Christoph Friedrich Breidbach

Achieving and maintaining sustainability in complex service ecosystems is a pressing challenge for service firms. Yet, many sustainability efforts, like compliance-driven measures, remain incremental and fall short in the face of accelerating global crises. To create meaningful impact, service firms are called upon to act as change agents within their ecosystems and have been given a mandate to drive systemic sustainability transformation. However, many struggle to operationalize such a shift. We argue this is due largely to a lack of conceptual clarity of what sustainability in service looks like, how service firms can advance sustainability objectives, as well as how service firms should enable ecosystem-wide transformation. To address these questions, we conduct an integrative review of 467 empirical and conceptual studies published between 2018 and 2024 that explore sustainability in service. We introduce the concept of sustainable service ecosystem orchestration and provide a novel typology of four sustainable service orchestration ideal types. In doing so, we position sustainable service orchestration as a foundational concept to advance theoretical understanding of sustainable service ecosystems, guide future research, and offer practical pathways for service firms through a managerial roadmap of sustainable service ecosystem orchestration.

How can incumbent firms reconfigure their legacy Enterprise Information Systems (EIS) for enterprise renewal? We address this question by developing an empirically grounded, mechanism-based theory of legacy EIS reconfiguration in incumbent firms that reconciles two opposing perspectives in IS research: legacy EIS as sources of technical debt that constrain agility, and legacy EIS as installed bases that can be leveraged for digital reinvention. Specifically, we draw on findings from a multiple-case study of five German incumbent manufacturing firms to identify four generative mechanisms through which incumbent firms leverage operational stability of their legacy EIS for digital pilots, activate historically accumulated data through analytics, augment legacy EIS with middleware interfaces, and retrofit legacy EIS for recurring revenue models. When enacted, these mechanisms reconfigure legacy EIS into ambidextrous EIS landscapes that preserve operational stability through contained and selectively reduced technical debt, while expanding potential options for future digital initiatives. We conclude by outlining actionable guidance for practitioners and a research agenda on how legacy EIS reconfiguration, rather than replacement, can serve as a foundation for enterprise renewal.

Purpose: The purpose of this study is to identify, analyze and explain the implications that could arise for service settings if artificial intelligence (AI) systems develop, or are perceived to develop, consciousness – the ability to acknowledge their own existence and the capacity for positive or negative experiences. Design/methodology/approach: This study proposes and explores four hypothetical scenarios in which conscious AI in service could manifest. We contextualize our resulting typology in the health service context and integrate extant literature on technology-enabled service, AI consciousness and AI ethics into the narrative. Findings: This study provides a unique theoretical contribution to service research in the form of a Type IV theory. It enables future service researchers to apprehend, explain and predict how functionally conscious AI in service might unfold. Practical implications: The ethical use of conscious AI in service could emerge as a distinct competitive advantage in the future. Achieving this outcome involves speculative yet actionable recommendations that include training, guiding and controlling how humans engage with such systems; developing appropriate wellbeing protocols for functionally conscious AI systems and establishing AI rights and governance frameworks. Originality/value: An increasingly prolific public discourse acknowledges that conscious AI systems may emerge. Against this backdrop, this study aims to systematically explore a question that is perhaps the most critical and timely, but also inherently speculative, in relation to AI in service research by introducing much-needed theory and terminology.

Technological advancements and evolving value orientations reshape future value creation and pose new requirements for service innovation. While a variety of disciplines are developing new approaches to drive service innovation, this is primarily done in isolation and generates only fragmented solutions. Sociological theory has proposed “boundary objects” as an effective umbrella for communication and cooperation among communities. Therefore, we introduce continuous value shaping (CVS) as a boundary object describing service innovation approaches along five principles. We reflect on this concept through the different disciplinary lenses of researchers in service marketing, information systems, service engineering, sociology of work, and innovation management. These perspectives highlight how the CVS principles already connect to discourses within the individual disciplines. However, the CVS concept will not only provide an umbrella to embrace existing activities in different academic disciplines. It also assists to identify research themes that will benefit from uniting the power of these disciplines, and it can serve as an integrating framework to conceptualize complex service innovation approaches. Thus, the CVS concept should guide both researchers and practitioners to develop and implement novel innovation and transformation efforts—in and across organizations.

The interdisciplinary nature of digital transformation requires a shift from theorizing within disciplinary silos to leveraging theory in a way that helps bridge disciplinary boundaries. This study seeks to contribute to this objective by demonstrating that service-dominant logic (S-D logic) as a meta-theory has strong potential to connect IS, service, innovation, and marketing scholars as well as practitioners in understanding and shaping digital transformation. For this purpose, we conduct a computational literature review and create a map of the S-D logic research landscape. Based on this map, we assess how the S-D logic can help address some of the key gaps in our understanding of digital transformation leading to a cross-disciplinary agenda for future research. We argue that an S-D logic perspective on digital transformation can also be informative for practitioners involved in digital transformation activities, whom we equip with an actionable roadmap for implementation.

Initial coin offerings (ICOs) and initial exchange offerings (IEOs) are distinct blockchain-based token offerings. Following multiple frauds associated with decentralized and unregulated ICOs, IEOs are emerging as a novel pathway that relies on centralized crypto exchange platforms acting as intermediaries. However, the question as to how this shift affects fundraising processes in what has traditionally been a decentralized environment remains unresolved. We here address this issue by empirically comparing the performance of ICOs and IEOs through the lens of signaling theory, focusing specifically on the impact of social media information across 305 token offerings (ICOs and IEOs). Our work introduces IEOs and explains how and why the volume and sentiment of social media signals may serve as predictors of fundraising performance. We furthermore find that the impact of these electronic word-of-mouth (eWOM) media signals is reduced in the case of IEOs—in the presence of a central cryptocurrency exchange platform mediator. We delineate implications for investors, ventures, platform providers, and regulators alike.

By Christoph F. Breidbach, Amol M. Joshi, Paul P. Maglio, et al., Published on 09/04/22