seven military classics (Jiang Ziya, the methods of the Sima, Sun Tzu, Wu Qi, Wei Liaozi, the three strategies of Huang Shigong and the Questions and Replies between Tang Taizong and Li Weigong). The entities studied then were nation states. Later, corporations often became just as powerful as states and their leaders demanded similar strategic thinking. Many of the ideas came initially from geopolitics as developed in the 19th century, and later with the spread of multinational companies at the end of the 20th century, with geoeconomics. What is unique for intelligence studies is the focus on information— not primarily geography or natural resources— as a source for competitive advantage. Ideas of strategy and information developed into social intelligence with Stevan Dedijer in the 1960s and became the title of a course he gave at the University of Lund in the 1970s. In the US this direction came to be known as business intelligence. At a fast pace we then saw the introduction of corporate intelligence, strategic intelligence and competitive intelligence. Inspired by the writings of Mikael Porter on strategy, as related to the notion of competitive advantage the field of competitive intelligence, a considerable body of articles and books were written in the 1980s and 1990s. This was primarily in the US, but interest spread to Europe and other parts of the world, much due to the advocacy of the Society of Competitive Intelligence Professionals (SCIP). In France there was a parallel development with “intelligence economique”, “Veille” and “Guerre economique”, in Germany with “Wettbewerbserkundung” and in Sweden with “omvarldsanalys,” just to give some examples. On the technological side, things were changing even faster, not only with computers but also software. Oracle corporation landed a big contract with the CIA and showed how data analysis could be done efficiently. From then on, the software side of the development gained most of the interest from companies. Business intelligence was sometimes treated as enterprise resource planning (ERP), customer relations management (CRM) and supply chain management (SCM). Competitive intelligence was associated primarily with the management side of things as we entered the new millennium. Market intelligence became a more popular term during the first decade, knowledge management developed into its own field, financial intelligence became a specialty linked to the detection of fraud and crime primarily in banks, and during the last decade we have seen a renewed interest for planning, in the form of future studies, or futurology and foresight, but also environmental scanning. With the development of Big Data, data mining and artificial intelligence there is now a strong interest in collective intelligence, which is about how to make better decisions together. Collective intelligence and foresight were the main topics of the ICI 2020 conference. All articles published in this issue are from presentations at that conference. The common denominator for the theoretical development described above is the Information Age, which is about one’s ability to analyze large amounts of data with the help of computers. What is driving the development is first of all technical innovations in computer science (both hardware and software), while the management side is more concerned with questions about implementation and use. Management disciplines that did not follow up on new technical developments but defined themselves separately or independently from these transformations have become irrelevant. Survival as a discipline is all about being relevant. It’s the journey of all theory, and of all sciences to go from “funeral to funeral” to borrow an often-used phrase: ideas are developed and tested against reality. Adjustments are made and new ideas developed based on the critic. It’s the way we create knowledge and achieve progress. It’s never a straight line but can be seen as a large number of trials and solutions to problems that change in shape, a process that never promises to be done, but is ever-changing, Journal of Intelligence Studies in Business Vol. 10, No 2 (2020) p. 4-5 Open Access: Freely available at: https://ojs.hh.se/ 5 much like the human evolution we are a part of. This is also the development of the discipline of intelligence studies and on a more basic level of market research, which is about how to gather information and data, to gain a competitive advantage. Today intelligence studies and technology live in a true symbiosis, just like the disciplines of marketing and digital marketing. This means that it is no longer meaningful to study management practices alone while ignoring developments in hardware and software. The competitive intelligence (CI) field is one such discipline to the extent that we can say that CI now is a chapter in the history of management thought, dated to around 1980-2010, equivalent to a generation. It is not so that it will disappear, but more likely phased out. Some of the methods developed under its direction will continue to be used in other discipline. Most of the ideas labeled as CI were never exclusive to CI in the first place, but borrowed from other disciplines. They were also copied in other disciplines, which is common practice in all management disciplines. Looking at everything that has been done under the CI label the legacy of CI is considerable. New directions will appear that better fit current business practices. Many of these will seem similar in content to previous contributions, but there will also be elements that are new. To be sure new suggestions are not mere buzzwords we have to ask critical questions like: how is this discipline defined and how is it different from existing disciplines? It is the meaning that should interest us, not the labels we put on them. Unlike consultants, academics and researchers have a real obligation to bring clarity and order in the myriad ideas. The articles in this issue are no exception. They are on collective intelligence, decision making, Big Data, knowledge management and above all about the software used to facilitate these processes. The first article by Teubert is entitled “Thinking methods as a lever to develop collective intelligence”. It presents a methodology and framework for the use of thinking methods as a lever to develop collective intelligence. The article by Calof and Sewdass is entitled “On the relationship between competitive intelligence and innovation”. The authors found that of the 95 competitive intelligence measures used in the study 59% were significantly correlated with the study’s measure of innovation. The third article is entitled “Atman: Intelligent information gap detection for learning organizations: First steps toward computational collective intelligence for decision making” and is written by Grezes, Bonazzi, and Cimmino. The research project shows how companies can constantly adapt to their environment, how they can integrate a learning process in relation to what is happening and become a "learning company". The next article by Calof and Viviers entitled “Big data analytics and international market selection: An exploratory study” develops a multi-phase, big-data analytics model for how companies can perform international market selection. The last article by Vegas Fernandez entitled “Intelligent information extraction from scholarly document databases” presents a method that takes advantage of free desktop tools that are commonplace to perform systematic literature review, to retrieve, filter, and organize results, and to extract information to transform it into knowledge. The conceptual basis is a semantics-oriented concept definition and a relative importance index to measure concept relevance in the literature studied. As always, we would above all like to thank the authors for their contributions to this issue of JISIB. Thanks to Dr. Allison Perrigo for reviewing English grammar and helping with layout design for all articles. Have a safe summer! On behalf of the Editorial Board,

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今天，竞争情报的僵局并不是失败。在ICI 2020大会上发表论文特刊

七种军事经典（江子雅，司马，孙子，吴起，魏辽子，黄世恭的三种策略以及唐太宗与李维公的问答）。当时研究的实体是民族国家。后来，公司常常变得和各州一样强大，而他们的领导人也要求类似的战略思维。许多想法最初起源于19世纪发展的地缘政治，后来随着20世纪末跨国公司的发展以及地缘经济学的出现而产生。情报研究的独特之处在于将重点放在信息（而不是地理或自然资源）上作为竞争优势的来源。战略和信息观念在1960年代与Stevan Dedijer一起发展为社会智能，并成为1970年代他在隆德大学开设的一门课程的标题。在美国，这个方向被称为商业智能。然后我们很快就看到了公司情报，战略情报和竞争情报的引入。受与竞争优势概念有关的竞争情报领域的米卡尔·波特（Mikael Porter）关于战略的著作的启发，在1980年代和1990年代撰写了大量文章和书籍。这主要是在美国，但是由于竞争情报专业人员协会（SCIP）的提倡，兴趣已传播到欧洲和世界其他地区。在法国，“智能经济”与之并行发展，“ Veille”和“ Guerre economique”，在德国的“ Wettbewerbserkundung”和在瑞典的“ omvarldsanalys”，仅举一些例子。在技​​术方面，不仅计算机而且软件的变化速度都在加快。甲骨文公司与中央情报局签订了一项大合同，并展示了如何有效地进行数据分析。从那时起，开发的软件方面吸引了公司的大部分兴趣。商业智能有时被视为企业资源计划（ERP），客户关系管理（CRM）和供应链管理（SCM）。进入新千年以来，竞争情报主要与事物的管理方面有关。在最初的十年中，市场情报成为一个比较流行的名词，知识管理发展到了自己的领域，金融情报已成为主要与银行欺诈和犯罪侦查相关的专业，并且在过去十年中，我们对规划有了新的兴趣，其形式包括未来研究，未来学和远见卓识以及环境扫描。随着大数据，数据挖掘和人工智能的发展，现在人们对集体智能产生了浓厚的兴趣，这是关于如何共同做出更好的决策。集体智慧和远见是ICI 2020会议的主题。本期发表的所有文章均来自该会议的演讲。上述理论发展的共同点是信息时代，它是一个人借助计算机来分析大量数据的能力。推动发展的首先是计算机科学（包括硬件和软件）方面的所有技术创新，而管理方面则更关注有关实现和使用的问题。没有跟进新技术发展但与这些转变分开或独立定义的管理学科变得无关紧要。生存作为一门学科是与之相关的。这是所有理论和所有科学从“丧葬到葬礼”，借用一个经常使用的短语的旅程：思想是针对现实而发展和检验的。根据评论家进行调整并提出新的想法。这是我们创造知识并取得进步的方式。它从来不是一条直线，但是可以看作是对形状变化的问题的大量试验和解决方案，一个从未承诺要完成但不断变化的过程，《商业情报研究》。10，No 2（2020）p。4-5开放获取：可从以下网址免费获得：https：//ojs.hh.se/ 5就像人类进化的一部分一样。这也是情报研究学科和更基本的市场研究水平的发展，这与如何收集信息和数据以获得竞争优势有关。如今，情报学和技术就像营销和数字营销学科一样，处于真正的共生关系中。这意味着仅研究管理实践而忽略硬件和软件的发展就不再有意义。竞争情报（CI）领域就是其中一门学科，以至于我们可以说CI现在是管理思想史上的一章，大约发生在1980-2010年，相当于一代人。并不是它会消失，而是更有可能被淘汰。在其指导下开发的某些方法将继续在其他学科中使用。最初，大多数被标记为CI的想法从来都不是CI独有的，而是从其他学科借来的。它们也被复制到其他学科中，这是所有管理学科的惯例。纵观以CI标签进行的所有操作，CI的遗产都是可观的。将会出现更适合当前业务实践的新方向。其中许多内容在内容上似乎与以前的贡献相似，但也有一些新内容。为确保新建议不仅仅是流行语，我们必须提出一些关键问题，例如：该学科如何定义？与现有学科有何不同？这应该使我们感兴趣，而不是我们贴在标签上的标签。与顾问不同，学者和研究人员有真正的义务要使无数个想法清晰明了。本期文章也不例外。他们涉及集体情报，决策，大数据，知识管理以及最重要的是用于促进这些流程的软件。泰伯特（Teubert）的第一篇文章的标题是“思考方法作为发展集体智慧的杠杆”。它提供了使用思维方法作为发展集体智慧的手段的方法论和框架。Calof和Sewdass的文章标题为“关于竞争情报与创新之间的关系”。作者发现，在研究中使用的95种竞争情报措施中，有59％与研究的创新措施显着相关。第三篇文章由Grezes，Bonazzi和Cimmino撰写，标题为“ Atman：学习型组织的智能信息缺口检测：迈向决策的计算集体智能的第一步”。该研究项目展示了公司如何才能不断适应环境，如何将学习过程与正在发生的事情结合起来并成为“学习型公司”。Calof和Viviers撰写的下一篇名为“大数据分析和国际市场选择：探索性研究”的文章为公司如何进行国际市场选择开发了一个多阶段的大数据分析模型。维加斯·费尔南德斯（Vegas Fernandez）的最后一篇题为“从学术文献数据库中进行智能信息提取”的文章提出了一种方法，该方法利用免费的桌面工具来进行系统的文献综述，检索，过滤和组织结果以及提取信息以进行转换它变成知识。概念基础是面向语义的概念定义，是衡量所研究文献中概念相关性的相对重要性指标。与往常一样，我们首先要感谢作者为这一期JISIB所做的贡献。感谢Allison Perrigo博士复习了英语语法并为所有文章提供了版式设计帮助。祝您夏天安全！代表编辑委员会，