This week’s readings explore the different types of costing systems available to businesses. In a 4-5 page paper, not including the cover and reference pages, compare and contrast the different cost

ORIGINAL RESEARCHpublished: 04 May 2018 doi: 10.3389/fenrg.2018.00036 Frontiers in Energy Research | www.frontiersin.org 1May 2018 | Volume 6 | Article 36 Edited by:

Federico Maria Pulselli, University of Siena, Italy Reviewed by:Giulia Goffetti, University of Siena, Italy Xiang yun Gao, China University of Geosciences, China Elliott Thomas Campbell, Maryland Department of Natural Resources, United States *Correspondence:Feni Agostinho [email protected]; [email protected] Specialty section:

This article was submitted to Energy Systems and Policy, a section of the journal Frontiers in Energy Research Received: 13 February 2018 Accepted: 16 April 2018 Published: 04 May 2018 Citation:

Marinho Neto HF, Agostinho F, Almeida CMVB, Moreno García RR and Giannetti BF (2018) Activity-Based Costing Using Multicriteria Drivers: An Accounting Proposal to Boost Companies Toward Sustainability. Front. Energy Res. 6:36.

doi: 10.3389/fenrg.2018.00036 Activity-Based Costing Using Multicriteria Drivers: An Accounting Proposal to Boost Companies Toward Sustainability Heitor F. Marinho Neto 1 , Feni Agostinho 1 * , Cecília M. V. B. Almeida 1 , Roberto R. Moreno García 2 and Biagio F. Giannetti 1 1 Laboratory of Cleaner Production and Environment, Post-Gr aduation Program in Production Engineering, Paulista University, São Paulo, Brazil, 2 Faculty of Economics and Business Sciences, Oriente Univer sity, Santiago de Cuba, Cuba Recognizing that natural environment is reaching its maxim um limits in providing resources and diluting the waste generated by human product ion systems, efforts toward more sustainable production systems are mandatory t o secure the development of future generations. For this purpose, changing the produ ctivity model adopted by companies that are almost exclusively rooted on circulatin g money to generate pro t, named business as usual, is an important issue. In this sense , an alternative would be establishing the relationship of stocks and ows of energy, material, and information with environmental, economic and social outcomes, thus res ulting in new accounting approaches. This work aims to propose an activity-based cos ting (ABC) based on multicriteria drivers including economic, emissions, and emergy (with an “m”) values. The proposed ABC costing allocates each one of the multicriteri a drivers into a speci c part of the sustainability conceptual model, in an attempt to emb race a holistic perspective and allow for a sustainable-based decision, rather than con sidering purely economic drivers. The goal programming (GP) method is considered so a s to support a decision based on multicriteria aspects. Results show that the propo sed accounting approach known as ABC sustainallows for decisions toward a company’s sustainability by a cting on both the amount and kind of a company’s product that should be managed, as well as on the effective increase of a speci c company’s activity or process. The proposed ABC sustain could make the insertion of environmental issues into compa nies strategic planning more effective. It is expected that environmental issues go beyond a simple diagnoses and begin to be considered as action in factum in th e companies’ decisions toward achieving a more sustainable world system.

Keywords: activity based costing, emergy, goal programming, o verhead allocation drivers, sustainable companies INTRODUCTION “Freedom in a commons brings ruin to all” ( Hardin, 1968 ). Since the 1960’s this statement has brought concerns on the limits of human growth, recognizing that humans live in a nite planet with limited resources availability; this highlights the n eed for appropriate management of natural storages of resources to maintain the commons. According to Franz and Campbell (2005) , the Marinho Neto et al.Multicriteria Drivers for Activity-Based Costing ecological ethic represented by the “vivantary responsibility” can be adduced as follows: (i) human life is dependent on life suppor t system; (ii) we ought to protect human life; (iii) therefore, we ought not to do anything that imperils the life support system.

Franz (2001) states that “vivantary responsibility” stands for the human obligation to protect the life support system, an ecological ethic of care. Advances toward an understanding of the relationship between human kind and nature has been carried out more densely these last 50 years. Among others experts, Odum (1996) argues that natural capital and ecosystem services are the real source of wealth, despite the common belief held by economists that it is labor and economic capital that are such source. In this sense, obtaining indicators of sustain ability for diagnostic studies under biophysical bases (e.g., life c ycle assessment, emergy accounting, etc.) could be considered c rucial in supporting decision toward a sustainable society. Although the indicators calculated under biophysical basis can provide important information on sustainability, those indicators usually have low practical use in supporting decisi ons for the management of companies at any scale. The point is that managers mainly consider economic indicators for thei r decisions, and this pattern will hardly be changed. Looking toward a sustainable development, e orts have been carried ou t aiming to include biophysical indicators expressing sustain ability in the companies’ decisions. On this issue, some examples can be found in scienti c literature. Thorton (2013) , for instance, highlights the importance of green accounting, by suggestin g the inclusion of the so-called asset-retirement obligations ( AROs) within the bookkeeping practices; in short, the AROs are a way to account for the action of allowing the company to establish its operation in return for exacting a promise to clean up the environment when operations cease. Similarly, based on the idea that emergy (with an “m”; Odum, 1996 ) content of a ow or storage is a measure of value, quality and real wealth, emergy could be considered as a proper measure of the Commons. Under this perspective, Bimonte and Ulgiati (2002) proposed the emergy and environmental taxation schemes (Envitax) as a way to quantify and tax companies. As another example, Campbell (2005, 2013) proposed the emergy- based environmental debt accounting as a new scheme for the traditional bookkeeping techniques. According to author, e mergy and emdollars t logically into the format of standard nanc ial accounting and bookkeeping tools, resulting in an uni ed sys tem of emergy and money accounting that could support political decisions on questions of appropriated debt load to be carried by society, and repaying the existing debts. All in all, there are possibilities in what concerns quantifying, taxing, and even adding environmental loads within the traditional account ing schemes as standardized by the International Financial Repor ting Standards (IFRS), however, who will manage the received mone y and who will decide where that money should be applied to restore and preserve natural capital are still questions with out proper answers. According to Ulgiati et al. (2009) , these aspects need special attention since the reinforcement feedback from humans to nature plays a crucial role in the whole process of keeping the natural system functioning and able to generate new resources and essential services for societal development.

Rather than taxing companies for their environmental load (i.e., acting after the problem has been created; an action done by external decisors), a promising alternative would be consider ing sustainability indicators within company’s decision tools ( i.e., acting before creating the problem; an action done by company’ s internal decisors). In this sense, incorporating sustainabi lity- related indicators in management decision tools that are alr eady accepted and widely used by the companies could lead to practical actions toward sustainability. Among others, the activity -based cost (ABC; Cooper and Kaplan, 1988 ) tool appears as the most promising one. It is important to point out that ABC is not related to a company’s balance sheet, so it is not subject to th e international accounting rules and it is not considered by th e government for tax calculations. ABC is a method used by companies for internal management and useful to create scenarios under simulation considering product-cost, production volume, and products diversi catio n, providing subsidies for decisions toward pro t increase.

Since pro ts are the current main target for the company managers, economic drivers are considered when applying the ABC procedure, however, those drivers could be replaced by environmental-related ones to subsidize decisions for sustainability. Among others, e orts in this sense have being developed by Tsai et al. (2010, 2012, 2015); Bagliani and Martini (2012) , and Yang et al. (2016) by integrating environmental cost-accounting and emissions inventory within the tradit ional ABC, however, none of these approaches recognize the quality o f energy, the hierarchical energy scale, and the energy donor side perspective as emergy accounting does. This work aims to integrate the environmental sustainabili ty aspect into the traditional ABC method as an attempt to provide an innovative business model to replace the current practices exclusively focused on economic issues. Speci cally, the inc lusion of emergy ows as drivers into the traditional ABC method in managing a company’s overheads is put forward. The procedure includes the contextualization of a sustainability model, followed by the establishment of economic and environmental drivers to be used into the ABC, and the application of goal programing to deal with multicriteria approaches. The hypothesis is that t he proposed procedure results in an optimized choice to reach bette r balance between economic and environmental performances fo r companies.

METHODS Allocating Companies’ Overheads Through Economic and Environmental Drivers The more precise the cost allocation is, the more precise will be the information generated supporting a company’s decision on which product should be prioritized in terms of production and sales to the market, or even which product-mix should be produced based on goals to thrive the companies’ strategy ( Ponisciakova et al., 2015 ). The costing management system known as Activity Based Costing (ABC) attempts to increase the accuracy in cost allocation to allow decisions on company’ s Frontiers in Energy Research | www.frontiersin.org 2May 2018 | Volume 6 | Article 36 Marinho Neto et al.Multicriteria Drivers for Activity-Based Costing product-mix, break-even-point, and contribution margin. ABC was developed by Cooper and Kaplan (1988) from their professional skills as entrepreneur consultants, and was rec ently updated and named as Time Driven Activity Based Costing aiming to reduce the implementation di culties and making adaptations by the users, whenever necessary, easier ( Kaplan and Anderson, 2007 ). Both ABC approaches are largely applied in di erent production sectors and organizations, as detailed b y Tsai et al. (2014) , while the choice for one or the other depends on the company’s management goals. For this present work, the traditional ABC is used considering di erent drivers for overheads costs allocation. Ellis-Newman and Robinson (1998) argue that ABC supports decision makers in improving or eliminating all company’s ine cient activities, thus resulting in an e ciency improve ment and pro tability. ABC allocates the company’s overheads (i.e ., indirect costs) to products following a di erent approach, when compared to the Traditional Costing Systems (TCS), which allocate overhead costs to the products without considering the complexity of production systems and their infrastructur e, which also include administration o ces; TCS can be conside red useful when allocating direct costs, but the indirect costs are disregarded. Overheads have been receiving higher importan ce over the years, since their percentage in the company’s total production costs have increased from 15 to 45% in average (in some cases reaching up to 90%; Kolosowski and Chwastyk, 2014 ); the reasons of overheads increase is mainly due to automatio n of manufacturing processes and outsourcing services. For a brief explanation on how the ABC works, Figure 1 shows the costs allocation drivers. Driver is a reference va lue carefully chosen to allocate the resource cost to activitie s demanding that resource, and to allocate the cost attribute d by an activity to the products. To properly use the ABC, it is crucial to choose allocation drivers with strong cause - e ect relation between the resources and activities, and bet ween activities and products. The stronger the cause-e ect relati on, the more precise the results will be, which supports a better- based decision ( Cooper, 1990 ). Traditional drivers used within the ABC are production time, industrial area occupied, machin e power-rating, machine setup, and the amount of labor hours, which helps to understand which products should be reduced or eliminated, which materials to change, and what process shou ld be modi ed in order to reach higher pro ts for the company. Although recognizing that economic aspects are important in sustaining the company’s perpetuation over time in a competitiv e market, the environmental and social aspects are beginning to be considered as having similar importance; this is relate d to the sustainable development de nition by the Brundtland (1987) report. In this sense, some adaptations in the ABC framework are being assessed to better t the companies’ objectives and the way they operate. For instance, Tsai et al.

(2010) applied a modi ed ABC to allocate the overheads, originated from the environmental sector of a given company, to their products; this approach was initially proposed by the United States Environmental Protection Agency (USEPA). The authors replaced the traditional cost drivers, which measure o nly economic aspects, with drivers related to the CO 2emissions released from the company’s production processes. As a result, those products that release the most CO 2received more overheads (i.e., they were penalized) than others with lower emissions. The work of Tsai et al. (2010) is here considered as reference for primary data of overheads, as well for economic and environmental drivers. Since both approaches are well developed and known by the scienti c community, the procedure in obtaining emergy drivers receives higher attention in th is work. FIGURE 1 | Allocating company’s overheads under the ABC framework.

Frontiers in Energy Research | www.frontiersin.org 3May 2018 | Volume 6 | Article 36 Marinho Neto et al.Multicriteria Drivers for Activity-Based Costing Among other examples, Schulze et al. (2012) proposed a conceptual framework for ABC to assess inter- rms relations hips instead of focusing on intra- rms as usual. In this study, a larger scale analysis is considered, under a supply chain perspective. Main outcomes emphasize that ABC can be applied in the supply chain for inter- rms purposes, but this has been done in a limited way, resulting in a decrease of e ciency in identifying key aspects for improvements. Tsai et al. (2012) applied emissions as drivers in allocating overheads for proje cts of buildings aiming to support a greener eet with reduced CO 2 emissions. Bagliani and Martini (2012) developed a framework to use the ABC and environmental pressures simultaneously (speci cally the footprint method) associated with companies ’ production. Authors state that the proposed framework is usefu l for complex and multi-utility production systems, whose init ial environmental impacts can hardly be directly assigned to na l products. Authors suggest that the proposed framework enables for choosing processes with a high utilization of renewable resources and low carbon emissions.

Proposals to modify the ABC by including environmental aspects could be considered as a positive step in supporting companies’ decisions toward more sustainable production systems. This is true since more than economic drivers are considered within the ABC framework. Although seen as an important advance, the proposed modi cations considering emissions as drivers for company overheads still lacks a bett er de ned conceptual model of sustainability. In other words, u sing emissions as drivers will support decisions based exclusively on emissions.

The Conceptual Model of Sustainability Behind the Proposed Modi ed ABC Pulselli et al. (2015) emphasize that sustainability is an issue of relationship among compartments. The conceptual sustainabi lity model developed by Pulselli et al. (2011) shows the evolution of the triple bottom line sustainability model based on a triang le divided in levels of priority, in which the environment is the basis and supports societal development (intermediary level) , while the upper level represents the economy. These authors argue that ecosystems are open systems where energy and matte r cross their boundaries to perform and maintain their functio ns, aiming to maximize the conversion of system inputs into usefu l goods and services outputs. Thus, through an analogy between the sustainability model represented by an inverted triangl e with the energy ows crossing the open system boundaries, the input - state-output (ISO) sustainability model is established ( Figure 2); this model can be applied to di erent natural and human-made systems ( Pulselli et al., 2011; Bastianoni et al., 2016 ), including companies. Figure 2 presents the proposed model of sustainability in an attempt to better represent the sustainability of companies , including input resources ows, the production processes, and the output of products and by-products. As representatives of each sector in the ISO model, emergy accounting (with an “m”; Odum, 1996 ), technical-economic approach and emissions are respectively considered. Pulselli et al. (2011) FIGURE 2 | Production systems as open systems showing the sectors in which the three different ABC approaches are focused on.

argue that using emergy accounting as a system input can represent the biophysical counterpart of the system output, i.e., emergy accounting is able to quantify the e ort of natur al environment in providing resources for human activities to reach the desirable societal well-being. Still regarding th e input sector, the importance of quantity and quality of resources as key elements for system development is recognized. Thus, environmental accounting using emergy rather than other biophysical approaches is important because it is based on a systemic view and considers a donor-side perspective that take s into account all resources from nature and from a larger econ omy required by the transformation system to provide a service or a product, which enables it to recognize the quality of energy ( Agostinho et al., 2016 ); in this sense, the input is represented in this work by the ABC emergymeasured in solar emjoules (abbreviated as sej). The state sector is represented by the ABC $in monetary units ($) as traditionally used. The “machine hours” driver was here considered in allocating overheads for the ABC $, however, other drivers are usually included as “hours of man-work” or even “employees training sections” that could represent the so cial aspect of ISO sustainability conceptual model. The output sect or is represented by the ABC env.( Tsai et al., 2010, 2012 ) which includes the emissions released into the environment by the productive process (e.g., kgCO 2eq).

By considering the proposed model of sustainability and its corresponding indicators for ABC, it is expected that the company’s internal management also consider the prerogative of sustainability in their decisions, which would be bene cial f or the economic aspects of companies as well as for the entire society through the increase of Earth’s biocapacity. The goal of this work is not to change the already acceptable and widely used ABC’s framework managing method, but to present an alternative to replace the traditional use of ABC focused on economic aspects with a more holistic perspective of sustainability. An d to reach this goal, the drivers used in allocating a company’s overhead are changed according to di erent methodological approaches supporting the proposed sustainability model. Since calculating traditional and environmental (emissions) dr ivers are well presented in literature, the next section presents, in de tail, drivers based on emergy accounting. Frontiers in Energy Research | www.frontiersin.org 4May 2018 | Volume 6 | Article 36 Marinho Neto et al.Multicriteria Drivers for Activity-Based Costing ABC emergy : Using Emergy Drivers to Allocate Company’s Overheads According to Odum (1996 , p. 7), emergy is the available energy of one kind previously used up directly and indirectly to make a service or product. Emergy accounting is routed on thermodynamic bases and system theory, with features that make it a powerful scienti c-based tool when assessing sustainability, including a donor- side approach in quantify ing value, biophysical basis; it recognizes the quality of energy , and suggests a universal energy hierarchy based on the energ y quality concept. Emergy accounting can be applied for di erent purposes, but usually, its use is related to the calculation of environmental performance indicators. Among those, the Unit Emergy Value (UEV) evaluates the emergy e ciency or the globa l e ciency in converting resources into goods and services; i ts unit relates the emergy demanded by the production system (in solar emjoules or sej) with the system output (usually in kg, J, or $ units). Although rstly expressing the e ciency in converting resources into goods and services, the UEV could a lso be related to the sustainability concept since using lower am ounts of resources (renewable and/or nonrenewable) could increa se the Earth’s biocapacity. Indirectly, the same comment can be appli ed to the total emergy demanded by systems: using lower amounts of emergy suggests, at principle, more sustainable systems du e to lower amount of global resources needed in their productio n processes—this is an important premise of this work. It is also recognized that a system demanding a high amount of emergy from renewable sources is also more sustainable, however, t his hardly happens when it comes to companies since they are mostly dependent on resources from the economy, which are classi ed as non-renewable. A potential advancement of the proposed ABC emergyapproach could be by identifying the origin of resources (renewable or non-renewable sources) and incl uding this information when accounting for the emergy demanded by production systems; this could support more accurate results about the sustainability of the evaluated systems. As a result of the increasing number of published emergy studies and the strengthening of emergy society (emergysociety.com), the amount of UEVs available in scient i c literature and databases is increasing exponentially, makin g its usage more accessible. It must be emphasized that rules for emergy algebra are respected, as described by ( Brown, 2015 , p.

273): Rule #1—emergy is the available energy (exergy) of one kind that is used up in transformations directly and indirec tly to make a product or service; Rule #2—in processes having one output, all independent emergy inputs are assigned to the processes’ output; Rule #3—when a pathway splits, the emergy is assigned to each branch of the split based on its percent of th e total available energy ow (or mass) on the pathway before the split; Rule #4—in processes having two or more co-products, all independent input emergy is assigned to each co-product; Rule #5—within a system, emergy cannot be counted twice, (a) emergy in feedbacks cannot be doubled counted, (b) co-produc ts, when reunited cannot be added to equal a sum greater than the source emergy from which they were derived. Figure 3shows the application of emergy rules in a generic company for illustrati ve purposes. To be considered as a driver within the ABC framework, the interpretation of emergy algebra rule #1 needs to be adapted to t into the cause-e ect relation required when allocating over heads.

Precisely, only the emergy from external sources applied in a company transformation activity (i.e., the emergy owing fr om outside the company boundaries) is accounted for, disregardi ng the emergy carried with a product from the previous internal FIGURE 3 | Energy diagram of a generic company to exemplify the emergy- based drivers calculation. R, external resources.

Frontiers in Energy Research | www.frontiersin.org 5May 2018 | Volume 6 | Article 36 Marinho Neto et al.Multicriteria Drivers for Activity-Based Costing transformation activity. This adaption is important to avoidthat a company activity located on the right side of a production cha in be always penalized with the emergy of previous activities. To exemplify this approach, Figure 3shows the emergy ows for a generic company and its emergy drivers. Focusing on activit y #1, it demands emergy from R1, R2, and R3 external sources totalizing 6 sej, while activity #2 demands a total of 3 sej fr om R5. Similarly, activity #3 requires 6 sej from R4 and R5 sources, and activity #4 demands 1 sej from R6. The emergy demand by activity #4 of 1 sej from R6 is an indirect cost of products #1 and #2, thus it is allocated to them according to the ABC theory; f or this, the total emergy of products #1 and #2 are considered as parameters for allocation. When focusing on both activities and products at the same time to establish the emergy drivers, the reading is as follows: product #1 receives 3.6 sej in activity #1, added to 3.0 sej in activity #2 and 0.44 sej in activity 4; produ ct #2 receives 2.4 sej in activity #1, added to 6 sej in activity # 3 and 0.56 sej in activity #4. Final emergy drivers are shown in the above-right table at Figure 3.

Although emergy rule #1 is di erently interpreted to t the ABC concepts and goals, the emjoules ows from external sources that are carried by products within the company still embody all previous directly and indirectly available energ y to make the external source available due to the usage of UEVs.

As a result, those companies’ activities demanding more emer gy will receive larger amounts of total overheads, which means they are causing a larger load (or stress) on the environment by demanding larger amounts of resources than all other activi ties.

For example, the emergy drivers provided on the table in Figure 3 indicate that product #1 should receive about 60% of total overheads in activity #1 (3.6 sej of 6 sej in total), whereas product #2 should receive the remaining 40% (2.4 sej). This implies that, in an attempt to reduce the emergy demanded by company, product #1 should receive more attention for actions from managers than product #2 during activity #1. The ABC emergyputs in evidence the companies’ products that demand higher e orts from the natural environment to be produced, in other words, a larger part of total overheads will b e allocated to them. The same approach is used as for the ABC $and ABC env., however these will focus on economic and emissions drivers and will put in evidence a perspective other than emergy .

For this reason, and also by considering the conceptual model of sustainability as presented in the Figure 2, the use of multicriteria techniques [goal programming (GP) in this work] are mandator y to support decision makers.

Goal Programming Supporting a Multicriteria-Based Decision Goal Programming (GP) is a subset of multi-objective optimization (MOO) based on linear or nonlinear programming to solve multidimensional and contradictory issues ( Marler and Arora, 2004 ). Linear programming considers the goals as hard constraints, while GP can deal with con icting goals , or soft constraints. Introduced by Charnes and Cooper (1977) , the GP aims to minimize the unwanted deviation from a goal, represented mathematically as m i= 1| di |. GP can mathematically be expressed as i(x ) + ni −pi = i, where di= ni−pi of a function i( Hanks et al., 2017 ).

Mathematical modeling is necessary to assign the equations represented in a general form as Min m i= 1ni −pi, subject to i(x ) + ni −pi = i. Among others, similar techniques derived from the GP are The Lexicographic Goal Programming, Weighted Goal Programming, and Chebyshev Goal Programming. GP is a widely recognized and used tool supporting decisions based on multi-criteria perspectives in the scienti c and non - scienti c communities. Among several other examples, its application includes a decision making process to choose among potential renewable energy plants considering contradicting goals, like social aspects, nancial, and location ( Zogra dou et al., 2017 ), or to support a better choice between public transport projects considering social and nancial aspects ( Yang et al., 2016 ), or to choose a community energy plan among several options with di erent performances for techno-econom ic aspects ( Huang et al., 2017 ). The usage of GP requires a deeper understanding about how the production system assessed work s, and precise information supported by primary data. Considering that its application varies from system to system, rather than provide all mathematical theory behind GP, the next section presents data, assumptions and the complete models used in this work to allow results replication; for deeper mathematics deta ils and concepts supporting GP please see Charnes and Cooper (1977) .

RESULTS AND DISCUSSION The ABC $is widely known and used by companies, and the usage of ABC env.has been increasing over the last few years. Thus, in this work the ABC emergyreceives higher attention, as well as the junction of these three approaches in the goal programing to provide better information for decision makers. As the main goal is to provide sustainability-based information regard ing the procedure proposed rather than a real study case, a generic company is used as reference by considering primary data from Tsai et al. (2010) .

Applying the ABC $and ABC ENV.in a Generic Company Table 1 presents the activities and cost drivers as used by Tsai et al. (2010) , who modi ed the initial framework of EPA (1995) by replacing the technical cost drivers with others, representing the end of pipe emissions, environmental damages prevention, environmental regulation, environmental taxe s, and environmental training hours. After de ning new drivers representing the ABC env., Table 2 shows the overhead allocation for the studied company throug h traditional (ABC $) and environmental (ABC env.) approaches.

Using the ABC $, product “P” receives 25.3 million USD/yr, while “Q” receives 2.7 million and all other products with 92 thousand USD/yr altogether. Although providing important indication about what product is responsible for most of the company’s overhead, this ABC approach does not provide any Frontiers in Energy Research | www.frontiersin.org 6May 2018 | Volume 6 | Article 36 Marinho Neto et al.Multicriteria Drivers for Activity-Based Costing TABLE 1 |Company’s activities and drivers considered by Tsai et al. (2010) . Activity # Cost drivers # Preventing air pollutionA1 Waste emissions (kg) D1 Preventing water pollution A2 Waste water (m3 ) D2 Ef cient utilization of water resource A3 Water input (m3 ) D3 Recycling general industrial waste A4 Recycled general waste (t) D4 Recycling hazardous industrial waste A5 Recycled hazardous waste (t) D5 Disposal of general industrial waste A6 Disposal general waste (t) D6 Disposal of hazardous industrial waste A7 Disposal hazardous waste (t) D7 Activity for monitoring environmental impact A8 Internal audit (units) D8 Activity for environmental training of employees A9 Time of training sessions (h) D9 R&D to curtail environ. impact at the manufacturing stage A1 0 Time of R&D (h) D10 R&D to curtail env. impact of distribution stage A11 Time of R&D (h) D11 Nature conservation, planting of greenery A12 Operating space (m²) D12 Financial support of environ. groups and local community’s activities A13 Operating revenue ($) D13 information regarding which activity is the most representa tive in causing that overhead. Thus, the likely actions that compa ny’s manager can take are essentially focused on products, i.e.

reducing or increasing the production amount of those product s with higher in uence on overheads (i.e., product “P” in this case), or replacing them with others, or even changing product processes. Di erently from ABC $, the ABC env.considers the company’s activities when allocating overheads and, mainly, it consi ders di erent drivers for allocation according to the either stro nger or weaker relationship between activities and their overhe ad- related costs. In so doing, Table 2shows the following overhead allocation for ABC env.: about 21.7 million USD/yr for product “P,” 4.7 million for “Q,” and 1.7 million for all other company products. The rst reading is that results are di erent betwee n ABC $and ABC env., since di erent allocation drivers were considered. This implies that managers can take di erent decision toward the overhead reduction according to method used for calculations. Notwithstanding, decisions will be b ased on the meaning of the drivers used, i.e., rather than focusin g on pure economic purposes as done by ABC $, the ABC env.focuses on environmental issues as the ones listed on Table 1. Under a sustainability perspective, this can be deemed important sinc e environmental issues are being, mainly over the last few yea rs, mandatory aspects basing decisions at any level. The second observation on Table 2is that ABC env.enables to verify which company’s activity is more intensively a ecting the nal resu lts.

Thus, decisions can be made not exclusively based upon the amount and kind of company products, but now the activities can also be the target for improvements in order to achieve tot al overhead reduction. In short, the ABC env.can be seen as an advancement of the ABC $in the following two aspects: (i) environmental drivers are strictly related to sustainability issues and they are n ow also considered for decisions rather than exclusively economic o nes; (ii) distinguishing the company’s activities allows for dec isions focused on both products and activities. Applying the ABC emergy Both ABC approaches previously presented consider economic and emissions aspects as drivers, but emergy is now considered as a cost driver to ful ll the conceptual model of sustainabil ity adopted in this work. The ABC emergyappears as a new variable to be taken into consideration by the decision maker, which ai ms to quantify the environmental e orts in providing resources f or the company’s production activities. Under this approach, the overheads are allocated based on the global resources demand ed by the company. Table 3shows the following allocation results from the ABC emergy: about 11.1 million USD/yr are allocated to product “P,” 13.8 million to “Q,” and 3.2 million for all other products. It is important to highlight that emergy drivers considered on Table 3 (precisely columns #4-6) were randomly assumed without a deeper evaluation, due to lack of precise data regardi ng the production system evaluated by Tsai et al. (2010) , which is the source of primary data for this work. Although this could be considered as a limitation of this present work, our intent ion herein was not to provide a real and precise ABC diagnostic, instead, the main goal is to propose an alternative framework in using the ABC that could result in better sustainability- based nal indicators for managers. Notwithstanding, in possessi on of all the descriptive information about a company’s production owchart, the procedure presented in Figure 3can be easily applied by someone in obtaining precise emergy drivers. As expected, Tables 2,3 show di erent values for a company’s overhead allocation to products, since di erent cost drivers we re used in the allocation procedure; ABC $focuses on monetary aspects, whereas ABC env.focuses on emissions and ABC emergy focuses on the e ort of natural environment in providing resources. When simultaneously used, the three approaches for ABC respect the conceptual model of sustainability adopted in this work, which means that jointly considering all three approaches will result in sustainability-based indicators to be further used by managers in reducing company’s overheads. Fo r this, it is necessary to merge the obtained numbers that resu lt on a Frontiers in Energy Research | www.frontiersin.org 7May 2018 | Volume 6 | Article 36 Marinho Neto et al.Multicriteria Drivers for Activity-Based Costing TABLE 2 |Activity- based costing using environmental drivers (ABCe nv.) and traditional costing system (ABC$) for the environm ental sector evaluated by Tsai et al. (2010) . Activity Cost drivers Overheads ( a ) ($/yr) Product “P” ( b ) (Unit/yr) Product “Q” ( b ) (Unit/yr) Other products (b ) (Unit/yr) Total ( c ) (Unit/yr) Unit Unit cost per activity driver ( d ) ($/Unit) Product “P” ( e ) ($/yr) Product “Q” (e ) ($/yr) Other products ( e ) ($/yr) A1 D1 2,657,100 5,603 692 623 6,918 kg 384 2,152,028 265,787 2 39,285 A2 D2 2,869,640 1,514,182 133,115 16,640 1,663,937 m 3 2 2,611,371 229,571 28,697 A3 D3 544,400 3,918,501 126,132 159,768 4,204,401 m 3 0 507,381 16,332 20,687 A4 D4 528,590 2,675 301 31 3,007 ton 176 470,229 52,912 5,449 A5 D5 2,304,990 1,231 312 16 1,559 ton 1479 1,820,040 461,294 23,656 A6 D6 2,051,100 1,985 252 277 2,514 ton 816 1,619,504 205,600 225,996 A7 D7 1,318,900 1,002 131 170 1,303 ton 1012 1,014,227 132,59 9 172,074 A8 D8 261,160 813 109 165 1,087 unit 240 195,329 26,188 39,643 A9 D9 887,925 219 25 3 247 h 3595 787,270 89,871 10,785 A10 D10 4,653,462 42,400 30,400 7,200 80,000 h 58 2,466,335 1 ,768,316 418,812 A11 D11 2,573,860 29,400 17,400 13,200 60,000 h 43 1,261,191 746,419 566,249 A12 D12 684,925 39,872 3,584 1,344 44,800 m 2 15 609,583 54,794 20,548 A13 D13 6,919,500 29,774 3,382 108 33,264 $ 208 6,193,518 703 ,516 22,466 Activity based-costing using environmental drivers (ABC env.):

21,708,007 4,753,197 1,794,347 Machine hours 28,255,552 693,120 76,380 2,508 772,008 h 37 2 5,368,246 2,795,514 91,793 Traditional costing system (ABC $): 25,368,246 2,795,514 91,793 ( a ) From company’s balance sheet; ( b ) Overheads allocation drivers for products “P,” Q,” and “Others,” obtained from c ompany’s internal quality control report;( c ) Sum of “P” +“Q” +“Others”; ( d ) (a)/(c); ( e ) (b) * (d). Frontiers in Energy Research | www.frontiersin.org 8May 2018 | Volume 6 | Article 36 Marinho Neto et al.Multicriteria Drivers for Activity-Based Costing TABLE 3 |Activity based-costing using emergy drivers (ABCemergy) f or the environmental sector evaluated by Tsai et al. (2010) . Activity Cost drivers Overheads (a)($/yr) Product “P” (b) (Unit/yr) Product “Q” (b) (Unit/yr) Other products (b) (Unit/yr) Total (c) 1,91E +15 (Unit/yr) Unit Unit cost per activity driver (d) ($/Unit) Product “P” (e) ($/yr) Product “Q” (e) ($/yr) Other products (e) ($/yr) A1 Emergy 2,657,100 9.3E +13 10.0E +13 6.0E +12 1.99E +14 sej 1.34E-08 1,241,760 1,335,226 80,114 A2 Emergy 2,869,640 3.0E +13 3.1E +13 10.0E +13 1.61E +14 sej 1.78E-08 534,716 552,539 1,782,385 A3 Emergy 544,400 9.3E +13 3.0E +13 10.0E +13 2.23E +14 sej 2.44E-09 227,037 73,238 244,126 A4 Emergy 528,590 8.2E +13 3.1E +13 7.0E +12 1.20E +14 sej 4.40E-09 361,203 136,552 30,834 A5 Emergy 2,304,990 1.6E +13 5.1E +13 8.0E +12 7.50E +13 sej 3.07E-08 491,731 1,567,393 245,866 A6 Emergy 2,051,100 10.0E +13 8.1E +13 5.0E +12 1.86E +14 sej 1.10E-08 1,102,742 893,221 55,137 A7 Emergy 1,318,900 10.0E +13 3.0E +13 1.0E +12 1.31E +14 sej 1.01E-08 1,006,794 302,038 10,068 A8 Emergy 261,160 4.1E +13 7.1E +13 3.0E +12 1.15E +14 sej 2.27E-09 93,109 161,238 6,813 A9 Emergy 887,925 8.1E +13 10.0E +13 3.0E +12 1.84E +14 sej 4.83E-09 390,880 482,568 14,477 A10 Emergy 4,653,462 2.2E +13 6.1E +13 6.0E +12 8.90E +13 sej 5.23E-08 1,150,294 3,189,451 313,717 A11 Emergy 2,573,860 3.0E +13 5.0E +13 4.0E +12 8.40E +13 sej 3.06E-08 919,236 1,532,060 122,565 A12 Emergy 684,925 4.5E +13 9.1E +13 7.0E +12 1.43E +14 sej 4.79E-09 215,536 435,861 33,528 A13 Emergy 6,919,500 9.6E +13 9.1E +13 8.0E +12 1.95E +14 sej 3.55E-08 3,406,523 3,229,100 283,877 Activity based-costing using emergy drivers (ABC emergy): 11,141,561 13,890,486 3,223,505 ( a ) From company’s balance sheet; ( b ) Total emergy demanded by each product in each company’s activity; ( c ) Sum of “P” +“Q” +“Others”; ( d ) (a)/(c); ( e ) (b) * (d). TABLE 4 | Amount of products that should be produced by the studied gen eric company, according to different ABC approaches.

Product Amount of products to be produced after applying goal programming under different approaches ABC$ (units) aABC env.

(units) b ABC emergy (units) c ABC sustain (units) d P 0 758,918 203,163 203,163 Q 1,487,134 0 0 0 Others 0 326,888 87,508 87,508 a Appendix 1.

b Appendix 2.

c Appendix 3.

d Appendix 4.

multicriteria issue, and this subject is discussed in the ne xt section by applying GP.

Goal Programming Supporting Decisions Toward Higher Degrees of Companies’ Sustainability More than overheads in USD/yr distributed among products under the three di erent ABCs approaches as previously presented, the managers usually demand information on units that allow them to more easily understand the current company ’s performance and take decisions toward improvements as promptly as possible. In this sense, managers prefer information in units of “amount of products” that should be produced rather than values in “USD/yr”. Therefore, Table 4shows the overheads distributed for the three ABCs individually viewed in units of “amount of products.” To obtain these numbers, di erent GP models were performed (Appendices 1–4) and run by using the LINGO R 11 software. It is important to emphasize that proposed models do not represent a real company, but rather, as previously mentioned, our intention is to provide essential informatio n to readers who may wish to replicate this work and/or apply the same approach in a speci c case study. In so doing, the models in Appendices can be changed to pursue di erent goals, however, always respecting the conceptual model of sustainab ility as established herein. Table 4 shows di erent values for the “amount of products” for the di erent ABCs. For instance, while the ABC $promotes the production of “Q,” the ABC env.and ABC emergypromote essentially “P” and a moderate amount of “Others.” Although providing important information for managers, none of these three approaches alone is able to represent sustainability-ba sed information, which claims for a joint assessment perspective as proposed by the conceptual model of sustainability as presented in Figure 2 . For this, the results of all three individual ABC approaches can now be modeled under the concepts of GP, including the restrictions (hard or soft constraints) for eac h ABC approach, deviation variables and objective function as desc ribed in Table 5 . Modeling this integrated ABC (named ABC sustain heretofore) demands some e orts, however the basic idea is to merge all advantages of every individual ABC (emergy, econo mic Frontiers in Energy Research | www.frontiersin.org 9May 2018 | Volume 6 | Article 36 Marinho Neto et al.Multicriteria Drivers for Activity-Based Costing TABLE 5 |Description of the variables considered in modeling the nal goal programming merging the three ABCs approachesa .

Eq.# Restriction equations, deviation variables and objective function Type Description 1 0,43*P =Others Hard Constraint The amount of product “Others” is 43% of product “P” as a process rule proposed to develop a production restriction. This changeable value is dependent on the strategic planning of company.

2 P ≥0 Hard Constraint The minimum amount of “P” to be produced. Thi s changeable value is dependent on the strategic planning of company.

3 Q ≥0 Hard Constraint The minimum amount of “Q” to be produced. Thi s changeable value is dependent on the strategic planning of company.

4 Others ≥0 Hard Constraint The minimum amount of “Others” to be produce d. This changeable value is dependent on the strategic planning of company.

5 39*P +19*Q +27* Others ≤28,255,552 Hard Constraint Distribution of production cos ts related to the maximum company’s overhead of 28,255,552 USD/yr from Table 2. The values of 39, 27, and 19 represents the products unitary cost in USD/unit of products P, Q and Others r espectively.

6 8.29*P +2.58* Others +8.18*Q ≤1,910,000 Hard Constraint Distribution of emergy on produc ts related to the maximum company’s emergy demand of 1.91 E15 sej/yr from Table 3. The values of 8.29, 2.58 and 8.18 E14 sej/unit represents the unitary emergy demand of products P, Others and Q respectively (from Table 3).

7 0.9*P +1.2*Q +0.1*Others ≤715,715 Hard Constraint Distribution of CO 2emissions on products related to the maximum company’s CO 2 emissions of 715,715 kgCO 2eq./yr obtained through value-based in h/yr from Table 2 . The values of 0.9, 0.1, and 1.2 kgCO 2eq./unit represents the emission per product and they were assumed in this work due to lack of data.

8 39*P +19*Q +27*Others +n2–p2 =28,255,552 Soft Constraint Equation #5 added to unwanted de viations n2 and p2 9 8.29*P +8.18*Q +2.58*Others +n3– p3 =1,910,000 Soft Constraint Equation #6 added to unwanted deviations n3 and p3 10 0.9*P +1.2*Q +0.1*Others +n4–p4 =715,715 Soft Constraint Equation #7 added to unwanted devia tions n4 and p4 11 P +n5-p5 =1 Soft Constraint Amount of product “P” planned to be produced added to unwanted deviation n5 and p5. The changeable value of 1 unit of “P” is dependent on the st rategic planning of company.

12 Q +n6-p6 =1 Soft Constraint Amount of product “Q” planned to be produced added to unwanted deviation n6 and p6. The changeable value of 1 unit of “Q” is dependent on the st rategic planning of company.

13 Others +n7-p7 =1 Soft Constraint Amount of product “Others” planned to be pr oduced added to unwanted deviation n7 and p7. The changeable value of 1 unit of “Others” is depend ent on the strategic planning of company.

14 n2, p2, n3, p3, n4, p4, n5, p5, n6, p6, n7, p7 Deviation varia bles Unwanted deviation variables.

15 Min: n2 – p2 +n3 – p3 +n4 – p4 +n5 – p5 + n6 – p6 +n7 – p7 Objective function The objective function to be minimized.

a Final model is presented in Appendix 4.

and emissions) to obtain nal indicators to provide managers with sustainable-based information. After running the ABC sustainmodel, a plausible solution provided by GP is presented in the last column on Table 4.

The numbers indicate that the amount of product “P” should be approximately 203 thousand units, while product “Others” should receive lower priority with 87 thousand units. It is interesting to note that product “Q” should not be produced at all in order to allow for higher degrees of sustainability to be achieved by the company. Additionally, nal numbers from the ABC sustainis the same as those provided by the emergy perspective; this is a result of the modeling speci cities assu med in this work, however any change in the boundary conditions w ill induce to di erent results. According to the premises of this work, if the manager aims to increase the company’s degree of sustainability, the amou nt of products provided by the ABC sustainmust be respected; this is the main goal of this work. Interesting to note that ABC sustain provided di erent gures compared to the traditional ABC $, implying that whether the managers accept the indicators from the proposed ABC sustain, the reduction of monetary costs probably will not be maximized. This could a ect the company’s pro tability, since costs management is an important aspect as the amount of products sold and their market price. It is important to emphasize that, instead of a real case study, the goal of this work was to propose the ABC sustainsupported by all three di erent allocation drivers and a conceptual mode l of sustainability. Thus, the assumptions on primary data can be easily overcome when applying the proposed approach in a real case study with available data. For advances over this study, future e orts could be focused on considering addition al constraints in the proposed model, including company pro t, process capacities, market demand for products, “takt time,” and others. This could lead to an even more detailed and Frontiers in Energy Research | www.frontiersin.org 10May 2018 | Volume 6 | Article 36 Marinho Neto et al.Multicriteria Drivers for Activity-Based Costing generalized model to be applied in di erent production systems, however always respecting the conceptual model of sustainability as proposed in this work.

CONCLUSIONS The result of the ABC sustainprovides a mix of products considered as an optimized solution by the GP supporting a multi-criteria-based decision. Results indicate that produ cing 203 thousand units of product “P,” 87 thousand units of “Others” and zero of “Q” will lead to a higher degree of sustainability for the evaluated company. Rather than using exclusively economic drivers that lead to a company’s costs reduction and, consequently, pro t increase, the proposed change in the business as usual thinking respect the company’s budget desig ned for production and it also considers environmental aspects in its strategic planning. The goal is to reach economic growth based on sustainable principles, i.e., it is crucial maintain the health of natural capital while also recognizing the fundame ntal importance of economy. The inclusion of emergy drivers into the activity-based cos t method could represent an innovative business approach in allocating a company’s overheads to products. This is true since it supports a decision also based on a reduced emergy demand and, a priori, causing lower load on the natural environment by requesting a lower amount of energy and materials for the production processes. Using emergy as drive r comes to collaborate in a synergic manner with the already established approaches in allocating overheads under econom ic and environmental (i.e., emissions) perspectives. Establis hing a conceptual model of sustainability that embraces these thre e perspectives shown, at least theoretically, comes to be a more scienti c-based approach in supporting quantitative informat ion aligned with sustainable development. Thus, managers in cha rge of strategic decisions within companies can use this optimized tool and put it into practice in the production processes in order to reach a better balance (complying with the restricti ons modeled) among emergy, economic and emissions performance for companies.

AUTHOR CONTRIBUTIONS HM: General work organization and raw data obtainment.

FA: General work organization, ABC drivers calculation and discussions. CA: Emergy-based drivers obtaintion and discussions. BG: Economic and environmental drivers discussions. RM: Goal programming application and discussions.

ACKNOWLEDGMENTS The rst draft of this work was rst presented during the Bienn ial Workshop Advances in Energy Studies (BIWAES) held in Naples, Italy, September 2017. Authors are grateful for the nancial support from Paulista University (UNIP), CAPES Brazil via the Prosup Program, and CNPq Brazil (307422/2015-1). Thanks al so to José Hugo de Oliveira for the English language review, and fo r the valuable comments of the reviewers.

SUPPLEMENTARY MATERIAL The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.338 9/fenrg.

2018.00036/full#supplementary-material REFERENCES Agostinho, F., Sevegnani, F., Almeida, C. M. V. B., and Giannet ti, B. F.

(2016). Exploring the potentialities of emergy accounting in stud ying the limits to growth of urban systems. Ecol. Indic.doi: 10.1016/j.ecolind.2016.

05.007. Available online at: https://www.sciencedirect.com/sc ience/article/pii/ S1470160X16302400 Bagliani, M., and Martini, F. (2012). A joint implementation of ecological footprint methodology and cost accounting techniques for measuring environmental pressures at the company level. Ecol. Indic. 16, 148–156. doi: 10.1016/j.ecolind.2011.

09.001 Bastianoni, S., Coscieme, L., and Pulselli, F. M. (2016). The inpu t-state- output model and related indicators to investigate the relationsh ips among environment, society and economy. Ecol. Modell.325, 84–88.

doi: 10.1016/j.ecolmodel.2014.10.015 Bimonte, S., and Ulgiati, S. (2002). “Exploring biophysical approache s to develop environmental taxation tools. Envitax, to face the “new scarcity”,” in Economic Institutions and Environmental Policy , eds M. Franzini and A. Nicita (Aldershot, UK: Ashgate Publishing Limited), 177-200.

Brown, M. T. (2015). Emergy and form: accounting principles for recycle pathways. J. Environ. Account. Manag. 3, 259–274.

doi: 10.5890/JEAM.2015.09.005 Brundtland, G. H. (1987). Report of the World Commission on Environment and Development: Our Common Future . Available Online at http://www.un- documents.net/our- common- future.pdf. [Accessed 2nd October 2 017].Campbell, D. E. (2005). “Financial accounting methods to further d evelop and communicate environmental accounting using emergy,” in Emergy Synthesis 3, Theory and Applications of the Emergy Methodology , eds M. T. E. Brown, D. E. Bardi, V. Campbell, S. Comar, T. Huang, D. T. Rydberg, and S. Ulgiat i (Gainesville, FL: Center for Environmental Policy, University of Florida), 185–198.

Campbell, D. E. (2013). Keeping the books for the environment and soc iety: the uni cation of emergy and nancial accounting methods. J. Environ. Account.

Manag. 1, 25–41. doi: 10.5890/JEAM.2012.01.003 Charnes, A., and Cooper, W. W. (1977). Goal programming and multiple objective optimizations: part 1. Eur. J. Oper. Res.1, 39–54.

doi: 10.1016/S0377-2217(77)81007-2 Cooper, R. (1990). Implementing an activity-based cost system. J. Cost Manage.

Manufact. Ind. 4, 33–42.

Cooper, R., and Kaplan, R. S. (1988). Measure costs right: make the ri ght decisions.

Harv. Bus. Rev. 66, 96–103.

Ellis-Newman, J., and Robinson, P. (1998). The cost of library serv ices: activity- based costing in an Australian academic library. J. Acad. Librar.24, 373–379.

doi: 10.1016/S0099-1333(98)90074-X EPA (1995). United States Environmental Protection Agency. An Introduct ion to Environmental Accounting as a Business Management Tool: Key Concepts and Terms . EPA 742-R-95-001. Available online at: https://www.epa.gov/ sites/production/ les/2014- 01/documents/busmgt.pdf. (Acces sed 23rd January 2018).

Franz, E. H. (2001). Ecology, values, and policy. Bioscience51, 469–474.

doi: 10.1641/0006-3568(2001)051[0469:EVAP]2.0.CO;2 Frontiers in Energy Research | www.frontiersin.org 11May 2018 | Volume 6 | Article 36 Marinho Neto et al.Multicriteria Drivers for Activity-Based Costing Franz, E. H., and Campbell, D. E. (2005). “Vivantary responsibility andemergy accounting,” in Emergy Synthesis 3, Theory and Applications of the Emergy Methodology , eds M. T. E. Brown, D. E. Bardi, V. Campbell, S. Comar, T. Huang, D. T. Rydberg, and S. Ulgiati (Gainesville, FL: Center fo r Environmental Policy, University of Florida), 229–234.

Hanks, R. W., Weir, J. D., and Lunday, B. J. (2017). Robust goa l programming using di erent robustness echelons via norm-based and ellipsoidal uncerta inty sets.

Eur. J. Oper. Res. 262, 636–646. doi: 10.1016/j.ejor.2017.03.072 Hardin, G. (1968). The tragedy of the commons. Science162, 1243–1248.

doi: 10.1126/science.162.3859.1243 Huang, Z., Yu, H., Chu, X., and Peng, Z. (2017). A goal programming based model system for community energy plan. Energy134, 893–901.

doi: 10.1016/j.energy.2017.06.057 Kaplan, R. S., and Anderson, S. R. (2007). Time-Driven Activity-Based Costing:

a Simpler and More Powerful Path to Higher Pro ts . Brighton; Boston, MA:

Harvard Business School Press.

Kolosowski, M., and Chwastyk, P. (2014). Economic aspects of co mpany processes improvement. Proc. Engineer. 69, 222–230. doi: 10.1016/j.proeng.2014.02.225 Marler, R. T., and Arora, J. S. (2004). Survey of multi-objective opt imization methods for engineering. Struct. Multidiscip. Optimiz. 26, 369–395.

doi: 10.1007/s00158-003-0368-6 Odum, H. T. (1996). Environmental Accounting: Emergy and Environmental Decision-Making . New York, NY: John Wiley & Sons.

Ponisciakova, O., Gogolova, M., and Ivankova, K. (2015). Calc ulations in managerial accounting. Proc. Econ. Fin.26, 431–437.

doi: 10.1016/S2212-5671(15)00837-0 Pulselli, F. M., Coscieme, L., and Bastianoni, S. (2011). Ecosys tem services as a counterpart of emergy ows to ecosystems. Ecol. Modell.222, 2924–2928.

doi: 10.1016/j.ecolmodel.2011.04.022 Pulselli, F. M., Coscieme, L., Neri, L., Regolim, A., Sutton, P. C., L emmi, A., et al. (2015). The world economy in a cube: a more rational structural representation of sustainability. Glob. Environ. Change35, 41–51.

doi: 10.1016/j.gloenvcha.2015.08.002 Schulze, M., Seuring, S., and Ewering, C. (2012). Applying activit y-based costing in a supply chain environment. Int. J. Prod. Econ.135, 716–725.

doi: 10.1016/j.ijpe.2011.10.005 Thorton, D. B. (2013). Green accounting and green eyeshades twe nty years later.

Critic. Perspect. Account. 24, 438–442. doi: 10.1016/j.cpa.2013.02.004 Tsai, W., Chang, Y., Lin, S., Chen, H., and Chu, P. (2014). A gree n approach to the weight reduction of aircraft cabins. J. Air Transp. Manag.40, 65–77.

doi: 10.1016/j.jairtraman.2014.06.004 Tsai, W., Lee, K., Liu, J., Lin, H., Chou, Y., and Lin, S. (2012) . A mixed activity- based costing decisions model for green airline eet planning unde r the constraints of the European Union Trading Scheme. Energy39, 218–226.

doi: 10.1016/j.energy.2012.01.027 Tsai, W., Lin, T. W., and Chou, W. (2010). Integrating activit y-based costing and environmental cost accounting systems: a case study. Int. J. Bus. Syst. Res.4, 186–208. doi: 10.1504/IJBSR.2010.030774 Tsai, W., Tsaur, T., Chou, Y., Liu, J., Hsu, J., and Hsieh, C. ( 2015). Integrating the activity-based costing system and life-cycle assessment i nto green decision- making. Int. J. Prod. Res. 53, 451–456. doi: 10.1080/00207543.2014.951089 Ulgiati, S., Zucaro, A., and Franzese, P. P. (2009). “Emergy and a po licy of the commons,” in Emergy Synthesis 5, Theory and Applications of the Emergy Methodology , eds M. T. Brown, S. Sweeney, D. E. Campbell, S. Huang, E.

Ortega, T. Rydberg, D. Tilley, and S. Ulgiati (Gainesville, FL: Cent er for Environmental Policy, University of Florida), 1–14.

Yang, C., Lee, K., and Chen, H. (2016). Incorporating carbon foot print with activity-based costing constraints into sustainable pub lic transport infrastructure project decisions. J. Clean. Prod.132, 1154–1166.

doi: 10.1016/j.jclepro.2016.06.014 Zogra dou, E., Kostantinos, P., Petridis, N. E., and Arabatzis , G. (2017).

A nancial approach to renewable energy production in Greece using goal programming. Renewab. Energy108, 37–51. doi: 10.1016/j.renene.2017.

01.044 Con ict of Interest Statement: The authors declare that the research was conducted in the absence of any commercial or nancial relations hips that could be construed as a potential con ict of interest.

Copyright © 2018 Marinho Neto, Agostinho, Almeida, Moreno Garcí a and Giannetti. This is an open-access article distributed unde r the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) a nd the copyright owner are credited and that the original publication in this journ al is cited, in accordance with accepted academic practice. No use, distribution or re production is permitted which does not comply with these terms.

Frontiers in Energy Research | www.frontiersin.org 12May 2018 | Volume 6 | Article 36