Transformation Towards Cloud Computing Minitrack
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To survive the multidimensional changes in markets related to frequent evolution of national and international regulations, consumers’ behavior, information and communications technologies (ICT) and the globalization phenomenon, companies have constantly to reinvent themselves. They seek to transform their information systems in order to integrate quickly the technological and sociological mutations such as cloud computing, big data or mobility (Hashem & al. 2015). These frequent changes and their induced reconfigurations are accelerating. In this new era of Internet of Everything (IoE), managers are increasingly aware of the necessity for transformation and rapid innovation.
In this context of disruptive innovations, such organizational transformations involve deep changes of business processes. It is therefore essential for these companies to find transformation models enabling them to lower costs and drive transitions, without hindering their development and degrading their quality of service, the customer satisfaction, or the level of security (Tiers & al 2013). This minitrack welcome research that investigates this transformation by exploring a large number of different companies’ situations. Cloud computing provides the ability to conduct ambitious transformation programs currently hampered by the need to overcome huge investments in Information Systems.
Minitrack Chair:
Mohamed Makhlouf
Kedge Business School
Email: mohamed.makhlouf@kedgebs.com
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Recent Submissions
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ItemLongitudinal Study on the Expectations of Cloud Computing Benefits and an Integrative Multilevel Model for Understanding Cloud Computing Performance( 2017-01-04)Cloud computing, a term introduced ten years ago, has proliferated rapidly both in developed and developing economies. Benefit expectations have impacted the rapid usage increase of this technology. We investigated with a five-year longitudinal survey changes in the expectations regarding cloud computing. We also crafted an integrated multilevel model to understand how cloud expectations and cloud readiness influence cloud computing deployment and performance combined with five IT business value (ITBV) factors. We tested empirically the crafted hypotheses and the research model using survey data collected from approximately 200+200 randomly selected business and IT executives in 2014 and 2015. Empirical results confirmed that our research model explained approximately one half of cloud computing performance for both years.
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ItemCustomer Relationship Management in a Public Cloud environment – Key influencing factors for European enterprises( 2017-01-04)Customer Relationship Management is crucial influencing factor for competitiveness in saturated markets. Public cloud-computing services for customer-relationship management provide many benefits. However, their usage in Europe is reluctant. Our research identifies several core and sub-influence factors and reveals how strong they are. Enterprises strive for covering risks in terms of safety and security. Further important influencing factors are functional completeness and integration into the existing environment. Our research provides new knowledge of the use of public cloud services in general and in particular for the use of customer relationship in a public cloud environment.
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ItemAnti-Pattern Specification and Correction Recommendations for Semantic Cloud Services( 2017-01-04)Given the economic and technological advantages \ they offer, cloud services are increasing being offered by \ several cloud providers. However, the lack of standardized \ descriptions of cloud services hinders their discovery. \ In an effort to standardize cloud service descriptions, \ several works propose to use ontologies. Nevertheless, \ the adoption of any of the proposed ontologies \ calls for an evaluation to show its efficiency in cloud \ service discovery. Indeed, the existing cloud providers \ describe, their similar offered services in different ways. \ Thus, various existing works aim at standardizing the \ representation of cloud computing services by proposing \ ontologies. However, since the existing proposals \ were not evaluated, they might be less adopted and considered. \ Indeed, the ontology evaluation has a direct impact \ on its understandability and reusability. In this paper, \ we propose an evaluation approach to validate our \ proposed Cloud Service Ontology (CSO), to guarantee \ an adequate cloud service discovery. To this end, this \ paper has a three-fold contribution. First, we specify a \ set of patterns and anti-patterns in order to evaluate our \ CSO. Second, we define an anti-pattern detection algorithm \ based on SPARQL queries which provides a set of \ correction recommendations to help ontologists revise \ their ontology. Finally, tests were conducted in relation \ to: (i) the algorithm efficiency and (ii) anti-pattern detection \ of design anomalies as well as taxonomic and \ domain errors within CSO.
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