Towards a Business Process Complexity Analysis Framework Based on Textual Data and Event Logs

Being an established discipline, Business Process Management (BPM) confronts various challenges related to digitization and rapid penetration of technologies into business processes (BPs). As a result, both generated and used data, such as textual data and event logs, grow exponentially, complicating the decision-making. Event logs are typically used to analyze BPs from several perspectives, including complexity. Recent approaches to BP complexity analyses focus on BP models and event logs, limiting the consideration of textual data. Hence, we propose a BP complexity analysis framework combining textual data and event logs. The framework has been conceptualized based on the IT Service Management (ITSM) case study of an international telecom provider and further developed in the IT department of an academic institution. The latter has also been used to investigate the value of the framework. Our preliminary findings show that the framework can enable comprehensive process redesign and improvements

Business Sentiment Analysis. Concept and Method for Perceived Anticipated Effort Identification

Representing a valuable human-computer interaction interface, Sentiment Analysis (SA) is applied to a wide range of problems. In the present paper, the researchers introduce a novel concept of Business Sentiment (BS) as a measurement of a Perceived Anticipated Effort (PAE) in the context of business processes (BPs). BS is considered as an emotional component of BP task contextual complexity perceived by a process worker after reading the task text. PAE is interpreted as a business process (BP) key performance indicator predicting urgency, criticality and complexity of the BP task processing. Using qualitative evaluation, the researchers proved the workability of both BS concept and its effective application method to measure PAE. As practical contributions of the research, quantitative support in a form of statistical reports and qualitative support in a form of task prioritization recommendations and time management for a BP worker are suggested

Application of Text Analytics in Public Service Co-Creation: Literature Review and Research Framework

The public sector faces several challenges, such as a number of external and internal demands for change, citizens' dissatisfaction and frustration with public sector organizations, that need to be addressed. An alternative to the traditional top-down development of public services is co-creation of public services. Co-creation promotes collaboration between stakeholders with the aim to create better public services and achieve public values. At the same time, data analytics has been fuelled by the availability of immense amounts of textual data. Whilst both co-creation and TA have been used in the private sector, we study existing works on the application of Text Analytics (TA) techniques on text data to support public service co-creation. We systematically review 75 of the 979 papers that focus directly or indirectly on the application of TA in the context of public service development. In our review, we analyze the TA techniques, the public service they support, public value outcomes, and the co-creation phase they are used in. Our findings indicate that the TA implementation for co-creation is still in its early stages and thus still limited. Our research framework promotes the concept and stimulates the strengthening of the role of Text Analytics techniques to support public sector organisations and their use of co-creation process. From policy-makers' and public administration managers' standpoints, our findings and the proposed research framework can be used as a guideline in developing a strategy for the designing co-created and user-centred public services

Business Process Management: Integrated Data Perspective. A Framework and Research Agenda

Business Process Management (BPM) is confronted with rapidly growing data flows of various types. One established way to address the complexity caused by structured log flows produced by Information Systems (IS) is Process Mining (PM). However, in this approach, unstructured natural language data generated by humans remains uncovered. With the significant advances in Natural Language Processing (NLP), we observe the attention of BPM research and practice shifting towards this type of data. In the study, building on the Task Technology Fit Theory and Contingency Theory, we derive a framework that addresses relevant future research questions in the context of integrated process data perspective, including structured logs and unstructured natural language. The proposed framework considers traditional BPM logics and highlights BPM as a sociotechnical discipline

Method to Address Complexity in Organizations Based on a Comprehensive Overview

Digitalization increasingly enforces organizations to accommodate changes and gain resilience. Emerging technologies, changing organizational structures and dynamic work environments bring opportunities and pose new challenges to organizations. Such developments, together with the growing volume and variety of the exchanged data, mainly yield complexity. This complexity often represents a solid barrier to efficiency and impedes understanding, controlling, and improving processes in organizations. Hence, organizations are prevailingly seeking to identify and avoid unnecessary complexity, which is an odd mixture of different factors. Similarly, in research, much effort has been put into measuring, reviewing, and studying complexity. However, these efforts are highly fragmented and lack a joint perspective. Further, this negatively affects the complexity research acceptance by practitioners. In this study, we extend the body of knowledge on complexity research and practice addressing its high fragmentation. In particular, a comprehensive literature analysis of complexity research is conducted to capture different types of complexity in organizations. The results are comparatively analyzed, and a morphological box containing three aspects and ten features is developed. In addition, an established multi-dimensional complexity framework is employed to synthesize the results. Using the findings from these analyses and adopting the Goal Question Metric, we propose a method for complexity management. This method serves to provide key insights and decision support in the form of extensive guidelines for addressing complexity. Thus, our findings can assist organizations in their complexity management initiatives

Modification of Zeolites Y and ZSM-5 adsorption of nanoparticles of transition metals from back-micellar solutions for separation of gas mixtures

On the basis of granular synthetic zeolites NaY, HY, and ZSM-5, adsorbents containing nanoparticles of silver, cobalt, molybdenum, and tungsten were obtained. The samples have a lower surface polarity in comparison with the initial zeolites, which is reflected in the selectivity of a number of samples with respect to argon. This is due to the fact that the argon molecule interacts with zeolites only through nonspecific forces. Modification was performed by interacting with reverse-micellar solutions of nanoparticles. The actual sizes of metal particles and their distribution over the surface of the modified samples of zeolites have been determined by the method of transmission electron microscopy. The samples’ equilibrium adsorption capacities for oxygen and argon (25°С and atmospheric pressure) and the separation coefficient of the argon–oxygen mixture as the ratio of Henry’s coefficients have been determined. It has been demonstrated that samples of the NaY zeolite modified with silver nanoparticles have the separation coefficient value of the argon–oxygen gas mixture equal to 1.6

Method to Address Complexity in Organizations Based on a Comprehensive Overview

Digitalization increasingly enforces organizations to accommodate changes and gain resilience. Emerging technologies, changing organizational structures and dynamic work environments bring opportunities and pose new challenges to organizations. Such developments, together with the growing volume and variety of the exchanged data, mainly yield complexity. This complexity often represents a solid barrier to efficiency and impedes understanding, controlling, and improving processes in organizations. Hence, organizations are prevailingly seeking to identify and avoid unnecessary complexity, which is an odd mixture of different factors. Similarly, in research, much effort has been put into measuring, reviewing, and studying complexity. However, these efforts are highly fragmented and lack a joint perspective. Further, this negatively affects the complexity research acceptance by practitioners. In this study, we extend the body of knowledge on complexity research and practice addressing its high fragmentation. In particular, a comprehensive literature analysis of complexity research is conducted to capture different types of complexity in organizations. The results are comparatively analyzed, and a morphological box containing three aspects and ten features is developed. In addition, an established multi-dimensional complexity framework is employed to synthesize the results. Using the findings from these analyses and adopting the Goal Question Metric, we propose a method for complexity management. This method serves to provide key insights and decision support in the form of extensive guidelines for addressing complexity. Thus, our findings can assist organizations in their complexity management initiatives