Uber-nization of transport: An investigation into the sustainability of ride-sharing applications in Malaysia

Commuting trips is projected to hit 72 million alongside the urban population growth 75% by 2020. However, transportation mode availability has only grown by 8% over the last 5 years, thereby creating an unfulfilled demand gap in transportation. This has led to delays in public transportation, causing a ripple effect on work productivity. Suppressed demand affects riders’ decision to use public transportation, spurred the use ride-sharing in the past 2 years in Malaysia. The research aims to investigate the factors that influence the adoption of ride-sharing services and to identify target segments of ride-sharing users in order to tailor offerings and solutions to them, thus assisting the government and industry to improve the sustainability of the transportation landscape of the country. The integration of the Technology Acceptance Model and Theory of Planned Behaviour adopted for this research aims to understand the adoption usage of the ride sharing app user’s consumer behavior. From a purposive convenient snowball sampling of 107 out 144 samples multiple linear regression and Hayes Process for mediation show significant results between the constructs of Perceived Ease of Use, Perceived Usefulness, Attitude and Intention in using ride sharing apps. The analysis was followed by a two-step cluster deriving 4 distinct clusters of ride-sharing users with individual consumer behavior and corresponding demographic characteristics. Results of this research can see larger applications replicated across various contextual scenarios and geographies not limited to just the transportation industry

Consumers' Use of Smartphone Technology for Travel and Tourism in a COVID Era: A Scoping Review

Mobile phone technology has become a necessary component for today's travellers. Information and communication technologies (ICTs) have substantially affected tourism and hospitality consumers over the past two decades. Mobile technologies such as smartphones, tablets, and mobile applications have become travellers' primary access to information. This study focuses on mobile technologies such as smartphones and mobile applications (apps) and consumers' use of mobile technology when travelling. A scoping review following PRISMA guidelines was used to answer the research question; "How do tourism consumers use mobile technologies for travel and tourism during the COVID era?" This study will identify and analyse any relationships, patterns, trends, and gaps in the literature. Peer-reviewed journal articles from the COVID era (2020 to 2022) were included in this study. Articles were sourced using the keywords listed below. The full articles were imported into NVivo, and the main themes and subthemes were extracted from the data and reported using an inductive qualitative thematic analysis. The results from this study identified "food" as the main theme and "food delivery" as the most frequent subtheme. Food, tourism, transportation, Fourth Industrial Revolution (4IR), Hotel Operations, and Shopping were the top 6 themes. The 4IR is changing how smartphone consumers use their devices for travel and tourism. In the COVID Era, Smartphone technology has been recognised as a solution to maintaining safe distancing and contactless transactions. This research will benefit tourism operators and policymakers to remain competitive in an ever-changing environment during the COVID er

Using attitudes and green consciousness as a determinant of travel behaviour and market segmentation

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Investigating individual preferences for new mobility services: the case of “mobility as a service” products

In just a few years, the Mobility as a Service (MaaS) concept has gone from an idea discussed by very few, to being a prominent topic in any transportation related debate. However, within this time, there have only been few rigorous studies that explore the various aspects of MaaS. This thesis aims to contribute to existing knowledge by providing empirical evidence on individual preferences for MaaS plans and their components. In doing so, first desk-research is conducted to summarise existing MaaS schemes and outline the MaaS ecosystem. Next, MaaS surveys that are able to capture individual preferences for MaaS products are designed and specific challenges in the design process identified. The MaaS surveys, including MaaS plan stated preference experiments, are applied in two case study areas of London and Greater Manchester. Using the novel data collected, individual preferences for MaaS plans are examined using two distinct studies: (1) a mixed methods research conducted in London, which expands the survey by adding a qualitative (in-depth interview) element to examine user preferences for MaaS plans and the ways individuals choose between them; and (2) a latent class choice model based on data collected from Manchester to examine whether there is heterogeneity in preferences. Finally, implications for industry and policy stakeholders are discussed as well as interventions that can best support the widespread adoption of MaaS. The results of this thesis show there is interest in the concept of MaaS among potential users as many see value in a single app that integrates different transport modes into a single service. In general, individuals are hesitant in purchasing pre-payed MaaS plans and would be more comfortable with a pay-as-you-go product option. While many people are reluctant towards MaaS plans, the results indicate that heterogeneity exists in preferences towards them and there are different user groups based on socio-demographic characteristics and current mobility habits. Smaller, less expensive plans including modes such as public transport and bike sharing can be used to target students or middle-income people with have high overall mode usage. Larger, more expensive plans that include modes such as taxi and car sharing in addition to public transport, will be attritive to individuals who are likely younger, male, well-educated, have higher income and already use many transport modes. Older population groups, individuals with low income and those that do not use any transport modes or are uni-modal are least likely to adopt MaaS plans. The thesis also provides insights into individuals’ preferences towards transport modes within MaaS plans. The analysis showed that respondents classify modes within MaaS plans into three categories: ‘essential’ modes that are pivotal to the individual and which they most likely already frequently use; ‘considered’ modes are those that they would be willing to include but may not yet use; and ‘excluded’ modes are those that they definitely do not want in their plans and would eliminate any plan that included these. Public transport consistently proved to be an essential mode, while taxi, car sharing and bike sharing could be ‘essential’, ‘considered’ or ‘excluded’ depending on the characteristics of the individual. The main contributions of this thesis are the novel data collected in two case study cities about individuals’ preferences for MaaS plans and the findings gained through the analysis providing insights into possible target audiences and product designs for MaaS plans

Customer Demographic Segmentation Based On Telecom Behavioral Data

In the modern world, digitalization becomes ubiquitous and covers almost every aspect of the business and daily life. Telecom services providers have a major role in these processes due to their involvement in collecting, storing and processing enormous amounts of customer data. This also includes personal telecom services usage data, which if correctly interpreted, might be used for many different purposes. Using telecom data to predict certain demographic characteristics of the customers is helpful in more than one aspect: 1) It could add the acquired knowledge into customer segmentation to better target different customer groups. 2) Such data could be used in cases where traditional historic data is not available- the potential strength of predicting customer credit worthiness based on behavior data is still not fully explored. 3) Last but definitely not least, is the use of data for verifying customer identification in fraud detection. In this paper, an overview of some successful use of telecom data for non-telecom services is shown, as well as with a set of real telco data, statistical techniques are used to demonstrate the relation between mobile telecom services usage and subscription owners’ age. Use of alternative customer data could have enormous implication both on traditional predictive models and could alter the role of the telecoms, making them one of the most important information sources for financial institutions, which operate with sensitive customer data

A business plan for a new mobile application to the consumer foodservice industry

The Portuguese consumer foodservice industry is experiencing a boost in technology adoption, driven by significant changes in consumer behavior and business dynamics, due to mobile increasing penetration. Accordingly, the present work project consists on developing a business plan for meeting an identified opportunity in the technological foodservice landscape. Therefore, this report is divided into three sections, each of which addressing different objectives: (A) External Environment, providing key external insights that support the opportunity; (B) Strategy Formulation, establishing a strategic direction; and (C) Action Plan, determining an implementation plan for starting the busines