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8Journal of Sustainable Development of Transport and Logistics
journal home page: https://jsdtl.sciview.net
Farchi, C., Touzi, B., Farchi, F., & Mousrij, A. (2021). Sustainable performance assessment: A systematic literature review. Journal of Sustainable Development of Transport and Logistics, 6(2), 124-142. doi: 10.14254/jsdtl.2021.6-2.8.
Scientific Vlatform
ISSN 2520-2979
Sustainable performance assessment: A systematic literature review
Chayma Farchi * , Badr Touzi **, Fadwa Farchi * , Ahmed Mousrij *
* Hassan 1er University, Settat, Morocco,
Department of Mechanical and Electrical Engineering, Research Laboratory: IMII (Engineering, Industrial Management, and Innovation), Faculty of Sciences and Technologies c.farchi@uhp.ac.ma; f.farchi@uhp.ac.ma; mousrij@gmail.com ** Mohammed V University, Rabat, Morocco,
Department of Economics and Management Sciences, Research, Faculty of Legal, Economic and Social Sciences - Souissi b.touzi@um5r.ac.ma
OPEN ^^ ACCESS | d
Article history:
Received: November 03, 2021
1st Revision: November 05, 2021
Accepted: November 26, 2021
DOI:
10.14254/jsdtl.2021.6-2.8
Abstract: Current development trends are driving ubiquitous sustainability requirements, pushing organizations to achieve new sustainability goals and targets. To this effect, continuous and continual performance measurements are the key to any business-related success. Therefore, the sustainable performance of an organization can be defined as the performance that takes a long time to achieve its goals. The outcome is a well-balanced balance of context, strategy, management processes, resources, and intangibles especially since it is closely related to the notion of sustainable development (TBL). The goal of this paper is two-fold. Firstly, a systematic literature review is conducted to highlight the importance and the need to assess the three pillars of sustainability and, finally, to encircle the sustainability concept by identifying the most used techniques and approaches in its evaluation. This paper can be considered as basic support for future studies in the application of sustainable performance measurement/assessment systems.
Keywords: sustainability assessment, sustainable performance, PMS, sustainable performance measurement, tripple bottom line
Corresponding author: Chayma Farchi E-mail: c.farchi@uhp.ac.ma
This open access article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license.
1. Introduction
Sustainable development is a complex issue associated with generally improving the living conditions of people on Earth without compromising the biosphere regulation and the ability of the world. It emerged about three decades ago, based on the publication of a report by the World Commission on Environment and Development (Cmed) (Vivien, et al., 2013).
The final purpose of companies is to proportionally implement a strategic long-term stakeholder value through the implementation of a business strategy based at first degree on the ethical, social, cultural, environmental, and economic aspects of practicing business. In practical reality, this shows that there are three main resources of the business in their operations: Social justice and human rights and social justice, Natural resource extraction and waste, and Short- and long-term thinking.
In globalization's context, the competition between companies has involved competitiveness between supply chains. Members of the Supply chain are now unanimous and hold a consensus on the importance of realizing sustainable supply chain management (SSCM) and integrating the approach of sustainable development into management systems (Wan et al., 2021).
SSCM has then emerged as a subject in the growth phase, taking raising and increasing interest in supply chain management area the sustainability (Seuring and Müller, 2008). Practicing and expanding such significant leverage on the stainability of national economies, aside from studies dominated by either case or survey-based research, measuring performances in the context of the sustainable supply chain has not attracted researchers' attention. Along with increasing pressure to act and report on sustainability strategies, an overwhelming number of principles, tools, and reporting formats have emerged and some of which are adopted by corporations to prove their loyal commitment to sustainable development (Beloff et al., 2004).
Given the above-mentioned concerns, this paper intends to review the literature related to the PMS in the context of SC. This paper also aims to encircle the notion of sustainability and its assessment and to detail the different evaluation methods and approaches found in the literature. Following the introduction, this paper is structured as follows : (2) the proposed methodology is developed, (3) the definitions of the main concepts relating to sustainability are given, (4) the main methods and approaches are detailed and analyzed, and (5) discussion, results and some, concluding remarks are provided.
2. Research methodology
This paper is derived from well-defined research goals and can be compared to a systematic review of the literature according to a structured protocol that minimizes subjectivity and allows critical evaluation of related research (Di Pasquale et al., 2017).
This study brings together the work of collecting, assessing, and synthesizing existing knowledge on the issue of measuring and evaluating sustainability and sustainable performance.
The aim is to first review and analyze documents and articles that discussed sustainability assessment and sustainable performance measurement and that provided frameworks, models, approaches, and sustainability-related indicators allowing its evaluation to highlight the importance and the need to assess the three pillars of sustainability (the three dimensions economic, environmental and social) contributing to the sustainability goals of organizations and finally present the most used techniques and approaches to encircle the concept of sustainability and its assessment.
2.1. Literature collection and selection
The collection and analysis of the literature included in this review were carried out for 4 months until the current structure of the topic of this review was formulated. Therefore, it is still difficult to quantify the incremental volume of retrieved and selected documents. The collection runs until the end of May 2020. Strategies for collecting, selecting, and reviewing existing literature are presented in Table 1.
Figure 1: Flowchart detailing the stages in the constitution of the article database
The retrieved literature emanates from an intersection of the three databases: ScienceDirect, ResearchGate, and Scopus without any constraint on the type of publication or journal. For the more than 506 documents discovered, the results were restricted by including the keywords: «Sustainable», «Sustainability», «Performance», «Assessment», «Evaluation», «Measurement», «Indicators»,« Mesure», «Model», «Framework», «Tool», «Approach» trying the different possible combinations. Only the works related to the sustainability assessment context were then included in the selection.
Table 1: Inclusion and exclusion criteria
1 Search and collection criteria Number of documents
1.1 Database selection ScienceDirect, ResearchGate, Scopus 506
1.2 Search date May 2021
1.3 Documents types ALL
1.4 Journals ALL
1.5 Search field Titles, Abstracts, Keywords, highlights
1.6 Publication period Until April 2021
2 Selection criteria Number of documents
2.1 Inclusions Keywords: Model, Framework, Tool, Approach, Assessment, evaluation, measurement, indicators, measure, Performance, Sustainable, Sustainability The model put into practice Model tested & applied 103
2.2 Exclusions Off-topics Duplicates No evaluation model
Excluding papers with no added value to our work, the most relevant literature has been analyzed for the aim of this current review. The final number of case studies, quantitative studies, and research papers are 82 out of 103 related documents retained and selected.
The flowchart above shows in detail the main stages of articles' selection Figure 1.
Figure 2 shows some initial thoughts and considerations regarding the collection and selection of literature to analyze. Eighty-two documents are distributed on a time scale from 2011 to 2021.
As can be seen, the number of articles surveyed has increased since the early 2016s, when awareness of the importance of sustainable development increased and grew.
Figure 2: Distribution of the documents among the time span according to their year of
publication
years
The citations of these articles were also analyzed to give Figure 3, which is the most frequently
cited.
We can note that, compared to the total number of articles contained in our database to be studied, those published before 2015 remain practically insignificant (0 articles were meeting our selection criteria for the three years: 2012, 2013, and 2014). It is only from the year 2018 that the publications became important and therefore significant given the emergence of the sustainability assessment and evaluation.
Figure 3: Distribution of the articles' citations
200 180 160 140 120 100 80 60 40 20 0
59
182 164
Citations Analysis
1210112
The number of times each article has been cited varies from one to another. The mainly cited articles (182, 164, and 108 times) propose new evaluation methods and frameworks mainly using fuzzy logic associated with another decision support method. This can be justified by the interest given to fuzzy logic transforming human knowledge into a mathematical formula and reducing the uncertainty and the ambiguity of the data. These same articles present frameworks tested and applied (in purely professional contexts). This demonstrates the importance attributed by the scientific community to practical studies.
2.2. Distribution of research papers according to methodology
Based on the 103 articles constituting the final database (after the exclusion), the authors have classified and categorized the articles selected according to whether they are "Literature reviews", "Research articles", "Case studies" or "Quantitative studies". Results are shown in the Table 2 below.
I Table 2: Distribution of research papers 1
Papers Numbers %
Case Studies 69 66,9902913
Literature Review 21 20,3883495
Research Articles 9 8,73786408
Quantitative Studies 4 3,88349515
Out of 103 articles, case studies remain the most predominant (64) in terms of the distribution, followed by literature reviews. While the number of quantitative research remains elementarThisich is due to the characterization of this field of research by strong applicability compared to other more theoretical fields of research.
3. Definitions
3.1. Sustainability assessment in SC
To implement a sustainable strategy, it is necessary to manage sustainability performance effectively. Sustainability performance measurement and assessment systems are some of the basic conditions for successful sustainability performance management. The measurement of the actual economic, environmental and social performance is an essential starting point to understand what, where, and how to improve (Beske-Janssen et al., 2015).
Table 3: Sustainability assessment
Contributions
Authors Year
Nature
Model
Key Strengths key weaknesses
< >>
■a
s
Pretended that assessing and managing Qorri et al. 2018
sustainability enable to eliminate and
reduce risks, confirm compliance with
standards and regulations, signal
opportunities and threats, reduce costs,
increase efficiency, strengthen
competitive advantages, facilitate
sustainability reporting, and sharpen
operational performance.
Explored various applications of the Kot concept of sustainable supply chain management (SCM) in the operation strategy of Small and Medium-sized Enterprises (SMEs).
Conducted a systematic literature Jia et al. review to identify the common themes across the literature on sustainable supply chains. They considered four factors regarding the adoption of SSCM: drivers, barriers, mechanisms, and outcomes and proposed an integrated conceptual model grounded on institutional theory.
Investigated the impact of SSCM Hong et al. practices on supply chain (SC) dynamic capabilities and the sustainability performances of organizations. They observed that SSCM practices have a significant positive effect on SC dynamic capabilities and over the three dimensions of sustainability performances, economic, environmental, and social. And they noticed that SC dynamic capabilities showed positive effects over environmental performances, but no effect over economic or social performances._
Defining study
2018 Exploratory study
2018 Exploratory Conceptuel study model
proposal
2018 Exploratory deductive study
Improvement of efficiency & operational performance Reduction of costs and risk
Inclusive management of operation strategies
Operational orientation
Operation strategies orientation
Integrated Omission of input evaluation model elements
Consideration of the three pillars of TBL Integration of a dynamic lever
Dynamic capabilities orientation
Operationalized SSCM and introduced a Zhang et al. 2018 Innovative Practical Operationalizing of Concentration on
factor, which is the derivative of study modem SSCM the environmental
external green SCM, internal green SCM, proposal Multi-item scales and social
and corporate social responsibility consideration dimensions
(CSR). They developed multi-item
scales for measurement for SSCM and
stressed the environmental and social
side of sustainability
Admitted that Social sustainability Ahmadi et 2017 Classifying - Clarification of the Concentration on
supports other sustainable initiatives al. deductive importance of the the social
and established a basic construction for study social pillar dimension
examining the social sustainability of Demonstration of
supply chains in manufacturing the link between
business, gave weight to different social the social
criteria and concluded that the dimension and
"contract stakeholder influence" was stakeholders
the most important criterion for
realizing social sustainability
Constructed a practical evaluation Popovic et 2018 Exploratory Practical Goal-oriented Concentration on
model for social sustainability that al. study model the social
includes indicators that can regularly proposal dimension
monitor the extent to which established
goals have been achieved
Stressed the importance of providing a Tseng et al. 2019 explanatory - Demonstration of Right oriented and
secure environment and promoting study the link between a based study
human rights for improving SSCM secure
performance. environment and human rights
Established a tool to evaluate and Sari and 2018 explanatory Quantitative Consideration of Concentration on
compare the green performance of hotel Suslu study & Qualitative basic green the environmental
supply chains by dividing green evaluation practices and dimension
standards into basic and advanced tool advanced green
green practices, showing that compared proposal practices
with advanced green practices,
managers pay more attention to basic
green practices.
Proposed a new economic, Kafa et al. 2013 Exploratory TBL Consideration of Benefits
environmental and social performance comparing evaluation the three pillars of orientation
evaluation model to realize the benefits study model TBL
of GSCM and evaluate its impact on proposal Consideration of
overall performance using a sustainability
comprehensive method. impact
3.2. Triple bottom line sustainability perspective
Sustainability is increasingly becoming the focus of governance and political dialogue as issues such as climate change, biodiversity loss, reduced availability of materials, and reduced demand for energy consumption need to be addressed.
Sustainability has different interpretations, from a cross-generational philosophical perspective to a multidimensional expression (M.M. Bappy et al, 2019). Originally considered a social issue, sustainability is receiving now increased attention from businesses (M.M. Bappy et al., 2019). Among the various perceptions of sustainability, the central idea that helps to operate sustainability is the triple bottom line (TBL approach), which achieves the lowest ecological, economic, and social levels of performance (Elkington, 1997). Taking economics into account, natural and social cases (Dyllick and Hockerts, 2002) also classify aspects of sustainability.
In addition, a sustainability perspective is presented in the literature, including the planet, people, and interests as key features of the analysis (Asif et al., 2011; Seuring et al., 2019). Organizations that consider economic and ecological and social issues generally produce longer-term value than organizations that focus solely on financial and profit-generating issues (M.M. Bappy et al., 2019).
The sustainability indicators address the sustainable development among the companies which has many definitions, the table below summarizes the main definitions found in the literature.
Table 4: Sustainable development
Sustainable development/ TBL
Basis
Authors
Year
It defines sustainable development as the development that Long-term needs Arena, M. et al. 2013
meets the needs of the present without comprising the satisfaction Beheiry, S. M. et
ability of future generations to meet their needs. al. 2003
the Triple Bottom Line (TBL) has emerged as the concept of sustainability as the integration of economic, environmental, and social dimensions.
Three dimensions consideration
Elkington, J
1997
The TBL is a critical concept for many organizations because it implies that the firm's responsibilities are much wider than simply those related to the economic aspects of producing products and services that customers want, to regulatory standards, at a profit.
The TBL adds social and environmental indicators of performance to the economic indicators typically used in most organizations' performance.
Companies must undertake their most basic economic, environmental and social responsibilities
Argued that enterprises are more and more thought responsible for the environmental, social, and economic consequences caused by their internal operations and those of their suppliers
Compagnies accountability
Addition of the two social and environmental dimensions
Compagnies accountability
Effect (on the three dimensions) consideration
Hubbard, G
Nappi, V. and Rozenfeld, H.
Wan et al.
Hartmann, J. and Moeller, S
2009
2015
2021
2014
Balancing or optimizing the three dimensions of the TBL Optimization and can guide supply chain members in achieving the balancing the sustainability goals demanded by multiple stakeholders_three dimensions
Allaoui et al.
2019
The TBL encompasses the basic dimensions used to evaluate supply chain sustainability. The three dimensions are described as follows.
The definition of the economic dimension includes the economic language related to the sustainability of the supply chain, such as costs and benefits (Ahi & Searcy, 2013). Supply chain members meet their needs and the needs of their stakeholders by adopting innovative and valuable co-creation strategies, and provide economic guarantees for the sustainable development of supply chains. Economic sustainability is an inexhaustible source of strength for improving the profitability and competitiveness of supply chains and contributes to the long-term survival of enterprises in difficult market conditions (Wan et al., 2021).
Due to increasing environmental problems, companies are under pressure to be environmentally responsible and integrate the environmental dimension into their business systems to mitigate environmental damage. (Paulraj, 2009) showed that ecologically responsible practices that organizations have adopted can create sustainable competitive advantages that can improve their profitability in the long run. Thus, the environmental dimension relates to sustainable environmental practices (Wan et al., 2021). Organizations in supply chains, taking into account the requirements of stakeholders, take measures to reduce the impact on the ecological environment through energy management and other activities, at least to avoid environmental damage, meet environmental requirements and improve the economic performance of supply chains.
Supply chain social sustainability is described as identifying, addressing and resolving social problems and concerns that arise throughout the supply chain, involving all upstream and downstream enterprises, internal processes and other stakeholders (Mani et al., 2015). It solves the aspects important for human rights and quality of life and directs the management layer to take into account the potential social consequences of decisions made (Laguna, 2014). Social sustainability practices require enterprises to maintain effective communication with other stakeholders.
4. Classification of PMS for sustainability assessment
An effective PMS is required in the context of SC to measure the right thing at right time. (Neely et al., 2000) defined the PMS as the total set of metrics used to measure both the effectiveness and
efficiency of action. Kaplan and Norton stated that "No measure, No improvement". Hence, identification of key performance measures (KPM) and selecting the suitable PMS is more important in the success of SC performance evaluation. For the last two decades, many researchers have developed and applied various performance measurement frameworks for different problems of SC (Jagan Mohan Reddy. K et al., 2019).
The majority of researchers have classified performance measurement and evaluation systems in the context of SC as models, frameworks, approaches, and techniques. Anyhow, (J,M.Reddy. et al., 2018) have classified the SCPMS as approaches and techniques.
4.1. Approaches
The approaches were, in turn, classified as processed-based approaches, perspective-based approaches, and hierarchical-based approaches (Jagan Mohan Reddy. K et al., 2019).
Table 5: Sustainability Assessment Approaches
Authors
Article
Year Attributes & contributions
Measure/Evaluation Orientation
1-Processed based
K.K. Ross-Smith, M. Yearworth
H.-J. Bullinger, M. Kühner, A. Van Hoof
A. Gunasekaran, C. Patel, R.E. McGaughey J. Thakkar, A. Kanda, S.G. Deshmukh
M.A. Wanous, Mohammed
P. Mishra, R.K. Sharma
S.A. Bagloee, M. Shnaiderman, M. Tavana, A. Ceder K. Govindan, S.K. Mangla, S. Luthra
A. Qazi, A. Dickson, J. Quigley, B. Gaudenzi
V.G. Venkatesh, A. Zhang, E. Deakins, S. Luthra, S. Mangla_
approaches
Dynamics of operational 2011
procurement: systems modeling for performance tracking and auditing
Supply chain performance using a 2002 balanced measurement method
A framework for supply chain 2004
performance measurement
Supply chain performance 2009
measurement framework for small and medium scale enterprises, Benchmarking
A proposed value model for 2009
prioritising supply chain performance measures Benchmarking SCM performance 2014 and empirical analysis A logic-based model for facility 2015 placement planning in supply chain management
The Management of Operations 2017
Prioritising indicators in
improving supply chain
performance using fuzzy AHP:
insights from the case example of
four Indian manufacturing
companies
Supply chain risk network 2018
management: A Bayesian belief network and expected utility-based approach for managing supply chain risks
A fuzzy AHP-TOPSIS approach to 2018 supply partner selection in continuous aid humanitarian supply chains_
Process-based approach to develop the models and also evaluated SC performance using six sigma metrics
Combination of top-level and lower-level metrics to develop a performance framework
Development of a framework taking into account the four SC processes (planning, sourcing, manufacturing, and delivering) process-based approach to measure SC performance measures in small and medium-sized industries
Hierarchical models were developed to prioritize performance measures in the context of the supply chain
Presentation of the relationship between Supply Chain performance measures and strategies Proposition of a model of SC performance measurement system integration at three levels (Distributor manufacturer supplier) hybrid method to evaluate the Supply Chain performance considering green performance measures
utility-based process approach capturing the interdependencies between risks, risk mitigation strategies, and performance metrics in the SC network.
Development of a framework to explore social issues related to suppliers and recognize performance measures in emerging economies.
Process-oriented and targeted model (Review On SC PMS -2019)
2-Perspective-based approaches
Does supply chain management pay? Six perspectives to measure A. Otto, H. Kotzab the performance of managing a supply chain
2003 Considered each perspective to provide the
measures in the evaluation of the perspective of the SC. It assembles the generic performance measures and also provides the interrelationship _among the performance measures_
2.1. Balanced Scorecard models (BSC)
R.S. Kaplan, D.P. Norton
M. Anand, B.S. Sahay, S. Saha
The Balanced Scorecard -Measures that Drive Performance The Balanced Scorecard — Measures
Balanced Scorecard in Indian Companies
1992 BSC approach generally applied to choose and combine the SC performance metrics from the balanced view
2005 Association of the SCM framework with the BSC to define performance measures of different _companies in different parts of the world._
BSC comprises traditional financial measures representing an organization's past and adds non-financial measures (operational measures)
E.W. Davis, R.E. Spekman
J. Chai, J.N.K. Liu, E.W.T. Ngai
A. Trivedi, K. Rajesh
G.F.
Khanaposhtani, S.S. Jafari, F. Ariana
D. Xia, Q. Yu, Q. Gao, G. Cheng
F. Rasolofo-Distler, F. Distler
S. Thanki, J Thakkar
The Extended Enterprise: Gaining 2004 Competitive Advantage Through Collaborative Supply Chains Application of decision-making 2013 techniques in supplier selection: A systematic review of literature A Framework for Performance 2013 Measurement in Supply Chain Using Balanced Score Card Method: A Case Study Formulating the supply chain 2017
strategy of automotive industry in Iran using balanced Scorecard
Sustainable technology selection 2017 decision-making model for enterprise in supply chain: Based on a Modi fi ed strategic balanced scorecard
Using the balanced scorecard to 2018 manage service supply chain uncertainty: Case studies in French real estate services
Quantitative framework for lean 2018
and green assessment of supply
chain performance_
Application of BSC in theory and practice with many advantages compared to other models
Use of this approach in the logistics industry to measure SC performance
combination of BSC and AHP methods to assess SC performance.
Use of a mixed approach consisting of BSC, Game theory, and System Dynamics (SD) to evaluate the automobile industry performance
Development of a modified strategic balanced scorecard evaluating the technology candidates in terms of their features of sustainability.
Analysis of the role of the BSC in the management of SC uncertainty in service activities
Proposition of a BSC and strategy map-based quantitative framework for assessing the lean and green performance of the SC_
representing the drivers of future performance which have been distributed between the four started classes. The fundamental quality of the BSC is that it measures the performance in all four main areas, which have associated with the strategic objectives (Review On SC PMS -2019)
2.2. Supply chain operations reference model(SCOR)
An integrated framework for 2010
supply chain performance measurement using six-sigma metrics
A review on benchmarking of 2008
supply chain performance measures
Supply chain performance 2009
measurement framework for small and medium scale enterprises Developing a model for agile 2013
supply: An empirical study from Iranian pharmaceutical supply chain,
Planning and modeling of 2017
Pharmaceuticals Wholesale-Distributors supply Chain using SCOR model: A Moroccan case study
Modeling of Critical Products 2018
Supply Chain Required to Affected People on Earthquakes and Tsunamis Through Use of SCOR Model
L.L.T. Li
W.P. Wong, W. Peng Wong, K. Yew Wong
J. Thakkar, A. Kanda, S.G. Deshmukh A.R.. Ghatari, G.. Mehralian, F.. Zarenezhad, H.. Rasekh D. Essajide, L. Rachidi
J. Zuniga, R.; Icarte, G.; Griffiths, J.; Lopez, J; Quezada
Model containing performance attributes and metrics depend on five different management processes (plan, source, make, deliver and return)
Application of SCOR measures as input variables and output variables for DEA to evaluate the performance of the SC
Mixing the features of the SCOR and BSC models to develop a PMS for the case of small and medium enterprises in India Expression of PMS based on the SCOR for distributors in pharmaceutical supply chains.
Adaptation of the SCOR models to the pharmaceuticals wholesale distributors in the performance of SC
Use of SCOR model to identify the key performance measures to reduce the complexities of the SC
SCOR contains thirteen metrics corresponding to level 1 which fall into five categories; SC reliability metrics, flexibility metrics, responsiveness metrics, cost metrics, and assets metrics. The first three categories have directly linked to the customers and are hence called customer-facing. The rest of the metrics, measurements within the internal operation of the SC and are named as internal facing. (Review On SC PMS -2019)
3. Hierarchical based approaches
A. Gunasekaran, C. Patel, E. Tirtiroglu
A. Gunasekaran, C. Patel, R.E. McGaughey D. Gallear, A. Ghobadian, Y. Li, N. Oregan, P. Childerhouse, M. Naim,
V.R. Pramod, D.K. Banwet
P.K. Dey, W. Cheffi
Performance measures and metrics in a supply chain environment
A framework for supply chain performance measurement
An environmental uncertainty-based diagnostic reference tool for evaluating the performance of supply chain value streams
Performance measurement of SHER service supply chain: a balanced score card - ANP approach
Green supply chain performance measurement using the analytic hierarchy process: a comparative analysis of manufacturing organisations_
2001 Development of a framework with the strategic level metrics, tactical metrics, and operational level metrics.
2004 Prioritization the metrics based on the three-point scores
2014 Classification of metrics based on the three hierarchical levels
2011 Hierarchical based-model to evaluating the
performance of service Supply Chain in terms of safety, risk, and health
2013 Empirical research on the development of tier-based performance measurement systems in the green supply chain
Hierarchical based models are useful to measure the performance of an SC at different hierarchical levels (strategic level, tactical level, and operational level)
4.2. Methods
According to researchers and practitioners, sustainability assessments are increasing as a fast-growing emerging area. (Brandenburg et al., 2014; Glock et al., 2012). Nonetheless, the number of posts on this topic is very limited. To assess the sustainability of the supply chain, quantitative models can be created based on recent studies using the following techniques (Hassini et al., 2012; Seuring, 2013; and Brandenburg et al., 2014).
Table б: Sustainability assessment Methods
Methods
Definitions
Characteristics
Limitations
Evaluation/Assessment perspective
Life Cycle Research and evaluate the potential Assessment environmental impacts associated (LCA) based with a product, process, or action. model LCA is the most widely used system
for studying sustainability issues in the supply chain (Seuring, 2013).
Analytical AHP is the second most commonly Hierarchy used approach to assess Process (AHP) sustainability (Seuring, 2013) To organize and analyze multi-objective decisions AHP is a structured technique (Moktadir et al., 2019).
It is often used as a basic semiquantitative decision-making procedure. To simplify and structure complex decisions, this approach is widely used (Ho, 2008; Moktadir et al., 2019). Multiple With this approach, the multi-
Criteria criteria planning problem is
Decision structured and solved.
Making Initially, the MCDM approach and
(MCDM) the equilibrium approach are
Structure comparable because the aim is to create a balance between the criteria. economic performance and the environment differently (Seuring, 2013). Models based IOA is another logical modeling on Input- approach for evaluating Output sustainability-related issues in the
Analysis (IOA) supply chain (Brandenburg et al., 2014)
Equilibrium Equilibrium modeling is an Model established standard method and another widely used approach for assessing supply chain sustainability (Seuring, 2013). Data Data Envelopment Analysis (DEA) is envelopment based on linear programming to analysis assess the relative efficiencies and (Sartori et al., inefficiencies of decision-making 2017) units (DMUs) producing outputs by using inputs. DEA was first proposed in the pioneering paper by Charnes, Cooper, and Rhodes (Charnes et al., 1978). It is used to estimate the technical efficiency of a DMU with constant returns to scale (CRS) in the frontier of the production possibility set. Fuzzy Logic A fuzzy set is a class of objects, with (Erol et al., a continuum of membership grades, 2011) _where the membership grade can
Multi-step criteria
and multi-
Multi-criteria method
Multi-criteria method
Interdependencies based method
Hypothetical method
Non-parametric technique
Versatile logic method
Depending only on assumptions and
scenarios.
The impact of comparing many objectives. Interdependence between
alternatives and objectives can lead an
inaccurate/wrong results.
Additional analysis is required to verify the results. The risk inconsistent judgments is high
Accuracy
convergence
problem
The assessment is done by identifying and assessing the materials used, energy consumed, and waste on land (Abdallah et al., 2012; Pishvaee and Razmi, 2012).
Typical components covered in the LCA are assessing environmental issues and trying to minimize their impact on the supply chain ( Cholette and Venkat, 2009; Edwards et al., 2010)
The AHP method helps to evaluate complex decision-making situations where economic and environmental objectives are evaluated
simultaneously (Faisal, 2010).
of
too
and
One-period setting with only two stages on the supply chain
networks
Results are
potentially sensitive to the selection of inputs and outputs
The main areas of emphasis of this approach are to provide an optimal solution by optimizing economic and environmental criteria (Georgiadis and Besiou, 2009; Koberg and Longoni, 2019)
The relationship between supply chain input parameters and the results of some key performance indicators can be analyzed. Environmental capital and economic goals, as well as supply chain network throughput, can also be assessed by IOA techniques (Bonney and Jaber, 2014; Jaber et al., 2013). The balance of economic and ecological problems by providing relevant optimal solutions was a typical basis for equilibrium models (Kainuma and Tawara, 2006; Saint Jean, 2008). Organization and analysis of the Data allows the performance to be changed over time and it has no frontier about efficiency boundary.
The necessity to A fuzzy subset A of a universal set X is regularly update defined by a membership function f the rules of a Fuzzy [A(x)] which maps each element x in X
be taken as an intermediate value between 0 and 1(I. Erol et al., 2011)
Composite A logical modeling approach that Metrics can be used to assess supply chain
sustainability by creating and using composite measurements (Brandenburg et al., 2014; Hassini et al., (2012).
There is an argument that composite metrics are more subjective and the results of are undesirably dependent on the specific weighting system (Singh et al., 2012).
Aggregate measures are associated with unpredictability (Turnhout et al., 2007) and are considered effective and functional tools for policy prioritization, fundamental decision-making, and communication-based system _performance_
5. Results and discussions
Among the selected papers 95.06% of them were published in the last six years with a growing trend, highlighting an increasing interest in the field by academics and researchers. All the articles have been thoroughly analyzed and studied to come out with as much information as possible on current research trends, about the several analytical aspects: journals, Methods & Approaches, Keywords, and Countries.
The following paragraphs demonstrate the results of the content analysis of the 82 selected papers.
5.1. Keywords and methods distribution
To ensure a better reading of the keywords retrieved from the collected articles, they have been categorized into four main categories: Evaluation/Assessment, Sustainability & SC, Approaches & Techniques, and Industries.
Table 7 shows the ranking by the importance of the four main categories: Key Evaluation / Assessment category first with a percentage of 30.15%.
I Table 7: Keyword classes distribution 1
Evaluation / Approaches & Assessment Techniques s Sustainability & S.C Industries / Areas Other
No 117 94 80 25 72
% 30.15 24.23 20.62 6.44 18.55
From the information in the table, it can be assumed that the statistical distribution of the keywords of the two categories Evaluation/Assessment Approaches & Techniques remains the most dominant and eminent compared to the Sustainability category. While the industry category is not too significant. The publication and scientific production are more and more numerous in this direction. This can be explained by the desire of researchers to fill an obvious lack in terms of tools and reproducible evaluation models.
The review of the literature revealed 40 various techniques & approaches - all included -. The authors have grouped all these methods into nine different categorizations detailed in fig. 3: Decision support method (33.33%), Analytical and statistical method (23.33%), Fuzzy (15.83%), Causal method
Logic control to a real number [0, 1]. When the grade
system of membership for an element is 1, it
means that the element is absolutely in that set. When the grade of membership is 0, it means that the element is not in that set. Ambiguous cases are assigned values between 0 and 1.
An arbitrary set of Provide misleading To summarize complex and mathematical messages and lead multifaceted problems into one metric
transformations based to simplistic the composite metrics are used as
method conclusions. practical tools.
(7.5%), Mathematical Modeling & Composite Metrics (4.16%), Probabilistic model (4.16%), Benchmarking (3.33%), Qualitative method (2.5%), Weighting (1.66%).
Figure 4: Pie chart detailing the methods' distribution
pie chart of methods
Decision support methods Analytical & statistical methods
Fuzzy
Cause / Effect Mathematical modeling & composite metrics
Probabilistic models Benchmarking
Qualitative methods
The decision support methods, analytical and statistical methods are by far the most used. Fuzzy logic is also present in the literature as it is generally associated with one of the methods mentioned above. Comparative and qualitative methods are used very little. Such use of methods amounts to considering several criteria at the same time and to reducing the uncertainty and subjectivity of the data in the assessment of sustainability.
5.2. Prominent countries & Journals
The geographical analysis carried out by country and continent presents by decreasing classification the number of publications and total cumulative contributions.
The Asian continent takes the upper hand with a percentage of 40.54% (with respectively 10 & 8 publications for India and China). Tables 8 and 9 below detail the list of continents whose countries record publications.
Table 8: Continents distribution
Continents
Countries
Total Times
%
Asia Europe America Africa Oceana
13 22 5 4 1
45 37 21 4 4
40.5405405 33.3333333 18.9189189 3.6036036 3.6036036
The histogram below Fig. 5 details the countries belonging to the continents that have published articles related to sustainability.
Figure 5: Distribution by country
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The continents of Asia and Europe remain those publishing the most articles with very important contributions (respectively 45 & 37). Come after the American continent with 21 publications. Publications from Africa and Oceania are minimal.
India and China remain the two most scientifically active countries. They are at the heart of all intellectual and scientific research and are very interested in initiatives in favor of sustainable measures and actions.
Fig.ure 4 shows the classification of these 82 documents by publication type. The selected journal articles were published in different kinds of journals, but a peak of publication occurs in «Journal of Cleaner Production» that has turned to be the recurrent Journal (38.27%), followed by «Socio-Economic Planning Sciences» (4.9%).
Figure 6: Journals' distribution according to the number of articles collected
Journals
Computational Science Journal of Building Engineering Urban Forestry & Urban Greening Renewable Energy Cities
Socio-Economic Planning Sciences Transport Policy Sustainable cities &/and Society Ecological Economics Transportation Research Procedia Transportation Research Part D Environmental Impact Assessment Review Journal of Cleaner Production
However, the other newspapers remain without any dominance. The dominance of the "Journal of Cleaner Production" turns out to be logical, as it is a journal focusing on cleaner production, which is one of the main goals of sustainability.
6. Conclusion
Endurance and sustainability assessments are generally conducted to support decision-making and policy in a wide range of environmental, economic, and social contexts. From this perspective, sustainability has been a major goal for businesses, nonprofits, and governments for the past decade, but it measures the extent to which an organization is sustainable or striving for sustainable growth. It can be difficult to do.
The triple bottom line which presents that the business goal states are inseparable from the society and environment in which it operates. While short-term economic benefits can be achieved, these business practices are considered unsustainable without considering the social and environmental impacts of these efforts.
In this study, sustainable supply chain measurement tools to evaluate the sustainability performance of supply chains have been discussed and reviewed. However, the systematic literature review conducted in this paper shows that, from one hand, the literature review is seen from a different point of view than the traditional state-of-art literature, the case studies and research articles have contributed to the development of a new generic vision of sustainable performance measurement systems. From another, the added benefit of this paper is that the review presented an evaluation of the advantages and weaknesses of all the methods and approaches detailed in section 4, their distinctions, and their common features. We notice that the MCDM methods are by far the most used, especially for the advantages they present as they can improve over time, especially as more cases are added to the database. They can also adapt to changes in the environment with their database of cases.
Different from the previous literature reviews on the subject, which provide limited techniques for measuring specific aspects of sustainability or sustainability indicators, this article presents the different main characteristics of each of these techniques by explaining which ones are the most used,
0 5 10 15 20 25 30 35 40 45
in which countries the publications are more numerous. This analysis also made it possible to emerge with the industries that most apply the applications of our subject namely transport and manufacturing.
Taking as main bases the results of this systemic review, in our future research we intend to conduct a meticulous and in-depth investigation on the essential dimensions to the measurement of sustainability other than the 3P (Profit, People, Planet) commonly translated by the economic, social and environmental dimensions and on the most exact and least subjective method on this subject.
Funding
The author(s) received no financial support for the research, authorship, and/or publication of this article.
Declaration of conflicting interests
The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Citation information
Farchi, C., Touzi, B., Farchi, F., & Mousrij, A. (2021). Sustainable performance assessment: A systematic literature review. Journal of Sustainable Development of Transport and Logistics, 6(2), 124-142. doi:10.14254/jsdtl.2021.6-2.8
References
Abdallah, T., Farhat, A., Diabat, A., & Kennedy, S. (2012). Green supply chains with carbon trading and environmental sourcing: Formulation and life cycle assessment. Applied Mathematical Modelling, 36(9), 4271-4285. https://doi.org/10.1016/j.apm.2011.11.056 Ahi, P., & Searcy, C. (2013). A comparative literature analysis of definitions for green and sustainable supply chain management. Journal of Cleaner Production, 52, 329341. https://doi.org/10.1016/j.jclepro.2013.02.018 Allaoui, H., Guo, Y., & Sarkis, J. (2019). Decision support for collaboration planning in sustainable supply chains. Journal of Cleaner Production, 229, 761-774.
https://doi.org/10.1016/j.jclepro.2019.04.367 Anand, M., Sahay, B. S., & Saha, S. (2005). Balanced Scorecard in Indian Companies. Vikalpa, 30(2), 1126. https://doi.org/10.1177/0256090920050202 Arena, M., Azzone, G., & Conte, A. (2013). A streamlined LCA framework to support early decision making in vehicle development. Journal of Cleaner Production, 41, 105-113. https://doi.org/10.1016/j.jclepro.2012.09.031
Asif, M., Searcy, C., Zutshi, A., & Ahmad, N. (2011). An integrated management systems approach to corporate sustainability. European Business Review, 23(4), 353367. https://doi.org/10.1108/09555341111145744 Askariazad, M., & Wanous, M. (2009). A proposed value model for prioritising supply chain performance measures. International Journal of Business Performance and Supply Chain Modelling, 1(2/3), 115. https://doi.org/10.1504/ijbpscm.2009.030637 Badri Ahmadi, H., Kusi-Sarpong, S., & Rezaei, J. (2017). Assessing the social sustainability of supply chains using Best Worst Method. Resources, Conservation and Recycling, 126, 99-106. https://doi.org/10.1016Zj.resconrec.2017.07.020
Bagloee, S. A., Shnaiderman, M., Tavana, M., & Ceder, A. (2015). A logit-based model for facility placement planning in supply chain management. International Journal of Logistics Systems and Management, 20(1), 122-147. https://doi.org/10.1080/03081060.2016.1266164
Bappy, M. M., Ali, S. M., Kabir, G., & Paul, S. K. (2019). Supply chain sustainability assessment with Dempster-Shafer evidence theory: Implications in cleaner production. Journal of Cleaner Production, 117771. https://doi.org/10.10167j.jclepro.2019.117771 Beheiry, S. M., Chong, W. K., & Haas, C. T. (2006). Examining the Business Impact of Owner Commitment to Sustainability. Journal of Construction Engineering and Management, 132(4), 384392. https://doi.org/10.1061/(asce)0733-9364(2006)132:4(384) Beloff, B., Tanzil, D., & Lines, M. (2004). Sustainable development performance assessment.
Environmental Progress, 23(4), 271-276. https://doi.org/10.1002/ep.10045 Beske-Janssen, P., Johnson, M. P., & Schaltegger, S. (2015). 20 years of performance measurement in sustainable supply chain management - what has been achieved?. Supply Chain Management: An International Journal, 20(6), 664-680. https://doi.org/10.1108/scm-06-2015-0216
Bonney, M., & Jaber, M. Y. (2014). Deriving research agendas for manufacturing and logistics systems: A methodology. International Journal of Production Economics, 157, 49-61. https://doi.org/10.1016/j.ijpe.2013.12.007 Brandenburg, M., Govindan, K., Sarkis, J., & Seuring, S. (2014). Quantitative models for sustainable supply chain management: Developments and directions. European Journal of Operational Research, 233(2), 299-312. https://doi.org/10.1016/j.ejor.2013.09.032 Bullinger, H.-J., Kühner, M., & Van Hoof, A. (2002). Analysing supply chain performance using a balanced measurement method. International Journal of Production Research, 40(15), 3533-3543. https://doi.org/10.1080/00207540210161669 Chai, J., Liu, J. N. K., & Ngai, E. W. T. (2013). Application of decision-making techniques in supplier selection: A systematic review of literature. Expert Systems with Applications, 40(10), 3872-3885. https://doi.org/10.1016Zj.eswa.2012.12.040
Charnes, A., Cooper, W. W., & Rhodes, E. (1979). Measuring the efficiency of decision-making units. European Journal of Operational Research, 3(4), 339. https://doi.org/10.1016/0377-2217(79)90229-7
Davis, E. W., & Spekman, R. E. (2004). The Extended Enterprise: Gaining Competitive advantage through
collaborative supply chains. FT press. Déprés, C., Vivien, F.-D., Lepart, J., & Pascal, M. (dir.). L'évaluation de la durabilité - Versailles, Quae, coll. «Indisciplines», 2013, 268 p., Économie rurale [En ligne], 349-350 | septembre-novembre 2015, mis en ligne le 15 décembre 2015, consulté le 24 septembre 2020. https://doi.org/10.4000/economierurale.4764
Dey, P. K., & Cheffi, W. (2012). Green supply chain performance measurement using the analytic hierarchy process: a comparative analysis of manufacturing organisations. Production Planning & Control, 24(8-9), 702-720. https://doi.org/10.1080/09537287.2012.666859 Di Pasquale, V., Franciosi, C., Iannone, R., Malfettone, I., & Miranda, S. (2017). Human error in industrial maintenance: a systematic literature review. In Proceedings of the XXII Summer School "Francesco Turco", pp. 164-170.
Dyllick, T., & Hockerts, K. (2002). Beyond the business case for corporate sustainability. Business
Strategy and the Environment, 11(2), 130-141. https://doi.org/10.1002/bse.323 Elkington, J. (1997). Cannibals with Forks: the Triple Bottom Line of 21st Century Business. Capstone, Oxford.
Erol, I., Sencer, S., & Sari, R. (2011). A new fuzzy multi-criteria framework for measuring sustainability performance of a supply chain. Ecological Economics, 70(6), 1088-1100. https://doi.org/10.1016/j.ecolecon.2011.01.00
Essajide, L., & Ali, R. (2017). Planning and modelling of Pharmaceuticals Wholesale-Distributors supply Chain using SCOR model: A Moroccan case study. International Journal of Management Sciences and Business Research, 6(3). Faisal, M.N., 2010. Sustainable supply chains: a study of interaction among the enablers. Business Process Management Journal, 16(3), 508-529. https://doi.org/10.1108/14637151011049476
Farajpour Khanaposhtani, G., Jafari, S. S., Ariana, F., Alaie, A., & Salimi, H. (2017). Formulating the supply chain strategy of automotive industry in Iran using balanced Scorecard, System Dynamics, and Game Theory. Marketing and Branding Research, 4, 135-147. Gallear, D., Ghobadian, A., Li, Y., O'Regan, N., Childerhouse, P., & Naim, M. (2013). An environmental uncertainty-based diagnostic reference tool for evaluating the performance of supply chain value streams. Production Planning & Control, 25(13-14), 1182-1197. https://doi.org/10.1080/09537287.2013.808838 Georgiadis, P., & Besiou, M. (2009). Environmental strategies for electrical and electronic equipment supply chains: which to choose?. Sustainability, 1(3), 722-733. https://doi.org/10.3390/su1030722
Ghatari, A. R., Mehralian, G., Zarenezhad, F., & Rasekh, H. R. (2013). Developing a model for agile supply: An empirical study from Iranian pharmaceutical supply chain. Iranian journal of pharmaceutical research: IJPR, 12(Suppl), 193. Glock, C. H., Jaber, M. Y., & Searcy, C. (2012). Sustainability strategies in an EPQ model with price- and quality-sensitive demand. The International Journal of Logistics Management, 23(3), 340-359. https://doi.org/10.1108/09574091211289219 Govindan, K., Mangla, S. K., & Luthra, S. (2017). Prioritising indicators in improving supply chain performance using fuzzy AHP: insights from the case example of four Indian manufacturing companies. Production Planning & Control, 28(6-8), 552-573. https://doi.org/10.1080/09537287.2017.1309716 Gunasekaran, A., Patel, C., & McGaughey, R. E. (2004). A framework for supply chain performance measurement. International journal of production economics, 87(3), 333-347. http://dx.doi.org/10.1016/j.ijpe.2003.08.003 Gunasekaran, A., Patel, C., & Tirtiroglu, E. (2001). Performance measures and metrics in a supply chain environment. International Journal of Operations & Production Management, 21(1-2), 71-87. https://doi.org/10.1108/01443570110358468
Hartmann, J., & Moeller, S. (2014). Chain liability in multitier supply chains? Responsibility attributions for unsustainable supplier behavior. Journal of Operations Management, 32(5), 281294. https://doi.org/10.1016/jjom.2014.01.005 Hassini, E., Surti, C., & Searcy, C. (2012). A literature review and a case study of sustainable supply chains with a focus on metrics. International Journal of Production Economics, 140(1), 69-82. https://doi.org/10.1016/j.ijpe.2012.01.042 Ho, W. (2008). Integrated analytic hierarchy process and its applications - A literature review. European
Journal of Operational Research, 186(1), 211-228. https://doi.org/10.1016Zj.ejor.2007.01.004 Hong, J., Zhang, Y., & Ding, M. (2018). Sustainable supply chain management practices, supply chain dynamic capabilities, and enterprise performance. Journal of Cleaner Production, 172, 3 5 0 8-35 1 9. https://doi.org/10.1016/j.jclepro.2017.06.093 Hubbard, G. (2009). Measuring organizational performance: beyond the triple bottom line. Business
Strategy and the Environment, 18(3), 177-191. https://doi.org/10.1002/bse.564 Jaber, M. Y., Glock, C. H., & El Saadany, A. M. (2013). Supply chain coordination with emissions reduction incentives. International Journal of Production Research, 51(1), 69-82. https://doi.org/10.1080/00207543.2011.651656
Jia, F., Zuluaga-Cardona, L., Bailey, A., & Rueda, X. (2018). Sustainable supply chain management in developing countries: An analysis of the literature. Journal of Cleaner Production, 189, 263-278. https://doi.org/10.1016/j.jclepro.2018.03.248 Kafa, N., Hani, Y., & El Mhamedi, A. (2013). Sustainability Performance Measurement for Green Supply Chain Management. IFAC Proceedings Volumes, 46(24), 71-78. https://doi.org/10.3182/20130911-3-br-3021.00050 Kainuma, Y., & Tawara, N. (2006). A multiple attribute utility theory approach to lean and green supply chain management. International Journal of Production Economics, 101(1), 99108.. https://doi.org/10.1016/j.ijpe.2005.05.010
Kaplan, R. S., & Norton, D. P. 1992. The balanced scorecard: measures that drive performance. Harvard
Business Review, 83(7), 172. Koberg E., & Longoni, A. (2019). A systematic review of sustainable supply chain management in global supply chains. Journal of Cleaner Production, 207, 1084-1098. https://doi.org/10.1016/j.jclepro.2018.10.033 Kot, S. (2018). Sustainable supply chain management in small and medium
enterprises. Sustainability, 10(4), 1143. https://doi.org/10.3390/su10041143 Laguna, J. M. (2014). Institutional politics, power constellations, and urban social sustainability: A
comparative-historical analysis. Doctoral dissertation, The Florida State University. Lin, L.-C., & Li, T.-S. (2010). An integrated framework for supply chain performance measurement using six-sigma metrics. Software Quality Journal, 18(3), 387-406. https://doi.org/10.1007/s11219-010-9099-2
Mani, V., Agrawal, R., & Sharma, V. (2015). Supply Chain Social Sustainability: A Comparative Case Analysis in Indian Manufacturing Industries. Procedia - Social and Behavioral Sciences, 189, 234251. "https://doi.org/10.1016Zj.sbspro.2015.03.219
Mishra, P., & Sharma, R. K. (2014). Benchmarking SCM performance and empirical analysis: a case from paint industry. Logistics Research, 7(1). https://doi.org/10.1007/s12159-014-0113-0
Moktadir, M. A., Ali, S. M., Paul, S. K., & Shukla, N. (2019). Barriers to big data analytics in manufacturing supply chains: A case study from Bangladesh. Computers & Industrial Engineering, 128, 10631075... https://doi.org/10.1016/j.cie.2018.04.013 Nappi, V., & Rozenfeld, H. (2015). The incorporation of sustainability indicators into a performance
measurement system. Procedia CIRP, 26, 7-12. https://doi.org/10.1016/j.procir.2014.07.114 Neely, A., Mills, J., Platts, K., Richards, H., Gregory, M., Bourne, M., & Kennerley, M. (2000). Performance measurement system design: developing and testing a process-based approach. International Journal of Operations & Production Management, 20(10), 11191145. https://doi.org/10.1108/01443570010343708
Otto, A., & Kotzab, H. (2003). Does supply chain management really pay? Six perspectives to measure the performance of managing a supply chain. European Journal of Operational Research, 144(2), 306-320. https://doi.org/10.1016/s0377-2217(02)00396-x Paulraj, A. (2009). Environmental motivations: a classification scheme and its impact on environmental strategies and practices. Business Strategy and the Environment, 18(7), 453-468. https://doi.org/10.1002/bse.612 Peng Wong, W., & Yew Wong, K. (2008). A review on benchmarking of supply chain performance measures. Benchmarking: An International Journal, 15(1), 25-51. https://doi.org/10.1108/14635770810854335 Pishvaee, M. S., & Razmi, J. (2012). Environmental supply chain network design using multi-objective fuzzy mathematical programming. Applied Mathematical Modelling, 36(8), 3433-3446. https://doi.org/10.1016/j.apm.2011.10.007
Popovic, T., Barbosa-Póvoa, A., Kraslawski, A., & Carvalho, A. (2018). Quantitative indicators for social sustainability assessment of supply chains. Journal of Cleaner Production, 180, 748-768. https://doi.org/10.1016/j.jclepro.2018.01.142 Pramod, V. R., & Banwet, D. K. (2011). Performance measurement of SHER service supply chain: a balanced score card - ANP approach. International Journal of Business Excellence, 4(3), 321. https://doi.org/10.1504/ijbex.2011.040108 Qazi, A., Dickson, A., Quigley, J., & Gaudenzi, B. (2018). Supply chain risk network management: A Bayesian belief network and expected utility based approach for managing supply chain risks. International Journal of Production Economics, 196, 24-
42. https://doi.org/10.1016/j.ijpe.2017.11.008 Qorri, A., Mujkic, Z., & Kraslawski, A. (2018). A conceptual framework for measuring sustainability performance of supply chains. Journal of Cleaner Production, 189, 570-584. https://doi.org/10.1016/j.jclepro.2018.04.073
Rasolofo-Distler, F., & Distler, F. (2018). Using the balanced scorecard to manage service supply chain uncertainty: Case studies in French real estate services. Knowledge and Process Management, 25(3), 129-142. https://doi.org/10.1002/kpm.1572 Reddy. K, J. M., Rao. A, N., & L, K. (2019). A review on supply chain performance measurement systems.
Procedia Manufacturing, 30, 40-47. https://doi.org/10.1016/j.promfg.2019.02.007 Ross-Smith, K., & Yearworth, M. (2011, May). Dynamics of operational procurement: systems modelling for performance tracking and auditing. In Proceedings of The 29th International Conference of the System Dynamics Society.
Saint Jean, M. (2008). Polluting emissions standards and clean technology trajectories under competitive selection and supply chain pressure. Journal of Cleaner Production, 16(1), S113-S123. https://doi.org/10.1016/j.jclepro.2007.10.009
Sari, K., & Suslu, M. (2018). A modeling approach for evaluating green performance of a hotel supply chain. Technological Forecasting and Social Change, 137, 53-60. https://doi.org/10.1016/j.techfore.2018.06.041 Sartori, S., Witjes, S., & Campos, L. M. S. (2017). Sustainability performance for Brazilian electricity power industry: An assessment integrating social, economic and environmental issues. Energy Policy, 111, 41-51. https://doi.org/10.1016/j.enpol.2017.08.054 Seuring S. (2013). A review of modeling approaches for sustainable supply chain management. Decision
Support Systems, 54(4), 1513-1520. https://doi.org/10.1016/j.dss.2012.05.053 Seuring, S., & Müller, M. (2008). Core issues in sustainable supply chain management-a Delphi
study. Business strategy and the environment, 17(8), 455-466. https://doi.org/10.1002/bse.607 Seuring, S., Brix-Asala, C., & Khalid, R. U. (2018). Analyzing base-of-the-pyramid projects through sustainable supply chain management. Journal of Cleaner Production. https://doi.org/10.1016/j.jclepro.2018.12.102 Singh, R. K., Murty, H. R., Gupta, S. K., & Dikshit, A. K. (2009). An overview of sustainability assessment methodologies. Ecological Indicators, 9(2), 189-212.
https://doi.org/10.1016/j.ecolind.2008.05.011
Thakkar, J., Kanda, A., & Deshmukh, S. G. (2009). Supply chain performance measurement framework for small and medium scale enterprises. Benchmarking: An International Journal, 16(5), 702723. https://doi.org/10.1108/14635770910987878 Thanki, S., & Thakkar, J. (2018). A quantitative framework for lean and green assessment of supply chain performance. International Journal of Productivity and Performance Management, 67(2), 366-400. https://doi.org/10.1108/ijppm-09-2016-0215 Trivedi, A., & Rajesh, K. (2013). A framework for performance measurement in supply chain using
balanced score card method: a case study. Int. J. Recent Trends Mech. Eng, 4(1), 20-23. Tseng, M.-L., Wu, K.-J., Lim, M. K., & Wong, W.-P. (2019). Data-driven sustainable supply chain management performance: A hierarchical structure assessment under uncertainties. Journal of Cleaner Production, 227, 760-771. https://doi.org/10.1016/j.jclepro.2019.04.201
Turnhout, E., Hisschemoller, M., & Eijsackers, H. (2007). Ecological indicators: Between the two fires of science and policy. Ecological Indicators, 7(2), 215-228.
https://doi.org/10.1016/j.ecolind.2005.12.003 Venkatesh, V. G., Zhang, A., Deakins, E., Luthra, S., & Mangla, S. (2019). A fuzzy AHP-TOPSIS approach to supply partner selection in continuous aid humanitarian supply chains. Annals of Operations Research, 283(1), 1517-1550.. https://doi.org/10.1007/s10479-018-2981-1 Wan, X., Liu, X., Du, Z., & Du, Y. (2021). A novel model used for assessing supply chain sustainability integrating the ANP and ER approaches and its application in marine ranching. Journal of Cleaner Production, 279, 123500. https://doi.org/10.1016/j.jclepro.2020.123500
Xia, D., Yu, Q., Gao, Q., & Cheng, G. (2017). Sustainable technology selection decision-making model for enterprise in supply chain: Based on a modified strategic balanced scorecard. Journal of Cleaner Production, 141, 1337-1348. https://doi.org/10.1016/j.jclepro.2016.09.083
Zhang, M., Tse, Y. K., Doherty, B., Li, S., & Akhtar, P. (2018). Sustainable supply chain management: Confirmation of a higher-order model. Resources, Conservation and Recycling, 128, 206-221. https://doi.Org/10.1016/j.resconrec.2016.06.015 Zuniga, R., Icarte, G., Griffiths, J., Lopez, J., & Quezada, J. (2018, February). Modeling of critical products supply chain required to affected people on earthquakes and tsunamis through use of SCOR model. In International Conference on Dynamics in Logistics (pp. 53-57). Springer, Cham.
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