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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

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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)

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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

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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

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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

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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

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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

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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

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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

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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.

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