Chapter One — 1.1 Background to the Study

Big Data Analytics has become one of the more actively explored innovations in the design of modern ride-hailing applications, promising gains in efficiency and reliability that legacy, largely manual approaches have struggled to deliver.

Despite this potential, many existing ride-hailing applications were not originally designed with big data analytics in mind, resulting in persistent gaps in threat detection accuracy that limit their overall effectiveness. This study examines how Big Data Analytics can be applied to help close that gap.

1.2 Statement of the Problem

Existing approaches to threat detection accuracy within ride-hailing applications remain largely reactive and fragmented, with little systematic use of big data analytics despite its demonstrated value elsewhere. This study addresses the resulting gap by designing and evaluating a solution built specifically around big data analytics.

1.3 Objectives of the Study

1. To design and implement a big data analytics-based approach to improving threat detection accuracy in ride-hailing applications.
2. To evaluate the effectiveness of Big Data Analytics in enhancing threat detection accuracy within ride-hailing applications.
3. To identify the key requirements and constraints relevant to deploying big data analytics in this context.
4. To assess user and stakeholder perception of the resulting system.

1.4 Research Questions

1. How can big data analytics be applied to improve threat detection accuracy in ride-hailing applications?
2. How effective is Big Data Analytics at enhancing threat detection accuracy within ride-hailing applications?
3. What requirements and constraints are relevant to deploying big data analytics in this context?
4. How do users and stakeholders perceive the resulting system?

1.5 Significance of the Study

Beyond its immediate technical contribution, this study offers value to organizations evaluating whether to invest in big data analytics for their own ride-hailing applications, and contributes to the broader literature on applied software technology / IT by documenting a concrete implementation and evaluation case.

1.6 Scope of the Study

As a MSc-level study, its scope is confined to designing and evaluating a big data analytics-based solution for ride-hailing applications, focused specifically on threat detection accuracy; broader deployment considerations fall outside this scope.