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Performance evaluation of airports or any other organisation is paramount for improving performance. The purpose of this paper is to evaluate and compare the performance of the three international airports in Libya (MJI, MRA, and LAQ airports) by considering five aspects of performance.

The considered aspects are airport service quality, airport operations, airport economy, safety and security, and environmental. The paper uses the grey system theory to assess these airports by summarizing the opinions of experts.

The finding of this study provides directions of the evaluated airports to take the correct actions to improve overall performance.

No literature has been found till date is to evaluate and compare the performance of the international airports in Libya.

The purpose of this paper is to propose a supplier selection method using grey system theory for a steelmaking company in Libya.

In order to tackle incompleteness and imprecision of human’s judgments, grey numbers were used. This work uses a grey-based approach to represent decision makers’ comparison judgments and extent analysis method to select the best supplier. Therefore, an example of a selection problem of a steelmaking company in Libya was used to illustrate the proposed approach.

Supplier selection in a supply chain is a critical strategic decision for company’s success and has attracted much attention of both academic scholars and decision makers. The authors have found that the Grey model can play an important role in improving supplier selection strategy, especially when it is in a situation where complex sustainability environments (i.e. Libya) exist.

No literature has been found till date for selection of supplier using grey system theory in a steelmaking company in Libya. An attempt in this regard could enhance a decision-making technique for selecting the best suppliers for the selected case company.

The purpose of this paper is to propose a site selection method using grey system theory for a desalination plant in Libya.

In order to tackle incompleteness and imprecision of human’s judgments, grey numbers were used. This work uses a grey-based approach to represent decision makers’ comparison judgments and extent analysis method to select the best site. Therefore, a real case study of a selection problem of a site selection of desalination plant in Libya was used to illustrate the proposed approach.

Site selection in a desalination plant can be one of the most important decisions in planning a desalination project. The decision affects both the project cost and potentially the project schedule. Based on the results of grey model, a clear order of these sites and the degree of preference are obtained. This paper presents a way to improve a site selection by using a grey model, especially in a complex environment like Libya.

To the best knowledge of the authors, there is no literature for site selection using grey system theory in a desalination plant in Libya. This attempt may well enhance and facilitate the decision-making process of the best site in the country involved in this research.

This paper aims to investigate the perceptions of Omani citizens toward the use of social media by the government for participatory and interactive relationships. More precisely, the descriptive nature of the study resides in its ability to explain how social media users regard the current status and levels of presence, transparency, engagement, responsiveness and trust about the current use of social media by the Omani Government.

A quantitative approach was used to collect data. This was done via a self-administered questionnaire from a return sample of 1,769 citizens drawn from different places in Oman. These citizens were considered as well-informed and regular active users of social media. The reviewed literature provided a basis for the construct of the questionnaire.

The overall results indicated modest levels of agreement in all of the investigated factors. The neutral findings suggest that there is a level of uncertainty among the respondents regarding how the government is determining the potential of social media for participatory and interactive relationships. Findings in this study advocate the outcomes of the recent Arab Social Media Report, plus the few relevant studies included in the literature, which nearly stated that although there is a growing use of social media among citizens, governments are failing to take full advantage of social media. Governments are also failing to engage citizens to design and deliver more efficient and collaborative services, per this study’s findings.

The findings call for the importance of strategically framing the use of participatory social media by the government. In a broader sense, the findings of this study are beneficial to all contexts that share similar political and socio-economic philosophy, especially the Arab states and most of the developing countries. The findings provide insights for governments in need of developing social media strategies to promote more collaborative and interactive governance.

The study aids in understanding the views of citizens who are the current major players in a highly technology-driven environment. This environment is found to be transforming the relationship between citizens and governments. The study adds knowledge to the currently scarce body of literature dealing with issues pertaining to citizen–government relationships in social media in the Arab states, and similar contexts in developing countries. Its findings may provide valuable insights for policy makers to leverage collaborative relationships between governments and citizens.

Rapid advancements in blockchain technology transform various sectors, attracting the attention of industrialists, practitioners, policymakers and academics, and profoundly affect construction businesses through smart contracts and crypto-economics. This paper explores the blockchain innovation ecosystem in construction.

Through a qualitative study of 23 diverse interviewees, the study explores how open or closed the blockchain innovation ecosystem in construction is and who its emerging orchestrators are.

The data showed that construction aims towards an open innovation blockchain ecosystem, although there are elements of hybridisation and closedness, each system pointing out to different orchestrators.

The study has implications for governments and large companies in construction, showing that open innovation initiatives need to be encouraged by policymakers through rules, regulations and government-sponsored demonstrator projects.

The data showed that there is lack of readiness for business model change to support open innovation blockchain ecosystems in construction.

This is the first study applying the open innovation theory in the construction industry and sheds light into the phenomenon of blockchain, suggesting routes for further democratisation of the technology for policymakers and practitioners.

This study aims to assess the essential elements of internal organisational capability that influence the cybersecurity effectiveness of a construction firm. An extended McKinsey 7S model is used to analyse the relationship between a construction firm's cybersecurity effectiveness and nine internal capability elements: shared values, strategy, structure, systems, staff, style, skills, relationships with third parties and regulatory compliance.

Based on a quantitative research strategy, this study collected data through a cross-sectional survey of professionals working in the construction sector in the United Kingdom (UK). The collected data was analysed using descriptive and inferential statistical methods.

The findings underlined systems, regulatory compliance, staff and third-party relationships as the most significant elements of internal organisational capability influencing a construction firm's cybersecurity effectiveness, organised in order of importance.

Future research possibilities are proposed including the extension of the proposed diagnostic model to consider additional external factors, examining it under varying industrial relationship conditions and developing a dynamic framework that helps improve cybersecurity capability levels while overseeing execution outcomes to ensure success.

The extended McKinsey 7S model can be used as a diagnostic tool to assess the organisation's internal capabilities and evaluate the effectiveness of implemented changes. This can provide specific ways for construction firms to enhance their cybersecurity effectiveness.

This study contributes to the field of cybersecurity in the construction industry by empirically assessing the effectiveness of cybersecurity in UK construction firms using an extended McKinsey 7S model. The study highlights the importance of two additional elements, third-party relationships and construction firm regulatory compliance, which were overlooked in the original McKinsey 7S model. By utilising this model, the study develops a concise research model of essential elements of internal organisational capability that influence cybersecurity effectiveness in construction firms.

In an ever-interconnected world dominated by discourses on the internationalization and marketization of higher education, concerns related to language and employability have been the focus of recent debates. There is, however, a dearth of research investigating how these dimensions relate to one another in recent comparative and international higher education research. By focusing on how issues related to language and employability have been presented in recent higher education research worldwide, this chapter aims to contribute to our understanding of this concern. To achieve this goal, we conducted a scoping literature review using the Web of Science, Scopus, and the Education Resources Information Center (ERIC) databases, considering the years 2011–2020. The findings, perhaps not surprisingly, suggested that language skills are perceived to be valued by both graduates and employers though the discussions predominantly focused on one language, English. The research focus on English for employability in Anglophone contexts is understandable. However, the fact that the trend is observed in contexts where the language is not the primary or official language seems to indicate the influence of internationalization of higher education and global labor markets primarily dominated by English. The literature also suggested that (English) language training in higher education programs needs to move from solely linguistic and qualification-related content areas to a broader sphere of English for communication purposes that cover both specialized disciplinary content and broader generic employability skills. Considering this finding, we suggest that higher education systems and institutions incorporate recent developments in English for occupational purposes in their curriculum. We also recommend that there needs to be a shift from the overwhelmingly English language-dominated discussions to more inclusive research that assesses the impact of other dominant languages on employability-related concerns.

Smart grid is an integration between traditional electricity grid and communication systems and networks. Providing reliable services and functions is a critical challenge for the success and diffusion of smart grids that needs to be addressed. The purpose of this study is to determine the critical criteria that affect smart grid reliability from the perspective of users and investigate the role big data plays in smart grid reliability.

This study presents a model to investigate and identify criteria that influence smart grid reliability from the perspective of users. The model consists of 12 sub-criteria covering big data management, communication system and system characteristics aspects. Multi-criteria decision-making approach is applied to analyze data and prioritize the criteria using the fuzzy analytic hierarchy process based on the triangular fuzzy numbers. Data was collected from 16 experts in the fields of smart grid and Internet of things.

The results show that the “Big Data Management” criterion has a significant impact on smart grid reliability followed by the “System Characteristics” criterion. The “Data Analytics” and the “Data Visualization” were ranked as the most influential sub-criteria on smart grid reliability. Moreover, sensitivity analysis has been applied to investigate the stability and robustness of results. The findings of this paper provide useful implications for academicians, engineers, policymakers and many other smart grid stakeholders.

The users are not expected to actively participate in smart grid and its services without understanding their perceptions on smart grid reliability. Very few works have studied smart grid reliability from the perspective of users. This study attempts to fill this considerable gap in literature by proposing a fuzzy model to prioritize smart grid reliability criteria.

The model and existing practice of the construction supply chain (CSC) in the United Kingdom (UK) and Australia was presented in this chapter. The policies and reports that support the practice of the CSC were examined in both countries. It was discovered from the review of literature that the UK has a more detailed report targeted at improving the CSC than Australia. However, both countries have a common factor affecting their CSC which originates from fragmentation experienced within their supply chain. Construction stakeholders in the UK and Australia believe that collaboration and integration are vital components for improving performance. The majority of the contractors in both countries embrace collaborative working for the sole purpose of risk sharing, access to innovation and response to market efficiency. However, most of the models developed for managing the CSC in the UK are built around building information modelling (BIM). Also, the reviewed studies show that supply chain management practice will be effective following the following principle: shared objectives, trust, reduction in a blame culture, joint working, enhanced communication and information-sharing. Finally, the UK has a more established framework and more CSC models compared to Australia.

This paper develops a decision-analysis model to prioritize and select the site to establish a new hospital over different indicators such as cost, market conditions, environmental factors, government factors, locations and demographics. In this way, an integrated model is proposed under the intuitionistic fuzzy information (IFI), the standard deviation (SD), the rank-sum (RS) and the measurement of alternatives and ranking using the compromise solution (MARCOS) approach for ranking hospital sites (HSs).

The IF-SD-RS model is presented to obtain the combined weight with the objective and subjective weights of diverse sub-criteria and indicators for ranking sites to establish the hospital. The IF-MARCOS model is discussed to prioritize the various sites to establish the hospital over several crucial indicators and sub-criteria.

The authors implement the developed model on a case study of HSs assessment for the construction of new hospital. In this regard, inclusive set of 6 key indicators and 18 sub-criteria are considered for the evaluation of HSs. This study distinguished that HS (h₂) with combined utility function 0.737 achieves highest rank compared to the other three sites for the given information. Sensitivity analysis is discussed with different parameter values of sub-criteria to examine how changes in weight parameter ratings of the sub-criteria affect the prioritization of the options. Finally, comparative discussion is made with the diverse extant models to show the reasonability of the developed method.

This study aims to develop an original hybrid weighting tool called the IF-SD-RS model with the integration of IF-SD and IF-RS approaches to find the indicators' weights for prioritizing HSs. The developed integrated weighting model provides objective weight by IF-SD and subjective weight with the IF-RS model. The model presented in the paper deals with a consistent multi-attribute decision analysis (MADA) concerning the relations between indicators and sub-criteria for choosing the appropriate options using the developed IF-SD-RS-MARCOS model.