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This paper focuses on the critical role of integrative leadership in inter- and transdisciplinary (ITD) research programs. ITD programs have become one of academia's responses to address contemporary sustainability challenges. Fulfilling the promise of such programs is extraordinarily challenging for all involved participants, but especially for program leaders who have to ensure that the perspectives of the involved program participants become truly integrated and that final and useful synthesis outputs are created. We present six core leadership challenges and respective strategies to address them to advance integration within ITD programs. These challenges include (1) mastering complexity and ambiguity, (2) advancing decision-making with lateral leadership, (3) ensuring responsibility and accountability, (4) setting program boundaries, (5) selecting suitable projects, and (6) dealing with misconceptions. We derived these challenges and respective strategies from both leading and studying in-depth three ITD programs focusing on sustainability issues in Switzerland. With this paper, we intend to promote awareness about the range of leadership challenges in ITD programs and provide actionable knowledge, which can support in particular fellow and future leaders, but also funders and heads of research institutions in their efforts to realize the integrative potential of such programs. Image 1: © Eawag: Lisa Deutsch & Sabine Hoffmann; Stückelberger Cartoons: Christof Stückelberger, CC BY-NC-ND 4.0 [ABSTRACT FROM AUTHOR]

Collaborative research projects are great opportunities for the involved design professionals to learn. Many design professionals join in such collaborations to contribute with their existing professional expertise, but also to further develop and extend that expertise. However, learning by individuals is usually not the main aim, and we lack insight in the learning opportunities through collaboration in such projects. We propose that we need to understand this learning process better in order to make this happen more often and more effectively. This paper presents how four design professionals who each participated in different collaborative research projects look back on their learning processes. We interviewed each participant and drew a process map with them. The results show that these projects offer multifaceted learning opportunities and outcomes of important value for the professionals.The paper shows that their learning a) is not always easily recognised by the professionals themselves, b) benefits from their active engagement as learners, and c) requires supportive conditions in project arrangements. The paper provides guidelines for lead researchers, design professionals, as well as funding agencies to recognise and value this learning, to support explicit reflection and articulation, and to facilitate supportive learning conditions. [ABSTRACT FROM AUTHOR]

Sea-level rise is accelerating globally and will continue for centuries under all shared socio- economic pathways. Although sea-level rise is a global issue, its impacts manifest heterogeneously at the local scale, with some coastal communities and infrastructure considerably more vulnerable than others. Aotearoa New Zealand is poorly prepared to deal with sea-level rise impacts, and some places are already approaching the limits of adaptation, short of relocation. Maladaptive choices threaten Aotearoa's ongoing ability to adapt going forward. Development of climate-resilient pathways requires an immediate adoption of non-partisan, long-term, system-scale approaches to governance and decision making (from local to national), that integrate effective adaptation and emissions mitigation. This also requires proactive and collective action underpinned by indigenous and actionable knowledge (e.g., NZ SeaRise projections) designed for our unique circumstances. There is still time to put in place sustainable, equitable and effective solutions, but funding and governance models need urgent attention. [ABSTRACT FROM AUTHOR]

Purpose: This research paper explores how grassroots innovation initiatives address and resolve the challenges of translating broad and inviting values such as sustainability, inclusiveness and aesthetics into practical and actionable structures. This study examines the tensions and difficulties projects face in operationalizing these values, revealing the gap between idealistic goals and real-world implementation. Moreover, this paper analyzes how role expectations and the concept of invitation ambiguity affect top down and bottom up approaches, offering insights for improving mechanisms to support grassroots innovations. Design/methodology/approach: This study uses an exploratory qualitative methodology with an embedded case study design, focusing on the New European Bauhaus (NEB) and its award-winning projects. Data were collected through online self-assessment surveys, secondary data analysis, and semi-structured interviews with project owners and NEB Unit representatives. Findings: The findings reveal significant challenges in translating broad and inviting values (sustainability, inclusion and aesthetics) into actionable outcomes for grassroots projects. Key issues include the need for clearer role definitions, tailored support, and adaptability. Conflicts between those values and a mismatch between expectations about stakeholders' contributions highlight the need for designing more flexible and robust frameworks and robust frameworks. Originality/value: This research explores the effects of invitational ambiguity within grassroots innovation, revealing how broad values ‐ like sustainability, inclusion and aesthetics ‐ are operationalized in real-world settings. By applying collective action theoretical frameworks to the unique case study of NEB projects, this study provides fresh insights into the dynamics between top-down European policies and bottom-up grassroots practices. [ABSTRACT FROM AUTHOR]

Linking science with action affords a prime opportunity to leverage greater societal impact from research and increase the use of evidence in decision-making. Success in these areas depends critically upon processes of producing and mobilizing knowledge, as well as supporting and making decisions. For decades, scholars have idealized and described these social processes in different ways, resulting in numerous assumptions that now variously guide engagements at the interface of science and society. We systematically catalog these assumptions based on prior research on the science-policy interface, and further distill them into a set of 26 claims. We then elicit expert perspectives (n = 16) about these claims to assess the extent to which they are accurate or merit further examination. Out of this process, we construct a research agenda to motivate future scientific research on actionable knowledge, prioritizing areas that experts identified as critical gaps in understanding of the science-society interface. The resulting agenda focuses on how to define success, support intermediaries, build trust, and evaluate the importance of consensus and its alternatives – all in the diverse contexts of science-society-decision-making interactions. We further raise questions about the centrality of knowledge in these interactions, discussing how a governance lens might be generative of efforts to support more equitable processes and outcomes. We offer these suggestions with hopes of furthering the science of actionable knowledge as a transdisciplinary area of inquiry.

Denne artikkelen utforsker utviklingen av marmorindustrien i Carrara i Italia, fra tradisjonelt håndverk til moderne industri. Ved å analysere historiske og sosiale endringer følger artikkelen marmorens vei fra fjellet til havnen og undersøker arbeidsforholdene og teknologiske innovasjoner som har formet bransjen. Gjennom tidene har marmorarbeiderne organisert seg, men splittelsen mellom anarkister og sosialister har påvirket bransjens lønnsomhet. Studiet dykker inn i organiseringen av arbeidet og identifiserer de ulike spesialiserte rollene. Videre beskrives hvilket inntrykk og lærdom Carraras marmorbrudd ga norske besøkende på 1800-tallet. Artikkelen bringer oss også til mer moderne tider, med et dypdykk i erfaringene til tidligere marmorarbeidere. Den beskriver overgangen fra manuelt arbeid til den omfattende introduksjonen av maskiner på 1950-tallet og senere teknologiske fremskritt. Er handlingsbåren kunnskap fortsatt relevant i dagens teknologiske æra, som har revolusjonert marmorutvinningen? Gjennom denne historien understrekes marmorens rolle som en bærer av kulturell arv og inviterer leserne til å fordype seg i historien til denne unike hjertesteinen i Carrara.

Abstract Amidst the ever-changing and increasingly complex challenges facing the planet and humanity, there is a growing need to educate the next generation of environmental stewards and leaders who are global citizens with sustainability mindsets. Universities have come a long way in developing sustainability programs – both in the curriculum and in terms of campus operations. Many research universities are highly focused on cutting-edge science and technology to address global challenges, and funders are looking for that innovation and entrepreneurialism. These are noteworthy efforts, but do they give students what they need or want? Has the commercialization and corporatization of college campuses led to a shift away from the notion that higher education is a public good that benefits society, not just individuals? Beyond the technical expertise, 21st century challenges demand that the workforce be diverse and capable of recognizing and tackling ethical, cultural, and equity issues for a sustainable and just future. An ethics-driven and interdisciplinarity curriculum framed around the Sustainable Development Goals (SDG), civic engagement, and experiential learning that allows students to put their knowledge into action is needed to prepare individuals for such a workforce. This paper provides both a critique of areas in which higher education is falling short of its responsibilities and some translatable models and opportunities for improvements in reframing sustainability initiatives on campus, including in the curriculum. Policy and Practice Recommendations • Campus leaders and faculty should take note of surveys of younger generations, especially Gen Z and Gen alpha, as they provide valuable insights into what youth are focused on and what knowledge and set of skills they desire to become innovative problem solvers and builders of more resilient communities. • To prepare the next generation of environmental stewards and leaders, high impact practices that move knowledge to action are needed. • Sustainability topics should be incorporated across the curriculum on campuses, not just in certain majors. • Higher education needs to re-embrace the notion of service to the public good and work collaboratively across institutions and sectors to address complex societal challenges.

While market research has been the cornerstone of the intelligence ecosystem, the emergence of 'insights' vendors is re-shaping the market. Adjacent practices, ranging from competitive intelligence, social listening and data science, could relegate market research to legacy status in firms. This investigation explores how expert market researchers respond to the commoditisation of market research techniques and their diminishing access to the client's organisation to address this issue. The findings show that market researchers are adapting – effectively reinventing themselves as 'insights' professionals – through the following four initiatives: (1) offering solution services, (2) creating architectures that integrate organic and designed data, (3) making heroes in the client's organisation and (4) forging performative relationships based on strategic guidance. These initiatives shift market research from ostensive (descriptive or declarative) to performative (effectual or actionable). Theoretically, the article conceptualises the changes in the market research industry through the performativity lens. [ABSTRACT FROM AUTHOR]

To advance actionable knowledge production in the context of water struggles, this article identifies ways to strengthen transformative learning processes within riverine social movements. The complex challenges associated with water struggles point to an increasing need to explore ways in which these processes can be shaped and to promote changes in the worldviews that inform how water and riverine environments are perceived and structured. This study draws on the grassroots movement for the social-ecological regeneration of the Taquara Stream in Porto Alegre, Brazil. Research on this case has shown that the actions conducted by this movement fostered learning processes through the creation of innovative forms of involvement that brought together multiple actors. A panel of experts conducted an in-depth analysis of the learning practices observed in this case. This article discusses five aspects of the learning process, which have been identified by the experts, that are essential to expanding the transformative potential of water-related social movements: (1) building relationships of trust between actors, (2) building links with and between key actors in the process, (3) creating dialogue spaces that promote the co-creation of actionable knowledge, (4) engaging actors spontaneously, proactively, and co-responsibly in the process, and (5) bringing participatory research into local processes. [ABSTRACT FROM AUTHOR]

Amidst the ever-changing and increasingly complex challenges facing the planet and humanity, there is a growing need to educate the next generation of environmental stewards and leaders who are global citizens with sustainability mindsets. Universities have come a long way in developing sustainability programs – both in the curriculum and in terms of campus operations. Many research universities are highly focused on cutting-edge science and technology to address global challenges, and funders are looking for that innovation and entrepreneurialism. These are noteworthy efforts, but do they give students what they need or want? Has the commercialization and corporatization of college campuses led to a shift away from the notion that higher education is a public good that benefits society, not just individuals? Beyond the technical expertise, 21st century challenges demand that the workforce be diverse and capable of recognizing and tackling ethical, cultural, and equity issues for a sustainable and just future. An ethics-driven and interdisciplinarity curriculum framed around the Sustainable Development Goals (SDG), civic engagement, and experiential learning that allows students to put their knowledge into action is needed to prepare individuals for such a workforce. This paper provides both a critique of areas in which higher education is falling short of its responsibilities and some translatable models and opportunities for improvements in reframing sustainability initiatives on campus, including in the curriculum. Policy and Practice Recommendations • Campus leaders and faculty should take note of surveys of younger generations, especially Gen Z and Gen alpha, as they provide valuable insights into what youth are focused on and what knowledge and set of skills they desire to become innovative problem solvers and builders of more resilient communities. • To prepare the next generation of environmental stewards and leaders, high impact practices that move knowledge to action are needed. • Sustainability topics should be incorporated across the curriculum on campuses, not just in certain majors. • Higher education needs to re-embrace the notion of service to the public good and work collaboratively across institutions and sectors to address complex societal challenges. [ABSTRACT FROM AUTHOR]

The purpose of this study is to investigate actionable knowledge in the context of creative projects. A participant inductive investigation that relies primarily on observations and individual interviews was employed. This study identifies two antecedents and three distinct, though complementary, actionable knowledge-related practices of narrowing, broadening, and echoing. These are proposed so as to assist in the development of creative project outcomes and in sustaining an agentic workspace that contributes to collective learning and equalisation of outcomes. The findings of this study enrich the current literature on actionable knowledge in the context of creative projects. [ABSTRACT FROM AUTHOR]

Although the Sustainable Development Goals (SDGs) provide a framework to guide and inform research at the interface between science and policy, engaging in sustainability science is not a value-free process and implies making a number of choices. This is especially pertinent to early career researchers (ECRs) who are faced with the need to engage with the content and frame of the SDGs, while navigating critical engagement in knowledge production. Here, we propose a framework to help early career sustainability scholars navigate these tensions. We describe four archetypes at play in sustainability research and argue that these positions allow ECRs to reflexively navigate their roles and purposes in sustainability research. [ABSTRACT FROM AUTHOR]

Higher education institutions play important roles in the community. Unfortunately, measuring the accomplishment of HEIs in developing communities is challenging. Most HEI contributions to the community are merely a formality and moral obligation. This study's identified gap is the absence of integration of community development activities into HEIs, which would boost their impact on environmental sustainability. This study intends to investigate how institutions that support entrepreneurial-oriented community development affect students' learning and impact society. This study employs an action research approach to develop long-term actionable knowledge. This approach employed a case study from the Rural Community Development Program, a community empowerment program based on institutionalized entrepreneurship practices (formal courses in the curriculum) from ABC University (a pseudonym). The RCDP allows the HEI to interact with society through a dual simultaneous cycle which allow knowledge transfer, social value transfer, and business development with its partners. This model allows more than 100 groups of students at ABC University to be more focused in developing community. On the theoretical side, the RCDP contributes by encouraging the role of social entrepreneurship courses which provides a more significant impact through practice-based lectures while also significantly impacting rural communities' business knowledge in developing their micro enterprises. [ABSTRACT FROM AUTHOR]

Rapidly increasing knowledge on environmental problems and their potential solutions is underused by policy and practice. This mismatch constitutes a knowledge-action gap. To bridge the gap, the concept of actionable knowledge has been proposed, which is often understood as outputs, data, policy briefs, or other types of products. We instead propose to understand actionable knowledge as a process that has (1) cumulative and stepwise, (2) iterative and cyclical, and (3) coevolutionary characteristics. These characteristics are often considered in isolation or even to be in contradiction with each other. We integrate these three characteristics in an analysis of transdisciplinary project developing a catchment-scale land use roadmap and catchment coordination in the Kiiminkijoki river catchment, northern Finland. Our analysis is based on four general phases in a knowledge co-production process (making sense together, knowledge validation, usable outputs, boundary spanning), which are concretized through nine practical steps. We find that collection, analysis, and usage of the knowledge has been even more important for action than the final output (i.e., the roadmap). Furthermore, the process of actionable knowledge does not end with the project but continues with negotiations to establish a catchment coordinator position. Our major finding is that there is no single point in time during a transdisciplinary project to bridge the knowledge–action gap but multiple planned and surprising opportunities emerge during the process. Overall, our approach contributes to advance sustainability transformations in catchment management and governance by understanding how transdisciplinary projects can initiate and are a part of evolving knowledge-action processes. • actionable knowledge can be understood as a process instead of a stable output. • we examine a transdisciplinary process on catchment governance. • actionable knowledge co-production is cumulative, iterative and coevolutionary. • multiple opportunities emerge during co-production to bridge a knowledge-action gap. • our approach can facilitate sustainability transformations in catchment governance. [ABSTRACT FROM AUTHOR]

Drawing on the conceptual framework of intermediations in grassroots innovation for sustainability, this paper presents the first in-depth analysis of the role of third sector organizations in citizen science. The empirical data are derived from 31 case studies of associations (representing 80% of third sector organizations in France). We identify two clusters of associations (social innovation and natural sciences) based on research domain. They differ in epistemic cultures, but they both value experiential and actionable knowledge. We present an analytical framework to characterize the role of these associations in citizen science. Derived from systemic intermediations for transitions, this framework is based on the association’s position in networks, infrastructures, and projects. Our results reveal four categories, three of which are intermediations that depend on the organization’s position in the network, the degree of structuration of its partnerships with academics, and the goals and achievements of the projects in which it is involved. Associations do not only articulate different knowledge in projects, they also contribute to organizational learning in networks. In addition, associations perform the boundary work required to build hybrid infrastructures with institutions. A fourth category unveils the complexity of structuring hybrid epistemic communities for sustainability. This four-way categorization of intermediations highlights the crucial roles of associations in a systemic approach to citizen science.

Collective action is needed to conceive and implement sustainability transitions within our society. Yet, it requires the coordination of a diversity of actors, each possessing their own reasoning. Integrating diversity, characterized by variety, disparity and balance, is thus a crucial methodological challenge to address, notably in order to enhance the quality of policy decisions concerning sustainability issues. Here we show how to tailor the way of collecting, analyzing and using actor reasoning diversity to the management style of collective action, characterized by the role the actors are allowed to play in defining collective action. To this purpose, we compare three design experiments using actor reasoning in the context of collective action aiming at developing sustainable food production: (1) considering actor reasoning in top-down decision-making (scallop fishery in Integrated Coastal Zone Management); (2) building consensus for a common strategy (quality in a sheep milk cooperative); and (3) fostering collective intelligence for individual and collective paths for action (agroecological transition of an agricultural territory). The diversity of actor reasoning in each of the design experiments was collected through cognitive mapping, a systemic representation tool adapted to represent actor reasoning. We propose a framework to adapt cognitive mapping methods to different management styles of collective action. In practice, adjusting the level and nature of the reasoning diversity considered at each step of a participatory process, through the way cognitive maps are collected and analyzed, is key to the tailoring of a cognitive mapping method to a management style of collective action. Overall, we show that the level of reasoning diversity considered in collective action should increase with actor involvement in analyses and decision-making. [ABSTRACT FROM AUTHOR]

The current literature on climate services for farmers predominantly focuses on seasonal forecasts, with an assumption that longer-term climate projections may not be suitable for informing farming decisions. In this paper, we explore whether certain types of long-term climate projections may be useful for some specific types of farming decisions. Through interviews with almond tree crop farmers and farm advisors in California, we examine how farmers perceive the utility and accuracy levels of long-term climate projections and identify the types of projections that they may find useful. The interviews revealed that farmers often perceive long-term climate projections as an extension of weather forecasts, which can lead to their initial skepticism of the utility of such information. However, we also found that when farmers were presented with long-term trends or shifts in crop-specific agroclimatic metrics (such as chill hours or summer heat), they immediately perceived these as valuable for their decision-making. Hence, the manner in which long-term projections are framed, presented, and discussed with farmers can heavily influence their perception of the potential utility of such projections. The iterative conversations as part of the exploratory interview questions, served as a tool for “joint construction of meaning” of complex and ambiguous terms such as “long-term climate projections,” “long-term decisions” and “uncertainty.” This in-turn supported a joint identification (and understanding) of the types of information that can potentially be useful for on-farm adaptive decisions, where the farmer and the interviewer both improvise and iterate to find the best types of projections that fit specific decision-contexts. Overall, this research identifies both the types of long-term climate information that farmers may consider useful, and the engagement processes that are able to effectively elicit farmers' long-term information needs.

The search for partners in open innovation settings often consumes substantial time and managerial attention. Yet, organizations tend to get trapped in local search, which typically leads to collaboration with partners already known to them. To improve the search for partners, this article develops a tool that exploits the power of state-of-the-art information technology. In a sample of 33 search queries conducted in six innovation intermediaries, it studies differences between search with and without the use of our tool. The tests confirm the tool’s effectiveness and efficiency, and highlight the importance of searching with keywords that represent the core roles and activities of a firm, next to keywords referring to market and technology characteristics. Network visualization and semantic algorithms thus appear to facilitate the effort to identify distant partners. The article also finds that local partners are not that easy to find as commonly assumed. [ABSTRACT FROM AUTHOR]

Green process innovation is itself a complex process and beneficially involves inter‐organizational collaboration across disciplinary, industry and university‐industry boundaries with many opportunities for network action learning. We investigate how green process innovation yields actionable knowledge when co‐directed, co‐developed and co‐deployed in a network of organizations. We undertook two case studies focused on innovation at the water‐energy nexus. With the use of action learning research, we describe and reflect on the actions undertaken by the network to co‐generate learning from green process innovation. We demonstrate how this inter‐organizational learning is grounded in shared experiences, subjected to critical questioning and supported by (and generating) actionable knowledge. Our paper links the green process innovation process with technical and collaborative learning outcomes, achieved through network action learning. Of managerial relevance are two forms of actionable knowledge: that towards solving engineering puzzles and that addressing the problem of collaboration and learning in networks. [ABSTRACT FROM AUTHOR]

Since March 2020, the COVID-19 pandemic propelled the “stay-at-home” policy worldwide under public health uncertainty, resulting in increased individualization, as well as an increased reliance or dependency on digital communication technology. Based on a review of existing literature alongside a reflection on personal fieldwork experiences, we aim to: (1) describe major elements of agroecological pedagogy, (2) explore adaptation pathways to combine digitalization and participatory action-learning, and (3) briefly discuss opportunities and challenges for agroecologists beyond COVID-19. Agroecological pedagogy is deeply embedded in the praxis, the scientific knowledge and ways of knowing (academic or not), and in the politics and agency of food movements. In line with Freire's liberation pedagogy, seeing what already exists (e.g., in: ecosystems, home-gardens, fields, farms, and watersheds) through participation and volunteering. Alongside a critical analysis to explain and explore certain phenomena, causes and consequences will likely result in the act leading to the implementation of transformative practices and novel designs that improve the state of any situation being addressed. Participatory action research/learning methods are strategic in agroecological pedagogy. Overall, the lockdown period led to increased societal digitalization of human interactions. During lockdown, however, the implementation of strategies for remote agroecology participatory action-learning were hampered, but not vanquished. Key changes to agroecology education projects “before” and “during” lockdown include an increased reliance on digital and remote strategies. Creative adaptations in the virtual classrooms were designed to nurture, deepen, and foster alternatives in favor of diverse knowledges and ways of knowing for food system transformations.

In this paper, we use conceptual insights from the actor–network theory (ANT) to explore the role of agroecological innovation systems (AeISs) in the reconfiguration of agricultural practices toward sustainability. AeISs are actor networks involving a diversity of individuals (e.g., farmers, traders, experts) and organizations (e.g., cooperatives, rural development agencies, teaching and research institutions) that mainstream agroecology principles and practices to enhance agroecosystems' resilience. Their composition and structure affect the way different agents of change interact, as well as how they access, exchange, and use knowledge as they drive the adoption of specific technologies. We document seven AeISs that were active between 2005 and 2020 in the northern uplands of Laos. Within the framework of these initiatives, action research was conducted for understanding the processes underpinning diverse technical, organizational, and institutional innovations to foster an agroecological transition. Building on a comparative analysis of AeIS, we consider how agency was distributed among collectives as they reorganized in time. Our discussion highlights the importance of configuring, enlarging, and nurturing spaces in which actors are empowered to adjust and adapt, as well as to think and act collectively in complexity. Lastly, what counts in the innovation is the underlying networking process itself, i.e., the process through which all actors of the AeIS interact and exchange. Changes in the networking processes come with a changing conception of knowledge. Moving from knowledge to knowing (i.e., knowledge in the making), AeISs no longer only promote products or technologies, but also collective intelligence based on an ethic of care. [ABSTRACT FROM AUTHOR]

Maintaining or restoring landscape multifunctionality is essential to ensuring that landscapes provide a broad array of services. Increased multifunctionality means that there are more diverse land uses bordering each other. The areas in which land uses interact are transition zones; those between grasslands and forests could fulfill multiple purposes due to their special ecological characteristics that support the needs of diverse species. However, with their management practices, local land users often shape the characteristics of land-use transition zones, with implications for ecological processes that build the base for service provision. Local ecological knowledge of land users could give important insights into the basis of their decisions. Here, we explore how land users' and farmers' local knowledge shapes their management that contributes to the maintenance and restoration of multifunctional landscapes. We conducted 21 semistructured qualitative interviews with livestock farmers and local experts for agriculture and nature conservation using grassland-forest transition zones as a specific example for interdependent components of multifunctional landscapes. We found that local knowledge of the interviewed farmers can contribute to the maintenance or restoration of multifunctional landscapes in several ways: it provides insight into landscape functions in grassland-forest transition zones, it enables land users to use landscape function-grassland production synergies, and it provides insight into the perceived negative and positive contributions of forests to grassland production. The perceived negative contributions of forests to grassland production were an important driver for farmers' management decisions. Farmers have a holistic view of both the field and the landscape. Managing landscapes for multifunctionality is dependent on this kind of holistic knowledge to identify synergies and trade-offs in landscape functions and how they contribute to agricultural production. However, current regulations such as the institutional separation of grassland and forest and grassland areadependent direct payments prevent farmers from acting according to their local knowledge. [ABSTRACT FROM AUTHOR]

Extended abstract Abstract Despite advances in the capabilities of data mining algorithms, the knowledge extracted by these algorithms require a great deal of refinement to become actionable for business executives. The main objective of this research is to identify common business problems of customer support domain that can be solved with the help of data mining techniques and to formulate an ontology of business understanding. Hence, customer support business problems are first identified through interviews with the domain experts, and then, with the review of related literature, the ontology of customer support problems is developed. As results of the research, the business objectives of the customer support domain that lead to value creation and profitability are identified along with key activities and outputs of each activity and the analytical steps required based on data mining techniques to achieve each business objective. Finally, based on CRISP-DM data mining model, the ontology of business understanding is introduced. Introduction Customer support is the establishment of a set of processes and systems aimed at achieving customer satisfaction and loyalty and ultimately creating a profitable and lasting business relationship. Customer-related data and information technology tools are the foundation of a successful customer support strategy. Today, the rapid growth of information technologies and the Internet have opened up new opportunities to create profitable and successful customer relationship through data mining. Business decision makers expect the output of the data mining process to be easily interpreted and applied. Therefore, data mining techniques should provide actionable knowledge to these people. The lack of focus on business understanding in formulating the data mining problem and the lack of knowledge of the business domain is the root of this problem (Cao, 2017. Li, 2014). So far, data mining has been seen as a data-driven process that has little focus on the context and knowledge of the business domain. The main purpose of this article is to model key customer support business problems, goals, and activities that can be solved by data mining techniques. In this regard, ontology is used as a tool for structuring and displaying knowledge of customer support. The ontology is a detailed and transparent explanation of a common conceptualization (Gruber, 1993). Cao argues that if the ontology integration between the framework and the methodology of data mining and organization/business can be established, the actionability of data mining output can be assured. Methods This study presents a model and method that facilitates business understanding of customer support for data mining problem and actioable knowledge discovery. To this end, first by interviewing software support experts in the software industry, the key concepts that are essentially business problems addressed by data mining algorithms are identified and presented in the form of basic artifacts. In the next step, related literature has been reviewed to generalize the basic artifact to the field of consumer support domain. The final artifact has been reconciled with the help of experts. Accordingly, the interview questions were formulated by experts. 1-What are the key activities in the area of ​​customer support? 2- What are the main goals in customer support? 3-What kind of data is stored in customer support? The purpose of the above questions is to identify the leading business goals in the area of ​​customer support first. Then, to reach each goal, data analysis steps must be made on specific data, and finally the outputs of the steps identified. The following five queries were searched through Google Scholar for literature review. The reason for choosing Google Scholar is to index all the databases in the world by the search engine's search algorithm. The last ten years date range, between 2009 and 2019, was considered as the search time limit. - Customer relationship + Literature review - Customer support + Literature review - Customer service + Literature review - Customer experience + Literature review - Customer journey + Literature review The reason for the literature search query in the search query is that identifying relevant concepts in the domain of customer support and building the ontology of understanding customer support business as the research goal is pursued. Discussion and Results Customer support business objectives were identified. Each goal has analytical steps that must be applied to specific customer support data. For example, two analytical steps have been identified for the purpose of optimizing revenue from existing customers, including finding the relationship between features and needs and matching the service portfolio to customer needs. These analytical steps are meant to classify customers based on similar features and assign customers to the product based on similar features. For this purpose, background data and client transaction databases should be used. The formulated artifact of the research acts like this. Conclusion Most efforts to improve the data mining process have so far focused on improving data mining modeling, processes, and algorithms. There is a profound semantic gap between what a knowledge engineer deduces from data mining algorithms and what a business user pursues for profitability and business metrics. There are two major limitations to an approach that overcomes knowledge engineering: first, business requirements are not considered correctly, and second, the business user does not have the technical and statistical knowledge needed to perform the data mining process himself. Current ontologies of data mining are generally focused on the modeling and technical evaluation of data mining outputs. There is no evidence of a business-centric system modeling and architecture review among data mining ontologies. The artifact of this research has not only provided understanding of customer support business problems to begin the data mining process but also provided the basis for producing architectures for recording and sharing the extracted knowledge and production of a learning system. Future research should focus on the prototype production of a learning system that also characterizes the data mining process modeling step associated with any problem identified in the research artifact. In other words, data mining ontologies first need to be scrutinized, and then the mapping or integration between data mining ontologies and ontology business support ontologies defined in which the user identifies the problem and other stages of the data mining process can be proposed.

In recent years, healthcare spending has risen and become a burden on many governments. There are multiple reasons for this increase such as overtesting, long medical treatment path, ignoring doctors' orders, ineffective use of technologies, medical errors, many hospital readmissions, unnecessary emergency room (ER) visits, and medical treatment acquired side effects and infections. The first part of this editorial presents Healthcare Cost and Utilization Project (HCUP) datasets and their hierarchical partition used to build hierarchically structured personalized recommendation systems in healthcare domain. The second part outlines a simple strategy for reducing the number of readmissions using the concept of action rules to provide recommendations. First, we extract from HCUP datasets all possible procedure paths (course of treatments) for a given initial medical procedure. Then, we cluster patients according to the similarities in their diagnoses in order to increase the predictability of the course of treatment following this initial procedure. Finally, we present a novel algorithm that provides recommendations (actionable knowledge) to the physicians to put patients on a treatment path that would result in optimal reduction of the number of readmissions for these patients. There is not much research done on decreasing the number of readmissions to hospitals after initial procedure and almost none based on action rules. [ABSTRACT FROM AUTHOR]

The act of theorising turns the attention from the outcome of theory generation to the act of theory generation itself. Revans' systems alpha, beta and gamma provide a foundational action theory that grounds the theorising process in action learning. This is the core of theorising in the praxeology of action learning as creating practical theory or actionable knowledge that makes Accounts of Practice more than merely interesting stories. This article explores how the process of writing an Account of Practice can also be seen as a process of theorising, articulating the kind of knowledge created from what is learned in and through action. [ABSTRACT FROM AUTHOR]

This symposium contains eight articles that address several methodological issues. The central theme is why authentic methodological diversity is important and how it can be achieved. This essay offers an overview of how methodology choice should be treated in regards to better theorizing, complex realities, and practical impact. It calls for more attention to qualitative inquires in the hope of methodological diversity with many strong arms. [ABSTRACT FROM AUTHOR]

The success of data mining learned rules highly depends on its actionability: how useful it is to perform suitable actions in any real business environment. To improve rule actionability, different researchers have initially presented various Data Mining (DM) frameworks by focusing on different factors only from the business domain dataset. Afterward, different Domain-Driven Data Mining (D3M) frameworks were introduced by focusing on domain knowledge factors from the context of the overall business environment. Despite considering these several dataset factors and domain knowledge factors in different phases of their frameworks, the learned rules still lacked actionability. The objective of our research is to improve the learned rules’ actionability. For this purpose, we have analyzed: (1) what overall actions or tasks are being performed in the overall business process, (2) in which sequence different tasks are being performed, (3) under what certain conditions these tasks are being performed, (4) by whom the tasks are being performed (5) what data is provided and produced in performing these tasks. We observed that the inclusion of rule learning factors only from dataset or from domain knowledge is not sufficient. Our Process-based Domain-Driven Data Mining-Actionable Knowledge Discovery (PD3M-AKD) framework explains its different phases to consider and include additional factors from five perspectives of the business process. This PD3M-AKD framework is also in line with the existing phases of current DM and D3M frameworks for considering and including dataset and domain knowledge accordingly. Finally, we evaluated and validated our case study results from different real-life scenarios from education, engineering, and business process domains at the end.

This article describes a dataset of different services acquired by users during the period in which they are active in a sports facility as well as their behavior in terms of frequency of the sport facility itself and the type of classes they prefer to attend. Each observation in the dataset corresponds to one user, including the features of subscriptions and frequency.Data were collected between June 1st 2014 and October 31st 2019 from a database of an ERP solution operating in a sports facility in Lisbon, Portugal. From this database, it was possible to perform operations of extraction, transformation and loading into the dataset.The dataset with real data can be useful for research in areas such as customer retention, machine learning, marketing, actionable knowledge and others.Although we present real data from users of a sports facility, in order to comply the GDPR legislation, the attributes that could identify the users were removed making the data anonymized.

Classification is one of the tasks that are most frequently carried out in real world applications. A large number of techniques have been developed based on statistics and machine learning methods. These classification techniques usually suffer from various limitations, and there is no single technique that works best for all classification problems. Two major drawbacks in existing techniques are accuracy and lack of actionable knowledge from results. To overcome these problems, a novel algorithm called Multi-Branch Ferns (MBFerns), and R-package has been developed to build multi-branch ferns (multi-branch decision tree) and to generate key features from training dataset employing Naïve Bayesian probabilistic model as classifier. The proposed algorithm performs well for general classification problems and extracting actionable knowledge from training data. The proposed method has been evaluated with best existing classification methods namely, Random Forest (RF), Support Vector Machine (SVM) and Artificial Neural Network (ANN) on medical benchmark data, available at https://archive.ics.uci.edu/ml/datasets/ such as Breast Cancer, Cryotherapy, Cardiotocography, Dermatology, Echocardiogram, EEG Eye State, Fertility, Haberman's Survival, Hepatitis, Indian Liver Patient, Mammographic Mass, Parkinsons, etc. Detailed investigation on proposed Multi-Branch Ferns (MBFerns) with respect to accuracy, time, space complexity and knowledge discovery has also been presented. [ABSTRACT FROM AUTHOR]

Vocational education and training for sustainable development aims to promote the readiness and competencies for sustainability-oriented professional action. A prerequisite for this is actionable knowledge. Against this background, the article highlights the potential of concept maps for knowledge acquisition and structuring and, in this context, the results of the additional qualification for sustainable management in the food trade “mach.werk”. [ABSTRACT FROM AUTHOR]

Drought risks pose serious threats to socio-ecological systems, built environments, livelihoods and human wellbeing. Managing these risks requires long-term collaboration between diverse groups with different values, interests and forms of knowledge. Funders, researchers and practitioners have increasingly advocated for collaborative models of knowledge production in which all participants recognise the multiple ways of understanding drought risk and strive to co-create knowledge for decision making. Such transdisciplinary research approaches aim to develop and sustain more equitable and meaningful interactions between scientific and societal actors, and have been shown to increase knowledge use and build resilience to climate variability. In practice, however, collaborations around drought remain largely science-driven and, as a result, can struggle to produce actionable knowledge necessary to better manage drought risk. This article draws from drought studies and related transdisciplinary fields to highlight common barriers inhibiting actionable knowledge production across a broad range of drought risk management contexts. We also propose opportunities for improved knowledge production that can guide researchers, practitioners and funders seeking to engage in transdisciplinary work. Diverse understandings of drought risk have hindered widespread advances in knowledge production and resilience building. We argue for multi-disciplinary researchers to come together with stakeholders and focus on creating inclusive and context-driven environments. While not appropriate or cost-effective in all situations, co-production between researchers, practitioners and other stakeholder groups offers opportunities for actionable management plans and policies that reflect the complex and contested problem framings and socio-ecological contexts in which droughts impact society.

Abstract 1. Despite aspirations for conservation impact, mismatches between research and implementation have limited progress towards this goal. There is, therefore, an urgent need to identify how we can more effectively navigate the spaces between research and practice. 2. In 2014, we ran a workshop with conservation researchers and practitioners to identify mismatches between research and implementation that needed to be overcome to deliver evidence‐informed conservation action. Five mismatches were highlighted: spatial, temporal, priority, communication, and institutional. 3. Since 2014, thinking around the ‘research–implementation gap’ has progressed. The term ‘gap’ has been replaced by language around the dynamic ‘spaces’ between research and action, representing a shift in thinking around what it takes to better align research and practice. 4. In 2019, we ran a follow‐up workshop reflecting on this shift, whether the five mismatches identified in the 2014 workshop were still present in conservation, and whether progress had been made to overcome these mismatches during the past 5 years. We found that while there has been progress, we still have some way to go across all dimensions. 5. Here, we report on the outcomes of the 2019 workshop, reflect on what has changed over the past 5 years, and offer 10 recommendations for strengthening the alignment of conservation research and practice.

Actionable Knowledge Discovery approaches to extract the business and technical significant actions/patterns to support direct decision making. These actions suggest how to transform an object from an undesirable status to a desirable status by incurring less cost and high profit. This article aims to propose a work that generates actionable patterns efficiently. It reduces the search space and number of iterations for attribute value change during action generation. Performance of the proposed method is compared with Yang's method and OF-CEAMA on the basis of four parameters i.e. the total number of rules required for action generation, run time of the methods, the total number of generated actions, total net profit and time and space complexity. Experiments have been carried out on four datasets retrieved from UCI Machine learning repository. Experimental results show that the proposed work takes less time than the other two methods to extract actions for all datasets. Also, the number of rules required to generate actions are less than the other two methods. Results also suggest that a decrease in execution time does not compromise the information and proposed work generates the same actions and net profit. Moreover, the proposed work tries to transfer an object from undesired status to the desired status.