ABC India Ltd.

, 224, 227, 229–230

Accountability

, 2, 99–100

Adaptability

, 82–83, 290

Adapting

, 23–24

Additive manufacturing

, 120, 277

Additive Ratio Assessment (ARAS)

, 208

Advanced analytics

, 16

Agri-food industry

, 134–135

archiving of detailed records for future use

, 139

context, data collection and description

, 136

definition of scope of study

, 135

evaluation and comparison of model formalization and validation

, 137–138

method and results peer review

, 139

model selection and testing

, 139

selection of most relevant methods/tools

, 136–137

significant aspects and impacts

, 137

AlkylVM

, 70

Allcargo Logistics Ltd.

, 224, 227, 229–230

Analytic Hierarchy Process (AHP)

, 208, 261–262

Analytic Network Process (ANP)

, 208

Artificial intelligence (AI)

, 3, 16, 32, 35, 71, 119, 127–128, 158, 188, 221, 256, 276–277, 283–284

for smart decision-making

, 6

via supply chain

, 128–129

Artificial neural networks (ANNs)

, 256

Auditing in digital age

, 187–188

Auditors, recommendations for

, 195

Augmented Dickey–Fuller test (ADF test)

, 223

Augmented reality (AR)

, 256, 277

Automation

, 35, 41–42, 280

Autonomous robots

, 256

Average Variance Extracted (AVE)

, 88

Barriers

, 54

Behavioral intentions (BIs)

, 82–83

and adoption of blockchain in supply chain

, 86

EE and

, 84–85

PE and

, 84

Best-Worst Method (BWM)

, 208, 238–239, 242–243, 259

Besu

, 71

Bi-objective optimization model

, 261–262

Big data (BD)

, 158, 221, 277

analytics

, 35, 120, 172

Blockchain

, 11, 67–68, 80, 82, 172, 188

adoption

, 72

blockchain-enabled smart contracts technology trends

, 69–70

methodology

, 68

regulatory and legal landscape of smart contracts

, 71–72

systematic search process for literature review

, 69

technology challenges of smart contracts in liner shipping industry

, 72–74

technology trends of smart contracts in liner shipping

, 70–71

Blockchain technology (BT)

, 80, 158

Bluedart

, 229–230

BMW Group Middle East–Automotive Sector

, 151–152

critical analysis and challenges

, 151–152

Bootstrapping

, 306

Businesses

, 144, 173–174

case issues

, 123

operation

, 298

privacy concerns

, 123

Carbon dioxide emissions (CO₂ emissions)

, 50

CargoX

, 71

Causal diagram

, 246–248

Challenges

, 238

Chartered logistic Ltd.

, 227

Circular economy (CE)

, 157–159, 172, 208

opportunities for

, 165

Closed-Loop Supply Chain (CLSC)

, 145–148

Closed-loop systems

, 152

Cloud computing

, 221, 277

Cloud connection

, 119

Cloud service (CS)

, 163–164

CloudMQTT

, 102–103

Collaboration

, 4

among stakeholders

, 44

Collaborative governance

, 21

Common method bias (CMB)

, 303

Compatibility challenges

, 106–107

Competitive advantage

, 80

Complex Proportional Assessment of Alternatives (COPRAS)

, 208

Compliance

, 40–41

Composite Reliability (CR)

, 88

“Consortium blockchain” architecture

, 81

Conventional SCM

, 100–101

Corona

, 218

Corporate social responsibility (CSR)

, 260–261

Corporate sustainable management activities (CSMA)

, 260–261

Corporations

, 102–103

Cost reduction

, 74–75

Cost-effective operations

, 75

COVID-19

, 219

Cronbach’s Alpha, rho_A

, 88

Cryptographic techniques

, 67–68

Cultural diversity

, 19

Customer satisfaction

, 256

application of proposed approach for supplier assessment

, 264–266

literature review

, 258–262

problem description

, 262–263

research methodology

, 263–264

result discussion and managerial implications

, 266–269

Cyber dependence

, 202

Cyber-physical systems (CPS)

, 1–2, 256

Cybersecurity

, 277

issues

, 121–122

risks

, 42

DAO

, 70

Data analytics

, 3–4, 122, 188

for decision-making

, 104–105

Data magic

, 4

insights from

, 5

Data quality

, 123

Data security

concerns

, 122–123

and privacy issues

, 106

Data-driven decision-making for sustainability

, 4–5

Decentralization

, 83

Decentralized ledger technologies (DLTs)

, 283, 288

Decision making

, 42–43

Decision-makers (DMs)

, 258

Decision-Making Trial and Evaluation Laboratory (DEMATEL)

, 208, 238–239, 243, 248, 261–262

direct relation matrix

, 245

final output and causal diagram

, 246–248

normalized direct-relation matrix

, 246

total relation matrix

, 246

DELIVER

, 71

Dell Middle East–Electronics Sector

, 148–151

critical analysis and challenges

, 149–151

Demographics

, 87

Descriptive analysis

, 160–162

Digital

, 202

Digital age

, 276

Digital innovations

, 302

Digital technologies (DTs)

, 32, 173, 238

Digital transformation

, 194, 218, 298–300

analysis results

, 303–306

effect of digital transformation on sustainability

, 301–302

enablers of digital transformation in TOE framework

, 300–301

implications

, 306–309

research gap and rationale for study

, 298–299

research methodology

, 302–303

Digital twins (DT)

, 120, 163–164

Digitalization

, 3–4, 165, 218, 238

challenges and risks of adopting

, 6–7, 10–11

creating transparent and sustainable supply chains

, 4

Digitization

, 72, 276

Direct relation matrix

, 245

Discriminant validity

, 90

Dynamic capabilities (DCs)

, 172, 174

Dynamic capabilities view (DCV)

, 172–173

Economic dimensions

, 17

decentralized ledger technologies

, 288

ethical business practices

, 287–288

supply chain transparency

, 288–289

of sustainability

, 287–289

Economic growth

, 37

Economic performance

, 81

Economic sustainability

, 22–23

opportunities for

, 163–164

Economy aspects

, 39–40

Edge computing for real-time decision-making

, 6

Edge processing

, 6

Effectiveness

, 54

Efficiency

, 2–3, 5–6

Effort Expectancy (EE)

, 84–85

EGARCH (1) model

, 1, 223–224

Emergency backup facilities

, 220–221

Emergency logistics systems

, 220–221

Employees, recommendations for

, 195–196

Employment creation

, 37

End-of-life (EOL)

, 144

Environment aspects

, 40–41

Environmental constraints

, 128, 136–137

Environmental dimensions

, 17

predictive modelling

, 285

real-time data analytics

, 285

resource optimization

, 285

of sustainability

, 285

Environmental factors

, 32, 308

Environmental performance

, 81

Environmental Performance Index (EPI)

, 173–174

Environmental sustainability

, 23

opportunities for

, 164

Esser shipping

, 228

Ethical AI and decision-making

, 291–292

Ethical and legal dimension

, 17

Ethical business practices

, 287–288

Ethical concerns

, 21

Ethical considerations

, 42–43

Ethical sustainability

, 21–22

European Union (EU)

, 280

External validity

, 92

Facilitating conditions (FC)

, 83, 85–86

Fairness

, 291

Firms

, 175

Fish canning industry

, 134–135

5G for connectivity and efficiency

, 5–6

Flint

, 69

Fourth Industrial Revolution (see Industry 4.0 (IR 4.0))

Future research scope

, 100

Fuzzy best worst method (FBWM)

, 261–262

Fuzzy inference system (FIS)

, 259

Fuzzy TOPSIS with Z-numbers

, 264

GKW

, 228

Global challenges

, 32

Global projects, interactions with

, 44–45

Global Shared Container Platform (GSCP)

, 71

Global Shipping Business Network (GSBN)

, 70–71

Globalization

, 81

Green supply chain (GSC)

, 127–128, 276–277, 284–285

approach for model application

, 129–134

archiving of detailed records for future use

, 133–134

artificial intelligence via supply chain

, 128–129

case study

, 134–139

context, data collection and description

, 131

definition of scope of study

, 130–131

evaluation and comparison of model formalization and simulation

, 132–133

implications

, 139–140

literature review

, 128–129

method and results peer review

, 134

model selection and testing

, 133

modelling

, 128

perspectives

, 140

selection of most relevant methods/tools

, 131–132

significant aspects and impacts

, 132

Greenhouse gas (GHG) emissions

, 162

Grey System Theory

, 261–262

Hawk

, 70

Horizontal system integration

, 277

Human dimensions of sustainability

, 289–292

ethical AI and decision-making

, 291–292

human–machine collaboration

, 290–291

workforce reskilling and upskilling

, 289–290

Human rights

, 86

Human-centric approach

, 19

challenges

, 23–24

data collection

, 18

economic sustainability

, 22–23

environmental sustainability

, 23

ethical and legal sustainability

, 21–22

Industry 4.0

, 16

integration of IR 4.0 technology and sustainability dimension

, 19

methodology

, 18

objectives

, 18

review of literature

, 16–18

social sustainability

, 19–21

synthesizing analysis

, 26

Human–machine collaboration

, 290–291

Human–Machine interaction (HMI)

, 122

Hyperledger Fabric

, 71

Implementation costs

, 107

Inclusivity

, 20–21

Individual empowerment

, 290

Industrial Internet of Things (IIOT)

, 118

Industry 4.0 (IR 4.0) (see also Supply chain 4.0 (SC 4.0))

, 1–2, 16, 32, 34, 36, 68, 116–117, 144–145, 159, 172, 175–176, 187–188, 202, 238, 256, 276–277

artificial intelligence

, 35

automation

, 35

big data analytics

, 35

integration of IR 4.0 technology and sustainability dimension

, 19

intersection of SDGs and

, 36–41

IoT

, 34–35

New-Age Digitalization

, 3

promise of

, 16

research issues in

, 122–123

and SA8000 audit

, 191–194

and SA8000 compliance

, 190–191

smart manufacturing and resource efficiency

, 3–11

on supply chain sustainability

, 221

sustainability

, 2–3

and technological pillars

, 277–278

technologies and sustainability

, 283–285

transformation of industries

, 35–36

Innovation

, 37

International Labor Organization (ILO) treaty

, 188–189

Internet of Things (IoT)

, 1–2, 16, 32, 34–35, 98, 116, 158, 172, 221, 256, 276–277, 284

benefits in IoT-SCM integration

, 104–106

challenges and concerns in IoT-SCM integration

, 106–108

devices

, 188

enhanced inventory management through

, 102–103

future scope

, 109–110

impact of IoT on SCV

, 101–102

IoT-enabled supply chain optimization

, 103

literature review

, 100–103

outcomes and managerial implications

, 108–109

sensors

, 98–99, 102–103, 149, 151

Interoperability challenges

, 106–107

Inventory control

, 98

Investors

, 218, 231

Jarque Bera test

, 224

Job displacement

, 41–42, 286

Justice

, 41

Key performance indicators (KPIs)

, 203

Kurtosis

, 224

Labor standards

, 189

Lancer container lines

, 228

Latent semantic analysis (LSA)

, 277–278

Legal

, 18

Legal challenges

, 43

Legal landscape

, 68

Legal sustainability

, 21–22

Legislation

, 43

Lex Mercatoria

, 72

Liner shipping

technology challenges of smart contracts in

, 72–74

technology trends of smart contracts in

, 70–71

Literature analysis

, 51–54

Literature review

, 166

Logistics (see also Reverse logistics)

, 80, 98, 218

industry

, 218

logistics 4.0

, 145–147

Loyalty

, 256

Machine learning (ML)

, 71, 102–103, 158

Maersk

, 73–74

Mahindra logistics

, 228

Managerial implications

, 45–46

Managers, recommendations for

, 194

Maritime sector

, 67–68

Measurement model assessment

, 88–89

Message queue telemetry transport (MQTT) protocol

, 102–103

Modelling

, 127–128

Multi-Agent Systems (MASs)

, 259

Multi-Attribute Relative Closeness Sorting (MARCOS)

, 208

Multi-criteria approaches for supplier performance evaluation

, 261–262

Multi-criteria decision-making (MCDM)

, 202, 258

problems, methods and applications

, 208–210

Multi-echelon supply chain model

, 81

Multinational company (MNC)

, 189–190

Navkar Corporation Ltd.

, 229–230

Neural Network

, 261–262

New-Age Digital Revolution

, 3

New-Age Digitalization

, 3

New-age technologies

conceptualizing relationship

, 282–283

economic dimensions of sustainability

, 287–289

environmental dimensions of sustainability

, 285

human dimensions of sustainability

, 289–292

industry 4.0 technologies and sustainability

, 283–285

literature review

, 277–282

practical implications, limitations and future research directions

, 292–293

social implications of industry 4.0

, 286–287

theoretical framework

, 282–283

Non-Fungible Tokens (NFTs)

, 70

Normalized direct-relation matrix

, 246

Operational efficiency

, 74, 166

Operations

, 6, 300

Opportunities of SC4.0

, 158

Optimization

, 69–70

Ordinal Priority Approach (OPA)

, 208

Organizational

, 248, 250

Organizational resilience

, 290

Original equipment manufacturer (OEM)

, 151

Partial Least Square Structural Equation Modelling (PLS-SEM) Approach

, 303

Patel integrated logistics ltd

, 227–228

Performance evaluation

, 257

Performance Expectancy (PE)

, 84

Performance indicators

, 98

Performance optimization

, 69–70

Portfolio

, 218

Precision

, 5

Predictive modelling

, 285

Predictive relevance

, 92

Preference-Ranking Organization Method for Enrichment of Evaluation (PROMETHEE)

, 261–262

Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA)

, 206

Privacy concerns

, 123

Proactivity

, 5

Production

, 32

Productivity

, 2, 173, 286

Profitable returns

, 2–3

Proposition development

, 178–179

moderating role of value chain

, 178–179

relationship between DC and SC sustainability

, 178

relationship between SC sustainability and I4.0

, 178

Radio frequency identification tags (RFID tags)

, 98–99, 102–103

Real-time data analytics

, 285

Real-time monitoring and tracking

, 104

Real-time visibility

, 4

Reduce, redesign, reuse, recover, remanufacture and recycle framework (6R framework)

, 283

Reduce, reuse and recycle (3R) approach

, 283

Regulatory frameworks

, 24, 289

Research contribution

, 262

Research questions (RQs)

, 203

identifying

, 204

keywords for

, 205

Resilience in supply chain system

, 220–221

Resource efficiency

, 3–11

Resource management

, 33

Resource optimization

, 285

Resource use

, 5

Resource utilization

, 34

Resource-based view (RBV)

, 172–173

Resource-efficient manufacturing process

, 145

Retail sector

, 81

Retailers

, 81, 263

Return on investment

, 107

Reverse logistics

, 144–145

conceptual framework of sustainable reverse logistics transformation in

, 148

reverse logistics 4.0

, 145–147

Risks

, 41–43

Robotic process automation (RPA)

, 119–120

Robotics

, 16, 119–120

Role of Industry 4.0

, 32–33

SA8000 auditing framework

, 188, 194

challenges and solutions

, 193

industry 4.0 and SA8000 audit

, 191–194

industry 4.0 and SA8000 compliance

, 190–191

recommendations

, 194–196

standard

, 188–190

SA8000 compliance

, 190–191

Safety

, 72

Science-Technology Scenario in Industry 4.0 (STS-S4.0)

, 281

Scilla

, 69

Scoping reviews

, 204

charting data

, 206–207

identification of relevant studies

, 204

identifying RQs

, 204

methodology

, 204–207

results

, 208–209

study selection

, 206

Scopus

, 204

Security optimization

, 69–70

Self-directed robots

, 277

Sensors/actuators

, 123

Service Level Agreements (SLAs)

, 70

Shipping

, 67–68

Silsal technology

, 71

Simulation

, 277

Skewness

, 224

Skilled workforce and training requirements

, 108

SmaCoNat

, 69

Small-and medium-sized Enterprises (SMEs)

, 173–174, 297–298

Smart contracts

, 69–70

regulatory and legal landscape of

, 71–72

Smart factories

, 2

Smart manufacturing (SM)

, 3, 11, 116–117, 283

from business perspective

, 118–120

enabling technologies for

, 118–120

implication

, 124

research issues in

, 122–123

technological requirements for adoption of SM in business operations

, 118

Smart Manufacturing System (SMS)

, 117, 121–122

challenges

, 121–122

principles

, 121–122

requirements for

, 119

Smart technologies

, 163–164

convergence

, 2

SmartBillions

, 70

Snowmen logistics

, 227, 229–230

Social Accountability International (SAI)

, 188–189

Social cognitive theory (SCT)

, 82–83

Social dimension

, 17

Social distancing

, 220–221

Social implications of industry 4.0

, 286–287

job displacement

, 286

societal well-being

, 287

workforce automation

, 286

Social Influence (SI)

, 85

Social performance

, 81

Social structures

, 19

Social sustainability

, 19–21

opportunities for

, 164–165

Societal well-being

, 287

Society aspects

, 37–39

Socio economic equity issues

, 42

Socio-ecological expectations

, 258

Socioeconomic inequality

, 202

Stakeholders

, 5, 44, 86

Standard/interfaces

, 122

Standardized root mean square residual (SRMR)

, 305–306

Streamlined logistics

, 105

Structural equation modeling (SEM)

, 89

Structural model assessment

, 89–92

Structured Analysis–Real Time (SA-RT)

, 136–137

Supplier assessment, application of proposed approach for

, 264–266

Supplier monitoring process

, 259–260

Supplier performance assessment

, 259–260

Supplier performance evaluation based on customer satisfaction

, 260–261

Supplier selection

, 257

Supply chain (SC) (see also Green supply chain (GSC))

, 81, 98, 128, 174, 219, 238, 256

BI and adoption of blockchain in supply chain

, 86

challenges for supply chain system during crisis

, 219–220

conceptual framework

, 84

EE and BI

, 84–85

facilitating conditions

, 85–86

methodology

, 86–87

PE and BI

, 84

questionnaire

, 86

resilience in

, 220–221

results

, 87–92

review of literature

, 82–86

SI and BI

, 85

strategies for sustainability

, 222

sustainability

, 176–177

theoretical framework

, 82–84

transparency

, 11, 288–289

Supply chain 4.0 (SC 4.0)

, 158–159, 238

barriers for sustainability in literature

, 240

BWM

, 242–243

challenges for sustainability

, 240–242

DEMATEL

, 243–248

findings

, 160–166

framework to overcome SC 4. 0 challenges for sustainability

, 248–250

future research

, 165–166

literature review

, 240–242

methodology

, 160

methodology

, 238–239

opportunities for sustainability

, 162–163, 166

theoretical background

, 158–159

Supply chain management (SCM)

, 50, 70–71, 80, 98, 176

evolution

, 100–101

reduction of costs and wastages in

, 105–106

Supply Chain Operation Reference (SCOR)

, 136–137

Supply chain optimization (SCO)

, 100

Supply chain system management (SSCM)

, 221

Supply chain visibility (SCV)

, 98–99

impact of IoT on

, 101–102

Sustainability

, 2–3, 16, 81, 157–159, 176, 202, 276–277, 297–298

framework

, 50

framework to overcome SC 4.0 challenges for

, 248–250

in industrial practices

, 278–279

in industry 4.0

, 279–282

SC 4.0 barriers for sustainability in literature

, 240

SC 4.0 challenges for

, 240–242

standards

, 189–190

technologies in shaping

, 5–6

Sustainable criteria

, 258

Sustainable development

, 16, 33, 176

Sustainable Development Goals (SDGs)

, 32, 50, 173, 279–280

industry 4.0

, 34–36

literature review

, 33–34

managerial implications

, 45–46

managing industry 4.0 for SDG attainment

, 43

policy and regulation

, 43–45

prospects and future developments in industry 4.0 for achieving

, 45

risks and difficulties in using industry 4.0

, 41–43

SDG 12

, 37–39

SDG 8

, 36–37

Sustainable digitalisation, key indicators to measure

, 209

Sustainable resource management

, 151

Sustainable reverse logistics transformation

, 148

Sustainable supply chain

, 173–174

Sustainable supply chain management (SSCM)

, 50, 116, 176

challenges and solutions

, 61

challenges in SSCM adoption

, 51–53

implications

, 54

potential solutions to overcome SSCM challenges

, 51, 54–55, 60

research method

, 51

Sustainable wealth-building strategies

data

, 222

findings

, 224–230

future research directions

, 231

literature review

, 219–222

managerial implications

, 231

methodology

, 223

research methodology

, 222–224

System integration

, 277

Systems theory

, 173

Taguchi loss function

, 261–262

TCI express

, 230

Technique for Order Preference by Similarity to Ideal Solution (TOPSIS)

, 208, 261–262

Technological

, 19

Technological research issues

, 122–123

Technological solutions

, 44

Technologies in shaping sustainability

, 5–6

Technology integration

, 238

Technology trends

, 69–70

Technology-organization-environment framework (TOE)

, 82, 298

Theory of planned behavior (TBP)

, 82

Theory of Reasoned Action (TRA)

, 82

3D printing

, 120, 277

Tiger logistics Ltd.

, 230

Total relation matrix

, 246

Traceability

, 81

TradeLens

, 72–74

Transformation of industries

, 35–36

Transparency

, 21

Transport corporation of India

, 230

Transportation management

, 105

Triple bottom line (TBL) approach

, 148, 202, 211–212, 278–279, 297–298

Truffle

, 69

Ukraine–Russia war

, 218

Unified Theory of Acceptance and Use of Technology 1 (UTAUT1)

, 82

Unified Theory of Acceptance and Use of Technology 2 (UTAUT2)

, 82

Unit root testing

, 223

United Arab Emirates (UAE supply chains)

, 149

background and significance of study

, 144

case studies

, 148–152

industry applications in

, 148–152

literature review

, 144–148

United Nations (UN) Convention on the Rights of the Child

, 188–189

Universal Declaration of Human Rights

, 188–189

Urbanisation

, 202

Value

, 177

Value chains

, 173

limitation and future scope

, 179

proposition development

, 178–179

theoretical background

, 174–177

Value creation

, 177

Value proposition

, 300

Vertical system integration

, 277

Virtual reality (VR)

, 277–278

Virtualization

, 163–164

VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR)

, 259

Volatility, Uncertainty, Complexity, and Ambiguity (VUCA)

, 165

VRL logistics

, 228

Waste reduction

, 105–106

Wave

, 71

Web of Data

, 16

Web of Science (WoS)

, 204

Workforce automation

, 286

Workforce reskilling and upskilling

, 289–290

challenges and solutions

, 290

individual empowerment

, 290

organizational resilience

, 290

Workforce transformation

, 41–42

World Commission on Environment and Development (WCED)

, 202

World crisis

, 219

World Health Organization (WHO)

, 50

Z-numbers

, 264

Z-TOPSIS

, 262, 266