Digital Factory Transformation from a Servitization Perspective: Fields of Action for Developing Internal Smart Services
Abstract
:1. Introduction
- Difficulties with international supply chains: Recently, partly due to the COVID-19 pandemic, global supply chains have faltered. As a consequence, for example, a seamless supply of spare parts and components is not always guaranteed. This has disrupted even particularly well-optimized JIT and JIS production processes. Sourcing and supply chain issues dominate the planning and management of manufacturing processes, making it difficult to fully assemble products and requiring improvisation, as well as ad hoc decision-making. Supply constraints in some industrial sectors have become so severe that they call into question the flexible mass production’s prior achievements [3]. Energy supply and price have recently forced companies to adjust their manufacturing processes. Overall, this will lead to a re-evaluation of their supply chain strategies [4].
- Sustainability: Sustainability is a challenge with several origins, such as the need to stay cost competitive while energy costs are increasing. Additionally, there is an increasing focus of the customers on the impact of their own consumption. The most obvious and most controversially discussed cause are regulations, for example, the European Green Deal or the restriction of internal combustion engine vehicles. As a result, the manufacturing industry has to rethink the whole life cycle of its products, starting from the design to how they are produced or even their whole business models [5,6].
- New global players: In addition to the growing international pressure of existing competitors and the advance of new technologies, new companies are increasingly entering the markets, putting pressure on established manufacturers. These companies do not have a production history stretching back decades but instead, build their manufacturing processes closely based on procedures and processes previously only known to the digital economy. The most prominent example is Tesla, which is focusing everything on software and digitalization and whose manufacturing plants are literally being built as greenfield projects [7].
- Digitalization of brown-field factories: Although traditional companies have advantages due to decades of experience, efficient product design, and deep knowledge of production processes, they must face challenges originating in the organic growth of factory layouts, processes, and technology. Most notably, this organic growth also took place in IT systems and led to a fast number of different systems that are not well-connected, hard to maintain, and difficult to replace. This brown-field burden prevents companies from benefiting easily from adopting and scaling new technological advances and, therefore, they are not able to react flexibly to changing conditions [8].
- Skilled labor shortage: In recent years, the labor market in industrialized countries is favoring the employee’s side. In addition to the rapidly expanded demand for specialized skills in IT and engineering, the obvious factor is the ever-increasing age of the average worker. This leads to a competitive environment where, in addition to the financial incentives, the working conditions in the form of work–life balance play an increasingly more prominent role [9]. These changes will have the added benefit that older workers can extend their working life [10]. The downside is that, especially in manufacturing, predominant shift models adapting to more flexible working conditions is difficult.
2. Servitization and the Development of Internal Smart Services
2.1. Digital Servitization: The Changing Character of Value Creation
2.2. Characterization of Smart Services
- First, services exhibit a high degree of immateriality, which means they are also represented by intangible elements. This can refer, on the one hand, to the resources used by the provider and, on the other hand, to the service outcome, for example, in the form of generated knowledge or customer experiences. Looking at smart services, data as a core characterizing element that is of an immaterial nature in the first place enables interaction between different actors, setting the fundament for value co-creation activities.
- The second dimension, “interactivity”, describes the integration of the customer and its resources into the value-creation process, in which an intensive exchange of resources occurs between the supplier and the customer. This can mean either the exchange of data, ideas, and information or the integration of physical resources of the customer (e.g., a physical machine component) that is processed by the supplier.
- The third dimension addresses the degree of individualization, i.e., the adaptation of service offerings to the needs of the customer in a specific situation. In the context of smart services, individualization is based on the availability of data on individual actors or individual activities. Allowing a case-by-case distinction, the execution of a service can be adapted to its specific requirements in each case.
2.3. AI-Based Quality Control as an Example of an Internal Smart Service
3. Taking a Service Perspective on Digital Factory Transformation
3.1. Developing Business Models for Internal Smart Services
3.2. Digital Platforms and Data Ecosystems
3.3. Data Analytics
3.4. Perceived Quality and Acceptance
3.5. Competence Shift
3.6. Culture and Incentives
4. Conclusions and Discussion
- For internal servitization to succeed, the smart services developed must be developed, implemented, and operated as professional service products from the outset. It is essential that companies address the question of profitability, i.e., whether smart services can be monetized directly or indirectly, how these effects can be evaluated, and how profits are shared among those involved. In addition, the professional development of smart services also offers the possibility of scaling them beyond the boundaries of the company’s production plant. Companies can, for example, offer data, trained algorithms, or fully developed value-added services to other production sites or external companies in outlined XaaS business models that are known for external servitization and thus generate independent revenues. In order to reduce investment and fixed costs against the background of market fluctuations and external uncertainties, companies should also examine the possibility of using XaaS offerings of equipment suppliers themselves for less important and lower-risk production steps.
- A service-oriented focus on internal value creation in production requires the establishment of integrated and scalable IT infrastructure that supports a high level of data continuity across new and existing systems. In addition, the added value of the individual smart services, as well as the whole service and production system, can be better and more holistically captured by data. The focus should, therefore, be on breaking down and merging internal data silos. This requires digital platforms in the technical sense, but also appropriate data governance and processes in the company that strengthen the sharing of data, and the creation of consistently high data quality is an important component of all departments. In addition, compensation mechanisms for contributions to high data quality should be created and incentive mechanisms for the efficient use of IT infrastructures should be developed to prevent limited resources from not being used efficiently and being threatened by overuse (tragedy of the commons) [74].
- For shifting toward service-oriented value creation and developing internal smart services, building up suitable technical capabilities for analyzing and processing data into insights and recommendations is necessary. Companies should consider the opportunities and risks of descriptive, diagnostic, predictive, and prescriptive analytics. Early consideration in the light of available data, in-house capabilities, and the need for certainty and transparency can help set realistic goals for service development. Particularly in the production environment, where errors can have critical consequences, companies should take appropriate measures to safeguard the use of prescriptive processes in AI-based smart services.
- To ensure that the increasing number of smart services within the production site is accepted by the workforce, users of the applications should be regarded as internal customers from the outset and involved during development, testing, and continuous optimization. This also includes focusing on the subjective perception of quality instead of objective quality. In the context of data-intensive, automated, and adaptive services, new quality characteristics must be considered during development, considering smart services’ unique character to ensure acceptance.
- To enable active engagement in service-oriented value creation for many departments in production, additional competencies are needed in the workforce. Following the concept of T-shaped competency profiles, horizontal competencies should be created that promote collaboration across divisional and departmental boundaries, problem-solving thinking, and a basic understanding of data and digital technologies, as well as services. Vertical, in-depth knowledge of the application domains should not be neglected.
- In addition, the internal service transformation also requires an adjustment of the corporate culture and corresponding incentive systems. This includes, for example, an open approach to errors that is often untypical for manufacturing and the use of data products and services that are not fully developed. Establishing a close and solution-oriented collaboration between departments, a high level of agility in software development processes in various departments, and a constant ability to innovate and adapt are central pillars of an internal service culture. This should be flanked by holistic and process-oriented incentive and motivation systems so that all employees continuously contribute to optimizing data quality and smart service quality along the manufacturing process.
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
- Reinhold, J.; Koldewey, C.; Dumitrescu, R.; Rausch, G. Smart Service-Transformation–Den Wandel der Wertschöpfung erfolgreich gestalten. In Proceedings of the 16th Symposium für Vorausschau Und Technologieplanung, Paderborn, Germany, 2–3 December 2021; pp. 337–341. [Google Scholar]
- Kagermann, H.; Wahlster, W. Ten Years of Industrie 4.0. Sci 2022, 4, 26. [Google Scholar] [CrossRef]
- Kagermann, H.; Süssenguth, F.; Körner, J.; Liepold, A.; Behrens, J.H. Resilienz der Fahrzeugindustrie: Zwischen Globalen Strukturen und Lokalen Herausforderungen; Acatech IMPULS: München, Germany, 2021. [Google Scholar]
- Spieske, A.; Birkel, H. Improving supply chain resilience through industry 4.0: A systematic literature review under the impressions of the COVID-19 pandemic. Comput. Ind. Eng. 2021, 158, 107452. [Google Scholar] [CrossRef]
- Schutzbach, M.; Kiemel, S.; Miehe, R. Eco Lean Management—Recent Progress, Experiences and Perspectives. Procedia CIRP 2022, 107, 350–356. [Google Scholar] [CrossRef]
- Urbinati, A.; Rosa, P.; Sassanelli, C.; Chiaroni, D.; Terzi, S. Circular business models in the European manufacturing industry: A multiple case study analysis. J. Clean. Prod. 2020, 274, 122964. [Google Scholar] [CrossRef]
- Thomas, V.J.; Maine, E. Market entry strategies for electric vehicle start-ups in the automotive industry—Lessons from Tesla Motors. J. Clean. Prod. 2019, 235, 653–663. [Google Scholar] [CrossRef]
- Schuh, G.; Anderl, R.; Dumitrescu, R.; Krüger, A.; Hompel, M.T. Using the Industrie 4.0 Maturity Indexin Industry. In Current Challenges, Case Studies and Trends; Acatech IMPULS: Munich, Germany, 2020. [Google Scholar]
- Binner, H.F. Digitale Revolution—Erfolgreiche Umsetzung über Organisation 4.0. Z. Für Wirtsch. Fabr. 2016, 111, 152–154. [Google Scholar] [CrossRef]
- Kohtamäki, M.; Parida, V.; Patel, P.C.; Gebauer, H. The relationship between digitalization and servitization: The role of servitization in capturing the financial potential of digitalization. Technol. Forecast. Soc. Chang. 2020, 151, 119804. [Google Scholar] [CrossRef]
- Khanra, S.; Dhir, A.; Parida, V.; Kohtamäki, M. Servitization research: A review and bibliometric analysis of past achievements and future promises. J. Bus. Res. 2021, 131, 151–166. [Google Scholar] [CrossRef]
- Rapaccini, M.; Saccani, N.; Kowalkowski, C.; Paiola, M.; Adrodegari, F. Navigating disruptive crises through service-led growth: The impact of COVID-19 on Italian manufacturing firms. Ind. Mark. Manag. 2020, 88, 225–237. [Google Scholar] [CrossRef]
- Bonamigo, A.; Frech, C.G. Industry 4.0 in services: Challenges and opportunities for value co-creation. J. Serv. Mark. 2021, 35, 412–427. [Google Scholar] [CrossRef]
- Ulaga, W.; Kowalkowski, C. Servitization: A State-of-the-Art Overview and Future Directions. In The Palgrave Handbook of Service Management; Edvardsson, B., Tronvoll, B., Eds.; Springer International Publishing: Cham, Switzerland, 2022; pp. 169–200. ISBN 978-3-030-91827-9. [Google Scholar]
- Kowalkowski, C.; Sklyar, A.; Tronvoll, B.; Sörhammar, D. Digital Servitization: How Data-Driven Services Drive Transformation. In Proceedings of the 55th Hawaii International Conference on System Sciences, Maui, HI, USA, 4–7 January 2022. [Google Scholar]
- Veile, J.W.; Schmidt, M.-C.; Voigt, K.-I. Toward a new era of cooperation: How industrial digital platforms transform business models in Industry 4.0. J. Bus. Res. 2022, 143, 387–405. [Google Scholar] [CrossRef]
- Kolagar, M.; Reim, W.; Parida, V.; Sjödin, D. Digital servitization strategies for SME internationalization: The interplay between digital service maturity and ecosystem involvement. J. Serv. Manag. 2022, 33, 143–162. [Google Scholar] [CrossRef]
- Zeithaml, V.A.; Bitner, M.J.; Gremler, D.D. Services Marketing: Integrating Customer Focus across the Firm, 7th ed.; McGraw-Hill Education: New York, NY, USA, 2018; ISBN 9780078112102. [Google Scholar]
- Sasser, W.E. Value Profit Chain: Treat Employees Like Customers and Customers LIKE Employees; Simon and Schuster: New York, NY, USA, 2014; ISBN 978-1-4767-9998-8. [Google Scholar]
- Tóth, Z.; Sklyar, A.; Kowalkowski, C.; Sörhammar, D.; Tronvoll, B.; Wirths, O. Tensions in digital servitization through a paradox lens. Ind. Mark. Manag. 2022, 102, 438–450. [Google Scholar] [CrossRef]
- Johnston, R. Internal service—Barriers, flows and assessment. Int. J. Serv. Ind. Manag. 2008, 19, 210–231. [Google Scholar] [CrossRef]
- Korper, A.K.; Purrmann, M.; Heinonen, K.; Kunz, W. Towards a Better Understanding of Smart Services—A Cross-Disciplinary Investigation. In Towards a Better Understanding of Smart Services—A Cross-Disciplinary Investigation, Proceedings of the Exploring Service Science, Porto, Portugal, 5–7 February 2020; Novoa, H., Dragoicea, M., Kühl, N., Eds.; Springer International Publishing AG: Cham, Switzerland, 2020; Volume 377, pp. 164–173. ISBN 3030387232. [Google Scholar]
- Neuhüttler, J.; Ganz, W.; Liu, J. An integrated approach for measuring and managing quality of smart senior care services. In Advances in the Human Side of Service Engineering: Proceedings of the AHFE 2016 International Conference on the Human Side of Engineering, Walt Disney World, FL, USA, 27 July–31 July 2016; Ahram, T.Z., Karwowski, W., Eds.; Springer International Publishing: Cham, Switzerland, 2017; pp. 309–318. [Google Scholar]
- Neuhüttler, J.; Fischer, R.; Ganz, W.; Urmetzer, F. Perceived Quality of Artificial Intelligence in Smart Service Systems: A Structured Approach. In Quality of Information and Communications Technology; Shepperd, M., Brito e Abreu, F., Da Rodrigues Silva, A., Pérez-Castillo, R., Eds.; Springer International Publishing: Cham, Switzerland, 2020; pp. 3–16. ISBN 978-3-030-58792-5. [Google Scholar]
- Neuhüttler, J.; Ganz, W.; Spath, D. An Integrative Quality Framework for Developing Industrial Smart Services. Serv. Sci. 2019, 11, 157–171. [Google Scholar] [CrossRef]
- Satzger, G.; Benz, C.; Böhmann, T.; Roth, A. Servitization and Digitalization as “Siamese Twins”: Concepts and Research Priorities. In The Palgrave Handbook of Service Management; Edvardsson, B., Tronvoll, B., Eds.; Springer International Publishing: Cham, Switzerland, 2022; pp. 967–989. ISBN 978-3-030-91827-9. [Google Scholar]
- Lee, J. Industrial AI: Applications with Sustainable Performance; Springer: Singapore, 2020; ISBN 9789811521447. [Google Scholar]
- Moll, C.; Lerch, C. KI-basierte Geschäftsmodelle im verarbeitenden Gewerbe—Anwendungspotenziale und Ausgestaltungsmöglichkeiten. In Künstliche Intelligenz im Dienstleistungsmanagement; Bruhn, M., Hadwich, K., Eds.; Springer Fachmedien Wiesbaden: Wiesbaden, Germany, 2021; pp. 98–119. ISBN 978-3-658-34323-1. [Google Scholar]
- Winter, J. Europa und die Plattformökonomie—Wie datengetriebene Geschäftsmodelle Wertschöpfungsketten verändern. In Dienstleistungen 4.0; Bruhn, M., Hadwich, K., Eds.; Springer Fachmedien Wiesbaden: Wiesbaden, Germany, 2017; pp. 71–88. ISBN 978-3-658-17551-1. [Google Scholar]
- Bullinger, H.-J.; Neuhüttler, J.; Nägele, R.; Woyke, I. Collaborative Development of Business Models in Smart Service Ecosystems. In Proceedings of the 2017 Portland International Conference on Management of Engineering and Technology (PICMET), Portland, OR, USA, 9–13 July 2017; IEEE: New York, NY, USA, 2017; pp. 1–9. [Google Scholar] [CrossRef]
- Hirsch-Kreinsen, H. Industry 4.0: Options for Human-Oriented Work Design. Sci 2023, 5, 9. [Google Scholar] [CrossRef]
- Neuhüttler, J.; Kett, H.; Frings, S.; Falkner, J.; Ganz, W.; Urmetzer, F. Artificial Intelligence as Driver for Business Model Innovation in Smart Service Systems. In Advances in the Human Side of Service Engineering; Spohrer, J., Leitner, C., Eds.; Springer International Publishing: Cham, Switzerland, 2020; pp. 212–219. ISBN 978-3-030-51056-5. [Google Scholar]
- Evcenko, D.; Kett, H.; Nebauer, S. Risiken managen—Einsatzpotenziale von EaaS-Lösungen in der Produktion. Z. Für Wirtsch. Fabr. 2022, 117, 872–878. [Google Scholar] [CrossRef]
- Bullinger, H.-J.; Ganz, W.; Neuhüttler, J. Smart Services—Chancen und Herausforderungen digitalisierter Dienstleistungssysteme für Unternehmen. In Dienstleistungen 4.0; Bruhn, M., Hadwich, K., Eds.; Springer Fachmedien Wiesbaden: Wiesbaden, Germany, 2017; pp. 97–120. ISBN 978-3-658-17549-8. [Google Scholar]
- Arbeitskreis Smart Service Welt/acatech. Smart Service Smart Service Welt: Umsetzungsempfehlungen für das Zukunftsprojekt Internet Basierte Dienste für die Wirtschaft; Abschlussbericht: Berlin, Germany, 2015. [Google Scholar]
- Mathis, C. Data Lakes. Datenbank Spektrum 2017, 17, 289–293. [Google Scholar] [CrossRef]
- Opresnik, D.; Taisch, M. The value of Big Data in servitization. Int. J. Prod. Econ. 2015, 165, 174–184. [Google Scholar] [CrossRef]
- Ardolino, M.; Rapaccini, M.; Saccani, N.; Gaiardelli, P.; Crespi, G.; Ruggeri, C. The role of digital technologies for the service transformation of industrial companies. Int. J. Prod. Res. 2018, 56, 2116–2132. [Google Scholar] [CrossRef]
- Rowley, J. The wisdom hierarchy: Representations of the DIKW hierarchy. J. Inf. Sci. 2007, 33, 163–180. [Google Scholar] [CrossRef]
- Martin, D.; Kühl, N.; von Bischhoffshausen, J.K. System-Wide Learning in Cyber-Physical Service Systems: A Research Agenda. In Designing for Digital Transformation: Co-Creating Services with Citizens and Industry, Proceedings of the 15th International Conference on Design Science RESEARCH in information Systems and Technology, DESRIST 2020, Kristiansand, Norway, 2–4 December, 2020; Hofmann, S., Ed.; Springer: Cham, Switzerland, 2020; pp. 457–468. ISBN 978-3-030-64822-0. [Google Scholar]
- Spohrer, J.; Bassano, C.; Piciocchi, P.; Siddike, M.A.K. What Makes a System Smart? Wise? In Advances in the Human Side of Service Engineering; Ahram, T.Z., Karwowski, W., Eds.; Springer International Publishing: Cham, Switzerland, 2017; pp. 23–34. ISBN 978-3-319-41946-6. [Google Scholar]
- Cardoso, J.; Fromm, H.; Nickel, S.; Satzger, G.; Studer, R.; Weinhardt, C. Fundamentals of Service Systems; Springer International Publishing: Cham, Switzerland, 2015; ISBN 978-3-319-23194-5. [Google Scholar]
- Hunke, F.; Schüritz, R. Smartere Produkte durch analysebasierte Dienstleistungen—Ein methodisches Werkzeug zur strukturierten Entwicklung. HMD 2019, 56, 514–529. [Google Scholar] [CrossRef]
- Delen, D.; Demirkan, H. Data, information and analytics as services. Decis. Support Syst. 2013, 55, 359–363. [Google Scholar] [CrossRef]
- Kühn, A.; Joppen, R.; Reinhart, F.; Röltgen, D.; Enzberg, S.; von Dumitrescu, R. Analytics Canvas—A Framework for the Design and Specification of Data Analytics Projects. Procedia CIRP 2018, 70, 162–167. [Google Scholar] [CrossRef]
- Heuchert, M.; Verhoeven, Y.; Cordes, A.-K.; Becker, J. Smart Service Systems in Manufacturing: An Investigation of Theory and Practice. In Proceedings of the 53rd Hawaii International Conference on System Sciences, Maui, HI, USA, 7–10 January 2020. [Google Scholar]
- Rai, A. Explainable AI: From black box to glass box. J. Acad. Mark. Sci. 2020, 48, 137–141. [Google Scholar] [CrossRef]
- Kutz, J.; Neuhüttler, J.; Spilski, J.; Lachmann, T. Implementation of AI Technologies in manufacturing—success factors and challenges. In The Human Side of Service Engineerin, Proceedings of the 13th International Conference on Applied Human Factors and Ergonomics (AHFE 2022), New York, NY, USA, 24–28 July 2022; AHFE International: New York, NY, USA, 2022. [Google Scholar]
- Medberg, G.; Grönroos, C. Value-in-use and service quality: Do customers see a difference? J. Serv. Theory Pract. 2020, 30, 507–529. [Google Scholar] [CrossRef]
- Klein, M.M.; Biehl, S.S.; Friedli, T. Barriers to smart services for manufacturing companies—An exploratory study in the capital goods industry. J. Bus. Ind. Mark. 2018, 33, 846–856. [Google Scholar] [CrossRef]
- Gonçalves, L.; Patrício, L.; Grenha Teixeira, J.; Wünderlich, N.V. Understanding the customer experience with smart services. J. Serv. Manag. 2020, 31, 723–744. [Google Scholar] [CrossRef]
- Wuenderlich, N.V.; Heinonen, K.; Ostrom, A.L.; Patricio, L.; Sousa, R.; Voss, C.; Lemmink, J.G. “Futurizing” smart service: Implications for service researchers and managers. J. Serv. Mark. 2015, 29, 442–447. [Google Scholar] [CrossRef]
- Mani, Z.; Chouk, I. Consumer Resistance to Innovation in Services: Challenges and Barriers in the Internet of Things Era. J. Prod. Innov. Manag. 2018, 35, 780–807. [Google Scholar] [CrossRef]
- Russo-Spena, T.; Mele, C. “Five Co-s” in innovating: A practice-based view. J. Serv. Manag. 2012, 23, 527–553. [Google Scholar] [CrossRef]
- Neuhüttler, J.; Hermann, S.; Ganz, W.; Spath, D.; Mark, R. Quality Based Testing of AI-based Smart Services: The Example of Stuttgart Airport. In Proceedings of the 2022 Portland International Conference on Management of Engineering and Technology (PICMET), Portland, OR, USA, 7–11 August 2022; pp. 1–10, ISBN 2159-5100. [Google Scholar]
- Neuhüttler, J. Ein Verfahren zum Testen der Wahrgenommenen Qualität in der Entwicklung von Smart Services; Fraunhofer Verlag: Stuttgart, Germany, 2022. [Google Scholar]
- Tuzovic, S.; Paluch, S. Conversational Commerce—A New Era for Service Business Development? In Service Business Development; Bruhn, M., Hadwich, K., Eds.; Springer Fachmedien Wiesbaden: Wiesbaden, Germany, 2018; pp. 81–100. ISBN 978-3-658-22425-7. [Google Scholar]
- Wixom, B.H.; Schüritz, R. Creating Customer Value Using Analytics. MIT CISR Res. Brief. 2017, 17, 1–4. [Google Scholar]
- Someh, I.; Davern, M.; Breidbach, C.F.; Shanks, G. Ethical Issues in Big Data Analytics: A Stakeholder Perspective. Commun. Assoc. Inf. Syst. 2019, 44, 718–747. [Google Scholar] [CrossRef]
- Huang, M.-H.; Rust, R.T. Artificial Intelligence in Service. J. Serv. Res. 2018, 21, 155–172. [Google Scholar] [CrossRef]
- Wiegard, R.-B.; Breitner, M.H. Smart services in healthcare: A risk-benefit-analysis of pay-as-you-live services from customer perspective in Germany. Electron Mark. 2019, 29, 107–123. [Google Scholar] [CrossRef]
- Ahner, L.; Bayrak, Y.; Cleaver, I.; Ge, M.L.; Neuhüttler, J.; Urmetzer, F. Impacts of Professional Education Measures on the Digital Transformation in Organisations. In Advances in the Human Side of Service Engineering; Leitner, C., Ganz, W., Satterfield, D., Bassano, C., Eds.; Springer International Publishing: Cham, Switzerland, 2021; pp. 173–180. ISBN 978-3-030-80839-6. [Google Scholar]
- Blumberg, V.S.L.; Kauffeld, S. Kompetenzen und Wege der Kompetenzentwicklung in der Industrie 4.0. Z. Für Angew. Organ. 2021, 52, 203–225. [Google Scholar] [CrossRef]
- Eckert, F.; Heidling, E. Hybridisierung in der Value Chain und Kompetenzent-Wicklung für Hybride Wertschöpfung in Cloudbasierter Kollaborativer Arbeit; Frühjahrskongress: Bochum, Germany, 2021. [Google Scholar]
- Cimini, C.; Adrodegari, F.; Paschou, T.; Rondini, A.; Pezzotta, G. Digital servitization and competence development: A case-study research. CIRP J. Manuf. Sci. Technol. 2021, 32, 447–460. [Google Scholar] [CrossRef]
- Demirkan, H.; Spohrer, J. T-Shaped Innovators: Identifying the Right Talent to Support Service Innovation. Res.-Technol. Manag. 2015, 58, 12–15. [Google Scholar] [CrossRef]
- Barile, S.; Saviano, M.; Simone, C. Service economy, knowledge, and the need for T-shaped innovators. World Wide Web 2015, 18, 1177–1197. [Google Scholar] [CrossRef]
- Demirkan, H.; Spohrer, J.C. Commentary—Cultivating T-Shaped Professionals in the Era of Digital Transformation. Serv. Sci. 2018, 10, 98–109. [Google Scholar] [CrossRef]
- Tronvoll, B.; Sklyar, A.; Sörhammar, D.; Kowalkowski, C. Transformational shifts through digital servitization. Ind. Mark. Manag. 2020, 89, 293–305. [Google Scholar] [CrossRef]
- Moraes, C.R.; de Cunha, P.R. Enterprise Servitization: Practical Guidelines for Culture Transformation Management. Sustainability 2023, 15, 705. [Google Scholar] [CrossRef]
- Münch, C.; Marx, E.; Benz, L.; Hartmann, E.; Matzner, M. Capabilities of digital servitization: Evidence from the socio-technical systems theory. Technol. Forecast. Soc. Chang. 2022, 176, 121361. [Google Scholar] [CrossRef]
- Grönroos, C.; Ojasalo, K. Service productivity. J. Bus. Res. 2004, 57, 414–423. [Google Scholar] [CrossRef]
- Vargo, S.L.; Webster, F.E.; Bolton, R.N.; Lusch, R.F. The Service-Dominant Logic of Marketing: Dialog, Debate, and Directions; CRC: Boca Raton, FL, USA, 2006; ISBN 9780765614902. [Google Scholar]
- Wasko, M.M.; Teigland, R. Public goods or virtual commons? Applying theories of public goods, social dilemmas, and collective action to Electronic networks of practice. J. Inf. Theory Appl. 2004, 6, 25–41. [Google Scholar]
- Tombeil, A.-S.; Kremer, D.; Neuhüttler, J.; Dukino, C.; Ganz, W. Potenziale von Künstlicher Intelligenz in der Dienstleistungsarbeit. In Automatisierung und Personalisierung von Dienstleistungen: Methoden—Potenziale—Einsatzfelder; Bruhn, M., Hadwich, K., Eds.; Springer Fachmedien: Wiesbaden, Germany, 2018; pp. 135–154. ISBN 978-3-658-30167-5. [Google Scholar]
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Neuhüttler, J.; Feike, M.; Kutz, J.; Blümel, C.; Bienzeisler, B. Digital Factory Transformation from a Servitization Perspective: Fields of Action for Developing Internal Smart Services. Sci 2023, 5, 22. https://doi.org/10.3390/sci5020022
Neuhüttler J, Feike M, Kutz J, Blümel C, Bienzeisler B. Digital Factory Transformation from a Servitization Perspective: Fields of Action for Developing Internal Smart Services. Sci. 2023; 5(2):22. https://doi.org/10.3390/sci5020022
Chicago/Turabian StyleNeuhüttler, Jens, Maximilian Feike, Janika Kutz, Christian Blümel, and Bernd Bienzeisler. 2023. "Digital Factory Transformation from a Servitization Perspective: Fields of Action for Developing Internal Smart Services" Sci 5, no. 2: 22. https://doi.org/10.3390/sci5020022