Dynamic business process modelling (BPM) for business process change

The high failure rates of many business process change deployments are attributed to the inability to predict the outcome of the exercise without actually implementing the change in the physical environment. This restriction could be a result of over 80% of business process change projects adopting a static modelling technique in order to model their business processes. Static modelling enables the display of activities and the flow of information. However, physical aspects of a process, such as the movement of an object through the process, cannot be replicated. A technique that is thought to overcome this problem is dynamic Business Process Modelling (BPM). As the term suggests dynamic modelling facilitates the representation of the dynamic aspects of a business process including resources and the movement of people and objects. The aim of this paper is to investigate the use of dynamic modelling, in comparison to static modelling, for the purpose of business process change. This is achieved by the using both static modelling and dynamic modelling to represent the change procedure of a process from the Helpdesk of a large multi-national company. The results achieved using both techniques are compared

Weight Determination of Static and Dynamic Influencing Factors of the Change of Waterflooding Oil Well Based on Grey Relational Analysis and Analytic Hierarchy Process

LaSaXing oilfield has entered into the extra high water cut development stage, when analysising dynamic the static factors, production factors and dynamic factors that influence oil well change are more,  only depended on the qualitative analysis, it is difficult to accurately judge the cause of oil well change, can not meet the urgent need of oilfield development. This paper selects the static and dynamic factors affect the oil well change, the weight of static and dynamic influencing factors of the change of waterflooding wells are determined using the grey correlation analysis and the analytic hierarchy process based on exponential scale. The practices show that the weight of static and dynamic factors of the oil well change that determined using this method is scientific and reasonable, accord with the actual of oilfield, and provide reliable basis for intelligent analysis of dynamic change of oil well

Model Dependency of the Digital Option Replication – Replication under an Incomplete Model (in English)

The paper focuses on the replication of digital options under an incomplete model. Digital options are regularly applied in the hedging and static decomposition of many path-dependent options. The author examines the performance of static and dynamic replication. He considers the case of a market agent for whom the right model of the underlying asset-price evolution is not available. The observed price dynamic is supposed to follow four distinct models: (i) the Black and Scholes model, (ii) the Black and Scholes model with stochastic volatility driven by Hull and White model, (iii) the variance gamma model, defined as time changed Brownian motion, and (iv) the variance gamma model set in a stochastic environment modelled as the rate of time change via a Cox-Ingersoll-Ross model. Both static and dynamic replication methods are applied and examined within each of these settings. The author verifies the independence of the static replication on underlying processes.digital options, dynamic and static replication, internal time, Lévy models, replication error, stochastic environment, stochastic volatility, variance gamma process

The determinants of apprenticeship training with particular reference tobusiness expectations

"Whilst in applied empirical research, training in general human capital is mainly explained by structural characteristics of firms, this paper introduces business expectations as an additional explanatory factor. Business expectations are strictly time-variate and firm-specific and reflect both a firm's development in competitive markets and in the business cycle. We assume that a firm's business expectations strongly modify the cost-utility concept for firms' decisions as regards providing apprenticeship places. When controlling for firms' structural characteristics, static econometric models support our assumption that a change in business expectations leads to an asymmetric adjustment process of firms' qualitative decisions regarding apprenticeship training. Concerning the quantitative decision as to how many apprenticeship places a firm provides we found a significant but not asymmetric response to a change in business expectations. A dynamic approach confirms the results obtained in the static models of a symmetric quantitative adjustment process in a short-term perspective. In a longer perspective the dynamic model supports the assumption of an asymmetric quantitative adjustment process. Further on an application shows that an increasing uncertainty regarding business expectations tends to reduce the apprenticeship training at firm level." (Author's abstract, IAB-Doku) ((en)) Additional Information Kurzfassung (deutsch) Executive summary (English)Ausbildungsverhalten - Determinanten, Betrieb, Ausbildungsbetrieb, Unternehmensentwicklung, Personalpolitik, Kosten-Nutzen-Analyse, Ausbildungskosten, betriebliche Berufsausbildung - Nutzen, betriebliche Berufsausbildung, Bildungsökonomie, Bildungsinvestitionen, wirtschaftliche Situation

Transition from static to dynamic macroscopic friction in the framework of the Frenkel-Kontorova model

A new generation of experiments on dry macroscopic friction has revealed that the transition from static to dynamic friction is essentially a spatially and temporally non-uniform process, initiated by a rupture-like detachment front. We show the suitability of the Frenkel-Kontorova model for describing this transition. The model predicts the existence of two types of detachment fronts, explaining both the variability and abrupt change of velocity observed in experiments. The quantitative relation obtained between the velocity of the detachment front and the ratio of shear to normal stress is consistent with experiments. The model provides a functional dependence between slip velocity and shear stress, and predicts that slip velocity is independent of normal stress. Paradoxically, the transition from static to dynamic friction does not depend explicitly on ether the static or the dynamic friction coefficient, although the beginning and end of transition process are controlled by these coefficients.Comment: 16 pages, 8 figure

A Systematic Review of Learning based Notion Change Acceptance Strategies for Incremental Mining

The data generated contemporarily from different communication environments is dynamic in content different from the earlier static data environments. The high speed streams have huge digital data transmitted with rapid context changes unlike static environments where the data is mostly stationery. The process of extracting, classifying, and exploring relevant information from enormous flowing and high speed varying streaming data has several inapplicable issues when static data based strategies are applied. The learning strategies of static data are based on observable and established notion changes for exploring the data whereas in high speed data streams there are no fixed rules or drift strategies existing beforehand and the classification mechanisms have to develop their own learning schemes in terms of the notion changes and Notion Change Acceptance by changing the existing notion, or substituting the existing notion, or creating new notions with evaluation in the classification process in terms of the previous, existing, and the newer incoming notions. The research in this field has devised numerous data stream mining strategies for determining, predicting, and establishing the notion changes in the process of exploring and accurately predicting the next notion change occurrences in Notion Change. In this context of feasible relevant better knowledge discovery in this paper we have given an illustration with nomenclature of various contemporarily affirmed models of benchmark in data stream mining for adapting the Notion Change