10 research outputs found
Citizen E-Participation: Bringing the “E” to Facilitated Workshops
Citizen participation initiatives enable public decision-makers to integrate the knowledge and preferences of citizens into municipal planning processes at an early stage. To this end, workshops are frequently and recurrently utilized instruments, which foster the collaboration of citizens with public authorities and with one another. With the rise of ICT, e-participation has evolved as a strategic pillar in digital governance, but has not fully reached participation workshops yet. Establishing an integrated e-participation approach that combines traditional and e-participation instruments poses a challenge in practice. Therefore, we apply Collaboration Engineering to design and evaluate an e-participation workshop process, which incorporates theoretical and practical requirements, allows the seamless transfer of digitally generated input across instruments and process steps, and sustains a workshop execution by domain-specific practitioners. Evaluation results suggest promising potentials of the developed process design for increased idea elaboration and more effective documentation of workshop-based participation
Integration of AI into Customer Service: A Taxonomy to Inform Design Decisions
Artificial Intelligence (AI) is increasingly deployed in customer service for various service delivery tasks. Research and practice alike have extensively dealt with the use, benefits, and effects of AI solutions in customer service contexts. Nevertheless, knowledge on AI integration is dispersed and unsystematized. This paper addresses this gap by presenting a taxonomy to inform design decisions for the integration of AI into customer service with five meta-dimensions, 12 dimensions, and 32 characteristics. Through a rigorous and systematic development process comprising multiple iterations and evaluation episodes, state-of-the-art AI solutions from practice and the current state of knowledge from research were systematized to classify AI use cases. Thus, we contribute with systemized design knowledge to, both, the theoretical knowledge base as well as to practice for application. Eventually, we disclose future research avenues addressing certain meta-dimensions as well as the extension of the taxonomy itself
May the Guide Be With You: CA-facilitated Information Elicitation to Prevent Service Failure
Companies automate the delivery of their online services by deploying artificial intelligence-based conversational agents (CAs). However, contemporary CAs still struggle to reliably answer the full range of requests from support seekers. To avoid service failure, service delivery activities of CAs and service employees should be interconnected by a handover of requests. This form of hybrid service delivery requires support seekers to disclose relevant information so that CAs can relay them to service employees prior to an imminent failure. By integrating and extending design knowledge from two DSR projects, we derive four design principles (DPs) to prepare handovers. These DPs guided the implementation of a service script in a CA prototype to facilitate the elicitation of information from support seekers. Based on two evaluation episodes, we show that support seekers feel supported by the CA in disclosing information which results in elaborate input for subsequent processing by service employees after handover
ICT-enabled job crafting: How Business Unit Developers use Low-code Development Platforms to craft jobs
Recently, businesses are introducing low-code development platforms (LCDP) that enable employees with little to no development expertise to develop their own systems to improve their work. These so-called business unit developers (BUDs) possess necessary domain knowledge to understand how to use LCDPs to create useful (self-) services. Using job resource demand theory and the job crafting model, we conceptualize that BUDs use of LCDPs can be framed using the theoretical lens of job crafting. Job crafting stems from vocational psychology and provides well-researched positive consequences, such as wellbeing and meaningfulness. Thus, our research objective is to understand how BUDs can use LCDPs to job craft to gain access to positive job crafting consequences. We interviewed 17 experts across three organizations that employ an LDCP for chatbots. Our results suggest that job crafting is a suitable framework for understanding the effects of LCDP use
Leveraging the Potential of Conversational Agents: Quality Criteria for the Continuous Evaluation and Improvement
Contemporary organizations are increasingly adopting conversational agents (CAs) as intelligent and natural language-based solutions for providing services and information. CAs promote new forms of personalization, speed, cost-effectiveness, and automation. However, despite their hype in research and practice, organizations fail to sustain CAs in operations. They struggle to leverage CAs’ potential because they lack knowledge on how to evaluate and improve the quality of CAs throughout their lifecycle. We build on this research gap by conducting a design science research (DSR) project, aggregating insights from the literature and practice to derive a validated set of quality criteria for CAs. Our study contributes to CA research and guides practitioners by providing a blueprint to structure the evaluation of CAs to discover areas for systematic improvement
(Re)Designing IT Support: How Embedded and Conversational AI Can Augment Technical Support Work
Striving for operational efficiency and cost-effectiveness, companies increasingly deploy artificial intelligence (AI). This trend also incrementally permeates service-related work in technical support. As current narrow AI cannot fully substitute service employees and greater effects are achieved with hybrid service delivery, adapted work settings are required. Based on a qualitative field study with a socio-technical approach, this research provides current problem scenarios in IT support and a support process redesign by integrating conversational and embedded AI. The study contributes evaluated insights about current work processes, work-related issues, and a hybrid IT support process that introduces substitution and augmentation of human tasks to improve service delivery
Hybrid Service Recovery: Design for Seamless Inquiry Handovers between Conversational Agents and Human Service Agents
The effort of companies to deploy conversational agents (CAs) for customer self-service has been renewed due to their recent technological improvements. Despite their efficiency in processing recurring simple customer inquiries, limited capabilities of CAs to handle complex inquiries still lead to service failure and unsatisfied customers. Therefore, we propose a hybrid service recovery strategy with real-time handovers of inquiries from CAs to human service agents (HSAs), if CAs’ capabilities are exceeded. Following a Design Science Research (DSR) approach, we present design principles (DPs) for the inquiry handover scenario, based on meta-requirements (MRs) derived from literature and expert interviews. By evaluating the DPs via prototype instantiation and process modulation, the suitability and interdependence of CAs’ information collection activities and information presentation for handover could be verified
Design and Evaluation of an Employee-Facing Conversational Agent in Online Customer Service
Conversational agents (CAs) are increasingly deployed to automate online customer service encounters. Hence, researchers and practitioners have so far predominantly addressed attributes and features of customer-facing CAs toward more efficient customer request processing. However, as CAs still regularly fail to answer complex issues, the concept of Hybrid Intelligence (HI) suggests combining artificial with human intelligence in a Hybrid Intelligence System to overcome the weaknesses of CAs and service employees (SEs) and promote their strengths leading to enhanced performance results and collaborative learning through mutual augmentation. Thus, following a Design Science Research approach, we formulate design principles (DPs) to develop an employee-facing CA for augmenting SEs simultaneously to their customer interaction. We implement a CA prototype and evaluate it with 21 participants in a user test. We found that the DPs were successfully implemented. Thereby, we contribute to practice, customer service, and HI research and provide avenues for future research
SUPPORTING THE IDEA GENERATION PROCESS IN CITIZEN PARTICIPATION - TOWARD AN INTERACTIVE SYSTEM WITH A CONVERSATIONAL AGENT AS FACILITATOR
Conversational agents are today implemented in everyday life. These so-called chatbots are inter alia used for customer support or as newsbots in messenger applications. However, have you ever used chatbots to submit ideas for your local community planning projects or policy making procedures? The present work suggests a possible application of a chatbot as a facilitator to promote the process and documentation of citizens’ idea generation for direct and active citizen participation initiatives. Therefore, we conduct a design-science-research project and consider relevant literature as well as specialists’ knowledge from the field of citizen participation by conducting expert interviews to gather insights on relevant capabilities for chatbots to facilitate citizens. We present design principles (DP) which are based on identified meta-requirements, to deliver guidance for the design and implementation of suitable chatbots, which are capable of conversing with and facilitating citizens during the idea generation process. A dialog scenario based on the DPs serves to instantiate and develop a software-chatbot-prototype to conduct a user test and check the fulfillment of the DPs in our implemented solution of a chatbot. By doing so, we reveal the potential of automated facilitation and show one possible way to instantiate the design principles