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The study discusses existing scenario methods in business and technology foresight and introduces electronically mediated scenario process in two varieties. The purpose of the study is to discuss the existing practice, position the IDEAS and SAGES methods, and outline their contribution to the state of the art.

The paper takes the form of a literature study and conceptual discussion, illustrated with a case example of electronically mediated scenario methods.

Both of the presented scenario methods, i.e. IDEAS and SAGES, are feasible means to compose scenarios. The methods can be positioned respectively to intuitive‐logical and heuristic schools of thought. The contribution to existing practice is that they consume fewer resources than do their more traditional counterparts.

The empirical validation of the presented methods is presently limited to case studies. Thus, the authors invite practitioners and researchers to examine the methods and to discuss the applicability of the results.

The IDEAS and SAGES methods offer tools for practicing managers to conduct scenario planning with practitioners and experts in a flexible and effective manner.

The paper adds to the ongoing discussion on business and technology foresight by presenting the novel scenario methods, and positioning them explicitly to the existing practice.

Research focussed on the scenario method has increasingly criticized the widely used intuitive logics (IL) approach to scenario development and introduced enhanced approaches, such as the backwards logic method (BLM) or the antifragile (AF) method, to overcome the restrictions associated with the IL approach. The BLM and the AF method have contributed to the further development of the scenario method by integrating backward reasoning and by increasing the method’s effectiveness for decision making. The purpose of this paper is to build on these ideas and introduce strategy scenarios as a further enhancement of the scenario method that directly applies the benefits of scenario-based planning to strategy development in corporations.

The authors argue that the existing methodologies do not fully integrate the benefits of scenario-based planning for strategic decision making and strategy development, as they mostly aim to develop macroenvironmental scenarios and test organizations’ existing strategies.

The paper suggests that changing the scope of scenario planning from environmental developments to the organization’s strategies themselves can further strengthen the method’s effectiveness for decision making.

The strategy scenario approach provides an enhanced approach to more comprehensively utilize the benefits of scenario-based reasoning for strategic decision making.

Corporate and institutional managers don’t get the full return on investment in scenarios that they should, nor do they employ scenarios on the full range of corporate issues suited to this methodology. Most often, scenarios are used by top management to provide a better understanding of the range of possible business environments they must contend with in the future. But mid‐level managers often grumble that these big picture “strategic scenarios” don’t address the competitive issues and the critical decisions that they face in the trenches of their business. To achieve more consistently productive uses of scenarios, there are several major challenges that must be addressed for the future of the scenario method: resolve the confusion over the definitions and methods of scenarios; and clarify and enlarge the appropriate application of scenarios. Beyond the confusion caused by the different definitions and methods of scenarios lies the uncertainty about when and how to apply scenarios in the business environment. In addition to planning and forecasting, scenarios can be used for market research and new product development. A major debate revolves around whether or not scenarios have successfully developed into a tool for investment and company decision‐making. One view has been that scenarios provide context, but not direct inputs for such decisions (R&D priorities, new products, and financial investments). This approach emphasizes the role of scenarios in team building, information gathering, learning, and strategic thinking. It advocates using scenarios primarily as a tool for corporate learning and for changing corporate culture. Another view, however, holds that scenarios can and should be used for near‐term business decision‐making. Scenarios need to be applied to the numerous operational issues that companies face. As such, they are a key method of analysis, especially for highly uncertain circumstances.

The purpose of this paper is to explore scenario development (SD) as a method for engaging known challenges in collaborative research projects, i.e. SD is the construct under investigation.

Criticism of the dominant, rational approach to project management (PM) and its underlying hypotheses highlights a considerable PM research gap for research projects (research problem). The authors undertake a six-step constructive research approach to investigate if SD (the construct) constitutes a fruitful method to support the management of collaborative research projects. A two-part literature review summarizes known challenges in collaborative research projects and introduces the history and application of SD methodology. The work includes participatory action research (PAR) in two case studies, constituting a qualitative research method.

The authors found the SD method to be useful for structuring and analyzing intuitive project processes. However, using SD in the management of single projects presents some fundamental challenges. SD, like PM, struggles with issues related to myopic decisions, a “predict and provide” attitude with clear aspects of path dependency in the project front-end as well as inconsistent and/or missing identification of success criteria among different stakeholders.

This paper does not provide any comprehensive, normative account of scenario techniques or compare SD with other foresight and future studies methods. Although PAR is in itself a research method that demands systematic description and execution, the focus of this paper is the overall constructive research approach.

The paper offers a broadened repertoire of methods to describe and analyse project stakeholder situations (collaborative aspects) and to structure and balance the need for both rational and intuitive project processes (research aspects). The SD method also supports development of graphical storylines and facilitates the use of influence diagrams, event trees and cost/benefit analysis.

Although PM literature contains several references to SD, the practical application of SD at single-project level has, to the authors’ knowledge, never been described in the PM literature.

Amidst a growing interest in greenhouse gas (GHG) science-based target setting by businesses, it is becoming increasingly urgent to understand how these are set in theory and in practice.

Using a model framework for science-based methods, the authors compare four different science-based target-setting methods: sectoral decarbonization approach, linear emission reduction to target year, GHG emissions per unit of value added and corporate finance approach to climate stabilizing targets. Input and output variables, GHG scopes, allocation principles and mathematical formulations are described, followed by a discussion of the differences and similarities between methods.

The authors show GHG emission mitigation scenarios are as important in the determination of targets as the allocation principle.

For this reason, businesses should apply well-bellow 2ºC scenarios with robust sectoral and regional granularity and the science community should consider the needs of these groups of stakeholders.

Policymakers should actively support efforts by corporations to set science-based targets and ensure that the research they commission can be translated into practical action by non-party stakeholders.

This paper contributes to the understanding of the theory and practice of science-based targets.

The purpose of this study is to formulate exploratory scenarios of Operations Research through the critical uncertainty approach and Soft Systems Methodology.

In this study, to formulate plausible scenarios, the discipline of operation research internal and external experts’ opinions of this field have been gathered through Delphi approach and uncertainty questionnaires. After use of the most important uncertainties, plausible scenarios of operations research have been mapped with the help of experts through co-thinking workshops.

Four scenarios are presented in this study. These scenarios include Solar System, Esfandiar's Eye, Rival’s Setraps and Legendary Simurgh. Naturally, the imagination of such a unitary future for all academic communities is an expectation far from reality, and given the conditions of each of these futures or any integration of them is imaginable.

Operations Research models have been faced with variously multiple changes since its emergence until now. Investigation into the future of operations research on the necessity for his planning has not received a reasonable notice in the literature. Sporadic activities that have been carried out are also lacking in the necessary methodology. Also, there has been no research about future study using the soft Operation Research tools (Soft Systems Methodology).

The purpose of this study is to measure the predictive value of future scenarios prepared using horizon scanning. The future scenarios prepared at the initiative of the Japanese Government have had low predictive value. They have frequently failed to contribute to industrial development and caused social loss. Horizon scanning, which is a key methodology applied in foresight activities, has begun to be used in countries as part of their national innovation systems in lieu of conventional forecasting methods based on the assumption of technological innovation. Research was conducted to actually measure the predictive value of future scenarios prepared using horizon scanning.

An online survey in Japan was conducted on ordinary people’s attitudes. The questionnaires presented 20 scenarios regarding future society, which were created with the conventional method or horizon scanning method.

Survey results verified that horizon scanning-based scenarios provided significantly higher predictive value than scenarios prepared using conventional methods.

Implication 1: By eliminating bias in input data and perspectives adopted when considering scenarios, it may be expected that scenarios will be derived that have even higher “predictive value.” Implication 2: By setting the layers of anticipated outputs high and the fields broad, it may be expected that scenarios will be derived that have even greater “change.”

The relatively high rate for the predictive value of the horizon scanning method, more than 40%, validated in this study was significant.

This article proposes a strategy to make the testing step easier, generating user acceptance tests (UATs) in an automatic way from requirements artifacts.

This strategy is based on two modeling frameworks: scenarios and task/method paradigm. Scenarios are a requirement artifact used to describe business processes and requirements, and task/method paradigm is a modeling paradigm coming from the artificial intelligence field. The proposed strategy is composed of four steps. In the first step, scenarios are described through a semantic wiki website. Then scenarios are automatically translated into a task/method model (step two). In the third step, the task/method model obtained in step two is executed in order to produce and store all possible achievements of tasks and thus scenarios. The stored achievements are saved in a data structure called execution tree (ET). Finally, from this ET (step four), the UATs are generated.

The feasibility of this strategy is shown through a case study coming from the agriculture production systems field.

Generally, test design approaches deal with a small number of variables describing one specific situation where a decision table or workflow is used to design tests. The proposed approach can deal with many variables because the authors rely on scenarios that can be composed in order to obtain a tree with all the testing paths that can arise from their description.

This article aims to describe a qualitative, exploratory study with the objective of developing scenarios for the road freight transport industry in Brazil and evaluating the effectiveness of the method applied, which used the stakeholders of said industry as a means to identify the variables of the scenarios.

According to the classification scheme developed by Huss and Honton, the authors' method fits into the intuitive logics approach to scenarios, employing concepts of stakeholder analysis as proposed by Freeman. Primary data collection was conducted through key informant interviews, as outlined by Fetterman. The use of the method of intuitive logics combined with the stakeholder analysis evaluates the consistency of experts' opinions on the characteristics of stakeholders. Four environmental scenarios, distinct but equally plausible, were generated for the road freight transport industry as it was felt that more than four scenarios tends to be too complex.

The method applied produced scenarios distinctive enough to classify them as contrasting, accounting for macroenvironmental variables and variables determined by influential stakeholders in the analyzed industry. Organized and connected, these variables produced precise end states that warrant consideration in the policies and strategies of industry players. The characteristics of the scenarios produced reveal that the method was effective. The authors found the most influential stakeholders in the industry to be the government, shipping clients, end consumers, logistics service providers, and trade associations. The industry's main uncertainties are tied to how the actions of government, shippers, and logistics service providers will unfold.

Some limitations could be identified in the method. One refers to the absence of procedures to govern the chronology of events at the time of preparation of scenario plots. Another shortcoming is the third and final stage of the research; the authors observed some weakness in the method when defining a variable that is independent because it can be independent of the variables selected for the last step but dependent on others considered but not selected.

The results of the study can stimulate reflection of stakeholders on factors that will affect their decision making, stimulate understanding of the conditions for sustainability of the industry, and identify business opportunities and necessary strategic resources for the success of organizations in the future.

The transport industry plays a vital role in factors that are paramount for the economical development of a country, such as exploration of resources and mass production, and, in Brazil, road freight transport is of particular importance. The research can guide public policy in regulating and investing in industry, since the plots facilitate the understanding of the consequences of causal relationships as well as the final states resulting from these. The scenarios reveal causal relationships strongly influenced by the stakeholder “government”, especially regarding investment in infrastructure, regulation and supervision of the industry.

Application of the method proposed by Boaventura and Fischmann to the road freight transport industry generated distinct, but equally plausible scenarios. The method considered the key uncertainties as dichotomous variables. The scenarios were different since combinations of final states of the key uncertainties led to a different logic or rationale. The authors may state that this particular application contributed towards improvement of the method, as it tested the method's logic when applied to a complex environment influenced by many stakeholders.

The purpose of this paper is to present the benefits of using the Lagrangian relaxation (LR) and subgradient methods in scenario studies for wavelength division multiplexing (WDM) network planning. The problem of WDM network planning for a given set of lightpath demands in a mesh topology network is to select lightpath routes and then allocate wavelength channels to the lightpaths. In WDM network planning, a scenario study is to find out the network performance under different lightpath demands and/or different network resource configurations.

A scenario study must solve a series of related static WDM network planning problems. Each static WDM network planning problem is an optimization problem, and may be formulated as an integer linear programming problem, which can be solved by the proposed Lagrangian relaxation and subgradient methods. This paper uses the Lagrange multipliers that are obtained from previous scenarios as initial Lagrange multiplier values for other related scenarios.

This approach dramatically reduces the computation time for related scenarios. For small to medium variations of scenarios, the method reduces the computation time by several folds. The proposed method is the first method that effectively considers the relations between related scenarios, and uses such relations to improve the computation efficiency of scenario studies in WDM network planning.

The method improves the efficiency of a scenario study in WDM network planning. By using it, many “what‐if” type of scenario study questions can be answered quickly.

Unlike other existing methods that treat each scenario individually, this method effectively uses the information of the relation between different scenarios to improve the overall computation efficiency.