• About Us +
• Editorial Board +
• For Contributors +
• Journal Search +
Journal Search Engine
ISSN : 1598-7248 (Print)
ISSN : 2234-6473 (Online)
Industrial Engineering & Management Systems Vol.21 No.2 pp.183-191
DOI : https://doi.org/10.7232/iems.2022.21.2.183

# Reducing Information Redundancy for an International Trade Transaction: A Lean Information Management Approach

Woramol C. Watanabe, Patchanee Patitad*
Department of Logistics and Digital Supply Chain Naresuan University, Phitsanulok, Thailand
*Corresponding Author, E-mail: P.patitad@gmail.com
August 11, 2020 ; January 6, 2022 ; January 6, 2022

## Abstract

An international trade transaction is a process to transfer products between different countries. This process requires a particular set of procedures and a wide range of documents and paperwork, which involves many organizations from both sides of the two countries. To identify complexity and redundancy in the processes, lean information management is applied. Complexity of flow and redundancy of information in the documents are found. They cause unnecessary costs of time and resources in the transaction process. Ponanan et al. (2019) and Srichanthamit and Suto (2019) have proposed an algorithm to reduce the complexity and information redundancy. In their algorithm, redundant information which can be considered as waste information is decreased. However, the distance, which is one of waste motion, when information is delivered from one organization to another, has not been addressed yet. In this paper, a new algorithm is proposed to include this issue when reducing redundant information. The proposed algorithm ensures information conservation of the flow and a decrease of the distance for receiving the information of each organization in the flow. Furthermore, a case of the exporting process between Thailand and Lao PDR is used to show the ability of the proposed algorithm.

## 1. INTRODUCTION

In the current era, international trade between different countries has an important role in economic development and the movement of goods, services, and materials. It allows countries to expand the markets for their products globally. An international trade transaction is one of the important processes in international trade, transferring products from the original country to the destination country. To improve the quality of international trade, regional economic integration such as the European Union (EU), the Association of Southeast Asian Nations (ASEAN), and North American Free Trade Agreement (NAFTA) helps to remove barriers to trading and establishes customs unions between countries. The above agreements focus on trade cooperation or negotiation at the management level. However, if we focus strictly on the operations level, there are still some problems in the transaction process, such as different languages and restrictions between the country of origin and the destination country, especially in paperwork.

In terms of the paperwork, the transaction process requires several documents and involves many organizations such as the customs and brokers of each country. In addition, each country has its own languages, restrictions, and document forms, which cause more complexity in the process. To submit all the required paperwork, the organizations involved need to prepare many documents which contain much information. Sometimes, the same information is contained in several documents. Under these circumstances, organizations have to fill in multiple documents at various stages of the cross-border process (Gopal, 2006).

For capturing waste in the processes, lean information management, which is a concept or philosophy that considers how to reduce and eliminate waste, making the information flow more flexible and responsive (Redeker et al., 2019), is applied. Based on the seven deadly wastes in the lean principle (Hicks, 2007), there are three main types of waste in processes: 1) overproduction, i.e., information and document redundancy, 2) unnecessary motion, i.e., time taken for information transmission, and, 3) unnecessary processes, i.e., complexity of the network of processes. Many countries are trying to reduce the complexity of the documentation requirements across borders in international trade transactions, for example, sharing their regulations and restrictions online and introducing online document submission systems (Civelek and Seçkin, 2017;World Bank, 2018). However, the problems have not yet been resolved.

To solve this problem, Ponanan et al. (2019) and Srichanthamit and Suto (2020) have proposed a framework for supporting the system for optimization of the information flow in international trade transactions. In the proposed framework, an algorithm for reducing information redundancy is presented. The concept of the proposed algorithm is to delete the edges between the nodes that are receiving the highest number of information and the nodes that are sending the most information. The authors have mentioned that, although their proposed algorithm can reduce redundant information, the distance between nodes has not yet been considered. The distance between the original node and destination node is one of the parameters that should be considered. In an international trade transaction, the distance may induce additional financial and time costs of transmissions. The time taken to retrieve information also has to be considered (Ponanan et al., 2019).

In this paper, an algorithm to reduce waste information (redundant information) in the information flow for international trade transactions is proposed. The contributions of the proposed algorithm are in ensuring information conservation of the flow and decreasing the distance for receiving the information of each organization in the flow. By using the proposed algorithm, all organizations are assured that they will receive all the information they need, and that nothing relevant will be lost as a result of the reduction of redundant information. And the distance over which all the information is to be sent from sources to each organization is not increased. The same case study as that in the work by Srichanthamit and Suto (2020) is used to explain and discuss the ability of the proposed algorithm.

## 2. BACKGROUND

In international trade, information represents the links and relationships between organizations (Meng, 2011). Information flows from one organization to other related organizations to convey the necessary information. This flow is one of the important factors that helps to maintain steady processing (Chaowarat et al., 2014). A lack of information or distorted information will cause significant problems in international trade.

While maintaining steady processing, to improve the information flow, some redundancy and unnecessary processes should be focused on. Lean thinking is one of the famous concepts or philosophies which are widely used to capture and systematically eliminate waste in a system (Thangarajoo, 2015). The term “lean” was coined by the research team working on international auto production both to reflect the nature of the waste reduction in the Toyota production system and to contrast it with craft and mass forms of production (Aziz and Hafez, 2013;Womack et al., 2007). This thinking has been applied on both manufacturing area which is lean manufacturing and administration area which called lean office. Information management is an essential part of lean thinking. One of the lean goals is to reduce waste and make information flows leaner and simpler. It also helps to streamline information flow in any administrative function and reducing the total cycle time (Yokoyama et al., 2019). Redeker et al. (2019) and Hölttä et al. (2010) have classified the wastes in information management as shown in Table 1.

There are many pieces of research that focus on improving the information flow in many kinds of networks, such as reducing information losses in a production company (Boersma et al., 2005;Petkova et al., 2005;Sander and Brombacher, 1999), increasing the efficiency and effectiveness of information spreading in a security system (Grabon and Chałupczak, 2019), reducing information delay in group cooperation in a laboratory (Caldwell, 2008), and trading of between information sharing and security (Kawanaka et al., 2018) The main feature of the above related research is the re-design of the flow to improve the information flow in many respects, such as reducing information losses, increasing the quality of information dissemination, or avoiding information delay.

However, in international trade, many organizations are involved, some of which are part of the government sector. This kind of network is quite limited in its ability to re-design its information flow due to the different countries’ restrictions and regulations. For example, some government organizations do not forward documents to other organizations. Thus the international trade network cannot be completely re-designed, and some paths in the network need to remain.

Ponanan et al. (2019) have proposed a framework for reducing the redundancy of information in international trade transaction processes. The framework has been developed based on a three-layer model which consists of a Presentation layer, Document flow layer and Information flow layer.

Figure 1 illustrates the proposed framework. The details of each layer are explained below:

• Presentation layer: Information labels are described in several languages. Documents are translated into suitable languages for the users on this layer.

• Document flow layer: The flow of all the documents in a process are represented by a network model on this layer.

• Information flow layer: The flow of all the information in a process is also represented by a network model on this layer.

To apply the framework proposed in the research, three procedures: 1) converting document flows to information flows, 2) optimizing information flows, and 3) generating document flows from information flows, are required. In the second procedure, they claim that the information flows which are generated from their proposed algorithm are optimized by using the framework proposed by Ponanan et al. (2019), and it is clear that two types of waste information: 1) overproduction, i.e., redundant information, and 2) processes, i.e., the complexity of the processes network, are eliminated. However, their algorithm only creates the information flows without any redundant information, and the information transmis- sion distance, which can be considered as waste motion, has not yet been included in the algorithm. To discuss this issue, Figure 2 shows an example of information flow. In graph (a), there are four edges and four nodes. After using the algorithm proposed by Ponanan et al. (2019), the information flow after reducing redundancy is shown in graph (b). From the comparison of the two graphs, we can see that the edge from node v2 and node v4 is eliminated, but that all of the nodes can still receive the information. However, the distance between nodes v2 and v4 is increased. Before reducing the information, the distance between nodes v2 and v4 is one unit (v2-v4), but after reducing the information, the distance becomes two units (v1-v3-v2).

The distance between the original node and destination node is one of the parameters that should be considered. In an international trade transaction, the distance may induce additional financial and time costs of transmission. The time taken to retrieve information also has to be considered (Ponanan et al., 2019). In this paper, an algorithm to optimize the information flow which involves the information transmission distance is proposed.

## 3. ALGORITHM FOR REDUCING INFORMATION REDUNDANCY

In this section, the proposed algorithm to reduce redundant information is discussed. To optimize information flows, firstly, document flows are converted into information flows. In this study, document flows and information flows are represented by a graph structure in which nodes stand for organizations and edges stand for the path of the documents or information (Srichanthamit and Suto 2019). The paperwork process in an international trade transaction named X is described as: $P X = ( D X , G X )$. Here, DX stands for a set of documents used in process X and GX stands for the structure of process X . A document $D a ( ∈ D X )$ is represented as a set of information included in the document: $D a = { i 1 , i 2 , ⋯ , i n }$ Here, $i m ( ∈ D a )$ stands for an item of information m included in Document a. Several information items are involved in a document, so documents can be considered as sets or groups of information. Obviously, all the information items contained in a document have the same network structure as the document. In addition, the same information is used in several documents. Thus, a structure of the information can be generated from the structure of the documents that contain the information. In this step, the network structure of information which is contained in different documents will be grouped into one structure. Gm, a network structure of information m, can be deduced as shown in Equation (1).

$G m = { ∪ D a ∈ D X G a | D a ∩ { i m } ≠ ∅ }$
(1)

After the flow of each information item is generated, each information flow is optimized by the proposed algorithm, which is shown in Algorithm 1.

The proposed algorithm starts with creating a set of the reachability path of information $P$ which contains reachability path, Pl, and a set of the transitive closure of the reachability path of information $P ′$ which contains the transitive closure of reachability path,$P ′ l$ (lines 1‒2). Each reachability path and its transitive closure is the set of a path of information flow from source node υi to destination node $υ j { ( υ i , υ j ) }$. In this algorithm, the transitive closure is used to check the reachability of all nodes in each path. The transitive closure of each path is checked to see if there is any redundant information that can be terminated (lines 4‒12). Then the information flow in which redundant information is reduced is returned (line 13).

### 3.1 Present Case Study

To briefly explain the proposed algorithm, the flow of information shown in Figure 3 is used as an example.

In the first step, a set of the reachability path of information a, $P a$, and a set of transitive closure of reachability path of information a, $P ′ a$, are created as shown below.

$P a = { P 1 a , P 2 a } P 1 a = { ( υ 1 , υ 2 ) , ( υ 2 , υ 3 ) } P 2 a = { ( υ 1 , υ 3 ) } P ′ a = { P ′ 1 a , P ′ 2 a } P ′ 1 a = { ( υ 1 , υ 2 ) , ( υ 1 , υ 3 ) , ( υ 2 , υ 3 ) } P ′ 2 a = { ( υ 1 , υ 3 ) }$

In the second step, redundancy paths are found. The redundant paths $P 1 a * , P 2 a *$ are ${ ( υ 2 , υ 3 ) } ∈ P 1 a$. Then, $P = { ( υ 2 , υ 3 ) } ∈ P 1 a$. Next, the redundant paths are deleted from both paths, then, $G 1 a * P 1 a * = { ( υ 1 , υ 2 ) }$. After all paths are chosen and checked for redundancy, new graphs are created which are.

## 4. CASE STUDY

In this section, in order to explain the details and show the ability of the proposed algorithm, an international trade transaction of exporting from Thailand to Lao PDR (Srichanthamit and Suto, 2020) is used as the case study. In this case study, there are seven organizations, which are 1) a seller, 2) a customs broker in Thailand, 3) a customs header in Thailand, 4) a freight forwarder, 5) a customs header in Lao PDR, 6) a customs broker in Lao PDR and 7) a buyer. There are four types of documents: 1) commercial invoice, 2) packing list, 3) bill of lading and 4) international transport permit. Table 2 illustrates the documents, the information contained in each document, and their notation. Figure 4 illustrates the document flow in the case study. Nodes stand for organizations, squares with a folded corner stand for documents and arrows indicate the path of the document flow. In Figure 4b, the document flows are represented as a graph with the symbols shown in shown in Table 2 and Table 3.

Here, we focus on the export name information (ien) for explanations. The information is contained in the commercial invoice (D1) and bill of lading (D3). The flow and graph structure are shown and described in Figure 5a. There are ten edges in the current flow which are from a combination of the flows of documents and $( υ 1 , υ 7 ) , ( υ 2 , υ 3 ) , ( υ 2 , υ 5 ) , ( υ 6 , υ 5 )$. By using the proposed algorithm, four edges, which are and of the flow, are eliminated. The optimized flow of the information is shown and described in Figure 5b. All the information flows are optimized in the same way.

Then the information flows are converted back to document flows. In this study, items of information which have completely the same network structure are grouped into the same document. The information is made into three groups:

$Group A ; i e n , i e a , i i n , i i a , i t n , and i υ n Group B ; i p n , i p d , i c p n , i c p a , i c o , i n p , i i υ n , i i υ d , and i t n Group C ; i i o d , i n o d , and i d l .$

Information items included in a group are arranged into a document. In this example, the information in Group A is arranged into Document A(DA), the information in Group B is arranged into Document B(DB), and the information in Group C is arranged into Document C(DC). The network structure of the new documents is shown in Table 1.

## 5. DISCUSSION

Table 4 illustrates the comparison of the number of information transmission and the average length of the longest path distance of all the information of the original information flow, the information flow after reducing the information by Ponanan et al. (2019), and the information flow after reducing the information using the proposed algorithm. In the comparison, three parameters, which are (1) the number of information transmissions, (2) the longest path distance of the information flow, and (3) the average length of the longest path distance of all the information in the flow, are used. The number of information transmissions shows how many times information is sent from one organization to another. This parameter can also represent overproduction and processes in the wastes in lean information management. The longest path distance of the information flow represents the distance the latest information is delivered to all organizations in the flow. The average length of the longest path distance of all the information is the average distance for all the information that is delivered to all the organizations in the flow. These two parameters can also represent the motion waste in lean information management.

After reducing redundancy in the information flow by using both algorithms, the number of information transmissions is decreased from 64 to 27 without any information loss. The longest path distance of all the information of the original information flow and the reduced information flow by Ponanan et al. (2019) are the same, which is a path via 4 nodes.

By using the proposed algorithm, the longest path distance of all the information is decreased from four to two. The average lengths of the longest path distance of all the information of the information flow for the original flow, the reduced information flow by Ponanan et al. (2019) and by the proposed algorithm are 2.67, 2.67, and 2.33 respectively.

As well as the number of information transmissions being decreased by using the algorithm proposed by Ponanan et al. (2019) and the proposed algorithm, also the longest path distance and the average length of the path distance of the flow from the proposed model are shorter. As mentioned before, the distance may induce additional financial and time costs of transmissions. If we assume that the time costs of transmission are equal in every path by using the proposed model, the information transmission time is faster.

## 6. CONCLUSION

In this paper, lean information management is applied to capture the waste in an international trade transaction. In the transaction, three wastes, which are overproduction, motion, and processes, are found. To eliminate the wastes, an algorithm for reducing information redundancy in the document flow has been proposed. To apply the proposed algorithm, firstly, all the documents which are required in a process and their flow are transformed into information flows. The information redundancy of each information flow is captured and reduced by the proposed algorithm. Then the reduced information flows are used to generate new document flows. In the proposed algorithm, transitive closure is applied to ensure the reliability of the flow. Redundant information is chosen to be reduced based on its distance from the source to the destination. By using the proposed algorithm, all organizations are able to confirm that the information received will include less redundant information, while the distance from the sources to each organization is not increased. To show the ability of the proposed algorithm, a case study of an international trade transaction is discussed. Based on the example, the proposed algorithm can reduce redundant paperwork and simplify the complexity of the paperwork processes required in international trade transaction processes. Moreover, the longest path distance over which all the information is delivered to all organizations is decreased. This means that if the transmission time of each information item is the same, the average time within which all organizations will receive the information is faster.

## Figures

An international trade transaction model (Ponanan et al., 2019;Srichanthamit and Suto, 2020).

Example of graphs by using the algorithm proposed by Ponanan et al. (2019).

Flow of information a.

Document flow of the case study.

Flow of export name information of the case study.

New document flow after reducing redundant information.

## Tables

Waste categories in lean information (Redeker et al., 2019)

Reducing redundant information

Documents and information used in the case study

Organizations in the case study.

Comparison result

## References

1. Aziz, R. F. and Hafez, S. M. (2013), Applying lean thinking in construction and performance improvement, Alexandria Engineering Journal, 52(4), 679-695.
2. Boersma, J. , Loke, G. , Petkova, V. T. , Sander, P. C. , and Brombacher, A. C. (2005), Improving the quality of information flows in the backend of a product development process: A case study, Quality and Reliability Engineering International, 21(2), 105-114.
3. Caldwell, B. S. (2008), Knowledge sharing and expertise coordination of event response in organizations, Applied Ergonomics, 39(4), 427-438.
4. Chaowarat, W. , Suto, H. , and Shi, J. (2014), An evaluation method of supply chain efficiency considering information sharing level, IEEJ Transactions on Electronics, Information and Systems, 134(11), 1640-1646.
5. Civelek, M. E. and Seçkin, N. (2017), Paperless trade evaluation of the current situation & towards the integrated single foreign trade document, Journal of Management Research, 9(2), Available from: https: //ssrn.com/abstract=3337587..
6. Gopal, C. R. (2006), Export Import Procedures - Documentation and Logistics, New Age International Pvt. Ltd., Publishers, New Delhi.
7. Grabon, C. M. and Chałupczak, W. (2019), Information flow in the security management system, Logistics and Transportation, 42(2), 21-25.
8. Hicks, B. (2007), Lean information management: Understanding and eliminating waste, International Journal of Information Management, 27(4), 233-249.
9. Hölttä, V. , Mahlamäki, K. , Eisto, T. , and Ström, M. (2010), Lean information management model for engineering changes, World Academy of Science, Engineering and Technology, 42, 1459-1466.
10. Kawanaka, T. , Rokugawa, S. , and Yamashita, H. (2018), Information sharing and security for a memory channel communication network, Industrial Engineering Management Systems, 17(3), 444-453.
11. Meng, Y. (2011), Effects of information and communication technology and relationship network on international trade. In: H. Tan and M. Zhou (eds), Advances in Information Technology and Education, Springer Berlin Heidelberg, Berlin, Heidelberg, 555-562.
12. Petkova, V. T. , Yuan, L. , Ion, R. A. , and Sander, P. C. (2005), Designing reliability information flows, Reliability Engineering System Safety, 88(2), 147-155.
13. Ponanan, K. , Srichanthamit, T. , Watanabe, W. C. , Watanabe, S. , and Suto, H. (2019), A framework of supporting system for optimizing information flow in international trade transaction, Transactions of Japan Society of Kansei Engineering, 18(1), 95-104.
14. Redeker, G. A. , Kessler, G. Z. , and Kipper, L. M. (2019), Lean information for lean communication: Analysis of concepts, tools, references, and terms, International Journal of Information Management, 47, 31-43.
15. Sander, P. C. and Brombacher, A. C. (1999), MIR: The use of reliability information flows as a maturity index for quality management, Quality and Reliability Engineering International, 15(6), 439-447.
16. Srichanthamit, T. and Suto, H. (2020), A mathematical model for a framework of supporting system for international trade transaction, Journal of Computational and Applied Mathematics, 375, 112810.
17. Thangarajoo, Y. (2015), Lean thinking: An overview, Industrial Engineering and Management, 4(2),.
18. Womack, J. , Jones, D. , and Roos, D. (2007), The Machine That Changed the World: The Story of Lean Production– Toyota’s Secret Weapon in the Global Car Wars That Is Now Revolutionizing World Industry, Free Press, New York.
19. World Bank (2018), Doing business 2019: Training for reform, Technical Report, Doing Business 2019, Washington, D.C.
20. Yokoyama, T. T. , de Oliveira, M. A. , and Futami, A. H. (2019), A systematic literature review on lean office, Industrial Engineering Management Systems,18(1), 67-77.
 Do not open for a day Close