lable at ScienceDirect

Renewable Energy 145 (2020) 1910e1922

Contents lists avai

Renewable Energy

journal homepage: www.elsevier .com/locate/renene

Designing linked journey maps to understand the complexities of theresidential solar energy market

Ekaterina Sinitskaya a, Kelley J. Gomez a, Qifang Bao b, Maria C. Yang b,Erin F. MacDonald a, *

a Mechanical Engineering, Stanford University, United Statesb Mechanical Engineering, Massachusetts Institute of Technology, United States

a r t i c l e i n f o

Article history:Received 6 July 2018Received in revised form15 May 2019Accepted 4 June 2019Available online 10 June 2019

Keywords:Journey mapsDesign methodsSolar panel installationHuman-centered designRenewable energy

* Corresponding author.E-mail address: erinmacd@stanford.edu (E.F. MacD

https://doi.org/10.1016/j.renene.2019.06.0180960-1481/© 2019 Published by Elsevier Ltd.

a b s t r a c t

A journey map is a visual representation of a process undertaken by a person, and is related to productuse and human-centered design. Here, we introduce combined (linked) journey mapping techniques anduse them to capture a complex systemdresidential solar panel purchase and installationdfrom theperspectives of both the homeowner and the installer at the same time. Few studies have analyzed theinstaller, who we found significantly influences the homeowner's decisions. The advantage of the linkedjourney map over individual journey maps is that it decreases subjectivity of findings as “pain points”worthy of further study, and modeling can be verified from two or more vantage points. We demonstratethese maps as a semi-formal analytical tool to categorize, parameterize, and unite insights affecting bothstakeholders. We gathered data from in-depth interviews with homeowners and installers and builtindividual journey maps. Then we identified interactions between the two, and merged their two mapsto identify points on the journey that create difficulty or frustration. These maps provide comprehensiveinsight analysis for later surveys and agent-based model creation. We found that post-contract stageswere filled with pain points. Both homeowners and installers found the lack of communication betweenall stakeholders, slow permit processing times and lack of assistance from utilities and housing juris-dictions, and lack of standardization for the permitting process to be painful.

© 2019 Published by Elsevier Ltd.

1 Net energy metering is a program initiated through a public utility where

1. Introduction

Current solar energy research assumes the homeowner, as theend-user in the residential solar market, is the principal decision-maker who directly affects the rates of residential solar adoption[1,2]. Likewise, the solar industry's marketing practices focusalmost exclusively on the homeowner and on the financial benefitsfor the homeowner, such as highlighting the federal tax credit thatallows homeowners to deduct 30% of their cost of installing solar[3] or advertising airlines miles earned for installing solar [4].

While existing studies assessing a homeowner's willingness toadopt changes have considered scenarios involving incentive pro-grams [5], cost structure [6], and regulatory environments [7,8],these studies have also revealed additional decision-makers whosepolicies, marketing strategies, and regulations can inhibit or pro-mote adoption. These other agents are: installers, manufacturers,

onald).

utility agents, government officials, and financing companies. Fewstudies detail how these various decision-makers currently affectthe market or how they will affect the market in the future.

The large number of agent interactions make it difficult torealistically capture how the solar environment will look in thenext 20 years. Some models attempt to represent a decision-maker's effect on the market by using a single variable, such asusing solar panel efficiency to represent how a manufacturer's de-cisions affect solar adoption rates [9], or using changes in net en-ergy metering (NEM)1 to represent the decisions of a utility agent[8]. One model uses various incentive scenarios to represent thedecisions of a government official [5], and another model uses third-party financing to represent a financing company's decisions [6].

unused energy, generated by a residential solar system, can feed back to the grid.Akin to the AT&T concept of rollover minutes, the homeowner of the system willthen receive a rollover credit on their electricity bill for the next month, in theinstance that their energy usage exceeded their solar energy generation [8].

E. Sinitskaya et al. / Renewable Energy 145 (2020) 1910e1922 1911

While all these agentsdmanufacturer, utility agent, governmentofficial, and financing companydmake decisions affecting the in-dustry on an institutional level, these agents do not actively makedecisions at the level of a single residential system. One agent whodoes make decisions at the single-residential level and whosignificantly affects a homeowner's installation experience is theinstaller, but very few studies have modelled the decisions ofinstallers.

Because the installer is an important agent in the installationprocess, and because the installer's decision-making process is notyet well-understood and described, we attempt to determine theinfluence of an installer's decisions, and the installer's interactionswith the homeowner, on the solar installation process.2 Re-searchers have analyzed survey data [10,11] and residential solardata [12] to predict future adoption patterns, but these frameworksare limited because they only consider a single decision-maker (thehomeowner). In contrast, we use a design approach that centersboth the homeowner and the installer to clarify, understand, andaddress the complexity surrounding the decisions to adopt solar.Our approach uses two journey maps that are linked together.

A journey mapda qualitative, human-centered design toold-tracks and visualizes the discrete actions, thoughts, and feelings ofan agent's experience [13]. A journey map guides quantitativeencoding because it breaks down an agent's “journey” into indi-vidual steps. Tracking the journeys of both homeowners and in-stallers helps us pinpoint where those experiences overlap.Targeting the interactions to encode them in a predictive modelwill ensure that a solar installer's decisions are equally representedalong with the homeowner's decisions. While there is a level ofsubjectivity in defining an agent's journey map, there is a decreasedlevel of subjectivity when looking at the process from two differentperspectives at the same time. Our resulting linked map is adescription that is more formal than a case study but less formalthan a simulation and, more importantly, can reveal individual andmutual pain points (points of frustration) in the experiences ofhomeowners and installers. Then, while still early in the designprocess, these pain points can be analyzed and solutions for themcan be generated. These pain points indicate different model sce-narios, which can forecast how changes in the solar industry, andthe installation process specifically, may affect future rates of resi-dential adoption.

The main advantage of using multiple linked journey maps isdecreasing the subjectivity of the analysis. For example, in thehomeowner's journey map, one of the issues is the price of thesystem and the problem of financing it. When we look at only thesingle homeowner's journey map, it is hard to determine if thisproblem is a subjective one or if it is a significant barrier to adoptionthat exists on the market. Adding the installer's perspective, welearn that price and financing is also a significant pain point for theinstaller, which arises from the installer's challenge of getting thehomeowner over the shock of the price, and we can clarify the typeand severity of the issue. We now know that it is a mutual problemand probably a significant barrier to adoption. In this case there isan opportunity for institutional intervention that could decreasethe level of pain for both the homeowner and the installer (forexample, intervention could range from education about thepayback period to providing easier access to financing).

Additionally, linking the maps gives an accurate representationof the timing and order of events, which may be confusing whenlooking at the two maps separately.

2 We define the solar installation process as beginning when the homeownerbecomes interested in solar and ending when the solar system becomesoperational.

The use of linked journey maps can guide a more profounddevelopment of other researchmethodologies, namely agent-basedmodels. Agent-based models, and all mathematical models thatdescribe or include human behavior, can easily suffer from prob-lems with subjectivity, which lead to biases in the model such asconfirmation bias. Confirmation bias is the tendency to collect/include information that supports one's viewpoint while ignoringinformation that does not. When such bias is introduced into amodel, it negatively impacts the accuracy and usefulness of theresults. This is a challenge specifically for agent-based models. Asthemodels are generative in purpose, meaning they are built to findinsight in future events, they are extra-prone to problems with bias,or finding the results the researcher wishes to find. Thus, reducingsubjectivity and associated biases is of great importance in agent-based models, and constructing linked journey maps beforebuilding agent-based models can lead to more useful and lesssubjective models.

The rest of the paper proceeds as follows: in the followingsection, we review the literature on attempts to model the de-cisions of the homeowner and other agents in the solar market; wealso describe the traditional journey map, as well as ways to extendit. In Section 3, we develop a methodology for creating a morecomprehensive, combined (linked) journey map which accountsfor the experiences of multiple agents. We describe the steps wetook to create each journey map. Ultimately, we want to presentboth the results and the process for deriving the results to create areplicable framework that can be used in future research of othercomplex and interactive systems. In Section 4, Results, we describeour combined journey map and our reasoning in creating it. InSection 5, we discuss a number of our actions that we found to becritical in the process and we discuss answers to our researchquestions. In Section 6, we draw conclusions and insights gainedfrom these journey maps. These insights are generalizable to ana-lyses of complex systems in other domains, and we hope that re-searchers at the intersection of social and engineering sciences willadopt the combined journey map more widely.

2. Literature review

To elaborate on the preferences and decisions of homeownersand installers, a general understanding of the residential solarmarket environment is necessary. The number of residential solarmarket installations in the US at the end of 2015 was more than820,000 [12]. This number falls short of the national “Million SolarRoofs” campaign, promoted by the Department of Energy, whichenvisioned onemillion solar roofs installed by 2010 [14]. Because ofthis slower-than-expected growth of the residential solar market,researchers have modelled different incentive scenarios to assesstheir effect on current and future rates of adoption [15]. Tradi-tionally, models like the Solar Deployment System (SolarDS), aneffort of the National Renewable Energy Laboratory, have assumedhomeowners' decisions are based only on finances, and so theyhave used payback time as a proxy for a homeowner decision [16].The Lawrence Berkeley National Laboratory is prolific in its in-vestigations of the nature of the residential solar market, especiallyin California, which is known for its leadership in solar adoption,3

and of specific problems in the adoption process; for example,Burkhardt et al. studied the effect of local permitting processes oninstallation time and adoption decisions [7]. Adomatis et al. andHoen et al. looked at the valuation of homeswith a solar installation

3 California accounts for approximately 17% of the residential solar systemsinstalled. Based on the California Solar Initiative statistics, in 2015, California hadinstalled nearly 143,000 residential systems [29].

E. Sinitskaya et al. / Renewable Energy 145 (2020) 1910e19221912

[17,18], which can be featured in marketing materials used in theinitial adoption stages.

2.1. Attempts to model the Homeowner's decisions

Because a homeowner must navigate many considerationswhen determining whether to adopt solar, researchers are nowconcentrating on the customer experience and preferences. Macalet al. discuss how socio-behavioral preferences provide an addi-tional level of complexity to financial considerations (i.e., availableincentives, financing, and home premiums) [19]. Islam and Meadeanalyze a homeowner's general awareness of the solar industry, aswell as homeowners' opinions of solar's financial accessibility andenvironmental impact [1]. Their work confirms Macal et al.'sinsight that a deeper understanding of a homeowner's decision toadoptdwhether extrinsically or intrinsically influenceddis neededto accurately forecast solar adoption rates.

Current literature assesses homeowners' preferences for resi-dential solar technologies, mostly by using utility-level data andsurveys. Data sets for solar systems connected to a local utilityreveal trends in rates of solar adoption based on geography, systemsize, and technology but are limited in their ability to predict thereasonswhy these systems were installed in the first place. Surveyshave been used to supplement this quantitative analysis and pro-vide a more complete profile of the homeowner for agent-basedmodels [1,2]. However, the assumption remains that adoption isbased on a single decision-making agent, the homeowner, and themethodology for deriving the survey questions may be arbitrarilychosen or built only from past literature. It is, therefore, difficult toensure that a survey is obtaining a comprehensive understandingof a homeowner's preferences for or against solar.

Creating a predictive model that incorporates homeowners'preference data has proven challenging to date, and currently, thereis no study that provides a systematic overview of the entireinstallation experience. More work needs to be done to more fullyunderstand the motivations and effects of other decision-makers.

2.2. Attempts to model other decision-makers

A systematic overview of the entire installation experienceneeds to include all influences on the homeowner, as well as adescription of the way other decision-makers operate. Researchersoften neglect to consider the other agents, namely installers, whomake decisions that affect the design and deployment of solarsystems. Installers expose homeowners to system design, financialopportunities, available incentives, and the solar installation pro-cesses [20]. They propose a system design and price, influencingwhether homeowners think solar is economically feasible. In fact,an installer's geographic location and size of business affect theprice per watt charged for a solar system [21]. For example,SolarCity, a national solar company, offers various financialoptionsdleases, power purchase agreements (PPAs), loans, andpaying outrightdall at a competitive rate [6]. After a homeownercommits to a project, an installer is responsible for execution, butthe installation process can be impeded by unexpected soft costsand variable times associated with permitting and utility inter-connection [22]. Installers have their own preferences with regardto determining whether they will take on a customer or not [11].However, few studies have investigated the installer's uniquepreferences and decisions affecting the solar industry, partlybecause modeling the preferences of one agent (the homeowner) isalready complex.

2.3. The traditional journey map as a modeling tool

After assessing the methodologies used to clarify and under-stand complex systems, we found that journey maps of customerexperiences are often effectively used in similar contexts. A journeymap, a human-centered design tool, tracks the development of thecustomer experience and helps market analysts better understandwhy customers purchase a product [23]. A journey map is similar toa timeline in that it progresses chronologically, but differs in thatthe visual organization highlights important stages as well asemotional triggers and effects flowing in and out. The strength of ajourney map lies in its ability to outline an entire experience ratherthan just the parameters directly related to purchasing a product. Ithighlights the actions and decisions a customer experiences beforeand after the moment of purchase. Often, developing a journeymapconsists of five steps:

1 Identifying users and the target experience they are navigating,2 Conducting and synthesizing ethnographic research using

existing literature and data,3. Delineating and visualizing (as a timeline) the steps of the

experience,4. Assessing the user's emotional and logical inputs and outputs

for each step, and5. Analyzing where improvements to the experience can be made

based on the quality of the inputs and outputs.

These steps clarify why a customer adopts a product and why acustomer would consider recommending it through theircommunication channels [24].

Within product development, designers have employed thesemapping practices to understand and refine the user experience[24]. Two case studies on e-commerce, Rose et al. [25] and Man-giaracina et al. [26], realizing the increasing complexity of onlineshopping, employed journey map frameworks to investigate im-provements to the customer's online experience.

Clarifying the complexity of consumer preferences, especially inproduct adoption, is a defining feature of the journey-mapping tool.It reframes an experience and asks researchers to think about theexperience and environment from the perspective of the humanagents [13]. However, the two studies on e-commerce also revealan organic development that differs from journey map to journeymap: in one instance, journey maps were used to brainstorm allvariables affecting the adoption of a product [25]; in the other,journey maps were the mechanism through which structuredscenarios of the product space were developed [26]. What both ofthese case studies had in common was that the journey mappingframework was (1) employed at the beginning of the investigation,and (2) provided the basis for developing the project's futuremethodology.

This semi-formal design framework has never been applied tounderstanding the customer experience of a residential solar sys-tem, which is simultaneously a product, a home improvement, anenergy source, and a mark of sustainability. Applying journey mapsto the residential solar installation process can begin to clarify anexceedingly complex, interactive process.

2.4. Extending the journey map

Journey maps, while historically a tool in marketing and productdevelopment, have extended to service design. Used to clarify thecustomer's service experience, it reads similarly to a customer'sproduct experience. However, mapping the service experience in-troduces more layers of complexity because it increasingly focuseson the need for customer satisfaction before the purchase of the

E. Sinitskaya et al. / Renewable Energy 145 (2020) 1910e1922 1913

product [27]. While journey mapping is an accepted marketingtechnique, its use as a methodological framework in scientificliterature is still developing.

The sole focus on the customer is a limitation of a traditionaljourney map framework and of the aforementioned cases([19,25,26]). Despite multiple agents actively affecting thecustomer experience, journey maps have been confined to visual-izing one type of agent's experience. No study has employed a se-ries of journey maps, one for each type of agent's experience. Thenature of journey maps has always been that of one agent seekingto understand the other: producers use journey maps to under-stand and refine a consumer's experience [28]. Because existingresearch assumes producers passively respond to customer pref-erences, no consideration has been given to also assessing thejourney of the producer. However, in a complex environment,singling out the customer's decisions, without regard for the pro-ducer, neglects to account for the influence of the producer's de-cisions and preferences with regard to their design of the product.Because each human agent actively contributing to the development ofa system has preferences, multiple journey maps are needed to providea realistic, comprehensive understanding of an experience.

3. Methodology for journey mapping

We empirically derived and mapped the homeowner's and theinstaller's solar installation experiences. Separately, these maps canprovide valuable insights, but overlaying the homeowner's expe-rience on the installer's experience clarifies the complex in-teractions between the two decision-making agents and revealspain points that inhibit or delay rates of adoption. To clarify: we didnot collect data from matched homeowner-and-installer pairs;rather we separately collected data about homeowners and dataabout installers.

We present not only the final, linked journey map (in Section 4)but also the process we used in creating and refining it. Combiningthe separate journey maps results in a more comprehensive over-view of the solar installation process and highlights the interactivenature of the experience. The ultimate decision to combine the twomaps guided our approach to developing the individual journeymaps. While our specific methodology and resulting combinedjourney map are unique to this project, researchers can adapt thesemi-formal framework of thought to other fields that deal withequally complex problems requiring new, innovative approachesand analyses of decision processes and stakeholders' incentives.

Sections 3.1e3.5 describe steps that were taken to create indi-vidual journey maps; specifically, we focus on generalizableexperiences.

Table 1Roles of active decision-making agents.

Agent Decision/Action

Homeowner

Decides to incrementally increase the natiocapacity with a roof-top solar installation.

Installer

Incrementally adds systems to the nationalinstalled capacity.

3.1. Ethnographic studies of the homeowner and installer

Empirical methods are used to understand the solar installationexperience and to develop a comprehensive journey map. To begin,two principal decision-making agents were identified: the home-owner and the installer. Table 1 describes the role of these twoagents and emphasizes how they interact to affect the rates ofresidential solar adoption.

While other agents are important to the installation experience,their involvement in the economic environment is passive and isreserved to promoting or discouraging installations behind thescenes.

To empathize with the homeowner and develop a frameworkfor their preferences and decisions, two researchers, one in SanJose, California, and one in Belmont, Massachusetts, simulated ahomeowner's solar installation experience by using their personalresidences as potential solar sites. The findings from these simu-lations directed empathy interviews with homeowners and alsoprovided insights into an installer's solar installation experience.Researchers familiarized themselves with the domain and gainedpreliminary knowledge of principal stakeholders and possible in-teractions between them. It should be noted that having well-versed investigators was vital at this stage, given the very highlevel of structural complexity of the photovoltaic (PV) market. Re-searchers specifically were attuned to the details and structure ofthe interactions between main market agents; these two re-searchers were able to generalize their own experiences and iterateon journey maps that were focused on the interactivity of thewhole experience.

A local homeowners' association in Los Altos, California, and amiddle-class neighborhood in Belmont, Massachusetts, served asthe interview pool. A call for interviews was issued, and 4 home-owners in California and 8 homeowners in Massachusettsresponded. We conducted phone interviews with the Californiahomeowners and in-person interviews with the Massachusettshomeowners for roughly 30e60min each. The interview questionsare listed in Appendix B. Thenwe deconstructed each interviewandaggregated the installation process into a set of discrete stages (aninitial journey map). Visualized as a timeline, these stages werepresented to homeowners in a follow-up phone consultation toconfirm and refine the timeline. They were asked if there were anymistakes or inaccuracies in the journey map, and they were askedto compare their experience with the generalized journey map.

The perspective of the installer wasmore difficult to capture.Weparticipated in CalSEIA's (California Solar Energy Industry Associ-ation) Contractor Day at Intersolar North America, the largest solarconference on the West Coast, which provided a baseline fromwhich we built an ethnographic profile of a residential solarinstaller. Through conversations with installers participating in theconference, we found that an installer's experience is highly

Interaction

nal installed Responds to installer's offerings.

Presents the system design and financingoptions to homeowner.

E. Sinitskaya et al. / Renewable Energy 145 (2020) 1910e19221914

affected by a prohibitive regulatory environment. This insightdirected us to develop additional interview questions for installers.Our interview pool consisted of the installers from CalSEIA'sContractor Day and the California Solar Initiative (CSI) database ofactive installers in San Jose. We contacted 117 installers, and 23responded. Of those who responded, 9 were qualified to interview;the other responders excused themselves for: being retired, beinginactive, only installing commercial systems, or moving out of thestudied area. We conducted phone interviews for roughly 30mineach. The interview questions asked of the installer are listed inAppendix C.

Similar to the methodology used for homeowners, we identifieddiscrete stages the installers experienced as they went through theinstallation process. These stages were visualized as a timeline andthen, in a follow-up consultation with each installer, wereconfirmed and refined. In this case, researchers had to supplementempirically derived installer data with other data derived fromanalysis of official statistics on installations and other research intothe decision-making process of installers, for example [11].

3.2. Accessing experiences of other market participants

As stated above, other agents act in the residential solar marketvia policy decisions, technology advancements, and new financialofferings. While creating journey maps for them might be one ofthe possible ways of improving and extending current research, it isout of the scope of the current endeavor. Our focus is on developingtechniques and tools for combining journey maps and analyzingthe resulting map of interactions between the active decision-making agents: the homeowner and the installer. Nevertheless, tosupplement and enrich the body of information needed to developthese two agents' journeys, we cross-validated the installationexperience, particularly the frustrations expressed in homeownerand installer interviews. The homeowners and installers particu-larly noted the slow processing times of permits and inspectionsand the lack of communication, standardization, and assistanceprovided by representatives of associated housing jurisdictions andutilities.

We spoke with a subset of representatives of California housingjurisdictions in San Jose, San Diego, and San Francisco. Over thephone, they elaborated on the disbursal of building permits and theinspection of installed systems. However, visiting San Jose's build-ing division revealed a disconnect between the presentation ofinformation online and the difficulty of moving through the processin-person. A representative gave us two instruction sheets and toldus to go online for permitting information. The representative alsodirected us to the fire division because they were unsure whetheror not that department had to do a supplementary inspection post-installation. The fire division told us that for residential installationsthe inspector completes the fire safety check; a supplemental checkis unnecessary. When we contacted the housing jurisdiction in SanDiego, representatives transferred the call three times, eventuallyreturning us to the first representative; no one department coulddescribe all of the requirements for solar system permitting.Additionally, we were directed to contact the historical buildingsociety for supplementary permitting requirements. When wecontacted the housing jurisdiction in San Francisco, a representa-tive said they were moving all of the permitting requirementsonline by 2016. When we contacted the housing jurisdiction inBelmont, Massachusetts, the division did not return our call. Whilethe representatives in San Jose and San Diego suggested that theprocess was more streamlined, their lack of knowledge and con-flicting explanations of the solar regulatory processes confirmedthe frustrations that installers say they feel in dealing with asso-ciated housing jurisdictions to install residential solar systems.

Iteratively confirming the accuracy of these frustrations allowedresearchers to refine the progression of the stages visually, adaptingthem to read as a journey map.

3.3. Visualizing the Homeowner's journey

Our empathic research revealed that homeowners experience abeginning and end in their installation experience. A linear journeymap best captured this process.

As visualized in Fig. 1, a continuous line connects the principalstages (1 through 6) of the journey, which is organized by over-arching decisions made over the course of those stages. Subsidiarystages are shown within these principal stages; some of thesesubsidiary stages occur in tandemwith each other and are shown ina connected ring. Appendix D provides a key to the journey mapicons. Because the solar installation experience does not exist in avacuum, the blue highlighted stages capture the interactions be-tween the homeowner and the installer. Finally, to retain the truecomplexity of the experience, a “thoughts” layer shows thereasoning process of the agent through the successive stages: theirquestions, decisions, and doubts. Because some homeowners needto replace or upgrade their roof and some do not, the dashed linewas used to show this part of Stage 5. Roofs with structural defectsare not able to support PV systems and need to be repaired beforeinstallation. In addition, most roofs tend to serve for a limitedamount of time, approximately 20 years; while the roof could bereplaced after the PV system is installed, this would incur theadditional expense of removing and reinstalling the PV system. Tothat end, installers recommend replacing old roofs before theinstallation.

3.4. Visualizing the Installer's journey

Over the life of their business, an installer cultivates relation-ships with multiple entities in the industry: manufacturers, utilitycompanies, and associated housing jurisdictions. Unlike home-owners, they do not have a defined end to their solar installationexperience because theymust maintain the system for the durationof a warranty. Because their experiences are more cyclical, weinitially struggled to include all of the interactions installersexperienced in a readable format like Fig. 1. Confining a figure tofocus on a particular experience proved more difficult than origi-nally thought. After revisiting the research questions,

(1) Which parts of the process does each agent focus on?(2) What kind of communication exists between agents? What

is the quality of that communication?(3) Where do pain points occur? Why are they occurring?

We realized the individual journey maps and the combinedjourney map had to act in tandem and focus on just one or two ofthese principal questions but not all. So, in Fig. 2, we chose to keepthe blue rings (interactions with the homeowner) consistent withthose in Fig.1. Thoughts and uncertainties were again described in aseparate layer. Note that the numbering of the principal stages forthe installer do not match the numbering of the stages for thehomeowner because the installer experiences more stages.

Like the homeowner, variability of experience had to beconsidered. The geographic region and regulatory environment ofthe installer greatly affects an installer's ability to estimate theirproject timeline. For example, inspection and interconnecting withthe electrical grid are highly variable stages that can only bepartially controlled by the installer. According to interviews, longerwait times means wasted project budget and lower customersatisfaction, which increases frustration (a pain point). These

Fig. 1. Homeowner Journey: This figure tracks the customer's solar installation journey and focuses on the actions, thoughts, and interactions with the installer. The blue circlesrepresent interactions with the installer. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)

E. Sinitskaya et al. / Renewable Energy 145 (2020) 1910e1922 1915

reported pain points increase in severity based on the installer'sability to estimate time and estimate cost spent in each stage. Thesemajor sources of uncertainty color installers' perceived difficulty ofacting in the market. Installers also noted that delivering proposalswas a pain point for them. At that stage, they needed to satisfycustomer needs and control uncertainty in the sourcing of mate-rials. To that end, they often offer a limited number of options to thehomeowner, and they mostly offer only one possible design.

3.5. Policy and modeling insights from the Homeowner's journeymap

One of the most challenging aspects of creating the homeownerjourney map was unifying disparate experiences. Specific physicalcharacteristics of a property and energy consumption patterns aremajor factors in assessing the viability of solar system adoption.Successful modeling of the residential solar market thus requiresapproaches that can account for these existing differences.

Another difficulty encountered was separating subjective frus-trations (pain points) from objectively complicated or difficultstages. Cross-validation techniques, including (1) interviews withassociated housing jurisdictions, and (2) analyses of hard data onpermitting process wait times were used to access and addresslevels of friction that exist during regulatory processes.

Ultimately, the principal challenge was determining if thehomeowner's and the installer's journeys should exist

independently or if they should be combined to embody the highlyinteractive solar installation experience. By cross-checking the ex-istence of each stage and combining the journey maps, we limit thelevel of subjectivity of the two individual maps. For example,assessing the installer's price estimations and proposal creation(See Fig. 2, Stage 4, “Create”) may refine amodel's assessment of thelevel of friction for homeowners' financial considerations whendeciding whether to adopt (See Fig. 1, Stage 4, “Review”).Combining these maps and maintaining a high level of clarity is thefocus of the following section.

4. Results

Based on the work described in Sections 3.3 and 3.4, we revis-ited and narrowed our research questions to focus on the following:Where do the pain points for the individual agents occur? Does frictionexist during points of interaction?

To prepare to merge the individual journey maps, we reassessedthe blue highlighted stages, representing points of homeowner-installer interaction. In merging the two maps (Fig. 3), this over-lap was shown in the middle of the map and defined as the “linkedprocesses” layer. The remaining individual steps of the homeownerand the installer were plotted in parallel, in “independent pro-cesses” layers, according to where they fell chronologically alongthis linked process timeline and were marked with the joinedsymbol. Icons for these independent steps are placed closer or

Fig. 2. Installer Journey: This figure tracks the installer's journey and focuses on the actions, thoughts, and interactions with the homeowner. The blue circles represent interactionswith the homeowner. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)

E. Sinitskaya et al. / Renewable Energy 145 (2020) 1910e19221916

farther from the middle of map depending on the agent's level ofengagement with the other agent. Tasks that homeowner andinstaller were accomplishing mostly on their own were placedfarther from the center, and more interactive tasks were placedcloser to the center. We pinpointed where installers and home-owners reported uncertainties, where specific frustrations occurred(“pain points”). We marked pain points for installer and home-owner with two different types of red circles.

Table 2 summarizes the pain points shown in Fig. 3, listing, bystage, individual pain points for the homeowner, individual painpoints for the installer, and mutual pain points experienced byboth. Most of these pain points will be discussed in the next section.

5. Discussion

In the process of creating two individual journey maps and thenlinking them, we discovered that a number of our actions werecritical, including: conducting multiple, in-depth interviews withhomeowners and installers using highly directed questions; pre-senting complex information visually and in discrete stages for theindividual journey maps; and, for the linked journey map, identi-fying and simplifying the shared principal stages in the overalljourney. Each of these actions are discussed below. Also discussedare answers to our research questions (Where do pain points forindividuals occur? Does friction exist during points of

interactions?) and insights we discovered, including that in-personinteractions between homeowner and installer decreases pain andthat there were inconsistences in the agents' process of identifyingpain points.

5.1. Conducting multiple, in-depth interviews

A systematic challenge we encountered was having limited ac-cess to the entire experiential process for both agents. We wereunable to directly access the real-life experiences of the home-owner and the installer. We could not shadow them or be privy topersonal conversations that homeowners had with their friendsand neighbors. We were only able to track the first half of thehomeowner's experience, up until the delivery of the contract, andwe were only able to track the second half of the installer's expe-rience, minus the installation. Interviewing homeowners and in-stallers was a solution to this roadblock. We expanded and built onthe empathetic foundation we had already laid by conductinglengthy interviews (up to 17 questions for homeowners and 23questions for installers; see Appendices B and C).

The ethnographic profiles of homeowners we created and thefindings and challenges we encountered during the simulations(when our researchers posed as homeowners interested ininstalling a solar system) confirmed some of the barriers toimplementation and inspired us to write more directed interview

Fig. 3. Linked Journey: This figure extrapolates the main points of interaction between the individual experiences of the homeowner and the installer. The individual processes ofeach agent are tracked in parallel.

E. Sinitskaya et al. / Renewable Energy 145 (2020) 1910e1922 1917

questions for homeowners. We learned that two major barriers toimplementation are inappropriate roof conditions and already lowenergy usage. Types of roofs that are not appropriate for solarpanels include roofs that do not have a large area exposed to thesun; roofs with cracks or other damage; and roofs that will need tobe replaced in the next five to ten years. If the homeowner's energyuse is already low, then installing solar panels may not beeconomically attractive.

5.2. Presenting complex information visually and in discrete stages

Another challenge we faced was how to break down a verycomplex experience into discrete stages. The decisions around thevisual organization of a journey mapddeciding on the principlestages and how those stages are connecteddaffects how informa-tion is received and understood by future modelers, who might usethis information to streamline the installation experience anddecrease the severity and amount of pain points. Our choiceregarding how to communicate a homeowner's and an installer'sindividual installation experiences allowed us to formalize theinstallation processes and distill a pertinent methodology for future

modeling efforts. If this tool is to be used in other cases, the visualpresentation of the information may determine the efficacy of thejourney mapping framework.

5.3. Identifying and simplifying shared stages for the linked journey

Our choice of aggregating separate journey maps allowed us toassess whowas making decisions, where in the installation processthese decisions were being made, and how these decisions werederived. Were the homeowner's decisions made independently ordid they depend on the influence of other agents' decisions? Tohelp us answer these questions, during the aggregation process wesimplified and renamed the linked principal stages; we identifiedfour stages: Engage, Estimate, Install, and Debrief.

5.4. Pain points in the solar installation experience

The “Install” stagedpopulated with many red pain points,signifying frustrationsdrevealed that a principal component of thiscommunicationwas interactions with third parties and their lack oftransparency. Because the red points appeared during regulatory

Table 2Individual pain points for the homeowner and the installer, and mutual pain points for both.

Stage Homeowner Installer Both

Engage Conduct marketing. Discuss project possibility.Provide online quote.Provide general feedback.

Estimate Provide request for design upgrade to roof. Assess site. Discuss contract.Install Complete roof upgrade. Apply for permit. Schedule install date.

Request inspection. Complete utility paperwork.Debrief e e e

E. Sinitskaya et al. / Renewable Energy 145 (2020) 1910e19221918

processes, it is possible to conclude that these processes impede theprogression of an installer's efforts, thereby increasing the in-staller's frustration. The homeowner reflects the installer's frus-tration because the “time to use” becomes longer than expected.Installers did say they were less frustrated when they had anextensive portfolio of projects in an associated housing jurisdictionbecause the inspector was then familiar with the installer's workand would pass them through inspection more quickly. However,increasing transparency generally, from the perspective of theinstaller, remains difficult to achieve because that transparency isdependent on the decisions of the government and local utilityagents. The majority of third-party interactions happen at the“Install” stage and happen on the side of the installer, and they tend

Fig. 3. (cont

to be painful. Therefore, decreasing the amount and severity ofthese pain points would require actions and changes from thegovernment and utility agents.

5.5. In-person interactions decreased pain

Considering each individual journey (Figs. 1 and 2), the in-teractions that appear to be the most pain-free are in-person in-teractions, for example, providing and receiving roofing advice andproviding and receiving site feedback. As the process decreased intechnological complexity (as homeowners/installers moved fromonline interactions to in-person site visits), the amount of pain thatthe homeowner experienced with direct interactions with the

inued).

CalSEIA California Solar Energy Industry AssociationNEM Net Energy MeteringSEIA Solar Energy Industry AssociationSolarDS Solar Deployment System

E. Sinitskaya et al. / Renewable Energy 145 (2020) 1910e1922 1919

installer decreased. This finding suggests that, for the homeowner,increasing in-person interaction at designated spots in the journeycould influence both parties' satisfaction. Interviews confirmed thissentiment; one case described how, after inputting informationonline, the homeowner received a call from the installation com-pany and was told that, based on the online information provided,an installation would not be possible. In spite of this off-puttingexperience, the homeowner did install a system, using a localinstaller who visited their house and was willing to explain some ofthe intricacies of the project. Few negative responses were recor-ded during in-person interactions; however, if the informationdelivered during the in-person interaction did not reflect thedevelopment of the project after “signing the contract” (the end ofthe “Estimate” stage), the frustration appeared in further in-personinteractions.

5.6. Inconsistencies in identifying pain points

Interestingly, when re-evaluating our journey map withhomeowners and installers during follow-up interviews, some ofthem reported that the designated “frustration,” such as goingthrough the interconnection process, was not actually a point offrustration for them. Other pain points differed between home-owners and installers and were based on the project site, the reg-ulatory bodies in that area, and the personal preferences of theinstaller and the homeowner. Identifying pain points proved chal-lenging because reported frustrations for one person, like having todeal with the complex process of interconnecting with the grid,was not a frustration to another person; this issue ties back to thevariability of experience in a particularly complex process.

6. Conclusions

The solar industry is peculiar, and the installation experiencecomplex. Until now, the installerdthe person selling and installingsolar panelsdhas largely been ignored in the literature as a keydecision-maker and one who may frame a homeowner's experi-ence, including the system design and price. Insights into theinstallation experience can only be extrapolated through human-centered design research, walking through the installation expe-rience of a homeowner and installer to assess what the individualagents' motivations, decisions, actions, and interactions were andwhen they occurred.

In our model, we detected multitude pain points; all of thesepain points present opportunities for improving the installationexperience and eventually for improving solar penetration rates.For example, a complicated installation process creates the problemof explaining it clearly to the homeowner at the very beginning ofthe process, and results in a pain point (“Discuss project possibility”in Fig. 3) for both homeowner and installer. In-person communi-cation eases this problem somewhat, but the overall complexity ofthe project overshadows the whole experience. This is a place forsimplifying and unifying the installation experience.

From the installer perspective, the challenge of explaining aproject's timeline and scope could inhibit the acquisition of newclients; this challenge is reflected in the installer's pain points:“Conduct marketing,” “Provide online quote,” and “Provide generalfeedback” in Fig. 3. This area could be improved by developingwide-scale information campaigns that would prepare potentialsystem owners and answer their basic questions. Another painpoint, from the installer's perspective, is applying for a permit (theInstallation Stage in Fig. 3). Simplifying and streamlining thepermitting process is an opportunity to improve the overallexperience.

Another area for improvement is simplifying assessing the state

of the roof and upgrading/replacing the roof (see Table 2, home-owner pain points: “Provide request for design upgrade to roof” and“Complete roof upgrade,” and installer pain point: “Assess site”).There are companies that work in this area; for example, Tesla'sSolar Roof offers a complete package to replace the roof and installsolar panels. Further improvements in this area would help in-crease penetration rates.

A mutual pain-point, “Discuss contract,” which includes dis-cussing financing options, could be improved by simplifying waysof financing PV systems; this has been and remains a major focus ofthe industry. Pain points that involve third parties are “Requestinspection” and “Complete utility paperwork,” both of whichsignificantly contributed to the overall experience. To improve thisarea, third parties can restructure and simplify the permittingprocess.

Because our combined map revealed mutual pain points, theseverity of these points provides insights for policy makers andother industry representatives as they assess and address their ownindividual sources of friction in the environment. Linked journeymaps provide a semi-formal tool of detecting those possible policytools that need to be analyzed. Detected pain points will create afoundation for the more formal effort of creating realistic models ofthe residential photovoltaic market. Before the formal tool can bebrought into the picture to provide numerical estimates of marketresponses to policy changes, the scope and focus of the model needto be specified. Our linked journey map bridges the informalcollection of case studies with formal numerical simulation toolsand offers a way of analyzing various experiences and unifyingthem so that they can be used to specify the formal simulationframework. Ultimately, combining journey maps creates a moreformal tool to analyze the conceptual framework for decision-making and create a more accurate, realistic, predictive agent-based model.

Declarations of interest

None.

Acknowledgments

This research was supported by the National Science Founda-tion, Grant #1463717. Any opinions, findings, and conclusions orrecommendations expressed in this material are those of the au-thors and do not necessarily reflect the views of the funder. Wethank Dickson Y.L. Chow for assistance in creating the figuresincluded in the paper. The authors would like to thank the re-viewers for their consideration and engagement.

Appendix A

Abbreviations

Appendix B. Homeowner Interview Questions

Walk me through the process you went through to install solarpanels.

E. Sinitskaya et al. / Renewable Energy 145 (2020) 1910e19221920

How did you become interested in solar?

Considering Installation

Why did you decided to install the solar system?Did you know anyone personally who installed solar beforeyou did?Did you expect to save money in the long run by installingyour system?How did you research different systems and contractors?What were the most important factors that influenced yourchoices?

Pre-InstallationWhich installer did you go with?Why did you decide to go with this particular installer?How many other installers did you consider?How much input did you provide to the design of yoursystem?

Post-InstallationWas the final price after installation different than when youbegan the process?Have you experienced any maintenance issues with yoursystem?When did you start having issues with your system?Has your electricity use behavior changed after installation?If you could go back in time, are there other considerationsyou would have made about your installation?

If you consider contacting the installer as the start of the pro-cess, how long did it take until you signed a contract?

If you consider signing the contract as the start of the project,how long it did take until you could use your system?

Appendix C. Installer Interview Questions

Walk me through the process you go through to install solarpanels for a residential customer.

Marketing

Would you say you have a typical demographic you serve?When marketing, do you have a target audience?How do you define that demographic?Why do you define your demographic in this way?What would you say is the typical demographic that solicitsinitial information? (Do they have a knowledge of solar?)

Before a customer contacts you, are there any processes ormaterials you use to market your business?What is the goal of these marketing techniques (e.g., tocontinually increase number of people, to spreadinformation)?What is the top reason, in your opinion, why people decide tocall you?When that person does initially call you, what are youthinking about (potential customer, stress of interacting withthe potential customer)?

Selecting ProjectsHow do you select projects to work on?Do you have any qualifiers/parameters that affect yourdecision?What is a factor that would prevent you from taking on aproject?

IssuesAre there any soft cost processes that affect your businessmore so than others?Which process, if any, is the most tedious? Why?How do you work around these issues?

Incentives and ProfitsDo you receive any benefits from state and federalincentives?How do these incentives affect your business?How do you consider profit?Why do you consider it this way?

OtherOn a scale of 1e10, what would you rate your interactionwith a city jurisdiction? The utility? (1 being a tediouspermitting process that makes the installer not want toinstall in that housing jurisdiction again; 10 being a great,expedited process that makes installation go flawlessly.)

What are your opinions on Net Metering? Permit process?Do people ask you about these topics? If so, at what stage in the

process?

Appendix D. Key to Journey Maps

E. Sinitskaya et al. / Renewable Energy 145 (2020) 1910e1922 1921

References

[1] T. Islam, N. Meade, The impact of attribute preferences on adoption timing:the case of photo-voltaic (PV) solar cells for household electricity generation,Energy Policy 55 (2013) 521e530.

[2] V. Rai, A.D. Henry, Agent-based modelling of consumer energy choices, Nat.Clim. Change 6 (May 2016) 556e562.

[3] Solar Investment Tax Credit (ITC, 2016 [Online]. Available: http://www.seia.org/policy/finance-tax/solar-investment-tax-credit. (Accessed 21 February2019).

[4] The HawaiianMiles Affiliate Solar Program by SunPower, SunPower Corpo-ration, 2016 [Online]. Available: https://go.sunpower.com/partner/hawaiian-airlines-miles/. (Accessed 21 February 2019).

[5] J. Palmer, G. Sorda, R. Madlener, Modeling the diffusion of residentialphotovoltaic systems in Italy: an agent-based simulation, Technol. Forecast.Soc. Change 99 (2015) 106e131.

[6] K. Corfee, S. Graham, B. Davis, J. Hummer, C. Bloch, J. Cullen, N. Fry, A. Meyer,S. Goffri, California Solar Initiative Third-Party Ownership Market ImpactStudy, Navigant Consulting, Inc, San Francisco, CA, 2014.

[7] J. Burkhardt, R.H. Wiser, N.R. Darghouth, C. Dong, J. Huneycutt, How Much DoLocal Regulations Matter? Exploring the Impact of Permitting and LocalRegulatory Processes on PV Prices in the United States, Lawrence BerkeleyNational Laboratory, Berkeley, CA, 2014.

[8] R. Boero, S.N. Backhaus, B.K. Edwards, The microeconomics of residentialphotovoltaics: tariffs, network operation and maintenance, and ancillaryservices in distribution-level electricity markets, Sol. Energy 140 (2016)188e198.

[9] V. Rai, S.A. Robinson, Agent-based modeling of energy technology adoption:empirical integration of social, behavioral, economic, and environmentalfactors, Environ. Model. Softw 70 (2015) 163e177.

[10] V. Rai, D.C. Reeves, R. Margolis, Overcoming barriers and uncertainties in theadoption of residential solar PV, Renew. Energy 89 (2016) 498e505.

[11] H.Q. Chen, T. Honda, M.C. Yang, Approaches for identifying consumer pref-erences for the design of technology products: a case study of residential solarpanels, J. Mech. Des. 135 (6) (2013) 61007.

[12] D. Millstein, S. Cates, N. Disanti, R. Widiss, G. Barbose, N. Darghouth, Trackingthe Sun IX the Installed Price of Residential and Non-residential PhotovoltaicSystems in the United States, Berkeley, 2016.

[13] D.W. Norton, B.J. Pine, Using the customer journey to road test and refine thebusiness model, Strat. Leader. 41 (2) (Mar. 2013) 12e17.

[14] S. Moon, C. Herig, Z. Chaudhry, Become One in A Million A Strong EnergyPortfolio for a Strong America the Million Solar Roofs Initiative, NationalRenewable Energy Laboratory, Boulder, CO, 1997.

[15] C. Bauner, C.L. Crago, Adoption of residential solar power under uncertainty:implications for renewable energy incentives, Energy Policy 86 (2015) 27e35.

[16] E. Drury, P. Denholm, R. Margolis, Modeling the U.S. Rooftop PhotovoltaicsMarket, National Renewable Energy Laboratory, Boulder, CO, 2010.

E. Sinitskaya et al. / Renewable Energy 145 (2020) 1910e19221922

[17] S.K. Adomatis, B. Hoen, A.C. Mills, R.T. Helmer, An analysis of solar homepaired sales across six states, Apprais. J. LXXXIV (2016) 1.

[18] B. Hoen, S. Adomatis, T. Jackson, J. Graff-Zivin, M. Thayer, G.T. Klise, R. Wiser,Selling into the Sun: Price Premium Analysis of a Multi-State Dataset of SolarHomes, Electricity Markets and Policy Group, Berkeley, CA, 2015.

[19] C.M. Macal, D.J. Graziano, J. Ozik, Modeling solar PV adoption: a social-behavioral agent-based framework, in: “AAAI Fall Symposium, 2014,pp. 24e31.

[20] V. Rai, S.A. Robinson, Agent-based modeling of energy technology adoption:empirical integration of social, behavioral, economic, and environmentalfactors, Environ. Model. Softw 70 (2015) 163e177.

[21] E. Nemet, Gregory Shaughnessy, R.H. Wiser, N.R. Darghouth, G.L. Barbose,K. Gillingham, V. Rai, Characteristics of Low-Priced Solar Photovoltaic Systemsin the United States, Electricity Markets and Policy Group, Berkeley, CA, 2016.

[22] J. Morris, K. Calhoun, J. Goodman, D. Seif, Reducing Solar PV Soft Costs: A Focuson Installation Labor, National Renewable Energy Laboratory, Boulder, CO,2013.

[23] A. Rawson, E. Duncan, C. Jones, The Truth about Customer Experience, Harvard

Business Review, Cambridge, Sept.2013.[24] K.N. Lemon, P.C. Verhoef, Understanding customer experience throughout the

customer journey, J. Mark. 80 (6) (Nov. 2016) 69e96.[25] S. Rose, M. Clark, P. Samouel, N. Hair, Online Customer Experience in e-

Retailing: an Empirical Model of Antecedents and Outcomes, J. Retail. 88(2012) 308e322.

[26] R. Mangiaracina, G. Brugnoli, A. Perego, The eCommerce customer journey: amodel to assess and compare the user experience of the eCommerce websites,J. Internet Bank. Commer. 2015 (2009).

[27] C. Laming, K. Mason, “Customer experience d an analysis of the concept andits performance in airline brands, Res. Transp. Bus. Manag. 10 (2014) 15e25.

[28] A. Richardson, Using Customer Journey Maps to Improve Customer Experi-ence, Harvard Business Review, 2010 [Online]. Available: https://hbr.org/2010/11/using-customer-journey-maps-to. (Accessed 12 December 2016).

[29] California Energy Commission & California Public Utilities Commission, Cali-fornia Solar Statistics, State of California, 2010 [Online]. Available: https://www.californiasolarstatistics.ca.gov/. (Accessed 24 May 2017).