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Cost Focus versus Comfort Focus: Evidence from a Discrete Choice Experiment with Swiss Residential Electricity Customers
Abstract
Based on a discrete choice experiment with 582 households in Switzerland, we find, that about 30% of the customers focus on price risks (cost focus) when they choose an electricity tariff, while 70% of the customers are more worried about volume risks (comfort focus). Customers with a cost focus, prefer contracts with low price risks and automatic load control, even when these contracts increased their volume risks and may lead to discomfort, while customers with a comfort focus are unlikely to choose a contract that exposes them to either price or volume risks.
All customers prefer direct load control of individual appliances to capacity subscriptions or other demand response approaches which limit their total electricity demand. While customers with a cost focus likely accept direct load control even if this reduces their comfort, enrolling customers with a comfort focus will require further efforts and contracts avoiding comfort loss.
Research today entails the use of complex and effective tools for research. Hoping to provide for this need, The Oxford Handbook of Quantitative Methods in Psychology hopes to deliver some valid and generalizable answers to contemporary challenging research quandaries. It is a source for learning and reviewing current best-practices in quantitative methods as practiced in the social, behavioral, and educational sciences. Made up of two volumes, this text covers a breadth of topics related to quantitative research methods. It starts by looking at essential philosophical and ethical issues related to science and quantitative research. It then examines core measurement topics before moving onto topics related to the design of studies. Principal issues related to modern estimation and mathematical modeling are also detailed. The text then moves forward to the realm of statistical inference and modeling with articles dedicated to classical approaches as well as modern latent variable approaches. Numerous articles associated with longitudinal data and more specialized techniques finish this study.
While automation helps to increase load-shifting, the combination of automation with time-of-use (TOU) or critical-peak prices (CPP) may lead to rebound peaks at the beginning of low-tariff periods which may exceed the original peak. Using a discrete choice experiment with a representative sample of 696 Swiss consumers, we find that a tariff menu including (i) a flat price with direct load control (DLC) and (ii) a time-of-use tariff without direct load control could avoid this problem. The majority (57%) of mostly younger customers, which could be interested in automation would likely sign up for a DLC with flat prices, while the remaining customers would either chose a TOU tariff with manual load control (28%) or avoid any form of load-shifting incentives (15%).
Utility controlled heat pumps and electric vehicles via Direct Load Control (DLC) programmes could potentially be a solution for tackling challenges in the distribution networks by balancing intermittent renewable electricity sources. However, in many countries, DLC programmes do not have satisfactory enrolment rates. This paper investigates acceptance and preferences of DLC programmes for heat pumps and electric vehicles (EV) offered by a local Distribution System Operator (DSO), using a discrete choice experiment on a sample of 556 respondents residing in Switzerland. We first found that the acceptance ranged between 33% and 71% in different socio-economic groups. Secondly, multinomial logit results showed that financial incentives were the most preferred attribute for heat pumps, whereas it was the overriding option for the EV DLC programme. Finally, we explored the source of heterogeneity in preferences among different socio-economic groups with a latent class model. Preferences are found to differ between three classes, different gender and employment groups tend to be sensitive to different attributes of the DLC programmes. We draw attention to attributes of the utility based DLC programmes and provide policy recommendations to successfully address the diverse household preferences when deploying DLC programmes.
Direct Load Control (DLC) of heat pumps and electric vehicles (EVs) could offer great potential to decarbonize the distribution grid network by aligning demand with intermittent renewable technologies as well as avoiding congestion during peak times. However, little is known about consumer preferences for different designs of a DLC programme and their reasonings. To address this gap, this study investigates the preferences for the design of DLC programmes for heat pumps and EVs, using a discrete choice experiment on a sample of 556 respondents residing in Switzerland. We then propose a theoretical framework to provide insights into the underlying reasons such as social-psychological factors and perceptions for those preferences. We applied a multinomial logit analysis to elicit the preferences and found that overall sample was more sensitive to financial incentives for the DLC for heat pumps whereas more sensitive to the overriding option for the DLC for EVs. We then estimated a latent class choice model to explore the heterogeneity in preferences, identifying three distinct classes that vary in their preferences of different attributes. The model suggests that the preferences for the design are influenced mainly by perceived concerns related to being too dependent on the DLC programmes, trust in the utility company that they are transparent when providing information, attitude towards and knowledge on DLC programmes. Utilities will need to carefully address these issues in the programme design to ensure a widespread acceptance.
Sensitivity to scope in nonmarket valuation refers to the property that people are willing to pay more for a higher quality or quantity of a nonmarket public good. Establishing significant scope sensitivity has been an important check of validity and a point of contention for decades in stated preference research, primarily in contingent valuation. Recently, researchers have begun to differentiate between statistical and economic significance. This paper contributes to this line of research by studying the significance of scope effects in discrete choice experiments (DCEs) using the scope elasticity of willingness to pay concept. We first formalize scope elasticity in a DCE context and relate it to economic significance. Next, we review a selection of DCE studies from the environmental valuation literature and derive their implied scope elasticity estimates. We find that scope sensitivity analysis as validity diagnostics is uncommon in the DCE literature and many studies assume unitary elastic scope sensitivity by employing a restrictive functional form in estimation. When more flexible specifications are employed, the tendency is towards inelastic scope sensitivity. Then, we apply the scope elasticity concept to primary DCE data on people’s preferences for expanding the production of renewable energy in Norway. We find that the estimated scope elasticities vary between 0.13 and 0.58, depending on the attribute analyzed, model specification, geographic subsample, and the unit of measurement for a key attribute. While there is no strict and universally applicable benchmark for determining whether scope effects are economically significant, we deem these estimates to be of an adequate and plausible order of magnitude. Implications of the results for future DCE research are provided.
Many consumers do not take advantage of lower energy prices available in liberalized retail markets. We provide evidence to explain why consumers may leave substantial amounts of “money on the table” in this way. We observe real decisions made by over 7,000 consumers in a collective switching auction, supplemented by their responses to a survey. We identify factors which may inhibit switching and show that expectations of high switching rates in an unregulated market may be unrealistic. Our findings have important implications for the design and regulation of energy markets, including imposition of price caps on “default” retail tariffs in 2019 in the UK and parts of Australia.
Empirical evidence across several electricity markets reveals heterogeneous customer preferences for direct load control and other electricity service offerings but relatively little is understood concerning the drivers of this preference heterogeneity. Using a discrete choice experiment examining the potential role of domestic appliance curtailment contracts as a means of shifting load, this paper investigates potential drivers of preference heterogeneity with respect to electricity services. The research finds that electricity customers’ personal characteristics, including their environmental attitudes and behaviours, are associated with preferences for curtailment contract attributes though the scale of the relationship is more nuanced and muted than might have been anticipated. Age, family size, and environmental attitudes are the respondent characteristics with the strongest association with preferences, though the nature of the association varies substantially across attributes.
Latent class analysis (LCA) is a statistical procedure used to identify qualitatively different subgroups within populations who often share certain outward characteristics. The assumption underlying LCA is that membership in unobserved groups (or classes) can be explained by patterns of scores across survey questions, assessment indicators, or scales. The application of LCA is an active area of research and continues to evolve. As more researchers begin to apply the approach, detailed information on key considerations in conducting LCA is needed. In the present article, we describe LCA, review key elements to consider when conducting LCA, and provide an example of its application.
Demand response is increasingly attracting policy attention. It involves changing electricity demand at different times based on grid conditions, which could help to integrate variable renewable generation and new electric loads associated with decarbonisation. Residential consumers could offer a substantial new source of demand-side flexibility. However, while there is considerable evidence that at least some residential users engage with at least some forms of demand response, there is also considerable variation in user engagement. Better understanding this variation could help to predict demand response potential, and to engage and protect consumers participating in demand response. Based on a systematic review of international demand response trials, programmes and surveys, we identify motivations for participation, and barriers and enablers to engagement including familiarity and trust, perceived risk and control, complexity and effort, and consumer characteristics and routines. We then discuss how these factors relate to the features of different demand response products and services. While the complexity of the evidence makes it difficult to draw unequivocal conclusions, the findings of this review could contribute to guide early efforts to deploy residential demand response more widely.
Residential demand response (meaning changes to electricity use at specific times) has been proposed as an important part of the low carbon energy system transition. Modelling studies suggest benefits may include deferral of distribution network reinforcement, reduced curtailment of wind generation, and avoided investment in reserve generation. To accurately assess the contribution of demand response such studies must be supported by realistic assumptions on consumer participation. A systematic review of international evidence on trials, surveys and programmes of residential demand response suggests that it is important that these assumptions about demand response are not overly optimistic. Customer participation in trials and existing programmes is often 10% or less of the target population, while responses of consumers in existing schemes have varied considerably for a complex set of reasons. Relatively little evidence was identified for engagement with more dynamic forms of demand response, making its wider applicability uncertain. The evidence suggests that the high levels of demand response modelled in some future energy system scenarios may be more than a little optimistic. There is good evidence on the potential of some of the least ‘smart’ options, such as static peak pricing and load control, which are well established and proven. More research and greater empirical evidence is needed to establish the potential role of more innovative and dynamic forms of demand response.
Latent class analysis (LCA) is a statistical method used to identify unobserved subgroups in a population with a chosen set of indicators. Given the increasing popularity of LCA, our aim is to equip psychological researchers with the theoretical and statistical fundamentals that we believe will facilitate the application of LCA models in practice. In this article, we provide answers to 10 frequently asked questions about LCA. The questions included in this article were fielded from our experience consulting with applied researchers interested in using LCA. The major topics include a general introduction in the LCA; an overview of class enumeration (e.g., deciding on the number of classes), including commonly used statistical fit indices; substantive interpretation of LCA solutions; estimation of covariates and distal outcome relations to the latent class variable; data requirements for LCA; software choices and considerations; distinctions and similarities among LCA and related latent variable models; and extensions of the LCA model. To illustrate the modeling ideas described in this article, we present an applied example using LCA. Specifically, we use LCA to model individual differences in positive youth development among college students and analyze demographic characteristics as covariates and a distal outcome of overall life satisfaction. We also include key references that direct readers to more detailed and technical discussions of these topics for which we provide an applied and introductory overview. We conclude by mentioning future developments in research and practice, including advanced cross-sectional and longitudinal extensions of LCA.
Time of use (TOU) tariffs, if widely adopted, could help make electricity more secure, clean and affordable. However, quite little is known about whether consumers will switch to a TOU tariff or what might increase uptake if switching rates are lower than required. This paper presents the results of a systematized review and meta-analysis combining the results of 66 measures of uptake to a variety of TOU tariffs across 27 studies conducted in six countries. It provides the first robust estimate of consumer demand and correlates of demand for TOU tariffs that is not based on the results from just a single study or tariff. Four main conclusions emerge. First, if consumers are left to opt-in to TOU tariffs, uptake could be as low as 1% unless efforts are made to close the intention-action gap, otherwise enrolment could reach 43%. Second, if enrolment is opt-out, uptake could approach 100%. Third, whilst national surveys indicate the potential appetite for TOU tariffs in a population, they are insufficient for predicting future TOU tariff adoption rates; the median proportion of domestic energy bill payers who say they would be willing to switch to a TOU tariff in national surveys is five times higher than the median enrolment rate to TOU tariffs offered by utilities. Fourth, real-time pricing tariffs, in which the price of electricity varies freely throughout the day, are less popular than static TOU tariffs which have fixed peak and off-peak rates. This paper discusses the limitations of opt-out enrolment for TOU tariffs and presents results suggesting that small upfront payments, bill protection and automation are promising alternative methods of increasing opt-in enrolment. Policymakers and researchers should now consider how recruitment will be performed , weighing up the benefits to society as a whole against the distributional impacts for individuals and groups.
Residential direct load control (DLC) is an important type of demand response designed to reduce electricity consumption during peak hours through utility companies' control over the operation of certain household appliances. Despite many benefits of DLC, customers' concern for losing control has been hindering its adoption. This study aims to investigate U.S. residents' willingness to accept two popular A/C-related DLC programs in summertime with or without financial incentives or an override option, and to identify the socio-demographic characteristics associated with the decisions. Results of an online survey among 1482 U.S. residents indicate half of the participants are willing to accept DLC without any conditions; however, both an incentive of $30 and an override option boost acceptance rates. Importantly, the override option is more effective than the financial incentive. Residents who are younger, Democrats, non-Whites, have higher education levels, live in larger dwellings, and live with more people are more likely to adopt DLC than their counterparts. Residents who are older, Republicans, Whites, homeowners, and live in a house preferred an override option to financial incentives more often. The implications were discussed in terms of improving power system stability through better DLC program design and implementation.
The Swiss Household Energy Demand Survey (SHEDS) has been developed as part of the research agenda of the Competence Center for Research in Energy, Society, and Transition (SCCER CREST). It is designed to collect a comprehensive description of the Swiss households’ energy-related behaviors, their longitudinal changes and the existing potentials for future energy demand reduction. The survey has been planned in five annual waves thus generating a rolling panel dataset of 5,000 respondents per wave. The first two waves of SHEDS were fielded in April 2016 and April-May 2017. This paper elaborates on SHEDS’s general objectives, design, and implementation. It also reports a series of practical examples of how the datasets are being used in empirical analyses.
Since 2008, fewer customers switched suppliers in British electricity and gas markets despite the potential for financial gains, suggesting that psychological factors may affect switching behaviors. Using a unique nation-wide British survey, we explore the influence of consumers’ attitudes and perceptions on switching behaviors and assess the differences in switching propensity across different groups. Support for simplifying energy tariffs, professed less difficulty in understanding energy bills, expected difficulty in changing suppliers and lack of attention to the issue of energy prices are associated with lower switching activity. At a time of high saliency, political party voting intention was strongly related to switching. Unlike the bivariate analyses conducted by the regulator and the competition authority, our multivariate analysis show few demographic factors affect the likelihood of switching except for educational attainment and tariff payment patterns. Remedies aiming to encourage switching cannot be targeted correctly unless the supporting analysis is robust to alternative model specifications.
Addressing the challenge of peak demand is a major priority for energy utilities, regulators and policymakers worldwide. Against this backdrop, residential demand management solutions – including direct load control technology that allows utilities to turn specific household appliances on and off during peak periods – are becoming increasingly important. While such technology has been available for decades, acceptance and adoption among residential consumers has not always kept pace. Why is this so? Drawing on key principles from psychology and behavioural economics, we propose that consumer distrust can play a significant role in the uptake of demand management solutions. As part of a large field study, a survey-experiment was conducted to investigate householders’ willingness to participate in a direct load control program offered by an Australian energy company. To specifically examine the relationship between self-reported distrust and willingness to participate, and how this relationship might be influenced, the survey included an unobtrusive experimental manipulation: a simple two-sentence message designed to rebuild consumer trust and confidence in the utility was conveyed to a randomly-selected subsample of participants. Results suggested that participants’ self-professed distrust in the utility was associated with significantly lower willingness to register for the DLC program. This unwillingness was modestly reduced for those participants who received the trust-restoring message upfront. Together, these results suggest that distrust may serve as an important decision-making heuristic used by consumers when choosing whether to accept new demand management technology and services. Implications for future research and practice are discussed.
Revenue management and dynamic pricing are concepts that have immense possibilities for application in the energy sector. Both can be considered as demand-side management tools that can facilitate the offering of different prices at different demand levels. This paper studies literature on various topics related to the dynamic pricing of electricity and lists future research avenues in pricing policies, consumers’ willingness to pay and market segmentation in this field. Demand and price forecasting play an important role in determining prices and scheduling load in dynamic pricing environments. This allows different forms of dynamic pricing policies to different markets and customers depending on customers’ willingness to pay. Consumers’ willingness to pay for electricity services is also necessary in setting price limits depending on the demand and demand response curve. Market segmentation can enhance the effects of such pricing schemes. Appropriate scheduling of electrical load enhances the consumer response to dynamic tariffs.
Consumer acceptance of smart meters remains crucial in achieving the potential carbon emission reductions offered by advanced metering infrastructures. Given this, the present research used deliberative focus groups to examine what is needed to secure acceptance and engagement from domestic consumers with services, products and ‘offers’ in smarter power systems. Our findings suggest that consumers are able to identify not just threats relating to smart metering initiatives but opportunities as well. In particular, our focus group participants responded positively to the idea of an automated system that could be used to achieve energy savings in combination with time-of-use tariffs. We conclude by outlining suggestions for policy recommendations that may help consumer acceptance of smart meter enabled services be more readily achieved.
The transition to smart grids is an on-going process that may both shape and be shaped by end-users' energy behavioural adaptations. This study explores current and potential energy behavioural adaptations in Portugal during the smart grid transition process. A web-based survey was made to a representative sample of a specific segment of Portuguese residential end-users. The survey evaluated current energy behaviours and hypothetical future behaviours in a dynamic pricing scenario. Results show this population segment has a positive predisposition towards smart technologies and demand shifting, but it is less likely to accept load control and switch to the liberalised energy market. Factors influencing the behavioural potential are mostly related with market regulation, households' practices and usage behaviours, interference with the private domain, information and technical aspects, and social values. To facilitate behavioural adaptations several strategies are recommended, such as improving the energy market regulation, assessing households' behaviours, prioritising actions already embedded in households daily routines, not interfering with their activities and ensure an override option, and improving energy services, trust and information provided to end-users. The conclusions of the present study are of utmost importance for the design of more effective demand response programmes and energy policies.
The provision of energy consumption feedback on in-home displays (IHDs) has a prominent role in government strategies for domestic energy demand reduction. Research suggests that IHDs can support energy consumption reduction, but also that engagement with IHDs can be limited to men and is often short-term. In this paper, we draw on research carried out in Smart Communities, a two-year project in which electricity and gas consumption feedback played a key role. This study was distinctive because it was accompanied by a weekly email communications programme and was provided within the context of community action. Project findings suggest that, although by no means panaceas, approaches such as these can support long-term engagement with energy consumption feedback, including by women, and can support behaviour change.
Domestic demand-side response (DSR), if widely adopted, could help make electricity more secure, clean and affordable. However, little is known about consumer demand for different approaches to achieving DSR. This study aimed to gauge the acceptability of a range of DSR tariffs, and explore factors affecting it. An online between-subjects survey experiment was deployed to a representative sample of bill payers in Great Britain (N = 2002), testing five tariffs including static/dynamic time of use (TOU) pricing (with/without automated response to price changes) and direct load control (DLC) of heating on a below-average flat rate.
The tariff permitting limited DLC of heating was significantly (p < .01) more popular than the TOU tariffs. This was surprising given evidence for concern around loss of control in DLC, and suggests that for many people DLC is acceptable in principle (within tight bounds and with override ability). The option of automated response made dynamic TOU (otherwise the least popular tariff) as acceptable as static TOU. This is important because dynamic TOU offers additional network benefits, while automation can improve duration and reliability of response. The TOU tariffs were rated highly for giving people control over spending on electricity, but other factors were more associated with overall acceptance.
Two basic theoretical approaches are available for making reliable estimates of households' willingness to pay: this paper investigates the approach termed the "contingent valuation method' because the interviewer poses questions within the context of a hypothetical market. The preliminary results strongly suggest that contingent valuation surveys are a feasible method for estimating individuals' willingness to pay for improved water services in rural Haiti. This has important policy implications for rural water supply projects because it seems to show that going into a village and conducting a relatively simple household survey can yield reliable information. Contingent valuation surveys may also prove to be a viable method of collecting information on individuals' willingness to pay for a wide range of public infrastructure projects and public services in developing countries. -from Authors
Smart grids are a key feature of future energy scenarios, with the overarching goal of better aligning energy generation and demand. The work presented here considers the role of the user in such systems, and the contexts in which such roles might emerge. The data used is drawn from focus groups with 72 participants, using novel scenario techniques to contextualise smart grid technologies in domestic settings. Two contrasting visions of the smart grid are presented, a centralised system based on current institutional arrangements, and an alternative system in which decentralisation of generation and control is pursued. Using the concepts of ‘energy consumer’ and ‘energy citizen’, the paper considers what forms of engagement are likely to be generated by the two visions. We propose that smart grid designs must look beyond simply the technology and recognise that a smart user who is actively engaged with energy is critical to much of what is proposed by demand side management. We conclude that the energy citizen holds out most promise in this regard. The implications of this for policy makers are discussed.
This review is motivated by our recognition that an adequate and reliable electricity supply is a critical element in economic growth. From a customer’s perspective, electricity has several distinct attributes: quality, reliability, time of use, consumption (kW h) volume, maximum demand (kW), and environmental impact. A differentiated product can be formed by packaging its non-price attributes at a commensurate price. The review weaves the academic literature with examples from the real world to address two substantive questions. First, is product differentiation a meaningful concept for electricity? Second, can product differentiation improve grid operations and planning, thereby lowering the cost of delivering electricity services? Based on our analysis and comprehensive review of the extant literature, our answer is “yes” to both questions. We conclude that applying product differentiation to electricity can greatly induce end-users to more effectively and efficiently satisfy their demands upon the system, and to do so in an environmentally friendly way.
This paper explores methodological issues surrounding the use of dis-crete choice experiments to elicit values for public goods. We develop an explicit game theoretic model of individual decisions, providing conditions under which surveys with a single binary choice question, or sequence of binary choice questions, are incentive-compatible. We complement the theory with a framed field experiment, with treat-ments that span the spectrum from incentive-compatible, financially binding decisions to decisions with no direct financial consequences. The results suggest truthful preference revelation is possible, pro-vided that participants view their decisions as having more than a weak chance of influencing policy. (JEL C83, C93, H41, Q23) S urvey-based methods for eliciting preferences have been a mainstay in vari-ous strands of research, including the valuation of public goods, the study of transportation mode choice, the measurement of the value of a statistical life, and the marketing of consumer products. More recently, surveys have been used to measure economic variables such as income expectations, life expectancy, and the level of happiness. Stated preference surveys are often the only practical approach for gauging preferences for non-market goods and for evaluating public policies prior to their implementation. In particular, these methods are widely recognized as the only approach for measuring passive-use values such as the existence value of endangered species protection. Estimates of non-market values are important com-ponents of many government-mandated benefit-cost analyses, and are admitted as evidence in legal proceedings over environmental damages (e.g., following an oil spill). Despite the widespread use of these methods, the role of economic incentives in shaping participant responses remains poorly understood.
We provide controlled laboratory evidence that open-ended hypothetical surveys do not always accurately elicit real economic commitments from individuals. We argue that they can provide biased measures of true values, where the latter are elicited using incentive-compatible institutions. We also evaluate if it is the hypothetical-payment aspect of these surveys which results in these biases or the lack of explicitly incentive-compatible provision rules. We conclude that it is the former. We are unable to devise a hypothetical survey that uses an incentive-compatible provision rule to elicit valuations that are demonstrably truthful.
This book describes the new generation of discrete choice methods, focusing on the many advances that are made possible by simulation. Researchers use these statistical methods to examine the choices that consumers, households, firms, and other agents make. Each of the major models is covered: logit, generalized extreme value, or GEV (including nested and cross-nested logits), probit, and mixed logit, plus a variety of specifications that build on these basics. Simulation-assisted estimation procedures are investigated and compared, including maximum simulated likelihood, method of simulated moments, and method of simulated scores. Procedures for drawing from densities are described, including variance reduction techniques such as anithetics and Halton draws. Recent advances in Bayesian procedures are explored, including the use of the Metropolis-Hastings algorithm and its variant Gibbs sampling. No other book incorporates all these fields, which have arisen in the past 20 years. The procedures are applicable in many fields, including energy, transportation, environmental studies, health, labor, and marketing.
The German energy transition has led to a strong expansion of renewable energies in recent years. As a result, the German population is increasingly coming into contact with generation facilities. To increase local acceptance for new installations and to create new sales channels for energy suppliers, the legislature has established the “System for Guarantees of Regional Origin” in 2019, which allows the marketing of electricity from subsidized facilities as “electricity generated in the region”. However, regional electricity comes with additional costs on the procurement and sales side of energy suppliers, and it is unclear whether and to what extent consumers are willing to pay a premium for electricity generated regionally. This study investigates the willingness to pay (WTP) of residential customers based on two samples of 838 and 59 respondents, respectively. Our model results show that, on average, WTP for regional electricity generation is positive, especially among female, younger and better-educated customers, although differences in WTP between these sociodemographic characteristics are small. Factors that are more relevant are the current type of electricity tariff, differentiated into non-green and green, with the latter having a positive influence, but also the tariff switching behavior of the past, which is a proxy for price sensitivity. Although WTP is positive, it is severely limited, and only pertains to a subgroup of electricity customers. Hence, it is not surprising that our simulation shows that including a regional green electricity tariff in an energy supplier's portfolio is likely to lead to product cannibalization, meaning that mainly green electricity customers will choose this tariff. From an energy supplier's perspective, these results raise the question of whether offering a regional electricity tariff is economically viable. Future research could further investigate what underlying factors drive preferences for regionally generated electricity and how it can contribute to local acceptance.
Latent class analysis is a probabilistic modeling algorithm that allows clustering of data and statistical inference. There has been a recent upsurge in the application of latent class analysis in the fields of critical care, respiratory medicine, and beyond. In this review, we present a brief overview of the principles behind latent class analysis. Furthermore, in a stepwise manner, we outline the key processes necessary to perform latent class analysis including some of the challenges and pitfalls faced at each of these steps. The review provides a one-stop shop for investigators seeking to apply latent class analysis to their data.
This article proposes contemporary best-practice recommendations for stated preference (SP) studies used to inform decision making, grounded in the accumulated body of peer-reviewed literature. These recommendations consider the use of SP methods to estimate both use and non-use (passive-use) values, and cover the broad SP domain, including contingent valuation and discrete choice experiments. We focus on applications to public goods in the context of the environment and human health but also consider ways in which the proposed recommendations might apply to other common areas of application. The recommendations recognize that SP results may be used and reused (benefit transfers) by governmental agencies and nongovernmental organizations, and that all such applications must be considered. The intended result is a set of guidelines for SP studies that is more comprehensive than that of the original National Oceanic and Atmospheric Administration (NOAA) Blue Ribbon Panel on contingent valuation, is more germane to contemporary applications, and reflects the two decades of research since that time. We also distinguish between practices for which accumulated research is sufficient to support recommendations and those for which greater uncertainty remains. The goal of this article is to raise the quality of SP studies used to support decision making and promote research that will further enhance the practice of these studies worldwide.
Rising shares of fluctuating renewables increase the need for flexibility in the power market. At the same time, the emergence of the prosumer has created new opportunities for co-creation of distributed flexibility. As of yet, there is surprisingly little empirical analysis in terms of whether individuals are actually ready to co-create flexibility, and if so, under which conditions these resources can be mobilized by grid operators or electricity supply companies. We address this gap in the energy economics literature with three studies analyzing in total 7′216 individual decisions in a series of choice experiments with 902 study participants in three main domains of residential energy prosumption: (1) solar PV plus storage, (2) electric mobility, (3) heat pumps. We develop a novel measure of the prosumers’ willingness to co-create flexibility, and solicit their preferences for power supply contracts with varying levels of flexibility to derive implied discomfort costs. Our results indicate that current and potential electric car and solar PV users exhibit a higher willingness to co-create flexibility than heat pump users. Reaping the potential in those two domains requires taking the prosumer perspective into account when designing policy instruments and creating adequate business models.
We design a choice experiment comparing policies that reduce agricultural nutrient pollution and harmful algal blooms in Lake Erie and administer it to Ohio residents using an online survey panel. We compare two treatments that have been found to mitigate hypothetical bias, cheap talk and honesty priming, with a neutral priming control. We find greater sensitivity to price among respondents during choices made immediately following the cheap talk intervention. As additional choices are made, the “wedge” between price sensitivity in the control and honesty prime treatments diminishes and eventually loses statistical significance. We find this effect in both our online choice experiments and among respondents to face-to-face choice experiments conducted by de-Magistris, Gracia, and Nayga. Our online implementation of an honesty priming intervention yields no significant change in price sensitivity compared to a control. While de-Magistris et al. implement an honesty priming intervention that fully mitigates hypothetical bias in a face-to-face setting, we show that this effect is also transient, and in later choice exercises we cannot reject the null hypothesis of equality between honesty priming and the control. Our results are robust to multiple specifications and suggest additional work is required to adapt priming interventions for online settings and to extend the effectiveness of popular hypothetical bias mitigation techniques when respondents face multiple choice tasks.
The increasing penetration of renewable energy sources (RES) in power systems intensifies the need of enhancing the flexibility in grid operations in order to accommodate the uncertain power output of the leading RES such as wind and solar generation. Utilities have been recently showing increasing interest in developing Demand Response (DR) programs in order to match generation and demand in a more efficient way. Incentive- and price-based DR programs aim at enabling the demand side in order to achieve a range of operational and economic advantages, towards developing a more sustainable power system structure. The contribution of the presented study is twofold. First, a complete and up-to-date overview of DR enabling technologies, programs and consumer response types is presented. Furthermore, the benefits and the drivers that have motivated the adoption of DR programs, as well as the barriers that may hinder their further development, are thoroughly discussed. Second, the international DR status quo is identified by extensively reviewing existing programs in different regions.
Consumers’ preferences regarding the security of supply (SoS) of electricity are generally assessed through economic estimates of the value of lost load. However, this monodisciplinary approach typically builds on homo oeconomicus assumptions and neglects consumers’ nonmonetary evaluations of SoS. This can result in short-sighted regulation, especially in the context of a transition like Germany’s Energiewende. This paper provides a consumer-centered perspective on SoS employing psychological and sociological research on energy. German consumers’ strong involvement in the Energiewende and their strong commitment to it make them a fascinating case. To determine the practical implications, we explore under what circumstances altered levels of SoS could be acceptable to consumers.
If widely adopted, domestic demand-side response (DSR) could help make Great Britain’s electricity system more secure, clean and affordable. However, research suggests some people have concerns about participating in DSR programmes, and prominent amongst these is a perceived loss of personal control. This programme of research used a combination of interview and survey methods to explore what such concern might encompass and how it relates to the acceptability of DSR. Initial focus group findings were drawn on to extend the Technology Acceptance Model (TAM) with perceived control constructs and develop an associated measurement scale. A survey experiment including the new scale was deployed to a representative sample of GB bill-payers (N=2002) to test for the first time the relative acceptability of static/dynamic time of use (TOU) tariffs, with/without automated response, and direct load control (DLC). DLC was shown to be acceptable in principle to many people, with a tariff permitting limited DLC of heating being significantly more popular than the TOU tariffs. The option of automated response made dynamic TOU (otherwise the least popular tariff) as acceptable as static TOU. This is important because dynamic TOU offers additional network benefits, while automation can improve duration and reliability of response. The tariffs were generally rated highly for giving people control over spending on electricity, but perceived control over general service quality, ease of use and savings potential were more important in overall acceptance and should be prioritized in product development/communication. Further research in a field trial including automated response by heat pumps to TOU tariffs highlighted various challenges if automated DSR is to be acceptable in reality. These include overheating potential when pre-heating at lower prices, the importance of ease of use, and effective override ability. The implications of these and other findings for policy, industry and research are discussed.
Many experts are concerned about the would-be character of smart grid users—specifically, that they will not engage with smart grid technologies out of disinterest or a lack of knowledge. This has been considered problematic because users are considered key to unlocking the full potential of the smart grid. This paper studied smart grid users from the Norwegian demo Steinkjer pilot and, through focus group interviews, collected articulations of everyday smart grid enactments. Eliciting little lack in knowledge or interest, users were able to articulate relevant smart grid enactments through a spectrum of skepticism, pragmatism and enthusiasm. Utilizing the concept of material publics [22], this paper argued that smart meters can bridge the green political economy of climate challenge issues with the user context of everyday energy consumption. The paper found evidence that user articulations, whether skeptical or enthusiastic, are rooted in political engagement as opposed to purely economic interest. This suggests a case for involving material publics in the smart grid and indicates that explanations for user disengagement can be found in active, subversive co-articulations among users rather than passive disinterest or a lack of knowledge. This paper suggests acknowledging smart grid users as politically engaged material publics.
Dynamic electricity pricing can produce efficiency gains in the electricity sector and help achieve energy policy goals such as increasing electric system reliability and supporting renewable energy deployment. Retail electric companies can offer dynamic pricing to residential electricity customers via smart meter-enabled tariffs that proxy the cost to procure electricity on the wholesale market. Current investments in the smart metering necessary to implement dynamic tariffs show policy makers’ resolve for enabling responsive demand and realizing its benefits. However, despite these benefits and the potential bill savings these tariffs can offer, adoption among residential customers remains at low levels. Using a choice experiment approach, this paper seeks to determine whether disclosing the environmental and system benefits of dynamic tariffs to residential customers can increase adoption. Although sampling and design issues preclude wide generalization, we found that our environmentally conscious respondents reduced their required discount to switch to dynamic tariffs around 10% in response to higher awareness of environmental and system benefits. The perception that shifting usage is easy to do also had a significant impact, indicating the potential importance of enabling technology. Perhaps the targeted communication strategy employed by this study is one way to increase adoption and achieve policy goals.
We review early technologies and experiments in the 1980's for implementing demand response. We argue that while new smart grid technologies are cheaper and provide more functionality the barrier to demand response implementation at the retail level lies in the development of business models that will incentivize customer participation on the retail side and facilitate integration of the aggregate responses into the wholesale market. We then describe such a model that is based on the concept of priority service where customer can choose different levels of interruption for segments of their loads which they can reallocate at will within the household. We review the theory of efficient pricing of such service along with alternative implementation forms. We then illustrate by means of an example the potential economic gains of such an approach.
Dynamic pricing is being discussed as one method of demand side management (DSM) which could be crucial for integrating more renewable energy sources into the electricity system. At the same time, there have been very few analyses of consumer preferences in this regard: Which type of pricing program are consumers most likely to choose and why? This paper sheds some light on these issues based on two empirical studies from Germany: (1) A questionnaire study including a conjoint analysis-design and (2) A field experiment with test-residents of a smart home laboratory. The results show that consumers are open to dynamic pricing, but prefer simple programs to complex and highly dynamic ones; smart home technologies including demand automation are seen as a prerequisite for DSM. The study provides some indications that consumers might be more willing to accept more dynamic pricing programs if they have the chance to experience in practice how these can be managed in everyday life. At the same time, the individual and societal advantages of such programs are not obvious to consumers. For this reason, any market roll-out will need to be accompanied by convincing communication and information campaigns to ensure that these advantages are perceived.
1. Choosing as a way of life Appendix A1. Choosing a residential telecommunications bundle 2. Introduction to stated preference models and methods 3. Choosing a choice model Appendix A3. Maximum likelihood estimation technique Appendix B3. Linear probability and generalised least squares models 4. Experimental design 5. Design of choice experiments Appendix A5. 6. Relaxing the IID assumption-introducing variants of the MNL model Appendix A6. Detailed characterisation of the nested logit model Appendix B6. Advanced discrete choice methods 7. Complex, non-IID multiple choice designs 8. Combining sources of preference data 9. Implementing SP choice behaviour projects 10. Marketing case studies 11. Transportation case studies 12. Environmental valuation case studies 13. Cross and external validity of SP models.
Recognizing the lack of retail-demand response, a state regulator, such as the California Public Utilities Commission (CPUC), seeks tariff proposals that transmit wholesale price signals to a local distribution company's (LDC) retail customers. To enable these proposals, the CPUC has authorized funding for advanced metering infrastructure (AMI) for two investor-owned LDCs. Assuming regulatory approval of the third LDC's application, the state's US$4.28 billion AMI investment will aid new rate designs for 11.3 million electricity customers. Now that California has AMI, what can the state do with it? With AMI in hand, an LDC can implement service options that can further the state's energy initiatives, ranging from resource adequacy requirement (RAR) to greenhouse gas (GHG) emissions reduction. These options can efficiently allocate limited capacity based on each customer's willingness to pay, without the unnecessary distinction between price rationing and reliability differentiation. They can be Pareto superior, welfare dominating the default tariffs that apply to these customers. A case in point is the generalized demand subscription service (GDSS) option proposed in this paper. However, it is unclear whether the option will find wide customer acceptance, without an LDC's intensive customer education and marketing efforts.
This paper investigates what a respondent is thinking when answering a willingness-to-pay question in a contingent valuation, using a "think aloud" technique from psychology called verbal protocol analysis. The willingness-to-pay responses we observed seem to be constructed from a variety of considerations, including an obligation to pay a fair share of the cost of the solution and signaling concern for a larger set of environmental issues. The finding that respondents seem to construct their values at the time they are asked, rather than reporting a more well-defined value, is seen as consistent with over two decades of research on the psychology of decision making. Potential uses of verbal protocols in contingent valuation studies are also discussed.