Comparison of sustainable information technologies for companies

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1 *Correspondng author. Comparson of sustanable nformaton technologes for companes... Onur Kartal 1 and Aslı GülÖncel 2 * 1 NETAS Telecommuncaton Inc., Alemdag Caddes, No:171, Umranye, Istanbul, Turkey; 2 Department of Management, Galatasaray Unversty, 34357, Ortaköy, Istanbul, Turkey... Abstract Ensurng the dversty of energy technology and usng energy-effcent nformaton technology are the key factors of sustanable energy poltcs n busness. In the present study, we focus especally on choosng the best alternatve to mprove energy effcency n busness. In ths context, ths queston may be analyzed va a survey method. We compare energy effcency mprovement alternatves of computer use methods n companes by TOPSIS methodology, whch s one of the mult-crteron decson-makng technques. Keywords: nformaton technologes; sustanablty; TOPSIS; energy effcency; survey Receved 4 March 2013; revsed ; accepted 7 May INTRODUCTION Sustanable energy poltcs have many aspects. One of these aspects s about the knd of energy used: renewable or nonrenewable. Today, 85% of energy resources used n the world come from fossl fuels. The reserves n the ground are very lmted whle ther use grows sgnfcantly every year. In addton to ths scarcty problem, burnng of fossl fuels releases all manner of pollutants nto the ar wth dangerous effects on human health and nto greenhouse gases, whch threaten the envronment. The man negatve mpacts of combuston of fossl fuel are ar polluton and clmate change, along wth the major harm comng from the extracton and transport of ths knd of energy source. There s wdespread consensus that energy polcy plays a vtal role n potentally mtgatng the mpacts of global warmng and crss of energy avalablty. Wth ncreasng negatve effects of narrow dependence on fossl fuels on the envronment, and further depleton of a fnte supply, many countres have been forced to nqure nto and begn adaptng more envronmentally frendly energy alternatves. The fact that ths type of non-renewable fuels and the problems they cause on both human health and the envronment has brought the concept of renewable energy sources and energy effcency. Sustanable energy poltcs plays a great role n the development of envronmentprotectng countres. When consderng a country, ts level of development n terms of energy can be examned by two key ndcators: one s energy consumpton per capta and the other energy effcency. Today, n our world the demand for energy s ncreasng. Dversfyng energy supples, ncreasng energy effcency n the regonal and global feld, ensurng the dversty of energy technology, addng renewable sources to the energy supply system, protectng the envronment and publc health n the producton of energy, takng nto account consumers accessblty to energy n terms of cost and tme, and mplementng measures for energy effcency are some of the measures for sustanable energy poltcs of countres and also for companes. In the context of ths paper, when we especally focus on sustanable nformaton technology (IT), ensurng the dversty of energy technology s the key factor. In ths present study, we frstly ntroduce basc computer applcaton alternatves for mprovng energy effcency n busness. Secondly, we present TOPSIS method, whch s a mult-crteron decson-makng technque. Then, we realze our analyss n the am to choosng the best alternatve to mprove energy effcency n busness. Ths queston may be analyzed va survey method. Fnally, we gve our results n the last part of our study and gve our remarks for further research. 2 ENERGY EFFICIENCY IN BUSINESS In our world, because of the ncreasng energy costs and greenhouse gas emssons produced by the ncreasng usage of the nformaton and communcaton technologes, there s an urgent demand for energy-effcent technologes [1]. Usng these technologes, a decrease n the overall energy costs, consumpton of Internatonal Journal of Low-Carbon Technologes 2015, 10, # The Author Publshed by Oxford Unversty Press. Ths s an Open Access artcle dstrbuted under the terms of the Creatve Commons Attrbuton Non-Commercal Lcense ( whch permts non-commercal re-use, dstrbuton, and reproducton n any medum, provded the orgnal work s properly cted. For commercal re-use, please contact journals.permssons@oup.com do: /jlct/ctt047 Advance Access Publcaton 17 July Downloaded from

2 Comparson of sustanable nformaton technologes computaton, storage and communcatons s expected. That s why energy effcency n the future nformaton and communcaton technologes s consdered to be ncreasngly mportant. In recent years, many companes are tryng to nvolve sustanable IT by mplementng sustanable technologes to make ther busnesses cost-effectve and sustanable. Companes are under ncreasng pressure from customers and shareholders to make a sustanable busness. The development of nformaton and communcaton technology (ICT)-based busnesses and socal practces has transformed most of the busnesses nto e-busnesses. On the other hand, global warmng and clmate change wth lmted energy reserves and rsng cost of energy are posng serous challenges for the sustanablty n busness. Data centers offer to a company a large varety of servces such as Internet, e-commerce, socal networkng, and more general servces such as software as a servce, Internet as a servce, platform as a servce, and grd and cloud computng [2]. Huge amount of computaton power s requred to provde these large systems. Ths wll result n emssons of greenhouse gases causng global warmng and clmate change. For all these reasons, the energy use and envronmental mpact of data centers has recently become an mportant ssue for companes. The servers consume a lot of energy and emt greenhouse gases lke CO 2. In Fgure 1, thelargepercentageofco 2 emssons, nearly 40% of the total emssons, produced by personal computers and montors are shown. Second huge part, 23% of total emssons belong to the servers wth coolng. It s estmated that energy consumpton and carbon emssons wll contnue to ncrease n the future [3]. Ths estmaton realzed by SMART 2020 study estmates also that CO 2 emssons from ICT wll ncrease at a rate of 6% per year and wll represent 12% of worldwde emssons by The envronment s affected by IT n dfferent ways. Ths effect occurs from the begnnng of a computer s producton untl t becomes a waste. Electrcty, raw materals, and chemcals are consumed by computers, and the harmful waste s produced at the last stage of a computer s lfe cycle. Whole ssues durng ths cycle provde many envronmental problems. Furthermore, the ncrease n energy consumpton results n ncreased greenhouse gas emssons as most of the electrcty s generated by burnng coal, ol, or gas. Old computers, whch contan toxc materals, are also an mportant resource of polluton. Powerful meda attenton has ncreased the awareness of people around the world for clmate change and greenhouse gas effect on global warmng. The data centers not only consume enormous energy but also ncrease the budget of electrcty consumpton of the company. There exsts a large feld of nterest about the electrcty used for ITequpment snce the frst Energy Star descrpton for personal computers was publshed [4]. Accordng to Gartner, f energy costs contnue to double every fve years, they wll consderably ncrease to 1600% between 2005 and 2025 [5]. On the other sde, lke the energy costs, energy use n data centers s also doublng every fve years [6]. Snce recent years, for companes t becomes urgent to develop envronmentally sustanable IT, from both an economc and envronmental vewpont. For ths reason, usng energy effcently can help the company control the energy costs and preserve the envronment. Energy effcency s the use of technology that requres less energy to perform the same functon. In ths context, energy sustanablty takes a great part of the energy effcency. The sustanablty focuses on long-term energy polces. The am s to ensure sutable energy to meet today s needs, as well as tomorrow s. Sustanablty ncludes research nvestment and development of envronmental technologes. Sustanablty n busness proposes major advantages and benefts as mentoned below: It reduces IT mantenance actvtes and costs; It reduces companes overall energy costs; It reduces the emsson of CO 2, whch s the man factor of greenhouse gas emssons; It reduces global clmate change effects; It reduces overall carbon footprnts. Ensurng the sustanablty n busness may be created by dfferent low-carbon technologes used on IT systems. In ths study, we frstly ntroduce basc computer applcaton alternatves for mprovng energy effcency n busness. Those alternatves are as follows: (1) common use of computng resources to provde lowerenergy savng computers (cloud computng), (2) reducng the number of servers by vrtualzed server, (3) company computers replaced wth energy-effcent components, (4) usng automatc desktop hard dsk backup system. Fgure 1. Estmated ICT CO 2 emssons. Cloud computng s a style of computng n whch scalable and elastc IT-enabled capabltes are delvered as a servce usng Internet technologes [7]. Ths technology uses the Internet and central remote servers to mantan data and applcatons. Cloud computng allows consumers and busnesses to use applcatons wthout nstallaton and access ther personal fles at any computer wth Internet access [8]. Any transactons by cloud computng users are not carred out on ther own computers but Internatonal Journal of Low-Carbon Technologes 2015, 10, Downloaded from

3 O. Kartal and A.G. Öncel from cloud computer servce provders. By ths fact, ths cloud computng users are not necessarly hgh-performance computers. Only cloud-performance computer used to access the Internet access s suffcent to run programs. Thus, energy s saved as lower-energy-consumng computers are realzed by performng operatons usng cloud computng. The second alternatve of our study s reducng the number of servers by vrtualzed server. Companes have been buyng separate server for transactons such e-mal and data storage. The use of vrtualzed servers for each transacton elmnates the need for a separate server. A sngle server acts as several servers wth the use of vrtual machnes on a sngle server. Thus, by reducng the number of servers, savngs on the energy used by servers, coolng energy consumed by servers and the purchase cost can be accomplshed [9]. The thrd alternatve s replacng company computers wth energy-effcent components. The energy effcency of components of computers s becomng more and more sgnfcant. Today, wth the development of technology as well as better performance, less energy-consumng processors are beng developed. By ths way, energy effcency s provded by changng the parts of exstng computers. The development of effcent components s a former charge of supplers [10]. Usng automatc desktop hard dsk backup system s the fourth alternatve. When employees leave the company f they don t turn off ther computer. To prevent ths waste of energy, ths alternatve lead to automatcally save the work on the computer. In ths study, we compare these four alternatves by TOPSIS methodology, whch s one of the mult-crteron decson-makng technques. By takng nto account the qualtatve and quanttatve nformaton obtaned from the results of our ntervews wth the specalsts of the subject, we tred to choose the best alternatve for the best energy-effcent technology n computer usage. 3 METHOD The mult-crteron decson-makng (MCDM) problems are wdespread n the feld of the theory of the decson as mentoned by Trantaphyllou [11]. Accordng to Hwang and Yoon, the problems of MCDM are commonly categorzed nto two groups, multple attrbute decson-makng (MADM) and multple objectfy decson-makng (MODM) [12]. MADM, defned as a technque of assstance, has the decson to evaluate and choose the alternatves that are characterzed wth several attrbutes of crtera. In ths study, we have chosen TOPSIS, whch s one of the methods of MADM developed by Hwang and Yoon [13]. Although the other methods have many advantages, TOPSIS s the best method for our study snce t has an approprate structure decreasng the response tme for the nformaton obtaned from the experts who contrbuted to our research. TOPSIS s based on the prncple where the chosen alternatve should be the one that s the closest to deal alternatve and the furthest from the negatve-deal alternatve explaned by Hung-Chang [14]. TOPSIS uses the followng sx steps: (1) Standardzaton of the data: the standardzaton of vector s employed to calculate the normal data: x j P m ¼1 x2 j r j ¼ qffffffffffffffffffffffffffffff ¼ 1; 2;...m; j ¼ 1; 2;...n; ð1þ where x j ndcates the effectve output of the th alternatve wth regard to jth crteron. (2) Calculaton of the weghed normal data: the weghted normal data are calculated as follows: v j ¼ w j r j ¼ 1; 2;...m; j ¼ 1; 2;...n; ð2þ where w j s the weght of jth crteron. (3) Determnaton of the deal and ant-deal solutons: the deal soluton (A*) and the ant-deal soluton (A 2 )are defned n terms of weghed normal values as follows: A ¼ ðmax v j j j [ JÞ; ðmn v j j j [ J 0 Þ; ¼ 1; 2;...m:g ¼fv j ; j ¼ 1; 2;...; ng A ¼ ðmn v j j j [ JÞ; ðmax v j j j [ J 0 Þ; ¼ 1; 2;...m:g ¼fv j ; j ¼ 1; 2;...; ng where j s the whole of crtera of proft and s the whole of crtera of cost. (4) Calculaton of measurements of dstance: the Eucldean dmensonal dstance of n can measure the dstance between the alternatve solutons. The dstance from each alternatve deal and ant-deal soluton s then ndcated by: vffffffffffffffffffffffffffffffffffffffffffffffffffffffffff X n D u ¼ t ðv j v j Þ 2 ; ¼ 1; 2;...; m; D j¼1 vffffffffffffffffffffffffffffffffffffffffffffffffffffffffffff ux n ¼ t ðv j v j Þ 2 ; ¼ 1; 2;...; m: j¼1 (5) Calculaton of the proxmty to the deal soluton: D ð3þ ð4þ C ¼ D þ D ; ¼ 1; 2;...; m; ð5þ (6) where C ndcates the proxmty of the th alternatve to the deal soluton. 0 C 1, where C ¼ 0whenA ¼ A and C ¼ 1whenA ¼ A Determnaton of the order of preference: the alternatve solutons are arranged n descendng order. The type of data s obtaned and formed from the responses gven by the experts to the questons of our survey questonnare. 376 Internatonal Journal of Low-Carbon Technologes 2015, 10, Downloaded from

4 Comparson of sustanable nformaton technologes These experts are from Netaş nformaton and telecommuncaton solutons company. In our study, frst of all, we determned the sample sze of ntervew by the followng formula: n ¼ z 2 N P Q ðn D 2 þ Z 2 P QÞ ; where Z, confdence level for %95; N, total number of populaton,.e. 600 engneers; P, the probablty of searchng attrbute. As our study s mult-purpose, we take t as %50; Q ¼ 1 2 P; D ¼ %10 of sample error. Table 1. Types of the crtera Man crtera Economcal (C1) Techncal (C2) Envronmental (C3) Socal (C4) Table 2. Results concernng the degrees of mportance of the crtera Crtera Sub-crtera C C C C ð6þ Investment cost (SC11) Management and mantenance costs (SC12) Return perod (SC13) Annual cost mpact (SC14) Impact on energy consumpton cost (SC15) Securty (SC21) System sustanablty (SC22) Improvng system mantenance and establshment (SC23) Impact on CO2 emsson reducton (SC31) Impact on nose reducton (SC32) Impact on reducton of physcal area usng by energy systems (SC33) User-frendlness (SC41) Impact on nformaton share speed (SC42) Impact on reducton of negatve externaltes (SC43) Table 3. Results of the degrees of mportance of the crtera Sub-crtera SC SC SC SC SC SC SC SC SC SC SC SC SC SC Degrees of mportance Degrees of mportance Dependngtothsformula,wefoundthesampleszeasn ¼ RESULTS The comparson of these computer systems depends on many crtera. Hence, we have determned four man crtera n the frame of ths study. These are economc, techncal, envronmental, and socal crtera. Each crteron has fourteen sub-crtera and they are shown n Table 1. After ths step, we converted the answers of the surveys from the qualtatve form to the quanttatve form. Dependng on the TOPSIS, we found the degrees of mportance of the man crtera by takng the average of the gven responses. The values from 1 to 5 were taken as answers: 1 for the answer much less mportant, 2 for less mportant, 3 for qute mportant, 4 for mportant, and 5 for very mportant. Usng these data, we formed Table 2. Inthesameway,wegotthedegreesofmportanceofthesubcrtera dependng on the man crtera shown n Table 3.Then,we used the steps of the TOPSIS method and obtaned the deal and non-deal solutons for each sub-crteron, Table 4. Table 5 shows the rankng of the possble alternatves for mprovng energy effcency n busness. In the next part, we gve results of our analyss. Table 4. Results of the deal and non-deal solutons Sub-crtera Ideal soluton Non-deal soluton SC SC SC SC SC SC SC SC SC SC SC SC SC SC Table 5. Rankng of the possble alternatves Cloud computng Reducng the number of servers by vrtualzed server Energy-effcent components Automatc desktop hard dsk regstraton system Ideal dstance Ant-deal dstance Proxmty to the deal soluton Rankng Internatonal Journal of Low-Carbon Technologes 2015, 10, Downloaded from

5 O. Kartal and A.G. Öncel In the next step, we calculated the deal and non-deal solutons for each sub-crteron, Table 4. The rankng of the possble alternatves for mprovng energy effcency n busness s gven n Table 5. 5 CONCLUSION In ths study, we focused on the basc computer applcaton alternatves for mprovng energy effcency n busness. We consdered four alternatves, whch can reduce energy usage and mprove the sustanablty n companes: cloud computng; reducng the number of servers by vrtualzed server; energy-effcent components; and automatc desktop hard dsk backup system. We compared these four alternatves usng a MADM method, TOPSIS. The data were collected from the survey results. The answers of the NETAŞ company engneers were evaluated. The automatc desktop hard dsk backup system gave the best result so that t s consdered as the frst n the rankng of four alternatves. For the sustanable development of countres and companes, energy use plays a great role. The results obtaned from the data used n ths study show that automatc desktop hard dsk backup system gave the best results compared wth other alternatves n the doman of computer applcatons for energy effcency. ACKNOWLEDGEMENT The authors acknowledge all experts n NETAŞ company, who flled out the questonnare and Galatasaray Unversty Research Foundaton for the support. REFERENCES [1] Berl A, De Meer H. An energy consumpton model for vrtualzed offce envronments. Future Gener Comp Sy 2011;27: [2] Loper J, Parr S. Energy effcency n data centers: a new polcy fronter. Envron Qual Manag 2007;16: [3] SMART 2020 report (February 2013, date last accessed). [4] Johnson B, Catherne J, Zo R. EPA Energy Star computers: the next generaton of offce equpment. In: Proceedngs of the ACEEE Summer Study on Energy Effcency n Buldngs, p [5] Gartner. Gong Green: the CIO s Role n Enterprse Wde Envronmental Sustanablty. Gartner EXP premer, [6] Kumar R. Meda relatons. Gartner, (September 2012, date last accessed). [7] Gartner glossary (February 2013, date last accessed). [8] (19 February 2012, date last accessed). [9] Dasgupta G, Sharma A, Verma A, et al. Workload management for power effcency n vrtualzed data centers. Commun ACM 2011;54:7. [10] Neugebauer R, Wabner M, Rentzsch H, et al. Structure prncples of energy effcent machne tools. CIRP J Manuf Sc Tech 2011;4: [11] Trantaphyllou E. Mult-crtera Decson Makng Methods: A Comparatve Study. Kluwer Academc Publsher, [12] Yoon K, Hwang CL. Multple Attrbute Decson Makng: An ntroducton. Sage, [13] Hwang CL, Yoon K. Multple Attrbute Decson Makng: Methods and Applcatons. Sprnger Verlag, [14] Hung-Chang L. Usng PCR-TOPSIS to optmze Taguch s mult-response problem. Int J Adv Manuf Technol 2003;22: Internatonal Journal of Low-Carbon Technologes 2015, 10, Downloaded from