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The aim of this article is to present a framework of the influencing factors in the land registration system in the Kingdom of Saudi Arabia. The framework is mainly developed to enhance the stockholders’ trust in purchasing properties. This framework is developed by reviewing the challenges in the land registration systems and identifying the factors that capture from socio-technical elements derived from the literature, interview with investors, and then validated by an expert review. The study applies a qualitative methodology that involves semi-structured interviews, and a thematic method to analysis the collected data to pursue the intended aim. The article suggests a social trust framework for the land registration system which enhances the trust in the provided information by mitigating the challenges in the current system. The findings also indicate that appropriate use of technology such as smart contracts and blockchain would reach the aim of the study.

The evolution of an Internet of Things-enabled Smart Grid affords better automation, communication, monitoring, and control of electricity consumption. It is now essential to supply and transmit the data required, to achieve better sensing, more accurate control, wider information communication and sharing, and more rational decision-making. However, the rapid growth in connected entities, accompanied by the increased demand for electricity, has resulted in several challenges to be addressed. One of these is securing the energy information exchange proactively, before an incident occurs. It is argued that Smart Grid systems were designed without any regard for security, which is considered a serious omission, especially for data security, energy information exchange, and the privacy of both the consumers and utility companies. This research is motivated by the gap identified in the requirements and controls for maintaining cybersecurity in the bi-directional data flow within the IoT-enabled Smart Grid. The Threat Modelling identified 9 internet-based threats. This research develops and confirms a security model which includes 45 relevant security controls and 7 security requirements on 7 access points. For future work, the confirmed model will be verified and validated using formal modelling methods.

The recent diagnosis of COVID-19 is based on real-time reverse-transcriptase polymerase chain reaction (RT-PCR) and is regarded as the gold standard for confirmation of infection. It has already been widely recognized that deep learning techniques can potentially have a substantial role in streamlining and accelerating the diagnosis of COVID-19 patients. Numerous open dataset enterprises have been set up over the past weeks to help the researchers develop and check methods that could contribute to countering the Corona pandemic. In order to report the above unique problems in the diagnosis of COVID-19, pioneering techniques should be developed. This special issue focuses on novel deep learning imaging analysis techniques related to COVID-19.

The growth of online retailing has exceeded expectations over the last few years. This has resulted in high product return rates, which retailers are struggling with due to complex and costly returns processing, logistics, and financial implications. Additionally, online returns come with increased opportunities for returns fraud. During the pandemic, new types of returns fraud have emerged and returns fraud rates have increased across all channels. Based on a series of semi-structured interviews with retailers and retail experts, we investigate factors that enable fraudulent returns from consumers' and retailers’ perspectives and outline strategies for retailers to combat product returns fraud in a multichannel environment, leading to a framework for retail fraud. We contribute critical insights to research and practices on understanding and addressing a growing problem that has economic, social and environmental implications.

Forensic readiness is important to ensure that the organization is fully prepared and well-equipped to be forensically ready to conduct the digital forensic investigation. Moreover, forensic readiness in IoT forensic investigation is different from the usual computer forensic readiness. This research discovered the importance of having the forensic readiness in place for the organization before conducting the IoT forensic investigation. Therefore, a readiness framework was proposed as a groundwork before further research is carried out. Literature on related this issues was collected, examined and criticized in order to scrutinize the impact factors in IoT forensics investigations. Finally, the proposed framework was validated by thirty experts from digital forensics in Malaysia using triangulation methods. From the results, this framework will be used in developing an instruments to measure readiness factors among digital forensics stakeholders.

The urban mobility landscape is evolving at an amazing rate, with the number of mobility services growing rapidly around the world. This evolution has brought about the concept of Mobility-as-a-Service (MaaS) in providing transportation services. MaaS capitalises on the Internet of Things to provide access to seamless multi- and inter-modal mobility to the end-user. A well implemented MaaS scheme involves many stakeholders, including passengers, producing, sharing, and consuming (personal) data. In order to encourage MaaS uptake in the general population, participating stakeholders must be confident of the ensuing data privacy and security, as part of their interactions with the system. In this paper, we use STRIDE Threat Modeling framework to analyse the threats that may arise in a MaaS ecosystem. From these threats, we develop mitigations that can be used to eliminate and/or reduce such threats. This threat elicitation and their accompanying mitigations can be used as springboards to establish the necessary security to engender trust in MaaS usage.

The combination of our need for efficient mobility systems coupled with cyber-physical systems has brought about the evolution of Mobility-as-a-Service (MaaS), integrating transport services to provide one-stop access through a custom interface. Our interactions with these MaaS systems lead to a surfeit of data generation and consumption. And for MaaS growth to be sustained, users' trust in the system, especially in their data privacy, needs to be addressed. In this paper, we use LINDDUN privacy analysis framework to elicit privacy requirements of MaaS systems. We show how User-Dependent Analysis, i.e. modularizing complete use cases to different usage contexts and analysing these usages, can help guide us to discern that usage's privacy requirements, which can be enacted by relevant MaaS participants.

This paper describes the process of developing a framework and an instrument for measuring and ascertaining the openness of a system applicable to system architectures and their implementations. An Open System is a system whose architecture uses standards for its key interfaces, where these standards are widely used, consensus based, published and maintained by recognised industry standards' organisations, and its systems design is modular, i.e. each module has minimal dependencies on other modules, and has been subjected to successful confirmation that ensure the openness of its key interfaces. Our process included in-depth review of pertinent literature in the areas of Open Systems and Open Architecture, followed by a selection of the appropriate methodology to use. We chose the Goal-Question-Metric (GQM) methodology to allow us to select relevant goals, factors and metrics that can be used to measure a system's level of openness. The paper details these goals, factors and metrics. We carried out studies of these factors with fourteen experts in Open Systems Engineering: an initial study with seven of these experts to help us refine the selected goals, factors and metric, with a second confirmatory study performed in conjunction with the remaining seven experts. The GQM methodology enabled us to select appropriate goals and factors that can affect system openness, especially in the Maritime industry. These factors are both technical and non-technical, and they are: (a) the prevailing culture of the organisation developing and/or hosting the system, (b) the prevailing culture of the employees of that organisation, (c) the system architecture produced as a result of the prevailing culture, (d) the system interfaces, (e) system design, (f) the degree of openness of the data used by the system, and (g) system implementation. The process provided a structure that we used to generate the relevant questions of these goals and the metrics that can be used to measure the degree of openness of the goals. The goals, questions and metrics are detailed in the Appendices.

There has been significant innovation in the domain of Internet of Things (IoT) as nowadays wireless data transmission is playing an essential role in various organizations like agriculture, defence, transportation, etc. Batteries are the most common option to power wireless devices. However, using batteries to power IoT devices has drawbacks including the cost and disruption of frequent battery replacement, and environmental concerns about battery disposal. Solar energy harvesting is a promising solution for long-term operation applications. However, solar energy harvesting varies drastically over location and time. Due to fluctuating weather conditions and the environmental effects on PV surface condition, output could be reduced and become insufficient. Environmental conditions including temperature, wind, solar irradiance, humidity, tilt angle and the dust accumulated over time on the photovoltaic (PV) module surface affects the amount of energy harvested. To address this issue, a novel solution is required to autonomously predict the harvested energy and plan the IoT device tasks accordingly, to enhance its performance and lifetime. Using Machine Learning (ML) algorithms could make it possible to predict how much energy can be harvested using weather forecast data. This research is ongoing, and aims to apply ML algorithms on historical weather data including environmental factors to generate solar energy predictions for IoT device energy budget planning.

PurposeThe purpose of this paper is to validate a framework for spatial representation, aka the spatial representation framework (SRF), to define spaces and building information required by people with visual impairment as a foundation of indoor maps for indoor navigation systems.Design/methodology/approachThe SRF was first created with seven main components by a review of the relevant literature and state-of-the-art technologies shown in the preliminary study. This research comprised of two tasks: investigating problems and behaviors while accessing spaces and buildings by visually impaired people (VIP) and validating the SRF where 45 participants were recruited (30 VIP and 15 experts).FindingsThe findings revealed a list of problems and challenges were used to validate and redefine the spatial representation, which was validated by both VIP and experts. The framework subsequently consisted of 11 components categorized into five layers, each layer of which is responsible for a different function.Research limitations/implicationsThis framework provides essential components required for building standard indoor maps as a foundation for indoor navigations systems for people with visual impairment.Practical implicationsThis framework lays the foundation for a range of indoor-based applications by using this SRF to represent indoor spaces. Example applications include: indoor navigation by people with disabilities, robots and autonomous systems, security and surveillance, and context and spatial awareness.Originality/valueThis paper presents the validated spatial representation for indoor navigation by people with visual impairment with its details and description, methodology, results and findings of the validation of the SRF.

Flow cytometry (FCM) involves the use of optical and fluorescence measurements of the characteristics of individual biological cells, typically in blood samples. It is a widely used standard method of analysing blood samples for the purpose of identifying and quantifying the different types of cells in the sample, the result of which are used in medical diagnoses. The multidimensional dataset obtained from FCM is large and complex, so it is difficult and time-consuming to analyse manually. The main process of differentiation and therefore labelling of the populations in the data which represent types of cells is referred to as Gating: Gating is the first step of FCM data analysis and highly subjective. Significant amounts of research have focussed on reducing this subjectivity, however a faster standard gating technique is still needed. Existing automated gating techniques are time-consuming or need many user-defined parameters which affect the differentiation to different clustering results. This paper presents and discusses FLOPTICS: A novel automated gating technique that is a combination of density-based and grid-based clustering algorithms. FLOPTICS has an ability to classify cells on FCM data faster and with fewer user-defined parameters than many state-of-the-art techniques, such as FlowGrid, FlowPeaks, and FLOCK.

The Large-scale natural and man-made hazards and disasters sometimes triggered and/or encouraged by regional conflicts, climate change, or migration are growing in intensity and frequency. These disasters, affecting thousands of homes and lives, have consequences for national security and defense. Adequate preparation, response and recovery are required to manage the effects of such large-scale disasters. With many organisations involved in their handling, often times crossing regional and national borders, information exchange is crucial in order to help save lives and properties. Very often, this information exchange is cumbersome and difficult due to differing vocabularies, semantics and representations at the human language, systems and data levels. This paper describes HERO, the Hazard and Emergency Response Ontology, a vocabulary used to describe hazards, either emerging, existing or ones that might have happened. Having a common vocabulary to describe hazards will give emergency management officials a common language (or a common set of terms) to describe an event, a disaster, or a hazard, making the information exchange between differing political and social boundaries easier, more efficient and more effective. We describe how we have made use of HERO to help us to model migration hazard data. We end with lessons learnt and conclusions.

Purpose The purpose of this paper is to create a building rating system (BRS) with its bottom-up design model that can be carried out manually and in the future automatically. Design/methodology/approach The BRS is built on the basis of the structure of spatial representation framework for indoor navigation by people with visual impairment, which was validated with visually impaired people, and incorporated with building design standards and regulations from around the world. The BRS was afterwards validated by three groups of five experts in the related fields such as research and development, accessibility, and building and interior designs. Finally, the user evaluation was carried out by three focus groups of three experts in risk assessment to verify the usability of the system. Findings This paper provides the design and methodology of the BRS used for classifying the accessibility in buildings into four levels of classification for people with visual impairment navigating around the buildings. This system is evaluated with system usability scales (SUS), which is found to be in a “Good” level on average (72.2 SUS scores). Research limitations/implications Success criteria used in the space classification are mainly created for people with visual impairment at this stage; other disabilities requirements must be taken into account for the next stage of the development. Practical implications The system can be carried out in the future automatically in the form of standalone software or plugins that can be integrated in buildings and interior design software to seek recommendations toward a creation of inclusive built environment. Originality/value This paper presents a design architecture of BRS with its details, description and success criteria used in the space classification.

Cloud computing has drastically altered the ways in which it is possible to deliver information technologies (ITs) to consumers as a service. In addition, the concept has given rise to multiple benefits for consumers and organizations. However, such a fast surge in the adoption of cloud computing has led to the emergence of the cloud as a new cybercrime environment, thus giving rise to fresh legal, technical and organizational challenges. In addition to the vast number of attacks that have had an impact on cloud computing and the fact that cloud-based data processing is carried out in a decentralized manner, many other concerns have been noted. Among these concerns are how to conduct a thorough digital investigation in cloud environments and how to be prepared to gather data ahead of time before the occurrence of an incident; indeed, this kind of preparation would reduce the amount of money, time and effort that is expended. As a number of cloud forensics challenges have not received enough attention, this study is motivated by a particular gap in research on the technical, legal and organizational factors that facilitate forensic readiness in organizations that utilize an Infrastructure as a Service (IaaS) model. This paper presents a framework with which to investigate the factors that facilitate the forensic readiness of organizations. This framework was identified by critically reviewing previous studies in the literature and by performing an in-depth examination of the relevant industrial standards. The factors were comprehensively studied and extracted from the literature; then, the factors were analysed, duplicates were removed, and the factors were categorized and synthesized to produce the framework. To obtain reliable results, the research method involved two steps: a literature review, followed by expert reviews. These techniques help us paint a comprehensive picture of the research topic and validate and confirm the results.

Zlto(zlah-toh) is a project to provide secure validation of credentials for young people. Many African youth find it difficult to obtain jobs because of a lack of formal qualification, but they have a breath of informal skills. In this paper we will describe how we implement the Zlto system to provide proof of skills completed through a peer-to-peer evaluation mechanism and stored using blockchain. Since its first deployment in 2016, Zlto has processed over 1 million transactions. We present simulation and analysis of the reputation protocol used to verify work, and further evaluate the peer review process using a think a loud focus group method with a group of peer reviewers in order to improve the system.

In spite of the unprecedented popularity to use innovative gaming concepts within the educational context in order to promote active learning, engage people and solve motivational problems, there is an emerging body of research work arguing that gamification is not effective to increase neither the students engagement nor the learning outcomes. In this research paper, an empirical study is conducted to explore how gamification can firstly affect the student learning engagement and the interactivity level with e-learning technologies. Secondly, whether it can be considered as a driving thrust to support sustained learning. A question board is designed and implemented to enable students ask and answer questions related to their taught modules where academic staff can also contribute and validate the most correct answers. The acquisition of data is performed through a period of 10 months in order to investigate the gamification impact over time. The gamified platform was integrated with the online e-learning portal of a university where the adoption of e-learning is considered extremely poor. The obtained results have revealed that gamification can be considered as a valuable tool to entice users for the uptake of educational systems and increase their interactivity and engagement.

A lot of visually impaired people have suffered from being left out of the activities that can discourage them from going out for any social activities and interactions, which are usually related to navigation. Regardless outdoors, travelling inside public spaces are a different story as many environmental cues cannot be used and have their own set of difficulties. Some technologies have come into play helping these people to have freedom in navigation (e.g., accessible map, indoor navigation systems, wearable computing devices, etc.). However, technologies like accessible maps or indoor navigation system are insufficient to fulfill the independent navigation gap due to additional information is required (obstacles, barriers, and accessibility). To promote the indoor navigation and create better use of technologies for visually impaired people, it is essential to understand the facts, and actual problems that they experience, and what behaviors and strategies they use to overcome any problems, which apparently led to this study. 30 visually impaired people and 15 experts were recruited and asked to give interviews regarding the behaviors, strategies, and challenges found with indoor navigation, especially public spaces e.g., universities, hospitals, malls, museums, and airports. The findings from this present study reveal that navigating inside buildings and public spaces full of unfamiliar features is too difficult to attempt the first time for a number of reasons, reducing their confidence in independent navigation.

Organisations are moving over from legacy telecommunications to Voice over IP (VoIP), enabling greater flexibility, resilience and an overall cost reduction. Session Initiated Protocol (SIP) is considered to be the main VoIP protocol in the business–to-business market, but the correct implementation and configuration is not always well- understood. The failure to configure SIP systems correctly has led to significant fraud exploiting a range of vulnerabilities and billions of dollars every year being stolen from companies of all sizes through PBX Hacking via the medium of Toll Fraud. Previous research into this area is now dated but suggested fast-changing approaches by attackers. Industry organisations such as the Communications Fraud Control Association (CFCA) acknowledged this is a fast-growing problem. To quantify the size of the current problem, a Honeypot experiment was undertaken using a popular phone system used by businesses. The Honeypot ran for 10 days and recorded just under 19 million SIP messages. This research has identified attackers are using various sophisticated methods to attempt to gain access and trick a PBX into making calls. When comparing previous research, the rate of attack is approximately 30 times more aggressive and the countries from where attacks originate are distributed over 75 countries.

SWOT analysis, a commonly used tool for strategic planning, is traditionally a form of brainstorming. Hence, it has been criticised that it is likely to hold subjective views of the individuals who participate in a brainstorming session and that SWOT factors are not prioritized by their significance thus it may result in an improper strategic action. While most studies of SWOT analysis have only focused on solving these shortcomings separately, this study offers an approach to diminish both shortcomings by applying Importance-Performance Analysis (IPA) to identify SWOT based on customer satisfaction surveys which produces prioritized SWOT corresponding to the customers’ perception. Through the use of IPA based SWOT analysis, it is expected that a organisation can efficiently formulate strategic planning as the SWOT factors that should be maintained or improved can be clearly identified based on customers’ viewpoints. The application of the IPA based SWOT analysis was illustrated and evaluated through a case study of Higher Education Institutions in Thailand. The evaluation results showed that SWOT analysis of the case study accurately reflected the organisation's situations thereby demonstrating the validity of this study.

The Internet of Things (IoT) is becoming the future of the Internet with a large number of connected devices that are predicted to reach about 50 billion by 2020. With proliferation of IoT devices and need to increase information sharing in IoT applications, risk-based access control model has become the best candidate for both academic and commercial organizations to address access control issues. This model carries out a security risk analysis on the access request by using IoT contextual information to provide access decisions dynamically. This model solves challenges related to flexibility and scalability of the IoT system. Therefore, we propose an adaptive risk-based access control model for the IoT. This model uses real-time contextual information associated with the requesting user to calculate the security risk regarding each access request. It uses user attributes while making the access request, action severity, resource sensitivity and user risk history as inputs to analyze and calculate the risk value to determine the access decision. To detect abnormal and malicious actions, smart contracts are used to track and monitor user activities during the access session to detect and prevent potential security violations. In addition, as the risk estimation process is the essential stage to build a risk-based model, this paper provides a discussion of common risk estimation methods and then proposes the fuzzy inference system with expert judgment as to be the optimal approach to handle risk estimation process of the proposed risk-based model in the IoT system.

The eGovernment initiative is aimed to improve government services to the public by improving the quality and availability of services that can be accessed regardless of time and place. Consequently, the services must always be available at any time, and any threat to the information and systems should receive attention to ensure business continuity in the event of an incident. Therefore, in implementing eGovernment, information assurance (IA) must be considered. To determine the extent to which IA implementation status to protect eGovernment services in Indonesia, it is necessary to measure the implementation using an instrument. The measurement instrument was developed using the Goal Question Metric (GQM) approach. The developed instrument was then used in a case study to test its effectiveness in measuring the IA implementation. From the results of the case study, it can be concluded that the IA measurement instrument for eGovernment was proven to be effective within Indonesian context.

PBX hacking is a multi-billion dollar per year criminal and terrorism funding source. This paper follows on from a previous 10-day Honeypot experiment, to run a VoIP PBX Honeypot for a longer period of 103-day to not only validate any similarities, but to also analyse non-VoIP methods hackers use in an attempt to gain access to a VoIP System. Over the 103-day data collection period, the Honeypot recorded over 100 million SIP messages. Different techniques were used (including SQL injections in Invites) and hackers of the same IP subnet also attempted using web vulnerabilities in different telephony phone systems to gain access. Of specific interest, over the Christmas period of 2018, attack intensity decreased significantly. To validate these findings, the Honeypot experiment was also conducted for a short period over the Christmas period of 2019 which found that unlike Christmas 2018, attacks increased. The sophistication, scale and complexity of the fraud would suggest an Advance Persistent Threat exists with an aim to infiltrate a VoIP system (including a PBX) to conduct Toll Fraud and where possible to also add that system to a botnet of infected voice systems.

The Internet of Things (IoT) represents a new technology that enables both virtual and physical objects to be connected and communicate with each other, and produce new digitized services that improve our quality of life. The IoT system provides several advantages, however, the current centralized architecture introduces numerous issues involving a single point of failure, security, privacy, transparency, and data integrity. These challenges are an obstacle in the way of the future developments of IoT applications. Moving the IoT into one of the distributed ledger technologies may be the correct choice to resolve these issues. Among the common and popular types of distributed ledger technologies is the blockchain. Integrating the IoT with blockchain technology can bring countless benefits. Therefore, this paper provides a comprehensive discussion of integrating the IoT system with blockchain technology. After providing the basics of the IoT system and blockchain technology, a thorough review of integrating the blockchain with the IoT system is presented by highlighting benefits of the integration and how the blockchain can resolve the issues of the IoT system. Then, the blockchain as a service for the IoT is presented to show how various features of blockchain technology can be implemented as a service for various IoT applications. This is followed by discussing the impact of integrating artificial intelligence (AI) on both IoT and blockchain. In the end, future research directions of IoT with blockchain are presented.

The healthcare data are considered as a highly valuable source of information that can improve healthcare systems to be more intelligent and improve the quality of the provided services. However, due to security and privacy issues, sharing data between healthcare organisations is challenging. This has led to data shortage in the healthcare sector which is considered as a significant issue not only in the Kingdom of Saudi Arabia (KSA) but also worldwide. The primary objective of conducting this paper is to investigate the various factors that enable secure sharing and exchange of healthcare information between different healthcare providers in the KSA. It starts by discussing the current literature and frameworks for managing healthcare data information and the challenges that health providers encounter, particularly when it comes to issues such as data security, patient privacy, and healthcare information exchange. These challenges in managing healthcare data have necessitated the nee d for implementing a solution that can allow medical providers to have access to updated healthcare information. Attention in the healthcare sector has been drawn to blockchain technology as a part of the solution, especially after the technology was successfully applied in the financial sector to improve the security of financial transactions, particularly involving digital currencies such as Bitcoin. Therefore, a framework based on the blockchain technology has been proposed to achieve the goals of the present research.

Stock market trading is an activity in which investors need fast and accurate information to make effective decisions. Since many stocks are traded on a stock exchange, numerous factors influence the decision-making process. Moreover, the behaviour of stock prices is uncertain and hard to predict. For these reasons, stock price prediction is an important process and a challenging one. This leads to the research of finding the most effective prediction model that generates the most accurate prediction with the lowest error percentage. This paper reviews studies on machine learning techniques and algorithm employed to improve the accuracy of stock price prediction.

Despite the effort and copious resources Saudi Arabia is investing in its transition towards e-government, it is hindered by the weakness of the information and communication technology infrastructure in its government agencies. The development of a private government cloud is a solution for improving and standardising the ICT infrastructure, but cloud computing is still in the early stages in the country. To effectively implement a private government cloud in Saudi Arabia it is necessary to identify the factors that will affect its success. Therefore, this research identifies the critical success factors for the implementation of a government cloud and based on these factors, a framework for the successful implementation of a government cloud (FSIGC) in Saudi Arabia was developed and confirmed by a methodological triangulation.

Employment uses trusted records such as award certificates as a part of hiring procedures. Some countries practices for employment history reference; either a service certificate or systems based on pension records which are based on number of years of employment that are also can be used for pension eligibility. However, there is an increase on the number of issued award certificates which are, in most cases, do not follow an agreed standard, which increases challenges for an authenticated record sharing. Moreover, employment systems are not required to share employment history nor to accommodate record requests educational institutes. Additionally, public employment systems are by design isolated from interaction with private sector. The research suggest that distributed systems would reduce costs for verifying and authenticating records while being flexible on allocating trusted records such as employment history, awarded certificates and resumes.

The gamification of anthropomorphic interfaces is one of technology interventions in health. Applying them into transitional care may encourage a patient to learn about their condition, so that they are able to self-manage. This research is based on the researcher’s previous developed framework to develop a rigorous scale that assesses the applicability of anthropomorphic interfaces gamification for transitional care in an application. By measuring, it may inform the software developer or designer of the design requirement for the application. We adopt a Goal-Question-Metric (GQM) approach to develop a new measurement instrument. The GQM offered a stepwise approach to refine a theoretical perspective of anthropomorphic gamification for transition care into measurable values. Thus, this research presents how the measurement items can be created using GQM. Later, these items will be grouped together as an instrument called Transitional Anthropomorphs Gamification Scale (TAGS). This instrument needs for further validation, ensuring they measured the right construct.

In many developing countries such as Saudi Arabia the adoption of cloud computing is still at an early stage. This research aims to investigate the influencing factors in the decision to adopt cloud computing in the private sector. An integrated model is proposed incorporating critical factors derived from a literature review, along with other factors (such as physical location) that have not been examined in previous studies as main factors in the organisation’s decision to adopt cloud services. Data were collected from 300 IT staff in different organisations in the private sector in Saudi Arabia, in order to test the cloud adoption model and explore factors that were positively or negatively associated with cloud adoption. The most influential determinants of cloud adoption were found to be quality of service and trust. However, security and privacy concerns still prevent cloud adoption in this country. This study also showed that the effect of these variables differed according to organisation size and in adopter and non-adopter companies. Overall, these research findings provide valuable guidelines to cloud providers, managers, and government policy makers on ways of encouraging the spread of cloud computing in Middle Eastern countries and increasing its implementation, particularly in Saudi Arabia.

This article illustrates the importance of gathering and analyzing preprocessing data for unlisted but rich firms such as venture capital firms. Using datasets from three major sources, the authors demonstrate how to query and analyze data using both Datastream and SQL.

Cloud computing technologies can play an essential role in public organisations and companies while it reduces the cost of using information technology services. It allows users to access the service anytime and anywhere, with paying for what they use. In developing countries, such as Saudi Arabia, the cloud computing is still not extensively adopted, compared to countries in the west. In order to encourage the adoption of cloud services, it is considerable to understand an important and particular complications regarding to cloud computing is the potential and perceived security risks and benefits posed by implementing such technology. This paper investigates the critical security factors that influence the decision to adopt cloud computing by Saudi government agencies. A framework was proposed for three categories, Social Factors category, Cloud Security Risks Category and Perceived Cloud Security Benefits that includes well-known cloud security features. The framework factors were identified by critically reviewing studies found in the literature together with factors from the industrial standards within the context of Saudi Arabia. An experiment study was conducted in five government agencies in Saudi Arabia by interview and questionnaire with experts in order to improve and confirm the framework. All the factors in the proposed framework were found to be statistically significant. An additional factor identified was Failure of client side encryption. Moreover, they suggested including this factor as a potential risk under Security Risk Factors Category. The initial framework was updated based on the expert reviews and questionnaires. The results were analysed via one-sample t-test with the data integrity analysed via Cronbach’s alpha. The outcome indicated the majority of cloud security adoption framework categories were statistically significant. Potential future study directions and contributions are discussed.

This paper explores avatar roles and design principles in helping to develop motivation in game environments. Different avatar applications could influence the experience of players in at least three ways: as a customisation tool, game strategy, and personal identification. These possible influences could be enhanced by the application of avatar design for motivational purposes, reflected through the integration between game design elements and the avatar implementation. This paper aims to situate avatar design as a design strategy to motivate users to change their behaviour and promote adherence to new habits. We start by reviewing the current papers that address avatar design utilisations for motivation in to Serious Games. Then, we analyse the main elements in gameful applications (e.g. Re-Mission, Pain Squad, CodeInGame and Monster Manor), in order to understand and explore the design of avatars. The analysis is followed by the development of a model for Avatar Design in Motivational contexts (ADAM), which could be used to provide the necessary guidance for designers and developers of gameful systems for motivational environments.