Human vs. Automated Sales Agents: How and Why Customer Responses Shift Across Sales Stages

2023 | Information Systems Research | Citations: 0

Authors: Adam, Martin; Roethke, Konstantin; Benlian, Alexander

Abstract: Customers in sales processes increasingly encounter automated sales agents (ASAs ... Expand

Abstract: Customers in sales processes increasingly encounter automated sales agents (ASAs) that complement or replace human sales agents (HSAs). Yet, little is known about whether, how, and why customers respond to ASAs in contrast to HSAs across successive decision stages of the same sales process. Even less is known about customer responses to HSA-ASA combinations, where both agents assume distinct roles and focus on complementary tasks that are traditionally performed by only one single sales agent. Against this backdrop, this paper explores the influence of increasingly common sales representative (rep) types (i.e., ASA, HSA, and HSA-ASA) on customer decisions across sales stages. Drawing on information processing theory and the literature on hedonic-utilitarian decision making, we investigate customer responses to text-based ASAs from vendor companies in two common early stages of email sales processes (i.e., sales initiation stages) when customers successively decide whether to indicate their initial interest in an offer and then, whether to provide their contact information. Specifically, we conducted two complementary multi-decision experiments, namely (1) a randomized field experiment in a high-stakes sales initiation setting (n = 325) and (2) a subsequent randomized online experiment to complement the real-world insights (n = 408). Our core findings reveal reversing effect patterns of sales rep types across stages: although customers are more likely to indicate their initial interest to HSAs (versus ASAs) because of HSAs’ higher levels of social presence, they are less likely to provide contact information to HSAs because of HSAs’ lower levels of performance expectancy and effort expectancy. We also show that HSA-ASA combinations can be reasonable options for single ASAs, yet contextual features of the sales setting may affect differential customer responses to HSA-ASA combinations (versus ASAs) in each sales stage. Taken together, we uncover shifting effect patterns in customer responses to sales rep types across successive sales stages and shed light on the consecutive underlying mechanisms that explain these shifts. These findings have significant implications for vendor companies seeking to allocate HSAs and/or ASAs effectively across various decision stages in sales processes and beyond. History: Wonseok Oh, Senior Editor and Khim Yong Goh; Associate Editor. Funding: This work was supported by the Center for Responsible Digitality (ZEVEDI) and the German Research Foundation (DFG) [Grant 471168026]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/isre.2022.1171. Collapse

Topics: electronic mail social presence decision making recommender system information system use

Methods: experiment randomized field experiment regression analysis method experimental task field experiment

Theories: information processing theory

Promise not fulfilled: FinTech, data privacy, and the GDPR

2023 | Electronic Markets | Citations: 0

Authors: Dorfleitner, Gregor; Hornuf, Lars; Kreppmeier, Julia

Abstract: This article analyzes how the General Data Protection Regulation (GDPR) has affe ... Expand

Abstract: This article analyzes how the General Data Protection Regulation (GDPR) has affected the privacy practices of FinTech firms. We study the content of 276 privacy statements respectively before and after the GDPR became binding. Using text analysis methods, we find that the readability of the privacy statements has decreased. The texts of privacy statements have become longer and use more standardized language, resulting in worse user comprehension. This calls into question whether the GDPR has achieved its original goal—the protection of natural persons regarding the transparent processing of personal data. We also link the content of the privacy statements to FinTech-specific determinants. Before the GDPR became binding, more external investors and a higher legal capital were related to a higher quantity of data processed and more transparency, but not thereafter. Finally, we document mimicking behavior among FinTech industry peers with regard to the data processed and transparency. Collapse

Topics: legal context General Data Protection Regulation privacy electronic finance website

Methods: parametric test paired t-test descriptive statistic Student's t-test qualitative content analysis

Theories: privacy calculus theory

Robo-advisors and investment intention: A perspective of value-based adoption

2023 | Information & Management | Citations: 0

Authors: Hong, Xianpei; Pan, Liwei; Gong, Yeming; Chen, Qian

Abstract: Financial robo-advisors have been widely used to assist individuals in their inv ... Expand

Abstract: Financial robo-advisors have been widely used to assist individuals in their investment decisions, making it important to reduce uncertainties in the assistance process. Existing empirical studies rarely explore uncertainty reduction strategies and their implications on users’ investment intentions in the context of financial roboadvisors; our study attempts to address this gap. We construct a model to explain how uncertainty reduction strategies affect users’ investment intention in using financial robo-advisors. By collecting and analyzing a sample of 307 financial robo-advisor users, we find that algorithmic interpretability, structural assurance, and interactivity as uncertainty reduction strategies are positively related to users’ investment intention through the value-based adoption mechanism. Our research extends the value-based adoption model and uncertainty reduction theory in the financial robo-advisor context. We provide insights to financial robo-advisor service providers about focusing on improving algorithmic transparency, third-party assurance, and interactivity of financial robo-advisors to enhance perceived value and investment intention. Collapse

Topics: robo advisor privacy artificial intelligence usage intention organizational productivity

Methods: survey computational algorithm factor analysis statistical hypothesis test structural equation modeling

Theories: uncertainty reduction theory

Towards Designing Robo-Advisory to Promote Consensus Efficient Group Decision-Making in New Types of Economic Scenarios

2023 | European Conference On Information Systems | Citations: 0

Authors: Namyslo, Nicole; Jung, Dominik

Abstract: Robo-advisors are a new type of FinTech increasingly used by millennials in pla ... Expand

Abstract: Robo-advisors are a new type of FinTech increasingly used by millennials in place of traditional financial advice. Building on artificial intelligence, robo-advisors provide personalized asset and wealth management services. Their application and study have hitherto focused exclusively on individual advisory regarding asset management. We observe a pressing need to investigate roboadvisors' application for complex artificial intelligence based recommendation tasks both, in context of group decision-making and in contexts beyond asset management, due to robo-advisors' potential as a lever for integrating artificial intelligence in the entire decision-making process. Thus, we present a action design research in progress aimed at designing such a robo-advisor. More specifically, this study investigates whether and how robo-advisory promotes consensus-efficient group decision-making in new types of economic scenarios (after-sales). Based on a comprehensive problem formulation, we aim towards deriving a set of meta-requirements and design principles that are embodied in a preliminary prototypical instantiation of a robo-advisor. Collapse

Topics: robo advisor decision making recommender system artificial intelligence requirements analysis

Methods: structured literature research design artifact design principle action design research kernel theory

What determines FinTech success?—A taxonomy-based analysis of FinTech success factors

2023 | Electronic Markets | Citations: 0

Authors: Werth, Oliver; Cardona, Davinia Rodríguez; Torno, Albert; Breitner, Michael H.; Muntermann, Jan

Abstract: Value creation in the financial services sector has been fundamentally transform ... Expand

Abstract: Value creation in the financial services sector has been fundamentally transformed by digitally born financial technology (FinTech) companies. FinTech companies synthesize information systems with financial services. Given its disruptive power, the FinTech phenomenon has received great attention in academic research, practice, and media. Still, limited systematic research provides a structure and holistic view of FinTechs’ success. Aiming to enhance understanding of the factors enabling FinTech success, we classify success factors across extant scientific literature on distinct FinTech business model archetypes. Our analysis reveals that the “cost–benefit dynamic of the innovation,” “technology adoption,” “security, privacy, and transparency,” “user trust,” “user-perceived quality,” and “industry rivalry” are crucial factors for FinTech success and can be seen as “grand challenges” for the FinTech ecosystem. In addition, we validate and discuss our findings with real-world examples from the FinTech industry and two interviews with stakeholders from the FinTech ecosystem. Our study contributes to the knowledge of FinTechs by providing a classification system of success factors for practitioners and researchers. Collapse

Topics: electronic finance business model privacy robo advisor technology adoption

Methods: qualitative content analysis qualitative interview case study literature study Google news

An Augmented UTAUT Model for Robo-Advisor Adoption

2022 | Americas Conference on Information Systems | Citations: 0

Authors: Horn, Maximilian; Missong, Martin

Abstract: This study aims at identifying factors influencing robo-advisory demand and usa ... Expand

Abstract: This study aims at identifying factors influencing robo-advisory demand and usage. We show that it is essential to tell apart the intention to invest in financial markets from the intention to use robo-advisor technology. Therefore, we develop an augmented model of the "Unified Theory of Adoption and Use of Technology" (augmented UTAUT model) that allows to explain both of these customers' intentions simultaneously. The model is evaluated by means of a PLS approach using online survey data collected in the US and Germany. Empirical results shed light on (potential) investors' intentions and attitudes towards robo-advisory services. The model developed in this paper is generally applicable whenever it comes to model adoption of a new technology that relies on the use of a basic product or a basic technology. Collapse

Topics: robo advisor usage intention privacy information system use behavioral intention

Methods: survey partial least squares regression partial least squares path modeling psychometrics computational algorithm

Theories: unified theory of acceptance and use of technology

The Digitization of Investment Management – An Analysis of Robo-Advisor Business Models

2022 | International Conference on Business Informatics | Citations: 0

Authors: Metzler, DennisRenee; Neuss, Nicole; Torno, Albert

Abstract: The emergence of so-called Robo-Advisors (RAs) is disrupting the financial servi ... Expand

Abstract: The emergence of so-called Robo-Advisors (RAs) is disrupting the financial services industry. RAs are algorithm-based systems that digitize and automate the investment advisory process including portfolio recommendation, risk diversification, portfolio rebalancing, and portfolio monitoring. Scientific research in this field is still in its infancy and lacks a comprehensive understanding of the underlying business model (BM) of RAs to comprehensively understand the RA business and to further identify their potential to disrupt the financial services industry. Therefore, in this article, we conduct a multiple case study across the fifteen biggest US-based RAs to explain the basic characteristics and special features of RA BMs. Thereby, we distinguish between pure algorithm-based RAs and hybrid RAs with dedicated human oversight. Through an in-depth analysis of publicly available qualitative data, we contribute to the existing research by unleashing significant elements that underline the power of RAs to disrupt the financial services industry. Collapse

Topics: database system value creation website information system use IT investment

Methods: computational algorithm case study qualitative content analysis multiple case study

Users taking the blame? How service failure, recovery, and robot design affect user attributions and retention

2022 | Electronic Markets | Citations: 0

Authors: Meyer (née Mozafari), Nika; Schwede, Melanie; Hammerschmidt, Maik; Weiger, Welf Hermann

Abstract: Firms use robots to deliver an ever-expanding range of services. However, as ser ... Expand

Abstract: Firms use robots to deliver an ever-expanding range of services. However, as service failures are common, service recovery actions are necessary to prevent user churn. This research further suggests that firms need to know how to design service robots that avoid alienating users in case of service failures. Robust evidence across two experiments demonstrates that users attribute successful service outcomes internally, while robot-induced service failures are blamed on the firm (and not the robot), confirming the well-known self-serving bias. While this external attributional shift occurs regardless of the robot design (i.e., it is the same for warm vs. competent robots), the findings imply that service recovery minimizes the undesirable external shift and that this effect is particularly pronounced for warm robots. For practitioners, this implies prioritizing service robots with a warm design for maximizing user retention for either type of service outcome (i.e., success, failure, and failure with recovery). For theory, this work demonstrates that attribution represents a meaningful mechanism to explain the proposed relationships. Collapse

Topics: robotic crowdsourcing robo advisor conversational commerce user behavior

Methods: ANOVA parametric test post-hoc analysis survey experiment

Theories: attribution theory cognitive theory

Helping or Hindering? How Clients’ Experiences Relate to Their Robo Advisory Use

2022 | HICSS | Citations: 0

Authors: Schulz, Anke; Tuschke, Anja; Ilgen, Alexander; Ilgen, Alexander

Abstract: Firms are increasingly introducing new business models based on digital technolo ... Expand

Abstract: Firms are increasingly introducing new business models based on digital technologies in knowledgeintensive, risky contexts that were long immune to them. In the financial industry, banks are opening themselves to robo advisory, an algorithm-based service supporting private clients’ investment decisions. Based on our access to a recent data set of 11,302 clients from a leading German robo advisory provider, we have the unique opportunity to analyze how clients react to algorithm-based services in contexts with high uncertainty and risk. Guided by theorical foundations of knowledge and routines, we find clients’ personal and business experiences with the focal bank to both, help and hinder their robo advisory use. Collapse

Topics: robo advisor digital service decision making decision support online banking

Methods: qualitative interview computational algorithm robustness check descriptive statistic regression analysis method

HICSS-55 Minitrack Introduction Algorithm-Based Advisory in the Service Sector

2022 | HICSS | Citations: 0

Authors: Schulz, Anke; Tuschke, Anja

Abstract: This minitrack focuses on the impact of algorithms on knowledge-intensive servic ... Expand

Abstract: This minitrack focuses on the impact of algorithms on knowledge-intensive services - such as portfolio or legal advice. Designing and implementing algorithmbased technologies and business models in knowledgeintensive, risky contexts is complex and challenged by clients’ considerable trepidations. Their successful design and implementation requires recognizing and meeting technical, organizational, as well as behavioral challenges. This minitrack sets out to explore such challenges facing algorithm-based advisory to better understand both, their foundations and solution approaches. It guides future research and practice by identifying real-world barriers to and enablers of algorithm-based innovation. Collapse

Topics: robo advisor artificial intelligence

Methods: personal interview computational algorithm qualitative interview regression analysis method