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Market information in life cycle assessment

2 Product substitution

We define a product substitution as a replacement of one product or group of products with another product or group of products, fulfilling the same needs of the customer. We define a product also in terms of its production process, which implies that a product substitution will always imply one or more process substitutions (understood as process changes or complete replacements), and that a process substitution can also be seen as a product substitution, even when the product itself is unchanged (e.g. in terms of its physical properties).

Product substitutions may occur anywhere in the life cycle, from raw material substitutions, over substitutions in the production and use stages, to substitutions between alternative waste handling options. In a consequential, comparative life cycle assessment, the object of study is the environmental impacts of a potential product substitution. This product substitution, as delimited by the functional unit, implies a change in demand as the customer replace one product in favour of another: More is bought of the one product, less of the others. This change in demand is transferred all the way backwards through the life cycle stages of the products involved in the substitution (and sometimes also forward, if the substituted products are not completely identical). At the other stages of the life cycle, further substitutions occur, as the suppliers scale their production up or down according to the change in demand.

Thus, product substitution is a core concept to consequential, comparative life cycle assessment. In spite of this, a proper methodology has been lacking for including the available knowledge about product substitution into life cycle assessments. This implies that life cycle assessments have often based their functional unit and system delimitation on intuitive or arbitrary choices, rather than on analytical grounds. This arbitrariness is unnecessary, since knowledge about product substitution is available, although requiring information from sources not traditionally used for life cycle assessments.

The objective of this chapter is to describe the general aspects of product substitution, including the issue of data availability (section 2.5), as well as those procedural steps that are common to the more specific elements of the life cycle assessment method, covered by the procedures presented in the following chapters of this report.

Knowledge on product substitution is applied in the following elements of life cycle assessment:

• When defining the functional unit and which alternative products can be or should be compared (chapter 3),
• When identifying the individual processes to be included in the system under study (chapter 4),
• When identifying the processes to be included in a system expansion to accommodate differences in the functions provided by the compared systems (chapter 5),
• When identifying the processes affected on future markets (chapter 6).

The following sections are structured according to the necessary conditions for a product substitution to take place, namely that:

• the products are substitutable, i.e. that the products have the obligatory properties ("must have" properties) required by the customer in the market segment in question (section 2.1),
  
• the products are available to the customer, i.e. that their supply is not constrained by market failures, declining markets, regulations, or shortages in supply of raw materials or other necessary production factors (section 2.2),
  
• a decision is made so that the potential product substitution is actually realised (section 2.3 and 2.4).

This division is in accordance with Sheth’s theory on buying behaviour that distinguish three main elements in the buying process: product requirements, supplier accessibility and customers ideal and actual choice (Sheth 1973, 1981).

2.1 Product properties and market segments

A product substitution is ultimately a decision of the customer. For a product to be considered relevant for a potential product substitution, the customer must see it as fulfilling the same need. This can be expressed in terms of the obligatory properties of the product. What is regarded as obligatory product properties change across market segments, and may thus be identified by analysing the requirements on the market in which the product is to be sold. However, in life cycle assessment, it is not uncommon to first describe the product in terms of it properties, and then to identify and describe the market on which it is to be sold. Thus, it is a bit of a “hen and the egg” situation, where the information on obligatory product properties and market segmentation is mutually dependent.

Product properties may be divided in three groups depending on their importance:

• Obligatory properties that the product must have in order to be at all considered as a relevant alternative. Example: A beverage container must not leak.
• Positioning properties that are considered nice to have by the customer and which may therefore position the product more favourably with the customer, relative to other products with the same obligatory properties. Example: A beverage container may be more or less easy to handle.
• Market-irrelevant properties that do not play a role for the customer’s preferences. Example: A (refillable) beverage container may be more or less easy to clean.

The obligatory properties determine substitutability and are related to market segmentation. Positioning properties may influence the extent to which a potential substitution is actually realised (see section 2.3) and may - together with the market-irrelevant properties - determine the amount of substituted product or the interaction with other product systems. For example, the ease of handling and cleaning a beverage container (positioning and non-market relevant properties, respectively) can influence the amount of car-driving on behalf of the consumer and the type and amount of cleaning agent, respectively.

The same product property may be placed in different groups on different markets (see below).

For a product substitution to be possible, the obligatory properties must be present. Only when these demands are met, the positioning properties can influence the willingness of the customer to switch from one product to another.

Product properties may be related to:

• Functionality, related to the main function of the product
• Technical quality, such as stability, durability, ease of maintenance
• Additional services rendered during use and disposal
• Aesthetics, such as appearance and design
• Image(of the product or the producer)
• Costs related to purchase, use and disposal
• Specific environmental properties

Functionality, aesthetics, and image characterise the primary services provided to the user.

Technical quality and additional services ensure the primary services during the expected duration of these.

Environmental properties may be included among the properties included in the functional unit. However, since the very purpose of a life cycle assessment is to study the environmental impacts of the products, it is not meaningful to state in advance that the studied products should have such general properties as ”environment-friendly” or ”non-toxic.” If environmental properties are included as obligatory, they must be expressed as specific properties, like ”the barley must be from ecological farms”, so that it is possible to judge - prior to the life cycle study - whether a product has the required property.

Of the above-mentioned properties, price is the only one that can be put into well-defined terms. Technical quality and functionality can be described a little less well defined, but still quantitatively. Other properties, such as aesthetics and image, cannot be measured directly, but must be described qualitatively. Some of these properties can seem very irrational, since they are not present in the product, but in the buyer’s perception of it. These properties can be greatly influenced by commercial activities of the supplier.

Markets are typically differentiated

• geographically,
• temporally, and
• in customer segments,

which each have their own uniform set of preferences and demands for product properties.

The geographical segmentation of markets may be determined by differences in:

• natural geography (climate, landscape, transport distances etc.),
• regulation or administration (regulation of competition and market transparency, legislative product requirements, product standards, taxes, subsidies),
• consumer culture.

Temporal segmentation of markets is common for service products (e.g. peak hours and night hours in electricity consumption, rush hours in traffic and telecommunication, seasons in the tourist industry). For physical goods, markets are generally only segmented temporally when adequate supply or storage capacity is missing, either due to the nature of the product (e.g. food products), or due to immature or unstable markets, as has been seen for some recycled materials.

This temporal segmentation should be distinguished from the fact that markets generally develop in time, e.g. governed by developments in fashion and technology, and that both geographical and temporal segmentation and customer segmentation therefore may change over time. In general, there is a tendency for positioning properties to become obligatory with time and for markets to become more transparent and geographically homogenous, but at the same time more segmented with regard to quality requirements.

Each geographical market is typically divided into a number of customer segments. Customer segments are generally defined in terms of clearly distinct function-based requirements, i.e. based on the needs fulfilled by the products rather than based on the physical products themselves. Very similar products may serve different needs and hence serve different markets. And very different products may serve the same need, thus being in competition on the same market. Differences in customer requirements may be based on differences in the purchase situation, the use situation, customer scale, age, sex, education, status, “culture”, attitudes etc.

To have a practical relevance, market segments must be (Lancaster & Massingham 1998):
of a size that can provide adequate revenue to support a separate product line. clearly distinct and with a minimum of overlap, so that all products targeted for a segment are considered substitutable by the customers of this segment, while there should be low probability that a product targeted for another segment would be substitutable, implying that product substitution from segment to segment can be neglected. For example, the market for office chairs is divided into at least three well distinguished customer segments exit, based on three different working situations: The labourer‘s chair, intended for the labourer who is sitting on the chair at intervals only and not for many hours at the time, the computer workstation chair, intended for the worker who is primarily sitting, and who is working behind a visual display unit at least two hours a day, and the manager‘s chair, intended for the design-oriented person, not working much on computer or desk, but rather reading, talking on the telephone and the like. The latter chair could typically be for the employer or senior employee, to whom design, aesthetics, and image/representativity to customers are important issues. There is only very little overlap between these groups of customers. The probability that a chair targeted for one segment should sell to a customer in one of the other segments is small, so that the product substitutability from segment to segment can be neglected. This implies that life cycle studies of office chairs should consider each of the market segments separately and not allow for comparisons between them.

2.2 Product availability and constraints in supply

Even when products have the same obligatory properties, they can only take part in a product substitution if they are available to the customer, i.e. that supply is not constrained.

There can be many reasons that a potentially substitutable product is not available to the consumer, notably market failures, declining markets, regulation, and shortages in supply of raw materials or other necessary production factors.

In a market with only one supplier of the specific product (a monopoly), product substitution is per definition not possible. However, few markets are monopolies. Even the so-called natural monopolies such as the railroads, telephone and electricity markets, which were long divided into regional monopolies, are now being opened up to competition. Still, patents and product standards may limit market entry of new suppliers, and transaction costs may be prohibitive for some potential substitutions to take place in practise.

In a declining market, the penetration of modern technology is constrained, since new capacity is not being installed, limiting competition to those suppliers already present.

Regulatory constraints typically take the form of minimum or maximum quotas on the process (like the Danish minimum quotas on the use of biofuels for heat and electricity generation) or any of its exchanges, e.g. product quotas (like the EU milk quotas) or emission quotas (like the Danish SO₂ and NO_x quotas for electricity generation, which limits the use of coal based technology). The forced phasing out of specific polluting technologies may also render these unavailable to substitution as a result of changes in demand. Taxes and subsidies may also constitute virtual constraints on production. An example is the negligible import of cereal grains to the EU, because of a very high import tax. Similarly, the farmer’s choice of crops is strongly dependent upon the level of subsidies given for different crops, virtually imposing a constraint on crops less subsidised.

The necessary production factors, notably raw materials, may not be locally available or may only be available in limited quantity (for example, the availability of fresh, untreated drinking water may be limited in areas with limited rainfall, water for hydropower likewise, and on an expanding market for a material, the availability of recycled material will be constrained). For products that do not store easily and products and semi-manufactured materials with a low price to weight ratio (such as biomass for energy and paper pulp), transport distances and infrastructure can impose a constraint on products and materials not produced locally. Waste treatment capacity may be a constraint on processes with specific hazardous wastes.

For multi-product processes, supply of a co-product may be constrained if it does not have a value that can sustain the production alone. In general, this will be the case if the studied product has a low value compared to the other co-products, so that the studied co-product cannot in itself provide an economic revenue that is adequate reason for changing the production volume (like animal manure versus milk and meat, or rape seed cakes versus rape seed oil), or if the market trend for the studied co-product is low compared to the market trend for the other co-products. See also section 5.4.

2.3 Realising substitution

Even when products have the same obligatory properties, and an unconstrained supply, substitution is only realised when active decisions are made by the customer.

In the first part of the life cycle (e.g. in relation to raw material substitution), price tends to play a larger role in purchase decisions and product quality is often less complex, more easy to define precisely, more dominated by technical aspects, and more stable over time than later in the life cycle (consumer products) where complexity increases, preferences change more quickly, and qualitative aspects and irrational behaviour may have larger influence.

It is possible to further subdivide market segments into market niches. A market niche is a further sub-category of a market segment, where a part of the customers consider only niche products substitutable, although the majority of the customers allow substitution between products from the niche and other products in the segment. Thus, the difference between a segment and a niche is that between segments substitution is negligible, while a large part of the customers in a segment will allow substitution between niche products. Niche products are aimed at a smaller group of consumers within a segment, for whom specific product properties are obligatory, while the same properties were only positioning properties in the broader market segment.

Office chair example: Market niches
The substitutability between chairs depends on customer preferences. And these preferences vary from customer to customer. From the 18 years old sporty person, who maybe just wants a chair and gives no thoughts what-so-ever to ergonomic properties, to the older secretary with back troubles. And from the small 10-employee private company to the public institution buying through the public purchase service. Especially within the market segment for computer workstation chairs (see Weidema et al. 2003a), there might be well-distinguished niches between which, the product substitutability is only limited. Examples are:

• The niche of occupational therapist prescribed purchase, within which high level ergonomic properties become obligatory, such as synchronic and weight adjusted movements of seat and back rest,
• In Denmark, public institutions of the state, counties, and municipalities can buy through the National Procurement institution (SKI - Statens og Kommunernes Indkøbsservice) that has bulk sales agreements with suppliers. SKI may then in turn specify requirements to be fulfilled by suppliers in order to deliver through SKI, which may include both functional and environmental requirements. For office chairs, these requirements include e.g. ergonomic properties, tests for stability, durability, and strength. Because public purchase is a very large share of the market for office chairs, SKI plays an important role, also in raising the general level of customer requirements.

Market segments and niches are typically identified by dividing the market according to a number of customer characteristics, such as customer scale, age, sex, education, status, “culture”, attitudes etc. in such a way that demand for product properties is homogenous within segments/niches and heterogeneous between each segment/niche (Lancaster & Massingham 1998). There is also some evidence that market segments and niches may better be modelled by purchase or use context, rather than by customer characteristics, thus allowing the same customer to have different preferences in different situations, and different customers to behave similarly in the same situation (Moss & Edmonds 1997). Edmonds et al. (1997) provide a model algorithm that enables quantitative market segmentation also in situations where domain experts lack confidence in their own judgements or where their initial segmentation is found not to be in accordance with available sales figures. Bech-Larsen & Skytte (1998) provide an example of using conjoint analysis for segmentation of the vegetable oil market into four niches: one with strong preferences for neutral colours and a low content of transfatty acids, one with strong focus on supplier characteristics in terms of quick delivery and ISO certification, one with a strong preference for a high oxidative resistance and antipathy for rape seed oil, and one with strong preferences for neutral taste and a high nutritional value.

2.4 Supply elasticity as a measure of actual substitution

The supply elasticity is a formal measure of the substitution realised (i.e. the change in supply) as a result of a change in an influencing factor, e.g. the demand. If a change in demand leads to a similar change in supply, that supply is said to be fully elastic. If a change in demand does not lead to any change in the supply, that supply is said to be fully inelastic.

On competitive, unconstrained markets (i.e. where there are no market imperfections and no absolute shortages or obligations with respect to supply of production factors, so that production factors are fully elastic in the long term), individual suppliers are price-takers (which means that they cannot influence the market price) and the long-term market prices will be determined by the long-term marginal production costs (which implies that long-term market prices, as opposed to short-term prices, are not affected by demand). In this situation, the long-term supply will be fully elastic. In most life cycle inventory models, this is applied as a default assumption: For each process in the life cycle, the demand for 1 unit of product is assumed to lead to the supply of 1 unit of product, and other customers/applications of the product are assumed not to be affected.

Individual suppliers or technologies may be constrained in the long and/or short term and therefore have an inelastic supply. In this situation, the demand will shift to an alternative supplier/technology that is not constrained.

If all suppliers to a specific market segment are constrained, or if one or more production factors are not fully elastic, a change in demand will lead to a change in market price and a consequent adjustment in demand (i.e. a behavioural change). This adjustment will be accommodated by the customer(s)/application(s) most sensitive to changes in price, measured in terms of their demand elasticity (i.e. their relative change in demand in response to a change in price).

A special class of constraints are those related to co-production. If the co-producing process is otherwise unconstrained, it is reasonable to apply the default assumption above, that the long-term supply elasticity is fully elastic, also for a determining co-product (see chapter 4 for a definition of determining co-products and a detailed description of our procedure for handling co-products). Thus, the demand for 1 unit of a determining co-product is assumed to lead to the supply of 1 unit of the determining co-product along with the corresponding amount of the dependent co-product(s). Depending on the market situation for each dependent co-product, this additional supply of dependent co-products will go to waste (when the dependent co-product is already only partially utilised), lead to a displacement of the most sensitive alternative supply (when the dependent co-product is already utilised fully and alternative suppliers are not constrained), or lead to an increase in consumption (when the dependent co-product is already utilised fully and all alternative suppliers are constrained). In the situation where displacement occurs, the default assumption implies that the suppliers are price-takers and the co-producing process cannot influence the market price. The market price for the dependent co-product will therefore be determined by the long-term marginal production costs of the displaced supply.

In this way, our treatment of co-production is simply a consistent application of the default assumptions generally applied in life cycle inventory modelling. It therefore appears inconsistent to dismiss our substitution procedure as “fairly unrealistic”, “rather unrealistic”, and to view it “not as part of inventory modeling, but as a type of allocation” (Guinée et al. 2001, part 3, page 125-6, 129). In contrast, Guinée et al. (2001) refrain from modelling the effects of co-production and recommend instead an allocation procedure based on the co-products’ shares of the total revenue. This allocation procedure is equivalent to assuming (see also section 5.10):

• that for any requested co-product a co-producing process will react to a change in demand with an increase in production volume in proportion to the co-product’s share in the total revenue, implying that the remaining part of the demand will be covered by an alternative supply and/or a reduction in consumption elsewhere,
• that the additional supply of other co-products, caused by the increased production volume of the co-producing process, will always be utilized fully and lead to an equivalent increase in consumption (since there is no additional increase in waste handling from the co-producing process, and no displacement of alternative supply) implying that the demand elasticities for these co-products are infinite (even for “near-to-waste” co-products that are partly disposed of as waste),
• that the environmental impacts of the above alternative supply and/or changes in consumption are insignificant (since the system is not expanded to include this alternative supply and/or changed consumption and related processes), and
• that there will be no displacement of alternative supply (i.e. that supply elasticity is 0, even when the supply is not constrained and the same supply elsewhere in the same study may be modelled to respond to a change in demand with the default fully elastic supply).

It is difficult to see how these assumptions can be regarded as more realistic than extending the default assumptions used in the remaining inventory modeling to cover also the situation of co-production.

In fairness, it shall be noted that Guinée et al. (2001), immediately having passed the above controversial and somewhat harsh judgment on our procedure, proceed to recommend the application of our procedure as a sensitivity analysis, “to gain an indication of the possible effects of substitution,” although this may be stretching the concept of sensitivity analysis beyond its original meaning. Rather, the intention is to suggest the inclusion of our procedure as a separate scenario, as an extension “for improving the quality of detailed LCA in these respects where shortcomings are most obvious. A key example is the absence of economic mechanisms in the model, an unfortunate feature in cases where there are extreme inelasticities of supply and demand” (Guinée et al. 2001, part 3, p.59, last bullet). Also in their research recommendations, they suggest: “By incorporating certain economic mechanisms in the inventory model, particularly in cases involving extremely high or low elasticities, inventory modeling might be made more realistic and some of the principal defects of LCA redressed” (op.cit., p. 133). Furthermore, it appears that their judgement of our method has been based on an insufficient understanding: “the … method of Weidema, still difficult to understand, …” (op. cit., p. 128), which is also confirmed by their extensive list of research recommendations (op.cit., p. 133-4).

It should be noted that applying the revenue-based allocation procedure in consequential studies, as recommended by Guinée et al (2001), leads to further inconsistencies when seen in combination with the general recommendation of Guinée et al. (2001) to identify the affected processes in terms of market averages. For example, if we assume that a market is supplied with 10% from a single-product process and 90% from a co-producing process, but this product only contributes with 10% of the revenue, then only a tenth of the co-producing process will be included in the system, implying either an unrealistic decrease in demand elsewhere or that the remaining 90% will be supplied from the single-product process, which is however not consistent with our knowledge that it supplies only 10%.

Further, applying the revenue-based allocation procedure in consequential studies is also inconsistent with defining the functional unit in terms of a single function from a multi-functional process (e.g. the isolated cleaning function of an anti-dandruff-shampoo). When the functional unit comes from a multi-functional process (the hair washing providing joint cleaning and anti-dandruff functions), the demand for the functional unit should – according to the allocation procedure – only affect a part of the analysed product systems equivalent to the share of the functional unit (the price that can be attributed to the isolated cleaning function) out of the total revenue. Nevertheless, when analysing this isolated function, Guinée et al. (2001, part 3, page 78) just mention this allocation procedure as one option, suggesting that the other functions may equally justifiable be either neglected or dealt with through system expansion (adding the anti-dandruff function to the functional unit).

As can be seen from this analysis, all three above elements of life cycle inventory modelling (the method for defining the functional unit, the method for identifying the processes to be included in the system, and the method for dealing with co-production) are interwoven and relate to the same issue, namely that of product substitution as outlined in this chapter. Only when applying the same fundamental method and assumptions for all three elements, as in the following three chapters, a consistent result will be obtained.

2.5 Availability of market data

For the study of product substitutions, and thus for consequential life cycle assessments, the availability of market data is essential. We have therefore investigated the current availability of market data, and have come to the conclusion that availability is a minor problem compared to the availability of technical data on environmental exchanges (the more well-known data availability problem in LCA), although access is still not straightforward.

On the basis of the description of product substitution in the previous sections, five types of market data can be distinguished, the availability of which are discussed separately (illustrated by milk as a specific product) below. Further examples of specific data are provided in chapters 3 and 4.

1. Obligatory and positioning product properties in different market segments and geographical markets. Information can be obtained from the marketing departments of the enterprises supplying products to the market segment. If such direct information is not available, the same information may be obtained from retailers, industrial organisations, industrial research institutions and industry consultants, regulating authorities and standardisation bodies (issues regulated in national and international legislation and standards will typically be obligatory properties), marketing and consumer research institutions, or trade statistics (the latter especially to document geographical market boundaries). Examples of publicly available information are the analyses of industrial sectors or “resource areas” provided by the Danish Agency for Industry and Trade (Erhvervsfremmestyrelsen 1993a,b,1994a,b, 2001). Weidema et al. (2003a) provide an example of identifying market segmentation and product properties of office chairs, based on a small survey of the Danish market.
   Milk example: Statistical publications have information on market share of various sales channels. Published nutritional surveys of food consumption per population, sex and age group (based on questionnaires) can be used to assess whether and to what extent specific products are consumed in sex- and age groups. Besides such public sources, marketing departments of dairies have a good understanding of the market segments, which they use for planning the marketing their products. The obligatory product properties of milk in each segment: temperature, age after milking, keeping ability, packaging properties etc., are also well known by the marketing departments of the dairies.
2. Data on constraints in production and supply. Regulatory and political constraints, typically in the form of minimum or maximum quotas, are obviously well known and public (examples: Political decisions not to build any more hydropower or nuclear power plants in Europe, Danish minimum quotas on the use of biofuels for heat and electricity generation, EU milk quotas, Danish SO₂ and NO_x quotas for electricity generation, which limits the use of coal based technology). Constraints in the availability of raw materials, waste treatment capacity, or other production factors are typically well known in the industry and not regarded as confidential. Constraints due to co-production can be determined from their share in the economic revenue combined with their relative market trends, cf. the procedure outlined in section 5.4. In case of missing information on constraints, it should be assumed that there are none. Unjustified exclusion of suppliers is thereby avoided.
   Milk example: Data on milk quotas, subsidies and restitution in the EU are publicly available. The same is true for agricultural fodder crops. Often, it is rather obvious what supplies are constrained, e.g. fodder by-products from the food industry, which depends on the demand for food products, not on changes in demand for fodder.
3. Data on market trends. This information is typically a combination of statistical data showing the past and current development of the market and different forecasts and scenarios. Trade and production statistics are typically publicly available, either from the national statistics or from product specific industrial organisations. Sector forecasts are typically available from national and supranational authorities, while more product specific forecasts are available from industrial organisations.
   Milk example: Statistical data are published yearly, e.g. sector profiles of the dairy sector with information on spending on milk and milk-products per capita, market share of milk and milk-products and the development in total use of milk and milk-products in kilograms per capita. Sector studies are available in which buying behaviour and scenarios for the future are described. These studies are mostly qualitative.
4. Data on the parameters that influence decisions on realised substitution, e.g. prices of different technologies and the effect of information on buying behaviour and investment decisions. Data on production costs for individual plants, countries, or technologies are obtained from the industry in question, from industry consultants, or from research organisations. Examples are Doms (1993) for data on the U.S. manufacturing energy market, World Steel Dynamics (2000) for data on steel (process-by-process costs and world cost curves replicating key process costs for 284 steel plants in 49 countries), Dernecon (2000) for newsprint, and SRIC (1999) for chemicals. If data cannot be obtained, it may be assumed that modern technology is the most competitive and the oldest applied technology is the least competitive. With respect to geographical location, it can be assumed that competitiveness is determined by the cost structure of the most important production factor (labour costs for labour intensive products, else energy and raw material costs). When comparing labour costs, local differences in productivity and labour skills should be taken into account.
   Milk example: Data on the costs of different technologies may be obtained from production engineers and suppliers of machinery. Public sources are not common. Prices of different fodder crops are published and can be used to calculate the changes in fodder composition as a result of changes in production. The most difficult decisions to model are those of the farmers, e.g. how the choice of crops are made. Models can be based on information on the marginal revenue of different crops and the relation between the costs of different inputs (fertiliser, pest control), the influence on the yield, and the price of the agricultural products.
5. Data on the scale of change that may influence what technologies and processes to include. These data regard boundary conditions of some of the above-described data on market sizes and constraints, market trends, and production costs. Thus, the sources and availability of these data are similar to the above.

A specific problem in data collection for consequential LCAs is that the product substitutions often involve processes that do not belong to the immediate supply chain. This means that data will be required from companies that may not see the immediate relevance of their participation, thus affecting their willingness to supply data. However, practical experience rather suggests that willingness to participate is more a question of the general company culture towards professional secrecy than a question of closeness of business relations.

Just as for technical data on environmental exchanges, market data can be provided in terms of best estimates, best-case, and worst-case data, the latter being suited to provoke data providers to supply data of improved quality.

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