Index

Electronic HRM in the Smart Era

ISBN: 978-1-78714-316-6, eISBN: 978-1-78714-315-9

Publication date: 9 August 2017

This content is currently only available as a PDF

Citation

(2017), "Index", Bondarouk, T., Ruël, H.J.M. and Parry, E. (Ed.) Electronic HRM in the Smart Era (The Changing Context of Managing People), Emerald Publishing Limited, Bingley, pp. 339-353. https://doi.org/10.1108/978-1-78714-315-920161014

Publisher

:

Emerald Publishing Limited

Copyright © 2017 Emerald Publishing Limited


INDEX

Ability-motivation-opportunity framework (AMO framework)
, 147

Access to Capital
, 16, 18, 22, 25

Activity dimension
, 36

‘Administrative/operational’ theory
, 325, 333–334

Adopter/abandonment system dynamic model
, 81

Agent dimension
, 36

‘Agential humanist’ position
, 267, 270, 271, 274, 276

Agential realism
, 270, 274

Alignment
, 142

Alternative research model test
, 160–162

Ambiguity
, 64

American Society for Personal Administration (ASPA)
, 63

AMO framework. See Ability-motivation-opportunity framework (AMO framework)

Amris
, 42, 43

“Analyzers”
, 146

Anticipated Organizational Growth
, 13, 14, 18, 25

Architectural competence
, 141

ASPA. See American Society for Personal Administration (ASPA)

Augmentation
, 225, 227

Australia, IS issues in
, 207–208

Australian organisations, e-HRM challenges in
, 202, 208, 211, 215, 217

Automational e-HRM systems
, 89

Average variance extracted (AVE)
, 155

Barclays
, 70

BBC instrument
, 332

Big data
, 62, 80, 101, 222

Business areas (BAs)
, 185, 197

Business relationships (BR)
, 206, 213

Capability Builder
, 325

Capability configuration
, 140, 151, 158, 160

analysis
, 166

SHRM and e-HRM
, 164

CedarCrestone HR Systems surveys
, 72, 82

Channels
, 66

Click-Call-Face customers
, 324

Client interface
, 36

Cloud-based

HR software
, 17–18

HRIS adoption model
, 24, 25

Cluster analysis
, 143, 152

Code of conduct
, 177, 299

Compatibility
, 7, 9, 18, 35, 216, 217

of business processes
, 12

of SMEs’ e-HRM technology
, 163

Component capabilities
, 141

Component competence
, 141

Conceptualisation of e-HRM
, 263, 267, 272

Configurational approach
, 160, 162, 251–252, 264

Constructive ethnographic research
, 276–277

Content analysis
, 184–185

Continuous professional development (CPD)
, 301

Controlled vocabularies
, 73

“CORE”
, 184, 186

role in supporting business strategy
, 193

strategic potential
, 192–193

Corporate strategic development
, 317–318, 326

Cost

efficiency improvement
, 187

reductions
, 177

Covariance-based techniques
, 154, 158

CPD. See Continuous professional development (CPD)

Cultural values
, 92, 176, 181

Customers
, 93, 99, 298

Click-Call-Face
, 324

for higher service quality
, 34

internal
, 203

service and efficiency improvement
, 187–188

Cyber-vetting
, 291, 294–295

D&M model. See DeLone and McLean model (D&M model)

Data analytic software
, 64n1

Data collection
, 148

descriptive statistics of

research variables
, 149

strategic HRM and e-HRM capabilities
, 150

HRD
, 148

Data governance programs
, 101–103

Data mining process
, 64, 294, 295

Data quality
, 95–97, 104, 105

issues
, 94

poor
, 102

recommendations
, 101–103

Data-driven business
, 323

Decision support systems perspective (DSS perspective)
, 97, 208

“Defenders”
, 146

DeLone and McLean model (D&M model)
, 92–96

integration into e-HRM
, 99–101

quality components
, 101

Descriptive analytics
, 63

Design mode
, 269

d-HRM. See Digital HRM (d-HRM)

Diffusion of innovation theory (DOI theory)
, 61, 62, 66, 67, 79–80

Diffusion process
, 62, 67, 68

Digital HRM (d-HRM)
, 35

Digital systems
, 312, 323, 326

Digital technologies
, 38, 315, 325, 335

Digitization model
, 46

Digitization on HRM profession

activities of HRM professional
, 334–335

automation risk role analysis
, 320

corporate strategy development
, 318

digital systems and robots
, 312

economic and social effects of
, 313

effects of
, 335–336

findings/results
, 322

secondary analysis HRM practice monitor
, 325–328, 331

sessions with HRM professionals
, 323–325

future work skills
, 316, 317

HRM roles
, 315

labels of HRM department
, 335

limitations of HRM practice monitor
, 330–334

primary role of HRM professional
, 334

research design
, 319

HRM professionals
, 319–321

secondary analysis HRM practice monitor
, 321–322

theoretical background
, 314

See also Electronic-HRM (e-HRM)

Direct effects model
, 160

DOI theory. See Diffusion of innovation theory (DOI theory)

Doomsday scenario
, 224

DSS perspective. See Decision support systems perspective (DSS perspective)

Economic and social effects of digitization
, 313

EDI adoption model
, 9, 23

Effective data governance
, 105

Effective training
, 101, 299

e-HRM. See Electronic human resource management (e-HRM)

Electronic human resource management (e-HRM)
, 5, 36–37, 88, 138, 139, 154, 175, 202, 262, 315

impact
, 178–179

Australian organisations
, 202–203

challenges
, 202, 211

consequences
, 178

descriptive statistics
, 150

development issues
, 214–215

discussion
, 98

data quality recommendations
, 101–103

future research
, 104–105

integrating D&M model into e-HRM
, 99–101

limitations
, 105

system quality recommendations
, 103–104

HR issues
, 212–214

implications, limitations and suggestions for future research
, 215–217

interview questions
, 108

limitations
, 279–280

literature review
, 203

e-HRM and outcomes
, 203–204

e-HRM literature on system success
, 91–92

information systems managerial issues reported in IT literature
, 204–207

IS issues in Australia
, 207–208

IS success model
, 92–94

methods
, 94–95, 208

considerations
, 276–278

perspectives on e-HRM
, 208–209

semi-structured interview questions
, 210

motives for e-HRM adoption
, 194

as nexus of practices and material arrangements
, 272–276

organizational capabilities
, 141–142

and outcomes
, 203–204

project
, 89–91

research
, 263

future
, 278–279

theories in
, 264–267

results
, 95

data quality
, 95–97

service quality
, 98

system quality
, 97–98

sociomateriality in information systems research
, 267–272

systems
, 88

technical challenges
, 211–212

See also Digitization on HRM profession; Strategic human resource management (SHRM)

Employee self-service
, 7, 19, 23, 83, 324, 334

Employer
, 120, 288, 294

branding
, 43, 45, 111, 115, 118, 292–293

Employment debate
, 223–226, 245

Enterprise resource planning system (ERP system)
, 35, 103–104, 263–264, 268–269

Environmental context
, 9, 14–16

Environmental factors
, 2, 8, 9, 24, 92

EQS, Covariance-based techniques
, 154

E-recruitment
, 111

experience with
, 120

perceived fairness
, 120

Web 2.0
, 129–130

ERP system. See Enterprise resource planning system (ERP system)

Ethical guidelines
, 289–290, 299

Ethnographic sensibility
, 276

Evidence-based approach
, 64

Experimenters
, 81

Facebook
, 43–44, 111–112, 117, 123–124

FinCO company
, 184, 185, 189, 193

business areas
, 197

HR in
, 186

HR professionals and line managers in
, 194

Firm

e-HRM organizational capabilities
, 147

systems capabilities
, 141

“Fit as covariation”
, 143

“Fit as gestalts”
, 143

“Fit as matching”
, 143

“Fit as mediation”
, 143

“Fit as moderation”
, 143

“Fit as profile deviation”
, 143

Formal recruitment procedures
, 110–111

Gamification
, 38, 39, 249, 250

“Gestalts” perspective
, 143, 144

See also Manufacturing SMEs

Glassdoor (websites)
, 292, 293

Global orientation improvement
, 187, 194

Google

N-Gram charts
, 72

Project Oxygen
, 69–70

Gravitate
, 42, 43

Growth need strength (GNS)
, 228, 244

Harvard Business Review
, 75

Headquarters (HQ)
, 40

Hermeneutical method
, 277

High-performance work systems (HPWS)
, 142

Homogeneity test
, 319

Hospitality industry
, 34, 37–38

Hotels
, 34, 36

HPWS. See High-performance work systems (HPWS)

HQ. See Headquarters (HQ)

HR. See Human resources (HR)

HRD. See Human resources director (HRD)

HRIS. See Human resource information systems (HRIS)

HRM approach. See Human Resource Management approach (HRM approach)

Human agency in social theory
, 271

Human resource information systems (HRIS)
, 2, 3, 11, 23, 35, 184

background
, 4–5

contributions
, 24–26

deployment
, 20

limitations
, 26

method
, 16

analyses
, 19

measures
, 17–19

participants
, 16–17

sample organization characteristics
, 17

previous HRIS adoption research
, 5–6

results
, 19

correlations among variables
, 21

hypotheses tests
, 19–22

regression analysis
, 22

SMEs
, 3

theories of information systems adoption
, 6–9

TOE model
, 9–16

Human Resource Management approach (HRM approach)
, 35, 62, 63, 174, 222, 288, 313–314

HRM4
, 212

HRM5
, 213

labels of HRM department
, 335

limitations of HRM practice monitor
, 330–334

Practice Monitor
, 317

practitioners
, 112

professional

activities of
, 334–335

primary role of
, 334–335

professionals
, 319–321, 323–325

research
, 262

secondary analysis
, 321, 325

bivariate correlations typification HRM department over time
, 328

data on ‘Personnel Administration’
, 326

e-HRM
, 328, 329

number of mentions, HRM practice monitor
, 330

statements on e-HRM, digital, computer
, 331

time spent by HRM professional
, 326

typification of HR department
, 327

Smart Industry research in
, 222, 244–245

direct effects on Job Characteristics
, 247–250

drastic organisational changes
, 222–223

employment debate
, 224–226

as inspiration for configurational approach
, 251–252

JCM
, 228–244

job characteristics
, 258–259

job design
, 226–227, 245–247

method
, 227

as moderator
, 250–251

Human resources (HR)
, 2, 35, 60, 116, 174, 176, 180, 183, 263

adopter/abandonment system dynamic model
, 81

analytics
, 60–61, 64, 80

Compliance Support
, 18

conceptualizing HR analytics as innovation
, 62–65

CORE’s role in making HR more strategic
, 192–193

department
, 102–103, 105

e-HRM technology
, 79–80

employee self-service
, 83

in FinCO
, 186

findings and discussion
, 40

benefits of innovative tools
, 49

criteria for classification of practices
, 45

digitalised HR system
, 47

digitisation model
, 46

innovation strategy
, 41

perception of digitalization
, 48

practices and systems
, 43

social media and mobile applications
, 42

‘super users’ of core system
, 50

T&D system
, 44

functions
, 95, 100, 203

HRM practice
, 62–63

as innovation
, 80–81

issues
, 212–214

literature review
, 35–39, 63–65

management fashions
, 82–83

methodology
, 39–40, 71

analysis
, 72–74

sample
, 71–72

metrics
, 60, 63–65

HR Analytics and
, 65

practices
, 146–147

professionals
, 191

skills
, 214

recommendations for HR practitioners
, 299–302

results
, 74–79

risks
, 297–298

service
, 190–191

theory and hypotheses
, 66

as innovation
, 66–68

as management fashion
, 68–69

management fashion theory
, 69–71

Human resources director (HRD)
, 148

Hypotheses tests/testing
, 19–22, 318

ICT
, 244, 313, 314

Ideation process
, 180

IDT. See Innovation diffusion theory (IDT)

IE. See Internal effectiveness (IE)

IHRIM. See International Human Resource Information Management (IHRIM)

ILO. See International Labour Organization (ILO)

Implementation costs
, 14, 18

Improved HR data
, 17

Individual-oriented models
, 8–9

“Industry 4.0”
, 222, 247, 248, 252

Informal recruitment processes
, 110–111

Information quality
, 11, 93, 99, 100

dimension
, 88

maximizing
, 101

Information systems (IS)
, 35, 89, 203

adoption theories
, 6

IDT
, 7–8

organizational-level adoption theories
, 8–9

TAM
, 6–7

TPB
, 7

UTAUT
, 8

issues in Australia
, 207–208

literatures
, 99, 104–105

managerial issues reported in IT literature
, 204–207

quality
, 97

sociomateriality in information systems research
, 267–272

success model
, 92–94

Information technology (IT)
, 34, 60, 138, 140, 174, 262

deployment
, 333

issues
, 206, 207

knowledgeable information technology staff
, 98

strategic alignment of
, 142–143

Informational e-HRM systems
, 89

Innovation
, 34

conceptualizing HR analytics as
, 63–65

diffusion
, 35, 51, 66, 79, 81

HR analytics as
, 66–68

innovation-decision process
, 67

Innovation diffusion theory (IDT)
, 7–8, 83

Innovativeness
, 118, 119, 120–121, 125, 128

Instagram
, 44, 118

Institutional theory
, 266

‘Institutionalists’ research
, 266

Integrative capabilities
, 141, 275

Intention to apply
, 124–125

for job
, 116, 130

job seekers
, 125

regression analysis of usability, attractiveness and interaction effects
, 127

Inter-level consequences
, 266

Inter-organisational service delivery
, 36

Internal effectiveness (IE)
, 206

International environments
, 176

International Human Resource Information Management (IHRIM)
, 61, 78–79

International Labour Organization (ILO)
, 289

Internet
, 36, 69, 264, 294

Internet of things (IoT)
, 37, 245, 252

Internet-based recruitment
, 115

Interviews
, 184, 209, 218

conducted
, 40

semi-structured
, 39, 211

transcribed
, 210

Intra-level consequences
, 266

Intra-organisational service delivery
, 36

Intranet
, 44, 45, 47, 204, 264, 315

IoT. See Internet of things (IoT)

Irish hotel industry
, 35

IS. See Information systems (IS)

IT. See Information technology (IT)

JCM. See Job characteristics model (JCM)

Job characteristics model (JCM)
, 227–228, 246, 258–259

and developments
, 228, 241

and findings regarding job character
, 228

identified job characteristics
, 241

graphical illustrations
, 241–244

direct effects of Smart Industry
, 247–250

Job design
, 223, 226–227

challenges
, 245

conceptual clarity
, 245–247

Smart Industry impact on
, 247

Job seekers
, 112–114, 125

perception of e-recruitment tools
, 131

perceptions and reactions
, 129

regression analysis of usability, attractiveness and interaction effects
, 127

willingness to apply
, 114

Knowledge processing system
, 97–98

Lean manufacturing approach
, 63

Legal guidelines
, 289–290

Line managers (LMs)
, 179, 183, 191–192

LinkedIn
, 43–44, 111, 117, 121–122, 124–125, 127–128

Linking code of conduct to training
, 299–300

LISREL
, 154, 158

Management fashion

HR analytics as
, 68–69

theory
, 62, 69–71, 79–80

Management innovation
, 63

Management system dimension
, 141

Manufacturing SMEs
, 138

alternative research model test
, 160–162

e-HRM
, 139

implications for theory and practice
, 162

return to strategic alignment model
, 164

SAM
, 163

SWOT approach
, 164–165

limitations
, 165–166

measurement model assessment
, 154

AVE
, 155

PLS
, 154

reliability, validity, and intercorrelations of research constructs
, 157

test of research model
, 156

methodology

data collection
, 148–151

operationalization of research concepts
, 144–148

research model
, 144, 145

research model assessment
, 158

covariance-based techniques
, 158

test of research model
, 159

variance
, 160

SHRM
, 140

taxonomic analysis of organizational capabilities
, 151

breakdown of antecedent, control, and SHRM performance variables
, 153

configurations
, 151

organizational capability configurations
, 152

use of e-HRM Software
, 154

theoretical and empirical background
, 140

e-HRM organizational capabilities
, 141–142

“Gestalts” alignment perspective
, 144

RBV theory
, 140–141

SHRM organizational capabilities
, 142

strategic alignment of IT
, 142–143

See also Small- to medium-sized enterprises (SME)

“Marker” variable
, 148

“Mass fashion”
, 70, 71

Measurement model assessment
, 154

AVE
, 155

PLS
, 154

reliability, validity, and intercorrelations of research constructs
, 157

test of research model
, 156

See also Research model—assessment

Measures
, 17–19, 120–121, 246

macro measures of system quality
, 100

objective SHRM performance
, 162

outcome
, 93

Microsoft Excel spreadsheet
, 96

MNCs. See Multinational corporations (MNCs)

Mobile applications
, 42, 203

“Moral courage”
, 289

Moral integrity, reliance on
, 290–291

Motivator-hygiene theory
, 226–227

Multi-level phenomenon
, 263, 264

Multidimensional framework of service innovation
, 36

Multinational corporations (MNCs)
, 174, 177

characteristics
, 176–183

consequences and impacts of e-HRM
, 189–190

CORE’s role in supporting business strategy
, 193

cost efficiency improvement
, 187

cost savings
, 190

global orientation improvement
, 187

HR service
, 190–191

HRM
, 174–175

impacts on different stakeholders
, 191

improving customer service and efficiency
, 187–188

LM
, 191–192

methods
, 183–185

motives

for e-HRM adoption
, 194

for introducing CORE
, 186

operational benefits and impacts of
, 194–195

practical implications
, 197

research limitations
, 196–197

stage for
, 175–176

stakeholders in MNC
, 193–194

strategic

e-HRM
, 175

HR role
, 188–189

impacts of e-HRM
, 195–196

potential of CORE
, 192–193

TM
, 192

Natural language processing techniques (NLP techniques)
, 63, 72, 80

Natural Language Toolkit (NLTK)
, 73

“Negativity bias”
, 293

Network-centric approach
, 244

Nexus of practices and material arrangements, e-HRM as
, 272

mangle of e-HRM
, 274–276

organisation of practice
, 273

NLP techniques. See Natural language processing techniques (NLP techniques)

NLTK. See Natural Language Toolkit (NLTK)

North American industrial products company
, 98–99

NVivo software package
, 210

Observability
, 35, 44, 50, 68, 75, 82

Online analytical processing tool (OLAP tool)
, 103–104

Online screening of candidates
, 294

Operational

goals
, 91–92, 203

objectives
, 265

perspective
, 88–89

Operationalization of research concepts
, 144

extant literature
, 146

firm’s e-HRM organizational capabilities
, 147

HR practices
, 146–147

HRM function
, 148

Oracle
, 61

HR analytics data sheet
, 61

PeopleSoft system
, 95

Organization(al)
, 102, 113, 298

attraction to organization as employer
, 120

capability configurations
, 152

breakdown of antecedent, control, and SHRM performance variables
, 153

use of e-HRM Software
, 154

context
, 12–14

culture
, 213

factors
, 9

growth
, 24

IT infrastructure capabilities
, 141

learning processes
, 277

organizational-level adoption theories
, 8–9

processes
, 277

protecting organizational reputation and brand
, 295–296

Participants
, 16–17, 118

“Partnership” approach
, 179

People & Strategy
, 75

Personnel Administration
, 318, 322, 326, 332, 333, 335

PLS
, 154, 158

Policies and processes, organizational perspective
, 102

Post-recruitment and selection concerns
, 295

HR risks
, 297–298

protecting organizational reputation and brand
, 295–296

social media competence
, 297

Practice theory
, 276

Pre-recruitment and selection issues
, 292

cyber-vetting or data mining applicants via social media
, 294–295

reputation management and employer branding
, 292–293

Predictive models
, 64

Project management
, 147, 186, 205, 278

Prospectors
, 146

Psychological empowerment
, 241

Radio frequency identification (RFID)
, 245

RBV. See Resource-based view (RBV)

Reactors
, 146

Realistic job previews
, 300

Recruitment process
, 110

Reductionism
, 266

Relational goals
, 91–92

Relational objectives
, 265

Relational ontology
, 271–272

Relative advantage
, 67–68

Reputation management
, 292–293, 300–301

Research model
, 144, 145

assessment
, 158

covariance-based techniques
, 158

test of research model
, 159

variance
, 160

See also Measurement model assessment

Research team
, 90

Resource-based view (RBV)
, 137, 140

theory
, 140–141

RFID. See Radio frequency identification (RFID)

SAM. See Strategic alignment model (SAM)

Scientific management
, 226

Service quality
, 93, 98, 100, 101

Shared performing
, 263–264

SHRM. See Society of Human Resource Management (SHRM); Strategic human resource management (SHRM)

Sierra-Cedar HR Systems Survey
, 72

Signalling theory
, 114, 129

SIM. See US Society for Information Management (SIM)

Six sigma approach
, 63

Small- to medium-sized enterprises (SMEs)
, 3, 4, 15, 138, 139, 158

implications for
, 25

SHRM performance of
, 166

taxonomic analysis of organizational capabilities of
, 151–154

vendor support
, 25–26

Smart Industry
, 222, 244–245

direct effects on Job Characteristics
, 247–250

as inspiration for configurational approach
, 251–252

job characteristics
, 258–259

as moderator
, 250–251

research in HRM field
, 222–223

drastic organisational changes
, 222–223

employment debate
, 224–226

JCM
, 228–244

job design
, 226–227, 245–247

method
, 227

“Smart”

industry as inspiration for configurational approach
, 251–252

smart-HRM
, 37

system
, 89

technologies
, 295

workforce management analytical systems
, 104

SMEs. See Small- to medium-sized enterprises (SMEs)

Snapchat
, 44

Social media
, 42, 110–112, 117

applications
, 43–44

browsing experience
, 129

impact of SNW features
, 113

legal and ethical guidelines
, 289–290

perceived SNW page attractiveness
, 120

perceived SNW page usability
, 120

post-recruitment and selection concerns
, 295–298

pre-recruitment and selection issues
, 292–295

recommendations for HR practitioners
, 299–302

reliance on moral integrity
, 290–291

time for critical reflection
, 302–303

Social media as recruitment tool

discussion
, 129

theoretical and managerial implications
, 129–130

job seekers
, 112–114

methodology
, 118

field survey
, 124–129

laboratory experiment
, 118–124

social networking websites
, 110–111

theoretical Framework
, 114–118

Social science theory
, 267

Social system
, 66

Social theory
, 269

Society of Human Resource Management (SHRM)
, 299

Sociomaterial phenomena
, 267

Sociomateriality in information systems research
, 267

emphasising role of human agency
, 268

ERP system
, 268–269

sociomateriality and agency
, 270–272

Software vendors
, 18

Sophisticated analytics
, 65

Spatial-temporal manifolds of human activity
, 276

S-shaped model
, 66

Standards
, 102

Strategic alignment model (SAM)
, 163

return to
, 164

Strategic e-HRM in MNC
, 175

characteristics
, 176

consequences and impact of e-HRM
, 178–179

motives for adopting
, 176–178

strategic potential of e-HRM
, 179–181

theoretical framework of study and summary of literature review
, 181–183

consequences and impacts of e-HRM
, 189

improving transparency
, 189–190

standardization and higher level of control
, 189

CORE’s role in supporting business strategy
, 193

cost efficiency improvement
, 187

cost savings
, 190

global orientation improvement
, 187

HR service
, 190–191

impacts on different stakeholders
, 191

improving customer service and efficiency
, 187–188

LM
, 191–192

methods
, 183

background information of case company
, 185

research approach, design, and methods
, 183–185

motives for e-HRM adoption
, 194

motives for introducing CORE
, 186

operational benefits and impacts of
, 194–195

practical implications
, 197

research limitations
, 196–197

stage for
, 175–176

stakeholders in MNC
, 193–194

strategic HR role
, 188–189

strategic impacts of e-HRM
, 195–196

strategic potential of CORE
, 192–193

TM
, 192

Strategic HR role
, 188–189

Strategic human resource management (SHRM)
, 138, 140

breakdown of antecedent, control, and SHRM performance variables
, 153

descriptive statistics
, 150

organizational capabilities
, 142

See also Electronic human resource management (e-HRM)

“Strengths-weaknesses-opportunities-threats” approach (SWOT approach)
, 164–165

Structural equation modeling
, 154

Structuration theory
, 264, 268, 270

SWOT approach. See “Strengths-weaknesses-opportunities-threats” approach (SWOT approach)

System dynamic model of innovation diffusion
, 81

System quality
, 93, 94, 97–98

recommendations
, 103–104

T&D. See Training and development (T&D)

TA. See Technology application (TA)

“Talent analytics”
, 64, 65

TAM. See Technology acceptance model (TAM)

Taxonomic analysis of organizational capabilities of SMEs
, 151

breakdown of antecedent, control, and SHRM performance variables
, 153

configurations
, 151

organizational capability configurations
, 152

use of e-HRM software
, 154, 155

Taxonomic statistical techniques
, 143

Technical system dimension
, 141

Technological determinism
, 269

Technology
, 102, 211

context
, 10–12

technological factors
, 8, 9, 11

technology-mediated networks
, 264

Technology acceptance model (TAM)
, 6–7, 91

Technology adoption model. See Technology acceptance model (TAM)

Technology application (TA)
, 206

Technology infrastructure (TI)
, 206

Technology Proponent
, 323

Technology–organization–environment model (TOE model)
, 9

environmental context
, 14–16

framework
, 10

organization context
, 12–14

technology context
, 10–12

Theory of planned behavior (TPB)
, 7, 91

TI. See Technology infrastructure (TI)

Time, HR analytics
, 66

Time for critical reflection
, 302–303

TM. See Top management (TM)

TOE model. See Technology–organization–environment model (TOE model)

Tokenization
, 72

Top management (TM)
, 183, 192

Top Management Support
, 18, 24

TPB. See Theory of planned behavior (TPB)

Training and development (T&D)
, 37

Transcribed interviews
, 210

Transformational

goals
, 92

objectives
, 265

perspective
, 88, 89

Transparency
, 189–190

Triability
, 68

Triangulation
, 166, 183

Twitter
, 38–39, 43–44, 111

Unified theory of acceptance and use of technology (UTAUT)
, 8, 91

Upward spiral
, 224

US Small Business Administration
, 16

US Society for Information Management (SIM)
, 205

Variance
, 160

Vault
, 293

Virtual HRM
, 263

Voluntarism in
, 268, 269

Web 1.0
, 36–37, 45

domain
, 117–118

recruitment methods
, 115

Web 2.0
, 36–37, 45, 116–117

e-recruitment
, 130

on recruiters
, 116–117

Web 3.0
, 36, 37, 45

Web-based

HRM
, 263–264

services
, 36

technology
, 138

Wireless communication
, 245

Workforce Analytics
, 64n1, 72, 79, 89

Workforce management

analyses
, 103

data quality in
, 102–103

decision-making analysis
, 101

“smart” system for
, 89, 98–99

tools
, 88

YouTube
, 43–45