Consumers from Generation Z appear particularly concerned about the economy. Over 90 percent of Gen Z consumers are worried about their personal financial situations and nearly half (40 percent) of them are taking action to keep up with inflation.

In a June 2021 survey, inflation was the greatest economic concern for around 29 percent of Baby Boomers, or those between the ages of 56 and 74 years old, in the United States. On the other hand, ** percent of Gen Z/Millennial respondents (those between the ages of ** and **) said that wages were the most important economic concern.

A 2023 survey conducted among Generation Z in Indonesia found that most respondents across all age groups had freelance work as their side jobs. Meanwhile, only about a ***** of respondents aged between 21 and 26 had no extra income sources. With living costs consistently on the rise, many Indonesian Gen Z members rely on side jobs to support themselves financially. Aiming for financial stability Many Generation Z members in Indonesia are part of the sandwich generation, where they have to support both their children and parents. Moreover, Gen Z spends most of their income on food as a basic necessity, leaving them with limited savings. Despite their efforts to invest for the future, most Indonesian Gen Z have not saved enough for emergency funds. The rise of the creator economy among Gen Z Known for their digital fluency, Gen Z in Indonesia drives the creator economy as they become increasingly interested in online side hustles. They are significantly influenced by social media in various aspects of life, from purchasing behavior to travel inspirations. Gen Z utilizes these platforms not only for self-expression but also to build personal brands and businesses, allowing them to generate extra income.

Generation Z is a demographic cohort born from 2000 to 2010. As the oldest of the generation reaches adulthood and seeks to enter the workforce, Gen Z consumers will exercise growing economic and cultural clout over the next decade. Read More

Raw data (total survey) for DSR in 2021 (in Vietnam)

This map layer shows the prevalent generations that make up the population of the United States using multiple scales. As of 2018, the most predominant generations in the U.S. are Baby Boomers (born 1946-1964), Millennials (born 1981-1998), and Generation Z (born 1999-2016). Currently, Millennials are the most predominant population in the U.S.A generation represents a group of people who are born around the same time and experience world events and trends during the same stage of life through similar mediums (for example, online, television, print, or radio). Because of this, people born in the same generation are expected to have been exposed to similar values and developmental experiences, which may cause them to exhibit similar traits or behaviors over their lifetimes. Generations provide scientists and government officials the opportunity to measure public attitudes on important issues by people’s current position in life and document those differences across demographic groups and geographic regions. Generational cohorts also give researchers the ability to understand how different developmental experiences, such as technological, political, economic, and social changes, influence people’s opinions and personalities. Studying people in generational groups is significant because an individual’s age is a conventional predictor for understanding cultural and political gaps within the U.S. population.Though there is no exact equation to determine generational cutoff points, it is understood that we designate generational spans based on a 15- to 20-year gap. The only generational period officially designated by the U.S. Census Bureau is based on the surge of births after World War II in 1946 and a significant decline in birth rates after 1964 (Baby Boomers). From that point, generational gaps have been determined by significant political, economic, and social changes that define one’s formative years (for example, Generation Z is considered to be marked by children who were directly affected by the al Qaeda attacks of September 11, 2001).In this map layer, we visualize six active generations in the U.S., each marked by significant changes in American history:The Greatest Generation (born 1901-1924): Tom Brokaw’s 1998 book, The Greatest Generation, coined the term ‘the Greatest Generation” to describe Americans who lived through the Great Depression and later fought in WWII. This generation had significant job and education opportunities as the war ended and the postwar economic booms impacted America.The Silent Generation (born 1925-1945): The title “Silent Generation” originated from a 1951 essay published in Time magazine that proposed the idea that people born during this period were more cautious than their parents. Conflict from the Cold War and the potential for nuclear war led to widespread levels of discomfort and uncertainty throughout the generation.Baby Boomers (born 1946-1964): Baby Boomers were named after a significant increase in births after World War II. During this 20-year span, life was dramatically different for those born at the beginning of the generation than those born at the tail end of the generation. The first 10 years of Baby Boomers (Baby Boomers I) grew up in an era defined by the civil rights movement and the Vietnam War, in which a lot of this generation either fought in or protested against the war. Baby Boomers I tended to have great economic opportunities and were optimistic about the future of America. In contrast, the last 10 years of Baby Boomers (Baby Boomers II) had fewer job opportunities and available housing than their Boomer I counterparts. The effects of the Vietnam War and the Watergate scandal led a lot of second-wave boomers to lose trust in the American government. Generation X (born 1965-1980): The label “Generation X” comes from Douglas Coupland’s 1991 book, Generation X: Tales for An Accelerated Culture. This generation was notoriously exposed to more hands-off parenting, out-of-home childcare, and higher rates of divorce than other generations. As a result, many Gen X parents today are concerned about avoiding broken homes with their own kids.Millennials (born 1981-1998): During the adolescence of Millennials, America underwent a technological revolution with the emergence of the internet. Because of this, Millennials are generally characterized by older generations to be technologically savvy.Generation Z (born 1999-2016): Generation Z or “Zoomers” represent a generation raised on the internet and social media. Gen Z makes up the most ethnically diverse and largest generation in American history. Like Millennials, Gen Z is recognized by older generations to be very familiar with and/or addicted to technology.Questions to ask when you look at this mapDo you notice any trends with the predominant generations located in big cities? Suburbs? Rural areas?Where do you see big clusters of the same generation living in the same area?Which areas do you see the most diversity in generations?Look on the map for where you, your parents, aunts, uncles, and grandparents live. Do they live in areas where their generation is the most predominant?

According to a survey conducted by Statista Consumer Insights among Generation Z in China, ** percent of respondents were trying to spend less money in light of the economic circumstances as of September 2024. In addition, ** percent of respondents felt that their cost of living has increased notably, and ** percent had been experiencing stress and anxiety. However, ** percent of respondents shared none of the worries mentioned in the survey.

Employment data in the United States for the millennial and baby boomer generations, broken up by the state, MSA, and industry for 2009-2013.

Source: Economic Modeling Specialists Inc (EMSI)

This research has revealed valuable insights into the motivations, opportunities, challenges, strategies and experiences experienced by Generation Z technopreneurs in Indonesia. Using a thematic qualitative approach and in-depth interviews, this study found that Generation Z is driven by intrinsic motivations such as interest in technology and the desire to have a positive impact. They are able to identify business opportunities from unmet market needs and develop innovative technology-based solutions. However, they also face challenges such as difficulty accessing start-up funding and a lack of business experience. To overcome these obstacles, Generation Z technopreneurs utilize digital technology and collaboration, with social media playing an important role in building networks, seeking funding, and conducting digital marketing. Even though it is full of challenges, the experience of building a technology-based business provides satisfaction and personal growth for Generation Z technopreneurs. This research confirms the great potential that Generation Z has as agents of change in driving the growth of technopreneurship in Indonesia. With their enthusiasm, courage and resilience, they have the opportunity to bring innovation and new solutions to the world of technology, contributing to increasing the competitiveness of the national economy through the creation of new jobs and innovative technological solutions. These findings provide practical implications for educators, policy makers and industry players in designing appropriate supporting programs, educational curricula and policies to guide and facilitate the growth of Generation Z technopreneurs in Indonesia.

Income quintiles are assigned based on equivalized household disposable income, which takes into account differences in household size and composition using a method proposed by the Organization for Economic Co-operation and Development (OECD). The OECD-modified" equivalence scale assigns a value of 1 to the first adult Age groups refer to the age group of the major income earner. Housing tenure of household Refers to the main source of income for the household, either from wages and salaries, self-employment income, net property income, current transfers received related to pension benefits, or from other current transfers received from non-pension related sources (others). Distributions by generation are defined as follows and are based on the birth year of the major income earner : pre-1946 for those born before 1946, baby boom for those born between 1946 and 1964, generation X for those born between 1965 and 1980 and millennials for those born after 1980. Note that generation Z has been combined with the millennial generation as their sample size is relatively small.

Generation Z’s entry into the workforce has led to changing workplace expectations, in which Gen Z employees are willing to walk away if these expectations are not met. In 2022, ** percent of Gen Z employees in the United States said that they would walk away from a job due to an unsatisfactory salary, while ** percent said they would quit if the job caused burnout and lacked work-life balance. ** percent of Generation Z employees also reported that they would quit if there were no remote work options available. Gen Z at Work Due to challenges such as the COVID-19 pandemic and recent economic turmoil, there are unique factors influencing Generation Z employees looking for work. Many prospective Gen Z employees are entering the workforce at a time of historically low unemployment, with job openings also much higher than usual. As a result, Gen Z employees are more likely to apply to jobs that meet their expectations regarding salary and work-life balance. Gen Z’s desire for clear salary expectations has shown to be a major factor on whether they even apply for a job. Additionally, Gen Z employees are more likely to appreciate flexible working options, with ** percent saying that they preferred hybrid work while ** percent preferred for work to be fully remote. Importance of Education While Generation Z has been reported to be the most educated age group in the United States, only ** percent of Gen Z employees said that they were very satisfied with how well their education has prepared them for the workforce. Therefore, having the opportunity to continue learning at work is an important factor for Gen Z employees in the United States, who value career development and workplace training. In particular, ** percent of surveyed Gen Z employees said that they would want to receive leadership training at work, while ** percent wanted to receive training in mental health.

Introduction

Creator Economy Statisitcs: The Creator Economy is an evolving digital ecosystem where individuals generate income by creating and sharing original content, products, or services directly to online audiences. This economy grew alongside the rise of social media and e-commerce platforms, enabling creators such as influencers, artists, educators, and gamers to build personal brands and earn through sponsorships, advertisements, subscriptions, and direct sales. Technological advancements have democratized content creation, making it accessible to anyone with internet access, thus transforming how creativity and expertise are shared and monetized without reliance on traditional media or corporate intermediaries.

The Creator Economy industry encompasses the platforms, tools, investors, and businesses that support creators’ activities and monetization efforts. It includes social media networks, content marketplaces, payment systems, analytics services, and creator enablement tools that allow individuals to grow their audience, manage their presence, and commercialize their work. This industry is rapidly expanding with millions of active creators worldwide and significant capital inflows. It is shifting traditional marketing approaches as brands increasingly partner with creators for authentic engagement and niche targeting.

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TLDR: Editor’s Choice

• The global creator economy is set to grow from USD 149.4 Billion in 2024 to USD 1,072.8 Billion by 2034, at a strong 21.8% CAGR.
• Only 4%-10% of creators earn over USD 100K annually, making high-income professionals rare.
• YouTube, Instagram, and TikTok deliver the best ROI for brand campaigns.
• Over 91% of creators now use generative AI to scale content production.
• Around 500 million people are active in the passion economy.
• Gender split shows 52% men, while 46.7% of creators work full-time.
• Just 13% are Gen Z, and 67% have 1K–10K followers, highlighting micro-creators’ dominance.
• On average, creators take 6.5 months to earn their first dollar.
• 70% spend 10 hours or fewer weekly on content production.
• Merchandise businesses generate USD 500 Million+ annually within this ecosystem.
• Shopify leads the creator economy revenues with USD 5.2 Billion.

This statistic shows the results of a 2013 survey among millennials (those aged between 18 and 30) about which country they think will be the biggest driver in the next 10 years for the growth of the global economy. The survey was conducted globally. ** percent of the surveyed millennials believe that India will be the country that drives the growth of global economy the most in the next 10 years.

The metaverse is progressively advancing toward broad application in real-world scenarios. However, as a key driving force of today’s digital economy, Generation Z has not demonstrated sufficient enthusiasm for participation. This study adopts a mixed-methods approach to systematically explore the resistance behaviors of Generation Z toward the metaverse and their underlying causes. In the first phase, grounded theory was employed to analyze data from 25 in-depth interviews. Through three levels of coding, seven key resistance factors were identified: interpersonal alienation, psychological burden, social norm conflict, value doubt, perceived complexity, perceived unavailability, and perceived risk. In the second phase, structural equation modeling (SEM) was used to examine the net effects of these factors on resistance behavior. The results indicate that all factors except perceived complexity have a significant positive influence on resistance behavior. In the third phase, fuzzy-set qualitative comparative analysis (fsQCA) was employed to identify nine configurations of conditions that lead to resistance, thus addressing the limitations of SEM in capturing complex causal relationships. This study not only extends the theoretical boundaries of user behavior research in the metaverse context but also provides empirical insights for platforms aiming to optimize user experience and develop operational strategies targeted at Generation Z.

As environmental degradation escalates, the critical need to understand green purchasing intentions and behaviours among Vietnamese Generation Z becomes increasingly urgent. Although the Theory of Planned Behavior (TPB) has been extensively applied to study pro-environmental behaviours, there remain discrepancies in how green attitudes, green subjective norms, and green perceived behavioural control influence green purchasing intentions and green purchasing behaviours. This study aims to clarify these relationships within the unique socio-economic and cultural context of Vietnamese Generation Z, a demographic influenced by collectivistic cultural values, generational characteristics, and dynamic economic conditions. These factors may reshape the conventional dynamics of TPB. Utilising quantitative methodologies, this research analysed responses from 237 Vietnamese Generation Z consumers through structural equation modelling to assess the impacts of green attitude, green subjective norms, and green perceived behavioural control on green purchasing intentions and green purchasing behaviours, particularly focusing on the mediating role of green purchasing intentions. The findings demonstrate that green attitude, green subjective norms, and green perceived behavioural control significantly affect both green purchasing intentions and green purchasing behaviours, thereby confirming the mediating influence of green purchasing intentions. This research reaffirms TPB’s relevance in Vietnam’s distinct cultural and economic environment while contributing to the broader TPB literature by exploring the mediating effects among key variables. These results also underscore the need for policymakers and businesses to create community-oriented environmental programs and tailor marketing strategies to enhance pro-environmental purchasing among young consumers.

"Targeting Millennials in Financial Services", report explores the attitudes and behaviors millennials have with regards to their financial services, using our extensive surveying of consumers in 20 key banking markets around the world. It identifies those aspects of the customer experience that financial services providers need to address to effectively engage with millennials and highlights successful providers, products, services, and campaigns. Best practice examples and studies presented are drawn from around the world and across the economy, encompassing banks, insurers, investment managers, consumer brands, and retailers. Read More

According to Cognitive Market Research, the global Gig Economy market size was USD 561245.2 million in 2024. It will expand at a compound annual growth rate (CAGR) of 17.20% from 2024 to 2031.

North America held the major market share for more than 40% of the global revenue with a market size of USD 224498.08 million in 2024 and will grow at a compound annual growth rate (CAGR) of 15.4% from 2024 to 2031.
Europe accounted for a market share of over 30% of the global revenue with a market size of USD 168373.56 million in 2024 and will grow at a compound annual growth rate (CAGR) of 15.7% from 2024 to 2031.
Asia Pacific held a market share of around 23% of the global revenue with a market size of USD 129086.40 million in 2024 and will grow at a compound annual growth rate (CAGR) of 19.2% from 2024 to 2031.
Latin America had a market share of more than 5% of the global revenue with a market size of USD 28062.26 million in 2024 and will grow at a compound annual growth rate (CAGR) of 16.6% from 2024 to 2031.
Middle East and Africa had a market share of around 2% of the global revenue and was estimated at a market size of USD 11224.90 million in 2024 and will grow at a compound annual growth rate (CAGR) of 16.9% from 2024 to 2031.
The transportation-based services category is the fastest growing segment of the Gig Economy industry

Market Dynamics of Gig Economy Market

Key Drivers for Gig Economy Market

Changing work approach driving the gig economy

The shift in work approach, particularly among younger generations, is a key driver of the gig economy. Millennials and Gen Z are prioritizing work that aligns with their passions and interests, seeking flexibility and autonomy over traditional career paths. The shift is majorly driven by the desire for work-life balance, alternate income sources and ability to work remotely, from anywhere. This shift has been on the rise particularly since the global pandemic that had pushed people to work from their homes and across various digital platforms. Businesses are embracing the flexible work arrangements to reduce costs and access specialized skills.

For instance,

Global research from the World Employment Confederation (WEC) finds that 83% of senior executives say that, since the pandemic, workers place as much value on flexibility in terms of when and where they work as on compensation.
A 2022 LinkedIn survey found that Gen Z workers were the cohort most likely to have left a role because of a perceived lack of flexibility (72% fell into this category, compared with 69% of Millennials, 53% of Gen X and 59% of Baby Boomers).
53% of Gen Z workers who freelance are moving away from traditional 9-to-5 jobs in favor of full-time freelancing.

(Source:https://insights.wecglobal.org/the-work-we-want/home/workplace-policy-younger-generations#:~:text=For%20example%2C%20new%20global%20research,the%20priorities%20of%20younger%20people. )

(Source: https://www.upwork.com/resources/gig-economy-statistics )

The digitalization of work is fueling demand for more gigs

Driven by technological advances and the increasing digitalization of skills and processes, the gig economy has expanded rapidly, by making work accessible to more people around the globe. The rise of online marketplaces like Upwork, Uber and Fiverr have made it easier for freelancers to find work and for companies to access a more flexible workforce. Improved technology and digital infrastructure have further made it easier and cheaper to connect with gig workers. The rise of e-commerce platforms and on-demand services such as ride-sharing, food delivery rely majorly on gig workers, contributing significantly to the growth of gig economy. Digital tools like instant messaging and video conferencing along with collaborative platforms like slack, MS Teams make it easy for employees to communicate from anywhere at any time.

With Artificial intelligence (AI) becoming one of the fastest-growing sectors and skill sets for independent professionals, AI has contributed to the growth of gig economy. AI is significantly impacting the gig economy by automating tasks, improving matching of workers and jobs. AI powered platforms also help streamline the recruitment process for businesses, by matching candidates with suitable projects based on skills, experience and availability.

For instance,

95% of respondents said generative AI makes them more competitive and 66...

This data provides a comprehensive view of how the growing use of GLP-1 medications such as Ozempic, Wegovy, and Mounjaro is influencing food and beverage consumption across mid-sized cities in North America. It uncovers the behavioral and economic ripple effects of a rapidly expanding health trend, giving consumer brands, retailers, and investors the ability to measure, anticipate, and adapt to shifting demand patterns. As part of a larger platform of global consumer insights, this data is designed to be both region-specific and globally scalable, enabling benchmarking across cities, categories, and demographics worldwide.

At the center of this work is the recognition that the adoption of GLP-1s is no longer a niche health issue—it has become a mainstream factor reshaping household budgets, eating habits, and retail sales. Millions of consumers now report weight-loss and appetite management effects that directly alter how much they purchase, how often they dine out, and which categories they prioritize. For the food and beverage industry, the impact is structural. The question is not whether demand will change, but by how much, in which categories, and among which segments of the population.

The data captures the percentage of consumers in each city currently on GLP-1s and quantifies the corresponding reduction in spending across four major food and beverage categories: snacks, beverages, fast food, and groceries. By breaking down the impact at this level, the data highlights where the steepest cutbacks are occurring and how they differ by market context. Snacks and beverages may show discretionary pullbacks, while grocery staples can reveal subtler, long-term consumption declines. Fast food spend, often linked to convenience and impulse behavior, can serve as a leading indicator of shifting routines. This category-specific visibility ensures that brands can adjust strategy not only at the portfolio level but also within each business unit.

Geographically, the coverage focuses on ten mid-sized North American cities, including Austin, Denver, Charlotte, Portland, San Antonio, Ottawa, Calgary, Guadalajara, Tijuana, and Puebla. These urban centers are chosen to complement insights already available from major hubs like New York or Mexico City. They represent diverse economies and consumer profiles, from tech-driven cities with younger populations to more traditional centers with multigenerational households. This makes the data particularly valuable for brands aiming to expand beyond top-tier markets and understand the broader regional picture.

The demographic detail enriches the picture further. Each record in the data is tied to age group (Gen Z, Millennials, Gen X, Boomers), income bracket (low, middle, high), and household type (single, couple, family with children, multi-generational). This allows users to isolate how different population segments respond to GLP-1 adoption. For instance, middle-income families may register sharper reductions in grocery and snack purchases, while high-income singles could show steadier spend but with different category reallocations. These contrasts reveal the complexity of the Ozempic economy: its effects are not uniform but filtered through demographic and socioeconomic contexts.

The use cases for this data are wide-ranging. For FMCG brands, it signals where demand erosion is most pronounced and where portfolio adjustments or innovation are required. Retailers can use it to recalibrate inventory and assortment planning, ensuring they are not overstocked in categories where consumption is structurally declining. Food service operators gain insight into how reduced appetite translates into lower frequency of dining out and what that means for long-term revenue projections. Investors can track which categories, companies, and geographies are most exposed to GLP-1-related demand shifts, and which may benefit from adjacency opportunities such as health and wellness products.

The implications also extend to marketing. Traditional advertising may struggle to stimulate demand when appetite itself is suppressed. Instead, marketers must explore new strategies that align with evolving consumer priorities—smaller portion sizes, healthier alternatives, or bundling strategies that deliver value even in a lower-consumption environment. Understanding the demographic makeup of GLP-1 adoption provides a critical edge here, ensuring campaigns are targeted at the right segments with the right message.

Because this data is built on zero-party input directly from consumers, it provides an authentic and unfiltered signal of how real people are adjusting their behavior. It is not modeled or inferred from secondary sales data alone, which often lags behind shifts already happening in households. Instead, it reflects what consumers report about their own usage of GLP-1s and the tangible impact on their food and beverage spending. This immediacy is what makes the data so powerful: it ca...

Gig Economy Platform Market Outlook

According to our latest research, the global Gig Economy Platform market size reached USD 244.3 billion in 2024, demonstrating robust expansion fueled by digital transformation and increasing workforce flexibility. The market is projected to grow at a CAGR of 16.5% from 2025 to 2033, reaching an estimated USD 771.5 billion by 2033. This remarkable growth trajectory is primarily driven by the rising adoption of on-demand services, technological advancements, and the growing preference among both enterprises and individuals for flexible work arrangements.

One of the key growth factors propelling the gig economy platform market is the proliferation of digital technologies and the widespread adoption of smartphones and high-speed internet connectivity. These technological advancements have made it easier for individuals to access gig platforms, connect with clients, and perform a variety of tasks remotely or on-demand. The integration of AI, machine learning, and data analytics into gig platforms has further enhanced user experience, enabling better job matching, secure payment processing, and improved trust and transparency. As organizations increasingly seek cost-effective and scalable workforce solutions, gig economy platforms have emerged as a strategic tool to access specialized talent, optimize labor costs, and drive operational efficiency.

Another significant driver is the evolving workforce preferences, particularly among millennials and Gen Z, who value flexibility, autonomy, and work-life balance. The gig economy offers opportunities for freelancers, independent contractors, and part-time workers to choose assignments that align with their skills, interests, and schedules. This shift in workforce dynamics has led to a surge in the number of individuals participating in the gig economy, spanning sectors such as ride-sharing, delivery services, freelancing, and home services. Governments and regulatory bodies are also beginning to recognize the importance of the gig economy, introducing frameworks to ensure fair labor practices, social security, and worker protection, which in turn is fostering market stability and growth.

The COVID-19 pandemic has acted as a catalyst for the gig economy platform market, accelerating the adoption of remote work and digital platforms. As businesses and consumers adapted to new norms, demand for on-demand services such as food delivery, logistics, and remote freelancing soared. Enterprises, particularly small and medium-sized businesses, increasingly turned to gig platforms to address workforce shortages and maintain business continuity. This paradigm shift is expected to have a lasting impact, with more organizations integrating gig workers into their talent strategies and leveraging platform-based models to access global talent pools and drive innovation.

From a regional perspective, North America continues to dominate the gig economy platform market, accounting for the largest share in 2024, followed closely by Europe and Asia Pacific. The United States, in particular, is home to several leading gig platforms and a mature digital infrastructure, fostering high adoption rates among both enterprises and individuals. Asia Pacific is anticipated to witness the fastest growth during the forecast period, driven by rapid urbanization, expanding internet penetration, and a burgeoning young workforce. Emerging economies in Latin America and the Middle East & Africa are also experiencing notable growth, supported by government initiatives and increasing entrepreneurial activity. These regional trends highlight the global nature of the gig economy and its potential to reshape the future of work across diverse geographies.

Component Analysis

The gig economy platform market is segmented by component into software and services, both of which play integral roles in the market’s ecosystem. Software forms the backbone of gig platforms, providing the digital infrastructure necessary to facilitate seamless interactions between service providers and clients. Key features of gig economy software include user-friendly interfaces, secure payment gateways, real-time communication tools, and advanced algorithms for job matching. The increasing adoption of AI and machine learning technologies within these platforms has significantly improved the accuracy of job recommendations, fraud detection, and personalized user experiences. As platforms continue to evolve, the deman