Continuous and collaborative technology transfer : Software engineering research with real-time industry impact

Context: Traditional technology transfer models rely on the assumption that innovations are created in academia, after which they are transferred to industry using a sequential flow of activities. This model is outdated in contemporary software engineering research that is done in close collaboration between academia and industry and in large consortia rather than on a one-on-one basis. In the new setup, research can be viewed as continuous co-experimentation, where industry and academia closely collaborate and iteratively and jointly discover problems and develop, test, and improve solutions. Objective: The objective of the paper is to answer the following research questions: How can high-quality, ambitious software engineering research in a collaborative setup be conducted quickly and on a large scale? How can real-time business feedback to continuously improve candidate solutions be gained? Method: The proposed model has been created, refined, and evaluated in two large, national Finnish software research programs. For this paper, we conducted thematic interviews with representatives of four companies who participated in these programs. Results: The fundamental change is in the mindset of the participants from technology push by academia to technology pull by companies, resulting in co-creation. Furthermore, continuous cooperation between participants enables solutions to evolve in rapid cycles and forms a scalable model of interaction between research institutes and companies. Conclusions: The multifaceted nature of software engineering research calls for numerous approaches. In particular, when working with human-related topics such as company culture and development methods, many discoveries result from seamless collaboration between companies and research institutes.Peer reviewe

The development of Knowledge Transfer and Technology Transfer with Port Talbot Waterfront Enterprise Zone

Wales has recently seen a concerted attempt by the Government, Academia, and Industry to transform into a knowledge-based economy through increased collaboration across these three sectors. Industry and Academia must share knowledge and technology to assist regional growth. Key to this change has been the emergence of policy-led programmes like Enterprise Zones to catalyse regional growth by focusing support on a specified area. Such efforts to foster innovation in a region have been contested. Can Enterprise Zones benefit from university innovation in Wales? The Port Talbot Waterfront Enterprise Zone is a unique illustration of how Enterprise Zones foster regional progress. This study used a qualitative, Action Research approach to map the South West Wales Port Talbot Waterfront Enterprise Zone's context. This involved identifying key issues that impact Knowledge and Technology Transfer in the region to identify barriers and possibilities. A careful evaluation of the literature and policy contexts revealed initial focus areas of interest to test throughout the investigation. Interviews were conducted in Academia, Industry, and Government to understand people's experiences and identify enablers and barriers to knowledge and technology transfer. The research findings give examples of regional knowledge and technology initiatives and suggested areas for improvement that might help South West Wales and the Port Talbot Waterfront Enterprise Zone promote these activities in the future. This analysis finds that stronger collaboration between Academia and projects like the Port Talbot Waterfront Enterprise Zone would boost South West Wales' knowledge and technology transfer potential. The Port Talbot Waterfront Enterprise Zone gives a chance to foster Industry, Academic, and Government collaborations. This would minimise the 'University Structure' barrier by allowing Academic stakeholders to work with Industry in a neutral setting. This thesis helps Academics and practitioners understand and create innovation in post-industrial regions

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

Exploring ML testing in practice - Lessons learned from an interactive rapid review with Axis Communications

There is a growing interest in industry and academia in machine learning (ML) testing. We believe that industry and academia need to learn together to produce rigorous and relevant knowledge. In this study, we initiate a collaboration between stakeholders from one case company, one research institute, and one university. To establish a common view of the problem domain, we applied an interactive rapid review of the state of the art. Four researchers from Lund University and RISE Research Institutes and four practitioners from Axis Communications reviewed a set of 180 primary studies on ML testing. We developed a taxonomy for the communication around ML testing challenges and results and identified a list of 12 review questions relevant for Axis Communications. The three most important questions (data testing, metrics for assessment, and test generation) were mapped to the literature, and an in-depth analysis of the 35 primary studies matching the most important question (data testing) was made. A final set of the five best matches were analysed and we reflect on the criteria for applicability and relevance for the industry. The taxonomies are helpful for communication but not final. Furthermore, there was no perfect match to the case company’s investigated review question (data testing). However, we extracted relevant approaches from the five studies on a conceptual level to support later context-specific improvements. We found the interactive rapid review approach useful for triggering and aligning communication between the different stakeholders

Enablers and Impediments for Collaborative Research in Software Testing: An Empirical Exploration

When it comes to industrial organizations, current collaboration efforts in software engineering research are very often kept in-house, depriving these organizations off the skills necessary to build independent collaborative research. The current trend, towards empirical software engineering research, requires certain standards to be established which would guide these collaborative efforts in creating a strong partnership that promotes independent, evidence-based, software engineering research. This paper examines key enabling factors for an efficient and effective industry-academia collaboration in the software testing domain. A major finding of the research was that while technology is a strong enabler to better collaboration, it must be complemented with industrial openness to disclose research results and the use of a dedicated tooling platform. We use as an example an automated test generation approach that has been developed in the last two years collaboratively with Bombardier Transportation AB in Sweden

Examining Collegiality and Social Justice in Academia and the Private Sector: an Exploratory SYMLOG Analysis

This research compares the perceptions of the private sector, high-technology employees to the perceptions of university faculty members regarding organizational culture, social justice and collegiality concepts. The SYMLOG assessment technique was used to record the perceptions of respondents to four different concepts of organizational culture, two different aspects of social justice and two measures of collegiality. Comparative findings of gender differences across the eight concepts raise key organizational culture, legal, measurement, governance, and social policy issues for academia and high tech organizations. The development of a conceptual framework to guide future research and a blueprint to discuss desired organizational change are highlighted

Practical Supply Chain Management Knowledge from Industry-Academia Dialogue

Value co-creation, which can be defined as a joint initiative by two or more supply chain members to create value that cannot be created by the sole effort of one member, is a cornerstone concept in Supply Chain Management (SCM). To provide needed clarity about the concept, the invitation-only summit World Class Supply Chain 2017: Value Co-creation , was convened on May 10th, 2017 in Milton, Ontario. The summit brought together accomplished executives, scholars, and students in the SCM field to engage in dialogue directed at uncovering actionable insights about three crucial issues: The business benefits of value co-creation The actions required for successful value co-creation The obstacles to value co-creation and ways to overcome them The deliberations covered an extensive range of content that included concrete real-world examples to reinforce the insights. Those insights can be summarized in the following three major points: Information technology innovations can (a) come from an industry’s established players instead of only from new entrants and (b) significantly improve not only standard operational efficiency metrics in supply chains but also how supply chains parties interact with each other to create value. The suite of key success factors in value co-creation spans three major stages of activities for any organization: (i) preparing for its discussions with potential co-creation partners, (ii) having those discussions with an intent to find common ground on the most important partnership parameters, and (iii) managing the ongoing relationship(s) with selected partners. To be better poised for future success in value co-creation, today’s young, upcoming professionals (e.g., internship and entry-level jobs) must have jobs that are designed with a view to nurturing interpersonal skills in forming and sustaining effective inter-organizational business relationships

Lessons learned in effective community-university-industry collaboration models for smart and connected communities research

In 2017, the Boston University Hariri Institute for Computing and the Initiative on Cities co-hosted two workshops on “Effective Community-University-Industry Collaboration Models for Smart and Connected Communities Research,” with the support of the National Science Foundation (NSF). These efforts brought together over one hundred principal investigators and research directors from universities across the country, as well as city officials, community partners, NSF program managers and other federal agency representatives, MetroLab Network representatives and industry experts. The focus was on transdisciplinary “smart city” projects that bring technical fields such as engineering and computer science together with social scientists and community stakeholders to tackle community-sourced problems. Presentations, panel discussions, working sessions and participant white papers surfaced operational models as well as barriers and levers to enabling effective research partnerships. To capture the perspectives and beliefs of all participants, in addition to the presenters, attendees were asked to synthesize lessons on each panel topic. This white paper summarizes the opportunities and recommendations that emerged from these sessions, and provides guidance to communities and researchers interested in engaging in these types of partnerships as well as universities and funders that endeavor to nurture them. It draws on the collective wisdom of the assembled participants and the authors. While many of the examples noted are drawn from medium and large cities, the lessons may still be applicable to communities of various sizes.National Science Foundatio