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Extensive research exists on the potential impacts of foresight; however, a comprehensive understanding of the factors that lead to foresight impact, particularly in influencing senior management decisions, is relatively sparse. This study addresses this by reporting on a Delphi and expert panel involving eight senior Canadian government foresight program leaders. These leaders were asked to help identify and then rate a list of factors that they felt resulted in their foresight projects impacting senior management decisions. Results suggested that factors such as foresight methodology, while leading to good foresight, do not necessarily result in senior decision-maker impact. Instead, criteria defined in this paper as the "consultants' toolkit," such as understanding the senior decision maker's pain points and foresight managers having a strong understanding of the organization's inner workings, play a crucial role. The expert panel discussion suggested that the importance of senior management decision-making factors depends on three mediating variables: The temporal orientation of the Department, the foresight orientation of the department's senior management, and the nature of the relationship between the foresight manager and the senior decision maker. • Paper identifies factors that lead to senior management accepting and implementing the results and recommendations of foresight projects. • A two round Delphi and expert panel was held as part of this study with eight senior Canadian government foresight program leaders • Managers identified factors that relate more to a consultant tool kit than foresight methodology that results in decision impact foresight. • A contingency model is presented with three elements which the impact factors importance • The paper highlights the importance of research partnerships that include both academics and practitioners [ABSTRACT FROM AUTHOR]

This paper provides a practical, systematic approach to the design and delivery of a Delphi survey. We prescribe a sequence of six steps to do with (i) setting up the Delphi process – including selecting respondents and generating a requisite number of focal issues, (ii) software/delivery choice, (iii) developing question items and response scales, (iv) providing feedback between a requisite number of Delphi rounds, (v) preventing and dealing with panellist drop out, and (vi) analysing and presenting the Delphi yield. At each step, the Delphi administrator has a range of choice options and we provide discussion of the pros and cons of each option - in order that the overall design and delivery of a particular Delphi survey is both well-founded and defensible. • This paper provides detailed guidance for anyone looking to run a Delphi exercise. • The Delphi process can be broken into 6 key steps. • The paper identifies and recommends decisions to be taken at each step. • The paper also reviews and evaluates recommendations for a defensible Delphi" • Following the "6 steps of Delphi" will help generate effective Delphi output. [ABSTRACT FROM AUTHOR]

Understanding changing consumer needs is crucial for a company's survival. Particularly in the context of vehicle autonomy, customer insights lay a significant foundation for strategic decision-making of organizations in the automotive industry. This paper outlines how a German car manufacturer explored customer needs in the context of highly automated vehicles (AVs). 1 1 Highly automated vehicles (SAE level 3) = highly AVs. by implementing corporate foresight research with visionary customers and how the findings supported the strategic decision-making process of the firm. A qualitative pilot study with 29 visionary, trend-receiving customers from Germany, the USA and China identified three innovative use cases for premium highly AVs. A subsequent quantitative online survey with 733 participants from the same three markets confirms the relevance of the use cases for mainstream and innovative consumers. The findings underline that highly AVs are a game changer, transforming future cars into extended living and office spaces, with several implications for practitioners. The findings helped to adapt the organization's business model and branding strategy, provided valuable insights for follow-up studies and shaped corporate communication. The contribution of the paper is threefold: It introduces the concept of strategic customer foresight, outlines specifically how organizations can implement customer foresight research as well as how such research benefits the decision-making process of companies. Further, the paper discloses future customer needs in the context of premium highly AVs. • Visionary, trend-receiving customers improve corporate foresight by providing consumer perspective to foresight research. • Customer foresight research supports strategic decision-making process of companies. • Strategic customer foresight provides managers with arguments to convince leaders of trends and emerging consumer needs. • Consumers expect new use cases and activities in highly automated vehicles. [ABSTRACT FROM AUTHOR]

This work makes the case for the integration of the circular economy (CE) and large-scale data (LD), also known as big data. The paper is one of the first to integrate conceptual and practical trends regarding: (a) the ReSOLVE based models of the circular economy; (b) key stakeholders roles in pursuing a more sustainable society; and (c) the volume, velocity, variety, and veracity (4V's) of large-scale data (LD) management. This study's contributions include: (1) introducing a new integrative framework to enhance the understanding of the CE-LD nexus; (2) a relational matrix which illustrates the complexity of large-scale data and stakeholders management; and (3) a research agenda, with clear research propositions and future research direction. The proposed CE-LD integrative framework provides socio-technical insights for academics, practitioners, managers, and policy decision-makers. • This paper integrates the disparate fields of the circular economy (CE) and large-scale data (LD). • Discusses how large-data can support the circular economy's business models. • An integrative framework for CE-LD is proposed. • A research agenda for the circular economy and large-data integration is proposed. • Implications for challenges and opportunities of sustainable production in a digital world. [ABSTRACT FROM AUTHOR]

The impact between time series may differ at different frequencies and time periods, and certain external events may cause sharp fluctuations in new financial markets. It is essential to conduct additional analyses on the extreme relationships in the time-frequency domain. However, extreme causal relationships and time-varying characteristics under various shocks usually cannot be detected simultaneously. Therefore, we reveal the extreme impacts and dynamic changes in global economic conditions on renewable energy by extending a fresh extreme wavelet-based method. Our results reveal significant extreme asymmetric impacts of economic conditions on renewable energy. Moreover, this effect was reinforced by extreme events such as the outbreak of the global financial crisis and the Russia–Ukraine conflict. This paper provides a deep analysis of economic conditions and renewable energy from a time-frequency domain perspective, which can aid investors and policy-makers in making relevant decisions under extreme conditions. • A extreme wavelet-based method is developed to reveal the extreme impacts and dynamic changes. • The significant extreme asymmetric between global economic conditions and renewable energy is confirmed. • A simulation technique is proposed to verify the robustness of our method. [ABSTRACT FROM AUTHOR]

Digital nomads are engaged in a complex quest to select their next destination. In this context, user-generated content (UGC) on social media is a pivotal source to glean insights into digital nomads' destination choices. Accordingly, this study investigates the principal topics that influence digital nomad's destination choice. To this end, data-mining techniques are applied to analyze user-generated content (UGC) from the social platform X (former Twitter). Based on the results, we identify a total of 11 topics associated with digital nomads' location preferences that can be grouped into 3 clusters (positive, negative, and neutral). Specifically, we find six positive topics (employment, retirement, gastronomy, co-working, work motivation, culture), one neutral topic (customer service), and four negative topics (connectivity, work hours, visa issues, loneliness). The results suggest that job flexibility, the attraction of travel, and cultural immersion emerge as positive factors influencing destination choice. By contrast, connectivity concerns, visa management, feelings of isolation, and emotional adjustments stand out as considerable impediments for digital nomads. We spotlight the long-term pursuit of quality of life and technological connectivity as the main drivers of digital nomads in their destination choice. The paper concludes with a formulation of 33 research questions related to digital nomad destination decisions to be addressed in further research. • Quality of life and reliable tech infrastructure drive digital nomad decisions. • Social media UGC impact on digital nomads' destination perception and choice. • Connectivity and visa issues present major barriers for digital nomads. • Job flexibility and cultural immersion are key for digital nomads' choices. • Emotional well-being and social connections are critical for digital nomads. [ABSTRACT FROM AUTHOR]

Abstract The United Nations aspirational agenda for sustainable development calls for the shared efforts of governments, business sector, society and stakeholders to promote prosperity while protecting the planet. In the business perspective, the joint pursuit of both durable competitive advantages and long-term benefits for society are not just the result of companies' reactions to goals of institutions or demands of stakeholders. Rather, they depend on a holistic integration of sustainability in companies' strategic decision-making. This paper proposes an application of the fuzzy Analytic Hierarchy Process (AHP) method for selecting those sustainability issues that are most relevant for creating shared value for both business and society, and that should be the focus of strategic planning and management. The integration of the ISO 26000 framework with the method permits a holistic treatment of all areas of sustainability. The paper also illustrates to managers how the method should be applied in practice through a step-by-step application to a medium-sized company operating in the water technology sector. Finally, its usefulness as a managerial tool for strategic decision-makers is discussed. Highlights • The method allows integrating sustainability into strategic decision-making. • The ISO 26000 standard is included in the method hierarchy. • Fuzzy logic handles subjectivity affecting sustainability decisions. • The proposed method allows direct involvement of different stakeholder types. • The method is particularly useful for companies with limited resources. [ABSTRACT FROM AUTHOR]

This paper has an empirical and theoretical focus: to empirically assess electric bicycle development in China, and to theoretically test and apply the “Multi-Level Perspective” on transitions and innovation. We examine the electric bicycle (e-bike) sector in China to understand the future prospects for urban mobility and the interaction of e-bikes as a form of vernacular technology within the existing transport regime. For this purpose, we address the following questions: 1) What factors will influence the future adoption of e-bikes? 2) How are alternative travel modes evaluated against e-bikes? 3) Will e-bikes become a popular sustainable mobility mode in the future or only an intermediary mode to cars? To provide answers, we conducted a survey in Nanjing city in order to assess the attitude of e-bike users, and other mode users (e.g. pedestrians; bicycle users). We then analyse responses from this survey through the lens of sociotechnical transitions theory, notably the “Multi-Level Perspective” notions of niches, regimes, and landscape. The paper explores the influential factors underpinning future e-bike adoption and the decision-making calculus behind alternative mode choices. Generalised Linear Models are used to investigate the factors influencing future e-bike adoption and alternative mode choices based on the survey data. We conclude that e-bikes are an intermediary mode on Nanjing's motorisation pathway, and that they therefore may eventually reflect a dying regime. [ABSTRACT FROM AUTHOR]

Industrial symbiosis (IS) can support the transition towards the circular economy: accordingly, wastes produced by a company can be used by other companies as an alternative to raw materials or directly used to create new products, sold on B2C markets. This paper aims at analyzing consumers' perception towards electronic products (e.g., laptops, smartphones, tablets) generated via the IS approach (hereafter mentioned as "IS products") and understanding which factors influence the consumers' purchase intention and willingness to pay a premium price for them. By relying on the Theory of Planned Behavior integrated with the Theory of Consumers' Decision-Making Process, we study the influence of environmental concern, perceived consumer effectiveness, social influence, perceived safety, functionality expectations, and green perceived utility. A survey was conducted involving 1.224 Italian consumers. Results highlight that perceived consumer effectiveness and social influence positively affect both purchase intention and willingness to pay a premium price for IS products, while green perceived utility, perceived safety, and functionality expectations positively affect only purchase intention. Results of this paper offers to managers insights useful to understand consumers' behavioral intention towards IS products and to develop appropriate production and marketing strategies. • The paper links industrial symbiosis and green consumer behavior literature. • Consumers' perceptions for products from industrial symbiosis are analyzed. • Consumers' purchase intention and willingness to pay a premium are assessed. • The determinants of consumer behavior on industrial symbiosis products are highlighted. • Theory of Planned Behavior and Theory of Consumers' Decision-Making Process are integrated. [ABSTRACT FROM AUTHOR]

Smart agriculture offers the potential to analyse agricultural data at a scale not previously possible. Researchers argue that the combination of rich data and intelligent decision support has the potential to improve productivity and profitability in agriculture, whilst also improving sustainability. We argue that achieving this potential requires not just on technological advancement, it also requires a detailed understanding of factors that impact technology acceptance in smart agriculture. Acceptance is necessary if technical advances are to translate into real-world impact. However, technology acceptance is complex and often poorly understood. This systematic review focuses on technology acceptance in prediction and decision support systems in crop production. Major databases were searched to identify papers that formally address technology acceptance and include detailed data. 16 papers met the inclusion criteria and were included in the final analysis. Common facilitators and barriers are identified, and papers are mapping against the Theoretical Framework of Acceptability. This analysis showed that constructs including perceived effectiveness are addressed frequently, but others such as opportunity costs and burden have received less attention. The findings suggest the necessity for greater application of formal methods and the need for standardized, domain-specific methods to support this assessment. • Presents a systematic review of technology acceptance in smart agriculture, focusing on decision support in crop farming. • Increased productivity, access to information, and support for training are amongst the most common facilitators of acceptance. • Complexity, infrastructure requirements, increased burden, and not directly addressing farming needs are common burdens. • While effectiveness has been widely addressed, issues such as burden, opportunity costs and ethicality have received limited attention. • The development of a validated models of technology acceptance, and associated instruments, should be prioritised. [ABSTRACT FROM AUTHOR]

Despite some recent progress, scenario planning's development as an academic discipline remains constrained by the perception it is solely a practical tool for thinking about the future, with limited theoretical foundations. The paper addresses this issue by showing that G. L. S. Shackle's ‘Potential Surprise Theory’ (PST) contains much that can lend theoretical support to scenario planning - especially its use of plausibility rather than probability, and its focus on potential extreme outcomes. Moreover, PST and scenario planning share the same ontology, viewing the future as constructed by the imagination of individuals. Yet, under PST, while the future is imagined and, therefore, subjective, individuals nevertheless seek to identify the ‘best’ option through a deductive process of elimination. PST therefore assists in overcoming the divide between the constructivist and deductivist perspectives in scenario planning as it employs both. Finally, the paper shows that theoretically underpinning scenario planning with PST would place it at the heart of contemporary debates on decision making under uncertainty taking place in economics and other fields, enhancing its status and profile as a discipline. [ABSTRACT FROM AUTHOR]

In linking the literature on the adoption of Information and Communication Technology (ICT) with the lead user theory, the paper presents the results of a living lab study on the adoption of high speed broadband and advanced ICT services in the Netherlands. The paper proposes that advanced users are able to shape ICT technologies based on their status, their needs and their ability to propose new solutions. In order to examine the role of advanced users, we use data from an on-line survey conducted in a living lab called “Kenniswijk” (Knowledge District) in the Netherlands carried out among 2994 residential users in July 2009. In a first step, the paper examines the leading-edge status of advanced users. Afterwards it studies the extent to which the choice of these users to adopt high speed broadband is related to their decision to adopt advanced ICT services. Finally, the paper utilizes an experimental choice design in order to examine the role of advanced users in defining new product and service characteristics of advanced ICT services. Our research shows that an advanced group of users expected to benefit from using a variety of advanced ICT services in areas such as e-surveillance and local television. In addition, they can contribute to the product and service generation phase within a living lab environment. [ABSTRACT FROM AUTHOR]

This paper seeks to reaffirm human kind's status as a superorganism, or what the paper will later call a social organism that operates as a biological individual. As such, the paper recognizes the existence of the Global Brain and its great potential to help organize our social organism into a more coordinated, more efficient, more democratic, and more collectively potent entity. This potential lies in its ability to foster more numerous and more diverse communications between both humans and technology, and then better link those communications to mechanisms of action. However the Global Brain remains just that: a potential. Power dynamics around the world continue to yield very much influence to a very small percentage of the population. Not only does this reality cause poor collective decisions to be made which is dangerous in its own right, but it also threatens the possible emergence of a true Global Brain that effectively coordinates a global society. It's the goal of this paper to highlight that danger we are facing and suggest a course of action that intentionally applies the Global Brain concept to reform the way our communities share information and make decisions in order to realize its dream. [ABSTRACT FROM AUTHOR]

This paper examines the nexus between sovereign environmental, social and corporate governance (ESG) issues and corporate investment decisions from a sustainable perspective. By utilising firm-level balance sheets data, country-level governance and policy uncertainty data, we find country governance has a significant positive effect on firm investment. Moreover, this paper shows that climate and migration policy uncertainty has a statistically and economically significant dampening impact on corporate investment, indicating that environmental and social prospect plays a key role in promoting business investment in the United Kingdom. In addition, the empirical evidence on the moderation analysis of corporate leverage suggests that superior environmental, social, and governance performance can help businesses relieve the burden of debt overhang on firm investment. These results provide several important implications on climate change with the objectives of the COP26 conference. • The nexus between sovereign environmental, social and governance (ESG) issues and corporate investment is examined. • Country governance has a significant positive effect on firm investment. • Climate and migration policy uncertainty has dampening impact on corporate investment • Superior environmental, social, and governance performance help businesses relieve the burden of debt overhang. • Several important implications on climate change regarding the objectives of the COP26 conference are provided. [ABSTRACT FROM AUTHOR]

• Emotions have a multifaceted and complex influence on innovation adoption. • Emotions' cognitive content should be considered when modelling innovation adoption. • Emotions are elicited by other targets than the innovation itself. • Emotions' influence on adoption changes through the phases of the process. • Emotion regulation explains the non-deterministic influence of emotions. The dominant models of innovation adoption have traditionally overlooked the role of emotions, despite the relevance of this construct in consumer decision-making. To address this historical gap, a notable stream of research on emotions in innovation adoption has emerged in recent years. To enrich our understanding of the psychology of innovation adoption, this paper integrates insights from research on emotions in psychology with a systematic review of the literature on consumer emotions in innovation adoption. Drawing on well-established theories of emotions and decision-making, we derive five fundamental dimensions that help define the role of emotions in the consumer adoption of innovations. A systematic review of existing evidence within the specific field of innovation adoption summarises the existing evidence through the lens of the five dimensions. The contributions of the paper are twofold. First, the paper offers a novel perspective that provides a deeper understanding of emotions as a psychological mechanism enabling or impeding innovation adoption. Second, we set an agenda for invigorating research in this important domain. [ABSTRACT FROM AUTHOR]

Social robots—such as autonomous vehicles, service robots, or healthcare robots—are designed to support tasks in a broad range of human activities. However, these robots face moral dilemmas because they must make decisions that may do good for one human but potentially inflict harm on another. We argue that Kant's categorical imperative provides a framework for algorithm-based moral decision-making. By systematically addressing ethical concerns from the outset in the development of the algorithms that steer social robots, their designers can help ensure that such robots promote the well-being of individuals, communities, and society. We conclude that those involved in the development of social robots need to embed ethics into their design and functioning. The solutions to the ethical dilemmas we advance in this paper can help improve the adoption and impact of social robots. The presented insights contribute to research, practice, and policy. • Social robots face moral dilemmas because they must decide whom to do good/harm. • Kant's categorical imperative provides a framework for algorithm-based moral decision-making. • Algorithms based on maxims can ensure that such robots promote the well-being. • Development of social robots need to embed ethics into their design and functioning. [ABSTRACT FROM AUTHOR]

This paper offers a study of real success experiences of SMEs, in relation to the motivations of selection and implementation of Enterprise Resource Planning (ERP) and its benefits that also allow the confrontation with theoretical concepts, based on reviewed literature. We followed a qualitative approach based on in-depth content analysis of SMEs online stories included in the 'Customer Stories' directory available on the SAP website using the R language to scrape data and statistical analyses. The findings provide evidence that the use of ERP, for managing SMEs, is constructive to their success and improves the quality of their decision-making processes. Although the technologies implemented by SMEs were characterized by their specialisation and adaptation, SAP Business One is the leading solution, without significant differences by sector compared to Europe. They also reveal that the effectiveness of implementing ERP is intrinsic to the reputation of the software vendors and the high professionalism of the partners. Additionally, the results indicated the short-term approach of SMEs when implementing this type of tool, takes precedence over the strategic and economic benefits. Furthermore, the empirical analysis supports the association of some motivational factors of ERP implementation and selection with characteristics of the organisations, such as activity and size. • Proposed a framework of the influencing factors, process and impact of adopting ERP in SMEs. • Explored and analysed online customer stories through a text mining approach. • ERP systems are identified as essential for the digital transformation of their businesses. • ERP vendors and its partners influence the adoption process. • Organisational benefits of the ERP implementation are valued above of the economic ones. [ABSTRACT FROM AUTHOR]

As individual investors who act independently can generate only limited influence on corporate decisions, this paper considers clustered institutional investors connected through investor networks as salient external stakeholders and investigates whether shared preferences for environmental, social, and governance (ESG) among clustered institutional investors induce more low-carbon innovation of family firms. Using a dataset with 9249 observations over the period of 2007–2019 of Chinese family firms, we develop a novel measurement for the shared preferences for ESG activities among clustered institutional investors and find that such shared preferences are positively related to corporate low-carbon innovation. From a stakeholder perspective, we explore the moderating effects of green finance and family control. Our findings suggest that green finance strengthens the above relationship, but this positive moderating effect is significant only in the low-uncertainty economic context. We also find that as family control increases, the positive impact of the shared preferences for ESG among clustered institutional investors on low-carbon innovation becomes less pronounced, and such a negative moderating effect disappears if a family successor is present in the top management team. • Shared ESG preference of institutional investors (S_ESG) spur low-carbon innovation • Green finance positively moderates the effect of S_ESG on low-carbon innovation • Such moderating effect of green finance is pronounced in stable economic situation • Family control negatively moderates the effect of S_ESG on low-carbon innovation • Such moderating effect of family control weakens if young family member present in TMT [ABSTRACT FROM AUTHOR]

This paper focuses on the question who companies should talk with to be able to make complex long-term decisions, find vision and develop products and services that only come to market in a few years. Currently, there is room for improvement within the process of profiling and identifying the right conversation partners for studies on future customer expectations. Therefore, twenty existing concepts such as lead users, early adopters, and cutting edgers were reviewed. A typology of the agents of the new is elaborated and based on literature, quantitative and qualitative research as well as practical experience, the trend receiver concept is developed. By the author's definition, a trend receiver is an individual who perceives and reflects changes and potentials of the new in a specific domain in a highly sensitive and differentiated way. Seventeen applications of this new concept at Audi (from 2009 to 2013) with over 300 trend receivers, contribute to an understanding of the value of this approach. This paper discusses the characteristics of trend receivers and reflects on the tailor-made search process and search profiles necessary to identify individuals with such capabilities. In addition, it discusses how to organize the conversation process with trend receivers and how this novel approach can best contribute to vision finding, long-term decisions and brand, product and service development. [ABSTRACT FROM AUTHOR]

• This paper identifies and analyzes the implementation challenges of Industry 4.0 in the Indian automobile industry. • The significance of each challenge is obtained through BWM (Best and Worst Model). • The DEMATEL (Decision Making Trial and Evaluation Laboratory) approach categorizes the challenges into cause and effect groups. • The research findings would help organizations in successful implementation of Industry 4.0 in the Indian automobile industry. Industry 4.0 is a novel concept in the manufacturing sector that will enhance productivity in the automobile industry. However, there are many challenges to its implementation in the context of the Indian automobile industry. This paper identifies the Human Resource Management (HRM) challenges associated with the implementation of Industry 4.0 in the Indian automobile industry and analyses them using a hybrid methodology. The hybrid model, which is a combination of the Best and Worst Model (BWM) and DEMATEL (Decision Making Trial and Evaluation Laboratory) is implemented in this paper for analysis of the weightages of various challenges followed by its categorization into cause and effect groups. This paper is a unique and novel one that addresses the most contemporary issues related to HRM challenges associated with the implementation of Industry 4.0 practices in the Indian automobile industry. The automobile manufacturers can infer from the results to mitigate the causes of HRM challenges and promote the implementation of Industry4.0 in their plants in a most productive manner. [ABSTRACT FROM AUTHOR]

This paper presents a system for analysis of municipal Critical Infrastructures, which offers integrated tools for target analysis, hazard scenario simulations and spatial analysis within a remotely accessible Web-based Geographic Information System. The system has been applied to research conducted in the city of Gdansk with the aid of blast attack, chemical leakage and flood hazard scenarios, as well as a spatial density algorithm, which highlights events in which the proximity of infrastructures influences their susceptibility to a single attack. The paper also discusses the way in which the tools provided by the system aim to assist in the processes of infrastructure vulnerability assessment, mitigating discovered risks as well as strategic planning of city development. [ABSTRACT FROM AUTHOR]

• A unique measure for corporate transformation toward industry 4.0. • Corporate transformation toward I4.0 in the UK is increasing over time. • CTTI4.0 can be viewed as enablers of the circular economy. • Corporate transformation toward I4.0 positively affects financial performance. • ESG strengthen this relationship. • Successful CTTI4.0 practices require a proper understanding of stakeholders' interests and expectations. • The results provide the theoretical evidence to the influence of national culture and boardrooms commitment on achieving the synergy between I4.0 and circular economy. Despite the importance of corporate transformation toward Industry 4.0 (CTTI4.0), almost no research exists on how companies communicate CTTI4.0 information in their annual reports and how this affects financial performance. To fill this gap, this paper uses computer-aided textual analysis to explore the current practices of CTTI4.0 in the UK context. It also uses quantitative analysis to examine the impact of CTTI4.0 information on financial performance. The analysis shows that strategic investment decision-making (SIDM) practices for CTTI4.0 have accelerated over the period, and these practices vary in industry sectors. Furthermore, it finds that CTTI4.0 disclosure has a positive impact on financial performance. In addition, it finds that environmental, social, and governance (ESG) practices moderate the relationship between CTTI4.0 disclosure and financial performance. This indicates that firms with better ESG performance tend to be more engaged in CTTI4.0 disclosure and better financial performance simultaneously. Our findings offer insights to decision-makers and regulatory bodies regarding the current practices of CTTI4.0 and its potential economic impact. Paper type : Research paper. [ABSTRACT FROM AUTHOR]

In complex systems, decision makers encounter uncertainty from various sources. In this paper, a new hybrid grey-based Multi-Criteria Decision Analysis (MCDA) approach is proposed to optimize the evaluation space in decision problems that are subject to subjective and objective uncertainty over different types of interrelated criteria. The four-phase methodology begins with the formulation of a decision problem through the analysis of the system of concern, its functionality, and substantial connections among evaluation criteria. The second phase involves the development of grey linguistic scales to handle the uncertainty of human judgements. The third phase integrates the grey linguistic scale, concepts of grey systems theory, and principles of Analytical Network Process to prioritize criteria. Finally, to evaluate and rank alternatives in such a complex setting, Preference Ranking Organization METHod for Enrichment Evaluation II is extended using a grey linguistic scale to articulate subjective uncertainty, grey numbers to account for objective uncertainty, grey operating rules to normalize evaluation measures, and the proposed approach of prioritizing evaluation criteria to establish relative preferences. To demonstrate the viability of the methodology, a case study is presented, in which a strategic decision is made within the context of innovation. To validate the methodology, a comparative analysis is provided. • Structure complexity should be considered while analyzing decision problems. • Subjective and objective uncertainty cannot be addressed using conventional MCDA. • A new methodology is proposed to address uncertainty in a complex structure. • Conventional MCDA approaches have been extended using grey systems theory. [ABSTRACT FROM AUTHOR]

To promote sustainable urban development and green industrial process are critical solutions for sustainable and low-carbon society transition in China, considering the significant environmental impacts derived from the industrialization and surging urbanization. Under this background, China adopts top-down programs on smart cities and smart industrial parks to forward the above efforts. While practices and lessons from these programs will be valuable to enlighten other regions and practitioners, to date, rather few studies have paid attentions to this issue. Particularly, the emerging smart technologies strongly support the practice, via offering smart solutions like better renewable energy projection, low-carbon life styles transformation, as well as energy planning and management. However, there has been a lack of discussing their future role in-depth. With this circumstance, this paper conducts an integrated and in-depth review on China's promotion on smart cities and smart industrial parks. In detail, the national pilots, key technical innovations, incentives and policies framework, as well as spatial features were discussed in-depth. Particularly, we further explored how the smart solutions can contribute to better decision making on low-carbon urban and industrial system planning. Finally, we highlighted policy recommendations targeting on future smart cities and industrial parks promotion, focusing on the perspectives of technological and social system innovations, innovative decision support tools, and smart management framework. Our results expect to offer critical enlightenments for policy makers to address future concerns on smart cities and industrial parks promotion and management. • China's progress on Smart cities and industrial parks were reviewed. • Related technological and social innovations were highlighted. • Discussed how emerging smart infrastructures support novel decision making. • Contribution to low-carbon society were discussed systematically. [ABSTRACT FROM AUTHOR]

Abstract: This paper provides a range of alternatives for analysts when dealing with geo-spatial data addressing activities in science, technology and innovation. There are two sets of theory which frame the debate concerning science, technology and innovation, and which drive further methodological advancements. The power of a good visualization in providing insight to decision-makers is well known. Visualizations complete a full cycle of decision-making involving analysis, design, action and then further monitoring. We advance the paper by assessing available geographic information in science and technology databases. The paper then systematically outlines current best practices and alternatives for visualizing geographic data. Different geographic map options provide different possibilities for the display of data. We show some of these options in the paper. Future research is needed into both the available tools and techniques, as well as a more in depth specification of the kinds of decision support needs that exist and have a geo-spatial component. [Copyright &y& Elsevier]

Abstract: Foresight the ability to plan and think systematically about future scenarios in order to inform decision-making in the present has been applied extensively by corporations and governments alike in crisis management. Foresight can be complicated because dispersed groups have diverse, non-overlapping pieces of information that affects an organization's ability to detect, mitigate, and recover from failures. This paper explores the failure of foresight in crisis management by drawing on data on events that preceded and followed the Mari disaster in a naval base in Cyprus in July 2011, where a large explosion killed 13 people and injured 62 others, while completely destroying the major power plant of the island. The paper examines how foresight into crisis management decisions was compromised because of a conscious effort by high ranking decision-makers to minimize emergent danger and avoid responsibility for the crisis, in joint with red tape, bureaucracy, and poor coordination and information flows. The paper explores the notion of operational and political responsibility of individual decision-makers and discusses an alternative approach to foresight in crisis management, one that is built on multiple layers of decision-making. [Copyright &y& Elsevier]

Abstract: Necessity and Sufficiency are two of the most important concepts in science. Indeed, they are the basis for establishing causal relationships between factors, variables, etc. In contradistinction to most treatments of causality, we show how to compute the probability that Necessity and Sufficiency obtain. We thus treat probabilistic causality, which is key to Technological Forecasting since we are never dealing with complete knowledge or perfect certainty. This paper shows how decision makers can obtain direct estimates of the probabilities of the Necessity and the Sufficiency of various proposed courses of action and thereby make better decisions with regard to their efficacy. The paper goes beyond typical chi-square analyses that show whether there are significant statistical relationships between two or more variables. Instead, whatever the level of statistical significance, it shows how one can determine the amount or degree of Sufficiency and Necessity that exists between two or more variables. In fact, we show how statistical significance and Sufficiency and Necessity are related. In particular, we show how the correlation coefficient between two variables is a direct function of Sufficiency and Necessity. To do this, we adapt a framework from epidemiology: Predictive Value Theory. Although Predictive Value Theory was originally developed to help physicians make critical decisions, e.g., whether to administer or not to administer a treatment, or to screen or not to screen for say cancer, it is so general that with little modification it applies equally well to decision making in general. By combining probability theory and elementary logic, we show how one can measure directly the Sufficiency and the Necessity of a test from the data that are gathered in a typical application of Predictive Value Theory. The result is not only a better understanding of Predictive Value Theory, but its extended application to decision making in general. Finally, the paper goes beyond traditional Bayesian ways of computing the probability of implication and hence Sufficiency and Necessity. [Copyright &y& Elsevier]

Computer Aided Design (CAD) software is one of the newest and most widely-used forms of critical system investment in the research and development units of manufacturing industries. This paper presents an application of the AHP used to examine the weights attached to and priorities of experts' perceptions. Besides, in the design of the expert questionnaire this study has mainly referred to the relevant literature, the process involved as organizations purchase products, and decision-making patterns. One hundred and twenty-six valid expert questionnaires were collected from five manufacturing industries. The model defines five main factors and 15 indicators. Moreover, the "Effect after purchasing" is the most critical factor, and "Performance between new and old software" is the first priority for all indicators according to most experts. The outcomes of this study could provide insights for academia and help 3D CAD software companies better understand the important factors influencing the purchase of software for different industries and decision makers. • Effect after purchasing was the key factor for five manufacturing industries when deciding to purchase 3D CAD software. • The performance between new and old software was the top-ranked and key indicator. • In addition to the Effect after purchasing factor, the Software license model and price factor are also important. • This study has empirically tested a new theoretical assessment framework for purchasing 3D CAD software. [ABSTRACT FROM AUTHOR]

Quantifying the spreading power of a pandemic like COVID-19 is important for the early implementation of early restrictions on social mobility and other interventions to slow its spread. This work aims to quantify the power of spread, defining a new indicator, the pandemic momentum index. It is based on the analogy between the kinematics of disease spread and the kinematics of a solid in Newtonian mechanics. This index, I PM , is useful for assessing the risk of spread. Based on the evolution of the pandemic in Spain, a decision-making scheme is proposed that allows early responses to the spread and decreases the incidence of the disease. This index has been calculated retrospectively for the pandemic in Spain, and a counterfactual analysis shows that if the decision-making scheme had been used as a guide, the most significant decisions on restrictions would have been advanced: the total number of confirmed cases of COVID-19 would have been much lower during the period studied, with a significant reduction in the total number of cases: 83 % (sd = 2.6). The results of this paper are consistent with the numerous studies on the pandemic that concluded that the early implementation of restrictions is more important than their severity. Early response slows the spread of the pandemic by applying less severe mobility restrictions, reducing the number of cases and deaths, and doing less damage to the economy. • Measuring a pandemics evolution through an index • Newtonian mecanics for the kinematics of a solid • Facilitating early implementation of policies [ABSTRACT FROM AUTHOR]

Abstract: Today''s business environment provides tougher competition than ever before, stressing the important role played by information and forecasts in decision-making. The scenario method has been popular for focused organizational learning, decision making and strategic thinking in business contexts, and yet, its use in communicating forecast information and advice has received little research attention. This is surprising since scenarios may provide valuable tools for communication between forecast providers and users in organizations, offering efficient platforms for information exchange via structured storylines of plausible futures. In this paper, we aim to explore the effectiveness of using scenarios as channels of forecast advice. An experimental study is designed to investigate the effects of providing scenarios as forecast advice on individual and group-based judgmental predictions. Participants are given time series information and model forecasts, along with (i) best-case, (ii) worst-case, (iii) both, or (iv) no scenarios. Different forecasting formats are used (i.e., point forecast, best-case forecast, worst-case forecast, and surprise probability), and both individual predictions and consensus forecasts are requested. Forecasts made with and without scenarios are compared for each of these formats to explore the potential effects of providing scenarios as forecast advice. In addition, group effects are investigated via comparisons of composite versus consensus predictions. The paper concludes with a discussion of results and implications for future research on scenario use in forecasting. [Copyright &y& Elsevier]

Abstract: A previous review of the use of scenarios in public policy found that the evidence for their impact on policy making was limited. One of the reasons suggested for this lack of policy impact was the disconnection between the time scales explored in long range scenarios, and those typical of the perspective of the policy maker. This paper argues that scenarios can have a valuable role in connecting long term policy goals to their implications for near term decisions. Key to the effectiveness of public policy scenarios in this regard is an actor-based view of the system, which connects long term pathways to the implications of near-term actor decisions. The paper focusses on developing a methodological framework for low carbon scenarios., Reviewing scenario literature, it identifies ‘trend based’, ‘actor based’ and ‘technical feasibility’ scenario approaches, and argues that the insights derived from each of these modes of analysis is important to consider in low carbon scenarios. Moreover, the iteration between these levels as the scenario moves through time is equally important. The paper therefore proposes a 3 level methodological framework as a basis for constructing low carbon scenarios with high policy tractability. [Copyright &y& Elsevier]

Abstract: Soil fertility depletion is considered one of the main biophysical limiting factors for increasing per capita food production for smallholder farmers in Sub-Saharan Africa. The adoption and diffusion of sustainable agricultural practices (SAPs), as a way to tackle this challenge, has become an important issue in the development policy agenda in the region. This paper examines the adoption decisions for SAPs, using recent primary data of multiple plot-level observations collected in 4 districts and 60 villages of rural Tanzania. The paper employs a multivariate probit technique to model simultaneous interdependent adoption decisions by farm households. The analysis reveals that rainfall, insects and disease shocks, government effectiveness in provision of extension services, tenure status of plot, social capital, plot location and size, and household assets, all influence farmer investment in SAPs. Policies that target SAPs and are aimed at organizing farmers into associations, improving land tenure security, and enhancing skills of civil servants can increase uptake of SAPs in smallholder systems. [Copyright &y& Elsevier]

Abstract: In recent years, accelerated by the economic and financial crisis, complex global issues have moved to the forefront of policy-making. These grand challenges require policy-makers to address a variety of interrelated issues, which are built upon yet uncoordinated and dispersed bodies of knowledge. Due to the social dynamics of innovation, new socio-technical subsystems are emerging, however there is lack of exploitation of novel ideas and sustainable solutions to address these grand challenges. In this paper we argue that issues of how knowledge is represented can have a part in this lack of exploitation. For example, when drivers of change are not only multiple but also mutable, it is not sensible to extrapolate the future from data and relationships of the past. This paper investigates ways in which futures thinking can be used as a tool for inspiring actions and structures that address the grand challenges. By analyzing several scenario cases, elements of good practices and principles on how to strengthen innovation systems through future scenarios are identified. This is needed because innovation itself needs to be oriented along more sustainable pathways enabling transformations of socio-technical systems. [Copyright &y& Elsevier]

Abstract: This paper reflects on the potential of future-oriented analysis (FTA) to address major change and to support decision-makers and other stakeholders in anticipating and dealing with transformations. It does so by critically reflecting on the selected papers for this special issue as well as on the discussions that took place at the fourth Seville International Conference on Future-oriented Technology Analysis. Considering the potential roles of FTA in enabling a better understanding of complex situations and in defining effective policy responses leads to the understanding that appropriate FTA practices are needed to enable FTA to fulfil such roles. Dealing with disruptive changes – and grand challenges in particular –, therefore, raises several conceptual, methodological and operational issues. Two of them are general, while further two are specific to the so-called grand challenges: i) distinguish known unknowns, unknown knows and unknown unknowns, ii) combine quantitative and qualitative approaches in a relevant and feasible way, iii) understand the complex and systemic nature of grand challenges, and iv) orchestrate joint responses to grand challenges. After a brief explanation of these issues, the paper outlines the main ideas of the papers published in this special issue. These present various methodological aspects of FTA approaches as well as some advances needed in practice to assist FTA practitioners and stakeholders in comprehending transformations and in tackling the so-called grand challenges. [Copyright &y& Elsevier]

Abstract: This paper aims at clarifying factors that played a role in the formation of public attitudes towards nuclear power generation in the 1970s and 1980s in the Netherlands. The paper especially focuses on the effects of a government initiated societal discussion on energy policy between 1980 and 1985. It thereby intends to draw lessons from the controversies of the past for discussions that might return as several groups are arguing in favor of a “nuclear renaissance”. The concept of ‘interpretive package’ is used as an intermediate concept to link the controversy on nuclear power to wider societal issues. First, the paper briefly describes the nuclear power controversy in the Netherlands. It then reconstructs public opinion on the nuclear power issue between 1974 and 2006. Finally, it analyzes how the media linked the nuclear power issue to wider issues in society. In its final analyses, the explanation of public opinion formation in terms of interpretive packages is compared to other explanatory models. The paper concludes that there is a strong indication that a main explanation for changes in the ‘nuclear public opinion’ in Western countries can be found in styles that governments apply in dealing with their citizens. The paper finally reflects upon possible consequences of these findings for future debates on nuclear power generation. [Copyright &y& Elsevier]

Abstract: Diffusion of new technology is an important driver of economic growth. In this paper, diffusion of mobile telephony in India is studied. There is a vast diffusion potential in this country which needs to be exploited efficiently and in a rational way. This paper investigates the social, technological, economical and political (STEP) factors that have influenced the diffusion process of mobile telephony especially the diffusion speed. The epidemic model, which is widely employed in the diffusion studies of mobile telephony, is used for the study. The data is fitted into logistic, gompertz, and bass models by nonlinear least squares and it is found that gompertz model best describes the diffusion process of mobile telephony in India. The study reveals that competition and government intervention played a significant role in accelerating the diffusion speed of mobile telephony by making the technology affordable. It is found that mobile telephony is a substitute for fixed line telephony in India. The findings will be useful in taking managerial decisions with respect to factors in forecasting and controlling the diffusion process of emerging technologies. [Copyright &y& Elsevier]

Abstract: Climate change presents a significant planning challenge for water management agencies in the western United States. Changing precipitation and temperature patterns will disrupt their supply and extensive distribution systems over the coming decades, but the precise timing and extent of these impacts remain deeply uncertain, complicating decisions on needed investments in infrastructure and other system improvements. Adaptive strategies represent an obvious solution in principle, but are often difficult to develop and implement in practice. This paper describes work helping the Inland Empire Utilities Agency (IEUA) explicitly develop adaptive policies to respond to climate change and integrating these policies into the organizations'' long-range planning processes. The analysis employs Robust Decision Making (RDM), a quantitative decision- analytic approach for supporting decisions under conditions of deep uncertainty. RDM studies use simulation models to assess the performance of agency plans over thousands of plausible futures, use statistical “scenario discovery” algorithms to concisely summarize those futures where the plans fail to perform adequately, and use these resulting scenarios to help decisionmakers understand the vulnerabilities of their plans and assess the options for ameliorating these vulnerabilities. This paper demonstrates the particular value of RDM in helping decisionmakers to design and evaluate adaptive strategies. For IEUA, the RDM analysis suggests the agency''s current plan could perform poorly and lead to high shortage and water provisioning costs under conditions of: (1) large declines in precipitation, (2) larger-than-expected impacts of climate change on the availability of imported supplies, and (3) reductions in percolation of precipitation into the region''s groundwater basin. Including adaptivity in the current plan eliminates 72% of the high-cost outcomes. Accelerating efforts in expanding the size of one of the agency''s groundwater banking programs and implementing its recycling program, while monitoring the region''s supply and demand balance and making additional investments in efficiency and storm-water capture if shortages are projected provides one promising robust adaptive strategy — it eliminates more than 80% of the initially-identified high-cost outcomes. [Copyright &y& Elsevier]

Abstract: This paper presents a new methodology to build internal business scenarios from the data gathered by some key performance indicators (KPIs) defined within a performance measurement system. The application of the principal components analysis technique leads to the identification of latent relationships between KPIs that underlies some important business aspects. Further, this methodology allows to represent not only the temporal evolution of the organisation as a function of these business aspects but also the definition and determination of internal business scenarios, being therefore the source of meaningful managerial information. At the end of the paper, results of a practical application are presented and discussed, as well as their importance for the organisation from a decision making point of view. [Copyright &y& Elsevier]

Abstract: Scenarios provide a commonly used and intuitively appealing means to communicate and characterize uncertainty in many decision support applications, but can fall short of their potential especially when used in broad public debates among participants with diverse interests and values. This paper describes a new approach to participatory, computer-assisted scenario development that we call scenario discovery, which aims to address these challenges. The approach defines scenarios as a set of plausible future states of the world that represent vulnerabilities of proposed policies, that is, cases where a policy fails to meet its performance goals. Scenario discovery characterizes such sets by helping users to apply statistical or data-mining algorithms to databases of simulation-model-generated results in order to identify easy-to-interpret combinations of uncertain model input parameters that are highly predictive of these policy-relevant cases. The approach has already proved successful in several high impact policy studies. This paper systematically describes the scenario discovery concept and its implementation, presents statistical tests to evaluate the resulting scenarios, and demonstrates the approach on an example policy problem involving the efficacy of a proposed U.S. renewable energy standard. The paper also describes how scenario discovery appears to address several outstanding challenges faced when applying traditional scenario approaches in contentious public debates. [Copyright &y& Elsevier]

Abstract: The sustainable transformation of infrastructure sectors represents a challenge of prime importance worldwide. Due to long life times of infrastructures, strategic decision making has to explicitly consider uncertainties in context conditions, value considerations and available technological alternatives. However currently, strategic infrastructure planning is often carried out in a very narrow perspective. The present paper argues that foresight informed strategic planning, allows addressing trade-offs related to context uncertainties, value conflicts and sustainability deficits in a structured way. The paper introduces a specific procedural proposal, the Regional Infrastructure Foresight method (RIF) and illustrates its potential virtues through an application to urban water management planning in a Swiss region (Kiesental). [Copyright &y& Elsevier]

This paper presents a new approach to Technology Roadmapping by integrating marketing and decision methodologies. While much of the research into technology roadmapping has been applied to products that represent a one-time ROI to the manufacturer, current Internet technologies are resulting in web services that use an entirely different financial and business model of licenses and subscriptions. This paper addresses the software services applicability and documents a start-to-finish application of cross-discipline models and tools to form a real-life roadmap from market drivers to project headcount. Pitfalls in the roadmapping process will be documented and suggestions for improvement will also be discussed. [Copyright &y& Elsevier]

Abstract: Technology Assessment (TA) has been a growing field of management study for the past four decades. An increasing number of studies have been carried out over the years contributing to the development of TA literature. Some of these studies summarized the history and growth of the field during its evolution. However, there has been no effort made to present an overview of the methods and tools that have been cited in TA literature. This paper attempts to fill that void. A thorough review of the TA articles published in leading journals in the management of technology field is conducted to identify the research methods or tools in those studies. The paper provides an introductory review of the use of technology assessment terminology during its development, which helps the readers avoid the confusion of the TA concept since its origination in public decision making forty years ago and where it is now — widely adopted in other sectors. A thorough presentation of the approaches, methods and tools that have been introduced or employed in both mainstream TA and “inverted TA” studies is then provided. The main content of the paper is related to the works published in leading international journals that involve certain research methods or techniques. [Copyright &y& Elsevier]

Abstract: There have been comments recently about the efficacy of Futures Studies (and scenario planning) projects, relating to confusion on knowledge aggregation and methodology, which can be summarised in the question: “how to determine the purpose of such projects”. The lack of a purpose framework makes it difficult for ‘clients’ initiating such projects to determine if outcomes meet their original expectations. This paper proposes a framework to help understand the nature, objective and purpose of Futures Studies (and scenario planning) projects, which we will argue helps to overcome these concerns. The proposed framework is based on Vickers'' definition of an Appreciative System, highlighting how decision making involves three areas of judgment — reality judgment, value judgment, and instrumental judgment. It will be argued that decision-makers and policymakers call for Futures Studies projects when they become aware of an organizational deficiency in one or more of these areas. Each element, alone or in combination, could form the basis of a purpose definition for a Futures Studies project, and, therefore, needs to be considered to ensure that the project meets client expectations and is experienced as purposeful and rewarding. The paper elaborates on each of the three elements, and then discusses their integrated nature. This is followed by a discussion of the implications of Appreciative System theory for three key players in the decision making process, the organizational leadership, the professionals and the organization at large involved in the practice of Futures Studies (and scenario planning) projects. [Copyright &y& Elsevier]

• The struggle in connecting futures intelligence to policy making can be read as a basic challenge in foresight. • Policy lenses are proposed to interpret futures intelligence from the perspective of a policy maker. • Lenses can focus on, for example, priorities such a mission-oriented policies, forms of Europeanisation or the variety of policy formation and implementation spaces • An experiment is presented in developing and applying tailored lenses for European research and innovation policy. The rich and complex outcomes of foresight activities are often difficult to translate into policy relevant intelligence. The struggle in connecting futures intelligence to policy making can be read as a basic challenge in foresight: working on futures intelligence has emerged as a way to improve policy, but once it is delegated to professional foresight practitioners with attendant quality and quality control, however, it also introduces a distance to policy making. Whilst independence and methodological rigour is desirable for high quality futures intelligence, bridging this intelligence with the policy context is essential for its use. Experiencing this challenge during a scenario exercise on the future European research and innovation system, the authors of this paper embarked on an experiment to go beyond evaluating the robustness of the scenarios, produced in a foresight exercise, by developing and applying "policy lenses" to translate the scenarios into policy tailored intelligence. This paper describes the experiment, which saw the development and application of three types of policy lenses: (1) a lens based on the layered processes of European policy making, (2) a lens based on three research and innovation policy priorities and (3) a lens on alternative geo-political situations of the European continent. The paper describes the logic behind the lenses, the interpretation of the original scenarios when viewed through these lenses, and then concludes by reflecting on how such an experiment could be generalised to other settings of policy-oriented foresight. [ABSTRACT FROM AUTHOR]

• A review of different methods for measuring carbon emissions and SCC. • SCC model improvement and decision support research are developing in China. • The differences in existing and future research direction were emphasized. With increasing international attention on the coupling system of carbon emission and social economy, governments need to formulate relevant policies and measures to control carbon dioxide and other greenhouse gas emissions. The social cost of carbon (SCC) can form the basis for such steps. To investigate research on SCC, this paper examines relevant literature in China and abroad for different methods to measure carbon emissions. It further reviews research methods for studying SCC, the effects of model parameters on SCC, and the application of SCC to policymaking. The purpose of researching the measurement of carbon emissions is to select the most appropriate, accurate, and precise methods to enhance data support for research on carbon emissions (including the measurement of social costs). Recording different models facilitates the estimation of SCC for more suitable and exact estimation methods. Analyzing the effects of model parameters on SCC clarifies decision-making and exogenous variables regarding estimating SCC, including the impact of equity weight, uncertainty, risk aversion, and discount and time preference rates on the value of SCC. Therefore, this paper reviews existing research on SCC policy to help frame policymaking appropriately, using the social cost of carbon emissions. [ABSTRACT FROM AUTHOR]

Scenarios are claimed to support strategic decision makers. They are especially effective in dealing with uncertainties. This paper addresses some drawbacks of the conventional scenario method, which is especially directed at handling these uncertainties, and indicates possible avenues for methodological adaptations. We take the approach, which rests in the Shell tradition, as exemplary for our discussion on the mainstream scenario methodology. This approach has some limitations when it comes to dealing with simultaneous trends and countertrends, and trends or clusters of trends that are not thought of beforehand, especially the methodological requirements of causality and consistency, which might be limiting factors in this respect. This paper indicates alternative ways for scenario construction. It discusses the use of either recombinant scenarios, context scenarios, or inconsistent scenarios and/or combinations of these scenarios. These options explicitly incorporate the notion of ‘paradoxical trend’ as the codriver of future developments into the methodology. [Copyright &y& Elsevier]

This paper proposes a new systems approach to foresight studies. The paper will first indicate the complex and conflicting nature of long-term decision-making process. Then, the need for systems approach will be highlighted by the analysis of 1995 UK Delphi survey results and the scenarios of 2000 UK foresight scenarios. The paper proposes two methodologies, namely Integrated Management Model (IMM) and Roadmapping, in order to overcome challenges introduced by the multidimensional characteristics and complex nature of foresight studies. Based on systemic approach, IMM offers a useful way of developing long-term normative policies and strategies and their transformations into actions by considering necessary changes in organizational structures and behaviors. In addition, roadmapping is used to capture, manipulate and manage information to decrease complexity in the foresight by constructing roadmaps. In the paper, IMM and roadmapping are employed first to analyze UK foresight results and then to develop a new methodology to formulate Delphi events and scenarios for the successful implementation of foresight. This paper also promotes the integrated use of foresight techniques such as scenarios and Delphi rather than one for another. [Copyright &y& Elsevier]

Abstract Despite the overwhelming consensus within the scientific community concerning the causes and effects of climate change, decision-making processes often do not point out in the same direction. In order to effectively and satisfactorily tackle climate change, a legally and politically binding long-term policy architecture is needed. In practice, however, central governments and international policymakers have been unable to provide a successful policy architecture. Yet, city-level initiatives within the Smart City framework are a promising way to tackle climate change. An example of such a Smart City framework is the London Environment Strategy (LES). In this paper, we propose a zero mean reverting model for greenhouse gas emissions to quantitatively analyze its consistency with the 2050 Zero Carbon objectives. We consider different policy scenarios proposed in the LES and the forward-looking policy uncertainty embedded in different economic sectors, primarily domestic, industrial and commercial and transport. We find that, on average, only transport improves the historical greenhouse gas emissions trend, and most of this reduction comes from Smart Mobility and/or Smart Regulation programs focusing on the environment. Highlights • Most actions oriented to mitigate the effects of climate change are being taken at the city level. • The current GHG emission trend in London is not in line with the 2050 zero level objective. • Stress test analysis considering a zero mean reverting process and different policy scenarios • Considering the simulation average trend only Transport sector improves the historical trend. • Industrial and Commercial sector reports the highest level of uncertainty. [ABSTRACT FROM AUTHOR]

Abstract The purpose of this work is to examine the role of intermediaries for knowledge transfer at different points in time. The planning of an integrated planning energy project is complex and involves diverse stakeholders with knowledge bases on different systems impacting energy planning. When to access the knowledge basis of these diverse stakeholders and how to sustain it overtime is not always clear. We propose intermediaries as both a process but also in the shape of actors to mediate knowledge transfer across different stakeholders to facilitate informed decision-making. We examine this within cases of three sustainable projects across Europe in different stages – early planning, later planning and implementation. Our findings indicate that intermediary processes and actors are key for knowledge transfer in integrated energy planning. In the early stage of integrated planning, practices need to become more aware of the role of intermediaries in resolving issues. Data and results from tools initiates a discursive intermediary process for knowledge transfer across different stakeholders. Intermediary is ongoing in the implementation stage but is more actor oriented and reactive to problems than in the planning stages. However, since this abstract text was not provided in the manuscript file, the production team did not include it in your final version. Let me know if this abstract text can be included now and I can arrange this correction for your paper. Highlights • Integrated energy planning calls for new planning practices in cities. • Intermediaries aid knowledge transfer of energy planning and implementation. • Uncertainty in futures affect engagement of stakeholders in the transfer of knowledge. • Planning tools stimulate intermediaries to connect different knowledge bases. [ABSTRACT FROM AUTHOR]

This paper presents an artificial intelligence algorithmic knowledge transfer approach to the models that have been developed throughout the world for smart grid networks. Many nations are moving forward to implement smarter ways to generate, distribute and network energy, while others are expecting the leading countries to take the initiative and then follow suit. Therefore, we theoretically identify three dimensions of experts' competencies—perception, judgment, and decision choice supported by the Throughput Model algorithms for knowledge transfer. Integrating the Throughput Model algorithmic framework and Deming Cycle (i.e., plan, do, check, act), we propose that Information and Communication Technology (ICT) systems influence experts' decision making towards implementation of Smart Grids (SG). This model was backed up with the perspectives of 32 global experts as surveyed using Carnegie Mellon Maturity model questions and analyzed the results using PLS to validate the findings and compare them to our enhanced knowledge transfer developed from Deming's PDCA cycle. Our results suggest that these key algorithmic decision-making components are critical in explaining the successful application of planning, doing, checking/ acting, and planning of renewable energy technology as well as for a greener environment. Throughput Model displaying perceptions (planning) and judgments (doing, checking/acting) regarding smart grid networks Where, P = perception, I = information, J = judgment, and D = decision choice. [Display omitted] • Implementing the Throughput Model to algorithmic pathways of decision choices may provide researchers and practitioners more clarity regarding Smart Grids. • Human decision-making is rife with comparable biases that algorithms might display, the accountability issue is strengthened when employing a model such as the Throughput Model. • ICT competencies in knowledge transfer on experts' planning can be assisted by an artificial intelligence algorithmic decision-making process of perceptions (planning) and judgments (doing, checking/acting) [ABSTRACT FROM AUTHOR]