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2021 Review | Research on macro and meso levels

Macro-level Resilience

At the Macro level, we are keen to assess whether the selected cases (India as well as Malaysia) are confronting premature deindustrialization amidst an abandoning of the commitment toward upgrading its productive sectors. The case of Korea (as well as Taiwan) will be used to compare the productive dynamics. We will also examine what measures have been taken by India (and also Malaysia) to address income inequality and to achieve resilient economies.

As for the Dynamic Capabilities assessment, we are keen to assess if the growth and wellbeing agendas of India and South Korea evolved along with societal empowering agendas. We are interested in examining evolution particularly in the time of pandemic crisis in 2020. The assessments will be compared to our observations for Taiwan and Malaysia cases. For India and South Korea we will examine the following factors in driving resilient society:

  1. Progressive and systematic investment in industrial upgrading programs,

  2. Advancement of civil services, human capital development,

  3. Social capital-cum-civil society empowerment

  4. Whether the interest of the society to take ownership in the process of collective welfare building is triggered from such investment. If the interest from the society is high – similar to the situation in tiger economies (Taiwan and South Korea) – this would point to the possible transition of India and Malaysia toward achieving resilient nations in the near future.

  5. We will examine the income inequality index (Gini) and assess whether there is gradual transformation of the economy from informal to formal orientation. We will also examine the impact of the pandemic crisis in 2020 on inequality.

A review of such transformation is crucial, as the formal economy conveys social security in the labour market and private firms in the formal setting are driven to invest in upskilling their employees. In addition, a government which administers a formal economy tends to receive higher revenue (from tax). As such, it would have a higher budget for social-related spending.


Meso-level Resilience

In addition, the meso-level research also plans to discover which system orientation is most resilient is particularly timely, as many cities and regions are currently facing challenges on various fronts – be it the spectre of a viral pandemic that now threatens all countries or an economic recession that has crippled growth and development. Our exploratory review of cities/regions will be grounded in the three orientations, as we wish to profile cities/regions built on grassroots innovation characteristics so that we may unveil the dynamics of their growth paths and their resulting resiliency. In studying the resiliency of cities around the globe, we postulate two possible impacts to growth when a region encounters difficult conditions.

  1. First, for a resilient city, the growth path will demonstrate a quick recovery following an economic downturn – implying that cities or regions of certain orientations will be determined to consistently upgrade their systems despite interruption.

  2. In contrast, in inherently fragile cities or regions, we will see a different growth rate after encountering a shock. This is particularly relevant to highly-specialised, rigidly-concentrated, or old industrial regions – as they are found to be vulnerable to crises (Sweeney et al. 2020).

Besides assessing the innovation systems in different regions, this project also takes on the investigation of a resilient industry. Specifically, the migrant labor supply chain for the semiconductor industry. Since most of the chip production processes require a large amount of labor forces, especially for the night shifts, many firms rely on migrant labor for the huge demand. This project therefore aims to investigate the labor supply chains of the semiconductor industry, and delineate the transformation of the supply chains under COVID-19.


Figure. The migrant labor supply chain for the semiconductor industry.

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