Supply chain integration strategies in fast evolving industries

Purpose - The purpose of this paper is to define the "fast evolving industry" (FEI) and its supply chain management (SCM) challenges. The authors review and structure the literature regarding integration strategies and implementation methods to develop a strategic decision-making framework for SCM in the FEI. Design/methodology/approach - The authors conduct a review of SCM literature, including supply chain strategy, supply chain integration (SCI), agile and responsive supply chain and SCM for innovative and fast-changing industries. The authors develop a conceptual model and a decision-making framework and use four mini cases to provide support for the model and framework. Findings - The FEI, characterised by a high level of innovation and differentiation, short products/services lifecycle and high variety, is yet to be fully defined. Inherent uncertainty in FEI supply systems makes SCM in these industries a complex but strategic task for their managers. The framework and the model offered in this study, which employ a core competency concept and provide risk management strategies, offer a strategic tool for managers and scholars in the field to optimise their integration strategies and to operationalise integration decisions. Originality/value - Little research has been published on transferable and cross-industrial SCM in FEIs. This paper defines the FEI and its resource-related concerns and then offers a conceptual model and a strategic decision-making framework for SCI in FEIs

Supply chain integration strategies in fast evolving industries

Purpose – We aim to define the ‘fast-evolving-industry’ (FEI) and its supply chain management (SCM) challenges. We review and structure the literature regarding integration strategies and implementation methods to develop a strategic decision-making framework for SCM in the FEI. Design/methodology/approach – We conduct a review of SCM literature, including supply chain strategy, supply chain integration (SCI), agile and responsive supply chain and SCM for innovative and fast-changing industries. We develop a conceptual model and a decision-making framework and use four mini cases to provide support for the model and framework. Findings – The FEI, characterised by a high level of innovation and differentiation, short products/services lifecycle and high variety, is yet to be fully defined. Inherent uncertainty in FEI supply systems makes SCM in these industries a complex but strategic task for their managers. The framework and the model offered in this study, which employ a core competency concept and provide risk management strategies, offer a strategic tool for managers and scholars in the field to optimise their integration strategies and to operationalise integration decisions. Original Value – Little research has been published on transferable and cross-industrial SCM in Fast Evolving Industries (FEIs). This paper defines the FEI and its resource-related concerns and then offers a conceptual model and a strategic decision-making framework for SCI in FEIs

Delivery time dynamics in an assemble-to-order inventory and order based production control system

System dynamics play a critical role in influencing supply chain performance. However, the dynamic property of the assemble-to-order (ATO) system remain unexplored. Based on control theory, the inventory and order based production control system (IOBPCS) family, can be utilized as a base framework for assessing system dynamics. However, the underlying assumption in traditional IOBPCS-based analytical studies is that the system is linear and the delivery time to end customers is negligible or backlog is used as a surrogate indicator. Our aim is to incorporate customer delivery lead-time variance as the third assessment measure alongside capacity availability and inventory variance as part of the so-called ‘performance triangle’– capacity at the supplier, the customer order decoupling point (CODP) inventory and the delivery lead-time. Using the ‘performance triangle’ and adopting non-linear control engineering techniques, we assess the dynamic behaviour of an ATO system in the electronics sector. We benchmark the ATO system dynamics model against the IOBPCS family. We exploit frequency response analysis to ensure a robust system design by considering three measures of the ‘performance triangle’. The findings suggest delivery LT variance can be minimised by maintaining the ATO system as a true Push-Pull hybrid state with sufficient CODP stock, although increased operational cost driven by bullwhip and CODP variance need to be considered. However, if the hybrid ATO system 'switches' to the pure Push state, the mean and variance of delivery LT can be significantly increased

System dynamics modelling, analysis and design of assemble-to-order supply chains

Background and purpose: The assemble-to-order supply chains (ATO) is commonly-adopted in personal computer (PC) and semiconductor industries. However, the system dynamics of PC and semiconductor ATO systems, one of the main sources of disruption, is not well-explored. Thereby this thesis aims to 1) develop a nonlinear system dynamics model to represent the real-world PC and semiconductor ATO systems, 2) explore the underlying mechanisms of ATO system dynamics in the nonlinear environment and 3) assess the delivery lead times dynamics, along with bullwhip and inventory variance. Design/methods: Regarding the semiconductor industry, the Intel nonlinear ATO system dynamics model, is used as a base framework to study the underlying causes of system dynamics. The well-established Inventory and Order based Production Control System archetypes, or the IOBPCS family, are used as the benchmark models. Also, the IOBPCS family is used to develop the PC ATO system dynamics model. Control engineering theory, including linear (time and frequency response techniques) and nonlinear control (describing function, small perturbation theory) approaches, are exploited in the dynamic analysis. Furthermore, system dynamics simulation is undertaken for cross-checking results and experimentation. Findings: The ATO system can be modelled as a pull (order driven) and a push (forecasting driven) systems connected by the customer order decoupling point (CODP). A framework for dynamic performance assessment termed as the ‘performance triangle’, including customer order delivery lead times, CODP inventory and bullwhip (capacity variance), is developed. The dynamic analysis shows that, depending on the availability of CODP Abstract iii inventory, the hybrid ATO system state can be switched to the pure push state, creating poor delivery lead times dynamics and stock-out issues. Limitations: This study is limited to the analysis of a closely-coupled two-echelon ATO systems in PC and semiconductor industries. Also, the optimization of control policies is not considered. Practical implications: Maintaining a truly ATO system state is important for both customer service level and low supply chain dynamics cost, although the trade-off control design between CODP inventory and capacity variance should be considered. Demand characteristics, including variance and mean, play an important role in triggering the nonlinearities present in the ATO system, leading to significant change in the average level of inventory and the overall transient performance. Originality / value: This study developed system dynamics models of the ATO system and explored its dynamic performance within the context of PC and semiconductor industries. The main nonlinearities present in the ATO system, including capacity, non-negative order and CODP inventory constraints, are investigated. Furthermore, a methodological contribution has been provided, including the simplification of the high-order nonlinear model and the linearization of nonlinearities present in the ATO system, enhancing the understanding of the system dynamics and actual transient responses. The ‘performance triangle’ analysis is also a significant contribution as past analytical studies have neglected customer order lead time variance as an inclusive metric

Supply chain adaptability in the mobile phones industry

Propósito: A presente investigação participa da discussão da adaptabilidade no estudo da Gestão da Cadeia de Abastecimento e relacionamentos colaborativos entre fornecedores e clientes quer externos ou internos no contexto da indústria de telefones celulares. Metodologia de investigação: Após a revisão da literatura relevante sobre as consequências do acoplamento rígido e ágil na cadeia de abastecimento elaborou-se a seguinte pergunta de investigação: como adaptar a procura na rede de abastecimento de forma a permitir utilizar os recursos disponíveis e maximizar a disponibilidade de produto nos diferentes canais de produção da indústria de telefones celulares? Recorreu-se ao método do Estudo de Caso com carácter exploratório para conduzir o presente estudo. Resultados obtidos: O estudo evidenciou com base em observações dum caso empresarial que é possível aos gestores fazerem modificações no sentido de criar adaptabilidade e desacoplar os sistemas trazendo-os de uma característica de rigidez a uma condição de flexibilidade. Limitações: A investigação em questão limitou-se a observar num unico caso os acontecimentos em questão sob a óptica qualitativa baseada na experiência do pesquisador. A utilização de um maior número de evidencias poderia contribuir para evidenciar melhor as questões intrínsecas do caso. A impossibilidade do pesquisador de revelar todos os dados empresariais por motivos de confidencialidade causou algum impacto na exemplificação do pretendido. Implicações praticas: Os resultados podem contribuir para que os gestores na área de Cadeia de Abastecimento possam encontrar referências para resolver problemas similares em suas respectivas áreas ou tão somente provocar a discussão interna dos temas abordadosPurpose – The present research participates in discussions in the adaptability on the study of Supply Chain Management and Buyer-Supplier collaborative internal or external relationships in the context of the mobile phones Industry Design/methodology/approach – After the review of the relevant literature on tight and loose coupling in Supply Chain Management, the following research questions was raised: “How to adapt the demand supply network in order to utilize the resources available and maximize product availability in different channels of the mobile phones industry?” As research methodology, it was utilized the current Thesis the Single exploratory Case Study, with explanatory characteristics Findings – The study has generated evidences that is possible for managers to modify and adapted the supply chain processes in order to bring them from a tight to a loose coupling characteristic. Research limitations/implications – The research was limited in observing the events in a single case under the qualitative aspect based in the experiences of the researcher. The utilization of a higher number of evidences could certainly have contributed in creating further insights about the case. Elements of data confidentiality and the lack of possibility of the researcher to reveal some aspects involved in the case also contributed to limit the description of certain examples of the case, which could not be made to the full extent. Practical implications – The results encourage managers to use to find references to solve similar problems in their respective areas and also can foster internal discussions on the topics referred in this stud

Optimising Supply Chain Performance via Information Sharing and Coordinated Management

Supply chain management has attracted much attention in the last decade. There has been a noticeable shift from a traditional individual organisation-based management to an integrated management across the supply chain network since the end of the last century. The shift contributes to better decision making in the supply chain context, as it is necessary for a company to cooperate with other supply chain members by utilising relevant information such as inventory, demand and resource capacity. In other words, information sharing and coordinated management are essential mechanisms to improve supply chain performance. Supply chains may differ significantly in terms of industry sectors, geographic locations, and firm sizes. This study was based on case studies from small and medium sized manufacturing supply chains in People Republic of China. The study was motivated by the following facts. Firstly, small and medium enterprises have made a big contribution to China’s economic growth. Several studies revealed that most of the Chinese manufacturing enterprises became aware of the importance of supply chain management, but compared to western firms, the supply chain management level of Chinese firms had been lagging behind. Research on supply chain management and performance optimisation in Chinese small and medium sized enterprises (SMEs) was very scarce. Secondly, there had been plenty of studies in the literature that focused on two or three level supply chains whilst considering a number of uncertain factors (e.g. customer demand) or a single supply chain performance indicator (e.g. cost). However, the research on multiple stage supply chain systems with multiple uncertainties and multiple objectives based on real industrial cases had been spared and deserved more attention. One reason was due to the lack of reliable industrial data that required an enormous effort to collect the primary data and there was a serious concern about data confidentiality from the industry aspect. This study employed two SME manufacturing companies as case studies. The first one was in the Aluminium industry and another was in the Chemical industry. The aim was to better understand the characteristics of the supply chains in Chinese SMEs through performing in-depth case studies, and built models and tools to evaluate different strategies for improving their supply chain performance. The main contributions of this study included the following aspects. Firstly, this study generalised a supply chain model including a domestic supply chain part and an international supply chain part based on deep case studies with the emphasis on identifying key characteristics in the case supply chains, such as uncertainties, constraints and cost elements in association with flows and activities in the domestic supply chain and the international supply chain. Secondly, two important SCM issues, i.e. the integrated raw material procurement and finished goods production planning, and the international sales planning, were identified. Thirdly, mathematical models were formulated to represent the supply chain model taking into account multiple uncertainties. Fourthly, several operational strategies utilising the concepts of just-in-time, safety-stock/capacity, Kanban, and vendor managed inventory, were evaluated and compared with the case company's original strategy in various scenarios through simulation methods, which enabled quantification of the impact of information sharing on supply chain performance. Fifthly, a single objective genetic algorithm was developed to optimise the integrated raw material ordering and finished goods production decisions under (s, S) policy (a dynamic inventory control policy), which enabled the impact of coordinated management on supply chain performance to be quantified. Finally, a multiple objectives genetic algorithm considering both total supply chain cost and customer service level was developed to optimise the integrated raw material ordering and finished goods production with the international sales plan decisions under (s, S) policy in various scenarios. This also enabled the quantification of the impact of coordinated management on supply chain performances