Service Science

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Now showing 1 - 6 of 6
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    When Choice Matters: Assortment and Participation for Performance on Digital Platforms
    ( 2021-01-05) Karhade, Prasanna ; Kathuria, Abhishek ; Konsynski, Benn
    Digital platforms are conveniently connecting multiple service providers with their consumers. How does assortment and participation influence the performance of service providers on digital platforms? In particular, food delivery platforms are providing consumers with a high level of home delivery convenience. Food delivery platforms are also unique as they provide a hybrid set of services to their consumers (both home delivery convenience and enable restaurant dining experience). The population of 95,735 restaurants on a pan India food discovery and delivery platform, serving a total of 135 different cuisines, located in 37 cities of India serves as our dataset. Ours is the first study to integrate induction and abduction to examine performance of service providers (restaurants) operating on a digital platform in a hybrid mode (providing both home delivery convenience and enabling restaurant dining experience). We find assortment matters and derive strong business implications for service science.
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    Towards Design Principles for Data-Driven Services in Industrial Environments
    ( 2021-01-05) Azkan, Can ; Iggena, Lennart ; Möller, Frederik ; Otto, Boris
    The ever-growing amounts of data offer companies many opportunities to exploit them. Resulting data-driven services hold great potential for creating unique value for customers and the achievement of competitive advantages. Nevertheless, especially companies in the industrial environment struggle to implement successful data-driven service innovations. Surprisingly, there is a lack of scientific research addressing this issue. Thus, our research generates design principles for data-driven services to aid in their development. For this purpose, we present a qualitative interview study with experts in different lines of businesses among the industry sector, holding varying positions and roles in service systems. Through practical examples, we show which challenges exist in the development and use of data-driven services. On this basis, we derive design principles to help understanding data-driven services and to overcome difficulties identified in practice, notably, that allows practitioners to develop new services or re-design existing ones.
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    Modelling for Ethical Concerns for Traceability in Time of Pandemic “Do no Harm” or “Better Safe than Sorry!”
    ( 2021-01-05) Badr, Nabil ; Drăgoicea, Monica ; Walletzký, Leonard ; Carrubbo, Luca ; Toli, Angeliki Maria
    We propose a service design for ethics framework that applies the four diamonds-of-context model for complex service design (4DocMod) framework to analyze, decompose, and interpret the main edicts of ethics (credibility, transferability, and validity) in data collection and use in public health complex service systems. We illustrate how different contexts of different actors can be accommodated ethically at the service design level. The paper explains the main artefacts of the 4DocMod framework (diamonds See, Recognize, Organize, Do) against community and individual ethics in several case studies related to the current COvID-19 pandemics facing the use of traceability technologies. The main contribution of the paper highlights how actions and goals in healthcare as a service ecosystem (H-SES) may have contexts, while contextual interpretation of activities constitutes the basis for ethical evaluation.
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    Drivers and Inhibitors for Organizations’ Intention to Adopt Artificial Intelligence as a Service
    ( 2021-01-05) Pandl, Konstantin D. ; Teigeler, Heiner ; Lins, Sebastian ; Thiebes, Scott ; Sunyaev, Ali
    The adoption of artificial intelligence promises tremendous economic benefits for organizations. Yet, many organizations struggle to unlock the full potential of this technology. To ease the adoption of artificial intelligence for organizations, several cloud providers have begun offering artificial intelligence as a service (AIaaS). Extant research on AIaaS exhibits a strong focus on technical aspects and has opposing views on what drives or inhibits the adoption of AIaaS within organiza-tions. In this research, we synthesize extant re-search on AIaaS adoption factors and conduct semi-structured interviews with practitioners. Our research yields 12 factors that drive and another 12 factors that inhibit the adoption of AIaaS in practice. We thereby close a gap in scholarly knowledge on adopting this emerging service technology, especially on inhibiting factors, and help guide future research on related behavioral and technical aspects.
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    Designing Local Food Service Ecosystem for Sustainability: An Agent-based Social Simulation Approach based on Service-Dominant Logic
    ( 2021-01-05) Trieu, Viet-Cuong ; Lin, Fu-Ren
    This paper aims to design a local food service ecosystem based on the Service-Dominant Logic to overcome the limitation of the alternative food networks in terms of sustainability. The three core components of this service ecosystem are trust mechanism, cooperative model, and blockchain-based service platform. The service design approach and agent-based social simulation method are used to design and evaluate the service ecosystem. From the simulation results, an actor-to-actor network trust mechanism and an intelligent cooperative model are proposed based on evaluating sustainability in economic, social, and environmental aspects. This study's results contribute to service design methodology and practical service ecosystem development for sustainability.
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    Introduction to the Minitrack on Service Science
    ( 2021-01-05) Shaw, Michael ; Lin, Fu-Ren ; Maglio, Paul