Big Data-Driven Socioeconomic Development: An Interdisciplinary Approach

Introduction

Big data has become one of the most important frontiers for research and development in academia and industries (Richardson, Schlegel, Sallam, Kronz, & Sun, 2021; Sun & Stranieri, 2021). Big data technologies including big data analytics have been revolutionizing our work, lifestyles, economies, and societies (Sun, Sun, & Strang, 2018) (Sun & Wu, 2021). Big data analytics has become a mainstream market adopted broadly across industries, organizations, geographic regions, and among individuals to facilitate big data-driven decision making for individuals, organizations, and governments (Richardson, Schlegel, Sallam, Kronz, & Sun, 2021). Big data and big data analytics have increasingly become critical elements for nearly all industries and keys to a successful digital business and intelligent business, digital trade and digital economy.

Socioeconomic development has drawn increasing attention in academia, industries, and governments. For example, Miladinov (2020) looks at the relationship between socioeconomic development and life expectancy based on the evidence from the EU accession candidate countries. The UN has used the Human Development Index (HDI) to measure the socioeconomic development of a nation worldwide annually (UNDP, 2020). The relationship between big data and socioeconomic development has drawn a certain attention in academia. For example, Pappalardo, et al. uses big data to study the relationship between human mobility and socioeconomic development (2015). However, the following research issues deserve significant attention for academia and industries.

• 1.

  Why does big data matter to socioeconomic development?

• 2.

  What is the relationship between big data and socioeconomic development?

• 3.

  How can big data and big data technologies contribute to socioeconomic development?

This chapter will address each of them from an interdisciplinary approach, consisting of a fundamental, technological, and socioeconomic perspective. To address the first research issue, This chapter looks at 10 Bigs, the ten big characteristics of big data from fundamental, technological, and socioeconomic approaches. This chapter reviews digital technologies and big data analytics. This chapter looks at digital trade and economy and analyzes that eSMACS goods and services have played an important role in digital trade and economy. To address the second research issue, this chapter looks at socioeconomic development and its relationships with the HDI of the UN and presents a GDDP (gross domestic data products) as a GDP-like data metric for measuring economic performance and social progress. To address the third research issue, this chapter presents a strategic model for big data-driven socioeconomic development, which consists of two levels: The first level is big data-centered, including big data-driven technologies, services, economies, and societies. The second level consists of big data-driven eSMACS technology, service, economy, and society as the example of the first level.

The remainder of this chapter is organized as follows. Section 2 examines 10 Bigs, the ten big characteristics of big data. Section 3 reviews digital technologies and big data analytics. Section 4 looks at digital computing, digital technologies and big data analytics, Section 4 overviews digital industry, trade, and economy; and analyzes the role of eSMACS goods and services in digital trade and economy. Section 5 looks at socioeconomic development and presents the GDDP as a GDP-like data metric for measuring economic performance and social progress. Section 6 discusses big data-driven smart socioeconomic development and exemplifies it with big data-driven eSMACS technologies, services, economies, and societies. The final sections discuss the related work and end this chapter with some concluding remarks and future work.