Index

Supply Chain Management and Logistics in Emerging Markets

ISBN: 978-1-83909-333-3, eISBN: 978-1-83909-331-9

Publication date: 20 November 2020

This content is currently only available as a PDF

Citation

(2020), "Index", Yoshizaki, H.T.Y., Mejía Argueta, C. and Mattos, M.G. (Ed.) Supply Chain Management and Logistics in Emerging Markets, Emerald Publishing Limited, Leeds, pp. 319-326. https://doi.org/10.1108/978-1-83909-331-920201019

Publisher

:

Emerald Publishing Limited

Copyright © 2021 Emerald Publishing Limited


INDEX

Agility
, 15–16

Allocation constraints
, 44–45

American Production and Inventory Control Society (APICS)
, 17

Analysis of variance (ANOVA)
, 5, 120, 145–146, 159

Analytical hierarchy process (AHP)
, 4, 90–91, 93, 115

case study
, 94–95

first application
, 94

literature review
, 91–92

methodology and empirical strategy
, 92–93

results
, 95–101

validation
, 96–101

Annual holding cost
, 220

Annual ordering costs
, 220

Area under the curve (AUC)
, 312

Auction. See also Multi-dimensional auctions
, 43

auction-based procurement
, 43

environment
, 43

framework
, 46–47

models
, 46–47

terminology
, 44

Bahía (BA)
, 177

Balance scorecard (BSC)
, 257

Better Cities for Logistics Toolkit
, 109–110

Bidding languages
, 45, 46–47

Bloom’s Taxonomy
, 256–257, 260, 262

Bodega Siglo XXI
, 313

Branch-and-price algorithm
, 180

Brazil
, 158–160, 176

British Petroleum (BP)
, 12

Business continuity planning (BCP)
, 17, 24–25

Business practices (BP)
, 236, 243

questionnaire
, 241

Capacity slack
, 15

Cargo

loss
, 162

robbery
, 161

theft
, 158–160

transportation
, 164

Cargo risks
, 158

source in supply chain
, 161–162

Cathedral
, 134–135

Causal loop diagram (CLD)
, 280

Center for Latin-American Logistics Innovation (CLI)
, 3

Center for Transportation and Logistics of the Massachusetts Institute of Technology (MIT-CTL)
, 136

Characteristic function
, 220–221

Círculo K
, 274

City logistics
, 135

City-wide assessment
, 109–110

Classification yards
, 182

Cluster

analysis
, 109

boundary delineation
, 136

theory analysis
, 136

Collaboration
, 15–16, 66

in supply chains
, 216

Collaborative assessment of promotions performance using financial KPIs

changing retail sector
, 61–64

collaborative promotion management
, 66–67

financial KPI for assessing promotions performance
, 67–71

promotions at retail supply chain in Colombia
, 72–81

promotions in retail sector
, 64–66

Collaborative inventory replenishment

accounting for additional objectives
, 229–231

birth of new actor in supply chain
, 227–229

empirical results
, 224–227

game theory approach
, 223–224

model solution approach
, 220–223

problem description and collaborative logistic strategy
, 217–218

Collaborative joint replenishment problem
, 218–220

Collaborative promotion planning
, 85

Collaborative strategy
, 5

Collaborative supply chain
, 66

Colombia

GMROI
, 74–76

market share variation
, 77

product category results
, 81

promotions at retail supply chain in
, 72–81

regional category results
, 81

ROI
, 73–74

Colombian supermarket chain
, 4

Combinatorial auctions model
, 42, 47–48, 53–54

Communality
, 138

Competitive advantage
, 94

Competitive uncertainties
, 16

Conceptual system evaluation and reformulation methodology (CSAR methodology)
, 4, 90–93, 95

Consistency index (CI)
, 99–100

Consistency ratio (CR)
, 100

Consumer-packaged-goods (CPG)
, 4, 274, 300, 312

Coordination
, 228

Córdoba in Argentina
, 132, 134

case study in old downtown of
, 140–142

Core stakeholder
, 177

Cost of goods sold (COGS)
, 71

Culture of risk management
, 15

Customer and store attributes
, 300

Daily train scheduling in seaport terminal
, 179

case study implementation
, 189–190

constraints
, 185–188

data collection
, 184

decision variables
, 185

formulation of generic optimization model to schedule trains at ports
, 184–189

indices and sets
, 184–187

literature review
, 179–181

methodology
, 182–189

objective function
, 188–189

parameters
, 185, 188

results
, 190

solution algorithm
, 189

Data analysis
, 101

Data envelopment analysis (DEA)
, 91

Data-driven solutions
, 109

freight trip generation models
, 123

general methodological framework
, 109–114

loading and unloading bays optimization models
, 114–115

logistic profile of Quito
, 109–110

logistics hotspots and data collection
, 110–114

methods and results
, 115–117, 118–121, 123–126

results and analysis of logistics solutions
, 114

transfer centers optimization models
, 118

Decision

decision-maker risk
, 16, 22

support methodologies
, 45

Descriptive analysis
, 276

Discounts
, 62–63

Discrete choice model

literature review
, 301–304

methods and procedures
, 304–309

results
, 309–312

Discrete simulation techniques (DESs)
, 216

Disruptions
, 15, 18

Disruptive events
, 17–18, 33–34

Distribution centers (DCs)
, 159

Double-track segments
, 189

Earthquakes (EQ)
, 27–28

Economic Order Quantity model
, 218

Economist Intelligence Unit (EIU)
, 19–20, 22–24

Efficient Customer Response (ECR)
, 66–67

Eigenvalue
, 99

7-Eleven
, 274

Elimination and choice expressing reality (ELECTRE)
, 91

Elitist approach
, 221–223

Emerging markets
, 108, 132, 274

En Route to Customer [RC]
, 163

En Route to Distribution Center [RDC]
, 164

Environmental

disruptive events
, 24

risk
, 16–17, 22

Erosion
, 2

Estrada de Ferro Carajás (EFC)
, 177

Euclidean 1-center problem
, 119–120

Everyday low prices (EDLP)
, 65

Exploratory factor analysis (EFA)
, 138

Factor analysis (FA)
, 5, 137–138, 143

Factor loading
, 143–144

Faculty of Exact, Physical and Natural Sciences (FCEFyN)
, 134

Fast-moving consumer goods sector (FMCG sector)
, 61–63

Fiado system
, 282

“Financial microcenter” of city
, 134–135

Firm[s]
, 12, 17

level models
, 28

organizational culture effect
, 34–35

Food processing
, 90

Freight generation (FG)
, 123

Freight transportation
, 5, 123, 126

Freight trip generation models (FTG models)
, 108, 123

situation and solution
, 123

Functional strategy map (FSM)
, 4, 90–93

Game theory approach
, 223–224

GeneSys
, 205–209

Genetic algorithm (GA)
, 220–223

Geographic culture effect
, 34–35

Geographical location risk
, 22–24

Geopolitical risk
, 13

Geospatial Intermodal Freight Transportation model
, 180

Global trade identification number (GTIN)
, 73

Greenhouse gas emissions
, 2

Gross domestic product (GDP)
, 1, 12, 61–62, 197–198

per capita
, 21, 25

Gross margin return on investment (GMROI)
, 68–71, 74–76

Gross national income (GNI)
, 1

Heuristics
, 181

High density high income (HDHI)
, 145–146, 148

High density low income (HDLI)
, 145–148

High-income areas

analysis of
, 286–288

customer service
, 294

nanostores in
, 292–294

operations
, 293–294

supply
, 292–293

High-low prices (HILO prices)
, 65

Historic downtown area
, 147

Hurricanes
, 27–28

Immersion
, 242

Independencia
, 134–135

Industry risk
, 16

Input market uncertainties
, 16

Insecurity
, 158

Intermodal transportation
, 180–181

Internal grain trains
, 183

Inventory management
, 292

Inventory slack
, 15

IT-based approaches
, 199–200, 202

Joint Replenishment Problem (JRP)
, 216

Key performance indicators (KPIs)
, 4, 64, 136, 178, 182–184, 256

assessment of KPI knowledge
, 260–261

usage and importance
, 261

KM2 methodology
, 136, 139–140

Knowledge attainment of concepts
, 258

Last mile

deliveries
, 134

distribution
, 108

Latin America (LATAM)
, 25, 28

micro and small firms in
, 197–200

research agenda on supply chain management for MSEs in
, 209–211

Latin America and the Caribbean (LAC)
, 1–2

supply chain and logistics operations in
, 2

urbanization and densification rates in
, 1

venues of applied research in SCM for
, 3–6

Latin Developing Countries (LDCs)
, 237

Loading bays optimization models
, 114–115

situation and solution
, 114–115

Logistics performance index (LPI)
, 2

Logistics. See also Urban logistics

regression
, 25, 159, 308–309

security
, 161

LOGYCA
, 3

Long-term

planning
, 42

return on investment
, 199–200

Low density high income (LDHI)
, 145–146, 148

Low density low income (LDLI)
, 145–146, 148

Low-income areas

analysis of
, 279–282

customer service
, 290–291

nanostores in
, 289–291

operations
, 290

supply
, 289–290

Loyalty programs
, 299–300

Macroeconomic risk
, 13, 17, 33

Major ordering costs
, 220

Management
, 236

Mann-Whitney test
, 265–266

Maranhão (MA)
, 177

Market share variation [ΔMS]
, 4, 71, 77

Mean Absolute Percentage Error (MAPE)
, 124–125

Mexico City metropolitan area (MCMA)
, 274

Micro and small enterprises (MSEs). See also Small-and medium-sized companies (SMEs)
, 198, 235–236

in Peru
, 238–239

productivity and good practices
, 237–238

research agenda on supply chain management for MSEs in Latin America
, 209–211

supply chain management for
, 201–209

Micro and small firms in Latin America
, 197–200

connection between productivity and SCM for small firms
, 198–199

fostering productivity and survival of small firms by focusing on SCM
, 200–201

research agenda on supply chain management for MSEs in Latin America
, 209–211

SCM for large firms vs. SCM for micro and small firms
, 199–200

supply chain management for MSEs
, 201–209

Mid-sized city
, 132, 140

Middle-income areas

analysis of
, 282–286

customer service
, 292

nanostores in
, 291–292

operations
, 291–292

supply
, 291

Minimum order quantity (MOQ)
, 290

Minor ordering costs
, 220

MIT Center for Transportation and Logistics
, 3

MIT GeneSys Project
, 200, 205–208

MIT SCALE Latin America network
, 3

Mixed research methodologies
, 91–92

Mixed-integer linear programming model (MILP model)
, 5, 180–181

Mixed-integer programming (MIP)
, 47

Model solution approach
, 220–223

Modi operandi
, 162

Mom-and-pop stores
, 274, 300

Monte Carlo Simulation
, 115

Multi-attribute auctions
, 45

Multi-attribute decision analysis (MCDA)
, 3–4

Multi-attribute utility method (MAUT)
, 91

Multi-criteria auctions
, 45

Multi-criteria decision analysis model (MCDA model)
, 42, 51–53, 55–57, 91

Multi-criteria value analysis
, 47

Multi-dimensional auctions
, 42

literature review
, 43–46

models, methods, and procedures
, 46–53

results
, 53–57

Multidimensional reverse auction
, 43–44

Nagelkerke determination factor
, 171

Nanostores
, 3, 300

business models
, 274–275

channel
, 300

methodological framework
, 276–278

recommendations for nanostore supply chains and operations
, 289–294

results
, 278–288

v2. 0
, 288

National Hurricane Center
, 18

Natural disaster risk
, 13, 17, 19–20, 33

Network-based models
, 181

Non-food items (NFI)
, 53

Nongovernmental organization (NGO)
, 3–4, 42

Norte-Sul railroad
, 177

North American Industry Classification System (NAICS)
, 124

North of Peru
, 236

literature review
, 237–239

methodology
, 239–242

results
, 242–248

Northern Arc
, 176

Objective function
, 188–189, 220

On time in full (OTIF)
, 55

One-way analysis of variance (one-way ANOVA)
, 138

Operation research techniques
, 181

Operational plan
, 95

Optimization model
, 120

Organization for Economic Co-operation and Development (OECD)
, 2

Organizational risk
, 16, 22

Origin-destination matrices (O-D matrices)
, 123

Oxxo
, 274

Package
, 43–44

Pará (PA)
, 177

Parked at Customer (PC)
, 163

Parked at Distribution Center (PDC)
, 164

Performance measurement systems (PMSs)
, 257–258

Performance metrics
, 257, 265

Peru
, 236

MSEs in
, 238–239

Piauí (PI)
, 177

Pilot study
, 207–208

Point of purchase (POP)
, 293

Points of sale (POS)
, 67

Political instability
, 16

Port

dwell time
, 179

operations
, 180–181

Pre-qualification questionnaire (PQQ)
, 47

Preference ranking organization method for enrichment of evaluations (PROMETHEE)
, 91

Pricing
, 65

Principal component analysis (PCA)
, 109, 138, 143

Proactive planning
, 16

Problem-specific risk
, 16, 22

Process mapping
, 182–184, 276

Product market uncertainties
, 16

Productivity
, 198, 235–236, 256

Promotion forecast accuracy (PFA)
, 4, 71, 76

Promotions
, 62–63

in retail sector
, 64–66

at retail supply chain in Colombia
, 72–81

Proximity
, 313

retailing
, 274

Puerto Rico
, 12–13, 18

Questionnaire
, 240

Quito
, 108

logistic profile
, 109–110

Railway logistics corridor
, 176–177

Random consistency index (RI)
, 99–100

Rapid Plant Assessment (RPA)
, 242

Reengineering
, 15–16

Regions of world
, 34–35

Regression analysis
, 245–248

Reinforcing loop
, 281–282

Request for quotation (RFQ)
, 42

Research gap analysis
, 181

Research questions (RQs)
, 209

Resilience culture
, 24–25

Resilient Enterprise, The
, 15

Resilinc Database
, 19–20

Retail industry
, 6

Retail landscape
, 274, 299–300

Retail sector

changing
, 61–64

promotions in
, 64–66

Retailer[s]
, 216–217

promotions
, 65

Retailing
, 61–62

Return of investment (ROI)
, 4, 67, 69–70, 73–74

Reverse auctions
, 43–44, 46

Risk[s]
, 12

analysis of transporting goods
, 158

data collection and risk location-related variables
, 163–164

literature review
, 159–162

management culture
, 16–17, 24–25, 159–160

matrix
, 166–168

methodological framework
, 162–165

numerical results
, 165–171

results and managerial insights
, 172

risk matrix framework
, 165

scores
, 13

statistical analysis
, 164

Road freight
, 159

Robberies
, 159, 164

Root Mean Square Error (RMSE)
, 124–125

Sales uplift
, 68

Sensitivity analysis
, 56–57

Shapley Value
, 220

Short-term planning
, 179

Simple logit model
, 27

Single-item reverse auction
, 43–44

Site level model
, 27–28

Small-and medium-sized companies (SMEs). See also Micro and small enterprises (MSEs)
, 199–200, 216, 256

obstacles for adoption of KPI in
, 258

Stakeholder’s interactions
, 276

Statistical

analysis
, 135, 164

methods
, 137–138

tests
, 165–166, 168–171

Stochastic Collaborative Joint Replenishment problem (S-CJRP)
, 5, 216

Stochastic Multi-Objective Joint Replenishment Problem (S-MJRP)
, 230

Stockyard product allocation and terminal routing
, 180

Strategy
, 90–91, 258

Supermarkets
, 300, 305

Supplier selection
, 42–43

problems
, 45

Supply Chain And Logistics Excellence (SCALE)
, 3

Supply chain collaboration
, 66

Supply chain management (SCM)
, 2, 91, 198, 236, 276

actions
, 203–205

experience
, 205

fostering productivity and survival of small firms by focusing on
, 200–201

for large firms vs. SCM for micro and small firms
, 199–200

lessons learning
, 202–205

for MSEs
, 201–209

research agenda on supply chain management for MSEs in Latin America
, 209–211

size matters
, 202–203

venues of applied research in SCM for LAC
, 3–6

Supply Chain Operations Reference model (SCOR model)
, 236–237

Supply chain resilience
, 12, 15–18, 158

data collection and processing
, 19–22

disruptive events
, 33–34

literature and hypothesis development
, 14–18

macroeconomic risk
, 33

managerial implications
, 35–36

methodology
, 19–28

natural disaster risk
, 33

regions of world
, 34–35

results
, 28–30

Supply chain risk management (SCRM)
, 14–16, 157, 160–161

framework
, 22–28

models
, 25–28

variables
, 22–25, 26–27

Supply chain risks (SCRs)
, 17, 158, 160

Survey-based methodology
, 200–201

System dynamic approach
, 276, 280

Technique for order of preference by similarity to ideal solution (TOPSIS)
, 91

Terminal dwell time
, 179

Termination condition
, 221–223

Theft
, 164

Third-Party Logistics (3PL)
, 217, 228

Tocantins (TO)
, 177

Traditional

auction
, 43

channel
, 274

Train

dispatching
, 178–179

scheduling
, 181

traffic management
, 178

Transfer centers optimization models
, 118

situation and solution
, 118

Transportation of bulk products for exports
, 179–180

Tukey HSD test
, 145–146

Two-sample t-test
, 120

Uniqueness
, 138

United Nations Database
, 20–21

United States Food and Drug Administration (USFDA)
, 12

Universidad San Francisco de Quito (USFQ)
, 112

Unloading bays optimization models
, 114–115

situation and solution
, 114–115

Urban logistics

case study in old downtown of Córdoba, Argentina
, 140–142

factors
, 132–133

general methodology
, 137–140

literature review
, 135–137

methods and procedures
, 137–146

numerical setting
, 142–146

results
, 146–149

solutions
, 4–5, 114

solutions
, 148–149

Urban planning
, 108

Urbanization
, 108

Valor Logíıstica Integrada (VLI)
, 177, 184

Value

functions and ranges
, 45

proposal
, 91–92

Variable inflation factor test (VIF test)
, 30

Vertical collaboration
, 66

Volume discount auctions model
, 42, 47, 49–51, 54–55

Vulnerability
, 160

reduction
, 158

Walmart strategy
, 65

Weights of streets and establishments
, 115

Winner determination problem
, 44–45

Wood and timber SMEs in Peru

assessment of KPI knowledge
, 260–261

literature review
, 257–258

methods and procedures
, 258–261

results
, 261–266

usage and importance of KPIs
, 261

World Bank Database
, 21

Yard management
, 180–181

Prelims
Chapter 1 Updates in Supply Chain Management and Logistics in Latin America and the Caribbean
Part I Strategic Topics in Supply Chain Management
Chapter 2 The Impact of Environmental Risks in Supply Chain Resilience
Chapter 3 NGO's Supplier Selection and Procurement Cost Reduction with Multi-dimensional Auctions
Chapter 4 A Collaborative Assessment of Promotions Performance Using Financial KPIs
Chapter 5 An Analytical Hierarchy Approach Applied in the Packaging Supply Chain
Part II Urban Logistics Operations and Freight Transportation
Chapter 6 Data-driven Solutions for Evaluating and Planning Last Mile Operations in Latin America: A Methodological Approach Focused in Quito, Ecuador
Chapter 7 Identifying Underlying Urban Logistics Factors in Old Downtown of Córdoba, Argentina
Chapter 8 Risk Analysis of Transporting Goods by Road in Brazil
Chapter 9 Daily Train Scheduling in Seaport Terminal: A MILP approach
Part III Supply Chain Operations for Micro and Small Firms and Retail Operations for Nanostores
Chapter 10 Supply Chain Management for Micro and Small Firms in Latin America
Chapter 11 Collaborative Inventory Replenishment: Discussions and Insights of a Cost-Effective Alternative for Noncompetitive Small- and Medium-sized Enterprises
Chapter 12 Adoption of Best Business and Supply Chain Practices and Micro/small Firms' Performance: Evidence from Northern Peru
Chapter 13 Managers' Knowledge of Key Performance Indicators in Small and Medium Enterprises: Wood and Timber SMEs in Peru
Chapter 14 Increasing Competitiveness of Nanostore Business Models for Different Socioeconomic Levels
Chapter 15 A Discrete Choice Model for Retailer Selection in Emerging Markets
Index