Emerging resource flows for social entrepreneurship; theorizing social investment

In the UK and elsewhere, a ‘market’ in social investment has been developing rapidly over the last 10-15 years, yet there has not been an academic study of the phenomenon to date. This paper aims to address this important gap in social entrepreneurship research. Empirically, the aim of this paper is to outline the nature, scale, and forms of these financial flows. Theoretically, the aim is to conceptualize social investment and build an analytic model of its different orientations. The paper suggests three future scenarios for social investment that blend, in different combinations, instrumental and substantive rationalities and logics

Resistance to multilateral influence on reform : the political backlash against private infrastructure investments

Coercive isomorphism is a prominent source of institutional change. The literature to date has emphasized how actors that are powerful and legitimate (for example, a national government) may coerce the adoption of reforms by dependent actors (for example, state governments and other organizations whose activities are governed by the federal government). The authors observe that an actor's power alone may be sufficient to promote reform, regardless of the actor's legitimacy. But such reforms are more susceptible to subsequent change than those that emerge from processes not subject to the influence of external actors whose sway derives from their power alone. They develop and test their arguments in the context of the worldwide electricity provision industry by analyzing countries'adoption of reforms in response to conditional lending practices by multilateral organizations such as the World Bank and the International Monetary Fund. The authors find that reforms adopted in response to coercive pressures exerted by these organizations encounter much greater resistance, and that the incidence of financial and economic crises, the absence of checks and balances in established political institutions, and the inexperience of investor coalitions dramatically increase the predicted level of resistance.National Governance,Health Monitoring&Evaluation,ICT Policy and Strategies,Politics and Government,Governance Indicators

Pattern Recognition: Industry seeking regulation – the case of crowdfunding. Bruges Political Research Papers 79/2020

At first it seems counterintuitive that an industry would seek regulation over itself, but from the point of view of crowdfunding, it was a logical step. Crowdfunding, as part of FinTech, is changing and challenging traditional financial institutions. The fragmentation of the EU market by national legislation on crowdfunding hindered its growth, and although FinTech is a diffuse interest, crowdfunding, as a pragmatic diffuse interest, formed legitimacy coalitions with the regulators. Utilizing Trumbull’s framework on pragmatic diffuse interest, my aim is to demonstrate through this case study that the industry lobby had influenced the agenda-setting and the policy-shaping, but only to the extent that there wasn’t conflicting interest from consumer groups. This is in line with previous finding on financial industry lobbying and some preliminary findings emerge, although as the proposal is still in first reading stage, the end results and conclusions remains to be see

Value proposition as a framework for value co-creation in crowd-funding ecosystem

The present paper suggests that crowd-funding in the arts and cultural sector occurs within a complex service ecosystem, where six categories of value propositions frame eight value co-creation processes, namely through ideation, evaluation, design, testing, launch, financing and authorship. Managerial contributions include the development of a crowd-funding service ecosystem model for arts managers, which offers not only a method of financing or economic value, but which also offers opportunities for strengthening bonds with customers and other stakeholders. Our paper is innovative in that we integrate value propositions categories with the micro – meso and macro contexts and analyse the different kind of co-creation are framed in the crowdfunding contextUniversidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Performative Work: Bridging Performativity and Institutional Theory in the Responsible Investment Field

Callon’s performativity thesis has illuminated how economic theories and calculative devices shape markets, but has been challenged for its neglect of the organizational, institutional and political context. Our seven-year qualitative study of a large financial data company found that the company’s initial attempt to change the responsible investment field through a performative approach failed because of the constraints posed by field practices and organizational norms on the design of the calculative device. However, the company was subsequently able to put in place another form of performativity by attending to the normative and regulative associations of the device. We theorize this route to performativity by proposing the concept of performative work, which designates the necessary institutional work to enable translation and the subsequent adoption of the device. We conclude by considering the implications of performative work for the performativity and the institutional work literatures

Understanding business strategies of networked value constellations using goal- and value modeling

In goal-oriented requirements engineering (GORE), one usually proceeds from a goal analysis to a requirements specification, usually of IT systems. In contrast, we consider the use of GORE for the design of IT-enabled value constellations, which are collections of enterprises that jointly satisfy a consumer need using information technology. The requirements analysis needed to do such a crossorganizational design not only consists of a goal analysis, in which the relevant strategic goals of the participating companies are aligned, but also of a value analysis, in which the commercial sustainability of the constellation is explored. In this paper we investigate the relation between strategic goal- and value modeling. We use theories about business strategy such as those by Porter to identify strategic goals of a value constellation, and operationalize these goals using value models. We show how value modeling allows us to find more detailed goals, and to analyze conflicts among goals

Complex City Systems

Information and communications technology (ICT) is being exploited within cities to enable them to better compete in a global knowledge-based service-led economy. In the nineteenth and twentieth centuries, cities exploited large technical systems (LTSs) such as the telegraph, telephony, electrical networks, and other technologies to enhance their social and economic position. This paper examines how the LTS model applies to ICT deployments, including broadband network, municipal wireless, and related services, and how cities and city planners in the twenty-first century are using or planning to use these technologies. This paper also examines their motivations and expectations, the contribution to date, and the factors affecting outcomes. The findings extend the LTS model by proposing an increased role for organizations with respect to an individual agency. The findings show how organizations form themselves into networks that interact and influence the outcome of the system at the level of the city. The extension to LTS, in the context of city infrastructure, is referred to as the complex city system framework. This proposed framework integrates the role of these stakeholder networks, as well as that of the socioeconomic, technical, and spatial factors within a city, and shows how together they shape the technical system and its socioeconomic contribution. The CCS framework has been presented at Digital Cities Conferences in Eindhoven, Barcelona, Taiwan, London and at IBM’s Global Smart Cities Conference in Shanghai between 2010 and 2012. Its finding are timely in the context of major policy decisions on investments at regional, national and international level on ICT infrastructure and related service transformation, as well as the governance of such projects, their planning and their deployment

Deep reinforcement learning for investing: A quantamental approach for portfolio management

The world of investments affects us all. The way surplus capital is allocated by ourselves or investment funds can determine how we eat, innovate and even educate kids. Portfolio management is an integral albeit challenging process in this task (Leković, 2021). It entails managing a basket of financial assets to maximize the returns per unit of risk, considering all the micro and macro economical, societal, political and environmental complex causal relations. This study aims to evaluate how a machine learning technique called deep reinforcement learning (DRL) can improve the activity of portfolio management. It also has a second goal of understanding if financial fundamental features (i.e., revenue, debt, assets, cash flow) improve the model performance. After conducting a literature review to establish the current state-of-the-art, the CRISP-DM method was followed: 1) Business understanding; 2) Data understanding; 3) Data preparation – two datasets were prepared, one with market only features (i.e., close price, daily volume traded) and another with market plus fundamental features; 4) Modeling – Advantage Actor-Critic (A2C), Deep Deterministic Policy Gradient (DDPG) and Twin-delayed DDPG (TD3) DRL models were optimized on both datasets; 5) Evaluation. On average, models had the same sharpe ratio performance in both datasets – average sharpe ratio of 0.35 vs 0.30 for the baseline, in the test set. DRL models outperformed traditional portfolio optimization techniques and financial fundamental features improved model robustness and consistency. Hence, supporting the use of both DRL models and quantamental investment strategies in portfolio management.Todos somos afetados pelo mundo dos investimentos. A forma como o excedente de capital é alocado tanto por nós como por fundos de investimentos determina a forma como comemos, inovamos e até mesmo como fornecemos educação às crianças. Gestão de portfólio é uma tarefa essencial e desafiadora neste processo (Leković, 2021). Envolve gerir um conjunto de ativos financeiros com o objetivo de maximizar os retornos por unidade de risco, tendo em consideração todas as relações complexas entre fatores macro e microeconómicos, sociais, políticos e ambientais. Este estudo pretende avaliar de que forma a técnica de machine learning intitulada de Aprendizagem por Reforço Profunda (ARP) consegue melhorar a tarefa de gestão de portfólios. Também tem um segundo objetivo de entender se variáveis relacionadas com a performance financeira de uma empresa (i.e., vendas, passivos, ativos, fluxos de caixa) melhoram a performance do modelo. Após o estado-de-arte ter sido definido com a revisão de literatura, utilizou-se o método CRISP-DM da seguinte forma: 1) Entendimento do negócio; 2) Entendimento dos dados; 3) Preparação dos dados – dois conjuntos de dados foram preparados, um apenas com variáveis de mercado (i.e., preço de fecho, volume transacionado) e o outro com variáveis de mercado mais variáveis de performance financeira; 4) Modelagem – usou-se os modelos Advantage Actor-Critic (A2C), Deep Deterministic Policy Gradient (DDPG) e Twin-delayed DDPG (TD3) em ambos os conjuntos de dados; 5) Avaliação. Em média, os modelos apresentaram o mesmo índice sharpe nos dois conjuntos de dados – média de 0.35 vs 0.30 para o modelo base, no conjunto de teste. Os modelos ARP apresentaram uma melhor performance do que os modelos tradicionais de otimização de portfólios e a utilização de variáveis de performance financeira melhoraram a robustez e consistência dos modelos. Tais conclusões suportam o uso de modelos ARP e de estratégias de investimentos quantamentais na gestão de portfólios

The Jatropha Biofuels Sector in Tanzania 2005-9: Evolution Towards Sustainability?

Biofuel production has recently attracted a great deal of attention. Some anticipate substantial social and environmental benefits, while at the same time expecting sound profitability for investors. Others are more doubtful, envisaging large trade-offs between the pursuit of social, environmental and economic objectives, particularly in poor countries in the tropics. The paper explores these issues in Tanzania, which is a forerunner in Africa in the cultivation of a bio-oil shrub called Jatropha curcas L. We trace how isolated Jatropha biofuel experiments developed since their inception in early 2005 towards a fully fledged sectoral production and innovation system; and investigate to what extent that system has been capable of developing ànd maintaining sustainable practices and producing sustainable outcomes. The application of evolutionary economic theory allows us to view the development processes in the sector as a result of evolutionary variation and selection on the one hand, and revolutionary contestation between different coalitions of stakeholders on the other. Both these processes constitute significant engines of change in the sector. While variation and selection is driven predominantly by localised learning, the conflict-driven dynamics are highly globalised. The sector is found to have moved some way towards a full sectoral innovation and production system, but it is impossible to predict whether a viable sector with a strong “triple bottom line” orientation will ultimate emerge, since many issues surrounding the social, environmental and financial sustainability still remain unresolved.biofuels, evolutionary theory, innovation systems, sustainability, stakeholder conflict, learning, Tanzania.