Strategic Management of IT Practices in Tourism for Operation and Service Enhancement.

The information technology infrastructure library (ITIL) standard describes processes that should be implemented in Information Technology (IT) departments for proper operations management, which includes human resources management, economic management, and strategic management, among others. This should be especially considered in the business management of industries with no relation to information technologies (IT), such as tourism and hospitality companies. This work aims to present a method to establish the order of adoption of the IT management processes in companies that belong to the tourism industry. We conducted a survey to obtain the necessary data and developed a methodology that is based on an optimization procedure. This procedure generates the optimal sequence of IT tasks to adopt in a generic small company in the tourism industry. The methodology was then applied to a representative tourism company. Through the sequence obtained, it is shown that it is necessary to implement operative processes, and subsequently, strategic processes. A comparative study was developed to find the differences with other authors’ proposals. The most important result we found was the possibility of efficient use of organizations’ information to build an optimized list of IT procedures to improve their administration. The obtained list of processes is specific for each organization, and not dependent on the solutions offered by other authors who proposed a general or underoptimal list of processes.2022-2

A Methodology to Sequence the Service Management Processes in IT Departments: Application to theTourism Industry

One of the key elements to consider in business management is the management of IT (In- formation Technology) departments by implementing processes as described in the ITIL (Information Technology Infrastructure Library) standard. This is particularly important in industries that are not directly related to ICT (Information and Communication Technologies), such as the tourism industry. In this paper, we present a methodology to sequence the implementation of the ITIL processes in any company to support its development. The methodology is based on an optimization algorithm and the information extracted from a survey. The optimal sequence is built from this information and from the information of the restrictions imposed by the company that implements the ITIL processes. We applied the methodology to a company in the tourism industry. The sequence obtained shows the need to implement operative processes (initial positions in the sequence), and afterwards strategic processes (final positions in the sequence). A comparison with other authors’ proposals shows differences in the order of processes proposed by this methodology. The main conclusion is that it is possible to use the information of companies to efficiently generate an optimal sequence of ITIL processes which enhances their management; this sequence is unique for every company that wants to implement ITIL in the tourism industry, and it is independent from the proposals of other authors who designed generic/non-optimal sequences.2021-2

Data driven decision support systems as a critical success factor for IT-Governance: an application in the financial sector

IT-Governance has a major impact not only on IT management but also and foremost in the Enterprises performance and control. Business uses IT agility, flexibility and innovation to pursue its objectives and to sustain its strategy. However being it more critical to the business, compliance forces IT on the opposite way of predictability, stability and regulations. Adding the current economical environment and the fact that most of the times IT departments are considered cost centres, IT-Governance decisions become more important and critical. Current IT-Governance research and practise is mainly based on management techniques and principles, leaving a gap for the contribution of information systems to IT-Governance enhancement. This research intends to provide an answer to IT-Governance requirements using Data Driven Decision Support Systems based on dimensional models. This seems a key factor to improve the IT-Governance decision making process. To address this research opportunity we have considered IT-Governance research (Peter Weill), best practises (ITIL), Body of Knowledge (PMBOK) and frameworks (COBIT). Key IT-Governance processes (Change Management, Incident Management, Project Development and Service Desk Management) were studied and key process stakeholders were interviewed. Based on the facts gathered, dimensional models (data marts) were modelled and developed to answer to key improvement requirements on each IT-Governance process. A Unified Dimensional Model (IT-Governance Data warehouse) was materialized. To assess the Unified Dimensional Model, the model was applied in a bank in real working conditions. The resulting model implementation was them assessed against Peter Weill‘s Governance IT Principles.Assessment results revealed that the model satisfies all the IT-Governance Principles. The research project enables to conclude that the success of IT-Governance implementation may be fostered by Data Driven Decision Support Systems implemented using Unified Dimensional Model concepts and based on best practises, frameworks and body of knowledge that enable process oriented, data driven decision support

Information technology service management: an experimental approach towards IT service prediction

Dissertation presented to obtain a Masters degree in Computer ScienceSoftware development and software quality improvement have been strong topics for discussion in the last decades. Software Engineering has always been concerned with theories and best practices to develop software for large-scale usage. However, most times those theories are not validated in real live environments. Therefore, the need for experiments is immense. The incidents database can be an important asset for software engineering teams. If they learn from past experience in service management, then they will be able to shift from a reactive approach to a more proactive one. The main goal of this dissertation is shedding some light on the influential factors that affect incidents lifecycle, from creation to its closure, and also to investigate to what accuracy the ARIMA models are a valid approach to model and predict not only the ITIL incident management process, but also other ITIL processes and services in general. The dissertation presented herein is on the crossroads of Empirical Software Engineering and of the emerging area of Services Science. It describes an experiment conducted upon a sample of incident reports, recorded during the operation of several hundred commercial software products, over a period of three years (2005-2007), on six countries in Europe and Latin America. The incidents were reported by customers of a large independent software vendor. The primary goal of an Incident Management process is to restore normal service operation as quickly as possible and minimize the adverse impact on business operations, thus ensuring that the best possible levels of service quality and availability are maintained. As a result of this, a software company can make use of a good incident management process to improve several areas of their business, particularly product development, product support, the relation with its customers and their positioning in the marketplace. The underlying research questions refer to the validation of which are the influencing factors affecting the incidents management lifecycle, and also aims at finding the existence of patterns and/or trends in incident creation and resolution based on a time series approach. Additionally, it presents the estimation, evaluation and validation of several ARIMA models created with the purpose of forecasting upon incident resolution based on incident creation historic data. Understanding causal-relationships and patterns on incident management can help software development organizations on optimizing their support processes and in allocating the adequate resources; people and budget

FIN-DM: finantsteenuste andmekaeve protsessi mudel

Andmekaeve hõlmab reeglite kogumit, protsesse ja algoritme, mis võimaldavad ettevõtetel iga päev kogutud andmetest rakendatavaid teadmisi ammutades suurendada tulusid, vähendada kulusid, optimeerida tooteid ja kliendisuhteid ning saavutada teisi eesmärke. Andmekaeves ja -analüütikas on vaja hästi määratletud metoodikat ja protsesse. Saadaval on mitu andmekaeve ja -analüütika standardset protsessimudelit. Kõige märkimisväärsem ja laialdaselt kasutusele võetud standardmudel on CRISP-DM. Tegu on tegevusalast sõltumatu protsessimudeliga, mida kohandatakse sageli sektorite erinõuetega. CRISP-DMi tegevusalast lähtuvaid kohandusi on pakutud mitmes valdkonnas, kaasa arvatud meditsiini-, haridus-, tööstus-, tarkvaraarendus- ja logistikavaldkonnas. Seni pole aga mudelit kohandatud finantsteenuste sektoris, millel on omad valdkonnapõhised erinõuded. Doktoritöös käsitletakse seda lünka finantsteenuste sektoripõhise andmekaeveprotsessi (FIN-DM) kavandamise, arendamise ja hindamise kaudu. Samuti uuritakse, kuidas kasutatakse andmekaeve standardprotsesse eri tegevussektorites ja finantsteenustes. Uurimise käigus tuvastati mitu tavapärase raamistiku kohandamise stsenaariumit. Lisaks ilmnes, et need meetodid ei keskendu piisavalt sellele, kuidas muuta andmekaevemudelid tarkvaratoodeteks, mida saab integreerida organisatsioonide IT-arhitektuuri ja äriprotsessi. Peamised finantsteenuste valdkonnas tuvastatud kohandamisstsenaariumid olid seotud andmekaeve tehnoloogiakesksete (skaleeritavus), ärikesksete (tegutsemisvõime) ja inimkesksete (diskrimineeriva mõju leevendus) aspektidega. Seejärel korraldati tegelikus finantsteenuste organisatsioonis juhtumiuuring, mis paljastas 18 tajutavat puudujääki CRISP- DMi protsessis. Uuringu andmete ja tulemuste abil esitatakse doktoritöös finantsvaldkonnale kohandatud CRISP-DM nimega FIN-DM ehk finantssektori andmekaeve protsess (Financial Industry Process for Data Mining). FIN-DM laiendab CRISP-DMi nii, et see toetab privaatsust säilitavat andmekaevet, ohjab tehisintellekti eetilisi ohte, täidab riskijuhtimisnõudeid ja hõlmab kvaliteedi tagamist kui osa andmekaeve elutsüklisData mining is a set of rules, processes, and algorithms that allow companies to increase revenues, reduce costs, optimize products and customer relationships, and achieve other business goals, by extracting actionable insights from the data they collect on a day-to-day basis. Data mining and analytics projects require well-defined methodology and processes. Several standard process models for conducting data mining and analytics projects are available. Among them, the most notable and widely adopted standard model is CRISP-DM. It is industry-agnostic and often is adapted to meet sector-specific requirements. Industry- specific adaptations of CRISP-DM have been proposed across several domains, including healthcare, education, industrial and software engineering, logistics, etc. However, until now, there is no existing adaptation of CRISP-DM for the financial services industry, which has its own set of domain-specific requirements. This PhD Thesis addresses this gap by designing, developing, and evaluating a sector-specific data mining process for financial services (FIN-DM). The PhD thesis investigates how standard data mining processes are used across various industry sectors and in financial services. The examination identified number of adaptations scenarios of traditional frameworks. It also suggested that these approaches do not pay sufficient attention to turning data mining models into software products integrated into the organizations' IT architectures and business processes. In the financial services domain, the main discovered adaptation scenarios concerned technology-centric aspects (scalability), business-centric aspects (actionability), and human-centric aspects (mitigating discriminatory effects) of data mining. Next, an examination by means of a case study in the actual financial services organization revealed 18 perceived gaps in the CRISP-DM process. Using the data and results from these studies, the PhD thesis outlines an adaptation of CRISP-DM for the financial sector, named the Financial Industry Process for Data Mining (FIN-DM). FIN-DM extends CRISP-DM to support privacy-compliant data mining, to tackle AI ethics risks, to fulfill risk management requirements, and to embed quality assurance as part of the data mining life-cyclehttps://www.ester.ee/record=b547227

ERP implementation methodologies and frameworks: a literature review

Enterprise Resource Planning (ERP) implementation is a complex and vibrant process, one that involves a combination of technological and organizational interactions. Often an ERP implementation project is the single largest IT project that an organization has ever launched and requires a mutual fit of system and organization. Also the concept of an ERP implementation supporting business processes across many different departments is not a generic, rigid and uniform concept and depends on variety of factors. As a result, the issues addressing the ERP implementation process have been one of the major concerns in industry. Therefore ERP implementation receives attention from practitioners and scholars and both, business as well as academic literature is abundant and not always very conclusive or coherent. However, research on ERP systems so far has been mainly focused on diffusion, use and impact issues. Less attention has been given to the methods used during the configuration and the implementation of ERP systems, even though they are commonly used in practice, they still remain largely unexplored and undocumented in Information Systems research. So, the academic relevance of this research is the contribution to the existing body of scientific knowledge. An annotated brief literature review is done in order to evaluate the current state of the existing academic literature. The purpose is to present a systematic overview of relevant ERP implementation methodologies and frameworks as a desire for achieving a better taxonomy of ERP implementation methodologies. This paper is useful to researchers who are interested in ERP implementation methodologies and frameworks. Results will serve as an input for a classification of the existing ERP implementation methodologies and frameworks. Also, this paper aims also at the professional ERP community involved in the process of ERP implementation by promoting a better understanding of ERP implementation methodologies and frameworks, its variety and history