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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.

Nowadays, there are various internet of things (IoT) applications covering many aspects of daily life. Many people own numerous smart objects that use these IoT applications. The purpose of this study is determining suitable IoT applications for each user which is a relevant challenge because it is amulti-criteria decision-making.

To solve this challenge, the authors propose fuzzy analytical hierarchy process model. Based on the opinions of IoT experts, the model and the hierarchy were designed to assess and compare three crucial IoT criteria, namely, object, application and providers.

The results indicated that the application criterion is far more relevant for users other than the two criteria. The findings of this study offer insights into more effective decision-making for IoT application developers and providers.

This study contributes to the IoT through proposing a fuzzy model to classify IoT applications. The findings provide meaningful implications for IoT application providers.

Smart homes are recent Internet of Things applications that aim to improve residents’ quality of life. Despite its potential, the adoption of smart homes, in general, and its devices and appliances, in specific, is not reaching a mass market yet. This study aims to investigate the factors that influence residents’ intention to buy smart homes devices in Jordan.

This paper proposes a novel model to study users’ intention to buy smart homes devices by following a quantitative method. Responses were collected and statistically analyzed from 375 households using structural equation modeling.

Results show that user awareness, perceived cost, perceived enjoyment, personalization, user trust and social influences significantly influence the intention to buy smart home devices.

To the best of the authors’ knowledge, this paper is the first study attempts to predict intention to buy smart home devices in Jordan. The findings provide meaningful implications for smart home devices providers.

This paper aims to empirically examine the impact of dynamic capabilities on Industry 4.0 capabilities in small and medium enterprises (SMEs) in Jordan. It also aims to examine the potential impact of industry 4.0 capabilities on technological innovation.

Data were collected from 210 respondents who work and own SMEs in Jordan. SmartPLS software based on the partial least squares-structural equation modeling approach was used to test hypotheses.

The findings reveal the positive effects of the three components of dynamic capabilities, including sensing, seizing and reconfiguring, on Industry 4.0 capabilities. They also confirm the positive effect of Industry 4.0 capabilities on technological innovation.

This study provides valuable practical implications and enriches the literature on the determinants of Industry 4.0 capabilities and its role in developing the dynamic capabilities of SMEs, such as technological innovation.

The increase in the number of healthcare wearable (Internet of Things) IoT options is making it difficult for individuals, healthcare experts and physicians to find the right smart device that best matches their requirements or treatments. The purpose of this research is to propose a framework for a recommender system to advise on the best device for the patient using machine learning algorithms and social media sentiment analysis. This approach will provide great value for patients, doctors, medical centers, and hospitals to enable them to provide the best advice and guidance in allocating the device for that particular time in the treatment process.

This data-driven approach comprises multiple stages that lead to classifying the diseases that a patient is currently facing or is at risk of facing by using and comparing the results of various machine learning algorithms. Hereupon, the proposed recommender framework aggregates the specifications of wearable IoT devices along with the image of the wearable product, which is the extracted user perception shared on social media after applying sentiment analysis. Lastly, a proposed computation with the use of a genetic algorithm was used to compute all the collected data and to recommend the wearable IoT device recommendation for a patient.

The proposed conceptual framework illustrates how health record data, diseases, wearable devices, social media sentiment analysis and machine learning algorithms are interrelated to recommend the relevant wearable IoT devices for each patient. With the consultation of 15 physicians, each a specialist in their area, the proof-of-concept implementation result shows an accuracy rate of up to 95% using 17 settings of machine learning algorithms over multiple disease-detection stages. Social media sentiment analysis was computed at 76% accuracy. To reach the final optimized result for each patient, the proposed formula using a Genetic Algorithm has been tested and its results presented.

The research data were limited to recommendations for the best wearable devices for five types of patient diseases. The authors could not compare the results of this research with other studies because of the novelty of the proposed framework and, as such, the lack of available relevant research.

The emerging trend of wearable IoT devices is having a significant impact on the lifestyle of people. The interest in healthcare and well-being is a major driver of this growth. This framework can help in accelerating the transformation of smart hospitals and can assist doctors in finding and suggesting the right wearable IoT for their patients smartly and efficiently during treatment for various diseases. Furthermore, wearable device manufacturers can also use the outcome of the proposed platform to develop personalized wearable devices for patients in the future.

In this study, by considering patient health, disease-detection algorithm, wearable and IoT social media sentiment analysis, and healthcare wearable device dataset, we were able to propose and test a framework for the intelligent recommendation of wearable and IoT devices helping healthcare professionals and patients find wearable devices with a better understanding of their demands and experiences.

Corruption in humanitarian aid is one of the most worried and worst problems around the world. The existence of corruption acts in humanitarian aid delivery can endanger the already susceptible lives of the neediest individuals in the community. Amid serious humanitarian allegation in the country, this study aims to capture meaningful insights in humanitarian aid corruption in Puntland State of Somalia.

The study applied qualitative method and used interview as a technique of data collection. The information obtained through the interview was analyzed by quoting and narration forms.

The findings indicated numerous acts of corruption in all project stages including corruption in project granting and humanitarian staff employment, distortion of project targets and diversion of humanitarian project from targeted communities. The research also found that governmental and non-governmental actors are involved in the humanitarian corruption such as project managers and support staffs in addition to line ministries, parliament and community representatives.

Corruption is a taboo and is difficult to research; people do not want to share the information for fear of victimization. Concerned institutions were not willing to provide necessary materials which led to shortage of secondary data. Another problem encountered during the study has been that the humanitarian stakeholders (for instance, government, non-government and private institutions) acted reluctantly to cooperate because of suspicion that disclosing information may lead to negative effect on their business. To overcome the challenges, the study assured the confidentiality of the members and that information collected would be used for research purposes only. The study further combined various tools of data collection so that the weakness of one tool becomes the strength of the other; while the researcher made efforts to build rapport with the research participants.

This study will contribute to the literature on corruption in the humanitarian aid. Specifically, the findings of this study will benefit academicians/researchers by giving empirical insights of corruption in the humanitarian aid in Puntland. It will benefit the government policymakers in the formulation of policies to combat corruption in the sector. Donors and aid agencies may also find the findings useful as they are key stakeholders who are interested in corruption in the humanitarian sector and finally the findings will benefit the wider society that is the primary victim of corruption in the humanitarian sector.

This paper aims to discuss the different practices and regulatory frameworks of Shariah supervision in Islamic Financial Institutions (IFIs) across Organisation of Islamic Cooperation (OIC) member states and to identify the gaps in current Shariah supervisory practices. Parallel with the rapid growth of Islamic finance worldwide, corporate governance has received a considerable amount of attention in Islamic finance. Shariah is a unique characteristic of Islamic finance. That is why the need for a good and efficient Shariah governance system for IFIs is considered to be a crucial requirement to ensure the development and the stability of the Islamic finance industry.

The paper is based on critical review of current laws and regulations for IFIs; this provides a reflective synthesis on the practical work of the Shariah supervisory system across the 25 different OIC member states.

The paper reveals several findings. First, the authors observe a weak and poor Shariah supervisory system in most OIC member states. Furthermore, the authors detect various gaps in the current Shariah supervisory practices. Most of these shortfalls are linked to the current regulatory frameworks: the roles and the responsibilities of the national Shariah authority, and the institutional Shariah board’s duties and attributes.

This paper’s originality and value lies in its critical review of current Shariah supervisory practices across 25 OIC member states. Also, the paper puts forward various suggestions to the regulatory authorities and to the Islamic Financial Services Board to enhance the Shariah governance system and to standardize the different practices of Shariah governance worldwide.