Understanding governance, risk and compliance information systems (GRC IS): the experts view

Although Governance, Risk and Compliance (GRC) is an emerging field of study within the information systems (IS) academic community, the concept behind the acronym has to still be demystified and further investigated. The study investigates GRC systems in depth by (a) reviewing the literature on existing GRC studies, and (b) presenting a field study on views about GRC application by professional experts. The aim of this exploratory study is to understand the aspects and the nature of the GRC system following an enterprise systems approach. The result of this study is a framework of particular GRC characteristics that need to be taken into consideration when these systems are put in place. This framework includes specific areas such as: goals and objectives, purpose of the system, key stakeholders, methodology and requirements prior to implementation, critical success factors and problems/barriers. Further discussion about the issues, the concerns and the diverse views on GRC would assist in developing an agenda for the future research on the GRC field

Access control and quality attributes of open data: Applications and techniques

Open Datasets provide one of the most popular ways to acquire insight and information about individuals, organizations and multiple streams of knowledge. Exploring Open Datasets by applying comprehensive and rigorous techniques for data processing can provide the ground for innovation and value for everyone if the data are handled in a legal and controlled way. In our study, we propose an argumentation and abductive reasoning approach for data processing which is based on the data quality background. Explicitly, we draw on the literature of data management and quality for the attributes of the data, and we extend this background through the development of our techniques. Our aim is to provide herein a brief overview of the data quality aspects, as well as indicative applications and examples of our approach. Our overall objective is to bring serious intent and propose a structured way for access control and processing of open data with a focus on the data quality aspects

Access control and quality attributes of open data: Applications and techniques

Open Datasets provide one of the most popular ways to acquire insight and information about individuals, organizations and multiple streams of knowledge. Exploring Open Datasets by applying comprehensive and rigorous techniques for data processing can provide the ground for innovation and value for everyone if the data are handled in a legal and controlled way. In our study, we propose an argumentation and abductive reasoning approach for data processing which is based on the data quality background. Explicitly, we draw on the literature of data management and quality for the attributes of the data, and we extend this background through the development of our techniques. Our aim is to provide herein a brief overview of the data quality aspects, as well as indicative applications and examples of our approach. Our overall objective is to bring serious intent and propose a structured way for access control and processing of open data with a focus on the data quality aspects

IoT and analytical practices in traditional industries: A view of the farming and agricultural sector

IoT and analytical practices in traditional industries: A view of the farming and agricultural secto

A cloud-based supply chain management system: effects on supply chain responsiveness

Purpose: Despite the ongoing calls for the incorporation of the cloud utility model, the effect of the cloud on elements of supply chain performance is still an evolving area of research. In this paper, we develop the architecture of a cloud-based supply chain management (C-SCM) ecosystem and explore how it enhances supply chain responsiveness. Design/methodology/approach: First, we discuss the potential benefits that cloud computing can yield compared to existing mature SCM information systems and solutions through a comprehensive literature review. We conceptualize SCR in terms of the level of visibility in the supply chain, supply chain flexibility, and rapid detection and reaction to changes and then we build the detailed architecture of a cloud based SCM system. The proposed ecosystem introduces a view of SCM and the associated practices when transferred to cloud environments. The potential to enhance SCR through the cloud is explored with scenarios on a case of supply chain operations in fashion retail industry. Findings: Our findings show that the proposed system can enhance all three dimensions of SCR. Implications for supply chain practice and how companies can migrate to a cloud supply chain are drawn. Originality/Value: Given that the development, creation, and delivery of goods and services is increasingly becoming a joint effort of several parties in a supply chain, we contribute to existing literature, by introducing a comprehensive cloud-based SCM system and show how companies can enhance their supply chain responsiveness

Data Supply Chain (DSC): development and validation of a measurement instrument

The volume and availability of data produced and affordably stored has become an important new resource for building organizational competitive advantage. Reflecting this, and expanding the concept of the supply chain, we propose the Data Supply Chain (DSC) as a novel concept to aid investigations into how the interconnected data characteristics relate to and impact organizational performance. Initially, we define the concept and develop a research agenda on DSC coupling theoretical background of strategy and operations literature. Along with the conceptualization, we develop a set of propositions and make suggestions for future research including testing and validating the model fit

Data supply chain (DSC): Research synthesis and future directions

In the digital economy, the volume, variety and availability of data produced in myriad forms from a diversity of sources has become an important resource for competitive advantage, innovation opportunity as well as source of new management challenges. Building on the theoretical and empirical foundations of the traditional manufacturing Supply Chain (SC), which describes the flow of physical artefacts as raw materials through to consumption, we propose the Data Supply Chain (DSC) along which data are the primary artefact flowing. The purpose of this paper is to outline the characteristics and bring conceptual distinctiveness to the context around DSC as well as to explore the associated and emergent management challenges and innovation opportunities. To achieve this, we adopt the systematic review methodology drawing on the operations management and supply chain literature and, in particular, taking a framework synthetic approach which allows us to build the DSC concept from the preexisting SC template. We conclude the paper by developing a set of propositions and outlining an agenda for future research that the DSC concept implies

A research agenda on Data Supply Chains (DSC)

Competition among organizations supports initiatives and collaborative use of data while creating value based on the strategy and best performance of each data supply chain. Supporting this direction, and building on the theoretical background of the supply chain, we propose the Data Supply Chain (DSC) as a novel concept to aid investigations for data-driven collaboration impacting organizational performance. In this study we initially propose a definition for the DSC paying particular attention to the need for collaboration for the supply chains of data. Furthermore, we develop a conceptual model of DSC collaboration coupling theoretical background of strategy and operations literature including, the resource-based view (RBV), supply chain management (SCM) and collaboration (SCC). Finally, we set propositions and a future research agenda including testing and validating the model fit

The implementation of Governance, Risk, and Compliance IS: adoption lifecycle and enterprise value

Governance, Risk, and Compliance has become an emerging field within the IS academic community. Motivated by this research direction, the study capitalizes on the theoretical background of enterprise systems and extends the focus on governance, risk, and compliance systems’ implementation (enterprise value and lifecycle). Building upon expert views on governance, risk, and compliance IS implementation projects, the analysis indicates that the three value drivers of integration, optimization, and information should be considered throughout the whole governance, risk, and compliance IS implementation lifecycle

Exploring industry 4.0 and smart manufacturing concepts

The last decade, manufacturing disruption is triggered mainly by the increasing role of data and technology in the production processes. Cyber-physical systems, Internet of things (IoT), cloud computing, analytics as well as data exchange between actors and processes have transformed the manufacturing landscape. Building on the theoretical foundations of Diffusion of Innovations (DOI) we explore the smart manufacturing and Industry 4.0 concepts through a literature review and case scenarios. The purpose of this research is to explore the literature around these concepts and how they were developed and outline the innovation perspective around them. To achieve this, we conduct a literature review and we conclude the study by developing a set of case scenarios, research propositions and an agenda for future research