From data to value: conceptualising data-driven product service system

Zambetti, Michela Giuseppina; Adrodegari, Federico; Pezzotta, Giuditta; Pinto, Roberto; Rapaccini, Mario; Barbieri, Cosimo

doi:10.1080/09537287.2021.1903113

Cited by 30 publications

(16 citation statements)

References 64 publications

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“…Moreover, this literature stream shows that firms can develop and offer three main types of servitization: (1) industrial servitization , such as training and consulting; (2) commercial servitization , such as online self-service data management tools for product configuration, purchasing, and adjustments; and (3) value servitization , such as outsourcing of production activities, materials provision and service agreements, including monitoring and/or customization, integration, and reconditioning of digital products in the customer's process ( Coreynen et al, 2017 ). During the COVID-19 pandemic, however, introducing new services is the only way to sustain customer interactions and obtain data from customers targeting production and product innovation ( Zambetti et al, 2021 ).…”

Section: Theoretical Background and Research Hypothesesmentioning

confidence: 99%

Overcoming pandemic challenges through product innovation: The role of digital technologies and servitization

Bettiol

Capestro

Maria

et al. 2022

European Management Journal

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Section: Theoretical Background and Research Hypothesesmentioning

confidence: 99%

Overcoming pandemic challenges through product innovation: The role of digital technologies and servitization

Bettiol

Capestro

Maria

et al. 2022

European Management Journal

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“…While previous research has shown that IoT platforms go hand-in-hand with the emergent discussion on digital servitization, there are still four important research gaps. First, previous literature looks either at specific digital technologies or their implications for the actual business models (Burstr€ om et al, 2021;Zambetti et al, 2021;Opresnik and Taisch, 2015) or at many digital technologies and their general implications for business models. In this study, the focus is on IoT platforms as well as a technology stack covering technologies for facilitating product connectivity, data collection, data analysis and data utilization for new and existing (digital) services.…”

Section: Motivationmentioning

confidence: 99%

“…The study of Kapoor et al (2021) is taking a platform ecosystem view on servitization in manufacturing drawing its conclusions from 14 interviews. Moreover, the study of Zambetti et al (2021) is suggesting a data driven product-servicesystem framework, relying on seven case studies. While all these insights are valuable and encouraging, the current dominance of qualitative research might prevent further theoretical development and validation.…”

Section: Motivationmentioning

confidence: 99%

“…IoT platforms bundle a set of technologies (Ardolino et al, 2020) that build the basis for value creation and commercial success. Accordingly, IoT platforms comprise various activitiesfrom connecting products to the data cloud, storing, combining and analyzing data, and sharing resources and responsibilities in the value-creation process with other companies as a key driver for product-service-software systems (Cenamor et al, 2017) or data-driven product-service-systems (Zambetti et al, 2021). For IoT platforms, these opportunities for creating and capturing value, extend far beyond traditional products and services to digital services delivered through ecosystems (Jovanovic et al, 2021;Eloranta and Turunen, 2016;Rajala et al, 2019).…”

Section: Langley Et Al (2021) Conceptualmentioning

confidence: 99%

See 1 more Smart Citation

Patterns of business model innovation for advancing IoT platforms

Markfort

Arzt

Kögler

et al. 2021

JOSM

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PurposeThe emergence of Internet of Things (IoT) platforms in product companies opens up new data-driven business opportunities. This paper looks at the emergence of these IoT platforms from a business-model perspective.Design/methodology/approachThe study applies a mixed method with two research studies: Study I–a cluster analysis based on a quantitative survey, and Study II–case studies based on qualitative interviews.FindingsThe findings reveal that there is no gradual shift in a company's business model, but in fact three distinct and sequential patterns of business model innovations: (1) platform skimming, (2) platform revenue generation and (3) platform orchestration.Research limitations/implicationsThe results are subject to the typical limitations of both quantitative and qualitative studies.Practical implicationsThe results provide guidance to managers on how to modify the components of the business model (value proposition, value creation and/or delivery and profit equation) in order to enable platforms to advance.Social implicationsAs IoT platforms continue to advance, product companies achieve better performance in terms of productivity and profitability, and more easily secure competitive advantages and jobs.Originality/valueThe paper makes three original contributions: (1) it is the first quantitative study on IoT platforms in product companies, (2) identifies three patterns of business model innovations and (3) offers a first process perspective for understanding the sequence of these patterns as IoT platforms advance.

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“…The manufacturing world has now taken up the challenge of the fourth industrial revolution, or Industry 4.0 [1], which is based on two foundations: automation [2] and data [3]. The new manufacturing paradigm of smart factories [4] is able to create environments that can adapt processes in real time to current needs through the elaboration of information based on the digital technologies of the Internet of Things [5].…”

Section: Introductionmentioning

confidence: 99%

Industry 4.0 and Smart Data as Enablers of the Circular Economy in Manufacturing: Product Re-Engineering with Circular Eco-Design

et al. 2021

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The digital transformation of manufacturing firms, in addition to making operations more efficient, offers important opportunities both to promote the transition to a circular economy and to experiment with new techniques for designing smarter and greener products. This study integrates Industry 4.0 technologies, smart data, Life Cycle Assessment methodology, and material microstructural analysis techniques to develop and apply a circular eco-design model that has been implemented in the Italian ceramic tile manufacturing industry. The model has been initially adopted in a simulation environment to define five different scenarios of raw material supply, alternative to the current production one. The scenarios were then validated operationally at laboratory scale and in a pilot environment, demonstrating that a proper selection of raw material transport systems significantly improves the environmental performance of the ceramic product. Both the results of the laboratory tests and of the pre-industrial experiments have demonstrated the technological feasibility of the solutions identified with circular eco-design, enabling the re-engineering of the ceramic product as the fifth of the 6Rs of the circular economy.

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From data to value: conceptualising data-driven product service system

Cited by 30 publications

References 64 publications

Overcoming pandemic challenges through product innovation: The role of digital technologies and servitization

Overcoming pandemic challenges through product innovation: The role of digital technologies and servitization

Patterns of business model innovation for advancing IoT platforms

Industry 4.0 and Smart Data as Enablers of the Circular Economy in Manufacturing: Product Re-Engineering with Circular Eco-Design

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