Ali Cheaitou, Sadeque Hamdan and Rim Larbi
This paper aims to examine containership routing and speed optimization for maritime liner services. It focuses on a realistic case in which the transport demand, and consequently…
Abstract
Purpose
This paper aims to examine containership routing and speed optimization for maritime liner services. It focuses on a realistic case in which the transport demand, and consequently the collected revenue from the visited ports depend on the sailing speed.
Design/methodology/approach
The authors present an integer non-linear programming model for the containership routing and fleet sizing problem, in which the sailing speed of every leg, the ports to be included in the service and their sequence are optimized based on the net line's profit. The authors present a heuristic approach that is based on speed discretization and a genetic algorithm to solve the problem for large size instances. They present an application on a line provided by COSCO in 2017 between Asia and Europe.
Findings
The numerical results show that the proposed heuristic approach provides good quality solutions after a reasonable computation time. In addition, the demand sensitivity has a great impact on the selected route and therefore the profit function. Moreover, the more the demand is sensitive to the sailing speed, the higher the sailing speed value.
Research limitations/implications
The vessel carrying capacity is not considered in an explicit way.
Originality/value
This paper focuses on an important aspect in liner shipping, i.e. demand sensitivity to sailing speed. It brings a novel approach that is important in a context in which sailing speed strategies and market volatility are to be considered together in network design. This perspective has not been addressed previously.
Details
Keywords
Digital-only fashion represents an ideal fusion of sustainability and fashionability, garnering growing interest among fashion professionals. However, there is a noticeable gap in…
Abstract
Purpose
Digital-only fashion represents an ideal fusion of sustainability and fashionability, garnering growing interest among fashion professionals. However, there is a noticeable gap in research focusing on digital-only fashion acceptance among consumers. Hence, this study aims to empirically examine consumers’ motivations, evaluations and acceptance of digital-only fashion based on the Functional Theory of Attitudes.
Design/methodology/approach
A US-based research agency was hired to collect data, resulting in 247 completed survey responses. Data analysis was conducted using the Partial Least Squares Structural Equation Modeling (PLS-SEM) approach.
Findings
Testing results highlight that consumer acceptance of digital-only fashion is directly influenced by both overall attitude and self-expressive attitude. Self-expression is particularly pivotal in digital-only fashion acceptance. Adorning avatars and dressing realistic on-screen bodies are distinct yet complementary aspects of using digital-only fashion. Consumers with positive environmental beliefs about digital-only fashion are concerned about how well digital-only fashion items allow them to express such beliefs.
Originality/value
This study innovatively applied the functional theory of attitudes to the emerging domain of digital-only fashion and identified consumers’ four functional attitudes toward digital-only fashion, along with the underlying motivations served by each functional attitude. Furthermore, this study provides valuable practical insights across the digital-only fashion value chain.
Details
Keywords
This paper aims to establish a theoretical framework that can comprehensively explain the executive compensation in state-owned enterprises (SOEs) within the context of socialism…
Abstract
Purpose
This paper aims to establish a theoretical framework that can comprehensively explain the executive compensation in state-owned enterprises (SOEs) within the context of socialism with Chinese characteristics.
Design/methodology/approach
The author develops a theoretical framework for executive compensation in SOEs from the perspective of Marxist economics and points out that the executives in SOEs are engaged in management labor, and their compensation should adhere to the principle of distribution according to labor contribution.
Findings
Based on this theory, the author posits that the continuous upward trend of executive compensation in SOEs, is consistent with the trend of SOEs' ongoing expansion, which reflects a continuous improvement of SOE executives' management labor in both quality and quantity.
Originality/value
It is necessary to start with Marxist economic theory and scientifically study the issue of SOE executive compensation, adhere to the principle of distribution according to work in the context of a socialist market economy and implement the specific guideline of the Party Central Committee; only in this way can the long-term healthy development of SOEs be promoted continuously.
Details
Keywords
Bianca Caiazzo, Teresa Murino, Alberto Petrillo, Gianluca Piccirillo and Stefania Santini
This work aims at proposing a novel Internet of Things (IoT)-based and cloud-assisted monitoring architecture for smart manufacturing systems able to evaluate their overall status…
Abstract
Purpose
This work aims at proposing a novel Internet of Things (IoT)-based and cloud-assisted monitoring architecture for smart manufacturing systems able to evaluate their overall status and detect eventual anomalies occurring into the production. A novel artificial intelligence (AI) based technique, able to identify the specific anomalous event and the related risk classification for possible intervention, is hence proposed.
Design/methodology/approach
The proposed solution is a five-layer scalable and modular platform in Industry 5.0 perspective, where the crucial layer is the Cloud Cyber one. This embeds a novel anomaly detection solution, designed by leveraging control charts, autoencoders (AE) long short-term memory (LSTM) and Fuzzy Inference System (FIS). The proper combination of these methods allows, not only detecting the products defects, but also recognizing their causalities.
Findings
The proposed architecture, experimentally validated on a manufacturing system involved into the production of a solar thermal high-vacuum flat panel, provides to human operators information about anomalous events, where they occur, and crucial information about their risk levels.
Practical implications
Thanks to the abnormal risk panel; human operators and business managers are able, not only of remotely visualizing the real-time status of each production parameter, but also to properly face with the eventual anomalous events, only when necessary. This is especially relevant in an emergency situation, such as the COVID-19 pandemic.
Originality/value
The monitoring platform is one of the first attempts in leading modern manufacturing systems toward the Industry 5.0 concept. Indeed, it combines human strengths, IoT technology on machines, cloud-based solutions with AI and zero detect manufacturing strategies in a unified framework so to detect causalities in complex dynamic systems by enabling the possibility of products’ waste avoidance.
Details
Keywords
Shiyuan Yang, Debiao Meng, Yipeng Guo, Peng Nie and Abilio M.P. de Jesus
In order to solve the problems faced by First Order Reliability Method (FORM) and First Order Saddlepoint Approximation (FOSA) in structural reliability optimization, this paper…
Abstract
Purpose
In order to solve the problems faced by First Order Reliability Method (FORM) and First Order Saddlepoint Approximation (FOSA) in structural reliability optimization, this paper aims to propose a new Reliability-based Design Optimization (RBDO) strategy for offshore engineering structures based on Original Probabilistic Model (OPM) decoupling strategy. The application of this innovative technique to other maritime structures has the potential to substantially improve their design process by optimizing cost and enhancing structural reliability.
Design/methodology/approach
In the strategy proposed by this paper, sequential optimization and reliability assessment method and surrogate model are used to improve the efficiency for solving RBDO. The strategy is applied to the analysis of two marine engineering structure cases of ship cargo hold structure and frame ring of underwater skirt pile gripper. The effectiveness of the method is proved by comparing the original design and the optimized results.
Findings
In this paper, the proposed new RBDO strategy is used to optimize the design of the ship cargo hold structure and the frame ring of the underwater skirt pile gripper. According to the results obtained, compared with the original design, the structure of optimization design has better reliability and stability, and reduces the risk of failure. This optimization can also better balance the relationship between performance and cost. Therefore, it is recommended for related RBDO problems in the field of marine engineering.
Originality/value
In view of the limitations of FORM and FOSA that may produce multiple MPPs for a single performance function, the new RBDO strategy proposed in this study provides valuable insights and robust methods for the optimization design of offshore engineering structures. It emphasizes the importance of combining advanced MPP search technology and integrating SORA and surrogate models to achieve more economical and reliable design.
Details
Keywords
Loris Nanni, Stefano Ghidoni and Sheryl Brahnam
This work presents a system based on an ensemble of Convolutional Neural Networks (CNNs) and descriptors for bioimage classification that has been validated on different datasets…
Abstract
This work presents a system based on an ensemble of Convolutional Neural Networks (CNNs) and descriptors for bioimage classification that has been validated on different datasets of color images. The proposed system represents a very simple yet effective way of boosting the performance of trained CNNs by composing multiple CNNs into an ensemble and combining scores by sum rule. Several types of ensembles are considered, with different CNN topologies along with different learning parameter sets. The proposed system not only exhibits strong discriminative power but also generalizes well over multiple datasets thanks to the combination of multiple descriptors based on different feature types, both learned and handcrafted. Separate classifiers are trained for each descriptor, and the entire set of classifiers is combined by sum rule. Results show that the proposed system obtains state-of-the-art performance across four different bioimage and medical datasets. The MATLAB code of the descriptors will be available at https://github.com/LorisNanni.
The study aims to build upon the Resource-based view of the firm (RBV) and Dynamic Capability Theory (DCT) to perform a meta-analysis on the eco-innovation/SMEs’ sustainable…
Abstract
Purpose
The study aims to build upon the Resource-based view of the firm (RBV) and Dynamic Capability Theory (DCT) to perform a meta-analysis on the eco-innovation/SMEs’ sustainable performance relationship.
Design/methodology/approach
Employing a psychometric meta-analytic approach with a random-effects model, the study examines a sample of 134,841 SMEs covering 99 studies and 233 study effects. Subgroup and meta-regression analysis were used to test the study`s hypotheses in Comprehensive Meta-Analysis (CMA) statistical software.
Findings
Results unveil that the average impact of eco-innovation on SMEs` sustainable performance is positively significant but moderate. Moreover, it was found that eco-process, eco-product, eco-organizational, and eco-marketing innovations positively influence SMEs’ sustainable performance, but the impact of eco-organizational innovation is the strongest. Findings further reveal that eco-innovation positively influences economic, social, and environmental performance, but its effect on social performance is the largest. Moreover, our findings reveal that contextual factors, including industry type, culture, industry intensity, global sustainable competitive index, and human development index, moderate the eco-innovation/SMEs’ sustainable performance relationship. Lastly, methodological factors, namely sampling technique, study type, and publication status, account for study-study variance.
Practical implications
Our findings imply that investing in eco-innovation is worthwhile for SMEs. Therefore, CEOs/managers of SMEs must adopt eco-innovation initiatives by establishing a sustainability vision, developing employee environmental development and training, building a stakeholder management system, and promoting employee engagement in sustainability activities.
Originality/value
The study develops a holistic conceptual framework to consolidate the distinct types of eco-innovation and their association with the sustainable performance of SMEs for the first time in this research stream, thereby resolving the anecdotal results and synthesizing the fragmented literature across culture, discipline, and contexts.
Details
Keywords
Qingdan Jia, Xiaoyu Xu, Minhong Zhou, Haodong Liu and Fangkai Chang
This study embraces the call for exploring the determinants of continuous intention in TikTok. Taking the perspective of social influence, this study not only tries to explore the…
Abstract
Purpose
This study embraces the call for exploring the determinants of continuous intention in TikTok. Taking the perspective of social influence, this study not only tries to explore the contextual sources of two types of social influence but also aims to unveil the influence mechanism of how social influence affects TikTok viewers’ continuous intention.
Design/methodology/approach
This study empirically analyzes how TikToker attractiveness, co-viewer participation, platform reputation and content appeal affect informative and normative social influence and then lead to the continuous intention of TikTok. Based on 547 valid survey data, this study adopts a mixed analytical approach for data analysis by integrating structural equation modeling (SEM) and fuzzy-set qualitative comparative analysis (fsQCA).
Findings
SEM results unveil that content appeal is the most critical antecedent of informational social influence, while the TikToker attractiveness and platform reputation have no effect on it. Differently, all four external sources positively lead to normative social influence. Among them, content appeal and co-viewer participation influence the most. The influences of both two types of social influence on continuous intention are demonstrated. FsQCA results reveal seven alternative configurations that are sufficient for influencing continuance intention and further complement and reinforce the SEM findings.
Originality/value
Addressing the critical contextual elements of TikTok, this study explores and confirms the sources which may engender social influence. The authors also demonstrate the critical role of social influence in affecting TikTok viewers’ continuous intentions by the hybrid analytical approach, which contributes to existing academic literature and practitioners.
Details
Keywords
Linu Babu, S. Vishnu Mohan, Mahesh Mohan and A.P. Pradeepkumar
This paper aims to examine the geochemical change experienced by laterites in Kerala, India, subjected to tropical monsoonal climate. These sediments are underlain by hard rock…
Abstract
Purpose
This paper aims to examine the geochemical change experienced by laterites in Kerala, India, subjected to tropical monsoonal climate. These sediments are underlain by hard rock. The source rock characteristics have a major stake on the ultimate composition of sediments, as also the climatic conditions which an area experience.
Design/methodology/approach
Core samples have been obtained from several locations in a lateritic plateau. The upper portions of the borehole cores are composed of the lateritic hard cap, followed by lateritic soils. The soil samples were subjected to sediment texture analysis and XRF analysis (Bruker S4 Pioneer Sequential Wavelength-Dispersive XRF) for the determination of major elements ((in oxide form).
Findings
Major element geochemistry has revealed the following order of relative proportions of elements (in oxide form) SiO2 > Al2O3 > Fe2O3 > TiO2 >> Na2O > P2O5 > CaO > K2O > MgO > MnO. Even though the concentrations of SiO2, Al2O3 and Fe2O3 contribute 90% of major element chemistry, there is no significant correlation found for these elements within themselves or with others.
Research limitations/implications
Microscale movement of elements could not be characterised in this study. This requires access to an electron probe micro analyzer.
Practical implications
The practical implication of tropical weathering is that enhanced chemical leaching leads to movement of most elements out of the system, except for Al, leading to the possible formation of bauxite, or aluminous laterite.
Social implications
The weathered products in this study provide livelihood sustenance for many of the local households, through manual production of laterite bricks, which are used in construction.
Originality/value
The indices of the intensity of chemical alteration/weathering like chemical index of alteration (CIA), chemical index of weathering (CIW) and weathering index of parker (WIP) reveal that the sediments indicate intense weathering of the source area prior to being deposited in the present location. This indicates enhanced monsoonal activity in the provenance areas, than that obtained today.
Details
Keywords
Emissions produced by oceangoing vessels not only negatively affect the environment but also may deteriorate health of living organisms. Several regulations were released by the…
Abstract
Purpose
Emissions produced by oceangoing vessels not only negatively affect the environment but also may deteriorate health of living organisms. Several regulations were released by the International Maritime Organization (IMO) to alleviate negative externalities from maritime transportation. Certain polluted areas were designated as “Emission Control Areas” (ECAs). However, IMO did not enforce any restrictions on the actual quantity of emissions that could be produced within ECAs. This paper aims to perform a comprehensive assessment of advantages and disadvantages from introducing restrictions on the emissions produced within ECAs. Two mixed-integer non-linear mathematical programs are presented to model the existing IMO regulations and an alternative policy, which along with the established IMO requirements also enforces restrictions on the quantity of emissions produced within ECAs. A set of linearization techniques are applied to linearize both models, which are further solved using the dynamic secant approximation procedure. Numerical experiments demonstrate that introduction of emission restrictions within ECAs can significantly reduce pollution levels but may incur increasing route service cost for the liner shipping company.
Design/methodology/approach
Two mixed-integer non-linear mathematical programs are presented to model the existing IMO regulations and an alternative policy, which along with the established IMO requirements also enforces restrictions on the quantity of emissions produced within ECAs. A set of linearization techniques are applied to linearize both models, which are further solved using the dynamic secant approximation procedure.
Findings
Numerical experiments were conducted for the French Asia Line 3 route, served by CMA CGM liner shipping company and passing through ECAs with sulfur oxide control. It was found that introduction of emission restrictions reduced the quantity of sulfur dioxide emissions produced by 40.4 per cent. In the meantime, emission restrictions required the liner shipping company to decrease the vessel sailing speed not only at voyage legs within ECAs but also at the adjacent voyage legs, which increased the total vessel turnaround time and in turn increased the total route service cost by 7.8 per cent.
Research limitations/implications
This study does not capture uncertainty in liner shipping operations.
Practical implications
The developed mathematical model can serve as an efficient practical tool for liner shipping companies in developing green vessel schedules, enhancing energy efficiency and improving environmental sustainability.
Originality/value
Researchers and practitioners seek for new mathematical models and environmental policies that may alleviate pollution from oceangoing vessels and improve energy efficiency. This study proposes two novel mathematical models for the green vessel scheduling problem in a liner shipping route with ECAs. The first model is based on the existing IMO regulations, whereas the second one along with the established IMO requirements enforces emission restrictions within ECAs. Extensive numerical experiments are performed to assess advantages and disadvantages from introducing emission restrictions within ECAs.