Green Operations Research Articles

Generating a path-search graph based on ship-trajectory data: Route search via dynamic programming for autonomous ships

Voyage optimization is critical for voyage planning and an important approach for realizing the autonomous and green operation modes for ships. In recent years, voyage optimization (also referred to as weather routing) has been extensively investigated and commercial solutions have also been launched. It is used to find the shortest path (optimum path) for voyage planning, which can help reduce the operating costs of the ship. However, accurately estimating fuel costs and validating routes within an acceptable computational time remain challenging. In this study, we devised methods to generate a path-search graph based on ship-trajectory data and determined an optimal route based on dynamic programming. The trajectory data of the vessels were extracted from their automatic identification systems, and the errors contained in the data were discarded via preprocessing. The trajectory data were subsequently simplified using the Douglas–Peucker method, following which a path-search graph was created using Delaunay triangulation and the number of vertices were reduced using the quadtree method. The search graph was validated using a high-resolution bathymetric chart, and dynamic programming was adopted to determine the optimal route for minimizing fuel costs. Changes in the operational performance caused by meteorological conditions were calculated, and the fuel costs were estimated using the wind resistance coefficient and SHOPERA-NTUA-NTU-MARIC method. The effect on power was determined by the effect of current on the vessel speed; this methodology was simulated and tested on oil tankers, container ships, and car and gas carriers. The fuel saved for each vessel compared to that used for the shortest path was estimated when sailing the transpacific and transatlantic routes; a maximum fuel reduction of approximately 7.8% was estimated. The proposed methods can be applied to various ship types and maritime zones to reduce the computation time of path-search graph generation while considering the high-resolution map and accurately estimating the fuel-oil consumption.

Factors Influencing Sustainable Logistics

The aim of this study is to investigate how the sustainable green logistics system is impacted by sustainable green logistics activities utilizing a theoretical framework. In the beginning of this research, the elements of green logistics are outlined, along with current changes to this concept. Following an examination of earlier work on green logistics, this idea is examined. The green logistics' independent variables are financial economics, company environmental & social performance, logistics networking & transport, and information sharing are applied to clarify the influence of sustainable green logistics, which are significant indicators for assessing a company's performance. This study used data from earlier studies and SPSS to authenticate the data. Ensuring the dependability, independence, and reliability of each of a variable utilized in research. Value of Cronbach’s alpha which should be above 0.7 then the construct is reliable. Few limitations in our study, including limited observations of 199 responses, so in our study the revalidation of variables has not been conducted Furthermore the green logistics concept is so wide that it is impossible to study the entire domain in a single study. A company would implement green logistics operations to maintain its place in the market if the management compared the study's findings to those of its rivals in the market. The principle of green logistics also helps organizations to create an intellectual framework that increases added value. The study's results strengthen the continuity of green logistics inside the company.

Green economic analysis for multi‐energy system with linearized CO2 electrolysis model

AbstractCO2 electrolysis system (CES), as a type of carbon capture, utilization, and storage, has significant potential for achieving carbon neutrality. By utilizing surplus renewable energy, CES can convert CO2 into valuable electrochemical products. This paper studies the advantages brought by the application of CES to the green economic operation of multi‐energy system. Firstly, a linear model based on the CES's operation data is developed to characterize its dynamic behaviour. In addition, a two‐stage stochastic programming model for the operation of CES within multi‐energy system is studied. Finally, a creative optimal‐operation‐based end‐of‐life net present value (OENPV) is proposed to assess the long‐term investment of CES. The results of the cases in different seasons and electrochemical products show that the application of CES not only brings significant carbon reduction to the multi‐energy system, but also alleviates the curtailment of renewable energy. Additionally, according to the OENPV analysis outcome, the production of formic acid gives the system the shortest return on investment, which is the fourth year of the 20‐year assessment cycle.

An Analysis of Green Operations Management by Integrated Fuzzy Six Sigma Model in the Textile Industry

An Analysis of Green Operations Management by Integrated Fuzzy Six Sigma Model in the Textile Industry

How do ESG activities affect corporate performance?

AbstractThis study investigates the impact of a company's environmental, social, and governance (ESG) activities on its financial performance. The COVID‐19 pandemic has caused unexpected difficulties in the operations of most companies, leading to a significant deterioration in their financial performance. We use empirical analysis to examine whether a company's ESG activities affect its financial performance. We employ the context‐dependent data envelopment analysis (DEA) model to evaluate the performance and provide a benchmark‐learning roadmap for 27 photoelectric companies in Taiwan. We also compare the marketability, innovation ability, and profitability of three sub‐industries: camera modules, optical component lenses, and optical components. Furthermore, we utilize a combination of classical DEA, stratification DEA, measurement of attractiveness, and progress for company evaluation. The results indicate that validating sustainability reports has a positive information effect, and high‐quality Global Reporting Initiative‐based external third‐party confirmed reports possess relatively high credibility, readability, and information value. The content and quality of these reports have an impact on performance. These findings offer insights into the role of ESG activities in the photoelectric industry and can help managers reflect upon and justify their choice to invest in specific ESG activities. Therefore, this research highlights the importance of green operations for firms.

Role of carbon emission linked financial leasing in shipping decarbonization

ABSTRACT Carbon emission-linked financial leasing (CFL) is a type of financial service that encourages commitment by borrowers to pursue decarbonization for greener operations. The main difference between CFL and traditional financial leasing (TFL) is that the financial lease hire is dynamically linked to the actual carbon emissions. This study investigates a green shipping operations system comprising a capital-constrained shipping firm providing green shipping services to shippers and a financial leasing firm providing the financial leasing business of green ships. By imposing a hard constraint on carbon emissions, we construct game theory models for CFL and TFL. The optimal equilibrium solutions in CFL and TFL are obtained, as well as comparisons of the profits and price of shipping services in different financial leasing models. Results corroborate that CFL is more effective for decarbonization. The participants need to sacrifice their profits, even if carbon reduction cost can be shifted to shippers through the price of shipping services. Tighter carbon emissions constraints can reinforce the effects of shipping decarbonization. Furthermore, we extend our study to cap-and-trade scheme for application. Most of the results derived in the models with a hard constraint on carbon emissions are applicable in the situation with cap-and-trade scheme

Atomically dispersed copper sites on titanium zirconium oxide accelerate the simultaneous oxidative removal of organic carbon and ammonia from landfill leachate

Landfill leachate is a refractory wastewater. Low-temperature catalytic air oxidation (LTCAO) has shown considerable potential for leachate treatment owing to its green and simple operation, but the simultaneous removal of chemical oxygen demand (COD) and ammonia from leachate remains challenging. Herein, TiZrO4 @CuSA hollow spheres with high-loading single-atom Cu were synthesized using isovolumic vacuum impregnation and co-calcination methods, and the catalyst was applied to the LTCAO treatment of real leachate. Consequently, the removal rate of UV254 reached 66% at 90 °C within 5 h, while that for COD was 88%. Simultaneously, the NH3/NH4+ (33.5 mg/L, 100 wt%) in the leachate was oxidized to N2 (88.2 wt%), NO2--N (11.0 wt%), and NO3--N (0.3 wt%) owing to the effect of free radicals. The single-atom Cu co-catalyst in TiZrO4 @CuSA exhibited a localized surface plasmon resonance effect at the active center, which could quickly transfer electrons to O2 in water to form O2.− with a high activation efficiency. The degradation products were determined and the deduced pathway was as follows: the bonds joining benzene rings were first broken, and then the ring structure was further opened to produce acetic acid and other simple organic macromolecules, which were finally mineralized to CO2 and H2O.

Assessing short- and long-term modifications of steady-state water infiltration rate in an extensive Mediterranean green roof

Green roof detention capacity is related to the steady-state infiltration rate, is, of the growing medium. With the aim to investigate short- and long-term modifications of the detention capacity of an extensive Mediterranean green roof, three mini-disk infiltrometer (MDI) measurement campaigns were conducted at construction, after one season and after five years of operation. A laboratory experiment was designed to separately measure is in the upper and the lower part of the substrate profile. During the first operating season, field is increased by a factor of 2.4 and 1.9 for near-saturated (applied pressure head, h0 = −30 mm) and quasi-saturated conditions (h0 = −5 mm), respectively. Similar rainfall height did not induce significant modifications in the upper layer of the laboratory columns, even if contribution of small pores to water infiltration tended to increase. Differently, is significantly decreased by a factor of 3.4–5.3 in the lower layer. After the simulated rainfall, the upper layer was less packed (mean bulk density, ρb = 1.083 kg m−3) and the lower layer was more packed (ρb = 1.218 kg m−3) as compared with the initial density (ρb = 1.131 kg m−3) and the lower part enriched in small particles. Short-term modifications in the experimental plot were thus attributed to fine particles washing-off and bulk density decrease in the upper layer, yielding an overall more conductive porous medium. After five years of green roof operation, field is did not further increase thus showing that the washing/clogging mechanism was complete after one season or it was masked by counteracting processes, like root development and hydrophobicity.

Research on the Influence of Green Degree on the Decision of Extended Warranty Service Supply Chain

The green supply chain not only relies on the manufacturer to provide green products, but also requires the supply chain members to provide green services. As a kind of green services, the extended warranty service can further expand the life cycle of products and reduce the frequency of products being eliminated due to damage. According to the existing literature research results, this paper finds that the influence of green degree on the enterprise's product green management strategy is gradually transferred to the product and service supply chain, and finally forms the green supply chain operation mode combining green production and green service. This paper analyzes the influence of product greenness and extended warranty service greenness on supply chain pricing strategy, and draws the following conclusions: Excessive green input will lead to the increase of extended warranty service price, resulting in the loss of consumers who buy extended warranty service. While reducing the green degree is good for enterprises to reduce costs, but low green will dampen the enthusiasm of consumers to buy products and the extended warranty service, and this will have a negative impact on the reputation of the company and the product. Therefore, this paper puts forward the suggestion that enterprises should consider the comprehensive effect of green degree and extended warranty service price, and set a reasonable green degree to improve the overall profit of supply chain.

Green Supply Chain Coordination Considering Carbon Emissions and Product Green Level Dependent Demand

As traditional supply chains face increasingly severe environmental issues, and as countries promote green development and sustainable development policy concepts, cultivating green supply chain operation models is gradually coming to be highly valued by governments and enterprises. Generally speaking, the production of green products incurs higher additional costs, and thus, their total production costs also increase. In this work, we studied the coordination mechanism, by considering carbon emissions and product green level dependent demand, in which the product green level is related to the random demand. Under the green supply chain buyback contract with the green product R&D cost sharing between the manufacturer and the retailer, both the product green level and the order quantity need to be decided, to maximize the channel profit. In order to coordinate the green supply chain, the manufacturer needs to share both the risk of good salvage and the green product R&D cost with the retailer. We found that both the wholesale price and the buyback price increase in the manufacturer’s proposition of the green product R&D cost, but decrease in the emission reduction efficiency coefficient or carbon trading price. In addition, the product green level, the optimal order quantity and the channel profit increase in the emission reduction efficiency coefficient, but decrease in the R&D cost coefficient of the product green level. Interestingly, we found that if the carbon trading price is low, the manufacturer will set a low product green level, and the product carbon emission trading is a cost for the supply chain. The increment of the carbon trading price leads to a higher cost, such that the channel profit is decreased. However, if the carbon trading price is high, the manufacturer will set a high product green level, and the product carbon emission trading is a revenue for the supply chain. The increment of the carbon trading price leads to a higher revenue, such that the channel profit is increased.

Efficient Photo-Oxidation Leaching of Ni and Co in a Spent Lithium-Ion Battery Cathode by Homogeneous UV/H2O2

Existing lithium-ion battery (LIB) leaching and recycling techniques have been widely applied in industrial production despite problems, such as difficult operation, high cost, and heavy pollution. Herein, we propose a novel photochemical oxidation method to leach Co and Ni ions in spent LIB cathodes, achieving leaching efficiencies of 99.73 and 97.54% when irradiated with hydrogen peroxide as the oxidant in acetonitrile and dichloromethane as the solvent under UV light for 4 h. The oxidation mechanism of the reaction was investigated by a series of tests. Three free radical oxidation pathways that functioned together with the reaction mechanism were proposed. This study is the first to combine the UV/H2O2 photo-oxidation reaction with spent LIB recycling to achieve a universal, green, and simple operation path for metal recycling field in the future.

Forging organizational resilience through green value co‐creation: The role of green technology, green operations, and green transaction capabilities

AbstractThe study assessed the mediating role of green organizational capabilities (green technology development, green operations, and green transactions), in the relationship between green value co‐creation and organizational resilience among Chinese manufacturing firms, that is, firms' ability to build strong organizational resilience in response to the COVID‐19 pandemic. It focused on manufacturing firms operating within Shenzhen, a coastal city located within the Guangdong province in southeastern China. The sample comprised 234 firms. Data were analysed using a covariance‐based structural equation modeling. Findings revealed that green value co‐creation had no direct effect on organizational resilience, rather, its effect was realized indirectly through green organizational capabilities. The study concludes that manufacturing companies can augment their organizational capabilities by leveraging the knowledge of their customers through green value co‐creation to build strong organizational resilience. Theoretical and managerial implications have been provided.

Green Economy: Community Pottery Development Process from Kradong Volcanic Rock Powder for the Sustainable Development of Communities in Thailand

The aim of this research is to establish a pottery production process from volcanic rock powder in Ban Kruat District, Thailand under the concept of the green economy operation by using research tools such as structured interviews as well as Exploratory Factor Analysis (EFA) and Multiple Regression Analysis. Moreover, it was found that the mixing ratios of pumice powder at 50%, local soil at 20% and kaolin at 30% with a shrinkage rate of 14%, water absorption of 1.88%, and a hardness of 304.75 kg/cm², having been fired at a temperature of 1,190 °C is considered a suitable ratio. In the same way, when transferring the production process of new pottery to the community in Ban Kruat District for production and distribution with the evaluation of consumer satisfaction, it can be summarized that there are six factors that affect consumer satisfaction: 1) Local Identity, 2) Uniqueness of the Materials, 3) Identity from Khmer Art Influence, 4) Factors in Lifestyle and Local Beliefs, 5) Functional Factors that Correspond to the Era, and 6) Factors of Current Market Conditions. Thus, these six factors have a predictive value of 61.365 (KMO =.533), and the results are as follows: F = 88.808, P = 0.000, R = 0.858, R2 = 0.736, Adj R2 = 0.728, SEE = 0.320, Durbin-Watson = 1.919. Therefore, the regression equation is defined as y ̂=-2.528+.345(X_1 )+.277(X_2 )+.287(X_3 )+.354(X_4 )+.373(X_5 )+.392(X_6 ), and it was concluded that all six factors affect consumer satisfaction towards pottery made from new types of volcanic rock powder with statistical significance at .01.
 
 Received: 28 January 2023 / Accepted: 14 April 2023 / Published: 5 May 2023

The fundamental solution to \Box_{𝑏} on quadric manifolds with nonzero eigenvalues

This paper is part of a continuing examination into the geometric and analytic properties of the Kohn Laplacian and its inverse on general quadric submanifolds of C n × C m \mathbb {C}^n\times \mathbb {C}^m . The goal of this article is explore the complex Green operator in the case that the eigenvalues of the directional Levi forms are nonvanishing. We (1) investigate the geometric conditions on M M which the eigenvalue condition forces, (2) establish optimal pointwise upper bounds on complex Green operator and its derivatives, (3) explore the L p L^p and L p L^p -Sobolev mapping properties of the associated kernels, and (4) provide examples.

Aliquots of MIL-140 and Graphene in Smart PNIPAM Mixed Hydrogels: A Nanoenvironment for a More Eco-Friendly Treatment of NaCl and Humic Acid Mixtures by Membrane Distillation.

The problem of water scarcity is already serious and risks becoming dramatic in terms of human health as well as environmental safety. Recovery of freshwater by means of eco-friendly technologies is an urgent matter. Membrane distillation (MD) is an accredited green operation for water purification, but a viable and sustainable solution to the problem needs to be concerned with every step of the process, including managed amounts of materials, membrane fabrication procedures, and cleaning practices. Once it is established that MD technology is sustainable, a good strategy would also be concerned with the choice of managing low amounts of functional materials for membrane manufacturing. These materials are to be rearranged in interfaces so as to generate nanoenvironments wherein local events, conceived to be crucial for the success and sustainability of the separation, can take place without endangering the ecosystem. In this work, discrete and random supramolecular complexes based on smart poly(N-isopropyl acrylamide) (PNIPAM) mixed hydrogels with aliquots of ZrO(O2C-C10H6-CO2) (MIL-140) and graphene have been produced on a polyvinylidene fluoride (PVDF) sublayer and have been proven to enhance the performance of PVDF membranes for MD operations. Two-dimensional materials have been adhered to the membrane surface through combined wet solvent (WS) and layer-by-layer (LbL) spray deposition without requiring further subnanometer-scale size adjustment. The creation of a dual responsive nanoenvironment has enabled the cooperative events needed for water purification. According to the MD's rules, a permanent hydrophobic state of the hydrogels together with a great ability of 2D materials to assist water vapor diffusion through the membranes has been targeted. The chance to switch the density of charge at the membrane-aqueous solution interface has further allowed for the choice of greener and more efficient self-cleaning procedures with a full recovery of the permeation properties of the engineered membranes. The experimental evidence of this work confirms the suitability of the proposed approach to obtain distinct effects on a future production of reusable water from hypersaline streams under somewhat soft working conditions and in full respect to environmental sustainability.

Green Operation Practice and Organizational Performance in Selected Manufacturing Firms in Akwa Ibom State, Nigeria

The goal of this study was to determine how green operation affected organizational performance in a selected Nigerian manufacturing companies in Akwa Ibom State. The study used a descriptive survey approach, and 179 sample were drawn from a total of 295 populations. With the research goal in mind, two hypotheses were developed. A structured questionnaire that was given to the respondent utilizing random sampling procedures served as the primary tool for data collection. Regression analysis was used for the data analysis. The findings indicate that green manufacturing and design have a significant impact on organizational performance in specific Akwa Ibom State manufacturing enterprises. Based on the analysis's findings, it is concluded that green manufacturing and green design are relational variables that can affect organizational performance at Nigerian manufacturing companies. As a result, it is suggested that industrial companies in Akwa Ibom State, Nigeria, incorporate these green design concepts. Designers may develop strategies that reduce negative environmental effects, conserve resources, advance human health and wellbeing, and help build a more resilient and sustainable future. Additionally, green manufacturing lowered resource use, reduced waste, and increased operational efficiency, all of which resulted in cost savings.

Green and non-green outcomes of green human resource management (GHRM) in the tourism context

Globally, organizational espousal of green and sustainable operations has been critically facilitated by green human resource management (GHRM) initiatives, especially in the tourism and hospitality sector. This research is an effort to examine the nuances of employees' responses to GHRM and contribute to this field by examining how narcissism, an individual trait and boundary condition, influences GHRM's relationship with employees' green (voluntary and task-related practices) and non-green outcomes (task performance and job satisfaction). Our hypotheses, grounded in social identity and trait activation theories, were tested with data obtained through a time-lagged two-wave survey of 219 UK-based hotel employees via the Prolific Academic platform. Analysis revealed significant associations between GHRM and all employee outcomes. Narcissism was shown to have a significant moderating effect on GHRM's associations with both green and non-green (task performance) behaviors. Our results imply important understandings for the advancement of theoretical knowledge and practical implementation of GHRM.

RUSSIAN TOURIST ETHICS IN BALI: LAW ENFORCEMENT ASPECTS TOWARD SUSTAINABLE TOURISM

With millions of foreign tourists traveling the globe each year, tourism is regarded as the largest and most significant industry in the world. Mainstream operators with a large volume of inexpensive and affordable vacations dominate tour operations market. A specialty operator sector coexists with the mainstream market and offers niche products to remain competitive. This study aims to determine whether specialized tour operators of Russian market in Bali view green and sustainable tourism as a niche market potential. Green and sustainable tourism has gained popularity over the past ten years. It will delve into the idea of green and sustainable tourism, look at how the Russian tourist market specialist view consumer demand for green and sustainable vacations’ products, and identify the crucial qualities for green and sustainable Bali tourism operators in terms of law enforcement as it is stipulated in Regional Law of No 2 of 2012 on Bali Cultural Tourism. Whether specialized tour operators of Russian market who promote green and sustainable tourism travel feel they may obtain a competitive advantage at a high cost will be determined.

Efficient online migration mechanism for memory write-intensive virtual machines

Online migration of virtual machines (VMs) is indispensable for system maintenance as it helps to achieve several resource management objectives such as load balancing, proactive fault tolerance, green operation, and resource management of data centers. The migration efficiency and reliability are two major challenges in the online migration of memory write-intensive VMs. For example, pre-copy migration transfers a large amount of data and takes a long time to migrate. This study proposes an efficient and reliable adaptive hybrid migration mechanism for memory write-intensive VMs. The mechanism optimizes the data transfer mode of the common migration method and improves the performance of conventional hybrid migration. First, the virtual machine (VM) memory data to be migrated are divided into dynamic and static data based on the bitmap marking method, and the migration efficiency is improved through parallel transmission based on different networks. Second, to accelerate the migration reliability, an iterative convergence factor is proposed to evaluate the current system load state and adaptively calculate the switching time of the migration mode for adaptive hybrid migration based on the convergence factor. Through adaptive hybrid migration can achieve migration completed successfully, shorten the post-copy migration duration, and minimize the impact on the performance of VMs. Finally, this paper implements the system prototype based on a kernel-based virtual machine (KVM), and experiments are performed using multiple memory write-intensive load VMs. The results show that the proposed migration algorithm can significantly improve migration performance and complete migration quickly to solve the pre-copy migration failure problem with a memory write-intensive load. Compared with the traditional hybrid migration with only one round of pre-copy, the proposed migration algorithm reduces the total migration time and transmits data by 23.2% and 26.7%, respectively.

Multi-UAV Path Learning for Age and Power Optimization in IoT With UAV Battery Recharge

In many emerging Internet of Things (IoT) applications, the freshness of the is an important design criterion. Age of Information (AoI) quantifies the freshness of the received information or status update. This work considers a setup of deployed IoT devices in an IoT network; multiple unmanned aerial vehicles (UAVs) serve as mobile relay nodes between the sensors and the base station. We formulate an optimization problem to jointly plan the UAVs' trajectory, while minimizing the AoI of the received messages and the devices' energy consumption. The solution accounts for the UAVs' battery lifetime and flight time to recharging depots to ensure the UAVs' green operation. The complex optimization problem is efficiently solved using a deep reinforcement learning algorithm. In particular, we propose a deep Q-network, which works as a function approximation to estimate the state-action value function. The proposed scheme is quick to converge and results in a lower ergodic age and ergodic energy consumption when compared with benchmark algorithms such as greedy algorithm (GA), nearest neighbour (NN), and random-walk (RW).