Search

Purpose – The study is interested in knowing “the role of the organizational structure as a mediating variable of the relationship between the information technology and organizational communication”. Design/methodology/approach – The study was conducted in several service companies, and the study adopted the questionnaire as a basic tool for the data collection on the practical side, as 267 opinions were surveyed, in addition to conducting personal interviews, and the normal distribution of data was tested, analyzing, describing and diagnosing study variables, testing correlations and determining direct effects. Findings – Findings show that there is no direct and significant statistical impact of information technology on organizational communications. Whereas there was a positive, direct and statistically significant impact of information technology on the organizational structure. There was also a positive, direct and statistically significant effect of the organizational structure on organizational communication. Research limitations/implications – This paper is restricted to the role of the organizational structure as a mediating variable of the relationship between the influence of information technology on organizational communication. Practical implications – As part of the practical implication, the paper suggests the need to increase support and attention to the importance of information technology in service organizations in order to increase coordination and organizational communication and achieve a high ability to explore and exploit ideas. Originality/value – Apart from the fact that several companies were engaged, the organizational structures of these companies were engaged too to examine the impacts of Information technology (ICT) on organizational communication.

Purpose – Organizations seek to achieve the best results for their strategic decisions by increasing the effectiveness of the vertical and horizontal interconnection. This leads to an efficient and effective flow of information when making decisions (from the bottom-up) and information related to those decisions when starting to implement them on the ground (from Top-down). Thus, the article aims that, it requires managers at all levels to practice relational leadership skills, the most important of which is dealing with emotions (through emotional intelligence (EI)) and conflicts (through personal styles). Design/methodology/approach – In this paper the views of 324 managers were surveyed in several small and medium-sized companies in Saudi Arabia. The respondents were selected randomly. Findings – A direct positive effect of EI, patterns of cooperation and comprehension to deal with conflict was found on the results of strategic decisions and indirectly through relational leadership. Research limitations/implications – This paper is restricted to the relevant literature on the influence of EI and personal styles of dealing with conflict on strategic decisions. Practical implications – As part of the practical implication and managerial decision, policymakers should note that intelligence directly impacts strategic decisions. Originality/value – This is one of the few studies that focused on the level of EI when choosing managers for organizational units and divisions.

Tasks ranging from synthesis to regression are executed within a computational farm environment during chip design. This process is managed by a compute farm scheduler, which handles job scheduling based on the availability of such computational resources as central processing units, memory, and storage. The increasing complexity of chip design over the years, combined with a growing number of cores per chip, has resulted in memory-intensive applications often being executed as compute jobs. Jobs submitted with inaccurate resource-related requests, especially those concerning memory, can overload a compute farm and lead to wasted resources. This study addresses this issue by using a data science-driven, machine learning-based approach to predict the memory required for a compute job at the time of its submission. Improving the accuracy of such predictions can significantly reduce the overall wait times of jobs and enable efficient use of the compute farm to reduce the overall cost because fewer machines are required to complete a set of jobs. We explored the use of the K-nearest neighbor, random forest, and ensemble methods to this end. The proposed approach yielded an accuracy of 80% in experiments, where this demonstrates the success of predicting the memory-related requirements of compute jobs across a diverse suite of applications used in the process of chip design.

This study examines the antecedents and consequences of credit risk (CR) in Iraqi banks' context from 2011 to 2020. POLS, FEM, and REM regression estimators were used to test the hypotheses after obtaining an appropriate model. The hypotheses test findings on CR antecedents reveal that the board's financial expertise, risk management committee, and foreign ownership have a negative impact on CR. Meanwhile, the results show an insignificant effect on CR of board independence, audit committee, institutional ownership, governmental ownership, and managerial ownership. Concentrating on the consequence of CR, the results stated that CR influenced financial distress (FD) positively. Finally, ownership concentration (OC) as moderating interacts with the association between CR and financial distress. The study enhances the knowledge and implications of the theory used for corporate governance dimensions. It provides feedback to regulators and policymakers on the effectiveness of corporate governance mechanisms regarding CR control. The study also offers the Iraqi regulators and policymakers evidence of the harmful impact of CR on financial distress, necessitating their protection of bank investors from such situations by improving established credit rules and laws. This study contributes to the existing body of knowledge by investigating the antecedents and consequences of credit risk in the banking sector. This study also took a further step by examining the moderating role of ownership concentration between CR and FD.

Introduction: The vaccine distribution for the COVID-19 is a multicriteria decision-making (MCDM) problem based on three issues, namely, identification of different distribution criteria, importance criteria and data variation. Thus, the Pythagorean fuzzy decision by opinion score method (PFDOSM) for prioritising vaccine recipients is the correct approach because it utilises the most powerful MCDM ranking method. However, PFDOSM weighs the criteria values of each alternative implicitly, which is limited to explicitly weighting each criterion. In view of solving this theoretical issue, the fuzzy-weighted zero-inconsistency (FWZIC) can be used as a powerful weighting MCDM method to provide explicit weights for a criteria set with zero inconstancy. However, FWZIC is based on the triangular fuzzy number that is limited in solving the vagueness related to the aforementioned theoretical issues. Objectives: This research presents a novel homogeneous Pythagorean fuzzy framework for distributing the COVID-19 vaccine dose by integrating a new formulation of the PFWZIC and PFDOSM methods. Methods: The methodology is divided into two phases. Firstly, an augmented dataset was generated that included 300 recipients based on five COVID-19 vaccine distribution criteria (i.e., vaccine recipient memberships, chronic disease conditions, age, geographic location severity and disabilities). Then, a decision matrix was constructed on the basis of an intersection of the ‘recipients list’ and ‘COVID-19 distribution criteria’. Then, the MCDM methods were integrated. An extended PFWZIC was developed, followed by the development of PFDOSM. Results: (1) PFWZIC effectively weighted the vaccine distribution criteria. (2) The PFDOSM-based group prioritisation was considered in the final distribution result. (3) The prioritisation ranks of the vaccine recipients were subject to a systematic ranking that is supported by high correlation results over nine scenarios of the changing criteria weights values. Conclusion: The findings of this study are expected to ensuring equitable protection against COVID-19 and thus help accelerate vaccine progress worldwide.

Wireless sensor networks (WSNs) are a major part of the telecommunications sector. WSN is applied in many aspects, including surveillance battlefields, patient medical monitoring, building automation, traffic control, environmental monitoring, and building intrusion monitoring. The WSN is made up of a vast number of sensor nodes, which are interconnected through a network. However, despite the growing usage of applications that rely on WSNs, they continue to suffer from restrictions, such as security issues and limited characteristics due to low memory and calculation power. Security issues lead to a lack of communication between sensors, wasting more energy. The need for efficient solutions has increased, especially with the rise of the Internet of Things, which relies on the effectiveness of WSNs. This review focuses on security issues by reviewing and addressing diverse types of WSN assaults that happened on each layer of the WSN that were published in security issues in the previous 3 years. As a consequence, this paper gives a taxonomy of security threats for each layer and different algorithmic solutions that numerous researchers who seek to counter this attack have explored. This study also presents a framework for constructing an intrusion detection system in the WSN by emphasising the drawbacks of each approach suggested by researchers to defend against specific forms of assault. In order to diminish the impact of this attack, this summary shows which attacks the majority of researchers have dealt with as well as which ones they have not yet addressed in their academic work.

The significance of deep learning techniques in relation to steady-state visually evoked potential- (SSVEP-) based brain-computer interface (BCI) applications is assessed through a systematic review. Three reliable databases, PubMed, ScienceDirect, and IEEE, were considered to gather relevant scientific and theoretical articles. Initially, 125 papers were found between 2010 and 2021 related to this integrated research field. After the filtering process, only 30 articles were identified and classified into five categories based on their type of deep learning methods. The first category, convolutional neural network (CNN), accounts for 70% (n=21/30). The second category, recurrent neural network (RNN), accounts for 10% (n=3/30). The third and fourth categories, deep neural network (DNN) and long short-term memory (LSTM), account for 6% (n=30). The fifth category, restricted Boltzmann machine (RBM), accounts for 3% (n=1/30). The literature’s findings in terms of the main aspects identified in existing applications of deep learning pattern recognition techniques in SSVEP-based BCI, such as feature extraction, classification, activation functions, validation methods, and achieved classification accuracies, are examined. A comprehensive mapping analysis was also conducted, which identified six categories. Current challenges of ensuring trustworthy deep learning in SSVEP-based BCI applications were discussed, and recommendations were provided to researchers and developers. The study critically reviews the current unsolved issues of SSVEP-based BCI applications in terms of development challenges based on deep learning techniques and selection challenges based on multicriteria decision-making (MCDM). A trust proposal solution is presented with three methodology phases for evaluating and benchmarking SSVEP-based BCI applications using fuzzy decision-making techniques. Valuable insights and recommendations for researchers and developers in the SSVEP-based BCI and deep learning are provided.

The problem complexity of multi-criteria decision-making (MCDM) has been raised in the distribution of coronavirus disease 2019 (COVID-19) vaccines, which required solid and robust MCDM methods. Compared with other MCDM methods, the fuzzy-weighted zero-inconsistency (FWZIC) method and fuzzy decision by opinion score method (FDOSM) have demonstrated their solidity in solving different MCDM challenges. However, the fuzzy sets used in these methods have neglected the refusal concept and limited the restrictions on their constants. To end this, considering the advantage of the T-spherical fuzzy sets (T-SFSs) in handling the uncertainty in the data and obtaining information with more degree of freedom, this study has extended FWZIC and FDOSM methods into the T-SFSs environment (called T-SFWZIC and T-SFDOSM) to be used in the distribution of COVID-19 vaccines. The methodology was formulated on the basis of decision matrix adoption and development phases. The first phase described the adopted decision matrix used in the COVID-19 vaccine distribution. The second phase presented the sequential formulation steps of T-SFWZIC used for weighting the distribution criteria followed by T-SFDOSM utilised for prioritising the vaccine recipients. Results revealed the following: (1) T-SFWZIC effectively weighted the vaccine distribution criteria based on several parameters including T = 2, T = 4, T = 6, T = 8, and T = 10. Amongst all parameters, the age criterion received the highest weight, whereas the geographic locations severity criterion has the lowest weight. (2) According to the T parameters, a considerable variance has occurred on the vaccine recipient orders, indicating that the existence of T values affected the vaccine distribution. (3) In the individual context of T-SFDOSM, no unique prioritisation was observed based on the obtained opinions of each expert. (4) The group context of T-SFDOSM used in the prioritisation of vaccine recipients was considered the final distribution result as it unified the differences found in an individual context. The evaluation was performed based on systematic ranking assessment and sensitivity analysis. This evaluation showed that the prioritisation results based on each T parameter were subject to a systematic ranking that is supported by high correlation results over all discussed scenarios of changing criteria weights values.

Jubran Alqanatish,1– 3 Banan Alsowailmi,1 Haneen Alfarhan,1 Albandari Alhamzah,1 Talal Alharbi1,2,4 1King Saud Bin Abdulaziz University for Health Sciences (KSAU-HS), Riyadh 14611, Saudi Arabia; 2King Abdullah International Medical Research Center (KAIMRC), Riyadh 14611, Saudi Arabia; 3Department of Pediatrics, King Abdullah Specialist Children’s Hospital and King Abdulaziz Medical City, Ministry of National Guard Health Affairs, Riyadh, Saudi Arabia; 4Department of Pediatric Hematology/Oncology, King Abdullah Specialist Children’s Hospital and King Abdulaziz Medical City, Ministry of National Guard Health Affairs, Riyadh, Saudi ArabiaCorrespondence: Jubran AlqanatishKing Saud Bin Abdulaziz University for Health Sciences (KSAU-HS), PO Box 22490, Riyadh 11426, Saudi ArabiaTel +966 118011111 Ext 53501Email qanatishj@ngha.med.saAbstract: Hereditary hemochromatosis (HH) is an inherited iron overload. The most common form of HH is type 1 hereditary hemochromatosis (HFE-related), which is associated with mutation of the HFE gene located on chromosome 6 and inherited in an autosomal recessive pattern. Type 2 hereditary hemochromatosis or juvenile hemochromatosis is less frequent autosomal recessive disease that results from mutations in the HJV gene on chromosome 1 (type2a) or the HAMP gene on chromosome19 (type2b). Mutation of type 2 transferrin receptor gene and mutation of the ferroportin gene result in hemochromatosis type 3 and hemochromatosis type 4, respectively. Juvenile hemochromatosis is characterized by an early onset of excess accumulation of iron in various organs. It could affect the liver, heart, pancreas and joints, resulting in arthropathy. Most juvenile hemochromatosis cases exhibit severe symptoms due to early onset. Cardiac and hypogonadism are the dominating features of the disease. Prevalence of arthropathy in juvenile hemochromatosis is higher than classic HH. Early diagnosis and intervention of juvenile hemochromatosis may prevent irreversible organ damage. The diagnosis can be made based on laboratory testing (of increased transferrin saturation, serum iron and ferritin levels), liver biopsy, imaging or genotype. According to international guidelines, treatment of HH is indicated when serum ferritin concentrations are above the upper limit of normal. We report two sisters who presented to the rheumatology clinic with arthralgia, which was subsequently found to have a homozygous mutation variant of unknown significance in the HFE2 gene: c.497A>G;p.(His166Arg) and has been treated with deferasirox (Exjade®). Musculoskeletal symptoms completely resolved in both patients in two months and remained so for one year on treatment.Keywords: hereditary hemochromatosis, HFE gene, arthritis, deferasirox

The fact pure strategy leads to superior performance was widely criticized. Academics have argued there has been a shift in emphasis from pure strategy to hybrid (integrating a set of strategies). This transformation is constantly increasing. Therefore, from now on, the hybrid strategy based on Miles and Snow and Porter’s strategies is a vital concept to successful performance. Researchers investigated different cases of adoption of Miles and Snow or Porter strategies. Regardless of the prevalence and value of Miles and Snow and Porter’s strategies, they often lead to disappointing performances. The disappointing results of Miles and Snow and Porter’s strategies are due to several firms adopting the hybrid strategy. A holistic view of prior research is needed to understand the importance of a hybrid strategy on performance based on Miles and Snow and Porter. Accordingly, this study provides a comprehensive review of hybrid strategies based on Miles and Snow and Porter’s strategies. The reviewed literature regarding hybrid strategy based on Miles and Snow and Porter’s strategies is categorized and discussed in two directions. Firstly, Miles and Snow’s strategies. Secondly, Porter’s strategies. We analyze the essential characteristics of the emerging field for the hybrid strategy along with the issues, challenges, advantages of a hybrid strategy, theoretical, and practical implications.

While mobile marketing is widely practised in developed countries, this is not always the case for developing countries, such as Jordan, where the acceptance level for mobile marketing remains low. This study aims to uncover the predictors for the behaviour of Jordanian customers with regard to the acceptance of mobile marketing. For this purpose, a questionnaire based on quantitative research was conceived. This investigation involved the unified theory of acceptance and use of technology (UTAUT2), which was extended to include two additional variables: ‘trust’ and ‘risk’. For the empirical testing of the model, data was collected from 321 respondents, and the hypotheses were tested through variance-based structural equation modelling. SmartPLS 3.0 was used to analyse the data. The findings from this study suggest that performance expectancy, effort expectancy, hedonic motivation, social influence, price value, facilitating conditions, habit and risk significantly influence the behavioural intention of customers regarding the adoption of mobile marketing. On the other hand, the trust factor was found to be an insignificant predictor in this area.

The study aimed to link psychological contract with organizational misbehavior directly and through the moderating and mediation effects of organizational health and psychological contract breach. For testing these relationships, the sample gathered from 224 employees, working in Iraqi Oil Tanks Company. The data collection tool was a structured questionnaire. The preliminary analysis was performed by using SPSS 22.0 while the hypothesis testing was done through AMOS, which measures structural equation modeling that helped in simultaneous testing of multiple relationships. The hypotheses of study underpinned by the social exchange theory and other related theoretical and empirical justifications found in the previous research results suggest a negative effect of PC on OM through the mediation of PCB. The findings were also consistent with prior studies concerning the interactive relationship between organizational health and psychological contract and their influence on organizational misbehavior. The theoretical and practical implications are also provided in this study, especially managers in Iraqi oil companies to be proactive in their role to minimize the impact of organizational misbehavior of employees through an open-door policy. Finally, this study helps managers to express their feedback, suggestions, and interaction with employees.

The study aimed to determine customers' perceptions of the ethics of social commerce platforms by investigating the role of the impact of information quality, information credibility, website quality, innovativeness, altruism, sense of belongingness, self-enhancement, social support, and valuation of electronic word of mouth (eWOM) on the perception of ethics of social commerce platforms. In addition, the strength of the relationship between these factors and the perception of ethics of social commerce platforms was determined by the mediating role of the perceived risk of ethical violations. To this end, this study complements academic literature by integrating structural equation modeling (SEM) and multi criteria decision making (MCDM) techniques. In order to complete the strategic decisive solution, this study uses a survey to collect data from customers of rural communities in Malaysia and Turkey. The results demonstrate that perceived risk of ethical violations has a partial mediating role in the relationship between dependent variables and the perception of ethics of social commerce platforms for Malaysia and Turkey. Benchmarking and ranking customers from best to worst based on the perception of ethics of social commerce would identify customers with a high perception of the ethics of social commerce platforms and motivate them as opinion leaders of such platforms. Contrarily, social commerce platforms can treat worst-ranked customers with caution and strive to turn a negative perception into positive ethics. Besides, the cross-cluster study at the level of Asia and Europe would contribute to the literature to identify insights into the differences and similarities between the Asian and European contexts based on multiple and diverse cultures regarding social commerce ethics of rural communities., Author(s): Abdullah Mohammed Sadaa [sup.1] , Yuvaraj Ganesan [sup.2] , Khai Wah Khaw [sup.3] , Alhamzah Alnoor [sup.3] [sup.4] , Sammar Abbas [sup.5] , XinYing Chew [sup.6] , Gül Erkol [...]

Regardless of the prevalence and value of change initiatives in contemporary organizations, these often face resistance by employees. This resistance is the outcome of change recipients' cognitive and behavioral reactions towards change. To better understand the causes and effects of reactions to change, a holistic view of prior research is needed. Accordingly, we provide a systematic literature review on this topic. We categorize extant research into four major and several subcategories: micro and macro reactions. We analyze the essential characteristics of the emerging field of change reactions along research issues and challenges, benefits of (even negative) reactions, managerial implications, and propose future research opportunities., Author(s): Khai Wah Khaw [sup.1] , Alhamzah Alnoor [sup.1] [sup.2] , Hadi AL-Abrrow [sup.3] , Victor Tiberius [sup.4] , Yuvaraj Ganesan [sup.5] , Nadia A. Atshan [sup.2] Author Affiliations: (1) [...]

Emergency remote teaching (ERT) has potential for transforming future instruction and learning across the K-12 educational domain. The study presented here evaluated empirical evidence from peer-reviewed literature pertaining to the challenges and opportunities experienced by teachers and students during the implementation of ERT prompted by the COVID-19 pandemic. To locate relevant reports and research, the authors explored three databases: Web of Science, ScienceDirect and Scopus. Based upon predefined selection criteria, they selected 51 studies for thematic and content analysis. Next, they developed a taxonomy which comprised three categories: (1) K-12 education responses to ERT; (2) educational inequality; and (3) learning outcomes. Using this taxonomy, the authors conducted a deep analysis and critical review to highlight multiple challenges and critical gaps in the literature surrounding ERT in K-12 education settings. Their review reveals innovative strategies for overcoming obstacles to technological readiness, online learning adaptation and teachers' and students' physical and mental health. This knowledge will be valuable to policymakers, researchers, practitioners and educational institutions in reducing the adverse effects of catastrophic situations on childhood education in the future.