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Since the end of the 1990s, the Algerian public authorities have implemented research and innovation policies in order to build a solid National Innovation System (NIS) and improve industrial and economic performance. Today, the NIS remains immature, which hinders the learning and innovation processes. Our objective here is to analyze under a broad vision the Algerian NIS by examining its various components, to evaluate the capacities of training and innovation, and to measure the production of the innovation and the economic performances. Our research question is the following: How could the Algerian public authorities build a solid NIS in order to improve economic performance? To answer this question, we use a research methodology that mobilizes three types of complementary indicators in order to analyze the processes of learning and innovation from a systemic and interactive perspective. We also use economic performance indicators in order to put the analysis into a broader perspective. At the end, we propose action policies in favor of the construction of a complete Algerian NIS to improve economic performance.

Purpose: Innovation is a multi-dimensional phenomenon influenced at the organisational level by internal and external factors that can determine how innovative an organisation can be, determining a firm’s business performance. This chapter measures and predicts how innovative a company can be, considering key internal factors using modern data analytics/science.

Need for Study: The increasing challenge of modern business operations is affected by how quickly, sustainably, effectively, and efficiently companies can innovate to mitigate the dynamic challenges of current business environments and evolving customer needs. The ability to predict, measure, and manage innovation becomes necessary to ensure that businesses are fit for purpose.

Methodology: A model was designed following the study hypotheses and statistically tested. A historical data sample from the OECD global industry dataset for eight years was used for the analysis. The ordinary least square method was used to test for model fit. Also, in machine learning engineering, predictive analysis using the multivariate linear regression analysis method was carried out.

Findings: The results support the hypotheses that an organisation’s capacity to be innovative can be measured and predicted, and it is influenced by a good number of internal factors or independent variables at various degrees.

Practical Implications: Managers must understand how to measure and predict innovation metrics to manage innovation better, ultimately leading to better business outcomes and performance. Also proposed are new measurement matrices for innovation management: innovation capacity (I_C), business innovation value (BIV), innovation creation factor (ICF), and a practical data-driven innovation management and prediction system.

This chapter evaluates the readiness of the higher education system to contribute to the competitiveness of African countries in the knowledge economy. Using institutions of higher learning in Kenya and Uganda as case studies, the study demonstrates that the higher education system in Africa is ill-equipped to fulfill the role of knowledge production for the advancement of African economies. The chapter proposed promising ways through which higher education in the region can play a more fulfilling role to the global knowledge economy through the formation of relevant skills for the growth of African economies. In an era where knowledge assets are accorded more importance than capital and labor assets, and where the economy relies on knowledge as the key engine of economic growth, this chapter argues that higher education institutions in Africa can assist in tackling the continent’s challenges through research in knowledge creation, dissemination, and utilization for improved productivity. These institutions need to engage in design-driven innovation in the emerging knowledge economy. To enhance their contributions toward human capital development and knowledge-intensive economies in the region, it is imperative to employ public-private initiatives to bridge and address various challenges and gaps facing universities and research institutions in Africa.

This chapter explores the role of colleges and universities supporting regional and national economic development with emphasis on leveraging innovation and entrepreneurship. Key focuses for economic development support from higher education include human resources development, technical assistance, capacity building, economic research and analysis, research, technology transfer, and new business development.

In this chapter, I analyze universities’ present context of commodification by suggesting a typology of market universities based on Levín’s three types of capital enterprises: the simple purpose, technological, and enhanced universities. The simple purpose university mainly commodifies teaching. On the contrary, the technological and enhanced universities, even if they may also commodify teaching, are focused on the commodification of research. The main difference between the technological and the enhanced universities is the capacity of the latter to enjoy the profits of its commodified research activity, while the former exchanges research results and sells its research capacity in a subordinated way, losing (at least part of) those benefits. These three proposed types also differ regarding financial autonomy and academic freedom.

In the network strategy view, relative competitive advantage stems not merely from opportunity structures embedded in networks but also from the distribution of ability and motivation among firms. Thus, there is a need to “bring the firm back in” to the network strategy narrative. We demonstrate that a mixed-methods design, blending large-sample data with micro-data on specific firms and their networks, can increase our understanding of the interplay of network structure and actor mechanisms, thus bridging the chasm between theory and practice in network strategy. We believe this is a critical step toward the “strategic design of networks.”

This chapter emphasizes the importance of potential and realized capabilities in building and sustaining social innovations. We present an assessment of the drivers and barriers to the development of social innovation ecosystems through the use of internal (absorptive capacities) and external organizational capabilities (open social innovation). A particular emphasis is placed on social innovation outcomes and impacts. The capability approach is particularly useful for measuring social innovation impacts and investigating the “micro-meso-macro” of linkages that underlie the process of social innovation.

Our methodological approach measures social innovations’ outcomes and impact through an aggregative model, which takes into consideration different forms of capabilities that are engendered in the process of or as a result of social innovation. This methodology highlights the importance of social innovation drivers and contexts in which knowledge exploration and exploitation lead to the creation of capabilities that help social innovators to respond to unfulfilled social needs.

The research presented in this chapter provides a new perspective on how the capability approach can be used to assess and measure individual and collective actions when facing social challenges.

Our research supports and complements the findings of the EU project SIMPACT an acronym for “Boosting the Impact of SI in Europe through Economic Underpinnings,” by highlighting the processes and outcomes and SI impact measurement.

The measurement of social innovation outcomes and impact has gained importance for policy makers and constitutes a strategic tool for designing policies in support of social entrepreneurs, social investors, and private and public organizations which participate in cocreating and implementing innovative projects.

The research presented in this chapter sheds light on the “micro-meso-macro” linkages that foster social innovation ecosystems, and offer valuable tools and guidelines to researchers, practitioners, and policymaker in the field of innovation in general and social innovation in particular.

This study examines organizational innovation in small- and medium-sized enterprises (SMEs) and develops an extensive framework of how innovation occurs, its end results in terms of positive, negative outcomes, and its impacts on business financial performance; using grounded methodology; interviews with entrepreneurs and executive experts from across industries. The study aims to fill gaps in the literature. Despite extensive research conducted on innovation, most focus on factors behind innovation and a company's innovativeness. The framework is useful to SMEs considering company-wide innovation. Transparent inputs and outputs enable companies to understand innovation processes, and its outcomes better as well as help monitor and implement individual innovation activities. The framework has a wide application, particularly, in an industry where innovation is hard to capture and understand. Using the model, we can determine innovation drivers, practices, and barriers as well as innovation inputs/outputs in different industries, thus promoting better management of innovation across a wide range of applications. Governments also require a better understanding of innovation, productivity, and operational efficiency to plan their policies in the promotion of innovation.

Purpose: While COVID-19 has upended lives, it has also catalyzed innovation with potential to advance health delivery. Yet, we know little about how the delivery system, and primary care in particular, has responded and how this has impacted vulnerable patients. We aimed to understand the impact of COVID-19 on primary care practice sites and their vulnerable patients and to identify explanations for variation. Approach: We developed and administered a survey to practice managers and physician leaders from 173 primary care practice sites, October-November 2020. We report and graphically depict results from univariate analysis and examine potential explanations for variation in practices' process innovations in response to COVID-19 by assessing bivariate relationships between seven dependent variables and four independent variables. Findings: Among 96 (55.5%) respondents, primary care practice sites on average took more safety (8.5 of 12) than financial (2.5 of 17) precautions in response to COVID-19. Practice sites varied in their efforts to protect patients with vulnerabilities, providing care initially postponed, and experience with virtual visits. Financial risk, practice size, practitioner age, and emergency preparedness explained variation in primary care practices' process innovations. Many practice sites plan to sustain virtual visits, dependent mostly on patient and provider preference and continued reimbursement. Value: While findings indicate rapid and substantial innovation, conditions must enable primary care practice sites to build on and sustain innovations, to support care for vulnerable populations, including those with multiple chronic conditions and socio-economic barriers to health, and to prepare primary care for future emergencies.