Designing a Process Mining-Enabled Decision Support System for Business Process Standardization in ERP Implementation Projects

Process standardization allows to optimize ERP systems and is a nec-essary step prior to ERP implementation projects. Traditional approaches to standardizing business processes are based on manually created "de-jure" process models, which are distorted, error-prone, simplistic, and often deviating from process reality. Theoretically embedded in the organizational contingency theory as kernel theory, this paper employs a design science approach to design a process mining-enabled decision support system (DSS) which combines bottom-up process mining models with manually added top-down standardization infor-mation to recommend a suitable standard process specification from a repository. Extended process models of the as-is process are matched against a repository of best-practice standard process model using an attributebased process similarity matching algorithm. Thus, the DSS aims to reduce the overall costs of process standardization, to optimize the degree of fit between the organization and the implemented processes, and to minimize the degree of organizational change re-quired in standardization and ERP implementation projects. This paper imple-ments a working prototype instantiation in the open-source process analytics platform Apromore based on a real-life event log and standardization attributes for the Purchase-to-Pay and Order-to-Cash processes from three SAP R/3 ERP systems at the industry partner

Cognitive Aspects of Structured Process Modeling

After visualizing data of various observational experiments on the way in which modelers construct process models, a promising process modeling style (i.e., structured process modeling) was discovered that is expected to cause process model quality to increase. A modeler constructs process models in a structured way if she/he is working on few parts of the model simultaneously. This paper describes cognitive theories that can explain this causal relation. Cognitive Load Theory (CLT) suggests that the amount of errors increases when the limited capacity of our working memory is overloaded. Cognitive Fit Theory (CFT) states that performance is improved when task material representation matches with the task to be executed. Three hypotheses are formulated and the experimental set-up to evaluate these hypotheses is described

Travel blogs on China as a destination image formation agent: A qualitative analysis using Leximancer

The Internet spreads tourism information around the world and specifically travel blogs function as an online version of word-of-mouth (eWOM). This research explored the role of blogs as a destination image formation agent for China's inbound tourism. Data were collected from 630 bloggers who wrote on two blog websites about their travels within China in 2011 and 2012. The bloggers on TravelBlog.org and TravelPod.com were mainly from English-speaking countries. Qualitative analysis using Leximancer software was applied and identified nine major textual themes and the relationships among these themes. In order of relative importance, the themes were place, Chinese, people, food, train, city, hotel, China, and students. The research indicated that international tourists tended to have positive images of China

Shared result identification for materialized view selection

Selecting views to materialize impacts on the efficiency as well as the total cost of establishing and running a data warehouse. As such, it is important to select the right views to materialize during the data warehouse design phase. A data warehouse may contain multiple views which can be defined over overlapping portions of data. Identifying the shared views or shared parts of a particular view can therefore improve data warehouse performance by diminishing the number of views which have to be materialized as well as reducing the amount of data which requires frequent refreshment. In this paper, we propose an extension to an already-existing solution for materialized view selection. We first discuss the concept of attribute hierarchies and then present how the hierarchy concept improves the view selection metho