Ahmed Elragal

Ahmed Elragal
Luleå University of Technology | LTU · Department of Computer Science, Electrical and Space Engineering (SRT)

PhD in Information Systems

About

81
Publications
291,267
Reads
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Citations
Introduction
Prof. Ahmed Elragal (PhD, MBA, BSc) is a Professor of Information Systems at Luleå University of Technology in Sweden, since January 2014. He is also an Adjunct Professor of Information Systems at Kristiania University College (KUC), Oslo. Prof. Elragal used to work at the Department of Business Informatics and Operations Management, German University in Cairo (GUC), 2007-2018 and the Arab Academy for Science, Technology, and Maritime Transport (AASTMT), 1992-2007.
Additional affiliations
January 2014 - present
Luleå University of Technology
Position
  • Professor (Associate)
August 2007 - present
The German University in Cairo
Position
  • Professor (Associate)
August 2007 - present
The German University in Cairo
Position
  • Professor (Associate)
Education
January 1999 - November 2001
University of Plymouth
Field of study
  • Decision Support Systems

Publications

Publications (81)
Conference Paper
Full-text available
In the information era, enormous amounts of data have become available on hand to decision makers. Big data refers to datasets that are not only big, but also high in variety and velocity, which makes them difficult to handle using traditional tools and techniques. Due to the rapid growth of such data, solutions need to be studied and provided in o...
Conference Paper
Full-text available
Service innovation is attracting attention with the expanding service industries and economies. Accompanied by major developments in ICT and sensory and digital technologies, the interest in digital service innovation (DSI), both from academia and industry, is increasing. Digitization and the accompanying technological advancements are leading to p...
Article
Full-text available
Most scientists are accustomed to make predictions based on consolidated and accepted theories pertaining to the domain of prediction. However, nowadays big data analytics (BDA) is able to deliver predictions based on executing a sequence of data processing while seemingly abstaining from being theoretically informed about the subject matter. This...
Article
Full-text available
Decisions continue to be important to researchers, organizations and societies. However, decision research requires re-orientation to attain the future of data-driven decision making, accommodating such emerging topics and information technologies as big data, analytics, machine learning, and automated decisions. Accordingly, there is a dire need f...
Article
Full-text available
The relationship between big data analytics (BDA) and smart cities (SCs) has been addressed in several articles. However, few articles have investigated the influence of exploiting BDA in data-driven decision-making from an empirical perspective in a case study context. Accordingly, we aim to tackle this scarcity of case-study research addressing t...
Article
Full-text available
Interest in smart cities (SCs) and big data analytics (BDA) has increased in recent years, revealing the bond between the two fields. An SC is characterized as a complex system of systems involving various stakeholders, from planners to citizens. Within the context of SCs, BDA offers potential as a data-driven decision-making enabler. Although ther...
Article
Full-text available
Transforming the state-of-the-art definition and anatomy of enterprise systems (ESs) seems to some academics and practitioners as an unavoidable destiny. Value depletion lead by early retirement and/or replacement of ESs solutions has been a constant throughout the past decade. That did drive an enormous amount of research that works on addressing...
Article
Ongoing advancements in technology have dramatically changed the disclosure media that companies adopt. Such disclosure media have evolved from traditional paper-based ones to the internet as the new platform for disclosing information on companies’ designated websites; however, the new media for disclosures are currently social media platforms. Am...
Article
Full-text available
Purpose Within digital innovation, there are two significant consequences of the pervasiveness of digital technology: (1) the increasing connectivity is enabling a wider reach and scope of innovation structures, such as innovation networks and (2) the unprecedented availability of digital data is creating new opportunities for innovation. According...
Article
Full-text available
Purpose Within digital innovation, there are two significant consequences of the pervasiveness of digital technology: (1) the increasing connectivity is enabling a wider reach and scope of innovation structures, such as innovation networks and (2) the unprecedented availability of digital data is creating new opportunities for innovation. According...
Article
Purpose-This study investigates the extent and characteristics of corporate Internet disclosure via companies’ websites as well via social media and networks sites in the four leading English speaking stock markets, namely Australia, Canada, the United Kingdom, and the United States. Design/methodology/approach–A disclosure index comprising of a se...
Article
Full-text available
Abstract Scholars have been increasingly calling for innovative research in the organizational sciences in general, and the information systems (IS) field in specific, one that breaks from the dominance of gap-spotting and specific methodical confinements. Hence, pushing the boundaries of information systems is needed, and one way to do so is by re...
Article
Purpose The purpose of this paper is to investigate corporate financial disclosure via Twitter among the top listed 350 companies in the UK as well as identify the determinants of the extent of social media usage to disclose financial information. Design/methodology/approach This study applies an unsupervised machine learning technique, namely, La...
Conference Paper
Many technologies have been used in education. Such technologies fall under three main types: learning management systems; education data mining; and AI-enabled technologies. This report focuses on the use of robotics in interactive education. Over the past few years, interest in utilization of robotics in education has increased. Multiple attempts...
Article
Full-text available
An analytics-empowered enterprise system looks to many organizations to be a far-fetched target, owing to the vast amounts of factors that need to be controlled across the implementation lifecycle activities, especially during usage and maintenance phases. On the other hand, advanced analytics techniques such as machine learning and data mining hav...
Article
Full-text available
Given the different types of artifacts and their various evaluation methods, one of the main challenges faced by researchers in design science research (DSR) is choosing suitable and efficient methods during the artifact evaluation phase. With the emergence of big data analytics, data scientists conducting DSR are also challenged with identifying s...
Research Proposal
Full-text available
Call for Papers- Special Issue: Rejuvenating Enterprise Systems Scandinavian Journal of Information Systems
Cover Page
Full-text available
Article
Full-text available
Introducing an Enterprise Resource Planning (ERP) system within an organization can bring many benefits and paybacks, yet an effective implementation of a fully functioning ERP system is still a challenge, the odds are high the costly investment might turn into an implementation failure or even lead to bankruptcy. To prevent such situations, organi...
Conference Paper
Full-text available
Smart City (SC) is an emerging concept aiming at mitigating the challenges raised due to the continuous urbanization development. To face these challenges, government decision makers sponsor SC projects targeting sustainable economic growth and better quality of life for inhabitants and visitors. Information and Communication Technologies (ICT) is...
Conference Paper
Big data visualization tools are analytical tools used by organizations for the purpose of discovering knowledge. With the support of interactive visual interfaces, methods and techniques for analyzing big data are applied to facilitate the knowledge discovery process and provide domain relevant insights. Many studies, both academic and industrial,...
Article
Full-text available
In the public sector, the EU legislation requires preservation and opening of increasing amounts of heterogeneous digital information that should be utilized by citizens and businesses. While technologies such as big data analytics (BDA) have emerged, opening of digital archives and collections at a large scale is in its infancy. Opening archives a...
Article
Full-text available
Information is a key success factor influencing the performance of decision makers, specifically the quality of their decisions. Nowadays, sheer amounts of data are available for organizations to analyze. Data is considered the raw material of the 21st century, and abundance is assumed with today's 15 billion devices [aka Things!] already connected...
Conference Paper
Information is a key success factor influencing the performance of decision makers, specifically the quality of their decisions. Nowadays, sheer amounts of data are available for organizations to analyze. Data is considered the raw material of the 21st century, and abundance is assumed with today’s 15 billion devices [aka Things!] already connected...
Article
Full-text available
In 2011, at the Hanover Fair, the term Industry 4.0 was first coined. In October 2012, the Working Group on Industry 4.0, presented a set of implementation recommendations to the German government.The term Industry 4.0 initiates from a project in the high-tech strategy of the German government. Such project advocates the computerization of the manu...
Article
Organizations rely on various types of information systems (IS) to manage day-to-day business and make decisions such as enterprise resource planning (ERP) and supply chain management (SCM) systems. Organizations rely on ERP systems to replace their legacy systems, integrate core business processes and to help adding value and increasing visibility...
Conference Paper
This research investigates how companies operating in emerging markets and investing in latest IT solutions can be supported in developing maturity in business-IT alignment faster than their predeces-sors in developed countries. It follows up the consultant perspective through documenting ex-post the participant’s observations, reflected through pa...
Technical Report
Full-text available
The research area known as big data is characterized by the 3 V's, which are volume ; variety; and velocity. Recently, also veracity and value have been associated with big data and that adds up to the 5 V's. Big data related information systems (IS) are typically highly distributed and scalable in order to handle the huge datasets in organizations...
Technical Report
Full-text available
The research area known as big data is characterized by the 3 V's, which are volume ; variety; and velocity. Recently, also veracity and value have been associated with big data and that adds up to the 5 V's. Big data related information systems (IS) are typically highly distributed and scalable in order to handle the huge datasets in organizations...
Technical Report
Full-text available
The research area known as big data is characterized by the 3 V's, which are volume ; variety; and velocity. Recently, also veracity and value have been associated with big data and that adds up to the 5 V's. Big data related information systems (IS) are typically highly distributed and scalable in order to handle the huge datasets in organizations...
Conference Paper
Abstract - A huge amount of location and tracking data is gathered by tracking and location technologies, such as global positioning system (GPS) and global system for mobile communication (GSM) devices leading to the collection of large spatiotemporal datasets and to the opportunity of discovering usable knowledge about movement behavior. Movement...
Article
Full-text available
Due to business dynamics and complexities, aligning information systems to the organizational strategy goals has appeared to be a concern for researchers and practitioners over the last decade. The challenge of achieving this alignment becomes even more severe and demanding day after day. Many published research is rich with regards to alignment mo...
Article
Full-text available
The world is witnessing an unprecedented interest in big data. Big data is data that is big in size (volume), big in variety (structured; semi-structured; unstructured), and big in speed of change (velocity). It was reported that almost 90% of the data worldwide was just created in the past 2 years. Therefore, this paper is an attempt to align ERP...
Conference Paper
Full-text available
This literature review paper summarizes the state-of-the-art research on big data analytics. Due to massive amount of data exchanged everyday and the increased need for better data-based decision, businesses nowadays are looking for ways to efficiently manage, and optimize these huge datasets. Moreover, because of globalization, partnerships, value...
Conference Paper
This paper aims to explore and investigate two ERP deployment methods (DM); on-premise (OP) and cloud-based (CB). The paper will focus on the differences between their benefits and challenges. In the end, a framework will be devised in order to assist companies with regards to whether to adopt the OP or the CB method. A case study is used as the mo...
Conference Paper
Huge amount of location and tracking data is gathered by location and tracking technologies, such as global positioning system (GPS) and global system for mobile communication (GSM) devices; leading to the collection of large spatiotemporal datasets and to the opportunity of discovering usable knowledge about movement behavior. Movement behavior ca...
Conference Paper
There is currently a huge amount of data being collected about movements of objects. Such data is called spatiotemporal data and paths left by moving-objects are called trajectories. Recently, researchers have been targeting those trajectories for extracting interesting and useful knowledge by means of pattern analysis and data mining. But, it is d...
Conference Paper
Nowadays, many organisations have a number of disparate data stores, which need a centralised single version of truth decision support system that would enable executives to monitor the business performance and make decisions in an efficient manner. Currently, emerging technological advancements pose lots of opportunities towards the transformation...
Article
Full-text available
Nowadays, many organizations have a number of disparate data stores, which need a centralized single version of truth decision support system that would enable executives to monitor the business performance and make decisions in an efficient manner. Currently, emerging technological advancements pose lots of opportunities towards the transformation...
Conference Paper
Full-text available
According to statistics, majority of ERP implementations fail. Failure means either total cancellation of the project, or failure to go-live on time and/or within budget constraints. Mainstream literature focuses on different reasons for failure including poor project management, resistance to change, lack of top management support, insufficient us...
Article
Purpose ‐ Trajectory is the path a moving object takes in space. To understand the trajectory movement patters, data mining is used. However, pattern analysis needs semantics to be understood. Therefore, the purpose of this paper is to enrich trajectories with semantic annotations, such as the name of the location where the trajectory has stopped,...
Conference Paper
There is currently an increasing availability of large spatiotemporal datasets. Sequences of spatiotemporal data or paths, also known as trajectories, can be captured by modern technology and stored in moving-object databases (MOD) or a trajectory data warehouse. It is a common challenge for knowledge discovery within MODs to query proximities and...
Article
Full-text available
A lot of research has been undertaken focusing on ERP systems lifecycles, but very little paid attention to retirement. ERP retirement means the replacement of an ERP with another. The aim of this research paper is to investigate why and when should organizations retire their ERP systems. A convenience case study of a SME has been selected from Egy...
Article
Full-text available
Enterprise resource planning (ERP) systems adoptions require substantial resources and investments. The majority of businesses around the globe can be considered to be small and medium sized enterprises (SMEs). Thus, SMEs are seen to be typical companies that are the cornerstone of most economies. Compared with large enterprises, an SME-context con...
Chapter
This chapter is an effort towards illustrating the use of expert panels (EP) as a means of eliciting knowledge from a group of enterprise resource planning (ERP) experts in an exploratory research. The development of a cost estimation model for ERP adoptions is very crucial for research and practice, and that was the main reason behind the willingn...
Article
Full-text available
This paper explores the enterprise resource planning (ERP) systems literature in an attempt to elucidate knowledge to help us see the future of ERP systems’ research. The main purpose of this research is to study the development of ERP systems and other related areas in order to reach the constructs of mainstream literature. The analysis of literat...
Conference Paper
Recent developments in wireless technology, mobility and networking infrastructures increased the amounts of data being captured every second. Data captured from the digital traces of moving objects and devices is called trajectory data. With the increasing volume of spatiotemporal trajectories, constructive and meaningful knowledge needs to be ext...
Article
Full-text available
The emergence of the Enterprise 2.0 technologies indicates that they can provide value to different types of users and potentially different types of value. Many published research explored what these E2.0 tools and applications can offer to organizations, such as collaboration platforms, social networking and user-created content, enhancing their...
Article
Full-text available
This paper provides a framework for comparison between the implementation of ERP systems in-house versus the in-cloud implementations. The paper first establishes a framework for the comparison based on three factors: pre-live i.e., the implementation methodologies of both options, post-live i.e., cost, time, and the user-friendliness of the system...
Chapter
This chapter is an effort towards illustrating the use of expert panels (EP) as a means of eliciting knowledge from a group of enterprise resource planning (ERP) experts in an exploratory research. The development of a cost estimation model for ERP adoptions is very crucial for research and practice, and that was the main reason behind the willingn...
Conference Paper
Full-text available
A lot of research has been undertaken focusing on ERP systems lifecycles, but very little paid attention to retirement. ERP retirement means the replacement of an ERP with another. The aim of this research paper is to investigate why and when should organizations retire their ERP systems. A convenience case study of an SME has been selected from Eg...
Technical Report
Full-text available
In this case study, Egypt’s Census Bureau (CAPMAS) is described in terms of how it uses business intelligence to support its mission and objectives. The case is organized as follows: CAPMAS is described in terms of its mission, data used, agencies served, and the on-demand information services it offers. Then, the fundamentals of business intellige...
Article
Full-text available
There is currently plenty of research concerning the effect of Enterprise Resource Planning (ERP) Systems on business performance. Previous research has shown a mixed relationship between ERP and business performance where some suggested that ERP improves performance and others found that it does not. Previous research was mainly based on quantitat...
Article
Full-text available
Classification of enterprise portal systems (EP) based on their features is the topic of this paper. We propose a classification based on cluster analysis which depends on features collected from the internet. Results showed that systems were found to belong to different classes based on their features.
Article
Integrating business intelligence (BI) as a framework to support EGov decisions is vital. Data mining, a major BI component, is a group of techniques used to find hidden patterns and unknown facts in data sets. In this paper, we implemented the Pan America Health Organization (PAHO) and World Health Organization (WHO) PAHO/WHO hospital safety index...
Chapter
There has been an increasing interest in ERP systems in both research and practice in the last decade. But unfortunately in many occasions a lot of companies have stopped using these systems after they went-live with the implementation. This study is an attempt to reveal the factors influencing users‘ intention to continue using the ERP system. A s...
Conference Paper
Full-text available
This paper is an effort towards illustrating the use of expert panel (EP) as a mean of eliciting knowledge from a group of enterprise resource planning (ERP) experts as an exploratory research. The development of a cost estimation model (CEM) for ERP adoptions is very crucial for research and practice, and that was the main reason behind the willin...
Conference Paper
Outliers, the odd objects in the dataset, can be viewed from two different perspectives; the outliers as undesirable objects that should be treated or deleted in the data preparation step of the data mining process, and the outliers as interesting objects that are identified for their own interest in the data mining step of the mining process. In t...
Article
Outliers, the odd objects in the dataset, can be viewed from two different perspectives; the outliers as undesirable objects that should be treated or deleted in the data preparation step of the data mining process, and the outliers as interesting objects that are identified for their own interest in the data mining step of the mining process. In t...
Article
A lot of research has been undertaken focusing on ERP systems lifecycles, but very little paid attention to retirement. ERP retirement means the replacement of an ERP with another. The aim of this research paper is to investigate why and when should organizations retire their ERP systems. A convenience case study of an SME has been selected from Eg...
Article
Full-text available
Due to the rapid advancements in technology, and the innovations in mobile, sensor, and GPS devices, increasing amounts of data related to moving objects has become available. Trajectory data mining is the application of conventional data mining techniques on the movement of such trajectories. However, traditional raw trajectories are depicted only...

Questions

Question (1)
Question
The question is related to the future of enterprise systems in organisations to cope with the widespread use of today's hottest ICT topics i.e., big data; data science; open data; & IoT? Sure there is an impact, but what kind of impact is expected?

Projects

Projects (10)
Project
The main objectives and aim of the project is to define which suitable beyond state-of-the-art techniques for forecasting of mine seismicity should be apply and developed in a future full-scale project. The complexity of the physical phenomena in combination with spatial-temporal inhomogeneous physical rock properties imply that standard geophysical modelling algorithms a classical probabilistic seismic hazard analyses methods most likely are not applicable for the specific tasks of forecasting. The purpose of the project is therefore to investigate also if the tools referred as Artificial Intelligence, Machine Learning and Big Data analyses can provide analyses and produce results upon which robust decision can be made.
Project
CFP LINK: http://iris.cs.aau.dk/index.php/special-issue-call-for-papers.html Guest Editors Ahmed Elragal, Luleå University of Technology, Luleå, Sweden Moutaz Haddara, Kristiania University College, Oslo, Norway Eli Hustad, University of Agder, Kristiansand, Norway Important dates Submission deadline: March 10th, 2019 Guest editors’ constructive rejection: April 2st, 2019 First review completed: June 1st, 2019 Revised manuscript due: August 15th, 2019 Second review completed: October 30th, 2019 Revised manuscript due: December 20th, 2019 Publication date: June 2020 Submission Guidelines Article submissions for this special issue should follow the submission format and guidelines of the Scandinavian Journal of Information Systems. All papers will be peer-reviewed based on the journal’s review procedures. Authors must indicate in the cover letter that the paper is aimed for the Rejuvenating Enterprise Systems special issue to ensure that the submission will be handled by the right editors. Review Strategy A constructive rejection approach will be applied prior to the review process. All submissions will be initially screened by all guest editors as soon as the submission deadline passes. The authors whose articles fail to meet the journal’s standards or specific requirements will be notified soon after the submission deadline. The papers that pass the initial screening and that may be accepted for publication subject to certain conditions, will undergo a rigorous review process according to the publication plan. Authors of articles that are expected to be accepted, will be offered an opportunity to revise and resubmit their papers within a specified period. At least two independent reviewers shall review the submitted manuscripts based on their originality, quality, and relevance to this special issue’s theme. Idea in Brief In this special issue, the guest editors seek a diverse collection of articles that address the future of enterprise systems. Enterprise systems have existed for decades, and the majority of large organizations worldwide have implemented their enterprise systems (Gattiker & Goodhue, 2005). However, fluctuating levels of success have been reported over the years (Hustad & Olsen, 2014; Svejvig & Jensen, 2013). Companies of all sizes have become increasingly dependent on enterprise systems to integrate their various business functions, manage their operational and routine transactions, comply with regulations, manage their global supply chains, and benefit from the systems’ timely reporting capabilities (Haddara & Zach, 2011). Generally, enterprise systems’ implementations are resource intensive and require considerable financial investments. Their adoptions also result in widespread organizational changes (Volkoff, Strong, & Elmes, 2007). Despite enterprise systems’ demanding and risky implementation efforts, their substantial business value is recognized (Tian & Xu, 2015). The ex post literature is rich and diverse; however, an apparent gap in enterprise systems’ future relates to emerging technologies (Elragal & Haddara, 2012). Thus, there is a need to investigate how emerging technologies can shape the future of such systems. Currently, the characteristics of enterprise systems have radically changed. Businesses require agility and flexibility. Therefore, among others, enterprise resource planning (ERP) systems should respond to such dynamic needs of today’s businesses. New sourcing models for enterprise systems have recently been offered, and cloud sourcing has become a popular approach for small- and medium-sized enterprises (SMEs) in particular (El-Gazzar, Hustad, & Olsen, 2016). Moreover, new applications have been integrated with enterprise systems, forming the so-called hybrid systems. Such a hybrid system also incorporates systems from multiple vendors, as well as integrates data from on-premises with those on the cloud (Loebbecke, Thomas, & Ullrich, 2012). Enterprises also seek to utilize enterprise systems in more intelligent ways by analyzing their transaction data to support decision making on both strategic and tactical levels. Future enterprise systems are expected to support digital transformation to a greater extent. We strongly believe that five areas are reshaping the future of enterprise systems. Therefore, such systems need rejuvenation to sustain their well-established presence in organizations. These areas are as follows: Area 1. Cloud computing Area 2. Gamification Area 3. Blockchain technology Area 4. Big data analytics Area 5. Digitalization Scope and Focus of the Special Issue Topics of interest include but are not limited to the following: Area 1. Enterprise systems and cloud computing - Which enterprise system modules can move to the cloud, and which modules should stay on-premises? - How can enterprises obtain sustainable business if they decide to discontinue their cloud solution? - How can data privacy and security for cloud-based enterprise systems be maintained? - How can cloud-based enterprise systems deal with the data mobility required for efficient business processes? - How does standardization affect the investment on cloud-based enterprise systems? (For example, customers of an ERP system in the cloud need to continue using the standard version of the system; customization opportunities are quite limited). - What are the differences between SMEs and large businesses regarding challenges in utilizing cloud-based enterprise systems? Area 2. Gamification - Benefits that gamification offers to enterprise systems across their lifecycle - Enterprise system lifecycle phases and the corresponding benefits of gamification - Approaches, techniques, methods and strategies to gamify ES lifecycle phases and their impact Area 3. Blockchain technology - The potentials of blockchain technology for enterprise systems - Blockchain integration with enterprise systems - Deploying blockchain technology in enterprise systems’ implementation - The impact of blockchain technology on the governance of the information stored in enterprise systems Area 4. Big data analytics - Utilizing big data analytics to develop a comprehensive view of the different master data management elements (e.g., customers, products) - Big data impact on enterprise systems’ lifecycle frameworks (e.g., selection phase) - The potentials of big data to extend the traditional enterprise systems’ functionalities and capabilities - The potentials of big data to enhance processes, operations, supply chains, and routine decision making - The analytical capabilities (e.g., process mining) that could extend enterprise systems’ capabilities Area 5. Digitalization - Digitalization as an enabler to force enterprise systems to be more open, agile, and hybrid - Enterprise systems require changes to facilitate digital transformation. What are these required changes, and what new features and functionalities do we expect from future enterprise systems? - How can enterprise systems support automation of work processes through software robotizing? How will robotizing affect knowledge workers? Call for Contributions In this special issue, we seek to attract researchers’ works that present novel approaches to inquiries into technical, operational, economic, and social impacts of emerging technologies with regard to their connection to and impact on enterprise systems. The special issue is open to all types of research methodologies and especially encourages a diversity of theoretical and empirical approaches. Basically, we are looking for theoretically well-defined research problems that are relevant to the topics intertwined in this special issue, with the objective to advance theories and methods or open the door for future knowledge to unfold. Accordingly, we differentiate between informative, theoretical and practical research problems, welcoming both scholarly pieces and studies with concrete applications. As a result, we expect the papers to demonstrate academic value and illustrate how the research contributes to businesses and society in general. Editorial Board - Asle Fagerstrøm, Westerdals- Oslo School of Arts, Communication and Technology, Norway - Ahmed Ghazawneh, IT University of Copenhagen, Denmark - Dag Olsen, University of Agder, Norway - Henk Akkermans, Tilburg University, Netherlands - Jalal Ahayeri, Tilburg University, Netherlands - Kari Smolander, Lappeenranta University of Technology, Finland - Knut Rolland, University of Oslo, Norway - Jose Esteves, IE Business School, Spain - Joao Varajao, University of Minho, Portugal - Maya Daneva, University of Twente, Netherlands - Maria Manuela Cruz-Cunha, Polytechnic Institute of Cávado and Ave, Portugal - Ravi Vatrapu, Copenhagen Business School, Denmark - Tom Roar Eikebrokk, University of Agder, Norway - Victor Bohorquez, Pontificia Universidad Católica Madre y Maestra, Dominican Republic References El-Gazzar, R., Hustad, E., & Olsen, D. H. (2016). Understanding Cloud Computing Adoption Issues: A Delphi Study Approach. Journal of Systems and Software, 118, 64-84. Elragal, A., & Haddara, M. (2012). The Future of Erp Systems: Look Backward before Moving Forward. Procedia Technology, 5, 21-30. Gattiker, T. F., & Goodhue, D. L. (2005). What Happens after Erp Implementation: Understanding the Impact of Inter-Dependence and Differentiation on Plant-Level Outcomes. MIS Quarterly, 29(3), 559-585. Haddara, M., & Zach, O. (2011). Erp Systems in Smes: A Literature Review. Paper presented at the 44 th Hawaii International Conference on System Sciences. Hustad, E., & Olsen, D. H. (2014). Erp Implementation in an Sme: A Failure Case Information Systems for Small and Medium-Sized Enterprises (pp. 213-228): Springer. Loebbecke, C., Thomas, B., & Ullrich, T. (2012). Assessing Cloud Readiness at Continental Ag. MIS Quarterly Executive, 11(1), 11-23. Svejvig, P., & Jensen, T. B. (2013). Making Sense of Enterprise Systems in Institutions: A Case Study of the Re-Implementation of an Accounting System. Scandinavian J. Inf. Systems, 25(1), 1. Tian, F., & Xu, S. X. (2015). How Do Enterprise Resource Planning Systems Affect Firm Risk? Post-Implementation Impact. MIS Quarterly, 39(1), 39-60. Volkoff, O., Strong, D., & Elmes, M. (2007). Technological Embeddedness and Organizational Change. Organization Science, 18(5), 832-848.
Project
The aim of the project is to introduce data science innovation which has the potential & capabilities to change the way enterprise systems are implemented and used. The project is funded by & in collaboration with EDRAKY: www.EDRAKY.com ; an SAP Global Partner