Strategic Human Resource Management As a Translation System In Digital Transformation: Evidence From Haier Smart Home

2026

Full text Open access: Hybrid Metadata (CSL-JSON)
DOI 10.51601/ijersc.v7i3.1041
Data confidence 70 medium
How this score is calculated

It is built from checkable properties of the record itself: whether the article has a DOI, how many independent sources confirmed its data, whether the required fields are filled in, and how recent the latest confirmation is. Disagreement between sources and a missing identifier lower it. A value of 80 or above means the record was published without further checking; 60 to 79 means it is published at reduced confidence, with a manual check advisable. A record verified by an editor by hand is never pushed below 90 by a recalculation. This scores our data about the article, not the article itself.

Abstract

Digital transformation often fails at execution because technologies do not automatically alter decision rights, talent allocation, incentives, or cross-boundary coordination. This study examines how strategic human resource management translates digital strategy into organisational action and value creation. A longitudinal embedded single-case study of Haier Smart Home was conducted using six semi-structured interviews (628 recorded minutes) collected in February-March 2026 and archival evidence covering 2020-2025. Gioia coding, process tracing, pattern matching, rival-explanation analysis, and data triangulation were applied. The findings identify four linked mechanisms: dynamic strategic alignment through decentralised authority and human-resource platforms; order-based human-capital reconfiguration through capability labels, opportunity orders, and flexible team boundaries; market-oriented incentives through user-paid compensation and traceable contributions; and platform governance through chain-group collaboration across internal units and ecosystem partners. These mechanisms improve organisational responsiveness and broaden value creation, but their effects depend on reliable data, divisible tasks, attributable feedback, talent depth, transparent rules, and sustained leadership commitment. The study reconceptualises digital human-resource management as a governance mechanism system rather than a set of automated functions.