Mapping customer needs to engineering characteristics: an aerospace perspective for conceptual design

Designing complex engineering systems, such as an aircraft or an aero-engine, is immensely challenging. Formal Systems Engineering (SE) practices are widely used in the aerospace industry throughout the overall design process to minimise the overall design effort, corrective re-work, and ultimately overall development and manufacturing costs. Incorporating the needs and requirements from customers and other stakeholders into the conceptual and early design process is vital for the success and viability of any development programme. This paper presents a formal methodology, the Value-Driven Design (VDD) methodology that has been developed for collaborative and iterative use in the Extended Enterprise (EE) within the aerospace industry, and that has been applied using the Concept Design Analysis (CODA) method to map captured Customer Needs (CNs) into Engineering Characteristics (ECs) and to model an overall ‘design merit’ metric to be used in design assessments, sensitivity analyses, and engineering design optimisation studies. Two different case studies with increasing complexity are presented to elucidate the application areas of the CODA method in the context of the VDD methodology for the EE within the aerospace secto

COBRA framework to evaluate e-government services: A citizen-centric perspective

E-government services involve many stakeholders who have different objectives that can have an impact on success. Among these stakeholders, citizens are the primary stakeholders of government activities. Accordingly, their satisfaction plays an important role in e-government success. Although several models have been proposed to assess the success of e-government services through measuring users' satisfaction levels, they fail to provide a comprehensive evaluation model. This study provides an insight and critical analysis of the extant literature to identify the most critical factors and their manifested variables for user satisfaction in the provision of e-government services. The various manifested variables are then grouped into a new quantitative analysis framework consisting of four main constructs: cost; benefit; risk and opportunity (COBRA) by analogy to the well-known SWOT qualitative analysis framework. The COBRA measurement scale is developed, tested, refined and validated on a sample group of e-government service users in Turkey. A structured equation model is used to establish relationships among the identified constructs, associated variables and users' satisfaction. The results confirm that COBRA framework is a useful approach for evaluating the success of e-government services from citizens' perspective and it can be generalised to other perspectives and measurement contexts. Crown Copyright © 2014.PIAP-GA-2008-230658) from the European Union Framework Program and another grant (NPRP 09-1023-5-158) from the Qatar National Research Fund (amember of Qatar Foundation

Model and management indicators in industrial omnichannel (B2B)

The COVID-19 pandemic has driven increases in the provision of services through digital channels, even by more traditional companies. An Omnichannel model of service provision poses new management challenges for companies. This research reviews the literature on Omnichannel Management by companies whose clients are other companies (B2B) and classifies the different areas of research to date. The principal finding is that, despite considerable academic interest in Omnichannel management, there have been few studies of Omnichannel in the B2B field. This emphasizes a significant research gap to address. We have also outlined the Research Agenda to highlight future lines of research

Quality of Information in Mobile Crowdsensing: Survey and Research Challenges

Smartphones have become the most pervasive devices in people's lives, and are clearly transforming the way we live and perceive technology. Today's smartphones benefit from almost ubiquitous Internet connectivity and come equipped with a plethora of inexpensive yet powerful embedded sensors, such as accelerometer, gyroscope, microphone, and camera. This unique combination has enabled revolutionary applications based on the mobile crowdsensing paradigm, such as real-time road traffic monitoring, air and noise pollution, crime control, and wildlife monitoring, just to name a few. Differently from prior sensing paradigms, humans are now the primary actors of the sensing process, since they become fundamental in retrieving reliable and up-to-date information about the event being monitored. As humans may behave unreliably or maliciously, assessing and guaranteeing Quality of Information (QoI) becomes more important than ever. In this paper, we provide a new framework for defining and enforcing the QoI in mobile crowdsensing, and analyze in depth the current state-of-the-art on the topic. We also outline novel research challenges, along with possible directions of future work.Comment: To appear in ACM Transactions on Sensor Networks (TOSN

Stochastic modeling of responsiveness, schedule risk and obsolescence of space systems, and implications for design choices

The U.S Department of Defense and the National Aeronautics and Space Administration continue to face common challenges in the development and acquisition of their space systems. In particular, space programs repeatedly experience significant schedule slippages, and spacecraft are often delivered on-orbit several months, sometimes years, after the initially planned delivery date. The repeated pattern of these schedule slippages suggests deep-seated flaws in managing spacecraft delivery and schedule risk, and an inadequate understanding of the drivers of schedule slippages. Furthermore, due to their long development time and physical inaccessibility after launch, space systems are exposed to a particular and acute risk of obsolescence, resulting in loss of value or competitive advantage over time. The perception of this particular risk has driven some government agencies to promote design choices that may ultimately be contributing to these schedule slippages, and jeopardizing what is increasingly recognized as critical, namely space responsiveness. The overall research objective of this work is twofold: (1) to identify and develop a thorough understanding of the fundamental causes of the risk of schedule slippage and obsolescence of space systems; and in so doing, (2) to guide spacecraft design choices that would result in better control of spacecraft delivery schedule and mitigate the impact of these "temporal risks" (schedule and obsolescence risks). To lay the groundwork for this thesis, first, the levers of responsiveness, or means to influence schedule slippage and impact space responsiveness are identified and analyzed, including design, organizational, and launch levers. Second, a multidisciplinary review of obsolescence is conducted, and main drivers of system obsolescence are identified. This thesis then adapts the concept of a technology portfolio from the macro- or company level to the micro-level of a single complex engineering system, and it analyzes a space system as a portfolio of technologies and instruments, each technology with its distinct stochastic maturation path and exposure to obsolescence. The selection of the spacecraft portfolio is captured by parameters such as the number of instruments, the initial technology maturity of each technology/instrument, the resulting heterogeneity of the technology maturity of the whole system, and the spacecraft design lifetime. Building on the abstraction of a spacecraft as a portfolio of technologies, this thesis then develops a stochastic framework that provides a powerful capability to simultaneously explore the impact of design decisions on spacecraft schedule, on-orbit obsolescence, and cumulative utility delivered by the spacecraft. Specifically, this thesis shows how the choice of the portfolio size and the instruments Technology Readiness Levels (TRLs) impact the Mean-Time-To-Delivery (MTTD) of the spacecraft and mitigate (or exacerbate) schedule risk. This work also demonstrates that specific combinations/choices of the spacecraft design lifetime and the TRLs can reduce the risk of on-orbit obsolescence. This thesis then advocates for a paradigm shift towards a calendar-based design mindset, in which the delivery time of the spacecraft is accounted for, as opposed to the traditional clock-based design mindset. The calendar-based paradigm is shown to lead to different design choices, which are more likely to prevent schedule slippage and/or enhance responsiveness and ultimately result in a larger cumulative utility delivered. Finally, missions scenarios are presented to illustrate how the framework and analyses here proposed can help identify system design choices that satisfy various mission objectives and constraints (temporal as well as utility-based).PhDCommittee Chair: Saleh Joseph; Committee Member: Brown Owen; Committee Member: Erwin R. Scott; Committee Member: Feron Eric; Committee Member: Mavris Dimitr

The Dimensions of Customer Satisfaction in the Jamaican Financial Service Industry

Bank leaders spend an average of $727 to acquire a new customer and$287 to retain current customers. Grounded in customer relationship management and adaptation level theories, the purpose of this correlational study was to examine the relationship between service quality and customers\u27 intention to switch banking service. An online survey was administered to 203 Jamaican banking customers. The target population was selected to identify if the Jamaican banks\u27 customer service adhered to the customer satisfaction principles developed by Parasuraman. The independent variables were the 10 dimensions of service quality. Competence, courtesy, credibility, and access were removed because of multicollinearity issues. The dependent variable was the customers\u27 intention. The results indicated a statistically significant relationship, F(6, 196) = 15.074, p \u3c .001, between service quality and customer intent to switch banking services. The six predictors: tangibles (r = -.303, p \u3c .005), reliability (r = -.253, p \u3c .008), responsiveness (r = .35, p \u3c .001), safety (r = -.433, p \u3c .001), communication (r = -.184, p \u3c .028), and empathy (r = -.357, p \u3c .001), accounted the largest variance for (β = -.316) of the customers\u27 intention of the Jamaican banking service. The implications for positive social change include the potential for bank leaders to develop customer-focused banking policy, increase customer satisfaction, and decrease costs related to losing customers, thus increasing profitability

Managing risks and system performance in supply network: a conceptual framework

Examining a certain risk will provide an insight into a single dimension, but a picture of different risks in the supply chain (SC) is still lacking, as risks do not take place independently, but typically simultaneously. This research aims to propose and validate a conceptual framework for linking various dimensions of risk to system performance in the SC by applying SC mapping - a new approach in the SC risk body of literature. In the model, risks were classified into three categories with regard to their level of impact on performance: 1) core risks, e.g., supply risk, investor-related operational risks, contractor-related operational risks and demand risks; 2) infrastructure risks, e.g., finance risk, information risk and time risk; 3) external risks, e.g., human-made risks; 4) natural risks. Using the framework, companies will have a systematic view of risks in the whole SC network whereby they can define risks in their own context and ascertain critical SC risks that cause negative effects on SC performance

Big data analytics:Computational intelligence techniques and application areas

Big Data has significant impact in developing functional smart cities and supporting modern societies. In this paper, we investigate the importance of Big Data in modern life and economy, and discuss challenges arising from Big Data utilization. Different computational intelligence techniques have been considered as tools for Big Data analytics. We also explore the powerful combination of Big Data and Computational Intelligence (CI) and identify a number of areas, where novel applications in real world smart city problems can be developed by utilizing these powerful tools and techniques. We present a case study for intelligent transportation in the context of a smart city, and a novel data modelling methodology based on a biologically inspired universal generative modelling approach called Hierarchical Spatial-Temporal State Machine (HSTSM). We further discuss various implications of policy, protection, valuation and commercialization related to Big Data, its applications and deployment

A systematic literature review on the semi-automatic configuration of extended product lines

Product line engineering has become essential in mass customisation given its ability to reduce production costs and time to market, and to improve product quality and customer satisfaction. In product line literature, mass customisation is known as product configuration. Currently, there are multiple heterogeneous contributions in the product line configuration domain. However, a secondary study that shows an overview of the progress, trends, and gaps faced by researchers in this domain is still missing. In this context, we provide a comprehensive systematic literature review to discover which approaches exist to support the configuration process of extended product lines and how these approaches perform in practice. Extend product lines consider non-functional properties in the product line modelling. We compare and classify a total of 66 primary studies from 2000 to 2016. Mainly, we give an in-depth view of techniques used by each work, how these techniques are evaluated and their main shortcomings. As main results, our review identified (i) the need to improve the quality of the evaluation of existing approaches, (ii) a lack of hybrid solutions to support multiple configuration constraints, and (iii) a need to improve scalability and performance conditions