Unleashing technological advancements through foreign direct investments in West Africa's non-oil manufacturing sectors

Unleashing technological advancements through foreign direct investments in West Africa's non-oil manufacturing sectors | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Unleashing technological advancements through foreign direct investments in West Africa's non-oil manufacturing sectors Isaac Mantey This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4228449/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract This paper explores the potential of Foreign Direct Investments (FDI) to drive technological advancements and promote sustainable growth in West Africa's non-oil manufacturing sector. The purpose of the study is to evaluate and ascertain the technological advancement that has been accompanied by FDI in West African countries. This study uses the FDI dataset of 5 West African countries and adopts the panel data analysis that spans from 1990 – 2022 to evaluate the factors that contribute to the diffusion and adoption of technological innovation. Data were sourced from the World Bank, International Monetary Fund, and Investment Promotion centers of selected countries. Findings from the study showed that factors that contribute to the diffusion and adoption of technological innovation come from FDI, political indicators, and Gross Domestic Product (GDP). Thus, there is a positive relationship between FDI and GDP on technological diffusion and adoption; the higher the FDI and GDP size the more improved the adoption and diffusion of technology in the specific market across the continent. The negative relationship between political stability and technology diffusion proves that the lower the occurrence of terrorism or political turmoil the higher the adoption of technology in manufacturing. The study recommends the need for governments to improve political stability and set up technology hubs and clusters to facilitate knowledge sharing and collaboration to absorb technology diffusion in their respective economies. JEL Codes: F2, L6, O33 foreign direct investment gross domestic product technology transfer non-oil manufacturing sectors west Africa. Figures Figure 1 1. Introduction Foreign Direct Investments (FDI) have long been recognized as a significant driver of economic growth and development in emerging markets (Fanglin and Risha, 2019 ; Adu-Danso and Abbey, 2020; Sun, 2011). The non-oil manufacturing sector in West Africa holds immense potential for fostering technological advancements through FDI. The non-oil sectors play a pivotal role in driving economic diversification and sustainable development. As countries in the region seek to reduce their dependence on oil exports and build more resilient economies, the non-oil sectors emerge as key drivers of growth, job creation, and technological advancement. Foreign Direct Investments (FDIs) have been growing in West African countries between the period 2012 – 2021 on an average of 5 – 8 % annually (IMF, 2021). FDI is necessary for every country to grow since it helps to inject extra capital to help stimulate production and manufacturing activities. Thus, FDI has long been recognized as a significant economic growth and development driver in emerging markets (Chen et al., 2015; Ricken and Malcotsis, 2018). The non-oil sectors mostly comprise Agriculture and Agribusiness, Manufacturing, Services, Mining and Minerals, and Construction among others (Adu-Danso and Abbey, 2012; Park and Tang, 2021). These non-oil sectors hold immense potential for fostering technological advancements, generating employment opportunities, and diversifying economies. In West Africa, these non–oil sector firms encompass a wide range of industries, including textiles, food processing, electronics, machinery, and automotive. Additionally, Agribusiness involves processing, packaging, and exporting agricultural products, adding value along the supply chain. Furthermore, the services sector includes finance, telecommunications, tourism, education, and healthcare. Expanding service industries can lead to improved infrastructure, quality of life, and opportunities for skilled employment. Also, concerning minerals and mining, there are sectors such as sustainable mining practices for extra gold, diamond, and bauxite, that contribute to the mining sector. Most importantly, promoting manufacturing activities can lead to value addition, job creation, and technological advancements (Antwi et al., 2016). Policy implementation is critical for firms and businesses in West Africa to adapt to technological advancement through FDI (Chang et al., 2016; Huynh et al., 2019). FDI channeled by investors brings with them advanced technologies, managerial expertise, and best practices from their home countries (Fu and Zanello, 2020). Technological advancement has supported developed countries with a huge impact on economic growth and development (Adzroe, 2015). The study from Nketiah-Amponsah and Sarpong (2019) noted that considering the growing inflows of FDI into non-oil sectors like Agriculture, Services, Manufacturing, and Infrastructure in countries like Ghana, Nigeria, Cote d’Ivoire, Senegal, Sierra Leone, Mali, and Burkina Faso. There has been a need for local manufacturing countries to capture and inculcate technologically advanced tools and resources in their local operations (Sarkodie et al., 2019; Atiase et al., 2020). Thus, countries such as Ghana and Nigeria between the period of 2016 – 2022 have received 15% increment in the FDI into the sectors of Agriculture and this in the long run has marginal been channeled into technological implementation. However, the adoption of tractors and equipment has seen wide adoption in the field of agriculture. The inflow of technologies can help upgrade local manufacturing processes, enhance product quality, and improve overall efficiency. The adoption of technological resources and tools in sectors such as agriculture, services, and manufacturing among others, have been evaluated to be in the lower stages. While Services have seen 25% adoption of technological activities between the period of 2015 and 2021. Other non-oil sectors have seen a massive boost in the inculcation of technology in operations. While the potential for technological advancement through FDI is huge, there is also the need to evaluate which areas of FDI can impact positively. Technology transfer through FDI has propelled the economies of different countries to much higher heights (Jibrilla and Dunusinghe, 2021). This has been one of the key factors of economic growth and development. FDI often encourages research and development (R&D) in technological activities in host countries (Auffray and Fu, 2015). Collaboration between local research institutions and foreign investors can lead to technological innovations that address specific challenges faced by West African economies. This can foster a culture of innovation and entrepreneurship, further propelling the non-oil manufacturing sector. Technological advancements play a crucial role in driving economic development and shaping the trajectory of nations (Wako, 2018). The significance of technological advancements for economic development is multifaceted and far-reaching. Few have been ascertained; thus, local workers can benefit from skill development and training, which can have a long-lasting positive impact on the labor force (Seyoum et al., 2015). FDI comes with varied factors and resources. However, the ability to establish which among these factors can be absorbed locally and used for business manufacturing and production is critical for the economic growth and development of countries in West Africa. FDI propels Technology Transfer (Fu and Zanello, 2020), thus,foreign investors bring with them advanced technologies, managerial expertise, and best practices from their home countries. These technologies can help upgrade local manufacturing processes, enhance product quality, and improve overall efficiency. Local workers can benefit from skill development and training, which can have a long-lasting positive impact on the labor force. FDI provides the necessary technological Knowledge Transfer and Technology Spillovers (Auffray and Fu, 2015). Thus, foreign investors often bring advanced technological expertise, best practices, and innovative processes that can be shared with local companies. This knowledge transfer can lead to technology spillovers, where local firms learn from foreign investors, adopt new techniques, and improve their operations. FDI often encourages research and development activities in host countries (Wako et al., 2018; Auffre and Fu, 2015). Collaboration between local research institutions and foreign investors can lead to technological innovations that address specific challenges faced by West African economies. This can foster a culture of innovation and entrepreneurship, further propelling the non-oil manufacturing sector. The adoption of technology in service has seen some growth in countries such as Nigeria, Ghana, Cote d’Ivoire, and others. This study focuses on evaluating the gaps that have lowered the ability of local firms to absorb and utilize technological advancement associated with FDI in non-oil manufacturing industries in West Africa. With the need for many West African countries to diversify their investment into manufacturing, services, agribusiness, and infrastructure, there is a need to evaluate the technological advancements that have been unleashed in these sectors. Problem Statement In West Africa, studies have posited the fact that local firms and businesses have been established to have low absorptive capabilities (Osabutey and Jackson, 2019; Akhtaruzzaman et al., 2018; Shukra et al., 2018). Studies have identified that depending on the various technological advancements from FDI, specific sectors can adopt an effective adaptive capacity to inculcate technological resources for local businesses and firms (Antwi et al., 2013). One of the non-oil manufacturing sectors such as agriculture has witnessed little technological advancement in their operations (Auffray and Fu 2015; Fu and Zanello, 2020). This means that the production capacity is still low, and they cannot compete on the global stage even though there are FDI inflows. Likewise, the issue of limitation on absorptive capacities. Thus, FDI, which is formed based on partnership, should be able to help in technological transfers to local businesses and enterprises. However, there is a gap in which these local enterprises have not been able to utilize this to their advantage. Compared to companies and businesses in China that have leveraged foreign technology to compete effectively, local companies in West Africa have not fully utilized these technological advantage opportunities. Developing countries in West Africa hardly utilize the technologically advanced capabilities that FDI brings. The study from Auffray and Fu (2015) noted that there is a lack of human resource capacity to absorb the technological innovation brought in by the FDI. In addition, absorptive capacity limitations. Local industries may lack the necessary absorptive capacity to effectively absorb and implement foreign technologies. This could result from a shortage of skilled human resources, limited access to training and education, or underdeveloped technical expertise needed for technology integration. While there have been studies on FDI in traditional, oil, and non-oil industries like manufacturing in West African countries (Managi and Bwalya, 2010), there are still gaps that need to be filled. Thus, West Africa's non-oil manufacturing sector currently faces significant challenges that hinder the effective utilization of FDI for technology transfer, knowledge dissemination, and sustainable economic development. These challenges encompass regulatory barriers, inadequate infrastructure, limited access to skilled labor, and a lack of coordinated policies from the public and government institutions. As a result, the region's potential to diversify its economy, reduce dependency on oil exports, and create job opportunities remains largely untapped. Addressing these challenges and identifying strategies to create an enabling environment for FDI-driven technological advancements is crucial for unlocking the transformative potential of West Africa's non-oil manufacturing sector and promoting a more resilient, inclusive, and sustainable economic landscape. Aim of the study This study aims to evaluate and ascertain the technological advancement that has been accompanied by FDI in West African countries. Additionally, the objectives of the study focus on evaluating the impact of this technological advancement on the development of businesses and the growth of their operations. Research Question The question that elucidates the necessary response is what are the factors that support the level of technological adaption accompanied by FDI in sub-Saharan African countries? Additionally, what are the government policies and efforts being made to sustain these factors to support technological adoption through FDI? Objectives of the study This study has focused on these objectives: a. To examine the types of technological advancements introduced through FDI in the non-oil manufacturing sector and their contributions to local industries. b. To evaluate the factors influencing the adoption and diffusion of foreign technologies within West Africa's non-oil manufacturing sector. c. To analyze the role of government policies, regulations, and institutional support in facilitating or hindering FDI-driven technological advancements. Delimitation of the study The delimitations of the study focus primarily on the technological advancements through foreign direct investments (FDI) in West Africa's non-oil manufacturing sector. Thus, evaluating the respective FDIs and how it has impacted technological advancements among the local businesses. Significance of the study This study is particularly important for local businesses and manufacturing companies in West Africa to harness the technological advancement that is infused by FDIs. This can improve their adaptive capabilities and ensure they have gained the necessary technological transfer and knowledge spillovers. This eventually improves their efficiency to compete globally and improves the margins of profitability and scale. Additionally, this study improves knowledge of the necessary strategies and practices that local businesses can adopt to gain more from the FDI’s facilitated Innovation and Research & Development (R&D). Thus, the ability to build Strategic partnerships between foreign investors and local institutions can stimulate innovation and R&D activities, leading to the creation of new products, processes, and solutions that cater for local and international markets. Theoretical Framework The theoretical framework of the study focuses on the concept of technological advancements through FDIs. The Innovation Diffusion Theory, formulated by Everett Rogers in the mid-20th century has been adopted by the study to provide the necessary framework and variables. At its core, this theory offers valuable insights into the dynamics of how FDI contributes to the adoption and diffusion of technological advancements within West Africa's non-oil manufacturing sector. The Innovation Diffusion Theory deals with the transfer of innovation from one specific context to the next, thus within the context of societal and business relationships there are direct and indirect procedures through which technological advancement can be transferred through FDI. Thus, the spread of a new idea is influenced by the innovation itself, communication channels, time, and a social system. Most importantly, the theory established that the willingness and ability to adopt an innovation depends on adopter awareness, interest, evaluation, trial, and adoption. People could fall into various categories for different innovations (Ajzen and Fishbein, 2005; Fishbein and Cappella, 2006) Concerning unleashing technological advancements through FDI in West Africa's non-oil manufacturing sector, the theory can bring much insight into relative advantage, compatibility, and efficiency in production through the adoption of foreign technologies by local industries. The key role is for local industries to be part of the majority adopters of the technology and influence driving the process. This theory provides the necessary key variables and factors to influence technological advancement through FDI in the West African context. Thus, the need to evaluate the challenges, and opportunities associated with FDI-driven technological advancements. The theory also harnesses the need for local companies to harness foreign investors’ technology such as operational technologies, management practices, and expertise, local industries, and businesses can be seen as potential adopters of these innovations. By analyzing FDI-driven technology adoption through the lens of the Innovation Diffusion Theory, we can explore how different segments of the local industry, from innovators to laggards, respond to and embrace the introduced technologies. Factors such as the perceived relative advantage of the technologies, compatibility with existing practices, and ease of implementation will influence the speed and extent of adoption. Incorporating the Innovation Diffusion Theory as a theoretical framework enriches our understanding of how FDI can lead to the diffusion and integration of advanced technologies, contributing to the growth, innovation, and sustainability of West Africa's non-oil manufacturing sector. 2. Literature Review The review of related literature, documents, and articles concerning the FDI towards technological advancements and knowledge transfer as well as the technological spillovers for local enterprises and businesses was reviewed. FDI has received incremental support from various governments and policymakers to enhance the operations and impact on local businesses and their impact. The issue concerning unleashing technological impact on the operations of local businesses and industries is partly related to the issue of the adaptive capacity of these businesses and enterprises (Auffray and Fu, 2015; You et al., 2020). The study by Fu and Zanello (2020) ascertained that FDI can contribute to skill development by offering training and education programs to the local workforce. This leads to an increase in the pool of skilled labor, which is essential for adopting and implementing advanced technologies. FDI and technological advancements in developing economies. The increase in FDI in major West African countries between the period of 2015 – 2022 has witnessed a growth rate of 15 – 19% per annum (World Bank, 2022). The growth in FDI over the years has not matched the impact of technological advancement in developing economies in West Africa (IMF, 2021). Additionally, there is the issue of the formation of industrial clusters around FDI-intensive regions, fostering knowledge exchange, innovation, and technology spillovers among firms (Chen et al., 2020). According to the IMF (2021) between the period of 1990 to 2020, Nigeria received much FDI % to GDP, and in the early 2000s to 2020, Ghana was portrayed as the country with the highest recipient of FDI % to GDP, the highest was attained in 2013 which was 9.58% of GDP, the lowest point was in 2003 which was 0.8% of GDP. This is shown in Figure 1 below. While South Africa received the highest value of FDI in the SSA between 2006 – 2014. Kenya, Cote d'Ivoire, and Nigeria have seen substantial growth in FDI in their economies. The table is illustrated in Figure 1 below. Table 1: FDI percentage to GDP Ghana South Africa Nigeria Cote d'Ivoire Kenya YR2015 6.46140124 0.438735792 0.621501637 1.079141547 0.883799936 YR2016 6.205533329 0.684612553 0.853395743 1.193758009 0.627591266 YR2017 5.388528138 0.539673957 0.642182922 1.856734863 1.640836904 YR2018 4.44143127 1.374291172 0.183821496 1.059986997 0.832686218 YR2019 5.67741655 1.314077523 0.485777628 1.417199805 0.468168547 YR2020 2.678041197 0.932200052 0.551893509 1.131922132 0.423520518 YR2021 3.285518752 9.677949361 0.75156918 1.939025596 0.422364158 YR2022 1.996311245 2.268805766 -0.039522367 2.261816176 0.34701381 Source: World bank, 2023 Unleashed technological advancement in non-oil sectors The accompanying technological advancement has been evaluated to play an important role in various non-oil sectors. Akhtaruzzaman et al. (2018) noted that FDI contributes to the upgrading of manufacturing capabilities by introducing advanced technologies, modern production methods, and managerial practices. Additionally, Seyoum et al. (2015) identified the spillover effects, where foreign firms' technology and knowledge dissemination benefit local suppliers and competitors, leading to broader technological diffusion within the sector. Furthermore, the study by Atiase et al. (2020) noted that the issue of the agribusiness sector which is a non-oil business has witnessed that there is the transfer of agricultural technologies, improved cultivation techniques, and enhanced productivity. Thus, there have been studies that noted that FDI stimulates the upgrading of agricultural supply chains through improved storage, processing, and distribution methods, thereby enhancing value-added activities (Wako, 2018). Specifically, In the early 2010s, multinational automakers like Volkswagen (VW) and Nissan invested significant FDI in Ghana's automotive industry. The study from Jibrilla and Dunusinghe (2021) ascertained that the FDI brought state-of-the-art manufacturing technologies and processes, including robotics and automation, to local assembly plants. In Nigeria, a multinational agribusiness corporation invested in FDI to establish agro-processing facilities (Osabutey, 2013; Jibrilla and Dunusinghe, 2021). This investment introduced advanced processing technologies for value-added products such as packaged foods and beverages. Considering the sector of services which is also noted to be a non-oil sector, empirical studies have established that FDI in services has introduced knowledge-intensive services such as information technology, financial services, and consulting, contributing to the development of local service industries (Owusu–Antwi et al., 2016). Furthermore, the study by Sarkodie et al. (2019) noted that FDI in services promotes skill development and human capital formation through training programs and knowledge transfer. The study by Dentie et al. (2019) noted that in Senegal, a consortium of international FinTech companies injected FDI to develop a robust digital financial ecosystem. Also, this involved the introduction of mobile payment platforms, digital banking services, and innovative lending models. The technology transfer not only brought convenient financial services to previously underserved populations but also spurred local entrepreneurship in developing complementary applications and services. Challenges and barriers to technological advancement of FDI on technology transfer A few of the challenges that result in a barrier to technological advancement from FDI in host countries come from institutional handicaps (Adu-Danso et al., 2020; Nketiah-Amponsah et al., 2018). Thus, the effectiveness of technology transfer is influenced by the institutional environment of the host country. There are core factors that serve as a major challenge such as Weak intellectual property protection, inadequate technology infrastructure, and limited research and development (R&D) capabilities that can hinder the successful absorption and utilization of foreign technologies (Chang et al., 2016). Gaps and inefficiencies in government policies and institutions do not promote the harnessing of FDI-related technological advancement for local businesses (Park and Tang, 2021). Also, there are the issues of policy regulation bottlenecks, and regulatory barriers, such as cumbersome bureaucratic processes, complex legal frameworks, and restrictions on foreign ownership, which can impede the smooth transfer of technology (Shukra et al., 2021; Wako, 2018). Additionally, there is the issue of lack of clear technology transfer strategies. A lack of well-defined strategies and frameworks for technology transfer within host countries can lead to ad hoc and inefficient technology adoption (Chen et al., 2015). Clear policies and guidelines are essential to facilitate a structured and organized approach to technology transfer. Inconsistent or ambiguous regulations related to intellectual property rights and technology licensing may deter foreign investors from sharing their proprietary technologies (Modarress et al., 2014; Gorodnichenko et al., 2017). Another challenge has to do with Absorptive Capacity Limitations: Local industries may lack the necessary absorptive capacity to effectively absorb and implement foreign technologies. This could result from a shortage of skilled human resources, limited access to training and education, or underdeveloped technical expertise needed for technology integration (Ricken and Malcotsis, 2018). Limitations of local businesses and firms’ absorptive capacity have been established as a major challenge for local businesses and enterprises in West Africa to adapt to technological advancement in their operations and performance (Fanglin and Risha, 2019). Thus, Local industries may lack the necessary absorptive capacity to effectively absorb and implement foreign technologies. This could result from a shortage of skilled human resources, limited access to training and education, or underdeveloped technical expertise needed for technology integration. Impacts and benefits of FDI on technology implications Developed Countries that have properly put in place policies and strategies to accommodate the technological advancement in their FDI have successfully achieved high efficiency and potential for local firms and enterprises. The ability to harness technological knowledge from foreign direct investment is crucial for local firms to be competitive in their operations. As noted by Gheribi and Voytovych (2018) firms and local manufacturing enterprises in China have successfully used foreign technology to reach global status in their operations and development. Additionally, the technology transfer not only improved production efficiency but also led to skill development among local workers who were trained to operate and maintain the advanced machinery (Sun and Anwar, 2017; Liao et al., 2018). The benefit gained from technological advancement through FDI has been catalyzing the growth of the domestic manufacturing industry across various countries. However, there are issues concerning the larger extent of the utilization of this technological advancement. FDI-related technological advancement has gone a long way to improve agribusinesses in various countries such as Sri Lanka, Venezuela, and China (Wie, 2015). Most empirically, local farmers and suppliers benefited from knowledge transfer regarding modern cultivation practices, post-harvest handling, and quality control. The key benefits from these investments in the local countries have resulted in the FDI-led technology transfer improving the overall agribusiness ecosystem by enhancing product quality, reducing post-harvest losses, and expanding market reach. 3. Methodology This study adopted the mixed method approach to data gathering and analysis. Thus, the mixed-methods approach combines qualitative and quantitative research methods to provide a holistic understanding of the phenomenon. The study chose 5 West African countries; Ghana, Nigeria, Cote d’Ivoire, Liberia, and Senegal. These countries were chosen because they received about 75–80% of the FDI inflows into the region between the period of 2015–2022. Additionally, they have demonstrated their capacity to leverage technological adoption in various areas of the economic sector. Thus, they have diverse FDI profiles and non-oil manufacturing sectors for in-depth case studies. Sampling Techniques Stratified and convenience sampling techniques were adopted for this study. The use of stratified sampling was necessary to put the non-oil sectors into perspective. Thus, businesses that received FDI were categorized into strata such as Agribusiness, Manufacturing, Services, and Infrastructure. The stratified sampling technique is necessary to provide equitable representation among all the participants (Creswell and Creswell, 2017 ). Thus, the owners and managers of these businesses that have received FDI support and have leveraged technology in their operations were selected using convenience sampling. Convenience sampling was also adopted to evaluate the respective policies that influence and support technological transfers or provide an enabling environment for FDI to enhance the capacity of local businesses and firms. Data Collection The panel data analysis was adopted for this study. Thus, the data from 1990–2022 were adopted for the analysis to evaluate the concept of leveraging foreign direct investments (FDI) to drive technological advancements in West Africa's non-oil manufacturing sector which is an intriguing proposition with the potential to yield significant economic and developmental benefits. Furthermore, the use of secondary data such as relying on Policy and Institutional Assessment from the respective countries. Thus, to evaluate government policies, regulations, and incentives that promote or hinder FDI-driven technology transfer in the non-oil manufacturing sector. Assess the role of institutions and support mechanisms in facilitating technology diffusion. Research Instruments The study adopts a mixed approach in using secondary and policy documents FDI and policy for non-oil manufacturing and businesses were done in other to solicit quantitative data from local industries, businesses, and stakeholders involved in FDI and technology transfer. Additionally, the research instruments focused on the review of secondary data solely focused on FDI-driven technology transfer. Additionally, interviews with key informants, including foreign investors, policymakers, and experts, to gather qualitative insights. Data Analysis The data analysis involved both quantitative and qualitative data analysis. The use of STATA version 15 was used for the analysis of the quantitative data. Thus, the Quantitative Analysis analyzes survey data using statistical techniques to identify patterns, trends, and correlations between FDI, technological advancements, and economic indicators. The qualitative analysis for the study focused on Performing thematic analysis on interview transcripts to extract key themes, challenges, and opportunities related to FDI-driven technology transfer. Last, but not the least, there was also the need to compare and contrast the case studies to identify commonalities, differences, and factors influencing the success of FDI-driven technological advancements. 4. Results, Analysis and Discussion The results and analysis were conducted based on the data from the World Bank, IMF, and national investment promotion authorities of the selected countries on technological advancements introduced through FDI in the non-oil manufacturing sector and their contributions to local industries. The results span the period from 1990–2022. The analysis was done based on the objectives of the study. From GIPC for Ghana about 25% of the transformation in technological advancement came from FDI, thus to the non-oil sectors, there has been increased automation of machinery in garment production. This has led to a 45% increase in production from the Ghana Textile Print (GTP) and the Akosombo Textile Limited (ATL). As a result, the exports of these products have improved greatly. In Nigeria, Food processing has witnessed a 45% increase in production at a lower cost due to the inclusion of technology and machinery for operations. Between 2001–2009 a capacity of 4.5 metric tonnes of production was recorded with the inclusion of technologically advanced automation, production increased to 33 metric tonnes between the period of 2013–2022. This was achieved based on the reduction in the cost of operation, cutting down on waste in the production line, and increased production. In Nigeria, there is also the inclusion of Industrial Internet of Things (IIoT) sensors in the operations and exploration of oil which has led to a high production capacity of about 12% over the period. These findings are supported by the study from Osabutey and Jackson (2019) who asserted the fact that developing countries can leverage FDI to boost their technological adoption in production. In line with these findings, Chukwu et al. ( 2022 ) noted in earlier studies that the benefits of technological adoption and advancement from FDI improve the operations and efficiency of production in diverse areas of the economy in terms of manufacturing and production capabilities. In South Africa, 75% of the production and assembling of cars were done by advanced technologies. Most importantly, capacity production was increased by 45% as a result of the automation that was added from 2012–2022 through the manufacturing at the Daimler plants to produce locally assembled cars. This has recorded a boost in production. The technologically advanced systems achieved a reduction in energy consumption and environmental footprint for the South African Automotive industry. Concerning Kenya, between the period of 2018–2023, there have been considerable improvements. Thus, the improvement in technological advance has recorded a 28% improvement in steel production, thus, the lean manufacturing practices improved on the cost of operation and lowered the excess waste at the production line. In the long run, about 75% improvement in the operations and production line was recorded. Additionally, the lean production from the technologically advanced tools recorded an optimized workflow and waste reduction that resulted in higher production capacity. These results support the study from Sarkodie et al. (2019), who asserted that technologies and the training of personnel have been spearheaded by FDI in manufacturing such as automobiles and this has gone a long way to improve on adaptation to various technologies and personnel. In a divergence of view from the study of Abor et al. (2018) they noted that the African market has not fully adopted and utilized the technological inflows and adaptation to their maximum capacity in different perspectives. In line with these study findings, Fu and Zanello (2020) pointed out that government support is necessary to provide the necessary foundation to support the growth and development of technological adoptions. In Cote d’Ivoire, the increased FDI brought in different forms of technological advancement that spearheaded green manufacturing in the textile mills over the period. Thus, between 2015–2022, there have been great improvements in the production capacity of these textile mills as a result of automation practices and green advancement in the production line. Additionally, the diversification of investment held by the public in the non-oil sectors has resulted in the growth of the telecommunication industries and seen advancement in operations and service quality. Thus, Cote D’Ivoire’s telecommunications system is considered one of the most effective and advanced in sub-Saharan Africa and has a significant improvement of about 80% capacity increase compared to the period of 2010–2012. The finding was supported by the study from Nketiah–Amponsah and Sarpong (2019) who noted that technological adoption from FDI has been advanced by investment in telecommunications and this has led to the training of personnel to adapt to the technological innovations and implementation. FDI in Senegal has witnessed a sharp increase of about 65% in the technologically advanced tools in the production of chemicals and Chemical manufacturing. This major boost has been essential to the production and operations of the necessary materials needed to aid in production. The inclusion of advanced robotics has drastically reduced the effects of hazardous materials and increased safety. In furtherance, defects have been reduced to about 25% over the period and this has increased the capacity of operations and production. Overall, SSA countries have witnessed machinery upgrades, process optimization software, and advanced logistics systems. This has in some ways cut down on operations costs and improved production capacities in the short and long term. Conclusively, the findings from Jibrilla and Dunusinghe ( 2021 ) noted that FDI has had a lot of positive impact on supporting operations and machinery optimization leading to production capacity increases. Table 2 Results of Technological Advancement from FDI Category Type Impact Examples 1. Machinery and Equipment - CNC machines - Increased production accuracy and speed ( Ghana : garment factory) - Automated assembly lines - Reduced labour costs and improved product quality ( Nigeria : food processing plant) - Advanced robotics - Enhanced safety and handling of hazardous materials ( Senegal : chemical manufacturing) 2. Processes and Techniques - Lean manufacturing practices - Waste reduction and optimized workflow ( Kenya : furniture production) - Six Sigma quality control - Minimized defects and improved product consistency ( Cote d'Ivoire : textile mill) - Green manufacturing techniques - Reduced energy consumption and environmental footprint ( South Africa : automotive industry) 3. Digital Tools and Systems - Enterprise resource planning (ERP) software - Improved data management and supply chain coordination ( Ghana : electronics assembly) - Industrial Internet of Things (IIoT) sensors - Real-time production monitoring and predictive maintenance ( Nigeria : oil and gas exploration) - Artificial intelligence (AI)-powered quality control - Automated defect detection and product optimization ( Senegal : cashew nut processing) Concerning the factors influencing the adoption and diffusion of foreign technologies within West Africa's non-oil manufacturing sector. The Panel Data Analysis was conducted for three models: Pooled OLS, Fixed Effects, and Random Effects models. The results are shown in Tables 3 , 4 , and 5 . The Fixed Effect regression model produced two statistically significant factors thus, FDI and Political Indicators which had − .05(*) and − .499(**) respectively. The Random Effect models provided 3 factors thus, the FDI, Political indicators, and GDP with values of − .049 (***) , − .598 (***) and .416 (**) . The factors that were identified to contribute to the adoption and diffusion of foreign technology in manufacturing in Sub Saharan African countries were Foreign Direct Investment (FDI), Political indicators (Absence of terrorism or war) and Gross Domestic Product (GDP). The positive relationship between FDI and GDP on technological diffusion and adoption points to the fact that the higher the FDI and GDP size the more improved in the adoption and diffusion of technology in the specific market across the continuant. While the negative relationship between political stability and technology diffusion proves that the lower occurrence of terrorism / political turmoil the higher the adoption of technology in manufacturing. The results have been supported by the study of Essel (2023) who noted from earlier research that GDP and absorptive capacities have proven to be essential in the technological inflows through FDI. In addition, Shan et al. ( 2018 ), Osinubi et al. ( 2022 ) and Shukra et al. ( 2021 ) support the results when they concluded that FDI has been a major boost towards technological advancement and production efficiency in manufacturing in SSA countries. Furthermore, Atiase et al. (2019) backed the assertion that governments should deploy policies that can accelerate the absorptive capacities of FDI in their respective countries. Table 6 points out the detection of the best model. Thus, in choosing the model best fit for such analysis, the Hausman test was used to identify that the Random Effect model (p > .983) proved that we cannot reject the null hypothesis and Random Effect produced more statistically significant factors such as FDI, GDP and political indicators that contribute to the adoption of technology in manufacturing. Seyoum et al. ( 2015 ) and Park and Tang ( 2021 ) provided evidence that supports the political indicators factors as a major contributor to FDI which potentially leads to technological adoption. Also, in line with the studies by Akhtaruzzaman et al. ( 2018 ) and Shirati ( 2018 ), the absence of political turmoil, coup d’états and the existence of democratic tendencies tend to improve education leading to higher personnel to absorptive capabilities and the technological skills and transfers that is accompanied by FDI. One of the studies that support GDP as a factor comes from Shukra et al. (2019) who noted that access to a larger market due to the size of GDP has been a major factor in FDI that drives technological activities. Table 3 Fixed Effect Regression results Technology Adoption Coef. Std. Err. t-value p-value [95% Conf Interval] Sig Trade .326 .641 0.51 .616 -1.003 1.655 FDI .05 .026 -1.89 .071 − .104 .005 * Political indicators − .499 .216 -2.31 .03 − .946 − .051 ** ICT − .231 .266 -0.87 .395 − .782 .32 Grants − .252 .414 -0.61 .549 -1.111 .607 GDP .34 .228 1.49 .15 − .132 .813 Manufacturing .291 .853 0.34 .736 -1.478 2.061 Constant − .966 2.09 -0.46 .648 -5.301 3.368 Mean dependent var 0.705 SD dependent var 0.285 R-squared 0.645 Number of obs 44 F-test 5.698 Prob > F 0.000 Akaike crit. (AIC) -33.859 Bayesian crit. (BIC) -19.585 *** p < .01, ** p < .05, * p < .1 Table 4 Random Effects Regression results Technology Adoption Coef. Std. Err. t-value p-value [95% Conf Interval] Sig Trade .329 .503 0.65 .514 − .658 1.316 FDI .049 .015 -3.19 .001 − .08 − .019 *** Political indicators − .598 .158 -3.78 0 − .908 − .288 *** ICT − .255 .216 -1.18 .237 − .677 .167 Grants − .041 .327 -0.13 .9 − .683 .6 GDP .416 .181 2.29 .022 .06 .771 ** Manufacturing .695 .632 1.10 .272 − .544 1.933 Constant -2.156 1.553 -1.39 .165 -5.2 .888 Mean dependent var 0.705 SD dependent var 0.285 Overall r-squared 0.655 Number of obs 44 Chi-square 68.319 Prob > chi2 0.000 R-squared within 0.637 R-squared between 0.688 *** p < .01, ** p < .05, * p < .1 Table 5 Model Selection Coefficients Fixed Random Difference Std. Error Trade .326 .329 − .0029635 .3965793 FDI − .05 .049 ** − .0003469 .0211709 Politics indicators − .499 − .598 *** .0994453 .1465594 ICT ser − .231 − .255 .0243948 .1553571 Grants − .252 − .041 − .21113 .2538789 GDP .34 .416 ** − .0756479 .1379991 Manufacturing .291 .695 − .4035352 .5735788 *** p < .01, ** p < .05, * p < .1 Table 6 Hausman (1978) specification test Coef. Chi-square test value 1.481 P-value .983 Evaluating government policies, regulations, and institutional support in facilitating or hindering FDI-driven technological advancements. The results concerning the government policies and regulations come from the fact that the countries in the sub-Saharan have different technological advancements due to policies that support their goals and development aspirations. In 2020, Government policy in Ghana points to the fact that Ghana's "One District, One Factory" initiative offers tax breaks and support for establishing new manufacturing plants. This attracted Turkish footwear company FLO, leading to technology transfer for automated cutting and stitching, increasing production capacity by 50%. As a result, there was a Technology diffusion within Ghana's footwear industry, improved product quality, and increased job creation. Further, Nigeria partnered with France to establish a pharmaceutical plant. The government facilitated knowledge sharing by connecting the plant with local universities, leading to joint R&D initiatives for adapting bioengineering techniques to the Nigerian context. Development of new medications adapted to regional needs enhanced local expertise in bioengineering and potential for future technology spillover to other sectors. In addition, that of Kenya, A German food processing company operating in Kenya implemented "lean manufacturing" practices. They partnered with local training providers to share these practices with other Kenyan manufacturers through workshops and training programs. Specifically, the Increased efficiency and reduced waste in the Kenyan food processing industry, knowledge diffusion among local companies, and improved competitiveness. In Cote d’Ivoire, technological development has improved the Chinese textile mill collaborating with a local design agency to use digital printing technology for innovative fabric designs. They participated in government-sponsored trade missions to China, connecting with potential technology partners and promoting regional technology awareness. Wako et al. (2018) and You et al. ( 2019 ) supported the assertion that government policies play a significant role in the adoption of technology in the operations and manufacturing processes across different African countries. As supported by You et al. (2021) investors are risk averse and are motivated by the ability of governments to support their investment with policies that enable capacity building to drive down the cost of production and open to a larger market. A policy in South Africa ensured that in the year 2020, South Africa's government supported R&D initiatives in advanced manufacturing technologies. This led to a local company developing and implementing a robotic system for car painting in a Japanese automotive factory. Achievement: Increased automation and efficiency in automobile production, highlighted local innovation potential, and attracted further investment in R&D. Considering the role of technological innovation, in 2020, regional integration efforts like the Economic Community of West African States (ECOWAS) promote easier trade and knowledge sharing across borders. This facilitated the sharing of AI-powered production optimization software from an American solar panel facility in Nigeria with other African countries. The results from these findings have been supported by Bait et al. ( 2021 ) who noted that the Accelerated technology diffusion and adoption within the renewable energy sector across West Africa, increased regional collaboration, and improved energy efficiency. 5. Conclusion and Recommendations This analysis explored the factors influencing technology adoption and diffusion in West Africa's non-oil manufacturing sector. We identified enabling factors such as supportive government policies, private sector initiatives, and favorable economic and market conditions, alongside potential barriers like infrastructure constraints, skills shortages, and cultural resistance. Examining specific examples across countries like Ghana, Nigeria, Kenya, Cote d'Ivoire, and South Africa demonstrated the tangible achievements possible when enabling factors are addressed. Technology transfer, skills development, knowledge sharing, and innovation highlighted the potential for transforming the West African manufacturing landscape. However, significant challenges remain. Infrastructure inadequacies, limited access to finance, and weak regulatory frameworks hamper progress. Addressing these limitations requires a concerted effort from governments, international organizations, and the private sector. In recommendation, there is the need for governments to improve on strengthening skills development programs and vocational education aligned with industry needs—Foster technology hubs and clusters to facilitate knowledge sharing and collaboration. Streamline regulatory procedures and provide intellectual property protection to attract technology transfer. There is much more African governments can do in recommendation thus, encouraging joint ventures and technology transfer agreements between local and foreign companies. Considering one of the hurdles is bureaucracies, there is a need to strengthen regulatory frameworks: Streamline administrative procedures, improve intellectual property protection, and foster transparency. Declarations Ethical Statement Funding : This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors. Conflict of Interest : The authors declare no conflicts of interest that could have influenced the research process or findings presented in this study. Ethical Approval : Ethical approval for this study was obtained from the Mendel University Review Board, ensuring compliance with ethical guidelines for research involving human subjects. Informed Consent : All participants included in the study provided informed consent before their involvement. Any identifiable information has been anonymized to protect the privacy and confidentiality of participants. This research study used secondary data sources for the analysis and information where all institutional data were given the necessary ethical consideration before usage. Author Contribution : The author contributed significantly to the conception, design, analysis, and interpretation of data for this study. The author has reviewed and approved the final version of the manuscript for submission. Data Availability Statement : The datasets generated and analyzed during the current study are available from the corresponding author upon reasonable request. This ethical statement ensures transparency and integrity in the conduct of research and demonstrates compliance with ethical principles and standards in academia. References Adu-Danso, E., and Abbey, E. (2020). Does foreign ownership enhance technological innovation amongst manufacturing firms in Sub-Saharan Africa? Journal of Small Business & Entrepreneurship , 34, 195 - 221. Adzroe, E. (2015). A study of e-business technology transfer via foreign direct investment in the Ghanaian construction industry. Ajzen, I., and Fishbein, M. (2005). The Influence of Attitudes on Behavior. 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You, K., Bianco, S.D., and Amankwah‐Amoah, J. (2020). Closing Technological Gaps to Alleviate Poverty: Evidence from 17 Sub-Saharan African Countries. Technological Forecasting and Social Change , 157, 120055. You, K., Dal Bianco, S., Lin, Z., and Amankwah‐Amoah, J. (2019). Bridging technology divide to improve business environment: Insights from African nations. Journal of Business Research . Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4228449","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":291172971,"identity":"039f2071-4fcd-44bc-a912-73f54356f58f","order_by":0,"name":"Isaac Mantey","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA5UlEQVRIiWNgGAWjYBACNjB5AEwyPgASPHzEa2FjYDYAaWEjzi6IFjYJhCF4AB//4YcffpzZJm8u33ys8muOnQzQtoePbuBzmESasWTPjduGO9vY0m7LbksGOozN2DgHrxYGA2mGD7cZNxzjMbstuY0ZqIWHTRqvFv7jn38DtdhvOMb/rVhyWz0RWhhyzKQZbtxOBNrCxvhx22EitEjklFn2nLmdvOFYmrE047bjPGzMBPwi3398840fx27bbjh8+OHHn9uq7fnZmx8+xqcFBTDzgElilYMA4w9SVI+CUTAKRsGIAQCuSkdYYBQxiwAAAABJRU5ErkJggg==","orcid":"","institution":"Mendel University in Brno","correspondingAuthor":true,"prefix":"","firstName":"Isaac","middleName":"","lastName":"Mantey","suffix":""}],"badges":[],"createdAt":"2024-04-06 18:00:23","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4228449/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4228449/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":54881261,"identity":"781347a9-eef4-4b5c-a29f-cbbf897c2891","added_by":"auto","created_at":"2024-04-18 04:49:13","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":19213,"visible":true,"origin":"","legend":"\u003cp\u003eFDI percentage to GDP\u003c/p\u003e\n\u003cp\u003eSource: World Bank Data, 2023\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-4228449/v1/d4d31cb215139c72bb4c2358.png"},{"id":54881698,"identity":"85cf8bb7-b806-45c0-878d-067080f705de","added_by":"auto","created_at":"2024-04-18 04:57:13","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":467937,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4228449/v1/7ad48f6e-7acd-4daf-a31c-7c5e16dec7b0.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Unleashing technological advancements through foreign direct investments in West Africa's non-oil manufacturing sectors","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eForeign Direct Investments (FDI) have long been recognized as a significant driver of economic growth and development in emerging markets (Fanglin and Risha, 2019\u003cem\u003e;\u0026nbsp;\u003c/em\u003eAdu-Danso and Abbey, 2020; Sun, 2011). The non-oil manufacturing sector in West Africa holds immense potential for fostering technological advancements through FDI. The non-oil sectors play a pivotal role in driving economic diversification and sustainable development. As countries in the region seek to reduce their dependence on oil exports and build more resilient economies, the non-oil sectors emerge as key drivers of growth, job creation, and technological advancement. Foreign Direct Investments (FDIs) have been growing in West African countries between the period 2012 – 2021 on an average of 5 – 8 % annually (IMF, 2021). FDI is necessary for every country to grow since it helps to inject extra capital to help stimulate production and manufacturing activities. Thus, FDI has long been recognized as a significant economic growth and development driver in emerging markets (Chen et al., 2015; Ricken and Malcotsis, 2018). The non-oil sectors mostly comprise Agriculture and Agribusiness, Manufacturing, Services, Mining and Minerals, and Construction among others (Adu-Danso and Abbey, 2012; Park and Tang, 2021). These non-oil sectors hold immense potential for fostering technological advancements, generating employment opportunities, and diversifying economies.\u003c/p\u003e\n\u003cp\u003eIn West Africa, these non–oil sector firms encompass a wide range of industries, including textiles, food processing, electronics, machinery, and automotive. Additionally, Agribusiness involves processing, packaging, and exporting agricultural products, adding value along the supply chain. Furthermore, the services sector includes finance, telecommunications, tourism, education, and healthcare. Expanding service industries can lead to improved infrastructure, quality of life, and opportunities for skilled employment. Also, concerning minerals and mining, there are sectors such as sustainable mining practices for extra gold, diamond, and bauxite, that contribute to the mining sector. Most importantly, promoting manufacturing activities can lead to value addition, job creation, and technological advancements (Antwi et al., 2016). Policy implementation is critical for firms and businesses in West Africa to adapt to technological advancement through FDI (Chang et al., 2016; Huynh et al., 2019).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFDI channeled by investors brings with them advanced technologies, managerial expertise, and best practices from their home countries (Fu and Zanello, 2020). Technological advancement has supported developed countries with a huge impact on economic growth and development (Adzroe, 2015). The study from Nketiah-Amponsah and Sarpong (2019) noted that considering the growing inflows of FDI into non-oil sectors like Agriculture, Services, Manufacturing, and Infrastructure in countries like Ghana, Nigeria, Cote d’Ivoire, Senegal, Sierra Leone, Mali, and Burkina Faso. There has been a need for local manufacturing countries to capture and inculcate technologically advanced tools and resources in their local operations (Sarkodie et al., 2019; Atiase et al., 2020). Thus, countries such as Ghana and Nigeria between the period of 2016 – 2022 have received 15% increment in the FDI into the sectors of Agriculture and this in the long run has marginal been channeled into technological implementation. However, the adoption of tractors and equipment has seen wide adoption in the field of agriculture. The inflow of technologies can help upgrade local manufacturing processes, enhance product quality, and improve overall efficiency. The adoption of technological resources and tools in sectors such as agriculture, services, and manufacturing among others, have been evaluated to be in the lower stages. While Services have seen 25% adoption of technological activities between the period of 2015 and 2021. Other non-oil sectors have seen a massive boost in the inculcation of technology in operations. While the potential for technological advancement through FDI is huge, there is also the need to evaluate which areas of FDI can impact positively. Technology transfer through FDI has propelled the economies of different countries to much higher heights (Jibrilla and Dunusinghe, 2021). This has been one of the key factors of economic growth and development.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFDI often encourages research and development (R\u0026amp;D) in technological activities in host countries (Auffray and Fu, 2015). Collaboration between local research institutions and foreign investors can lead to technological innovations that address specific challenges faced by West African economies. This can foster a culture of innovation and entrepreneurship, further propelling the non-oil manufacturing sector. Technological advancements play a crucial role in driving economic development and shaping the trajectory of nations (Wako, 2018). The significance of technological advancements for economic development is multifaceted and far-reaching. Few have been ascertained; thus, local workers can benefit from skill development and training, which can have a long-lasting positive impact on the labor force (Seyoum et al., 2015). FDI comes with varied factors and resources. However, the ability to establish which among these factors can be absorbed locally and used for business manufacturing and production is critical for the economic growth and development of countries in West Africa.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFDI propels Technology Transfer (Fu and Zanello, 2020), thus,foreign investors bring with them advanced technologies, managerial expertise, and best practices from their home countries. These technologies can help upgrade local manufacturing processes, enhance product quality, and improve overall efficiency. Local workers can benefit from skill development and training, which can have a long-lasting positive impact on the labor force. FDI provides the necessary technological Knowledge Transfer and Technology Spillovers (Auffray and Fu, 2015). Thus, foreign investors often bring advanced technological expertise, best practices, and innovative processes that can be shared with local companies. This knowledge transfer can lead to technology spillovers, where local firms learn from foreign investors, adopt new techniques, and improve their operations. FDI often encourages research and development activities in host countries (Wako et al., 2018; Auffre and Fu, 2015). Collaboration between local research institutions and foreign investors can lead to technological innovations that address specific challenges faced by West African economies. This can foster a culture of innovation and entrepreneurship, further propelling the non-oil manufacturing sector. The adoption of technology in service has seen some growth in countries such as Nigeria, Ghana, Cote d’Ivoire, and others.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis study focuses on evaluating the gaps that have lowered the ability of local firms to absorb and utilize technological advancement associated with FDI in non-oil manufacturing industries in West Africa. With the need for many West African countries to diversify their investment into manufacturing, services, agribusiness, and infrastructure, there is a need to evaluate the technological advancements that have been unleashed in these sectors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;Problem Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn West Africa, studies have posited the fact that local firms and businesses have been established to have low absorptive capabilities (Osabutey and Jackson, 2019; Akhtaruzzaman et al., 2018; Shukra et al., 2018). Studies have identified that depending on the various technological advancements from FDI, specific sectors can adopt an effective adaptive capacity to inculcate technological resources for local businesses and firms (Antwi et al., 2013). One of the non-oil manufacturing sectors such as agriculture has witnessed little technological advancement in their operations (Auffray and Fu 2015; Fu and Zanello, 2020). This means that the production capacity is still low, and they cannot compete on the global stage even though there are FDI inflows. Likewise, the issue of limitation on absorptive capacities. Thus, FDI, which is formed based on partnership, should be able to help in technological transfers to local businesses and enterprises. However, there is a gap in which these local enterprises have not been able to utilize this to their advantage. Compared to companies and businesses in China that have leveraged foreign technology to compete effectively, local companies in West Africa have not fully utilized these technological advantage opportunities. Developing countries in West Africa hardly utilize the technologically advanced capabilities that FDI brings. The study from Auffray and Fu (2015) noted that there is a lack of human resource capacity to absorb the technological innovation brought in by the FDI. In addition, absorptive capacity limitations. Local industries may lack the necessary absorptive capacity to effectively absorb and implement foreign technologies. This could result from a shortage of skilled human resources, limited access to training and education, or underdeveloped technical expertise needed for technology integration.\u003c/p\u003e\n\u003cp\u003eWhile there have been studies on FDI in traditional, oil, and non-oil industries like manufacturing in West African countries (Managi and Bwalya, 2010), there are still gaps that need to be filled. Thus, West Africa's non-oil manufacturing sector currently faces significant challenges that hinder the effective utilization of FDI for technology transfer, knowledge dissemination, and sustainable economic development. These challenges encompass regulatory barriers, inadequate infrastructure, limited access to skilled labor, and a lack of coordinated policies from the public and government institutions. As a result, the region's potential to diversify its economy, reduce dependency on oil exports, and create job opportunities remains largely untapped. Addressing these challenges and identifying strategies to create an enabling environment for FDI-driven technological advancements is crucial for unlocking the transformative potential of West Africa's non-oil manufacturing sector and promoting a more resilient, inclusive, and sustainable economic landscape.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;Aim of the study\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study aims to evaluate and ascertain the technological advancement that has been accompanied by FDI in West African countries. Additionally, the objectives of the study focus on evaluating the impact of this technological advancement on the development of businesses and the growth of their operations.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;Research Question\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe question that elucidates the necessary response is what are the factors that support the level of technological adaption accompanied by FDI in sub-Saharan African countries? Additionally, what are the government policies and efforts being made to sustain these factors to support technological adoption through FDI?\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;Objectives of the study\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study has focused on these objectives:\u003c/p\u003e\n\u003cp\u003ea. To examine the types of technological advancements introduced through FDI in the non-oil manufacturing sector and their contributions to local industries.\u003c/p\u003e\n\u003cp\u003eb. To evaluate the factors influencing the adoption and diffusion of foreign technologies within West Africa's non-oil manufacturing sector.\u003c/p\u003e\n\u003cp\u003ec. To analyze the role of government policies, regulations, and institutional support in facilitating or hindering FDI-driven technological advancements.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;Delimitation of the study\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe delimitations of the study focus primarily on the technological advancements through foreign direct investments (FDI) in West Africa's non-oil manufacturing sector. Thus, evaluating the respective FDIs and how it has impacted technological advancements among the local businesses.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;Significance of the study\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study is particularly important for local businesses and manufacturing companies in West Africa to harness the technological advancement that is infused by FDIs. This can improve their adaptive capabilities and ensure they have gained the necessary technological transfer and knowledge spillovers. This eventually improves their efficiency to compete globally and improves the margins of profitability and scale. Additionally, this study improves knowledge of the necessary strategies and practices that local businesses can adopt to gain more from the FDI’s facilitated Innovation and Research \u0026amp; Development (R\u0026amp;D). Thus, the ability to build Strategic partnerships between foreign investors and local institutions can stimulate innovation and R\u0026amp;D activities, leading to the creation of new products, processes, and solutions that cater for local and international markets.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eTheoretical Framework\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe theoretical framework of the study focuses on the concept of technological advancements through FDIs. The Innovation Diffusion Theory, formulated by Everett Rogers in the mid-20th century has been adopted by the study to provide the necessary framework and variables. At its core, this theory offers valuable insights into the dynamics of how FDI contributes to the adoption and diffusion of technological advancements within West Africa's non-oil manufacturing sector.\u003c/p\u003e\n\u003cp\u003eThe Innovation Diffusion Theory deals with the transfer of innovation from one specific context to the next, thus within the context of societal and business relationships there are direct and indirect procedures through which technological advancement can be transferred through FDI. Thus, the spread of a new idea is influenced by the innovation itself, communication channels, time, and a social system. Most importantly, the theory established that the willingness and ability to adopt an innovation depends on adopter awareness, interest, evaluation, trial, and adoption. People could fall into various categories for different innovations (Ajzen and Fishbein, 2005; Fishbein and Cappella, 2006)\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eConcerning unleashing technological advancements through FDI in West Africa's non-oil manufacturing sector, the theory can bring much insight into relative advantage, compatibility, and efficiency in production through the adoption of foreign technologies by local industries. The key role is for local industries to be part of the majority adopters of the technology and influence driving the process. This theory provides the necessary key variables and factors to influence technological advancement through FDI in the West African context. Thus, the need to evaluate the challenges, and opportunities associated with FDI-driven technological advancements.\u003c/p\u003e\n\u003cp\u003eThe theory also harnesses the need for local companies to harness foreign investors’ technology such as operational technologies, management practices, and expertise, local industries, and businesses can be seen as potential adopters of these innovations.\u003c/p\u003e\n\u003cp\u003eBy analyzing FDI-driven technology adoption through the lens of the Innovation Diffusion Theory, we can explore how different segments of the local industry, from innovators to laggards, respond to and embrace the introduced technologies. Factors such as the perceived relative advantage of the technologies, compatibility with existing practices, and ease of implementation will influence the speed and extent of adoption. Incorporating the Innovation Diffusion Theory as a theoretical framework enriches our understanding of how FDI can lead to the diffusion and integration of advanced technologies, contributing to the growth, innovation, and sustainability of West Africa's non-oil manufacturing sector.\u0026nbsp;\u003c/p\u003e"},{"header":"2. Literature Review","content":"\u003cp\u003eThe review of related literature, documents, and articles concerning the FDI towards technological advancements and knowledge transfer as well as the technological spillovers for local enterprises and businesses was reviewed. FDI has received incremental support from various governments and policymakers to enhance the operations and impact on local businesses and their impact. The issue concerning unleashing technological impact on the operations of local businesses and industries is partly related to the issue of the adaptive capacity of these businesses and enterprises (Auffray and Fu, 2015; You et al., 2020). The study by Fu and Zanello (2020)\u003cem\u003e\u0026nbsp;\u003c/em\u003eascertained that FDI can contribute to skill development by offering training and education programs to the local workforce. This leads to an increase in the pool of skilled labor, which is essential for adopting and implementing advanced technologies.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFDI and technological advancements in developing economies.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe increase in FDI in major West African countries between the period of 2015 \u0026ndash; 2022 has witnessed a growth rate of 15 \u0026ndash; 19% per annum (World Bank, 2022). The growth in FDI over the years has not matched the impact of technological advancement in developing economies in West Africa (IMF, 2021). Additionally, there is the issue of the formation of industrial clusters around FDI-intensive regions, fostering knowledge exchange, innovation, and technology spillovers among firms (Chen et al., 2020). According to the IMF (2021) between the period of 1990 to 2020, Nigeria received much FDI % to GDP, and in the early 2000s to 2020, Ghana was portrayed as the country with the highest recipient of FDI % to GDP, the highest was attained in 2013 which was 9.58% of GDP, the lowest point was in 2003 which was 0.8% of GDP. This is shown in Figure 1 below. While South Africa received the highest value of FDI in the SSA between 2006 \u0026ndash; 2014. Kenya, Cote d\u0026apos;Ivoire, and Nigeria have seen substantial growth in FDI in their economies. The table is illustrated in Figure 1 below.\u003c/p\u003e\n\u003cp\u003eTable 1: FDI percentage to GDP\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"675\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.501483679525222%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"15.578635014836795%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eGhana\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.881305637982194%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eSouth Africa\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.172106824925816%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eNigeria\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.178041543026705%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eCote d\u0026apos;Ivoire\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.688427299703264%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eKenya\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.501483679525222%\" valign=\"bottom\"\u003e\n \u003cp\u003eYR2015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.578635014836795%\" valign=\"bottom\"\u003e\n \u003cp\u003e6.46140124\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.881305637982194%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.438735792\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.172106824925816%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.621501637\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.178041543026705%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.079141547\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.688427299703264%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.883799936\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.501483679525222%\" valign=\"bottom\"\u003e\n \u003cp\u003eYR2016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.578635014836795%\" valign=\"bottom\"\u003e\n \u003cp\u003e6.205533329\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.881305637982194%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.684612553\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.172106824925816%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.853395743\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.178041543026705%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.193758009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.688427299703264%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.627591266\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.501483679525222%\" valign=\"bottom\"\u003e\n \u003cp\u003eYR2017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.578635014836795%\" valign=\"bottom\"\u003e\n \u003cp\u003e5.388528138\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.881305637982194%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.539673957\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.172106824925816%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.642182922\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.178041543026705%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.856734863\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.688427299703264%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.640836904\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.501483679525222%\" valign=\"bottom\"\u003e\n \u003cp\u003eYR2018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.578635014836795%\" valign=\"bottom\"\u003e\n \u003cp\u003e4.44143127\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.881305637982194%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.374291172\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.172106824925816%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.183821496\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.178041543026705%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.059986997\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.688427299703264%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.832686218\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.501483679525222%\" valign=\"bottom\"\u003e\n \u003cp\u003eYR2019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.578635014836795%\" valign=\"bottom\"\u003e\n \u003cp\u003e5.67741655\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.881305637982194%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.314077523\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.172106824925816%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.485777628\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.178041543026705%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.417199805\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.688427299703264%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.468168547\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.501483679525222%\" valign=\"bottom\"\u003e\n \u003cp\u003eYR2020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.578635014836795%\" valign=\"bottom\"\u003e\n \u003cp\u003e2.678041197\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.881305637982194%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.932200052\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.172106824925816%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.551893509\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.178041543026705%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.131922132\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.688427299703264%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.423520518\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.501483679525222%\" valign=\"bottom\"\u003e\n \u003cp\u003eYR2021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.578635014836795%\" valign=\"bottom\"\u003e\n \u003cp\u003e3.285518752\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.881305637982194%\" valign=\"bottom\"\u003e\n \u003cp\u003e9.677949361\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.172106824925816%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.75156918\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.178041543026705%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.939025596\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.688427299703264%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.422364158\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.501483679525222%\" valign=\"bottom\"\u003e\n \u003cp\u003eYR2022\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.578635014836795%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.996311245\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.881305637982194%\" valign=\"bottom\"\u003e\n \u003cp\u003e2.268805766\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.172106824925816%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.039522367\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.178041543026705%\" valign=\"bottom\"\u003e\n \u003cp\u003e2.261816176\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.688427299703264%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.34701381\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eSource: World bank, 2023\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eUnleashed technological advancement in non-oil sectors\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe accompanying technological advancement has been evaluated to play an important role in various non-oil sectors. Akhtaruzzaman et al. (2018) noted that FDI contributes to the upgrading of manufacturing capabilities by introducing advanced technologies, modern production methods, and managerial practices. Additionally, Seyoum et al. (2015) identified the spillover effects, where foreign firms\u0026apos; technology and knowledge dissemination benefit local suppliers and competitors, leading to broader technological diffusion within the sector.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFurthermore, the study by Atiase et al. (2020) noted that the issue of the agribusiness sector which is a non-oil business has witnessed that there is the transfer of agricultural technologies, improved cultivation techniques, and enhanced productivity. Thus, there have been studies that noted that FDI stimulates the upgrading of agricultural supply chains through improved storage, processing, and distribution methods, thereby enhancing value-added activities (Wako, 2018). Specifically, In the early 2010s, multinational automakers like Volkswagen (VW) and Nissan invested significant FDI in Ghana\u0026apos;s automotive industry. The study from Jibrilla and Dunusinghe (2021)\u003cem\u003e\u0026nbsp;\u003c/em\u003eascertained that the FDI brought state-of-the-art manufacturing technologies and processes, including robotics and automation, to local assembly plants. \u0026nbsp;In Nigeria, a multinational agribusiness corporation invested in FDI to establish agro-processing facilities (Osabutey, 2013; Jibrilla and Dunusinghe, 2021). This investment introduced advanced processing technologies for value-added products such as packaged foods and beverages.\u003c/p\u003e\n\u003cp\u003eConsidering the sector of services which is also noted to be a non-oil sector, empirical studies have established that FDI in services has introduced knowledge-intensive services such as information technology, financial services, and consulting, contributing to the development of local service industries (Owusu\u0026ndash;Antwi et al., 2016). Furthermore, the study by Sarkodie et al. (2019) noted that FDI in services promotes skill development and human capital formation through training programs and knowledge transfer. The study by Dentie et al. (2019) noted that in Senegal, a consortium of international FinTech companies injected FDI to develop a robust digital financial ecosystem. Also, this involved the introduction of mobile payment platforms, digital banking services, and innovative lending models. The technology transfer not only brought convenient financial services to previously underserved populations but also spurred local entrepreneurship in developing complementary applications and services.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eChallenges and barriers to technological advancement of FDI on technology transfer\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA few of the challenges that result in a barrier to technological advancement from FDI in host countries come from institutional handicaps (Adu-Danso et al., 2020; Nketiah-Amponsah et al., 2018). Thus, the effectiveness of technology transfer is influenced by the institutional environment of the host country. There are core factors that serve as a major challenge such as Weak intellectual property protection, inadequate technology infrastructure, and limited research and development (R\u0026amp;D) capabilities that can hinder the successful absorption and utilization of foreign technologies (Chang et al., 2016).\u003c/p\u003e\n\u003cp\u003eGaps and inefficiencies in government policies and institutions do not promote the harnessing of FDI-related technological advancement for local businesses (Park and Tang, 2021). Also, there are the issues of policy regulation bottlenecks, and regulatory barriers, such as cumbersome bureaucratic processes, complex legal frameworks, and restrictions on foreign ownership, which can impede the smooth transfer of technology (Shukra et al., 2021; Wako, 2018). Additionally, there is the issue of lack of clear technology transfer strategies. A lack of well-defined strategies and frameworks for technology transfer within host countries can lead to ad hoc and inefficient technology adoption (Chen et al., 2015). Clear policies and guidelines are essential to facilitate a structured and organized approach to technology transfer. Inconsistent or ambiguous regulations related to intellectual property rights and technology licensing may deter foreign investors from sharing their proprietary technologies (Modarress et al., 2014; Gorodnichenko et al., 2017). Another challenge has to do with Absorptive Capacity Limitations: Local industries may lack the necessary absorptive capacity to effectively absorb and implement foreign technologies. This could result from a shortage of skilled human resources, limited access to training and education, or underdeveloped technical expertise needed for technology integration (Ricken and Malcotsis, 2018).\u003c/p\u003e\n\u003cp\u003eLimitations of local businesses and firms\u0026rsquo; absorptive capacity have been established as a major challenge for local businesses and enterprises in West Africa to adapt to technological advancement in their operations and performance (Fanglin and Risha, 2019). Thus, Local industries may lack the necessary absorptive capacity to effectively absorb and implement foreign technologies. This could result from a shortage of skilled human resources, limited access to training and education, or underdeveloped technical expertise needed for technology integration.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eImpacts and benefits of FDI on technology implications\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDeveloped Countries that have properly put in place policies and strategies to accommodate the technological advancement in their FDI have successfully achieved high efficiency and potential for local firms and enterprises. The ability to harness technological knowledge from foreign direct investment is crucial for local firms to be competitive in their operations. As noted by Gheribi and Voytovych (2018) firms and local manufacturing enterprises in China have successfully used foreign technology to reach global status in their operations and development. Additionally, the technology transfer not only improved production efficiency but also led to skill development among local workers who were trained to operate and maintain the advanced machinery (Sun and Anwar, 2017; Liao et al., 2018). The benefit gained from technological advancement through FDI has been catalyzing the growth of the domestic manufacturing industry across various countries. However, there are issues concerning the larger extent of the utilization of this technological advancement.\u003c/p\u003e\n\u003cp\u003eFDI-related technological advancement has gone a long way to improve agribusinesses in various countries such as Sri Lanka, Venezuela, and China (Wie, 2015). Most empirically, local farmers and suppliers benefited from knowledge transfer regarding modern cultivation practices, post-harvest handling, and quality control. The key benefits from these investments in the local countries have resulted in the FDI-led technology transfer improving the overall agribusiness ecosystem by enhancing product quality, reducing post-harvest losses, and expanding market reach.\u003c/p\u003e"},{"header":"3. Methodology","content":"\u003cp\u003eThis study adopted the mixed method approach to data gathering and analysis. Thus, the mixed-methods approach combines qualitative and quantitative research methods to provide a holistic understanding of the phenomenon. The study chose 5 West African countries; Ghana, Nigeria, Cote d\u0026rsquo;Ivoire, Liberia, and Senegal. These countries were chosen because they received about 75\u0026ndash;80% of the FDI inflows into the region between the period of 2015\u0026ndash;2022. Additionally, they have demonstrated their capacity to leverage technological adoption in various areas of the economic sector. Thus, they have diverse FDI profiles and non-oil manufacturing sectors for in-depth case studies.\u003c/p\u003e \u003cp\u003e \u003cb\u003eSampling Techniques\u003c/b\u003e \u003c/p\u003e \u003cp\u003eStratified and convenience sampling techniques were adopted for this study. The use of stratified sampling was necessary to put the non-oil sectors into perspective. Thus, businesses that received FDI were categorized into strata such as Agribusiness, Manufacturing, Services, and Infrastructure. The stratified sampling technique is necessary to provide equitable representation among all the participants (Creswell and Creswell, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Thus, the owners and managers of these businesses that have received FDI support and have leveraged technology in their operations were selected using convenience sampling. Convenience sampling was also adopted to evaluate the respective policies that influence and support technological transfers or provide an enabling environment for FDI to enhance the capacity of local businesses and firms.\u003c/p\u003e \u003cp\u003e \u003cb\u003eData Collection\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe panel data analysis was adopted for this study. Thus, the data from 1990\u0026ndash;2022 were adopted for the analysis to evaluate the concept of leveraging foreign direct investments (FDI) to drive technological advancements in West Africa's non-oil manufacturing sector which is an intriguing proposition with the potential to yield significant economic and developmental benefits.\u003c/p\u003e \u003cp\u003eFurthermore, the use of secondary data such as relying on Policy and Institutional Assessment from the respective countries. Thus, to evaluate government policies, regulations, and incentives that promote or hinder FDI-driven technology transfer in the non-oil manufacturing sector. Assess the role of institutions and support mechanisms in facilitating technology diffusion.\u003c/p\u003e \u003cp\u003e \u003cb\u003eResearch Instruments\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe study adopts a mixed approach in using secondary and policy documents FDI and policy for non-oil manufacturing and businesses were done in other to solicit quantitative data from local industries, businesses, and stakeholders involved in FDI and technology transfer. Additionally, the research instruments focused on the review of secondary data solely focused on FDI-driven technology transfer. Additionally, interviews with key informants, including foreign investors, policymakers, and experts, to gather qualitative insights.\u003c/p\u003e \u003cp\u003e \u003cb\u003eData Analysis\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe data analysis involved both quantitative and qualitative data analysis. The use of STATA version 15 was used for the analysis of the quantitative data. Thus, the Quantitative Analysis analyzes survey data using statistical techniques to identify patterns, trends, and correlations between FDI, technological advancements, and economic indicators. The qualitative analysis for the study focused on Performing thematic analysis on interview transcripts to extract key themes, challenges, and opportunities related to FDI-driven technology transfer. Last, but not the least, there was also the need to compare and contrast the case studies to identify commonalities, differences, and factors influencing the success of FDI-driven technological advancements.\u003c/p\u003e"},{"header":"4. Results, Analysis and Discussion","content":"\u003cp\u003eThe results and analysis were conducted based on the data from the World Bank, IMF, and national investment promotion authorities of the selected countries on technological advancements introduced through FDI in the non-oil manufacturing sector and their contributions to local industries. The results span the period from 1990\u0026ndash;2022. The analysis was done based on the objectives of the study.\u003c/p\u003e \u003cp\u003eFrom GIPC for Ghana about 25% of the transformation in technological advancement came from FDI, thus to the non-oil sectors, there has been increased automation of machinery in garment production. This has led to a 45% increase in production from the Ghana Textile Print (GTP) and the Akosombo Textile Limited (ATL). As a result, the exports of these products have improved greatly. In Nigeria, Food processing has witnessed a 45% increase in production at a lower cost due to the inclusion of technology and machinery for operations. Between 2001\u0026ndash;2009 a capacity of 4.5 metric tonnes of production was recorded with the inclusion of technologically advanced automation, production increased to 33 metric tonnes between the period of 2013\u0026ndash;2022. This was achieved based on the reduction in the cost of operation, cutting down on waste in the production line, and increased production. In Nigeria, there is also the inclusion of Industrial Internet of Things (IIoT) sensors in the operations and exploration of oil which has led to a high production capacity of about 12% over the period. These findings are supported by the study from Osabutey and Jackson (2019) who asserted the fact that developing countries can leverage FDI to boost their technological adoption in production. In line with these findings, Chukwu et al. (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) noted in earlier studies that the benefits of technological adoption and advancement from FDI improve the operations and efficiency of production in diverse areas of the economy in terms of manufacturing and production capabilities.\u003c/p\u003e \u003cp\u003eIn South Africa, 75% of the production and assembling of cars were done by advanced technologies. Most importantly, capacity production was increased by 45% as a result of the automation that was added from 2012\u0026ndash;2022 through the manufacturing at the Daimler plants to produce locally assembled cars. This has recorded a boost in production. The technologically advanced systems achieved a reduction in energy consumption and environmental footprint for the South African Automotive industry. Concerning Kenya, between the period of 2018\u0026ndash;2023, there have been considerable improvements. Thus, the improvement in technological advance has recorded a 28% improvement in steel production, thus, the lean manufacturing practices improved on the cost of operation and lowered the excess waste at the production line. In the long run, about 75% improvement in the operations and production line was recorded. Additionally, the lean production from the technologically advanced tools recorded an optimized workflow and waste reduction that resulted in higher production capacity. These results support the study from Sarkodie et al. (2019), who asserted that technologies and the training of personnel have been spearheaded by FDI in manufacturing such as automobiles and this has gone a long way to improve on adaptation to various technologies and personnel. In a divergence of view from the study of Abor et al. (2018) they noted that the African market has not fully adopted and utilized the technological inflows and adaptation to their maximum capacity in different perspectives. In line with these study findings, Fu and Zanello (2020) pointed out that government support is necessary to provide the necessary foundation to support the growth and development of technological adoptions.\u003c/p\u003e \u003cp\u003eIn Cote d\u0026rsquo;Ivoire, the increased FDI brought in different forms of technological advancement that spearheaded green manufacturing in the textile mills over the period. Thus, between 2015\u0026ndash;2022, there have been great improvements in the production capacity of these textile mills as a result of automation practices and green advancement in the production line. Additionally, the diversification of investment held by the public in the non-oil sectors has resulted in the growth of the telecommunication industries and seen advancement in operations and service quality. Thus, Cote D\u0026rsquo;Ivoire\u0026rsquo;s telecommunications system is considered one of the most effective and advanced in sub-Saharan Africa and has a significant improvement of about 80% capacity increase compared to the period of 2010\u0026ndash;2012. The finding was supported by the study from Nketiah\u0026ndash;Amponsah and Sarpong (2019) who noted that technological adoption from FDI has been advanced by investment in telecommunications and this has led to the training of personnel to adapt to the technological innovations and implementation.\u003c/p\u003e \u003cp\u003eFDI in Senegal has witnessed a sharp increase of about 65% in the technologically advanced tools in the production of chemicals and Chemical manufacturing. This major boost has been essential to the production and operations of the necessary materials needed to aid in production. The inclusion of advanced robotics has drastically reduced the effects of hazardous materials and increased safety. In furtherance, defects have been reduced to about 25% over the period and this has increased the capacity of operations and production. Overall, SSA countries have witnessed machinery upgrades, process optimization software, and advanced logistics systems. This has in some ways cut down on operations costs and improved production capacities in the short and long term. Conclusively, the findings from Jibrilla and Dunusinghe (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) noted that FDI has had a lot of positive impact on supporting operations and machinery optimization leading to production capacity increases.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eResults of Technological Advancement from FDI\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCategory\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eType\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eImpact Examples\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003e1. Machinery and Equipment\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e- CNC machines\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e- Increased production accuracy and speed (\u003cb\u003eGhana\u003c/b\u003e: garment factory)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e- Automated assembly lines\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e- Reduced labour costs and improved product quality (\u003cb\u003eNigeria\u003c/b\u003e: food processing plant)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e- Advanced robotics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e- Enhanced safety and handling of hazardous materials (\u003cb\u003eSenegal\u003c/b\u003e: chemical manufacturing)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003e2. Processes and Techniques\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e- Lean manufacturing practices\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e- Waste reduction and optimized workflow (\u003cb\u003eKenya\u003c/b\u003e: furniture production)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e- Six Sigma quality control\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e- Minimized defects and improved product consistency (\u003cb\u003eCote d'Ivoire\u003c/b\u003e: textile mill)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e- Green manufacturing techniques\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e- Reduced energy consumption and environmental footprint (\u003cb\u003eSouth Africa\u003c/b\u003e: automotive industry)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003e3. Digital Tools and Systems\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e- Enterprise resource planning (ERP) software\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e- Improved data management and supply chain coordination (\u003cb\u003eGhana\u003c/b\u003e: electronics assembly)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e- Industrial Internet of Things (IIoT) sensors\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e- Real-time production monitoring and predictive maintenance (\u003cb\u003eNigeria\u003c/b\u003e: oil and gas exploration)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e- Artificial intelligence (AI)-powered quality control\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e- Automated defect detection and product optimization (\u003cb\u003eSenegal\u003c/b\u003e: cashew nut processing)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eConcerning the factors influencing the adoption and diffusion of foreign technologies within West Africa's non-oil manufacturing sector. The Panel Data Analysis was conducted for three models: Pooled OLS, Fixed Effects, and Random Effects models. The results are shown in Tables\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, \u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, and \u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e. The Fixed Effect regression model produced two statistically significant factors thus, FDI and Political Indicators which had \u003cem\u003e\u0026minus;\u0026thinsp;.05(*) and \u0026minus;\u0026thinsp;.499(**)\u003c/em\u003e respectively. The Random Effect models provided 3 factors thus, the FDI, Political indicators, and GDP with values of \u0026minus;\u0026thinsp;.049 \u003cem\u003e(***)\u003c/em\u003e, \u0026minus;\u0026thinsp;.598 \u003cem\u003e(***)\u003c/em\u003e and .416 \u003cem\u003e(**)\u003c/em\u003e. The factors that were identified to contribute to the adoption and diffusion of foreign technology in manufacturing in Sub Saharan African countries were Foreign Direct Investment (FDI), Political indicators (Absence of terrorism or war) and Gross Domestic Product (GDP). The positive relationship between FDI and GDP on technological diffusion and adoption points to the fact that the higher the FDI and GDP size the more improved in the adoption and diffusion of technology in the specific market across the continuant. While the negative relationship between political stability and technology diffusion proves that the lower occurrence of terrorism / political turmoil the higher the adoption of technology in manufacturing. The results have been supported by the study of Essel (2023) who noted from earlier research that GDP and absorptive capacities have proven to be essential in the technological inflows through FDI. In addition, Shan et al. (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), Osinubi et al. (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) and Shukra et al. (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) support the results when they concluded that FDI has been a major boost towards technological advancement and production efficiency in manufacturing in SSA countries. Furthermore, Atiase et al. (2019) backed the assertion that governments should deploy policies that can accelerate the absorptive capacities of FDI in their respective countries.\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e points out the detection of the best model. Thus, in choosing the model best fit for such analysis, the Hausman test was used to identify that the Random Effect model \u003cem\u003e(p\u0026thinsp;\u0026gt;\u0026thinsp;.983)\u003c/em\u003e proved that we cannot reject the null hypothesis and Random Effect produced more statistically significant factors such as FDI, GDP and political indicators that contribute to the adoption of technology in manufacturing. Seyoum et al. (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) and Park and Tang (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) provided evidence that supports the political indicators factors as a major contributor to FDI which potentially leads to technological adoption. Also, in line with the studies by Akhtaruzzaman et al. (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) and Shirati (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), the absence of political turmoil, coup d\u0026rsquo;\u0026eacute;tats and the existence of democratic tendencies tend to improve education leading to higher personnel to absorptive capabilities and the technological skills and transfers that is accompanied by FDI. One of the studies that support GDP as a factor comes from Shukra et al. (2019) who noted that access to a larger market due to the size of GDP has been a major factor in FDI that drives technological activities.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eFixed Effect Regression results\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"12\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTechnology Adoption\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eCoef.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eStd. Err.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003et-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e[95% Conf\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003eInterval]\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003eSig\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTrade\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e.326\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.641\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e0.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.616\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e-1.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003e1.655\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFDI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.026\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e-1.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.071\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.104\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003e.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePolitical indicators\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.499\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.216\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e-2.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.946\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.051\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eICT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.231\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.266\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e-0.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.395\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.782\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003e.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGrants\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.252\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.414\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e-0.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.549\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e-1.111\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003e.607\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGDP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.228\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e1.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.132\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003e.813\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eManufacturing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e.291\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.853\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e0.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.736\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e-1.478\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003e2.061\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConstant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.966\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e-0.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.648\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e-5.301\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003e3.368\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cem\u003eMean dependent var\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003e\u003cem\u003e0.705\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003e\u003cem\u003eSD dependent var\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e\u003cem\u003e0.285\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cem\u003eR-squared\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003e\u003cem\u003e0.645\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003e\u003cem\u003eNumber of obs\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e\u003cem\u003e44\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cem\u003eF-test\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003e\u003cem\u003e5.698\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003e\u003cem\u003eProb\u0026thinsp;\u0026gt;\u0026thinsp;F\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e\u003cem\u003e0.000\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cem\u003eAkaike crit. (AIC)\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003e\u003cem\u003e-33.859\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003e\u003cem\u003eBayesian crit. (BIC)\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e\u003cem\u003e-19.585\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"12\" nameend=\"c12\" namest=\"c1\"\u003e \u003cp\u003e\u003cem\u003e*** p\u0026thinsp;\u0026lt;\u0026thinsp;.01, ** p\u0026thinsp;\u0026lt;\u0026thinsp;.05, * p\u0026thinsp;\u0026lt;\u0026thinsp;.1\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eRandom Effects Regression results\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"12\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTechnology Adoption\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eCoef.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eStd. Err.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003et-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e[95% Conf\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003eInterval]\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003eSig\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTrade\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e.329\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.503\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e0.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.514\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.658\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003e1.316\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFDI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e.049\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e-3.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePolitical indicators\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.598\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.158\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e-3.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.908\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.288\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eICT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.255\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.216\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e-1.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.237\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.677\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003e.167\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGrants\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.041\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.327\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e-0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.683\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003e.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGDP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e.416\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.181\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e2.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003e.771\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eManufacturing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e.695\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.632\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e1.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.272\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.544\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003e1.933\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConstant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e-2.156\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.553\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e-1.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.165\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e-5.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003e.888\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cem\u003eMean dependent var\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003e\u003cem\u003e0.705\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003e\u003cem\u003eSD dependent var\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e\u003cem\u003e0.285\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cem\u003eOverall r-squared\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003e\u003cem\u003e0.655\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003e\u003cem\u003eNumber of obs\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e\u003cem\u003e44\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cem\u003eChi-square\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003e\u003cem\u003e68.319\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003e\u003cem\u003eProb\u0026thinsp;\u0026gt;\u0026thinsp;chi2\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e\u003cem\u003e0.000\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cem\u003eR-squared within\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003e\u003cem\u003e0.637\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003e\u003cem\u003eR-squared between\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e\u003cem\u003e0.688\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"12\" nameend=\"c12\" namest=\"c1\"\u003e \u003cp\u003e\u003cem\u003e*** p\u0026thinsp;\u0026lt;\u0026thinsp;.01, ** p\u0026thinsp;\u0026lt;\u0026thinsp;.05, * p\u0026thinsp;\u0026lt;\u0026thinsp;.1\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eModel Selection Coefficients\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFixed\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRandom\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDifference\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eStd. Error\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTrade\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.326\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.329\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.0029635\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.3965793\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFDI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.049\u003cem\u003e**\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.0003469\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.0211709\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePolitics indicators\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.499\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.598\u003cem\u003e***\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.0994453\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.1465594\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eICT ser\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.231\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.255\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.0243948\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.1553571\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGrants\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.252\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.041\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.21113\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.2538789\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGDP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.416\u003cem\u003e**\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.0756479\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.1379991\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eManufacturing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.291\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.695\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.4035352\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.5735788\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003cem\u003e*** p\u0026thinsp;\u0026lt;\u0026thinsp;.01, ** p\u0026thinsp;\u0026lt;\u0026thinsp;.05, * p\u0026thinsp;\u0026lt;\u0026thinsp;.1\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eHausman (1978) specification test\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCoef.\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChi-square test value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.481\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.983\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eEvaluating government policies, regulations, and institutional support in facilitating or hindering FDI-driven technological advancements. The results concerning the government policies and regulations come from the fact that the countries in the sub-Saharan have different technological advancements due to policies that support their goals and development aspirations. In 2020, Government policy in Ghana points to the fact that Ghana's \"One District, One Factory\" initiative offers tax breaks and support for establishing new manufacturing plants. This attracted Turkish footwear company FLO, leading to technology transfer for automated cutting and stitching, increasing production capacity by 50%. As a result, there was a Technology diffusion within Ghana's footwear industry, improved product quality, and increased job creation. Further, Nigeria partnered with France to establish a pharmaceutical plant. The government facilitated knowledge sharing by connecting the plant with local universities, leading to joint R\u0026amp;D initiatives for adapting bioengineering techniques to the Nigerian context. Development of new medications adapted to regional needs enhanced local expertise in bioengineering and potential for future technology spillover to other sectors. In addition, that of Kenya, A German food processing company operating in Kenya implemented \"lean manufacturing\" practices. They partnered with local training providers to share these practices with other Kenyan manufacturers through workshops and training programs. Specifically, the Increased efficiency and reduced waste in the Kenyan food processing industry, knowledge diffusion among local companies, and improved competitiveness. In Cote d\u0026rsquo;Ivoire, technological development has improved the Chinese textile mill collaborating with a local design agency to use digital printing technology for innovative fabric designs. They participated in government-sponsored trade missions to China, connecting with potential technology partners and promoting regional technology awareness. Wako et al. (2018) and You et al. (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) supported the assertion that government policies play a significant role in the adoption of technology in the operations and manufacturing processes across different African countries. As supported by You et al. (2021) investors are risk averse and are motivated by the ability of governments to support their investment with policies that enable capacity building to drive down the cost of production and open to a larger market.\u003c/p\u003e \u003cp\u003eA policy in South Africa ensured that in the year 2020, South Africa's government supported R\u0026amp;D initiatives in advanced manufacturing technologies. This led to a local company developing and implementing a robotic system for car painting in a Japanese automotive factory. Achievement: Increased automation and efficiency in automobile production, highlighted local innovation potential, and attracted further investment in R\u0026amp;D. Considering the role of technological innovation, in 2020, regional integration efforts like the Economic Community of West African States (ECOWAS) promote easier trade and knowledge sharing across borders. This facilitated the sharing of AI-powered production optimization software from an American solar panel facility in Nigeria with other African countries. The results from these findings have been supported by Bait et al. (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) who noted that the Accelerated technology diffusion and adoption within the renewable energy sector across West Africa, increased regional collaboration, and improved energy efficiency.\u003c/p\u003e"},{"header":"5. Conclusion and Recommendations","content":"\u003cp\u003eThis analysis explored the factors influencing technology adoption and diffusion in West Africa's non-oil manufacturing sector. We identified enabling factors such as supportive government policies, private sector initiatives, and favorable economic and market conditions, alongside potential barriers like infrastructure constraints, skills shortages, and cultural resistance. Examining specific examples across countries like Ghana, Nigeria, Kenya, Cote d'Ivoire, and South Africa demonstrated the tangible achievements possible when enabling factors are addressed. Technology transfer, skills development, knowledge sharing, and innovation highlighted the potential for transforming the West African manufacturing landscape. However, significant challenges remain. Infrastructure inadequacies, limited access to finance, and weak regulatory frameworks hamper progress. Addressing these limitations requires a concerted effort from governments, international organizations, and the private sector.\u003c/p\u003e \u003cp\u003eIn recommendation, there is the need for governments to improve on strengthening skills development programs and vocational education aligned with industry needs\u0026mdash;Foster technology hubs and clusters to facilitate knowledge sharing and collaboration. Streamline regulatory procedures and provide intellectual property protection to attract technology transfer.\u003c/p\u003e \u003cp\u003eThere is much more African governments can do in recommendation thus, encouraging joint ventures and technology transfer agreements between local and foreign companies. Considering one of the hurdles is bureaucracies, there is a need to strengthen regulatory frameworks: Streamline administrative procedures, improve intellectual property protection, and foster transparency.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthical Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e: This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of Interest\u003c/strong\u003e: The authors declare no conflicts of interest that could have influenced the research process or findings presented in this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical Approval\u003c/strong\u003e: Ethical approval for this study was obtained from the Mendel University Review Board, ensuring compliance with ethical guidelines for research involving human subjects.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInformed Consent\u003c/strong\u003e: All participants included in the study provided informed consent before their involvement. Any identifiable information has been anonymized to protect the privacy and confidentiality of participants. This research study used secondary data sources for the analysis and information where all institutional data were given the necessary ethical consideration before usage.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contribution\u003c/strong\u003e: The author contributed significantly to the conception, design, analysis, and interpretation of data for this study. The author has reviewed and approved the final version of the manuscript for submission.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement\u003c/strong\u003e: The datasets generated and analyzed during the current study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003eThis ethical statement ensures transparency and integrity in the conduct of research and demonstrates compliance with ethical principles and standards in academia.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eAdu-Danso, E., and Abbey, E. (2020). Does foreign ownership enhance technological innovation amongst manufacturing firms in Sub-Saharan Africa? \u003cem\u003eJournal of Small Business \u0026amp; Entrepreneurship\u003c/em\u003e, 34, 195 - 221.\u003c/li\u003e\n \u003cli\u003eAdzroe, E. (2015). 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Bridging technology divide to improve business environment: Insights from African nations. \u003cem\u003eJournal of Business Research\u003c/em\u003e.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"foreign direct investment, gross domestic product, technology transfer, non-oil manufacturing sectors, west Africa.","lastPublishedDoi":"10.21203/rs.3.rs-4228449/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4228449/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis paper explores the potential of Foreign Direct Investments (FDI) to drive technological advancements and promote sustainable growth in West Africa's non-oil manufacturing sector. The purpose of the study is to evaluate and ascertain the technological advancement that has been accompanied by FDI in West African countries. This study uses the FDI dataset of 5 West African countries and adopts the panel data analysis that spans from 1990 – 2022 to evaluate the factors that contribute to the diffusion and adoption of technological innovation. Data were sourced from the World Bank, International Monetary Fund, and Investment Promotion centers of selected countries.\u003c/p\u003e\n\u003cp\u003eFindings from the study showed that factors that contribute to the diffusion and adoption of technological innovation come from FDI, political indicators, and Gross Domestic Product (GDP). Thus, there is a positive relationship between FDI and GDP on technological diffusion and adoption; the higher the FDI and GDP size the more improved the adoption and diffusion of technology in the specific market across the continent. The negative relationship between political stability and technology diffusion proves that the lower the occurrence of terrorism or political turmoil the higher the adoption of technology in manufacturing.\u003c/p\u003e\n\u003cp\u003eThe study recommends the need for governments to improve political stability and set up technology hubs and clusters to facilitate knowledge sharing and collaboration to absorb technology diffusion in their respective economies.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eJEL Codes:\u003c/strong\u003e F2, L6, O33\u003c/p\u003e","manuscriptTitle":"Unleashing technological advancements through foreign direct investments in West Africa's non-oil manufacturing sectors","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-04-18 04:49:08","doi":"10.21203/rs.3.rs-4228449/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"c862c097-49ca-4690-95c6-b9e55d12c1ec","owner":[],"postedDate":"April 18th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-04-18T04:49:08+00:00","versionOfRecord":[],"versionCreatedAt":"2024-04-18 04:49:08","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4228449","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4228449","identity":"rs-4228449","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}