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

Acquayea, Paul Barrattb, Nasir Ranaa, Johan Kuylenstiernacand David Gibbsb a Logistics and Supply Chain Management LSCM Research Centre, Centre for Energy, Environment and Sustainability

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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

evidence-based 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

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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 Kuylenstiernacand 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 9 May 2012; final version received 4 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

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 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

1 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

http://dx.doi.org/10.1080/00207543.2012.705042 Vol 51, No 7, 2092–2109,

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

2 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 Mu¨ller 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

Scope

Sustainable Purchasing

CSR Purchasing

Green Purchasing

Sustainable Supply Chain

CSR Supply Chain

Green Supply Chain

Figure 1 Green/CSR/sustainable supply chain frameworks classification

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 ¼ Green Purchasing þ 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 materialFows in the supply chain (Carter and Carter 1998) and a good understanding of mutual responsibilities and capabilities

3 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

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)1developed 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

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 1 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

Supply Chain Carbon Calculations

Low Carbon Interventions

Supply Chain

Performance

Evaluation

Informed

Decision

Making

Figure 2 Methodological framework of the decision support

system

Table 1 Supply chain material transfer matrix

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:

Emissions impact ¼ Ep 0

0 Eio

Ap D

U ðI  AioÞ

y 0

 

ð1Þ where:

Ap Square matrix representation of process inventory (dimension: s  s)

Aio MRIO technology coefficient matrix (dimension: m  m)

I Identity matrix (dimension: m  m)

U Matrix representation of upstream cut-offs to the process system (dimension: m  s)

D Matrix of downstream cut-offs to the process system (dimension: s  m)

Ep Process inventory environmental extension matrix CO2-eq emissions are diagonalised (dimen-sion: m  s)

Eio MRIO environmental extension matrix CO2-eq emissions are diagonalised (dimension: m  s)

y

0

 

Functional unit column matrix with dimension ðs þ m, 1Þ where all entries are 0 except y Matrix Ap describes the supply chain inputs into processes as captured in the process LCA system Aio is the (896896) 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

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 CO2emissions 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-to-face interviews and from SCEnAT subsequent users Case studies from external sources are provided in the database

Table 2 Typology of low carbon interventions

4 Logistics and transport Options for reducing emissions relating to logistics (the transportation of goods,

personnel, and delivery of services)

5 Energy interventions Interventions relating to scope 1 and 2 emissions from energy production and

consumption on site

6 Process and practice Alteration in process/practice within firm or supply chain to reduce energy used in

comparison to old process

7 Product, packaging and waste Reductions in emissions by product alteration and or the prevention/reduction of

waste going to landfill throughout the supply chain

carbon reductions detailed within procurement contracts

9 Offsetting and carbon neutrality Quantifiable offsetting of overall CO2emissions through offsetting (offsetting does

not represent an actual reduction in CO2emission and therefore should not be reported as such)

behavioural change with associated reductions in emissions

governance structure to assign environmental responsibilities to existing staff

consumptive practice and activities in order to tackle carbon emissions

13 Supply chain/networked Intervention undertaken as part of a wider network or organisations

14 Knowledge based Interventions stimulated via consultancy, knowledge exchange, or other case based

learning

environmentally aware manner

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

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

Table 4 Environmental measures and indicators

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 Materials sent to landfill 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 (per unit of product) Recycled waste resulting from the production process as a percentage of total

waste (in weight or in value)

CO2emitted (per unit of product) Kg of CO2emitted per unit of product

Transportation use Mileage in kilometres (or, alternatively, fuel use in litres; or, alternatively, vehicle

movements) per unit of product

Percentage of energy use from

renewable sources/energy re-use

Energy (KWh) use from renewable sources/energy re-use as a percentage of total energy utilised per unit of product

Environmental penalties Total amount of environmental penalties and fines across product supply chain

Table 5 Social measures and indicators

Degree of jobs localisation Regional-based jobs as a percentage of total jobs (measurable both at focal firm and across

product supply chain) Job security Permanent jobs as a percentage of total jobs (measurable both at focal firm and across product

supply chain) CSR expenditure Expenditure on CSR projects (measurable both at focal firm and across product supply chain) Degree of purchasing

localisation

Regional-based purchases as percentages of total purchases (measurable both at focal firm and across product supply chain)

Community Percentage of facilities with community complaints (measurable both at focal firm and across

product supply chain)

product supply chain) Employee CSR training Percentage of employees with CSR training (measurable both at focal firm and across product

supply chain)

Table 3 Economic and efficiency measures and indicators

Level of defect-free deliveries to final customers Defect free order lines as percentage of total order lines Level of defect-free deliveries from 1st tier suppliers Defect free order lines as percentage of total order lines