“ABC” test

, 183–184

Academic perspective

BLS

, 26

gig economy

, 27–28

gig personas

, 29–30

gig selection

, 28–29

gig workers

, 28–29

Access economy

, 10

Adaptive learning techniques

, 90

Adkins-Green, Sheryl (CEO of Mary Kay Inc. )

, 241–247

Advanced analytics

, 79

Advocating principles and values

, 164–167

Affiliate(s)

, 167

marketers

, 64

marketing

, 64, 224

Airbnb

, 3, 14, 66–67, 70, 74–75, 97, 186, 200–201, 225–226

Ajjan, Haya

, 74

Alibaba

, 224–225

“Alternative employment arrangements”

, 26–27

Amazon

, 13, 64, 83, 89, 167, 233, 236

Amazon effect

, 77

Amazon’s Alexa

, 76–77

AmazonFlex

, 12

Amazon Associates Program

, 224

“American Dream”

, 44–45

American Express

, 83

Amway Business Owners (ABOs)

, 229–230

Amway corporation

, 229–235

Analytical data warehouse

, 86

Analytical infrastructure

, 84

Analytics

technologies

, 85

types of

, 81

value of

, 81–82

App

, 73–74

Apple iPhones

, 87

Apple’s Siri

, 76–77

Artificial intelligence (AI)

, 73–74, 77

in analytics

, 84

in helping gig economy participants

, 88–91

Assembly Bill 5

, 184–185

Assets

, 8, 68

Associates

, 97

Attributes

, 65

Automated Clearing House transactions (ACH transactions)

, 92–96

Avon, principles guide

, 166–167

Baby Boomers

, 33

Babylonian law

, 98

Beldham, Paul (founder and CEO of PayQuicker)

, 73–74, 91–92

Belief system management

, 174–175

Bellhop

, 12

Best-in-class analytics

, 87–88

Big data

, 83

BlaBlaCar

, 212

Black’s Law Dictionary

, 182

Body Shop

, 76

Bonanza

, 13

Bookkeeping system

, 205

“Borello” test

, 183–184

Bottom-up economy

, 10

Bureau of Labor Statistics (BLS)

, 26

Bush, Lori

, 137

Business Week magazine

, 99

Business(es)

, 20

analytics

, 81, 84

models

, 58–59, 168, 186

C-level executives

, 209–210

sponsor

, 85

California Assembly Bill 5

, 181–184

Care. com

, 12

Career decisions

, 34–35

Caviar

, 216–217

Cavitt, Robert (CEO of Jenkon)

, 73–74

Chatbots in helping gig economy participants

, 88–91

ChefsFeed

, 215

Chief analytics/chief data officer

, 85

Chief executive officer (CEO)

, 213, 229, 235

Chief marketing officer (CMO)

, 229

Cleanliness

, 82

Code of ethics, adopting strong

, 167

Compensation

, 75

plans

, 103, 187–188

Complexity

, 187–188

Conditioning

, 173–174

Consultants

, 97

Consumer packaged goods (CPG)

, 25–26

Consumer-focused organizations

, 186

Consumers

, 9, 75

COREPlus+

, 233

Coronavirus

, 185

Corporations

, 65

COVID-19 pandemic

, 8, 18–19, 58, 71, 104, 107–108, 133–134, 151–152, 181–182, 185, 226

Creativity

, 21–22, 65, 70, 162, 191

Credit

, 177–178

Crowdfunding sectors

, 218

Cultural/culture

, 132–133

attitudes

, 15–16

shift

, 15, 142–143

Customer experience (CX)

, 75

Customer focus

, 63–64

DASH Project

, 216

Dashers

, 12

Data

lake

, 86

scientists/data analysts

, 85

Debts

, 177–178

“Decision Cockpits”

, 83

Deep learning in analytics

, 84

Deliveroo

, 217

Delivery services

, 216

Demographic shifts

, 107–108

Descriptive analytics

, 81

Diagnostic analytics

, 81

Didi Chuxing

, 211–212

Digital marketing

, 53–54, 105

Digital media platforms

, 82–83

Digital processors

, 78–79

Digital services

, 14

Direct selling

, 58–59, 97, 100–101, 131–132, 183, 201–202, 229–230

amazing story of direct selling entrepreneur

, 120–127

business model

, 98

checklist for selecting direct selling company

, 117

companies

, 14, 63, 128–129, 168

components

, 118

future

, 108

highlights of conversations with direct sellers

, 108–117

importants

, 103

lessons direct selling companies

, 129

model

, 7, 65, 157, 187

opportunities

, 103–108

S.W.O.T. analysis

, 101–108

strengths

, 102

ultimate gig research team outlook

, 129

understanding

, 117–119

Direct-to-consumer model

, 131–132

Distributors

, 97

DNA

, 244–245

Domain experts

, 85

“Door-to-door sellers”

, 98, 99

DoorDash

, 12, 74–75, 216

Drizly

, 216–217

Dynamex approach

, 184

Earnest Loans

, 40–41

eBay

, 13, 51, 53

Economic realities

, 15, 18–19

Economic Security Act

, 185

Economies

, 145–146

Electronically mediated employment

, 27

Employee-type benefits

, 192

Employment

laws

, 182

perspective of gig

, 27–28

Enhancer

, 29–30

Enterprise-wide analytics process

, 81

Entrepreneur. See also Microentrepreneurs

, 7, 9, 58, 63–64, 89, 132–133

amazing story of direct selling

, 120–127

creative

, 12–13

Entrepreneurial model

, 58–59

Entrepreneurship

, 70, 158

additional findings and attributes

, 65

brilliant use of technology

, 64–65

customer focus

, 63–64

fueling fire and fanning flames

, 70–71

gig economy growth

, 57–58

power of innovation, creativity, and trust

, 65–70

simplicity

, 60–63

Ethics

insights and unexpected learning

, 191–194

perspective on

, 188–191

Etsy

, 4, 13, 51, 53–55, 63–64, 73–74, 97, 218–219, 222

External data

, 82–83

External factors

, 106–108

Facebook

, 89

Fair Labor Standards Act

, 182

Fair rewards

, 3–4, 9, 162, 245

Falcon-9

, 66

Fanning flames

, 70–71

Financial

asset management

, 177–178

investment

, 58

pressures

, 35–41

stress

, 18–19

Firms

, 30

Fiverr

, 3, 54–55, 213

Flexibility

, 3–4, 9, 22–23, 41, 44, 131–132, 162, 192, 231

Fortune 500 company

, 157

Franchise model

, 7

Franchising

, 58–59, 186

Free economies function

, 21–22

Freedom

, 3–4, 8–10, 22–23, 55, 131–132, 162, 192, 231

Freelance computer work

, 196

Freelancers

, 6, 213

Freelancing in America (FIA)

, 6

Fueling fire

, 70–71

Funding Circle

, 218

Game-changers

, 209–210, 239

companies changing game

, 210–227

eliminating everyday inconveniences

, 214–217

individuals changing game

, 228–247

interview with Kevin Guest, CEO, USANA Health Sciences, Inc.

, 235–241

leasing idea changed game

, 225–227

Milind Pant, CEO, Amway corporation

, 229–235

new ways to access funding

, 217–218

profiles of companies changing game

, 250, 266

selling gigs and platforms

, 218–225

service gigs changed game

, 212–218

Sheryl Adkins-Green, CEO, Mary Kay Inc.

, 241–247

transportation gigs changed game

, 211–212

Gender equality

, 134

Generation Z (Gen Z)

, 33–34, 42–43, 92, 96, 197

Generations

, 34

Gen Xers

, 33

Gen Y

, 33–34

Generation X

, 33

Get-A-Round

, 70

Giertz, Simone

, 222–223

Gig, 196–197. See also Ultimate Gig

adopting strong code of ethics

, 167

advocating principles and values

, 164–167

belief system management

, 174–175

checklist of questions to support quick planning for gig workers

, 159

excellent communication benefits gig providers and gig workers

, 163–164

financial asset management

, 177–178

gig work

, 154–157

gig-providing companies

, 210

insights and unexpected learning

, 168–169

life management

, 170–171

mental health management

, 171–173

pay quicker

, 91–96

physical health management

, 173–174

planning

, 157–160

principles guide Avon

, 166–167

research team

, 11–15

short course in personal development

, 169–170

social relationship management

, 175–177

start-up guidelines for selling gigs

, 160

start-up guidelines for transportation, service, and leasing gigs

, 159–160

time management

, 161

tracking expenses

, 161–162

Gig business models

, 74

Gig economy

, 2–3, 7, 9, 19, 27–28, 41, 44, 50–51, 57–60, 68, 73, 97, 131–132, 143–144, 151–152, 165, 168, 181, 186, 188, 190–194, 210, 224–225, 228, 232, 240

cultural attitudes

, 15–16

economic realities

, 18–19

I. W

, 5–6

impact

, 19–22

key drivers of gig economy growth

, 15–19

labor

, 8

technology changes game

, 16–17

types of gigs

, 11–15

US

, 2

worth exploring

, 22–23

Gig Economy Data Hub

, 27–28

Gig exclusive

, 30

Gig participant

, 9, 100, 134, 138, 153, 158

Gig providers

, 9, 63, 146, 153, 161–162

excellent communication benefits

, 163–164

“Gig worker bill”. See California Assembly Bill 5

Gig workers

, 9, 28, 68, 133–134, 154, 161, 168, 197–198, 203–204, 209–210

checklist of questions to support quick planning for

, 159

excellent communication benefits

, 163–164

primary motivations driving

, 199–202

selection

, 145

work of

, 199

Gigster

, 13, 54–55

GoFundMe

, 218

Good to Great

, 209

Google

, 89

Google’s Assistant

, 77

GoPuff

, 216

Grab

, 217

Gracious Leadership

, 140–141, 143–144

Great Recession

, 35

GrubHub

, 74–75, 216

Guest, Kevin (CEO of USANA Health Sciences, Inc. )

, 235–241

Guidance gig-providing companies

, 158

Hamilton Project

, 183

Han, Vince (CEO and founder of Mobile Coach)

, 73–74

Handy

, 12

HelloTech

, 12

Hire-A-Chef

, 13, 215

“Home-based business”

, 44, 50–51

HomeAway

, 15, 74–75, 227

Homestay

, 227

HopSkipDrive

, 12

House Rules

, 226

Human Resource Department

, 41–42

HyreCar

, 14

Income

, 28, 153

income-earning opportunity

, 157

residual

, 54–55

scalable

, 53–54

Independent contractors

, 105, 153–154, 182, 192

“Independent worker” category

, 183

Independent workforce (I. W)

, 5–6

Industrial Revolution

, 5

Informal economy

, 20

Innovation

, 162, 191

InstaCart

, 216–217

Instant payment

, 92

Institutionalize data-driven decision-making

, 84–88

Integrated reporting

, 87

Internal data

, 82–83

Internal factors

, 104–106

International Franchise Association

, 106

International Monetary Fund (IMF)

, 20

Internet

, 106–107

Internet of Things technologies (IoT technologies)

, 74, 78–79

IT analysts

, 85

JustEats

, 74–75, 217

Kajabi

, 53–54, 64, 223–224

Kickstarter

, 218

Know your customer (KYC)

, 92–96

Labor

, 8

Landlords

, 186–187

Law of physics

, 171

Leadership

, 139

Lean In

, 132

Leasing

, 11

gigs

, 14–15

“Less-is-more” approach

, 187–188

Life

, 170, 181

management

, 170–171

Locker, Maria (CEO of RevolutionHER)

, 135

Lyft

, 3, 11, 67, 70, 74, 131, 204–205, 211–212

Machine learning (ML)

, 77

in analytics

, 84

Manual skill-based services

, 196

Market professional skills

, 62–63

Marketplace

, 182

Mary Kay

, 241

McConnell, David (founder of Avon)

, 166–167

McVeigh, Stephanie (founder and CEO of Strategic Incentive Solutions Inc. )

, 129

Members of Unilever Network

, 75

Mental health management

, 171–173

Mercari

, 13–14

Microcomputer

, 78

Microentrepreneurs

, 9, 63–64, 75, 154

experience

, 75

Microentrepreneurship. See also Entrepreneurship

, 154

Microsoft’s Cortana

, 77

Millennials

, 33–34, 92, 96, 197

MIT Sloan Management Review

, 82

Mobile

devices

, 74

pay

, 92–96

Mompreneurs

, 136

Money

, 35, 166, 177

Motivations for working gig

ability to own boss

, 49–50

financial pressures

, 35–41

flexibility

, 41–44

improve quality of life

, 44–48

residual income

, 54–55

scalable income

, 53–54

work from home

, 50–53

Musk, Elon

, 17

Netflix

, 74, 83

Networked economy

, 10

Networking

, 175

New York University (NYU)

, 4–5

Nutrilite products

, 99

“Office-centric” environment

, 8

Ola Cabs

, 211–212

On-demand economy

, 10

OneFineStay

, 14

Online e-commerce platform

, 54–55

Online groceries

, 87

Pant, Milind (CEO of Amway corporation)

, 230

Parking Panda

, 14

Part-time

job

, 9, 134–135

ncome

, 42

opportunities

, 60

work

, 145–146

Passion economy

, 10

Payee Support

, 92–96

Paying quicker

, 96

Peer economy

, 10

Peer-to-peer (P2P)

, 218

Personal assistance

, 196

Personal development, short course in

, 169–170

Personalized service

, 105

Personas

, 29

enhancer

, 29–30

gig

, 29–30

gig exclusive

, 30

Pew Research Center

, 36

Physical health management

, 173–174

Platform economy

, 10

Policymakers

, 182–183

Poshmark

, 14

Postmates

, 12, 216

Power of innovation

, 65–70

Pre-COVID-19

, 35, 145–146

Predictive analytics

, 81

Predictive models

, 83, 86

Prerequisite

, 168–169

Prescriptive analytics

, 81

Prescriptive models

, 86

Pricing

, 8

Prime Pantry

, 87

Procter & Gamble (P&G)

, 83

Professional services

, 196

Prosper

, 218

Quick payment for services rendered

, 134

Quiq Messaging

, 163–164

Record-keeping tools

, 162

Rental economy

, 10

Renting personal property

, 196–197

Residual income

, 54–55

RevolutionHER

, 136, 143

Richness

, 82

Ride-sharing services

, 197

Roadie

, 12

Rover

, 12, 213–214

Ruby Lane

, 14

Safety nets

, 204–205

Scalable income

, 53–54

Second Life

, 106–107

“Self-talk”

, 173

Selling

, 11

products

, 196

Selling gigs. See also Transportation gigs

, 13–14

and platforms

, 218–225

start-up guidelines for

, 160

Sensors

, 78–79

Service gigs

, 12–13

changed game

, 212–218

Services

, 11

Shankar, Yogi (CEO and founder of Prescriptive Insights)

, 73–74

Sharing economy

, 3–5, 10

Shopify

, 13–14, 51, 53–55, 64, 70–71, 73–74, 148, 218–222

Short-term real-estate rental

, 196–197

Short-term work opportunities

, 134–135

Simplicity

, 60, 63, 153–154, 187–188

Smartphones

, 106–107

smartphone-enabled Fintech solutions

, 92–96

Social entrepreneurship

, 138

Social media platforms

, 82–83, 107

Social relationship management

, 175–177

Socializing

, 175

Software technologies

, 76

Space travel

, 66

SpaceX

, 66, 69

Spirituality

, 174

Squarespace

, 14, 64

Stakeholders

, 191

“Stay Here” (Netflix original show)

, 227

Strategic plans

, 157

Strategy

development

, 86

monitoring and validation

, 87

Strengths, weaknesses, opportunities, and threats analysis (S.W.O.T. analysis)

, 101–108

Structured data

, 82–83

Subscription fee

, 148

TaskRabbit

, 3, 11–13, 70, 97, 215

Tassopoulos, Kerry

, 181

Tassopoulos Law Firm

, 181

Teachable Company

, 64

Team

, 103

Technology

, 15, 73–74, 78, 162

AI and Chatbots in helping gig economy participants

, 88–91

brilliant use of

, 64–65

changes game

, 16–17

critical importance of data

, 82–88

gigs pay quicker

, 91–96

increased use of machine learning, deep learning, and AI in analytics

, 84

institutionalize data-driven decision-making

, 84–88

internet of things

, 78–79

leverage technology to enable analytics and optimize decision-making

, 79–82

technology-driven gig economy

, 42

technology-fueled innovation

, 64

types of analytics

, 81

value of analytics

, 81–82

The Principles that Guide Avon

, 165

The Sharing Economy

, 4–5, 61–62, 67

Thinkific

, 223–224

Thumbtack

, 3

Time management

, 161

Toptal

, 13, 54–55, 213

Tracking expenses

, 161–162

Traditional independent contractors

, 26–27

Transportation

, 11, 197

Transportation gigs. See also Selling gigs

, 11–12, 16, 63, 73–74

changed game

, 211–212

Trust

, 65–70

Tupperware

, 99

Turo

, 14–15

Twitch

, 223

Uber

, 3, 11, 70, 74, 131, 200–201, 204–205, 211–212

Uber Eats

, 216

Ultimate Gig

, 145

checklist

, 146–147

designing

, 147–148

gig workers

, 197–199

insights and unexpected lessons learn

, 151–152

primary motivations driving gig workers

, 199–202

project

, 155

research

, 195

safety nets

, 204–205

satisfaction in comparison to expectation

, 202–204

survey crosstabulation of gig earning expectations

, 195

testimonials from people

, 148–151

Unstructured data

, 82–83

Upstart

, 217

Upwork

, 3, 13, 63, 70, 213

US Department of Labor

, 20, 26, 185

US Postal Service

, 42

US-based LendingClub

, 218

Vacasa

, 15

Value of analytics

, 81–82

Value-adding benefits

, 28–29

Variety

, 83

Velocity

, 83

Via (ridesharing service)

, 11–12

Video content

, 223

Virtual assistants (VAs)

, 77

Virtual cards

, 92–96

Volume

, 83

VRBO

, 14, 74–75, 227

Wag!

, 213–214

Wallets

, 91–92

Walmart

, 64, 224

Wealthy Affiliate

, 70, 224–225

Wix

, 14

Women and of gigs future

hypothesize

, 132–135

insights

, 141–144

Women’s workforce participation

, 141–142

Work

, 210

work–life balance

, 8

Work from home (WFH)

, 50, 53, 138

YouTube

, 53–54, 222–223

Zimmer, John

, 67