Choice determinants for the (non) adoption of energy efficiency technologies in households
A literature review
Elvira Moukhametshina
Environmental Management in the Swedish Manufacturing Industries
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Acknowledgements
This report was developed through the vast body of literature that had been evolving over the last four decades. I would like to extend my gratitude to Mses. Mithra Moezzi, Lisa Skumatz, Diana Uitdenbogerd and Françoise Bartiaux for being open and kindly advising me in the very beginning of this review. Not the least I appreciate their practical help in providing me with some key references and publications that helped to further structure this report.
Messrs. Harold Wilhite and Richard Wilk have also been very helpful in providing access to some of their key publications.
Particular thanks belong to Professor Lena Neij whose structured and clear vision as well as academic and professional experience made, first of all, the project possible in the time when it is of the essence. Her supervision allowed posing the right questions and looking for objective answers, and guided this report.
Finally, I would like to thank Luis Mundaca for contributing with revision and streamlining the finalisation.
Lund, October 2008
Elvira Moukhametshina.
Table of Contents
List of Figures
List of Tables
List of Appendices
1. Introduction 3
2. Analytical frameworks to approach the (non) adoption of energy efficiency technologies 3
2.1 Co- (or non-energy) benefits approach 3
2.2 Intervention factors approach 3
2.3 Innovation-related studies 3
2.4 Implicit discount rates 3
2.5 Others approaches 3
3. Determinants induced by energy efficient technologies 3
3.1 Price 3
3.2 Operating costs 3
3.3 Time 3
3.4 Status/visibility/appearance 3
3.5 Comfort 3
3.6 Branding / design 3
3.7 Compatibility 3
3.8 Performance 3
3.9 Observability 3
3.10 Complexity 3
3.11 Choice/problem solving 3
4. Demographical factors 3
4.1 Age 3
4.2 Household size and/or composition 3
4.3 Gender 3
5. Factors related to buyer’s characteristics 3
5.1 Income 3
5.2 Knowledge/information/awareness 3
5.3 Attitude/environmental consciousness 3
5.4 Education/occupation 3
5.5 Type of dwelling 3
5.6 Life style 3
5.7 Timing / Appropriate moment 3
6. Contextual factors 3
6.1 Ownership/split incentive problem 3
6.2 Intermediaries 3
6.3 Policy incentives 3
7. Energy (efficiency) technologies 3
7.1 Space conditioning and building envelope 3
7.2 Sanitary hot water 3
7.3 Renewable energy technologies 3
7.4 Lighting 3
7.5 Consumer appliances 3
8. Concluding remarks 3
List of Figures
Figure 1. Comparison of U.S. and Thai consumer priorities. 3
Figure 2. Main factors preventing increased saturation of CFLs in the households with CFLs. Northwest Pacific. 2006. 3
Figure 3. Main factors preventing increased saturation in the households without CFLs. Northwest Pacific. 2006. 3
Figure 4. Distribution of the external influence in the adoption of consumer durable products. 3
List of Tables
Table 1: Main drivers for adopting energy related measures. Results of the on-line survey. 3
Table 2: Estimated NEBs within EnergyStar New Homes programme. 3
Table 3: Estimated NEBs within EnergyStar Homes Performance programme. 3
Table 4: Reasons to buy and not to buy energy-efficient appliances (in %) 3
Table 5: Rank order of insulation by men and women 3
Table 6: Demographic and attribute perception ratings 3
Table 7: Effect of market factors on CFL sales in California in 2005. 3
Table 8: Ownership of CFLs according to social-demographic characteristics. 3
Table 9: Main reasons for obtaining a CFL among owners. Cultural survey. 3
Table 10: Non-energy benefits / impacts of household appliances. Percent of overall non-energy benefits. 3
Table 11: Overall effectiveness of energy labelling. 3
Table 12: Differences among adopter categories (vitroceramic hobs). 3
Table 13: Effect of market factors on resource efficient washing machines sales in California (US). 3
List of Appendices
Appendix 1: Bibliography reviewed but not referenced 57
Appendix 2: Bibliography not reviewed 3
III
1. Introduction
This study presents a literature review focused on energy efficiency and determinants of the (non) adoption of energy efficient technologies in the household sector. The key guiding question is what determinant should be taken into account when analysing future energy (service) demand and potentials of reducing future energy demand by the use of different energy policy instruments. Based on a literature review, the objective of this report is to identify (mostly) quantitative studies that look at the criteria that determine the (non) adoption of energy efficient technologies in the household sector.[1] The report highlights rational economic considerations complemented with co-benefits and behavioural aspects.
Low investment in energy efficient technologies is often identified as a result of the ‘energy efficiency gap’ (see e.g. Jaffe and Stavins, 1994a; Stern and Aronson, 1984; Weber, 1997). This term attempts to capture the slow diffusion of profitable energy efficient technologies that fail to achieve market success. The energy efficiency gap is described in terms of market failures and barriers, indicating that the investors do not choose energy technologies although they are cost effective. In addition, it could be argued that consumer decisions do not respond to the model of rational choice behaviour. Early work done by Lutzenhiser (1992) spotted evidences of lack of economic rationality in consumer decisions to forego some obviously energy efficient measures. In fact, one can safely argue that the approach of economic rationality is inadequate to properly reflect technological consumer preferences. Investment costs are only part of a great variety of variables that frame and drive energy related consumer’s investment decisions. For instance, design, comfort, equipment’s brand, timing, functionality, reliability, learning, marketing, environmental awareness, etc., are likely do influence altogether the decision about an energy-technology choice/purchase. From the societal point of view e.g. environment, the investment outcome is likely to be unsatisfactory so there is a great need in public policy to better understand consumer investment decisions in the context of energy use.
The literature review presented here is an attempt to picture the whole spectrum of determinants and to highlight those playing the strongest roles in households’ adoption decision-making within a range of energy (efficient) technologies. The objective is to capture studies focusing on qualitative as well as quantitative aspects of investments determinants. The determinants have been described form different perspectives:
· Determinants induced by energy efficient technologies
· Demographic aspects that affect (non) adoption
· Factors related to buyer’s characteristics that affect the determinants of investments
· Contextual factors that affect the decision-making process of (non) adoption
The outline of this report is as follows. Chapter 2 is devoted to a short overview of earlier meta- studies and reviews in the field of investments determinants of energy efficiency technologies. This report highlights different analytical approaches to investigate determinants of the (non) adoption of energy efficiency technologies. In Chapter 3 the report addresses the identified criteria or determinants of (non) adoption decisions based features of technologies. Cases of determinants are provided in terms of geographical location of samples, observed results and methods by which the results were obtained. In Chapter 4, 5 and 6 the report describes the (non) adoption of efficient technologies in terms of demographic aspects, the characteristics of (potential) adopter/households and the contextual factors in which the (non) adoption process can take place. In Chapter 7, takes a different approach, as it looks into specific technologies and describe the most important determinants on a technology-basis; highlighting that different determinants will be of different importance for different technologies. Finally, in Chapter 8 some concluding remarks are drawn.
2. Analytical frameworks to approach the (non) adoption of energy efficiency technologies
Research in the area of choice determinants for in the adoption of energy efficiency technologies is not novel. Hirst and Goeltz (1985:25) state that “the critical determinants of the household decisions to retrofit are assumed to be the capital and operating costs of the retrofit choices”. This is generally the case of conventional wisdom for various household appliances. However, the literature on several determinants affecting energy (efficiency) technologies in the household sector is vast. In fact, approaches to identify and/or quantify the choice determinants have been developed over the years. Several studies have been published as well as a number of reviews addressing this topic, in particular looking at determinants outside pure financial aspects (see e.g. Lutzenhiser, 1993; Stern, 1986; Wilhite et al., 2000; Uitdenbogerd, 2007).
2.1 Co- (or non-energy) benefits approach
To begin with, several research efforts are identified in the literature when it comes to co-benefits (e.g. improved housing comfort level, reduced noise, etc.) of energy efficiency technologies influencing their adoption. For instance, Mills and Rosenfeld (1996) note that many co-benefits (also called ‘non-energy benefits’) play critical role in consumer perception (and adoption) of energy-related technologies. Likewise, yet in the early 80s Stern and Aronson (1984:62) noted that “people do not usually weigh the potential value of the energy saved by one purchase against the pleasure, convenience or status achievable by alternative purchases”.
Stoecklein and Skumatz (2007) have weighted co-benefits for four various technologies associated with residential energy efficiency initiative (New Zealand, Zero and Low Energy Homes). Both positive and negative impacts (benefits/losses) have been reviewed. It is suggested, “residents place considerable value on the lifestyle benefits from energy-efficiency features of their homes, beyond benefits from energy savings”. The authors observed that energy related technologies have a potential to bring benefits other than energy saving (e.g. reduced noise, increased comfort, better energy bill control, etc.).[2] Significant benefits may relate to lifestyle and natural environment.[3] This type of non-energy impacts either becomes a “component of decision-making” or a “contributing reason for satisfaction”. Stoecklein and Skumatz (2007:1962) continue with noting that co-benefits are, indeed, market goods that influence the adoption of energy efficiency technologies as “they are purchased by consumers bundled with the energy-efficiency appliances that produce them”. The authors refer to ‘motivation’ factors that were classified earlier by Lutzenhiser (2006:90), namely: specific system/building concern; environmental health and energy costs; comfort level; and resource conservation. Amann (2006) stresses data collection and work to develop for a proper methodology for incorporating co-benefits in cost-benefit analysis. At earlier stage Skumatz (2002:307-316) compared use of three methods to estimate ‘hard-to-measure’ non-energy benefits of participants of low-income weatherisation programmes. Skumatz (2002) concluded that estimation of overall non-energy benefits in relation to energy benefits within weatherisation programmes could range from 80% to 100% or USD65-USD100.
· Relative valuation. The following benefits have been reported as more valuable than energy savings according to this approach: Control of bills (by 52% of respondents); comfort (34%); environmental (17%); maintenance (16%); moving avoided (13%); change in number of sick days (8%); appearance (6%); added features (6%); noise reduction (4%).
· Willingness-to-pay. This evaluation method approached what programme participants care about. The following results were obtained: comfort (76%); education/control (55%); features/options (30%); noise reduction (30%); appearance (29%). Yet, this resulted in overstatement of individual non-energy benefits that generated a bigger sum than participants would be willing to pay for overall benefits (including energy benefits).
· Labelled Magnitude Scaling. This approach brought about the figure close to the first method. Non-energy benefits comprised 99% of energy benefits from weatherisation and house envelope improvement. In dollar terms value of non-energy benefits was computed to USD70-USD110.
Within the context of co-benefits, Knight et al. (2006) bring forward that motivational surveys suggest that customers incorporate “perceived non-energy benefits” into their decisions, which does not exclude their rational choice. The benefits that accompany retrofitting choices (insulation, appliances, etc.) include increased comfort, reduced noise, improved health, safety, durability properties, and a sense of environmental citizenry, first-on-the-block status, long-term value, and overall peace in mind. They may have a dominating influence on decisions compared to the energy (operational) costs, use and conservation aspects as such. They conclude that based on their survey’s tentative results, “most homeowners appear to value the variety of non-energy benefits much more higher than the energy cost savings”. (Knight et al., 2006: 5-8).
While some authors did not place focus on decision-making phase, for others it seemed central. Knight et al. (2004) do highlight the existence of “full range of performance benefits” that helps homeowners to justify their (investment or purchase) decisions when “energy efficiency alone is insufficient”. (Knight et al., 2004: 7-162). They note that such other benefits would have their subjective utility being characteristic to individual homeowners. Such benefits like “family health, safety, comfort, or prestige” may be significant to become a factor in a purchase or investment decision. Further on the authors share their reservation on available dependable statistical data or studies underway to shed some light on measurable co-benefits effects or perceptions (though rather on the retrofitting part).[4]
2.2 Intervention factors approach
Another important systematic approach looking into energy efficiency intervention success factors was taken by Uitdenbogerd et al. (2007).[5] Their review covered vast body of research in various energy efficiency measures beyond housing envelope and weatherisation. It aimed to identify the determinants influencing different components of end-use energy efficiency and present their significance. The approach was to estimate importance of determinants, including the investment behaviour of households with the help of Intervention Mapping Protocol (normally applied in healthcare). This evaluation is basically derived from the number of times respondents in the reviewed references were revealing statistical significance of one or another determinant in a specific context. The team has arrived at the estimations of importance of various criteria on household investment behaviour: They identified personal and external determinants, demographical and contextual factors and quantified their influence/strength with the help of Intervention Mapping Protocol.