The circular bioeconomy represents a societal paradigm shift and transition challenge that inevitably influences how companies act in their evolving operational environment. The disruptive features may be particularly difficult to foresee and tackle strategically in companies with long-term operations and a relatively stable marketplace position, such as firms operating in the forest sector. Here we consider large forest sector companies in a circular bioeconomy sphere and scrutinize opportunities to hasten their sociotechnical transition pathway with a combination of open foresight and open innovation activities. We present a synthesis drawn from contemporary strategic business management literature and adapt that to forest sector multinationals. A greater openness to the actors, knowledge, and expertise outside the forest sector may be an essential element of successful bioeconomy transition for incumbent forest sector firms. This requires leadership to shift culture and an investment in the skills and expertise held by company employees. Increased investment in human capital and embracing a broader network of collaborators may pave the way for forest industry companies towards sophisticated corporate foresight and open innovation, corresponding to Future-Fittest status.

The aims of this study were two-fold: to provide decision aid for a practical bioeconomy research, development and innovation (RDI) and education challenge, and to elaborate hybrid strengths, weaknesses, opportunities, threats (SWOT) methodologies for providing tangible suggestions as to strategic choices to alleviate the challenge. Scientifically, the new methodology developed is the main result of the study, as it can be used for other strategy processes as well, while the case-wise strategic choices may not be generalized. A hybrid method was developed based on the combined use of SWOT that was enlarged by goals and actions, social choice theory and robust portfolio modelling (RPM). The method was applied to deriving joint strategic choices for developing forest bioeconomy education and RDI together by three universities in eastern Finland. A joint brainstorming process was organized in order to choose together the means to develop the co-operation efficiently and in a manner acceptable for all the universities. Voting methods and the core value calculation of RPM were used for prioritizing elements in normal SWOT, goals and actions. The most prioritized elements formed the basis for the co-operation development portfolio. The method development suggestions include, for example, a recommendation to prefer approval voting over cumulative voting in the workshop setting.

The idea in using Multiple Criteria Decision Support (MCDS) and voting methods within a SWOT framework is to evaluate systematically the SWOT factors, and to assess them with respect to their priorities. The MCDS method applied initially, and most often, with SWOT has been the Analytic Hierarchy Process (AHP), and the hybrid AHP-SWOT approach has been called the A'WOT. Any MCDS method can, however, be applied; the choice of the method depending on the strategy process in question. In this article, experiences of using the A'WOT method with AHP, SMART and SMAA-O techniques is summarized. In addition, an illustrative example of making use of social choice theory within SWOT framework is presented. The hybrid MCDS-SWOT approach has gained growing popularity, and it has been applied in different fields world-widely. It may provide not only a solid decision support but also an effective framework for learning in strategic decision support, as well as for communication in strategy processes with multiple stakeholders. The Voting-SWOT approach (VotSWOT) fits especially well with participatory strategy processes, as it reflects decision makers' and stakeholders' natural ways of communication.

Research Highlights: The majority of non-conformities (NCs) occurred under environmental impact (Principle 6) in all regions, and contributed on average to 40% and 48% of the total number of minor and major NCs respectively. Background and Objectives: The performance of certified companies operating has been frequently criticized in Russia. The aim of this study was to analyse the NCs of FSC (Forest Stewardship Council) -certified companies in northwestern (NW) Russia during the period 2011–2015. Materials and Methods: In total, 69 FSC certificates were assessed, representing 112 FSC-certified companies. It should be noted that the number of certificates in this study increased 2.4-fold (from 29 to 69) during the period 2011–2015. At the same time, the number of minor NCs increased only 1.6-fold (from 221 in 2011 to 363 in 2015), while the number of major NCs increased 3.4-fold (from 25 in 2011 to 84 in 2015). Results: During the five-year period, the highest number of NCs was issued in the Arkhangelsk region and in Republic of Karelia, followed by the Vologda region. On the contrary highest number of issued NCs both minor and major per 1000 ha of certified area was in the Novgorod region. The data were also analyzed on leaseholder level and preliminary split into three categories. Conclusions: The number of NCs was, on average, higher for large-sized leaseholders for both the major and minor NCs in comparison to medium- and small-sized leaseholders. However, there were no significant statistical differences observed.

Creating common ground among research groups is a prerequisite for scientifically sound case study research, especially in multi-national and multi-disciplinary research projects. Therefore, this paper proposes a new procedure for case study selection: stochastic cognitive mapping (sCM). sCM complements the previously illustrated conceptual content cognitive mapping (3CM) with email enquiry on concepts and their interconnections, simple multi-attribute rating and stochastic estimation of priorities. The procedure was applied to select case studies in a study on the role of community-based initiatives (CBIs) in societal change towards sustainability. The procedure performed well, based on project members’ evaluations, and enabled them to consistently identify a map and ranked list of criteria for selecting case initiatives. Researchers of the project had two to some extent exclusive orientations towards case selection: sampling and searching strategies, i.e. emphasis on the representativeness of a case set or on the features that interesting and useful study cases should possess. Strategies were integrated and CBIs selected through the sequence of snowball, random, and purposive samplings. Moreover, the method and the criteria list are adaptable to support comparable studies across diverse contexts.