Green Operations Research Articles

Numerical version of complex scaling Green operator method

Abstract A new treatment of scattering problems is formulated by improving the complex scaling Green operator (CSGO) method, which can calculate the transition or scattering matrix from the spectral representation of the complex-scaled Green function and the asymptotic solution expressed in terms of the analytic function. In the present formulation, the CSGO method is extended to handle the general scattering problem in the charged particle systems by employing the Coulomb wave function numerically calculated under the complex-scaled asymptotic Hamiltonian. We call the new method the CSGO-numerical (CSGON) method, and the CSGON method is applied to the scattering problem of the 4He + proton system to check its validity. The method of the continuum level density (CLD), which is another method to solve the scattering problem, is also applied to the same system. The numerical precision and the applicability of the CSGON method is discussed by comparing with the CLD and CSGO methods.

The effect of green hydrogen feed rate variations on e-methanol synthesis by dynamic simulation

Methanol is a promising fuel and important intermediate chemical in the transformation of renewable power to chemical products since it can be directly synthesized from captured CO2 and electrolytic H2. However, the intermittency of renewable power generation poses challenges to green methanol production process design and operation, necessitating high operational flexibility to facilitate coupling with intermittent renewable power.In this study, a green crude methanol (a mixture of methanol and water from methanol synthesis) production process was dynamically modeled. The results show that the minimum load of the model is 20%, with maximum allowable ramping rates of 3.25%/minute for ramp-down and 2.10%/minute for ramp-up between full and minimum load. The introduction of a standby mode, in which a make-up H2 stream is supplied when electrolytic H2 is unavailable, allows continuous operation of the process at the minimum load. With the constructed control structure, the model demonstrates that the process can effectively handle continuous variations of electrolytic H2 input.

Assessment of supply chain efficiency through a sustainable supply chain management strategy in the textile sector

The textile industry processes fiber into yarn or fabric. Problems often faced by textile companies are delays in raw materials, which result in the production and distribution of fabrics not reaching the target, so consumers are unsatisfied and switch to competing companies. In addition, solid waste from the production process is still disposed of, potentially polluting the environment. This study uses the Green Supply Chain Operation Reference (Green SCOR) approach to evaluate the performance of green supply chain management (GSCM) in textile companies located in Yogyakarta. The findings of this study could significantly impact the textile industry as they provide a comprehensive evaluation of GSCM performance. Twenty-two performance indicators have been validated using the Item-Content Validity Index (I-CVI) method and weighted using the Analytical Hierarchy Process (AHP) method. Based on the calculation results, the GSCM performance value is 60.208. Improvement recommendations are given for three indicators that need to be prioritized based on Importance Performance Analysis (IPA) matrix mapping and the actual condition of the company. Improvements can be made by using the Vacuum Flash Evaporation method so that recycled PVA can be reused, using natural materials or alternative auxiliary materials that are more environmentally friendly, increasing cooperation with companies engaged in processing weaving waste or textile waste appropriately and effectively, checking the concentration of starch solution not only when changing construction but every beam change, and forming a checklist form that is filled in for monitoring after machine settings and preparation of the production process.

Towards net-zero operating in neurosurgery

Background The climate crisis is one of the greatest threats to public health and surgery is a significant contributor to carbon emissions generated by the NHS. In this paper, we describe our experience of sustainable operating by using evidence-based methods to reduce our carbon footprint across three neurosurgical theatres during our ‘Green operating day’. Methods The Green operating day was run at a single site over a 12-hour operative day and included 10 neurosurgical cases. Following discussions with the theatre, anaesthetic and sustainability team, each operative case was reviewed and changes in the consumables, surgical instruments and utilities recorded. Carbon footprint was calculated using an environmentally extended input-output model for baseline and Green operating day. Qualitative data was collected on the participants of the Green operating day to assess attitudes and behaviours towards sustainability in neurosurgery. Results There was a total reduction of carbon emissions by 31%, equivalent to 1.04 tonnes CO2e. Reductions were seen across different aspects of surgery including anaesthetics, surgical instruments, waste and utilities. Discussion This study demonstrates the feasibility of carbon footprint reduction within neurosurgical theatres which was not associated with increases in operative duration or adverse patient outcomes. This study advocates for environmentally conscious decision making in neurosurgical procedures.

THE IMPACT OF GREEN FINANCE ON BANKING PERFORMANCE IN INDONESIA

Green Finance refers to financial practices that can be described through financial services and products that take environmental sustainability to support sustainable development. The role of green finance is to connect financial goals with the environment to encourage inclusive economic growth. One form of green finance implementation is in financial institutions, especially banking. This study aims to analyze the impact of green finance implementation in the banking sector on banking performance as proxied by the profitability ratio in the 2018-2022 period. The Generalized Method of Moments (GMM) dynamic panel is used. The Green Daily Operation (GDO) and Green Finance Policy (GFP) variables indicate the implementation of green finance in banking. Other independent variables use banking performance ratios consisting of the capital adequacy ratio, non-performing loans, and the bank's operational efficiency ratio. The study results show that green finance represented by implementing GFP can increase profitability, while GDO does not significantly affect banks' profitability in Indonesia. Furthermore, the internal banking ratio that is not significant to profitability is the capital adequacy ratio, while increasing non-performing loans and operational efficiency ratio significantly negatively impacts bank performance because it reduces profitability. This research supports applying the green concept in the banking sector to improve sustainable bank performance.

Green dynamic capability and green product innovation for sustainable development: Role of green operations, green transaction, and green technology development capabilities

Green dynamic capability and green product innovation for sustainable development: Role of green operations, green transaction, and green technology development capabilities

Green supply chain management in the Southern Brazilian rice industry: A survey and structural analysis

The purpose of this study is to evaluate the influence of Green Supply Chain Management (GSCM) dimensions on the performance of an agrifood supply chain, with a specific focus on the rice industry in southern Brazil. The region's rice industry produces a substantial amount of biomass, fostering circular economy practices that align with both economic and environmental objectives. Using Structural Equation Modeling with Partial Least Squares (SEM-PLS), this research analyzes data from a survey of 92 companies. The measurement model incorporates 21 input and 11 output indicators, organized into six constructs. The input constructs—green strategy, green innovation, and green operations—are instrumental in shaping industry competitiveness, the fourth construct. The output constructs measure results and reputation. The findings indicate that green innovation and green operations significantly enhance competitiveness, whereas green strategy exerts minimal influence. The scope is limited to the rice industry in southern Brazil. Practical implications include offering a strategic framework for agrifood industry practitioners to improve competitiveness by optimizing green practices within their supply chains. Theoretical implications suggest that while green strategy alone may not be sufficient to drive competitiveness, the integration of green innovation and operations can enhance it. The originality of this research lies in the development of a comprehensive measurement model for assessing competitiveness in agrifood businesses, which evaluates both operational outcomes and reputational impact.

A Winning Green Profile to Stay Ahead? Companies’ Green Value Chain Profiles Based on Competitive Advantage Attainment

The world is entering an era of net zero carbon emissions, and companies are under pressure from their stakeholders to be environmentally friendly or green. While companies must engage in greener operations, they also need to juggle their financial performance. Companies need guides on allocating their limited resources to embed green practices and achieve competitive advantage. Academic studies, thus far, have overlooked this. This study aims to fill the gap by studying companies’ green value chain profiles with different competitive advantage attainments. The 207 companies that responded to the survey are classified into four clusters based on their level of competitive advantage: no competitive advantage (cluster 1), only efficiency advantage (cluster 2), only value advantage (cluster 3), and both efficiency and value advantage (cluster 4). The results of variance analysis showed significant differences in eight out of nine value chain activities across the clusters, except green marketing and sales. Companies with competitive advantages demonstrate greater commitment to green activities, especially those from the value advantage-only and both competitive advantage groups. Between them, they embed green initiatives in different value chain activities. Interestingly, green marketing and sales is the only activity with no significant difference among the four clusters of companies, yet they committed the highest green initiatives to this activity. While this study reaffirms the positive impact of companies’ commitment to green initiatives on achieving competitive advantage, companies need to carefully strategize their level of commitment to green initiatives based on the competitive advantage they pursue.

Nexus between green credit efficiency and strategic, business and management digital transformation–based on 114 commercial banks in China

With the expansion of green finance and the digital economy, the discussion on the evolution of green credit business and the digitalization of commercial banks have grown in prominence. However, limited research has been done on how different degrees of digital transformation in commercial banks—the main issuers—affect the way of green credit efficiency. To fill this gap, based on data from 114 Chinese commercial banks between 2010 and 2021, this paper explores the impact of digitalization on the green credit efficiency through the integration of several methodologies. The paper indicates that enhancing the digitalization, business digitization, and management digitization of commercial banks can greatly enhance the effectiveness of green credit businesses, but the impact of strategic digitization is not significant. Further analysis reveals that digitization facilitates the expansion of overall bank assets, thereby bolstering the green credit business. It also investigates the characteristics of commercial banks and the geographical distribution of their headquarters, indicating a diminished promotional impact for urban and rural banks, as well as banks in the central areas. Finally, this study contends that commercial banks ought to leverage digital resources extensively to facilitate digital transformation and bolster the advancement of green credit operations. It is also recommended that the government should implement preferential policies for regions and banks exhibiting slower developmental progress.

Examining the impact of green entrepreneurship drivers on sustainable development in the context of emerging country

PurposeGreen entrepreneurship (GE) is a novel concept in business and enhances environmentally friendly production and operation activities for “sustainable development” (SD). The aim of this study is to determine the drivers that contribute to the growth and success of “micro, small, and medium enterprises” (MSMEs) in the manufacturing sector in India. The study also examines the mutual and cause-and-effect relationships among these identified drivers.Design/methodology/approachThe study used integrated research methodology and identified nine key drivers of GE (GEDs) through extensive literature reviews, theoretical perspectives (i.e. “resource-based view” (RBV), “natural resource-based view” (NRBV) and “critical success factor theory” (CSFT)), and expert opinions. Further, “total interpretive structural modeling” (TISM) and “matrice d'impacts croisés multiplication appliquée á un classment” (MICMAC) analysis are used here to develop a hierarchical model and cluster the drivers, and fuzzy “decision-making trial and evaluation laboratory” (fuzzy-DEMATEL) is used to develop causal relationships among the drivers. Further, a sensitivity analysis is conducted to ensure the robustness of the results.FindingsResults indicated that green manufacturing and operation capability development, green business process management and attitudes toward developing sustainable business models significantly impacted GE and SD. The findings of this study help managers, policymakers, and practitioners gain an in-depth understanding of the drivers of GE.Research limitations/implicationsThe study considers a limited number of drivers and is specific to Indian manufacturing MSMEs only. Further, a limited number of experts from different enterprises are considered for data analysis. This study is also based on interrelationships and their relative importance based on multicriteria decision-making techniques. This study aids government decision-making, policy formulation and strategic decision-making for manufacturing businesses in achieving SD goals. In addition, this research also encourages green entrepreneurs to start eco-driven companies and facilitate the use of environmentally friendly goods to offset environmental challenges and accomplish sustainable development goals.Originality/valueThis study proposes an integrated methodology that will benefit managers, practitioners and others in developing strategies and innovations to improve and develop green practices. This study further helps with responsive, sustainable business development in various manufacturing MSMEs.

Energy harvesting for automated storage and retrieval system with sustainable configuration of storage assignment and input/output point

The warehouse automation market has experienced significant growth due to the necessity for quick responses to customer needs. The adoption of Automated Storage and Retrieval System (AS/RS) aims to enhance operational efficiency and expedite order fulfillment, although environmental considerations are frequently overlooked. This study introduces the implementation of energy harvesting using Regenerative Braking System (RBS) on AS/RS to minimize the carbon emission impact. The best configuration of storage assignments and Input/Output (I/O) points is examined to improve travel time, response time, and carbon emission as sustainability indicators. This study employs a discrete-event simulation mimicking the AS/RS and warehouse environment under uncertainty. Simulation-based experiment was performed under 96 different scenarios and the result was assessed through statistical tests revealing the main and interaction effects between factors to performance indicators, including the trade-off between them. The result reveals that the implementation of RBS in AS/RS can result in 13% energy saving on average or equal to additional travel range of 28,800 m indicating the suitability adoption towards green operation. However, the lowest carbon emission is followed by higher travel time and response time. Thus, metamodel-based optimization was also performed via desirability function analysis. The optimization result reveals that the sustainable AS/RS configuration is obtained with a single-side for I/O point, non-class for storage classification, closest open location with column-order for slot selection, and closest open location with row-order for retrieval selection.

Effective light-induced Hamiltonian for atoms with large nuclear spin

Ultracold fermionic atoms, having two valence electrons, exhibit a distinctive internal state structure, wherein the nuclear spin becomes decoupled from the electronic degrees of freedom in the ground electronic state. Consequently, the nuclear spin states are well isolated from the environment, rendering these atomic systems an opportune platform for quantum computation and quantum simulations. Coupling with off-resonance light is an essential tool to selectively and coherently manipulate the nuclear spin states. In this paper, we present a systematic derivation of the effective Hamiltonian for the nuclear spin states of ultracold fermionic atoms due to such an off-resonance light. We obtain compact expressions for the scalar, vector, and tensor light shifts taking into account both linear and quadratic contributions to the hyperfine splitting. The analysis has been carried out using the Green operator approach and solving the corresponding Dyson equation. Finally, we analyze different scenarios of light configurations which lead to the vector- and tensor-light shifts, as well as the pure spin-orbit coupling for the nuclear spin. Published by the American Physical Society 2024

Exploring Industrial Engineering Knowledge and Environmental Sustainability

This research identifies the relationship between industrial engineering and environmental sustainability knowledge components. A combination of a systematic literature review (SLR) and applied thematic analysis (ATA) is employed to uncover the pertinent literature associated with the purpose of this research. Whilst various forms of strategies, theories, methods, and practices were uncovered in each of the knowledge components, only a few were overlapping. These overlapping components include green supply chain operations, circular economy, and technology management. This study is the first in a series of studies contextualising industrial engineering knowledge in terms of its applicability to environmental sustainability. These results reveal concepts from industrial engineering and environmental sustainability knowledge components that can be used to systematically design methodologies or practically implement them in an industry or organisation. Methods and practices were a dedicated theme in the analysis, and these can be used by practitioners. A circle packing diagram is crafted using the IISE Body of Knowledge as a means of categorisation. This study considered industrial engineering as a catalyst in creating new forms of transdisciplinary knowledge areas. It also considers how industrial engineering knowledge can contribute to meeting environmental challenges.

Mitigating yield uncertainty from the perspectives of contract manufacturing and technology licensing

In the low-carbon environment, green manufacturing by manufacturers often requires upstream to provide precision components. However, the lack of production experience of high-tech upstream leads to yield uncertainty. To explore the impact of yield uncertainty on green supply chain operations and analyze its solution, we propose a contract manufacturing mode with technology licensing and further consider pricing licensing or production licensing. The Stackelberg game is employed to construct these three models and a benchmark model without contract manufacturing. Moreover, we discuss the supplier’s mode preference by numerical analysis. Our findings reveal that the contract manufacturing mode with technology licensing mitigates the detrimental influence of yield uncertainty, boosting supplier profitability by 49.00% and manufacturer profitability by 61.76% when the expected yield rate is small or the expected yield rate is large with a small yield fluctuation. Furthermore, when both expected yield rate and profit-sharing ratio are low, increased yield fluctuation predominantly affects the downstream, whereas a win–win–win situation can be achieved through increased profit-sharing ratio. Additionally, compared with contract manufacturing mode with technology licensing, additional pricing licensing or production licensing augments supplier profitability by more than 10.56% in certain cases. Interestingly, improving production efficiency may not enhance the contract manufacturer profitability in both modes due to potential trade-offs with competition and the high cost. This paper contributes to the development of contract manufacturing policies, guiding suppliers and contract manufacturers towards achieving synergetic economic and environmental development. Future research could examine the applicability of the proposed contract manufacturing mode in various industries or identify additional factors affecting supplier profitability.

Sustainable solutions: using MCDM to choose the best location for green energy projects

Purpose This study aims to find the best location for constructing green energy facilities in India and reducing CO2 emissions. Incorporating green energy is a priority for many countries under the Paris Agreement. This task is challenging due to factors that affect implementation, and making the wrong decision wastes resources. India’s goals are net-zero emissions by 2070 and 50% renewable electricity by 2030. Other developing nations should emulate India’s renewable energy strategy. India ranks fourth in renewable energy and wind power, and fifth in solar power capacity. This research aims to identify the best locations in India for implementing green energy projects. Design/methodology/approach To identify the optimal green energy implementation sites in India, this research uses the hybrid multicriteria decision analysis (MCDA) in an uncertain environment. This research uses the Delphi method to identify the most suitable green energy implementation sites in India. It adapts the elements for this investigation. In addition, the utilization of the Fermatean fuzzy weighted aggregated sum product assessment technique is implemented to effectively prioritize the factors that impact the selection of these sites. This study used the MEREC method (method based on the removal effects of criteria) to identify the most suitable areas in India for implementing green energy. The highest accuracy is attained through the amalgamation of these hybrid methods. Findings Following the computation data by hybrid MCDA in uncertainty environment, NP Kunta in Andhra Pradesh emerges as the recommended green energy site among the 11 considered. Also among the factors political strategies and objectives hold the highest priority among them. Originality/value This study is pioneering in its efforts to provide a comprehensive perspective on the development and management of green energy operations in India. The study proves advantageous for diverse sites in the successful adoption and management of green energy. The study is additionally valuable in informing policy development aimed at promoting the use of green energy by employees through the utilization of MCDA methods in uncertain environments.

A Green Marketing and Operations Management Decision-Making Approach Based on QFDE for Photovoltaic Systems

A Green Marketing and Operations Management Decision-Making Approach Based on QFDE for Photovoltaic Systems

Personalized context-aware systems for sustainable agriculture development using ubiquitous devices and adaptive learning

Advanced technologies offer a promising answer, especially integrating personalized context-aware systems through ubiquitous devices and adaptive learning. This paper explores the ability of these technologies to transform agricultural practices, improving performance and sustainability. This study aims to analyze the effect of integrating context-aware structures in agriculture using ubiquitous gadgets and adaptive learning fashions. It specializes in assessing the upgrades in helpful resource control, crop yield, and environmental sustainability and explores the farming community's economic, social, and academic advantages. Utilizing a combined-methods approach, the studies combine intensive literature with empirical statistics series, including discipline experiments, surveys, and interviews with key agricultural stakeholders. It examines contemporary farming practices, the capabilities of rising technology, and the conditions for enforcing robust context-aware systems in farming. Implementing context-aware systems improves agricultural practices by optimizing water and chemical usage, enhancing soil health, and increasing crop yields. Ubiquitous devices and adaptive learning models facilitate specific, real-time selection-making, leading to extra sustainable and green farming operations. Feedback from the rural community similarly underscores the positive effect of technology on improving accessibility to facts and collaborative learning. The study demonstrated that integrating personalized, context-aware systems with IoT and adaptive learning significantly improves agricultural efficiency and sustainability, evidenced by enhanced resource management and increased crop yields. This study contributes to the discourse on leveraging advanced technology to reap agricultural sustainability and units the groundwork for destiny research and coverage development in era-better farming.

Green Operations Practices and Their Role in Achieving Environmental Sustainability Through Intelligent Quality Management (An Analytical Study of The Opinions of a Sample of Employees at the Ur General Company in Iraq)

This study aimed to determine the impact of green operations practices in achieving environmental sustainability through intelligent quality management. The hypothetical plan was built according to the three variables of the study, in light of which the main and sub-hypotheses were developed. This study was applied and tested in the government sector of Ur General Company, affiliated with the Iraqi Ministry of Industry and Minerals. The questionnaire was used as a method to collect data from a sample of 290 individuals. The results indicated that there is a positive impact of green operations practices on environmental sustainability. Therefore, when the company conducts its operations while paying attention to the concept of the environment, it will produce green operations with many opportunities that can be developed. Based on the results that were reached, a number of recommendations were proposed, the most prominent of which was the interest in implementing green operations practices in the company sample of the study by developing all green practices that would work to reduce the environmental damage resulting from the organization’s operations from polluting emissions and waste of resources and energy.

Optimal supply chain performance: risk aversion to green innovation

PurposeAlthough many countries are focusing on the management of construction and demolition waste (CDW) resource utilization, the effect of risk aversion of the green innovation-led enterprise on the performance of the CDW resource utilization supply chain is unclear when considering different green innovation contexts (green innovation led by the building materials remanufacturer or by the construction waste recycler). This study aims to investigate how the level of risk aversion of the green innovation-led enterprise affects CDW resource utilization under different green innovation contexts based on contingency theory.Design/methodology/approachUsing Stackelberg game theory, this study establishes a decision model consisting of a building materials remanufacturer, construction waste recycler and CDW production unit and investigates how the level of risk aversion of the green innovation-led enterprise under different green innovation contexts influences the performance level of the supply chain.FindingsThe conclusions are as follows. (1) For the green innovation-led enterprise, the risk-averse behaviour is always detrimental to his own profits. (2) For the follower, the profits of the construction waste recycler are negatively correlated with the level of risk aversion of the green innovation-led enterprise in the case of a small green innovation investment coefficient. If the green innovation investment coefficient is high, the opposite result is obtained. (3) When the green innovation investment coefficient is low, the total supply chain profits decrease as the level of risk aversion of the green innovation-led enterprise increases. When the green innovation investment coefficient is high, total supply chain profit shows an inverted U-shaped trend with respect to the degree of risk aversion of the green innovation-led enterprise.Originality/value(1) This study is the first to construct a green innovation context led by different enterprises in the CDW resource utilization supply chain, which provides a new perspective on green management and operation. (2) This study is the first to explore the operation mechanism of the CDW resource utilization supply chain based on contingency theory, which provides new evidence from the CDW resource utilization supply chain to prove contingency theory. At the same time, this study examines the interactive effects of the green innovation cost coefficient and the degree of risk aversion of green innovation-led enterprises on the performance of supply chain members, expanding the contingency theory research on contingencies affecting enterprise performance. (3) This study will guide members of the CDW resource utilization supply chain to rationally face risks and achieve optimal supply chain performance.

Penguatan Permodalan Koperasi dengan Skema Crowdfunding pada Koperasi ISM Karya Sinar Bahari, Desa Tanggul Jaya, Kelurahan Banten, Kecamatan Kasemen, Kota Serang, Provinsi Banten

The ISM Karya Sinar Bahari Cooperative, located in Tanggul Jaya Village, Banten, faces significant challenges in accessing adequate capital to sustain its green mussel aquaculture operations. This community service project explores the implementation of crowdfunding as an innovative solution to strengthen the cooperative's capital base. Through this initiative, cooperative members received intensive training on crowdfunding-based capital management. The study identifies the potential of crowdfunding to enhance the cooperative's financial capacity and assesses its impact on improving member welfare and the success of the aquaculture business. The findings demonstrate that this scheme successfully engaged member participation and diversified the cooperative's funding sources.