A systematic literature review of Total Quality Management (TQM) implementation in the organization

[EN] In today’s market situation and complex business environment, organization must be able to deliver the customer’s requirement and the expectations which are critical to the satisfaction such as high product quality, faster delivery and competitive cost. Organization need to apply a comprehensive concept and method on managing those requirements. The concept of Total Quality Management (TQM) is considered as one of a popular concept used to manage the quality of product and services comprehensively. This research is to observe is this concept and method still relevant to be use and effectively improved the business performance as well as customer satisfaction. It is a systematic literature review to the literatures from many industry sectors that were collected and reviewed in detail. The result show that this concept is still being used by many organizations around the world and its successfully help the organization to improve their competitiveness, business growth and the sustainability as well as increase employee’s morale.This article was completed thanks to the financial support from the university of Mercu Buana, Jakarta-Indonesia. It also completed with the purpose and motivation of the authors to have an innovate research thinking as well as the contribution to the future researcher.Permana, A.; Purba, H.; Rizkiyah, N. (2021). A systematic literature review of Total Quality Management (TQM) implementation in the organization. International Journal of Production Management and Engineering. 9(1):25-36. https://doi.org/10.4995/ijpme.2021.13765OJS253691Alanazi, M.H. (2020). The mediating role of primary TQM factors and strategy in the relationship between supportive TQM factors and organisational results: An empirical assessment using the MBNQA model. Cogent Business and Management, 7(1). https://doi.org/10.1080/23311975.2020.1771074Antunes, M.G., Mucharreira, P.R., Justino, M. do R.T., & Quirós, J.T. (2018). Total Quality Management Implementation in Portuguese Higher Education Institutions. Proceedings MDPI, 2(21), 1342. https://doi.org/10.3390/proceedings2211342Arifin, J. (2016). Penguatan Manajemen Syariah Melalui Total Quality Managementbagi Pelaku Lembaga Keuangan Syariah Di Kota Semarang. Jurnal At-Taqaddum, Volume 8, Nomor 2, November 2016, 8(2), 180. https://doi.org/10.21580/at.v8i2.1170Balasubramanian, M. (2016). Total Quality Management [TQM] in the Healthcare Industry - Challenges, Barriers and Implementation Developing a Framework for TQM Implementation in a Healthcare Setup. Science Journal of Public Health, 4(4), 271. https://doi.org/10.11648/j.sjph.20160404.11Benzaquen, J., Carlos, M., Norero, G., Armas, H., & Pacheco, H. (2019). Quality in private health companies in Peru: The relation of QMS & ISO 9000 principles on TQM factor. International Journal of Healthcare Management, 0(0), 1-9. https://doi.org/10.1080/20479700.2019.1644472Bigliardi, B., & Galati, F. (2014). The implementation of TQM in R&D environments. Journal of Technology Management and Innovation, 9(2), 157-171. https://doi.org/10.4067/S0718-27242014000200012Bunglowala, A., & Asthana, N. (2016). A Total Quality Management Approach in Teaching and Learning Process. International Journal of Management (IJM), 7(5), 223-227. http://www.iaeme.com/MasterAdmin/uploadfolder/IJM_07_05_021/IJM_07_05_021.pdfBusu, M. (2019). Applications of TQM Processes to Increase the Management Performance of Enterprises in the Romanian Renewable Energy Sector. Processes MDPI. https://doi.org/10.3390/pr7100685Dahlgaard, J.J., Kristensen, K., & Kanji, G.K. (2002). Fundamentals of Total Quality Management: Process analysis and improvement Jens. Original illustrations © Taylor & Francis 2002. https://doi.org/10.4324/9780203930021Dewi, H.P., Lumbanraja, P., & Matondang, R. (2015). Implementation of Total Quality Management and Interpersonal Communication in Achieving Student Satisfaction through Service Quality at Yayasan Pendidikan Islam, Miftahussalam, Medan. International Journal of Research and Review, 2(6), 343-347. http://www.gkpublication.in/IJRR_Vol.2_Issue6_June2015/IJRR0066.pdfEltawy, N., & Gallear, D. (2017). Leanness and agility: A comparative theoretical view. Industrial Management and Data Systems, 117(1), 149-165. https://doi.org/10.1108/IMDS-01-2016-0032Fitriani, F. (2019). Persiapan Total Quality Management (Tqm). Adaara: Jurnal Manajemen Pendidikan Islam, 9(2), 908-919. https://doi.org/10.35673/ajmpi.v9i2.426Garcia-Alcaraz, J.L., Flor-Montalvo, F.J., Avelar-Sosa, L., Sánchez-Ramírez, C., & Jiménez-Macías, E. (2019). Human resource abilities and skills in TQM for sustainable enterprises. Sustainability MDPI, 11(22), 6488. https://doi.org/10.3390/su11226488George, S., & Weimerskirch, A. (1998). Total quality management: Strategies and techniques proven at todays' most successful companies (Second ed.). John Wiley & Sons, Inc.Green, F.B. (2006). Six-sigma and the revival of TQM. Total Quality Management and Business Excellence, 17(10), 1281-1286. https://doi.org/10.1080/14783360600753711Gómez-López, R., Serrano-Bedia, A.M., & López-Fernández, M.C. (2016). Motivations for implementing TQM through the EFQM model in Spain: an empirical investigation. Total Quality Management and Business Excellence, 27(11-12), 1224-1245. https://doi.org/10.1080/14783363.2015.1068688Haffar, M., Al-Karaghouli, W., & Ghoneim, A. (2013). An analysis of the influence of organisational culture on TQM implementation in an era of global marketing: The case of Syrian manufacturing organisations. International Journal of Productivity and Quality Management, 11(1), 96-115. https://doi.org/10.1504/IJPQM.2013.050570Hasan, K., Islam, M.S., Shams, A.T., & Gupta, H. (2018). Total Quality Management (TQM): Implementation in Primary Education System of Bangladesh. International Journal of Research in Industrial Engineering, 7(3), 370-380. https://doi.org/10.22105/riej.2018.128170.1041Houston, D. (2007). TQM and higher education: A critical systems perspective on fitness for purpose. Quality in Higher Education, 13(1), 3-17. https://doi.org/10.1080/13538320701272672Kaname, O. (2003). Handbook for TQM and QCC Vol 1. In Handbook (Vol. 1). Kantardjieva, M. (2015). The Relationship between Total Quality Management (TQM) and Strategic Management. Journal of Economics, Business and Management, 3(5), 537-541. https://doi.org/10.7763/JOEBM.2015.V3.242Kim, G.-S. (2016). Effect of Total Quality Management on Customer Satisfaction. International Journal of Engineering Sciences & Research Technology, 5(6), 507-514. https://doi.org/10.5281/zenodo.55618Kiruthiga, K. (2016). Major factors affecting the execution of total quality management in the construction industry in India. Journal of Chemical and Pharmaceutical Sciences, 9(2), E135-E140.Kumar, S., & Shanmuganathan, J. (2019). A structural relationship between TQM practices and organizational performance with reference to selected auto component manufacturing companies. International Journal of Management, 10(5). https://doi.org/10.34218/IJM.10.5.2019/009Kumar, U., Kumar, V., de Grosbois, D., & Choisne, F. (2009). Continuous improvement of performance measurement by TQM adopters. Total Quality Management & Business Excellence, 20(6), 603-616. https://doi.org/10.1080/14783360902924242Kuo, C. (2016). Effects of Total Quality Management Implementation and Supply Chain Management Capability on Customer Capital. The Journal of Global Business Management, 12(2), 47-60.Lawrence, J.J., & McCollough, M.A. (2004). Implementing Total Quality Management in the Classroom by Means of Student Satisfaction Guarantees. Total Quality Management and Business Excellence, 15(2), 235-254. https://doi.org/10.1080/1478336032000149063Mensah, J.O., Copuroglu, G., & Fening, F.A. (2012). Total Quality Management in Ghana: Critical Success Factors and Model for Implementation of a Quality Revolution. Journal of African Business, 13(2), 123-133. https://doi.org/10.1080/15228916.2012.693444Mercy, O., & Taiye, T.B. (2015). Strategic Imperatives of Total Quality Management and Customer Satisfaction in Organizational Sustainability. International Journal of Academic Research in Business and Social Sciences, 5(4), 1-22. https://doi.org/10.6007/IJARBSS/v5-i4/1538Mitreva, E., Cvetkovik, D., Filiposki, O., Taskov, N., & Gjorshevski, H. (2016). The Effects of Total Quality Management Practices on Performance within a Company for Frozen Food in the Republic of Macedonia. TEM Journal, 5(3), 339-346. https://doi.org/10.18421/TEM53-14Morath, C., & Doluschitz, R. (2009). Total Quality Management in the food industry - Current situation and potential in Germany. Applied Studies In Agribusiness And Commerce, 3(3-4), 83-87. https://doi.org/10.19041/APSTRACT/2009/3-4/18Musenze, I.A., & Thomas, M.S. (2020). Development and validation of a total quality management model for Uganda's local governments. Cogent Business and Management, 7(1), 1-22. https://doi.org/10.1080/23311975.2020.1767996Neyestani, B., & Juanzon, J.B.P. (2016). Developing an Appropriate Performance Measurement Framework for Total Quality Management (TQM) in Construction and Other Industries. IRA-International Journal of Technology & Engineering (ISSN 2455-4480), 5(2), 32. https://doi.org/10.21013/jte.v5.n2.p2Ngambi, M.T., & Nkemkiafu, A.G. (2015). The Impact of Total Quality Management on Firm's Organizational Performance Marcel. American Journal of Management, 15(4), 57-76.Nicolaou, N., & Kentas, G. (2017). Total Quality Management Implementation Failure Reasons in Healthcare Sector. Journal of Health Science 5 (2017) 110-113, 5(2), 110-113. https://doi.org/10.17265/2328-7136/2017.02.007Nugroho, T.W., & Nurcahyo, R. (2018). Analysis of Total Quality Management (TQM) implementation in small medium industries. Proceedings of the International Conference on Industrial Engineering and Operations Management, 2018(Jul), 607-618.Oakland, J.S. (2003). Total quality management - Text with cases. In Butterworth-Heinemann (Third Edit). Butterworth-Heinemann.Phan, A.C., Nguyen, H.T., Nguyen, H.A., & Matsui, Y. (2019). Effect of total quality management practices and jit production practices on flexibility performance: Empirical evidence from international manufacturing plants. MDPI Sustainability (Switzerland), 11(11). https://doi.org/10.3390/su11113093Prajogo, D.I., & Brown, A. (2004). The Relationship between TQM Practices and Quality Performance and the Role of Formal TQM Programs: An Australian Empirical Study. Quality Management Journal, 11(4), 31-42. https://doi.org/10.1080/10686967.2004.11919131Ramlawati, & Putra, A.H.P.K. (2018). Total Quality Management as the Key of the Company to Gain the Competitiveness, Performance Achievement and Consumer Satisfaction. International Review of Management and Marketing, 8(5), 60-69.Rogers, R.E. (2013). Implementation of Total Quality Management A Comprehensive Training Program. 1996 by The Haworth Press, Inc. All rights reserved.Sabet, E., Adams, E., & Yazdani, B. (2014). Quality management in heavy duty manufacturing industry: TQM vs. Six Sigma. Total Quality Management and Business Excellence, 27(1-2), 215-225. https://doi.org/10.1080/14783363.2014.972626Sader, S., Husti, I., & Daróczi, M. (2017). Suggested Indicators To Measure the Impact of Industry 4.0 on Total Quality Management. International Scientific Journal: Industry 4.0, 2(6), 298-301. https://stumejournals.com/journals/i4/2017/6/298/pdfSadikoglu, E., & Olcay, H. (2014). The Effects of Total Quality Management Practices on Performance and the Reasons of and the Barriers to TQM Practices in Turkey. Laboratory Management Information Systems: Current Requirements and Future Perspectives, 2014, 996-1027. https://doi.org/10.1155/2014/537605Sainis, G., Haritos, G., Kriemadis, T., & Fowler, M. (2017). The quality journey for Greek SMEs and their financial performance. Production and Manufacturing Research, 5(1), 306-327. https://doi.org/10.1080/21693277.2017.1374891Santos, A.C. de S.G. dos, Carvalho, L.M., Souza, C.F. de, Reis, A. da C., & Freitag, A.E.B. (2019). Total Quality Management: the case of an electricity distribution company. Brazilian Journal of Operations & Production Management, 16(1), 53-65. https://doi.org/10.14488/BJOPM.2019.v16.n1.a5Sari, & Firdaus, A. (2018). The Impact of Total Quality Management Implementation on Small and Medium Manufacturing Companies. Esensi: Jurnal Bisnis Dan Manajemen, 8(1), 67-78. https://doi.org/10.15408/ess.v8i1.5852Sila, I., & Walczak, S. (2017). Universal versus contextual effects on TQM: a triangulation study using neural networks. Production Planning and Control, 28(5), 367-386. https://doi.org/10.1080/09537287.2017.1296598Sivalai, T., & Rojniruttikul, N. (2018). Determinants of the state railway of Thailand's (SRT) total quality management process: SEM analysis. Journal of International Studies, 11(2). https://doi.org/10.14254/2071-8330.2018/11-2/9Small, E.P., Ayyash, L., & Hamouri, K. Al. (2017). Benchmarking Performance of TQM Principals in Electrical Subcontracting in Dubai: A Case Study. Procedia Engineering, 196(June), 622-629. https://doi.org/10.1016/j.proeng.2017.08.050Sousa-Mendes, G.H. de, Gomes-Salgado, E., & Moro-Ferrari, B.E. (2016). Prioritization of TQM practices in Brazilian medical device SMEs using Analytical Hierarchy Process (AHP) Glauco. DYNA (Colombia), 83(197), 195-203. https://doi.org/10.15446/dyna.v83n197.52205Steiber, A., & Alänge, S. (2013). Do TQM principles need to change? Learning from a comparison to Google Inc. Total Quality Management and Business Excellence, 24(1-2), 48-61. https://doi.org/10.1080/14783363.2012.733256Suarez-Barraza, M.F., & Ablanedo-Rosas, J.H. (2014). Total quality management principles: Implementation experience from Mexican organisations. Total Quality Management and Business Excellence, 25(5-6), 546-560. https://doi.org/10.1080/14783363.2013.867606Sukardi, R.A. (2016). Pengaruh Total Quality Management (TQM) Terhadap Kepuasan Pelanggan Pada Matahari Department Store di Plaza Mulia Samarinda. EJournal Administrasi Bisnis, 4(3), 758-772.Sukdeo, N., Pretorius, J.H., & Vermeulen, A. (2017). The role of Total Quality Management (TQM) practices on improving organisational performance in manufacturing and service organisations. Proceedings of the International Conference on Industrial Engineering and Operations Management, 2017(OCT), 1133-1152.Sutrisno, T.F.C.W. (2019). Relationship between Total Quality Management element, operational performance and organizational performance in food production SMEs. Jurnal Aplikasi Manajemen, 17(2), 285-294. https://doi.org/10.21776/ub.jam.2019.017.02.11Sweis, R., Ismaeil, A., Obeidat, B., & Kanaan, R.K. (2019). Reviewing the Literature on Total Quality Management and Organizational Performance. Journal of Business & Management (COES&RJ-JBM), 7(3), 192-215. https://doi.org/10.25255/jbm.2019.7.3.192.215Talib, F., & Rahman, Z. (2015). Identification and prioritization of barriers to total quality management implementation in service industry: An analytic hierarchy process approach. TQM Journal, 27(5), 591-615. https://doi.org/10.1108/TQM-11-2013-0122Tervonen, P., Pahkala, N., & Haapasalo, H. (2009). Development of TQM in steel manufacturers' production. Ibima Business Review, 1-3, 52-59.Tesfaye, G., & Kitaw, D. (2017). A TQM and JIT Integrated Continuous Improvement Model for Organizational Success: An Innovative Framework. Journal of Optimization in Industrial Engineering, 22, 15-23. https://doi.org/10.22094/joie.2017.265Vukomanovic, M., Radujkovic, M., & Nahod, M.M. (2014). EFQM excellence model as the TQM model of the construction industry of southeastern Europe. Journal of Civil Engineering and Management, 20(1), 70-81. https://doi.org/10.3846/13923730.2013.843582Yang, C.O., & Tsai, M.C. (2014). Improving operations performance through TQM in the post-financial crisis era: An exploratory case study of a multinational IM firm in the Greater China region. Total Quality Management and Business Excellence, 25(5-6), 561-581. https://doi.org/10.1080/14783363.2013.839167Yeng, S.K., Jusoh, M.S., & Ishak, N.A. (2018). The impact of Total Quality Management (TQM) On competitive advantage: A conceptual mixed method study in the Malaysia Luxury hotel industries. Academy of Strategic Management Journal, 17(2), 1-9.Zairi, M. (1991). Total Quality Management for Engineers. In Ccc (Vol. 1). Woodhead Publishing Limited. https://doi.org/10.1533/9781845698911.1Žitkienė, R., & Deksnys, M. (2018). Organizational agility conceptual model. Montenegrin Journal of Economics, 14(2), 115-129. https://doi.org/10.14254/1800-5845/2018.14-2.

Considerations about quality in model-driven engineering

The final publication is available at Springer via http://dx.doi.org/10.1007/s11219-016-9350-6The virtue of quality is not itself a subject; it depends on a subject. In the software engineering field, quality means good software products that meet customer expectations, constraints, and requirements. Despite the numerous approaches, methods, descriptive models, and tools, that have been developed, a level of consensus has been reached by software practitioners. However, in the model-driven engineering (MDE) field, which has emerged from software engineering paradigms, quality continues to be a great challenge since the subject is not fully defined. The use of models alone is not enough to manage all of the quality issues at the modeling language level. In this work, we present the current state and some relevant considerations regarding quality in MDE, by identifying current categories in quality conception and by highlighting quality issues in real applications of the model-driven initiatives. We identified 16 categories in the definition of quality in MDE. From this identification, by applying an adaptive sampling approach, we discovered the five most influential authors for the works that propose definitions of quality. These include (in order): the OMG standards (e.g., MDA, UML, MOF, OCL, SysML), the ISO standards for software quality models (e.g., 9126 and 25,000), Krogstie, Lindland, and Moody. We also discovered families of works about quality, i.e., works that belong to the same author or topic. Seventy-three works were found with evidence of the mismatch between the academic/research field of quality evaluation of modeling languages and actual MDE practice in industry. We demonstrate that this field does not currently solve quality issues reported in industrial scenarios. The evidence of the mismatch was grouped in eight categories, four for academic/research evidence and four for industrial reports. These categories were detected based on the scope proposed in each one of the academic/research works and from the questions and issues raised by real practitioners. We then proposed a scenario to illustrate quality issues in a real information system project in which multiple modeling languages were used. For the evaluation of the quality of this MDE scenario, we chose one of the most cited and influential quality frameworks; it was detected from the information obtained in the identification of the categories about quality definition for MDE. We demonstrated that the selected framework falls short in addressing the quality issues. Finally, based on the findings, we derive eight challenges for quality evaluation in MDE projects that current quality initiatives do not address sufficiently.F.G, would like to thank COLCIENCIAS (Colombia) for funding this work through the Colciencias Grant call 512-2010. This work has been supported by the Gene-ralitat Valenciana Project IDEO (PROMETEOII/2014/039), the European Commission FP7 Project CaaS (611351), and ERDF structural funds.Giraldo-Velásquez, FD.; España Cubillo, S.; Pastor López, O.; Giraldo, WJ. (2016). Considerations about quality in model-driven engineering. Software Quality Journal. 1-66. https://doi.org/10.1007/s11219-016-9350-6S166(1985). Iso information processing—documentation symbols and conventions for data, program and system flowcharts, program network charts and system resources charts. ISO 5807:1985(E) (pp. 1–25).(2011). Iso/iec/ieee systems and software engineering – architecture description. ISO/IEC/IEEE 42010:2011(E) (Revision of ISO/IEC 42010:2007 and IEEE Std 1471-2000) (pp. 1–46).Abran, A., Moore, J.W., Bourque, P., Dupuis, R., & Tripp, L.L. (2013). Guide to the Software Engineering Body of Knowledge (SWEBOK) version 3 public review. IEEE. ISO Technical Report ISO/IEC TR 19759.Agner, L.T.W., Soares, I.W., Stadzisz, P.C., & Simão, J.M. (2013). A brazilian survey on {UML} and model-driven practices for embedded software development. Journal of Systems and Software, 86(4), 997–1005. {SI} : Software Engineering in Brazil: Retrospective and Prospective Views.Amstel, M.F.V. (2010). The right tool for the right job: assessing model transformation quality. pages 69–74. Affiliation: Eindhoven University of Technology, P.O. Box 513, 5600 MB, Eindhoven, Netherlands. Cited By (since 1996):1.Aranda, J., Damian, D., & Borici, A. (2012). Transition to model-driven engineering: what is revolutionary, what remains the same?. In Proceedings of the 15th international conference on model driven engineering languages and systems, MODELS’12 (pp. 692–708). Berlin, Heidelberg: Springer.Arendt, T., & Taentzer, G. (2013). A tool environment for quality assurance based on the eclipse modeling framework. Automated Software Engineering, 20(2), 141–184.Atkinson, C., Bunse, C., & Wüst, J. (2003). Driving component-based software development through quality modelling, volume 2693. Cited By (since 1996):3.Baker, P., Loh, S., & Weil, F. (2005). Model-driven engineering in a large industrial context—motorola case study. In Briand, L., & Williams, C. (Eds.) Model Driven Engineering Languages and Systems, volume 3713 of Lecture Notes in Computer Science (pp. 476–491). Berlin, Heidelberg: Springer.Barišić, A., Amaral, V., Goulão, M., & Barroca, B. (2011). Quality in use of domain-specific languages: a case study. In Proceedings of the 3rd ACM SIGPLAN workshop on evaluation and usability of programming languages and tools, PLATEAU ’11 (pp. 65–72). New York: ACM.Becker, J., Bergener, P., Breuker, D., & Rackers, M. (2010). Evaluating the expressiveness of domain specific modeling languages using the bunge-wand-weber ontology. In 2010 43rd Hawaii international conference on system sciences (HICSS) (pp. 1–10).Bertrand Portier, L.A. (2009). Model driven development misperceptions and challenges.Bézivin, J., & Kurtev, I. (2005). Model-based technology integration with the technical space concept. In Proceedings of the Metainformatics Symposium: Springer.Brambilla, M. (2016). How mature is of model-driven engineering as an engineering discipline @ONLINE.Brambilla, M., & Fraternali, P. (2014). Large-scale model-driven engineering of web user interaction: The webml and webratio experience. Science of Computer Programming, 89 Part B(0), 71 – 87. Special issue on Success Stories in Model Driven Engineering.Brown, A. (2009). Simple and practical model driven architecture (mda) @ONLINE.Bruel, J.-M., Combemale, B., Ober, I., & Raynal, H. (2015). Mde in practice for computational science. Procedia Computer Science, 51, 660–669.Budgen, D., Burn, A.J., Brereton, O.P., Kitchenham, B.A., & Pretorius, R. (2011). Empirical evidence about the uml: a systematic literature review. Software: Practice and Experience, 41(4), 363–392.Burden, H., Heldal, R., & Whittle, J. (2014). Comparing and contrasting model-driven engineering at three large companies. In Proceedings of the 8th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement, ESEM ’14 (pp. 14:1–14:10). New York: ACM.Cabot, J. Has mda been abandoned (by the omg)?Cabot, J. (2009). Modeling will be commonplace in three years time @ONLINE.Cachero, C., Poels, G., Calero, C., & Marhuenda, Y. (2007). Towards a Quality-Aware Engineering Process for the Development of Web Applications. Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 07/462, Ghent University, Faculty of Economics and Business Administration.Challenger, M., Kardas, G., & Tekinerdogan, B. (2015). A systematic approach to evaluating domain-specific modeling language environments for multi-agent systems. Software Quality Journal, 1–41.Chaudron, M.V., Heijstek, W., & Nugroho, A. (2012). How effective is uml modeling? Software & Systems Modeling, 11(4), 571–580. J2: Softw Syst Model.Chenouard, R., Granvilliers, L., & Soto, R. (2008). Model-driven constraint programming. pages 236–246. Affiliation: CNRS, LINA, Universit de Nantes, France; Affiliation: Pontificia Universidad Catlica de, Valparaiso, Chile. Cited By (since 1996):8.Clark, T., & Muller, P.-A. (2012). Exploiting model driven technology: a tale of two startups. Software and Systems Modeling, 11(4), 481–493.Corneliussen, L. (2008). What do you think of model-driven software development?Costal, D., Gómez, C., & Guizzardi, G. (2011). Formal semantics and ontological analysis for understanding subsetting, specialization and redefinition of associations in uml. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 6998 LNCS:189–203. cited By (since 1996)3.Cruz-Lemus, J.A., Maes, A., Género, M., Poels, G., & Piattini, M. (2010). The impact of structural complexity on the understandability of uml statechart diagrams. Information Sciences, 180(11), 2209–2220. Cited By (since 1996):14.Cuadrado, J.S., Izquierdo, J.L.C., & Molina, J.G. (2014). Applying model-driven engineering in small software enterprises. Science of Computer Programming, 89 Part B(0), 176 – 198. Special issue on Success Stories in Model Driven Engineering.Da Silva, A.R. (2015). Model-driven engineering: a survey supported by the unified conceptual model. Computer Languages Systems and Structures, 43, 139–155.Da Silva Teixeira, D.G.M., Quirino, G.K., Gailly, F., De Almeida Falbo, R., Guizzardi, G., & Perini Barcellos, M. (2016). PoN-S: a Systematic Approach for Applying the Physics of Notation (PoN), (pp. 432–447). Cham: Springer International Publishing.Davies, I., Green, P., Rosemann, M., Indulska, M., & Gallo, S. (2006). How do practitioners use conceptual modeling in practice? Data and Knowledge Engineering, 58(3), 358 – 380. Including the special issue : {ER} 2004ER 2004.Davies, J., Milward, D., Wang, C.-W., & Welch, J. (2015). Formal model-driven engineering of critical information systems. Science of Computer Programming, 103(0), 88 – 113. Selected papers from the First International Workshop on Formal Techniques for Safety-Critical Systems (FTSCS 2012).De Oca, I.M.-M., Snoeck, M., Reijers, H.A., & Rodríguez-Morffi, A. (2015). A systematic literature review of studies on business process modeling quality. Information and Software Technology, 58, 187–205.DenHaan, J. (2009). 8 reasons why model driven development is dangerous @ONLINE.DenHaan, J. (2010). Model driven engineering vs the commando pattern @ONLINE.DenHaan, J. (2011a). Why aren’t we all doing model driven development yet @ONLINE.DenHaan, J. (2011b). Why there is no future model driven development @ONLINE.Di Ruscio, D., Iovino, L., & Pierantonio, A. (2013). Managing the coupled evolution of metamodels and textual concrete syntax specifications. cited By (since 1996)0.Dijkman, R.M., Dumas, M., & Ouyang, C. (2008). Semantics and analysis of business process models in {BPMN}. Information and Software Technology, 50(12), 1281–1294.Domínguez-Mayo, F.J., Escalona, M.J., Mejías, M., Ramos, I., & Fernández, L. (2011). A framework for the quality evaluation of mdwe methodologies and information technology infrastructures. International Journal of Human Capital and Information Technology Professionals, 2(4), 11–22.Domínguez-Mayo, F.J., Escalona, M.J., Mejías, M., & Torres, A.H. (2010). A quality model in a quality evaluation framework for mdwe methodologies. pages 495–506. Affiliation: Departamento de Lenguajes y Sistemas Informíticos, University of Seville, Seville, Spain., Cited By (since 1996):1.Dubray, J.-J. (2011). Why did mde miss the boat?.Escalona, M.J., Gutiérrez, J.J., Pérez-Pérez, M., Molina, A., Domínguez-Mayo, E., & Domínguez-Mayo, F.J. (2011). Measuring the Quality of Model-Driven Projects with NDT-Quality, (pp. 307–317). New York: Springer.Espinilla, M., Domínguez-Mayo, F.J., Escalona, M.J., Mejías, M., Ross, M., & Staples, G. (2011). A Method Based on AHP to Define the Quality Model of QuEF (Vol. 123, pp. 685–694). Berlin, Heidelberg: Springer.Fabra, J., Castro, V.D., Álvarez, P., & Marcos, E. (2012). Automatic execution of business process models: exploiting the benefits of model-driven engineering approaches. Journal of Systems and Software, 85(3), 607–625. Novel approaches in the design and implementation of systems/software architecture.Falkenberg, E.D., Hesse, W., Lindgreen, P., Nilsson, B.E., Oei, J.L.H., Rolland, C., Stamper, R.K., Assche, F.J.M.V., Verrijn-Stuart, A.A., & Voss, K. (1996). Frisco: a framework of information system concepts. Technical report, The IFIP WG 8. 1 Task Group FRISCO.Fettke, P., Houy, C., Vella, A.-L., & Loos, P. (2012). Towards the Reconstruction and Evaluation of Conceptual Model Quality Discourses – Methodical Framework and Application in the Context of Model Understandability, volume 113 of Lecture Notes in Business Information Processing, chapter 28, pages 406–421, Springer, Berlin, Heidelberg.Finnie, S. (2015). Modeling community: Are we missing something?Fournier, C. (2008). Is uml [email protected], R., & Rumpe, B. (2007). Model-driven development of complex software: a research roadmap. In Future of Software Engineering, 2007, FOSE ’07 (pp. 37–54).Gallego, M., Giraldo, F.D., & Hitpass, B. (2015). Adapting the pbec-otss software selection approach for bpm suites: an application case. In 2015 34th International Conference of the Chilean Computer Science Society (SCCC) (pp. 1–10).Galvão, I., & Goknil, A. (2007). Survey of traceability approaches in model-driven engineering. cited By (since 1996)22.Giraldo, F., España, S., Giraldo, W., & Pastor, O. (2015). Modelling language quality evaluation in model-driven information systems engineering: a roadmap. In 2015 IEEE 9th International Conference on Research Challenges in Information Science (RCIS) (pp. 64–69).Giraldo, F., España, S., & Pastor, O. (2014). Analysing the concept of quality in model-driven engineering literature: a systematic review. In 2014 IEEE Eighth International Conference on Research Challenges in Information Science (RCIS) (pp. 1–12).Giraldo, F.D., España, S., & Pastor, O. (2016). Evidences of the mismatch between industry and academy on modelling language quality evaluation. arXiv: 1606.02025 .González, C., & Cabot, J. (2014). Formal verification of static software models in mde: a systematic review. Information and Software Technology, 56(8), 821–838. cited By (since 1996)0.González, C.A., Büttner, F., Clarisó, R., & Cabot, J. (2012). Emftocsp: a tool for the lightweight verification of emf models. pages 44–50. Affiliation: cole des Mines de Nantes, INRIA, LINA, Nantes, France; Affiliation: Universitat Oberta de Catalunya, Barcelona, Spain. Cited By (since 1996):1.Gorschek, T., Tempero, E., & Angelis, L. (2014). On the use of software design models in software development practice: an empirical investigation. Journal of Systems and Software, 95(0), 176– 193.Goulão, M., Amaral, V., & Mernik, M. (2016). Quality in model-driven engineering: a tertiary study. Software Quality Journal, 1–33.Grobshtein, Y., & Dori, D. (2011). Generating sysml views from an opm model: design and evaluation. Systems Engineering, 14(3), 327–340.Haan, J.d. (2008). 8 reasons why model-driven approaches (will) fail.Harel, D., & Rumpe, B. (2000). Modeling languages: Syntax, semantics and all that stuff, part i: The basic stuff, Israel. Technical report Jerusalem Israel.Harel, D., & Rumpe, B. (2004). Meaningful modeling: what’s the semantics of semantics? Computer, 37(10), 64–72.Hebig, R., & Bendraou, R. (2014). On the need to study the impact of model driven engineering on software processes. In Proceedings of the 2014 International Conference on Software and System Process, ICSSP 2014 (pp. 164–168). New York: ACM.Heidari, F., & Loucopoulos, P. (2014). Quality evaluation framework (qef): modeling and evaluating quality of business processes. International Journal of Accounting Information Systems, 15(3), 193–223. Business Process Modeling.Heymans, P., Schobbens, P.Y., Trigaux, J.C., Bontemps, Y., Matulevicius, R., & Classen, A. (2008). Evaluating formal properties of feature diagram languages. Software, IET, 2(3), 281–302. ID 2.Hindawi, M., Morel, L., Aubry, R., & Sourrouille, J.-L. (2009). Description and Implementation of a UML Style Guide (Vol. 5421, pp. 291–302). Berlin: Springer.Hoang, D. (2012). Current limitations of mdd and its implications @ONLINE.Hodges, W. (2013). Model theory Zalta, E.N. (Ed.) The Stanford Encyclopedia of Philosophy. Fall 2013 edition.Hutchinson, J., Rouncefield, M., & Whittle, J. (2011a). Model-driven engineering practices in industry. In Proceedings of the 33rd International Conference on Software Engineering, ICSE’11 (pp. 633–642). New York: ACM.Hutchinson, J., Whittle, J., & Rouncefield, M. (2014). Model-driven engineering practices in industry: social, organizational and managerial factors that lead to success or failure. Science of Computer Programming, 89 Part B(0), 144–161. Special issue on Success Stories in Model Driven Engineering.Hutchinson, J., Whittle, J., Rouncefield, M., & Kristoffersen, S. (2011b). Empirical assessment of mde in industry. In Proceedings of the 33rd International Conference on Software Engineering, ICSE’11 (pp. 471–480). New York: ACM.Igarza, I.M.H., Boada, D.H.G., & Valdés, A.P. (2012). Una introducción al desarrollo de software dirigido por modelos. Serie Científica, 5(3).ISO/IEC (2001). ISO/IEC 9126. Software engineering—Product quality. ISO/IEC.Izurieta, C., Rojas, G., & Griffith, I. (2015). Preemptive management of model driven technical debt for improving software quality. In Proceedings of the 11th International ACM SIGSOFT Conference on Quality of Software Architectures, QoSA’15 (pp. 31–36). New York: ACM.Jalali, S., & Wohlin, C. (2012). Systematic literature studies: Database searches vs. backward snowballing. In Proceedings of the ACM-IEEE International Symposium on Empirical Software Engineering and Measurement, ESEM’12 (pp. 29–38). New York: ACM.Kahraman, G., & Bilgen, S. (2013). A framework for qualitative assessment of domain-specific languages. Software & Systems Modeling, 1–22.Kessentini, M., Langer, P., & Wimmer, M. (2013). Searching models, modeling search: On the synergies of sbse and mde (pp. 51–54).Kitchenham, B., & Charters, S. (2007). Guidelines for performing Systematic Literature Reviews in Software Engineering. Technical Report EBSE 2007-001, Keele University and Durham University Joint Report.Kitchenham, B., Pfleeger, S., Pickard, L., Jones, P., Hoaglin, D., El Emam, K., & Rosenberg, J. (2002). Preliminary guidelines for empirical research in software engineering. IEEE Transactions on Software Engineering, 28(8), 721–734.Klinke, M. (2008). Do you use mda/mdd/mdsd, any kind of model-driven approach? Will it be the future?Köhnlein, J. (2013). Eclipse diagram editors from a user’s perspective.Kolovos, D.S., Paige, R.F., & Polack, F.A. (2008). The grand challenge of scalability for model driven engineering. In Models in Software Engineering (pp. 48–53): Springer.Kolovos, D.S., Rose, L.M., Matragkas, N., Paige, R.F., Guerra, E., Cuadrado, J.S., De Lara, J., Ráth, I., Varró, D., Tisi, M., & Cabot, J. (2013). A research roadmap towards achieving scalability in model driven engineering. In Proceedings of the Workshop on Scalability in Model Driven Engineering, BigMDE’13 (pp. 2:1–2:10). New York: ACM.Krill, P. (2016). Uml to be ejected from microsoft visual studio (infoworld).Krogstie, J. (2012a). Model-based development and evolution of information systems: a quality approach, Springer Publishing Company, Incorporated.Krogstie, J. (2012b). Quality of modelling languages, (pp. 249–280). London: Springer.Krogstie, J. (2012c). Quality of models, (pp. 205–247). London: Springer.Krogstie, J. (2012d). Specialisations of SEQUAL, (pp. 281–326). London: Springer.Krogstie, J., Lindland, O.I., & Sindre, G. (1995). Defining quality aspects for conceptual models. In Proceedings of the IFIP International Working Conference on Information System Concepts: Towards a Consolidation of Views (pp. 216–231). London: Chapman & Hall, Ltd.Kruchten, P. (2000). The rational unified process: an introduction, 2nd edn. Boston: Addison-Wesley Longman Publishing Co., Inc.Kruchten, P., Nord, R., & Ozkaya, I. (2012). Technical debt: from metaphor to theory and practice. Software, IEEE, 29(6), 18–21.Kulkarni, V., Reddy, S., & Rajbhoj, A. (2010). Scaling up model driven engineering – experience and lessons learnt. In Petriu, D., Rouquette, N., & Haugen, y. (Eds.) Model Driven Engineering Languages and Systems, volume 6395 of Lecture Notes in Computer Science (pp. 331–345). Berlin, Heidelberg: Springer.Laguna, M.A., & Marqués, J.M. (2010). Uml support for designing software product lines: the package merge mechanism, 16(17), 2313–2332.Lange, C. (2007a). Model size matters. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 4364 LNCS:211–216. cited By (since 1996)1.Lange, C., & Chaudron, M. (2005). Managing Model Quality in UML-Based Software Development. In 13th IEEE International Workshop on Technology and Engineering Practice, 2005 (pp. 7–16).Lange, C., Chaudron, M.R.V., Muskens, J., Somers, L.J., & Dortmans, H.M. (2003). An empirical investigation in quantifying inconsistency and incompleteness of uml designs. In Incompleteness of UML Designs, Proceedings Workshop on Consistency Problems in UML-based Software Development, 6th International Conference on Unified Modeling Language, UML, 2003.Lange, C., DuBois, B., Chaudron, M., & Demeyer, S. (2006). An experimental investigation of uml modeling conventions. In Nierstrasz, O., Whittle, J., Harel, D., & Reggio, G. (Eds.) Model Driven Engineering Languages and Systems, volume 4199 of Lecture Notes in Computer Science (pp. 27–41). Berlin, Heidelberg: Springer.Lange, C.F.J., & Chaudron, M.R.V. (2006). Effe

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. Available online at http://www.internetworkingindonesia.org/Issues/Vol9-No1-2017/iij_vol9_no1_2017_eruvankai.pdf.Fleisch, Elgar; Weinberger, Markus; Wortmann, Ass Felix; Wortmann, Felix (2014): Geschäftsmodelle im Internet der Dinge. In HMD Praxis der Wirtschaftsinformatik 51 (6), pp. 812-826. https://doi.org/10.1365/s40702-014-0083-3Geissbauer, Reinhard; Schrauf Stefan; Koch Volkmar; Kuge Simon (2014): Industry 4.0 : Opportunities and Challenges of the Industrial Internet. Edited by Pricewaterhousecooper Aktiengesellschaft. München.Gibbons, Paul M.; Burgess, Stuart C. (2010): Introducing OEE as a measure of lean Six Sigma capability. In Lean Six Sigma Journal 1 (2), pp. 134-156. https://doi.org/10.1108/20401461011049511Grebe, Michael; Rüssmann, Michael,Leyh Michael; Franke, Roman (2019): HOW DIGITAL CHAMPIONS INVEST. Edited by Boston Consulting Group. München. Available online at http://image-src.bcg.com/Images/BCG-How-Digital-Champions-Invest-June-2019_tcm15-223286.pdf, checked on 1/6/2020.Gürdür, Didem; El-khoury, Jad; Törngren, Martin (2019): Digitalizing Swedish industry. What is next? In Computers in Industry 105 (1), pp. 153-163. https://doi.org/10.1016/j.compind.2018.12.011Henssen, Robert; Schleipen, Miriam (2014): Interoperability between OPC UA and AutomationML. In Procedia CIRP 25, pp. 297-304. https://doi.org/10.1016/j.procir.2014.10.042Hopp, Wallace J.; Spearman, Mark L. (2004): To Pull or Not to Pull. What Is the Question? In Manufacturing & Ser-vice Operations Management 6 (2), pp. 133-148. https://doi.org/10.1287/msom.1030.0028Imtiaz, Jahanzaib; Jasperneite, Jürgen (2013): Scalability of OPC-UA down to the chip level enables "Internet of Things". In IEEE intelligent Systems, pp. 500-505. https://doi.org/10.1109/INDIN.2013.6622935Industrial Value Chain Initiative (2018): Industrial Value Chain Reference Architecture -Next. 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. In Robert Obermaier (Ed.): Handbuch In-dustrie 4.0 und Digitale Transformation. Betriebswirtschaftliche, technische und rechtliche Herausforderungen. 1st ed. 2019. Wiesbaden: Springer Fachmedien Wiesbaden, pp. 529-564. https://doi.org/10.1007/978-3-658-24576-4_22Osterwalder, Alexander (2004): The business model ontology: A proposition in a design science approach. Disserti-ation. Universite de Lausanne, Lausanne. Ecole des Hautes Etudes Commerciales. Available online at https://doc.rero.ch/record/4210/files/1_these_Osterwalder.pdf.Osterwalder, Alexander; Pigneur, Yves (2010): Business model generation: a handbook for visionaries, game changers, and challengers. Hoboken: John Wiley & Sons.Palm, Florian; Grüner, Sten; Pfrommer, Julius; Graube, Markus; Urbas, Leon (2014): open62541-der offene OPC UA Stack. In Onlinepublikation des Fraunhofer IOSB, Lehrstuhl Prozessleittechnik der RWTH Aachen; TU Dresden, Professur für Prozessleitechnik,Porter, Michael E. (2010): Wettbewerbsvorteile. Spitzenleistungen erreichen und behaupten. 7. durchgesehene Auflage Auflage. Frankfurt, New York: Campus.Porter, Michael E.; Heppelmann, James E. (2014): How smart, connected products are transforming competition. In Harvard business review 92 (11), pp. 64-88.Rachinger, Michael; Rauter, Romana; Müller, Christiana; Vorraber, Wolfgang; Schirgi, Eva (2019): Digitalization and its influence on business model innovation. In Journal of Manufacturing Technology Management 30 (8), pp. 1143-1160. https://doi.org/10.1108/JMTM-01-2018-0020Remane, Gerrit; Hanelt, Andre; Wiesboeck, Florian; Kolbe, Lutz M. (2017): Digital maturity in traditional industries - an exploratory analysis. Twenty-Fifth European Conference on Information Systems (ECIS),. Guimarães,Portugal, 2017.Rese, Mario; Meier, Horst; Gesing, Judith; Boßlau, Mario (2013): An ontology of business models for industrial prod-uct-service systems. In Yoshiki Shimomura, Koji Kimita (Eds.): The Philosopher's Stone for Sustainability. Pro-ceedings of the 4th CIRP International Conference on Industrial Product-Service Systems, Tokyo, Japan, Novem-ber 8th - 9th, 2012. Heidelberg: Springer (Lecture Notes in Production Engineering), pp. 191-196. https://doi.org/10.1007/978-3-642-32847-3_32Sauer, Olaf (2014): Information Technology for the Factory of the Future - State of the Art and Need for Action. In Procedia CIRP 25, pp. 293-296. https://doi.org/10.1016/j.procir.2014.10.041Schmenner, Roger W. (2015): The Pursuit of Productivity. In Production and Operations Management 24 (2), pp. 341-350. https://doi.org/10.1111/poms.12230Schuh, G.; Anderl, R.; Dumitrescu, R.; Hompel, M. ten; Krüger, A. (Eds.) (2020): Industrie 4.0 Maturity Index. Man-aging the Digital Transformation of Companies - UPDATE 2020 - (acatech STUDY). MUNICH: Herbert Utz Verlag.Schuh, Günther; Reuter, Christina; Hauptvogel, Annika; Dölle, Christian (2015): Hypotheses for a Theory of Produc-tion in the Context of Industrie 4.0. In : Advances in Production Technology: Springer, pp. 11-23. Available online at https://link.springer.com/10.1007/978-3-319-12304-2_2 https://doi.org/10.1007/978-3-319-12304-2_2Skilton, Mark; Gordon, Penelope; Harding, Chris (2010): Building return on investment from cloud computing. Cloud Business Artifacts Project, Cloud Computing Work Group, The Open Group. Edited by The Open Group. Burling-ton, MA.Solow, R. M. (1987): We'd better watch out. In New York Times Book Review 36.Strauss, Anselm; Corbin, Juliet (2010): Grounded theory. Grundlagen qualitativer Sozialforschung. Unveränd. Nachdr. der letzten Aufl. Weinheim: Beltz.Tantik, Erdal; Anderl, Reiner (2016): Industrie 4.0. Using Cyber-physical Systems for Value-stream Based Production Evaluation. In Procedia CIRP 57, pp. 207-212. https://doi.org/10.1016/j.procir.2016.11.036Veile, Johannes; Kiel, Daniel; Voight, Kai-Ingo; Müller, Julian Marius (2019): Lessons learned from Industry 4.0 implementation in the German manufacturing industry. In Journal of Manufacturing Technology Management (ahead-of-print). https://doi.org/10.1108/JMTM-08-2018-0270Witzel, Andreas (2000): Das problemzentrierte Interview. In Forum Qualitative Sozialforschung / Forum: Qualitative Social Research 1 (1). https://doi.org/10.1016/j.lrp.2015.04.001Ylipää, Torbjörn; Skoogh, Anders; Bokrantz, Jon; Gopalakrishnan, Maheshwaran (2017): Identification of maintenance improvement potential using OEE assessment. In International Journal of Productivity and Performance Manage-ment 66 (1), pp. 126-143. https://doi.org/10.1108/IJPPM-01-2016-0028Zennaro, Ilenia; Battini, Daria; Sgarbossa, Fabio; Persona, Alessandro; Marchi, Rosario de; van der Wiele, Ton (2018): Micro Downtime - Data Collection, Analysis and Impact on OEE in Bottling Lines The San Benedetto Case Study. In Int J Qual & Reliability Mgmt 17 (9), p. 0. https://doi.org/10.1108/IJQRM-11-2016-0202Zott, Christoph; Amit, Raphael; Massa, Lorenzo (2011): The Business model: Recent Developments and Future Re-search. In Journal of management 37 (4), pp. 1019-1042. https://doi.org/10.1177/0149206311406265Zuehlke, Detlef (2010): SmartFactory-Towards a factory-of-things. In Annual Reviews in Control 34 (1), pp. 129-138. https://doi.org/10.1016/j.arcontrol.2010.02.00

A B2B Architecture and Protocol for Researchers Cooperation

Acknowledgement: Electronic version of an article published as International Journal of Cooperative Information Systems, Volume 22, Issue 02, 2013, DOI: 10.1142/S021884301350010X © World Scientific Publishing Company http://www.worldscientific.com/Some works on the researchers cooperation's literature provide the key lines for building research networks and propose new protocols and standards for business to business (B2B) data exchange, but none of them explains how researchers should contact and the procedure to select the most appropriate partner of a research enterprise, institute or university. In this paper, we propose a B2B architecture and protocol between research entities, that uses ebXML protocol. The contacts for cooperation are established based on some defined parameters and an information retrieval system. We explain the information retrieval system, the researcher selection procedure, the XML-based protocol and the workflow of our proposal. We also show the information that has to be exchanged to contact other researchers. Several simulations demonstrate that our proposal is a feasible architecture and may be used to promote the research cooperation. The main purpose of this paper is to propose an efficient procedure for searching project partners.Lloret, J.; Tomás Gironés, J.; García Pineda, M.; Lacuesta Contreras, R. (2013). A B2B Architecture and Protocol for Researchers Cooperation. International Journal of Cooperative Information Systems. 22(2):1-27. doi:10.1142/S021884301350010XS127222B. Wellman and S. D. Berkowitz, Social Structures: A Network Approach (Cambridge University Press, Cambridge, 1988) pp. 19–61.Wasserman, S., & Faust, K. (1994). Social Network Analysis. doi:10.1017/cbo9780511815478Wellman, B., Salaff, J., Dimitrova, D., Garton, L., Gulia, M., & Haythornthwaite, C. (1996). Computer Networks as Social Networks: Collaborative Work, Telework, and Virtual Community. Annual Review of Sociology, 22(1), 213-238. doi:10.1146/annurev.soc.22.1.213Fulk, J., & Steinfield, C. (1990). Organizations and Communication Technology. doi:10.4135/9781483325385B. Wellman and M. Gulia, Networks in the Global Village (Westview Press, Boulder, CO, 1997) pp. 331–367.Marsden, P. V., & Campbell, K. E. (1984). Measuring Tie Strength. Social Forces, 63(2), 482-501. doi:10.1093/sf/63.2.482Wellman, B., & Wortley, S. (1990). Different Strokes from Different Folks: Community Ties and Social Support. American Journal of Sociology, 96(3), 558-588. doi:10.1086/229572Adamic, L., & Adar, E. (2005). How to search a social network. Social Networks, 27(3), 187-203. doi:10.1016/j.socnet.2005.01.007Ebel, H., Mielsch, L.-I., & Bornholdt, S. (2002). Scale-free topology of e-mail networks. Physical Review E, 66(3). doi:10.1103/physreve.66.035103Jung, J.-Y., Kim, H., & Kang, S.-H. (2006). Standards-based approaches to B2B workflow integration. Computers & Industrial Engineering, 51(2), 321-334. doi:10.1016/j.cie.2006.02.011Lloret, J., Palau, C., Boronat, F., & Tomas, J. (2008). Improving networks using group-based topologies. Computer Communications, 31(14), 3438-3450. doi:10.1016/j.comcom.2008.05.030Lloret, J., Garcia, M., Tomás, J., & Boronat, F. (2008). GBP-WAHSN: A Group-Based Protocol for Large Wireless Ad Hoc and Sensor Networks. Journal of Computer Science and Technology, 23(3), 461-480. doi:10.1007/s11390-008-9147-6Lloret, J., Garcia, M., Bri, D., & Diaz, J. R. (2009). Study and performance of a group-based Content Delivery Network. Journal of Network and Computer Applications, 32(5), 991-999. doi:10.1016/j.jnca.2009.03.008Lloret, J., Garcia, M., Tomas, J., & Sendra, S. (2010). A group-based architecture for grids. Telecommunication Systems, 46(2), 117-133. doi:10.1007/s11235-010-9279-1Lin, T.-C., & Huang, C.-C. (2010). Withholding effort in knowledge contribution: The role of social exchange and social cognitive on project teams. Information & Management, 47(3), 188-196. doi:10.1016/j.im.2010.02.001Maron, M. E., & Kuhns, J. L. (1960). On Relevance, Probabilistic Indexing and Information Retrieval. Journal of the ACM, 7(3), 216-244. doi:10.1145/321033.321035Tomás, J., Lloret, J., & Casacuberta, F. (2005). Phrase-Based Alignment Models for Statistical Machine Translation. Lecture Notes in Computer Science, 605-613. doi:10.1007/11492542_74Turel, O., & Zhang, Y. (Jenny). (2011). Should I e-collaborate with this group? A multilevel model of usage intentions. Information & Management, 48(1), 62-68. doi:10.1016/j.im.2010.12.004Okuda, T., Tanaka, E., & Kasai, T. (1976). A Method for the Correction of Garbled Words Based on the Levenshtein Metric. IEEE Transactions on Computers, C-25(2), 172-178. doi:10.1109/tc.1976.500923

Interoperability, Trust Based Information Sharing Protocol and Security: Digital Government Key Issues

Improved interoperability between public and private organizations is of key significance to make digital government newest triumphant. Digital Government interoperability, information sharing protocol and security are measured the key issue for achieving a refined stage of digital government. Flawless interoperability is essential to share the information between diverse and merely dispersed organisations in several network environments by using computer based tools. Digital government must ensure security for its information systems, including computers and networks for providing better service to the citizens. Governments around the world are increasingly revolving to information sharing and integration for solving problems in programs and policy areas. Evils of global worry such as syndrome discovery and manage, terror campaign, immigration and border control, prohibited drug trafficking, and more demand information sharing, harmonization and cooperation amid government agencies within a country and across national borders. A number of daunting challenges survive to the progress of an efficient information sharing protocol. A secure and trusted information-sharing protocol is required to enable users to interact and share information easily and perfectly across many diverse networks and databases globally.Comment: 20 page

Purposive Teaching Styles for Transdisciplinary AEC Education: A Diagnostic Learning Styles Questionnaire

With the progressive globalisation trend within the Architecture, Engineering, and Construction (AEC) industry, transdisciplinary education and training is widely acknowledged as being one of the key factors for leveraging AEC organisational success. Conventional education and training delivery approaches within AEC therefore need a paradigm shift in order to be able to address the emerging challenges of global practices. This study focuses on the use of Personalised Learning Environments (PLEs) to specifically address learners’ needs and preferences (learning styles) within managed Virtual Learning Environments (VLEs). This research posits that learners can learn better (and be more readily engaged in managed learning environments) with a bespoke PLE, in which the deployment of teaching and learning material is augmented towards their individual needs. In this respect, there is an exigent need for the Higher Educational Institutions (HEIs) to envelop these new approaches into their organisational learning strategy. However, part of this process requires decision-makers to fully understand the core nuances and interdependencies of functions and processes within the organisation, along with Critical Success Factors (CSFs) and barriers. This paper presents findings from the development of a holistic conceptual Diagnostic Learning Styles Questionnaire (DLSQ) Framework, comprised of six interrelated dependencies (i.e. Business Strategy, Pedagogy, Process, Resources, Systems Development, and Evaluation). These dependencies influence pedagogical effectiveness. These finding contribute additional understanding to the intrinsic nature of pedagogy in leveraging transdisciplinary AEC training within organisations (to improve learner effectiveness). This framework can help organisations augment and align their strategic priorities to learner-specific traits

Performance factors for successful business incubators in Indonesian public universities

Measuring the performance of business processes is already a main concern for both faculty and enterprise players, since organizations are motivated to reach the productivity stage. Employing a performance achievement framework for the relationship between business incubator success factors will guarantee connection with commercial schemes, which support a high level of performance indicators in successful business incubator models. This research employs a quantitative approach, with the data analyzed using the IBM SPSS version 23 and Smart PLS version 3 statistical software packages. Employing a sample of 95 incubator managers from 19 universities which geographically located in Indonesia, it is shown that the image of business incubator factors has a positive effect on incubator performance. The study investigates the relationship between incubator performance and business incubator success factors in Indonesia. It was found that IT, as part of the business incubators’ facets/abilities, partially supports their performance; that the entry criteria directly support the performance of the incubators; that mentoring networks also support the performance, with good infrastructure systems as a moderating factor; that funding supports the performance of business incubators, also with good infrastructure systems as a moderating factor; and that university regulations and government support and protection enhance the performance of business incubators, with credits and rewards as a moderating factor. In addition, a variety of indicators from the local context affiliate positively to promote a community that highlighted the incubators’ strategies.N/

Modelling Fresh Strawberry Supply "From-Farm-to-Fork" as a Complex Adaptive Network

 The purpose of this study is to model and thereby enable simulation of the complete business entity of fresh food supply. A case narrative of fresh strawberry supply provides basis for this modelling. Lamming et al. (2000) point to the importance of discerning industry-specific product features (or particularities) regarding managing supply networks when discussing elements in "an initial classification of a supply network" while Fisher (1997) and Christopher et al. (2006, 2009) point to the lack of adopting SCM models to variations in products and market types as an important source of SCM failure. In this study we have chosen to move along a research path towards developing an adapted approach to model end-to-end fresh food supply influenced by a combination of SCM, system dynamics and complex adaptive network thinking...