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The chapter describes the basics of developed high-level spatial grasp technology (SGT) and its spatial grasp language (SGL) allowing us to create and manage very large distributed systems in physical, virtual and executive domains in a highly parallel manner and without any centralized resources. Main features of SGT with its self-evolving and self-spreading spatial intelligence, recursive nature of SGL and organization of its networked interpreter will be briefed. Numerous interpreter copies can be installed worldwide and integrated with other systems or operate autonomously and collectively in critical situations. Relation of SGT, with capability of holistic solutions in distributed systems, to the gestalt psychology and theory, showing unique qualities of human mind and brain to directly grasp the whole of different phenomena, will be explained too, with SGT serving as an attempt to implement the notion of gestalt for distributed applications.

Promoting low-carbon in the construction industry is important for achieving the overall low-carbon goals. Public–private partnership is very popular in public infrastructure projects. However, different perceptions of low-carbon and behaviors of public and private sectors can hinder the realization of low-carbon in these projects. In order to analyze the willingness of each stakeholder to cooperate towards low-carbon goals, an evolutionary game model is constructed.

An evolutionary game model that considers the opportunistic behavior of the participants is developed. The evolutionary stable strategies (ESSs) under different scenarios are examined, and the factors that influence the willingness to cooperate between the government and private investors are investigated.

The results illustrate that a well-designed system of profit distribution and subsidies can enhance collaboration. Excessive subsidies have negative impact on cooperation between the two sides, because these two sides can weaken income distribution and lead to the free-riding behavior of the government. Under the situation of two ESSs, there is also an optimal revenue distribution coefficient that maximizes the probability of cooperation. With the introduction of supervision and punishment mechanism, the opportunistic behavior of private investors is effectively constrained.

An evolutionary game model is developed to explore the cooperation between the public sector and the private sector in the field of low-carbon construction. Based on the analysis of the model, this paper summarizes the conditions and strategies that can enable the two sectors to cooperate.

This paper seeks to discuss the process and results of a scenario exercise applied to the Portuguese tourism and hospitality industries with a 2020 horizon.

Through an intuitive‐logical process adapted to the specific purposes of the research, four alternative scenarios of the evolution of the industry were developed. The exercise involved three workshops, with the participation of a group of experts, academics, representatives from industry and local government.

Based on the nature and dynamics of the key forces and trends, the four scenarios identified are: southern experience; global emotions; “sin surprise”; and non‐charming Portugal. In all scenarios there is increased global competition amongst tourist destinations. A desire for authenticity opens the opportunity for Portugal as a tourist destination but it also poses challenges for managers and policy makers. These scenarios are of practical use for managers, policy makers and other practitioners as they provide a framework for the development and assessment of robust strategies and policies, i.e. strategies that will survive several kinds of external development.

The paper contributes to the knowledge of scenario methods in practice and to help policy planners and managers recognize, consider and reflect on uncertainties they are likely to face. The work is also valuable for the international foresight community by discussing the method and addressing some drawbacks of the scenario exercise and recommendations for practice.

This chapter provides a brief overview of the need to study sustainable futures. It provides an outline of the importance of inventing futures in the third decade of the twenty-first century. It offers conceptual tools for building sustainable futures scenarios and discusses the importance of long-term thinking in business, government and society. This chapter is divided into four sections. Section One presents the opportunities to invent futures and the role of long-term scenarios. Section Two describes the contest for reimagination and the reinvention of futures. Section Three provides the historic background of the evolution of scenario methodology. Section Four offers a concise introduction to futures studies and futurology. Finally, a short preamble on the empirical research on Sustainable Futures for Latin America and the Caribbean considers climate change.

The purpose of this paper is to create ways of improving the alignment of strategy formulation and implementation in Brazil’s higher education institutions (HEIs).

Evolution of scenarios and models through a 12-step process to assist strategy formulation and implementation for managerial/social activity in Brazil’s HEIs. Simple set theory was used as a backbone to assist scenario building. Two models were created. First, focused on an autopoietic model relating to Brazil’s HEIs. The second embedded the autopoietic model in a limited number of forces in Brazil that influence the HEIs but lie beyond their control. The process was corroborated by survey methods using respondents from Brazil and elsewhere.

In total, 22 respondents from within and outside Brazil confirmed the content of the scenarios while a small sample from within Brazil’s HEIs confirmed their usefulness in assisting strategy formulation and implementation.

Further experience in using the autopoietic model is needed to widen its corroboration beyond experience in this study.

Confirmation of a 12-step scenario-based process for strategy formulation and implementation and corroboration of its usefulness through a limited sample of respondents.

The purpose of this paper is to understand how the unfolding diet transformation in East and Southern Africa is likely to influence the evolution of employment within its agrifood system (AFS) and between that system and the rest of the economy. To briefly consider implications for education and skill acquisition.

The authors link changing diets to employment structure. The authors then use alternative projections of diet change over 15- and 30-year intervals to develop scenarios on changes in employment structure.

As long as incomes in ESA continue to rise at levels near those of the past decade, the transformation of their economies is likely to advance dramatically. Key features will be: sharp decline in the share of the workforce engaged in farming even as absolute numbers rise modestly, sharp increase in the share engaged in non-farm segments of the AFS, and an even sharper increase in the share engaged outside the AFS. Within the AFS, food preparation away from home is likely to grow most rapidly, followed by food manufacturing, and finally by marketing, transport, and other AFS services. Resource booms in Mozambique and (potentially) Tanzania are the main factor that may change this pattern.

Clarifying policy implications requires renewed research given the rapid changes in Africa over the past 15 years.

This is the first paper to explicitly link changing diets to changing employment within the AFS.

Among the Somalis living in the diaspora, there is a growing number that are returning or are interested in returning to Somalia for personal, economic and political reasons. The purpose of this paper is to examine the potential impact the diaspora has on the future of Somalia by understanding the anticipatory assumptions held by young Somali-Canadians. This research will also examine the role that Soomaalinimo [1] (Somali identity) plays in the transnational ties that diasporic individuals keep with their country and its people.

Using an indigenist research approach, this paper explores the evolution of Soomaalinimo over time in a way that is culturally informed and decolonial. Young Somali-Canadians in two cities (Toronto and Edmonton) were given an opportunity to define Soomaalinimo for themselves and create scenarios of how it might evolve in the future for their great-grandchildren. An analysis of these scenarios reveals anticipatory assumptions that shape how they think about the future.

Three distinct futures scenarios emerged, and this research revealed three key anticipatory assumptions held by the participants: Somalia will always be home; returning to Somalia is important to maintain Soomaalinimo; and it is the responsibility of the previous generations to transmit Soomaalinimo to future generations. These anticipatory assumptions are examined and an analysis of the implications on decolonizing futures is presented.

This study expands the conceptualization of the future of a country to include the diaspora and uses the concept of anticipatory assumptions to reveal some of the potential implications of this group.

The purpose of this paper is to propose a graph-based representation approach for evolutionary knowledge under the big data circumstance, aiming to gradually build conceptual models from data.

A semantic data model named meaning graph (MGraph) is introduced to represent knowledge concepts to organize the knowledge instances in a graph-based knowledge base. MGraph uses directed acyclic graph–like types as concept schemas to specify the structural features of knowledge with intention variety. It also proposes several specialization mechanisms to enable knowledge evolution. Based on MGraph, a paradigm is introduced to model the evolutionary concept schemas, and a scenario on video semantics modeling is introduced in detail.

MGraph is fit for the evolution features of representing knowledge from big data and lays the foundation for building a knowledge base under the big data circumstance.

The representation approach based on MGraph can effectively and coherently address the major issues of evolutionary knowledge from big data. The new approach is promising in building a big knowledge base.

The chapter offers complete details of the latest SGL version particularly suitable for dealing with large security systems and emerging crisis situations. It describes main types of constants representing information, physical matter or both and five very different and specific types of variables operating in fully distributed spaces and even being mobile themselves when serving spreading algorithms. Also given full repertoire of the language operations, called rules, which can be arbitrarily nested and carry different navigation, creation, processing, assignment, control, verification, context, exchange, transference, echoing, timing and other loads. The rules equally operate with local and remote values, process both, matter and distributed networked knowledge, and can express active graph-based patterns navigating, matching, conquering and changing distributed environments. Elementary programming examples in SGL are also provided.