Artificial Intelligence-Driven Convergence and its Moderating Effect on Multi-Source Trust Transfer

2023 | HICSS | Citations: 0

Authors: Renner, Maximilian; Lins, Sebastian; Söllner, Matthias; Jarvenpaa, Sirkka; Sunyaev, Ali

Abstract: AI-driven convergence describes how innovative products emerge from the interpla ... Expand

Abstract: AI-driven convergence describes how innovative products emerge from the interplay of embedded artificial intelligence (AI) in existing technologies. Trust transfer theory provides an excellent opportunity to deepen prevailing discussions about trust in such converged products. However, AI-driven convergence challenges existing theoretical assumptions. The context-specific interplay of multiple trust sources may affect users’ trust transfer and the predominance of trust sources. We contextualized AI-driven convergence and investigated its impact on multi-source trust transfer. We conducted semi-structured interviews with 25 participants in the context of autonomous vehicles. Our results indicate that users’ perceived trust source control, perceived trust source accessibility, and perceived trust source value creation share may moderate users’ trust transfer. We contribute to research by contextualizing convergence in AI, revealing the impact of AI-driven convergence on trust transfer and the importance of trust as a dynamic construct. Collapse

Topics: artificial intelligence value creation conversational agent perceived usefulness vehicular automation

Methods: qualitative interview qualitative coding personal interview experiment literature study

Identifying User Innovations through AI in Online Communities– A Transfer Learning Approach

2023 | International Conference on Information Systems | Citations: 0

Authors: Resch, Christian; Streibel, Julian; Feiter, Tim; Kock, Alexander

Abstract: Identifying innovative users and their ideas is crucial, for example, in crowds ... Expand

Abstract: Identifying innovative users and their ideas is crucial, for example, in crowdsourcing. But, analyzing large amounts of unstructured textual data from such online communities poses a challenge for organizations. Therefore, researchers started developing automated approaches to identify innovative users. Our study introduces an advanced machinelearning approach that minimizes manual work by combining transfer learning with a transformer-based design. We train the model on separate datasets, including an online maker community and various internet texts. The maker community posts represent need-solution pairs, which express needs and describe fitting prototypes. Then, we transfer the model and identify potential user innovations in a kitesurfing community. We validate the identified posts by manually checking a subsample and analyzing how words affect the model's classification decision. This study contributes to the growing portfolio of user innovation identification by combining state-of-the-art natural language processing and transfer learning to improve automated identification. Collapse

Topics: innovation management online community internet technology computer hardware open source

Methods: machine learning BERT qualitative coding transformer model natural language processing

From playmate to assistant; User experiences of integrating ChatGPT into knowledge work

2023 | International Conference on Information Systems | Citations: 0

Authors: Retkowsky, Jana; Hafermalz, Ella; Huysman, Marleen

Abstract: While Generative AI is believed to impact societies, organizations, and work, l ... Expand

Abstract: While Generative AI is believed to impact societies, organizations, and work, little is known about how ChatGPT is experienced by early users and its impact on their work practices for knowledge work. This is concerning as ChatGPT is exactly the opposite of many of the technological systems studied before -it is decentralized (from an organizational perspective), multipurpose, and open-ended, and it is more autonomous by creating new syntactic content. Building on an explorative interview study with 31 early adopters, we identified different use types for ChatGPT. Thereupon, we theorize a phase model of experiencing Generative AI use as an emotional process. The exploratory insights challenge the information systems field to rethink the passive role of technology to which 'users' delegate subtasks toward a collaborative role with AI as a teammate or colleague. Finally, we observe worker-system intertwinement, and we discuss its potential consequences on the level of the individual, organization, and even society. Collapse

Topics: knowledge work generative AI productivity customer service marketing management

Methods: chatGPT qualitative interview theory development ethnography business process modeling

Theories: sociomaterialism theory

Human–Artificial Intelligence Collaboration in Prediction: A Field Experiment in the Retail Industry

2023 | Journal of Management Information Systems | Citations: 0

Authors: Revilla, Elena; Saenz, Maria Jesus; Seifter, Matthias; Ma, Ye

Abstract: This study investigates the role of human intervention in artificial intelligenc ... Expand

Abstract: This study investigates the role of human intervention in artificial intelligence/machine learning (AIML)-driven predictions. By doing so, we distinguish between three different types of human-AIML collaboration: automation, adjustable automation, and augmentation. We theorize that prediction uncertainty and time horizon represent two critical determinants of forecast accuracy. Based on a field experiment involving AIML-driven demand forecasts approximately 1,888 stock-keeping units in the retail industry, we rely on a multivalued treatment effect methodology to measure the effects of human-AIML collaboration on forecast accuracy. Our findings show that human intervention complements AIML-driven forecasts most effectively (augmentation) in predictions with long time horizons and low uncertainty. However human intervention is least likely to contribute to the effectiveness of AIML predictions (automation) in environments with short time horizons and high uncertainty. We discuss implications for extant theory and propose a framework outlining the conditions in which human intervention is most likely to add predictive value to human-AIML collaborations. Collapse

Topics: artificial intelligence human computer interaction human AI collaboration decision making task uncertainty

Methods: machine learning computational algorithm field experiment experiment regression analysis method

Analysing cooperatives’ digital maturity using a synthetic indicator

2023 | International Journal of Information Management | Citations: 0

Authors: Ribeiro-Navarrete, Belén; Martín Martín, José María; Guaita-Martínez, José Manuel; Simón-Moya, Virginia

Abstract: A company’s digitalisation journey spans multiple dimensions and processes. Howe ... Expand

Abstract: A company’s digitalisation journey spans multiple dimensions and processes. However, studies of digital maturity have focused only on certain parts of the process. This study presents a method capable of fully capturing a company’s level of digital maturity. A DP2 indicator of digital maturity was constructed. This in­ dicator is based on responses to a company survey of digitalisation in different business areas and processes. Companies with the highest degree of digitalisation are the oldest and largest (most employees). Differences between companies and sectors can be explained by the level of digitalisation in terms of digital management intensity, departmental agility and digital orientation. Collapse

Topics: IS maturity mobile system IS management innovation management cloud computing

Methods: survey field study literature study descriptive statistic linear regression analysis

Creating Data Policies for Digital Business Ecosystems

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Ribeiro, Vitor; Barata, João; Cunha, Paulo Rupino da

Abstract: Data policies are high-level guidelines that define how the organization handle ... Expand

Abstract: Data policies are high-level guidelines that define how the organization handles data. In the age of crossorganizational digital business ecosystems, organizations are facing the need to define data policies that allow them to operate in decentralized scenarios. We conducted a Design Science Research (DSR) project to develop an approach for data policy management for digital business ecosystems. Our artifact was developed and demonstrated in a leading European IT provider. Our results include (1) an approach for data policy creation and (2) a data policy cycle. For theory, our work extends the literature with an approach for data policy management in digital business ecosystems in a highly regulated sector. For practice, our approach can support practitioners in developing the necessary data policies based on their context, considering their location, data-related regulations, available data assets, and organizational environment. Collapse

Topics: digital ecosystem data governance data quality legal context General Data Protection Regulation

Methods: literature study design science kernel theory

Decentralizing Data Governance: A Case Study in TELCO Data Ecosystems

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Ribeiro, Vitor; Barata, João; Cunha, Paulo Rupino da

Abstract: Data governance is crossing organizational boundaries. However, governance mech ... Expand

Abstract: Data governance is crossing organizational boundaries. However, governance mechanisms for data ecosystems have particularities, and tools to assist companies in steering decentralized data governance are lacking. This paper addresses these two gaps by presenting the results of a case study in the telecommunications industry (TELCO). After evaluating seventeen data governance maturity models and modeling the network actors' architecture, we classify data governance mechanisms across different companies according to the most prevailing profile of (1) data consumer, (2) data producer, and (3) data prosumer. Our findings confirm the significant differences in governing data ecosystems and present foundational data governance mechanisms for socio-technical networks. The results offer a starting point for the required data governance dimensions of more advanced maturity models crucial to developing a data ecosystem. For practice, our work illustrates essential decentralized data governance mechanisms in a highly regulated sector of the economy. Collapse

Topics: data governance digital ecosystem supply chain management data security value creation

Methods: maturity model case study qualitative interview literature study design science

Beyond Paper and Plastic: A Meta-Model for Credential Use and Governance

2023 | European Conference On Information Systems | Citations: 0

Authors: Richter, Daniel; Praas, Christopher; Anke, Jürgen

Abstract: ID cards, public transport tickets, and diplomas are examples of credentials th ... Expand

Abstract: ID cards, public transport tickets, and diplomas are examples of credentials that society has established as a means to provide trustworthy information to others. In the digital world, the emergence of self-sovereign identity as a new paradigm for the management of digital credentials aims to narrow the conceptual gap between digital and physical credentials. The ongoing digital transformation in the public sector requires dealing with a large variety of credentials in different forms systematically. However, there is still currently no generic conceptual model of credentials in the Information Systems (IS) discipline. We employ design science research to develop a unified meta-model on credentials, their use, and their governance. Our results contribute to research through an empirically grounded conceptualization of credentials and provide practitioners with a common basis to capture, analyze, and design the handling of credentials in real-world scenarios. Collapse

Topics: knowledge base Near Field Communication IT governance security policy government system

Methods: design science metamodel design requirement literature study qualitative interview

Decoding the Landscape of Smart City Platforms: A Taxonomy Approach

2023 | International Conference on Business Informatics | Citations: 0

Authors: Richter, Kenneth; Zimmer, Markus P.; Lemmer, Kristina

Abstract: The notion of Smart Cities (SCs) has gained significant attention in recent yea ... Expand

Abstract: The notion of Smart Cities (SCs) has gained significant attention in recent years as cities become increasingly connected, integrated, and technologically advanced. Smart City Platforms (SCPs) are an important element of this movement representing the backbone for collecting, processing and analyzing urban data streams from peripheral devices and systems in a city. This study seeks to identify the key dimensions and characteristics of SCPs. Based on existing literature, we craft a taxonomy following Nickerson et al.'s (2013) guidelines. The resulting SCP taxonomy contributes to the literature on SCs by offering a set of characterizations of SCPs that provide a framework to analyze SCPs and identify types of SCPs. Collapse

Topics: IT security open source access control data encryption big data

Methods: structured literature research literature sample case study literature study

EDUCATING, EVALUATING, ADVISING, AND ENTERTAINING - DIGITAL INFLUENCERS AND THEIR NARRATIVES

2023 | European Conference On Information Systems | Citations: 0

Authors: Richter, Shahper; Richter, Alexander

Abstract: Organizations have been increasingly exploring storytelling as a valuable strat ... Expand

Abstract: Organizations have been increasingly exploring storytelling as a valuable strategy to engage customers to increase their attention and retention. Social media platforms like Instagram have become essential tools for many brands to use storytelling through influencers. In this study, we explore the narratives constructed by digital influencers, as they play a crucial role in shaping their brand image and engagement with their audience. By analysing the narrative strategies used by digital influencers, we contribute to a deeper understanding of the role and impact of digital storytelling. We identify, illustrate, and discuss four narrative strategies: educating, evaluating, advising, and entertaining. Our study motivates further research to develop a detailed conceptual understanding of digital influencers and digital storytelling. Collapse

Topics: Instagram social media website Snapchat marketing management

Methods: qualitative interview theory development narrative analysis qualitativ observational study participant observation

Theories: flow theory social penetration theory communication theory