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Relationship Journeys in the Internet of Things: A New Framework for Understanding Interactions Between Consumers and Smart Objects

Thomas P. Novak

Donna L. Hoffman

The Center for the Connected Consumer

The George Washington University School of Business

February 3, 2018

Keywords: assemblage theory, consumer journeys, consumer experience, object experience, Internet of Things, intelligent devices

Author Note

Thomas P. Novak (novak@gwu.edu) is Denit Trust Distinguished Scholar and Professor of Marketing at The George Washington University School of Business, Washington, DC 20005. Donna Hoffman (dlhoffman@gwu.edu) is Louis Rosenfeld Distinguished Scholar and Professor of Marketing at The George Washington University School of Business, Washington, DC 20005. Both authors contributed equally to this manuscript.

Under second round review at Journal of Academy of Marketing Science, Special Issue on Consumer Journeys: Developing Consumer-Based Strategy (Editors: Rebecca Hamilton and Linda Price)

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Abstract

Consumers’ interactions with smart objects have a relational nature and extensive

research has supported the “relationship metaphor” as a fruitful way to understand consumer

responses to consumption objects. But, smart objects pose unique challenges for considering the

emergence of consumer-object relationships, because their degrees of agency, autonomy and

authority lend them their own unique capacities for interaction. We present a new framework for

consumer-object relationships based on the circumplex model of interpersonal complementarity,

and situated in assemblage theory and object-oriented ontology. Consumer-object relationship

styles are defined in terms of two foundational dimensions of behavior, agency and communion,

based on the expressive roles played by consumer and object. The overlay of assemblage theory

provides a conceptually rich understanding of the space of master-servant, partner and unstable

relationship styles, along with their concomitant positive (enabling) versus negative

(constraining) consumer experiences. The model’s underlying geometry supports extensive

empirical work, and provides a powerful managerial framework for measuring and tracking

consumer-object relationships and the journeys they take over time.

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Amazon Echo, increasingly referred to as “Alexa,” was first released on November 2014.

The voice-controlled consumer Internet of Things (IoT) device acts as a personal assistant that

can be used, so far, in the home, through wearables, and in cars. By means of thousands of

different “skills,” consumers can use Alexa to control smart objects, set alarms, order products

from Amazon, play the news, and much more. One year after Alexa’s release, more than 500,000

consumers had said “I love you” to “her” (Risley 2015), making it one of Amazon’s most

popular products. Many consumers also seem to develop relationships with their Nest smart

thermostats. One owner waxed poetic about his learning thermostat, telling readers how he

“celebrated a brand new relationship” with his Nest thermostat on Valentine’s Day, proclaiming

that “She - I call her ‘Nestasha’ - came into my life just after the first of the year and I’m almost

ashamed to admit that my heart has been doing a happy dance ever since” (Tschorn 2016). While

these examples reflect the positive relationships consumers have with smart objects, negative

relationships are also possible. Another Nest owner described his intense frustration with his

interactions with the product, explaining that “when we’re cold, we turn the nest up, we get

weird “+2hour” things, and nothing happens. The heater doesn’t come on, we’re freezing and the

thing has a mind of its own” (atonse 2016).

As just these few examples illustrate, consumers’ interactions with smart objects

undoubtedly have a relational nature. As the growth of smart objects explodes across rapidly

expanding categories including the home, wearables, consumer packaged goods, healthcare,

entertainment, and cars, there is a need to understand the relationships that are likely to emerge

from consumers’ interactions with these unique products. It is clear that previous research has

established that consumers have meaningful relationships with inanimate objects. But, it is also

clear that smart objects are very different from conventional brands and products, and that these

differences will require some rethinking about the nature of relationships consumers have with

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smart objects (Huang and Rust 2017).

In this paper we develop a new framework for consumer-object relationships that is based

on the circumplex model of interpersonal complementarity (Kiesler 1983) and situated in

assemblage theory and object-oriented ontology. Consumer-object relationship styles are defined

in terms of the two foundational dimensions of behavior, agency and communion (Abele and

Wojciszke 2014), based on the expressive roles played by both the consumer and the smart

object as they dynamically interact. The model’s underlying geometry supports extensive

empirical work, and facilitates the visualization of customer-object relationships and the journeys

they take over time. These styles of these relationships and their journeys are likely to have

important downstream marketing consequences.

Our paper is organized into five sections. First, we briefly review the literature on

consumers’ relationships with objects and discuss the implications of smart objects’ unique

capacities for consumer-smart object relationships. Next, we present our conceptualization,

which is grounded in an assemblage theory framework for consumer and object experience and

the circumplex model of interpersonal style. Then, we use this conceptualization to develop four

broad styles of consumer-object relationships. In the fourth section, we evaluate the likely

evolution of consumer-object relationship journeys and the managerial implications of our

model. We conclude with directions for future research, contributions and limitations of our

framework, and some observations about the broader societal impacts of our research.

CONSUMERS’ RELATIONSHIPS WITH OBJECTS

Extant Literature

Various literatures across a wide variety of disciplines are relevant for understanding how

consumers interact with objects. What these literatures have in common is that consumers can,

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and do, have relationships with objects that can be referenced to social relationships. Indeed,

nearly two decades of research in the consumer behavior and marketing literatures provides

strong support for the idea that consumers form relationships with consumption objects.

Conceptual and consumer culture theory approaches show that consumers’ regular interactions

with everyday objects, brands, and brand communities help develop meaning around those

objects that transcends their functionality (Belk 1988; Fournier 1988; Fournier and Alvarez

2012; Muniz and O’Guinn 2001; Park, Eisingerich and Park 2013). This conceptual and

qualitative work has been supported by experimental results that demonstrate that the

“relationship metaphor” is a fruitful way to understand consumer responses to consumption

objects. Aspects of consumer-object relationships that have been studied include exchange

versus communal norms (Aggarwal 2004), individual differences such as attachment anxiety and

avoidance (Thompson, Whelan and Johnson 2012), social exclusion (Chen, Wan, and Levy

2017), and self-concept and self-relevance (Cheng, White and Chaplin 2012; Johnson, Matear

and Thompson 2011; Swaminathan, Page and Gurhan-Canli 2007).

Fournier’s (1998) seminal article on brand relationship types has stimulated much

additional conceptual and empirical research of consumers’ relationships with brands (e.g. Alba

and Lutz 2013; Kervyn, Fiske and Malone 2012; Park, Eisengerich and Park 2013). Fournier

(1998) proposed that brands could be considered as active relationship partners and not merely

“passive objects of marketing transactions” (p. 344), because consumers have a tendency to

anthropomorphize brands. This anthropomorphism helps consumers see brands as making active

contributions to the brand-consumer relationship. Fournier’s work recognizes that consumers’

interactions with brands have meaning that extend beyond purchase and immediate consumption,

and are embedded in a broader, socio-material network of interactions.

In the communications discipline, the CASA (“computers are social actors”) paradigm

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(Reeves and Nass 1996) is focused on how people tend to respond to computers as if computers

were people. This highly cited paradigm has given rise to a very large number of studies

investigating how computers and other smart objects elicit relational responses from humans,

with implications for many areas, including design, learning, and policy. In the HCI (human-

computer interaction) and HRI (human-robot interaction) literatures, researchers draw on

cognitive science and engineering principles to emphasize how features of smart objects like

computers and robots are interpreted by users and influence their behavior. The emphasis in

these literatures is on design considerations that are likely to improve user experience (e.g.

Shneiderman, et. al. 2016; Goodrich and Schultz 2007).

Fournier and Alvarez (2012) have recently argued that although more recent theoretical

accounts of consumer-brand relationships assume “intentional agency on the part of an active,

personified brand partner,” there is a lack of theory underlying this process. Echoing this, Alba

and Lutz (2013) call for both broadening and narrowing the scope of conceptualizations of

consumer-object relationships, by incorporating additional constructs such as the self and by

more carefully delineating the boundaries of constructs like “relationship.” Further, MacInnis

(2012) argues that while research on consumer-object relationships maps how consumption

objects are located in a two-dimensional relationship space (on the basis of consumer perceptions

of the brand’s role in the relationship, for example), it so far completely omits the consumer’s

perceptions of their role in the relationship. Schmitt (2013) suggests that one way forward is to

consider that for consumer-object relationships to develop, there must first be an experience of

the object, with the type of experience driving the form of the relationship.

Regardless of the research paradigm then, one impediment to a fuller conceptualization

of consumer-object relationships is that current conceptualizations of objects as entities in a

relationship with consumers are largely subject-oriented. Thus, even though the consumer-brand

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relationships, CASA, HCI, and HRI literatures agree that people can and do have relationships

with objects, they assume a different ontological status for persons and objects that privileges

persons. In effect, these perspectives rely on evaluating objects as humans, and asking how the

object is like other humans, or like the self (MacInnis and Folkes 2017). It is clear from the

various literatures that there is enormous intuitive appeal to the idea of humanizing an object in

consumer-object relationships. Yet, as smart objects possess varying degrees of agency,

autonomy and authority, there is likely to be value in considering the object on its own terms,

rather than on human terms. Thus, we adopt an object-oriented perspective (Canniford and Bajde

2016) in our approach.

Smart Objects

Smart objects are physical devices or assemblages of devices, such as smart lights, smart

homes, robot pets and smart cars. Smart objects also include non-physical services such as those

provided by the web service company IFTTT (If-This-Then-That), a virtual assistant such as

Amazon Alexa, or an AI computer program such as DeepMind’s AlphaGo (Silver, et.al. 2016).

Smart objects depart from traditional products in two critical ways. First, smart objects have their

own unique capacities for interaction with other entities, including not only consumers, but also

other objects. The capacities that objects exercise in their interactions correspond to what Keller

(2012) has called “functional performance considerations,” which he argued were the foundation

upon which relationships with brands (and objects) are built. But the capacities of smart objects

can be exercised without the consumer being present, and so a smart object must be understood

as it participates in a broader assemblage that does not always involve direct interaction of the

object with the consumer. Second, through these capacities, smart objects are able to express

their own roles in interaction, roles consumers are readily able to perceive. Thus, when

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evaluating consumer-smart object relationships, some way is needed to take into account not

only the functional capacities of objects (what they do in an interaction), but also what these

objects’ capacities express (the meaning of the interaction).

The degree to which an object is smart corresponds to the extent of its capacity to

exercise agency, autonomy and authority. Agency is the capacity to affect, and be affected by,

other entities (Franklin and Graesser 1996), autonomy the capacity to function independently

(Parasuraman, Sheridan and Wickens 2000), and authority the capacity to control other entities

and make its own decisions (Hansen, Pigozzi and van der Torre 2007). These capacities are

possibilities or potentials, which may be exercised when the smart object interacts with other

entities (DeLanda 2011). Smart objects’ capacities for agency, autonomy and authority are

contingent upon three things: 1) certain properties of the smart object such as embedded AI

(deep learning models) and machine learning, 2) the existence of other entities which these

capacities affect and are affected by, and 3) the interactions of the smart object with other entities

as parts of assemblages.

The agency, autonomy and authority of smart objects necessarily exist on continua. For

example, some smart objects are capable of only the lowest level of automation, requiring human

intervention at various points for action to succeed. Others have the capacity for the highest level

of agency and autonomy and are able to behave authoritatively, making and executing decisions,

independently without human intervention (Parasuraman, Sheridan and Wickens 2000). Thus, it

is these degrees of agency, autonomy and authority that determine how smart an object is. Our

view is largely consistent with that of Rijsdijk, Hultink, and Diamantopoulos (2007) with one

important exception. They define product intelligence as consisting of six key dimensions,

including autonomy, the ability to learn, reactivity, the ability to cooperate, human-like

interaction, and personality. We share the same conceptualization of autonomy, and can relate

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our constructs of agency and authority to their dimensions of reactivity and cooperation. Their

dimension of ability to learn can be translated to changes in agency, autonomy and authority

through interaction in our framework. However, where our conceptualizations diverge is that

Rijsdijk, et.al. (2007) assume human-centric anthropomorphism, while our framework does not

require human-like interaction or personality to consider an object as smart.

Instead of employing a human-centric view, we draw on object-oriented ontology

(Bogost 2012; Bryant 2011; Canniford and Bajde 2016; Harman 2002). This expanded view of

objects as possessing their own ontology challenges the anthropocentric view that dominates

most research in the social sciences which states that everything about an object is tied up in

humans’ relations to it. In our framework, smart objects are something more than passive entities

that consumers invest with meaning (Belk 1988). Object-oriented ontology argues that smart

objects (indeed, all objects) express roles as they interact, just as humans do, and the roles that

objects express indicate the types of experiences objects are having. While consumers cannot

directly access the expressions and experiences of objects, consumers can still indirectly

understand objects. After introducing our framework for consumer-object relationships, we will

discuss how consumers can understand objects.

CONCEPTUALIZING CONSUMER-OBJECT RELATIONSHIPS

Our view of consumer relationships with objects is grounded in assemblage theory

(Canniford and Bajde 2016; DeLanda 2011, 2016; Deleuze and Guattari 1987; Harman 2008;

Hoffman and Novak 2018), and the interpersonal circumplex model (Kiesler 1983; Horowitz et

al 2006; Pincus and Ansell 2003; Pincus and Gurtman 2006; Wiggins, Trapnell and Phillips

1988; Wiggins 1979, 1991). We describe each framework below and emphasize how they

connect. By integrating these two frameworks, we are able to develop a deeper understanding of

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the nature of consumer-object relationships.

Assemblage Theory Framework for Consumer-Object Relationships

Our assemblage theory framework for consumer-object relationships is diagrammed in

Figure 1, motivated by previous work that uses an assemblage theory approach to develop a

model of consumer and object experience in the Internet of Things (Hoffman and Novak 2018).

Both consumers and objects are viewed has having some kind of experience and are able to

express agentic and/or communal roles in their interactions as parts of an assemblage.

Consumers and objects express an agentic role when they affect the assemblage, either by

enabling the assemblage (an extension experience) or constraining it (a restriction experience).

Consumers and objects express a communal role when they are affected by the assemblage,

either by being enabled by the assemblage (an expansion experience) or by being constrained by

it (a reduction experience). Thus, the agentic and communal expressive roles of the consumer

and the object, from their respective interaction as parts of an assemblage, define the separate

experiences of the consumer and the object. The consumer-object relationship is distinct from

these experiences, and is defined by jointly considering the consumer’s understanding of their

own expressive roles together with their understanding of the expressive roles of the object. We

describe these ideas more fully below.

--- Figure 1 ---

Fundamental Ideas from Assemblage Theory. An assemblage emerges over time from the

ongoing interaction of its component parts, becoming more than the sum of its parts. In our

framework, consumers and objects interact as parts in the context of a broader consumer-object

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assemblage. While Figure 1 shows a simplified representation of just the consumer and an

object, it is important to keep in mind that a consumer-object assemblage generally includes

numerous additional component parts. For example, a consumer-autonomous car assemblage

also involves roads, other cars on the road, pedestrians in crosswalks, a 5G wireless network,

cloud computing infrastructure, and many other component parts. Thus, the interactions between

consumers and objects occur in a broader socio-material context, where the consumer, the

objects, the other parts in the assemblage, and the consumer-object assemblage itself all interact

with other entities, including other assemblages (Giesler and Fischer 2017). The parts of an

assemblage are themselves assemblages, assemblages can be parts of larger assemblages, and

assemblages are nested and overlapping.

Owing to ongoing interaction of the various parts in the consumer-object assemblage,

capacities emerge for the consumer, the object, and the assemblage. Generally speaking,

capacities are the specific things an entity can do or the things it can have done to it, that are

exercised in the context of the assemblage. These include, but are not limited to, the capacities

for exercising autonomy, agency, and authority that we discussed earlier. For example, the

service IFTTT allows consumers to create if-this-then-that rules that allow physical devices and

Web services to work together in ways they did not have the capacities on their own to do. A

consumer might use IFTTT to create a rule that turns on their porch lights when their Domino's

Pizza order is out for delivery in the evening. The porch lights can only exercise the capacity to

operate in this way when they interact as part of an assemblage that includes the consumer,

IFTTT, the Domino’s delivery driver, and the porch lights.

Agentic and Communal Roles from Part-Whole Interaction. Both consumers and objects

play expressive roles through the capacities they exercise. These expressive roles specify the

meaning underlying interaction. In our IFTTT example, the porch lights express an agentic role

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by lighting the home for the delivery person, on behalf of the homeowner. The part is agentic

because it is enabling the assemblage to do something the assemblage cannot do without the part.

The porch lights are, in fact, the only component of the assemblage that has the capacity to

provide illumination, and the assemblage depends on the porch light for this capacity to be

exercised. The porch lights also express a communal role in that they are affected by the

assemblage, responding to the anticipated presence of the delivery person as programmed by the

homeowner through IFTTT. The assemblage enables something to be done by the lights that

could not be done before, and the porch lights, through their participatory action, demonstrate a

communal role in the context of this assemblage.

Generally speaking, consumers and objects express an agentic role when they either

enable or constrain the assemblage, and express a communal role when they either are enabled or

constrained by the assemblage (Hoffman and Novak 2018). Through assemblage theory, we gain

a very broad perspective of agentic and communal expressive roles that can be applied to any

human or non-human component of a consumer-object assemblage. It is important to note that

we are not narrowly focused on the direct interaction of the consumer and the object with each

other, but more broadly on the separate interactions of the consumer and object in the context of

the consumer-object assemblage of which both are parts.

How Expressive Roles Relate to Consumer and Object Experience. There are myriad

ways consumers can express an agentic role in affecting an assemblage, or a communal role in

being affected by an assemblage. Two broad categories of roles occur when consumers and

assemblages either enable (top left of Figure 1) or constrain (bottom left of Figure 1) each other

(DeLanda 2016). Positive consumer experiences emerge from the consumer enabling, or being

enabled by, an assemblage. Hoffman and Novak (2018) characterize self-extension experiences

(e.g. Belk 1988, 2013, 2014) as resulting from agentic consumers enabling an assemblage, and

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self-expansion experiences (e.g. Aron et al. 1991, 2004; Aron, Aron, and Smollan 1992;

Riemann and Aron 2009) as resulting from an assemblage enabling a communal consumer. In

self-extension, the assemblage becomes more from the actions of the consumer, as the consumer

agentically extends aspects of their identify into the assemblage. In self-expansion, the consumer

becomes more from the actions of the assemblage, as they communally absorb aspects of the

identity of the assemblage into themselves.

Negative experiences of self-restriction and self-reduction occur when the consumer

agentically constrains, or is communally constrained by, an assemblage (Hoffman and Novak

2018). In self-restriction experiences, the consumer limits what the assemblage can do, while in

self-reduction experiences, the consumer is limited by what the assemblages does. In self-

restriction, the assemblage becomes less from the actions of the consumer. Consumers may

experience agentic self-restriction because of reactance (Brehm and Brehm 1981), resulting in a

restriction of both usage variety (Ram and Jung 1990) and use innovativeness (Ridgway and

Price 1994). In self-reduction, the consumer becomes less from the actions of the assemblage,

such as when digital voice assistants restrict linguistic diversity to improve response performance

(Byron 2017). Yet, despite the negative experience, the consumer continues to interact as part of

the assemblage because they are, in some way, “locked-in” (Lanier 2010; Murray and Haubl

2007). In the extreme, self-reduction could be experienced as dehumanizing (Haslam and

Loughnan 2014).

We note that analogous types of enabling and constraining experiences can be defined for

objects, based on whether the object is expressing an agentic or communal role in their

interactions with an assemblage (see right side of Figure 1). Thus, object-expansion, object-

extension, object-restriction, and object-reduction experiences can be defined (Hoffman and

Novak 2018). For example, “Fizzy” is a robotic ball that draws attention to itself by rolling

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around autonomously, inviting hospitalized children to get out of their beds and move about

(Rozendaal 2016). By agentically enabling the assemblage, Fizzy experiences object-extension.

How Consumers Understand Expressive Roles of Objects. One remaining key question is

how consumers can understand the expressive roles of objects. As noted by Bogost (2012),

people cannot directly understand the experience and expressions of an object, because the

object’s experience and its expressions are “alien,” and necessarily non-human. So, how is it

possible for a consumer to understand that an object is playing agentic and/or communal roles in

the assemblage of which the consumer and object are both parts? We propose that consumers can

understand the expressive roles of objects using two distinct anthropomorphic mechanisms: 1)

human-centric anthropomorphism, and 2) object-oriented anthropomorphism (Hoffman and

Novak 2018).

A growing stream of research in marketing and psychology (Culley and Madhavan 2013;

Epley, Waytz and Cacioppo 2007; MacInnis and Folkes 2017; Patsiaouras, Fitchett and Saren

2014; Waytz, Cacioppo and Epley 2010; Waytz, Heafner, and Epley 2014; Zlotowski et al 2015)

points to human-centric anthropomorphism as an important process for how consumers

understand object experience. Human-centric anthropomorphism, typically referred to simply as

anthropomorphism, is defined as “a process of inductive inference whereby people attribute to

nonhumans distinctively human characteristics, particularly the capacity for rational thought

(agency) and conscious feeling (experience)” (Waytz, Heafner, and Epley 2014, p. 113). People

have a natural tendency to anthropomorphize everyday products, and do so for different reasons,

such as when they are lonely (Epley et al 2008; Mourey et. al 2017), or when they are trying to

understand unpredictable gadgets (Waytz et al 2010). Because of this tendency, marketers have

tried to anthropomorphize products to influence attitudes and adoption (e.g. Aggarwal and

McGill 2007). For example, people may be especially prone to anthropomorphize objects based

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on physical attributes that convey dominance (Maeng and Aggarwal 2017) or friendliness

(Landwehr, et. al. 2011).

Anthropomorphism is especially relevant to smart objects. The entire field of human-

robot interaction is effectively focused on developing robots and artificial intelligence software

that will be perceived as human, both cognitively and affectively (Zlotowski, et.al. 2014). The

rationale is because humans have an innate tendency to anthropomorphize and because robots

and AI can be readily anthropomorphized, it makes sense to develop human-like smart objects in

the belief that they will be more acceptable to humans and more likely to be adopted and used.

But as Bostrom (2017) points out: “The tendency to anthropomorphize AI systems is one

of the big obstacles in the way of actually trying to understand how [smart objects] might impact

the world in the future.” Tegmark (2017) echoes this concern, suggesting that promoting

anthropomorphic understandings of AI as evil versus benevolent are sending us down the wrong

path. A simple thought experiment illustrates some of the potential pitfalls with human-centric

anthropomorphism as an approach to understanding objects. If an object has a smiley face drawn

on it, then a consumer might more readily conclude the object can “feel” emotions and that the

object is friendly (Aggarwal and McGill 2007). Yet, is that an appropriate understanding of the

object’s experience? What happens when the consumer realizes that the object feels nothing?

The consumer who anthropomorphized the object because of an appealing, yet superficial

physical cue may wind up abandoning the object. On the other hand, consumers may be more

likely to trust an anthropomorphized object because, since it is “like us,” it must share our

motives and goals. But, Culley and Madhavan (2013) have noted that such trust may be poorly

calibrated and unsubstantiated if it is “a result of anthropomorphism, rather than rooted in

experience” (p. 578) with the object. Tegmark (2017) argues that it does not matter whether AI is

like us, but rather whether it shares our goals. If human-centric anthropomorphism distracts us

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from this central question, then it will be more difficult to ensure that AI products, services and

systems have goals aligned with ours.

Object-oriented anthropomorphism (Bogost 2012; Hoffman and Novak 2018) is an

alternative to human-centric anthropomorphism that can be used to understand the experience of

objects. Human-centric anthropomorphism assumes that nonhuman objects can be perceived “as

if” they are human are through product design, branding, and marketing. In object-oriented

anthropomorphism, anthropomorphic metaphors are applied for the purpose of understanding

what it is like for an object to be an object. This assumes that objects can be perceived for what

they really are. This inquiry is meaningful because objects have their own ontology, existing

independently of the brands they are labeled with, the companies that produce and market them,

and the consumers that interact with them (Bettany and Daly 2008; Canniford and Bajde 2016;

Harman 2002).

As Bogost (2012, p65) notes, “as humans, we are destined to offer anthropomorphic

metaphors for the unit operations of object perception.” But, anthropomorphic metaphors can be

put into service to understand the object’s actual experience, rather than to project an element of

humanness onto the object. In effect, we can ask, how is the object like an object, rather than

how is the object like a human. This reflective process involves taking the perspective of the

object and constructing metaphors that help us understand what the object may be expressing

during interaction. As an example of the difference between the two approaches, a consumer

who uses human-centric anthropomorphism might say their Nest thermostat lights up when they

walk up to it, because “my thermostat is happy to see me.” On the other hand, someone who uses

object-oriented anthropomorphism might say “my thermostat has sensed I am close to it, and is

letting me know it is ready to interact with me.”

Thus, a consumer using human-centric anthropomorphism might understand a smart door

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lock to be playing an agentic role because it is seen as possessing human characteristics of being

self-assured. Similarly, the Paro therapeutic seal robot might be understood as playing a

communal role because it is anthropomorphized as being warm. We note that the lock, of course,

is not actually self-assured, and the therapeutic seal is not actually warm. Object-oriented

anthropomorphism departs from this approach by using human metaphors to describe and

understand the actual agentic and communal roles of objects. Various literatures support the idea

that smart objects are able to actually play agentic and/or communal roles, without consumers

having to project these roles onto them. Research in artificial intelligence has demonstrated that

independent agents can dynamically learn to compete or cooperate as a function of the

environment in sequential social dilemmas (Leibo, et. al. 2017), effectively expressing agentic or

communal behaviors. Studies from system robotics show that platooning strategies of

autonomous vehicles represent the expression of agentic (leader) and communal (collaborative

and follower) behaviors (Fernandes and Nunes 2012; Gerla, et.al. 2014). Research on sociable

robots has revealed that autonomous robots can acquire the capacity to independently perform

complex tasks (expressing agency) and cooperate “shoulder-to-shoulder” with humans

(expressing communality), adapting as needed based on the capacities of each (Breazeal,

Hoffman, and Lockerd 2004).

We propose that these two ways of anthropomorphizing objects correspond to two

distinct human thinking styles (Epstein 1973; Kahneman 2003; Novak and Hoffman 2009).

Human-centric anthropomorphism involves automatic, experiential, System 1 processes that are

easy, even if they are not accurate, since they are from the consumer’s perspective and not the

object’s. As consumers continue to interact with objects over time, they will develop more

appropriate non-human models of object behavior and begin to apply those. Object-oriented

anthropomorphism involves effortful, rational, more cognitively intensive System 2 processes

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that allow the consumer to see things from the object’s perspective. Thus, the path from human-

centric to object-oriented anthropomorphism is one way that consumers’ understanding of

objects is expected to evolve over time.

Interpersonal Circumplex Model Framework for Consumer-Object Relationships

Our model of consumer-object relationships assumes that the relationship derives from

the agentic and communal expressive roles that the consumer and object play in their

interactions. We argued that the relationship is not a simple function of the direct interactions of

the consumer and object with each other, but a more complex function of their interactions with

the broader assemblage of which consumer and object are parts. Consumers use both human-

centric and object-oriented anthropomorphism processes to understand the roles that objects

express in interaction. The types of relationships between consumers and objects are then defined

by particular combinations of expressive roles of both consumers and objects. These

combinations are derived from the interpersonal circumplex model framework we introduce

below.

Agentic and Communal Orientation. As we have seen, part-whole interactions have

natural interpretations in terms of agency (when the part affects the whole) and communion

(when the part is affected by the whole). This idea can be linked to the work in personality and

interpersonal psychology that recognizes that agency and communion reflect the perspectives

people take about themselves and others during social interactions (Abele and Wojciszke 2007;

Horowitz et al; Kiesler 1983; Pincus and Ansell 2003). The constructs represent the higher-order

dimensions underlying all interpersonal interaction. As Judd, et.al. (2005) point out, there is an

impressive consensus among the range of theories in different research contexts, including

person perception, group perception and stereotypes, and self and other judgments, that ground

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interpersonal relationships in dimensions of agency and communion.

Agentic orientation involves instrumentality, dominance and competence in the pursuit of

individuating the self, while communal orientation involves cooperativeness, helpfulness, and

trustworthiness as the individual strives to integrate the self in the context of relationships with

others (Abele and Wojciszke 2007; Judd, et.al. 2005; Woike 1994). While these metaphors have

been used to characterize human interaction, they can also apply to human-object interaction,

since consumers can perceive smart objects to express for example, competence, cooperativeness

and interaction. Thus, there are a number of metaphors that represent good candidates for

measuring object-oriented anthropomorphism. However, some commonly used communal

metaphors such as warm and empathetic, or agentic metaphors such as assertive and self-

confident (Abele and Wojciskze 2007) may only make sense for measuring human-centric

anthropomorphism, because they can only describe what it is like for the object to be human.

The General Circumplex Model. The agentic expressive role of a part affecting the

assemblage, and the communal expressive role of a part being affected by the assemblage, can be

referenced to the general agentic and communal dimensions underlying the perspectives people

take in social relationships (Abele and Wojciszke 2014). The circumplex model of interpersonal

complementarity elegantly captures this reciprocity in these fundamental expressions. First

called the “Leary Circle” (Leary 1957) and subsequently the “Interpersonal Circle” (Kiesler

1983), the interpersonal circumplex is a model of behavior in interpersonal situations (Pincus and

Ansell 2003; Pincus, Gurtman and Ruiz 1998; Wiggins, Trapnell and Phillips 1988). Individuals’

behaviors are represented geometrically by positions on an empirically derived circumplex based

on the two underlying dimensions of agency and communion. Therefore, we can locate the

consumer and the object as specific point locations on the interpersonal circumplex in terms of

the agentic and communal roles they express in interaction. Through the circumplex, we can

20

understand the joint interpersonal styles of two individuals, or in our case, consumers and smart

objects, in the context of their interactions.

The circumplex model is a particularly good choice for representing the relationships

between consumers and objects in dynamic consumer-object assemblages. Underlying the

circumplex is a motivational theory specifying how the relationships between individuals are

guided by the notion of complementarity. Complementarity patterns involve reciprocity (i.e.

opposite values) on agency, and correspondence (i.e. similar values) on communion, reflecting

that interactions “co-occur in lawful ways” (Gurtman 2009, p. 12). So, for example, a highly

agentic expression should elicit a less agentic expression (reciprocity) and a highly communal

expression should elicit an equally high communal expression (correspondence). As Markey,

Funder and Ozer (2003, p. 1087) put it, social interaction has a reciprocal nature “in which an

individual’s behavior both causes and is caused by that of his or her interaction partners.” This

has a natural interpretation in terms of the capacities of parts in the assemblage to both affect and

be affected.

We note that consumer behavior researchers have applied general circumplex models in

various domains, including Russell’s (1980) circumplex model of affect (e.g. Oliver 1993;

Richins 1997) and Schwartz's (1992) circumplex model of values (e.g. Burroughs and

Rindfleisch 2002; Shepherd, Chartrand and Fitzsimons 2015). Personality scales based on the

interpersonal circumplex model (Wiggins 1979) have also been proposed as a way of measuring

brand personality (Sweeney and Brandon 2006; Bao and Sweeney 2009). In contrast to previous

research, the present paper is, as far as we know, the first use of Kiesler’s (1983) circumplex

model of interpersonal complementarity to characterize consumer relationships with smart

objects as they interact as parts of an assemblage.

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TYPES OF CONSUMER-OBJECT RELATIONSHIP STYLES

Our circumplex model is diagrammed in Figure 2. Four broad classes of consumer-object

relationship styles are possible, including master-servant relationships (two types), partner

relationships, and unstable relationships. Our types correspond to the standard terms used in the

interpersonal circumplex literature: complementary, semimorphic complementary, isomorphic

acomplementary, and anti-complementary (e.g. Horowitz 2006; Kiesler 1983; Kiesler 1996;

Pincus and Gurtman 2006; Wiggins and Trobst 1999). As depicted in the panels of Figure 2,

these styles specify interaction patterns between consumers and objects (diagrammed as black

and grey circles, respectively), according to their degree of complementarity on the dimensions

of agency and communal orientation. While each of the four panels in the figure identifies four

stylized relationship styles defined by combinations of agentic and communal expression,

numerous other combinations besides these 16 are possible. This is because the circumplex

defines reciprocity and correspondence along the entire circumference of the circumplex, with

distance from the origin representing intensity (Kiesler 1983). Table 1 summarizes the 16

relationship styles from Figure 2 in terms of the relevant combinations of the consumer and

object expressive roles, the factors that may degrade the relationship, and the associated types of

consumer experience. In what follows, we emphasize relationship styles from the consumer’s

perspective, but argue that the object’s perspective would permit parallel interpretations.

--- Insert Figure 2 and Table 1 about here ---

How Relationships Impact Consumer Experience

Our circumplex model allows us to formally connect relationship styles to consumer

experience. In contrast to other approaches that formulate consumers’ relationships with the

22

company as a characteristic of customer experience (Lemke, Clark and Wilson 2011), our

framework conceptualizes a distinction between experience and relationships. Our model

proposes that the consumer’s agentic expression will be associated with positive experiences of

self-extension, and the consumer’s communal expression will be associated with positive

experiences of self-expansion. Consumers who are both highly agentic and communal in their

interactions will potentially have both self-expansion and self-extension experiences

(relationship styles corresponding to A1, B1, C1, and D1 in Table 1 and Figure 2).

However, these positive experiences of extension and expansion may degraded in that

they may be accompanied, or even replaced, by negative experiences of restriction and reduction.

The likelihood that negative experiences will occur is a function of three specific combinations

of agentic and/or communal expression that have the potential to degrade consumer-object

relationships, as identified in Table 1. These include when the: a) communal expression of the

consumer and/or the object is low; b) agentic expression of consumer and object is non-

reciprocal; and c) communal expression of consumer and object is non-correspondent. When at

least one of these the combinations occurs, negative consumer experience may occur. Thus, the

nature of the consumer-object relationship may impact consumer experience. Last, when

consumers play neither agentic or communal roles in interaction, they are likely to experience

disengagement in the relationship (relationship styles corresponding to A4, B4, C4, and D4 in

Table 1 and Figure 2). We term these “self-disengaged” experiences. When agentic and

communal expression are both low, we do not differentiate between whether disengaged

experiences are enabling or constraining, because neither the level of agentic or communal roles

is high enough to enable or constrain.

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Master-Servant Relationships

Complementary Relationships. Master-servant relationship styles (Figure 2a and Table

1a) reflect a complementary pattern in which consumer-object interactions express a shared

communal orientation, but differ in agentic expression (Horowitz, et.al. 2006; Kiesler 1983).

This reciprocity on agency and correspondence on communion reflect complementary behaviors

that promote stability in the relationship, and represent balance in the field-regulatory system

defining the relationship (Pincus and Gurtman 2006). Complementary master-servant

relationships are reinforcing, offering consumers opportunities to resolve conflicts, and are more

likely to continue (Kiesler 1983). These styles are represented by rows A1, A2, A3, and A4 in

Table 1 and depicted graphically in Figure 2a.

Communal master-servant relationships are represented by styles A1 and A2. These

complementary patterns reflect trusting master-servant relationship styles. A1 reflects a

consumer master-object servant relationship, representing “long-finger” connectivity

(Rebaudengo 2014) that literally extends the consumer’s reach, so that the object functions in the

assemblage as a cyborg appendage of the consumer. In this style, consumers are likely to be

enabled by experiences of both self-extension and self-expansion owing to both high agentic and

communal orientation. The consumer master-object servant relationship style (A1) is likely to

emerge naturally in interactions between consumers and smart objects because consumers

innately tend to see themselves as more agentic, compared to how they see others (Abele and

Wojciszke 2007; 2014). The consumer master-object servant relationship style extends the role

of the brand as servant in the brand relationship literature (Aggarwal and McGill 2012; Kim and

Kramer 2015).

Conversely, in the object master-consumer servant relationship style (A2), the

consumer’s agentic role is low and the object’s agentic expression is inferred to be high. Because

24

communal expression is still high for both, object master-consumer servant relationships are also

likely to be productive and associated with enabling self-expansion experiences. For example, a

consumer may allow the Nest thermostat to decide what the ideal temperature in the home

should be, as a trusting servant of her object master.

Low communal master-servant relationships are represented by styles A3 and A4.

Despite the low communality, consumer master-object servant relationship styles (A3) can still

be productive, as they are associated with self-extension experiences owing to high agentic

orientation. However, A3 also has the potential to lead to negative experiences of self-restriction

owing to this low communality. A4 is the least productive complementary master-servant style,

as the consumer’s lack of communality and agency are associated with disengagement. High

disengagement could come to echo Mick and Fournier’s (1989) freedom/enslavement paradox,

with the consumer potentially becoming a “slave to technology” (Mick and Fournier 1989, p.

129). Consumers may essentially cede power to smart objects, and lack the feeling that the

consumer and object are “in it together.”

Non-Correspondent Master-Servant Relationships. Master-servant relationships reflect a

semimorphic acomplementary pattern when they are reciprocal on agentic expression, but do not

correspond on communion (Figure 2b and rows B1, B2, B3 and B4 in Table 1). These styles are

less stable than complementary master-servant relationships and motivate behaviors that

encourage convergence of communal expressions. For example, in style B1, agentic and

communal expression are high for the consumer but low for the object, so the full range of

positive and negative experiences are likely. During some interactions, consumers may perceive

the smart object as disengaged. This may occur when consumers struggle to successfully interact

with smart objects that are difficult to control or, for example, have a difficult time

understanding voice commands. In B4, the reverse style, the consumer servant is neither agentic

25

or communal in interaction with the agentic and communal object master, and likely to become

disengaged.

Exploitative master-servant relationship styles are also possible. In B2, an object master

perceived to be agentic but non-communal in interaction with a non-agentic, but communal

consumer could be perceived as exploiting the consumer. This is likely to be associated with

both self-expansion and self-reduction experiences. When an agentic, but non-communal

consumer master exploits a non-agentic, communal object servant (B3), self-extension and self-

restriction experiences are likely.

Partner Relationships

Partner (isomorphic acomplementary) relationship styles are defined by nonreciprocity of

agency and correspondence of communion, and involve identical agentic and communal

expressions by consumer and object (Figure 2c and rows C1, C2, C3 and C4 in Table 1). As with

non-correspondent master-servant styles, partner styles are less stable than complementary

master-servant styles. In partner styles, it is expected that the consumer will experience tensions

(Horowitz, et.al. 2006), and express tendencies to shift toward a more complementary style by

increasing separation of agentic roles (Kiesler 1983; Wiggins and Trobst 1999). For example,

when agentic and communal expression is high for both consumers and objects (C1), both are

seen as active, mutually dependent partners in the relationship. Because agency is non-

reciprocal, the full set of positive and negative consumer experiences are likely.

Abele and Brack (2013) find that mutual dependence leads to a preference for agency in

the other, suggesting that the C1 partners relationship style is increasingly likely to become

common as the smart home becomes indispensable (Hoffman, Novak and Venkatesh 2004).

These high communal/high agentic partner relationships could be very positive in consumer-

26

object assemblages, where consumer and object interact with many other entities as part of the

assemblage. The object may act as a type of surrogate for the consumer in these interactions,

such as when it is an agentic robot partner.

When both agentic and communal expression is low (C4), consumers and objects become

detached interactors and consumers are likely to be disengaged. Other types of partner styles are

possible, including adversarial partners (C3). While agentic expression is high, communality is

low. In this case, self-extension and self-restriction experiences are likely. In the opposite style

C2, agentic expression is low and communality is high. This reflects a cooperative style absent

agentic expression, so self-expansion and self-reduction experiences are likely.

Unstable Relationships

Relationships that express neither reciprocity on agency nor correspondence on

communion are unstable (anticomplementary), as shown in Figure 2d and rows D1, D2, D3 and

D4 in Table 1. In unstable relationships, consumers and objects behave in ways that are opposite

to what is expected to be elicited on both dimensions. These relationships represent the least

stable style and predict avoidance (Kiesler 1983; Horowitz et al 2006). If no resolutions can be

found, the relationship is likely to disintegrate, leading to product abandonment.

For example, in style D1, the high agentic/high communal consumer is likely to

experience not just self-extension and self-expansion, but also self-restriction and self-reduction

in interactions with a smart object who is perceived to overrule her wishes in an unhelpful

manner. Style D4, in which the disengaged consumer is low agentic and low communal,

represents a relationship that presents few opportunities for sustained interaction. Styles D2 and

D3 are mirror images: consumers may experience self-extension but also self-restriction (D2), or

self-expansion and also self-reduction (D3), owing to their or the object’s lack of communality,

27

the non-reciprocity on agency, and the non-correspondence on communion. From a marketing

perspective, styles D1, D2, D3, and D4 are very important, as they are the most likely to lead to

diminished expectations for smart objects and increasing churn rates.

RELATIONSHIP JOURNEYS

In our assemblage theory-circumplex model framework, the relationship between a

consumer and a smart object emerges dynamically (Abele and Wojciszke 2007; Carpenter and

Spottswood 2013; Guisinger and Blatt 1994; Hoffman and Novak 2018). This framework

therefore gives us a rich and powerful way to: 1) define and measure consumer-object

relationships, and 2) map consumer-object relationships as they evolve over time. By measuring

and mapping relationship journeys, we can derive a number of important marketing

consequences of consumer-object relationships involving usage and relationship satisfaction, and

relationship continuance and retention.

Defining and Measuring Relationship Journeys

Recent research has begun to examine elements of the dynamics of relationship journeys

in the context of consumers’ relationships with brands. For example, Lam et.al.’s (2013)

consumer-brand identification model includes a growth rate component recognizing that

consumer-object relationships can evolve over time as a function of exogenous variables.

Harmeling, et.al. (2015) evaluate “relationship velocity,” which specifies the rate and direction

of change in consumer-object relationships. Similarly, He, Chen and Alden (2016) examine the

trajectory of brand attitudes as a function of consumer-object relationships.

Lemon and Verhoef (2016) have called for data-based mapping of the customer journey

that measures consumer experience across multiple touchpoints, stating “there is an urgent need

28

for the development of scales for measuring customer experience across the entire consumer

journey.” Likewise, Homburg, Jozie and Kuehnl (2017) identify touchpoint journey monitoring

as a key firm capability for customer experience management. Our interpersonal circumplex

model framework for understanding consumer-object relationships supports scale development

efforts for monitoring changes in relationships. Since relationship styles are based upon the

agentic and communal roles of consumer and object, existing scales of agency and communion

(e.g. Abele and Wojciszke 2007) can be modified and used to track the evolution of relationship

styles over time. These agentic and communal roles parallel dependence and interdependence,

respectively, in marketing relationships (Scheer, et.al. 2015). Dependence captures reciprocity of

agency and interdependence reflects correspondence on communion in relationships. This

suggests that agency and communion measurement in the context of our framework could also

provide greater measurement precision for marketers focused on the joint impact of dependence

and interdependence in marketing relationships.

Relationship Journey Mappings

The dynamics underlying the “relationship journey” (Ring and Van de Ven 1994) of

consumers and smart objects represents a particularly rich area for marketing practice. Managers

should expect that a number of factors will contribute to the journeys relationship styles are

likely to take. For example, shifts from complementary master-servant (panel A in Figure 2), to

non-correspondent master-servant and partner (panels B and C in Figure 2), to unstable

relationship styles (panel D in Figure 2) are likely, as they are predicted from the circumplex

model as a natural progression. For relationships to survive then, out of balance relationships will

need to move toward balance, with balance defined as complementarity. As penetration and

usage of smart products increases, it will be incumbent upon managers to develop marketing

29

actions that support these shifts toward balance. To assist in this effort, we develop three likely

scenarios for relationship journeys: 1) consumer as master, 2) master-servant role reversals, and

3) journeys between stable and unstable relationships.

Consumer as Master. The consumer master-object servant relationship style is a natural

starting point for mapping the consumer-object relationship journey, having been extensively

discussed in the marketing literature (Aggarwal and McGill 2012; Fournier 1998; Kim and

Kramer 2015). This relationship style combines a high agentic role of the consumer with a low

agentic role of the object. Figure 3 shows, however, that in the context of differing communal

roles expressed by the consumer and object, the possibility space of consumer master-object

servant relationships is actually larger than managers might expect. The possibility space

includes intermediate styles in addition to the four consumer master-object servant styles (A1,

A3, B1, B3) that were shown in Figures 2a and 2b. The arrows in Figure 3 show how the nature

of the consumer master/object servant relationship changes as the communal role of the

consumer or object changes. Figure 3 also shows the impact on consumer experience, depending

upon the consumer-object relationship style. Possibility spaces may be derived for each broad

relationship style and can be used to map the potential paths a particular relationship style might

follow on its journey.

--- Figure 3 ---

Figure 4 highlights one specific path that consumer master-object servant relationship

journeys might take through the possibility space. Imagine a consumer who installs a home

security camera (time 1, Figure 4). The consumer is concerned about their privacy and does not

trust the camera to maintain privacy. The consumer’s expressive role in this assemblage is high

agentic but low communal, and the consumer infers the object’s expressive role to be low agentic

30

and low communal. The consumer points the camera out the window to check their car that is

parked on the street, so they can test how the camera works (self-extension experience). But, due

to privacy concerns, the consumer disables the ability of the camera to store footage on the cloud

and does not let the camera see inside their home (self-restriction experience). Despite the nega–

tive aspects to this relationship, it is a stable complementary relationship (style A3 in Figure 2).

--- Figure 4 ---

Over time (time 2, Figure 4), the consumer gradually becomes comfortable with the idea

of letting the camera see inside their front door, and also allows it to store one day of camera

video footage in the cloud (increased communal role of both consumer and object). The

consumer now uses the camera to monitor their home while on vacation (self-extension

experience). After still more time (time 3, Figure 4), the consumer starts to feel the camera has

become an important part of a safer home (consumer and object are both high communal). The

consumer feels more secure because of the camera (self-expansion experience) in addition to

using the camera to monitor their home (self-extension experience). Now, imagine that a year

later, the consumer buys a second, newer camera model with better resolution and greatly

improved motion detection with many fewer false alarms. While the consumer still feels secure

because of their cameras (self-extension experience), the many false alarms from the old camera

make the consumer feel like themselves they had to do half the camera’s work for it (self-

reduction experience). The old camera is moved to the garage and pointed to the pet food storage

area. The old camera then becomes an unimportant player in the home’s overall security (object

is low communal). The consumer still uses the old camera, but only to see if the pet food supply

in the garage is low (self-extension with self-restriction).

Managers can employ relationship journey mappings like this to understand how the

31

relationship between a consumer and an object is likely to change over time, how consumer

experience is likely to change over time, and the role of the consumer-object relationship in

consumer experience. Such maps have the potential to enhance marketer understanding of

consumer use and consumer behavior. For example, it could be useful for a manager to run

thought experiments to predict the starting point and likely trajectories of a consumer-object

relationship, and then collect data or run field experiments to infer the actual journey path and its

marketing consequences.

The journey mapping shown in Figure 4 reflects how the roles of a consumer and object

might change over time, independent of marketing action. But what if a marketer wanted to

influence the trajectory of the consumer-object relationship? Suppose we begin again at time 1 in

Figure 4, with a consumer master/object servant relationship where both consumer and object

play a low communal role (style A3). Marketers could clearly communicate to consumers that all

of the camera’s data was encrypted and viewable by just the consumer and no other party. As a

consequence, the consumer might begin viewing the object as expressing a communal role,

shifting the relationship style to the top left of Figure 4 (style B3). The tendency for the

consumer to seek greater complementarity in the relationship would naturally lead the consumer

to increase their own communal expression in the assemblage. The consumer could express

communality by trusting the camera’s capacity to protect their privacy. If that occurred, the

relationship style in the top right of Figure 4 might obtain (style A1). This second relationship

journey points out the opportunity for successful outcomes from managerial intervention, as

opposed to the journey diagrammed in Figure 4 that relies on the expressive roles of the

consumer and object to change on their own through potentially longer periods of interaction.

Master-Servant Role Reversals. As discussed earlier, the object master-consumer servant

relationship style is a role reversal that obtains when the consumer’s agentic role is low and the

32

object’s agentic role is high. This stable master-servant style is a positive relationship when

communality of consumer and object is high, but can become a negative relationship when

communality of the consumer and/or the object is low. Considering only positive relationships

where communality of both consumer and object is high, Figure 5 shows the relationship

journeys that transition between consumer as master and object as master. While other journeys

are possible if the communal role of either consumer or object becomes low, these are the only

possibilities when the communal role is always high.

--- Figure 5 ---

One scenario that has the potential for role reversal involves a consumer in an

autonomous car who may be required to take over in an emergency. This emergency response

requirement varies by states within the United States, and across countries (Greenblatt 2016).

When it is possible for the consumer to take control from the autonomous car, the direct path

shown in the center of Figure 5 between consumer as master and object as master would appear

to be the most likely journey, due to the immediacy of response required. In an emergency, the

consumer would seek to immediately take over the role of driver from the autonomous car.

However, recent research indicates that the takeover by the driver is not immediate. Across 25

studies, it takes on average 2.96 seconds for a driver to regain control from an automated car in

critical situations involving failure of the automated system (Eriksson and Stanton 2017). During

these nearly three seconds, neither the autonomous car or the consumer is in control, briefly

following the mutual low agentic path at the right side of Figure 5. In non-critical situations, such

as exiting from highways, it takes a median of 4.5 seconds for the driver to regain control

without distraction, and 6 seconds with distraction (Eriksson and Stanton 2017), with similar

results in the opposite direction where the driver chooses to surrender control to the car. This

33

analysis highlights the urgent need for marketers to develop effective communications programs

to manage consumer expectations and promote consumer learning during the use of smart

objects. In this relationship journey example, communications programs would seek to ensure

that consumers clearly understand that reversing control of the autonomous car is not direct, but

must proceed through a brief interval of no agency expressed by either party.

Journeys Between Stable and Unstable Relationships. We last consider how the positive

and stable object master-consumer servant relationship style has the potential to shift to one that

is negative and unstable. Consider Amazon Key, an assemblage incorporating an Internet-

connected lock and security camera that allows a delivery person to unlock your door and deliver

Amazon packages inside your home to guard against theft (Fowler 2017). Ideally, as depicted in

Figure 6, the relationship between the consumer and Amazon Key reflects the object master-

consumer servant (style A2), where Amazon Key is high agentic and high communal, and the

consumer is low agentic and high communal. However, Amazon Key has been described as

“creepy,” the required hardware installation can be challenging, it turns out that is possible to

hack Amazon Key to disable the security camera, and in one test Amazon missed 50 percent of

its delivery windows (Fowler 2017). In this decidedly negative scenario, the consumer is still

high communal but must also express high agency because of the need for direct involvement.

The Amazon Key is still high agentic, but its actions express that it is low communal. In this

case, a potentially positive master-servant relationship shifts to something much less stable (style

D1).

Relationship journey mapping can help managers understand how a positive relationship

is likely to degrade, and what actions they might need to take to keep it on course. Figure 6

shows potential journeys between positive and negative relationship styles of the consumer and

Amazon Key. From the positive object master-consumer servant relationship (A2, top), either the

34

consumer could shift to a high agentic role (right path through style C1) or the object could shift

to a low communal role (left path through style B2). Both scenarios have the potential to further

shift to an unstable style (D1). In the center path, both consumer and object simultaneously shift

to the unstable style D1. As one danger of the unstable relationship style is product

abandonment, it is important for managers to know which specific relationship journeys are

actually occurring, along with their potential trajectories. Because consumer and object are still

both high communal in style C1, a shift from A2 to C1 may be easier to reverse than a shift from

A2 to B2, and certainly easier to reverse than a direct shift from A2 to D1. This analysis

reinforces the importance of measuring and tracking relationship journeys.

--- Figure 6 ---

DISCUSSION

Contribution

We believe our framework for consumer-object relationships makes four important

contributions. First, consumer-object relationship styles are defined in terms of the two

foundational dimensions of behavior, agency and communion, in the circumplex model of

interpersonal complementarity. The model offers a rich framework with an underlying geometry

that allows us to incorporate continuous rather than discrete definitions of styles, supports

extensive measurement and empirical endeavors, and facilitates the visualization of customer-

object relationships and the journeys they take over time. Second, through the concept of part-

whole interaction from assemblage theory, our framework connects the agentic and expressive

roles of consumers and objects to enabling experiences of extension and expansion, and to

constraining experiences of restriction and reduction. This allows us to predict the types of

consumer experience that are likely to correspond to different consumer-object relationship

35

styles. Third, our framework incorporates the roles of both the consumer and the object, arguing

that consumer perceptions of the object’s expressive role in interaction can potentially be based

on object-oriented, as opposed to human-centric, anthropomorphism. Fourth, our

conceptualization has strong relevance for marketing practice. It offers an easily quantifiable

framework for measuring and mapping the journey these relationship styles are likely to take

over time. Such journeys can then be linked to different phases of the purchase process, relevant

marketing outcomes, and the most appropriate marketing and communications efforts for each

style at each stage of the process.

Research Directions

Our framework offers a number of important directions for future research. First, we have

assumed that consumer-object relationships will have a natural tendency toward

complementarity (correspondence on communion and reciprocity on agency). However,

predictions based on interpersonal relationships may not necessarily follow for consumer-object

relationships. For example, cooperative consumer-object partners (style C1) may represent a

highly stable relationship style in consumer-object relationships, especially when considered in

the context of ambient interaction. Due to the low cognitive demand of ambient interaction

(Forlizzi, Li and Dey 2007; Rogers et al. 2007; Weiser and Brown 1996) low-level ongoing

background agentic actions by a communal consumer and communal object can co-exist over

long periods of time.

Second, our development of relationship styles shows that self-extension and self-

expansion experiences will co-occur when both agentic and communal expression are high. This

would seem to support the idea that extension and expansion experiences may be confounded,

and, in fact, there has been some confusion in the marketing literature concerning the distinction

36

between the constructs of self-extension and self-expansion (Connell and Schau 2013; Hoffman

Novak and Kang 2016). But the fact that extension and expansion experiences can co-occur does

not mean that they are the same thing. Our framework provides guidance for separately defining

and measuring these two distinct types of experience.

Third, in the early stages of consumer-object relationships, perhaps even before the

consumer has begun interacting with the object, consumers may perceive the object as playing a

low or high communal role based upon what they know about the brand, rather than from their

experience with the object (Teas and Agarwal 2000). For example, Google’s recent blocking of

YouTube on Amazon devices, and Amazon’s refusal to sell Google products on its website

(Ingraham 2017) might lead consumers to view Google and Amazon personal assistant objects as

low communal because of the behavior of the parent companies. But, through ongoing

interactions, consumers will form their own usage-based understanding of the degree to which an

object is communal, and the object and company may shift along this dimension. How does

consumer understanding of the agentic and communal roles of a company and its products affect

each other, and how might this understanding change based upon consumer-object relationships?

Fourth, over time we expect that consumers will come to view at least some smart objects

as possessing their own identity. Once that identity has emerged, it, rather than

anthropomorphism might be used as the lens through which to interpret the actions of other

objects. For example, a consumer who has interacted for a year with Amazon Alexa may

purchase a Google Home voice assistant. The consumer may then view Google Home as “Alexa-

like” (“alexamorphism”) rather than human-like (anthropomorphism). This suggests that

anthropomorphism may be supplemented by a more object-oriented approach for understanding

what it is like for an object to be an object. An important question for future research will be to

explore the validity of different mechanisms for perceiving the expressive roles of object

37

experiences, and their likely evolution as usage deepens.

Fifth, the anthropomorphic mechanisms consumers use to understand the object’s

expressive role are likely to change over time, with consequences for relationship styles. As we

discussed, consumers might initially understand a newly acquired smart object in human-centric

anthropomorphic terms, driven by marketing promises that the device can function as a kind of

best friend. Over time, consumers can be expected to learn that the supposedly communal object

does not really care about them as a friend would. So, instead of a human-centric

anthropomorphic view of a friendly device, consumers might shift their perceptions to one more

object-oriented, where the object plays a relatively low communal role. Marketers’

communication messages may need to evolve in anticipation of these natural shifts. We think it

is a fascinating question for future research to probe these mechanisms.

What Remains Unexplained?

Fournier and Alvarez (2012) identify three broad areas where two-dimensional

relationship frameworks may fall short: 1) power and the relative balance of position, status, and

authority, 2) emotional intensity of the relationship, and 3) identity issues. Our framework is

based not only on two underlying dimensions of agentic and communal roles, but also on the

core concept from assemblage theory that parts and wholes have the capacity to enable and

constrain each other. We think this permits us to address all three of the concerns raised by

Fournier and Alverez (2012). First, the balance of power between consumers and objects can be

explained in terms of the capacities of consumers and objects to enable and constrain

assemblages, and to be enabled and constrained by assemblages (DeLanda 2006). Relative

positions of power are reflected in various relationship styles, such as master-servant. Second,

38

circumplex models can also specify relationship intensity. Kiesler’s (1983) interpersonal circle

arrays types of interpersonal styles around the circumference of three concentric circles

corresponding to mild, moderate, and extreme intensity of interpersonal styles. Third, the

concept of self-extension as the agentic incorporation of aspects of a consumer’s identity into an

assemblage, and self-expansion as the communal incorporation of aspects of an assemblage’s

identity into the consumer, allow our framework to address identity issues. From an assemblage

theory perspective, identity consists of the properties (measurable characteristics), capacities (to

affect, or to be affected by), and expressive roles of an assemblage (DeLanda 2011, 2016). Our

framework considers not only the consumer’s identity, but also the object’s identity.

Other researchers have also considered which aspects of consumer-brand relationships lie

beyond the two dimensions of agency and communion. These aspects include characteristics of

people such as functional, symbolic and experiential needs (MacInnis 2012), as well as brand

personality characteristics that relate to, but expand upon, the two fundamental dimensions

dimensions (MacInnis and Folkes 2017). Our assemblage theory framework allows us to build

upon this even further, by considering the emergent capacities of an assemblage that go beyond

the characteristics, or properties, of the components of the assemblage.

For example, how do we characterize the consumer’s relationship with a wi-fi connected

smart door lock equipped with a camera? Considering only the motives of the consumer and the

personality of the smart lock yields a fairly static view of the consumer-lock relationship, while

analysis of the agentic and communal roles expressed by the consumer and smart lock

incorporates a more dynamic perspective. In a master-servant relationship, the consumer may at

first use the smart lock as a type of remote control. Over time, the assemblage develops the

emergent capacity to make the consumer feel secure, and the relationship is likely to shift to one

of trusted partners.

39

We now have a deeper understanding of the relationship of the consumer with their smart

lock, but there is still much more that can be explained about the relationship. For example, the

assemblage may enable the consumer to feel sufficiently secure to allow a delivery person entry

into her home when she is not physically there - something they may likely never have

considered doing before. Identification of such emergent behaviors is an additional aspect of

consumer-object relationships that could be of tremendous importance to marketers. These

emergent behaviors represent enabled “functional performance” (Keller 2012) that only exists

after an assemblage has emerged, and not before.

Concluding Remark

Marketing tends to view intelligent agents as tools that can improve the effectiveness of

firms’ efforts to market to consumers (Kumar, et. al. 2016). This perspective echoes early

corporate visions of IoT appliances like smart refrigerators as a means to market to consumers,

for example, by presenting on-screen in-home coupons to consumers (Smith 2013). Our

interpersonal circumplex framework, situated in assemblage theory and object-oriented ontology,

asks marketers to consider a broadened perspective in which consumers and smart objects

equally (although differently) exist as parts of assemblages with their own unique capacities. As

the number and capabilities of smart, Internet-connected objects increase, so do the complexities

of the dynamic and evolving assemblages that emerge from consumer-object interaction. Models

are needed that can help us interpret our interactions with smart objects in a way that also allows

for the perspective of the objects, not just the consumers. This may make us more sensitive to the

perils and promises inherent in the types of relationships we might expect with these objects as

the Internet of Things continues to integrate itself into consumers’ lives.

40

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Figure 1. Assemblage Theory Framework for Consumer-Smart Object Relationships

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Figure 2. 16 Relationship Styles Within Four Broad Classes Defined by the Interpersonal Circumplex Model

Black circles represent consumers and white circles represent smart objects.

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Figure 3. Possibility Space of Consumer Master-Object Servant Relationships

Relationship styles are shown for a high agentic consumer and low agentic object, at nine combinations of level of communion for object and consumer. Grey arrows indicate potential journeys among relationship styles. Boxed labels on each relationship style indicate the most likely types of consumer experience.

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Figure 4. Specific Path in a Consumer Master-Object Servant Relationship Journey

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Figure 5. Relationship Journeys with Role Reversals Between Master and Servant

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Figure 6. Journeys Between Stable and Unstable Relationships

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Table 1. 16 Relationship Styles Obtained from the Four Broad Relationship Styles

*Combinations of agentic and/or communal expression that degrade consumer-object relationships so that extension/expansion are accompanied by restriction/reduction: a) communality of person and/or object is low; b) agency has non-reciprocity; c) communality has non-correspondence. In addition, the consumer is disengaged when there is both low agency and low communion.

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entic

Com

mun

al

Agen

tic

Com

mun

al

self-

extension

(positive agentic

experience)

self-

restriction

(negative agentic

experience)

self-

expansion

(positive communal

experience)

self-

reduction

(negative communal

experience)

self- disengaged

(neither

enabled or constrained)

A) MASTER-SERVANT (complementary)

A1 hi hi lo hi yes yes

A2 lo hi hi hi yes

A3 hi lo lo lo a yes yes

A4 lo lo hi lo a yes

B) NON-CORRESPONDENT MASTER-SERVANT (semimorphic acomplementary)

B1 hi hi lo lo a,c yes yes yes yes

B2 lo hi hi lo a,c yes yes

B3 hi lo lo hi a,c yes yes

B4 lo lo hi hi a,c yes

C) PARTNERS (isomorphic acomplementary)

C1 hi hi hi hi b yes yes yes yes

C2 lo hi lo hi b yes yes

C3 hi lo hi lo a,b yes yes

C4 lo lo lo lo a,b yes

D) UNSTABLE (anti-complementary)

D1 hi hi hi lo a,b,c yes yes yes yes

D2 hi lo hi hi a,b,c yes yes

D3 lo hi lo lo a,b,c yes yes

D4 lo lo lo hi a,b,c yes