Machine Learning in IT Service Management

Zuev, Dmitry; Kalistratov, Alexey; Zuev, Andrey

doi:10.1016/j.procs.2018.11.063

Cited by 19 publications

(11 citation statements)

References 4 publications

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“…The finding indicates that in-house has a strong customer focus, always interested to resolve users IT problems; however, the limitation is that they do not have control over the process or activity to deliver the service to the customer. This finding is consistent with the literature finding that the time of incidents' resolution is the key performance indicator for IT service management (Zuev, Kalistratov & Zuev 2018). This is also supported by the following statement by participant I:…”

Section: Reliabilitysupporting

confidence: 91%

The impact of outsourcing information technology services on business operations

Mtsweni

Mokwena

Moeti

2021

SA Journal of Information Management

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Background: Organisations outsource Information Technology (IT) services in order to keep up with the IT evolution and to remain competitive. Although the IT operations department is responsible to manage service provider service quality, they are not in a position to evaluate IT services performance because of the loss of control and capability in the IT environment.Objectives: This article investigated the impact of outsourcing in-house IT services on the performance of IT operations and how it affects the performance of the organisation.Methods: The qualitative approach was used in this research. Data was collected using structured interviews and were analysed using thematic analysis.Results: Outsourcing of IT services was found to have negative and positive impact on the organisation. Knowledge of the operating environment proved to be significant in the provision of relevant services that add value to the organisation. The results of the analysis revealed that in-house IT and the quality of IT services provided have a direct impact on the performance of the organisation.Conclusion: The study demonstrated that outsourcing IT services impacts the quality and the performance of the organisation positively and negatively. The study recommended that in-house IT and outsource service providers need to collaborate to ensure smooth service delivery, process alignment and also to equip in-house IT with skills to handle first-line support.

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Section: Reliabilitysupporting

confidence: 91%

The impact of outsourcing information technology services on business operations

Mtsweni

Mokwena

Moeti

2021

SA Journal of Information Management

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“…The service sector contributes to the key macroeconomic indicators of the world economy development, produces the largest share of global GDP, leads in the total employment rate, and creates sustainable opportunities for equality and social wellbeing. Currently, the growth of the service sector is driven by digital transformation, the growing penetration rate of Internet and mobile technologies, the emergence of new business models, and the increasing attractiveness of the sharing economy [1][2][3][4]. It has led to dramatic changes in service production systems [5] and consumer behavior [6] and the emergence and fast development of electronic services.…”

Section: Introductionmentioning

confidence: 99%

E-Service Quality from Attributes to Outcomes: The Similarity and Difference between Digital and Hybrid Services

Vatolkina

Gorbashko

Kamynina

et al. 2020

Journal of Open Innovation: Technology, Market, and Complexity

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Our research goal is to offer an e-service quality model based on experience and multidimensional quality and compare its applicability for e-services to find differences and similarities in consumer perceptions and behavioral intentions. Additionally, we seek to compare attributes that compose quality dimensions for hybrid and digital e-services. The study was based on an online survey conducted in July–September 2019 among citizens and foreign residents in the Russian Federation. Respondents had to answer questions concerning a specific e-service brand to capture real consumer behavior. The data of 365 questionnaires were analyzed using the Spearman correlation to determine the relationship between the model components. Customer experience is a valid outcome variable in the e-service model that strongly influences customer satisfaction and repurchase intentions. The model proved to be equally valid for hybrid and digital e-services. The key differences between digital and hybrid e-services lie within the distribution of e-service attributes between quality dimensions. Ease of use and perceived usefulness are the most essential attributes that have a direct influence on customer satisfaction. The findings show the necessity of best practices diffused between different types of e-services and present an opportunity to widely spread research findings between different e-service sectors.

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“…Parmar, Biju [37] x Patidar, Agarwal [38] x Saberi, Theobald [39] x Silva, Pereira [9] x Stein, Flath [7] x Qamili, Shabani [3] x x x Zhou, Zhu [40] x Zuev, Kalistratov [10] x Xu, Zhang [41] x Chagnon [4] x Giurgiu, Wiesmann [42] x…”

Section: Sent Pred Othermentioning

confidence: 99%

“… Automate labeling of tickets, either for training or for easier ticket resolution by a support agent [34]  Chatbots [15,33,44]  Spam detection [3]  Performance optimization [24]  Automated analysis of pictures attached to a support ticket [11]  Business/process/text mining for better support system architecture [25,45]  AI explainability in support ticket automating [22]  Ticket resolution time prediction [10]  Automated STSs in context of Internet of Things (IoT) [28]  Using answering bot (Microsoft LUIS) for automated request responses [29] The findings and results in these topics were as diverse as the topics itself. Nevertheless, we were able to carve out some general findings:  As in nearly any research in the field of Machine Learning the accessibility and quality of training data importantly influences the outcome of the project [1,3,25]  The metrics precision and recall are by far the most-used metrics for evaluating ML ticket classification tools [5,6,18,36].…”

Section: Specific Topics According To the Special Use Case -The Category Othermentioning

confidence: 99%

“…At the same time, the volume of support tickets in IT-companies created by customers has significantly grown due to the digitalization efforts currently made across all industries [7]. This means that IT-companies face an increasing pressure in automating their STSs to cope with the rising volume of tickets [7], to increase customer satisfaction [1,8], to accelerate support management processes [8,9], and to reduce costs [4,10].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Improving Support Ticket Systems Using Machine Learning: A Literature Review

Fuchs¹,

Drieschner²,

Wittges³

2022

Proceedings of the Annual Hawaii International Conference on System Sciences

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Processing customer support requests via a support ticket system is a key-element for companies to provide support to their customers in an organized and professional way. However, distributing and processing such tickets is much work, increasing the cost for the support providing company and stretching the resolution time. The advancing potential of Machine Learning has led to the goal of automating those support ticket systems. Against this background, we conducted a Literature Review aiming at determining the present state-of-the-art technology in the field of automated support ticket systems. We provide an overview about present trends and topics discussed in this field. During the Literature Review, we found creating an automated incident management tool being the majority topic in the field followed by request escalation and customer sentiment prediction and identified Random Forrest and Support Vector Machine as best performing algorithms for classification in the field.

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Machine Learning in IT Service Management

Cited by 19 publications

References 4 publications

The impact of outsourcing information technology services on business operations

The impact of outsourcing information technology services on business operations

E-Service Quality from Attributes to Outcomes: The Similarity and Difference between Digital and Hybrid Services

Improving Support Ticket Systems Using Machine Learning: A Literature Review

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