EmC-ICDSST 2019: 5th International Conference on Decision Support System Technology - ICDSST 2019 & EURO Mini Conference 2019 on "Decision Support Systems: Main Developments & Future Trends"

info:eu-repo/semantics/publishedVersio

ERP implementation methodologies and frameworks: a literature review

Enterprise Resource Planning (ERP) implementation is a complex and vibrant process, one that involves a combination of technological and organizational interactions. Often an ERP implementation project is the single largest IT project that an organization has ever launched and requires a mutual fit of system and organization. Also the concept of an ERP implementation supporting business processes across many different departments is not a generic, rigid and uniform concept and depends on variety of factors. As a result, the issues addressing the ERP implementation process have been one of the major concerns in industry. Therefore ERP implementation receives attention from practitioners and scholars and both, business as well as academic literature is abundant and not always very conclusive or coherent. However, research on ERP systems so far has been mainly focused on diffusion, use and impact issues. Less attention has been given to the methods used during the configuration and the implementation of ERP systems, even though they are commonly used in practice, they still remain largely unexplored and undocumented in Information Systems research. So, the academic relevance of this research is the contribution to the existing body of scientific knowledge. An annotated brief literature review is done in order to evaluate the current state of the existing academic literature. The purpose is to present a systematic overview of relevant ERP implementation methodologies and frameworks as a desire for achieving a better taxonomy of ERP implementation methodologies. This paper is useful to researchers who are interested in ERP implementation methodologies and frameworks. Results will serve as an input for a classification of the existing ERP implementation methodologies and frameworks. Also, this paper aims also at the professional ERP community involved in the process of ERP implementation by promoting a better understanding of ERP implementation methodologies and frameworks, its variety and history

Implementation of Collaborative, Planning, Forecasting and Replenishment (CPFR) to Reduce the Bullwhip Effect in MSME Sate Madura Cak Kholil

The aims of this study are: (1) to identify and analyze the estimated demand for chicken and goat satay products in the MSME of Sate Madura Cak Kholil; and (2) to find out the stock safety to overcome the surge in product demand at the MSME of Sate Madura Cak Kholil. The research method used is a descriptive method with a quantitative approach. The sample was determined based on a non-probability sampling technique using the purposive sampling method. The data used in this study included primary data and secondary data, namely data on supply and demand for the MSME of Sate Madura Cak Kholil. The results of the study indicate that the application of collaborative planning, forecasting, and replenish menthasan effect on reducing the bullwhip effect in the MSME of Sate Madura Cak Kholil

New Trends in the Use of Artificial Intelligence for the Industry 4.0

Industry 4.0 is based on the cyber-physical transformation of processes, systems and methods applied in the manufacturing sector, and on its autonomous and decentralized operation. Industry 4.0 reflects that the industrial world is at the beginning of the so-called Fourth Industrial Revolution, characterized by a massive interconnection of assets and the integration of human operators with the manufacturing environment. In this regard, data analytics and, specifically, the artificial intelligence is the vehicular technology towards the next generation of smart factories.Chapters in this book cover a diversity of current and new developments in the use of artificial intelligence on the industrial sector seen from the fourth industrial revolution point of view, namely, cyber-physical applications, artificial intelligence technologies and tools, Industrial Internet of Things and data analytics. This book contains high-quality chapters containing original research results and literature review of exceptional merit. Thus, it is in the aim of the book to contribute to the literature of the topic in this regard and let the readers know current and new trends in the use of artificial intelligence for the Industry 4.0

Semantic discovery and reuse of business process patterns

Patterns currently play an important role in modern information systems (IS) development and their use has mainly been restricted to the design and implementation phases of the development lifecycle. Given the increasing significance of business modelling in IS development, patterns have the potential of providing a viable solution for promoting reusability of recurrent generalized models in the very early stages of development. As a statement of research-in-progress this paper focuses on business process patterns and proposes an initial methodological framework for the discovery and reuse of business process patterns within the IS development lifecycle. The framework borrows ideas from the domain engineering literature and proposes the use of semantics to drive both the discovery of patterns as well as their reuse

Project Management in the Fourth Industrial Revolution

The Fourth Industrial Revolution (also referred to as Industry 4.0) is driven by a massive utilization of new technologies, such as robots, artificial intelligence, Internet of Things (IoT), Big Data, Quantum Computing and Quantum Communications, replacing humans by machines in certain tasks or the development of new or more efficient tasks. The Fourth Industrial Revolution is originating huge modifications in society and organizations. Human adaptation to the new paradigm is required, as it will have a high impact on jobs and on the required skills

Implementing Industry 4.0 in SMEs

This open access book addresses the practical challenges that Industry 4.0 presents for SMEs. While large companies are already responding to the changes resulting from the fourth industrial revolution , small businesses are in danger of falling behind due to the lack of examples, best practices and established methods and tools. Following on from the publication of the previous book ‘Industry 4.0 for SMEs: Challenges, Opportunities and Requirements’, the authors offer in this new book innovative results from research on smart manufacturing, smart logistics and managerial models for SMEs. Based on a large scale EU-funded research project involving seven academic institutions from three continents and a network of over fifty small and medium sized enterprises, the book reveals the methods and tools required to support the successful implementation of Industry 4.0 along with practical examples

Artificial intelligence in innovation research: A systematic review, conceptual framework, and future research directions

Artificial Intelligence (AI) is increasingly adopted by organizations to innovate, and this is ever more reflected in scholarly work. To illustrate, assess and map research at the intersection of AI and innovation, we performed a Systematic Literature Review (SLR) of published work indexed in the Clarivate Web of Science (WOS) and Elsevier Scopus databases (the final sample includes 1448 articles). A bibliometric analysis was deployed to map the focal field in terms of dominant topics and their evolution over time. By deploying keyword co-occurrences, and bibliographic coupling techniques, we generate insights on the literature at the intersection of AI and innovation research. We leverage the SLR findings to provide an updated synopsis of extant scientific work on the focal research area and to develop an interpretive framework which sheds light on the drivers and outcomes of AI adoption for innovation. We identify economic, technological, and social factors of AI adoption in firms willing to innovate. We also uncover firms' economic, competitive and organizational, and innovation factors as key outcomes of AI deployment. We conclude this paper by developing an agenda for future research

Business process modelling in ERP implementation literature review

Business processes are the backbone of any Enterprise Resource Planning (ERP) implementation. Business process modelling (BPM) has become essential for modern, process driven enterprises due to the vibrant business environments. As a consequence enterprises are dealing with a substantial rate of organizational and business processes change. Business process modelling enables a common understanding and analysis of the business processes, which is the first step in every ERP implementation methodology (blueprint phase). In order to represent enterprise processes models in an accurate manner, it is paramount to choose a right business process modeling technique and tool. The problem of many ERP projects rated as unsuccessful is directly connected to a lack of use of business process models and notations during the blueprint phase. Also, blueprint implementation phase is crucial in order to fit planned processes in an organization with processes implemented in the solution. However, business analysts and ERP implementation professionals have substantial difficulties to navigate through a large number of theoretical models and representational notations that have been proposed for business process modeling (BPM). As the availability of different business process modeling references is huge, it is time consuming to make review and classification of all modeling techniques. Therefor, in reality majority of ERP implementations blueprint documents have no business process modeling included in generating blueprint documents. Choosing the right model comprise the purpose of the analysis and acquaintance of the available process modelling techniques and tools. The number of references on business modelling is quit large, so it is very hard to make a decision which modeling notation or technique to use. The main purpose of this paper is to make a review of business process modelling literature and describe the key process modelling techniques. The focus will be on all business process modeling that could be used in ERP implementations, specifically during the blueprint phase of the implementation process. Detailed review of BPM (Business process modeling) theoretical models and representational notations, should assist decision makers and ERP integrators in comparatively evaluating and selecting suitable modeling approaches