The concepts associated with business analytics, such as business intelligence and data science, ... more The concepts associated with business analytics, such as business intelligence and data science, are generally murky. However, this misconception has a harmful impact on both academics and practitioners. This uncertainty may cause universities to develop misleading or incoherent curricula. This lack of clarity may also cause enterprises to choose an inappropriate analytical solution to a business problem, resulting in project failure and wasted resources. Despite its significance; it appears that only practitioners and major consulting firms are exerting significant effort to address this matter. Hence, this study aims to fill this void and uses the Delphi method to indicate that business intelligence and data science may be classified using eight dimensions which are: types of analytics, analytics process, skill set, data sources, business value, the scope of analytics, methods & techniques, and finally, technological platforms & tools. Significant implications for theory and practice are offered.
The concepts associated with business analytics, such as business intelligence and data science, ... more The concepts associated with business analytics, such as business intelligence and data science, are generally murky. However, this misconception has a harmful impact on both academics and practitioners. This uncertainty may cause universities to develop misleading or incoherent curricula. This lack of clarity may also cause enterprises to choose an inappropriate analytical solution to a business problem, resulting in project failure and wasted resources. Despite its significance; it appears that only practitioners and major consulting firms are exerting significant effort to address this matter. Hence, this study aims to fill this void and uses the Delphi method to indicate that business intelligence and data science may be classified using eight dimensions which are: types of analytics, analytics process, skill set, data sources, business value, the scope of analytics, methods & techniques, and finally, technological platforms & tools. Significant implications for theory and practice are offered.
There is a stressing need in the literature for the application of the well-known social cognitiv... more There is a stressing need in the literature for the application of the well-known social cognitive theory in the area of electronic commerce (e-commerce), but more specifically, in the developing countries such as Jordan. To better understand how individual differences influence the use of e-commerce (B2C e-commerce) a conceptual framework was developed and modeled based on Bandura's social cognitive theory to test the importance of dynamic and stable traits (i.e., e-commerce self-efficacy, outcome expectations, trait anxiety, e-commerce anxiety, and consumer trust) on the intention of an individual to shop online. A self-administered questionnaire was used to capture the data from individual users in Jordan, from whom only 3% are e-commerce users (Arab Advisors Group Survey, 2011). In order to test the hypotheses introduced in the research model of this study, a method that engages individuals in a free simulation of real-life e-commerce situations was adopted. The findings indicate that ecommerce self-efficacy, outcome expectation, technology anxiety, and consumer trust are all significant predictors of the Jordanian intention to use e-commerce. E-commerce self-efficacy was the second powerful factor after consumer trust in determining consumer intention to shop online. In addition, this study surprisingly shows that general self-efficacy and trait anxiety do not influence the specific e-commerce self-efficacy. From a theoretical perspective, the study attempts to further our understanding of the nomological network of individual differences that lead to e-commerce usage. From a practical perspective, the findings can help in designing more effective strategies aiming to increase the use of e-commerce for individuals with different dispositional characteristics by providing some valuable insights into the performance and adoption of e-commerce by individual customers. These insights can help designers/developers, implementers, and managers of organizations of e-commerce systems to improve the effectiveness of their electronic services and increase the usage rates of e-commerce in the developing world in general. [Mahmoud Al-dalahmeh, Anas Aloudat, Omar Al-Hujran, Mutaz M. Al-Debei. An empirical investigation on the Role of Self-efficacy, Outcome Expectations, Anxiety, and Trust in B2C e-commerce from the Aspects of Social Cognitive Theory.
Nowadays, most of the economic activities and business models are driven by the unprecedented evo... more Nowadays, most of the economic activities and business models are driven by the unprecedented evolution of theories and technologies. The impregnation of these achievements into our society is present everywhere, and it is only question of user education and business models optimization towards a digital society. Progress in cognitive science, knowledge acquisition, representation, and processing helped to deal with imprecise, uncertain or incomplete information. Management of geographical and temporal information becomes a challenge, in terms of volume, speed, semantic, decision, and delivery. Information technologies allow optimization in searching an interpreting data, yet special constraints imposed by the digital society require on-demand, ethics, and legal aspects, as well as user privacy and safety. The event was very competitive in its selection process and very well perceived by the international scientific and industrial communities. As such, it is attracting excellent con...
Ontology engineering is a relatively new field in computer and information sciences. Its primary ... more Ontology engineering is a relatively new field in computer and information sciences. Its primary goal is to develop methodologies for modelling and building ontologies. These ontologies represent knowledge as a set of concepts within a specific domain. A common problem is, though, that it is almost impossible for domain experts to design and model their own ontology in the domain of E-Government without having the basic knowledge of computer science, especially in the field of ontology engineering. The goal of this paper is to describe, how the Rich Ontology Creation Kit for E-Government Transition (ROCKET), an ontology creation tool based on the Eclipse RCP framework, supports legal experts to bridge the gap between domain and technical specialists. To accomplish that goal, the web application SeGoF is described, which uses ontologies as an input for the automatic generation of E-Government forms based on semantic descriptions. Moreover, the methodology “Ontology Driven EGovernment...
In response to the COVID-19 pandemic, governments worldwide are pursuing digital government strat... more In response to the COVID-19 pandemic, governments worldwide are pursuing digital government strategies and exploring innovative technologies to provide up-to-date information. Many countries, such as the United Arab Emirates (UAE), are embracing digital transformation and accelerating the use of smart government technologies to increase the resilience of healthcare systems and improve public services. The extant literature requires rigorous development of the concept of smart government. Indeed, prior literature indicates an urgent need for research on smart government policy and use. Therefore, this study aims to evaluate the smart government capabilities of the UAE’s Ministry of Health and Prevention by developing criteria for evaluating smart government. The findings reveal that the Ministry is forward thinking in promoting state-of-the-art technologies such as new mobile apps and services that have helped in the fight against COVID-19
The International Arab Journal of Information Technology, 2020
For financial institutions and the banking industry, it is very crucial to have predictive models... more For financial institutions and the banking industry, it is very crucial to have predictive models for their core financial activities, and especially those activities which play major roles in risk management. Predicting loan default is one of the critical issues that banks and financial institutions focus on, as huge revenue loss could be prevented by predicting customer’s ability not only to pay back, but also to be able to do that on time. Customer loan default prediction is a task of proactively identifying customers who are most probably to stop paying back their loans. This is usually done by dynamically analyzing customers’ relevant information and behaviors. This is significant so as the bank or the financial institution can estimate the borrowers’ risk. Many different machine learning classification models and algorithms have been used to predict customers’ ability to pay back loans. In this paper, three different classification methods (Naïve Bayes, Decision Tree, and Rand...
The International Arab Journal of Information Technology, 2020
For financial institutions and the banking industry, it is very crucial to have predictive models... more For financial institutions and the banking industry, it is very crucial to have predictive models for their core financial activities, and especially those activities which play major roles in risk management. Predicting loan default is one of the critical issues that banks and financial institutions focus on, as huge revenue loss could be prevented by predicting customer’s ability not only to pay back, but also to be able to do that on time. Customer loan default prediction is a task of proactively identifying customers who are most probably to stop paying back their loans. This is usually done by dynamically analyzing customers’ relevant information and behaviors. This is significant so as the bank or the financial institution can estimate the borrowers’ risk. Many different machine learning classification models and algorithms have been used to predict customers’ ability to pay back loans. In this paper, three different classification methods (Naïve Bayes, Decision Tree, and Rand...
Based on the Resource-Based View (RBV) literature, this study aims at developing and implementing... more Based on the Resource-Based View (RBV) literature, this study aims at developing and implementing a novel and comprehensive model so as to measure the effect of CRM resources on CRM capabilities and the effect of the latter on business performance. CRM resources are defined as infrastructural CRM resources (i.e. technological resources, human resources, and organizational resources), and cultural CRM resources (i.e. customer orientation, learning orientation, and result orientation). CRM capabilities are measured through an organization’s customer interaction capability, customer relationship upgrading capability, and customer win-back capability. As for performance, this study measures business performance comprehensively from financial and marketing perspectives. Although the results indicate that CRM infrastructural resources has a positive and direct effect on CRM capabilities, the effect of customer orientation culture and learning orientation culture on CRM capabilities was si...
Based on the Resource-Based View (RBV) literature, this study aims at developing and implementing... more Based on the Resource-Based View (RBV) literature, this study aims at developing and implementing a novel and comprehensive model so as to measure the effect of CRM resources on CRM capabilities and the effect of the latter on business performance. CRM resources are defined as infrastructural CRM resources (i.e. technological resources, human resources, and organizational resources), and cultural CRM resources (i.e. customer orientation, learning orientation, and result orientation). CRM capabilities are measured through an organization’s customer interaction capability, customer relationship upgrading capability, and customer win-back capability. As for performance, this study measures business performance comprehensively from financial and marketing perspectives. Although the results indicate that CRM infrastructural resources has a positive and direct effect on CRM capabilities, the effect of customer orientation culture and learning orientation culture on CRM capabilities was si...
Ontologies are key enablers for sharing precise and machine-understandable semantics among differ... more Ontologies are key enablers for sharing precise and machine-understandable semantics among different applications and parties. Yet, for ontologies to meet these expectations, their quality must be of a good standard. The quality of an ontology is strongly based on the design method employed. This paper addresses the design problems related to the modelling of ontologies, with specific concentration on the issues related to the quality of the conceptualisations produced. The paper aims to demonstrate the impact of the modelling paradigm adopted on the quality of ontological models and, consequently, the potential impact that such a decision can have in relation to the development of software applications. To this aim, an ontology that is conceptualised based on the Object Role Modelling (ORM) approach is re-engineered into a one modelled on the basis of the Object Paradigm (OP). Next, the two ontologies are analytically compared using the specified criteria. The conducted comparison highlights that using the OP for ontology conceptualisation can provide more expressive, reusable, objective and temporal ontologies than those conceptualised on the basis of the ORM approach.
Ontologies are key enablers for sharing precise and machine-understandable semantics among differ... more Ontologies are key enablers for sharing precise and machine-understandable semantics among different applications and parties. Yet, for ontologies to meet these expectations, their quality must be of a good standard. The quality of an ontology is strongly based on the design method employed. This paper addresses the design problems related to the modelling of ontologies, with specific concentration on the issues related to the quality of the conceptualisations produced. The paper aims to demonstrate the impact of the modelling paradigm adopted on the quality of ontological models and, consequently, the potential impact that such a decision can have in relation to the development of software applications. To this aim, an ontology that is conceptualised based on the Object Role Modelling (ORM) approach is re-engineered into a one modelled on the basis of the Object Paradigm (OP). Next, the two ontologies are analytically compared using the specified criteria. The conducted comparison highlights that using the OP for ontology conceptualisation can provide more expressive, reusable, objective and temporal ontologies than those conceptualised on the basis of the ORM approach.
Mutaz M. Al-Debei Brunel University, UB8, 3PH, London, UK. School of Information Systems, Computi... more Mutaz M. Al-Debei Brunel University, UB8, 3PH, London, UK. School of Information Systems, Computing and Mathematics. Tel.: +44 (0) 1895 267099, Fax: +44 (0) 1895 251686 [email protected] ... Cellular networks and telecommunications bring major ...
Proceedings of the Americas Conference on Information Systems (AMCIS), 2008
Recent rapid advances in ICTs, specifically in Internet and mobile technologies, have highlighted... more Recent rapid advances in ICTs, specifically in Internet and mobile technologies, have highlighted the rising importance of the Business Model (BM) in Information Systems (IS). Despite agreement on its importance to an organization's success, the concept is still fuzzy and vague, and there is no consensus regarding its definition. Furthermore, understanding the BM domain by identifying its meaning, fundamental pillars, and its relevance to other business concepts is by no means complete. In this paper we aim to ...
Recent rapid advances in Information and Communication Technologies (ICTs) have highlighted the r... more Recent rapid advances in Information and Communication Technologies (ICTs) have highlighted the rising importance of the Business Model (BM) concept in the field of Information Systems (IS). Despite agreement on its importance to an organization's success, the concept is still fuzzy and vague, and there is little consensus regarding its compositional facets. Identifying the fundamental concepts, modeling principles, practical functions, and reach of the BM relevant to IS and other business concepts is by no means complete. This paper, following a comprehensive review of the literature, principally employs the content analysis method and utilizes a deductive reasoning approach to provide a hierarchical taxonomy of the BM concepts from which to develop a more comprehensive framework. This framework comprises four fundamental aspects. First, it identifies four primary BM dimensions along with their constituent elements forming a complete ontological structure of the concept. Second, it cohesively organizes the BM modeling principles, that is, guidelines and features. Third, it explains the reach of the concept showing its interactions and intersections with strategy, business processes, and IS so as to place the BM within the world of digital business. Finally, the framework explores three major functions of BMs within digital organizations to shed light on the practical significance of the concept. Hence, this paper links the BM facets in a novel manner offering an intact definition. In doing so, this paper provides a unified conceptual framework for the BM concept that we argue is comprehensive and appropriate to the complex nature of businesses today. This leads to fruitful implications for theory and practice and also enables us to suggest a research agenda using our conceptual framework.
The concept of Big Data has become a reality due to our capability to create and collect digital ... more The concept of Big Data has become a reality due to our capability to create and collect digital data at an extraordinary rate. Despite its significance, the concept of Big Data is still largely overlooked and underestimated. Drawing on seven case studies of service providers and customers from different countries, this study contributes to the existing body of knowledge by comprehensively addressing the opportunities and challenges of Big Data.
The concepts associated with business analytics, such as business intelligence and data science, ... more The concepts associated with business analytics, such as business intelligence and data science, are generally murky. However, this misconception has a harmful impact on both academics and practitioners. This uncertainty may cause universities to develop misleading or incoherent curricula. This lack of clarity may also cause enterprises to choose an inappropriate analytical solution to a business problem, resulting in project failure and wasted resources. Despite its significance; it appears that only practitioners and major consulting firms are exerting significant effort to address this matter. Hence, this study aims to fill this void and uses the Delphi method to indicate that business intelligence and data science may be classified using eight dimensions which are: types of analytics, analytics process, skill set, data sources, business value, the scope of analytics, methods & techniques, and finally, technological platforms & tools. Significant implications for theory and practice are offered.
The concepts associated with business analytics, such as business intelligence and data science, ... more The concepts associated with business analytics, such as business intelligence and data science, are generally murky. However, this misconception has a harmful impact on both academics and practitioners. This uncertainty may cause universities to develop misleading or incoherent curricula. This lack of clarity may also cause enterprises to choose an inappropriate analytical solution to a business problem, resulting in project failure and wasted resources. Despite its significance; it appears that only practitioners and major consulting firms are exerting significant effort to address this matter. Hence, this study aims to fill this void and uses the Delphi method to indicate that business intelligence and data science may be classified using eight dimensions which are: types of analytics, analytics process, skill set, data sources, business value, the scope of analytics, methods & techniques, and finally, technological platforms & tools. Significant implications for theory and practice are offered.
There is a stressing need in the literature for the application of the well-known social cognitiv... more There is a stressing need in the literature for the application of the well-known social cognitive theory in the area of electronic commerce (e-commerce), but more specifically, in the developing countries such as Jordan. To better understand how individual differences influence the use of e-commerce (B2C e-commerce) a conceptual framework was developed and modeled based on Bandura's social cognitive theory to test the importance of dynamic and stable traits (i.e., e-commerce self-efficacy, outcome expectations, trait anxiety, e-commerce anxiety, and consumer trust) on the intention of an individual to shop online. A self-administered questionnaire was used to capture the data from individual users in Jordan, from whom only 3% are e-commerce users (Arab Advisors Group Survey, 2011). In order to test the hypotheses introduced in the research model of this study, a method that engages individuals in a free simulation of real-life e-commerce situations was adopted. The findings indicate that ecommerce self-efficacy, outcome expectation, technology anxiety, and consumer trust are all significant predictors of the Jordanian intention to use e-commerce. E-commerce self-efficacy was the second powerful factor after consumer trust in determining consumer intention to shop online. In addition, this study surprisingly shows that general self-efficacy and trait anxiety do not influence the specific e-commerce self-efficacy. From a theoretical perspective, the study attempts to further our understanding of the nomological network of individual differences that lead to e-commerce usage. From a practical perspective, the findings can help in designing more effective strategies aiming to increase the use of e-commerce for individuals with different dispositional characteristics by providing some valuable insights into the performance and adoption of e-commerce by individual customers. These insights can help designers/developers, implementers, and managers of organizations of e-commerce systems to improve the effectiveness of their electronic services and increase the usage rates of e-commerce in the developing world in general. [Mahmoud Al-dalahmeh, Anas Aloudat, Omar Al-Hujran, Mutaz M. Al-Debei. An empirical investigation on the Role of Self-efficacy, Outcome Expectations, Anxiety, and Trust in B2C e-commerce from the Aspects of Social Cognitive Theory.
Nowadays, most of the economic activities and business models are driven by the unprecedented evo... more Nowadays, most of the economic activities and business models are driven by the unprecedented evolution of theories and technologies. The impregnation of these achievements into our society is present everywhere, and it is only question of user education and business models optimization towards a digital society. Progress in cognitive science, knowledge acquisition, representation, and processing helped to deal with imprecise, uncertain or incomplete information. Management of geographical and temporal information becomes a challenge, in terms of volume, speed, semantic, decision, and delivery. Information technologies allow optimization in searching an interpreting data, yet special constraints imposed by the digital society require on-demand, ethics, and legal aspects, as well as user privacy and safety. The event was very competitive in its selection process and very well perceived by the international scientific and industrial communities. As such, it is attracting excellent con...
Ontology engineering is a relatively new field in computer and information sciences. Its primary ... more Ontology engineering is a relatively new field in computer and information sciences. Its primary goal is to develop methodologies for modelling and building ontologies. These ontologies represent knowledge as a set of concepts within a specific domain. A common problem is, though, that it is almost impossible for domain experts to design and model their own ontology in the domain of E-Government without having the basic knowledge of computer science, especially in the field of ontology engineering. The goal of this paper is to describe, how the Rich Ontology Creation Kit for E-Government Transition (ROCKET), an ontology creation tool based on the Eclipse RCP framework, supports legal experts to bridge the gap between domain and technical specialists. To accomplish that goal, the web application SeGoF is described, which uses ontologies as an input for the automatic generation of E-Government forms based on semantic descriptions. Moreover, the methodology “Ontology Driven EGovernment...
In response to the COVID-19 pandemic, governments worldwide are pursuing digital government strat... more In response to the COVID-19 pandemic, governments worldwide are pursuing digital government strategies and exploring innovative technologies to provide up-to-date information. Many countries, such as the United Arab Emirates (UAE), are embracing digital transformation and accelerating the use of smart government technologies to increase the resilience of healthcare systems and improve public services. The extant literature requires rigorous development of the concept of smart government. Indeed, prior literature indicates an urgent need for research on smart government policy and use. Therefore, this study aims to evaluate the smart government capabilities of the UAE’s Ministry of Health and Prevention by developing criteria for evaluating smart government. The findings reveal that the Ministry is forward thinking in promoting state-of-the-art technologies such as new mobile apps and services that have helped in the fight against COVID-19
The International Arab Journal of Information Technology, 2020
For financial institutions and the banking industry, it is very crucial to have predictive models... more For financial institutions and the banking industry, it is very crucial to have predictive models for their core financial activities, and especially those activities which play major roles in risk management. Predicting loan default is one of the critical issues that banks and financial institutions focus on, as huge revenue loss could be prevented by predicting customer’s ability not only to pay back, but also to be able to do that on time. Customer loan default prediction is a task of proactively identifying customers who are most probably to stop paying back their loans. This is usually done by dynamically analyzing customers’ relevant information and behaviors. This is significant so as the bank or the financial institution can estimate the borrowers’ risk. Many different machine learning classification models and algorithms have been used to predict customers’ ability to pay back loans. In this paper, three different classification methods (Naïve Bayes, Decision Tree, and Rand...
The International Arab Journal of Information Technology, 2020
For financial institutions and the banking industry, it is very crucial to have predictive models... more For financial institutions and the banking industry, it is very crucial to have predictive models for their core financial activities, and especially those activities which play major roles in risk management. Predicting loan default is one of the critical issues that banks and financial institutions focus on, as huge revenue loss could be prevented by predicting customer’s ability not only to pay back, but also to be able to do that on time. Customer loan default prediction is a task of proactively identifying customers who are most probably to stop paying back their loans. This is usually done by dynamically analyzing customers’ relevant information and behaviors. This is significant so as the bank or the financial institution can estimate the borrowers’ risk. Many different machine learning classification models and algorithms have been used to predict customers’ ability to pay back loans. In this paper, three different classification methods (Naïve Bayes, Decision Tree, and Rand...
Based on the Resource-Based View (RBV) literature, this study aims at developing and implementing... more Based on the Resource-Based View (RBV) literature, this study aims at developing and implementing a novel and comprehensive model so as to measure the effect of CRM resources on CRM capabilities and the effect of the latter on business performance. CRM resources are defined as infrastructural CRM resources (i.e. technological resources, human resources, and organizational resources), and cultural CRM resources (i.e. customer orientation, learning orientation, and result orientation). CRM capabilities are measured through an organization’s customer interaction capability, customer relationship upgrading capability, and customer win-back capability. As for performance, this study measures business performance comprehensively from financial and marketing perspectives. Although the results indicate that CRM infrastructural resources has a positive and direct effect on CRM capabilities, the effect of customer orientation culture and learning orientation culture on CRM capabilities was si...
Based on the Resource-Based View (RBV) literature, this study aims at developing and implementing... more Based on the Resource-Based View (RBV) literature, this study aims at developing and implementing a novel and comprehensive model so as to measure the effect of CRM resources on CRM capabilities and the effect of the latter on business performance. CRM resources are defined as infrastructural CRM resources (i.e. technological resources, human resources, and organizational resources), and cultural CRM resources (i.e. customer orientation, learning orientation, and result orientation). CRM capabilities are measured through an organization’s customer interaction capability, customer relationship upgrading capability, and customer win-back capability. As for performance, this study measures business performance comprehensively from financial and marketing perspectives. Although the results indicate that CRM infrastructural resources has a positive and direct effect on CRM capabilities, the effect of customer orientation culture and learning orientation culture on CRM capabilities was si...
Ontologies are key enablers for sharing precise and machine-understandable semantics among differ... more Ontologies are key enablers for sharing precise and machine-understandable semantics among different applications and parties. Yet, for ontologies to meet these expectations, their quality must be of a good standard. The quality of an ontology is strongly based on the design method employed. This paper addresses the design problems related to the modelling of ontologies, with specific concentration on the issues related to the quality of the conceptualisations produced. The paper aims to demonstrate the impact of the modelling paradigm adopted on the quality of ontological models and, consequently, the potential impact that such a decision can have in relation to the development of software applications. To this aim, an ontology that is conceptualised based on the Object Role Modelling (ORM) approach is re-engineered into a one modelled on the basis of the Object Paradigm (OP). Next, the two ontologies are analytically compared using the specified criteria. The conducted comparison highlights that using the OP for ontology conceptualisation can provide more expressive, reusable, objective and temporal ontologies than those conceptualised on the basis of the ORM approach.
Ontologies are key enablers for sharing precise and machine-understandable semantics among differ... more Ontologies are key enablers for sharing precise and machine-understandable semantics among different applications and parties. Yet, for ontologies to meet these expectations, their quality must be of a good standard. The quality of an ontology is strongly based on the design method employed. This paper addresses the design problems related to the modelling of ontologies, with specific concentration on the issues related to the quality of the conceptualisations produced. The paper aims to demonstrate the impact of the modelling paradigm adopted on the quality of ontological models and, consequently, the potential impact that such a decision can have in relation to the development of software applications. To this aim, an ontology that is conceptualised based on the Object Role Modelling (ORM) approach is re-engineered into a one modelled on the basis of the Object Paradigm (OP). Next, the two ontologies are analytically compared using the specified criteria. The conducted comparison highlights that using the OP for ontology conceptualisation can provide more expressive, reusable, objective and temporal ontologies than those conceptualised on the basis of the ORM approach.
Mutaz M. Al-Debei Brunel University, UB8, 3PH, London, UK. School of Information Systems, Computi... more Mutaz M. Al-Debei Brunel University, UB8, 3PH, London, UK. School of Information Systems, Computing and Mathematics. Tel.: +44 (0) 1895 267099, Fax: +44 (0) 1895 251686 [email protected] ... Cellular networks and telecommunications bring major ...
Proceedings of the Americas Conference on Information Systems (AMCIS), 2008
Recent rapid advances in ICTs, specifically in Internet and mobile technologies, have highlighted... more Recent rapid advances in ICTs, specifically in Internet and mobile technologies, have highlighted the rising importance of the Business Model (BM) in Information Systems (IS). Despite agreement on its importance to an organization's success, the concept is still fuzzy and vague, and there is no consensus regarding its definition. Furthermore, understanding the BM domain by identifying its meaning, fundamental pillars, and its relevance to other business concepts is by no means complete. In this paper we aim to ...
Recent rapid advances in Information and Communication Technologies (ICTs) have highlighted the r... more Recent rapid advances in Information and Communication Technologies (ICTs) have highlighted the rising importance of the Business Model (BM) concept in the field of Information Systems (IS). Despite agreement on its importance to an organization's success, the concept is still fuzzy and vague, and there is little consensus regarding its compositional facets. Identifying the fundamental concepts, modeling principles, practical functions, and reach of the BM relevant to IS and other business concepts is by no means complete. This paper, following a comprehensive review of the literature, principally employs the content analysis method and utilizes a deductive reasoning approach to provide a hierarchical taxonomy of the BM concepts from which to develop a more comprehensive framework. This framework comprises four fundamental aspects. First, it identifies four primary BM dimensions along with their constituent elements forming a complete ontological structure of the concept. Second, it cohesively organizes the BM modeling principles, that is, guidelines and features. Third, it explains the reach of the concept showing its interactions and intersections with strategy, business processes, and IS so as to place the BM within the world of digital business. Finally, the framework explores three major functions of BMs within digital organizations to shed light on the practical significance of the concept. Hence, this paper links the BM facets in a novel manner offering an intact definition. In doing so, this paper provides a unified conceptual framework for the BM concept that we argue is comprehensive and appropriate to the complex nature of businesses today. This leads to fruitful implications for theory and practice and also enables us to suggest a research agenda using our conceptual framework.
The concept of Big Data has become a reality due to our capability to create and collect digital ... more The concept of Big Data has become a reality due to our capability to create and collect digital data at an extraordinary rate. Despite its significance, the concept of Big Data is still largely overlooked and underestimated. Drawing on seven case studies of service providers and customers from different countries, this study contributes to the existing body of knowledge by comprehensively addressing the opportunities and challenges of Big Data.
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Papers by Mutaz Debei