Get the Cogs in Synch – Time Horizon Aspects of Industry–Academia Collaboration

In industry–academia collaboration projects, there are many issues related to different time horizons in industry and academia. If not adressed upfront, they may hinder collaboration in such projects. We analyze our experiences from a 10 year industry–academia collaboration program, the EASE Industrial Excellence Center in Sweden, and identify issues and feasible practices to overcome the hurdles of different time horizons. Specifically, we identify issues related to contracts, goals, results, organization (in)stability, and work practices. We identify several areas where the time horizon is different, and conclude that mutual awareness of these dif- ferences and management commitment to the collaboration are the key means to overcome the differences. The launch of a mediating institute may also be part of the solution

An industry-academia, multidisciplinary and expertise-heterogeneous design approach: a case study on designing for mobility

Trabalho apresentado na: "DIGICOM 2021 – 5th International Conference on Design and Digital Communication", 4-6 November 2021, Teatro Gil Vicente, Barcelos, Portugal.The purpose of this article is to provide a better understanding of how to effectively develop design projects that simultaneously leverage industry and academic partners, participants from various disciplinary backgrounds, and vari- ous levels of expertise to solve complex problems. The article reports a single case of an ongoing project focused on designing smart and connected devices for mobility, which integrates the dimensions of interest. Our findings highlight the importance of careful planning of the collaborative process, contemplating of- fline and real-time communication opportunities, identifying cross-boundary roles, and considering the development of shared expertise and knowledge within the team. By confronting these findings with key literature, we offer five recom- mendations to inform similar future projects.This work is supported by European Structural and Investment Funds in the FEDER component, through the Operational Competitiveness and Internationalization Pro- gramme (COMPETE 2020) [Project no 039334; Funding Reference: POCI-01-0247- FEDER-039334]. This work has additional financial support from Project Lab2PT - Landscapes, Heritage and Territory laboratory - AUR/04509, with financial support from FCT/MCTES through national funds (PIDDAC) and co-financing from the Eu- ropean Regional Development Fund (FEDER) POCI-01-0145-FEDER-007528, in line with the new partnership agreement PT2020 through COMPETE 2020 – Compet- itiveness and Internationalization Operational Program (POCI)

Critical Success Factors of Digital Business Strategy

Digitalization does fundamentally impact firms’ strategy develop-ment. With the fusion of IT and business strategy, Digital Business Strategy (DBS) creates the foundation for digital business models [1]. In this paper, we develop a DBS framework, based on a structured review of 21 industry reports. From this analysis, we yield 8 generic dimensions with a total of 40 critical suc-cess factors (CSFs) for DBS. The CSFs represent a rich set of actions specific to DBS and to the design of business models in the digital business environment. The discussion shows that academic research is lagging behind in contributing to DBS. Future research is suggested to further formalize the concept of DBS and to create a better understanding about how firms can successfully establish DBS

The 4+1 View Model of Industri-Academia Collaboration

Abstract Industry-academia projects exist in complex contexts of various stakeholders, time perspectives, and goals. In order to analyze projects and communicate about them, we have defined an "architectural" model for industryacademia collaboration, inspired by Kruchten's software architecture model. The model has four views of i) time, ii) space, iii) activity and iv) domain, corresponding to the questions: when, where, how and what. The +1 view is the scenario, binding the other four together. We illustrate the model by applying it to the Industrial Excellence Center EASE and the Sigrun Software Innovation and Engineering Institute. The model helps analyzing industry-academia collaboration projects, to find gaps and reduce redundant work

On collaboration between academia and practice for research and innovation: A pilot study for BillerudKorsnäs

Collaboration between academia and industry is believed important for innovation: industry needs academic expertise and know-how and academics need empirical data, test beds and more. So what needs to be improved? A pilot study conducted for BillerudKorsnäs confirms findings in previous research: the main challenge to industry-academia collaboration is the lack of mutual understanding of each other’s needs, expectations and output. However, despite the clear importance of mutual understanding, there are few suggestions in the literature how to improve the situation beyond checklists for collaboration. The pilot study addresses issues of how to find sharp research tasks that are relevant to both parties, how to bridge cultural differences and different demands, and what kind of interaction model to aim for? Based on a literature review, interviews with accomplished academics at Lund University and practitioners from BillerudKorsnäs, the conclusions drawn in summary are: • Finding a good research builds on mutual understanding of different needs, combining industry problems with issues relevant for developing the greater knowledge base (theory). • Bridging cultural and other differences is best done through a greater “understanding of each other’s worlds,” spending time together, building trust, and improving communication through key persons from both sides who play the role of “translators” or “liaison officers.” • Finding the best interaction model (i.e. PhD, consortia etc) requires time and other resources to address needs, research goals and expectations, team members, responsibilities, and not least: deliverables. There is no one model, but as a general rule, long-term strategic collaboration efforts are found more fruitful based on an equal partner approach where learning is at the core. Furthermore, the authors of the study suggest that an important step forward, for a firm who wishes to collaborate with academia, is to develop a visual tool to facilitate mutual understanding. Drawing from previous and more recent findings, one such tool could be a further development of the so-called Technology Readiness Levels (TRL) model, or other generic models for project, process, or product development

Industry-academia collaborations in software testing: experience and success stories from Canada and Turkey : Special Issue Industry Academia Collaborations in Software Testing

Collaboration between industry and academia supports improvement and innovation in industry and helps to ensure industrial relevance in academic research. However, many researchers and practitioners believe that the level of joint industry–academia collaborations (IAC) in software engineering (SE) is still relatively very low, compared to the amount of activity in each of the two communities. The goal of the empirical study reported in this paper is to characterize a set of collaborative industry–academia R&D projects in the area of software testing conducted by the authors (based in Canada and Turkey) with respect to a set of challenges, patterns and anti-patterns identified by a recent Systematic Literature Review study, with the aim of contributing to the body of evidence in the area of IAC, for the benefit of SE researchers and practitioners in conducting successful IAC projects in software testing and in software engineering in general. To address the above goal, a pool of ten IAC projects (six completed, two failed and two ongoing) all in the area of software testing, which the authors have led or have had active roles in, were selected as objects of study and were analyzed (both quantitatively and qualitatively) with respect to the set of selected challenges, patterns and anti-patterns. As outputs, the study presents a set of empirical findings and evidence-based recommendations, e.g.: it has been observed that even if an IAC project may seem perfect from many aspects, one single major challenge (e.g., disagreement in confidentiality agreements) can lead to its failure. Thus, we recommend that both parties (academics and practitioners) consider all the challenges early on and proactively work together to eliminate the risk of challenges in IAC projects. We furthermore report correlation and interrelationship of challenges, patterns and anti-patterns with project success measures. This study hopes to encourage and benefit other SE researchers and practitioners in conducting successful IAC projects in software testing and in software engineering in general in the future