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The energy turnaround and the shift towards sustainable mobility threaten the stability of European energy distribution grids due to substantially increasing load fluctuations and power demand. These challenges can critically impact assets in the distribution grid—e.g., switchgears—intensifying the need to plan, conduct, and manage the maintenance of such assets. Predictive maintenance strategies that analyze assets' current and historical condition data have been discussed as promising approaches toward that end. However, the extant research focuses on designing and improving analytical algorithms or information technology (IT) artifacts while not considering how a maintenance service is cocreated by companies with IT. This research article posits that IT and service must be aligned closely, presenting an ensemble artifact comprising a digital industrial platform and a smart service system for predictive maintenance on the distribution grid. The artifact is evaluated by conducting a willingness-to-pay analysis with asset operators, documenting their demand for condition monitoring and predictive maintenance as an integrated solution, although they still struggle with even getting the condition data of their assets. Building on these results, we formalize the knowledge in the form of design principles and implications for managing the maintenance of critical assets in the distribution grid.

While the Information Systems (IS) discipline has researched digital platforms extensively, the body of knowledge appertaining to platforms still appears fragmented and lacking conceptual consistency. Based on automated text mining and unsupervised machine learning, we collect, analyze, and interpret the IS discipline’s comprehensive research on platforms—comprising 11,049 papers spanning 44 years of research activity. From a cluster analysis concerning platform concepts’ semantically most similar words, we identify six research streams on platforms, each with their own platform terms. Based on interpreting the identified concepts vis-à-vis the extant research and considering a temporal perspective on the concepts’ application, we present a lexicon of platform concepts, to guide further research on platforms in the IS discipline. Researchers and managers can build on our results to position their work appropriately, applying a specific theoretical perspective on platforms in isolation or combining multiple perspectives to study platform phenomena at a more abstract level.

ABSTRACTBusiness process management distinguishes the actual “as-is” and a prescribed “to-be” state of a process. In practice, many different causes trigger a process’s drifting away from its to-be state. For instance, employees may “workaround” the proposed systems to increase their effectiveness or efficiency in day-to-day work. So far, ethnography or critical incident techniques are used to identify how and why workarounds emerge. We design a deep-learning-based method that helps detect different workaround types in event logs. Our method tracks indications of potential workarounds in the early stages of their emergence among deviating behaviour. Our evaluation based on four real-life event logs reveals that our method performs well and works best for business processes with fewer variations and a higher number of different activities. The proposed method is one of the first information technology artefacts to bridge the boundaries between the complementing research disciplines of organisational routines and business processes management.

Technological developments such as Cloud Computing, the Internet of Things, Big Data and Artificial Intelligence continue to drive the digital transformation of business and society. With the advent of platform-based ecosystems and their potential to address complex challenges, there is a trend towards greater interconnectedness between different stakeholders to co-create services based on the provision and use of data. While previous research on digital transformation mainly focused on digital transformation withinorganizations, it is of growing importance to understand the implications for digital transformation on different layers (e.g., interorganizational cooperation and platform ecosystems). In particular, the conceptualization and implications of public data spaces and related ecosystems provide promising research opportunities. This special issue contains five papers on the topic of digital transformation and, with the editorial, further contributes by providing an initial conceptualization of public data spaces' potential to foster innovative progress and digital transformation from a management perspective.

Proof-of-concept projects have demonstrated that used electric vehicle batteries (EVBs), after their removal from electric vehicles due to insufficient performance, can be repurposed for less demanding applications. It is expected that numerous batteries will be available for repurposing in the 2020s. However, the information asymmetries and transaction costs of trading used EVBs have remained unexplored, as have principles that guide the design of information systems that support the trade. Based on existing literature and in-depth interviews with battery experts, we conceptualize two key transactions for trading used EVBs. We then identify potential information asymmetries and transaction costs based on new institutional economic theory and propose five design principles that information systems should implement to address these information asymmetries and transaction costs. Subsequent research can build on our results to further frame the economic properties of trading used EVBs and to design information systems in line with new institutional economic theory.

Recent years have seen the emergence of physical products that are digitally networked with other products and with information systems to enable complex business scenarios in manufacturing, mobility, or healthcare. These “smart products”, which enable the co-creation of “smart service” that is based on monitoring, optimization, remote control, and autonomous adaptation of products, profoundly transform service systems into what we call “smart service systems”. In a multi-method study that includes conceptual research and qualitative data from in-depth interviews, we conceptualize “smart service” and “smart service systems” based on using smart products as boundary objects that integrate service consumers’ and service providers’ resources and activities. Smart products allow both actors to retrieve and to analyze aggregated field evidence and to adapt service systems based on contextual data. We discuss the implications that the introduction of smart service systems have for foundational concepts of service science and conclude that smart service systems are characterized by technology-mediated, continuous, and routinized interactions.

A citizen-centric view is key to channeling technological affordances into the development of future cities in which improvements are made with the quality of citizens’ life in mind. This paper proposes City 5.0 as a new citizen-centric design paradigm for future cities, in which cities can be seen as markets connecting service providers with citizens as consumers. City 5.0 is dedicated to eliminating restrictions that citizens face when utilizing city services. Our design paradigm focuses on smart consumption and extends the technology-centric concept of smart city with a stronger view on citizens’ roadblocks to service usage. Through a series of design workshops, we conceptualized the City 5.0 paradigm and formalized it in a semi-formal model. The applicability of the model is demonstrated using the case of a telemedical service offered by a Spanish public healthcare service provider. The usefulness of the model is validated by qualitative interviews with public organizations involved in the development of technology-based city solutions. Our contribution lies in the advancement of citizen-centric analysis and the development of city solutions for both academic and professional communities.

Erfahrungen mit dem Online-Handel und der alltäglichen Nutzung digitaler Technologien haben das Kaufverhalten und die Erwartungshaltung der innerstädtischen Kunden nachhaltig verändert. Insbesondere die kleinen und mittelständischen Einzelhändler und Fachgeschäfte sind angesichts abnehmender Marktanteile herausgefordert. Der einzelne Händler kann oftmals nicht mit den digitalen Diensten der Großfilialisten und den Preisen des Online-Handels konkurrieren. Zur Abgrenzung von Konkurrenten legen daher viele Händler den Fokus auf kundenseitige Einkaufserlebnisse. Digitale Technologien, die Einzug in den Alltag der Kunden gehalten haben, können in die physische Umgebung der Ladengeschäfte integriert werden, um neue Formen der Interaktion zwischen Händlern und Kunden zu schaffen, die potentiell zu positiven digitalenEinkaufserlebnissen beitragen. Dieser Artikel fokussiert auf interaktive, händlerübergreifende Lösungen im Sinne eines digitalen Marktplatzes. Wir skizzieren einen möglichen Gestaltungsansatz einer händler- und kundenübergreifenden mobilen Plattform, die neue digitale Technologien einbindet und dem physischen innerstädtischen Marktplatz als digitaler Kompagnon zur Seite steht. Diese Plattform vereint die Gruppen der innerstädtischen Händler und Innenstadtbesucher und ermöglicht die Interaktion zwischen beiden Parteien auf verschiedenen Ebenen. Ein digitaler innerstädtischer Marktplatz kann Beiträge dazu leisten, ein digitales Einkaufserlebnis zur Stütze des gesellschaftlich geschätzten, aber durch den Online-Handel herausgeforderten, „Einkaufserlebnis Innenstadt“ zu schaffen. The emergence of online shopping and digital technologies have transformed consumers’ shopping behavior and have also risen their expectations towards the digital profile of high street retailers. However, small and medium-sized retailers in particular – who cannot compete with the large-scale digital initiatives conducted by major retail chains and pure online retailers – struggle to retain and attract customers to their stores. Eventually, their market share might decline. Improving customer experience creation is a viable path to re-build a competitive edge for high street retailers. By introducing new digital technologies into their stores and by integrating customers’ devices into their physical servicescape, new types of interactions between retailers and customers emerge that allow co-creating digital customer experience. This article proposes building and implementing a digital platform that local retailers can use to collectively offer digital customer experience. We sketch the design of a mobile platform that accompanies traditional high street retailing with a digital counterpart. The platform connects local stores with digital customers and enables different levels of interaction among its users. In doing so, the platform enables the co-creation of digital customer experience, strengthening the competitive position of retailers in consumers’ buying decisions.

Large communities built around social media on the Internet offer an opportunity to augment analytical customer relationship management (CRM) strategies. The purpose of this paper is to provide direction to advance the conceptual design of business intelligence (BI) systems for implementing CRM strategies. After introducing social CRM and social BI as emerging fields of research, the authors match CRM strategies with a re-engineered conceptual data model of Facebook in order to illustrate the strategic value of these data. Subsequently, the authors design a multi-dimensional data model for social BI and demonstrate its applicability by designing management reports in a retail scenario. Building on the service blueprinting framework, the authors propose a structured research agenda for the emerging field of social BI.

With respect to the scientific method, reproducing empirical research is a necessary step to develop generalisable knowledge. However, in service productivity measurement and managerial science in general, little attention seems to be paid to replicating empirical studies. One reason could be that many studies do not report their data and methodology in the degree of detail sufficient to reproduce them. In this paper, we provide evidence for a lack of reproducibility of empirical studies on service productivity measurement with data envelopment analysis (DEA), based on reviewing service productivity measurement literature. The major impediments identified comprise a superficial description of the measurement process and data sources, insufficient details on the retrieval methodology, and an incomplete account of the extraction methodology. To improve the reproducibility of future studies, this article offers a structured set of guidelines with which authors can report their studies more comprehensively.

Abstract: When managing their growing service portfolio, many manufacturers in B2B markets face two significant problems: They fail to communicate the value of their service offerings and they lack the capability to generate profits with value-added services. To tackle these two issues, we have built and evaluated a collaborative filtering recommender system which (a) makes individualized recommendations of potentially interesting value-added services when customers express interest in a particular physical product and also (b) leverages estimations of a customer’s willingness to pay to allow for a dynamic pricing of those services and the incorporation of profitability considerations into the recommendation process. The recommender system is based on an adapted conjoint analysis method combined with a stepwise componential segmentation algorithm to collect individualized preference and willingness-to-pay data. Compared to other state-of-the-art approaches, our system requires significantly less customer input before making a recommendation, does not suffer from the usual sparseness of data and cold-start problems of collaborative filtering systems, and, as is shown in an empirical evaluation with a sample of 428 customers in the machine tool market, does not diminish the predictive accuracy of the recommendations offered.

Das Artikelstammdaten-Management als Aufgabe des Enterprise Content Management (ECM) ist für die automatische Abwicklung des Handelsgeschäfts von hoher Bedeutung. Ohne korrekt erfasste Artikelgrunddaten ist keine Annahme, Einlagerung oder kein Abverkauf von Ware möglich. Häufig werden diese Daten bereits vom Hersteller elektronisch an den Handel geliefert. Da allerdings bilaterale Datenaustausche einen hohen Aufwand bedeuten, haben sich Unternehmen auf die Nutzung von zentralen Stammdatenpools geeinigt. Diese sind jedoch nur auf das Kerngeschäft und die Datengrundversorgung ausgerichtet und unterstützen nicht oder kaum die Anforderungen neuartiger automatisiert ablaufender Verkaufsförderungsaktionen. Vor diesem Hintergrund werden in diesem Artikel — ausgehend von den Anforderungen, die sich durch die Abwicklung von Coupon-Aktionen an die Handels-IT und die Artikelstammdaten ergeben — die konzeptionelle Spezifikation und prototypische Umsetzung einer Verkaufsförderungsplattform für Artikelstammdaten betrachtet. Diese erlaubt die unternehmensübergreifende Erfassung, Verwaltung, Speicherung und Bereitstellung von Informationen im Sinne eines Cross Enterprise Content Management.