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