Unpacking the Resource Curse and Realism Challenges on Economic Development in the Democratic Republic of Congo (DRC)

The third theme of the book seeks to understand the role of mineral resources in the African continent's socio-economic development. The case study of the DRC is used to understand the role played by the state-owned mining company Gecamines to socio-economic conditions of employees and the country's development at large. Resource curse and realism theories are utilised in this case study to unpack the role of mineral resources to Gecamines employees' access to education and healthcare in particular and to the entire country in general. The chapter employed a case study design with a qualitative approach research in its endeavour of exploring Gecamines' socio-economic contribution to its employees. Semi-structured interviews were conducted with Gecamines' managers, unskilled mine workers, and the Provincial Department of Mines' officers.

Contribution of Mining Operations Towards Education, Healthcare, Food Security, Housing, Sports, and Recreation in Katanga Province of the DRC

Some resource-rich countries face challenges when it comes to the socio-economic development of its employees and the community at large. This study seeks to examine Gecamines' contribution to the socio-economic conditions of its employees based in the Lubumbashi area and to some extent the province of Katanga under the rubric of resource curse theory. Through this study, lessons can be learnt from the findings on how state-owned mining companies could work on improving their socio-economic contributions in the interest of the employees and the entire population through generated revenues for the state. The study employed a case study design with a qualitative approach research in its endeavour of exploring Gecamines' socio-economic contribution to its employees in the city of Lubumbashi and the development of Katanga Province as a whole. Semi-structured interviews were conducted with Gecamines' managers, unskilled mine workers, and the Provincial Department of Mines' officers in the city of Lubumbashi. The key findings from these interactions are that the company's low level of production caused by poor management, political interference, corruption, and poor institutions had negative ramifications on the socio-economic conditions of the workers. A remedy to these challenges lies in strengthening the country's institutions to fight corruption and poor management of parastatals. Autonomy of parastatals from political influence and control is also important to enable the company to play a crucial role in the socio-economic development of employees.

Pandemic Challenges for the Technological Startups in the Russian Regions

Technological startups help to adapt to the global risks and allow one to track future trends. This paper identifies the main trends and birth factors of new high-tech companies in the Russian regions during 2013-2020. In 2020, fewer than 10,000 startups were created, this number has been steadily declining (by 40% since 2015), especially during the pandemic (-21%). Most of the startups are concentrated in Moscow, the Moscow region, St Petersburg, and the largest metropolitan areas. The share of the Leningrad, Belgorod, Kaliningrad, Lipetsk, Ulyanovsk, and Kaluga regions is growing due to the proactive policies of local authorities. Most startups are associated with knowledge-intensive services for business (B2B) and digital technologies. In 2020, their number increased in pharmaceuticals (about 100%) and in the production of medical devices (by about 30%).Based on the results of econometric analysis, start-up activity in Russia, analogous to countries with an established market economy, depends upon human capital concentration, market access, and a favorable business climate. Universities, through attracting students, especially those in STEM specialties, stimulate startup creation; although the share of university startups does not exceed one third of a percent. Budgetary and university expenditures on R&D are ineffective in terms of creating new companies. The influence of development institutions on start-up activity was not found, while clusters and technology parks have a weak effect. The growth of startups is lower in regions with a predominance of large organizations, as well as in resource centers. The latter may be one of the manifestations of the “resource curse”. Startup activity is stable over time and depends on the situation in neighboring regions, which limits the chances to change the situation by means of entrepreneurship support policy. During the pandemic, start-up activity decreased minimally in regions with large metropolitan areas and a high level of education. Recommendations include tools for establishing a more balanced cross-regional situation by implementing the model of an entrepreneurial university, an expansion of start-ups’ access to capital and markets, and the regionalization of entrepreneurship policies.