Adam, Martin (2019)
Social Cues as Digital Nudges in Information Systems Usage Contexts.
Technische Universität Darmstadt
Dissertation, Erstveröffentlichung
Kurzbeschreibung (Abstract)
Analysing human cognition and decision-making has become highly relevant in information systems (IS) research. Yet, although the notion of cognitive biases has been studied for more than 40 years in psychology and other related fields, IS researchers have only recently expressed explicit interest in this phenomenon. Even more nascent is the IS stream that emphasizes the usage and understanding of biases in the favor of humanistic outcomes (e.g., the well-being of individuals) beyond previous scientific endeavors to pursue instrumental goals (e.g., the profit of companies). This fact is reflected in the recent emergence and call for digital nudges - influences that rely on heuristics and biases to guide individuals to beneficial decisions through modest adjustments of the digital choice environments. To advance the emergent research in this field, this thesis targets one of the major bias categories: the social bias (i.e., systematic errors that result from an individual’s interpretation of social cues). Within four articles, the thesis addresses the role of social cues as digital nudges in various IS usage contexts. The first two articles investigate how directly-traceable social cues can overcome service adoption hurdles: Precisely, the first article investigates how employing a verbal (i.e., platform self-disclosure) and a nonverbal social cue (i.e., message interactivity) in a conversational agent (i.e., chatbot) influence users to voluntary self-disclose private information (i.e., e-mail addresses). Moreover, the results revealed that the analysed social cues do not have individual effects, but in fact boost each other through their interaction. The second article deals with the application of various directly-traceable social cues (e.g., pictures of human avatars) as well as the role of personalized recommendations in financial advisory services to improve investors’ financial well-being. The results demonstrate that not only directly-traceable social cues but also recommendations can increase a user’s perceived social presence during the interaction, which in turn influences potential investors to invest higher amounts. The third article continues with recommendations as social cues, yet analyses them from an indirectly-traceable perspective and is devoted to investigating whether the source of the recommendation (i.e., seller or other customers) influences the acceptance of the recommendation in augmented reality applications to help customers in finding the best product for their needs. The findings indicate that customer recommendations reduce a customer’s perceived fit uncertainty of a product, resulting in a higher intention to purchase of a product that previous customers recommended. However, customers refrain from adhering to an automatically-generated recommendation despite recent technological advances that may provide more personalized and thus more suitable recommendations than generic customer recommendations. The fourth and last article examines the impact of displaying sold-out products on campaign success in reward-based crowdfunding. The valuable information indicate how potential backers make use of displayed sold-out product as social cues to derive information for their decision-making from previous backing behavior. In addition, the findings also showed that sold-out products do not have an impact on their own, however, their effect is also influenced by other factors in the environment, namely discount amount and the number of backers (i.e., another social cue). Thus, the article provides learnings for project creators on the design of reward option menus. Overall, this thesis showcases the variety and importance of social cues in numerous applications and is, therefore, to be understood as a first approach to expanding the understudied research field. Furthermore, the results enrich previous research and elucidate various underlying explanatory mechanisms of how and why biased decision-making takes place and how these mechanisms may be used to nudge users in directions beneficial for them and for the employer of these nudges. The overarching contributions of this thesis for research consists of (1) investigating the existence and effects of various social cues on user decision-making, and (2) probing social cues in several IS usage contexts with their unique circumstances and influences, not only in a vacuum but also in conjunction with other interacting variables. Additionally, this thesis provides interesting and sometimes even counterintuitive recommendations as well as actionable and generalizable guidelines on social cues that practitioners can easily apply to various contexts.
| Typ des Eintrags: | Dissertation | ||||
|---|---|---|---|---|---|
| Erschienen: | 2019 | ||||
| Autor(en): | Adam, Martin | ||||
| Art des Eintrags: | Erstveröffentlichung | ||||
| Titel: | Social Cues as Digital Nudges in Information Systems Usage Contexts | ||||
| Sprache: | Englisch | ||||
| Referenten: | Benlian, Prof. Dr. Alexander ; Buxmann, Prof. Dr. Peter | ||||
| Publikationsjahr: | Juli 2019 | ||||
| Ort: | Darmstadt | ||||
| Datum der mündlichen Prüfung: | 4 Juli 2019 | ||||
| URL / URN: | https://tuprints.ulb.tu-darmstadt.de/8848 | ||||
| Kurzbeschreibung (Abstract): | Analysing human cognition and decision-making has become highly relevant in information systems (IS) research. Yet, although the notion of cognitive biases has been studied for more than 40 years in psychology and other related fields, IS researchers have only recently expressed explicit interest in this phenomenon. Even more nascent is the IS stream that emphasizes the usage and understanding of biases in the favor of humanistic outcomes (e.g., the well-being of individuals) beyond previous scientific endeavors to pursue instrumental goals (e.g., the profit of companies). This fact is reflected in the recent emergence and call for digital nudges - influences that rely on heuristics and biases to guide individuals to beneficial decisions through modest adjustments of the digital choice environments. To advance the emergent research in this field, this thesis targets one of the major bias categories: the social bias (i.e., systematic errors that result from an individual’s interpretation of social cues). Within four articles, the thesis addresses the role of social cues as digital nudges in various IS usage contexts. The first two articles investigate how directly-traceable social cues can overcome service adoption hurdles: Precisely, the first article investigates how employing a verbal (i.e., platform self-disclosure) and a nonverbal social cue (i.e., message interactivity) in a conversational agent (i.e., chatbot) influence users to voluntary self-disclose private information (i.e., e-mail addresses). Moreover, the results revealed that the analysed social cues do not have individual effects, but in fact boost each other through their interaction. The second article deals with the application of various directly-traceable social cues (e.g., pictures of human avatars) as well as the role of personalized recommendations in financial advisory services to improve investors’ financial well-being. The results demonstrate that not only directly-traceable social cues but also recommendations can increase a user’s perceived social presence during the interaction, which in turn influences potential investors to invest higher amounts. The third article continues with recommendations as social cues, yet analyses them from an indirectly-traceable perspective and is devoted to investigating whether the source of the recommendation (i.e., seller or other customers) influences the acceptance of the recommendation in augmented reality applications to help customers in finding the best product for their needs. The findings indicate that customer recommendations reduce a customer’s perceived fit uncertainty of a product, resulting in a higher intention to purchase of a product that previous customers recommended. However, customers refrain from adhering to an automatically-generated recommendation despite recent technological advances that may provide more personalized and thus more suitable recommendations than generic customer recommendations. The fourth and last article examines the impact of displaying sold-out products on campaign success in reward-based crowdfunding. The valuable information indicate how potential backers make use of displayed sold-out product as social cues to derive information for their decision-making from previous backing behavior. In addition, the findings also showed that sold-out products do not have an impact on their own, however, their effect is also influenced by other factors in the environment, namely discount amount and the number of backers (i.e., another social cue). Thus, the article provides learnings for project creators on the design of reward option menus. Overall, this thesis showcases the variety and importance of social cues in numerous applications and is, therefore, to be understood as a first approach to expanding the understudied research field. Furthermore, the results enrich previous research and elucidate various underlying explanatory mechanisms of how and why biased decision-making takes place and how these mechanisms may be used to nudge users in directions beneficial for them and for the employer of these nudges. The overarching contributions of this thesis for research consists of (1) investigating the existence and effects of various social cues on user decision-making, and (2) probing social cues in several IS usage contexts with their unique circumstances and influences, not only in a vacuum but also in conjunction with other interacting variables. Additionally, this thesis provides interesting and sometimes even counterintuitive recommendations as well as actionable and generalizable guidelines on social cues that practitioners can easily apply to various contexts. |
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| Alternatives oder übersetztes Abstract: |
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| URN: | urn:nbn:de:tuda-tuprints-88487 | ||||
| Sachgruppe der Dewey Dezimalklassifikatin (DDC): | 100 Philosophie und Psychologie > 150 Psychologie 300 Sozialwissenschaften > 330 Wirtschaft |
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| Fachbereich(e)/-gebiet(e): | 01 Fachbereich Rechts- und Wirtschaftswissenschaften 01 Fachbereich Rechts- und Wirtschaftswissenschaften > Betriebswirtschaftliche Fachgebiete 01 Fachbereich Rechts- und Wirtschaftswissenschaften > Betriebswirtschaftliche Fachgebiete > Fachgebiet Information Systems & E-Services |
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| Hinterlegungsdatum: | 28 Jul 2019 19:55 | ||||
| Letzte Änderung: | 28 Jul 2019 19:55 | ||||
| PPN: | |||||
| Referenten: | Benlian, Prof. Dr. Alexander ; Buxmann, Prof. Dr. Peter | ||||
| Datum der mündlichen Prüfung / Verteidigung / mdl. Prüfung: | 4 Juli 2019 | ||||
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| Suche nach Titel in: | TUfind oder in Google | ||||
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