Figure 1 - uploaded by Marcel Ruoff
Content may be subject to copyright.
Source publication
Teams are crucial for organizations in making data-driven decisions. However, current business intelligence & analytics (BI&A) systems are primarily designed to support individuals and, therefore, cannot be used effectively in co-located team interactions. To address this challenge, we conduct a design science research (DSR) project to design a mul...
Context in source publication
Context 1
... on their conceptualization, effective use is an aggregated construct comprising three hierarchical dimensions: (1) transparent interaction, (2) representational fidelity, and the outcome dimension (3) informed action (Burton-Jones and Grange 2013). As illustrated in Figure 1, the three dimensions of effective use are influencing each other. Initially, the unimpeded access to the system's representations (transparent interaction) improves the ability to obtaining representations that faithfully reflect the domain (representational fidelity). ...
Similar publications
Stationary retail is suffering from both the digital transformation and the influence of the COVID-19 pandemic. Furthermore, the perception of stationary retail is strongly influenced by customer emotions. Thus, an important aspect of designing successful service interactions (SI) is the ability of the service personnel (SP) to recognize, understan...
Process mining has received tremendous attention from research and industry, establishing itself as a highly sought-after technology. Despite the technological maturity of process mining solutions, which has been achieved through extensive investments in research and development, organizations still face the challenge of elusive value when systemat...
There is a constantly growing demand for accessible transactional data, not only for analytical purposes, but also to support the rapid global adoption of open banking. Around a quarter of the world’s data is generated by financial institutions (Winship et al., 2016), with an estimated total of 708.5 billion global non-cash transactions between 201...
Serverless functions have emerged as a prominent paradigm in software deployment, providing automated resource scaling, resulting in demand-based operational expenses. One of the most significant challenges associated with serverless functions is the cold start delay, preventing organisations with latency-critical web applications from adopting a s...
Due to urban expansion, agriculture, and the long history of the cadastre in Finland, the cadastral index map has millions of border markers that have low spatial accuracy, incomplete feature properties or both. The low quality of the border markers creates issues, such as forest cutting machines cutting from the wrong side of the border. As it is...
Citations
... The interviews and sales conversations were recorded and transcribed. Similar to previous studies with formative evaluations (e.g., [9,35]), we analyzed the data using a Strength-Weakness-Opportunity-Threat (SWOT) analysis. The results are shown in Table 1. ...
Large language models (LLMs) have generated excitement in many areas and may also make human-like conversations with social robots possible. Drawing from human-robot interaction literature and interviews, we developed Saleshat based on the commercial social robot Furhat and the large language model GPT-4. Saleshat emphasizes refined natural language processing and dynamic control of the robot’s physical appearance through the LLM. Responses from the LLM are processed sequentially, enabling the robot to react quickly. The results of our first formative evaluation with six users engaging in a sales conversation about Bluetooth speakers show that Saleshat can provide accurate and detailed responses, maintain a good conversation flow, and show dynamically controlled non-verbal cues. With our findings, we contribute to research on social robots and LLMs by providing design knowledge for LLM-based social robots and by uncovering the benefits and challenges of integrating LLMs into a social robot.
... Toreini et al. (2022) also conclude that dashboard users face difficulties in managing their limited attentional resources when processing the presented information. Consequently, achieving effective use of dashboards for business users remains a challenge (Ruoff and Gnewuch, 2021). "The benefits that organizations accrue from information systems depend on how effectively the systems are used" (Trieu et al., 2022, p. 645). ...
... An essential factor in the successful implementation of BI&A solutions is whether the system is capable of supporting the skills of the targeted user (Michalczyk et al., 2020). While the specific contexts may differ, dashboards are usually designed for business users who are familiar with the application domain and use the dashboard regularly for their daily work (Ruoff and Gnewuch, 2021). ...
With the proliferation of Business Intelligence and Analytics, data storytelling has gained increasing importance to improve communicating analytical insights to business users and support decision-making. While conceptual research on data storytelling suggests that these techniques can help improve decision-making, there is a lack of prescriptive knowledge on how to design data stories in Business Intelligence and Analytics. Moreover, it is not understood how data stories can facilitate effective use and support decision-making of business users. To address this challenge, we conduct a Design Science Research (DSR) project. Drawing on the theory of effective use and data storytelling techniques, we propose three design principles that we instantiate in a prototype. The results of two focus groups indicate that enhancing dashboards with data storytelling techniques increases transparent interaction and representational fidelity. Our DSR project contributes novel design knowledge for data stories that facilitate effective use.
... For example, several studies address the challenges of ambiguity in natural language by proposing design features for disambiguating unclear user input (e.g., Gao et al., 2015;Setlur et al., 2016). In addition, an emerging body of work explores how users interact with conversational dashboards using speech, touch, and keyboard (e.g., Ruoff & Gnewuch, 2021;Saktheeswaran et al., 2020). ...
Governments and health organizations increasingly use dashboards to provide real-time information during natural disasters and pandemics. Although these dashboards aim to make crisis-related information accessible to the general public, the average user can have a hard time interacting with them and finding the information needed to make everyday decisions. To address this challenge, we draw on the theory of effective use to propose a theory-driven design for conversational dashboards in crisis response, which improves users’ transparent interaction and access to crisis-related information. We instantiate our proposed design in a conversational dashboard for the COVID-19 pandemic that enables natural language interaction in spoken or written form and helps users familiarize themselves with the use of natural language through conversational onboarding. The evaluation of our artifact shows that being able to use natural language improves users’ interaction with the dashboard and ultimately increases their efficiency and effectiveness in finding information. This positive effect is amplified when users complete the onboarding before interacting with the dashboard, particularly when they can use both natural language and mouse. Our findings contribute to research on dashboard design, both in general and in the specific context of crisis response, by providing prescriptive knowledge for extending crisis response dashboards with natural language interaction capabilities. In addition, our work contributes to the democratization of data science by proposing design guidelines for making information in crisis response dashboards more accessible to the general public.
... Joseph Weizenbaum (1966) already introduced the idea of enabling users to interact through natural language with technological artifacts in the 1960s by developing ELIZA. However, only recently have conversational assistants been introduced and researched in various application areas, such as customer service (Gnewuch et al. 2017), financial advisory (Morana et al. 2020), health care (Prakash and Das 2020), and data analytics (Ruoff and Gnewuch 2021a). ...
Forecasting support systems (FSSs) support demand planners in important forecasting decisions by offering statistical forecasts. However, planners often rely on their judgment more than on system-based advice which can be detrimental to forecast accuracy. This is caused by a lack of understanding and subsequent lack of trust in the FSS and its advice. To address this problem, we explore the potential of extending the traditional static assistance (e.g., manuals, tooltips) with conversational assistance provided by a conversational assistant that answers planners' questions. Drawing on the theory of effective use, we aim to conduct a framed field experiment to investigate whether conversational (vs. static) assistance better supports planners in learning the FSS, increases their trust, and ultimately helps them make more accurate forecasting decisions. With our findings, we aim to contribute to research on FSS design and the body of knowledge on the theory of effective use.
... Subsequently, a suitable kernel theory is selected from which authors directly derive, for instance, meta-requirements and design principles. As an example, Ruoff and Gnewuch (2021) derive two meta-requirements for designing multimodal BI&A systems from the Theory of Effective Use that is, in turn, developed further into design principles for multimodal BI&A systems. Seidel et al. (2017) derive preliminary design principles based on "(…) salient affordances required in the sensemaking process." ...
Theory is an essential part of design research and helps us to explain what we see or guide what we design. In the paper, we shed light on how kernel theories are used in developing design principles in Design Science Research (DSR). We do this by reporting on a systematic literature review, from which we have extracted a set of six mechanisms to operationalize kernel theory. Each mechanism consists of an activity (e.g., "transform to" or "derive from") and an application point (e.g., meta-requirements or design principles) representing wherein the chain of concepts the kernel theory was used. The paper reflects on what we have learned about the use of kernel theories and translates this into recommendations and issues for further research. We provide researchers with guidance to use kernel theories more efficiently and give a big picture of the possibilities of kernel theory operationalization.
... Today, decision makers can use BI&A systems on their smart phones or tablets while on the go (Power 2013). In meetings, cross-functional teams can make decisions together by collaboratively interacting with BI&A systems on large interactive screens (e.g., Microsoft's Surface Hub) (Ruoff and Gnewuch 2021). To facilitate transparent interaction, particularly for non-expert users, BI&A systems increasingly support multiple modalities. ...
... Despite the increasing interest in NLIs for data visualization tools (e.g. [5,8,10,20,26,[29][30][31]35]), NLIs are still vulnerable to breakdowns due to various potential errors in executing natural language commands. The errors can be classifed into three categories [38]: ...
... A promising application of CUIs is their ability to "aid, assist and advise people in personal and organizational decision situations" (Power et al., 2019, p. 1). Therefore, CUIs are increasingly implemented in AI-enabled systems in general and dashboards in specific to assist the user in the interaction with these systems (Morana et al., 2020;Ruoff et al., 2020) and to enhance current systems for better decision making (Quamar et al., 2020;Rzepka & Berger, 2018). However, existing research has often focused on the technical challenges (Gao et al., 2015;Quamar et al., 2020), resulting in a lack of design knowledge for conversational dashboards. ...
Dashboards are increasingly used by governments and health organizations to provide important information to the general public during a crisis. However, in contrast to organizational settings, the majority of the general population has not or rarely used dashboards before and therefore often struggles to interact effectively with these dashboards. To address this challenge, we conduct a design science research (DSR) project to design a conversational dashboard that enables natural language-based
interactions to facilitate its effective use. Drawing on the theory of effective use, our DSR
project aims to provide theory-grounded design knowledge for conversational dashboards that help users to access and find information via natural language. Moreover, we seek to provide novel insights that support researchers and practitioners in understanding and designing more natural and effective interactions between users and dashboards.
In low-resource settings, effective and impactful decision-making within healthcare systems is essential due to limited resources. Extracting meaningful information from Health Management Systems like the District Health Information System(DHIS2) dashboard has significant implications in improving healthcare planning, and resource allocation. In this study, we investigate values that govern managers’ effective use of DHIS2 Dashboard. We conducted a total of fourteen interviews, which yielded six fundamental objectives (data accuracy, resource optimization, scalability, interactivity, data silos, stakeholder engagement) and thirteen means-ends objectives assessed by managers when operating the dashboard effectively. The developed means-ends objectives network will provide an information springboard for researchers as it uncovers key drivers of effective use of health information systems. Moreover, this research will assist both practitioners and implementers in enhancing features of comparable platforms, to be rolled out in similar contexts.
