How knowledge sharing and business process contribute to organizational performance: Using the fsQCA approach

The purpose of this research is to carry out a comparative analysis of organizational factors that facilitate knowledge sharing and business process, ultimately contributing to the improvement of organizational performance. The literature considers knowledge sharing a key factor for driving innovation as well as the organization's business performance, as both explicit and tacit knowledge sharing promotes a novel robust approach for business-knowledge process. This research explores the application of fuzzy-set qualitative comparative analysis as a set-theoretic comparative analysis approach to investigate the relationships between knowledge sharing, business process, and organizational performance through the identification of key organizational operation factors. Based on empirical data collected from 28 cases, the analysis results demonstrate the important role of organizational operation factors in knowledge sharing and business-knowledge process, which directly contribute to the improvement of organizational performance

New structured knowledge network for strategic decision-making in IT innovative and implementable projects

This study investigates the development of a structured knowledge network model in information technology (IT) innovative and implementable projects to facilitate knowledge sharing and transfer in a multi-organization context. The study employs a practice-based perspective by using an exploratory case study approach and a combination of thematic analysis and comparative analysis to analyze the data across public organizations, private organizations, and international companies. The results identify organizational factors and their influence on knowledge channels and knowledge networks. The study contributes to organizational, administrative and knowledge management theories regarding organizational strategy, organizational culture, organizational capacity, knowledge network externalities, knowledge network intermediaries, and knowledge network infrastructures

Cost-Savings Associated with Multi-Disciplinary Team Approach for Reducing Macrovascular and Microvascular Complications in Patients with Type 2 Diabetes: A Predictive Model

Abdulmajeed Alshowair,1 Saleh Altamimi,1 Faisal A Alruhaimi,1 Saad Alshahrani,2 Fatima Alsuwailem,3 Mona Alkhaldi,4 Haiam Abdalla,5 Fahad Hamad Alkhuraiji,6 Montaser Saad Alaqeel,6 Salman Sulaiman Almureef,7 Salman Alhawasy,8 Amro Abdel-Azeem3,9 1Community Health Excellence, Riyadh First Health Cluster Ministry of Health, Riyadh, Saudi Arabia; 2Academic and Training Affairs, Riyadh First Health Cluster Ministry of Health, Riyadh, Saudi Arabia; 3Population Health Management and Research, Riyadh First Health Cluster Ministry of Health, Riyadh, Saudi Arabia; 4Health Administration Office, Riyadh First Health Cluster Ministry of Health, Riyadh, Saudi Arabia; 5Model of Care, Riyadh First Health Cluster Ministry of Health, Riyadh, Saudi Arabia; 6Financial Affairs, Riyadh First Health Cluster Ministry of Health, Riyadh, Saudi Arabia; 7Cost Department, Riyadh First Health Cluster Ministry of Health, Riyadh, Saudi Arabia; 8Reporting Department, Riyadh First Health Cluster Ministry of Health, Riyadh, Saudi Arabia; 9Department of Community, Environmental and Occupational Medicine, Faculty of Medicine Zagazig University, Zagazig, EgyptCorrespondence: Amro Abdel-Azeem, Population Health Management and Research, Riyadh First Health Cluster Ministry of Health, Riyadh, Saudi Arabia, Tel +966547135224, Email [email protected]: This study aims to predict the expected cost savings associated with implementing a multidisciplinary team (MDT) approach to reduce macrovascular and microvascular complications among patients with type 2 diabetes mellitus (T2DM).Methods: This economic evaluation study was conducted in Riyadh First Health Cluster, Saudi Arabia as a predictive model conceptualized by the authors based on models used in previous studies, particularly the CORE Diabetes Model. Our model was designed based on 1) the level of glycemic control among 24,755 T2DM patients served by MDTs; 2) the expected incidence of diabetes-related complications without intervention; 3) the predicted risk reduction of developing diabetes-related complications with MDTs. Costs of complications and cost savings were then calculated and expressed as mean incremental annual cost savings adjusted for a 1% reduction in HbA1c, and a 10 mmHg reduction in systolic blood pressure (SBP).Results: Along with the expected reduction in all diabetes-related complications, the average incremental cost savings per diabetic patient is predicted to be ($38,878) with approximately ($11,108) in the year of complication onset and ($27,770) over the subsequent post-index 10-years. On adjustment of cost savings, the average incremental cost savings are predicted to be ($22,869) for each 1% reduction in HbA1c per diabetic patient and ($27,770) for every 10 mmHg reduction in SBP per diabetic patient.Conclusion: MDT as a model of care is effective in glycemic control among T2DM patients with a predicted significant reduction of all diabetes-related complications and in turn, a predicted significant cost savings.Keywords: cost-savings, multi-disciplinary team, complications, type 2 diabetes, predictive mode

Knowledge network modelling to support decision-making for strategic intervention in IT project-oriented change management

This is the Accepted Manuscript version of an article published by Taylor & Francis in Journal of Decision Systems on 20 March 2014, available online: http://www.tandfonline.com/doi/abs/10.1080/12460125.2014.886499.This paper focuses on knowledge management to enhance decision support systems for strategic intervention in information technology (IT) project-oriented change management. It proposes a model of change management knowledge networks (CMKNM) to support decision by tackling three existing issues: insufficient knowledge traceability based on the relationships between knowledge elements and key factors, lack of procedural knowledge to provide adequate policies to guide changes, and lack of ‘lessons learned’ documentation in knowledge bases. A qualitative method was used to investigate issues surrounding knowledge mobilisation and knowledge networks. Empirical study was undertaken with industries to test the CMKNM. Results are presented from the empirical study on the key factors influencing knowledge mobilisation in IT project-oriented change management, knowledge networks and connections. The CMKNM model allows key knowledge mobilisation factors to be aligned with each other; it also defines the connections between knowledge networks allowing knowledge to be mobilised by tracing knowledge channels to support decision.Peer reviewe

Association between Gingival Phenotype and Periodontal Disease Severity—A Comparative Longitudinal Study among Patients Undergoing Fixed Orthodontic Therapy and Invisalign Treatment

This longitudinal study aimed to compare the association between gingival phenotype (thin vs. thick) and periodontal disease severity in patients undergoing fixed orthodontic therapy (FOT) and Invisalign treatment over a six-month follow-up period. Clinical periodontal parameters, including full mouth plaque score (FMPS), full mouth bleeding score (FMBS), gingival index (GI), probing pocket depth (PPD), clinical attachment loss (CAL), gingival recession (GR), keratinized tissue width (KTW), transgingival probing, and gingival biotype assessment, were recorded at baseline and 6 months into treatment for both orthodontic groups and a control group. Statistical analysis evaluated differences in parameters between groups and across time points. In the thick phenotype, both Invisalign and FOT groups showed a significant mean reduction in FMPS (baseline to 6 months) by −24.8707 and −12.3489, respectively (p p p p > 0.05). Similar changes were seen in the thin phenotype too. This study highlights the positive influence of both Invisalign and fixed orthodontic therapy on periodontal health, particularly in patients with thin and thick gingival biotypes. These findings, with significant reductions in key periodontal parameters, offer valuable insights to guide orthodontic treatment decisions and enhance patient outcomes

Deep Analysis of Student Body Activities to Detect Engagement State in E-Learning Sessions

In this paper, we propose new 3D CNN prediction models for detecting student engagement levels in an e-learning environment. The first generated model classifies students’ engagement to high positive engagement or low positive engagement. The second generated model classifies engagement to low negative engagement or disengagement. To predict the engagement level, the proposed prediction models learn the deep spatiotemporal features of the body activities of the students. In addition, we collected a new video dataset for this study. The new dataset was collected in realistic, uncontrolled settings from real students attending real online classes. Our findings are threefold: (1) Spatiotemporal features are more suitable for analyzing body activities from video data; (2) our proposed prediction models outperform state-of-the-art methods and have proven their effectiveness; and (3) our newly collected video dataset, which reflects realistic scenarios, contributed to delivering comparable results to current methods. The findings of this work will strengthen the knowledge base for the development of intelligent and interactive e-learning systems that can give feedback based on user engagement

Developing innovative tool to enhance the effectiveness of decision support system

This research centres on Usability Evaluation Methods (UEMSs) with the aim of supporting developers’ decisions in the use of learning resources in achieving efficient usable system design. The suggestion is made pertaining to a new usability evaluation model dEv (stand for Design Evaluation) with the objective to support decisions to overcome three key obstacles: firstly, the involvement of users in the preliminary stages of the development process; (2) developers’ mind set-related issues as a result of either their lack of UEMS or the provision of too many; and (3) the complete lack of understanding surrounding UEMS importance. An experimental approach was applied in addition to a survey-based questionnaire in an effort to examining the issues pertaining to UEMS. Empirical works were carried out with system developers in order to test the dEv, the results of which have been presented from the empirical study to support various considerations, such as: system developers’ decisions and their involvement in the earlier phases of the design of systems; the gathering of specifications and end-users’ feedback; and enhancing usability evaluation learning capacity