Yuyu Sun, Yuchen Zhang and Zhiguo Zhao
Considering the impact of the Free Trade Zone (FTZ) policy on forecasting the port cargo throughput, this paper constructs a fractional grey multivariate forecasting model to…
Abstract
Purpose
Considering the impact of the Free Trade Zone (FTZ) policy on forecasting the port cargo throughput, this paper constructs a fractional grey multivariate forecasting model to improve the prediction accuracy of port cargo throughput and realize the coordinated development of FTZ policymaking and port construction.
Design/methodology/approach
Considering the effects of data randomization, this paper proposes a novel self-adaptive grey multivariate prediction model, namely FDCGM(1,N). First, fractional-order accumulative generation operation (AGO) is introduced, which integrates the policy impact effect. Second, the heuristic grey wolf optimization (GWO) algorithm is used to determine the optimal nonlinear parameters. Finally, the novel model is then applied to port scale simulation and forecasting in Tianjin and Fujian where FTZs are situated and compared with three other grey models and two machine learning models.
Findings
In the Tianjin and Fujian cases, the new model outperforms the other comparison models, with the least mean absolute percentage error (MAPE) values of 6.07% and 4.16% in the simulation phase, and 6.70% and 1.63% in the forecasting phase, respectively. The results of the comparative analysis find that after the constitution of the FTZs, Tianjin’s port cargo throughput has shown a slow growth trend, and Fujian’s port cargo throughput has exhibited rapid growth. Further, the port cargo throughput of Tianjin and Fujian will maintain a growing trend in the next four years.
Practical implications
The new multivariable grey model can effectively reduce the impact of data randomness on forecasting. Meanwhile, FTZ policy has regional heterogeneity in port development, and the government can take different measures to improve the development of ports.
Originality/value
Under the background of FTZ policy, the new multivariable model can be used to achieve accurate prediction, which is conducive to determining the direction of port development and planning the port layout.
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Hui Ma, Shenglan Chen, Xiaoling Liu and Pengcheng Wang
To enrich the research on the economic consequences of enterprise digital development from the perspective of capacity utilization.
Abstract
Purpose
To enrich the research on the economic consequences of enterprise digital development from the perspective of capacity utilization.
Design/methodology/approach
Using a sample of listed firms from 2010 to 2020, this paper exploits text analysis of annual reports to construct a proxy for enterprise digital development.
Findings
Results show that enterprise digital development not only improves their own capacity utilization but also generates a positive spillover effect on the capacity utilization of peer firms and firms in the supply chain. Next, based on the incomplete information about market demand and potential competitors when making capacity-building decisions, the mechanism tests show that improving the accuracy of market forecasts and reducing investment surges are potential channels behind the baseline results. Cross-sectional tests show the baseline result is more pronounced when industries are highly homogeneous and when firms have access to less information.
Originality/value
This paper contributes to the research related to the economic consequences of digital development. With the development of the digital economy, the real effects of enterprise digital development have also triggered extensive interest and exploration. Existing studies mainly examine the impact on physical operations, such as specialization division of labor, innovation activities, business performance or total factor productivity (Huang, Yu, & Zhang, 2019; Yuan, Xiao, Geng, & Sheng, 2021; Wang, Kuang, & Shao, 2017; Li, Liu, & Shao, 2021; Zhao, Wang, & Li, 2021). These studies measure the economic benefits from the perspective of the supply (output) side but neglect the importance of the supply system to adapt to the actual market demand. In contrast, this paper focuses on capacity utilization, aimed at estimating the net economic effect of digital development by considering the supply-demand fit scenario. Thus, our findings enrich the relevant studies on the potential consequences of digital development.
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Jindong Song, Jingbao Zhu and Shanyou Li
Using the strong motion data of K-net in Japan, the continuous magnitude prediction method based on support vector machine (SVM) was studied.
Abstract
Purpose
Using the strong motion data of K-net in Japan, the continuous magnitude prediction method based on support vector machine (SVM) was studied.
Design/methodology/approach
In the range of 0.5–10.0 s after the P-wave arrival, the prediction time window was established at an interval of 0.5 s. 12 P-wave characteristic parameters were selected as the model input parameters to construct the earthquake early warning (EEW) magnitude prediction model (SVM-HRM) for high-speed railway based on SVM.
Findings
The magnitude prediction results of the SVM-HRM model were compared with the traditional magnitude prediction model and the high-speed railway EEW current norm. Results show that at the 3.0 s time window, the magnitude prediction error of the SVM-HRM model is obviously smaller than that of the traditional τc method and Pd method. The overestimation of small earthquakes is obviously improved, and the construction of the model is not affected by epicenter distance, so it has generalization performance. For earthquake events with the magnitude range of 3–5, the single station realization rate of the SVM-HRM model reaches 95% at 0.5 s after the arrival of P-wave, which is better than the first alarm realization rate norm required by “The Test Method of EEW and Monitoring System for High-Speed Railway.” For earthquake events with magnitudes ranging from 3 to 5, 5 to 7 and 7 to 8, the single station realization rate of the SVM-HRM model is at 0.5 s, 1.5 s and 0.5 s after the P-wave arrival, respectively, which is better than the realization rate norm of multiple stations.
Originality/value
At the latest, 1.5 s after the P-wave arrival, the SVM-HRM model can issue the first earthquake alarm that meets the norm of magnitude prediction realization rate, which meets the accuracy and continuity requirements of high-speed railway EEW magnitude prediction.
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Łukasz Kryszak, Katarzyna Świerczyńska and Jakub Staniszewski
Total factor productivity (TFP) has become a prominent concept in agriculture economics and policy over the last three decades. The main aim of this paper is to obtain a detailed…
Abstract
Purpose
Total factor productivity (TFP) has become a prominent concept in agriculture economics and policy over the last three decades. The main aim of this paper is to obtain a detailed picture of the field via bibliometric analysis to identify research streams and future research agenda.
Design/methodology/approach
The data sample consists of 472 papers in several bibliometric exercises. Citation and collaboration structure analyses are employed to identify most important authors and journals and track the interconnections between main authors and institutions. Next, content analysis based on bibliographic coupling is conducted to identify main research streams in TFP.
Findings
Three research streams in agricultural TFP research were distinguished: TFP growth in developing countries in the context of policy reforms (1), TFP in the context of new challenges in agriculture (2) and finally, non-parametric TFP decomposition based on secondary data (3).
Originality/value
This research indicates agenda of future TFP research, in particular broadening the concept of TFP to the problems of policy, environment and technology in emerging countries. It provides description of the current state of the art in the agricultural TFP literature and can serve as a “guide” to the field.
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Junru Zhang, Yumeng Liu and Bo Yan
This study aims to research the large cross-section tunnel stability evaluation method corrected after considering the thickness-span ratio.
Abstract
Purpose
This study aims to research the large cross-section tunnel stability evaluation method corrected after considering the thickness-span ratio.
Design/methodology/approach
First, taking the Liuyuan Tunnel of Huanggang-Huangmei High-Speed Railway as an example and taking deflection of the third principal stress of the surrounding rock at a vault after tunnel excavation as the criterion, the critical buried depth of the large section tunnel was determined. Then, the strength reduction method was employed to calculate the tunnel safety factor under different rock classes and thickness-span ratios, and mathematical statistics was conducted to identify the relationships of the tunnel safety factor with the thickness-span ratio and the basic quality (BQ) index of the rock for different rock classes. Finally, the influences of thickness-span ratio, groundwater, initial stress of rock and structural attitude factors were considered to obtain the corrected BQ, based on which the stability of a large cross-section tunnel with a depth of more than 100 m during mechanized operation was analyzed. This evaluation method was then applied to Liuyuan Tunnel and Cimushan No. 2 Tunnel of Chongqing Urban Expressway for verification.
Findings
This study shows that under different rock classes, the tunnel safety factor is a strict power function of the thickness-span ratio, while a linear function of the BQ to some extent. It is more suitable to use the corrected BQ as a quantitative index to evaluate tunnel stability according to the actual conditions of the site.
Originality/value
The existing industry standards do not consider the influence of buried depth and span in the evaluation of tunnel stability. The stability evaluation method of large section tunnel considering the correction of overburden span ratio proposed in this paper achieves higher accuracy for the stability evaluation of surrounding rock in a full or large-section mechanized excavation of double line high-speed railway tunnels.
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Waqas Bin Khidmat, Man Wang and Sadia Awan
The purpose of this paper is to investigate the value relevance of Research and development (R&D) and free cash flow (FCF) in an efficient investment setup. Most importantly, this…
Abstract
Purpose
The purpose of this paper is to investigate the value relevance of Research and development (R&D) and free cash flow (FCF) in an efficient investment setup. Most importantly, this paper examines whether the value relevance of R&D and FCF is associated with life cycle stages. Furthermore, this paper reports whether the market response to R&D and FCF is different in competitive market as compared to the concentrated market.
Design/methodology/approach
The analysis is based on the Ohlson (1995) model for the determination of value relevance of earnings and book value. Capitalized R&D and FCF data comprising of the Chinese A-listed firms from the year 2008 to 2016 are selected for this study. Following Anthony and Ramesh (1992), the authors divided the firm life cycle into different stages. HHI index is used to measure the product market competition.
Findings
The main result shows that R&D and FCF are value relevant in Chinese A-listed firms. The impact of R&D and FCF on the value relevance of earnings and book value is also positive and significant. The findings of the effect of R&D and FCF on the value relevance of accounting information signify that the information content (R2=0.46) of the mature stage is higher than that of the growth and stagnant stage. The explanatory power measured by R2 value for competitive industries (0.47) is much higher than the concentrated industries (0.33).
Research limitations/implications
Despite taking into account all the possible available variables, there are few limitations of the study. This study only studies the effect of EPS, BPS, R&D and FCF on the value relevance of accounting information. Other determinant such as size, growth, leverage and firm age is ignored. Since the R&D expenditure is discretionary, therefore the findings cannot be generalized to all the sectors. A sector wise comparative study can be done in future, to understand the differences in the information contents of R&D and FCF. Also, the tax effect of R&D is ignored in this study. For future call, the value relevance of tax effect on R&D can be explored.
Practical implications
The investors can now determine the present value of all the future cash flows of investing activities. The results of the study are significant for the Chinese investors who should incorporate the R&D and FCF along with investment efficiency. The investors should keep in mind the life cycle stage while investing in a certain stock. The competitive markets have more information content than the concentrated markets. The corporate managers can benefit from this study while issuing new shares. The market responds positively to the stock having investment efficient R&D and FCF investment. For the policy implication perspective, the security market regulator should devise the effective pro-effective product market regulations.
Originality/value
The contribution of this study is manifold. First, according to the authors’ knowledge, this is the first study that incorporates investment efficiency with R&D and FCF and explores its effect on the value relevance of accounting information. Second, the impact of R&D on the value relevance is studied by numerous researchers (Lev and Sougiannis, 1996; Han and Manry, 2004). Similarly, FCF-agency cost effect has also been investigated by (Rahman and Mohd-Saleh, 2008; Chen et al., 2012) but the value relevance of R&D and FCF during different life cycle stages still needs to be answered. Finally, this study also tries to answers the question if the market response to R&D and FCF is different in a competitive market as compared to the concentrated market.
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Antonia D'Amico, Annalisa De Boni, Giovanni Ottomano Palmisano, Enrica Morea, Claudio Acciani and Rocco Roma
The agricultural sector is facing pressure due to concerns about its impact on the environment. Farmers must adapt to ensure high-quality, sustainable production. This requires…
Abstract
Purpose
The agricultural sector is facing pressure due to concerns about its impact on the environment. Farmers must adapt to ensure high-quality, sustainable production. This requires efficient techniques such as soilless farming. The development of agricultural innovations depends on social acceptance; thus, it is crucial to identify the factors that influence consumers' purchasing decisions. The aim of this paper is to analyse consumers' perceptions of hydroponic cultivation techniques and their willingness to pay (WTP) a premium price for hydroponic tomatoes certified as “nickel-free” and “zero-residue”.
Design/methodology/approach
The survey was conducted in Italy using tomatoes as a case study. Data were collected through an online questionnaire from a convenience sample of 292 respondents and were analysed using statistical analysis and a multiple linear regression model.
Findings
The results showed that WTP was influenced by frequency of purchase, familiarity with soilless technology, environmental sustainability, income and education. Consumers place a high value on the sustainability of the hydroponic production process and their perception of increased safety positively influences WTP. It is therefore recommended that marketing strategies focus on the environmental sustainability and safety of hydroponic products. In addition, it may be beneficial to implement a certification system specific to hydroponic cultivation, in addition to the existing “nickel-free” and “zero-residue” certifications.
Originality/value
This study introduces several novel elements: it is the first to assess the Italian consumers’ perceptions and WTP for a hydroponic product. Secondly, it assesses WTP in relation to several aspects of increasing relevance related to health claims, namely “nickel-free” and “zero-residue”.
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This study aims to demonstrate the importance of recognizing stress in the workplace. Accurate novel objective methods that use electroencephalogram (EEG) to measure brainwaves…
Abstract
Purpose
This study aims to demonstrate the importance of recognizing stress in the workplace. Accurate novel objective methods that use electroencephalogram (EEG) to measure brainwaves can promote employee well-being. However, using these devices can be positive and potentially harmful as manipulative practices undermine autonomy.
Design/methodology/approach
Emphasis is placed on business ethics as it relates to the ethics of action in terms of positive and negative responsibility, autonomous decision-making and self-determined work through a literature review. The concept of relational autonomy provides an orientation toward heteronomous employment relationships.
Findings
First, using digital devices to recognize stress and promote health can be a positive outcome, expanding the definition of digital well-being as opposed to dependency, non-use or reduction. Second, the transfer of socio-relational autonomy, according to Oshana, enables criteria for self-determined work in heteronomous employment relationships. Finally, the deployment and use of such EEG-based devices for stress detection can lead to coercion and manipulation, not only in interpersonal relationships, but also directly and more subtly through the technology itself, interfering with self-determined work.
Originality/value
Stress at work and EEG-based devices measuring stress have been discussed in numerous articles. This paper is one of the first to explore ethical considerations using these brain–computer interfaces from an employee perspective.
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Natthapong Chuchottaworn and Pairoj Raothanachonkun
This paper seeks to evaluate the factors that contribute to congestion at port entrances, propose a comprehensive approach to managing port gates that addresses the factors…
Abstract
Purpose
This paper seeks to evaluate the factors that contribute to congestion at port entrances, propose a comprehensive approach to managing port gates that addresses the factors causing traffic jams and assess the outcomes of resolving the issue through an optimal model for incoming container truck traffic.
Design/methodology/approach
The study employed a one-way ANOVA and a one-way MANOVA to examine the impact of congestion-causing factors on the waiting time of trucks in each lane at the entrance gate. The purpose of this was to comprehend the intricate issue and demonstrate the outcomes of the resolution. We used the identified factors that were causing congestion to develop a management strategy for the port gate. As part of this strategy, we implemented a policy where traffic flows in the opposite direction in certain lanes. The Simulation of Urban Mobility program introduced the microscopic traffic simulation model as a discrete event simulation.
Findings
The examination of variables influencing the congestion at the port entrance revealed that there were four factors contributing to the congestion: (1) the quantity of lanes; (2) the level of bookings; (3) the factors related to the traffic signal cycle and (4) the assignment of lane types. The one-way MANOVA analysis of the three factors yielded significant evidence for a single pair of interactions. (1) The factors to consider are the quantity of lanes, the level of booking and the assignment of lane types. If the entrance to the rear alley consists of two lanes with a width of 1.85 at the 50% capacity level, and if the critical value of the uneven queue coefficient is reached, it can result in a maximum reduction of the average waiting time by 15.02%.
Originality/value
This study is unique because it examines the surrounding environment and operational behavior of the port to identify how individual and group congestion factors interact. It uses various statistical tools to determine the allocation of the number of port entrances with a reversible lane policy and appointment level. Additionally, it analyzes the detailed results using microscopic traffic simulation modeling. The established foundational model can assist operators in simulating the queue length and mean waiting time of trucks for this specific waiting line in other ports with comparable entrance characteristics.
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Prosper Babon-Ayeng, Eric Oduro-Ofori, De-Graft Owusu-Manu, David James Edwards, Ernest Kissi and Augustine Senanu Komla Kukah
There is a pressing need to increase investments in sustainable infrastructure to promote low carbon economic growth and ensure environmental sustainability. Consequently, this…
Abstract
Purpose
There is a pressing need to increase investments in sustainable infrastructure to promote low carbon economic growth and ensure environmental sustainability. Consequently, this study examines the socio-political factors underlying the adoption of green bond financing of infrastructure projects.
Design/methodology/approach
Primary data was gathered from experts with advanced experience in, or knowledge of green bonds in the Kumasi Metropolis. To identify respondents with pertinent knowledge that is relevant to the study, purposive and snowball sampling techniques were used. One-sample t-test and relative importance index were used in this study's statistical analysis.
Findings
‘Training and experience with sustainable finance’ was seen as the most important social factor underlying the adoption of green bond financing of infrastructure projects by the respondents and ‘Governmental tax-based incentives’ was rated as the leading political factor.
Originality/value
This pioneering research attempts to ascertain the socio-political factors affecting the adoption of green bond financing of infrastructure projects. Emergent results of analysis and concomitant discussions add knowledge to fill a void in literature on the social and political factors affecting the adoption of green bond financing of infrastructure projects in developing countries.