. These facilities are constructed, maintained, planned, and implemented individually before being brought together collectively using MAS and SOA techniques.

Technology for training military teams has evolved through a convergence of advances in simulation technology for individual and collective training, methods for analyzing teamwork and designing training solutions, and intelligent tutoring technologies that adapt training to the student, to accelerate learning. A number of factors have slowed this evolution toward intelligent team tutoring systems (ITTS), including the challenges of processing communications data, which are the currency of teamwork, and the paucity of automated and generalizable measures of team work. Several systems fulfill a subset of the features required of an ITTS, namely the use of team training objectives, teamwork models, measures of teamwork, diagnostic capability, instructional strategies, and adaptation of training to team needs. We describe these systems: the Advanced Embedded Training System (AETS), Synthetic Cognition for Operational Team Training (SCOTT), the AWO Trainer, the Benchmarked Experiential System for Training (BEST), and the Cross-Platform Mission Visualization Tool. We close this chapter with recommendations for future research.