Modelling of Container Terminal Logistics Processes - Essay Example

AWARENESS OF BUSINESS SYSTEMS METHODOLOGIES Modelling of container terminal logistics processes Using a hard systems approach to identify the problem situation The hard systems approach (HSA) has been noted to be one of the most effective means used in addressing both qualitative and quantitative problems by the use of step-by-step procedure. Why using HSA, Chu and Huang (2005) observed that the procedure to addressing problems may be iterative, which require the problem to be revised based on any new information that arises at later stages of the whole process. Based on this understanding, there are very specific stages that are used in HSA which can be applied in analysing the problem situation discussed in the work of ElMesmary, Song and Dinwoodie (2014). The first stage as given by Dong, Xu and Song (2013) in analysing a problem situation is to clearly identify the problem or opportunity. In the context of ElMesmary, Song and Dinwoodie (2014), the problem identified can be said to be issues with the strategic/tactical and operational planning problems involved in the container terminal logistics processes in Alexandria. ElMesmary, Song and Dinwoodie (2014) observed that strategic/tactical planning problems arise at the first stage of the planning process for container terminals as planners seek to tackle terminal design problems as part of the overall technical feasibility and performance. Operational planning problems have also been noted to come about when logistics processes are being taken in the container terminals (ElMesmary, Song and Dinwoodie, 2014). The second stage of using HSA in analysing problem situation has been said to involve the description of the situation in its current state via the use of diagrams and open discussion. Based on Azevedo, Ferreira, Dias and Palma. (2009), the following diagram can be used to describe the identified problem with strategic/tactical and operational planning. Figure 1: Using HSA to explain the problem Based on the diagram given above, the main source of the problem can be said to come from the Alexandria container terminal, which is transmitted in the form of multimodal interfaces and IT systems. As the problem manifests, it becomes further amplified with bottlenecks in the container terminal logistics process which act as noise source. The diagram also shows that the problem identified is received by the strategic/tactical and operational planners and further dropped with the container terminal managers as destination (Kim, 2005). The third stage with the use of the HSA has been said to involve the process of describing the situation as it would ideally be. In this regard, it can be said that the strategic/tactical and operational planning was expected to ideally be a modality by which the planners will be made aware of the best design forms and systems that help in proactively engaging in container activities at the Alexandria container terminals. With such proposed strategic/tactical and operational planning yielding system design, it would have been expected that the container terminal’s performance would be measured as an improved one that makes use of limited individual resources within the whole system (ElMesmary, Song and Dinwoodie, 2014). Usefulness of hard systems modelling in the problem context With the problem context clearly identified with the use of the HSA, it is also possible to use hard systems modelling (HSM) in the problem context to finding practical approaching to handling the problem. ElMesmary, Song and Dinwoodie (2014) used their own modelling perspective based on modelling logistics process at container terminals, which was pipe flow modelling. The modelling logistics process at container terminals was based on three major paradigms which are terminal internal operations planning, landside operational planning and integrated operations planning. It is important to note however that each of these paradigms can be incorporated into a HSM which changes the issue from a problem context into a solution context. To achieve this usefulness of HSM, there are specific stages that would be used. The first stage in utilising the usefulness of HSM has been said to be the identification of metrics that can be used in determining that the goals of the whole system has been achieved (Meisel, 2009). In the current context, it is possible to use both quantitative and qualitative metrics for measuring the achievement of the goals. To use a combined metric made up of qualitative and quantitative assessment, the planners could use the ideal of operational-level simulation. This operational-level simulation serves as an evaluation tool that seeks for the entire logistics process (Song, Dinwoodie and Roe, 2007). ElMesmary, Song and Dinwoodie (2014) however noted that in using the operational-level simulation, there are two major perspectives of service quality measure which are import and export flows and how these were taken as part of the whole logistics process. The next stage in utilising the HSM involves an evaluation of how all identified determinants will behave in practice. By this, it is possible to engage the input and ideas of experts who have previously been engaged in strategic/tactical and operational planning to critique the viability of the operational-level simulation working in practice (Murty, Liu, Wan and Linn, 2005). Doing this form of critique of determinants would then yield a brainstorm outcome that clearly identifies from a professional perspective, the types of determinants which were listed that should really be pursued as part of the use or planning for the whole system being dealt with at the Alexandria container terminals (Yang and Shen, 2013). From a very practical perspective, the last stage of HSM would require the need to effectively follow the settled determinants and further monitor and evaluate their outcomes. For example, among the several determinants that were mentioned, the HSM could for example idealise the use of reliability, credibility and security. With the list reduced to only three, it can be expected that the planners and their managers can easily pursue them as part of interventions to easing the problems, difficulties and challenges with the whole process. Measures of supply chain collaboration in container logistics Conceptual model of how supply chain managers can enhance collaboration in container logistics The work of Seo, Dinwoodie and Roe (2014) proposed various measures that can be used as a reliable instrument for knowing accurately and objectively the multiple dimensions of supply chain collaboration (SCC). The work of Seo, Dinwoodie and Roe (2014) was used to propose a measure to identify the effectiveness of the collaboration between container ports and maritime logistics organisations. Based on their measures proposed, the adaptive supply chain management (A-SCM) conceptual framework can be used to better understand ways in which supply chain managers can enhance their collaboration with container logistics (Hair, Black, Babin & Anderson, 2010). The A-SCM is considered as the first step in the automation of the adaptive supply chain (SC) networks with the use of new technologies such as agent-based and web services (Nam and Song, 2011). From this deduction alone, it is possible to infer the applicability of the S-SCM in making the collaboration between chain managers and container logistics possible. In the first place, with the application of A-SCM, a paradigm which is based on the preliminary initiative of SC networks require that SC be processes do not be undertaken as a singular display of events but connected and coordinated set of events which form a holistic project that can be managed with the use of professional and academic methodologies. In effect, SC managers see their roles as better and effectively executed when they have as many networks as possible. Carbone and De Martino (2003) however advised that to create the said network, it is always necessary that work and activities that are directly related to what the SC managers be selected. Meanwhile, container logistics can be noted to be one such functional activity that is directly linked to the activities of SC, making it very necessary and valid that the network be built to link SC managers and container logistics. In principle therefore, the adaptive SC network component of the identified conceptual framework sets the tone for the idea of collaboration to be validated. Secondly, the A-SCM conceptual framework functions on the basis or principle of automated SC networks. By extension, it is not sufficient to have a SC network but in order to make A-SCM fully applied the network must be an automated one. By automated SC network, Islam, Dinwoodie and Roe, M. (2005) explained that it is a type of network whose operations and functionalities are automatically connected to a system that ensures that service delivery takes place in a mechanised, controlled and designed manner. Meanwhile, the benefits of having an automated SC engagement of any type, instead of the use of a manual system have been extensively studied in literature. For example, Bichou and Gray (2004) stated that the automated system makes efficiency and effectiveness a must rather than an option. Relating this to the collaboration between SC managers and container logistics and how the collaboration can be enhanced, it can be said that the A-SCM enforces effectiveness and efficiency. The reason it is said that effectiveness and efficiency are made a must is that through the automated system, the processes of work involved in both SC and container logistics are always running, which means that the collaboration must also be effective so that it can run with the system. Collin and Lorenzin (2006) used the figure below to depict the functional operation of the A-SCM in order to attain its benefits. Figure 2: Framework of A-SCM From the figure, it would be seen that the A-SCM functions from an integrated approach where there is no need to set off different value chain strategies with each other. By so doing, it is possible to encapsulate the merits of SCM, agility, and sustainability in achieving those specific objectives on the right side of the diagram, all of which come together to yield profitability (Collin & Lorenzin, 2006). Adapting and evaluating the A-SCM with an alternative supply chain context In order to adapt and evaluate the A-SCM conceptual model given above, the agent based decision support (ABDS) in the supply chain context may be used. With root in the agent theory, the ABDS has been explained to be a SC context which follows that an agent be identified who functions and plays roles that serve and promote the interest of a principal during the decision making process (Paixão and Marlow, 2003). In effect, the ABDS basically require that agents take beneficial decisions for and on behave of the principals. In the current context based on the work of Seo, Dinwoodie and Roe (2014), using the ABDS can be said to be an effective SC context for adapting and evaluating the A-SCM for a number of reasons. In the first place, the adaptability comes and is made easier as in both the A-SCM and ABDS functionaries of the SC process do not work alone but in collaboration with others. That is, in the present circumstance, there is expected to be an adapted collaboration between SC managers and container logistics on the part of the A-SCM conceptual model, while collaboration between agent and principals exist for the ABDS. Having said the point above, it will also be appreciated that when the A-SCM conceptual model is adapted, it can easily be evaluated with the use of the ABDS. The major characteristic of the ABDS that makes it possible to be the basis of evaluating the A-SCM is the fact that the principals on whose behave the agents act become third party and external judges who evaluate the performance and inputs of the agents. In a typical organisational setting such as a container terminal, the principals could be shareholders of the company whiles the agents are the managers. Based on the ABDS, the managers will not be working for themselves or serving their interests but that of the shareholders. In effect, evaluation of the agents becomes continuous and periodic. In the same vein, evaluation of the extent of collaboration and the effectiveness of it in achieving desired results can easily be ascertained. Towards a sustainability management system for smaller ports The “Green bullseye” template to assess sustainability issues in smaller ports as an aide memoire The issue of sustainability in professional logistics is one that has been noted to be very critical for the perpetual growth of logistics as a profession (Ginemez, Sierra & Rodon, 2012). Meanwhile, ports can easily be identified as one organisational location where different roles, activities and functions that has to do with logistics take place. It can therefore be said to be a step in the right direction that the works of Kuznetsov (2014) and Kuznetsov et al. (2015) all look at the subject of sustainability management systems in smaller ports. First, the use of such sustainability management systems hase been noted to be ideal in fostering and championing the quest for sustainability in ports (Visbeck et al., 2014). Secondly, the emphasis placed on smaller ports is highly appropriate because these are the types of ports commonly identified to be faced with operational challenges which threaten their continued survival in business and thus face sustainability difficulties (Dinwoodie et al., 2012). With these points well known, Kuznetsov (2014) and Kuznetsov et al. (2015) devised the bull’s eye target which is based on the Port Sustainability Management System (PSMS) to be a model for assisting smaller ports to achieve sustainability. The concept of green bull’s eye target has actually been seen to be a template that smaller ports can replace with their own realistic operational outcomes as part of their sustainability agenda. The current discussion has to do with the functional practicality of the green bull’s eye target template in assessing whether it is not only an aide memoire to assist harbour masters in attempting to develop cognitive map of managing sustainability issues in their ports. Certainly, by accepting this ascertain, it would mean that the green bull’s eye target template is not seen as having the realistic potential of yielding or bringing about sustainability but only serves as a cognitive guide. In the light of this, the claim is refused as the green bull’s eye target template is actually seen as having what it takes to achieve practical sustainability management in the ports. In the first place, it would be noted that the green bull’s eye target template builds on the PSMS, which actually helps harbour masters to identify pillars on which the survival of the ports hang on (Kuznetsov, 2014). Certainly, this first step to the identification of pillars alone can be said to be a practical step in the right direction, which is not only focused on cognitive map creation. This is because even though the pillars are based on theoretical framework, some of these theoretical frameworks including safety management, stakeholder engagement, environmental knowledge and awareness, customer service and satisfaction, change management, environmental management, proactive partnership, and the rest can all be independently verified in evidence based research about how feasible they are in making ports functional. Meanwhile, when functionality is excluded in the management of a port, sustainability remains only a mirage (Roome, 2006). Secondly, the green bull’s eye target template can be said not to only help harbour managers identify the pillars with basis in PSMS but also encourages them to measure the pillars (Kuznetsov, 2014). Indeed the act or practice of measuring the pillars is certainly something that goes beyond ordinary cognitive mapping which serving as an aide memoire. This is because the act of measuring the pillars, whether it is taken from a qualitative perspective or a quantitative one involves series of tasks and actions which trigger the evaluation of the pillars. For example for each of the eleven pillars, the measurement that is undertaken can help harbour managers to assign real scores based on how well the harbour is performing in each of the identified areas. Once the scores are known, and given the theoretical understanding that the pillars support the roof and floors of sustainability, they can easily tell aspects of sustainability where they may be lacking in or threatened with. Certainly, once the realisation is created for areas of positive performance, the harbour manager may associate those areas as the strength or opportunities of the harbour when designing any SWOT analysis. At the same time, areas within the pillars that score low marks can be seen as the weaknesses and threat of the harbour when preparing a SWOT analysis. All said and done, Kuznetsov et al. (2014) made a strong claim that the green bull’s eye target template offers modalities for the improvement of the pillars found with the PSMS and this claim can be justified made on the above discussions. For example with the measurement done for the pillars based on the green bull’s eye target template, the next step to take will be to put structures in place to better weaknesses and overcome threats based on the scores produced. While this is being done, it will be the pillars that will be indirectly be prepared for improvement. Meanwhile, pillars have already been argued to have practical potential of leading to sustainability as they form the engine of operations and growth (Tullbeg, 2012). In effect, by improving the pillars, the harbour manager will be improving the chances of sustainability for the harbour. References Azevedo, S., Ferreira, J. Dias, J. & Palma, S. (2009). “Performance Evaluation of the Main Terminal Containers in the Iberian Seaports: A Benchmarking Approach.” Paper presented at POMS 20th annual conference, Orlando, FL, May 1–4. Bichou, K. & Gray, R. (2004). “A logistics and supply chain management approach to port performance measurement” Maritime Policy & Management, Vol. 31 No. 1, pp. 47–67. Carbone, V. & De Martino, M. (2003). “The changing role of ports in supply-chain management: An empirical analysis” Maritime Policy & Management, Vol. 30 No. 4, pp. 305–320. Chu, C. Y. & Huang W. C. (2005). “Determining Container Terminal Capacity on the Basis of an Adopted Yard Handling System.” Transport Review: A Transnational Transdisciplinary Journal, Vol. 25 No. 2, pp. 181–199. Collin J. & Lorenzin D (2006) Plan for supply chain agility at Nokia. Int J Phys Distrib Logist Manag 36(6):418–430 Dinwoodie, J.,Tuck S., Knowles H, Benhin J. & SansomM. (2012). “Sustainable development of maritime operations in ports” Bus Strategy Environ, Vol. 21 No. 2, pp. 11–26. Dong, J. X., Xu, J.& Song, D. P. (2013). “Assessment of Empty Container Repositioning Policies in Maritime Transport.” International Journal of Logistics Management, Vol. 24 No. 1, pp. 49–72. ElMesmary HM, Song D., Dinwoodie, J., (2014), Pipe flow modelling of container terminal logistics processes: a case study in Alexandria. International Journal of Logistics: Research and Applications. DOI:10.1080/13675567.2014.986443 Ginemez, C., Sierra V. & Rodon J. (2012). “Sustainable operations: their impact on the triple bottom line” Int J Prod Econ, 140, pp. 149–59. Hair, J.F., Black, W.C., Babin, B.J. & Anderson, R.E. (2010). Multivariate Data Analysis. New York: Prentice Hall. Islam, D.M.Z., Dinwoodie, J. & Roe, M. (2005). “Towards supply chain integration through multimodal transport in developing economies: The case of Bangladesh” Maritime Economics & Logistics, Vol. 7 No. 4, pp. 382–399. Kim, K. (2005). “Models and Methods for Operations in Port Container Terminals.” Logistics Systems: Design and Optimization, Vol. 43 No. 2, pp. 213–243. Kuznetsov, A, Dinwoodie J, Gibbs,D., Sansom, M. Knowles, H. (2015) Towards a sustainability management system for smaller ports. Marine Policy (forthcoming). Kuznetsov, A. (2014) A port sustainability management system for smaller ports in Cornwall and Devon, PhD thesis. Meisel, F. (2009). Seaside Operations Planning in Container Terminals. Heidelberg: Springer Dodrecht Heidelberg. Murty, K., Liu J., Wan Y. & Linn R. (2005). “A Decision Support System for Operations in a Container Terminal.” Decision Support Systems, Vol. 39 No. 3, pp. 309–332. Nam, H.S. & Song, D.W. (2011). “Defining maritime logistics hub and its implication for container port” Maritime Policy & Management, Vol. 38 No. 3, pp. 269 292. Paixão, A.C. & Marlow, P.B. (2003). “Fourth generation ports – A question of agility?” International Journal of Physical Distribution & Logistics Management, Vol. 33 No. 4, pp. 355–376. Roome N. (2006). “Current issues in the greening of industry” Bus Strategy Environ, Vol. 15 No. 137, p. 138. Seo Y.J., Dinwoodie J., & Roe, M., (2014). Measures of supply chain collaboration in container logistics. Maritime Economics and Logistics. Song, D. P., Dinwoodie J. & Roe M. (2007). “Integrated Vehicle Fleet-sizing, Leasing and Dispatching Policy in a Shuttle Service System.” International Journal of Logistics Research and Applications, Vol. 10 No. 1, pp. 29–40. Tullbeg, J. (2012). “Triple bottom line – a vaultingambition?” Bus Ethics, Vol. 21 No. 3, 310–24. Visbeck, M., Kronfeld-Goharani U., Neumann B., Rickels W., Schmidt J., Van Doorn E., Matz-LückN, Ott K. & Quaas M. (2014). “Securing blue wealth: the need for a special sustainable development goal for the ocean and coasts” Mar Policy, 48, pp. 184–91. Yang, Y. C. & Shen K. Y. (2013). “Comparison of the Operating Performance of Automated and Traditional Container Terminals.” International Journal of Logistics Research and Applications: A Leading Journal of Supply Chain Management, Vol. 16 No. 2, pp. 158–173. Read More