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While the trade sector has long been the backbone of growth followed by real estate development in Dubai, the impact of reduced oil revenues in the Gulf Cooperation Council (GCC) has affected Dubai. GCC countries have identified innovation and transitioning to a knowledge-based economy as critical components of sustainable growth in the post-oil world. The purpose of this chapter is twofold: (1) to examine UAE’s competitiveness relative to four economies for which we can draw meaningful conclusions (Qatar, Singapore, Norway, and Switzerland) and (2) to integrate macro- and micro-level findings in an actionable framework. Using the composite Knowledge Economy Index (KEI) developed by the World Bank (2008, 2012), we conclude that UAE should prioritize three key areas to ­transition to a knowledge-based economy: the regulatory regime, innovation, and human capital. These findings are consistent with a recent study by the UAE Department of Economic Development/INSEAD, which highlights two areas that need addressing: “Creation” (knowledge creation) and “Anchoring” (institutional environment for innovation). We integrate these macro-level findings with research at the innovation ecosystem level (and particularly survey-based research completed by Wamda Research Lab) to propose a comprehensive action framework across all ecosystem stakeholders (i.e., government, entrepreneurs, academia, support ecosystem, and corporates). The action matrix allows individual stakeholders to drive corresponding actions and prioritize across short- and long-term initiatives.

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.

The Kingdom of Saudi Arabia (KSA) has a comprehensive and coherent innovation system producing significant outcomes. However, as with every system, continuous improvement is required to optimize system performance. This chapter analyzes KSA’s innovation system based on the 2018 Global Innovation Index indicators among 127 countries. The chapter identifies the highlighted performance areas of the system and its market failures. In turn, the systemic analysis of the country’s NIS reveals the strong interactions but also the system’s failures, proposing a set of action policies to be undertaken that will generate a significant improvement over the expected results of the system. The main system failures identified are the low knowledge diffusion or knowledge spillover effects and the minimal access to equity funding for startups, or the absence of a risk capital culture. However, the country’s innovation system is coherent, presenting strong interaction linkages between the research, innovation, and commercialization node. It presents a remarkable improvement since 2011, presenting an above-average performance in terms of allocated resources for research and innovation.

Colleges and universities play a vital role in the creation and dissemination of the innovations that feed the knowledge economy. First, universities carryout a significant portion of the basic research that is conducted in the United States. In 2006, the National Science Foundation reported having awarded $30 B in research-based funding to colleges and universities (National Science Foundation, 2007). While this figure is not an indicator of innovation output, the number helps to demonstrate the scope of research activity that is occurring within the academy. Mansfield (1995) noted that government funding for university research is bent toward science that holds commercial potential and highlighted that such research is likely to produce a high amount of social benefits. Mansfield also concluded that measuring the social returns of university-born (and federally funded) innovations though difficult, is important. Second, universities are instrumental in the production of economically relevant human capital, including students trained in key science and technology disciplines (Leslie & Brinkman, 1988). Audretsch (2007) indicates a highly educated workforce that is capable of creating and moving innovative technologies into the marketplace is a critical component of the current entrepreneurial economy. Also, faculty who intersect industry through consulting and other commercial-related activities make valuable contributions to the economic growth and prosperity of communities, regions, and beyond. In short, colleges and universities are key contributors to the production and function of the innovations that largely drive the knowledge economy.

As a sector, higher education is at the low end of innovation rankings. The challenges we face – demographic, technological, political, and pedagogical – will require sustained innovation at a strategic level. Recent research with mature companies has identified exemplars in strategic innovation (e.g., O’Connor, Corbett, & Peters, 2018). This work explores whether – and how – higher education institutions might adapt insights from the corporate sector for strategic innovation in teaching and learning.

The introductory section provides an overview of the nature of strategic innovation (and why it is hard to sustain), strategic issues facing higher education, and the status and challenges of sustaining strategic innovation for teaching. The next two sections describe insights from research with corporate exemplars of sustaining strategic innovation. Each section uses a scenario from higher education as a proof-of-concept test to explore the application of the corporate sector insights for strategic innovation in higher education teaching and learning.

The final section of the chapter discusses the planned next steps to prototype and test adaptation of these corporate sector insights with institutional innovation leaders in higher education, as well as additional potential sources of insights (from other research in the corporate sector and from strategic innovation in the public sector).

The purpose of this chapter is to illustrate the role of higher education establishments in Middle Eastern countries specifically Saudi Arabia. The contributions of higher education establishments are particularly significant in relation to regional and national innovation system, which have been earmarked as engine for growth of the local economy across the region. Our study has chartered the dynamic nature of higher education in the region and their networking capabilities in order to be recognized as key stakeholders of the emerging economy. The study is informed by theoretical dimensions of “open innovation” and how the framework can accommodate the dynamic nature of higher education establishments in order to provide further impetus to ambitious projects such as Vision 2030 in Saudi Arabia. Our study is limited by further empirical evidence but has implication for the region in offering new insights around the evolving conceptualization of entrepreneurial universities and national innovation system.

Platform, open/user innovation, and ecosystem strategies embrace and enable interactions with external entities. Firms pursuing these approaches conduct business and interact with environments differently than those pursuing traditional closed strategies. This chapter considers these strategies together highlighting similarities and differences between platform, open/user innovation, and ecosystem strategies. We focus on managerial and organizational challenges for organizations pursuing these strategies and identify four institutional logic shifts associated with these strategic transitions: (1) increasing external focus, (2) moving to greater openness, (3) focusing on enabling interactions, and (4) adopting interaction-centric metrics. As mature incumbent organizations adopt these strategies, there may be tensions and multiple conflicting institutional logics. Additionally, we consider four strategic leadership topics and how they relate to platform, open/user innovation, and ecosystem strategies: (1) executive orientation and experience, (2) top management teams, (3) board-management relations, and (4) executive compensation. We discuss theoretical implications, and consider future directions and research opportunities.

In this chapter, we apply diffusion of innovation theory and the theory of management fashion to examine the diffusion trajectory of human resource (HR) analytics in a U.S. context. We focus on the role mass media plays in influencing the diffusion process and address two research questions. First, does the mass media on HR analytics make observable the positive outcomes of HR analytics and is this related to increasing HR analytics adoption over time? Second, does the mass media on HR analytics show evidence of management trendsetting rhetoric?

We analyze published popular trade, business press, and peer-reviewed academic articles over a decade using a big data discourse analytical technique, natural language processing.

We find preliminary evidence that suggests that although the media has broadcasted positive outcomes of HR analytics, adoption has tailed off. In concert with the tailing off of HR analytic adoptions, the media appears to be recasting HR analytics as solving newer problems such as managing talent. Whether this shift makes a difference has yet to be determined.

Business press appears to influence the adoption process, both by broadcasting positive outcomes and through creating management fashion trendsetting rhetoric.

To promote the use of HR analytics, academic institutions and the HR profession need to train HR professionals in the use and benefits of HR analytics.

We lay the groundwork to improve our understanding of the role media plays in influencing how new HRM practices spread across organizations. We introduce the application of an emerging big data analytic technique, natural language processing, to analyze published media on HR analytics.

The literature documents a shortage in the supply of external funding to small- and medium-sized enterprises (SMEs) in general and to innovative SMEs in particular. This study separates cognitive from financial constraints on innovative SMEs’ growth opportunities. Using data gathered through in-depth interviews with the CEOs of 115 SMEs, we reveal that over and above a problem with supply, there exists a twofold problem on the demand side. Specifically, we document that there is a tendency for these companies to avoid approaching external funding sources, especially ones that gear their investments toward innovation. Our results reveal a cognitive bias (over-pessimism) affecting the entrepreneurs’ (lack of) demand for external financing over and above other firm-specific factors. CEO tenure — our proxy for human and social capital — is significantly lower (higher) in firms that did (did not) pursue external funding. This finding may provide some support for our hypothesis regarding the cognitive bias and over-pessimism of the more veteran CEOs who have had negative experiences regarding recruiting external resources. The impact of this entrepreneurial cognition is shown to be economically detrimental to the enterprise. Nevertheless, the negative effects are not limited to the micro level, but have implications at the macro level as well, due to under-realization of the potential for employment, productivity, and growth of the firms comprising the vast majority of the economy.