Methodologies and Technologies for Networked Enterprises

The technological dimension and the organizational dimension are the two faces of Information Technology (IT) revolution shaping the life of large and small firms in last 50 years, from the first adoption of mainframe and reusable software to the recent integration of hardware and software technologies within Internet of Things. Over the last few decades, a number of scholars coming from computer science and from organization theory shared a deep confidence on the magic power of networks, especially of technological networks, more and more fast and reliable, and of organizational networks, more and more effective in balancing cooperation and competition among firms. Coherently with the aim of this volume, in this chapter we assume a more critical perspective deriving from the joint analysis of organizational challenges and of technological opportunities for networked enterprises aimed at developing new products/services. The management of innovation within networked enterprises requires a strategic approach to many dimensions. In this chapter we apply at open-closed trade-off the model developed by Pisano & Verganti in the paper Which kind of Collaboration is Right for You published by Harvard Business Review in December 2008. In the Chapter 4 we will focus the strategic models aimed at managing the new product development within the networked enterprise modelled as a design discourse. In the Chapter 5 authors will propose a third strategic perspective, proposing the application of a platform strategy in order to promote the a doption of advanced network infrastructures by Small and Medium Enterprises (SMEs).

[1]  Diego Calvanese,et al.  The Description Logic Handbook: Theory, Implementation, and Applications , 2003, Description Logic Handbook.

[2]  Das Amrita,et al.  Mining Association Rules between Sets of Items in Large Databases , 2013 .

[3]  Alberto Sillitti,et al.  A case-study on using an Automated In-process Software Engineering Measurement and Analysis system in an industrial environment , 2009, 2009 IEEE 31st International Conference on Software Engineering.

[4]  Adwait Ratnaparkhi,et al.  A maximum entropy model for parsing , 1994, ICSLP.

[5]  Hajo A. Reijers,et al.  Discovering Social Networks from Event Logs , 2005, Computer Supported Cooperative Work (CSCW).

[6]  A. Sillitti,et al.  A Perspective on Non Invasive Software Management , 2006, 2006 IEEE Instrumentation and Measurement Technology Conference Proceedings.

[7]  Ian G. MacDonald,et al.  Information Engineering , 2019, Information Systems Design Methodologies: Improving the Practice.

[8]  Douglas M. Hawkins Identification of Outliers , 1980, Monographs on Applied Probability and Statistics.

[9]  Ralph Kimball,et al.  The Data Warehouse Lifecycle Toolkit , 2009 .

[10]  D. Edwards Data Mining: Concepts, Models, Methods, and Algorithms , 2003 .

[11]  Dan Klein,et al.  Feature-Rich Part-of-Speech Tagging with a Cyclic Dependency Network , 2003, NAACL.

[12]  Enrico Motta,et al.  Knowledge Extraction by Using an Ontology Based Annotation Tool , 2001, Semannot@K-CAP 2001.

[13]  L. Rabiner,et al.  An introduction to hidden Markov models , 1986, IEEE ASSP Magazine.

[14]  Wil M. P. van der Aalst,et al.  Trace Clustering in Process Mining , 2008, Business Process Management Workshops.

[15]  Lluís Padró,et al.  FreeLing 1.3: Syntactic and semantic services in an open-source NLP library , 2006, LREC.

[16]  Andrew McCallum,et al.  Maximum Entropy Markov Models for Information Extraction and Segmentation , 2000, ICML.

[17]  Adwait Ratnaparkhi,et al.  A Simple Introduction to Maximum Entropy Models for Natural Language Processing , 1997 .

[18]  Wil M. P. van der Aalst,et al.  Rediscovering workflow models from event-based data using little thumb , 2003, Integr. Comput. Aided Eng..

[19]  Stuart M. Shieber The design of a computer language for linguistic information , 1984 .

[20]  Jonathan D. Cryer,et al.  Time Series Analysis , 1986 .

[21]  Stuart M. Shieber,et al.  An Introduction to Unification-Based Approaches to Grammar , 1986, CSLI Lecture Notes.

[22]  Dan Klein,et al.  Fast Exact Inference with a Factored Model for Natural Language Parsing , 2002, NIPS.

[23]  H. Chertkow,et al.  Semantic memory , 2002, Current neurology and neuroscience reports.

[24]  Alberto Sillitti,et al.  Collecting, integrating and analyzing software metrics and personal software process data , 2003, 2003 Proceedings 29th Euromicro Conference.

[25]  Matteo Golfarelli,et al.  Data Warehouse Design: Modern Principles and Methodologies , 2009 .

[26]  John A. Hartigan,et al.  Clustering Algorithms , 1975 .

[27]  Christopher D. Manning,et al.  Stanford typed dependencies manual , 2010 .

[28]  Gerard Salton,et al.  A vector space model for automatic indexing , 1975, CACM.

[29]  Tat-Seng Chua,et al.  A Public Reference Implementation of the RAP Anaphora Resolution Algorithm , 2004, LREC.