Sustainability practices in port operations are critical issue to achieve port sustainability involving economic, social and environmental issues. To assist ports to successfully implant sustainability practices into their operations, this paper conceptualized the structure of sustainability practices in international port operations, by clustering the relevant issues, empirically. Using 203 samples collected from port stakeholders in the major ports in Northeast Asia, multi-measurement items were analyzed on exploratory factor analysis in SPSS 21. Results generated a structure that consists of five sub-dimensions conceptualizing sustainability practices in the context of port operations. As operative practices to accommodate current and future demands in a port, the five-factor model clustering the relevant issues incorporate environmental technologies, process and quality improvement, monitoring and upgrading, communication and cooperation, and active participation. Providing useful insights for strategic agenda to assist ports to incorporate sustainability practices in their operations, the five-factor model offer both a descriptive and diagnostic management tool for future improvement in port operations.

The Fintech business, which was initially focused on the payment sector, is becoming a global issue due to the entry of nonfinancial firms into the banking business. With the advent of the “mobile age in your hand”, global ICT companies are actively entering the banking business through alliances and competitions with existing financial companies. Classifying the alliance companies of Apple Pay and Samsung Pay into the downstream alliance and the upstream alliance, this study analyzed the signaling effect of service opening and its impact on the firm value. To analyze the effect of a specific event on firm value, this study adopted the event study. Additionally, ordinary least squares regression analysis was carried out to examine the influence of up- and downstream alliance on the firm value. The result shows that Apple Pay’s service launch in the USA. has a positive impact on stock prices of up- and downstream alliance companies, providing new experience and satisfaction to users through active alliance with credit card companies. On the other hand, downstream alliance companies that showed a negative response to the launch of Korean services turned to a positive response to USA service launch because to the difference in the specificity of credit card penetration rate and the portion of premium smartphones. Analyzing the impact of the expansion of the service area toward the payment platform on the firm value, research results provide important implications for establishing technology management strategies to ensure the sustainability in rapidly changing technical advances by comparing the different market response of Apple Pay and Samsung Pay.

Considering the lifecycle of products, firms are releasing new products through diversified strategic partnerships via the global supply chain. As the uncertainty about the future increases and strategic partnership grows more important, part suppliers are becoming more and more significant in assessing firm value. From the perspective of the signaling effect, this study analyzed the impact of partner volatility (new partner, old partner, revocation partner) on firm value in terms of global supply chain management. Regarding both Apple and Samsung which have bisected the premium smart phone market, research results reveal that companies eliminated from partnership selection are found to show negative signaling effect, and the newly selected companies have the stronger innovative capacity and higher signaling effect of higher excess earning rate than that of re-selected companies. The findings indicate that the partner volatility of partner companies work as a reliable investment signal for investors to recognize as an investment indication, contributing to firm value. In particular, it is meaningful to confirm that a new partner's differentiated R&D capacity is a key factor of new product launching and a significant variable capable of determining a firm's survival in the smart phone market.

Since the introduction of containerization in 1956, its growth has led to a corresponding growth in the role of container seaborne traffic in world trade. To respond to such growth, requirements for setting up the common standards in various kinds of container harbor equipment, and identifying performance indicators to assess container handling equipment performance have increased. Although the operating systems in ship-to-shore cranes may be different at each container terminal, the four main movements are the same: hoist, trolley, gantry, and boom. By determining in this work the hour metrics for each movement, it was possible to define the key performance indicators to be adopted and assess ship-to-shore crane performance. The research results identified that the mean time between failures is decreasing because of the accumulation of long-lasting heavyweight operations, while the number of maintenance of machine parts incidents and man-hours is steadily increasing. The key performance indicators offer a management tool to guide future ship-to-shore container crane inspection and the results provide useful insights for future container crane equipment operation improvements.

An accurate container throughput forecast is vital for any port. Since overall improvements in port performance and competitiveness can be derailed by port bottlenecks, ports need to find leverage to identify and prioritize measures to improve weak key performance indicators (KPIs) to attain growth opportunities. Prior studies had modeled container throughput from socio-economic and growth projection factors. This study aims to provide a practical method for forecasting the optimal container throughput a port can physically handle/attract given a certain level of terminal operation efficiency through random forest (RF) and multilayer perceptron (MLP) models. The study variables are derived from the port operations dimension and include ship turnaround time, vessel draft, container dwell time, berth productivity, container storage capacity, and custom declaration time. Evaluations are made based on the R-squared, NRMSE, MAE and MAPE. Model comparison is deduced with seven competing models in container throughput forecasting. The findings indicate that the RF model is a potential candidate for forecasting the engineering optimal throughput of Douala port. Model interpretation is provided through feature importance and partial dependence plots. The findings from this study will help reduce uncertainty and provide leverage for port management to spot bottlenecks and engage in better port planning and development projects which will strengthen their international competitive advantage.