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The food industry is a well-established and complex industry. New entrants attempting to penetrate it via the commercialization of a new technological innovation could face high uncertainty and constraints. The capability to innovate through collaboration and to identify suitable strategies and innovative business models (BMs) can be particularly important for bringing a technological innovation to this market. However, although the potential for these capabilities has been advocated, we still lack a complete understanding of how new ventures could support the technology commercialization process via the development of BMs. The paper aims to discuss these issues.

To address this gap, this paper builds a conceptual framework that knits together the different bodies of extant literature (i.e. entrepreneurship, strategy and innovation) to analyze the BM innovation processes associated with the exploitation of emerging technologies; determines the suitability of the framework using data from the exploratory case study of IT IS 3D – a firm which has started to exploit 3D printing in the food industry; and improves the initial conceptual framework with the findings that emerged in the case study.

From this analysis it emerged that: companies could use more than one BM at a time; hence, BM innovation processes could co-exist and be run in parallel; the facing of high uncertainty might lead firms to choose a closed and/or a familiar BM, while explorative strategies could be pursued with open BMs; significant changes in strategies during the technology commercialization process are not necessarily reflected in a radical change in the BM; and firms could deliberately adopt interim strategies and BMs as means to identify the more suitable ones to reach the market.

This case study illustrates how firms could innovate the processes of their BM development to face the uncertainties linked with the entry into a mature and highly conservative industry (food).

The purpose of this paper is to illustrate the development of the final outputs of a research project looking at partnerships between technology‐based start‐ups and large firms (“asymmetric” partnerships). It presents the stage of the research aimed at understanding how best to design outputs to assist firms in managing such partnerships.

A combination of company case studies, company workshops, an end‐user survey and pilot dissemination programme were used to identify an appropriate form for the packaging and delivery of the research findings (i.e. what problems can be encountered in such partnerships, and what approaches companies have implemented to overcome these problems).

A range of approaches for overcoming the problems of managing partnerships between firms whose age and size are markedly different were catalogued. The research presented in this paper revealed that companies felt best able to learn from the experiences of others through a combination of direct support, multi‐company workshops, and online access to selected materials.

The generalisability of the findings may be limited by the fact that the majority of the organisations collaborating in this research either were located in the high‐technology business cluster in and around the city of Cambridge, UK or had formed partnerships with companies in this geographic region.

Partnerships between technology‐based start‐ups and technology‐intensive large firms can provide an effective means of accessing and integrating the complementary assets required to bring a novel technology to market. This research will help firms overcome the numerous challenges involved in setting up and managing such partnerships by providing stakeholders with easier access to academic research findings. It will assist researchers who are considering how to disseminate research outputs to industry.

There is a strong body of work on improving the performance of partnerships in general, but less on overcoming the practical challenges of managing partnerships between firms of markedly different age and scale. In addition, the selection of the optimum process for ensuring that the findings of such research are used to support implementation remains a topic of debate. This work helps to address both gaps.

Innovation is an increasingly distributed process, involving networks of geographically dispersed players with a variety of possible, and dynamic, value chain configurations (Fraser, Minshall, & Probert, 2005). ‘Open innovation’ is one term that has emerged to describe ‘[…] the use of purposive inflows and outflows of knowledge to accelerate internal innovation, and expand the markets for external use of innovation, respectively’ (Chesbrough, Vanhaverbeke, & West, 2006). This is contrasted with the ‘closed’ model of innovation where firms typically generate their own ideas which they then develop, produce, market, distribute and support.

The purpose of this paper is to propose and discuss a definition and a classification scheme for direct writing (DW) technologies.

Both the definition and the classification are developed based on the perspectives of the growing DW community in the UK, through consultation with members, workshops and a survey across the community. In addition, current DW technologies and literature on classification techniques are reviewed.

The classification is structured in order to encompass current technologies, but also to be expandable to accommodate new ones that could be identified in the future as belonging to the DW remit. It is developed considering three dimensions related to DW: “Technology” to encompass all the processes, apparatuses, principles and tools which allow DW manufacturing; “Applications” to consider all the “types of manufactured goods” which could be produced with the DW technologies; and “Materials” which could be employed in DW manufacturing. The classification scheme is visualised into navigation maps and used as the basis of a software tool which can allow the community to exchange information on DW.

The paper proposes a classification as a tool for knowledge exchange and to support knowledge organisation and retrieval. However, the classification proposed in this paper might not be the only possible solution.

The definitional framework is proposed to the DW community as a language tool to help communication among members with different perspectives and to be used to support the creation of information databases. It is embodied in a software tool through which they could file personal profiles (i.e. their expertise and interests) and hence map the community.

It is evident that, due to the heterogeneity of the community of scientists and practitioners interested in these technologies, many perspectives coexisted and that a communication platform is required. The authors decide to develop a classification which could be flexible enough to encompass new emerging technologies as the use of classifications as tools for supporting communication across the scientific community is well known and as the authors could not identify in literature any other DW technology classification which could satisfy these requirements.

Since the first definition of open innovation (OI), the indivisible relationship between this concept and entrepreneurship was undeniable. However, the exact mechanisms by which an entrepreneurial approach may benefit OI processes and vice versa are not yet fully understood. The study aims to offer an accurate map of the knowledge evolution of the OI–entrepreneurship relationship and interesting gaps to be filled in the future.

The study adopted a bibliometric analysis, coupled with a systematic literature review performed over a data set of 106 peer-reviewed articles published from 2005 to 2020 to identify thematic clusters.

The results show five thematic clusters: entrepreneurial opportunities, organisational opportunities, strategic partnership opportunities, institutional opportunities and digital opportunities for OI. Investigating each of them, the authors created a framework that highlights future avenues for further developing the topic.

This study is the first of its kind to systematise, analyse and critically interpret the literature concerned with the topic of the OI–entrepreneurship.