Analysis of dynamic effects on seaports adopting port security policy

https://doi.org/10.1016/j.tra.2013.01.039Get rights and content

Abstract

Policy variables, such as security levels at seaports, affect port efficiency in a non-linear way while other factors affecting efficiency at ports such as a number of berths, the area of port yard, and the number of port labors have linear structural relation. Ensuring a certain level of regulations can increase port efficiency, while an excess of the level may result in the reverse of these gains. Addressing seaport-related issues is not a simple undertaking because a seaport is regarded as a system-of-system, which is both difficult to understand and to model. Therefore, studies that adequately analyze the overall dynamic of a port complex in terms of security concerns have been seen insufficient, leaving a significant research gap to fill in. To analyze the relationship between seaport security levels and container volumes, this study adopts the method of System Dynamics (SD). Use of the SD can demonstrate the benefits of simulations, such as suggesting the visual causal loops among evaluation factors, representing the several sub-models, and enabling various forms of analysis, such as the base model, optimistic scenario model, and pessimistic scenario model. As a result of simulation, the impacts on handling container cargo volumes in Korea due to the increasing level of security is estimated at 2,770,000 TEUs by the year 2015 and 3,050,000 TEUs by 2020. Appropriate tailor of the proposed SD based methodology can stimulate security–economic quantitative analysis in a wider range of port context, thus promoting effective implementation of security measures.

Highlights

► Develop a port security economic model to evaluate the impacts of port security policies to container volumes. ► Identify the major factors influencing port security and economics. ► Analyze the interrelationship between the factors using primary data from port operators and shipping companies. ► Provide a transparent decision making tool for port operators to determine their security policies and container volumes. ► Predict the container volume of Korean ports in the next 10 years at different security levels.

Introduction

Maritime security has emerged as an important international issue after the events of terrorist attacks on September 11, 2001. Seaports, through which large-volume cargoes pass, remain a vulnerable target against terrorism threats. Various efforts are routinely requested to reduce the likelihood and consequences of port terrorism and threats, and to improve port security. The international community, including governments and industry participants, has focused on improving maritime security through establishing legislation, developing new technologies, and using various training programs. Significant security initiatives, including the International Ship and Port Facility Security code (ISPS code), the Container Security Initiative (CSI), the 24-h Advance Manifest Rule, Customer-Trade Partnership Against Terrorism (C-TPAT), and the Authorized Economic Operator (AEO) of the World Customs Organization, have been implemented. The process of achieving international agreement on legislation relating to port security is exceptionally fast compared to other areas of international law. Although such regulations and policies have greatly enhanced port security performance, the need to strengthen security urgently in the post 9–11 era has led to the establishment of a regulatory framework lacking an integrated strategy. The integration of risk assessment and cost benefit analysis has been highly commended by the IMO in its policy making process, evidenced by the approval of the formal safety assessment framework in 2003 (IMO, 2003). While the ISPS Code provides port security stakeholders with useful practical guide of implementing security measures, it does not prescribe a generally-accepted methodology to carry out the relevant cost benefit analysis, especially in a quantitative manner, which clearly indicates the existence of a significant research gap. Furthermore, little research has been conducted on port security using quantitative analysis (Yang et al., 2009) because of difficulties of adopting appropriate methodologies and due to the complexity of dealing with this subject.

In the meantime, tightening port security inevitably affects the flow through materials into seaports. In terms of cargo volume, more than 80% of world trade is realized through maritime transportation (Paulo et al., 2010). Seaports also have a large impact on the national and international economy. To obtain the minimum required level of compliance in terms of security, seaports have to implement technical as well as organizational measures that will bring additional costs (Bichou, 2004). This result has triggered particular attention to port related stakeholders.

In spite of this importance, scant research has investigated the issues as to how port security affects port cargo volume and port profits, while there are more research on the efficiency of ports (Cullinane et al., 2005, Chin and Low, 2010, Hung et al., 2010, Wu and Goh, 2010, and Odeck and Bråthen (2012)) and port competition (Wap and Lam, 2006, Yeo et al., 2008, Yeo and Song, 2006, Hoshino, 2010 and Ishii et al. (2013)) to investigate different port choice determinants such as infrastructure, cargo handling speed, congestion and logistics costs. Moreover, dynamics behavior, which creates non-liner relations and complex systems, exits between port security and port cargo volume, but not be well addressed. Considering the above concerns, it is strongly interesting to initiate structural analysis on the effects of security policies on seaport throughputs.

To fill the research gap in the literature, this paper aims to analyze the effects of port security levels on container volumes, for the very first time, using a well-established methodology of System Dynamics (SD). SD is widely adapted to solve problems that have characteristics of complexity and dynamic relations among system components. This methodology can also show how systems change when there are substantial changes in the structure and components, as well as indicate relations associated with a system or sub-systems (Hirsch et al., 2007).

This paper, using the analytical SD framework, can provide implications: (1) by representing evaluation factors, several sub-models, and their causal relations, (2) by undertaking what-if analysis in order to determine trade-offs between port security levels and container volume, (3) by investigating a real case of Korean seaports which have adopted a higher security level compared to those in neighboring countries. This study brings fresh insights to stakeholders in the port industry namely importers, exporters, and cargo carriers. More importantly, it provides port policy makers with a transparent decision support tool for the implementation of rational cost effective port security policies. This paper consists of five sections. Section 2 presents a literature review on the issues of port security and cargo volumes in seaports. Section 3 examines the development of a base model, including the methodology of the study to find a causal loop diagram and build a sub-system. Sections 4 Case study and model validation, 5 Scenarios development present the case study and scenario analyzes. Finally, conclusions and implications to academic and industrial stakeholders and beneficiaries are suggested in Section 6.

Section snippets

Literature review

The ISPS Code was adopted by the IMO Conference of Contracting Governments on December 12, 2002 (IMO, 2002). The IMO stated that the objective of the ISPS code is to strengthen the security of ships and port security in response to the perceived and implied threats to ships and port facilities in the wake of the 9/11 attacks to the United States. The C-TPAT program, which is primarily intended as a self-help voluntary mechanism to enhance security along an entire supply chain by collaboration

Characteristics of SD modeling

SD is a methodology used to analyze the effects of policy by modeling the structure of a system using a computer-based simulator, which was introduced by Forrester, 1961, Forrester, 1969, Forrester, 1973. SD is a broader concept that combines two factors: System and Dynamics. System generally indicates any object to observe, and an area in space, the amount of any substance, or can be separated from other things distinctly, while Dynamics means the changes in an object depending on time. This

Case study and model validation

To run the base model, the simulation period was set from 1970 to 2020, and the actual data of container volume in Korea was used from 1970 to 2010. The time-step for simulation is 1 year. The Korean container volume handled started with 19,000 TEUs in 1970, after that, Korea has been enjoying two-digit growth rates. The treated container throughputs finally exceeded 10 million TEUs in year 2002, scoring 18,949,000 TEUs in 2010, as shown in Fig. 6.

Regarding the definition of port security levels,

Scenarios development

The scenario for simulation is composed of two cases: the optimistic and pessimistic scenarios, which are formulated using the definition of IMO and ILO (2003) for port security levels. This is a parameter-based scenario method that looks for the impact of one parameter change to other variables. Using this process, the user of the model can understand problematic behavior that has occurred, or that will occur, due to changes of key variables. The container cargo volumes in Korean ports will be

Conclusions

To address maritime security issues, international societies have adopted port security-related regulations, such as the ISPS code, CSI, C-TPAT, 24-advanced Rule, and AEO. The implementation of the regulations provides the potential to impact negatively and/or positively on additional costs, delaying cargo transit times, and the efficiency of port service. However, there is a lack of clear empirical studies on this issue to provide a quantitative indicator for policy makers to make rational

Acknowledgements

The authors thank the anonymous reviewers of this paper for their time and effort they put in reviewing the paper to improve the quality of this paper. This work is supported by the University of Incheon (International Cooperative) Research Grant in 2011. The usual disclaimers apply.

References (51)

  • J. King

    The security of merchant shipping

    Marine Policy

    (2005)
  • S.F. King et al.

    Beyond critical success factors: a dynamic model of enterprise system innovation

    International Journal of Information Management

    (2006)
  • E. Larsen et al.

    The growth of service and the service of growth: using system dynamics to understand service quality and capital allocation

    Decision Support Systems

    (1997)
  • I.E. Manataki et al.

    A generic system dynamics based tool for airport terminal performance analysis

    Transportation Research Part C

    (2009)
  • J. Odeck et al.

    A meta-analysis of DEA and SFA studies of the technical efficiency of seaports: a comparison of fixed and random-effects regression models

    Transportation Research Part A

    (2012)
  • J.A. Roach

    Initiatives to enhance maritime security at sea

    Marine Policy

    (2004)
  • E. Suryani et al.

    Air passenger demand forecasting and passenger terminal capacity expansion: a system dynamics framework

    Expert Systems with Applications

    (2010)
  • Y.C.J. Wu et al.

    Container port efficiency in emerging and more advanced markets

    Transportation Research Part E

    (2010)
  • Y.C. Yang

    Risk management of Taiwan’s maritime supply chain security

    Safety Science

    (2011)
  • G.T. Yeo et al.

    Evaluating the competitiveness of container ports in Korea and China

    Transportation Research Part A

    (2008)
  • N. Bakshi et al.

    Securing the containerized supply chain: analysis of government incentives for private investment

    Management Science

    (2010)
  • Barlas, Y., 1994. Model validation in system dynamics. In: International System Dynamics Conference, pp....
  • K. Bichou

    The ISPS code and the cost of port compliance: an initial logistics and supply chain frame work for port security assessment and management

    Maritime Economics and Logistics

    (2004)
  • K. Bichou

    Assessing the impact of procedural security on container port efficiency

    Maritime Economics and Logistics

    (2011)
  • Conrad, S., Beyeler, W., Thomas, R., Corbet, T., Brown, T., Hirsch, G., Hatzi, C., 2003. How do we increase port...
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