Traditional Enterprise Information Systems Research Articles

Determinants of switching intention to cloud computing in large enterprises

PurposeThe purpose of this paper is to investigate switching intention from traditional enterprise information systems (EISs) to private cloud EIS in large enterprises. The authors propose that the factors motivate and inhibit enterprises’ switching intention to private EIS by integrating technology–organization–environment (TOE) framework and two-factor theory.Design/methodology/approachA research model draws from TOE framework and two-factor theory. Data were collected from 227 top managers and owners of the enterprises in China and used to analyze 11 hypotheses.FindingsThe results show that the technological context (compatibility), organizational context (financial support) and environmental context (vendor support and industry pressure) significantly influence switching benefits while data security and costs significantly influence switching costs. Switching benefits and switching costs significantly influence switching intention.Originality/valuePast studies have focused mainly on the adoption of cloud computing. However, few studies have addressed the switching issues, especially in large enterprises. The findings are useful to understand switching issues from traditional EIS to private cloud EIS for both researchers and practitioners.

An integrated framework of enterprise information systems in smart manufacturing system via business process reengineering

Enterprise information systems play a significant role in the Industry 4.0 era and are the crucial component to realize smart manufacturing systems. However, traditional enterprise information systems have some limits: (1) lack of complete information, (2) only satisfy limited business needs, and (3) lack of seamless integration, business intelligence, value-driven processes, and dynamic optimization. Clearly, the existing enterprise information systems are unable to satisfy the requirements for smart manufacturing systems: (1) autonomous operation, (2) sustainable values, and (3) self-optimization. In addition, smart manufacturing systems have become more efficient and effective, demanding for seamless information flow in enterprise information systems, knowledge, and data-driven accurately decision. Therefore, a new enterprise information systems framework is needed to bridge gaps between the requirements for traditional manufacturing system and smart manufacturing system. In this article, the integrative framework is proposed based on the business process reengineering, lean thinking, and intelligent management methods, with inclusion of six enterprise information systems aspects to provide upgrading guidelines from traditional manufacturing to smart manufacturing. The procedure of this method contains three steps: (1) it identifies requirements and acquires best practices using AS-IS model, (2) it redesigns six aspects of enterprise information systems using TO-BE model, and (3) it proposes a new enterprise information systems framework. Finally, the proposed framework is validated by real cases.

Smart-EIS: An End to End Enterprise Information Systems Framework

Enterprise Information Systems (EIS) are widely and extensively used in many domains such as banking, telecommunication, e-commerce and government. Although several research studies and investigations were performed that explore the importance of EIS, only a few studies have focused on effective and efficient end-to-end approaches to developing such systems. In this article, a proposed software development framework (Smart-EIS) is presented. The primary objective of Smart-EIS is making the development of high-quality EIS more effective and efficient. In particular, it aims to reduce the development cost and to provide built-in transparent quality, security, performance and user-experience features. A comprehensive review of the traditional EIS is presented. This includes a discussion of the characteristics and patterns of such systems, the layered architectural patterns and the main components of these systems. The working methodology for the work discussed in this article depends on dynamically construct the common and general aspects of EIS at runtime. The methodology starts with extracting metadata models from the traditional architectural and components patterns. Based on these metadata, APIs have been designed and implemented. These libraries were then composed to make the full and complete proposed framework. In terms of validation and evaluation, the proposed framework -including its APIs- has been implemented as open-source projects, used to build a simple human resource management system, then utilized to re-build a student information system. Results of validation and evaluation have been presented and discussed, which show promising potential.

REA2: A unified formalisation of the Resource-Event-Agent ontology

Through a proof of concept in SWI-Prolog, this paper demonstrates a business transaction model by which the trading partners can derive their own, personal perspective from shared data. The demonstration is an innovative formalisation of the Resource-Event-Agent (REA) ontology as it allows for switching viewpoints in real-time between one trading-partner’s perspective and that of a trading-partner with an opposing view (i.e. customer or supplier), or a trading-partner independent perspective (e.g. trusted third-party). The business transaction model is achieved by uniting REA with the Open-EDI Business Transaction Ontology (OeBTO). The resulting unified formalisation of the REA ontology (REA2) also highlights implications for the future development of a) enterprise information systems (EIS) in the cloud, b) social-mediabased EIS, c) blockchain EIS, and d) EIS interoperability across business paradigms. The EIS interoperability such as between traditional EIS (which typically uses a tradingpartner perspective), and EIS for the collaborative economy (which typically uses a trading-partner independent perspective) is particularly highlighted as it becomes much more transparent than previously.

A notification-oriented solution for data-intensive enterprise information systems – A cloud manufacturing case

ABSTRACTThe application of Industrial Internet of Things (IIoT) has brought a series of new challenges to the traditional Enterprise Information Systems (EIS). More and more networked manufacturing entities are combined with data sensing, collection, transmission, and actuation capabilities. EIS are now facing large amounts of heterogeneous data. To address this issue, this paper proposes a notification-oriented solution for the data-intensive EIS within a distributed, collaborative, and heterogeneous environment. The solution is then applied in terms of model to a cloud-based smart factory prototype. This work indicates the suitability of the proposition and discusses the existing drawbacks and perspectives that include the manual modelling process and the application on a prototype.

The industrial management of SMEs in the era of Industry 4.0

Industry 4.0 provides new paradigms for the industrial management of SMEs. Supported by a growing number of new technologies, this concept appears more flexible and less expensive than traditional enterprise information systems such as ERP and MES. However, SMEs find themselves ill-equipped to face these new possibilities regarding their production planning and control functions. This paper presents a literature review of existing applied research covering different Industry 4.0 issues with regard to SMEs. Papers are classified according to a new framework which allows identification of the targeted performance objectives, the required managerial capacities and the selected group of technologies for each selected case. Our results show that SMEs do not exploit all the resources for implementing Industry 4.0 and often limit themselves to the adoption of Cloud Computing and the Internet of Things. Likewise, SMEs seem to have adopted Industry 4.0 concepts only for monitoring industrial processes and there is still absence of real applications in the field of production planning. Finally, our literature review shows that reported Industry 4.0 projects in SMEs remained cost-driven initiatives and there in still no evidence of real business model transformation at this time.

Determinants of firms' knowledge management system implementation: An empirical study

As knowledge becomes an increasingly valuable and important organizational asset, many firms anticipate that implementing the knowledge management systems (KMS) will effectively support and enhance organizational knowledge management activities. Even some firms regard KMS as an emerging and powerful source of competitive advantages.However, the implementation of KMS differs from that of traditional enterprise information systems. The implementation of KMS is difficult and risky since these systems are unstructured and so technologically innovative. Thus, effort is required to identify determinants affecting KMS implementation in businesses.Based on innovation diffusion theory and technology-organization-environment framework, this study develops and tests an integrated model of knowledge management systems implementation for businesses. Survey data were collected from 291 businesses in Taiwan. Confirmatory factor analysis and logistic regression technique were used test the hypothesized relationships. The results show that technological innovation factors (perceived benefits, complexity, and compatibility), organizational factors (top management support, organizational culture), and environmental factors (competitive pressure) are significant influences on KMS implementation in firms. Finally, the implications and future research on KMS implementation are discussed.

Data Cleaning for RFID and WSN Integration

Today's manufacturing environments are very dynamic and turbulent. Traditional enterprise information systems (EISs) have mostly been implemented upon hierarchical architectures, which are inflexible to adapt changes and uncertainties promptly. Next-generation EISs must be agile and adaptable to accommodate changes without significant time delays. It is essential for an EIS to obtain real-time data from the distributed and dynamic manufacturing environment for decision making. Wireless sensor networks (WSNs) and radio-frequency identification (RFID) systems provide an excellent infrastructure for data acquisition, distribution, and processing. In this paper, some key challenges related to the integration of WSN and RFID technologies are discussed. A five-layer system architecture has been proposed to achieve synergistic performance. For the integration of WSN and RFID, one of the critical issues is the low efficiency of communication due to redundant data as redundant data increases energy consumption and causes time delay. To address it, an improved data cleaning algorithm has been proposed; its feasibility and effectiveness have been verified via simulation and a comparison with a published algorithm. To illustrate the capacity of the developed architecture and new data cleaning algorithm, their application in relief supplies storage management has been discussed.

Business Process Management System Modeling in the Virtual Enterprise Based on Stochastic Colored Petri Net

Traditional enterprise information systems have many defects, so business process management (BPM) system was applied to the virtual enterprise and virtual enterprise process model is established based on BPM system. The dominant enterprise and the member enterprises used BPM system for their own information management system in the virtual enterprise. The BPM system model of the virtual enterprise was divided into the formation process and the operation process. The analysis method based on stochastic colored Petri net(SCPN) was also presented which can be used to model and analyze the process model in order to obtain the system performance analysis data. The virtual enterprise resources utilization rate can be seen. The model extends the application area of BPM system and provides a reference for the construction and management of virtual enterprise.