Search

A striking feature of micro-level plant data is the presence of significant variation in factor cost shares across plants within an industry. We develop a methodology to decompose this variation into idiosyncratic and group-specific components and to use cluster analysis to recover the number and membership of groups using breaks in the dispersion of factor cost shares across firms. We apply our methodology to Chilean plant-level data and find that group-specific variation accounts for approximately one-third of the variation in factor shares across firms. We motivate our results with an economic model in which group-specific variation can arise from differences in production technologies or through distortions that affect different groups of firms. We evaluate several potential explanations for our results and argue that our findings are most consistent with the interpretation of group-specific variation arising from the presence of multiple production technologies. Under this interpretation, ignoring groups overstates the gains from eliminating mis-allocation by roughly one-third.

This study proposes a novel approach to forecast a transhipment port's competitiveness on the basis of market share. The potential reasons for escalating or diminishing competitiveness are explored by utilising a multi-criteria decision-making (MCDM) methodology. We assess the competitiveness of transhipment ports by seven major components: connectivity, port facility, efficiency, cost factor, policy and management, information systems and green port management, and contribute to the understanding of the interdependence among the components. We investigate the Bangladesh container market due to the uniqueness of its regional context and dimensions of competitiveness. Bangladesh has direct connections to four regional hubs, namely, Singapore, Colombo, Port Klang and Tanjung Pelepas. These regional hubs compete to grasp a significant volume of container movements in line with the rapid growth of Bangladesh's industrialisation and national economy. We find that Singapore outperforms others in terms of competitiveness, but all ports perform below expectations in green port management practices. These findings would benefit port authorities for improving their competitiveness, and liner shipping companies and shippers in making strategic port choice decisions.

Wireless dynamic charging (WDC), while the vehicle is in motion, perceived as an enabling technology to mass roll-out of electric vehicles. High output power with minimized pulsation (ripple) is the key-success for such a technology. This paper is presenting a parametric-analysis procedure, aiming at providing design tools for coupler coils of three-phase WDC to achieve specific efficiency and cost requirement. A general design procedure is proposed for a high power WDC system supported by extensive analytical analysis and finite-element analysis (FEA) simulations for wide ranges of transmitter and receiver dimensions, constrained by the stray fields level limitation. Subsequently, other parameters such as the resonant tank are then recalculated to satisfy the system specification. The calculated efficiency is derived according to the loss model of every single component while a cost model is utilized to determine the associated cost, where the tradeoff between efficiency and cost is obtained by parametric-analysis results. The viability of the proposed procedure is experimentally validated using a 3-kW WDC prototype. The practical results show that the efficiency of 88.2% is achievable with an air gap of 15 cm and a normalized cost factor of 0.845.

Aircraft powered by green hydrogen (H2) are a lever for the aviation sector to reduce the climate impact. Previous research already focused on evaluations of H2 aircraft technology, but analyses on infrastructure related cost factors are rarely undertaken. Therefore, this paper aims to provide a holistic overview of previous efforts and introduces an approach to assess the importance of a H2 infrastructure for aviation. A short- and a medium-range aircraft are modelled and modified for H2 propulsion. Based on these, a detailed cost analysis is used to compare both aircraft and infrastructure related direct operating costs (DOC). Overall, it is shown that the economy of H2 aviation highly depends on the availability of low-cost, green liquid hydrogen (LH2) supply infrastructure. While total DOC might even slightly decrease in a best LH2 cost case, total DOC could also increase between 10 and 70% (short-range) and 15–102% (medium-range) due to LH2 costs alone.

Producing Synthetic Natural Gas (SNG) via Power-to-Gas (PtG) is favourable for two reasons; it can be substituted for natural gas in the gas network, and it enables CO2 recycling as energy systems transition towards a low-carbon future. However, the expensive SNG production process is a barrier to being cost-competitive with other market gases. Several diverse factors influence SNG production cost, which results in several possible process configurations with varying performance which influence it. The hydrogen (H2) and carbon dioxide (CO2) required to produce SNG are available from multiple sources, while the SNG production cost is also influenced by the capital investment required for PtG process units, interim storage facilities, and operating expenses. Hence, an in-depth analysis of the factors affecting SNG production is required to understand their effect on the cost and to provide information on cost savings, economic implications, and optimal SNG production setup for decision-makers. In this paper, an optimisation algorithm is developed to model the PtG process units. The main objective of this work is to determine optimal process configurations for SNG production by analysing its influencing cost factors. A factorial design approach is integrated into the optimisation process to minimise the production cost by choosing the cost-effective process configurations. This work also determines the factors with a significant influence on the production cost using an ANOVA. The algorithm identifies the cost-effective H2 and CO2 source to obtain the least expensive SNG production setup. Based on the values of the cost factors, strategies for lowering the production cost in an existing setup are identified. The factors with the most influence on the SNG production cost are the capacity and capex of the methanator unit

Competition between one-way car-sharing operators is currently increasing. Fleet relocation as a means to compensate demand imbalances constitutes a major cost factor in a business with low profit margins. Existing decision support models have so far ignored the aspect of a competitor when the fleet is rebalanced for better availability. We present mixed-integer linear programming formulations for a pickup and delivery orienteering problem under different business models with multiple (competing) operators. Structural solution properties, including existence of equilibria and bounds on losses as a result of competition, of the competitive pickup and delivery problem under the restrictions of unit-demand stations, homogeneous payoffs, and indifferent customers based on results for congestion games are derived. Two algorithms to find a Nash equilibrium for real-life instances are proposed. One can find equilibria in the most general case; the other can only be applied if the game can be represented as a congestion game, that is, under the restrictions of homogeneous payoffs, unit-demand stations, and indifferent customers. In a numerical study, we compare different business models for car-sharing operations, including a merger between operators and outsourcing relocation operations to a common service provider (coopetition). Gross profit improvements achieved by explicitly incorporating competitor decisions are substantial, and the presence of competition decreases gross profits for all operators (compared with a merger). Using a Munich, Germany, case study, we quantify the gross profit gains resulting from considering competition as approximately 35% (over assuming absence of competition) and 12% (over assuming that the competitor is omnipresence) and the losses because of the presence of competition to be approximately 10%.

Cloud services gain more attention due to its accessibility, performance, and cost factors. Cloud offers a wide range of services and completes the task without any delay due to its scheduling policies. Task scheduling is an important factor in cloud computing applications. The performance of applications increases due to an effective scheduling strategy. The cloud resources are allocated to the tasks through task scheduling. Factors like customer satisfaction, resource utilization, better performance make task scheduling crucial for service providers. Depending on the scheduling schemes support in clouds, scheduling is categorized into single cloud or multi-cloud scheduling. Multi-cloud environment provides diverse resources and significantly reduces the cost and commercial limitations. However, reducing the cost functions and makespan are the major factors considered to avoid customer dissatisfaction. But it is essential to concentrate on other factors, such as throughput, delay, Makespan, waiting time, response time, utilization, and efficiency to improve the quality of services. This research work presents a Multi-Swarm Optimization model for Multi-Cloud Scheduling for Enhanced Quality of Services for a multi-cloud environment. Experimental results demonstrate that the proposed approach performs better in all aspects compared to existing techniques, such as Adaptive energy-efficient scheduling, single objective particle swarm optimization scheduling, and improves the quality of services.

This paper presents a real-time 3D LiDAR mapping framework based on global matching cost minimization. The proposed method constructs a factor graph that directly minimizes matching costs between frames over the entire map, unlike pose graph-based approaches that minimize errors in the pose space. For real-time global matching cost minimization, we use a voxel data association-based GICP matching cost factor that is able to fully leverage GPU parallel processing. The combination of the matching cost factor and GPU computation enables constraint of the relative pose between frames with a small overlap and creation of a densely connected factor graph. The mapping process is managed based on a voxel-based overlap metric that can quickly be evaluated on a GPU. We incorporate the proposed method with an external loop detection method in order to help the voxel-based matching cost factors to avoid convergence in a local solution. The experimental result on the KITTI dataset shows that the proposed approach improves the estimation accuracy of long trajectories., IEEE Robotics and Automation Letters, Video: https://youtu.be/TarRKF_Xd2E

PurposeThis paper proposes an evaluation model for prefabricated construction to guide a supply chain with controllable costs. Prefabricated construction is prevalent due to area limitations. Nevertheless, the development is limited by budget control and identifying the factors affecting cost. The degree of close collaboration in the supply chain is closely interconnected with cost performance that includes direct and indirect factors. This paper not only quantizes these factors but also distinguishes the degree of influence of various factors.Design/methodology/approachSystem dynamics is applied to simulate and analyze the construction cost factors through Vensim software. It can also clarify the relationship between cost and other influencing factors. The input data are collected from an Internet of Things (IoT)-enabled system under a Building Information Modeling (BIM) system and Hong Kong government reports.FindingsSimulation results indicate that prefabricated construction cost is mainly influenced by government promotion degree (GPD), working pressure from on-site construction (WPOSC), prefab quality (PQ), load-bearing capacity per vehicle (LBPV) and mold quality (MQ). However, it is more sensitive toward GPD, which indicates that the government should take measures to promote this construction technology. On-site worker management is also essential for the assembly process and indirectly influences the construction cost.Research limitations/implicationsThis paper quantifies indirect influential factors to clarify the specific features for prefabricated construction. The investigated factors are limited.Practical implicationsThe contractor can identify all factors and classify the levels of influence to make decisions under the supply chain system boundary.Social implicationsThe input data are collected from an IoT-enabled system under a BIM system and Hong Kong government reports. Thus, the relationship between construction cost influential factors can be investigated.Originality/valueThis paper quantifies indirect influencing factors and clarifies the specific features in prefabricated construction. The contractor could identify these factors to make decisions and classify the levels of influence under the supply chain system boundary.

In today’s market, supply chain players have to cooperate mutually for extra benefits, long lasting paybacks, and to control carbon emission for a clean environment. In this study, a two-echelon sustainable supply chain model with a supplier–retailer scenario is considered to investigate the overlooked area of growing items and reducing carbon emissions. These joint effects will benefit the firms for interim financing as well as minimize carbon emission for a clean environment. The main task for the supplier is to breed new-born animals with respect to a biologic growth pattern, then slaughters them and controls the carbon emission to maintain the sustainability. The supplier then delivers the slaughtered items to the retailer where it is used as final products to satisfy customers demand and also experienced deterioration during the inventory replenishment cycle. Carbon emission is considered due to transportation of slaughtered items to the retailer. The main goal of this paper is to analyze the model under decentralized and centralized chain structures and in the centralized case profit-sharing contract is incorporated as the cooperation tool. The model has been solved with an analytic solution approach to obtain the global optimum solution. Sensitivity analysis is carried out to investigate the impact of different input parameters. The results support the claim that centralized chain structure can provide the partners with more benefits if an appropriate coordination mechanism is applied. Moreover, it is shown that the unit purchasing cost of each echelon has a significant effect on the profit in comparison to the other cost factors. Finally the results reveal that the supplier’s inventory cycle is more dependent on the growth pattern rather than external cost factors.

Cloud-edge computing is an emerging computing model based on Service Oriented Architecture that provides reliable and available cloud services as scalable resources by collaborating fog nodes on Internet of Things (IoT) environments. One of the important issues on service discovery is energy efficiency and security for existing cloud providers and fog nodes. An optimal service discovery and selection approach as an NP-Hard problem can effective on decreasing time and cost in cloud providers to achieve through maximum capacity of Quality of Service (QoS) factors. To address of the above challenges, this paper focuses on above-mentioned outcomes and presents a QoS-aware cloud-edge service discovery and selection model in IoT environment. This model is evaluated based on a hybrid multi-objective meta-heuristic algorithm based on a Grey Wolf Optimizer and a Genetic Algorithm (GWO-GA) for evaluating QoS factors as non-functional properties. The proposed model is meant to guarantee QoS factors such as the response time, energy consumption and cost factors for the service discovery and selection problem in the IoT environment. Experimental showed that the proposed method performs 30% better than the other algorithms for decreasing cost factor.

With the rapid increase in the functionality of IoT applications, the services provided by edge/IoT devices have surged in the recent past. Fog computing is gaining momentum as a contemporary computational framework for IoT-enabled smart applications that offers a latency sensitivity advantage over cloud computing. Effective task scheduling reduces application computation and latency durations while improves QoS. Many researchers have proposed a variety of heuristic and metaheuristic approaches for effective scheduling; however, there is still scope for improvement. The present work proposes a hybrid of heuristic and metaheuristic techniques for the scheduling of tasks. fireworks algorithm (FWA) is a metaheuristic algorithm, and Heterogeneous Earliest Finish Time (HEFT) is a heuristic algorithm. The bi-objective optimization approach is presented to minimize the makespan and cost factors. To compare the performance of the algorithm, the experiments have been conducted on distinct and independent scientific workflows. The results of exhaustive simulations have established the significance of the presented BH-FWA algorithm over other comparative approaches. To validate the relevance of the technique for fog computing networks, the metrics utilized for comparisons are makespan, cost, and throughput.

Approximately 22 million U.S. workers are exposed to hazardous workplace noise. The industries with the highest prevalence of self-reported occupational HL were Mining (61%), Construction (51%) and Manufacturing (47%). "Buy Quiet" is the most strategic way to reduce noise exposure. However, there are other safety, health, and cost factors that significantly influence a purchasing decision for equipment. A more holistic approach is needed. The safety requirements procurement standard (SAE AS6228) has extensive guidance for evaluating all the safety, health, and cost factors influencing a purchasing decision for equipment. The factors are systematically incorporated into a five-year life cycle score. Unfortunately, this standard is underutilized. Publication of SAE AIR6916 and one-page guidance for each tool type will help to address the underutilization. SAE AIR6916 provides simplified guidance for using the AS6228 standard. One-page guidance documents with example evaluations of life cycle scores will make it easier for additional tools to be evaluated in a consistent and comparable manner. Working with retailers and online shopping websites is needed to make the life-cycle score information more easily accessible and easy to use for making purchasing decisions. Additional efforts are aimed at making the life-cycle score methodology routinely utilized and adaptable to new applications.

We perform this study in order to enhance management of accounting functions in firms, esp. In the case of Hoi An Tourism company in Vietnam.Before covid 19 Vienam tourism has developed fast and achieved high growth, but during covid 19 Vietnam tourism sector has been affected so much, with declining GDP contribution and tourism unemployment.This study mainly use combination of quantitative methods (statistics, calculation formulas) and qualitative methods including synthesis, inductive and explanatory methods.Our study findings tell us that all cost factors such as COGS and sale cost and administrative expense have negative relationship with accounting net profit.Besides, this study also give out recommendations for suitable financial accounting processes and policies as well as directions or implications for tourism management in post-covid in future.

This paper empirically investigates the impact of bilateral investment treaties (BITs) on foreign direct investment (FDI) using data on British multinational firms’ outward FDI in a panel of 140 countries across 2009-2017. We apply the Knowledge-Capital model to demonstrate that BITs act as a market access mechanism to parent country multinational enterprises. Our core result confirms the negative impact of BIT membership on horizontal FDI in the host economy. This result is robust to changes in partner sample composition, hypothetical stock levels, and inclusion of trade policies. Our findings imply that factor cost advantages are unable to compensate for the adverse effect of BIT entry, which raises concerns regarding the potency of BIT-centered development policies.

This study is conducted based on a real case study - AGIFISH company (AGF) in An Giang province, Vietnam, which use OLS regression model to measure impacts from internal cost factors (COGS, sale cost, admin expense) on accounting net profit of the firm. Authors mainly use combination of quantitative methods (statistics, calculation formulas) and qualitative methods including synthesis, inductive and explanatory methods, combined with dialectical materialism method. Our study findings show us that Cost-income ratio has negative relationship with accounting net profit whereas COGS and sale cost have negative correlation with net profit. Besides, this study also give out recommendations for enhancing management accounting policies in the company. For instance AGF management need to control COGS better and reduce COGS/income ratio to increase accounting net profit. Our limitation of research is that we can expand researches to further industries and markets.

Network function virtualization (NFV) is introduced to effectively deliver end-to-end network services for the emerging Internet of Things (IoT), multiaccess edge computing, and 5G communication techniques. In NFV, the network service request can be accommodated in the form of a service function chain (SFC). The SFC will have to reserve abundant resources, such as link bandwidth, service functions, and computation in the physical network to meet the demands of customers. Minimizing the cost from the resource reservation in NFV remains challenging, even though a few works in the literature proposed cost-optimization methodologies with assumptions to guarantee their correctness. In this article, we comprehensively investigate how to minimize the cost when delivering network services as SFCs with provable bounds and fewer assumptions. We formally define the problem of minimum cost service function chaining and embedding (MC-SFCE) and propose an algorithm, namely, cost factor-based SFCE optimization with shortcut (COFO-SC), for MC-SFCE. Novel mathematical analysis is provided to demonstrate the correctness of our approaches and related bounds. Our extensive simulations and analysis also show that the proposed COFO-SC outperforms the schemes directly extended from the existing work.

Quantification and analysis of manufacturing costs in additive manufacturing (AM) are important research tasks, since materials and machines for AM are relatively expensive. To enable the cost estimation in AM, a number of studies have focused on the development of cost estimation software tools for AM. However, these studies mainly focused on single AM systems and materials pre-selected for individual cases. The literature still lacks of a more general perspective on the cost factors and cost structure in different AM processes. Addressing this issue, this paper contributes a general cost model for AM processes and the development of a cost estimation application (App) based on the model. The developed App covers a variety of AM materials and systems. In order to validate the usability of the App, three use cases are performed. The result of the use cases demonstrates that the App, as well as the underlying cost model, is a powerful tool for estimating and assessing the build cost of AM in different design issues.

Human resources which are needed is cost factor due to central to providing services in an organization .Any methods and its aims the organization was created based on the range of vision for the benefit of man and in the implementation of the mission is managed by human beings .Be a man of the main factor of a strategic part of all activities of the organization .The purpose of this research is to know the deployment of an officer at offices of head of subdistricts sebulu in Kutai Kartanegara regency. Then the kind of research that is used is identification descriptive of by the use of of a quantitative approach where is trying in giving a snapshot of the outline or explanation of the an accurate assessment of the areas that can be analyzed in terms of interprestasy and a detailed explanation of existing data shows that in an unsystematic manner based on obyektivitas which appeared to be or as they always have so as to give a picture in on totally objective criteria about the actual state of things of an object that is analyzed in terms of .The results of the study viewed from the side of dimensions expertise be on a level either by the percentage 78,05% and the average score 3.90 dimensions skills are on a level either by the percentage 63,03% and the average score 62,59% dimensions the level of education be on a level either by the percentage 72,22% the average score 3,61 dimensions physically be on a level either by the percentage 62,34% and the average score 3,12 and dimension experience of being on a level either by the percentage 76,22% and the average score 3,81.All are at intervals class good. Keywords: Analysis of Employee Placement

This study investigates the overlooked area of growing items through a two-echelon supply chain with a hybrid-price-stock-dependent demand under trade credit policy. A supplier–retailer scenario is studied where the supplier breeds newborn animals with respect to a biological growth pattern and then slaughters them. The items are sent to the retailer where experiencing deterioration during the inventory cycle. The demand in the retail end is assumed to be multivariate function of unit selling price and the level of on-hand inventory. The model is analyzed under decentralized and centralized chain structures. An analytic solution approach and an algorithm are developed to solve the problem. The proposed structure is illustrated through experimental results with factual growth patent. Sensitivity analysis and graphical illustrations are carried out to investigate the impact of different input parameters. The results support the claim that centralized chain structure can provide the partners with more benefits if an appropriate coordination mechanism is applied. Moreover, it is shown that the unit purchasing cost of each echelon has a significant effect on the profit in comparison with the other cost factors. Finally, the results reveal that the supplier’s inventory cycle is more dependent on the growth pattern rather than external cost factors which is the basic insight of this study.

Aims: This study illustrates the main factors that influence the cost overruns and schedule delays of tunnel construction megaprojects. Objective: An empirical analysis was carried out based on a dataset collected from a number of recent tunnel megaprojects worldwide. Methods: Analyses of variances and regression analyses were conducted to infer statistical significance and understand the relationships that exist between cost overruns, time delays and variables of context, technical, and governance characteristics of the sample projects. Results: The most significant factors are those related to the complexity of infrastructure and the type of contracting system used to deliver the project. In particular, some technical characteristics pertinent to the size of the tunnel reveal to be influencing factors of both schedule delay and cost overrun, while the usage of a traditional contracting mechanism is likely to impact the cost overrun. The type of infrastructure, region, ownership, and funding scheme are not found to be statistically significant determinants of cost and time performance. Conclusion: This analysis reaffirms that the size and complexity are important factors of typical low performance of tunnel construction megaprojects. The results of this study can be used for strategic design and planning by decision-makers, project managers and designers.

Globalization has unleashed a new era of prosperity in economic terms. This has completely changed our outlook towards lifestyle. The recent surge of consumption in the past few decades has led to the escalation in the production of goods which in turn puts a huge burden on the environment. The increasing over consumption of resources has created a sense of urgency to track the level of expenditure as well emissions from a product. One of the major concerns related to the development of green products is the cost factor that comes into play while sourcing the alternate green materials. Identifying the alternate green material increases the overall manufacturing cost for the company. There are a lot of Life Cycle Assessment (LCA) models that look into the environmental quality of a product. Similarly, there are many Supply Chain Management (SCM) models that look into the cost of the product. However very few have researched the combination of both LCA and SCM. There is a need to establish a balance between the cost and the environmental quality of a product. This paper investigates the cost of manufacturing sustainable products by looking into existing LCA and SCM models.

The reasonable cost budget of the e-government scheme can effectively promote the construction of the digital government. To analyze the cost impact components of the e-government system and find out the impact factor model works in China, this paper reviews relevant literature on software cost impact factors and proposes the impact factors model based on COCOMO II. Besides, combined with the actual construction of digital government and specific cases, this paper analyzes the mechanism of each impact factor in detail. The model can be used to guide the cost estimation of e-government software in China, especially with artificial intelligence estimation method. An enhanced decision theory of theory based on fuzzy set has been adopted for analysis of cost factor on E-government software cost.

One of the most important problems for governments and private sectors on construction industry is how to allocate budgets for public residential projects. Low-income residential projects in developing countries have major effects on implementing the principles of sustainable development. Limited budgets in concrete rehabilitation structures represent challenges for the decision-makers. The budget allocation methods proposed in this paper can be easily meet the actual changing demands of response budget policies. This paper proposed a comprehensive comparison between the Topsis method and Simo's ranking method in low-income residential rehabilitation projects. Also, the assignment problem presented to select a suitable project depending on the different clusters. This proposed comparative study aims the decision-maker (DM) to select the optimum method. Finally 13 criteria have been gathered from comprehensive literature. The gathered criteria have been reviewed through unstructured interviews with engineers work in the required field, and selective research according to the designed sample size. These criteria have been classified into three main clusters, economic aspects cluster, social aspects cluster, and environmental aspects cluster. Statistical analysis has been conducted on the interviews feedback. The research aims to trade-off in guiding the decision-maker to direct very limited budgets in the quality of restoration and rehabilitation the efficiency of low-cost or economic housing projects sustainably based on cost factors of projects.

The low economy of fuel cell hybrid electric vehicles is a big challenge to their wide usage. In this article, a road, health, and price-conscious optimal cost minimization strategy based on a decision-making framework was developed to decrease their overall cost. First, an online applicable cost minimization strategy was developed to minimize the overall operating costs of the vehicles, including the hydrogen cost and degradation costs of the fuel cell and battery. Second, a decision-making framework composed of the driving pattern recognition-enabled, prognostics-enabled, and price prediction-enabled decision makings, for the first time, was built to recognize the driving pattern, estimate the health states of power sources, and project future prices of hydrogen and power sources. Based on these estimations, optimal equivalent cost factors were updated to reach the optimal results on the overall cost and charge sustaining of a battery. The effects of driving cycles, degradation states, and pricing scenarios were analyzed.

External factors, such as the increasing environmental awareness among consumers and introduction of environmental regulations by governments, have stimulated manufacturers to produce new green products. Cost factors, on the other hand, encourage the continuation of older generation products and hinder the launch of new green products. To study this dilemma, we consider a single manufacturer with the ability of cost learning from the production of an older generation product, and it intends to launch a new green product. We first derive the optimal pricing and production strategies of the manufacturer based on accumulated cost learning using dynamic programming techniques. Then, we identify the threshold conditions for producing the new green product and the Pareto area that can increase both the profit of the manufacturer and surplus of consumers. For comparison purposes, we also study the impact of external regulations such as environmental taxes on the introduction of a new green product – with results suggesting that the implementation of environmental taxes promotes the accessibility of green products and reduces the Pareto area of profit and consumer surplus. We also find that, under the influence of cost learning, the introduction of new greener products and the implementation of environmental taxes serve to reduce the total environmental damage done by the manufacturer. Results of our models should provide instructive managerial insights for the introduction of new greener products.

Environmental damage and global warming has become an issue in the world. Developments in the construction project has a large influence in environmental change on the surface of the earth. Construction activities start from the constructing stage to the operating stage. Green construction is one part of the sustainable development that is required to participate in environmental sustainability. With this background, the author agreed to explain the criteria, stages of difficulty and obstacles in implementing Green Construction. Data collected by questionnaire method and data analysis using SPSS Statistics 26. The results of this study obtained the value of the Green Construction criteria that applied is waste project variables with an average value of 3,748 and the lowest is site project variables with average 3,198. The most dominant factor of difficulty in applying Green Construction is the water usage variable with an average value of 3,283 and the lowest difficulty in applying is the energy variable with an average of 2,817. The most challenging obstacle factor in implementing Green Construction is the cost factor with an average value of 4.00 and the lowest obstacle is the efficient design variable with an average of 2.96. Thus, from the results of this study is expected that the contractor can help more actively in improving the implementation of Green Construction in this construction project.

Water being one of the classical elements of Earth, is life’s matter and matrix; mother; and medium whose usage rate is always at a hike. The call for conservation of water has always been paramount and there are sundries for conserving it. To reduce the colloidal and shortage of water hitch, the desideratum to conserve water has risen to the next level with the unbalanced water budget equation. In this aspect of interest, Rainwater Harvesting has a pre-eminent role to play and sites the collection and utilization of rainwater and thereby, reducing runoff. A lot of research works and publications dealing with RWH technologies have been insightful. The present paper intends to unearth the various myths and methodologies that are in collaboration with RWH. In addition to the quotidian methods, new flanged technologies will be at a clear glance and the water budget equation balance centralized with examples and cost factors will be explained in a more pellucid way, focusing on the rarity of RWH incorporating the perquisites. High demand of water being a Gordian-Knot, cost-effectiveness along with conservation will be taken into account, thereby proposing suitable and necessary actions with new creative techniques to contrive upon the water as well as energy conservation to meet the apogee demand of water. The cardinal focus of this review paper anent to legitimize water conservation with new creations and the cost-effectiveness of Rainwater Harvesting prudently.

E-business benefit both large and small businesses. However, the aggregate cost of successful online trading, including initial and recurring costs, continues to pose a great challenge to micro-enterprises. For these willing businesses, the result is a mere web presence and for some, the thought of trading online is a no-go area. Using a multi-case study qualitative approach, this study adopts the technology-organisation-environment theoretical lens to explore empirically the strategies used by e-retail microbusinesses to potentially advance their e-business adoption. The findings revealed the actual cost of adoption, the technology-organisation-environment strategies in use to lower the cost barrier, and how the pursuit of the cost barrier simultaneously lowers some adoption barriers outside the cost factors. The study also highlighted the intrinsic idiosyncratic nature of small firms’ ecosystems, and the fact that government resources and services provided by companies, both private and public, could effectively reduce the costs associated with e-business adoption.

The plethora of available IoT connectivity technologies makes selection of the most suitable and affordable offering challenging for IoT service providers. This is a typical problem when considering deployments over Low-Power Wide-Area Networks (LPWAN). Each technology has different implications as to how edge, fog, and cloud resources can be utilized to provide an end-to-end service. The connectivity decision directly affects the initial investment, operating expenditure, level of control desired over the underlying infrastructure, and the resulting managerial overhead. This article provides a generic cost model and framework to assist IoT service providers towards cost-aware LPWAN technology selection and dimensioning decisions. Our framework captures key cost factors and considers both network and compute infrastructure elements. Considering a monitoring IoT application as a reference, we analyze various deployment strategies enabled by two major IoT connectivity technologies, namely LoRaWAN and NB-IoT, quantifying their associated costs and distilling general deployment guidelines.

Green wireless networks or energy-efficient wireless networks have gained popularity as a research topic due to the ecological and economic concerns of cellular operators. The specific power supply requirements for the cellular base station, such as cost-effectiveness, efficiency, sustainability, and reliability, can be met by utilizing the technological advances in renewable energy. There are numerous drivers for the deployment of renewable energy technologies and the transition towards green energy. Renewable energy is free, clean, and abundant in most locations throughout the year. Accordingly, this work proposes a novel framework for energy-efficient solar-powered base stations for the Oman site, specifically for off-grid locations where fuel transportation for diesel generator (DG) is a serious concern. To demonstrate the effectiveness of the proposed system for off-grid sites, the Hybrid Optimization Model for Electric Renewables optimization software is adapted by considering real-time conditions and its technical feasibility. Different cost factors such as capital cost, salvage cost, replacement cost, operational, and maintenance cost of PV panels, inverters, and batteries also undergo extensive analysis. From the observed results, the total net present cost (NPC) of the proposed system is $27,887, while the net NPC of the DG is estimated at $32,900. Remarkably, the proposed scheme can potentially achieve considerable savings in the operational expenditure at approximately 15.24%. Indeed, these outcomes can provide profound economic, technical, and ecological benefits to the cellular operators of Oman. It also ensures a sizeable reduction in greenhouse gas that supports sustainable green wireless network deployment in remote areas.

Energy generation through solar has become more tedious due to huge investment required over its equipment and land. Though the equipment cost factor can be managed by latest technologies, availability of land has become a major setback for the development of solar industries. To eliminate the land requirement for power generation using solar, a concept has been proposed to use the available railway lines for dual purpose. A deck can be formed above 10 m from the ground level to establish a solar park of capacity of 50,000 MW using 300 Wp monocrystalline PV module at a cost of 5 trillion rupees, which includes module, civil works, installation, commissioning, operation and maintenance cost for a period of 25 years with Return of Investment in 10 years. If the concept is implemented throughout India, it not only increases the power generation capacity through renewable energy but also has other various benefits including longer life of rail tracks & coaches, employment opportunities and reduce CO2 emission in environments.

Purpose- The purpose of the study is to propose a model to measure the success performance of businesses which have adopted Sustainable Supply Chain Management (SSCM) practices. Methodology- A literature review was carried out based on some concepts such as SSCM, sustainability and business performance, social performance and financial performance, and sustainable cost management. Findings- When the literature is examined, it is seen that SSCM is considered to be more of a business's practices for reducing environmental impact. In addition, In many studies which examine the relationship between SSCM and firm performance, cost savings are often used as financial performance indicators. But, the fact that sustainability-based practices will generate many different cost factors has been overlooked in many studies. On the other hand, It is seen that the number of studies on cost management and performance measurement in SSCM practices is quite limited. Conclusion- Considering the effects of sustainability-based practices in measuring business performance is important for the definition of long-term success indicators and accurate performance measurements.

The last decades have seen a tremendous amount of research being devoted to effectively managing vehicle fleets and minimizing empty mileage. However, in contrast to, e.g., the air transport sector, the question of how to best assign crews to vehicles, has received very little attention in the road transport sector. The vast majority of road freight transport in Europe is conducted by single drivers and team driving is often only conducted if there are special circumstances, e.g., security concerns. While it is clear that transport companies want to avoid the costs related to additional drivers, vehicles manned by a single driver sit unused whenever the driver takes a mandatory break or rest. Team drivers, on the other hand, can travel a much greater distance in the same amount of time, because mandatory breaks and rests are required less frequently. This paper investigates under which conditions trucking companies should use single or team driving to maximize their profitability. We present a novel optimization approach for simultaneously optimizing routes and crewing decisions and provide experimental evidence that, for a wide range of cost factors, operating a fleet with a mix of team and single drivers can significantly reduce operational costs when compared to typical profit margins in the sector.

Purpose of the study: The purpose of this study was to explain the infrastructure and the need to establish a mobile payment in Iran in the form of a phenomenological study. Methodology: In this study, experts active in the first mobile organization in Tehran have been selected as the statistical population of the study. In this study, sampling was continued until the research structures reached the data saturation level. So that newer interviews did not add a new variable to the previous variables. This saturation is achieved in the fifteenth interview. However, to ensure the expressed saturation, four more interviews were conducted and the number of sample members reached 19 of these people. To improve the validity and reliability of the research, all interviews were recorded with the knowledge of the participants, and key points were reviewed to extract. After announcing the agreement, an interview was held with the focus on perception, perception, and desired indicators for an infrastructure model and the need to establish a mobile payment in Iran. Results: According to the findings, two models were presented to explain the need for mobile payment deployment in Iran with three main factors of deployment strategies, technical strategies, and management-marketing strategies, and a model to explain mobile payment deployment infrastructure in Iran with four main cost factors. Infrastructure, management infrastructure, hardware infrastructure, and software infrastructure were designed and developed. Applications of this study: Finally, it was suggested that by modeling the models presented in this study at the level of national strategies, it is possible to provide the grounds for the establishment of mobile payment in Iran. The novelty of the study: The novelty of this research is the establishment of mobile payment in Iran in the form of phenomenology.

In the recent years, the Egyptian agricultural policy has led to some structural changes that aimed to maximizing economic returns under the technical potential and economic determinants of the local and global economies. The total financial income achieved for the Egyptian cotton crop is estimated at about 9710.8 pounds per acre, as an average for the period of study (2000-2018). Such income was less than the economic value of those revenues at the border prices by about 5.7%, with the economic value of that revenue amounting to about 10261,6 pounds to the ears. The value of the nominal protective coefficient for cotton production was about 0.94 during the study period, which illustrates the absence of a fair production policy during that period due to the depreciation of this coefficient from the correct coefficient. It turns out that the nominal protection factor for production requirements is about 0.91 for this crop, which illustrates the apparent decrease in the amount of support provided by the state for the production requirements as the value of this coefficient approached the correct one. It turns out that the value of the effective protection coefficient is less than the correct one, which amounted to about 0.94 which shows that the value added of the cotton crop is reduced in domestic prices from world prices. The value of the local resource cost factor was about 0.41 during the period 2000-2018.

In this paper, the generalized and new cascaded modular multilevel inverter topology is presented that is designed with reduced power electronic components. Each module comprises ten power switches...

A new alternative of electricity bill payment exists in Indonesia at present, namely prepaid systems. The system is intended to facilitate customers in electricity saving where the electricity utilization could be adjusted. In reality, however, post-paid electricity system utilization still receives great demand. As a consequence, it could not suppress electricity consumption. This research aims to learn factors inhibiting consumers to switch to prepaid electricity systems for their electricity consumption. A descriptive research carries out to answer the research problems. Sample consists of 100 people determined via a snowball sampling technique. Data collection is conducted using questionnaires and measured using Likert Scale of 1-5. Factory analysis is used as an analysis tool. The research results indicate that the main factor that becomes a barrier for electricity customers to switch to prepaid systems is habitual using factor. Switching cost factor, lack of prepaid system information, and relationship and reputation of post-paid products are the second, third, and fourth factors, respectively.Keywords: Switching barrier, electricity, prepaid, and household sectorJEL Classifications: C42, D10, M00, O30DOI: https://doi.org/10.32479/ijeep.10237

We have developed an educational model of power compensated differential scanning calorimeter with a few modifications for the science students of academic institutions. In order to demonstrate the instrumentation and analytical aspects involved in the system, all the building blocks are constructed using local industry and are explained in detail. A few deviations from the conventional model have been attempted without compromising the basic calorimetric concept. This is done with a due consideration for cost factor and also to keep the openness in the development. The paper discusses the calibration procedure of the modified system to arrive at the on-set temperature and enthalpy of the samples. We are able to measure the onset temperature within ±1.18 °C and the enthalpy values using this proto version with an error 5%.

This study identifies consumers’ perceived benefits and costs when using Samsung Health (a healthcare app) based on consumer reviews from Google Play Store’s app and social media discourse. We examine the differences in the benefits and the costs of Samsung Health using these two sources of data. We conducted text frequency analysis, clustering analysis, and semantic network analysis using R programming. The major findings are as follows. First, consumers experience benefits and costs on several functions of the app, such as step counting, device interlocking, information acquisition, and competition with global consumers. Second, the results of semantic network analysis showed that there were eight benefit factors and three cost factors. We also found that the three costs correspond to the benefits, indicating that some consumers gained benefits from certain functions while others gained costs from the same functions. Third, the comparison between consumer app review and social media discourse showed that the former is appropriate to assess the performance of app functions, while the latter is appropriate to examine how the app is used in daily life and how consumers feel about it. The current study suggests managerial implications to healthcare app service providers regarding what they should strengthen and improve to enhance consumers’ satisfaction. It also suggests some implications from the two media, which can be mutually complementary, for researchers who study consumer opinions.

In this era, some people use E-commerce for online transportation. Go-Jek is one of the alternatif online transportation that used by people. The aim of the research is to know the effect of factor cost, quality of services, and E-Commerce technologi to decision for using Go-Jek service in Kecamatan Cibinong. The type of research is used correlational research. The data analysis is used linear regression of multiple with helping SPSS program version 17.0. Result of the research shows the test linear regression of multiple obtained the regression equation is: Y = 3.340+ 0,631X1+ 0,180X2+ 0,678X3. The meaning is every it increases the values of free variable (cost, quality of services, and E-Commerce) so it will increase the value of customers decision using Go-Jek in Kecamatan Cibinong. The results of the coefficient of determination show that the value Adjust R Square of 0,446 (44,6%) Which means together factors cost , the quality of services and E-Commerce have contribution or affecting decision to use Go-Jek in Kecamatan Cibinong of 44,6 %, while the rest 55,4% affect by the other factors that is not discussed in the research. The results of the hypothesis whether partial and simultaneously Prove that factors price , the quality of services and e-commerce affect decision costumers using Go-Jek in Kecamatan Cibinong. The most dominant factors affecting decision to using go-jek in Kecamatan Cibinong is a factor information technology E-Commerce , this is proven by value the regression coefficient of 0,678

This study is the first report in the literature of exergetic, economic, and environmental (3E) analysis for low cost solar heaters (LCSH). In this context, 3E analyses were performed for two LCSH configurations, tubes of the absorber plate connected in series and parallel. The mean exergy efficiency of the LCSH in parallel was 2.56% while for the LCSH in series it was 2.01%. The parallel collector presented lower rates of exergetic destruction and entropy generation, besides a higher overall efficiency. The use of alternative materials in the construction of the LCSH made it possible to achieve low values of embodied energy and embodied carbon emission and consequently excellent environmental indicators. It was found that the simple payback period (SPP) and the leveled heating cost (LCOH) found were 0.38 years and 0.014 US$ kWh−1 for the collector in parallel and 0.42 years and 0.016 US$ kWh−1 for the collector in series. Based on the analyses performed, the LCSH in parallel proved to be the most attractive alternative among the evaluated ones and is indicated for operations where high efficiencies and high temperatures are not required and the cost factor is important.