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Nowadays, the agri-food sector is facing several challenges due to a rapid technological change which calls for knowledge sharing (KS) practices to enhance businesses’ performance. This has spurred a collaborative approach and the creation of networks. Since there still is a paucity of research on the quality degree of KS, the purpose of this study is to offer an empirical research on the quality degree of KS by exploring outcome expectations and social exchange dimensions. Theoretically, it is examined by a double lens of social capital and social cognitive theory.

This study offers an empirical analysis of 313 directors of 11 “consortia” in the agri-food sector in Italy by using the fuzzy expert system. The model allows to aggregate multi criteria dimensions of KS and rates its quality.

As resulted, the quality degree of KS is influenced by outcome expectations – personal and community expectations – and three forms of dimensions of social exchange: structural, relational and cognitive. The paper ends with a discussion of research findings, its limitations and implications.

As there is still a paucity of research on the determinants of quality degree of KS, the research adopts a double lens of social capital and social cognitive theories to explore what are these determinants.

This study aims to build and test an International Market Selection (IMS) decision process method that is able to capture, within a small firm’s risk-averse setting, the entrepreneur's experience, reduce cognitive biases, and preserve the flexibility of the decision, by combining the advantages of systematic and behavioural-based international market selection approaches.

The unit of analysis is the IMS decision process of a small firm venturing abroad. We adopt a ranking approach based on three-step screening. We assess the markets through a multi-criteria approach with a wider set of variables aggregated within a tree-shaped model. To obtain the ranking, we use a Fuzzy Expert System (FES) as an evaluative tool.

The results show that the proposed decision method is consistent with the entrepreneur’s strategic orientation and experience, while preserving the flexibility requested for decision-making in small firms. Unlike traditional behavioural IMS approaches, the method demonstrates an ability to reduce the cognitive biases associated with the use of a limited set of variables and unreliable evaluation models.

The single-case-study approach limits generalization of the findings.

The proposed methodology helps the decision-maker to improve the quality of the IMS decision by reducing the effect of cognitive biases that usually affect traditional behavioural models.

For the first time, a decision-process methodology based on an FES is applied to a small firm’s IMS problem.

The purpose of the paper is to focus on the rating, ranking and valuing of firms.

Fuzzy logic and expert systems are used in order to provide a score for the firm(s) under consideration, representing the firm value‐creating power.

The fuzzy expert system introduced is capable of dealing with both quantitative and qualitative variables and integrates financial, managerial and strategic variables. A sensitivity analysis corroborates the model.

The system is apt to rate and rank firms within a sector. Some regression analysis can lead to a determined price for the target firm.

The expert system may be used by rating agencies for ranking firms, and by financial analysts and potential buyers to furnish a price for acquisition.

The use of a fuzzy expert system for ranking firms within a sector and pricing firms is a first attempt at an alternative way of measuring performance and value.

The purpose of this paper is to propose a method to measure intellectual capital (IC) in firms involved in strategic alliances, an area that has received scant attention in the literature, as existing research is focused mainly on organizational level mainly and increasingly on macro-level unit such as regions or nations. There are very few works at the meso-level (i.e. alliances, clusters), and the paper aims to fill this void, by providing researchers and practitioners with a tool capable of combining measurement and management aims, developed at organizational level with the active participation of the researchers.

The method of analysis is based on a model formalized through a fuzzy expert system (FES). The FES are able to merge the capabilities of an expert system to simulate the decision-making process with the vagueness typical of human reasoning, maintaining the ability to still have a numeric value as a response. Its construction requires the participation of experts, whose knowledge of the problem is accumulated in the form of blocks of rules. These features make it possible to formalize the decision-making process related to the IC valuation, handling qualitative and quantitative variables, and exploring the cognitive mechanisms underlying this process.

The outcome of the application is a system designed to measure the intangible performance deriving from participation in a strategic alliance using FES. This study contributes to the broadening of the research community’s understanding regarding the alternative measurement of IC created within strategic alliances.

To the best of the authors’ knowledge, IC literature lacks methods expressly designed to measure the incremental value of IC originating from collaboration among firms. From a measurement perspective, the results may be regarded as valuable proof that IC performance within strategic alliances can be measured quantitatively.

On the management side, the possibility of retracing the determinants of different IC intermediate indicators composing the final IC index allows strategic alliances managers to use this information for decision-making purposes.

To the best of the authors’ knowledge this is the first study applying FES to measure IC in a firm belonging to a strategic alliance. In the authors’ opinion, fuzzy logic methodology, recently applied in empirical work designed to evaluate IC, represents a reliable methodology because of the “fuzzy” nature of IC.

The paper aims to investigate the role of the network in managing the tradition and innovation paradox in the agribusiness industry. In particular, this study aims to demonstrate that agribusiness firms can innovate through tradition by joining a network, to capture the way intellectual capital (IC) is created, shared and transformed.

The authors approached the study using the social capital conceptual framework, considering the network a critical determinant of social capital, which enhances the organization's ability to share, create and utilize knowledge. Then, the authors also employed the extended territorial strategy theory. The authors derived empirical evidence from companies belonging to the PGI-labeled Consortium of Pasta di Gragnano (Consortium). The authors used a quantitative approach, carrying out a panel data analysis.

The results suggested that belonging to Consortium had a positive impact on the operating performance, the financial performance and the environment where consortium firms operate. Thus, being part of a network helps firms to innovate in a traditional industry.

The evidence of this work provided several implications for managers, IC community and the policy public. For managers, the authors observed that agribusiness firms can preserve their traditions through knowledge sharing with firms that operate in the same network. For IC community, the authors contributed to the debate on the social capital theory, arguing that the one area of IC that has received significant attention is the role of the network, which enhances the organization's ability to generate, share and apply knowledge effectively (Lin, 2017; Solitander and Tidström, 2010). Finally, the authors argued that policymakers should implement new reforms that facilitate the formation of networks, especially in socio-economic contexts where the unemployment rate is high.

This is the first study that employs quantitative analysis to investigate this paradox.

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.