Development of an augmented reality remote maintenance adoption model through qualitative analysis of success factors

Maike Mueller, Dirk Stegelmeyer, Rakesh Mishra

Research output: Contribution to journalArticlepeer-review

Abstract

In recent decades, engineering manufacturers have increasingly adopted servitization strategies, making efficient maintenance service delivery a key corporate activity for revenue growth and profitability. Recently, augmented reality remote maintenance (ARRM) has become available and promises service delivery efficiency gains, which is why engineering manufacturers are starting to adopt it. Therefore, the purpose of this paper is to analyze the promoting and inhibiting factors of ARRM adoption in support of industrial service delivery. To this end, a qualitative explorative approach based on the technology–organization–environment (TOE) framework has been deployed. Data were collected from a systematic literature review and an empirical interview study with 16 companies. In total, 38 interviewees from different hierarchical levels participated in the interview study. Based on a thematic analysis, this paper provides a novel ARRM adoption model and contributes six technological, seven organizational, and four environmental adoption success factors. The promoting factors are ARRM key features, qualitative operational advantages, quantitative operational advantages, value proposition, value creation network, finance, image, adoption management, resource allocation, strategic realignment, skills gap, and governmental regulation; further, augmented reality user experience, data connection, information provision, intellectual property protection, and remote service acceptance were identified as inhibiting factors. This paper qualifies as the first attempt to consolidate engineering-focused ARRM literature with respect to remote service delivery, adding the industrial adoption perspective and elaborating on the impact of the inter-organizational nature of ARRM technology on industrial adoption. Thus, this research contributes to the transition from pure engineering research to industrial ARRM adoption research.
Original languageEnglish
Pages (from-to)1490-1519
Number of pages30
JournalOperations Management Research
Volume16
Issue number3
Early online date20 Apr 2023
DOIs
Publication statusPublished - 1 Sep 2023

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