This thesis focuses on eco-design trade-offs and material selection in a Small to Medium–Sized Enterprise (SME) producing office furniture. The rationale for undertaking this work is based on the wide acceptance that eco-design uptake in SMEs remains low and the need for SMEs to adopt eco-design is pressing. SMEs constitute 99.9% of UK private sector business and it has been estimated that SMEs account for approximately 64-70% of overall pollution from industry. Supporting SMEs in adopting eco-design is challenging. The complexities of eco-design decision-making, poor understanding of environmental trade-offs, limited access to relevant information and complex eco-design methods (amongst others) negatively affect an SME’s ability to reduce a product’s environmental impacts. The aim of this research is to deepen understanding of eco-design by investigating eco-design trade-offs and material selection during the development of eco-innovative office furniture products. This improves understanding of environmental impact reduction at the material selection and concept stage of the design process. The research design is an intensive single case study at Orangebox, a UK market leader in the design and manufacture of office furniture. The case company is selected, as a best practice example of eco-design integration within an SME. Four embedded case studies of New Product Development (NPD) are conducted within the main case. The research employs a multi-strategy design using both qualitative and quantitative methods and is delivered over two stages. The contributions to knowledge of the thesis are (1) the identification and description of a set of eco-design trade-offs linked to specific eco-design strategies (design for disassembly, light-weighting, material streamlining) and (2) the thesis argues that stakeholders play a crucial role in eco-innovative material selection. From this, the thesis presents a conceptual classification of a material portfolio incorporating eco-design strategies and trade-offs to facilitate eco-innovation during NPD.

This thesis takes an exploratory look at the phenomenon of silence in the ethnographic setting of an inter-organisational project, to review how project group members talk about their own practice of silence within the ongoing process of project delivery. The research swaps a transmission model of communication, which has been used in much of the previous work on silence in the field of organisational behaviour, for a dialogic model of communication, which prioritises temporal contingency and local processes of meaning-making in order to explore how participants develop the social significance of silence. Firstly, the thesis shows how participants discursively construct silence as an emergent phenomenon connected with the development and maintenance of social relationships through the lifecycle of the project. I identify three common-sense storylines (Davies and Harré, 1990) - each with a different underpinning logic: of relating, of representing, and of doing - which provide discursive resources by means of which participants position their practice of silence within the management of different types of relationship. Secondly, the thesis covers how silence emerges in various forms over the course of the project lifecycle: as discrete acts of withholding but also as outcomes of other processes of social interaction. What emerges from the use of a dialogic model of communication is a potential new approach to silence in organising processes, which focuses less on silence as a discrete entity produced by an agentic individual and more on its temporal and embodied features in a way that may help to integrate some of the diverse organisational and management perspectives on the topic.

Permutation flowshop scheduling problem (PFSP) is a classical combinatorial optimisation problem, which has attracted much attention from academia and industry in the last two decades. However, there are still great challenges to overcome. In existing heuristic methods, jobs with similar processing times cannot be efficiently distinguished, so that jobs are not effectively sequenced, which could result in a poor scheduling solution. Also, most existing research has focused on static PFSPs with a single-objective, however, a single objective is sometimes not good enough, and multiple objectives are often required. In addition, many interruptions or disturbances such as newly arrived orders frequently occur, which creates significant challenges and needs to be addressed in scheduling research. This work focused on new job differentiation methods, multi-objective optimisation, and dynamic scheduling methods in static and dynamic environments respectively. In the static environment, three new priority rules using high moments of a probability distribution of job processing times are proposed, for the first time, so that jobs can be effectively distinguished and ordered. As a result, three new heuristics as well as a new tie-breaking rule are developed based on Nawaz-Enscore-Ham (NEH) heuristic for single-objective PFSPs. For multi-objective PFSPs, with makespan and idletime as the bicriteria, a new heuristic method is developed by incorporating a new priority rule and a new tie-breaking rule. As a result, our work has proved that makespan and idletime are not equivlent in sheduling optimisation, which corrects the existent misunderstanding in the scheduling community. In the dynamic environment, PFSPs with new order arrivals are investigated, and a new heuristic method is proposed by integrating a new match-up and real-time strategy through orders’ mixing. Also, a new meta-heuristic algorithm derived from iterated greedy algorithm is developed with a new enhanced destruction & construction method and a novel repair mechanism. For ease of application, a digital tool is developed to automatically implement these algorithms. A real industrial case is used to demonstrate the validity of these scheduling methods.

In 2015, 15 of the 28 European Member States had design included in national innovation policy and design action plans were in operation in Denmark, Estonia, Finland, France and Latvia. Design is an approach to problem-solving that can be applied across the private and public sectors and is becoming more relevant to policy as part of a paradigm shift towards user-centred innovation. According to the European Commission’s Action Plan for Design-driven Innovation: ‘A more systematic use of design as a tool for user-centred and market-driven innovation in all sectors of the economy, complementary to R&D, would improve European competitiveness.’ Furthermore, the European Commission encourages all European countries and regions to develop design action plans. However, the route to building effective national and regional design capacity is not clear. The rationale for this research was framed as much by a gap in theoretical knowledge among research practitioners as a gap in applied knowledge among policy practitioners for evidence-based policy-making in design. It is widely acknowledged that policy intervention for innovation is justified by systems failure theory. Innovation researchers and policy-makers have been able to quantify and thus benchmark the performance of innovation ecosystems to inform policy actions. Design researchers have also argued that policy intervention for design can be justified by systems failure theory but asserted that design is not well captured in European benchmarking exercises. As such, this research has taken a design-led approach to developing a quantitative framework of 46 indicators to assess the performance of a country’s Design Innovation Ecosystem to inform policy-making. The framework of indicators is called the Design Policy Monitor. The findings from the Design Policy Monitor reveal that between 2012 and 2014 public expenditure on design in Denmark, Estonia, Finland and the UK increased by 34% compared to an increase of 8% for public expenditure on research and development (R&D). In a time of austerity, this funding increase is significant although overall government expenditure on R&D is more than 500 times greater than government expenditure on design. 3 Although the Design Policy Monitor remains theoretical, the Design Innovation Ecosystem construct and the indicators within the framework have been jointly developed and tested with innovation policy-makers, managers in design centres and academics. It has been subject to an iterative process of refinement and peer-review as part of a consensus-building exercise with expert stakeholders. With more data on design becoming available, it would be an ambition of the investigator to review the indicators and collect new data as part of future research. In taking a design-led approach, this research has also sought to explore and operationalise the Double Diamond process as a research framework. The Double Diamond is widely accepted as a process for design practitioners but there is only permissive consensus that the Double Diamond can also be applied as a design research framework. The concepts of design and policy are very closely intertwined; both are concerned with problem-solving and ideally, involving users in solving those problems. This body of work has sought to demonstrate that design is not only a method for user-centred research but also, by extension, a method for user-centred policy-making. This research has been conducted in parallel to leading the SEE Platform (Sharing European Experience in Design Innovation Policy), a network of 11 European partners, led by the investigator at PDR (the International Design and Research Centre) at Cardiff Metropolitan University. SEE was funded by the European Commission to the value of €1.1m between 2012 and 2015. As a result of workshops, research and advocacy the SEE partners successfully integrated design into 18 policies and 48 programmes at regional and national levels across Europe.

Production systems typically involve significant uncertainty in their operation due to either external or internal sources. The existence of uncertainty transforms conventional deterministic process models to stochastic/parametric problems, the solution of which requires the application of specialized optimization techniques. The main objective of this thesis is to develop suitable algorithms and numerical techniques for the efficient solution of process engineering problems involving uncertain parameters. Based on modelling issues regarding uncertainty classification (deterministic and stochastic uncertain parameters) and design objectives with respect to uncertainty (fixed degree of flexibility and optimal degree of flexibility), a unified multiperiod/stochastic two-stage optimization formulation is proposed and a decomposition based algorithmic procedure is developed for its efficient solution. The proposed algorithm forms the basis for addressing process design problems, planning and scheduling problems and problems related to behavioural analysis under uncertainty. For batch plant design problems involving uncertainty in the description of process parameters such as transfer coefficients, kinetic constants, etc., as well as variability of external parameters such as product demand, economic cost data etc., the exploitation of the special structure coupled with the relaxation of feasibility requirement regarding product demands enables the transformation of the stochastic two-stage programming problems to a single optimization model where the structure of the deterministic problem is fully preserved. For the case of continuous size of equipments, an efficient global optimization procedure is proposed, whereas for the case of discrete equipment sizes the algorithm reduces to the solution of a mixed integer linear programming problem. For short term production planning and long-range planning problems including capacity expansion options, the application of the proposed approach results in the optimal production plan (i. e. process utilization levels, purchases and sales of materials) and/or an optimal capacity expansion policy that maximize an expected profit and ensure an optimal level of future feasibility. Finally, an attempt to address the question of the future "value" of uncertainty is presented based on the concept of value of perfect information. It is shown that the proposed algorithmic developments can be effectively extended to include both the solution of the here-and-now and the wait-and-see models in order to analyze and integrate the

The importance of the changeover process in the manufacturing industry is becoming widely recognised. Changeover is a complete process of changing between the manufacture of one product to manufacture of an alternative product until specified production and quality rates are reached. The initiatives to improve changeover exist in industry, as better changeover process typically contribute to improved quality performance. A high-quality and reliable changeover process can be achieved through implementation of continuous or radical improvements. This research examines the changeover process of Saudi Arabian manufacturing firms because Saudi Arabia’s government is focused on the expansion of GDP and increasing the number of export manufacturing firms. Furthermore, it is encouraging foreign manufacturing firms to invest within Saudi Arabia. These initiatives, therefore, require that Saudi manufacturing businesses develop the changeover practice in order to compete in the market and achieve the government’s objectives. Therefore, the aim of this research is to discover the current status of changeover process implementation in Saudi Arabian manufacturing businesses. To achieve this aim, the main objective of this research is to develop a conceptual model to understand and examine the effectiveness of the changeover process within Saudi Arabian manufacturing firms, facilitating identification of those activities that affect the reliability and high-quality of the process. In order to provide a comprehensive understanding of this area, this research first explores the concept of quality management and its relationship to firm performance and the performance of manufacturing changeover. An extensive body of literature was reviewed on the subject of lean manufacturing and changeover practice. A research conceptual model was identified based on this review, and focus was on providing high-quality and reliable manufacturing changeover processes during set-up in a dynamic environment. Exploratory research was conducted in sample Saudi manufacturing firms to understand the features of the changeover process within the manufacturing sector, and as a basis for modifying the proposed conceptual model. Qualitative research was employed in the study with semi-structured interviews, direct observations and documentation in order to understand the real situation such as actual daily practice and current status of changeover process in the field. The research instrument, the Changeover Effectiveness Assessment Tool (CEAT) was developed to evaluate changeover practices. A pilot study was conducted by examining the CEAT, proposed for the main research. Consequently, the conceptual model was modified and CEAT was improved in response to the pilot study findings. Case studies have been conducted within eight Saudi manufacturing businesses. These case studies assessed the implementation of manufacturing changeover practice in the lighting and medical products sectors. These two sectors were selected based on their operation strategy which was batch production as well as the fact that they fulfilled the research sampling strategy. The outcomes of the research improved the conceptual model, ultimately to facilitate the firms’ adoption and rapid implementation of a high-quality and reliability changeover during the set-up process. The main finding of this research is that Quality’s factors were considering the lowest levels comparing to the other factors which are People, Process and Infrastructure. This research contributes to enable Saudi businesses to implement the changeover process by adopting the conceptual model. In addition, the guidelines for facilitating implementation were provided in this thesis. Therefore, this research provides insight to enable the Saudi manufacturing industry to be more responsive to rapidly changing customer demands.

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Over the last three decades the political economy debate abandoned its focus on manufacturing as the main engine of the technological dynamism and the source of the wealth of nations. However recent years have witnessed a renewed interest in manufacturing production. This has led analysts to announce and welcome a worldwide 'manufacturing renaissance' emerging in different contexts with multiple focuses. The thesis provides new analytical and empirical lenses for disentangling the dynamics of manufacturing development. We do this by showing how learning processes are the fundamental category responsible for production capabilities dynamics which in turn trigger structural change. Essay 1 'The Manufacturing Renaissance: Transforming Industrial Systems and the Wealth of Nations' presents a novel synthesis of two strands of economic research, Structural Economic Dynamics and the Economics of Capabilities. Within this framework we integrate structural change and production capabilities dynamics. The following Essays of this dissertation apply and extend this theoretical synthesis by focusing firstly on learning in production structures and cumulative (non-linear) structural change dynamics (Essays 2 and 3 respectively); secondly, in developing new diagnostics for industrial policies design (Essay 4); finally, in investigating industrial policies for manufacturing development (Essay 5). Essay 2 'Structural Learning: Embedding discoveries and the dynamics of production' extends the current framework by rembedding learning dynamics from which production capabilities are generated in the production structure itself. Essay 3 'Manufacturing Agrarian Change. Agricultural production, intermediate institutions and Intersectoral commons: Lessons from Latin America' than applies the concept of structural learning developed in Essay 2 to the intersectoral interdependencies on the interface of agriculture and manufacturing. Moreover, we show how in the context of Chile and Brazil intersectoral learning from which intersectoral commons derive was facilitated by the development of intermediate institutions. Essay 4 'Production Capability Indicators. Mapping countries' structural trajectories and the assessment of industrial skills in LDCs: The case of Tanzania' addresses the problem of capturing these learning dynamics through production capabilities indicators at the national level. Not only do we propose a new theoretically-sensitive methodology for quantifying learning dynamics but also we apply this to industrial skills assessment in Tanzania. Finally, Essay 5 'Industrial Policy for Manufacturing Development. Structural dynamics and institutional changes in a dual economy: A case of dependent industrialisation in the Italian Mezzogiorno' focuses on the development of industrial policies, the latter understood as mechanisms to trigger learning dynamics at the sectoral and intersectoral level. The Italian 'Mezzogiorno' case is presented to illustrate these dynamics in a context of dependent industrialisation.

The increasing trends of logistics outsourcing have forced logistics service providers (LSPs) to more effectively leverage their productive resources to provide superior service performance. The current logistics literature has identified some strategic logistics resources and their performance impacts but there is a lack of knowledge on the combined effects of such resources. The main objective of this research is to identify logistics resources - called resource-based logistics (RBL) – acquired by LSPs and to examine the impacts of RBL on logistics performance. Based on the resource-based view (RBV) theory, this research develops constructs and measurements for logistics resources (RBL) and logistics performance (LP) and further examines the impacts of RBL on logistics performance in terms of customer service innovation (customer service and service innovation) and cost leadership. Based on data from interviews and a survey of 123 Malaysian LSPs, factor analyses were used to establish five groups of logistics resources - technology, physical, management, relational and organizational resources, contributing to the development of constructs and measurements for logistics resources from the LSP perspective. While simple regression analyses suggest that each RBL was positively associated with customer service innovation and cost leadership, further stepwise regression analyses suggest customer service innovation was enhanced when organizational and technology resources were bundled together. These two resources largely mediated the relationships between physical, relational and management expertise and customer service innovation. Similarly, the analyses suggest that cost leadership was enhanced when organizational and management expertise resources were bundled together; these two resources mediated the relationships between technological, physical, and relational resources and cost leadership. The implications of the results for theory and practice are significant. This research provides empirical evidence for the development of a theoretical model for logistics resources grounded in RBV theory. The detailed bundling and mediating effects of logistics resources represent novel empirical evidence needed to enhance the understanding of LSP performance. This research recommends that LSPs should embark on developing capabilities in the five RBL. Especially, logistics managers should focus on developing and bundling their organizational, management and technology resources more effectively. In addition this research proposes a theoretical model for future research into the competitive advantage of LSPs.

In recent times large numbers of end-of-use/end-of-life returns have been the result of the increasing pressure from environmental legislations, particularly the directive on Waste Electrical and Electronic Equipment (WEEE) in the European Union. These returns incur acquisition costs and take-back operation costs regarded as a sunk cost by many industries. Thus, returned/recovered product valuation and marketing issues become crucial factors for survival and profitability of many firms in various sectors in today's competitive world . • The research undertaken is relevant as pricing and revenue management for recovered products. Indeed, this theme is considered as a niche research and the fifth phase (prices and markets) of the evolution of closed loop supply chain research. Hence, it has been noted as one of the most critical research areas in quantitative modelling for reverse logistics and closed loop supply chain management studies. The research area is in its early stage because it can be seen that only a handful of articles have been published in peer- reviewed international journals, exploring a pricing and marketing decision of recovered products. Hence, there are significant opportunities to conduct pricing and revenue management research in reverse logistics, particularly with regard to multiple recovery options. The primary objective of this research work is to formulate three pricing models by using a non-linear programming approach to determine optimal profit-maximising acquisition prices and selling prices, together with UK-based case studies in the mobile phone and computer recycling businesses. Moreover, this research aims to formulate two simulation models based on these case companies by investigating the impact of the uncertainty element in terms of return quantity and reprocessing time on firm's profit. The triangulation approach is employed, specifically the multi level model comprising case studies, questionnaire survey, and empirical quantitative models in order to address the principal research questions i.e. "What are optimal acquisition prices of received mobile phones and optimal selling prices of reprocessed handsets?", "What are optimal selling prices of • reprocessed computers?", and based on the total profit, "What if the model's parameters change?" The contribution of this research covers the generation of pricing and simulation models that are suitable for the recycled mobile phone and computer sector. The literature review discovers that the research on this subject lacks considerations of multiple recovery options, return rate and demand rate as exponential functions, recovery capacity limitation, product substitution policy, the element of uncertainty in terms of return quantity and reprocessing time, and multiple time periods. Hence, this research fulfils six main research gaps in academic literature as follows. First, this study takes multiple recovery options into account. Second, return and demand rate are modelled as an exponential function. Third, pricing and simulation models cope with a limit to recovery capacity. Fourth, models with product substitution policy are investigated. Fifth, the element of uncertainty in terms of return quantity and reprocessing time is added into proposed models. Finally, this study proposes models with multiple time periods. The results from this research work support current pricing and revenue management research and most importantly, the results generated from these proposed models can enhance managers' decision making in recovery operations and reverse logistics.