Human–AI resource relations in value cocreation in service ecosystems

业务 价值(数学) 服务(商务) 资源(消歧) 知识管理 营销 计算机科学 计算机网络 机器学习
作者
Valtteri Kaartemo,Anu Helkkula
出处
期刊:Journal of Service Management [Emerald Publishing Limited]
标识
DOI:10.1108/josm-03-2023-0104
摘要

Purpose Applications of artificial intelligence (AI), such as virtual and physical service robots, generative AI, large language models and decision support systems, alter the nature of services. Most service research centers on the division between human and AI resources. Less attention has been paid to analyzing the entangled resource relations and interactions between humans and AI entities. Thus, the purpose of this paper is to extend our metatheoretical understanding of resource integration and value cocreation by analyzing different human–AI resource relations in service ecosystems. Design/methodology/approach The conceptual paper adapts a novel framework from postphenomenology, specifically cyborg intentionality. This framework is used to analyze what kinds of human–AI resource relations enable resource integration and value cocreation in service ecosystems. Findings We conceptualize seven different human–AI resource relations, namely background, embodiment, hermeneutic, alterity, cyborg, immersion and composite relation. The sociotechnical entangled perspective on human–AI resource relations challenges and reframes our understanding of interactions between humans and nonhumans in resource integration and value cocreation and the distinction between operant and operand resources in service research. Originality/value Our primary contribution to researchers and service providers is dissolving the distinction between operant and operand resources. We present two foundational propositions. 1. Humans and AI become entangled value cocreating resources in inherently sociotechnical service ecosystems; and 2. Human and AI entanglements in value cocreation manifest through seven resource relations in inherently sociotechnical service ecosystems. Understanding the combinatorial potential of different human–AI resource relations enables service providers to make informed choices in service ecosystems.

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