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Organizations are reaching beyond typical firm boundaries to achieve competitive advantage. Human resource (HR) systems must simultaneously support alignment across the business ecosystem while acknowledging the benefits of disruption. The authors provide a fresh perspective on strategic HR management (SHRM), expanding the view beyond organizations to look at the ecosystem as a whole. The authors address the need for HR systems to balance the dualistic tensions of alignment and disruption. While examining the environmental logic of the ecosystem, the authors provide examples of disruption through competition and alignment through cooperation. The authors then examine potential research implications that could assist managers as they govern in a constantly changing and complex ecosystem. This chapter presents the HR ecosystem framework which provides a clear discussion of how different governance mechanisms might be utilized to help firms achieve a competitive advantage through the balance between alignment and disruption.

Purpose: To outline recent developments in digital service delivery in order to encourage researchers to pursue collaborations with computer science, operations research, and data science colleagues and to show how such collaborations can expand the scope of research on emotion in service delivery.

Design/methodology/approach: Uses archived resources available at http://LivePerson.com to extract data based in genuine service conversations between agents and customers. We refer to these as “digital traces” and analyze them using computational science models.

Findings: Although we do not test significance or causality, the data presented in this chapter provide a unique lens into the dynamics of emotions in service; results that are not obtainable using traditional research methods.

Research limitations/implications: This is a descriptive study where findings unravel new dynamics that should be followed up with more research, both research using traditional experimental methods, and digital traces research that allows inferences of causality.

Practical implications: The digital data and newly developed tools for sentiment analyses allow exploration of emotions in large samples of genuine customer service interactions. The research provides objective, unobtrusive views of customer emotions that draw directly from customer expressions, with no self-report intervention and biases.

Originality/value: This is the first objective and detailed depiction of the actual emotional encounters that customers express, and the first to analyze in detail the nature and content of customer service work.