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The attributes of services can be categorised as service quality and service preference. While studies have addressed the importance of service quality, shippers’ service preference and its relationship to perceived value and purchase intentions remain unexplored. Therefore, the purpose of this study is to propose a causal model in the context of short sea shipping services to investigate the influence of purchase intention through the shipper’s service preference and perceived value.

Structural equation modelling is applied to assess the empirical strength of the relationships in the proposed model. The model is validated through empirical testing by taking samples from shippers in Taiwan.

The results show that service attributes, namely, timing related, pricing related, warehousing, sales, door-to-door, information and advertising, positively affect shippers’ service preference. Service preference significantly affects customer perceived value as well as purchase intentions. Moreover, perceived value strongly affects purchase intentions.

Matching between the product offered and the diversified customer need is key to the business operation’s success. This study suggests that carriers should position themselves to both self-competence and market values.

Short-sea shipping (SSS) plays an important role in regional transportation networks by supporting regional trade and improving inter-modality. In particular, countries in north-east Asia, such as China, South Korea and Japan have been served well by local SSS services. While SSS markets in Northeast Asia (NEA) have been developed by bilateral routes with sub-markets, the market structure of each sub-markets varies depending on concentration and competition levels as well as government intervention. The purpose of this paper is to analyse the market structure of SSS markets in the Northeast Asia.

Herfindahl–Hirschman Index (HHI) and concentration ratio are adopted to measure the market concentration from 2013 to 2017 for SSS markets in NEA. Additionally, the balance between supply and demand is investigated by measuring the capacity utilisation factor (CUF) based on slot capacity.

The market structure in the NEA SSS markets is influenced by firms’ behaviour under different levels of governmental intervention. Shipping firms in a market with more governmental intervention in market entry tend to focus on balancing supply and demand rather than increasing market share, whereas firms in a market with less intervention (and more competition) tend to increase their market share by pursuing efficient capacity management.

The period of data set is limited to 2013–2017. Furthermore, prices or revenue for specific routes are not available.

This paper sheds light on the market structure and behaviour of players in SSS market. In addition, the work has value to measure capacity utilisation based on slot capacity.

The shipper selects a suitable shipping route and plans for a voyage in order to import and export cargo on the basis of published sailing schedules. The reliability of the sailing schedule will influence the shipper’s logistics expense, which means that the logistics costs will depend on the reliability of schedules published by container shipping companies. Therefore, it is important to consider factors which can cause delays would for container ships sailing on sea routes. The reliability of published sailing schedules can be affected by a number of different factors. This study adopts the multi-criteria decision making (MCDM) method to estimate the importance of the delaying factors in a sailing schedule. In addition, the consistent fuzzy preference relations (CFPR) method is applied to identify the subjective importance (weights) of the delaying factors. The entropy weight method combined with the actual performance of the container shipping company are both used when estimating the objective importance (weights) of the delaying factors. According to the analysis results, the criteria can be divided into four quadrants with different management implications, which indicate that instructions for chase strategy, sailing schedule control, fleet allocation, transship operation arrangement and planning for ports in routes are often ignored by container shipping companies. Container shipping companies should consider adjusting their operational strategies, which would greatly improve their operational performance.

This present study uses political, economic, social, technological, legal and environmental (PESTLE) analysis and the strategic management theory to examine how external factors, namely the coronavirus (COVID-19) pandemic, the industrial revolution (IR) 4.0 technologies, the fuel price crisis and Sultanate of Oman Logistics Strategy (SOLS) 2040, affect the performance of container terminals in Oman.

A hybrid decision-making method that combined the analytical hierarchy process technique and Bayesian network model was used to achieve the objective of the present study.

The COVID-19 pandemic (54.60%) most significantly affected the performance of container terminals in Oman, followed by IR 4.0 technologies (19.66%), SOLS (17.00%) and fuel price crisis (8.74%). Container terminals in Oman were also found to perform “moderately,” considering the uncertainty of external factors.

This study enriches existing literature by using PESTLE analysis to assess the impact of the external business environment on firm performance in the context of the maritime industry as well as highlights how challenging external environmental factors affect the performance of container terminals in Oman.

This study contributes to developing novel study models and determining the performance level of container terminals in Oman considering integrated uncertainties and external factors such as the COVID-19 pandemic, IR 4.0 technologies, the SOLS 2040 and the fuel price crisis.

Technology acceptance is a measure of that technology’s usefulness. Oil palm is one of the biggest contributors to Indonesia’s revenues, thus fueling its economy. Using remote sensing would allow a plantation to monitor and forecast its production and the amount of fertilizer used. This review aims to provide a policy recommendation in the form of a strategy to improve the added value of Indonesia’s oil palm and support the government in increasing oil palm production. This recommendation needs to be formulated by determining the users’ acceptance of remote sensing technology (state-owned plantations, private plantation companies and smallholder plantations).

This review’s methodology used sentiment analysis through text mining (bag of words model). The study’s primary data were from focus group discussions (FGDs), questionnaires, observations on participants, audio-visual documentation and focused discussions based on group category. The results of interviews and FGDs were transcribed into text and analyzed to 1) find words that can represent the content of the document; 2) classify and determine the frequency (word cloud); and finally 3) analyze the sentiment.

The result showed that private plantation companies and state-owned plantations had extremely high positive sentiments toward using remote sensing in their oil palm plantations, whereas smallholders had a 60% resistance. However, there is still a possibility for this technology’s adoption by smallholders, provided it is free and easily applied.

Basically, technology is applied to make work easier. However, not everyone is tech-savvy, especially the older generations. One dimension of technology acceptance is user/customer retention. New technology would not be immediately accepted, but there would be user perceptions about its uses and ease. At first, people might be reluctant to accept a new technology due to the perception that it is useless and difficult. Technology acceptance is the gauge of how useful technology is in making work easier compared to conventional ways.

Therefore, technology acceptance needs to be improved among smallholders by intensively socializing the policies, and through dissemination and dedication by academics and the government.

The social implications of using technology are reducing the workforce, but the company will be more profitable and efficient.

Remote sensing is one of the topics that people have not taken up in a large way, especially sentiment analysis. Acceptance of technology that utilizes remote sensing for plantations is very useful and efficient. In the end, company profits can be allocated more toward empowering the community and the environment.