Artificial Intelligence as a Service: Trade-Offs Impacting Service Design and Selection

2023 | International Conference on Information Systems | Citations: 0

Authors: Brecker, Kathrin; Lins, Sebastian; Trenz, Manuel; Sunyaev, Ali

Abstract: AI as a Service (AIaaS) is a promising path to leverage AI capabilities from th ... Expand

Abstract: AI as a Service (AIaaS) is a promising path to leverage AI capabilities from the cloud. However, there is no one-size-fits-all service, but heterogenous service options since interdependent AIaaS characteristics require trade-offs. We lack knowledge on these tradeoffs and how they result from conflicting characteristics. Therefore, we interviewed 39 AIaaS providers, customers, and consultants to provide rich descriptions of interdependent characteristics and uncover resulting trade-offs and their consequences. This study contributes to a better understanding of the inner functioning and interplay of AIaaS characteristics and discusses how this complex nature of service offerings impacts providers' design and customers' selection decisions. Collapse

Topics: artificial intelligence cloud computing ease of use data protection economies of scale

Methods: qualitative interview design artifact constant comparative analysis qualitative coding triangulation

Theories: SERVQUAL core competency theory

A temporal graph framework for intelligence extraction in social media networks

2023 | Information & Management | Citations: 0

Authors: Chung, Wingyan; Lai, Vincent S.

Abstract: Social media networks (SMNs) are increasingly used in professional management of ... Expand

Abstract: Social media networks (SMNs) are increasingly used in professional management of knowledge workers and related assets. However, the factors affecting behavioral trends and activity levels in these networks are not well understood. Although social and cognitive theories can help to explain human behavior in traditional social networks, their application to SMNs has not been validated. Traditional social network modeling techniques may not accurately predict real-world SMN activities. This research developed a temporal graph framework for in­ telligence extraction in SMNs. Theory-based, data-driven models (Conformity Model (COM), Recency-Primacy Model (REM), Trend Interaction Model (TIM), Periodic Interaction Model (PIM)) were developed based on the framework to capture various aspects of user behavior: conformity effect, recency, primacy, periodicity, and dynamic trend. The models capture the activity history and dynamically combine pricing information to enhance predictive accuracy. Using data of 83,536 GitHub software repositories on cryptocurrency, this article reports the results of experiments that compare the models’ performance in predicting SMN activities over time. Experi­ mental results show that the model (REM) that captures recency/primacy effects of human cognitive processing outperformed other models in 9 (out of 18) measures pertaining to engagement, contribution, influence, and popularity. Primacy plays a dominant role in predicting engagement, contribution, and popularity, whereas recency plays a key role in predicting influence. Short-term trend (modeled with TIM) was found to yield significantly better performance on predicting user contribution. The models also outperformed an integrated machine learning (IML) model by most measures. Overall, the effects modeled by REM and TIM were found to be more significant than the effects modeled by COM, PIM, and IML. The research contributes to enhancing un­ derstanding of SMN behavior, developing new models to simulate and predict SMN activities, and designing new artifacts for information systems practitioners to manage knowledge assets and to extract SMN intelligence. Collapse

Topics: cryptocurrency social network systems development situation awareness user behavior

Methods: experiment machine learning longitudinal research computational algorithm time series analysis

Theories: psychological theory social contagion theory social interactionist theory social impact theory social sciences theory

Social Media Data in an Augmented Reality System for Situation Awareness Support in Emergency Control Rooms

2023 | Information Systems Frontiers | Citations: 0

Authors: Fromm, Jennifer; Eyilmez, Kaan; Baßfeld, Melina; Majchrzak, Tim A.; Stieglitz, Stefan

Abstract: During crisis situations, emergency operators require fast information access to ... Expand

Abstract: During crisis situations, emergency operators require fast information access to achieve situation awareness and make the best possible decisions. Augmented reality could be used to visualize the wealth of user-generated content available on social media and enable context-adaptive functions for emergency operators. Although emergency operators agree that social media analytics will be important for their future work, it poses a challenge to filter and visualize large amounts of social media data. We conducted a goal-directed task analysis to identify the situation awareness requirements of emergency operators. By collecting tweets during two storms in Germany we evaluated the usefulness of Twitter data for achieving situation awareness and conducted interviews with emergency operators to derive filter strategies for social media data. We synthesized the results by discussing how the unique interface of augmented reality can be used to integrate social media data into emergency control rooms for situation awareness support. Collapse

Topics: Twitter situation awareness augmented reality smart device social media

Methods: qualitative interview computational algorithm design principle machine learning qualitative content analysis

Exploring the use of IoT Data for Heightened Situational Awareness in Centralised Monitoring Control Rooms

2023 | Information Systems Frontiers | Citations: 0

Authors: Horita, Flávio; Baptista, João; de Albuquerque, João Porto

Abstract: This paper traces the expansion of a network of IoT sensors to improve the effec ... Expand

Abstract: This paper traces the expansion of a network of IoT sensors to improve the effectiveness of a centralised control room in Brazil in anticipating natural hazards. This centralised model relies on using IoT data by highly qualified experts replacing previous smaller local structures. We draw on the notion of Situational Awareness to carry out the study. Results show that although the operators were not always familiar with the characteristics of locations, the use of IoT data heightened their situational awareness in the centralised control room by improving perception and comprehension. However, they still relied on local knowledge and learned experiences to support projection and anticipation of risks. The study highlights that although data analytics systems are capable of expanding operators’ perception of local elements, they must be complemented by local richer forms of information, needed to anticipate risks and make critical decisions with major impact on local population. Collapse

Topics: mobile system internet of things situational awareness decision making analytical information system

Methods: qualitative interview personal interview case study qualitative coding machine learning

Theories: situation awareness theory

Model-Based Cybersecurity Analysis

2023 | Business & Information Systems Engineering | Citations: 0

Authors: Jiang, Yuning; Jeusfeld, Manfred A.; Ding, Jianguo; Sandahl, Elin

Abstract: Critical infrastructure (CIs) such as power grids link a plethora of physical co ... Expand

Abstract: Critical infrastructure (CIs) such as power grids link a plethora of physical components from many different vendors to the software systems that control them. These systems are constantly threatened by sophisticated cyber attacks. The need to improve the cybersecurity of such CIs, through holistic system modeling and vulnerability analysis, cannot be overstated. This is challenging since a CI incorporates complex data from multiple interconnected physical and computation systems. Meanwhile, exploiting vulnerabilities in different information technology (IT) and operational technology (OT) systems leads to various cascading effects due to interconnections between systems. The paper investigates the use of a comprehensive taxonomy to model such interconnections and the implied dependencies within complex CIs, bridging the knowledge gap between IT security and OT security. The complexity of CI dependence analysis is harnessed by partitioning complicated dependencies into cyber and cyber-physical functional dependencies. These defined functional dependencies further support cascade modeling for vulnerability severity assessment and identification of critical components in a complex system. On top of the proposed taxonomy, the paper further suggests power-grid reference models that enhance the reproducibility and applicability of the proposed method. The methodology followed was design science research (DSR) to support the designing and validation of the proposed artifacts. More specifically, the structural, functional adequacy, compatibility, and coverage characteristics of the proposed artifacts are evaluated through a three-fold validation (two case studies and expert interviews). The first study uses two instantiated power-grid models extracted from existing architectures and frameworks like the IEC 62351 series. The second study involves a real-world municipal power grid. Collapse

Topics: IT security virtualization technology database system knowledge representation data center

Methods: reference modelling case study qualitative interview design artifact simulation

Navigating within the Digitalization Journey: Results and Implications of the First Maturity Assessment of German Public Health Agencies

2023 | International Conference on Business Informatics | Citations: 0

Authors: Kauffmann, Anna Lina; Neubauer, Maria; Reinsch, Felix; Reuther, Melina; Schick, Doreen; Stark, Jeannette; Bley, Katja; Heidmann, Nick; Eymann, Torsten

Abstract: The Covid 19 pandemic revealed the need for Public Health Agencies to mature di ... Expand

Abstract: The Covid 19 pandemic revealed the need for Public Health Agencies to mature digitally. To help those agencies with their digitalization endeavor, a public health agency maturity model (PHAMM) has been developed, evaluated, and employed by 366 institutions to determine their digital maturity and to prioritize actions within digitalization projects. This paper discusses the digital maturity of German public health institutions and derives first insights into components spanning the PHAMM dimensions. Public health agencies can use these components to leverage their digital maturity in future digitalization projects. Implications are discussed for how digitalization projects with an enhanced impact can be defined and for future maturity modeling research. Collapse

Topics: IS maturity user friendliness system efficiency usability situation awareness

Methods: data transformation principal component analysis survey maturity model design science

Theories: balance theory situation awareness theory

How Sociotechnical Realignment and Sentiments Concerning Remote Work are Related – Insights from the COVID-19 Pandemic

2023 | Business & Information Systems Engineering | Citations: 0

Authors: Kohn, Vanessa; Frank, Muriel; Holten, Roland

Abstract: The COVID-19 pandemic forced sociotechnical systems (STS) to highly integrate re ... Expand

Abstract: The COVID-19 pandemic forced sociotechnical systems (STS) to highly integrate remote work. Large-scale analyses show that the positivity of tweets about work from home decreased until COVID-19 was declared a pandemic by the WHO and re-increased in the weeks that followed. Nevertheless, it is unclear if this reaction is due to personal and organizational developments or if it mirrors the realignment of entire STS. The present study uses Q methodology to identify differences in how STS realign to the externally enforced integration of remote work. Only STS that reach a state of high alignment to remote work conditions by successfully shifting communication and procedures to digital spheres can be considered resilient. The results show that employees describe their personal experiences with remote work as more positive the higher their level of sociotechnical realignment. Furthermore, personal digital resilience is correlated to successful STS realignment as well. The results confirm the importance of realigning not only the technical and social components of STS but above all their sociotechnical interaction. Negative sentiments relate in particular to the low realization of humanistic objectives in STS. Collapse

Topics: remote work IT supported collaboration pandemic productivity privacy

Methods: sentiment analysis Q methodology qualitative interview linear regression analysis Mann Whitney U test

Theories: sociotechnical systems theory socio technical theory

Is a Pretrained Model the Answer to Situational Awareness Detection on Social Media?

2023 | HICSS | Citations: 0

Authors: Lo, S.; Lee, K.; Zhang, Y.

Abstract: Social media can be valuable for extracting information about an event or incid ... Expand

Abstract: Social media can be valuable for extracting information about an event or incident on the ground. However, the vast amount of content shared, and the linguistic variants of languages used on social media make it challenging to identify important situational awareness content to aid in decision-making for first responders. In this study, we assess whether pretrained models can be used to address the aforementioned challenges on social media. Various pretrained models, including static word embedding (such as Word2Vec and GloVe) and contextualized word embedding (such as DistilBERT) are studied in detail. According to our findings, a vanilla DistilBERT pretrained language model is insufficient to identify situation awareness information. Fine-tuning by using datasets of various event types and vocabulary extension is essential to adapt a DistilBERT model for real-world situational awareness detection. Collapse

Topics: Twitter situational awareness social media Wikipedia wiki

Methods: BERT DistilBERT support vector machine machine learning word embedding

When AI joins the Team: A Literature Review on Intragroup Processes and their Effect on Team Performance in Team-AI Collaboration

2023 | European Conference On Information Systems | Citations: 0

Authors: Zercher, Désirée; Jussupow, Ekaterina; Heinzl, Armin

Abstract: Although systems based on artificial intelligence can collaborate with humans o ... Expand

Abstract: Although systems based on artificial intelligence can collaborate with humans on various complex tasks, little is known about how AI systems can successfully collaborate with human teams (team-AI collaboration). Team performance research states that team composition and intragroup processes are important predictors of team performance. However, it remains unclear how intragroup processes differ in team-AI collaboration from processes in human teams and how these differences affect team performance. To answer these questions, we synthesize evidence from 18 empirical articles. The results indicate that intragroup processes like communication and coordination are less effective in team-AI collaboration. Moreover, empirical findings are conflicting on whether team cognition and trust are higher in team-AI collaboration compared to human teams. Likewise, the results on team performance differences between team-AI collaboration and human teams are inconsistent. With this article, we offer a foundation for future research on team-AI collaboration.One of our main findings is that communication and coordination behavior is less apparent in team-AI collaboration compared to human teams. This can be explained by a lack of human-like behavior and the low communicative and coordinative capabilities of the AI system. At the same time, the expectation of humans to collaborate with AI might have reduced their own communication and coordination behavior in the sense of a self-fulfilling prophecy. That denotes that the expectation of collaborating with an AI system with low communicative and coordinative capabilities impairs participants' own communication and coordination. However, the included literature did not clearly differentiate between communication with the AI system and communication between the human team members, which would have offered more insight into this possible explanation. Moreover, it was not clearly differentiated between coordination and communication, which were mainly used synonymously. This can be regarded as problematic since coordination always requires a form of communication, but the opposite is not necessarily true. Therefore, our literature review does not offer selective results on communication and coordination. Generally, the experimental setting offered limited room for communication and coordination since there was no face-to-face interaction. Future research should clearly distinguish between communication and coordination. In a similar vein, future research will have to identify how AI participation affects different forms of communication (e.g., verbal, nonverbal, paraverbal) and communication contents (e.g., information exchange, formal and informal communication) in more detail. Equally, different forms of coordination behavior in team-AI collaboration need to be investigated in more detail. Finally, there are several aspects that indicate a more complex relationship between communication, coordination, and team performance in team-AI collaboration. Communication and coordination in team-AI collaboration can be improved by training Successful Team-AI Collaboration Thirty-first European Conference on Information Systems (ECIS 2023), Kristiansand, Norway 11and prior collaboration experience. Both are affected by attitudes, AI systems capabilities, and time spent collaborating with AI. Future research will have to further improve our understanding of these factors and their relationship with communication and coordination in team-AI collaboration. Collapse

Topics: artificial intelligence team productivity human AI collaboration human computer interaction robotic

Methods: literature study literature sample experimental task cross sectional research conceptual modelling

Crisis-driven digital transformation as a trigger for process virtualization: Fulfilling knowledge work process requirements for remote work

2023 | International Journal of Information Management | Citations: 0

Authors: Zeuge, Anna; Schaefer, Cindy; Weigel, Andreas; Eckhardt, Andreas; Niehaves, Bjoern

Abstract: Process Virtualization Theory (PVT) proposes a set of requirements and relations ... Expand

Abstract: Process Virtualization Theory (PVT) proposes a set of requirements and relationships to explain and predict whether or not a knowledge work process can be successfully virtualized. However, at least in remote work, the crisis-driven digital transformation (e.g., during the COVID-19 pandemic) shows that almost all knowledge work processes can be virtualized unexpectedly and immediately. Since the requirements for these processes remain the same and need to be met to continue the processes remotely, an interesting question arises of how infor­ mation technology (IT) can help to meet these requirements in a crisis-driven digital transformation of knowl­ edge work. To address this question, we conducted 40 semi-structured interviews with a multiple-case approach using a critical realist perspective. Our findings contribute to information systems (IS) research in a twofold way. First, we demonstrate that the crisis-driven digital transformation of knowledge work triggers a revisited perspective on PVT by turning virtualized knowledge work processes into a prerequisite. Second, we show how the IT characteristics of PVT (representation, reach, monitoring capability) help to fulfill knowledge work pro­ cess requirements in remote work settings and outline two additional IT characteristics (social presence and situation awareness) that positively support the fulfillment. Collapse

Topics: knowledge work digital transformation pandemic remote work IT supported collaboration

Methods: qualitative interview personal interview case study qualitative coding qualitative content analysis