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The management of the US Department of Defense (DoD) enterprise must change. Years of under‐funding have led to a wide gap between enterprise support requirements and resources. Private sector firms have faced similar choices. This paper shows how the public enterprise can be changed. Our hypothesis is that private sector implementations of standard software will lead to increased effectiveness and efficiency in public sector organizations. Sufficient detail is provided on how to transition to a modern integrated public sector enterprise, and the steps for implementing such a project are outlined, following standard private sector implementation practices. To explain the problem and solution, the DoD installation management enterprise is used as an example.

Bankruptcy is a financial failure of a business or an organization. Different kinds of bankruptcy prediction techniques are proposed to predict it. But, they are restricted as techniques in predicting the bankruptcy and not addressing the associated activities like acquiring the suitable data and delivering the results to the user after processing it. This situation demands to look for a comprehensive solution for predicting bankruptcy with intelligence. The paper aims to discuss these issues.

To model Business Intelligence (BI) solution for BP the concept of reference model is used. A Reference Model for Business Intelligence to Predict Bankruptcy (RMBIPB) is designed by applying unit operations as hierarchical structure with abstract components. The layers of RMBIPB are constructed from the hierarchical structure of the model and the components, which are part of the reference model. In this model, each layer is designed based on the functional requirements of the Business Intelligence System (BIS).

This reference model exhibits the non functional software qualities intended for the appropriate unit operations. It has flexible design in which techniques are selected with minimal effort to conduct the bankruptcy prediction. The same reference model for another domain can be implemented with different kinds of techniques for bankruptcy prediction.

This model is designed using unit operations and the software qualities exhibited by RMBIPB are limited by unit operations. The data set which is applied in RMBIPB is limited to Indian banks.

A comprehensive bankruptcy prediction model using BI with customized reporting.

The purpose of the paper is to propose a reference model describing a holistic view of the master data lifecycle, including strategic, tactical and operational aspects. The Master Data Lifecycle Management (MDLM) map provides a structured approach to analyze the master data lifecycle.

Embedded in a design oriented research process, the paper applies the Component Business Model (CBM) method and suggests a reference model which identifies the business components required to manage the master data lifecycle. CBM is a patented IBM method to analyze the key components of a business domain. The paper uses a participative case study to evaluate the suggested model.

Based on a participative case study, the paper shows how the reference model makes it possible to analyze the master data lifecycle on a strategic, a tactical and an operational level, and how it helps identify areas of improvement.

The paper presents design work and a participative case study. The reference model is grounded in existing literature and represents a comprehensive framework forming the foundation for future analysis of the master data lifecycle. Furthermore, the model represents an abstraction of an organization's master data lifecycle. Hence, it forms a “theory for designing”. More research is needed in order to more thoroughly evaluate the presented model in a variety of real‐life settings.

The paper shows how the reference model enables practitioners to analyze the master data lifecycle and how it helps identify areas of improvement.

The paper reports on an attempt to establish a holistic view of the master data lifecycle, including strategic, tactical and operational aspects, in order to provide more comprehensive support for its analysis and improvement.

Evaluating and optimizing e‐government services is imperative for governments especially due to the capacity of e‐services to transform public administrations and assist the interactions of governments with citizens, businesses and other government agencies. Existing widely applied evaluation approaches neglect to incorporate citizens' satisfaction measures. The purpose of this paper is twofold: to contribute to the understanding of citizen‐centric e‐government evaluation and unify existing key performance indicators (KPIs); and to propose a reference process model of a novel evaluation approach that uses the unified KPIs to facilitate the creation of a “know‐how” repository.

The authors adopt a quantitative research approach for the evaluation of e‐government services that is based on data envelope analysis (DEA). A survey was conducted for the empirical investigation and data were collected from 13 e‐government services in Turkey. Based on the empirical application of the e‐government evaluation method, a reference process model is designed.

The proposed evaluation method was proved valid and able to provide assessment with richer explanations than traditional statistical measurements. DEA enabled the identification of insufficient e‐government services and the provision of suggested improvements.

The reference process model is constructed based on the experience gained by applying the method to a sole cultural setting;, i.e. e‐government services in Turkey.

The proposed evaluation method, in comparison to other user‐oriented ones, provided assessments with richer explanations than traditional statistical measurements, such as structured equation modelling. The reference process model constructed based on the empirical research is expected to accelerate the citizen‐oriented evaluation of e‐government and promote impact‐oriented indicators.

This is the first application of DEA in the e‐government field, although it has been widely applied for performance measurement in other fields, especially operations research. The novelty of DEA is that the assessment results provide suggestions for strategic improvement of the e‐services.

The US Department of Defense (DoD) is engaged in a multi‐year transformation of logistics planning and execution, known as the Future Logistics Enterprise (FLE). It is currently being defined in policy documents and an implementation plan known as the Future Logistics Architecture (FLA). The systems strategy for the FLE is still emerging, but it is anticipated that commercial standard software will play a significant role in the enablement of the new logistics business processes. A number of products are available for implementation, but this paper focuses on mySAP.com from SAP AG. We show the strategy for aligning the SAP reference hierarchy and the associated reference business process models with the FLA. The result of the mapping and associated analysis is an SAP reference model for the FLE, which can be used as a guide for the software vendor for future product development strategies. This paper reports on the development of the FLA, its alignment with mySAP.com and the development of the SAP reference model.

This paper presents a reference model for the process of management of quality and improvement based on a conceptual framework for managing the process of systematically deriving improvement actions from customer expectations and strategic decisions through business processes, and prioritising actions that will most contribute to achievement strategic objectives. After some introductory theoretical background to discuss the need for systematically managing quality and improvement as well as the contribution of mapping business processes, the process reference model is described to a certain extent and detailed by means of activity tree and event‐driven process chain (EPC) diagrams. Finally, some considerations are made on the benefits of using such an approach.

For the past 20 years production planning and control has been dominated by manufacturing resource planning (MRPII) and its antecedents. The authors are completing case study based research that is aimed at developing novel planning and scheduling reference models for industrial sectors where the MRPII paradigm is not appropriate. It outlines the process mapping approach adopted for data capture within the case study companies and the use of ARIS, Scheer’s enterprise modelling tool, for the production of sector reference models.

This paper aims to automate the supply chain operations reference (SCOR) model as an enabler for process‐oriented supply chain business intelligence.

The hypothesis is the following: SCOR model automation is possible using data that is directly extracted from integrated enterprise systems. To test the hypothesis, an alignment product that allows the SCOR model to be automated with information that is directly extracted from the Oracle E‐Business Suite was developed.

In order to achieve the full benefits from the SCOR model, effective business process management and the SCOR key performance indicators (KPIs) must be implemented and used. Unless data collection to support KPI construction is automated, it is difficult to institutionalize the SCOR model as a measurement and benchmarking framework. We have demonstrated that automated support for KPIs is feasible and achievable.

The E‐Business Suite is a single enterprise solution, but we assert that the same procedures could be followed with other enterprise solutions or even applied in a legacy system environment.

The developed solution described in the paper can immediately be applied to the design, development, and deployment of corporate performance management systems.

The paper proposes an innovative systemic method helping decision-makers to control servitization transition process, through decision process risk diagnosis.

The proposed method is based on the modeling of decision processes and risk identification and analysis. This method was based on an action-research approach, in close relationship with two companies (SMEs). The paper develops the feasibility experiment at Automelec company.

The method was successfully implemented and delivered concrete diagnosis results.

The generalization of the applicability of the method needs to be tested on several different cases.

The first practical implication is related to the efficiency of the method to help decision-makers in a servitization context to limit uncertainty and get a global view of the weaknesses of their decision-making process, it raises their awareness about servitization transition for their companies. Furthermore, the method also helps to explain the strategy of a servitization transition. It enhances the level of maturity of the decision process of the company, and can be used as a training/learning tool for managers.

The results brought by the research contribute to give the decision-making boards for organization living a servitization transition and especially SMEs a better control over the servitization decision process and related risks, which will increase the economic stability of the company and its vision over long, medium and short horizons. This will bring positive impact on the overall economic and social environment and networks of the servitized SME, and enhance the confidence of coworkers, subcontractors and clients.

The first originality of the paper is related to the new way of considering risk, not only as an analysis criterion but as the central driver in steering a strategic transition for the company, such as servitization. The second originality of the study is about assessing risk occurrence over a decision-making process through decision reliability and decision confidence.

The purpose of this paper is to illustrate and evaluate the semantic process benchmarking concept.

The authors' approach includes the use of metamodels and ontologies, which make the process models syntactically and semantically comparable. Furthermore, a software prototype is presented to analyze and compare individual process models and their performance information. Thereafter, the technical, conceptual, and economic perspectives of the approach's evaluation are aligned with their respective outcomes.

The evaluation proves that this approach is generally suitable to generate novel and useful information on different process models and their performance within the same problem domain. However, the initial set‐up costs are high and will only pay off once process models are used regularly.

The proposed approach depends strongly on the availability of appropriate metrics and ontologies, as well as on the annotation of these ontologies to process models, which is a time‐consuming task. If large benchmarking clearing centers are established, the approach will be more cost‐effective. The developed SEMAT prototype, that demonstrates and proves the proposed approach's general viability, supports cost‐effective ontology engineering and annotation in the context of semantic process benchmarking initiatives.

To date, process benchmarking has primarily been a manual process. In this article, the authors suggest an approach that allows time‐consuming and costly process analysis to be partially automated, which makes the performance indicators, as well as qualitative differences between processes, apparent.