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The purpose of this paper is to focus on investigating the impact of crowd participation on degree of project success, which is defined as the total amount of funds a project can obtain after it reaches its initial funding goal threshold.

Drawing on the theory of crowd capital, this study develops six hypotheses about the impact of crowd capability of a fundraiser (i.e. project updates, goal setting, reward levels and social media usage) and crowd participation (i.e. namely, funds pledge and on-site communication) on degree of project success. The hypotheses are tested using data sets of successful projects collected from two popular crowdfunding websites.

This study finds that funds pledge has an inverse U-shaped relationship with degree of project success. Project updates, reward levels and on-site communication positively influence degree of project success, while funding goal negatively affects degree of project success.

This study contributes to prior literature by investigating the degree of project success determinants using the perspectives of both fundraisers and crowds, which provides a more comprehensive understanding of what makes a crowdfunded project a success.

The empirical results of this study provide fundraisers with guidelines about how to access more funds after achieving the initial funding goals.

This work is one of the first to investigate the degree of project success and its determinants from the perspectives of both fundraisers and crowds.

With the advent of Internet technologies, shorter product life cycles and increasing competition, organisations have started looking for innovation sources outside the organisational boundaries. The external community of crowds can be used as a valuable source of co-creation in a company's innovation process to generate value. Despite its growing popularity, organisations often face difficulty capturing value from crowdsourcing due to the lack of proper mechanisms behind crowdsourcing-based value co-creation between a crowd and an organisation and their impact on organisational learning and innovation performance. The present study seeks to understand the crowdsourcing-based co-creation mechanism that influences knowledge transfer effectiveness and the organisation's absorptive capacity, resulting in improved innovation performance.

The model was empirically tested using online survey data received from 300 managers of IT firms. Partial least squares structural equation modelling was used to test the model.

The empirical results reveal that crowdsourcing-based value co-creation causes structural, cognitive and relational linkages between a crowd and a firm, among which crowdsourcing-based cognitive linkage contributes more to organisational value capture. Further, an organisation's effective knowledge transfer and absorptive capacity play an important role in influencing the crowdsourcing-based-co-creation organisational learning-innovation performance framework.

This is the first and foremost study that has developed an integrated model using social capital dimensions to understand the entire mechanism behind crowdsourcing-based value co-creation between a crowd and an organisation and their impact on organisational learning and innovation performance. The study provides organisations with theoretical and practical implications of using crowdsourcing as a value co-creation tool and its effects on enhancing organisational learning and value capture.

The aim of this paper is to analyse the relationship between public debt, corporate debt service costs and private capital formation in South Africa.

To capture the long-run characteristic of investment, the study adopts the Fully Modified Ordinary Least Squares approach and tests for cointegration using Hansen (1992)'s Parameter Instability test.

We find that private capital formation increases in domestic debt and decreases in external debt during the pre-crisis period. However, during the period post the Global Financial Crisis, we find evidence of domestic public debt crowding out private capital formation, whereas external debt crowds-in capital formation. Debt service costs are found to reduce investment due to the effect of the debt overhang throughout the period under analysis.

The paper has important implications for macroeconomic policy. In particular, there is need for deleveraging and allocation of a higher proportion of debt to public infrastructure expenditure which has complementary effects on private investment.

Debt overhang signal that South African firms could be over-leveraged, which hinders future growth prospects. Firms that face high levels of debt should consider debt restructuring.

Empirical studies undertaken to explore this relationship have yielded contradicting results suggesting that the relationship between public debt and private investment is heterogeneous depending on a given economy or prevailing macroeconomic environment. In particular, existing research does not provide evidence on whether recent increases in public debt in South Africa have led to crowding-in or crowding-out of private investment. This paper therefore contributes to empirical literature on the impact of public debt on private investment within a small open economy.

The purpose of this paper is to examine the crowding-in or crowding-out relationship between public and private investment in India.

The autoregressive distributed lag (ARDL) bounds testing approach is used to estimate the long run relationship between public and private investment using annual data from 1971-1972 to 2009-2010.

Based on the empirical findings, it is observed that aggregate public investment has a positive effect on private investment both in the long run and the short run. In contrast to the findings of previous studies, no significant impact of public infrastructure investment on private investments is found in the long run, while non-infrastructure investment has a positive impact on private investment in the short run. Among the various categories of infrastructure sector, a positive and significant impact in the case of electricity, gas and water supply is observed. Similarly, the result indicates that public investment in machinery and equipment and construction have substantially influenced the private sector machinery and equipment in the long run and the short run. In the case of the role of macroeconomic uncertainty, the results find a negative and significant impact on private investment and the impact is higher in the short run than in the long run.

The present study extends the literature in three important ways: First, the study attempts to capture heterogeneity of public investment as well as disaggregate effects of two different categories of public infrastructure on private investment. The extent to which two different types of public assets impact the private investment in machinery and equipment investment is also examined. Second, ARDL model is used to examine the long-run relationship between public and private investment. Third, the study incorporates macroeconomic uncertainty into the empirical analysis to examine the role of macroeconomic volatility in determining private investment decision.

This contribution aims to evaluate key theoretical bases that were used in previous research, to investigate the use of crowdfunding platforms by small businesses and startups. It presents the findings from a systematic review to better explain the pros and cons of utilizing these disruptive technologies for crowdsourcing and/or crowd-investing purposes.

The researchers adopt the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodical protocol to search, screen, extract and scrutinize seventy-two (72) articles that were indexed in both Scopus and Web of Science. They examine their research questions, describe their methodologies. Afterwards, they synthesize the findings from previous literature, outline implications and discuss about future research avenues.

A thorough review of the relevant literature suggests that there are opportunities as well as challenges for project initiators as well as for crowd-investors, if they are considering equity crowdfunding, peer-to-peer (P2P) lending and rewards-based crowdfunding platforms, among others, to raise awareness about their projects and to access finance from crowd-investors.

Further research is required on this timely topic. There are a number of theories relating to technology adoption and/or innovation management, strategic management, accounting and financial reporting, and normative/business ethics, among other research areas, that can be utilized as theoretical bases, to explore this topic.

Crowd-investors are striving in their endeavors to find a trade-off between risks and rewards associated with crowd-financing.

Currently, there are few systematic reviews and conceptual articles focused on the crowdfunding of small businesses and startups. Hence this contribution closes this gap in the academic literature. Moreover, it links the extant theory to practice. It clarifies that the resource-based view theory of the firm, the theory of planned behavior, the diffusion of innovations theory as well as the signaling theory, among other conceptual frameworks, can be used to investigate different facets of crowdsourcing and crowd-investing.

This paper investigates the link between Intellectual Capital (IC) and Open Innovation (OI). Scholars worldwide consider the topics as standing alone and so they give scarce attention to the possible link between them. Managerial experiences (and few theoretical contributions), instead, hypothesize a significant role that IC can play over OI processes in order make them successful.

The methodology of a single case study is used to investigate the link between IC and OI. In particular, an OI process managed by a global company, LEGO, and named Mindstorms is rebuilt and analysed herein.

Intermediate results achieved by LEGO through its OI process were unsuccessful since the company had not developed its own IC (made up of relational, human and structural capital). The subsequent development of IC, instead, has driven to successful results. This suggests that if companies do not develop their IC before launching OI processes, then these processes might be not successful.

One limitation is the use of a single case study. Despite this, the present article is a warning for all the companies: before launching OI processes they need to develop their IC.

To the best knowledge of the authors, this is one of the first works that deepens the investigation of the link between IC and OI. Very often, scholars investigating IC shyly refer to OI, without mentioning it, while the scholars investigating OI allude to IC, without citing it. In this study, IC and OI are investigated together.

The purpose of this paper is to evaluate the nature and characteristics of crowd logistics business models. Using this evaluation, a new concept for a sustainable implementation of crowd logistics services is proposed.

The Design Science process was followed to develop the proposed crowd logistics business model concept. The data are derived from expert interviews and a document-based data analysis of 13 companies.

Four relevant steps that companies should follow to implement sustainable crowd logistics services are identified. Open research questions are also identified and guide five research tasks, which may lead to a greater understanding of this emerging field.

The present research is based on data from companies operating in Germany. The holistic approach gives a broad overview but lacks detailed descriptions.

Managers can use the four steps and the crowd logistics business model concept to plan future activities (e.g. new service provision). These steps increase the understanding, awareness and knowledge of opportunities and risks of specific crowd logistics services.

This paper provides initial insights into social changes in terms of drivers for the use of crowd logistics services. However, further research is needed to capture the social implications in detail.

Crowd logistics is an emerging concept, and this paper is one of the first dealing with this topic generally and the first providing an analysis of crowd logistics business models. The developed concept includes implications for practice in the forms of common, and best practices, and science in the form of open research questions and tasks. Overall, the present research provides new insights into this emerging topic.

The purpose of this paper is to analyse the institutional threshold effects of foreign aid on foreign direct investment (FDI).

This paper develops a theoretical model from an extended Solow model that introduces the conductive effect of institutions in an aid recipient country towards the capacity of attracting FDI. This study evidences threshold effects with the most recent panel threshold models that consider endogeneity issues. The data on economic institutions and foreign aid are decomposed into disaggregated level to reveal the detailed threshold pattern. Several sample subsets are used for a heterogeneity analysis.

Conducting empirical research on a sample of 62 countries during the period 2003–2016, this study finds robust evidence of the existence of an institutional threshold in the aid–FDI nexus which a country must attain to reap the full attraction of FDI by foreign aid providing financial resources. Furthermore, foreign aid tends to promote FDI in institutions characterized by a right-sized government, a strengthened legal system and an appropriate regulatory environment. On the other hand, aid may crowd out FDI. The results are robust to regional combinations and a subset of low and lower-middle-income countries. In addition, this study finds that aid targeted at social infrastructure and services has a positive effect regardless of institutional threshold.

This paper contributes to the literature by introducing a non-linear and discontinuous effect of aid on FDI, i.e. a threshold effect, highlighting the relevance of legal systems and regulations and the possibility of a crowding-out effect on FDI for specific institutional regimes. The thresholds provide a guide for donor countries to ensure aid effectiveness at the risk of being counterproductive and for recipient countries to better assess the institutional dimensions that need to be improved.

The purpose of this paper is to provide a new framework for managing intellectual capital (IC) inside a university considering the collective intelligence perspective.

The research method uses the fourth stage of IC research and adopts the collective intelligence approach. The underlying assumption behind the framework is to consider the university as a collective intelligence system in which the tangible and intellectual assets are coordinated towards the achievement of strategic goals.

The conceptual framework for IC management harnesses the power of IC, collectively created by the engagement of multiple stakeholders inside the university network. The main components are the final goal of a university (what); the collective human capital to achieve the goal (who); the processes activated inside the university (how); and finally the motivations behind the achievement of the goal (why).

The research is exploratory and the framework offers opportunities for refinement. Future research is needed to verify the application of the framework to other organisations in the public sector intended as collective intelligence systems. A new perspective for managing IC in universities adopting the collective intelligence approach is developed. Contribution to the fourth stage (ecosystem) of IC research is highlighted, expanding the concept of IC value creation beyond the university into wider society.

The framework can be used to manage IC strategically in all the systems interpreted as collective intelligence systems in which the role of IC creation from multiple actors is relevant. This makes possible the understanding of how IC helps create value for the society and the region in which the university operates.

The originality of the paper is in bringing together issues usually dealt within the literature in separate domains, such as IC management and collective intelligence perspective. The concept of collective intelligence remains an unexplored field in relation to IC management in the public sector. The collective intelligence approach provides a novel contribution to managing IC and is intended to inspire future research.

This study explores the asymmetric linkage between public investment and private sector performance in Nigeria. This is due to the presence of nonlinear structures in the behavior of domestic investment series with evidences of structural time breaks, which fall within periods of global financial crises and oil shocks.

Main data on gross capital formation, gross fixed capital formation, domestic credit to private sector, domestic credit to private sector by banks are used for the study span through 1986 to 2017. Evidence of asymmetry spurs the study to adopt the nonlinear autoregressive distributed lag, asymmetric generalized impulse response and variance decomposition and asymmetric granger causality techniques.

It is shown that positive (negative) investment shocks exhibit a non-negligible and substantial stimulating (dampening) influence on the long-run performance of private sector in the economy. However, there is evidence that negative investment shocks portend a positive influence on the performance of private sector in the short run. This suggests that negative shocks to investment may not dampen the effectiveness of private sector in the short run, and this thus brings to bear the debate on the tenability of public investment as a potent counter cyclical tool in enhancing short-run private sector growth. The nonlinear granger causality also shows a unidirectional nonlinear causality from public investment to private sector performance. However, there is no evidence of bidirectional nonlinear causality.

This study provides quantitative evidence that Nigeria still depends exclusively on public investment, and as an oil-based rentier economy its economic diversification drive still remains bleak.