Mobile emergency warning apps are essential for effective emergency communication – of course, provided the population intends to use them. Drawing on protection motivation theory, the study validated a psychometric model to explain what motivates individuals to install a warning app for the first time and to keep using it over time. Multi-group covariance-based structural equation modeling was used

The study considers the application of text mining techniques to the analysis of curricula for study programs offered by institutions of higher education. It presents a novel procedure for efficient and scalable quantitative content analysis of module handbooks using topic modeling. The proposed approach allows for collecting, analyzing, evaluating, and comparing curricula from arbitrary academic disciplines

Explorative business process management (BPM) is attracting increasing interest in the literature and professional practice. Organizations have recognized that a focus on operational efficiency is no longer sufficient when disruptive forces can make the value proposition of entire processes obsolete. So far, however, research on how to create entirely new processes has remained largely conceptual,

Arguably, automation is fast transforming many enterprise business processes, transforming operational jobs into monitoring tasks. Consequently, the ability to sustain attention during extended periods of monitoring is becoming a critical skill. This manuscript presents a Brain-Computer Interface (BCI) prototype which seeks to combat decrements in sustained attention during monitoring tasks within

Organizations strive to develop a variety of capabilities to improve and measure business processes. Researchers have used various maturity models to investigate the development of a business process orientation (BPO), and most have argued that such a development comes in stages. Current literature underestimates the interrelationships between BPO capabilities and fails to consider multidimensional

Software requirements (SRs) selection is a multicriteria group decision making (MCGDM) problem whose objective is to select the SRs from the pool of the requirements on the basis of different criteria. In MCGDM, different decision makers have different opinions of the same requirement so it is difficult to decide which set of SRs to implement during the different releases of the software. During the

The study analyzes data collected in two case studies in the healthcare industry, which is characterized by a variety of social and technical elements forming an activity system where all elements interact with each other. The findings indicate that many problems emerging during the implementation of a health information system can be traced back to contradictions between elements of the activity systems

Problem Definition: Queensland’s Compulsory Third-Party (CTP) Insurance Scheme provides a mechanism for persons injured as a result of a motor vehicle accident to receive compensation. Managing CTP claims involves multiple stakeholders with potentially conflicting interests. It is therefore pertinent to investigate whether ‘best practice’ for claims processing can be identified and measured so all

Business process simulation marks an essential technique for analyzing business processes and for reasoning about process improvement. With first contributions dating back to the mid-1990s, computerized business process simulation has been a continuing research focus and is widely acknowledged as foundational to Business Process Management research and practice. Reviewing contributions to the field

Business Process Standardization (BPS) is a strategy for improved efficiency and effectiveness of business processes. However, BPS approaches are known to vary much in practice, can consume inordinate time and resources, and are ill-understood. This study applies an exploratory analysis of BPS literature to identify alternative BPS strategies. The analysis identified three key decision-points when

To achieve ambitious climate goals, it is necessary to increase the rate of purposeful retrofit measures in the building sector. As a result, Energy Performance Certificates have been designed as important evaluation and rating criterion to increase the retrofit rate in the EU and Germany. Yet, today’s most frequently used and legally required methods to quantify building energy performance show low

To achieve a sustainable energy system, a further increase in electricity generation from renewable energy sources (RES) is imperative. However, the development and implementation of RES entail various challenges, e.g., dealing with grid stability issues due to RES’ intermittency. Correspondingly, increasingly volatile and even negative electricity prices question the economic viability of RES-plants

Context awareness is essential for successful business process management (BPM). So far, research has covered relevant BPM context factors and context-aware process design, but little is known about how to assess and select BPM methods in a context-aware manner. As BPM methods are involved in all stages of the BPM lifecycle, it is key to apply appropriate methods to efficiently use organizational resources

Artificial intelligence (AI) offers organizations much potential. Considering the manifold application areas, AI’s inherent complexity, and new organizational necessities, companies encounter pitfalls when adopting AI. An informed decision regarding an organization’s readiness increases the probability of successful AI adoption and is important to successfully leverage AI’s business value. Thus, companies

Blockchain technology is often proposed as an infrastructure for decentralized Know-Your-Customer (KYC) verification, i.e., a process determining whether a customer is eligible for a given transaction. The benefit of using blockchain technology lies in the expected compliance costs reduction for companies by automatically enforcing KYC-requirements, whose results are accessible by multiple financial

Owing to advancements in artificial intelligence (AI) and specifically in machine learning, information technology (IT) systems can support humans in an increasing number of tasks. Yet, previous research indicates that people often prefer human support to support by an IT system, even if the latter provides superior performance – a phenomenon called algorithm aversion. A possible cause of algorithm

Organizations introduce virtual assistants (VAs) to support employees with work-related tasks. VAs can increase the success of teamwork and thus become an integral part of the daily work life. However, the effect of VAs on virtual teams remains unclear. While social identity theory describes the identification of employees with team members and the continued existence of a group identity, the concept

The study aims to identify whether algorithmic decision making leads to unfair (i.e., unequal) treatment of certain protected groups in the recruitment context. Firms increasingly implement algorithmic decision making to save costs and increase efficiency. Moreover, algorithmic decision making is considered to be fairer than human decisions due to social prejudices. Recent publications, however, imply

Some information systems research has considered that individual personality traits influence whether users feel stressed by information and communication technologies. Personality research suggests, however, that personality traits do not act individually, but interact interdependently to constitute a personality profile that guides individual perceptions and behavior. The study relies on the differential

Research has shown that aggregation of independent expert judgments significantly improves the quality of forecasts as compared to individual expert forecasts. This “wisdom of crowds” (WOC) has sparked substantial interest. However, previous studies on strengths and weaknesses of aggregation algorithms have been restricted by limited empirical data and analytical complexity. Based on a comprehensive

The presented method reconstructs a network (a graph) from AIS data, which reflects vessel traffic and can be used for route planning. The approach consists of three main steps: maneuvering points detection, waypoints discovery, and edge construction. The maneuvering points detection uses the CUSUM method and reduces the amount of data for further processing. The genetic algorithm with spatial partitioning

Content website providers have two main goals: They seek to attract consumers and to keep them on their websites as long as possible. To reach potential consumers, they can utilize several online channels, such as paid search results or advertisements on social media, all of which usually require a substantial marketing budget. However, with rising user numbers of online communication tools, website

When talking about blockchain technology in academia, business, and society, frequently generalizations are still heared about its – supposedly inherent – enormous energy consumption. This perception inevitably raises concerns about the further adoption of blockchain technology, a fact that inhibits rapid uptake of what is widely considered to be a groundbreaking and disruptive innovation. However

Nowadays, IT operations devolve many tasks in IT services to internal customers (i.e., IT self-service). The rationale for this service task devolvement is often to reduce the IT personnel’s workload. However, prior research has shown that IT operations often fail to achieve this goal. Existing methods for modeling and analyzing services fall short of supporting service providers in identifying and

Online reviews, i.e., evaluations of products and services posted on websites, are ubiquitous. Prior research observed substantial variance in the language of such online reviews and linked it to downstream consequences like perceived helpfulness. However, the understanding of why the language of reviews varies is limited. This is problematic because it might have vital implications for the design

Digitalization is changing the mobility sector. Companies have developed entirely new mobility services, and mobility services with pre-digital roots, such as ride-sharing and public transport, have leveraged digitalization to become more convenient to use. Nevertheless, private car use remains the dominant mode of transport in most developed countries, leading to problems such as delays due to traffic

Transparency in transport processes is becoming increasingly important for transport companies to improve internal processes and to be able to compete for customers. One important element to increase transparency is reliable, up-to-date and accurate arrival time prediction, commonly referred to as estimated time of arrival (ETA). ETAs are not easy to determine, especially for intermodal freight transports

The importance of gaining insights into informal organizational structures for management purposes is acknowledged by both research and practice. However, “traditional” approaches to analyzing informal organizational social networks involve significant manual effort and do not scale for larger datasets. Enterprise Social Networks (ESN) have emerged as important tools for informal employee interactions

Process mining offers a set of techniques for gaining data-based insights into business processes from event logs. The literature acknowledges the potential benefits of using process mining techniques in Six Sigma-based process improvement initiatives. However, a guideline that is explicitly dedicated on how process mining can be systematically used in Six Sigma initiatives is lacking. To address this

Business Process Management is a boundary-spanning discipline that aligns operational capabilities and technology to design and manage business processes. The Digital Transformation has enabled human actors, information systems, and smart products to interact with each other via multiple digital channels. The emergence of this hyper-connected world greatly leverages the prospects of business processes

Predictive process monitoring aims at forecasting the behavior, performance, and outcomes of business processes at runtime. It helps identify problems before they occur and re-allocate resources before they are wasted. Although deep learning (DL) has yielded breakthroughs, most existing approaches build on classical machine learning (ML) techniques, particularly when it comes to outcome-oriented predictive

Several domain-specific assistants in the form of chatbots have conquered many commercial and private areas. However, there is still a limited level of systematic knowledge of the distinctive characteristics of design elements for chatbots to facilitate development, adoption, implementation, and further research. To close this gap, the paper outlines a taxonomy of design elements for chatbots with

Package bids, i.e., bids on sets of items, are an essential aspect of combinatorial auctions. They can allow bidders to accurately express their preferences. However, bidders on packages consisting of few items are often unable to outbid provisionally winning bids on large packages. To resolve this, both coordination as well as cooperation are needed. Coordination, since smaller bidders need to bid

Robotic process automation (RPA) is an emerging technology that allows organizations automating repetitive clerical tasks by executing scripts that encode sequences of fine-grained interactions with Web and desktop applications. Examples of clerical tasks include opening a file, selecting a field in a Web form or a cell in a spreadsheet, and copy-pasting data across fields or cells. Given that RPA

Business process management (BPM) is a mature discipline that drives corporate success through effective and efficient business processes. BPM is commonly structured via capability frameworks, which describe and bundle capability areas relevant for implementing process orientation in organizations. Despite their comprehensive use, existing BPM capability frameworks are being challenged by socio-technical

Nowadays, the organic nature of business processes and the increasingly complex and dynamic business environment make organizations face severe operational risks. However, current risk analysis methods of Information Technology (IT) resources ignore inter-process correlation and thus inter-process risk propagation. This gap needs a solution since the rigid alignment of organizations cause the risks

In any data science and analytics project, the task of mapping a domain-specific problem to an adequate set of data mining methods by experts of the field is a crucial step. However, these experts are not always available and data mining novices may be required to perform the task. While there are several research efforts for automated method selection as a means of support, only a few approaches consider

In software development, crosscutting concerns, such as security, audit, access control, authentication, logging, persistence, transaction, error handling etc. can be modularized using the aspect-oriented paradigm. In business process modeling, aspects have been used to reduce visualization complexity, increase reuse and improve model maintainability. There are techniques which address aspects in modeling

The increasing capabilities of conversational agents (CAs) offer manifold opportunities to assist users in a variety of tasks. In an organizational context, particularly their potential to simulate a human-like interaction via natural language currently attracts attention both at the customer interface as well as for internal purposes, often in the form of chatbots. Emerging experimental studies on

With the advent of end-user and cloud computing, business users can implement information systems for work practices on their own – either from scratch or as extensions to existing systems. The resulting information systems, however, often remain hidden from managers and official IT units, and are therefore called “shadow IT systems”. When a shadow IT system is identified, the organization has to decide

Enterprise architecture (EA) models are tools of analysis, communication, and support towards enterprise transformation. These models need a suitable maintenance process to support comprehensive knowledge of the enterprise’s structure and dynamics. This study aims to identify and discuss the existing approaches to EA model maintenance published in the scientific literature. A systematic literature

Digital software platforms allow third parties to develop applications and thus extend their functionality. Platform owners provide platform boundary resources that allow for application development. For developers, platform integration, understood as the employment of platform resources, helps to realize application functionality effectively. Simultaneously, it requires integration effort and increases

Forms are central interfaces for information exchange between a government and its citizens. As a way to translate laws into practice, forms are an essential part facilitating this exchange. Unfortunately, forms often require substantial development effort to ensure they comply with legal requirements, with the result that citizens often describe them as highly complex. Standardization of forms through

Crowdfunding is now established as a valid alternative to conventional methods of financing for startups. Unfortunately, to date, research has not investigated how backers can be encouraged to support entrepreneurs beyond funding. The aim of this study is to design and evaluate certain design elements for reward-based crowdfunding platforms that can engage backers in co-creational activities for product

In the insurance sector, Asset Liability Management refers to the joint management of the assets and liabilities of a company. The liabilities mainly consist of the policies portfolios of the insurance company, which usually contain a large amount of policies. In the article, the authors mainly develop a highly efficient automatic generation of model points portfolios to represent much larger real

The complexity of development and deployment in today’s IT world is enormous. Despite the existence of so many pre-fabricated components, frameworks, cloud providers, etc., building IT systems still remains a major challenge and most likely overtaxes even a single ambitious developer. This results in spreading such development and deployment tasks over different team members with their own specialization

With the ever-growing popularity of sharing economy platforms, complementors increasingly face the challenge to manage their reputation on different platforms. The paper reports the results from an experimental online survey to investigate how and under which conditions online reputation is effective to engender trust across platform boundaries. It shows that (1) cross-platform signaling is in fact

Nowadays, we live surrounded by heterogeneous and distributed services that are available to people anytime and anywhere. Even though these services can be used individually, it is through their synchronized and combined usage that end-users are provided with added value. However, existing solutions to service composition are not targeted at ordinary end-users. In fact, these solutions require technical

In the course of the ongoing digitalization of production, production environments have become increasingly intertwined with information and communication technology. As a consequence, physical production processes depend more and more on the availability of information networks. Threats such as attacks and errors can compromise the components of information networks. Due to the numerous interconnections

Privacy regulations for data can be regarded as a major driver for data sovereignty measures. A specific example for this is the case of event data that is recorded by information systems during the processing of entities in domains such as e-commerce or health care. Since such data, typically available in the form of event log files, contains personalized information on the specific processed entities

Business processes and their outcomes rely on data whose values are changed during process execution. When unexpected changes occur, e.g., due to last minute changes of circumstances, human errors, or corrections of detected errors in data values, this may have consequences for various parts of the process. This challenges the process participants to understand the full impact of the changes and decide

Software development enterprises are under consistent pressure to improve their management techniques and development processes. These are comprised of several software development methodology (SDM) disciplines such as requirements acquisition, design, coding, testing, etc. that must be continuously improved and individually tailored to suit specific software development projects. The paper proposes

Existing methodologies for identifying data quality problems are typically user-centric, where data quality requirements are first determined in a top-down manner following well-established design guidelines, organizational structures and data governance frameworks. In the current data landscape, however, users are often confronted with new, unexplored datasets that they may not have any ownership

Today, as organizations constantly adjust their activities to meet ever-changing circumstances, continuous business transformation is taking place. However, planning and steering this transformation can be a daunting task as complexity has been built into the organization over the years. Enterprise Architecture (EA) has been widely adapted as a planning and governance approach to manage the complexity

Process mining represents a collection of data driven techniques that support the analysis, understanding and improvement of business processes. A core branch of process mining is conformance checking, i.e., assessing to what extent a business process model conforms to observed business process execution data. Alignments are the de facto standard instrument to compute such conformance statistics. However

Condition-based maintenance (CBM) has emerged as a proactive strategy for determining the best time for maintenance activities. In this paper, a case of a milling process with imperfect maintenance at a German automotive manufacturer is considered. Its major challenge is that only data with missing labels are available, which does not provide a sufficient basis for classical prognostic maintenance

Business process compliance is one of the prevalent challenges for companies. Despite an abundance of research proposals, companies still struggle with manual compliance checks and the understanding of compliance violations in the light of missing root-cause explanations. Moreover, approaches have merely focused on the control flow perspective in compliance checking, neglecting other aspects such as

The rapid standardization and specialization of cloud computing services have led to the development of cloud spot markets on which cloud service providers and customers can trade in near real-time. Frequent changes in demand and supply give rise to spot prices that vary throughout the day. Cloud customers often have temporal flexibility to execute their jobs before a specific deadline. In this paper

Convolutional neural network has been widely investigated for machinery condition monitoring, but its performance is highly affected by the learning of input signal representation and model structure. To address these issues, this paper presents a comprehensive deep convolutional neural network (DCNN) based condition monitoring framework to improve model performance. First, various signal representation

Modern manufacturing systems build on an effective scheduling scheme that makes full use of the system resource to increase the production, in which an important aspect is how to minimize the makespan for a certain production task (i.e., the time that elapses from the start of work to the end) in order to achieve the economic profit. This can be a difficult problem, especially when the production flow