Objectives. The research aims to investigate how firms can achieve alliance success. In global markets, the alliance failure rate is very high. This study will try to understand why, facing with such a high failure rate, more and more firms decide to enter or form strategic alliances. It appears necessary to identify key factors and show how firms can successfully manage them in each phase of alliance lifecycle.Methodology. For this study, a qualitative approach was adopted, in order to explore and understand the research problem. The issues of alliance success factors is investigated through the analysis of the existing literature, focusing in particular on the last two decades.Findings. By reviewing several theoretical perspectives, we identified alliance success factors and showed what kind of relevance they have in each phase of alliance lifecycle. It was found that strategic alliances develop through three phases. Alliance success lies on successful management of key factors, involved in each phase.Research Limits. Research deals with the issues of alliance success factors at the level of a single alliance and not at the level of an alliance portfolio. Further research should extend the analysis perspective.Managerial Implications. Firms involved in a strategic alliance should consider several critical aspects. For the entire alliance lifecycle, they have to look for a high degree of fit with their own partners. Another important aspect is related to the risk of opportunistic behavior, which could be reduced through the choice of an appropriate governance form and the development of social capital.

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Thematic Area Label Description Source Year Population Pop.2017 Total population on 1st January Eurostat [demo_r_d2jan] 2017 % Pop. >65 People aged 65 and over (% of total population) elaboration on Eurostat [demo_r_pjanaggr3] 2017 % Pop. <15 People aged less than 15 (% of total population) elaboration on Eurostat [demo_r_pjanaggr3] 2017 % foreigners Foreign (EU and non-EU countries) population (% of total population) elaboration on Eurostat [cens_11ctzo_r2] 2011 Pop. Density Population density (per km2) Eurostat [demo_r_d3dens] 2017 % Pop upper secondary/ tertiary educ. Population aged 25-64, with upper secondary and tertiary education (ISCED levels 3-8) (% of total population) Eurostat [edat_lfse_04] 2017 Economy and labour market per capita GDP Gross domestic product (GDP) at current market prices in Purchasing Power Standard, per inhabitant Eurostat [nama_10r_2gdp] 2016 Unempl. Rate Unemployment rate (15-74 years) Eurostat [lfst_r_lfu3rt] 2017 Empl. Rate Employment rate (15-64 years) Eurostat [lfst_r_lfe2emprt] 2017 Sectoral structure* Due to the presence of missing values in the structural business statistics (SBS) section, the values for year 2015 can be replaced with the values from the closest available year (2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015).However, for some regions and some NACE Rev.2 divisions, no data are available for the whole period under consideration. In these cases, a value equal to 0 is assigned to the specific region/division.

The last twenty years have witnessed the diffusion of regional innovation policies supporting networks of innovators. The underlying aim of these policies is to encourage firms, particularly SMEs, to undertake collaborations with organisations possessing complementary knowledge. Focusing on a set of SMEs that have participated, over time, in several innovation networks funded by the same regional 2 government, the paper investigates how their relationships have evolved with respect to the following aspects: (i) reiteration of pre-existing relationships as opposed to experimentation of new relationships; (ii) collaboration with organisations possessing complementary rather than similar knowledge and competencies; (iii) creation of local relationships rather than experimentation of extra-local collaborations; (iv) reliance upon intermediaries to connect with other organisations. Our findings reveal that the involvement in these policy-supported networks changed the firms' relational patterns, leading them to collaborate with a wider variety of agents than those with whom they were linked before the policies. Sectoral heterogeneity had a negative effect on the probability to collaborate, while co-localisation increased the likelihood to collaborate. Mutual involvement with intermediaries also had a positive effect.However, in the case of firm-to-university relationships only specialized intermediaries were likely to perform a positive role and, therefore, encourage networking.

We analyse whether public subsidies supporting collaborative research and development (R&D) projects in small and medium-sized enterprises (SMEs) are able to encourage persistent R&D investment and interorganisational networking more than subsidies supporting individual R&D projects. Adopting a counterfactual approach to policy evaluation, we compare subsidies for collaborative R&D and for individual R&D implemented in the same Italian region in the same period. Our findings suggest that, once public support is no longer available, the two subsidies have different effects on different types of SMEs. If the policymakers' objective is to increase the number of R&D-performing SMEs over time, they should provide subsidies for collaborative R&D to firms with modest R&D experience. If their objective is to increase the amount of spontaneous R&D investment over time, they should target SMEs with some prior R&D experience, using either subsidy. Finally, if their objective is to induce SMEs to network with external organisations, subsidies for collaborative R&D projects should be preferred to subsidies for individual R&D projects.

The paper focuses on a key uniqueness of the simultaneous generation of social and business value -across science, technology and society -involving academics, businesses, policy makers, innovation intermediaries, NGOs and citizens that share and integrate assets in developing solutions to address economic and societal challenges.By contrasting with a broad literature using the term 'co-creation' to denote close working relationship between actors, the paper outlines a conceptual framework explaining how the diversity of agents involved, their motivations and goals, and incentive structures in which they operate impact on science-based co-creation. This multidimensional perspective is discussed with regard to the scope of innovation, reach and types of values that are generated, and the distinctive features to be considered when both social and business value are at the core of collaboration.Policy implications to support science-based co-creation are discussed with regard to the rationale for public interventions and the critical dimensions of policy implementation and assessment. It highlights that policy design aiming at supporting societal challenges through cocreation should address mechanisms to integrate tangible and intangible inputs, define suitable operational models and enhance specific capabilities and practices.

A growing number of innovation policies rely on publicly funded innovation intermediaries to provide knowledge-intensive services to firms, particularly small and medium-sized ones. The performance of innovation intermediaries is often assessed using indicators that need to be closely aligned with policy objectives to be effective. However, this alignment is difficult to achieve and is often overlooked in practice. We analyse the relationship between performance indicators and the behaviour of intermediaries by examining a case study of innovation intermediaries funded with public resources in Tuscany (Italy). The intermediaries implemented actions that allowed them to achieve their performance targets rapidly. However, due to a misalignment between indicators and policy objectives, these actions were not entirely consistent with the latter. After reviewing the literature on this key issue, we build on our findings to suggest how to design performance indicators that can induce intermediaries to more effectively support the achievement of policy objectives.

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