Decarbonising product supply chains design and development of an integrated evidence based decision support system the supply chain environmental

International Journal of Production Research ISSN: 0020-7543 (Print) 1366-588X (Online) Journal homepage: https://www.tandfonline.com/loi/tprs20 Decarbonising product supply chains: design and development of an integrated evidencebased decision support system – the supply chain environmental analysis tool (SCEnAT) S.C Lenny Koh , Andrea Genovese , Adolf A Acquaye , Paul Barratt , Nasir Rana , Johan Kuylenstierna & David Gibbs To cite this article: S.C Lenny Koh , Andrea Genovese , Adolf A Acquaye , Paul Barratt , Nasir Rana , Johan Kuylenstierna & David Gibbs (2013) Decarbonising product supply chains: design and development of an integrated evidence-based decision support system – the supply chain environmental analysis tool (SCEnAT), International Journal of Production Research, 51:7, 2092-2109, DOI: 10.1080/00207543.2012.705042 To link to this article: https://doi.org/10.1080/00207543.2012.705042 Published online: 03 Aug 2012 Submit your article to this journal Article views: 1145 View related articles Citing articles: 45 View citing articles Full Terms & Conditions of access and use can be found at https://www.tandfonline.com/action/journalInformation?journalCode=tprs20 International Journal of Production Research, 2013 Vol 51, No 7, 2092–2109, http://dx.doi.org/10.1080/00207543.2012.705042 Decarbonising product supply chains: design and development of an integrated evidence-based decision support system – the supply chain environmental analysis tool (SCEnAT) S.C Lenny Koha*, Andrea Genovesea, Adolf A Acquayea, Paul Barrattb, Nasir Ranaa, Johan Kuylenstiernac and David Gibbsb a Logistics and Supply Chain Management (LSCM) Research Centre, Centre for Energy, Environment and Sustainability (CEES), Management School, University of Sheffield, Sheffield, UK; bDepartment of Geography, University of Hull, Kingston Upon Hull, Hull, UK; cStockholm Environment Institute, University of York, Grimston House, York, UK (Received May 2012; final version received June 2012) Based upon an increasing academic and business interest in greening the industrial supply chains, this paper establishes the need for a state-of-the-art decision support system (DSS) for carbon emissions accounting and management, mainly across the product supply chains by identifying methodological shortcomings in existing tools, and proposing a supply chain (SC) framework which provide businesses with a holistic understanding of their supply chains and ensuring partners within supply chain collaborative networks have a shared understanding of their emissions It describes the design and development of a DSS now known as supply chain environmental analysis tool (SCEnAT) in detail, putting its unique and innovative features into a comparative perspective vis-a`-vis existing tools and software of different types The methodological framework used to design and develop SCEnAT integrates different individual techniques/methods of supply chain (SC) mapping, SC carbon accounting, SC interventions and SC interventions evaluation on a range of key performance indicators (KPIs) These individual methods have been used and applied innovatively to the challenge of designing SCEnAT within the desired framework Finally, we demonstrate the application of SCEnAT, especially the advantage of using a robust carbon accounting methodology, to a SC case study The SCEnAT framework pushes the theoretical boundary by addressing the problems of intraorganisational approach in decision making for lowering carbon along the supply chain; with an open innovation, cutting edge, hybridised framework that considers the supply chain as a whole in co-decision making for lowering carbon along the supply chain with the most robust methodology of hybrid life cycle analysis (LCA) that considers direct and indirect emissions and interventional performance evaluation for low carbon technology investment and business case building in order to adapt and mitigate climate change problems This research has implications for future sustainability research in SC, decisions science, management theory, practice and policy Keywords: SC management; SC decarbonisation; decision support system; SC mapping; SC carbon accounting; SC low carbon interventions Introduction In recent years, an increasing environmental and ethical awareness has favoured the emergence of new ways of conducting business and operations Indeed, there is a growing consensus that firms should not only be managed efficiently, but also behave in a sustainable way This means adhering to the ‘triple bottom line’ framework; that is, taking into account social and environmental issues in performance evaluation in addition to economic assessments At the same time, it has been understood that these objectives cannot be achieved by just optimising performance at the firm level The complexity of contemporary value creation processes implies that the transition to a sustainable way of conducting business can be completed only by adopting collaborative approaches encompassing the whole value creation activity within supply chain scenarios (Vachon and Klassen 2007) Therefore, as a result of these two different phenomena, academic and corporate interest in green and sustainable supply chain management has risen considerably in recent years (Hervani et al 2005, Vachon 2007, Koh et al 2011, Bai et al 2012, Shi et al 2012) Some common themes within the sustainable supply chain literature have started to emerge, even though most of the literature, until now, has addressed single corporate functions; for instance, purchasing (Ciroth et al 2002), logistics (Weidema 1998), and product development (Osse´s de Eicker et al 2010) instead of focusing on an entire *Corresponding author Email: S.C.L.Koh@sheffield.ac.uk ß 2013 Taylor & Francis International Journal of Production Research 2093 supply chain system Thus, sustainable supply chain is still an evolving field of study, in which there is a lack of unifying theories Therefore, it is not surprising that attempts to de-carbonise supply chains have not been supported by the presence of instruments capable of identifying carbon creation hot-spots at a supply chain level and suggesting interventions to target them This study will attempt to fill this gap, by illustrating the methodological framework of a decision support system that can provide insights to collaborative networks of firms for informed decision making in de-carbonising operations at a supply chain level The remainder of the paper is organised as follows In the next two sections, a brief literature review highlighting the sustainable supply chain concept and the need for decision support system for greening operations in supply chain will be presented; then, the complete methodological framework underlying the proposed decision support system will be illustrated A case study concerning the decarbonisation of a supply chain of a malting firm will be then shown, allowing for some conclusions Sustainable supply chain management: introduction and evolution Academic and corporate interest in sustainable and green supply chain management has risen considerably in recent years (Hsu et al 2009, Lyon and Maxwell 2011, Muntons plc 2011) This can be seen looking at the consistent increase in papers published on this topic in international journals (Seuring and Muăller 2008) However, clear and well-accepted definitions about this field are still lacking To this end, international peer reviewed scientific journals have been reviewed, looking for the key-words: Green/ Sustainable/Low Carbon Supply Chain Management Framework The results of this process reveal that Green/ Sustainable/Low Carbon Supply Chain is still an evolving field of study, in which there is a lack of unifying theories Some common themes within the green supply chain literature have started to emerge, even though most of the literature has addressed a single corporate function instead of focusing on an entire supply chain Therefore, there is the need for classifying the existing frameworks according to an evolutionary perspective based on two dimensions: The scope of the framework, namely the width of the operations and corporate functions that are included and considered The degree of sustainability awareness, namely the extent to which sustainability issues are considered In this way, it is possible to classify frameworks according to a two-axis diagram: on the horizontal one (abscissa), the scope is reported; on the vertical one (ordinate), the sustainability awareness is accounted for For example, Carter and Jennings (2002a, 2004) introduce the ‘corporate socially responsible purchasing and logistics’ framework They evaluate the impact of purchasing and logistics decisions on several dimensions, such as diversity, human rights, philanthropy and safety Interestingly, the environmental dimension is also cited Then, by broadening the scope, Carter and Jennings (2002b) define the ‘corporate socially responsible supply chain’, focusing on CSR issues throughout the whole supply chain, by measuring the performance across the above-mentioned dimensions not only at the focal firm but along the whole value creation process In Figure 1, the paper is reported Sustainability Awareness Sustainable Purchasing Sustainable Supply Chain CSR Purchasing CSR Supply Chain Green Purchasing Green Supply Chain Scope Figure Green/CSR/sustainable supply chain frameworks classification 2094 S.C.L Koh et al in the centre-right corner as it covers a wide scope, but mainly considers social issues and, slightly, environmental ones In the same way, Carter and Jennings (2004) framework about ‘corporate socially responsible purchasing’ is classified in the centre-left corner, as it is focused just on one corporate function (purchasing) rather than the whole supply chain, and it takes into account social (and, slightly, environmental) responsibility Zsidisin and Siferd (2001) talk about environmental and green purchasing defining it as ‘a subset of Green Supply Chain management’ They account, in great detail, for green and environmental issues, but completely discard social ones This way, ideally, this framework should be reported in the bottom-left corner Coherently, Hervani et al (2005) define green supply chain management as the ‘addition of the Green component to supply chain management, addressing the influence and relationships of supply chain management to the natural environment Motivated by an environmentally-conscious mindset, it can also stem from a competitiveness motive within organisation’ In particular, they introduce the following conceptual equation: Green Supply Chain Management ẳ Green Purchasing ỵ Green Manufacturing þ Materials Management þ Green Distribution and Marketing þ Reverse Logistics’ For this reason, green supply chain management includes (as already mentioned by Zsidisin and Siferd 2001) the subsets of all the mentioned sub-disciplines Tsoulfas and Pappas (2008) introduce a comprehensive set of metrics for evaluating the environmental performance of a supply chain across all the dimensions identified by Hervani et al (2005) Therefore, papers like these are classified in the bottom-right corner, as they cover a wide scope (the whole supply chain) by just addressing green and environmental issues (discarding the social issues) Seuring et al (2008) work introduces an even more complete definition, that describes sustainable supply chain management as the management of material, information and capital flows as well as cooperation among companies along the supply chain while taking goals from all three dimensions of sustainable development, i.e., economic, environmental and social, into account which are derived from customer and stakeholder requirements Therefore, in sustainable supply chains, environmental and social criteria need to be fulfilled by the members to remain within the supply chain, while it is expected that competitiveness would be maintained through meeting customer needs and related economic criteria Therefore, this definition ‘includes’ the ones of green supply chain management and corporate socially responsible (CSR) supply chain management and it is reported in the upper right corner in the chart (Figure 1) However, several papers develop sustainability-related frameworks and models for single functions in a supply chain, like sustainable logistics (Frota Neto et al 2008) and sustainable purchasing Coherently, these approaches should be reported in the upper left quadrant The definition provided by Zsidisin and Siferd (2001) highlights the need for co-operation and collaboration across the supply chain for achieving the objective of sustainable supply chains Indeed, Vachon and Klassen (2007) show that supply chain performances from a sustainability point of view are strongly influenced by the degree of collaboration among supply chain actors More specifically, collaboration can be deEned as the direct involvement of an organisation with its suppliers and customers in planning jointly for identifying and implementing opportunities for sustainability management and environmental solutions Collaboration also includes the exchange of technical information (regarding the production processes) and a mutual willingness to learn about mutual supply chain interactions, in order to plan and set goals for environmental improvement (Vachon and Klassen 2007) It also implies co-operation to reduce the environmental impact associated with material Fows in the supply chain (Carter and Carter 1998) and a good understanding of mutual responsibilities and capabilities Decision support system (DSS) for sustainable supply chains: state-of-the-art The above-mentioned theoretical debates within the academic literature regarding sustainable supply chain management, and the increasing number of regulatory measures in the public policy circles, particularly within the European context, has helped create a demand for methods and tools for carbon emission calculations Nevertheless, the previously described lack of unifying theories in the field of sustainable supply chain management also influences the development of these tools Indeed, very few calculation methodologies involve adherence to PAS 2050 (International Standard Organization 1998) However, even the methodological basis underpinning PAS 2050 (that is, process lifecycle assessment methodology) has been described by Berners-Lee et al (2011) and Censa (2010) as suffering from system boundary truncation error In this paper, the development of SCEnAT tries to address a major part of these limitations employing a comprehensive approach to emission estimations and supporting the search for appropriate solutions International Journal of Production Research 2095 From another perspective, the review of available approaches shows that a great majority of these carbon emission reduction/management tools and software have been devised with the focus only on the focal firm (that is, the main firm delivering the main product associated with the supply chain), while it is now widely accepted that a broader perspective to address the problems of environmental efficiency associated with the delivery of a finished product is more effective than focusing on the operations of an individual firm/link in the chain (Hameri and Paatela 2005, Bayraktar et al 2009) Indeed, by focusing on the single-firm dimension, these tools are completely missing the collaborative dimension that the above-mentioned literature has shown to be crucial for any attempt to achieve more sustainable supply chains However, there are limited exceptions and recently some studies have been published which take a whole supply chain perspective to the issue of carbon emission calculations (Acquaye et al 2011) Most of the tools available on the market focus only on carbon emissions calculations; hence there is a need to distinguish between emission calculation and management, with more emphasis placed on the latter Furthermore, treating carbon calculation and carbon management separately or as separate functions encourages the modular approach which does not fit comfortably within a supply chain framework and analysis, and aggravate the system boundary issue and data truncation problem further Therefore, there is the need for an integrative approach to carbon emission accounting and management along a supply chain with a view to evaluate and upgrade its performance on a comprehensive sustainability metric The range of the foregoing issues has also shaped the critical perspective with which the available carbon accounting literature and tools have been reviewed in the following There is little academic literature which specifically concerns the development or design of carbon accounting tools or calculators Key word searches for this purpose (for example, utilising the web-based search engine ScienceDirect) returned little or no relevant literature To complement this, internet searches were run with various key words and the assessments that follow are based on a review of the results of those internet searches which threw up an array of types of carbon emission calculation calculators/tools Taking an inventory of the search results and classifying them into major categories of tools is a difficult task To handle such a large volume of data and make sense of the ensuing complexity, it was thought appropriate to categorise all the results into four methodology-based major leagues of tools First of these methodologies is a simple energy consumption based formula (which in turn is based on emission factors of certain energy types embedded into a formulae) to calculate the emission from certain activities This approach to carbon calculation is also characterised by inflexibility and is exemplified by many carbon calculators available in the market space Focusing on a particular economy sector, the second methodological approach builds a database of greenhouse gases (GHG) emissions for major economic activities in a particular sector The database can be flexibly manipulated and using the formula-based calculator, calculate the GHG emissions including carbon Compared with the first approach, this methodology affords some degree of flexibility in determination of carbon emission for different situational demands A prototype of this approach is an Emissions Inventory Tool (EMIT)1 developed by Cambridge Environmental Research Consultants (CERC) in the UK The third approach identified in this research is a host of modelling software which takes a supply chain view of emission calculation but stops short in its application beyond the sector it was developed or intended for As its methodological engine, it adopts lifecycle assessment (LCA) to cover emissions beyond the focal firm and over a good part of the upstream supply chain An example of such software is a modelling package developed by AB Agri.2 The final approach takes a supply chain perspective, adopts LCA methodology and covers more than one economy sector in its emission estimations This approach can be regarded as quite comprehensive as it follows the emission estimation with suggestions of some interventions at macro level and tries to point to the environmental as well as economic impacts of interventions to be made This research work was recently developed at the University of Manchester under a project called Carbon Calculations over the Life Cycle (CCalC)3 of industrial activities It is our considered view that a tool or software should be judged on the strength and sophistication of the methodology it brings to the state of the practice in the fields of carbon emission management and decarbonisation of supply chains The above literature review finding formed that basis for the subsequent conception, design and development of SCEnAT In the following sections the methodological issues associated with the development of SCEnAT as a package, its individual components/modules and their integration are presented 2096 S.C.L Koh et al 3.1 Methodological framework of the DSS (or SCEnAT) for decarbonising supply chains SCEnAT works on the principle that in order to decarbonise the supply chain for a product, the product lifecycle (including the sources and levels of carbon emissions) must be fully understood by all the actors within a supply chain through a collaborative effort (Vachon and Klassen 2007) According to Beamen (1999) and Linton et al (2007) green supply chain management describes the integration of environmental thinking into supply chain management, including design, supplier selection and sourcing of raw materials, manufacturing processes, packaging, delivery of the product to the consumers and end-of-life management of the product after its use The aim of the DSS or SCEnAT presented in this paper is to provide insights and evidence to collaborative supply chains for informed decision making in greening operations at a supply chain level The methodological framework underpinning SCEnAT is composed of the following logical steps (see also Figure 2): Supply chain mapping Devoted to the reproduction and the representation of the operation flows across the whole supply chain thanks to information exchange among focal firm and suppliers Carbon calculation across the supply chain Oriented to the identification of the carbon hot-spots (that is the high carbon emissions inputs/paths or processes) across the entire supply chain using a hybrid LCA methodology; Identification of potential Interventions Aimed at targeting carbon hot-spots and reducing their emissions through appropriate low carbon interventions Supply chain performance evaluation Devoted to the assessment of the performance of the supply chain using key performance indicators 3.1.1 Supply chain mapping Understanding the environmental impacts of a supply chain starts with a collaborative effort aimed at mapping of the supply chain In producing a supply chain map, the following have to be traced: the origin of each product component back to its original source, identifying the companies involved, their mutual relationships; materials and energy usage at each level of the supply chain; focal company manufacturing processes; product deliveries and transportation activities throughout the whole supply chain and reverse flows (disposal, recycling, waste) Fundamentally, in this framework, the supply chain can be represented through a network, in which nodes reproduce the actors (focal firm, suppliers, customers) and oriented edges account for flows (materials, transportation, energy, waste) within the chain Acquired data can be organised in matrix structures A matrix representation for material transfer is shown in Table Elements on the rows represent origins, while elements on the columns represent destinations The matrix accounts for quantities of a given material transferred from an origin Supply Chain Mapping Informed Decision Making Supply Chain Carbon Calculations Table Supply chain material transfer matrix FF S11 S12 ÁÁÁ ÁÁÁ Snk Supply Chain Performance Evaluation Low Carbon Interventions Figure Methodological framework of the decision support system FF S11 S12 ÁÁÁ ÁÁÁ Snk Q 0 0 0 0 K 0 0 0 0 0 0 0 0 0 0 0 0 International Journal of Production Research 2097 i to a destination j Similar matrices can be developed to show relationships between actors in the supply chain, transportation activities, energy use and waste production within the supply chain These raw data provide the network structure for the supply chain map and the input into the carbon accounting module of SCEnAT in the base case scenario The supply chain carbon map can be enhanced after the initial carbon calculations by prioritising data collection of identified hot-spots within the supply chain and thereafter updating the map and calculations 3.1.2 Carbon calculation across supply chains The mapping of supply chains provides very useful data, boundary and insight into the assessment technique used in the environmental performance evaluation of supply chains Lifecycle assessment (LCA) is a well-known tool used to undertake environmental performance evaluation of supply chains (Tan and Khoo 2005, Laı´ nez et al 2008, Roy et al 2009) The LCA supply chain framework for a product, process or activity/operation can bring together the impacts of collaborative supply chain partners arising from extraction and processing of raw materials; manufacturing, transport and distribution; re-use, maintenance recycling and final disposal, etc LCA is therefore a holistic approach which brings environmental impacts into one consistent framework, wherever and whenever these impacts have occurred or will occur (Guinee et al 2001) Integrating LCA in supply chains has advantages in supply chain management Besides gaining an understanding of the environmental performance evaluation of the supply chain, high carbon emission paths (here defined as carbon hot-spots) can be identified and the appropriate intervention strategy identified and implemented in order to reduce the overall impact of the supply chain The general steps undertaken when implementing LCA are well described (International Standards Organization 1997) Two base methodologies can be used to systematically quantify impacts in supply chains These are process LCA and environmental input-output (EIO) LCA These methodologies have different levels of accuracy and system boundary completeness Traditional (or process) LCA methodology has been described as incomplete, primarily because it is not possible to account for the infinite inputs into the LCA system (Crawford 2008, Rowley et al 2009) To overcome this limitation, process LCA is complemented with EIO LCA which is used to estimate missing indirect inputs in the process LCA system (Lenzen and Dey 2000, Wiedmann 2009) The integration of the two base approaches leads to the development of a more robust methodology, that is, the hybrid LCA In the hybrid LCA approach used in this paper, a multi-regional input-output (MRIO) matrix used in the EIO is interconnected with the matrix representation of the physical process LCA system As a result, in the upstream and downstream inputs into the LCA system, where there are no or better process LCA data available, EIO estimates are used (Suh and Huppes 2005) A detailed explanation of the hybrid LCA methodology is provided in Acquaye et al (2011) and Wiedmann et al (2011) Acquaye et al (2011), for instance, applied the methodology and structural path analysis to decompose the supply chain of rape methyl ester biodiesel and Wiedmann et al (2011) accounted for indirect GHG emissions of wind power technologies in the UK The consistent mathematical framework for the hybrid LCA methodology is given below: ! !À1 ! Ap ÀD y Ep ð1Þ Emissions impact ẳ Eio U I Aio ị where: Ap AiÀo I U D Ep EÂiÀoà y Square matrix representation of process inventory (dimension: s  s) MRIO technology coefficient matrix (dimension: m  m) Identity matrix (dimension: m  m) Matrix representation of upstream cut-offs to the process system (dimension: m  s) Matrix of downstream cut-offs to the process system (dimension: s  m) Process inventory environmental extension matrix CO2-eq emissions are diagonalised (dimension: m  s) MRIO environmental extension matrix CO2-eq emissions are diagonalised (dimension: m  s) Functional unit column matrix with dimension s ỵ m, 1ị where all entries are except y Matrix Ap describes the supply chain inputs into processes as captured in the process LCA system AiÀo is the (896Â896) multi regional input-output (MRIO) technology matrix describing input and output coefficients requirements from one sector to another within the UK–Rest of the World supply and use MRIO framework 2098 S.C.L Koh et al Matrix U which is assigned a negative sign, represents the higher upstream inputs from the MRIO system to the process system Matrix D, also assigned a negative sign, represents the (downstream) use of goods/process inputs from the process to the background economy (MRIO system) The negative signs represent the direction of flow of inputs 3.1.3 Identification of potential low carbon interventions There are many factors that influence supply chain carbon emissions; for example, strategic investments in energy efficient technologies, awareness campaigns to lever behavioural changes or flux in emissions relating to the conditions of the global economy and marketplace for products and services In recognition that SCEnAT is primarily interested in strategic emission reductions, we define a low carbon intervention as any decision or deliberate change that directly leads to a reduction in CO2 emissions in a supply chain During the carbon mapping phase SCEnAT automatically identifies a range of potential low carbon interventions for businesses from a knowledge-base of low carbon interventions structured by a thematic typology The typology was developed in response to multiple calls from businesses requesting a source for information on low carbon practice available from a single easily accessible location The typology currently includes 16 broad intervention types (see Table 2) that cascade down into further sub-divisions of specific interventions There are several specific interventions under each broad intervention type, and for each of these SCEnAT provide users with a brief general description of the intervention including (where possible) a quantification detailing the potential CO2 reduction of implementing the intervention These interventions are also classed as ‘soft’ or ‘hard’ outcome interventions to indicate whether the emissions reductions that they produce are/will be quantifiable and thus able to provide, and substantiate, an accurate payback period calculation to support the business case for capital expenditure – a feature that is recognised by Walker et al (2009) as the key driver of green supply chain initiatives Specific interventions are also illustrated by case studies collected by the project team during a series of face-toface interviews and from SCEnAT subsequent users Case studies from external sources are provided in the database Table Typology of low carbon interventions Broad intervention type Technological ICT Building Logistics and transport Energy interventions Process and practice Product, packaging and waste Procurement Offsetting and carbon neutrality 10 Awareness 11 Employee 12 Strategic 13 14 Supply chain/networked Knowledge based 15 16 Bolt on End user Description Investment in more efficient technological equipment and machinery Green IT software and hardware solutions Methods of greening buildings (new builds and retrofitting) Options for reducing emissions relating to logistics (the transportation of goods, personnel, and delivery of services) Interventions relating to scope and emissions from energy production and consumption on site Alteration in process/practice within firm or supply chain to reduce energy used in comparison to old process Reductions in emissions by product alteration and or the prevention/reduction of waste going to landfill throughout the supply chain Reduction of supply chain emissions through environmental requirements and carbon reductions detailed within procurement contracts Quantifiable offsetting of overall CO2 emissions through offsetting (offsetting does not represent an actual reduction in CO2 emission and therefore should not be reported as such) Interventions used to raise awareness of staff/supply chain partners enabling behavioural change with associated reductions in emissions Formally employing personnel with environmental responsibility Altering corporate governance structure to assign environmental responsibilities to existing staff Development of strategy and policy to enable an understanding of resource consumptive practice and activities in order to tackle carbon emissions Intervention undertaken as part of a wider network or organisations Interventions stimulated via consultancy, knowledge exchange, or other case based learning Intervention that is not central to firms’ carbon footprint Behavioural change at point of use Use/disposal of product and/or service in a more environmentally aware manner International Journal of Production Research 2099 alongside further guidance and support from relevant organisations, such as the Department for Energy and Climate Change (DECC) and the Carbon Trust In addition to being integrated into the mapping function of SCEnAT whereby interventions are selected automatically according to identified hot-spots, the interventions database also has a standalone capability In this guise the database becomes a searchable one-stop-shop source of information regarding low carbon interventions The thematic structure and search function of the database makes it easy for the user to navigate and find information relevant according to intervention type, cost, business (name, size and sector), hard or soft outcomes, as well as a range of other keywords that are specifically attached to each intervention The use of the intervention database has benefits for the host firm but also has recognised implications for decarbonise their supply chain These strategic benefits include: (1) The promotion of environmental requirements across the supply chain (Walton et al 1998) (2) The alignment of supply chain goals on efficiency and environmental matters (United States Environmental Protection Agency 2009) (3) The transfer of environmental knowledge and solutions across the supply chain (California Environmental Protection Agency 2009) (4) The development of closer ties between supply chain partners through environmental collaboration (Fu and Piplani 2004, Lu et al 2007) These benefits illustrate how SCEnAT becomes more than a decision support tool by contributing to effective supply chain management 3.1.4 Supply chain performance evaluation This SCEnAT module is closely linked to the supply chain mapping and to the low carbon intervention modules A set of performance evaluation measures has been implemented within SCEnAT with the aim of keeping track of the change in supply chain performances due to the potential implementation of low carbon interventions Indeed, it is important to understand that the decarbonisation process should not jeopardise supply chain performances across other dimensions For instance, it would be less desirable implementing interventions that, despite a reduction of carbon emissions, would imply a remarkable increase in logistic costs or significant job cuts Therefore, it is important to provide an estimation of the impact of the interventions on a set of relevant measures, including environmental ones (for example, the above-mentioned carbon reduction potential of each intervention) but also other variables The development of this performance evaluation framework has been the result of a thorough literature review combined with a series of workshops run with a range of MNEs and SMEs, in order to identify a set of relevant key performance indicators (KPIs) In particular, looking at existing performance evaluation frameworks, it has emerged that, both in practitioners (for example, Green SCOR Model) and scientific literature (see Hervani et al 2005), they suffer from the following drawbacks: Huge number of dimensions to be measured Intangible variables to be taken into account Some redundant dimensions exist, while others are often overlooked (for instance, social dimensions) Therefore, a revised performance evaluation framework has been developed, capable of assessing the effectiveness and the efficiency of low carbon interventions on the supply chain from several dimensions The performance evaluation measures are grouped into three categories (reported, with respective indicators, in Tables 3–5): Economic and efficiency measures (including labour cost, net profit of focal firm within the supply chain, throughput time, percentage of late deliveries to the final customer, level of 1st tier suppliers defect rate) Environmental measures (including carbon emissions, water, energy and electricity usage, percentage of waste sent to landfill, percentage of recycled waste, transportation usage) Social measures (including measures capable of quantifying the impact of the supply chain on local communities in terms of jobs creation, expenditure on CSR and environmental training projects) A matrix (Figure 3) stores the impact of each intervention (expressed in terms of percentage variations) from the above-mentioned data-base on each considered KPI, in order to provide performance evaluation before and after interventions are considered on the specific supply chain These values have been obtained from the analysis of case studies and secondary data 2100 S.C.L Koh et al Table Economic and efficiency measures and indicators Economic and efficiency measures Indicator Labour cost Profitability Throughput time On-time delivery to customers On-time delivery from suppliers Buyer-1st tier supplier partnership level Level of defect-free deliveries to final customers Level of defect-free deliveries from 1st tier suppliers Labour cost as percentage of product unit cost Focal firm net profit Total supply chain throughput time Late order lines as percentage of total order lines Late order lines as percentage of total order lines Ownership percentage Defect free order lines as percentage of total order lines Defect free order lines as percentage of total order lines Table Environmental measures and indicators Environmental measures Indicator Use of recycled material Recycled material utilised in the production process as a percentage of total material (in weight or in value) per unit of product Waste sent to landfill resulting from the production process as a percentage of total waste (in weight or in value) per unit of product Recycled waste resulting from the production process as a percentage of total waste (in weight or in value) Kg of CO2 emitted per unit of product Percentage of ISO14001 certified facilities (across product supply chain) Litres of water utilised per unit of product KWh of electricity utilised per unit of product Mileage in kilometres (or, alternatively, fuel use in litres; or, alternatively, vehicle movements) per unit of product Energy (KWh) utilised per unit of product Energy (KWh) use from renewable sources/energy re-use as a percentage of total energy utilised per unit of product Total amount of environmental penalties and fines across product supply chain Materials sent to landfill Recycled waste (per unit of product) CO2 emitted (per unit of product) ISO 14001 standards Water use Electricity use Transportation use Energy use Percentage of energy use from renewable sources/energy re-use Environmental penalties Table Social measures and indicators Social measures Degree of jobs localisation Job security CSR expenditure Degree of purchasing localisation Community Reporting Employee CSR training Indicators Regional-based jobs as a percentage of total jobs (measurable both at focal firm and across product supply chain) Permanent jobs as a percentage of total jobs (measurable both at focal firm and across product supply chain) Expenditure on CSR projects (measurable both at focal firm and across product supply chain) Regional-based purchases as percentages of total purchases (measurable both at focal firm and across product supply chain) Percentage of facilities with community complaints (measurable both at focal firm and across product supply chain) Percentage of firms publishing a CSR report (measurable both at focal firm and across product supply chain) Percentage of employees with CSR training (measurable both at focal firm and across product supply chain) 3.2 Comparison of SCEnAT with existing tools At the start of this section we presented a review of the types of existing tools/software This review also identified their shortcomings vis-a`-vis carbon accounting and management needs across a supply chain Those gaps in features of the existing tools provided us with the reason and insight to design and develop SCEnAT which has been described in the previous sections of the paper It appears now appropriate to put the design and development of 2101 International Journal of Production Research Interventions Impact Key Performance Indicators (KPIs) Figure Impact matrix SCEnAT into a comparative perspective vis-a`-vis features of other existing types of tools (see Table also) and to highlight its unique and innovative features A traditional LCA-base methodology is not very effective for carbon accounting across organisational/firm boundaries due to data truncation problems An integrated methodology (process LCA and economic input-output LCA) used by SCEnAT is very effective in tackling this problem and has been accepted by the research community as more robust to the traditional (process) LCA approach (Acquaye et al 2011) SCEnAT offers complete flexibility not only in terms of a firm’s need for mapping, analysing and experimenting with and evaluating measure(s) to reduce carbon emission along/across a firm’s supply chain by providing state of the art knowledge and solutions at each step, but also complete behavioural flexibility when modelling a particular emission reduction strategy SCEnAT has been designed in such a way that a user would be under no compulsion to follow all the steps Depending upon their needs, a user would have complete flexibility in terms of what they want to with SCEnAT Most tools limit themselves to diagnosis and stop short of offering a solution Few tools offer intervention options and only one of them offers intervention at three levels SCEnAT is designed to afford interventions at four levels: product, process, firm and supply chain SCEnAT is also envisaged to be a living tool capable of learning and adapting itself through the experiences of its users by retaining these experiences into an inbuilt system database which also functions as the knowledge base for other pieces of system information and data In other words, low carbon intervention measures which have been implemented by user companies, best practices in industries and case studies of different solutions detailing the context in which all of these were applied will be captured within the intervention database (after validation by the project team) through users using SCEnAT and the project team also continually updating it with new information This is another unique and robust feature of SCEnAT which no other publicly available tool in the market offers Most tools available in the market besides being only carbon calculators are sector specific Few tools cover more than one sector of economy As we know supply chains by default are cross-sectoral Therefore, a tool that aspires to cover the entire economy or at least the principal sectors of an economy without the distinction of services or manufacturing will be desirable SCEnAT is designed to fulfil this role Finally, another unique and very advanced feature of SCEnAT’s design and architecture is that that it is also aimed at companies, whether transnational companies (TNCs) or SMEs, which have adopted triple bottom line (TBL) accounting or thinking of doing this in near future The firms lagging in this regard are doing this at their peril as they would also be forced by the future regulatory environment to adopt TBL practice Only one other tool in the field offers this kind of evaluation of carbon reduction interventions Still, it takes into account only environmental and economic parameters and that too in an unstructured way The design of SCEnAT brings this feature to carbon reduction management practice not only in a structured and robust manner but also its design and methodology have the potential of providing an evaluation of interventions on all three parameters, i.e environmental, economic and social Table presents this comparison and analysis in a tabular format 3.3 ICT-based structure of SCEnAT SCEnAT is designed to be an interactive and dynamic supply chain modelling tool which offers both carbon assessment capabilities at a whole supply chain and carbon management solutions by integrating different supply chain modules (supply chain mapping, carbon assessment, emissions reduction using low carbon intervention solutions and supply chain evaluation using key performance indicators) Within SCEnAT, these different modules can also be implemented independently to analyse product supply chains 2102 S.C.L Koh et al Table SCEnAT features in comparison to the existing types of decision support tools Features Tool/software type Carbon calculation SC mapping Carbon hot-spot identification Methodology Type Type Type Industrial activity coverage Yes N/A N/A Emissions inventory and formula based calculations Sectoral focus Behavioural flexibility within the approach Availability of option for Intervention Level of interventions Impact estimation Types of impacts Little or no flexibility No N/A No N/A No N/A No N/A Yes Three Yes Economic and environment Optimisation of carbon footprints In-built database Case studies Comprehensive system knowledge base N/A Yes No No N/A Not clear No No Yes Yes Yes No SCEnAT Yes N/A N/A Very basic LCA Yes Not clear Not clear Comprehensive LCA Yes Yes Yes Process LCA þ I/ O analysis based LCA More than one sector Some flexibility More than one sector Good flexibility Entire economy Complete flexibility Yes Four Yes Social, economic and environment Yes Yes Yes Yes Operation platform of SCEnAT application: The SCEnAT tool was written in C# using the NET Framework It is an MVC application running on the Windows Azure cloud platform It uses a SQL Azure database for all knowledge and intervention storage The application makes uses of Unity DI for Dependency Injection and Entity Framework is the ORM (Object Relational Mapper) The front-end uses the jQuery library for most client-side interactions whilst the mapping screen, which is the most complex on the site, was built using Backbone.js and a REST API SCEnAT can run as a Windows or Macintosh application and has been optimised for usage with modern, standards-compliant browsers We recommend using Google Chrome, Mozilla FireFox, Internet Explorer Version or Apple Safari A system diagram for the SCEnAT framework showing the flow of data is shown in Figure Key features: SCEnAT offers a very flexible user interface for product supply chain modelling Some of the key features include: A dynamic supply chain mapping screen for product supply chains A whole supply chain perspective to supply chain carbon assessment which ensures that a collaborative network of focal firm and upstream supply chain tiers is achieved The ability to manually input company specific data relevant to product as well as automatically calling-up secondary data from the ecoinvent database An in-built hybrid LCA model which integrates environmental input-output LCA with process LCA to overcome the system boundary truncation of traditional LCA assessments The system is integrated with a multi-regional input-output (MRIO) model which is used to evaluate the impacts of indirect inputs (Scope emissions) of the product supply chain Generation of supply chain carbon map and automatic carbon hot-spotting capabilities An automatic linkage between carbon hot-spot to relevant low carbon interventions which has been populated within the carbon management database with project-specific interventions, case studies, best practices in industry, etc Users can take advantage of the cloning capability of SCEnAT to remodel its supply chain to determine the baseline scenario, inputs and output flows and the impacts an implemented low carbon intervention will have on the product supply chain in future scenarios Inputs and outputs of SCEnAT: The main inputs required by SCEnAT to undertake the modelling of the product supply chain include information used to define and characterise the supply chain such as: name of company and International Journal of Production Research 2103 Figure System diagram of SCEnAT showing input and output flow of data product supply chain, the input-output classification of the main product, the functional unit of the supply chain Other information includes processes within the supply chain network, inputs into these processes, quantities of materials and energy and the corresponding units, unit cost of product inputs into supply chain, input-output classification of each inputs into supply chain The main outputs of SCEnAT include: Supply chain map and carbon map Total lifecycle emissions corresponding to the functional unit Contributions and sources of direct and upstream lifecycle emissions Emissions contributions of each supply chain input Automatic identification of carbon hot-spots in product supply chain Automatic linkage between hot-spots and low carbon interventions Performance evaluation of low carbon interventions All results for the whole supply chain and impacts of each input are displayed in graphical as well as tabular form with SCEnAT also having the functionality to generate executive reports in portable document format (pdf) Case study and results One of the case studies used to test SCEnAT is the Malting Supply Chain of Muntons plc Muntons, based in Suffolk in the UK, are manufacturers of malt, malt extracts and malted ingredients The functional unit adopted for the case study is tonne of malt The hybrid LCA methodology described in Section 3.1.2 and integrated within SCEnAT is employed as the carbon accounting methodology in the case study The LCA system encompasses all processes from agricultural production of barley on the farm to the malting process 2104 S.C.L Koh et al Table Inputs into the process LCA system Input classification Unit processes Quantity Unit Agricultural production: work processes Tillage, harrowing, by rotary harrow Tillage, ploughing Fertilising by broadcaster Combine harvesting Plant protection products, by field sprayer Sowing Transport, tractor and trailer 0.533 0.133 0.500 0.133 0.533 0.133 hectare hectare hectare hectare hectare hectare tkm Agricultural production: seed Barley seed 21.33 kg Agricultural production: fertiliser Calcium ammonium nitrate, as N Triple superphosphate, as P2O5 Potassium chloride, as K2O 20.07 5.75 0.098 kg kg kg Agricultural production: pesticide Diphenylether-compounds Pesticide unspecified Pyretroid-compounds Cyclic N-compounds 0.008 0.182 0.001 0.0383 kg kg kg kg Transportation Barley haulage from farm 0.324 tkm Malting process and storage Electricity Gas Water Waste water treatment Transportation Malt haulage 0.324 tkm Business travel Car travel Train travel Air travel 1.150 0.300 1.150 km km km 122.4 795 3.5 kwh kwh m3 m3 Data for the LCA system were obtained from three main sources: Primary process data for the malting supply chain were obtained from Muntons This consisted of data on haulage, the malting process, storage, energy input and business travel Secondary process inventory data obtained from Ecoinvent (2010) include validated secondary data of agricultural production processes: work processes, seed, fertiliser, pesticide use Disaggregated input-output data and environmental extensions The basic layout of the input-output framework is a two region model based on supply and use tables for the UK and the rest of world (ROW) (Wiedmann et al 2010) Table provides a detailed breakdown of process inventory inputs into the process LCA system The quantities of the inputs are referenced to tonne production of malt The LCA results consisted of the environmental impacts due to global warming potential of the malting supply chain The total lifecycle carbon impact can be divided into two: process impacts and indirect impacts The process impacts are impacts associated with the lifecycle inventories shown in Table This contributed 87% of the total lifecycle impacts of the malting supply chain Indirect impacts accounted within the MRIO framework contributed 13% of total lifecycle emissions of the malting supply chain These indirect impacts across the MRIO economic sectors are aggregated across 18 sectors namely: agriculture, forestry, fishing, mining, food, textiles, wood and paper, fuels, chemicals, minerals, metals, equipment, utilities, construction, trade, transport and communication, business services, personal services The use of the hybrid LCA ensures that the MRIO framework is used to capture and estimate those inputs that might otherwise be missed in the process LCA system, such as such as construction of commercial buildings (to account for construction of plants and related buildings), service related inputs (such as administration and business related activities), and other special purpose machinery or agriculture machinery sectors Hence by employing the hybrid LCA, technology-specific processes in the process LCA are integrated in a generalised environmental-economic, multi-region input-output modelling framework in order to include economywide GHG emissions in the assessment International Journal of Production Research 2105 Figure Screen shot of SCEnAT showing the supply chain carbon map for the malting supply chain The most significant carbon hot-spots in the malting supply chain include energy inputs (gas: 30.0% of the total lifecycle emissions; electricity: 11.4%), fertiliser (28.5%), farm machinery (14.2%), and upstream emission from the agriculture sector (9.5%).The results of the carbon accounting module of the malting supply chain using hybrid LCA is translated into a supply chain carbon map to identify carbon hot-spots and quantify their impacts The following subjective scale is used in the ranking (see Figure 5): very high (colour coded in red, indicates inputs with emissions greater than 10% of the total lifecycle emissions); high (light red; 5–10%); medium (0.3–5%); low (0.2–0.3%); very low (0–0.2%) The concept of a supply chain carbon map within a complete system boundary therefore provides relevant information and further insight and assists in the design of low carbon products and supply chains This approach improves the effectiveness of carbon reductions in the overall supply chain by directing investment either to reduce emissions from internal processes or by helping supply chain partners and suppliers to reduce their own carbon intensity SCEnAT has a role in creating a shared understanding concerning emissions within firms and between their supply chain partners which Carter and Rogers (2008) emphasise is critical in the development and operation of a green supply chain Emissions supply chain carbon maps promote such an understanding and hold partners accountable for their contributions to product life cycle emissions (Walton et al 1998) Consequently this information becomes integral to organisational decision making whereby accountability for emissions can be strengthened by the application of green procurement practices within the supply chain (Finkbeiner 2009), providing the required leverage to promote supply chain wide investment in low carbon interventions (Simpson and Power 2005) Pagell et al (2010) argue that these practices are responsible for the evident trend towards sustainable supply chain management in recent years, an assertion that is supported by the burgeoning research documenting the multiple and cumulative benefits of greening the supply chain (Sarkis 2003, Rao and Holt 2005, Walker et al 2008, Pagell and Wu 2009) The low carbon interventions module within SCEnAT serves as an evidence based approach to reducing carbon emissions in the malting supply chain by targeting identified carbon hot-spots in the supply chain after the carbon calculation Muntons have already begun a programme to decarbonise their supply chain and the information we 2106 S.C.L Koh et al have gained from them has been used within SCEnAT’s database of low carbon interventions to inform other businesses from within and beyond the food and drink sector At an intra-firm level investments have been made by Muntons in ensuring best available technology is being utilised within one of the identified hot-spot (gas inputs into the supply chain) by adopting energy efficient gas burners As regards impact on the above-mentioned measures, this specific intervention has seen consumption reduced by 8% in the kilns, accompanied by an increase of the percentage of staff receiving environmental training at induction and a refresher every three years, with no relevant side effects on other dimensions Work has also been undertaken in collaboration with their supply chain to centralise barley drying and storage as well as crop movement In terms of impacts, this has saved 650 tonnes of CO2 and reduced 1700 vehicle movements per annum, with no side effects on other dimensions Results from their supply chain carbon map (Figure 5) have also highlighted other carbon saving opportunities for which interventions are being designed and implemented For example, 45% of the malt supply chain emissions are derived from the growing stage, notably from fertiliser production and usage, and diesel consumed by farm machinery Muntons are now targeting these emissions by engaging with their supply chain, promoting and trailing alternative fertiliser regimes and precision farming techniques using GPS to ensure fertiliser is only applied where it is needed Looking to the future Muntons are considering further investments in onsite renewable such as installing a wind turbine The payback for such schemes are considerable; however, further information and case study examples from within the SCEnAT’s intervention database are helping Muntons recognise how their business can benefit which is helping them to develop the business case The example of Muntons illustrates how we intend SCEnAT to develop and evolve Users initially take advice and guidance and then, where appropriate, provide their own case studies to further populate the database of low carbon interventions These additional case studies alongside those brought together from other sources within the structure of our typology (see Table 2) will result in an up-to-date, comprehensive and usable learning resource to support decisions relating to low carbon capital investments As part of a holistic approach to account, map, intervene and evaluate supply chain emissions the interventions database is intended to drive greater environmental accountability within businesses and their supply chains in order to mitigate their contribution towards climate change This visible process of strategic emission reduction allows firms to promote their green credentials to supply chain partners and customers in an increasingly environmentally aware economic climate where greenwash no longer satisfies (Lyon and Maxwell 2011) SCEnAT will also assume an open innovation platform to facilitate collaboration between suppliers and customers along the supply chain with a open understanding, sharing and partnership on interventions to reduce CO2 emission Conclusions Although some businesses have taken on board the agenda of greening their supply chains, there has been a general lack of holistic framework that integrates a collaborative supply chain view within a consistent decision support system (DSS) The paper provides a holistic and practical evidence-based framework to aid decision making for the decarbonisation of supply chains This framework consists of four integrated supply chain modules: supply chain mapping, supply chain carbon accounting, low carbon interventions and supply chain performance evaluation The novel framework of an integrated green supply chain management ensures that the collaborative supply chain networks of firms can be mapped and using the robust hybrid LCA approach which integrates input-specific processes in LCA system into a UK and Rest of the World environmental-economic input-output framework, direct and indirect GHG emissions are quantified and carbon hot-spots within supply chain identified Furthermore, a database of low carbon interventions integrated within SCEnAT can be called upon and applied to the carbon hotspots Within SCEnAT, a triple bottom line (TBL) environmental, economic and social framework of key performance indicators is then used to evaluate the impact of interventions on supply chain performance The practicality of SCEnAT was demonstrated in the application to the malting supply chain The major advantages of SCEnAT lies in the production of the supply chain collaborative network carbon maps, robust methodology underlining the carbon accounting, a thematic database of hard and soft low carbon interventions and a flexible TBL Key Performance Indicators for evaluating the impact of these interventions The SCEnAT framework eliminates the problems associated with supply chain boundary and complexity by providing businesses with a holistic and an open supply chain collaborative framework to enhance shared International Journal of Production Research 2107 understanding of their CO2 emissions via a novel decision support mechanism This pushes the theoretical boundary by addressing the problems of intra-organisational approach in decision making for lowering carbon along the supply chain; with an open innovation, cutting edge, hybridised framework that considers the supply chain as a whole in co-decision making for lowering carbon along the supply chain with the most robust methodology of hybrid LCA that considers direct and indirect emissions and interventional performance evaluation for low carbon technology investment and business case building in order to adapt and mitigate climate change problems This research has implications for future sustainability research in SC, decisions science, management theory, practice and policy Policy impact includes the Climate Change Act 2008, the Carbon Plan 2011, the Energy Act 2011 and the Carbon Reduction Commitment (CRC), which all call for a lower carbon future This research calls for the need from industry to change the way they make decisions and view their carbon management This research suggests a more holistic and a balanced approach The integrated supply chain and decision science fields are further advanced via this research with the deployment of advanced LCA in the methodological development within SCEnAT The science and art of decision making has been advanced with a co-approach, which inspires co-decision making across the supply chain The management domain has been enhanced with a new sustainability angle of open innovation form of management in lowering carbon along the supply chain Acknowledgements We gratefully acknowledge the financial support from Yorkshire Forward to support the Centre for Low Carbon Future (CLCF), which is a collaborative research centre between the Universities of Sheffield, York, Leeds and Hull We wish to thank Muntons plc particularly Dr Nigel Davies (Manufacturing and Technical Director) for the case study; and the Business Advisory Board of the CLCF Low Carbon Supply Chain programme We also wish to express our thanks to Shaping Cloud for their help in SCEnAT Notes See http://www.cerc.co.uk/environmental-software/EMIT-tool.html See http://www.abagri.com/Nimoi/sites/abagri/resources/CarbonTrustBrochure_1st%20ed.pdf See http://www.ccalc.org.uk/documents.php References Acquaye, A.A., et al., 2011 Identification of ‘carbon hot-spots’ and quantification of GHG intensities in the biodiesel supply chain using hybrid LCA and structural path analysis Environmental Science & Technology, 45 (6), 2471–2478 Bai, C., et al., 2012 Evaluating 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(0–0.2%) The concept of a supply chain carbon map within a complete system boundary therefore provides relevant information and further insight and assists in the design of low carbon products and supply. .. across supply chains The mapping of supply chains provides very useful data, boundary and insight into the assessment technique used in the environmental performance evaluation of supply chains