A systems thinking approach for modelling supply chain risk propagation

Supply Chain Risk Management (SCRM) is rapidly becoming a most sought after research area due to the influence of recent supply chain disruptions on global economy. The thesis begins with a systematic literature review of the developments within the broad domain of SCRM over the past decade. Thematic and descriptive analysis supported with modern knowledge management techniques brings forward seven distinctive research gaps for future research in SCRM. Overlapping research findings from an industry perspective, coupled with SCRM research gaps from the systematic literature review has helped to define the research problem for this study. The thesis focuses on a holistic and systematic approach to modelling risks within supply chain and logistics networks. The systems thinking approach followed conceptualises the phenomenon of risk propagation utilising several recent case studies, workshop findings and focus studies. Risk propagation is multidimensional and propagates beyond goods, finance and information resource. It cascades into technology, human resource and socio-ecological dimensions. Three risk propagation zones are identified that build the fundamentals for modelling risk behaviour in terms of cost and delay. The development of a structured framework for SCRM, a holistic supply chain risk model and a quantitative research design for risk assessment are the major contributions of this research. The developed risk assessment platform has the ability to capture the fracture points and cascading impact within a supply chain and logistics network. A reputed aerospace and defence organisation in UK was used to test the experimental modelling set up for its viability and for bridging the gap between theory and practice. The combined statistical and simulation modelling approach provides a new perspective to assessing the complex behavioural performance of risks during multiple interactions within network

ICT enabled approach for humanitarian disaster management: a systems perspective

Purpose Each stage in disaster management faces different challenges concerning information gathering, sharing, interpretation and dissemination. However, a comprehensive understanding of different information and communication technology (ICT) systems utilised for humanitarian disaster management is limited. Therefore, the paper follows a systems thinking approach to examine ten major man-made and/or natural disasters to comprehend the influence of ICT systems on humanitarian relief operations. Design/methodology/approach A longitudinal, multi-case study captures the use of ICT tools, stakeholders involvement, disaster stages and zones of operations for relief operations over the past two decades. A systems thinking approach is utilised to draw several inferences and develop frameworks. Findings Multiple ICT tools such as geographic information systems, online webpages/search engines, social media, unmanned aerial vehicles/robots and artificial intelligence are used for rapid disaster response and mitigation. Speed and coordination of relief operations have significantly increased in recent years due to the increased use of ICT systems. Research limitations/implications Secondary data on the past ten disasters is utilised to draw inferences. The developed ICT-driven model must be validated during upcoming humanitarian relief operations. Practical implications A holistic understanding of a complex inter-relationship between influential variables (stakeholders, disaster stages, zones of operation, ICT systems) is beneficial for effectively managing humanitarian disasters. Originality/value Broadly classifying the ICT systems into surveillance, decision support and broadcasting systems, a novel ICT-enabled model for humanitarian relief operations is developed

An integrated Bayesian-Markovian framework for ascertaining cost of executing quality improvement programs in manufacturing industry

Purpose Typically, the budgetary requirements for executing a supplier’s process quality improvement program are often done in unstructured ways in that quality improvement managers purely use their previous experiences and pertinent historical information. In this backdrop, the purpose of this paper is to ascertain the expected cost of carrying out suppliers’ process quality improvement programs that are driven by original equipment manufacturers (OEMs). Design/methodology/approach Using inputs from experts who had prior experience executing suppliers’ quality improvement programs and employing the Bayesian theory, transition probabilities to various quality levels from an initial quality level are ascertained. Thereafter, the Markov chain concept enables the authors to determine steady-state probabilities. These steady-state probabilities in conjunction with quality level cost coefficients yield the expected cost of quality improvement programs. Findings The novel method devised in this research is a key contribution of the work. Furthermore, various implications related to experts’ inputs, dynamics related to Markov chain, etc., are discussed. The method is illustrated using a real life of automotive industry in India. Originality/value The research contributes to the extant literature in that a new method of determining the expected cost of quality improvement is proposed. Furthermore, the method would be of value to OEMs and suppliers wherein the quality levels at a given time are the function of quality levels in preceding period(s)

Managing risks in next generation supply chains: a systems approach

Supply chain risk management follows three basic processes to manage supply chain risks: Identify, Assess and Mitigate. This paper considers a systems perspective towards managing these risks. It presents variables that may affect Next Generation Supply Chains and applies a System dynamics modelling approach (Oehmen, et. al. 2009) towards depicting the causal linkages of these variables with future supply disruptions. To understand the interdependencies within these factors and the risk propagation on account of these factors it was decided to adopt a systems perspective. This perspective is based upon application of a causal loop diagram which considers the interdependencies between the factors affecting next-generation supply chains. The causal linkages between the variables are then highlighted with regards to the supply chain process and the nodes, and the causes of future risks are identified

Service provider boundaries in competitive markets: the case of the logistics industry

The study empirically investigates service provider firms’ attempts to move to higher value added market segments in competitive and fragmented markets; using logistics services as a context. Novelty is added by taking the provider not the customer or outsourcing actor perspective, common to current third-party logistics perspectives. Data were collected in the form of semi-structured interviews with management at various provider firms. The interview guide was based on theoretical constructs regarding tangible and intangible capabilities (RBV) as well as constructs related to governance and integration (TCE). Unlike customer focused studies, this study is able to identify what distinguishes the rare successful boundary crossing attempts that lead to a more profitable market position. The key finding which contradicts studies based on the customer/outsourcing actor perspective, is that a switch from a highly commoditized market position to a higher margin position is only possible, if relationships and network capabilities are leveraged, regardless of the assets and physical resources available to the firm. The presentation of service boundaries as both dynamic and fluid and the use of RBV are contributions, building on existing theory, illustrating why providers of commoditized services cannot escape from low-margin, competitive market positions simply by acquiring tangible assets

A supplier performance evaluation framework using single and bi-objective DEA efficiency modelling approach: individual and cross-efficiency perspective

In view of complexities associated with supplier performance evaluation based on traditional business criterions (such as costs, quality levels, and delivery timelines) and emerging criterions (such as those related to environmental sustainability), we in this research evolve two different supplier efficiency measurement models that unify such criterions possessing characteristics of both desirable and undesirable outputs. The first model is a single-objective DEA efficiency assessment model wherein both types of outputs are integrated into a single composite efficiency measure. Using data from suppliers of Hyundai Steel Company, we determine composite efficiencies of each of these suppliers thus ranking them in terms of an overall efficiency score that would be useful as far as the first-cut supplier discrimination is concerned. However, due to the relative inability of evolved single-objective efficiency model to perform trade-offs amongst desirable and undesirable outputs and, owing to unidimensionality aspects, we evolve a goal programming based bi-objective efficiency model wherein trade-offs can be performed between both conventional and emerging dimensions criterions leading to different supplier evaluations for varied scenarios. We also integrate our evolved models with the cross-efficiency view of efficiency determination in order to enable the decision-makers to achieve peer-to-peer evaluation and maximum discrimination amongst suppliers

A data mining-based framework for supply chain risk management

Increased risk exposure levels, technological developments and the growing information overload in supply chain networks drive organizations to embrace data-driven approaches in Supply Chain Risk Management (SCRM). Data Mining (DM) employs multiple analytical techniques for intelligent and timely decision making; however, its potential is not entirely explored for SCRM. The paper aims to develop a DM-based framework for the identification, assessment and mitigation of different type of risks in supply chains. A holistic approach integrates DM and risk management activities in a unique framework for effective risk management. The framework is validated with a case study based on a series of semi-structured interviews, discussions and a focus group study. The study showcases how DM supports in discovering hidden and useful information from unstructured risk data for making intelligent risk management decisions

Product bundling and advertising strategy for a duopoly supply chain: A power-balance perspective

The paper studies product bundling in a duopoly supply chain network under the influence of different power-balance structures, bundling decisions and advertising efforts on total supply chain profit. Mathematical models comprising two manufacturers and a single retailer are developed to capture the impact of bundling policy and advertisement strategy under three power-balance structures, namely Manufacturer Stackelberg, Retailer Stackelberg and Vertical Nash. Following game theory models and numerical examples, the study found that the total profit of the supply chain is undifferentiated under the manufacturer Stackelberg and Vertical Nash case in the manufacturer bundling and retailer bundling strategies. However, total supply chain profit under manufacturer bundling strongly dominates under retailer bundling in Retailer Stackelberg and Vertical Nash, and remains valid under multiple settings of market size, price elasticity and advertising elasticity. It is also found that manufacturer bundling is significantly affected by advertising effort compared to retailer bundling. The study contributes to the literature interfacing supply chain and marketing by studying bundling policy and advertising strategy simultaneously for homogenous products, under various power-balance structures and price competitio