Business Process Event Log Transformation into Bayesian Belief Network

Business process (BP) mining has been recognized in business intelligence and reverse engineering fields because of the capabilities it has to discover knowledge about the implementation and execution of BP for analysis and improvement. Existing business knowledge extraction solutions in process mining context requires repeating analysis of event logs for each business knowledge extraction task. The probabilistic modelling could allow improved performance of BP analysis. Bayesian belief networks are a probabilistic modelling tool and the paper presents their application in BP mining. The paper shows that existing process mining algorithms are not suited for this, since they allow for loops in the extracted BP model that do not really exist in the event log,and presents a custom solution for directed acyclic graph extraction. The paper presents results of a synthetic log transformation into Bayesian belief network showing possible application in business intelligence extraction and improved decision support capabilities

Challenging Dyadic Interaction in the Context of Multi-Organizational Business Processes

Value creation of today is often a co-production in multi-organizational settings. This requires knowledge about how to conceive multi-organizational actor roles as foundations for co-ordinating and efficiently co-produce customer value. Some contemporary business process modelling approaches builds upon modelling interaction between two business parties (i.e. dyadic interaction), but do not acknowledge interaction patterns involving several network actors in their different actor roles. In this paper value creation in multi-organizational businesses are seen as value chains in value networks. The notion of assignments is the underlying structure in a multi-organizational perspective on business processes and is used to create foundations for distinguishing interaction patterns. Modelling and improving multi-organizational business processes conceived as action and interaction arranged in assignment structures, imply that dyadic role models need to be challenged as generative instruments. In this paper four generic multi-organizational network actor roles are brought forward (end-customer, main actor, co-ordinating actor, and co-producing actor) given meaning in and further instantiated in generic assignment actor roles based on their involvement in different multi-organizational interaction patterns. Thus, patterns of interaction constituting multi-organizational business processes are distinguished creating the necessary conditions for diverse network actors by the identification of their role in the action logic

Financial requirements for nationwide fibre access coverage

It is common knowledge that Next Generation Access (NGA) networks require significant investments and that for many regions, especially in more rural areas, there is no viable business case. Taking note of the broadband strategies formulated by European governments the deployment cost is analysed to assess options for extending the profitable coverage of FTTH. In this paper a bottom-up cost model is applied to determine the investment and cost of deploying and operating a FTTH network in Germany on a national level. The monthly cost per subscriber at rising penetration is compared with the Average Revenue Per User (ARPU) to determine the required penetration level or the required revenue for profitable operation in a steady market state. Those regions for which there is no business case are analysed with regard to the level of required subsidies. All modelling is based on differentiated geotypes reflecting urban and rural areas. The basic cost model used has been applied to numerous case studies before and was adapted to determine different forms of subsidies. The research questions addressed are. What is the limit of profitable FTTH coverage in Germany? What is the level of prices, internal subsidisation or investment subsidy necessary to increase the coverage of FTTH in Germany? These results inform policy makers and operators of the relevant investment deltas and/or price levels needed to increase the coverage of next generation broadband access infrastructure. --Next Generation Access,FTTH,cost modelling,GPON,P2P,broadband strategy

nD modelling: Industry uptake considerations

Purpose – The purpose of this paper is to identify the key enablers and obstacles to the effective adoption and use of nD modelling technology. Design/methodology/approach – This paper explores the feasibility of industry absorbing and diffusing nD modelling technology by considering key technology transfer issues; namely, organisational direction, inter-organisational networks and the knowledge characteristics of technology. Findings from semi-structured interviews around a diagnostic technology transfer framework are used to offer implications for theory and practice. Findings – The results from 15 survey interviews indicate that construction professionals appreciate the potential significant benefits of nD modelling technology, but at present, nD modelling technology is seen as too embryonic; too far removed from construction firms' “comfort zones”; requiring too much investment; and, containing too many risks. Originality/value – The paper stresses that the challenge for nD modelling technology, along with any new technology, is to shift from its “technology push” emphasis, to a more balanced “market orientated” stance, which allows the technology to be shaped by both strategic design concerns, and day-to-day operational needs. If this trajectory is pursued, nD modelling technology could have a positive future

Big data-savvy teams’ skills, big data-driven actions and business performance

Prior studies on big data analytics have emphasized the importance of specific big data skills and capabilities for organizational success; however, they have largely neglected to investigate the use of cross-functional teams’ skills and its links to the role played by relevant data-driven actions and business performance. Drawing on the resource-based view (RBV) of the firm and on the data collected from big data experts working in global agrifood networks, we examine the links between the use of big data-savvy (BDS) teams’ skills, big data-driven (BDD) actions and business performance. BDS teams depend on multidisciplinary skills (e.g., computing, mathematics, statistics, machine learning, and business domain knowledge) that help them to turn their traditional business operations into modern data-driven insights (e.g., knowing real time price changes and customer preferences), leading to BDD actions that enhance business performance. Our results, raised from structural equation modelling, indicate that BDS teams' skills that produce valuable insights are the key determinants for BDD actions, which ultimately contribute to business performance. We further demonstrate that those organisations that emphasise BDD actions perform better compared to those that do not focus on such applications and relevant insights

A survey of simulation techniques in commerce and defence

Despite the developments in Modelling and Simulation (M&S) tools and techniques over the past years, there has been a gap in the M&S research and practice in healthcare on developing a toolkit to assist the modellers and simulation practitioners with selecting an appropriate set of techniques. This study is a preliminary step towards this goal. This paper presents some results from a systematic literature survey on applications of M&S in the commerce and defence domains that could inspire some improvements in the healthcare. Interim results show that in the commercial sector Discrete-Event Simulation (DES) has been the most widely used technique with System Dynamics (SD) in second place. However in the defence sector, SD has gained relatively more attention. SD has been found quite useful for qualitative and soft factors analysis. From both the surveys it becomes clear that there is a growing trend towards using hybrid M&S approaches