Index

Citation

(2023), "Index", Tyagi, P., Chilamkurti, N., Grima, S., Sood, K. and Balusamy, B. (Ed.) The Adoption and Effect of Artificial Intelligence on Human Resources Management, Part A (Emerald Studies in Finance, Insurance, and Risk Management), Emerald Publishing Limited, Leeds, pp. 283-290. https://doi.org/10.1108/978-1-80382-027-920231014

Publisher

:

Emerald Publishing Limited

Copyright © 2023 Pallavi Tyagi, Naveen Chilamkurti, Simon Grima, Kiran Sood and Balamurugan Balusamy

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INDEX

Accuracy

, 208–209

Active sensing

, 58

Adaboost

, 203, 205

Adequate and fair compensation

, 22–23

Alexa

, 133

Ambit

, 143

Amy

, 219

Analytics (see also People analytics)

, 160–161

Appcast

, 32

Artificial intelligence (AI)

, 2–5, 48, 61, 72, 162, 184, 198, 217–218

AI-assisted detection and IoT application for employee engagement

, 79

AI-connected consultation services and remote monitoring services delivered through AI devices

, 53–54

AI-powered virtual learning assistants

, 29

algorithms

, 112

artificial intelligence-aided human resource management

, 108

artificial intelligence-based people analytics transforming human resource management practices

, 230

assist

, 56–58, 63–64

challenges of AI application in HRM

, 111–114

challenges of AI-enabled people analytics

, 241–242

computer applications

, 3

conceptual model for sustainable use of AI in HRM

, 114–117

confluence of AI and HRM

, 109–111

creating diverse team culture using

, 33–34

effect

, 3

findings

, 114–117, 240–241

for FWS model

, 189–191

HRM practices post-pandemic and role

, 128–143

HRM with

, 3

impact of IOT and AI on healthcare industry

, 89–90

method

, 64–66

methodology

, 109, 232–233

objective

, 231

opportunities for AI in L&D

, 219–223

potential to aid

, 60, 62–63

principal use in virtual health care

, 53

raters

, 168

scope

, 231–232

theoretical background and literature review

, 234–239

use of

, 125

Association of Business Schools (ABS)

, 20, 126

Asynchronous interview

, 168

Attrition

, 252–253

Attrition Hassle in Indian IT Industry

, 257

Augmented intelligence

, 237–238

Augmented Reality (AR)

, 27

Australian Business Deans Council (ABCD)

, 20

Automated recruitment techniques

, 162–169

Automated screening of resumes

, 33

Automation

, 161, 238

Autonomy

, 167

Belongco

, 133

Best Buy

, 37

Big data

, 88–89

Brazen

, 163

Business expertise

, 187

Business intelligence processor

, 238

Business Source Ultimate (EBSCO)

, 20, 127, 218

Capgemini’s Common HR Dashboard

, 262

Career growth

, 26

Case studies

, 165

Challenges

, 109

Charlson score

, 56

Chatbots

, 25, 145, 163

chatbots-based learning

, 222–223

Chloroquine

, 60

Churn rate

, 257–258

Cisco’s HR Advanced Analytics Group

, 262–263

Clara

, 219

Classification algorithms

, 203–205

Clinical Frailty Score

, 56

Clinically relevant interface

, 65

Cloud computing

, 88

Clustering

, 249

Cognitive learning

, 108

Collaborative robots (cobots)

, 238

Commitment

, 75

Communication

, 34–36

systems

, 6

Compensation and providing benefits

, 193

Competence

, 167

Computational games

, 164

Conceptualisation

, 19

Consequences of HRM digitalisation

, 102–103

Consistency

, 188

Consistent feedback

, 221

Context awareness

, 178

Contingent workforce management through AI

, 130–134

Continued growth, opportunity for

, 26

Coronavirus

, 48, 51

Corporate social responsibility (CSR)

, 31

Coursera

, 143

COVID-19

, 124

epidemic

, 50, 52

individuals

, 57

pandemic

, 24, 50

Cox proportional hazards model

, 56

Critical thinking

, 188

Data

analysis

, 8

analytics

, 125–126, 191

extraction

, 179

inquisitiveness

, 186–187

IT approaches

, 87–88

privacy

, 177

security

, 79

Decision trees

, 204

Decision-making

, 108

Deep Blue computer program

, 199

Deep learning

, 108, 160

Deeplearning. ai

, 143

Dell

, 257

Descriptive analytics

, 249

Digital biomarker applications

, 25

Digital era

, 100

Digital marketing

, 179

Digital technology

, 83

Digital transformation

, 100

Digitalisation

, 100

consequences of HRM

, 102–103

factors affecting digitalisation of HR

, 101–102

of health care and prominent figures

, 86–87

review of literature

, 100–101

Diversity and inclusion (D&I)

, 31–34

accurate D&I initiatives

, 34

Duolingo

, 219

e-HRM

, 113

Eden Workplace

, 134

Educational games

, 164

Eightfold

, 163

Eightfold AI

, 134

Electronic Health Records (EHRs)

, 55

Electronic performance monitoring

, 126

Elsevier

, 162

Emerald

, 162

Emotional and social intelligence (ESI)

, 188

and AI

, 181–183

in AI for HRM

, 185–186

methodology

, 184

and organisational practices

, 180–183

purpose

, 183

Emotional intelligence (EI)

, 180

Employee attrition

, 246

Employee development

, 216

Employee engagement

, 16

conceptual framework

, 37–39

drivers of employee engagement in new normal in context of AI

, 21–36

future work

, 40–41

increasing role of

, 140–141

managerial implication

, 40

outcomes of employee engagement in new normal in context of AI

, 36–37

research methodology

, 19–21

survey generator

, 238

theoretical framework of study

, 19

working mode pre-covid-19

, 17

Employee personal attributes

, 271

Employee pulse surveys

, 25–26

Employee relations

, 192–193

Employee retention

, 257–258

Employee salary-related attributes

, 272

Employee turnover

, 263

Employee well-being

, 25, 37

Employee wellness

, 25

Employee work-related attributes

, 271–272

Engazify

, 219

Entelo

, 132

Espressive

, 163

Euclidean distance

, 204

Event

, 157

External hiring

, 29

F-Measure

, 208–209

Facebook

, 158, 217

Federated learning

, 114

Feedback

, 35

Fieldglass

, 134

FitBit

, 25

Flight Risk programme

, 260

Fourth Industrial Revolution (4IR)

, 3

Future work skill (FWS)

, 177

and AI

, 179–180

in AI for HRM

, 184–185

and global scenario

, 177–179

methodology

, 184

purpose

, 183

Games

, 163–167

Gamification

, 163–167

Gen X

, 222

Gen Y

, 222

Gen Z

, 222

General Management (GM)

, 127

Generation Z

, 165

Genpact’s FLM Surveys & Overall Performance Rankings

, 260

Goal achievement

, 166

Google

, 37, 217, 230–231, 249, 258–260

Google Scholar

, 162, 218

Great Resignation age (see Post-pandemic era)

Green HRM process

, 7

Grid computing

, 88

Guider

, 224

Harvard Business School (HBS)

, 31

Health care

, 50

AI-connected consultation services and remote monitoring services delivered through AI devices

, 53–54

AI’s principal use in virtual health care

, 53

background of study

, 50–51

clinical studies

, 62

customised programmes for patient care and management

, 58–59

diagnosis

, 54

differing policies for diagnosing and treating

, 61

effective policy reforms

, 61–62

EHRs

, 55

follow-up with patient

, 53

highly prioritised patient scheduling

, 55

issues in healthcare sector during COVID-19

, 52

methods

, 51

participation in formulation of policy

, 55

personnel

, 52

policy advice

, 60–61

realistic difficulties in implementation of efficient healthcare resource management

, 51–52

recommendation of AI approaches for implementing in health sector

, 58

research challenges

, 63

shortage of medical resources

, 53

uncertainty

, 62

Health care, social care, and well-being (HSCWB)

, 87

Health Company

, 73

Health maintenance organisations (HMOs)

, 65

Health Technology Performance Assessment (HTPA)

, 85

Healthcare employees

benefits and well-being

, 84

effectiveness of theory-based method

, 75

future research directions

, 91–92

improve healthcare professional engagement through IOT

, 83–89

impact of IOT and AI on healthcare industry

, 89–90

methodology

, 74–75

motivating and engaging

, 76–77

selection of articles

, 74

theoretical perspective for literature review

, 75–83

Healthcare Internet of things (H-IoT)

, 87

Healthcare sector

, 84

Healthcare technology

, 84–85

Hebbian Learning

, 198

Hewlett-Packard (HP)

, 257–260

Hire Safe

, 133

Hire Value

, 132–133

HireVue

, 163

Human capacities, immediate opportunity to use and develop

, 28

Human capital management (HCM)

, 2

Human resource development (HRD)

, 4

Human resource management (HRM)

, 2, 20, 72, 124, 161, 176, 199, 218, 246

AI

, 2–3

AI and FWS model for

, 189–191

with AI and ML

, 3

challenges of AI application in

, 111–114

conceptual model for sustainable use of AI in

, 114–117

consequences of HRM digitalisation

, 102–103

critical roles

, 75–76

data analysis

, 8

ESI in AI for

, 185–186

functions

, 189

FWS in AI for

, 184–185

literature review

, 3–7

machine learning

, 3

objectives of this study

, 7

practices post-pandemic and role of AI

, 128–143

research methodology

, 7

sampling

, 7–8

Human resourceanalysis (HRA)

, 5

Human resources (HR)

, 100, 108, 191

analytical tools

, 248–249

factors affecting digitalisation of

, 101–102

functionalities

, 108

functions

, 6

HR/people analytics categories

, 249

workers

, 176

Human Resources Information Systems (HRIS)

, 73

Humanly

, 163

IBM

, 198–199, 217, 257

comprehensive analysis and visualisation

, 209–210

data preparation

, 207–208

dataset

, 205–207

identifying factors affecting attrition

, 210–212

literature review

, 200–202

methodology

, 202–205

metrics

, 208–209

objectives

, 200

result and analysis

, 205–212

Watson

, 86

Ideal

, 163

IEEE

, 162

Immersive learning

, 143

India’s Vishwas

, 133

Informatics

, 84–85

Information and communication technology (ICT)

, 75

Information and techniques

, 248–249

Information Management (IM)

, 127

Information retrieval process

, 249

Information technology (IT)

, 4, 75, 237

Infosys’s Advanced Analytics

, 262

Intelligent Agents

, 221

Intelligent tutor systems

, 222

Internal job mobility

, 29

International Business (IB)

, 127

International HRM (IHRM)

, 236

Internet of Things (IoT)

, 50, 72, 236

improve healthcare professional engagement through

, 83–89

impact of IOT and AI on healthcare industry

, 89–90

technology and packages

, 73

Involuntary attrition

, 253

IPEVO Annotator

, 140

Jawbone

, 25

Job analysis and design

, 77

Job seekers

, 166

JSTOR database

, 162

Juniper Network

, 230–231, 259

Justice

, 75

theory

, 75

K-nearest neighbours (KNN)

, 203–204

Knowledge, skills, and abilities (KSA)

, 219

Knowledge management (KM)

, 220–221

Knowledge repositories

, 221

Knowledge sharing

, 221

Knowledge strategy

, 187

Koru

, 133

Labour market development

, 179

Lattice

, 37

Learning

for diverse pool of learners

, 222

gaps

, 28

Learning and development plan (L&D plan)

, 4, 26–27

Legal and ethical functions of HRM

, 77

Limnu

, 140

Linkedln

, 158

Literature review of healthcare employee engagement

, 73

Lockdown

, 124

Logistic regression (LR)

, 203, 205

Lopinavir/Ritonavir

, 60

Machine learning (ML)

, 3, 5, 49, 73, 108, 160, 198, 230

algorithms

, 49

HRM with

, 3

Manhattan distance

, 204

Marico Kaya Ltd

, 261–262

Market automation

, 179

McKinsey ’Machine Learning Strategy

, 261

Merit management

, 6

Metrics

, 208–209

Microsoft

, 230, 257

Microsoft Excel

, 248

MiFit

, 25

Mindfulness

, 25

through AI

, 134–138

Mindtree

, 261

Minitab

, 260–261

Minkowski distance

, 204

Miro

, 140

Multiple Choice Questions

, 165

MURAL

, 140

Mya

, 163

MyAlly

, 33

Naive Bayes

, 203–204

Nation-wide network

, 65

Natural language processing

, 26, 160

Nestlé

, 260–261

Network analysis

, 26

Neural network-based system

, 56

New skills

, 26

Nielsen’s ’predictive risk model

, 262

Niles

, 219

Obie

, 219

Olivia

, 163

Onboarding

, 6, 128–129

Open. ai

, 143

Oracle Sysco

, 37

Organisational development

, 238

Organisational factors

, 101–102

Outsourcing

, 158

Pandemic

, 17, 124

Paradigm shift

, 125

future direction

, 146

HRM practices post-pandemic and role of AI

, 128–143

managerial implication

, 145–146

proposed conceptual framework

, 143–144

research methodology

, 126–128

Partner Safe

, 133

Peer to peer/collaborative learning

, 28

People analytics

, 161, 236, 239, 246, 254, 257

attrition

, 252–253

copious companies

, 258–259

data points and tools for analysis and results

, 259–263

domain

, 246–247

essential components

, 248–249

evolution

, 247–248

literature review

, 257–265

major/common triggering attribute

, 254

methodology

, 265–277

organisations

, 251–252, 254

recent trends in

, 250–251

results

, 277–278

People factors

, 102

People Operations

, 231

People perception

, 239

Performance management (PM) (see also Human resource management (HRM))

, 73, 19

and promotion

, 129

Person-specific user interface

, 65

Personalised learning

, 221

plans

, 28–29

Point cards

, 164

Post-pandemic era

, 24

Practical training

, 78

Precision

, 208–209

Predictive analysis

, 255–257

Prejudices

, 32

Prescriptive analysis

, 249

Primary health care (PHC)

, 90

Processability

, 55

Productivity

, 74, 77

productivity/performance-based compensation

, 23

Project Oxygen

, 260

Proquest

, 162

Public Health England

, 65

Pymetrics

, 133

Python

, 143

Quality of work life

, 21–31

Quarantine

, 124

Quinyx

, 134

R-Studio

, 248

Random forest (RF)

, 203–205

Randomised clinical trials (RCTs)

, 49, 62

Recall

, 208–209

Recognition

, 23–24

Recruitment

, 32, 157, 251–252

analytics

, 160–161

automated recruitment techniques

, 162–169

future studies

, 170

methodology

, 162

process

, 4

Technology Organization Environment theory

, 160–162

Recruitment and selection process (R&S process)

, 9, 128

development

, 191–192

Remdesivir

, 60

Remote workforce management

, 128–130

Remote working

, 124–125

Reskilling

, 27

workforce towards new competencies

, 141–143

Resume parsing

, 33

Resume screening

, 162, 168–169

using ML algorithms

, 33

Return of investment (ROI)

, 2, 179

Rewards

, 23–24

Risks and identify challenges to organisational functions

, 78–79

Robotics

, 238

Royal Dutch Shell

, 230

Safe and healthy working conditions

, 24

Sampling

, 7–8

Satisfaction

, 75

Scheduling Software

, 134

Science Direct

, 20, 127

Scoping literature review method

, 162

Scopus

, 20, 218

Screening

, 32–34

Security, opportunity for

, 26

Self-determination theory (SDT)

, 75

Self-help

, 25

Self-management

, 25

Self-motivation

, 166

7shifts

, 134

Skillate

, 132

Skills

, 186

skills-based review

, 23

Slackbot buddies

, 140

Smart candidate ranker

, 238

Smart human resource management technology (SHRMT)

, 126

Smash fly

, 163

SnackNation

, 25

Social capital through AI

, 138–140

Social distancing

, 124

Social intelligence (SI)

, 180

Social isolation

, 18, 39

Social media

, 156

Social networking sites (SNS)

, 156, 158

Social relevance of work life

, 31

Social sciences citation index (SSCI)

, 20, 126

Sophia (AI robot)

, 6

Sourcing

, 32

Staffing

, 77

Starbucks Reinforcement Learning Technology

, 263

Statistical learning

, 108

Stormboard

, 140

Strategic games

, 164

Strategic human resource management (SHRM)

, 3, 238

Strategic plan

, 85–86

Structured learning

, 28

Structured resume analyser

, 238

Support vector machines (SVM)

, 203, 205

Symphony Talent

, 163

Synchronous interview

, 168

Sysco

, 261

Talent management

, 130

Talespin

, 143

Task automation

, 178

Technical feasibility approach

, 75

Technological factors

, 101

Technological strategies

, 83

Technology acceptance model

, 75

Technology Enabled Treatment Services (TECS)

, 65

Technology invention

, 85

Technology Organization Environment theory

, 160–162

TensorFlow

, 143

Textio

, 132

Theory-based method, effectiveness of

, 75–76

Time Tracking Software

, 134

Toggl

, 37

Traditional analytics

, 161

Traditional HRM to AI integration in healthcare industry

, 86–89

Train Safe

, 133

Training and development

, 129–130, 192

Transfer learning

, 50, 64

Transferability

, 55

Trend analyses

, 179

Trust

, 75

Turnover

, 251

intentions

, 255

modelling

, 261

Udacity

, 143

Unconscious biases

, 32

Upskilling workforce towards new competencies

, 141–143

Vendor Management System (VMS)

, 132

Vervoe

, 33

VirBELA

, 140

Virtual Assessment Centers (VAC)

, 27

Virtual environment interviews

, 167–168

Virtual health care, AI’s principal use in

, 53

Virtual interviews

, 162

Virtual mentoring

, 222

Virtual Personal Mentor

, 222

Virtual Reality (VR)

, 27, 219

Voluntary attrition

, 253

Wade

, 132, 163

Wal-Mart

, 230–231, 259, 262

Wearable technology

, 25

Web of Science

, 20

Wendy

, 132, 163

Woebot

, 25

Work and total life space

, 30

Work Market

, 134

Worker attrition

, 263–265

WorkJam

, 133

Workplace L&D

, 216

discussion and implications

, 223–224

limitations and future scope of research

, 224

literature review

, 217–218

methodology

, 218–219

opportunities for AI in

, 219–223

World Economic Forum (WEF)

, 142

World Wide Web (WWW)

, 158

Xerox Corporation

, 260

XG Boost (XGB)

, 203, 205

XOR

, 163

Your learning

, 224