Agent-based Truck Appointment System for Containers Pick-up Time Negotiation

Congestion in the seaports area is a common issue in many parts of the world. Fluctuating truck arrival has been identified as one of the significant determinants of congestion. In response, a truck appointment system (TAS) is introduced to manage truck arrival, particularly at peak times. In the existing TAS mechanism, the scheduling decision is centralized and disregards the concerns of trucking companies. Moreover, TAS may complicate the business operation of trucking companies that already have a constrained truck schedule. This study proposes a decentralized negotiation mechanism in TAS that allows trucking companies to adjust arrival times by utilizing the waiting time estimation provided by the terminal operator. We develop an agent-based model of a TAS in the container terminal pick-up procedure. The simulation results indicate that compared to the existing TAS mechanism, the negotiation TAS mechanism generates a shorter average truck turnaround time regardless of truck arrival rates. In terms of average net time cost, the negotiation TAS mechanism provides better value under high truck arrival rate conditions. The incentive for trucking companies to participate in the negotiations is even higher at peak times

Warehouse Specification Proposition for Urbanis (Urban Farming Company) Using Discrete Event Simulation Method

Two percent of the world's surface use for cities, yet it consumes 75 percent of its resources. Urban farming is an emerging alternative food network that could supply some of the food needs in cities with less emission, healthier food, and the environment. Urbanis is a company that likes to contribute to the acceleration of urban farming, especially in Indonesia, by utilizing vacant land and labor. In 2021, Urbanis plans to scale up the production capacity to 10 tonnes per month or 400 kg per day. It requires us to have a warehouse to store the food product that has not been absorbed by the market. The purpose of this study is to find warehouse specifications for Urbanis and the amount of labor and rack inside the warehouse alongside capital and operational expenditure. This research uses a layout with an area of 5x14 meters for experimental design. The model then translated into a discrete-event simulation model named Anylogic. The results show, for each amount of arrival, the number of labor that utilizes effectively are two labors with a maximum number of rack 50. Given these results, the author conducted operational and capital expenditure, which consist of variable analysis and additional variables such as a table, fan, and chair. The result is Urbanis need Rp 50.738.000 for capital expenditure while Rp 10.871.337 for operational expenditure

Integrated Multi-Income Stream Performance Dashboard: a Japanese Corporate Banking Case

In response to the complex operational challenges faced by Japanese Corporate Banking (JCB), arising from the coexistence of disparate core banking systems post-merger, this study aims to address inherent issues affecting marketing performance monitoring. The existing condition at JCB is characterized by data inconsistency, limited system interoperability, and fragmented income tracking through multiple Excel reports and management systems. Recognizing the gaps in the current setup, the research question revolves around how to enhance marketing performance monitoring effectively. The research objectives, therefore, encompass the development and implementation of a tailored integrated report utilizing the CRISP-DM methodology. This innovative performance dashboard harmoniously consolidates data from diverse sources, presenting a cohesive representation crucial for comprehensive marketing performance assessment. Leveraging advanced methodologies like data normalization and cross-platform integration, the research approach ensures streamlined income tracking, mitigating existing limitations. The data, drawn from various product applications, undergoes meticulous processing to facilitate a unified view on the integrated dashboard. The anticipated result is a significant improvement in monitoring efficiency, heightened data accuracy, and an empowered decision-making process within JCB's operations. The business implication of this initiative is the tangible enhancement of the bank's ability to comprehensively assess income performance, thereby elevating the quality of strategic decision-making and reinforcing JCB's competitive positioning in the banking sector

Agent-based inter-organizational systems in advanced logistics operations

“Agent-based Inter-organizational Systems (ABIOS) in Advanced Logistics Operations” explores the concepts, the design, and the role and impact of agent-based systems to improve coordination and performance of logistics operations. The dissertation consists of one conceptual study and three empirical studies. The empirical studies apply various research methods such as a multiple-case study research, coordination mechanism design, and predictive analytics using big data. The conceptual study presents a theoretical exploration and synthesis explaining the demand for inter-organizational systems (IOS) and the corresponding IOS functionalities. The first empirical study presents a multiple-case study exploring real

Managing Inherent IT Business Risk against Cyber Threats: a Decision Analysis Case Study of an Oil and Gas Company

XYZ, an anonymized oil and gas company, aims to enhance cyber resilience by strategically managing inherent risk profiles in cybersecurity, aligned with business needs and stakeholder expectations. This research addresses challenges including Information Security Control determination, proficiency improvement in risk management, and ISMS preparedness. Additionally, it tackles procurement strategy for Security Operations Control across XYZ Group, operating under PSC Gross Split, Cost Recovery, and Non-PSC statuses. Utilizing diverse frameworks such as problem tree analysis, stakeholders’ power-interest matrix, MITRE ATT&CK, NIST 800-53, COBIT 2019, ISO 27005:2022, KAMI 5.0, and SMART, data analysis includes risk documents, interviews, and cyber-attack data. The research establishes effective IS Control for risk mitigation, readiness for Information Security Management System ISMS implementation, strategic programs enhancing risk management capability, and refined Security Operations Control procurement. These outcomes, incorporated into a collaborative contract structure, significantly mitigate cyber threats and potential impacts, such as disruptions to operations, revenue reduction, increased costs, data theft, and non-compliance

A Comparative Case Study on Performance Management System in Architecture, Engineering, and Construction Start-up Enterprises in Indonesia

Abstract. Despite a growing sense that start-up enterprise is critical to economic growth, the topic of performance management affects strategic and organizational processes remains largely understudied. In Indonesia, as a sphere where the entrepreneurial ecosystem is on the rise, we explored the strategy of Architecture, Engineering, and Construction (AEC) start-up firms using a Balanced Scorecard (BSC). This research aims to determine how suitable the BSC is applied to AEC start-ups and how this tool is implemented as the enterprise evolves. We conduct in-depth case studies using multiple data sources, including interviews and field observation. By performing the comparative analysis, we identified managerial practices that enable the networking of BSC perspectives – learning and growth, internal process, customer, and financial – during the start-up lifecycle. From the contribution to the literature perspective, this study provides empirical evidence that the BSC is a valuable performance management tool for early-stage firms. However, the BSC must be reconfigured regularly to reflect the current development stage’s objectives throughout implementation. As the business implications, this research helps AEC entrepreneurs see the significance of achieving organizational balance to drive growth and transition from agile start-ups to sustainable companies. Future research may examine the interconnection between managerial control systems and leadership attributes in different business contexts.Keywords:  AEC firms, Balanced Scorecard, Performance Management System, Start-up Lifecycl

Relocating a Multiple-tenants Logistics Center: Lesson Learned from an Air Cargo Terminal Relocation Project

AbstractMoving a logistics center while assuring uninterrupted operation is a complex process. The task is even more complex as the relocation project intersects with the concerns the multiple stakeholders. Defining a proper plan to ensuring smooth transition execution is key. Stakeholders conditioning, infrastructure and facilities readiness, human resources, and the logistics operation transition plan are some of the concerns that have to be considered when defining the relocation action plan. Several relocation scenarios have to be developed and assessed before defining the final relocation plan. In this case study, we share our first-hand empirical experience in preparing an action plan for relocating an operating air cargo terminal of one of the biggest airports in the south-east Asia. The paper offers two main contributions. The first one is the air cargo center relocation framework which elaborated important sequences in translating the facility relocation objectives into the final relocation action plan definition. The second contribution, is the conceptual model of air cargo center relocation planning process which portrays the interdependencies and the contingencies among different aspects of the relocation components

Advancing Smart Sustainable Seaports:Auction-based Truck Appointment System for Automated Container Terminal

This study proposes alternative solutions to the container pick-up reservation problem involving container terminals and drayage operators by introducing two variations of a modified auction mechanism - cost-based and service-oriented - into the terminal's truck appointment system, with the First Come First Served (FCFS) scheme as a baseline. Each scheme is evaluated using key performance indicators relevant to terminals, drayage operators, and the environment, such as yard crane utilization, container retrieval/service time, storage cost/dwelling time, reservation costs, appointment tardiness, truck turnaround time, congestion, and CO2 emissions. Results indicate that retrieval-cost-based schemes achieve the lowest container retrieval costs, while storage-cost-based schemes maintain consistent container dwelling times; service-based schemes excel in minimizing appointment tardiness but require more reservation communication cycles. All proposed mechanisms significantly enhance environmental outcomes, improving truck turnaround time, queue length, and CO2 emissions by at least 85% compared to FCFS. This study highlights the critical need for decentralized coordination to effectively integrate the interests of business actors, emphasizing the importance of aligning stakeholder objectives for overall system enhancement.</p

Data Driven Building Electricity Consumption Model Using Support Vector Regression

Every building has certain electricity consumption patterns that depend on its usage. Building electricity budget planning requires a consumption forecast to determine the baseline electricity load and to support energy management decisions. In this study, an algorithm to model building electricity consumption was developed. The algorithm is based on the support vector regression (SVR) method. Data of electricity consumption from the past five years from a selected building object in ITB campus were used. The dataset unexpectedly exhibited a large number of anomalous points. Therefore, a tolerance limit of hourly average energy consumption was defined to obtain good quality training data. Various tolerance limits were investigated, that is 15% (Type 1), 30% (Type 2), and 0% (Type 0). The optimal model was selected based on the criteria of mean absolute percentage error (MAPE) &lt; 20% and root mean square error (RMSE) &lt; 10 kWh. Type 1 data was selected based on its performance compared to the other two. In a real implementation, the model yielded a MAPE value of 14.79% and an RMSE value of 7.48 kWh when predicting weekly electricity consumption. Therefore, the Type 1 data-based model could satisfactorily forecast building electricity consumption

Business Process Improvement of Fixed Wing UAV Assembly Process: Imperia Dirgantara Case

Abstract. Imperia Dirgantara is a company engaged in providing aerial survey solutions using their own university-based research Unmanned Aerial Vehicle (UAV) technology and data processing systems. To anticipate an increasing demand of the aerial survey, the UAV has to be prepared in a short preparation time. Currently, Imperia Dirgantara is facing an issue of lengthy assembly process of the UAV which may lead to lost sales opportunity. In response, this research focuses on providing proposition improvements for the UAV assembly business process, All of data source directly from Imperia Dirgantara internal archives. This business process improvement research is initiated with thorough analysis of bottleneck process in the existing UAV assembly process. Following the bottleneck process identification, we conduct root cause analyses and propose the corresponding business process improvement propositions. Finally we assess the impact of the solution propositions, define the required resources and provide a plan to implement the solution proposition. This research resulting time reduce in processing time as much 12.66% or equal to 10 days. The suggestion of keep improving the current business process instead picking up another option is stated in this research’s report.Keywords: Business Process Improvement; Business Process Model; Bottleneck Analysis; Unmanned Aerial Vehicle; UAV Assembly Process