Investigating transportation research based on social media analysis: A systematic mapping review

Social media is a pool of users’ thoughts, opinions, surrounding environment, situation and others. This pool can be used as a real-time and feedback data source for many domains such as transportation. It can be used to get instant feedback from commuters; their opinions toward the transportation network and their complaints, in addition to the traffic situation, road conditions, events detection and many others. The problem is in how to utilize social media data to achieve one or more of these targets. A systematic review was conducted in the field of transportation-related research based on social media analysis (TRRSMA) from the years between 2008 and 2018; 74 papers were identified from an initial set of 703 papers extracted from 4 digital libraries. This review will structure the field and give an overview based on the following grounds: activity, keywords, approaches, social media data and platforms and focus of the researches. It will show the trend in the research subjects by countries, in addition to the activity trends, platforms usage trend and others. Further analysis of the most employed approach (Lexicons) and data (text) will be also shown. Finally, challenges and future works are drawn and proposed

Exploring how Interactions and Responses within the Servicescape combine to form Customer Experience – A Text Mining Approach

The core research objective in this thesis is to address the ways in which Customer Experience (CX) emerges through the combinational effects of multiple customer interactions at touchpoints and their resulting CX responses. The empirical study designed in this work is positioned to build upon existing literature within the Service Management field. According to extant work, CX can be viewed from both the provider’s perspective (e.g. ‘intended’ or designed), and the customer’s perspective (e.g. ‘realised’ or subjective). The thesis integrates both accounts through the presentation of a new conceptual model which forms the basis for the design of the empirical study. Several limitations are addressed in this work. First, building on the notion that CX emerges across multiple touchpoint interactions (Lemon and Verhoef, 2016) the study explores the impact multiple interaction types, and their associated responses, have on overall CX. Extant studies have tended to view CX at single touchpoint interactions (Becker and Jaakkola, 2020). CX emerges across multiple touchpoint interactions, which each induce responses in the customer. As it stands, little is known about how this process occurs, or the relationships which exist between customer interaction, customer response, and overall CX. Second, the study widens the field and its understanding of the servicescape from an ‘unbounded’ perspective (Rosenbaum and Massiah, 2011). Traditionally, studies have explored CX through the impact of provider-owned touchpoints, predominantly within bounded service sites. The study addresses requests to explore the impact of wider, non-provider-controlled touchpoints on overall CX (Kandampully et al., 2018). Relating to this aim, very little existing work deals with the impact of natural servicescape touchpoints on CX. The case studies in this work have been chosen for their suitability to address this gap. The study employs a comparative case study approach from the cultural heritage sector. Text mining (TM) and text analytics (TA) techniques are employed to capture and assess CX elements found within customer feedback data from an online review depository. Contrary to existing work in this field, the study employs a three-step annotation process to concept classification which can ensure rigour in the results. The purpose of the analysis process is to capture patterns of CX responses and customer interactions within the data and assess their relationship to overall CX ratings. Both quantitative measures (e.g. statistical analysis) and qualitative measures (e.g. verbatim text analysis) are used to explore a number of key questions relating to the core research objective. The empirical study performed in this work results in several key findings. The study finds that CX arises as a combination of customer interactions and CX responses, with each pattern impacting the overall experience in different ways. Results suggest that pattern prevalence and prominence are not core drivers of customer rating, but rather that significance measures need to be employed. From a customer perspective, negative CX responses have a stronger effect on overall CX rating than positive responses. These can be induced through touchpoint interactions beyond the control of the provider. The emotional content of the experience is key, with customer surprise, anger, and sadness significantly impacting CX to a greater degree than other discrete emotions. The findings suggest that customer expectations play an important role in the delivery of CX. Customer expectations can be used to make sense of the differences in terms of patterns and the statistical significance of their relationship to CX rating. Several potential avenues for future work to further develop these themes are put forward in the final stages of the thesis.EPSRC and University of Exeter Business Schoo

Smart Product Design Methodology

The noticeable emergence of new technological advances, such as Artificial Intelligence (AI) and Internet of Things (IoT), and their continuous developments in today’s market, have paved the way for an apparent transformation from conventional products to smart connected products. Smart products are Cyber-Physical Systems (CPS) that provide services to users through Internet and Communication capabilities. The use of smart products offers exceptional potential for the users to meet their expectations and needs intelligently and effectively. Hence, designers and manufacturers are encouraged to cope with constantly changing consumers’ requirements and help in satisfying their needs. It is necessary to achieve a high level of awareness when interacting with smart products, where in some cases, ambiguity and uncertainty may lead to an undesired outcome. Thus, the objective of this research thesis is to introduce a novel smart product design methodology that reveals a new design dimension that was found by conducting an extensive literature review. Smart product design methodology uses integration between existing Design Theory and Methodologies (DTM), both Systematic Design Approach (SDA) and Axiomatic Design Theory (ADT) which are integrated through the features and functions of smart products. The proposed design methodology concentrates on reducing the complexity of the product and raising its affordances for the users to perceive. This research includes a case study on smart speakers and voice-initiated virtual assistants specifically on Amazon’s Alexa, where the methodology proposed was applied. As a result, the complexity was reduced by achieving an uncoupled design, and affordances’ measures were discussed using the guidelines and recommendations concerning both visual and voice design perspectives for designers and developers of virtual assistants in order to maximize the affordances for the user to perceive with the least amount of ambiguity and doubtfulness

Towards More Nuanced Patient Management: Decomposing Readmission Risk with Survival Models

Unplanned hospital readmissions are costly and associated with poorer patient outcomes. Overall readmission rates have also come to be used as performance metrics in reimbursement in healthcare policy, further motivating hospitals to identify and manage high-risk patients. Many models predicting readmission risk have been developed to facilitate the equitable measurement of readmission rates and to support hospital decision-makers in prioritising patients for interventions. However, these models consider the overall risk of readmission and are often restricted to a single time point. This work aims to develop the use of survival models to better support hospital decision-makers in managing readmission risk. First, semi-parametric statistical and nonparametric machine learning models are applied to adult patients admitted via the emergency department at Gold Coast University Hospital (n = 46,659) and Robina Hospital (n = 23,976) in Queensland, Australia. Overall model performance is assessed based on discrimination and calibration, as measured by time-dependent concordance and D-calibration. Second, a framework based on iterative hypothesis development and model fitting is proposed for decomposing readmission risk into persistent, patient-specific baselines and transient, care-related components using a sum of exponential hazards structure. Third, criteria for patient prioritisation based on the duration and magnitude of care-related risk components are developed. The extensibility of the framework and subsequent prioritisation criteria are considered for alternative populations, such as outpatient admissions and specific diagnosis groups, and different modelling techniques. Time-to-event models have rarely been applied for readmission modelling but can provide a rich description of the evolution of readmission risk post-discharge and support more nuanced patient management decisions than simple classification models

Combining SOA and BPM Technologies for Cross-System Process Automation

This paper summarizes the results of an industry case study that introduced a cross-system business process automation solution based on a combination of SOA and BPM standard technologies (i.e., BPMN, BPEL, WSDL). Besides discussing major weaknesses of the existing, custom-built, solution and comparing them against experiences with the developed prototype, the paper presents a course of action for transforming the current solution into the proposed solution. This includes a general approach, consisting of four distinct steps, as well as specific action items that are to be performed for every step. The discussion also covers language and tool support and challenges arising from the transformation

Factors Influencing Customer Satisfaction towards E-shopping in Malaysia

Online shopping or e-shopping has changed the world of business and quite a few people have decided to work with these features. What their primary concerns precisely and the responses from the globalisation are the competency of incorporation while doing their businesses. E-shopping has also increased substantially in Malaysia in recent years. The rapid increase in the e-commerce industry in Malaysia has created the demand to emphasize on how to increase customer satisfaction while operating in the e-retailing environment. It is very important that customers are satisfied with the website, or else, they would not return. Therefore, a crucial fact to look into is that companies must ensure that their customers are satisfied with their purchases that are really essential from the ecommerce’s point of view. With is in mind, this study aimed at investigating customer satisfaction towards e-shopping in Malaysia. A total of 400 questionnaires were distributed among students randomly selected from various public and private universities located within Klang valley area. Total 369 questionnaires were returned, out of which 341 questionnaires were found usable for further analysis. Finally, SEM was employed to test the hypotheses. This study found that customer satisfaction towards e-shopping in Malaysia is to a great extent influenced by ease of use, trust, design of the website, online security and e-service quality. Finally, recommendations and future study direction is provided. Keywords: E-shopping, Customer satisfaction, Trust, Online security, E-service quality, Malaysia

Safety cases and safety culture : a safety case elicitation tool for light unmanned air vehicles

EThOS - Electronic Theses Online ServiceThe intention of this thesis is to define a guideline for the creation of a safety case for use in the field of civil light UAVs. It provides stakeholders with an opportunity to understand how the UAV, as a complete system, has been designed, assembled and will be operated in a safe and competent manner. Not only can it be used to create a safety argument to prove an extant system's integrity, it can be used to identify weaknesses within a new system to allow further energy to be focussed uponGBUnited Kingdo