Mohammad Atwah Al-ma'aitah
@bau.edu.jo
Management Information System
Al-Balqa Applied University
Mohammad Atwah Al-maaitah is an Associate Professor of computer Information Systems at Al Balqa’ Applied University (BAU). He obtained his Doctorate degree in Electronic
Collaboration systems in 2008. Master degree in Information System, 2002. Bachelor of
Computer Science in 1996. He has published several journals papers in the area of Social
media in Arab world, cloud computing, e-government and e-learning. His interested
research areas are information systems, e-business, cloud ERP, database and knowledge
management. He worked at many administration duties such as vice dean for Graduate
Studies, Department Head-Business Administration and MIS and Dean Assistant for
Quality Assurance and Development.
EDUCATION
PHD in computer information system
RESEARCH INTERESTS
Social Media, Data Mining, Bigdat, E-government,
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
Mohammad Atwah Al‐ma'aitah
Wiley
AbstractWith innovation becoming more collaborative, the influence of digital business strategy (DBS) on interfirm cooperation has grown. This study investigates how DBS can enhance collaboration innovation capabilities across pharmaceutical companies in developing countries. Further, it investigates organizational culture as a moderating variable in the relationship between DBS and collaborative innovation capability (CIC). A total of 205 questionnaire responses were gathered on six Jordanian pharmaceutical corporations. The findings showed that each DBS element (development, objectives, resources, management capabilities, and digital leadership) positively affected CIC, and that organizational culture positively moderated the relationship between DBS and CIC. These results provide valuable insights for managers seeking to improve collaborative capability by leveraging digital business strategies and organizational culture.
Mohamad Al-laham, Mohammad Al-ma'aitah, and Ziad Alqadi
Zarqa University
The main purpose of the classification of fingerprints is to devise a formula by which a given collection of fingerprints can be tracked and registered. To accelerate the system for classifying fingerprints, it is necessary to utilize fingerprint image characteristics and avoid the different fingerprint forms arising from fingerprint rotation. This paper presents a simple, new approach to the extraction of characteristics from fingerprint images. The proposed method demonstrates that, for a given image, the features remain constant even after being subjected to a wide range of rotations; thus, it creates an array of characteristics which can be used to identify a person from their fingerprint. To achieve this goal, a basic hit-and-miss operation with different structural components is used to detect and count various features in the fingerprint picture; these features are directly identified based on the texture of the fingerprint. The chosen features are used to index the finger image by generating a frequency of occurrences for each one, such that every fingerprint is represented as a vector of these features. The application of the proposed method shows efficient utilization of execution time and memory usage.
Mohamad Al-Laham, Salwani Abdullah, Mohammad Atwah Al-Ma’aitah, Mohammed Azmi Al-Betar, Sofian Kassaymeh, and Ahmad Azzazi
The Science and Information Organization
Effort estimation in software development (SEE) is a crucial concern within the software engineering domain, as it directly impacts cost estimation, scheduling, staffing, planning, and resource allocation accuracy. In this scientific article, the authors aim to tackle this issue by integrating machine learning (ML) techniques with metaheuristic algorithms in order to raise prediction accuracy. For this purpose, they employ a multilayer perceptron neural network (MLP) to perform the estimation for SEE. Unfortunately, the MLP network has numerous drawbacks as well, including weight dependency, rapid convergence, and accuracy limits. To address these issues, the SSA Algorithm is employed to optimize the MLP weights and biases. Simultaneously, the SSA algorithm has shortcomings in some aspects of the search mechanisms as well, such as rapid convergence and being susceptible to the local optimal trap. As a result, the genetic algorithm (GA) is utilized to address these shortcomings through fine-tuning its parameters. The main objective is to develop a robust and reliable prediction model that can handle a wide range of SEE problems. The developed techniques are tested on twelve benchmark SEE datasets to evaluate their performance. Furthermore, a comparative analysis with state-ofthe-art methods is conducted to further validate the effectiveness of the developed techniques. The findings demonstrate that the developed techniques surpass all other methods in all benchmark problems, affirming their superiority. Keywords—Software development effort estimation; machine learning; multilayer perceptron neural network; salp swarm algorithm; genetic algorithm
Mohammad Atwah Al‐ma'aitah
Wiley
Bayan Qaddumi, Omar Ayaad, Mohammad Atwah Al-Ma'aitah, Laila Akhu-Zaheya, and Aladeen Alloubani
Elsevier BV
Abstract Objectives This study aimed to examine the impact of the influential factors (technical support, training and learning, organizational culture, and infrastructure) on team effectiveness with the mediating role of e-collaborative use in hospitals. Methods A cross-sectional design was conducted in six private hospitals. About 434 participants were selected using a random sampling technique. A self-administered questionnaire was developed to collect the data. Results The results of multiple linear regression showed that there was a significant impact of the influential factors (technical Support, training and learning, organizational culture, and infrastructure) on the team effectiveness (F = 40.198. p > 0.05). The results of simple linear regression showed a significant impact on the use of the e-collaborative tool on team Effectiveness (F = 261.445; p > 0.05). Also, the results showed that the use of e-collaborative tools had a significant impact as a mediating role in the relationship between influential factors and team (CMIN = 0.701, p > 0.05). Conclusions Hospital administration interested in enhancing Electronic collaboration should evaluate the work environment to assure that workers operate to promote intra-organizational teamwork and effectiveness.
Khaled Saleh Al-Omoush, Virginia Simón-Moya, Mohammad Atwah Al-ma'aitah, and Javier Sendra-García
Elsevier BV
Abstract Despite a growing interest in social media adoption by corporations, there is minimal knowledge about the drivers of social customer relationship management (SCRM). This study examines the determinants of SCRM entrepreneurship from an institutional perspective and specifically from the banking sector. Data on 19 banks were obtained from 183 responses to a questionnaire. These data were analyzed using Partial Least Square (PLS) path modeling. The findings show that organizational and technological contexts have a significant positive impact on SCRM entrepreneurship. The results also reveal a significant impact of institutional normative and coercive pressures on SCRM entrepreneurship. The findings of this study provide researchers and practitioners with a deeper understanding of how external institutional pressures and internal organizational and technological contexts can interact to create SCRM entrepreneurship. Furthermore, this study contributes to knowledge about the motivations and methods of SCRM adoption and evaluation.
Mohammad Atwah AL-Ma�aitah
Science Publications
This study investigates the impact of Big Data and Predictive Analytics (BDPA) capability on crisis management in the Greater Amman Municipality (GAM), Jordan. Effective utilization of BDPA is considered in the study to depend upon the five dimensions: Tangible resources, technical skills, management skills, organizational learning and data driven culture. Crisis management is classified into the three stages of crisis preparedness, crisis response and crisis recovery. A32 item questionnaire was developed for the purpose of the study, which was completed by 140 participants; with128 responses deemed suitable for research analysis. PLS2 software was used to analyze the data. The study results confirm that the Greater Amman Municipality has medium levels of big data availability and predictive analytics capability overall. The study’s findings further demonstrate that big data and predictive analytics capability has a significant impact on crisis management. The main recommendation of the study is that organizations enhance their ability to utilize big data through expanding their tangible resources infrastructure, including machine learning algorithms, python software, simulation and regression analysis for understanding huge volumes of data. In addition, the study recommends that organizations improve the technical skills of their staff by providing the necessary training for performing big data analysis.
Mohammad Al-Ma'aitah
IGI Global
This study investigated the impact of drivers of e-government, particularly social CRM, citizen trust, and quality of electronic services, on citizen satisfaction with e-government services in the Jordanian environment. In addition to measuring the impact of social CRM on citizen trust and service quality respectively and its impact on citizen satisfaction. A convenience sample was used to achieve the study purpose consisting of 386 questionnaires collected online. The resulting data was analyzed using PLS.2 software. The study findings reveal that social CRM has a significant impact on citizen trust and quality of electronic services, and furthermore that citizen trust and quality of electronic services have significant impacts on citizen satisfaction with e-government services. The study found no direct relationship between the use of social CRM and citizen-government satisfaction but showed a significant indirect impact via customer trust and service quality.
Mohammad Atwah Al-Maaitah
Science Publications
This study aims to identify the role of business intelligence competencies (Managerial competencies, Technical competencies and cultural competencies) on the organizational capabilities in Jordanian banks (process improvement, innovations, flexibility, agility). Hence, a questionnaire was used to gather data to achieve the purpose of this study. Since it is difficult to cover the total population, a convenient sample was used. Therefore, 385 questionnaires were distributed and 340 were retrieved, 320 of which were suitable for analysis. Structural equation modeling via PLS3 was used to analyze the data. The findings from this study show that the level of availability of Business Intelligence competencies and organizational capabilities in Jordanian banks were medium. The core conclusion of this study proves that business intelligence competencies have a significant impact on the organizational capabilities in Jordanian banks. The main recommendation of this study was to continually assess the efficiency of business intelligence competencies in Jordanian commercial banks in order to develop them in line with the changing environment and new business requirements.
Khaled Saleh Al Omoush, Saad Ghaleb Yaseen, and Mohammad Atwah Alma’aitah
Elsevier BV
RECENT SCHOLAR PUBLICATIONS
MOST CITED SCHOLAR PUBLICATIONS
Publications
The determinants of social CRM entrepreneurship: An
institutional perspective . Journal of Business Research