Generational Dynamics of Innovation Adoption in Chinese Consumer Markets: A Comprehensive Analysis
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Keywords

Innovation adoption
Consumer markets
Generations
Digital technologies
Social media platforms
E-commerce ecosystems

DOI

10.26689/pbes.v6i6.5693

Submitted : 2023-11-28
Accepted : 2023-12-13
Published : 2023-12-28

Abstract

This extensive and comprehensive study delves into the intricate dynamics of generational responses to innovative marketing strategies within the dynamic landscape of the Chinese consumer market. Given China’s rapid economic growth and technological advancements, it has become imperative for businesses and marketers to grasp how different generations engage with marketing innovations. This study encompasses Baby Boomers, Generation X, Millennials, and Generation Z, each shaped by unique life experiences and societal contexts, resulting in distinct preferences and behaviors. Furthermore, the study offers a thorough analysis of how diverse generations in China interact with and respond to innovative marketing strategies, providing academic researchers and businesses operating in the rapidly evolving Chinese consumer marketing landscape with actionable insights. Understanding these generational dynamics is crucial for developing marketing strategies that resonate with diverse generational segments and harnessing the power of technology to connect with consumers across all age groups. The dynamic landscape is further enriched by the proliferation of digital technologies, social media platforms, and e-commerce ecosystems. This study scrutinizes how these generational cohorts interact with innovation in marketing, considering preferences, technological adoption patterns, cultural influences, and attitudes toward trust and privacy. Additionally, it examines generational disparities in marketing channel preferences, offering valuable insights for companies aiming to tailor their marketing strategies to effectively engage diverse generational segments in China. Importantly, this research underscores the strategic significance of understanding generational differences in marketing innovation adoption. It emphasizes that this knowledge is not solely an academic pursuit but rather a critical necessity for companies seeking to thrive in one of the most competitive consumer markets globally. By acknowledging and responding to the distinct preferences and behaviors of various generational cohorts, businesses can forge meaningful connections, optimize return on investment, and adeptly navigate the evolving consumer landscape.

References

Park K, Igielnik R, 2020, On the Cusp of Adulthood and Facing an Uncertain Future: What We Know About Gen Z So Far. Pew Research Center, viewed September 12, 2023, https://www.pewresearch.org/social-trends/2020/05/14/on-the-cusp-of-adulthood-and-facing-an-uncertain-future-what-we-know-about-gen-z-so-far-2/

Howe N, Strauss W, 2000, Millennials Rising: The Next Great Generation, Vintage Books, New York.

Bruton GD, Lau C-M, 2008, Asian Management Research: Status Today and Future Outlook. Journal of Management Studies, 45(3): 636–659. https://doi.org/10.1111/j.1467-6486.2007.00758.x

Hofstede G, Hofstede GJ, Minkov M, 2010, Cultures and Organizations: Software of the Mind, Third Edition, McGraw Hill Education, New York.

Venkatesh V, Thong JYL, Xu X, 2012, Consumer Acceptance and Use of Information Technology: Extending the Unified Theory of Acceptance and Use of Technology. MIS Quarterly, 36(1), 157–178.

Rogers EM, 2010, Diffusion of Innovations, Fourth Edition, Free Press, New York.

Zhao X, Lynch JG Jr, Chen Q, 2010, Reconsidering Baron and Kenny: Myths and Truths about Mediation Analysis. Journal of Consumer Research, 37(2), 197–206. https://doi.org/10.1086/651257

Goldsmith RE, Flynn LR, Clark RA, 2012, Materialism, Brand Engaged and Status Consuming Consumers and Clothing Behaviors. Journal of Fashion Marketing and Management, 16(1), 102–119. https://doi.org/10.1108/13612021211203050

Rogers EM, 2003, Diffusion of Innovations, Fifth Edition, Free Press, New York.

Venkatesh V, Thong JYL, Xu X, 2016, Unified Theory of Acceptance and Use of Technology: A Synthesis and the Road Ahead. Journal of the Association for Information Systems, 17(5), 328–376.

Wang Y, Sun S, 2010, Understanding the Impact of Social Media on People’s Lives: An Integration of Social Presence Theory and Social Capital Theory. AMCIS 2010 Proceedings, 2010: 396.

Belk R, 2014, You are What You Can Access: Sharing and Collaborative Consumption Online. Journal of Business Research, 67(8), 1595–1600. https://doi.org/10.1016/j.jbusres.2013.10.001

Vinson DE, Scott JE, Lamont LM, 1977, The Role of Personal Values in Marketing and Consumer Behavior. Journal of Marketing, 41(2): 44–50. https://doi.org/10.1177/002224297704100215

Wang Y, Yu C, 2017, Social Interaction-Based Consumer Decision-Making Model in Social Commerce: The Role of Word of Mouth and Observational Learning. International Journal of Information Management, 37(3), 179189.https://doi.org/10.1016/j.ijinfomgt.2015.11.005

Smith AN, Fischer E, Chen Y, 2012, How Does Brand-Related User-Generated Content Differ across YouTube, Facebook, and Twitter? Journal of Interactive Marketing, 26(2): 102–113. https://doi.org/10.1016/j.intmar.2012.01.002

Zhang JQ, Craciun G, Shin D, 2010, When Does Electronic Word-of-Mouth Matter? A Study of Consumer Product Reviews. Journal of Business Research, 63(12), 1336–1341. https://doi.org/10.1016/j.jbusres.2009.12.011

Soelaiman L, Ekawati S, 2022, The Role of Social Media in Enhancing Business Performance. Proceedings of the Tenth International Conference on Entrepreneurship and Business Management 2021 (ICEBM 2021). https://doi.org/10.2991/aebmr.k.220501.060

Holt D, 2016, Branding in the Age of Social Media. Harvard Business Review, 94(3), 40–48 + 50.

Berger J, Milkman KL, 2012, What Makes Online Content Viral? Journal of Marketing Research, 49(2): 192–205. https://doi.org/10.1509/jmr.10.0353

Lee Y, Kozar KA, 2012, Investigating the Effect of Website Quality on E-Business Success: An Analytic Hierarchy Process (AHP) Approach. Decision Support Systems, 42(3), 1383–1401. https://doi.org/10.1016/j.dss.2005.11.005