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The present study identifies investment in Africa's cultural and creative industries (CCIs) as one of the strategic moves in the right direction for achieving sustainable development across the African continent. Cultural and creative industries (CCIs) offer an alternative approach to development through their wealth creation potential, socioeconomic development, employment opportunities, and promotion of cultural diversity. Nevertheless, CCIs are yet to feature categorically as a development strategy, owing to their many challenges, as indicated by the study. The study submits that partnerships under the Belt and Road Initiatives (BRI) could offer an alternative source of mobilizing support for CCIs, as the BRI is a development framework with robust financing, infrastructure, and human resources development. However, it will require the pragmatic support of policymakers to leverage BRI and boost the expansion of CCIs in Africa.

15 pages ; In this paper we propose a novel method to forecast the result of elections using only official results of previous ones. It is based on the voter model with stubborn nodes and uses theoretical results developed in a previous work of ours. We look at popular vote shares for the Conservative and Labour parties in the UK and the Republican and Democrat parties in the US. We are able to perform time-evolving estimates of the model parameters and use these to forecast the vote shares for each party in any election. We obtain a mean absolute error of 4.74%. As a side product, our parameters estimates provide meaningful insight on the political landscape, informing us on the quantity of voters that are strongly pro and against the considered parties.

The digital transformation is driving revolutionary innovations and new market entrants threaten established sectors of the economy such as the automotive industry. Following the need for monitoring shifting industries, we present a network-centred analysis of car manufacturer web pages. Solely exploiting publicly-available information, we con- struct large networks from web pages and hyperlinks. The network properties disclose the internal corporate positioning of the three largest automotive manufacturers, Toyota, Volkswagen and Hyundai with respect to innovative trends and their international outlook. We tag web pages concerned with topics like e-mobility & environment or autonomous driving, and investigate their relevance in the network. Toyota and Hyundai are concerned with e-mobility throughout large parts of their web page network; Volkswagen devotes more specialized sections to it, but reveals a strong focus on autonomous driving. Sentiment analysis on individual web pages uncovers a relationship between page linking and use of positive language, particularly with respect to innovative trends. Web pages of the same country domain form clusters of different size in the network that reveal strong correlations with sales market orientation. Our approach is highly transparent, reproducible and data driven, and could be used to gain complementary insights into innovative strategies of firms and competitive landscapes.