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The literature on economic forecasting, is showing an increase in criticism, of the inaccuracy of forecasts, with major implications for economic, and fiscal policymaking. Forecasts are subject to the systemic uncertainty of human systems, considerable event-driven uncertainty, and show biases towards optimistic growth paths. The purpose of this study is to consider approaches to improve economic foresight.

This study describes the practice of economic foresight as evolving in two separate, non-overlapping branches, short-term economic forecasting, and long-term scenario analysis of development, the latter found in studies of climate change and sustainability. The unique case of Ireland is considered, a country that has experienced both steep growth and deep troughs, with uncertainty that has confounded forecasting. The challenges facing forecasts are discussed, with brief review of the drivers of growth, and of long-term economic scenarios in the global literature.

Economic forecasting seeks to manage uncertainty by improving the accuracy of quantitative point forecasts, and related models. Yet, systematic forecast failures remain, and the economy defies prediction, even in the near-term. In contrast, long-term scenario analysis eschews forecasts in favour of a set of plausible or possible alternative scenarios. Using alternative scenarios is a response to the irreducible uncertainty of complex systems, with sophisticated approaches employed to integrate qualitative and quantitative insights.

To support economic and fiscal policymaking, it is necessary support advancement in approaches to economic foresight, to improve handling of uncertainty and related risk.

While European Union Regulation (EC) 1466/97 mandates pursuit of improved accuracy, in short-term economic forecasts, there is now a case for implementing advanced foresight approaches, for improved analysis, and more robust decision-making.

Building economic resilience and adaptability, as part of a sustainable future, requires both long-term strategic planning, and short-term policy. A 21st century policymaking process can be better supported by analysis of alternative scenarios.

To the best of the authors’ knowledge, the article is original in considering the application of scenario foresight approaches, in economic forecasting. The study has value in improving the baseline forecast methods, that are fundamental to contemporary economics, and in bringing the field of economics into the heart of foresight.

This study aims to provide probable future developments in the form of holistic scenarios for business negotiations. In recent years, negotiation research did not put a lot of emphasis on external changes. Consequently, current challenges and trends are scarcely integrated, making it difficult to support negotiation practice perspectively.

This paper applies the structured, multi-method approach of scenario analysis. To examine the future space of negotiations, this combines qualitative and quantitative measures to base our analysis on negotiation experts’ assessments, estimations and visions of the negotiation future.

The results comprise an overview of five negotiation scenarios in the year 2030 and of their individual drivers. The five revealed scenarios are: digital intelligence, business as usual, powerful network – the route to collaboration, powerful network – the route to predominance and system crash.

The scenario analysis is a suitable approach that enables to relate various factors of the negotiation environment to negotiations themselves and allows an examination of future changes in buyer–seller negotiations and the creation of possible future scenarios. The identified scenarios provide an orientation for business decisions in the field of negotiation.

As systems get complex, requirements elicitation and analysis are becoming increasingly difficult and important in software development. Even though various analysis methods have been proposed, including scenario‐based analysis, goal‐based analysis, combining goal with scenario and use case‐driven analysis – each method has its own strengths and weaknesses and do not support requirements elicitation and analysis efficiently. This paper proposes a multi‐view approach to analyze the requirements of complex software systems. The multi‐view approach comprises four views, which incorporate many factors that are part of existing methods. This paper discusses the need for these four views, the activities that are part of each view and how they are carried out. As a proof of concept, we apply the multi‐view approach to an automatic teller machine system development.

Some scenario projects, especially those that take short cuts, have design flaws that undermine the whole purpose of scenario analysis. This article aims to investigate these.

This article is a guide to avoiding four common project flaws.

Selecting one desired future and using scenario analysis to promote it to the exclusion of other possibilities is not a wise approach.

Scenarios that ignore the likelihood of serious competition from fledgling startups, market invaders from other industries, or even the possibility of several companies combining to gain the competencies needed to be a threat, are not addressing the future’s full spectrum of competitive uncertainty.

By becoming aware of the four “blind alleys” of scenario analysis warned about in this article, practitioners are more likely to use this planning tool effectively to scope out the true outlines of uncertainty or the fallout from discontinuity and prepare their firm to cope with new realities.

The purpose of this paper is to determine the best approach to customer segmentation and to extrapolate associated rules for this based on recency, frequency and monetary (RFM) considerations as well as demographic factors. In this study, the impacts of RFM and demographic attributes have been challenged in order to enrich factors that lend comprehension to customer segmentation. Different types of scenario were designed, performed and evaluated meticulously under uniform test conditions. The data for this study were extracted from the database of a global pizza restaurant chain in Turkey. This paper summarizes the findings of the study and also provides evidence of its empirical implications to improve the performance of customer segmentation as well as achieving extracted rule perfection via effective model factors and variations. Accordingly, marketing and service processes will work more effectively and efficiently for customers and society. The implication of this study is that it explains a clear concept for interaction between producers and consumers.

Customer relationship management, which aims to manage record and evaluate customer interactions, is generally regarded as a vital tool for companies that wish to be successful in the rapidly changing global market. The prediction of customer behaviors is a strategically important and difficult issue because of the high variance and wide range of customer orders and preferences. So to have an effective tool for extracting rules based on customer purchasing behavior, considering tangible and intangible criteria is highly important. To overcome the challenges imposed by the multifaceted nature of this problem, the authors utilized artificial intelligence methods, including k-means clustering, Apriori association rule mining (ARM) and neural networks. The main idea was that customer clusters are better enhanced when segmentation processes are based on RFM analysis accompanied by demographic data. Weighted RFM (WRFM) and unweighted RFM values/scores were applied with and without demographic factors and utilized to compose different types and numbers of clusters. The Apriori algorithm was used to extract rules of association. The performance analyses of scenarios have been conducted based on these extracted rules. The number of rules, elapsed time and prediction accuracy were used to evaluate the different scenarios. The results of evaluations were compared with the outputs of another available technique.

The results showed that having an appropriate segmentation approach is vital if there are to be strong association rules. Also, it has been determined from the results that the weights of RFM attributes affect rule association performance positively. Moreover, to capture more accurate customer segments, a combination of RFM and demographic attributes is recommended for clustering. The results’ analyses indicate the undeniable importance of demographic data merged with WRFM. Above all, this challenge introduced the best possible sequence of factors for an analysis of clustering and ARM based on RFM and demographic data.

The work compared k-means and Kohonen clustering methods in its segmentation phase to prove the superiority of adopted segmentation techniques. In addition, this study indicated that customer segments containing WRFM scores and demographic data in the same clusters brought about stronger and more accurate association rules for the understanding of customer behavior. These so-called achievements were compared with the results of classical approaches in order to support the credibility of the proposed methodology. Based on previous works, classical methods for customer segmentation have overlooked any combination of demographic data with WRFM during clustering before proceeding to their rule extraction stages.

This paper aims to examine the design and use of scenarios in planning and management control processes.

The study is based on an exploratory case-study approach. Qualitative data have been collected between 2008 and 2011 from three energy companies operating in Italy.

The paper sheds light on three styles of designing and using scenarios. In the first (called “reactive”), scenarios provide a means for corporate actors to analyse past performance in the light of future expected performance. In the second (“proactive”), scenarios contribute to envision different future states of the world. In the third (“disciplined”), scenarios contribute to develop plausible, if not accurate, narratives about future outcomes.

The study is comparative and exploratory. Possible areas for further work based on in-depth studies of scenarios within planning and control processes are identified.

The comparative analysis of the case-study material has implications for the ways in which flexible forms of management control can be mobilised by managers as a resource of action. It is shown that choices around the design and use of scenarios can mitigate some concerns with traditional planning and management control processes focused on the achievement of a single set of targets, but also raise new ones.

The paper sheds light on a scenario-based approach – called “disciplined flexibility” – that avoids the restrictive nature of budgetary controls without losing the benefits of setting a plan and a target for the future. The paper outlines elements that may support the use of “disciplined flexibility”, but also its potential limitations.

This chapter describes the scenario technique used for the integrative methodological approach (IMA) of the German global change project GLOWA Elbe. It is outlined how regional scenarios are systematically derived to analyze water use conflicts and their resolution in the context of global change for the German Elbe river basin. Through the combination of frameworks of development and policy strategies a consistent set of developmental scenarios can be generated that makes it possible to examine the regional impact of policy strategies under conditions of different future global change development paths. The scenario analysis of the framework of development starts on the global level with qualitative IPCC storylines, translates them to the regional level, and quantifies their regional effects by means of modeling and statistical estimation methods. The policy strategies are derived in close cooperation with regional stakeholders.

The purpose of this paper is to investigate a possible business model for telecom operators for entering the IPTV (digital television) market.

The approach takes the form of a case study, literature search and interviews.

The IPTV business model always has to adjust to the change of external factors and uncertainties in the exploration and the exploitation phase. The four scenarios presented in this paper explicitly address the demand, regulatory and competition‐related uncertainties. The scenarios represent the different future possibilities in terms of regulatory environment, industry structure and consumer attitudes towards (IP)TV service. By choosing the right business model, telecom operators can sustain the market competition and deliver customer value and economic benefits. In the light of limited resources, when balancing the requirement of IPTV business model design, telecom operators have to focus on the critical design issues in each of the scenarios.

This is a one‐case study, so no cross‐analysis with other cases was possible.

The research does not stop when the critical design issues have been analysed, but takes them a step further to shed light on the viability of the business model in an exploration phase. This is done by integrating the business model framework analysis with scenario analysis. Scenario analysis indicates various future possibilities and provides a platform for analyzing the decisions regarding critical design issues that have to be made in an uncertain future environment. The competing views on future developments are helpful in reducing the future uncertainties with regard to viability and feasibility of business models for IPTV.

This is one of the first studies that looks into the relationships between business models and scenarios. Also, the application on IPTV is quite novel.

Analysis of relationship between energy and growth offers the sustainable energy pathway for a country’s sustainable economic development. This study aims to focus on the evaluation of the Pakistan’s energy system using long-run energy alternative planning (LEAP) modeling framework through different growth scenarios.

Principal component analysis has been adopted for indicators index formation. Study period of 1980 to 2030 is covered by forward and backward simulations in LEAP software.

The study reveals that current energy policy does not have the potential to lead the country toward a desired goal of economic sustainability.

In falling off scenario, negative growth rate (-5 per cent) assumption is also debatable; LEAP shows an error in the analysis and takes the last positive available value for any further analysis as a default. This case could have been simply omitted from results but for research contribution, the computations for this case are also reported.

Long-range energy alternative planning model has been applied to answer the corresponding question for simulation period of 1980 to 2030 to better compare the past trend and future expectations. Critical analysis of four selected scenarios (BAU, moderate, advanced and falling off) indicate that energy policy of Pakistan is poorly managed to maintain energy system’s effectiveness.

As far as statistical difference is concerned, early years have more fluctuation; however, from 2009, curve flattens for energy consumption and energy demand. The increasing demand of energy impacts the society and hence disturbs all sectors.

Policymakers have been so dragged off from the main route to sustainability, despite all odds there is a huge unexplored potential in the country for use to move in step with the world for a better tomorrow. The study educates the policymakers to comprehend the future energy scenarios and make rational decisions based on the study outcomes.

This paper aims to study the ongoing and emerging technological changes in the global energy sector from the frequently neglected perspective of their potential destructive impact on the Russian economy.

Having reviewed existing global energy forecasts made by reputable multilateral and national government agencies, major energy corporations and specialised consulting firms, the authors noticed that most of them are by and large based on the extrapolation of conventional long-term trends depicting gradual growth of fossil fuels’ demand and catching-up supply. Unlike this approach, the paper focuses on the possible cases when conventional trends are broken, supply–demand imbalances become huge and the situation in the global energy markets is rapidly and dramatically changing with severe consequences for the Russian economy, seriously dependent on fossil fuels exports. Revealing these stress scenarios and major drivers leading to their realisation are in the focus of the research. Based on the Social, Technological, Economic, Environmental, Political, Values (analytical framework) (STEEPV) approach, the authors start from analysing various combinations of factors capable to launch stress scenarios for the Russian economy. Formulating concrete stress scenarios and assessing their negative impact on the Russian economy constitute the next step of the analysis. In conclusion, the paper underlines the urgency to integrate stress analysis related to global energy trends into the Russian national systems of technology foresight and strategic planning, which are now in the early stages of development.

The analysis of global energy market trends and various combinations of related economic, political, technological and ecological factors allowed to formulate four stress scenarios particularly painful for the Russian economy. They include the currently developing scenario “Collapse of oil prices”, and three potential ones: “Gas abundance”, “Radical de-carbonisation” and “Hydrogen economy”. One of the most important conclusions of the paper is that technology-related drivers are playing the leading role in stress scenario realisation, but it is usually a specific combination of other drivers (interlacing with technology-related factors) that could trigger the launch a particular scenario.

This study’s approach is based on the assumption that Russia’s dependence on hydrocarbons exports as one of the main structural characteristics of the Russian economy will remain intact. However, for the long-term perspective, this assumption might not hold true. So, new research will be needed to review the stress scenarios within the context of radical diversification of the Russian economy.

This paper suggests a number of practical steps aimed at introducing stress analysis as one of the key functions within the energy-related sectoral components of the Russian national systems of technology forecasting and strategic planning.

The novelty of this paper is determined both by the subject of the analysis and approach taken to reveal it. In contrast to most of research in this area, the main focus has been moved from the opportunities and potential benefits of contemporary technology-related global energy shifts to their possible negative impact on the national economy. Another important original feature of the approach is that existing global energy forecasts are used only as a background for core analysis centred around the cases when conventional energy trends are broken.