IS solutions – A life cycle impact modelling approach

Environmental Modelling & Software xxx (2014) 1e11

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Measuring the environmental impact of IT/IS solutions e A life cycle impact modelling approachq Florian Stiel*, Frank Teuteberg Osnabrück University, Research Group Accounting and Information Systems, Katharinenstraße 1, 49069 Osnabrück, Germany

a r t i c l e i n f o

a b s t r a c t

Article history: Received 22 May 2013 Received in revised form 18 December 2013 Accepted 19 December 2013 Available online xxx

The academic community has already taken notice of the interactions between information technologies (IT), information systems (IS), business organizations and the environment. Despite the interest garnered, research and modelling approaches on the environmental impact of IT/IS are usually explored only through qualitative approaches. This paper introduces a way for researchers and practitioners to engage with the environmental impact of IT/IS solutions in a more quantitative manner using flow based life cycle assessments (LCA). Distinct from other life cycle assessment studies, this research paper confirms that integration of information flows within life cycle inventory analysis can be both useful and viable. Our work presents a conceptual framework for flow-based LCA within the context of IT/IS consisting of possibilities for defining functional units, a meta model for building symbiotic inventory models, the use of established software tools and databases as well as concrete actions to apply our framework within simulation studies. We hope that better knowledge of the environmental impact of IT/ IS solutions will facilitate an effort for more sustainable solutions. The framework was derived by literature review, design science research and evaluated via a simulation. Ó 2014 Elsevier Ltd. All rights reserved.

Keywords: Life cycle assessment Information technology Information systems Life cycle inventory analysis Conceptual framework Design science Symbiotic modelling

1. Introduction Throughout the last two decades, intensive research has been performed on the interaction of information technologies and the environment. Jenkin et al. (2011) identify multiple driving forces for organizations to implement environmental strategies, such as ecological (e.g. rate of resource renewal), organizational (e.g. employee stewardship), political (e.g. laws), socio-cultural (e.g. norms), and economic drivers (e.g. customer demands). These drivers lead to environmental strategies, technologies and systems and pave the way for behavioural changes as well as a more sustainable way of thinking. The impact associated with IT/IS is often characterized by two phenomena: the energy and resource consumption caused by the use of these systems, and the huge potential to improve business processes in order to reduce environmental impacts (Vom Brocke et al., 2012; Elliot, 2011; Hilty et al., 2006; Watson et al., 2012a; Yi and Thomas, 2007). Today first, second and third order effects are distinguished in order to categorize the environmental impact of IT/IS (Dompke et al., 2004; Hilty

q Thematic Issue on the Sustainability of Smart Solutions. * Corresponding author. E-mail addresses: fl[email protected] (F. Stiel), frank.teuteberg@ uni-osnabrueck.de (F. Teuteberg).

and Lohmann, 2013). Already in 2006, first approaches for a systematic and extensive assessment of all three kinds of environmental effects were introduced (Hilty et al., 2006). The results suggest that the downsides of IS typically correspond with the physical presence of the technology, e.g. by energy and resource consumptions in the first order, while the benefits of IS, such as contribution to the increase of efficiency or transparency, only appear in the second order (Yi and Thomas, 2007). Due to its scientific maturity, Life cycle assessment (LCA) is a frequently mentioned methodology to assess first and second order effects of various technologies (Melville, 2010; Nidumolu et al., 2009). Yi and Thomas (2007) consider LCA to be the most common, favourable and reliable methodology to assess the physical impact of IT/IS. A striking research gap for the environmental assessment of IT/ IS can be identified by reviewing the works of Jenkin et al. (2011), Yi and Thomas (2007) and Watson et al. (2012b): Most research on the environmental impact of IT/IS remains either incomprehensible, i.e. addressing just the physical IT infrastructure, or qualitative, i.e. addressing first, second and third order effects without quantitative measures. Current research suffers from a lack of flow network based “symbiotic physical and informational modelling and simulation” (Watson et al., 2012b). To bridge the gap between physical and informational systems, we develop a conceptual framework for symbiotic flow system based life cycle assessments. Thereby we try to answer the following research question:

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Please cite this article in press as: Stiel, F., Teuteberg, F., Measuring the environmental impact of IT/IS solutions e A life cycle impact modelling approach, Environmental Modelling & Software (2014), http://dx.doi.org/10.1016/j.envsoft.2013.12.014

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Is it useful and feasible to apply life cycle assessment for environmental impact assessment of symbiotic physical and informational systems? To answer the research question, widely accepted information systems research methods are applied. The paper builds upon a systematic literature review (Vom Brocke et al., 2009; Fettke, 2006; Webster and Watson, 2002) within the field of LCA in the context of IT/IS in section 2. In section 3, the design science approach (Hevner et al., 2004; Österle and Otto, 2010) will be introduced, explaining how the results of this work are derived. The conceptual framework is outlined in section 4. We evaluate the framework by conducting a life cycle assessment of an information distribution system based on empirical data and use the established LCA modelling and simulation tool Umberto which is based on flow modelling (cf. section 5). Conclusions, limitations of our research as well as forthcoming work and open research questions are addressed in section 6. 2. Status quo Many arguments have been put forward describing LCA as a preferred approach to determine the environmental impact of IT/IS (Melville, 2010; Nidumolu et al., 2009; Yi and Thomas, 2007). Therefore, we start our research with a brief description of the most important aspects of LCA. Following the international organisation for standardization, LCA is a method of “compilation and evaluation of the inputs, outputs and the potential environmental impacts of a product system throughout its life cycle” (ISO, 2006a). Principles of the LCA methodology are the environmental life cycle perspective (from cradle to grave), the relative approach (referring to a functional unit), an iterative scientific approach as well as a transparent and comprehensive proceeding. According to the ISO standard 14040, the consistency of a LCA with these principles needs to be reviewed to enhance its credibility (ISO, 2006a). Besides the requirements determined by the ISO standard, the topic of comparability was discussed by Emblemsvåg and Bras (1999). Even though comparability of the LCA’s results is not crucial for its methodical correctness, it is essential to ensure its recognition within a scientific debate as well as in business context (e.g. for benchmarking purposes). The framework introduced in the ISO standard 14040, structures LCA into four phases: (1) definition of goal and scope, (2) inventory analysis, (3) impact assessment and (4) interpretation (ISO, 2006a). Finnveden et al. (2009) and the ISO (2006) underline the importance of the first of the four phases to set methodologies and the choice of data during the other phases. The choice of a functional unit and system boundaries to define the scope of the LCA has a significant influence on the consistency with the mentioned principles (Guinée et al., 2002). The definition of the functional unit also influences comparability of alternative solutions to fulfil the same functional demand, e.g. paper versus email information distribution (Bousquin et al., 2012; Emblemsvåg and Bras, 1999). Moreover, different approaches for the definition of system boundaries (Finnveden et al., 2009), such as cradle-to-gate or gate-to-gate analysis (Jiménez-González et al., 2000) and cradle-to-grave (FullLCA) (ISO, 2006a), lead to incomparable results between the derived environmental impact data (Emblemsvåg and Bras, 1999). The second phase inventory analysis focuses on the understanding of the system under study. Data for the quantification of the system is collected, the system is modelled and the inputs and outputs of the system are calculated (ISO, 2006a). The ISO standard focused primarily on the understanding of the physical product system. However, Watson et al. (2012b) suggests symbiotic physical and informational models in order to identify environmental impact

of IT/IS. To look into this issue more closely, we applied a systematic literature review (Vom Brocke et al., 2009; Fettke, 2006; Webster and Watson, 2002). The review was applied in order to identify existing works containing quantitative environmental impact determination of products or services in general and of IT/IS in particular. We tried to determine how LCA researchers considered information flows, IT and IS within their approaches. The organisation of our review is concept-centric (Webster and Watson, 2002), aiming for an integration of successful and promising approaches into one conceptual framework. Vom Brocke et al. (2009) consider encyclopedias and handbooks as appropriate sources to determine concepts within a literature review. We choose two handbooks on LCA to develop the concepts for our literature review: the handbooks of Guinée et al. (2002) and Klöpffer and Grahl (2009), both written by scientists with extensive expertise in the field of LCA. All publications were examined with regard to the following concepts:  Assessed industry sectors: Which processes or product systems are assessed? Which industry sectors are affected (e.g. logistics and transportation, agriculture and food, information and communication technology (ICT) and electrical components)?  Research methodology: Are methodologies applied to contrast or to support LCA or to enrich results? Are meta-studies applied to summarize LCA results regarding a special product or process? Are Monte-Carlo simulations, expert interviews or sensitivity analyses applied to evaluate results? Are individual cases or different scenarios analysed? Is LCA used to design generalized models?  Data sources: Which data sources are used to perform life cycle inventory modelling? Are life cycle databases (e.g. ecoinvent) applied? Is generic data (e.g. literature values) or specific data (e.g. measured data, data from expert interviews) used to conduct the LCA?  Software and simulation tools: Which software is used to develop life cycle inventory models, to perform life cycle impact assessment or to run simulations? Publications containing the assessment of IT/IS related processes and product systems were analysed in more detail. Sub concepts for the detailed examination of IT/IS related LCA publications include:  Comparative and scenario approaches: Was the LCA performed to compare two systems or to assess different scenarios?  Functional unit: What was the functional unit of the LCA study? How was the function of IT/IS expressed?  System boundaries: What are the system boundaries of the LCA?  Impact categories: How is the environmental impact categorized? How many impact categories are addressed?  Evaluation approach: Are the results proofed by evaluation? What are the methods used for evaluation? Publications were identified using the literature search process introduced by Vom Brocke et al. (2009) covering three search steps: journal search, database search and keyword search. For identification of relevant journals widely accepted journal rankings have been used. Within the field of information systems, the VHB ranking1 as well as the AIS ranking2 are the most common and widely accepted journal rankings with a strong focus on scientific

1 Journal ranking of the German Academic Association for Business Research (VHB), available at http://www.vhbonline.org/. 2 Journal ranking of the Association for Information Systems, available at http:// www.aisnet.org/.

Please cite this article in press as: Stiel, F., Teuteberg, F., Measuring the environmental impact of IT/IS solutions e A life cycle impact modelling approach, Environmental Modelling & Software (2014), http://dx.doi.org/10.1016/j.envsoft.2013.12.014

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quality. However, the AIS ranking tends more to journals covering behavioural science approaches whereas the VHB ranking also includes journals covering engineering and design science approaches. Therefore, we applied the VHB ranking to identify the relevant journals. To ensure scientific quality and impact, only journals rated AeC from the partial ranking for production and environmental management were included within the initial literature review. In the second step, databases providing access to these journals have to be identified (Vom Brocke et al., 2009). Most of the journals we reviewed appear within the databases ScienceDirect and ISI Web of knowledge. In the case of missing journals, the Google Scholar search engine was queried. The third search step covers the identification of keywords. A set of search terms is recommended (Vom Brocke et al., 2009; Rowley and Slack, 2004; Webster and Watson, 2002). Rowley and Slack (2004) propose that researchers initially use sets of precise terms. Therefore, in order to obtain a broad overview of the research on LCA, we started querying the databases with the search term “life cycle assessment” within the abstract, title or keywords of recent publications. The initial search process yielded 98 papers within 5 journals. The number of results by publishing journals is presented in Table 1. The complete list of papers is accessible online via http://bit.ly/13AXt1f. Fig. 1 depicts an increase of 88% from 2009 to 2013 of publications on LCA in the first stage. The literature review was conducted in February 2013 and encompasses all papers published until the first of February 2013. Therefore, publications of 2013 are not completely included. All 98 papers were skim read and checked for the main concepts: assessed processes or product systems, research methodology as well as data sources software and simulation tools. Fig. 2 shows the results of the analysis on the assessed industry sectors. In the 25 papers in which LCAs are conducted, the sector of agriculture and food production constitutes the biggest share of all identified publications e.g. milk production (Bartl et al., 2011) or production of crops (Cellura et al., 2012; Iriarte et al., 2010). The ICT and electrical components sector, e.g. LCA in online retailing (Edwards et al., 2010) or semiconductor manufacturing (Liu et al., 2010), is only represented in five papers. These data show that LCA is widely used within the agriculture & food as well as in the energy & power generation, disposal & recycling and material & chemical processing sector, whereas LCA is rarely used within the ICT & electrical components sector. It is therefore necessary to improve the conceptual and methodological foundation for LCA in the field of IT/IS in order to facilitate further investigations. Methodologies associated with LCA are scenario analysis (33 papers, e.g. (Carpenter et al., 2012; Moberg et al., 2005; Rigamonti et al., 2010)), Monte-Carlo simulation (18 papers), sensitivity analysis (21 papers) and meta-analysis (9 papers). Methodology for the 42 papers includes physical flow modelling, e.g. using material and energy flows (Xie et al., 2011), mass flows (Ziegler et al., 2013) and carbon flows (Levasseur et al., 2013). The most widely used physical flow models in this context are those based on material and energy flow systems. Therefore, a central requirement for the Table 1 Number of search results by journal. Journal Ecological Economics International Journal of Physical Distribution and Logistics Management Journal of Environmental Economics and Management Journal of Cleaner Production Journal of Industrial Ecology Total

Relevant papers 8 1 1 57 32 98

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development of the conceptual framework in this paper was to integrate material and energy flows in order to describe the physical part of the symbiotic systems. Main data sources for the quantification of physical flows within recent publications are measured data and company information as well as life cycle databases. The ecoinvent database, as a source of life cycle inventory data, is mentioned in 52 papers. The Gabi (10 papers) and IDEMAT (5 papers) databases are less frequently used. Moreover, the authors of all papers gather additional generic data from the literature. Software and simulation tools are applied in 55 papers, with Simapro being the most common tool (41 papers). Other software tools used within LCA research are GaBi (10 papers), Umberto (2 papers), TEAM and OpenLCA (1 paper). All of these tools use flow models in order to describe physical systems. The tools are therefore basically capable to support the physical part of symbiotic flow system based life cycle assessment. However, it is not clear from the literature whether or not they are capable to depict informational flows. For the detailed review on IT/IS related LCA publications the literature search was further specified. Rowley and Slack (2004) propose to subsequently relate specific search terms by Boolean operators (AND, NOT, OR). Following this proposal, we queried the online databases ScienceDirect, Google Scholar and ISI Web of Knowledge with keywords relating “life cycle assessment” with IT/ IS specific phrases such as “IT infrastructure”, “IS solution”, “ecommerce” using the Boolean operator AND. The detailed keyword search revealed 12 publications that were analysed according to the sub concepts and are depicted in Table 2. The publication dates indicate that there has been a growing interest in the environmental impacts of IT/IS within the last years. However, methodological divergence makes comparability and transparency impossible, thus limiting the use of the results in further research (e.g. further LCA studies). The publications show significant varieties in the definition of the functional units. The use of information flows within inventory analysis or the characterization of a product by informational values were applied by Moberg et al. (2010), Boyd et al. (2009) and Taylor and Koomey (2008). Here, physical products (e.g. book, music album, item, wafer) are primarily chosen to quantify the performance of the IT/ IS. This solution eases the use of LCA tools and improves comparability with other similar physical products. However, neglecting a precise informational quantification of a flow or product also results in a lack of transparency and comparability between the different IT/IS studies. The defined system boundaries vary between cradle-to-grave, cradle-to-gate and gate-to-gate approaches. Sometimes single processes or life cycle stages are excluded, which reduces the comparability of the results and impedes transparent verification. The differences regarding impact categories varying between single carbon footprints and full-LCA also contributes to a limited comparability and transparency. The fact that one publication classifies the results to other LCA studies for evaluation supports the finding of a limited comparability between the studies. Often, Monte Carlo simulation and sensitivity analysis are the main evaluation methods. To improve the approach of LCA to determine the environmental impact of IT/IS, we will now introduce a conceptual framework to strengthen LCA studies within the initial stage of goal and scope definition and inventory analysis. It should guide authors to improve transparency and comparability of the results to advance knowledge of the environmental impact of IT/IS. 3. Methodology The development of a conceptual framework for symbiotic flow system based life cycle assessments refers to the design science

Please cite this article in press as: Stiel, F., Teuteberg, F., Measuring the environmental impact of IT/IS solutions e A life cycle impact modelling approach, Environmental Modelling & Software (2014), http://dx.doi.org/10.1016/j.envsoft.2013.12.014

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Fig. 1. Number of search results by year of publication.

Fig. 2. Assessed industry sectors.

research approach. Design science research significantly differs from other scientific approaches, such as theory testing or interpretative research (Peffers et al., 2007). The research output of design science are things, i.e. artefacts, built to serve human purpose (March and Smith, 1995). Hevner et al. (2004) introduce seven guidelines for researcher to design and evaluate artefacts. Their work found tremendous response within the scientific community and is already cited more than 4000 times.3 Österle and Otto (2010) applied the results of Hevner et al. (2004) to their own research process by balancing instantiations of their own work to the seven guidelines. In Table 3, we provide a similar juxtaposition of the guidelines and the instantiations of our research. The design process encompasses building and evaluation of the artefact (March and Smith, 1995). In the first stage of this research,

3

Citations estimated using http://scholar.google.de/.

the conceptual framework for symbiotic flow system based life cycle assessments is derived from literature. In the second stage, the framework will be evaluated by means of a simulation based literature data. 4. Conceptual framework design As derived in the status quo section, the divergent LCA methodologies used in recent work neglect precise quantification of the information flows of IT/IS solutions. Also, a symbiotic modelling of informational and physical flows within inventory analysis is uncommon. To develop informational, quantified functional units and apply symbiotic physical and informational models within the phase of inventory analysis, a conceptual framework for the definition of the functional unit and the inventory analysis is introduced to guide researchers and practitioners. The huge variety of functional units in recent work points to the underlying difficulties in finding an appropriate, comprehensive

Please cite this article in press as: Stiel, F., Teuteberg, F., Measuring the environmental impact of IT/IS solutions e A life cycle impact modelling approach, Environmental Modelling & Software (2014), http://dx.doi.org/10.1016/j.envsoft.2013.12.014

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Table 2 LCA literature on ICT and information systems. Object description & reference

Comparative approach or scenarios

Functional unit

System boundaries

Impact Categories

Evaluation approach

Internet advertising (Taylor and Koomey, 2008) Computational logic (Boyd et al., 2009)

No

Gate-to-gate use phase

2

Sensitivity analysis

No

Million impression distributions (44 kB per impression) MIPS

2

Uncertainty assessment

Yes

One music album delivery

Cradle-to-gate without end of life Gate-to-gate

2

Monte Carlo simulation

No

Average device, transistors, chip area 8 inch wafer Newspaper distribution for one year

Gate-to-gate

Full-LCA

None

Cradle-to-grave Cradle-to-grave

Full-LCA Full-LCA

Six music delivery methods (Weber et al., 2009) Computational logic during the last 15 years (Boyd et al., 2010) RAM production (Liu et al., 2010) Printed and tablet e-paper (Moberg et al., 2010)

Conventional vs. online retailing (Edwards et al., 2010) E-book vs. print media (Moberg et al., 2011) Server (Weber, 2012) Sensor network designs (Bonvoisin et al., 2012) PC vs. thin client computing (Maga et al., 2012) Public administration information systems (Mirabella et al., 2013)

No Yes

Yes

One item sold

Gate-to-gate

1

None Sensitivity analysis classification to recent work None

Yes No Yes

Cradle-to-grave Cradle-to-grave Cradle-to-grave

Full-LCA 1 Full-LCA

Sensitivity analysis Monte Carlo simulation None

Yes

One book brought and read One server Hourly data provision for ten years One computer workplace

Cradle-to-grave

2

None

Yes

Forms managed in one year

Cradle-to-gate

Full-LCA

None

unit for the abstract products and services provided by IT/IS. In other disciplines we find widely recognized units even for strongly inhomogeneous sets of processes, such as tkm for transport services, t for manufacturing processes or kWh for energy processing and storage. However, a common informational metric is not applied to IT/IS. According to Pal (2008), IT/IS products and services can be traced back to a system providing information transfer, processing and storage functionalities. The resulting functionality of IT/IS can thus be interpreted as multifunctional processes providing the three functionalities (e.g. running calculations within a data centre). When applying the LCA, this process can be subdivided into single functional processes (transfer, processing, storage) using allocation. Hence, the assessment of environmental impacts is referred to just one differentiated function, enabling comparison and verification to other systems with one or more equal functionalities. Characterization of an informational system is depicted in Fig. 3. Due to the delivered functionality we call it functionalization of IT/IS. An example for functionalization could be the provision of a computer workplace introduced by Maga et al. (2012). The bundle computer workplace delivered to the worker provides a specific set of all three functionalities limited by the hardware performance. Using functionalization, the environmental impacts of the bundle can be allocated to the single functionalities. The environmental outcome of the system can now be quantitatively compared to other systems (e.g. typewriter workplace or mail delivery) including strongly different products or verified against other LCA studies. The second step of functional unit development focuses on the definition of a scale to quantify functionalities. To achieve transparency, verifiability and comparability it is reasonable to make recourse to widely recognized metres. IS functionality related quantities defined in existing standards and norms are: (1) entropy for syntactical information (IEC, 2002), (2) distance for dislocation (ISO, 2006b), (3) (calculating) performance for processing (IEC, 2005) and (4) time for delay (ISO, 2006b). There are different units to measure these quantities dependent on the quantities’ context (e.g. Bit, Shannon and Ban for information or MIPS and FLOPS for performance). The correct use of the units strongly depends on the examined IS bundle and cannot equally be determined for all LCA applications. However, the operators between the

involved quantities are the same. Table 4 shows the quantification of IS functionalities as a framework for functional unit definition. The quantifications have been derived from analogue units used in the LCA database ecoinvent by deductive reasoning. Processes (units) used for deduction are: (1) electricity transmission as shown by energy multiplied by distance (kWh*km), (2) energy processing defined as electrical power multiplied by time (kW*h) and material storage described by mass multiplied by time (t*h). The definition of informational quantified functional unit comes from a need for symbiotic informational and physical models within the phase of inventory analysis. As presented in section 2, flow modelling is a central methodology within LCA used to perform inventory analysis. According to Möller and Rolf (1995), petri nets (Murata, 1989) are especially appropriate to perform flow modelling within LCA approaches because they are capable to depict not only flows but also stocks of energy and material. This property of petri nets is also needed within informational modelling due to the characteristic of IT/IS to store, process and transfer information. Jabri et al. (2010) considers petri nets to consist of transitions and places as well as the arcs connecting them. While transitions are depicted as boxes or bars in graphical representations, places are presented as circles. A node may not be connected to another node of the same kind, e.g. transitions cannot be connected directly to other transitions. In modelling, the use of a transition marks an event, and the use of a place represents a condition. Within petri nets for inventory analysis, places represent stocks of energy or material while transitions represent physical transformation processes (Möller and Rolf, 1995). Häuslein and Hedemann (1995) explain how this approach was realized within a software tool for inventory assessment. All material and energy forms depicted by the nets are included in the term material, specified by name and unit. Every material is a composition of one name and one physical unit, e.g. energy content (measured in mega joule/MJ) and weight (measured in kilogram/kg). Transitions are interpreted as physical processes determined by inputs and outputs of materials and energy. Within a symbiotic model and informational storing, processing and transferring has to be included within the petri net. This, however, indicates that the understanding of material related to a physical unit does not comprehensively reflect the needs of

Please cite this article in press as: Stiel, F., Teuteberg, F., Measuring the environmental impact of IT/IS solutions e A life cycle impact modelling approach, Environmental Modelling & Software (2014), http://dx.doi.org/10.1016/j.envsoft.2013.12.014

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Table 3 Conceptual framework design in the context of design science research (Österle and Otto, 2010). Guideline

Description

Instantiation in the inventory model

1

Design as an artefact

2

Problem relevance

3

Design evaluation

4

Research contributions

5

Research rigour

6 7

Design as a search process Communication of research

The conceptual framework is developed in order to conceptualize the problem of environmental impact assessment of IT/IS. Therefore, it can be described as a construct, a typical research artefact of design science research (March and Smith, 1995). Just a few works aim to improve and extend existing methodologies and approaches on how to assess and measure environmental impacts of IT/IS. However, indicators have to be developed to determine the impact of IT/IS on different aspects of the environment (Yi and Thomas, 2007) Only little understanding exists on how to measure environmental impacts within the context of IT/IS, which is essential to verify propositions mentioned (Jenkin et al., 2011). Especially the concept of inventory analysis needs to be reconsidered in order to investigate symbiotic physical and informational systems (Watson et al., 2012b). A widely recognized evaluation method for artefacts is simulation (Vom Brocke and Buddendick, 2006; Hevner et al., 2004). We run simulations, based on data of an LCA case study (Moberg et al., 2010) and data of the ecoinvent database. Our research contributes to systematic approaches for the analysis of the environmental outcome of IS (Hilty et al., 2006; Jenkin et al., 2011; Melville, 2010; Nidumolu et al., 2009; Watson et al., 2012b; Yi and Thomas, 2007) as well as recent work in the field of LCA, provided in section 2. The design of the framework builds on recent work within the field of LCA (Finnveden et al., 2009; Guinée et al., 2002; ISO, 2006a) and is further guided by methodologies for literature reviews (Vom Brocke et al., 2009; Fettke, 2006; Webster and Watson, 2002) design research (Hevner et al., 2004; Österle and Otto, 2010; Peffers et al., 2007)and the evaluation of design science research artefacts (Hevner et al., 2004). Multiple iteration cycles have been passed in between model design and its evaluation. Results will be communicated to a technical audience by dissemination of this paper. The results were also communicated to the interviewed experts with a management background.

Fig. 3. Functionalization of IT/IS.

symbiotic modelling. Traditional petri nets (Murata, 1989) are capable to depict informational flows as well as physical flows. Consequently, a symbiotic inventory analysis can be performed within the scope of petri nets, but it has to be built on a wider understanding of the term material including informational elements. In order to include informational elements into inventory analysis, we added a second possibility to express the quantity of a material by its informational content in bit. This allows for the modelling of causal relations between information containing systems and the environment, such as  replacement of physical based information systems by virtual information systems, e.g. to quantify the environmental impact of dematerialization solutions,  junction of separated physical systems by information flows, e.g. to relate physical systems along an information flow,

 identification of cross connections between social behaviour and physical systems, e.g. to determine environmental impacts of different IT usage patterns or Green IT strategies. A meta-model embracing the essential elements of a symbiotic, physical and informational inventory modelling is presented in Fig. 4. The deducted framework for functional unit and the metamodel for inventory analysis are embedded into the ISO 14040 LCA framework, as shown in Fig. 5. The adjustments refer to the phases of goal definition, scope definition and inventory analysis. Goal and scope definition is affected in functional unit and system boundary definition. For the inventory analysis, the framework attributes the modelling of informational flows as an additional feature within the scope of petri nets. The other LCA phases are not affected by the developed framework.

5. Evaluation Table 4 Framework for functional unit definition. IS functionality

Quantification

Information transfer Information processing Information storage

Entropy*distance Performance*time Entropy*time

Utility, quality and efficiency of the introduced framework are evaluated by conducting a LCA for a business scenario based on artificial data. This evaluation method refers to the method of evaluation by simulation within the design science research approach (Hevner et al., 2004). The simulation of the framework was conducted applying a similar use case as outlined recent LCA

Please cite this article in press as: Stiel, F., Teuteberg, F., Measuring the environmental impact of IT/IS solutions e A life cycle impact modelling approach, Environmental Modelling & Software (2014), http://dx.doi.org/10.1016/j.envsoft.2013.12.014

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Petri Net Model Petri Net Diagram

Node Arc Transition

Place Quantity Material Input Physical Unit Output Name System Input System Output Connection

Fig. 4. Meta-model for inventory analysis of symbiotic physical and informational systems based on a synthesis of Häuslein and Hedemann (1995), Jabri et al. (2010), Möller and Rolf (1995), Watson et al. (2012b).

studies on IT/IS. The majority of LCA studies within the context of IT/IS deals with information distribution systems, e.g. distribution of music or other multimedia (c.f. Table 2), based on specific data measured in the field and generic data from life cycle inventory (LCI) databases. Thus, the simulation of an information distribution system is a suitable means to demonstrate the performance of our framework within its intended application context. Moreover, it has to be conducted using specific as well as generic data. Specific data for the simulation was extracted from the corresponding literature (Table 2) without conducting our own measurements. This was done to evaluate performance of the framework rather than to make deterministic statements. However, the framework itself is meant to facilitate the research by producing a methodological foundation. Additionally, the granularity of the simulation was used to illustrate the performance of the framework. Therefore, the scope of the inventory model is reduced by waste, recycling and disposal flows. Although the authors are aware that their modelling approach does not lead to convincing inventory data, validity of the evaluation remains preserved as all elements of the framework, i.e. functional unit definition and

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symbiotic physical and informational modelling within the inventory, being tested. From the corresponding literature, the studies by Moberg et al. (2010) have been chosen as specific data sources due to the comprehensiveness of the outlined inventory data. Moreover, the simulation has been built on a base of realistic and commonly accepted generic inventory data. As the database ecoinvent is the most frequently mentioned database in recent LCA publications, we use it as our main generic data source. The case studies by Moberg et al. (2010) encompass the distribution of the information content of one newspaper. We use the LCA modelling tool Umberto to create the inventory model for the distribution of 41 million bits of information, which, according to Moberg et al. (2010), equals the information content in one newspaper. The result of the modelling approach, based entirely on the specific data gathered from Moberg et al. (2010), is shown in Fig. 6. Horizontally directed flows contain informational, vertical flows which represent physical flows. To complete the inventory, additional flows based on generic data have to be added in order to constitute indirect effects of the information distribution system. The additional flows represent the physical flows necessary to provide the electrical energy, fuels, supplies and infrastructures for the system. The indirectly involved system is shown in Fig. 7. The figure shows that the indirectly effected systems, such as paper or aluminium manufacturing, are located around the informational flows within the inner system boundaries. Material flows emerging from the environment on the left side or ending at the environment on the right side represent the environmental impact of the system. In order to execute the inventory analysis, places, transitions and arcs have to be specified in terms of materials and quantities contained. Specifications for the indirectly effected systems in Fig. 7 can be made by generic data sources, such as LCI databases. The generic data we used to specify our model are derived from the ecoinvent database and described in Table 5. Specific data for the specification of the transitions and places within the inner system boundaries is described in Table 6. Specifications of places and arcs are executed by definition of the contained material and its quantity. Material and quantity at the input and output site of the place are identical. Input and output site of a transition are distinct in material and/or quantity. Fig. 8 shows the first 22 materials and quantities for the generic specification of one transition using ecoinvent. The transition represents resource consumptions and emissions by IT infrastructure and energy consumption for one hour of office use.

LCA framework (ISO 14040) Iterative information flows

Goal and scope definition Functional unit defintion Function quantification (IEC 60027-2) (IEC 60027-3) (ISO 31-1) Performance functionalization (Pal, 2008) Interpretation

Application

Inventory Analysis

Symbiotic phyical and informational modelling (Watson et al., 2012b) (Jabri et al., 2010) (Häuslein and Hedemann, 1995) Impact Assessment Fig. 5. Framework for symbiotic flow system based life cycle assessments.

Please cite this article in press as: Stiel, F., Teuteberg, F., Measuring the environmental impact of IT/IS solutions e A life cycle impact modelling approach, Environmental Modelling & Software (2014), http://dx.doi.org/10.1016/j.envsoft.2013.12.014

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F. Stiel, F. Teuteberg / Environmental Modelling & Software xxx (2014) 1e11

Fig. 6. LCI model inner system boundaries.

Specifications of transitions within the inner system boundaries were conducted by using specific inventory data and the materials provided by the related places. Fig. 9 illustrates the specification of the transition called prepress. The materials for the specification of the transition prepress were found in the related places information at editor, IT-infrastructure and energy, alu plate, plate production supplies and information on printing plate. The material information is received from the place information at editor and then delivered to the place information on printing place and referred to 1 bit. The

transition displayed in Fig. 8 shows that IT infrastructure and energy is referred to 1 h of office use. The consumption of aluminium (alu plate) and the consumption of supplements (plate production supplies) are referred to the weight of the offset plate in kg. Coefficients including measured data and company information, used to specify the quantity of the transition, are extracted from Table 6. The coefficient regarding the processed information content of one newspaper can be directly taken from the table. The coefficients for office use (prepress office time per circulation/

Fig. 7. LCI model outer system boundaries.

Please cite this article in press as: Stiel, F., Teuteberg, F., Measuring the environmental impact of IT/IS solutions e A life cycle impact modelling approach, Environmental Modelling & Software (2014), http://dx.doi.org/10.1016/j.envsoft.2013.12.014

F. Stiel, F. Teuteberg / Environmental Modelling & Software xxx (2014) 1e11

9

6. Conclusions

Table 5 Generic inventory data. System within the model

Ecoinvent specification

Paper production processes

Paper, newsprint, at regional storage [RER] Aluminium, production mix, at plant [RER] Operation, lorry 7.5e16 t, EURO4 [RER] Aluminium production manufacturing, average metal working [RER] Use, computer, desktop, with LCD monitor, office use [RER]

Aluminium for offset plate production Diesel production and consumption Supplements and energy for offset plate production IT-infrastructure and energy consumption

Table 6 Specific inventory data of one newspaper. Description

Unit

Coefficient

Source

Newspaper information content Newspaper circulation Newspaper size Newspaper pages Page weight Fuel consumption Thickness offset plate Prepress office time per circulation

Bit

419,43,040

(Moberg et al., 2010)

Pieces m2 Number g/m2 l/Newspaper mm Hours

32,000 0.114 (tabloid) 40 45 0.0043 0.0002 m 40

(Moberg et al., 2010) (Moberg et al., 2010) (Moberg et al., 2010) (Moberg et al., 2010) (Moberg et al., 2010) ISO 12635:2008 Own assumption

newspaper circulation), as well as alu plate and plate production supplies (newspaper size  thickness offset plate  newspaper pages) are calculated from the extracted data. After specification of all petri net elements, the life cycle inventory is calculated by the calculation engine of the software tool. Fig. 10 shows the calculated gate-to-gate inventory for the distribution of the information content of a newspaper. The inventory contains supplements for manufacturing the offset plate, aluminium, diesel used for lorry operation, paper and IT infrastructures as well as energy used in the office. The complete cradle-to-grave inventory includes more than 1000 positions and is accessible via http://bit.ly/1078DtS. Input Material Transformation, to sea and ocean [resource/land] Transformation, from shrub land, sclerophyllous [resource/land] Magnesite, 60% in crude ore, in ground [resource/in ground] Transformation, to dump site, slag compartment [resource/land] Gold, Au 6.7E-4%, in ore, in ground [resource/in ground] Transformation, from tropical rain forest [resource/land] Praseodymium, 0.42% in bastnasite, 0.042% in crude ore, in ground [resource/in ground] Coal, brown, in ground [resource/in ground] Transformation, to shrub land, sclerophyllous [resource/land]

Our results confirm that the integration of informational flows into flow based LCA is both useful and feasible. It is useful, because it offers researchers and practitioners additional opportunities to structure and relate inventory models. Moreover, symbiotic models can be used to identify the relation between physical and informational systems. It is also rigorously viable, because symbiotic modelling can be conducted within the scope of the highly mutable and academically rigorous petri nets methodology. Compared to recent publications on the environmental impacts of information systems, our approach to enrich physical flows and processes by supplementary informational flows is fairly unconventional. Even though there is a certain interest for LCA studies in IT/IS solutions and models, and simulations on information flows do exist in the IS literature, information flows are not commonly recognized within the scope of inventory modelling. The reason for the absence of information flows within recent LCA studies might be that information flows do not have a direct, physical impact on the environment. Nevertheless, nonphysical systems, such as information systems, do affect the physical systems indirectly. Therefore, information flows should not be disregarded within inventory considerations. Due to our research approach, there are some specific limitations to our work. First, the literature review is limited to the range of AeC journals of the VHB ranking. A more detailed literature review will be conducted within our future work in the field of LCA. Influential journals to be included in an extensive review of the LCA literature might be also found outside of the considered VHB ranking. Additionally, we applied a keyword search to identify relevant research papers and although we identified more than 500 publications, we cannot exclude the possibility, that important papers eluded our review. A second limitation results from our evaluation approach. We used the modelling software Umberto and the ecoinvent database to evaluate the papers. The compatibility of our results with LCI software tools is therefore limited to the applied software and database. The question of whether information flows can be represented by other LCA modelling tools remains unacknowledged. It is also not possible to visualize the full process of Output

Place

Coefficient

Unit

Material

Place G5: IT-Infrastructure and Energy

Coefficient

Unit

P2: Environment

7.2583E-11 m2

use, computer, desktop, with LCD monitor, office use [RER]

P2: Environment

7.4075E-07 m2

Thorium-234 [air/low population density] P1: Environment

7.57E-08 kBq

P2: Environment

5.5762E-06 kg

Uranium-238 [air/unspecified]

P1: Environment

7.14E-10 kBq

Ruthenium-103 [water/river]

P1: Environment

1.54E-10 kBq

P2: Environment

1.013E-09 m2

1.00E+00 hour

P2: Environment

1.1814E-08 kg

Cobalt-58 [water/river]

P1: Environment

1.37E-06 kBq

P2: Environment

9.2311E-09 m2

Niobium-95 [air/low population density]

P1: Environment

7.21E-13 kBq

P2: Environment

1.7152E-10 kg

Xenon-133m [air/low population density] P1: Environment

2.69E-06 kBq

P2: Environment

0.0074015 kg

Cesium-134 [air/low population density] P1: Environment

8.87E-12 kBq

P2: Environment

6.2981E-07 m2

Xenon-135 [air/low population density]

P1: Environment

3.15E-04 kBq

3.328E-08 kg

Uranium-238 [water/river]

P1: Environment

4.78E-06 kBq

7.2604E-09 m2

Thorium-232 [water/river]

P1: Environment

3.00E-07 kBq

0.00010691 m3

Thorium-228 [air/unspecified]

P1: Environment

1.37E-10 kBq

Gypsum, in ground [resource/in ground] P2: Environment Transformation, from arable, nonirrigated, fallow [resource/land] P2: Environment Water, unspecified natural origin [resource/in water] P2: Environment

Fig. 8. Specification of a transition (generic data).

Please cite this article in press as: Stiel, F., Teuteberg, F., Measuring the environmental impact of IT/IS solutions e A life cycle impact modelling approach, Environmental Modelling & Software (2014), http://dx.doi.org/10.1016/j.envsoft.2013.12.014

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F. Stiel, F. Teuteberg / Environmental Modelling & Software xxx (2014) 1e11

Fig. 9. Specification of a transition (specific data).

Input

Output

Material Quantity aluminium product manufacturing, average metal working [RER] 1.20E-07 aluminium, production mix, at plant [RER] 1.20E-07 Information 4.19E+07 operation, lorry 7.5-16t, EURO4 [RER] 3.23E-03 paper, newsprint, at regional storage [RER] 2.05E-01 use, computer, desktop, with LCD monitor, office use [RER] 1.25E-03

Unit

Material

kg

Information

Quantity

Unit

4.19E+07 bit

kg bit km kg hour

Fig. 10. Gate-to-Gate inventory.

inventory implementation using the framework because several iterations typically occur during inventory analysis. The presented results may be thought of as a snapshot within the iterative design science research process. Therefore, further iterations and investigations within real-world scenarios have to be performed to complete and evaluate our findings. This approach strongly depends on the availability of primary inventory data for information and physical flows associated with IT/IS. Collection of such data is a time-consuming task. However, empirical findings from the application would support the validation of the propositions underlying the evaluation of this research. Subsequently, we will apply our results within our own LCA case studies in the context of IT/IS. Possible cases for our model could include dematerialization processes, smart solutions or other innovative solutions from the field of sustainable information systems and Green IT/IS. To enhance our evaluation approach, we also plan to conduct additional experiments, lab studies and action research. In this way, we will find out more about the usability and applicability of our results. This paper examined issues relating to first and second order environmental effects. Future research will consider the dynamics of user behaviour in the third order, e.g. by using system dynamic approaches. Finally, we plan to apply this conceptual framework in regard to the environmental impact of recent IT/IS solutions such as

solutions for cloud computing, energy consumption feedback or multimodal transport. We hope that our conceptual framework will guide researchers as well as LCA practitioners to conduct LCA in the context of information systems and will help to derive quantitative data describing the environmental impact of IT/IS. Acknowledgement This work is part of the project IT-for-Green (Next Generation CEMIS for Environmental, Energy and Resource Management). The IT-for-Green project is funded by the European regional development fund (grant number W/A III 80119242). The authors are pleased to acknowledge the support by all involved project partners. Furthermore, we would like to thank the anonymous reviewers for their insightful and constructive comments. References Bartl, K., Gómez, C. a, Nemecek, T., 2011. Life cycle assessment of milk produced in two smallholder dairy systems in the highlands and the coast of Peru. J. Clean. Prod. 19 (13), 1494e1505. Bonvoisin, J., Lelah, A., Mathieux, F., Brissaud, D., 2012. An environmental assessment method for wireless sensor networks. J. Clean. Prod. 33 (16), 145e154. Elsevier Ltd.

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Please cite this article in press as: Stiel, F., Teuteberg, F., Measuring the environmental impact of IT/IS solutions e A life cycle impact modelling approach, Environmental Modelling & Software (2014), http://dx.doi.org/10.1016/j.envsoft.2013.12.014