000			02866nam a22003135i 4500
001			239122
003			ES-VaUE
005			20240306114301.0
007			cr nn 008mamaa
008			210818s2021 gw | o |||| 0|eng d
020			_a9783658351168
024	7		_a10.1007/978-3-658-35116-8 _2doi
040			_aES-VaU _bspa _cES-VaU _dES-VaU
050		4	_aHF5549-5549.5 _b2021 EB
100	1		_aTheres, Christian. _eautor. _4aut _4http://id.loc.gov/vocabulary/relators/aut
245	0	0	_aAntecedents and Consequences of Digital Human Resource Management : _bAn Exploratory Meta-Analytic Structural Equation Modeling (E-MASEM) Approach to a Multifaceted Phenomenon _cby Christian Theres
250			_a1st ed. 2021.
264		1	_aWiesbaden _c2021 _bSpringer International Publishing
300			_a1 recurso en línea
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
490	0		_aGabler Theses _x2731-3239
505	0		_aIntroduction and Motivation -- DHRM: A Multifaceted Field of Research -- Methodology -- Data Collection and Findings -- Discussion, Implications, and Limitations.
520			_aDuring the last decades, a considerable amount of research has been directed towards explaining the concept of Digital Human Resource Management (DHRM). Yet, a holistic assessment of DHRM antecedents and consequences with respect to possible contextual contingencies is still missing. To this end, this thesis introduces a research framework illuminating the multifaceted phenomenon of DHRM from various perspectives. An exploratory four-step meta-analytic structural equation modelling (E-MASEM) approach tailored to address the domain-specific challenges of DHRM is introduced and applied. Results identify 32 constructs associated with the DHRM usage phenomenon which are categorized into DHRM antecedents and DHRM consequences. Findings reveal that user perceptions, expectations, attitudes, and intentions are essential in predicting DHRM usage while HRM service quality and user satisfaction are found crucial in explaining other DHRM consequences. Further, practitioners are informed about the relative importance of factors for both facilitating DHRM adoption and measuring DHRM success. Lastly, this thesis also contributes to the MASEM methodology by outlining a new approach to summarize statistical inferences from multiple moderator tests. About the author Christian Theres is working as a researcher at the chair of management information systems at Saarland University. His focus is on digital human resource management.
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-658-35116-8 _zAcceso a este recurso digital (usuarios Universidad Europea de Valencia)
942			_2lcc _cLE
988			_aSpringer_Business_2021
999			_c239122 _d239122