Conversational Agents - Exploring Generative Mechanisms and Second-hand Effects of Actualized Technology Affordances

Many organisations jumped on the bandwagon and implemented conversational agents (CAs) as a new communication channel. Customers benefit from shorter resolution times, ubiquitous availability, and consistent and compliant responses. However, despite the hype around CAs and the various benefits for customers, we know little about the effects of external facing CAs on the human workforce. This is crucial to better manage the possible changes in the work organisation. Adopting a critical realist stance and using the lens of technology affordances we explore a) why users increasingly actualize CA affordances and b) the first and second-hand effects of affordance actualisation on customers and human employees. We conducted semi-structured interviews with 18 experts in the field and introduce the term affordance effects pairs describing the relationships between the first and second-hand effects. We further explain which generative mechanisms lead to an increasing actualization of affordances and the associated effects

Digital Feedback for Digital Work? Affordances and Constraints of a Feedback App at InsurCorp

Little is known about how digital work shapes the exchange of performance feedback, even though today’s digital and global world demands for more continuous feedback than annual reviews. This research investigates a feedback app in a naturalistic context within a globally leading financial service corporation (InsurCorp). Drawing on malleability and voluntary participation, the app offers possibilities to send and request feedback between employees. Rich contextual insights from a multinational pilot study with 568 users are gained by triangulating qualitative data from 21 semi-structured interviews and69 feedback app user reviews with usage data. Anchored in the theory of affordances, we provide insights on use practices and find that the app affords operational-level feedback exchange on specific subjects, while general feedback on sensitive topics is preferably exchanged in person. To understand actualization facilitators and barriers, we take a social-technical systems perspective to elaborate contextual factors that influence the individual’s actualization decision

LOOKING BENEATH THE TIP OF THE ICEBERG: THE TWO-SIDED NATURE OF CHATBOTS AND THEIR ROLES FOR DIGITAL FEEDBACK EXCHANGE

Enterprises are forecasted to spend more on chatbots than on mobile app development by 2021. Up to today little is known on the roles chatbots play in facilitating feedback exchange. However, digitization and automation put pressure on companies to setup digital work environments that enable reskilling of employees. Therefore, a structured analysis of feedback-related chatbots for Slack was conducted. Our results propose six archetypes that reveal the roles of chatbots in facilitating feedback exchange on performance, culture and ideas. We show that chatbots do not only consist of conversational agents integrated into instant messenger but are tightly linked to complementary front-end systems such as mobile and web apps. Like the upper part of an iceberg, the conversational agent is above water and visible within the chat, whereas many user interactions of feedback-related chatbots are only possible outside of the instant messenger. Further, we extract six design principles for chatbots as digital feedback systems. We do this by analyzing chatbots and linking empirically observed design features to (meta-)requirements derived from explanatory theory on feedback, self-determination and persuasive systems. The results suggest that chatbots benefit the social environment of conversation agents and the richness of the graphical user interface of external applications

The Impact of Anthropomorphic and Functional Chatbot Design Features in Enterprise Collaboration Systems on User Acceptance

Information technology is rapidly changing the way how people collaborate in enterprises. Chatbots integrated into enterprise collaboration systems can strengthen collaboration culture and help reduce work overload. In light of a growing usage of chatbots in enterprise collaboration systems, we examine the influence of anthropomorphic and functional chatbot design features on user acceptance. We conducted a survey with professionals familiar with interacting with chatbots in a work environment. The results show a significant effect of anthropomorphic design features on perceived usefulness, with a strength four times the size of the effect of functional chatbot features. We suggest that researchers and practitioners alike dedicate priorities to anthropomorphic design features with the same magnitude as common for functional design features in chatbot design and research

User-Friendly MES Interfaces:Recommendations for an AI-Based Chatbot Assistance in Industry 4.0 Shop Floors

The purpose of this paper is to study an Industry 4.0 scenario of ‘technical assistance’ and use manufacturing execution systems (MES) to address the need for easy information extraction on the shop floor. We identify specific requirements for a user-friendly MES interface to develop (and test) an approach for technical assistance and introduce a chatbot with a prediction system as an interface layer for MES. The chatbot is aimed at production coordination by assisting the shop floor workforce and learn from their inputs, thus acting as an intelligent assistant. We programmed a prototype chatbot as a proof of concept, where the new interface layer provided live updates related to production in natural language and added predictive power to MES. The results indicate that the chatbot interface for MES is beneficial to the shop floor workforce and provides easy information extraction, compared to the traditional search techniques. The paper contributes to the manufacturing information systems field and demonstrates a human-AI collaboration system in a factory. In particular, this paper recommends the manner in which MES based technical assistance systems can be developed for the purpose of easy information retrieval

Augmented Facilitation: Designing a multi-modal Conversational Agent for Group Ideation

Human facilitators face the challenge to structure and collect relevant insights from collaborative creative work sessions, which can suffer if they face a high workload. Hence, for effective value co-creation in organizational ideation we suggest an facilitation augmentation with a conversational agent (CA). CAs have the ability to support respective collaborative work by documenting and analyzing unstructured data. Following the design science research paradigm, and based on the literature about facilitation and human-AI collaboration, we derive design principles to develop a CA prototype that collects ideas from a group ideation session and displays them back in a structured (multi-modal) manner. We evaluate the CA by conducting four focus groups. Key findings show that the CA successfully distills and enriches information. Our study contributes to understanding the role of CA in augmenting facilitation and it provides guidance for practice on how to integrate these technologies in group meetings

Designing Process-based Chatbots in Enterprises: The Case of Business Travel Organization Considering the Users’ Perspective and Business Value

Chatbots have attracted much research attention in recent years, and organizations have increasingly begun applying them in everyday working life. However, researchers have rarely investigated how chatbots can support everyday tasks in enterprises. As such, we lack design knowledge for chatbots that support internal business processes since research has mostly examined customer-facing use cases. Notably, researchers have rarely considered chatbots’ economic and user-related effects, which, thus, remain unknown. To address this gap, we conducted a design science research study to survey a process-based chatbot application for business processes. From examining the scenario, we deduced design principles and implemented a software artifact. We evaluated the concept with 69 participants and surveyed the users’ perspective in terms of design and acceptance and the organizational perspective in terms of process efficiency and quality. In doing so, 1) we derived six design principles for process-based chatbots and implemented a respective chatbot, which enabled a user-adapted process and provided situational-dependent input options and support; 2) we found that users had a positive attitude towards using chatbots for business processes in terms of user experience and acceptance; and 3) the process performed at an economically efficient level that compared well with existing solutions and that IT affinity and prior experience had no influence on performance. Furthermore, our solution improved the process quality compared to the existing solution

Responsible AI and Analytics for an Ethical and Inclusive Digitized Society

publishedVersio

Chatbots at Digital Workplaces – A Grounded-Theory Approach for Surveying Application Areas and Objectives

Background: Chatbots are currently on the rise as more and more researchers tackle this topic from different perspectives. Simultaneously, workplaces and ways of working are increasingly changing in the context of digitalization. However, despite the promised benefits, the changes still show problems that should be tackled more purposefully by chatbots. Application areas and underlying objectives of a chatbot application at digital workplaces especially have not been researched yet. Method: To solve the existing problems and close the research gap, we did a qualitative empirical study based on the grounded-theory process. Therefore, we interviewed 29 experts in a cross-section of different industry sectors and sizes. The experts work in the information systems domain or have profound knowledge of (future) workplace design, especially regarding chatbots. Results: We identified three fundamental usage scenarios of chatbots in seven possible application areas. As a result of this, we found both divisional and cross-divisional application areas at workplaces. Furthermore, we detected fifteen underlying objectives of a chatbot operation, which can be categorized from direct over mid-level to indirect ones. We show dependencies between them, as well. Conclusions: Our results prove the applicability of chatbots in workplace settings. The chatbot operation seems especially fruitful in the support or the self-service domain, where it provides information, carries out processes, or captures process-related data. Additionally, automation, workload reduction, and cost reduction are the fundamental objectives of chatbots in workplace scenarios. With this study, we contribute to the scientific knowledge base by providing knowledge from practice for future research approaches and closing the outlined research gap. Available at: https://aisel.aisnet.org/pajais/vol12/iss2/3