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The dramatic rise in online purchasing in the last few years has highlighted the importance of the last mile delivery (LMD) task across the globe. However, it faces many economic, social, and environmental challenges (Triple bottom line). This has led to exploring a variety of solutions to develop an efficient last mile delivery system. Amongst them, one rapidly growing innovative solution is Crowd Logistics Delivery (CLD). CLD is assigning a delivery task to a network of individuals who are not employed by the company, that work flexibly as driver full time or part time to deliver goods from point to point. However, up to now, far too little attention has been paid to understanding the multiple perspectives of stakeholders in developing an efficient CLD system. Thus, this study aims to explore CLD in relation to the perspectives of the different stakeholder groups: institutional: decision makers, industrial: CLD applications owners, logistic service providers' managers, and retailers' owners, and individual: customers and drivers/crowd in a rapidly emerging economy – the Kingdom of Saudi Arabia (KSA). This study uses an inductive qualitative case study approach which would allow exploration of this new topic and provide more flexibility to understand the impact of social and contextual factors. Furthermore, it can provide information richness and a deep understanding of an evolving phenomenon in real-world settings. Besides, there has been little qualitative analysis of this novel topic. While the findings of this thesis broadly support the work of other studies in this area, it provides new insights that no previous study has offered. Particularly, by exploring its business models, the study shows how CLD is implemented for LMD. This study has identified three different practices of CLD in the context presented by business models: B-to-B-Contract, Bto-C, and C-to-C. It also identified the internal success factors of each business model, including registration, assigning orders, compensation, and the payment model. It further reveals the motivations for stakeholders to use CLD as a last mile delivery solution, such as LMD-related benefits and the social impact on society. In addition, the study has identified the four main challenges CLD faces in last mile delivery that impede its success: legislation, availability of supply/drivers, trust, and culture. These results add to the rapidly expanding field of CLD. By empirically focussing on the impact of different stakeholders based on their saliency to CLD, the study contributes in several ways to the understanding of CLD and provides a basis to improve CLD as a last mile delivery solution, and particularly in the context of an emerging economy. It also provides a comprehensive study to understand different aspects of CLD and the significant role of stakeholders in shaping the nature and destiny of development initiatives. Furthermore, this study extends the theory in the context of CLD and further extends our understanding of the factors that influence CLD through the stakeholders' involvement. It shows that failing to include the key stakeholders will impact on an organisation's success. Therefore, it shed light on the issues that were captured through involving key stakeholders in the study. These issues may result from not involving key stakeholders, including drivers' participation limitations, and customers' adoption of a certain business model. It also helped to differentiate between the various understandings of trust, privacy, security, quality, and handling.

The suitable location of facilities is a key factor in achieving efficient supply systems both in the public and in the private sectors. Nowadays, most public and non-profit bodies offering essential services (such as healthcare or environmental management facilities) are suffering from severe funding limitations and budget cuts. In handling this scenario, the decision-makers must take any possible action to ensure facility networks can keep operating and providing a minimum required service level, even though, due to financial reasons, some facilities might be downsized (and their operating hours reduced) or, in extreme cases, closed down. Any reduction that is made might limit the service level, hence increasing the congestion level of the system. For essential services, this means an increase in demand's waiting times for server availability; as such, users could consider moving to another available facility or, at a certain point, leave the system. This study aims to develop a mathematical model for reorganising the operations of existing facility networks which encounter budget reductions issues. Due to reorganisational actions, the network size might be reduced. Hence, this study is also concerned with the effect of the reorganisation, i.e. the congestion problems which might derive from the changes imposed onto the network. Limited studies were found in the area of reorganisation of facilities' operations, especially in a scenario of supply shortage problem. Moreover, no study considered congestion problem as part of reorganisation effect. Hence, this study proposed a dynamic mathematical model using a multi-period logic as the main approach to solve the reorganisation problem. The proposed model was adapted and used to solve two real-world case studies from the City of Sheffield (UK): the first one concerned with the rationalisation of Household Waste Recycling Centres (HWRC); the second one devoted to the organisation of General Practitioners (GP) Facilities. Both types of facilities are currently dealing with budget limitations issues. The contribution of this thesis is twofold. First of all, the effect of reorganisational actions on the networks was also considered and integrated, through explicit consideration of congestion issues by means of a novel multi-period model which was proposed in order to solve facility networks reorganisation problems. As such, this work provides an enrichment of the literature related to reorganisation problems of existing facility networks; which not many authors have explored. Secondly, such model was applied to two real-world cases faced by local authorities and other planning bodies; through these implementations, the study also contributed to practical problem-solving issues.

Despite the growing body of literature recognising the influence of supply chain leadership and governance mechanisms on supply chain practices, studies on these two domains are currently disconnected. Furthermore, while the importance of supply chain leadership is mentioned and highlighted in the literature, less is known about the role of buying firms' leadership styles as the determinants of governance mechanisms and suppliers' performance. Drawing upon theories of stakeholder, institutional, transformational-transactional leadership, social exchange and transaction cost economics, this thesis fills some of the gaps in the current literature by examining the effects of supply chain leadership on governance mechanisms and suppliers' performance. A number of hypotheses were developed and proposed, and a convergent parallel mixed methods research design was used to examine the effects of supply chain leadership on governance mechanisms and suppliers' performance in Malaysian manufacturing industries. 190 questionnaire survey responses were collected and analysed using structural equation modelling, while 25 semi-structured interviews were analysed using thematic analysis. The findings reveal that transformational and transactional leadership positively influenced different governance mechanisms with transformational leadership driving towards trust-based governance and transactional leadership pushing towards contract-based governance. The direct positive effects of transformational and transactional leadership towards suppliers' performance are also evident in this thesis. However, the findings reveal that laissez-faire leadership negatively influenced contract-based governance and suppliers' performance. Nonetheless, this thesis discovers that the indirect effects of supply chain leadership to suppliers' performance were partially mediated through governance mechanisms. The findings provide insights on reconceptualising supply chain leadership. This thesis integrates supply chain leadership and governance mechanisms in one model and reconciles the role of both concepts towards suppliers' performance. Furthermore, this thesis provides an explanation of the relationships between supply chain leadership and suppliers' performance by looking into the mediating role of governance mechanisms. By integrating those concepts, the disengagement between supply chain leadership, governance mechanism and suppliers' performance is minimised. Nonetheless, the findings offer guidance and suggestions to supply chain managers (in both buying firms and suppliers) on the role of buying firms' leadership styles and their influence towards suppliers' performance regardless of both parties' supply chain positions. Findings from this thesis can help the buying firms to re-evaluate their leadership styles as the relationship with each supplier is unique and the idea of relying on a single leadership style has a potential to disrupt the performance of both parties.

Big Data Analytics (BDA) is perceived as one of the most prodigious technologies of the 21st century. However, relatively few studies have demonstrated the positive outcome of developing BDA capabilities. Moreover, although BDA is argued to advance innovation (Tan et al. 2015), the influence of BDA on innovation performance is yet to be confirmed empirically. Studies explaining the underlying mechanism through which BDA influences operational and innovation performances are limited, especially from a BDA maturity and organisational learning perspective. Further, the phenomenon of a digital divide, between SMEs and large organisations, instigated by the adoption of BDA remains unexplored. Therefore, the main purpose of this study is to address these gaps and contribute to the literature by empirically investigating the value of Big Data Analytics capabilities from a maturity perspective, and to explore the digital divide in the context of the UK's manufacturing sector. A systematic literature review is conducted to identify potential research gaps and to frame the research questions. Drawing on the Resource-Based View, Dynamic Capabilities, and a hierarchy of capabilities perspective, a conceptual model is developed depicting the relationship between the BDA capabilities, the higher-order capabilities such as absorptive capacity, data and information quality and supply chain analytics, and its effect on innovation and operational performance. A survey-based research method is adopted to investigate the model and test the hypotheses. For data collection, an online questionnaire is distributed via Qualtrics to senior executives in UK manufacturing sector. After a rigorous pre-processing of collected data, a sample of 221 responses is estimated to be appropriate for further analysis. This study used two types of data analysis techniques: Structural equation modelling and Cluster analysis. Structural equation modelling is used to examining the causal relationship between the variables in the conceptual model. Whereas, cluster analysis is used to explore the phenomenon of a digital divide between SMEs and large organisations. The findings of this study indicate that BDA capabilities improves operational and innovation performances. The impact of BDA capabilities on operational performance is partially mediated by absorptive capacity, data and information quality, and supply chain analytics capability. However, the impact of BDA capabilities on innovation performance is only mediated by absorptive capacity. In terms of cluster analysis, the findings indicate the presence of four homogeneous clusters of organisations with varied levels of BDA capabilities maturity, signifying the reality of digital divide. This study makes some significant contributions. First, in terms of the contribution to literature, this study synthesised arguments from the Resource-Based View, the Dynamic Capabilities View and the hierarchy of capabilities view to provide a holistic explanation of the relationship between lower-order capabilities, higherorder capabilities and operational and innovation performances. Second, in terms of contribution to practice, this research will help to improve the practitioners' understanding about how BDA capabilities can improve firm performance. The BDA maturity framework developed in this research can be used by the practitioners to assess the current level of BDA capabilities allowing the organisations to determine the areas of improvement. Third, this research provides implications for policy that could be advantageous to SMEs, who are mainly data and information poor.

This research presents a picture of the current status and the future developments of the LV electricity grid and the capabilities of the smart metering programme in the UK as well as investigating the major research trends and priorities in the field of Smart Grid. This work also extensively examines the literature on the crucial LV network performance indicators such as losses, voltage levels, and cable capacity percentages and the ways in which DNOs have been acquiring this knowledge as well the ways in which various LV network applications are carried out and rely on various sources of data. This work combines 2 new smart meter data sets with 5 established methods to predict a proportion of consumer’s data is not available using historical smart meter data from neighbouring smart meters. Our work shows that half-hourly smart meter data can successfully predict the missing general load shapes, but the prediction of peak demands proves to be a more challenging task. This work then investigates the impact of smart meter time resolution intervals and data aggregation levels in balanced and unbalanced three phase LV network models on the accuracy of critical LV network performance indicators and the way in which these inaccuracies affect major smart LV network application of the DNOs in the UK. This is a novel work that has not been carried out before and shows that using low time resolution and aggregated smart meter data in load flow analysis models can negatively affect the accuracy of critical low voltage network estimates.

This research investigates how project contracts can coordinate the supply chain between a project manager and contractor and if the solutions can be ensured as equitable. The main features of this type of supply chain are the trade-offs between the selection of a higher rate of resource consumption with a consequent higher cost to the contractor and a lower rate of resource consumption leading to later delivery and a reduction of the project-reward to the project manager. This broader problem could lead to a coordination problem for the overall supply chain. This research proposed a solution to this broader problem in two different scenarios: Take it or leave it scenario and negotiation scenario. Finally, the fair allocation of the risks and benefits and the related decision-making issues are addressed as one of the behavioural barriers to the supply chain coordination. The coordination issues in a take it or leave it scenario are addressed using time-based and fixed price project contracts using Stackelberg games. Models of coordination were proposed with time-based contracts, but the fixed price contracts failed to coordinate. The coordination problems in negotiation scenario are addressed with the Nash's bargaining, the Kalai Smorodinsky bargaining, and the utilitarian approach. A cost plus contract has been found to dominate the solutions over any cost sharing contract and fixed price contract for Nash's bargaining and Kalai Smorodinsky bargaining cases. Finally, the issues of fairness of allocation of risks and benefits as one of the challenges of supply chain coordination, have been investigated. The fixed price contracts were found to coordinate the supply chain under consideration alongside the time-based contracts if the members had fairness concern. Some of the key features of this research include the incorporation of various probability distributions for the project completion time and cost, the inclusion of various forms of risk preference, and addressing the challenges of fair allocation in project supply chains.

Managing risk in supply chains has emerged as an important topic in contemporary supply chain management theory and practice. This is due to a number of trends, including increased globalisation of markets, creating more complex supply networks and a move towards 'leaner', more efficient supply chain operation generally. Whilst these trends have undoubtedly produced significant benefits in terms of productivity and profitability, for many organisations, they have also increased susceptibility to disruption. It is generally accepted that risk can be segmented into those which are internal to the organisation or its supply chain, operational risks (commonly referred to as supply, process and demand risks) and those which are external to the organisation and its supply chain, corporate-level disruption risks. The vulnerability of global supply chains to external risk of this nature has been catapulted in to the spotlight in recent years, following a number of high-profile events including, the financial crises in North America, Europe and Australia (2007-08), the Chao Phraya river floods in Thailand (2011) and the Tohoku Earthquake/ Tsunami in Japan (2012), amongst many others. Whilst there is a broad and growing body of literature around supply chain risk management (SCRM) generally, focus on understanding and building supply chain resiliency to the impact of corporate-level disruption risk at a strategic level remains an area of the field in its relative infancy. Following an extensive review of the SCRM literature, a demonstrable research gap was highlighted for more in-depth analysis of organisationsthat are taking steps to manage supply chain risk, especially corporate-level disruption risk. In addressing this gap, the current research adopts an applied case study methodology to assess how a leading automotive manufacturer strategically approaches supply chain risk management, gaining an understanding of how and why traditional processes are evolving to manage corporate-level disruption risk (Case Study 1). Organisational SCRM strategy, including mitigation and response processes, are critically discussed in relation to the literature. The study finds that, whilst proactive strategy is employed for operational risk within the organisation's control, a lack of upstream supply chain visibility inhibits initiatives to mitigate the impact of corporatelevel disruption risk within the extended upstream supply chain. The study is set against a background of significant regulatory drivers forcing organisations to increase upstream supply chain visibility. These are critically reviewed, including how the focal organisation is responding to them through a collaborative supply chain mapping initiative. Building upon findings from Case Study 1, the research presents a conceptual 'stakeholder salience' framework, exploring how increased visibility might be used to better assess susceptibility to corporate-level supply chain disruption risk (Case study 2). This framework is empirically explored using an example of a 'critical' automotive component supply chain – the Lithium-ion battery cell. It applies a combination of upstream geographic supply chain mapping data with weighted geo-political, economic and environmental indicators, in a GIS environment, to assess stakeholder salience amongst suppliers. The study highlights the significant susceptibility of supply chains to corporate-level risk beyond lower tiers and argues that through better understanding of where key hotspots lie, limited resources can be more appropriately targeted onto the mitigation and strategic management of risk within those areas.