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Like several of its neighbouring countries, the Kingdom of Saudi Arabia (KSA) has seen a move away from an oil-based economy towards a knowledge-based economy in recent decades. Research productivity in the Kingdom is increasing quickly along with international collaborations. Nonetheless, postgraduate research at universities in KSA is a relatively young domain, which certainly is a core factor in the evolving research management structures in the country.

Going forward, increased openness in research, along with continuing significant investment into higher education and research both by the government and the strong private sector points to a need for refined research governance and policy frameworks with designated expert research management staff developing and facilitating the underlying processes to enable Saudi institutions to engage at the forefront of academic research.

This chapter provides an overview of the potential use of Intelligent Transport Systems (ITS) and associated artificial intelligence (AI) techniques in the land transport sector in an attempt to achieve related United Nations Sustainable Development Goals (SDGs) targets. ITS applications that have now been extensively tested worldwide and have become part of the everyday transport toolkit available to practitioners have been discussed. AI techniques applied successfully in specific ITS applications such as automatic traffic control systems, real-time image processing, automatic incident detection, safety management, road condition assessment, asset management and traffic enforcement systems have been identified. These methods have helped to provide traffic engineers and transport planners with novel ways to improve safety, mobility, accessibility and efficiency in the sector and thus move closer to achieving the various SDG targets pertaining to transportation.

Many European businesses are small and medium enterprises (SMEs), contributing significantly to the well-being of local economies and regions. Even so, SMEs face many challenges in fostering innovation and improving performance. Furthermore, the raw material consumption is increasing globally, necessitating the development of strategies that will reduce the number of raw materials extracted and imported while improving the sustainability of small and medium-sized businesses. Consequently, promoting circular economy (CE) strategies, such as industrial symbiosis (IS) partnerships, whereby waste products from other industries serve as a source of raw materials for companies, is critical. Identifying and analysing enablers or drivers that support IS collaborations among SMEs is necessary to achieve this goal. In this regard, the purpose of this study will explore the enablers of IS among SMEs considering sustainability dimensions (environmental, social and economic). As facing a decision-making (DM) problem, the multiple attribute decision-making (MADM) approach was applied in a hesitant fuzzy (HF) environment in this research to answer the research questions. In this regard, in phase 1, IS enablers were identified and extracted using a literature review and experts’ opinions. In phase 2, the hesitant fuzzy Delphi (HFD) method was implemented to screen and finalise the enablers identified. In phase 3, casual relations among final enablers were determined using the hesitant fuzzy ANP (HF-ANP) method. Finally, in phase 4, the relative importance of enablers was calculated using the hesitant fuzzy best–worst method (HF-BWM). Consequently, this study provided potential strategies for IS that can be implemented quickly and used by local authorities to support SMEs in achieving circular waste management.

This chapter focusses on analysing the origins and evolution of the SWOT analysis. It explains the drivers and limitations of the conventional SWOT analysis, laying the groundwork for new decision-making models that can aid researchers and practitioners in comprehending both the external landscape and the internal characteristics of a company. This chapter demonstrates how the strengths, weaknesses, opportunities, and threats of the SWOT analysis can be approached dynamically. Conventional SWOT analysis offers only a limited perspective on the environment and employs terminology that can confuse users, hindering their clear understanding of the factors that influence an organisation’s situation. This chapter provides a concise literature review of tools for evaluating quality management, its resources, and the surrounding environment, which serves as a valuable means to grasp the economic and social context within which a firm operates.

Purpose: The main goal of this discussion is to explain how competitiveness could be an important source of knowledge and economic power in a society, especially in the period of higher demands on knowledge, innovation and organisational base growth. Our focus of the discussion will be tourism as an important service sector economic activity in countries all over the world.

Methodology: The chapter will be conceptually based on its goal to develop the theories of competitiveness and to discuss how competitiveness influences knowledge, organisational processes and forms with a focus on tourism services.

Findings: Competitiveness in tourism depends on many factors. As an intangible source of knowledge, organisational culture processes and organisational forms generally influences tourism activity. For this reason, not only is comparative advantage important in the competitiveness concept, but also competitive advantage and the way of deploying resources play an important role.

Significance: Resources are not only based on labour, capital and land (neoclassical theory approach), but resource-advantage theory underlines the importance of financial, physical, legal, human, organisational, informational and relational capital. In this process, new processes and organisational forms must be created, as well as innovative approaches to processes and the importance of knowledge capital.

Practical Implications: New ideas about this process could be helpful for researchers and practitioners to recognise the importance of competitiveness for their work and research.

Adsorption parameters (e.g. Langmuir constant, mass transfer coefficient and Thomas rate constant) are involved in the design of aqueous-media adsorption treatment units. However, the classic approach to estimating such parameters is perceived to be imprecise. Herein, the essential features and performances of the ant colony, bee colony and elephant herd optimisation approaches are introduced to the experimental chemist and chemical engineer engaged in adsorption research for aqueous systems. Key research and development directions, believed to harness these algorithms for real-scale water treatment (which falls within the wide-ranging coverage of the Sustainable Development Goal 6 (SDG 6) ‘Clean Water and Sanitation for All’), are also proposed. The ant colony, bee colony and elephant herd optimisations have higher precision and accuracy, and are particularly efficient in finding the global optimum solution. It is hoped that the discussions can stimulate both the experimental chemist and chemical engineer to delineate the progress achieved so far and collaborate further to devise strategies for integrating these intelligent optimisations in the design and operation of real multicomponent multi-complexity adsorption systems for water purification.

The decision to become international is a highlighted organisational decision that affects all dimensions at all firm levels. Human resources are also among the parts of the organisation affected by this decision. Paying attention to employees can speed up and facilitate this process. Organisational integrity is one of the most significant issues that must be considered. In this regard, identifying, investigating and planning to deal with the destructive effects that may influence the employees of small and medium-sized enterprise (SMEs) in internationalisation, are among the subjects that have so far received less attention and should be studied more. The present study explores the destructive influences of internationalisation on the employees of SMEs by a hybrid multi-layer decision-making model-psychological solution. First, by reviewing the literature, the destructive impacts of internationalisation on employees are extracted. In the next stage, these factors are screened according to the condition of the SMEs in an emerging economy by interval-valued intuitionistic hesitant fuzzy Delphi (IVIHF-Delphi). The impact of these factors on each other is then evaluated applying interval-valued intuitionistic hesitant fuzzy DEMATEL-based ANP (IVIHF-DANP). Consequently, the highlighted destructive impacts are determined and the psychological solutions to face them are provided.