a framework of sustainable service supply chain management ... · a framework of sustainable...
TRANSCRIPT
884
Journal of Engineering Technology (ISSN: 0747-9964) Volume 6, Issue 2, July, 2017, PP. 884-896
A framework of sustainable service supply chain management (Iranian National
Tax Administration)
Majid Kavosi*, Hassanali Agha Jani, Mahmood yahyazadehfar, Abdolhamid Safaei
Ghadikolaei
Department of Industrial Management, University of Mazandaran, Babolsar, Mazandaran, Iran.
Abstract: The new global reality that has emerged from the latest economic crisis has called for supply
chains to be more lean and cost effective. In addition, and due to stricter regulations and increased
community, legislatives, and consumer pressures, companies need to effectively integrate sustainability
initiatives and programs into their regular logistics and supply chain operations. In Iran, the stability of the
supply chain less attention compared to other countries has attracted. In the current research, especially in
service organizations there is a lack of sustainability of the supply chain in the process of development. This
study was identified several factors and aspects related to the development of a sustainable supply chain
management model that are useful for service supply chain. In this paper, data was collected using the
grounded theory. Grounded theory is a qualitative research analysis technique whereby theory is generated
from collected data. Inductive processes are used to collect and analyse the data, while theories, concepts,
hypotheses and propositions are generated without prior theories, assumptions or other research. Data from
the 11-member Organization tax experts was collected. According to the results of the study were identified
twelve factors in the Iranian National Tax Administration supply chain. This contributes to the continuing
research of supply chain sustainability and provides supply chain managers with a practical approach for
measuring and implementing sustainability practices across service supply chains.
Keywords: Supply chain, Sustainability, Service supply chain management, Grounded theory, Taxation.
1. Introduction
Today, organizations have realized that supply chain management to gain competitive advantage has
become a very important issue. As defined by Bowersox et al. (2002) the supply chain refers to all those
activities associated with the transformation and flow of goods and services, including money and information
flows, from the sources of materials to end users. Supply chain management (SCM) includes all programs,
initiatives, and management activities that aim at effectively running, controlling and improving supply chain
operations.
Called new reality of global supply chains that are more reliable and more affordable. In addition, due to
stricter laws and increased pressure from society, legislators and consumers organizations to effectively
integrate sustainability initiatives and programs with their supply chain needs. Therefore, due to increasing
importance of this issue, Organizations need to have stability in their operations. Sustainable Supply Chain
Management (SSCM) aims to make products and deliver quality services throughout the supply chain and at
the same time increase efficiency, reduce waste and costs, environmental responsibility is on the
agenda (Hussain and Al-Aomar, 2015). SSCM is a relatively new concept in the service sector. This challenge
is similar to the challenge of manufacturing companies: reducing environmental and social impacts while
improving profitability. Supply chain sustainability in both manufacturing and services sectors in Iran and
Middle East countries are attracting more attention from the scientific and academic organizations. However,
studies especially in the field of service supply chain are very small. This development is even more
885
apparent in the sustainable service supply chain. Thus, the aim of this paper is to present a comprehensive
model of sustainable service supply chain coordination in Iranian National Tax Administration (INTA).
2. Review of Literature
In a service supply chain coordination of members of supply chain with other members is important. In fact,
the true spirit of modern supply chain management, which distinguishes from the traditional management, is
the emphasis on coordination and cooperation between members of the supply chain channel. Thus,
coordination in service supply chain management is essential. Boyaci and Gallego (2004) investigate how
customer service achieves supply chain coordination under competition. They find that the optimal retail
service level is higher in a coordinated supply chain than that in an un-coordinated supply chain. Sethi et al.
(2007) examine a single-period two-stage service supply chain with information updating. They consider a
case in which the buyer can reorder after observing a market signal for improving the service quality (i.e., fill
rate). They identify the optimal order quantity and study the effect of order cancellations in such a service
supply chain. They use the buyback contract to coordinate the supply chain in the presence of a service
constraint.
Katok et al. (2008) examine how the inventory service-level commitment strategy can be used as a supply
chain coordination mechanism via a behavioural experiment. They first construct analytical models and then
investigate the problem in a controlled laboratory with human decision-makers. They suggest that supply
chain managers should use the service-level commitment strategy to mitigate the double marginalization
effect, and think carefully about the length of the review period. Chen and Shen (2012) examine the effect of
customer service level in a one-period two-member PSSC. They find that the optimal service level non-
increasingly affects the retailer’s profit, but non-decreasingly affects the supplier’s profit. They develop a
special class of contracts to coordinate the PSSC system, under which the profits of both parties do not
decrease, with at least one being strictly better off (i.e., a Pareto improvement). Sieke et al. (2012) propose
several service level-based supply contracts to achieve supply chain coordination. They identify the optimal
service level contracts and show how the supply chain performance differs. Liu et al. (2013) examine a
coordinating mechanism in the logistics service industry for a multi-period supply chain. They find that well-
determined punishment intensity helps to ensure the quality of logistics service. They suggest several
approaches, such as reducing information asymmetry, making logistics more visible, and reviewing
periodically the potential service quality to improve the quality of logistics services. Liu and Xie (2013)
investigate the effects of service quality on logistics service supply chains for achieving channel coordination.
They identify the optimal service quality, which increases with customer punishment. Xiao and Xu (2013)
study the service level in a supply chain under the vendor managed inventory (VMI) system. They identify the
equilibrium price and service levels under both decentralized and centralized scenarios and find that a
revenue-sharing contract can achieve supply chain coordination. Heydari (2014) investigates a coordination
mechanism in a supply chain with customer service level consideration and finds that stochastic lead time
harms the customer service level.
The literature on supply chain sustainability has mostly focused on environmental impacts while some
researchers have put together the environmental, economic and social impacts to form the widely known triple
bottom line (Hacking and Guthrie, 2008).. Linton et al. (2007) argued that sustainability in supply chains
should be moved from optimization of environmental factors to consideration of the entire supply chain, i.e.
production, consumption, customer service, and disposal of products. They posed a number of questions for
the future of supply chains, such as (a) type of resources to be used, (b) level of pollution, (c) extent of
renewable resources, (d) use of technology, and (e) the role of government policies in achieving a competitive
rank in sustainability. Ilskog (2008) recommended measuring technical impact while Herva and Roca (2013)
added institutional impact to triple bottom line in sustainable supply chain management.
Seuring and Müller (2008) acknowledged the growing significance of sustainability in supply chain literature.
They reviewed 191 articles from 1994 to 2007 and categorized them into (a) supplier management and (b)
886
supply chain management for sustainable products. They offered a conceptual framework for studying the
relationship between Stakeholders in a supply chain to improve its performance and avoid the risks involved.
They claimed that the outcomes of their conceptual framework will depend on the knowledge, experience and
mind set of the researchers or research groups. Roca and Searcy (2012) analysed 94 corporate reports to
identify 585 different sustainability indicators used in Canadian firms. These reports spanned various
corporate sectors in Canada and covered indicators ranging from customer satisfaction through emission
levels, waste generation, and water consumption. They found that all these indicators were evenly distributed
along the triple bottom line while 31 of those corporate were using the indicators identified explicitly by the
Global Reporting Initiative (GRI). This set of indicators can act as a baseline for further research in
sustainability measurement and could be used to advance the current trends in sustainability measurement in
public and private sectors. Mori and Christodoulou (2012) reviewed the requirements for the City
Sustainability Index (CSI) based on a number of indices such as ecological footprint, human development, and
genuine progress. These indices spanned the triple bottom line of social, economic and environmental aspects.
The CSI is vital for comparing the sustainability performance of cities across the world and it can help
authorities set a guideline for accomplishing their sustainability endeavours.
Ahi and Searcy (2013) identified 22 definitions of green supply chain management and 12 definitions for
SSCM through a systematic literature review. They tried to identify convergence and divergence among the
definitions presented under the two notions. For this analysis, they used a number of dimensions in business
sustainability (i.e., economic, environmental, social, and long-term focuses) and SCM (i.e., flow,
coordination, stakeholder relationship, and efficiency).
As mentioned earlier, this is a relatively new area of sustainability research and with limited number of studies
and literature. For example, Hasan (2013) examined the relationship between sustainable supply chain
practices and operational/environmental performance. He devised a framework for this study and validated it
through case studies in a number of service and manufacturing firms. The study found that sustainable supply
chain practices have a significant impact on the environmental performance of both manufacturing and service
firms. Kuo et al. (2013) developed an empirical model to study the impact of pressure, strategy, uncertainty,
internal management and external management on sustainable service supply chain practices in Taiwan and
Vietnam. Their hypotheses proved that all the five factors have a prominent impact on the SSCM in the
corporate in both countries though the level of impact may be different.
Brindley and Oxborrow (2013) emphasized the need for aligning the green practices in marketing to
sustainability objectives. They demonstrated this through a case study at a university in the UK. The study
also outlined the importance of reverse information flow and intermediaries in this context.
Chen et al. (2011) deployed the Theory of Planned Behaviour (TPB) to study sustainability practice in more
than 500 dining services at USA-based colleges and universities. They analysed how personal attitudes
(personal norms, PN) and pressure from administration and students (subjective norm, SN) influence
sustainable behaviours. They used Exploratory Factor Analysis (EFA) to group the indicators for various
latent variables and used CFA and SEM to investigate the developed model.
Govindan et al. (2014) performed a review of research on evaluating suppliers in the light of their green
practices. They found that researchers have mostly focused on suppliers' environmental management systems.
Similarly, Grimm et al. (2013) studied two food supply chains and identified fourteen critical success factors
in managing sub-supplier relationship. They classified these success factors as (a) focal firm-related, (b)
relationship-related, (c) supply chain partner-related, and (d) context-related factors.
In the summary, most researchers have focused on different aspects. Some studies also an extensive review of
sustainability with a framework and /or development indicators have provided. As noted above, several
studies have identified various indicators of stability, but little of them attention to setting up a comprehensive
service supply chain coordination model. Although these studies contain a number of articles that review
the indicators and models in the production section, enough attention for exploring the relevant index has not
887
been in the service industry. Therefore, measuring of sustainability in the service sector is a fertile area to
explore.
Hence, this paper tries to use grounded theory and fuzzy cognitive map analysis to modelling sustainable
supply chain coordination in Iranian National Tax Administration.
3. Methodology of the Study
The main objective of this study is to identify sustainable supply chain activities and coordinated action in
the service sector. In order to achieve this objective, a comprehensive research method has been developed.
First, the data was collected by means of grounded theory. After collecting and theoretical saturation coding
process to achieve the dimensions of the model is done. For data analysis techniques of fuzzy cognitive map
(FCM) was used. For drawing and analysis of fuzzy cognitive maps, UCINET and FCMapper software was
used.
3.1 Data collection
Grounded theory (GT) is a qualitative research analysis technique whereby theory is generated from collected
data. Inductive processes are used to collect and analyse the data (Punch, 1998; Charmaz, 2000), while
theories, concepts, hypotheses and propositions are generated without prior theories, assumptions or other
research. There are no rigid prescriptions for grounded theory, but there is a set of flexible strategies that
allows the researcher to experiment with. It specifies analytic strategies, not data collection methods (Chamaz,
2000). The interpretation of the data by the researcher shapes the emerging codes. According to Strauss and
Corbin (1990), GT is: "a qualitative research method that uses a systematic set of procedures to develop and
inductively derive a phenomenon". Strauss and Corbin's analysis involves posing analytic questions. Glaser
(1992) defines grounded theory as: "a general methodology of analysis linked with data collection that uses a
systematically applied set of methods to generate an inductive theory about a substantive area".
There are many varied ways of conducting research using GT. Some of these ways are very prescriptive
(Strauss and Corbin, 1990) but others leave room for the researcher to direct his or her research in a way that
suits the research environment. The proponents of GT method, however, urge researchers to use the method
flexibly (Glaser and Strauss, 1967) and are strongly supported by Charmaz (2006), who refuses to accept any
prescriptive way of using this method. Instead she regards the method as a guiding framework, that is, "a set
of principles and practices" which any researcher can fine tune to suit the context of the particular research
project (Charmaz, 2006). The basic tenet of GT is to allow free discovery of theory and, by all means, to limit
any preconceptions (Mavetera and Kroeze, 2009)
In this study, 11 deep and semi-structured interviews were carried out Tax Experts. According to
the terms and the key points in interviews labels concept has been chosen for them. After the initial coding,
the researcher combine codes and put it similar codes in abstract classes that named Categories, Finally,
similar Categories were a particular conceptual level. In this study 15 categories and 40 properties associated
with the categories were extracted:
Features Tax Service (prerequisite of economic activity, long duration of service), the need to
outsource (Organizational restrictions, the number and diversity of the taxpayers, need to focus on technology
and skills), associated costs (taxpayers, staff), institutional mechanisms (taxpayers management , capacity
and skills management, Service performance management , relationship management with suppliers,
knowledge management, risk management),technical and technological mechanisms (IT), mechanisms for
information sharing (sharing of benefits, Sharing information, managing the process of assessment
of taxation), the hardware Capability (infrastructure of IT, infrastructure of human resources), the behavioural
capability (tax culture, confidence, learn and procedural knowledge sharing, attitude to
cooperation),conditions in the state (importance of income taxation, environmental issues,
social responsibility), features of suppliers (positions suppliers in the state, the number of suppliers,
Level of technical potential, Level of behavioural potential), Performance (taxes just
888
in time, reduce costs),quality of service (fair taxation, determining the actual income), flexibility(speed
of response, the discovery of new sources of taxation), organizational synergies (synergies operation of
tangible assets, synergies operation of intangible assets) and cultural excellence (organizational culture ,
tax culture).
3.2 Data analysis
The output of a systematic approach using fuzzy cognitive map to reach the final sustainable supply chain
coordination model in INTA will be analyzed.
Cognitive maps have been recognized as important instruments for the structuring and clarification of
complex decision situations (cf. Eden 2004; Ackermann et al. 2011; Ferreira et al. 2011; Carlucci et al. 2013).
As stated by Gavrilova et al. (2013: 1758), “maps as visual tools facilitate the representation and
communication, support the identification and the interpretation of information, facilitate consultation and
codification, and stimulate mental associations”. These maps are interactive, versatile, and perhaps most
importantly, they foster discussion among decision makers, allowing for a better understanding of decision
situations through recourse to participants’ existing knowledge and their joint creation of new insights.
Cognitive mapping became an even more powerful tool with the development of fuzzy cognitive maps
(Kosko 1986, 1992), which have been extensively applied to a variety of different contexts and decision
problems, sharing the common trait of complexity (e.g. Kim and Lee 1998; Stylios and Groumpos 1999;
Tsadiras et al. 2003; Carvalho 2013; Ferreira et al. 2015a). In this type of maps, the relationships between
criteria can be represented by positive and negative causality; the intensity of which is then translated into a
number which can vary from –1 to 1. Specifcally, all the values in the map can be fuzzy and, therefore, each
concept has a state value Ai that can be a fuzzy value in the range [0, 1] or a bivalent logic in {0, 1}.
Additionally, the weights of the relationships/arcs can be a fuzzy value within [–1, 1] or a trivalent logic
within {–1, 0, 1}. As pointed out by Salmeron (2012) and Carlucci et al. (2013),the resulting map then allows
for dynamism, by including feedback links between the criteria, as shown in Figure 1, where Ci is criterion i
and Wij represents the extent to which criterion i influences criterion j. As discussed, this relationship (Wij)
can be of positive, negative or null causality, depending on whether Ci causes a move in the same direction,
the opposite direction or has no impact on Cj.
Behind this graphical representation, there is a mathematical background. As discussed by Mazlack (2009)
and Carlucci et al. (2013), there is a 1 x n state vector A that includes the values of the n criteria; and a n x n
adjacency matrix W that gathers the weights Wij of the interconnections between the n criteria. Kok (2009)
states that non-zero values on the main diagonal might be considered, but the adjacency matrix usually
presents all the entries of the main diagonal equal to zero, meaning that no criterion causes itself. The value of
each criterion is influenced by the values of the interconnected criteria (with the appropriate weights) and by
its previous value. Te mathematics behind FCMs can be summarized in formulation (1), where Ai (t) is the
activation level of criterion Ci at time t; Ai(t-1) is the activation level of criterion Ci at time t-1; Aj(t-1) is the
activation level of criterion Cj at time t-1; Wji is the weight of the interconnection between both criteria; and f
represents a threshold activation function:
1
( ) ( 1) ( 1).n
i i j ji
j
A t f A t A t W
(1)
As explained by Mazlack (2009: 6), every criterion has a new value at every step of interaction, and “the new
state vector A new is computed by multiplying the previous state vector A old by the weight matrix W”. This
means that the overall impact of a change in the value of one criterion can be given by Anew. According to
Carlucci et al. (2013: 213), “the resulting transformed vector is then repeatedly multiplied by the adjacency
matrix and transformed
889
until the system converges to a fixed point. Typically it converges in less than 30 simulation time steps”. The
result is that: (1) the impact of changes in the value of any single criterion can be assessed; (2) the strength of
variables’ impact on each other can be determined; and (3) “what-if” questions can be formulated, to ascertain
the impact on the system as whole of changes in some variables and/or the addition/removal of criteria.
3.3 Analysis of concepts in the causal map
Domain Analysis that includes input, the output and centrality is a means to determine the position of each of
the concepts in the causal map.
Domain analysis maps of Experts indicates that operating conditions in the state, the software capability, the
hardware capability, outsourcing, costs of service, institutional mechanisms as more effective and strategies,
quality, performance, flexibility, synergies, cultural excellence, institutional mechanisms, mechanisms to
share information and technical mechanisms are Impressionable respectively. The centrality index of maps
indicates that strategic, institutional mechanisms, technical mechanisms, the situation in the state, the software
mechanisms to share information and hardware capability of the most important factors in the cognitive
map of Experts (Table 1).
Table 1. Domain analysis of maps
The Concept output Input centrality
Feature Services 4.10 0.00 4.10
Outsourcing 6.50 0.00 6.50
Cost of Services 5.80 0.00 5.80
Institutional mechanisms 4.80 5.40 10:20
Technical mechanisms 4.20 4.90 9.10
Mechanisms of sharing information. 3.60 5.00 8.60
hardware capability 6.80 1.20 8.00
Software capability 7.50 1.20 8.70
The situation in the state 8.70 1.20 9.90
Sustainable Strategies 4.50 8.00 12:50
Organizational Culture 2.60 0.60 3.20
Features suppliers 2.60 0.60 3.20
IT maturity level 2.60 0.60 3.20
Performance 0.00 7.10 7.10
Quality 0.00 7.20 7.20
Flexibility 0.00 7.10 7.10
Synergies 0.00 7.10 7.10
Cultural excellence 0.00 7.10 7.10
3.4 Similarities and differences between the maps
According to research implementation process, after extracting cognitive maps of each of the experts turn to
do the necessary analysis to examine the feasibility and integration of extracting cognitive maps. For
890
analysing the causal maps of experts, similarity and distance between the causal expert’s maps checked using
analytical tools.
Quadratic Assignment Procedure Correlation (QAP) was used to measure the similarity of expert’s maps. The
output of this analysis is Square matrix which shows the correlation maps of Experts on mutually. Hypothesis
of this analysis are as follows:
The null hypothesis: between the i -th and j –th maps correlation does not exist.
Alternative hypothesis: between the i -th and j -th maps there was a linear correlation.
Figure 1. The correlation of expert’s maps
Figure 2. A significant amount of correlation of expert’s maps
Given that a significant number of all paired comparisons of less than 0.05, so the null hypothesis is rejected
in all cases and correlation is confirmed.
In addition, for the nature of similarity or difference between the cognitive maps of Experts, testing of
advanced statistical processing multi-dimensional scale and cluster analysis was used.
Method of multi-dimensional scale is a multivariate statistical method that explains the drawing pattern
similarity or difference between participants in a multidimensional space. The method for providing
a graphical analysis of the state of similarity or dissimilarity of subjects and understand the pattern of them
and For this reason researchers in social network analysis and cognitive map, this method is considered one
of the advanced statistical methods and used it (Schaffernicht and Groesser 2011).
Figure 3. Shows similarities expert’s maps
891
Figure 4. Shows the difference expert’s maps
As can be seen the results of this analysis are similar and almost equal and there is no difference between
the maps.
4. Results and analysis
Considering results associated with correlation analysis (QAP) and the distance between cognitive maps show
that there is no significant difference between them. As you can see the results of Multidimensional Scaling
and cluster analysis are almost similar, and there is no difference between the maps. So cognitive maps of
experts can be merged. In this study, for merging cognitive maps of Experts using known pattern in the
literature of cognitive maps which is same map that means the map all the experts have solidarity about its
components (Figure 5).
Ruling contexts:
*Hardware Capability Infrastructure of IT
Infrastructure of HR
*Behavioural Capability Culture
Confidence
Attitude Procedural knowledge
Sharing
*Conditions in the state Environmental and
Social responsibility
Importance of Income tax
Causal
conditions:
*Features Tax
Service
Prerequisite Long duration
*Outsource Restri
ctions Diversity of The taxpayers
Personnel
*Costs
Coordination mechanisms *Institutional mechanisms
Taxpayers’ management Supplier management
Skills management
Risk management Knowledge management
Financial management
ServicesPerformance Management
*IT mechanisms
*Sharing information
mechanisms
Sharing of benefits and Information
Assessment tax management
Sustainable strategies: Environmental Management
Social responsibility
Outcome: *Performance Taxes just in time
Reduce costs
*Quality Fair taxation
Increase the level of
service
* flexibility Response speed
Discover new resources of tax
*Synergy Exploitation of tangible and
intangible assets
*Promoting culture Organizational
Culture
Tax culture
Interferer conditions *Culture
*Suppliers Features Position of suppliersin the
state
Number of suppliers Degrees of technical and
behavioural potential
*the maturity level of IT
892
Figure 5. The model of sustainable supply chain coordination in State Tax Organization
The integrating model consists of six sections; in following describe each of them.
4.1. The main phenomenon
According to the aim of the research, designing sustainable supply chain coordination model in INTA
after collecting data and analyzing them and checking the features, this section as main phenomenon has been
chosen that contains: institutional mechanisms (taxpayer (customer) management, relationship management
with suppliers, capacity and skill management, risk management, knowledge management, Financial
management , Services Performance Management), technical and technological mechanisms (IT
management), mechanisms of sharing information.(sharing information, sharing interests, tax detection
process management).
4.2. Causal conditions:
These conditions develop the main phenomenon. Causal conditions provoke some structural characteristic and
also affect strategy of coordination mechanisms. Causal conditions include: features of services tax (tax as a
prerequisite, long time of service), need of outsource (organizational restrictions, diversity of customers, the
need of focus on personnel skills) and costs associated with the coordination.
4.3. Sustainable strategies:
Strategies reflect the behaviours, actions and interactions purposeful which cause consequences of core
classes and conditions under the influence of Interferer conditions and Ruling contexts. This class includes:
Environmental Management and Social responsibility.
4.4. Ruling contexts:
The certain conditions that affect the interactions called contexts. This situation is a set of concepts
and classes or variable contexts. Ruling contexts in the supply chain coordination, in fact, parameters are
constant, which determines the method of Coordination of INTA with suppliers that include: hardware
capabilities (infrastructure information technology, infrastructure human resources), behavioural capability
(culture, confidence, attitude to work and procedural knowledge sharing) and the situation in the state
(importance of taxation in the state, the importance of social responsibility, the importance of environmental
responsibility).
4.5. Interferer conditions:
Interferer variables include a set of variable of interface which affected the strategies that include:
organizational culture, characteristics of suppliers(position of suppliers in the state, the number of suppliers,
degrees of technical potential, degrees of behavioural potential) and the level of IT maturity.
6. Outcome (s):
Some categories include outcomes that caused by adoption of strategies. Such as performance (taxes just in
time, reduce costs), quality (fair taxation, increase the level of service), flexibility (speed of response, the
discovery of new sources of taxation), Synergy (Exploitation of tangible and intangible assets) and promoting
culture (Organizational culture and tax culture) are.
5. Discussion and conclusion
As mentioned in the introduction, the nature of services supply chain will require a model based on
characteristics of the services that developed to evaluate service supply chain.
Reviewing results shows that further studies have been done on service supply management, and few studies
on demand management or coordination of service supply chain are focused. In fact, studies on the
893
coordination of service supply chain are less than the two other. These findings highlight two issues. First, the
effect of service supply chain management has remained undeveloped because most studies on a single aspect
of service supply management or demand management are focused. Second, it is needed to combine the
supply and demand management to achieve the best service supply chain system. Therefore, more emphasis
on service supply chain coordination is needed. So, previous studies indicate that the framework and available
models for this study was not suitable, so in this study taking into account the objectives of the research,
knowledge and experience of experts, a coordinated model for sustainable supply chain management in The
INTA has developed.
Issues such as social welfare and environmental sustainability, in connection with the service supply chain
still completely not covered, sustainable supply chain management in the service sector is a relatively new
field of research and there are a small number of studies. The three dimensions of sustainability in the service
supply chain management investigating and provideing a comprehensive model is not almost exist.
There are many Frameworks, models and theories about the service supply chain that generated from product
supply chain, but further work on the framework of service supply chain in particular should be done. In this
research in order to identify aspects of the model with the use of qualitative methods, grounded theory, aspects
of sustainable supply chain coordination model in the services sector, is one of the innovations of
the important in this research. Grounded Theory is a research method of inductive and discovery that allows
researchers in various fields rather than relying on existing theories develop a theory. In this way, using
regular method of gathering data identifies categories, content and the relationship between them and
represents a theory for explaining a process.
Developing a supply chain model is a starting point in order to achieve organizational maturity. Since the
income index is too favourable by the managers of the organization's tax affairs, it would lead a decrease in
the proper performance of the supply chain in the long term. With regarding the analysis obtained from
expert’s cognitive maps, the most important factors in the model are: institutional mechanisms, technical
mechanisms, the situation in the state, behavioural capability, the mechanisms of sharing information and
hardware capability.
5.1 Future research directions
Due to differences between service industries, the methodology of this research in service supply chain
organizations could be examined. On the other hand of analytical studies -comparing, adjusting the
dimensions of the model, to be considered results in all government agencies, or any individual or similar
organization.
References
Ackermann, F.; Andersen, D.; Eden, C.; Richardson, G. (2011). ScriptsMap: a tool for designing multimethod
policy-making workshops, Omega: Te International Journal of Management Science 39(4):427–434.
Ahi P, Searcy C. (2013). A comparative literature analysis of definitions for green and sustainable supply
chain management. J Clean Prod. 52:329–41.
Axelrod R., (1976). Structure of Decision: The Cognitive Maps of Political Elites, Princeton University Press.
Bowersox DJ, Closs DJ, Cooper MB. (2002). Supply chain logistics management. New York: McGraw-Hill.
Boyaci T., GallegoG., (2004). Supply chain coordination in a market with customer service competition.
Production and Operation Management, 13:1, 322-42
Brindley C, Oxborrow L.(2013). Aligning the sustainable supply chain to green marketing needs: a case
study. Ind Mark Manag.
Carlucci, D.; Schiuma, G.; Gavrilova, T.; Linzalone, R. (2013). A fuzzy cognitive map based approach to
disclose value creation dynamics of ABIs, in Proceedings of the 8th International Forum on Knowledge
Asset Dynamics (IFKAD-2013), 12–14 June 2013, Zagreb, Croatia, 207–219.
894
Carter CR, Easton PL. (2011). Sustainable supply chain management: evolution and future directions. Int J
PhysDistLogist Manag.41:46–62.
Carvalho, J. (2013). On the semantics and the use of fuzzy cognitive maps and dynamic cognitive maps in
social sciences, Fuzzy Sets and Systems 214: 6–19.
Charmaz K (2000). “Grounded theory: objectivist and constructivist methods”. In: Denzin, NK and Lincoln
YS (Eds.), Handbook of Qualitative Research, 2nd ed., Sage, Thousand Oaks, CA.
Charmaz K (2006). Constructing grounded theory: A practical guide through qualitative analysis. Sage,
Thousand Oaks’, California.
Chen CR, Gregoire MB, Arendt S, Shelley MC.(2011). College and university dining services administrators’
intention to adopt sustainable practices: results from US institutions. Int J Sustain High Educ.12:145–62.
Chen X., Shen Z., (2012). An analysis of a supply chain with options contracts and service requirements. IIE
Transactions, 44(10), 805–819
Christopher ,M(2005),Logistics and supply chain management: creating value-adding networks, 4th ed.
Includes index. ISBN 978-0-273-73112-2
Colin A. Hodgkinson, David Goldman, Judith Jaeger, ShaliniPersaud, John M. Kane ,Robert H. Lipsky , Anil
K. Malhotra (2004). Disrupted in Schizophrenia 1 (DISC1): Association with Schizophrenia,
Schizoaffective Disorder, and Bipolar Disorder, 75(5) 862–872.
Creswell, J. W. (2005), Educational Research: Planning, Conducting, andEvaluating Quantitative and
Qualitative Research (2nd edition).
Eden, C.; Ackermann, F. (2004). Cognitive mapping expert views for policy analysis in the public sector,
European Journal of Operational Research 152(3): 615–630.
Ferreira, F.; Jalali, M.; Ferreira, J.; Stankevičienė, J.; Marques, C. (2015a). Understanding the dynamics
behind bank branch service quality in Portugal: pursuing a holistic view using fuzzy cognitive mapping,
Service Business, AOP 21 April.
Ferreira, F.; Santos, S.; Rodrigues, P. (2011). Adding value to branch performance evaluation using cognitive
maps and MCDA: a case study, Journal of the Operational Research Society 62(7): 1320–1333.
Gavrilova, T.; Carlucci, D.; Schiuma, G. (2013). Art of visual thinking for smart business education, in
Proceedings of the 8th International Forum on Knowledge Asset Dynamics (IFKAD-2013), 12–14 June
2013, Zagreb, Croatia, 1754–1751.
Glaser B (1992). Basics of Grounded Theory Analysis: Emergence vs Forcing. Sociology Press, Mill Valley,
CA
Glaser, Barney G. (1978), Theoretical Sensitivity: Advances in the Methodology of Grounded Theory, Mill
Valley, California: The Sociology Press.
Glaser, Barney G., Strauss,(1967). The Discovery of Grounded Theory: The Strategies for Qualitative
Research.
Gold S, Seuring S, Beske P.(2010). Sustainable supply chain management and inter‐organizational resources:
a literature review. Corp SocResp Environ Manag.17:230–45.
Govindan K, Azevedo SG, Carvalho H, Cruz-Machado V. (2014). Impact of supply chain management
practices on sustainability. J Clean Prod.85:212–25.
Grimm JH, Hofstetter JS, Sarkis J. (2013). Critical factors for sub-supplier management: a sustainable food
supply chains perspective. Int J Prod Econ
Hacking T, Guthrie P. (2008).A framework for clarifying the meaning of Triple Bottom-Line, Integrated, and
Sustainability Assessment. Environ Impresses Rev, 28:73–89.
Hagiwara M. (1992) “Extended Fuzzy Cognitive Maps”, Proceedings of the 1st IEEE International
Conference on Fuzzy Systems, New York, NY, 795–801.
Hasan M. (2013). Sustainable supply chain management practices and operational performance. Am J Ind Bus
Manag. 3:42–48.
895
Herva M, Roca E. (2013). Review of combined approaches and multi-criteria analysis for corporate
environmental evaluation. J Clean Prod. 39: 355–71.
Heydari J., (2014). Coordinating supplier’s reorder point: A coordination mechanism for supply chains with
long supplier lead time. Computers & Operations Research 48, 89–101
Hussain M, Khan M, Al-Aomar R,(2015). A framework for supply chain sustainability in service industry
with Confirmatory Factor Analysis. Renewable and Sustainable Energy Reviews.16(3),1-12
Ilskog E.(2008). Indicators for assessment of rural electrification—an approach for the comparison of apples
and pears. Energy Policy.36:2665–73.
Jänicke M.(2008). Ecological modernisation: new perspectives. J Clean Prod.16:557–65.
Kandasamy, V. S Florentin, (2003). "Fuzzy cognitive maps and neutrosophic cognitive maps".
Katok E., Thomas D., Davis A., (2008). Inventory service-level agreements as coordination mechanisms: the
effect of review periods. Manufacturing & Service Operations Management, 10(4), 1–16
Kim, H.; Lee, K. (1998). Fuzzy implications of fuzzy cognitive map with emphasis on fuzzy causal
relationship and fuzzy partially causal relationship, Fuzzy Sets and Systems 97(3): 303–313.
Kok, K. (2009). Te potential of fuzzy cognitive maps for semi-quantitative scenario development, with an
example from Brazil, Global Environmental Change 19(1): 122–133.
Kosko, B. (1986). Fuzzy Cognitive Maps. International Journal of ManMachine Studies, 65-75.
Kuo TC, Chen GY, Dang HT, Chiu M, Hsu C. (2013). The adoption of sustainable supply chain management
practices in Taiwan and Vietnam. J EngTechnolManag.
Langfield-Smith, K. & Wirth, A. (1992). Measuring Differences Between Cognitive Maps, Journal of the
Operational Research Society, 43(12), 1135-1150.
Linton JD, Klassen R, Jayaraman V. (2007). Sustainable supply chains: an introduction. J Oper
Manag.25:1075–82.
Liu W., Xie D., Xu X.,( 2013). Quality supervision and coordination of logistic service supply chain under
multi-period conditions. International Journal of Production Economics, 142(2), 353–361.
Liu W.H., Xie D., (2013). Quality decision of the logistics service supply chain with service quality guarantee,
International Journal of Production Research, 51(5), 1618–1634.
MarkoczyL , Goldberg J (1995), A method for eliciting and comparing causal maps, Journal of Management.
21(2), 305-333.
Mazlack, L. (2009). Representing causality using fuzzy cognitive maps, in Proceedings of the Annual Meeting
of the North American Fuzzy Information Processing Society, 14–17
Mavetera N, Kroeze JH (2009). Practical considerations in grounded theory research. Sprouts: Working
Papers on Information Systems, 2:9-32.
Miles, L., & Keenan, M. (2003). Practical Guide to Regional Foresight in United Kingdom. Paper presented at
the Office for Official Publications of the European Communities, Luxemburg.
Miller, J. (1999). Foresight ICT report. Foresight sector working group: Information and communications
Technology.
Mollenkopf D, Stolze H, Tate WL, Ueltschy M. (2010) Green, lean, and global supply chains. Int J
PhysDistLogist Manag.40:14–41.
Mori K, Christodoulou A. (2012) Review of sustainability indices and indicators: towards a new City
Sustainability Index (CSI). Environ Impact Assess Rev.32:94–106.
Niculescu M, (2006) “Strategic positioning in Romanian higher education”, Journal of Organizational Change
Management. 19 (6) 1-13.
Özesmi, U. (1999). Modelling ecosystems from local perspectives: fuzzy cognitive maps of the Kizilirmak
Delta wetlands in Turkey. Paper presented at the 1999 World Conference on Natural Resource
Modelling, Halifax, NS, Canada.
Özesmi, U., Özesmi, S. L. (2004). Ecological models based on people’s knowledge: a multi-step fuzzy
cognitive mapping approach. Ecological Modelling, 176, 43–64 .
896
Punch KF (1998). Introduction to social research: quantitative and qualitative approaches. Sage, Thousand
Oaks, California.
Roca LC, Searcy C. (2012) An analysis of indicators disclosed in corporate sustainability reports. J Clean
Prod.20:103–18.
Salmeron, J. (2012). Fuzzy cognitive maps for artificial emotions forecasting, Applied Sof
Computing12(12):3704–3710
Sarkis J, Zhu Q, Lai K. (2011)An organizational theoretic review of green supply chain management
literature. Int J Prod Econ.130:1–15.
Schaffernicht Ma , Stefan N. Groesser (2011) A comprehensive method for comparing mental models of
dynamic systems, European Journal of Operational Research 210, 57–67.
Sethi S.P., Yan H., Zhang H., Zhou J., (2007). A supply chain with a service requirement for each market
signal. Production and Operations Management, 16(3), 322–342
Seuring S, Müller M.(2008) From a literature review to a conceptual framework for sustainable supply chain
management. J Clean Prod.16:1699–1710.
Sieke M.A., Seifert R.W., Thonemann U.W., (2012). Designing service level contracts for supply chain
coordination. Production and Operation Management, 21(4), 698–714
Srivastava SK. (2007) Green supply‐chain management: a state‐of‐the‐art literature review. Int J Manag
Rev;9:53–80.
Sundarakani B, de Souza R, Goh M, Van Over D, Manikandan S , Koh SL. (2010) A sustainable green supply
chain for globally integrated networks. In: Enterprise networks and logistics for agile manufacturing.
Springer;191–206.
Strauss A ,Corbin J,(1990). Basics of qualitative research, li.suu.edu.
Strauss A ,Corbin J,(1997). Grounded theory in practice. books.google.com
Stylios, C.; Groumpos, P. (1999). Fuzzy cognitive maps: a model for intelligent supervisory control systems,
Computers in Industry 39(3): 229–238.
Tsadiras, A.; Kouskouvelis, I.; Margaritis, K. (2003). Using fuzzy cognitive maps as a decision support
system for political decisions, in Proceedings of the 8th Panhellenic Conference on Informatics (PCI-
2001), 8–10 November 2001, Nicosia, Cyprus, 172–182.
Xiao T., Xu T., (2013). Coordinating price and service level decisions for a supply chain with deteriorating
item under vendor managed inventory. International Journal of Production Economics, 145(2), 743–752
Yaman D., Polat S.,(2009) “A fuzzy cognitive map approach for effect-based operations: An illustrative case”,
Information Sciences 179, 382 – 403.
Yundong C., Chunyan M., Hwee T., ZhiqiSh., (2008) “Context Modelling with Evolutionary Fuzzy Cognitive
Map in Interactive Storytelling”.