Influencing Factors for the Adoption of Speech Assistance in Manufacturing

2023 | International Conference on Business Informatics | Citations: 0

Authors: Klingner, Philipp; Scharfe, Philipp

Abstract: In recent years, there has been a steady increase in the use of speech assistan ... Expand

Abstract: In recent years, there has been a steady increase in the use of speech assistants in the private environment. Although such assistance systems would also be beneficial for manufacturing (for example, because workers have their hands free), speech assistants have not yet been widely used in the industrial environment. Against this background, we develop in this article a model with factors that influence the decision of industrial firms whether to adopt speech assistance for manufacturing. In order to do so, we rely on the Technology-Organization-Environment (TOE) framework and by interviewing 10 experts from firms that develop or use speech assistance solutions. Our model consists of 17 context factors that influence whether companies adopt speech assistance in manufacturing. Collapse

Topics: data integrity data protection computer data storage privacy

Methods: qualitative interview machine learning natural language processing personal interview

Theories: theory of everything

A Prototype to Support Business Model Innovation through Crowdsourcing and Artificial Intelligence

2023 | International Conference on Business Informatics | Citations: 0

Authors: Klippenstein, Arthur; Weskamp, Dr Christoph; Laux, Florian; Neuhaus, Florian; Pfannschmidt, Karlson; Bülling, Melissa; Kassanke, Dr Stephan

Abstract: The development of new and innovative business models is a central challenge fo ... Expand

Abstract: The development of new and innovative business models is a central challenge for many companies, particularly for small and medium-sized companies. Information systems could support these companies by actively guiding them through a business model development process. However, the existing business model development tools only provide passive support for their users (e.g., digital whiteboards). Therefore, we set out to develop a prototype that actively supports its users by generating business model ideas. Informed by an existing design theory, we built a prototype relying on hybrid intelligence (i.e., the combination of human and artificial knowledge). The prototype iteratively generates new business model ideas by recombining existing knowledge, posts the ideas to a crowdsourcing platform for evaluation, and learns from the crowds' evaluation. This demonstration paper presents the prototype, the challenges we faced during its implementation, and directions for future research on machine-supported business model development. Collapse

Topics: business model crowdsourcing user interface usability value creation

Methods: design artifact design theory machine learning focus group survey

Theories: socio technical theory

Identifying Practical Challenges in the Implementation of Technical Measures for Data Privacy Compliance

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Klymenko, Oleksandra; Meisenbacher, Stephen; Matthes, Florian

Abstract: Modern privacy regulations provide a strict mandate for data processing entitie ... Expand

Abstract: Modern privacy regulations provide a strict mandate for data processing entities to implement appropriate technical measures to demonstrate compliance. In practice, determining what measures are indeed "appropriate" is not trivial, particularly in light of vague guidelines provided by privacy regulations. To exacerbate the issue, challenges arise not only in the implementation of the technical measures themselves, but also in a variety of factors involving the roles, processes, decisions, and culture surrounding the pursuit of privacy compliance. In this paper, we present 33 challenges faced in the implementation of technical measures for privacy compliance, derived from a qualitative analysis of 16 interviews with privacy professionals. In addition, we evaluate the interview findings in a survey study, which gives way to a discussion of the identified challenges and their implications. Collapse

Topics: privacy Google+

Methods: survey qualitative interview personal interview qualitative content analysis survey design

SHIFTING STRUCTURES - A SYSTEMATIC LITERATURE REVIEW ON PEOPLE ANALYTICS AND THE FUTURE OF WORK

2023 | European Conference On Information Systems | Citations: 0

Authors: Klöpper, Miriam; Köhne, Sonja

Abstract: The sudden decentralisation of work caused by the COVID-19 pandemic challenges ... Expand

Abstract: The sudden decentralisation of work caused by the COVID-19 pandemic challenges institutionalised work practices, which some companies seek to counter by using people analytics. Narratives around people analytics often portray it as an enabler of remote workers' (self-)organisation. Simultaneously, especially when deployed for performance management, people analytics is considered an enabler of workplace surveillance. Further, algorithmic biases in the systems can perpetuate social injustice and discrimination of marginalised groups, impacting established hierarchies and social structures in the workplace. Our study 1) provides an overview of the status of emerging themes around people analytics, remote working, and leadership, and 2) assesses the impact people analytics has on shifting structures in organisations. We guide our analysis by deploying and extending the Structurational Model of Technology. Our results suggest that people analytics poses vastly different challenges for employees and leaders, and that it can potentially contradict current trends towards flat hierarchies. Collapse

Topics: IT supported collaboration remote work pandemic database system IS impact

Methods: literature study field study structured literature research

Theories: structuration theory

EVERY BREAK YOU TAKE, EVERY CLICK YOU MAKE - EMPIRICAL INSIGHTS ON EMPLOYEES' PERCEPTION OF PEOPLE ANALYTICS

2023 | European Conference On Information Systems | Citations: 0

Authors: Klöpper, Miriam

Abstract: As work becomes increasingly decentralised, employers and employees alike are s ... Expand

Abstract: As work becomes increasingly decentralised, employers and employees alike are searching for tools that support (self-) organising and leadership in dispersed teams. Therefore, people analytics, as a form of algorithmic management, is increasingly gaining popularity. However, besides the alleged potential held by people analytics, it also has an inherent potential to serve as surveillance software and to perpetuate existing biases and discrimination. Whilst vendors of people analytics software provide a positive narrative and researchers from different disciplines provide extensive literature reviews, empirical insights remain scarce. Falling back on privacy calculus theory, we develop a research model to explain employees' perception of people analytics deployment in their workplace. Leveraging insights from a scenario-based online survey, we find that employees overwhelmingly disagree with the concept of people analytics. Implementing people analytics causes privacy concerns and erodes employees' trust in their organisation to a level where they are likely to consider leaving the company. Collapse

Topics: privacy perceived usefulness information privacy concern systems implementation human resource management

Methods: survey partial least squares path modeling ANOVA literature study field experiment

Theories: privacy calculus theory

Tools of Trade of the Next Blue-Collar Job? Antecedents, Design Features, and Outcomes of Interactive Labeling Systems

2023 | European Conference On Information Systems | Citations: 0

Authors: Knaeble, Merlin; Nadj, Mario; Germann, Luisa; Maedche, Alexander

Abstract: Supervised machine learning is becoming increasingly popular -and so is the nee ... Expand

Abstract: Supervised machine learning is becoming increasingly popular -and so is the need for annotated training data. Such data often needs to be manually labeled by human workers, not unlikely to negatively impact the involved workforce. To alleviate this issue, a new information systems class has emerged -interactive labeling systems. However, this young, but rapidly growing field lacks guidance and structure regarding the design of such systems. Against this backdrop, this paper describes antecedents, design features, and outcomes of interactive labeling systems. We perform a systematic literature review, identifying 188 relevant articles. Our results are presented as a morphological box with 14 dimensions, which we evaluate using card sorting. By additionally offering this box as a web-based artifact, we provide actionable guidance for interactive labeling system development for scholars and practitioners. Lastly, we discuss imbalances in the article distribution of our morphological box and suggest future work directions.To alleviate these issues, labeling tasks are nowadays performed in cooperation with machine intelligence. Hereby, a new class of information systems has emerged -that of interactive labeling (IL) systems. IL is defined as "combining automatic steps with incremental user input" (Bernard et al., 2018). IL differentiates from plain labeling tasks by incorporating machine intelligence in an interactive fashion, as opposed to using manual work start to end. For instance, when having crowdworkers annotate documents, Ramos et al. (2020) provide guidance in form of an iterative, incremental process, leveraging the workers capabilities to teach humans a skill. With only minimal training, their novices matched the performance of professionals. Their guidance further leads to lower frustration among participants. Chang et al. (2017) have worked on designing IL systems leveraging the scalability of crowdworking platforms. When having images labeled, they used a series of synchronized stages involving multiple workers each. By allowing for ambiguity and labeling as structures instead of binary decisions, they could decrease instruction effort and allow for an ex-post setting of label boundaries. While it may be easy to decide that a photo of a house cat should be labeled 'cat', and that of a Caterpillar-branded (short CAT) excavator should not be, the decision for a wild leopard is not straight forward. Hereby the stages of their system allow for labeler-led creation of new subcategories, if disagreement occurs. This is especially helpful to prevent fatal inconsistencies in the dataset, if, for instance, some labelers find leopards to be cats, while others do not. The IL system asks labelers for explanations for such disagreement, extracts sub-category names, and uses these as new labels to allow for the task issuers to resolve the question after labeling has concluded. So far, a considerable number of articles have already been published despite the young nature of this new class of information systems. Amershi et al. (2014) provide an initial overview, differentiate IL from previous works, and introduce the mistreatment of users as oracles. Further, we have previously studied user archetypes addressed in IL research illustrating two competing perspectives of how users are treated (Knaeble et al., 2020): (a) oracle (e.g. users are asked if a label is correct) versus (b) teacher (e.g. users can provide deeper explanations in labeling tasks). Moreover, recently, we derived five general design principles along prominent literature findings and exemplary IL approaches illustrating that the design of such systems is diverse, and can significantly vary in scope and functionality . However, this diversity encompasses a complex of dimensions and characteristics across different IL systems that is not currently well understood. Y. Zhang et al. (2022) have recently argued for more support for those developing IL systems, as they commonly need to be tailor-made. Knowing which design features IL systems offer (and which alternatives exist) is therefore of utmost importance. Hereby, designers and developers of IL systems require an overview of the available design features of IL systems, to be able to make educated decisions. Furthermore, research needs to draw connections between such design features, foregoing antecedents, and following outcomes. Recent research in crowdworking has highlighted the importance of both (Alpar and Osterbrink, 2020). Antecedents are hereby task and context specific requirements and necessities, in the context of IL systems this could be what data is supposed to be labeled, whereas outcomes are goals which are seen as desirable by designers, such as efficiency. By understanding such antecedents and outcomes, IL designers and developers get examples on how to optimize their systems regarding given antecedents or desired outcomes. As IL is a young and popular field of research the need for conducting such a study is exacerbated further. As we will show, the amount of relevant research is increasing rapidly. While we have derived knowledge about how IL systems currently treat users (Knaeble et al., 2020) and we outlined general goals to aim for when creating IL systems , there is a gap of design knowledge on how to achieve such goals. Specifically there is no overview of existing design features, foregoing antecedents, and following outcomes. Hereby, research has created, implemented, and evaluated numerous design features of IL systems, but is yet to aggregate such results for a holistic picture. On this basis, we formulate the following research question (RQ): How to describe antecedents, design features, and outcomes of interactive labeling systems in a morphological box? Hereby, we rely on a systematic literature review (SLR), deductive and inductive coding, as well as a card sorting evaluation. Our theoretical contributions lie in the following. First, we present a literature-grounded and userevaluated systematic overview of a new class of information systems, along antecedents, design features, Collapse

Topics: database system recommender system crowdsourcing open source systems development

Methods: qualitative interview card sorting literature sample literature study qualitative coding

Can you trust me? Using AI to review more than three decades of AI trust literature

2023 | European Conference On Information Systems | Citations: 0

Authors: Knickrehm, Charlotte; Voss, Marleen; Barton, Marie-Christin

Abstract: The ability of artificial intelligence (AI) to take on complex tasks can facili ... Expand

Abstract: The ability of artificial intelligence (AI) to take on complex tasks can facilitate humans' life, but also raise concerns about AI replacing the human workforce. Acceptance and prior trust are prerequisites for successfully using AI. Yet, there is no overview of the research streams that covers the topic of AI trust. We, therefore, analyzed all AI trust literature to this date. We first organized a large number of publications using a topic modeling approach, clustered the results into research streams within AI trust, and built a conceptual framework of human trust in AI. Our analysis yielded 56 topics which we assigned to 11 clusters. Further in-depth analysis of the cluster "human trust" revealed different organizational, AI, and human factors influencing AI trust. Our results contribute to the AI trust literature by reviewing the field, offering a model of human trust in AI using a novel mixed methods approach and uncovering areas for further research. Collapse

Topics: artificial intelligence privacy explainable artificial intelligence usability ergonomics

Methods: topic model cluster analysis literature sample literature study mixed method

Evaluation Criteria for Sociotechnical Systems for the Digitally Disadvantaged

2023 | International Conference on Information Systems | Citations: 0

Authors: Kniepkamp, Sophie; Noeltner, Markus; Kroenung, Julia

Abstract: This paper addresses the challenge of finding criteria to evaluate social inclu ... Expand

Abstract: This paper addresses the challenge of finding criteria to evaluate social inclusiveness of sociotechnical systems (STS). While IT offers opportunities to reduce inequalities, the "digital divide" is a growing challenge. This divide between individuals with access and sufficient digital literacy, has economic and social consequences. Although several factors have been identified as barriers to the use of IT or design principles for socially inclusive research, there is a gap in the literature in assessing the final STS in their social inclusivity. This paper aims to identify criteria for evaluating STS in terms of social inclusion of the digitally disadvantaged. Based on the STS perspective, design requirements and principles are derived to help design a checklist of whether needs of digitally disadvantaged have been met. The paper contributes to the existing body of knowledge by adding the STS design evaluation step to the current literature. Collapse

Topics: digital divide evaluation criteria Sustainable Development Goal

Methods: design principle literature study design requirement design artifact literature sample

Theories: sociotechnical systems theory

A Systematic Review of Anomaly Detection for Business Process Event Logs

2023 | Business & Information Systems Engineering | Citations: 0

Authors: Ko, Jonghyeon; Comuzzi, Marco

Abstract: While a business process is most often executed following a normal path, anomali ... Expand

Abstract: While a business process is most often executed following a normal path, anomalies may sometimes arise and can be captured in event logs. Event log anomalies stem, for instance, from system malfunctioning or unexpected behavior of human resources involved in a process. To identify and possibly fix these, anomaly detection has emerged recently as a key discipline in process mining. In the paper, the authors present a systematic review of the literature on business process event log anomaly detection. The review aims at selecting systematically studies in the literature that have tackled the issue of event log anomaly detection, classifying existing approaches based on criteria emerging from previous literature reviews, and identifying those research directions in this field that have not been explored extensively. Based on the results of the review, the authors argue that future research should look more specifically into anomaly detection on event streams, extending the number of event log attributes considered to determine anomalies, and producing more standard labeled datasets to benchmark the techniques proposed. Collapse

Topics: process mining database system business process management

Methods: event log anomaly detection literature sample literature study survey

Contributing to the Success of PLS in SEM: An Action Research Perspective

2023 | Communications of the Association for Information Systems | Citations: 0

Authors: Kock, Ned

Abstract: I share with Evermann and Rönkkö (2023) the belief that classic composite-based ... Expand

Abstract: I share with Evermann and Rönkkö (2023) the belief that classic composite-based partial least squares path modeling (PLS-PM) presents shortcomings when used to conduct structural equation modeling (SEM) analyses. The shortcomings can be traced back to one fundamental problem, which is that latent variables (LVs) are approximated in PLS-PM as exact linear combinations of their corresponding indicators. In SEM, each LV is in fact a factor; i.e., a linear combination of the indicators and a measurement residual. My approach to addressing the shortcomings of PLS-PM is rather unique among researchers concerned with quantitative methods. I have employed an action research approach, helping investigators employ SEM in their empirical studies. This has led to my development of a widely used software tool for SEM analyses. I illustrate my action research orientation by discussing three recent methodological developments with which I have been closely involved. Collapse

Methods: structural equation modeling partial least squares path modeling Monte Carlo simulation action research statistical power analysis