THE DINU-MODEL – A PROCESS MODEL FOR THE DESIGN OF NUDGES

The sociotechnical paradigm legitimates our discipline and serves as core identity of IS. In this study, we want to focus on IS-induced human behavior by introducing a process model for nudging in IS. In behavioral economics, the concept of nudging has been proposed, which makes use of human cognitive processes and can direct people to an intended behavior. In computer science, the concept of persuasion has evolved with similar goals. Both concepts, nudging and persuasion, can contribute to IS research and may help to explain and steer user behavior in information systems. We aim for an integration of both concepts into one digital nudging process model, making it usable and accessible. We analyzed literature on nudging and persuasion and derived different steps, requirements, and nudging elements. The developed process model aims at enabling researchers and practitioners to design nudges in e.g. software systems but may also contribute to other areas like IT governance. Though the evaluation part of our study has not yet been completed, we present the current state of the process model enabling more research in this area

Social Bots as Initiators of Human Interaction in Enterprise Social Networks

Enterprise Social Networks (ESNs) are said to have the potential to significantly improve communication and collaboration between employees. However, utilization is still a problem in organizations, as participation is voluntary. Current research on Affordance theory in IS research suggests one reason being that users may not always recognize the opportunities for action and the potential outcome of the corresponding actualization. In our qualitative study in a medium-sized company, we investigate how experiencing offline networking with other ESN users will help to recognize online networking potentials, leading to an increased actualization of ESN affordances. In addition, we investigate the role of social bots (here: Lunch Roulette Bot), which provoke interaction by inviting users to meet other employees for lunch, therefore nudging users to experience certain actualizations like offline networking. We find that social bots can be more helpful than conventional one-to-many solicitations of the management and increase human interaction in ESN

Status Quo, Critical Reflection, and the Road Ahead of Digital Nudging in Information Systems Research: A Discussion with Markus Weinmann and Alexey Voinov

Research on digital nudging has become increasingly popular in the information systems (IS) community. In this paper, we overview the current progress of, critically reflect on, and discuss further research on digital nudging in IS. To do so, we reviewed the literature and interviewed Markus Weinmann from Rotterdam School of Management at Erasmus University, one of the first scholars who introduced digital nudging to the IS community, and Alexey Voinov, Director of the Centre on Persuasive Systems for Wise Adaptive Living at University of Technology Sydney. We uncovered a gap between what we know about what constitutes digital nudging and how we can actually put consequent requirements into practice. In this context, the original nudging concept bears inherent challenges about, for example, the focus on individuals’ welfare, which, thus, also apply to digital nudging. Moreover, we need to better understand how nudging in digital choice environments differs from that in the offline world. To further distinguish itself from other fields that already tested various nudges in many different domains, digital nudging research in IS may benefit from a design science perspective in order to go beyond testing effectiveness and provide specific design principles for the different types of digital nudges

Ethical Guidelines for the Construction of Digital Nudges

Under certain circumstances, humans tend to behave in irrational ways, leading to situations in which they make undesirable choices. The concept of digital nudging addresses these limitations of bounded rationality by establishing a libertarian paternalist alternative to nudge users in virtual environments towards their own preferential choices. Thereby, choice architectures are designed to address biases and heuristics involved in cognitive thinking. As research on digital nudging has become increasingly popular in the Information Systems community, an increasing necessity for ethical guidelines has emerged around this concept to safeguard its legitimization in distinction to e.g. persuasion or manipulation. However, reflecting on ethical debates regarding digital nudging in academia, we find that current conceptualizations are scare. This is where on the basis of existing literature, we provide a conceptualization of ethical guidelines for the design of digital nudges, and thereby aim to ensure the applicability of nudging mechanisms in virtual environments

Theorizing the Concept of Agency in Human-Algorithmic Ensembles with a Socio-Technical Lens

The growing relevance of algorithmic systems, including artificial intelligence, for processes of value creation raise theoretical and practical interest in the conceptualization of actorhood and the balancing of human and technological agencies within socio-technical ensembles. Prominent theories of the IS discipline still reflect a human-centric conceptualization of agency, which we deem challenged by advances in machine learning technology. We therefore motivate a revised theorizing of the concept of agency with a socio-technical lens. For that, we apply an inductive top-down theorizing approach. In this short paper, we present the first inductive step by describing tensions, oppositions and contradictions in the discourse on agency in IS literature of the last 30 years in the AIS Senior Scholars’ Basket of journals. The preliminary findings uncover a conceptual and ontological incoherence surrounding the concept of agency in IS scholarship, and a gap between reviewed publications and the agency claims of algorithmic systems

IMPACT OF DATA COLLECTION ON ML MODELS: ANALYZING DIFFERENCES OF BIASES BETWEEN LOW- VS. HIGH-SKILLED ANNOTATORS

Labeled data is crucial for the success of machine learning-based artificial intelligence. However, companies often face a choice between collecting few annotations from high- or low-skilled annotators, possibly exhibiting different biases. This study investigates differences in biases between datasets labeled by said annotator groups and their impact on machine learning models. Therefore, we created high- and low-skilled annotated datasets measured the contained biases through entropy and trained different machine learning models to examine bias inheritance effects. Our findings on text sentiment annotations show both groups exhibit a considerable amount of bias in their annotations, although there is a significant difference regarding the error types commonly encountered. Models trained on biased annotations produce significantly different predictions, indicating bias propagation and tend to make more extreme errors than humans. As partial mitigation, we propose and show the efficiency of a hybrid approach where data is labeled by low-skilled and high-skilled workers

Enterprise social networks as digital infrastructures - understanding the utilitarian value of social media at the workplace

In this study, we first show that while both the perceived usefulness and perceived enjoyment of enterprise social networks impact employees’ intentions for continuous participation, the utilitarian value significantly outpaces its hedonic value. Second, we prove that the network’s utilitarian value is constituted by its digital infrastructure characteristics: versatility, adaptability, interconnectedness and invisibility-in-use. The study is set within a software engineering company and bases on quantitative survey research, applying partial least squares structural equation modeling

From Top to Bottom - Investigating the Changing Role of Hierarchy in Enterprise Social Networks

Social media, such as social networking platforms, are increasingly gaining importance in enterprise contexts. Enterprise social networking (ESN) is often associated with improved communication, information-sharing and problem-solving. At the same time, ESN has been argued to diminish the role of formal influence in that users increasingly derive authority from their contributions to the network rather than from their position in the organizational hierarchy. Others argue that ESN will diminish influence considerably by producing more democratic and inclusive communication structures. Yet, these assertions have so far remained largely unexplored empirically. Against this background, we explore what influence both a user’s position in the organization’s hierarchy and a user’s contributions on the network have on the the ability to elicit responses from other ESN users. We draw on a unique data set of more than 110,000 messages collected from the ESN platform used at Deloitte Australia. While we find evidence for both kinds of influence, our data also reveals that informal influence has a stronger effect and that, as the ESN community matures over time, communication structures become indeed more inclusive and balanced across hierarchical levels. We contribute a set of propositions that theorize the ways in which influence and communication pattern are shaped during the process of ESN emergence. Our results further underline the potentials of ESN to improve organic, user-driven communication and knowledge sharing within firms