Xiaojie Xu and Yun Zhang
Forecasts of commodity prices are vital issues to market participants and policy makers. Those of corn are of no exception, considering its strategic importance. In the present…
Abstract
Purpose
Forecasts of commodity prices are vital issues to market participants and policy makers. Those of corn are of no exception, considering its strategic importance. In the present study, the authors assess the forecast problem for the weekly wholesale price index of yellow corn in China during January 1, 2010–January 10, 2020 period.
Design/methodology/approach
The authors employ the nonlinear auto-regressive neural network as the forecast tool and evaluate forecast performance of different model settings over algorithms, delays, hidden neurons and data splitting ratios in arriving at the final model.
Findings
The final model is relatively simple and leads to accurate and stable results. Particularly, it generates relative root mean square errors of 1.05%, 1.08% and 1.03% for training, validation and testing, respectively.
Originality/value
Through the analysis, the study shows usefulness of the neural network technique for commodity price forecasts. The results might serve as technical forecasts on a standalone basis or be combined with other fundamental forecasts for perspectives of price trends and corresponding policy analysis.
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Cheng-Wei Lin, Wan-Chi Jackie Hsu and Hui-Ju Su
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…
Abstract
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.
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Tao Xu, Hanning Shi, Yongjiang Shi and Jianxin You
The purpose of this paper is to explore the concept of data assets and how companies can assetize their data. Using the literature review methodology, the paper first summarizes…
Abstract
Purpose
The purpose of this paper is to explore the concept of data assets and how companies can assetize their data. Using the literature review methodology, the paper first summarizes the conceptual controversies over data assets in the existing literature. Subsequently, the paper defines the concept of data assets. Finally, keywords from the existing research literature are presented visually and a foundational framework for achieving data assetization is proposed.
Design/methodology/approach
This paper uses a systematic literature review approach to discuss the conceptual evolution and strategic imperatives of data assets. To establish a robust research methodology, this paper takes into account two main aspects. First, it conducts a comprehensive review of the existing literature on digital technology and data assets, which enables the derivation of an evolutionary path of data assets and the development of a clear and concise definition of the concept. Second, the paper uses Citespace, a widely used software for literature review, to examine the research framework of enterprise data assetization.
Findings
The paper offers pivotal insights into the realm of data assets. It highlights the changing perceptions of data assets with digital progression and addresses debates on data asset categorization, value attributes and ownership. The study introduces a definitive concept of data assets as electronically recorded data resources with real or potential value under legal parameters. Moreover, it delineates strategic imperatives for harnessing data assets, presenting a practical framework that charts the stages of “resource readiness, capacity building, and data application”, guiding businesses in optimizing their data throughout its lifecycle.
Originality/value
This paper comprehensively explores the issue of data assets, clarifying controversial concepts and categorizations and bridging gaps in the existing literature. The paper introduces a clear conceptualization of data assets, bridging the gap between academia and practice. In addition, the study proposes a strategic framework for data assetization. This study not only helps to promote a unified understanding among academics and professionals but also helps businesses to understand the process of data assetization.
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Yang Li, Yaochen Qin, Liqun Ma and Ziwu Pan
The ecological environment of the Loess Plateau, China, is extremely fragile under the context of global warming. Over the past two decades, the vegetation of the Loess Plateau…
Abstract
Purpose
The ecological environment of the Loess Plateau, China, is extremely fragile under the context of global warming. Over the past two decades, the vegetation of the Loess Plateau has undergone great changes. This paper aims to clarify the response mechanisms of vegetation to climate change, to provide support for the restoration and environmental treatment of vegetation on the Loess Plateau.
Design/methodology/approach
The Savitsky–Golay (S-G) filtering algorithm was used to reconstruct time series of moderate resolution imaging spectroradiometer (MODIS) 13A2 data. Combined with trend analysis and partial correlation analysis, the influence of climate change on the phenology and enhanced vegetation index (EVI) during the growing season was described.
Findings
The S-G filtering algorithm is suitable for EVI reconstruction of the Loess Plateau. The date of start of growing season was found to gradually later along the Southeast–Northwest direction, whereas the date of the end of the growing season showed the opposite pattern and the length of the growing season gradually shortened. Vegetation EVI values decreased gradually from Southeast to Northwest. Vegetation changed significantly and showed clear differentiation according to different topographic factors. Vegetation correlated positively with precipitation from April to July and with temperature from August to November.
Originality/value
This study provides technical support for ecological environmental assessment, restoration of regional vegetation coverage and environmental governance of the Loess Plateau over the past two decades. It also provides theoretical support for the prediction model of vegetation phenology changes based on remote sensing data.
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This research proposes a framework to conceptualise the potential realm of data regarding shipping connectivity for application of data analytics which can be used to generate…
Abstract
Purpose
This research proposes a framework to conceptualise the potential realm of data regarding shipping connectivity for application of data analytics which can be used to generate deeper insights with respect to the state of such linkages and potential areas for practical application.
Design/methodology/approach
The study method involved comprehensive presentation of different perspectives of assessing shipping connectivity and levels of data contained within container shipping services and proposed potential application to analyse profitability, performance, competitiveness, risk and environmental impact.
Findings
Advances in capabilities to handle large volumes of data offer scope for an integrated approach which utilises all available data from various stakeholders in analyses of liner shipping connectivity. Research shows how different types of data contained in container shipping services are related and can be organised for application of data analytics.
Research limitations/implications
Research implications are offered to shipping lines, port managers and operators and policymakers.
Practical implications
This research presented a conceptual framework that captures the range of data involved in container shipping services and how data analytics can be practically applied in an integrated manner.
Originality/value
This paper is the first in literature to discuss in detail the different levels of data that reside within shipping services that constitute liner shipping connectivity for application of data analytics.
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Zhishuo Liu, Qianhui Shen, Jingmiao Ma and Ziqi Dong
This paper aims to extract the comment targets in Chinese online shopping platform.
Abstract
Purpose
This paper aims to extract the comment targets in Chinese online shopping platform.
Design/methodology/approach
The authors first collect the comment texts, word segmentation, part-of-speech (POS) tagging and extracted feature words twice. Then they cluster the evaluation sentence and find the association rules between the evaluation words and the evaluation object. At the same time, they establish the association rule table. Finally, the authors can mine the evaluation object of comment sentence according to the evaluation word and the association rule table. At last, they obtain comment data from Taobao and demonstrate that the method proposed in this paper is effective by experiment.
Findings
The extracting comment target method the authors proposed in this paper is effective.
Research limitations/implications
First, the study object of extracting implicit features is review clauses, and not considering the context information, which may affect the accuracy of the feature excavation to a certain degree. Second, when extracting feature words, the low-frequency feature words are not considered, but some low-frequency feature words also contain effective information.
Practical implications
Because of the mass online reviews data, reading every comment one by one is impossible. Therefore, it is important that research on handling product comments and present useful or interest comments for clients.
Originality/value
The extracting comment target method the authors proposed in this paper is effective.
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There are many different pollution reduction strategies even within different ports in the same country. Every port can learn from these environmental protection strategies. What…
Abstract
Purpose
There are many different pollution reduction strategies even within different ports in the same country. Every port can learn from these environmental protection strategies. What remains universally key, though, is to select the optimum strategy to reduce pollution. This paper aims to use a fuzzy analytic hierarchy process (FAHP) to prioritize the relative weights of key criteria assessing the port environmental protection and select the best port in Taiwan.
Design/methodology/approach
Four criteria and eleven sub-criteria of the FAHP model are developed through expert interviews and relevant literature review. Three alternative ports considered are Kaohsiung, Keelung and Taichung. The expert questionnaire samples (23) include four groups: shipping operators, port operators, governmental officials and academics.
Findings
Results indicate that finance is the most important evaluation criteria, followed by port environmental policy, technology and stakeholders. Among the three ports compared, Kaohsiung Port is selected as the best port, followed by Keelung and Taichung port.
Originality/value
The result of this paper can help fill the gap in the existing literature regarding decision analysis techniques for port pollution regulation and expect to present a holistic picture of the important evaluation criteria related to port environmental protection as well as raise issues of public awareness concern and consequently improve green port sustainability.
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Joshua Shackman, Quinton Dai, Baxter Schumacher-Dowell and Joshua Tobin
The purpose of this paper is to examine the long-term cointegrating relationship between ocean, rail, truck and air cargo freight rates, as well as the short-term dynamics between…
Abstract
Purpose
The purpose of this paper is to examine the long-term cointegrating relationship between ocean, rail, truck and air cargo freight rates, as well as the short-term dynamics between these four series. The authors also test the predictive ability of these freight rates on major economic indicators.
Design/methodology/approach
The authors employ a vector error-correction model using 16 years of monthly time series data on freight rate data in the ocean, truck, rail and air cargo sectors to examine the interrelationship between these series as well as their interrelationship with major economic indicators.
Findings
The authors find that truck freight rates and as well as dry bulk freight rates have the strongest predictive power over other transportation freight rates as well as for the four major economic indicators used in this study. The authors find that dry bulk freight rates lead other freight rates in the short-run but lag other freight rates in the long run.
Originality/value
While ocean freight rate time series have been examined in a large number of studies, little research has been done on the interrelationship between ocean freight rates and the freight rates of other modes of transportation. Through the use of data on five different freight rate series, the authors are able to assess which rates lead and which rates lag each other and thus assist future researchers and practitioners forecast freight rates. The authors are also one of the few studies to assess the predictive power of non-ocean freight rates on major economic indicators.
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Jihong Chen, Renjie Zhao, Wenjing Xiong, Zheng Wan, Lang Xu and Weipan Zhang
The paper aims to identify the contributors to freight rate fluctuations in the Suezmax tanker market; this study selected the refinery output, crude oil price, one-year charter…
Abstract
Purpose
The paper aims to identify the contributors to freight rate fluctuations in the Suezmax tanker market; this study selected the refinery output, crude oil price, one-year charter rate and fleet development as the main influencing factors for the market analysis.
Design/methodology/approach
The paper used the vector error correction model to evaluate the degree of impact of each influencing factor on Suezmax tanker freight rates, as well as the interplay between these factors.
Findings
The conclusion and results were tested using the 20-year data from 1999 to 2019, and the methodology and theory of this paper were proved to be effective. Results of this study provide effective reference for scholars to find the law of fluctuations in Suezmax tanker freight rates.
Originality/value
This paper provides a decision-making support tool for tanker operators to cope with fluctuation risks in the tanker shipping market.