Real-Time Delphi data: How to identify and interpret weak signals of change in the forest bioeconomy

Data from: Mauno, T., Catelo, F., Bengston, D.N., Pykäläinen, J. &amp; Hujala, T. 2023. How to identify and interpret weak signals of change in the forest bioeconomy. Forest Policy and Economics. https://doi.org/10.1016/j.forpol.2023.103075 This exploratory study sought to understand how to identify and interpret weak signals of change that may have an impact on the forest bioeconomy. An international panel of experts in the forest bioeconomy and in foresight provided their views through a two-stage Real-Time Delphi method which utilized the multiple rounds of traditional Delphi and the instantaneous feedback of the Real-Time Delphi method. The Real-Time Delphi exercise was conducted in two stages through the eDelphi software (edelphi.org); the first stage was focused on <em>Changes</em> and the second on <em>Weak Signals</em>. For the Real-Time Delphi exercise, two expert matrices (forest bioeconomy matrix and futures &amp; foresight matrix) were prepared with the aim of obtaining diverse expertise to participate in the study. The first stage was conducted during a 10-day period in early September 2022 (Sep 5, 2022 – Sep 14, 2022). The second stage was also conducted during a 10-day period later in September 2022 (Sep 21, 2022 – Sep 30, 2022). A total of 11 (6 forest bioeconomy experts and 5 futures research and foresight specialists) participated in both eDelphi stages. This dataset includes: (i) completed Real-Time Delphi stages (including anonymized answers and discussions of 11 participants) (ii) questions for both Real-Time Delphi stages, and (iii) anonymized expert matrices (forest bioeconomy matrix and futures &amp; foresight matrix) For more information, please contact the corresponding author (data controller): Tuomas Mauno (University of Eastern Finland), [e-mail]数据来源：Mauno, T.、Catelo, F.、Bengston, D.N.、Pykäläinen, J. 与 Hujala, T.，2023年。《如何识别与解读森林生物经济中的变革弱信号》，《林业政策与经济学》（Forest Policy and Economics）。https://doi.org/10.1016/j.forpol.2023.103075 本探索性研究旨在厘清如何识别并解读可能对森林生物经济产生影响的变革弱信号。研究采用融合传统德尔菲多轮迭代与实时德尔菲即时反馈机制的两阶段实时德尔菲法（Real-Time Delphi），邀请森林生物经济与前瞻研究领域的国际专家分享观点。 本次实时德尔菲调研通过eDelphi软件（edelphi.org）分两阶段开展：第一阶段聚焦**变革（Changes）**，第二阶段聚焦**弱信号（Weak Signals）**。为吸纳多元专业背景的专家参与本研究，本次调研筹备了两类专家矩阵（expert matrices）——森林生物经济矩阵与前瞻与未来研究矩阵。 调研时间安排如下：第一阶段于2022年9月初开展，为期10天（2022年9月5日—2022年9月14日）；第二阶段于2022年9月下旬开展，同样为期10天（2022年9月21日—2022年9月30日）。最终共有11名专家参与了两阶段调研，其中6名来自森林生物经济领域，5名来自未来研究与前瞻研究领域。 本数据集包含以下三部分内容： (i) 完整的两阶段实时德尔菲调研数据（含11名参与者的匿名回复与讨论记录）； (ii) 两阶段实时德尔菲调研所用的全部问卷； (iii) 匿名化的专家矩阵（森林生物经济矩阵与前瞻与未来研究矩阵） 如需获取更多信息，请联系通讯作者（数据负责人）图奥马斯·马乌诺（东芬兰大学），邮箱：[e-mail]