An enterprise engineering approach for the alignment of business and information technology strategy

Information systems and information technology (IS/IT, hereafter just IT) strategies usually depend on a business strategy. The alignment of both strategies improves their strategic plans. From an external perspective, business and IT alignment is the extent to which the IT strategy enables and drives the business strategy. This article reviews strategic alignment between business and IT, and proposes the use of enterprise engineering (EE) to achieve this alignment. The EE approach facilitates the definition of a formal dialog in the alignment design. In relation to this, new building blocks and life-cycle phases have been defined for their use in an enterprise architecture context. This proposal has been adopted in a critical process of a ceramic tile company for the purpose of aligning a strategic business plan and IT strategy, which are essential to support this process. © 2011 Taylor & Francis.Cuenca, L.; Boza, A.; Ortiz, A. (2011). 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Inconsistency-tolerant business rules in distributed information systems

The final publication is available at Springer via http://10.1007/978-3-642-41033-8_41Business rules enhance the integrity of information systems. However, their maintenance does not scale up easily to distributed systems with concurrent transactions. To a large extent, that is due to two problematic exigencies: the postulates of total and isolated business rule satisfaction. For overcoming these problems, we outline a measure-based inconsistency-tolerant approach to business rules maintenance.Supported by ERDF/FEDER and MEC grants TIN2009-14460-C03, TIN2010-17139, TIN2012-37719-C03-01.Decker, H.; Muñoz Escoí, FD. (2013). Inconsistency-tolerant business rules in distributed information systems. En On the Move to Meaningful Internet Systems: OTM 2013 Workshops. Springer Verlag (Germany). 8186:322-331. https://doi.org/10.1007/978-3-642-41033-8_41S3223318186Abiteboul, S., Hull, R., Vianu, V.: Foundations of Databases. 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What are the competences in information system required by managers? Curriculum development for management and public administration degrees

[EN] This paper analyzes the competences required by executives to manage information system, and consequently, the competences that must define the information system subjects in non-technical degrees, degrees, such as Public Administration or Business Management. This work reviews the literature about business managers competences on Information Technologies (IT) and compares the theory with the traditional body of knowledge about information systems taught at business schools. By analyzing the executives function, their role in the information system management, and, above, all the importance of their decisions in the effective integration of IT in business processes, this work proposes specific development in seven knowledge areas that facilitate the acquisition of these types of executive competencesDevece Carañana, CA.; Peris-Ortiz, M.; Rueda Armengot, C. (2016). What are the competences in information system required by managers? 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The effectiveness of crowdsourcing in knowledge-based industries: the moderating role of transformational leadership and organisational learning

[EN] Crowdsourcing provides an opportunity for SMEs to exploit collective knowledge that is located outside the organisation. Crowdsourcing allows organisations to keep pace with a fast-changing environment by solving business problems, supporting R&D activities, and fostering innovation cheaply, flexibly, and dynamically. Nevertheless, managing crowdsourcing is difficult, and positive outcomes are not guaranteed. Drawing on the Resource-based View, we study transformational leadership and organisational learning capability as complementary assets to help SMEs deploy crowdsourcing. An empirical study of Spanish telecommunications and biotechnology companies confirmed the moderating effect of organisational learning on the relationship between crowdsourcing and organisational performance.Devece Carañana, CA.; Palacios Marqués, D.; Ribeiro-Navarrete, B. (2019). The effectiveness of crowdsourcing in knowledge-based industries: the moderating role of transformational leadership and organisational learning. Economic Research-Ekonomska Istra ivanja. 32(1):335-351. https://doi.org/10.1080/1331677X.2018.1547204S335351321Amitay, M., Popper, M., & Lipshitz, R. (2005). Leadership styles and organizational learning in community clinics. The Learning Organization, 12(1), 57-70. doi:10.1108/09696470510574269Atapattu, M., & Ranawake, G. (2017). Transformational and Transactional Leadership Behaviours and their Effect on Knowledge Workers’ Propensity for Knowledge Management Processes. Journal of Information & Knowledge Management, 16(03), 1750026. doi:10.1142/s0219649217500265Aragón-Correa, J. A., García-Morales, V. J., & Cordón-Pozo, E. (2007). Leadership and organizational learning’s role on innovation and performance: Lessons from Spain. Industrial Marketing Management, 36(3), 349-359. doi:10.1016/j.indmarman.2005.09.006Bal, A. 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Enhancing modeling and change support for process families through change patterns

The increasing adoption of process-aware information systems (PAISs), together with the variability of business processes (BPs), has resulted in large collections of related process model variants (i.e., process families). To effectively deal with process families, several proposals (e.g., C-EPC, Provop) exist that extend BP modeling languages with variability-specific constructs. While fostering reuse and reducing modeling efforts, respective constructs imply additional complexity and demand proper support for process designers when creating and modifying process families. Recently, generic and language independent adaptation patterns were successfully introduced for creating and evolving single BP models. However, they are not sufficient to cope with the specific needs for modeling and evolving process families. This paper suggests a complementary set of generic and language-independent change patterns specifically tailored to the needs of process families. 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Customer relationship management: digital transformation and sustainable business model innovation

[EN] The point of departure for this study is the understanding of customer relationship management (CRM) as a set of technological solutions key for efficient business management, the benefits of which, highlighted by previous works, are presented and defined here as crucial for entrepreneurial success. Of particular interest for this purpose are the existing studies on sustainability, which provide a viable research model to assess and validate the potential effect of each CRM component (sales, marketing, and services) on the three dimensions of sustainability (economic, environmental, and social). Upon confirmation of our hypotheses, the subsequent validation of such model should bring a better understanding of the way in which CRM-related benefits may increase the positive impact of its components on each dimension of sustainability. CRM can hence be considered a sort of Green IT, oriented toward digital transformation and sustainable business model innovation. 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Resolving the productivity paradox of digitalised production

[EN] Although Industry 4.0 and other initiatives predict widespread adoption of digitalised technology on the factory floor, few companies use new digitalised production technology holistically in their ecosystems; in practical implementation, companies often decide against digitalisation for financial reasons. This is due to a paradox (akin to the so called “productivity paradox”) caused by the complexity of value creation and value delivery within digitalised production. This article analyses and synthesises cross-disciplinary research using a grounded theory model, thus offering valuable insights for businesses considering investing in digitalised production. A qualitative model and an associated toolbox (complete with tools for practical application by business leaders and decision-makers) are presented to address organisational uncertainty and leadership disconnect that often contribute to the paradoxical gap between digital strategy and operational implementation.Dold, L.; Speck, C. (2021). Resolving the productivity paradox of digitalised production. International Journal of Production Management and Engineering. 9(2):65-80. https://doi.org/10.4995/ijpme.2021.15058OJS658092Al-Debei, Mutaz M.; Avison, David (2010): Developing a unified framework of the business model concept. In Euro-pean Journal of Information Systems 19 (3), pp. 359-376. https://doi.org/10.1057/ejis.2010.21Andulkar, Mayur; Le, Duc Tho; Berger, Ulrich (2018): A multi-case study on Industry 4.0 for SME's in Brandenburg, Germany. Proceedings of the 51st Hawaii International Conference on System Sciences. Hawaii, 2018. https://doi.org/10.24251/HICSS.2018.574Arnold, Christian; Kiel, Daniel; Voight, Kai-Ingo (2017): Innovative Business Models for the Industrial Internet of Things. In Berg Huettenmaenn Monatsh 162 (9), pp. 371-381. https://doi.org/10.1007/s00501-017-0667-7Arnold, Christian; Voight, Kai-Ingo (2017): Ecosystem Effects of the Industrial Internet of Things on Manufacturing Companies. In Acta INFOLOGICA 1 (2), pp. 99-108.Berghaus, Sabine (2018): The Fuzzy Front End of Digital Transformation. Activities and Approaches for Initiating Organizational Change Strategies. Universität St. Gallen. Available online at https://www1.unisg.ch/www/edis.nsf/SysLkpByIdentifier/4704/$FILE/dis4704.pdf.Berghaus, Sabine; Back, Andrea; Kaltenrieder, Bramwell. (2017): Digital Maturity & Transformation Report 2017. Zürich: Crosswalk AG,. In Veröffentlichung zur Studie der Universität St. Gallen in Kooperation mit Crosswalk. St. Gallen, March 2017.Bouwman, Harry; Nikou, Shahrokh; Molina-Castillo, Francisco J.; Reuver, Mark de (2018): The impact of digitaliza-tion on business models. In Digital Policy, Regulation and Governance 20 (2), pp. 105-124. https://doi.org/10.1108/DPRG-07-2017-0039Buchholz, Birgit; Ferdinand, Jan-Peter; Gieschen, Jan-Hinrich; Seidel, Uwe (2017): Digitalisierung industrieller Wertschöpfung. Eine Studie im Rahmen der Begleitforschung zum Technologieprogramm AUTONOMIK für In-dustrie 4.0 des Bundesministeriums für Wirtschaft und Energie. Berlin: iit-Institut für Innovation und Technik der VDI/VDE Innovation + Technik GmbH.Burggräf, Peter; Dannapfel, Matthias; Voet, Hanno; Bök, Patrick-Benjamin; Uelpenich, Jérôme; Hoppe, Julian (2017): Digital Transformation of Lean Production. Systematic Approach for the Determination of Digitally Pervasive Val-ue Chains. In World Academy of Science, Engineering and Technology, International Journal of Social, Behavioral, Educational, Economic, Business and Industrial Engineering 11 (10), 2462-2471.Burmeister, Christian; Luettgens, Dirk; Piller, Frank T. (2016): Business Model Innovation for Industrie 4.0. Why the 'Industrial Internet' Mandates a New Perspective. In Die Unternehmensführung ; RWTH-TIM Working Paper 70 (2), pp. 124-152. https://doi.org/10.2139/ssrn.2571033Cañas, Héctor; Mula, Josefa; Díaz-Madroñero, Manuel; Campuzano-Bolarín, Francisco (2021): Implementing Industry 4.0 principles. In Computers & Industrial Engineering 158 (1), p. 107379. https://doi.org/10.1016/j.cie.2021.107379Charmaz, Kathy (2014): Constructing grounded theory. 2nd edition. Los Angeles, London, New Delhi, Singapore, Washington DC: SAGE.Chesbrough, Henry (2010): Business model innovation: opportunities and barriers. Opportunities and Barriers. In Long range planning 43 (2-3), pp. 354-363. https://doi.org/10.1016/j.lrp.2009.07.010Chesbrough, Henry; Rosenbloom, Richard S. (2002): The role of the business model in capturing value from innova-tion: evidence from Xerox Corporation's technology spin‐off companies. In Industrial and corporate change 11 (3), pp. 529-555. https://doi.org/10.1093/icc/11.3.529Cottyn, Johannes; Stockman, Kurt; Hendrik, van Landeghem (2008): The Complementarity of Lean Thinking and the ISA 95 Standard. WBF 2008. WBF. Barcelona, November 2008. Available online at http://hdl.handle.net/1854/LU-524679.Dold, Luzian (2020): Beurteilung von Investitionen in die digitalisierte Produktion. Eine Mixed-Method-Studie zur moderierenden Wirkung von Nutzenkonstrukten aus Geschäftsmodellen an der Lücke zwischen digitaler Strategie und operativen Prozessen. Dissertation. Middlesex University, London.Dold, Luzian (2021): A Value Centred Paradigm to Moderate the Digital Transformation of Manufacturing. In Adv. J Social Sci. 8 (1), pp. 86-95. DOI: 10.21467/ajss.8.1.86-95.Döring, Nicola; Bortz, Jürgen (2016): Forschungsmethoden und Evaluation in den Sozial- und Humanwissenschaften. With assistance of Sandra Pöschl. 5. vollständig überarbeitete, aktualisierte und erweiterte Auflage. Berlin, Heidel-berg: Springer (Springer-Lehrbuch). https://doi.org/10.1007/978-3-642-41089-5Dorst, Wolfgang (2016): Implementation Strategy Industrie 4.0. Report on the results of the Industrie 4.0 Platform. With assistance of W. Dorst, C. Glohr, T. Hahn, U. Loewen, Rosen, R. Schiemann, T., F. Vollmar et al. Edited by BITKOM e.V., VDMA e.V., ZVEI e.V. Berlin, Frankfurt am Main.Eruvankai, Saju; Muthukrishnan, Murugesan; Mysore, Anantharamaiah Kumar (2017): Accelerating IIOT Adoption with OPC UA. In INTERNETWORKING INDONESIA 9 (1), pp. 3-8. 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Strategic implementation framework of industrial value chain for connected industries. Edited by Industrial Value Chain Initiative. Monozu-kuri Nippon Conference c/o. Tokyo.Jesse, Norbert (2016): Internet of Things and Big Data - The Disruption of the Value Chain and the Rise of New Soft-ware Ecosystems. In IFAC-PapersOnLine 49 (29), pp. 275-282. https://doi.org/10.1016/j.ifacol.2016.11.079Jüttemann, Gerd (Ed.) (1989): Qualitative Forschung in der Psychologie. Grundfragen, Verfahrensweisen, Anwen-dungsfelder. 2. Aufl. Heidelberg: Asanger.Kagermann, Henning; Anderl, Reiner; Gausemeier, Jürgen; Schuh, Günther; Wahlster Wolfgang (2016): Industrie 4.0 im globalen Kontext. Strategien der Zusammenarbeit mit internationalen Partnern. Acatech Studie. München: Her-bert Utz Verlag.Kagermann, Henning; Wahlster, Wolfgang; Helbig, Johannes (2013): Umsetzungsempfehlungen für das Zukunftspro-jekt Industrie 4.0. Abschlussbericht des Arbeitskreises Industrie 4.0. Edited by Prof. Dr. Henning Kagermann. For-schungsunion Wirtschaft und Wissenschaft, Arbeitskreis Industrie 4.0. Frankfurt am Main.Kagermann, Henning; Wahlster, Wolfgang; Lukas, Wolf-Dieter (2011): Industrie 4.0 : Mit dem Internet der Dinge auf dem Weg zur 4. Industriellen Revolution. In VDI Nachrichten 2011, 4/1/2011 (13).Kiel, Daniel; Müller, Julian; Arnold, Christian; Voight, Kai-Ingo (2017): Sustainable Industrial Value Creation. Benefits and Challenges of Industry 4.0. In International Journal of Innovation Management (ijim) 21 (8), pp. 1-34. https://doi.org/10.1142/S1363919617400151Koch, Arno (2016): OEE für das Produktionsteam. Das vollständige OEE-Benutzerhandbuch - oder wie Sie die ver-borgene Maschine entdecken. 3., korrigierte Auflage. Herrieden: CETPM Publishing (Operational Excellence, Nr. 5).Legrenzi, Christopher (2017): THE DIGITAL PARADOX. INFORMATION, INFORMATICS, AND INFOR-MATION SYSTEM. In ISM Journal of International Business, pp. 35-42.Lerch, Christian; Jäger, Angela; Maloca, Spomenka (2017): Wie digital ist Deutschlands Industrie wirklich. Arbeit und Produktivität in der digitalen Produktion. In Mitteilungen aus der ISI-Erhebung Modernisierung der Produktion, Ausgabe 71.Leyh, Christian; Bley, Katja (2016): Digitalisierung. Chance oder Risiko für den deutschen Mittelstand? - Eine Studie ausgewählter Unternehmen. In HMD 53 (1), pp. 29-41. https://doi.org/10.1365/s40702-015-0197-2Lin, Shi-Wan; Crawford, Mark; Mellor, Stephen (2017): The Industrial Internet of Things Volume G1: Reference Architecture. Version 1.80. Needham, MA. In Industrial Internet Consortium (IIC) Tech. Rep.Magruk, Andrzej (2016): Uncertainty in the Sphere of the Industry 4.0 - Potential Areas to Research. In Business, Management & Education/Verslas, Vadyba ir Studijos 14 (2), pp. 275-291. https://doi.org/10.3846/bme.2016.332Maier, W.; Weber, M. (2013): Management von Big-Data-Projekten. Leitfaden. Berlin: Bundesverband Information-swirtschaft,Telekommunikation und neue Medien e. V.Maklan, Stan; Peppard, Joe; Klaus, Philipp (2015): Show me the money. In European Journal of Marketing 49 (3/4), pp. 561-595. https://doi.org/10.1108/EJM-08-2013-0411Mayring, Philipp (2008): Einführung in die qualititative Sozialforschung. Eine Anleitung zu qualitativem Denken. 5. Aufl. Weinheim, Basel: Beltz (Beltz Studium).Obermaier, Robert (2019): Industrie 4.0 und Digitale Transformation als unternehmerische Gestaltungsaufgabe. In Robert Obermaier (Ed.): Handbuch Industrie 4.0 und Digitale Transformation. Betriebswirtschaftliche, technische und rechtliche Herausforderungen. 1st ed. 2019. Wiesbaden: Springer Fachmedien Wiesbaden, pp. 3-46. https://doi.org/10.1007/978-3-658-24576-4_1Obermaier, Robert; Schweikl, Stefan (2019): Zur Bedeutung von Solows Paradoxon. Empirische Evidenz und ihre Übertragbarkeit auf Digitalisierungsinvestitionen in einer Industrie 4.0. 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Autonomous Agents for Business Process Management

Traditional approaches to managing business processes are often inadequate for large-scale organisation-wide, dynamic settings. However, since Internet and Intranet technologies have become widespread, an increasing number of business processes exhibit these properties. Therefore, a new approach is needed. To this end, we describe the motivation, conceptualization, design, and implementation of a novel agent-based business process management system. The key advance of our system is that responsibility for enacting various components of the business process is delegated to a number of autonomous problem solving agents. To enact their role, these agents typically interact and negotiate with other agents in order to coordinate their actions and to buy in the services they require. This approach leads to a system that is significantly more agile and robust than its traditional counterparts. To help demonstrate these benefits, a companion paper describes the application of our system to a real-world problem faced by British Telecom

Meter Scoping Study

This report presents a summary of metering technology and cost information from past studies in an attempt to identify key barriers to more widespread implementation