The Affective Response Model: A Theoretical Framework of Affective Concepts and Their Relationships...

MISQ Forthcoming Zhang, ARM

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The Affective Response Model: A Theoretical Framework of Affective Concepts and Their Relationships in the ICT Context

This is a pre-publication version of the paper as of 2012.05.01. Suggested citation is:

Zhang, P. (Forthcoming), The Affective Response Model: A Theoretical Framework of Affective Concepts and their Relationships in the ICT Context, MIS Quarterly.

Ping Zhang

School of Information Studies, Syracuse University, Syracuse, NY 13244 U.S.A.

[email protected]

Abstract

Affect is a critical factor in human decisions and behaviors within many social contexts. In

the information and communication technology (ICT) context, a growing number of studies

consider the affective dimension of human interaction with ICTs. However, few of these studies

take systematic approaches, resulting in inconsistent conclusions and contradictory advice for

researchers and practitioners. Many of these issues stem from ambiguous conceptualizations of

various affective constructs and their relationships. Before researchers can address questions

such as “what causes affective responses in an ICT context,” and “what impacts do affective

responses have on human interaction with ICTs,” a theoretical foundation for affective concepts

and their relationships has to be established.

This theory and review paper addresses three research questions: (1) What are pertinent

affective concepts in the ICT context? (2) In what ways are these affective concepts similar to, or

different from each other? (3) How do these affective concepts relate to or influence one


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another? Based on theoretical reasoning and empirical evidence, the Affective Response Model

(ARM) is developed. ARM is a theoretically-bound conceptual framework that provides a

systematic and holistic reference map for any ICT study that considers affect. It includes a

taxonomy that classifies affective concepts along five dimensions: the residing, the temporal, the

particular/general stimulus, the object/behavior stimulus, and the process/outcome dimensions.

ARM also provides a nomological network to indicate the causal or co-occurring relationships

among the various types of affective concepts in an ICT interaction episode. ARM has the power

for explaining and predicting, as well as prescribing potential future research directions.

Keywords: Affect, emotion, mood, affective response, affective evaluation, affective quality,

individual reactions toward ICT, theory, Affective Response Model, ARM


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Introduction Affect is conceived of as an umbrella term for a set of more specific concepts that includes

emotions, moods, and feelings (Bagozzi et al. 1999; Liljander and Mattsson 2002; Russell 2003).

Affect is a fundamental aspect of being human, playing an integral role in human motivation

(Reeve 2005), influencing reflexes, perceptions, cognitions, social judgments, and impacting

various behaviors (Brief 2001; Forgas 1995; Forgas and George 2001). Evidence in

organizational behavior, marketing, social psychology, management, and information systems

has confirmed affect as a strong determinant of job satisfaction (Weiss et al. 1999), decision-

making behavior (Mittal and Ross 1998), consumer shopping behavior (Childers et al. 2001),

creative problem-solving (Isen et al. 1987), and attitude change or persuasion (Petty et al. 2001).

These studies suggest that affect can explain a significant amount of variance in one’s cognition

and behavior, and can even have more explanatory power than cognition under certain

circumstances. Contrary to the widespread assumption that affective reactions are inherently

subjective, contextually labile, and thus unreliable, studies find that people often exhibit greater

similarity in affective reactions than in reason-based or cognitive assessments (Pham et al. 2001).

As such, understanding affect, its causes, and its effects, is important both for its own sake, and

for understanding other mainstream concepts and issues studied in various disciplines, including

those concerned with ICTs. A robust understanding of affect may also have practical

implications for design, acceptance, use, and management of ICTs.

Affect-related phenomena and concepts have been studied since the early days of the

information systems (IS) discipline. Examples include attitude and satisfaction, which are still of

interest to scholars (Hess et al. 2006; Zhang and Sun 2009). However, the intensity of interest in

affective concepts and phenomena has fluctuated over the decades, largely due to inconsistent


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and inconclusive results, echoing similar patterns in psychology and other disciplines. In recent

years, IS and human-computer interaction (HCI) studies have broadened the coverage of

affective concepts in studying human interaction with ICTs1. For example, Norman has shifted

from usability-centric design (1992; 1993; 1983; 1988) to emotional design (2002; 2004;

Norman et al. 2003). Studies have focused on a number of affective topics including emotional

usability (Kim et al. 2003), affect in organizational communication behavior (Te'eni 2001),

affective reactions toward information technologies (Zhang and Li 2004; Zhang and Li 2005),

emotion on information technology use (Beaudry and Pinsonneault 2010), mood in IS usage

(Loiacono and Djamasbi 2010), affective user interface (Johnson and Wiles 2003; Lisetti and

Nasoz 2002), computer playfulness (Webster and Martocchio 1992), flow in computer mediated

environments (Finneran and Zhang 2003; Finneran and Zhang 2005; Ghani 1995; Koufaris

2002), cognitive absorption (Agarwal and Karahanna 2000; Zhang et al. 2006), fun (Carroll and

Thomas 1988) and funology (Blythe et al. 2005), hedonic quality (Hassenzahl 2001), among

others (Sun and Zhang 2006a; Thatcher and Perrewe 2002; Venkatesh 2000).

As ICT use has grown beyond organizational and work contexts into nearly every facet of

our lives, interest in affect is particularly timely and relevant as we seek to understand

individuals’ use and exploration behaviors. Users’ choices of ICTs have grown tremendously,

with many competing ICT products and services available for similar purposes. For example,

when choosing a mobile phone, one considers more than just usability, functionality, and

reliability. The final decision is likely based on both cognitive factors (such as price, service,

features, and usability) and affective factors (how cute the product is, how unique it is from

others, or how it makes one feel). Such technological changes have prompted researchers to

1 In this paper, we consider ICT broadly, including technologies for personal, organizational, and societal communication, information processing, learning, entertaining, and other purposes.


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challenge the cognitive-dominant paradigm in studying individual reactions toward ICTs

(Agarwal and Karahanna 2000; Beaudry and Pinsonneault 2010; Loiacono and Djamasbi 2010;

Sun and Zhang 2006a; Zhang and Li 2004; Zhang and Li 2005).

The majority of affect-related empirical studies within the ICT context have focused on the

causes and/or effects of affect (for reviews, see Brave and Nass 2003; Sun and Zhang 2006a).

Yet, many studies showed inconsistent and inconclusive findings. As we will demonstrate in

greater detail in this paper, there is a lack of agreement on the names, labels, meanings,

connotations, and even measures of affective concepts. Also realized is the practice of adding

various measures (such as affective and emotional) to certain ICT phenomenon but lacking

specific theories tailored for affect/emotion in the ICT context (Bagozzi 2007). Although

affective studies in psychology have established certain consensus, the ICT literature is largely

disconnected from this consensus and exhibits a lack of systematic examination of affective

phenomena that may involve relationships among affective concepts. Compared to the broad

coverage of the cognitive and behavioral aspects of ICT interaction, only a small number of

studies consider more than one affective construct in the same study (see Appendix A for detail),

and an even smaller number of studies provide examinations of the relationships among affective

constructs (see Appendix B for detail). All these gaps indicate a lack of systematic and

theoretical examination of affective phenomena, concepts and their relationships in the ICT

context. Such lack of research attention may be a major contributing factor to the inconclusive

findings. As a result, research progress is hindered, and future research directions become

indecisive. Given the importance of, and increased interest in the affective dimension of human-

ICT interaction, theoretically-grounded systematic analyses of affective concepts must be

established before one can investigate the causes or impacts of affective responses in the ICT


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context.

In this paper, our grand research question is: What are the affective concepts in the ICT

context? This question can be further examined along three detailed aspects:

1. What are pertinent affective concepts (not just terms or labels) in the ICT context?

2. In what ways are these affective concepts similar to or different from each other?

3. How do these affective concepts relate to (or influence) one another?

Answers to these questions are timely, interesting and important to the IS community. With

an increasing interest in affect in the ICT context, scholars need to be aware of the issues in the

current literature, and be guided with theoretically bounded foundations, frameworks and

research directions. The Affective Response Model developed in this paper provides a

theoretically bounded framework to understand the intrinsic meanings of all types of affective

concepts, their similarities and differences, and how they may relate or influence each other in an

ICT interaction episode. As a framework, ARM explains and predicts certain findings in the

literature, depicts gaps and holes, synthesizes and unifies existing studies on particular affective

concepts and their relationships, and prescribes future research efforts and directions.

To remain focused, this study’s scope is set by the following considerations. First, since the

ICT literature has extensively covered cognitive reactions, this paper mainly covers affective

concepts, although at times we discuss cognitive and behavioral concepts briefly to better explain

affective concepts. Second, we avoid detailed discussions about the causes and consequences of

affect unless such discussions help explain what affective concepts are. Third, as we are

interested in one’s direct experience with an ICT, we rule out studies or situations that may focus

on managers or executives who express satisfaction or other affective responses to ICTs (such as

ERP implementation) that are not based on direct or hands-on experience with ICTs.


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The paper proceeds as follows. In the next section, we introduce briefly a set of basic

affective concepts from the psychology and social sciences literature to provide a foundation for

ICT-specific affective concepts that appear in the Affective Response Model (ARM). In the

following section, we focus on the first part of ARM: a taxonomy of affective concepts. Based

on extensive literature reviews of empirical studies that include affective constructs in the ICT

context, as well as theoretical reasoning and justification, the taxonomy contains five dimensions

for conceptualizing various types of affective responses. The taxonomy section is followed by

the section on the second part of ARM where a set of propositions that describe the relationships

among various types of affective concepts, resulting in a nomological network. We conclude the

paper with discussions, limitations, theoretical and practical implications, and future research

directions.

Basic Affective Concepts in Psychology & Social Sciences Despite diverse perspectives, approaches, theories and findings on affect and related

phenomena, recent developments in psychology and social sciences have achieved a level of

consensus on both the meanings and structures of various affective concepts (Barrett and Russell

1999; Rosenberg 1998; Russell 2003; Russell 2009; Watson and Clark 1994; Watson et al. 1999;

Weiss and Cropanzano 1996). In general, it is widely recognized that the term affect is an

umbrella term that represents a set of concepts that can be very different from each other (Russell

2003) and that affect-related phenomenon is much broader than emotions (Russell 2009). In this

paper, we do not intend to and cannot provide a comprehensive review of all views and works on

affect in psychology and social sciences. Rather, we plan to build our framework on several

pertinent concepts and theories in the psychology and social sciences literature. Specifically, we

introduce the two most fundamental concepts, core affect and stimulus, and then a set of basic


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affective concepts such as perceived affective quality, affective quality, affective cue, mood,

temperament, emotion, and attitude. We will also briefly introduce the structure of affect as it is

used to define what concept is considered an affective concept.

Core Affect and Stimulus: the Fundamentals

Among all affective concepts, the most fundamental is core affect (Barrett et al. 2007;

Russell 2003; Russell 2009). Supported by neuroanatomical evidence, core affect is considered

an intrinsic aspect of consciousness (Barrett et al. 2007). It is a neurophysiological state

consciously accessible as a simple, non-reflective feeling that is an integral blend of hedonic or

valence value (pleasure–displeasure, the extent to which one is generally feeling good or bad)

and arousal or activation value (sleepy–activated, the extent to which one is feeling engaged or

energized) (Russell 2003). As consciously experienced, core affect is mental but not cognitive or

reflective (Russell 2009; Zajonc 2000). It is primitive, universal, and ubiquitous, existing without

being labeled, interpreted, or attributed to any cause (that is, Object free or free-floating). An

analogy of core affect’s existence is one’s felt body temperature: you can notice it whenever you

want (Russell 2003). An analogy of core affect as a single feeling is color, where dimensions of

hue, saturation, and brightness combine in an integral fashion to form one unified sensation of

any particular color (Russell 2009). To varying degrees, core affect is the core of all emotion-

laden events, is involved in most psychological events, and is what makes any event “hot” (i.e.,

emotional or affective) (Russell 2003). Core affect was referred to by other names in the past,

such as affect or basic affect (Batson et al. 1992; Watson et al. 1988) and mood (Morris 1989,

based on early conceptualization of mood). These references thus should be read carefully in

light of the new conceptual consensus.

Like body temperature, core affect can change due to individual genetic differences, internal


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factors (e.g., activities of immune cells and hormone changes), and external factors (e.g., a bear

caused Alice’s core affect to change from tranquility to distress) (Russell 2003; Russell 2009).

Change in core affect can be caused by drugs (e.g., stimulants and depressants), or by a

combination of events. Some causes are obvious and yet sometimes one may go through a

change in core affect without knowing why. The key is that people have either no direct access to

these causal connections or limited ability to track complex causal connections. Instead, a person

makes attributions. Through attribution, core affect can become directed at an Object/a stimulus

(Russell 2003).

Stimulus is defined as something or some event in one’s environment that a person reacts or

responds to. Stimulus is a psychological representation; it can be real, imagined, fictitious ,

remembered, in the future or anticipated, or in other forms of virtual reality (Russell 2003).

Stimuli enter consciousness being affectively interpreted (Russell, 2003). This leads to a number

of affective concepts that concern the subject (the person) or/and the object (the stimulus). These

are briefly introduced below.

Basic Affective Concepts

Table 1 provides a summary of the fundamental and basic concepts in the psychology

literature that play a role in both the development of other affective concepts and the

relationships among affective concepts in the ICT context. Each basic affective concept is

discussed in detail below.

**** Insert Table 1about here ****

Perception of affective quality (PAQ) is an individual’s perception of a stimulus’ ability to

change his or her core affect. It is a perceptual process that estimates the affective quality of the

stimulus. It begins with a specific stimulus and remains tied to that stimulus (Russell 2003), but


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it varies by individual. Different people may perceive the same stimulus to have different

affective qualities (thus the notion: beauty is in the eye of the beholder). Perception of affective

quality is considered a ubiquitous and elemental process (Cacioppo et al. 1999; Russell 2003;

Zajonc 1980). It is important to note that perception of an affective quality per se is a “cold”

(meaning cognitive/logical) perceptual process (made “hot” [meaning affective/emotional]

through its linkage to core affect) that fixes a belief about the affective consequences of

something without having to undergo those consequences; it is the anticipation (or

representation), rather than the experience of a change in core affect. For example, a change in

core affect is not needed in order to know that a garden is lovely (Russell 2003). The concept of

perception of affective quality was called by other names in the past, such as evaluation,

automatic evaluation, affective judgment, appraisal, affective reaction, and primitive emotion

(Russell 2003). These names all touched upon some aspects of PAQ but may also introduce

confusions when being referenced without considering the new consensus in conceptualization.

Closely related to but different from perception of affective quality is the concept of affective

quality. Affective quality is the affective property of a stimulus that has the ability to cause a

change in a person’s core affect (Russell 2003). Whereas core affect exists as a feeling inside

oneself (it is Alice who feels upset), affective quality exists in the stimulus (it is the bear that is

upsetting) (Russell 2003). Objects and events all have their own affective qualities (regardless

who perceive them), just as they have other function or performance related qualities that can be

perceived and judged as being relative to other similar stimuli. For example, films and role

playing are frequently used to elicit certain feelings in people because of these stimuli’s strong

affective qualities.

Affective cues are specific features or characteristics of a stimulus that can manifest the


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affective quality of the stimulus. Continue the examples from the last paragraph: it could be the

size or the look of the bear that makes it upsetting. Thus size, look, and other features of a

stimulus function as affective cues that manifest the stimulus’ affective quality. Affective cues

have been studied as environmental cues or signals containing affective information that can

influence emotions (Valdez and Mehrabian 1994) and cognitive processing strategies (Soldat et

al. 1997). In the literature, colors (Soldat et al. 1997), music (Scherer 2004), images (Chowdhury

et al. 2008), and visual presentations (Park et al. 2008) are found to be distinctive affective cues.

Mood is defined as prolonged core affect that has an unclear or unknown stimulus (Russell

2003), thus is not tied to a specific event, situation, or behavior (Lazarus 1991; Moore and Isen

1990; Watson and Clark 1994). Temperament is characteristic of a habitual inclination or mode

of affective response that can be a result of affective traits (a stable individual difference in the

tendency to experience a corresponding mood state) (Watson and Clark 1994).

One of the most complex affective concepts is emotion. Put simply, emotions are induced

affective states (Clore and Schnall 2005), or core affect attributed to stimuli (Barrett et al. 2007;

Russell 2003). Emotions typically arise as reactions to situational events in an individual’s

environment that are appraised to be relevant to his/her needs, goals, or concerns. Once

activated, emotions generate subjective feelings (such as anger or joy), generate motivational

states with action tendencies, arouse the body with energy-mobilizing responses that prepare the

body for adapting to whatever situation one faces, and express the quality and intensity of

emotionality outwardly and socially to others (Damasio 2001; Izard 1993; Reeve 2005). Emotion

is thus formally defined as “an episode of interrelated, synchronized changes in the states of all

or most of the five organismic subsystems in response to the evaluation of an external or internal

stimulus event as relevant to major concerns of the organism” (Scherer 2005, p697). Emotional


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episodes have been modeled to understand various elements of emotions and emotional

experiences (Russell 2003; Scherer 2005; Weiss and Cropanzano 1996). This is a concept we

will revisit and build on later in the paper.

A very special affective concept is attitude. Attitude is one of the most studied concepts on

judgments and behaviors in social psychology, and thus has numerous definitions from many

social science disciplines, including Information Systems. To remain focused, this study uses the

generally agreed upon definition of attitude as a summative evaluation of a stimulus that may

help guide behavior toward the stimulus (Cacioppo and Berntson 1994; Crites et al. 1994; Fazio

1986; Petty et al. 1997; Zanna and Rempel 1988). Attitude can be considered as either a

multidimensional construct comprised of cognitive, affective, and behavioral components, or a

two dimensional construct with instrumental (mostly cognitive) and experiential (mostly

affective) aspects (Ajzen and Fishbein 2005). Similar to some of the previous studies that treat

attitudes as possibly an affect (Bagozzi et al. 1999), we consider attitude a special type of

affective concept by focusing on its affective component, at the same time, note its summative

nature. This is largely consistent with many conceptual treatments of attitude in the IS literature

(e.g., the TAM studies, Davis 1993; Davis et al. 1989).

The Structure of Affect

Besides conceptualization, the structure and measurement of affect also has emerging

consensus. It is generally agreed that affect can be represented by a circumplex model (Russell

1980; Schlosberg 1941; Schlosberg 1952; Watson et al. 1999; Yik et al. 1999), one of the most

widely studied affect models (Barrett and Russell 1999; Remington et al. 2000). This model

includes two independent dimensions: the pleasure dimension (or the valence dimension), which

ranges from one extreme (e.g., misery, agony) to another (e.g., ecstasy), and the arousal


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dimension (or the activation dimension), which ranges from sleepiness/deactivation to activation

(Russell 2003). Figure 1 depicts the affect structure, which can be used as a base to measure all

affective constructs including emotions, moods, temperaments, and affective evaluations.

Variations of the circumplex model have been investigated and tested empirically, further

validating the basic structure of affect (Scherer 2005; Watson and Clark 1984; Watson et al.

1999).

**** Insert Figure 1 about here ****

A Taxonomy of Affective Concepts in the ICT Context We now attend to the ICT literature to review disconnection between the efforts and

findings in the ICT context to the consensus in the psychology and social sciences literature and

to review some inconsistent definitions and treatments of affective concepts (Norman 2002; Sun

and Zhang 2006a). Such a review will lead to the development of a taxonomy where

fundamental and basic affective concepts introduced earlier will guide the understanding of ICT-

specific affective concepts. We consider a concept to be affective if it touches on any of the two

dimensions of the circumplex model. We are particularly interested in two types of stimuli: ICT

(as an object), and interacting with ICT (as a behavior). To illustrate the main ideas of various

ICT-specific affective concepts, we start this section with one of many possible scenarios of

humans interacting with ICT. The scenario will be revisited throughout the paper to illustrate

various concepts and ideas. In each of the following subsections, we first review the ICT

literature to point out certain gaps, then introduce one dimension of ARM to address the gaps.

The ARM taxonomy is finally summarized in the last sub section.


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A Scenario

Imagine a person named Alex. Alex usually does not get easily over-excited about novel

things in his surroundings. He does not like playing computer games in general, yet tends to like

colorful things. One day, while passing by an electronics store in a calm mood, Alex was

attracted to a set of sharp, colorful and dynamic screen displays of a game. He said to himself,

“Wow, that is cool!” He stepped in and started exploring the game. Soon, he felt engaged,

stimulated, playful, and overall was having a lot of fun. Alex was really enjoying himself without

realizing the passing of time. Once he finished the exploration, he was thinking: “Playing this

game was really engaging and enjoyable.” As a result of this experience, Alex concluded that

“This is a really cool game that is well designed, and I liked playing it.” Then, he wondered that

maybe “playing computer games is not such a bad idea.”

The scenario can be considered an emotional episode. It contains various categories of

affective concepts that can be represented by the ARM taxonomy, which consists of five

dimensions to compare and differentiate various affective concepts: the residing, the temporal,

the particular/general stimulus, the object/behavior stimulus, and the process/outcome

dimensions.

The Residing Dimension

Most studies that contain affective constructs in the ICT literature are concerned with ICT-

related stimuli, such as computers, software applications, websites, GSS (group support

systems), mobile data services, e-vendors, and instant messengers, as well as behaviors on such

objects including viewing, using, interacting, and working with them. For example, in our

scenario, stimuli are “computer games” and “playing computer games.” In the literature,

“microcomputer playfulness” is defined as the degree of cognitive spontaneity in microcomputer


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interactions (Webster and Martocchio 1992, p211). It emphasizes a user’s feelings that arise

while interacting with computers. The meaning of this concept is tied to both the person and

“computer interactions.” Here, “computer interactions” cause the person to feel a certain way,

thus the stimulus.

Some affective constructs do not concern a particular stimulus. For example, “negative

affectivity” is defined as the general experience of negative emotions such as guilt or shame

regardless of the situation (Thatcher and Perrewe 2002). Thus, “negative affectivity” occurs

without stimuli. “Perceived mood” of a feedback giver (Ang et al. 1993) is measured with the

following: “looked as if he had had a bad day,” “seemed to be in a good mood today,” and

“looked as if he did not want to be disturbed.” Thus perceived mood is not concerned with a

particular stimulus.

When studying affective concepts, similarly named constructs have been found to differ in

referring to stimuli or not. For example, the above mentioned “perceived mood” (Ang et al.

1993) has no stimulus, while “positive mood” (Webster and Martocchio 1992) relates to how

participants feel during a (computer) training session. In this case, the training session is the

stimulus because positive mood is induced by or reflective of the training session. Another study

defines “mood” as a state variable that refers to how people feel when they are engaged in any

number of activities (Venkatesh and Speier 1999). In this case, its cause is clearly identified

(“engaging in a number of activities”). Such different conceptualizations need to be examined on

whether a stimulus is involved or not when an affective concept is concerned.

Categorizing Affective Concepts along the Residing Dimension

The need to differentiate where the meanings reside can go back to some of the heated

philosophical debates on subjectivity and objectivity in human perception and interaction with


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objects in the environment. Such debates can be found in many disciplines and on various

concepts such as perception, consciousness, affect and aesthetics, to name a few. On the affect

front, the related debate is concerned with the distinction between subject (the person) and object

(the stimulus). Fortunately, the debate has reached certain consensus in that certain concepts are

about subject (the person) due to their insistent self-reference implicit in feeling (thus the states

of the subject such as “no pleasure - extreme pleasure”). Other concepts are about measures of

hedonic value of a stimulus (such as “pleasing – displeasing”) (Batra and Ray 1986; Mehrabian

and Russell 1974). It is beyond the scope of this paper to go deeper into these debates and

consensus. In ARM, we propose that affective concepts can be examined by where their

meanings exist and grouped into three categories accordingly. Table 2 outlines these categories

and lists relevant affective concepts according to the residing dimension. Core affect is not listed

in the table because it is the basis to all affective concepts and is something that makes a concept

affective in nature. For this reason, core affect is not treated in parallel with other affective

concepts, and thus is not listed in Table 2 (and some other tables).

**** Insert Table 2 about here ****

1. Residing within a person without a stimulus

The meaning of an affective concept can reside within a person, either without a clear

stimulus or regardless of stimuli. For example, in our scenario, “Alex usually does not get overly

excited easily about novel things in his surroundings” is a temperament. Its value has little to do

with any stimuli. Another example would be moods, which are specific affective states without

any stimuli (especially ICT related stimuli), the stimulus cannot be clearly identified. In general,

moods and temperaments are not dedicated to specific objects: cheerful moods and cheerful

temperaments may make things seem positive in general (Clore and Schnall 2005, pp. 438).


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2. Residing within an ICT related stimulus

An affective concept can be purely about an ICT-related stimulus, regardless of who

perceives or interprets it. In this case, it is an objective attribute or property of the stimulus, such

as an ICT’s specific design features or attributes. This category includes affective quality and

affective cues. Affective cues manifest affective quality and can be directly perceived by a

person. For example, in our scenario, affective cues are “a set of sharp, colorful and dynamic

screen displays” that attracted Alex.

3. Residing between a person and an ICT related stimulus

These affective concepts can be about a person’s responses to a stimulus and thus

considered to be between a person and a stimulus. For the same stimulus, different people may

have different responses; while for the same person, different stimuli may generate different

responses. To build on the distinction between self-reference in induced feelings (directed

towards subject) and evaluative scales on measuring the hedonic value of a stimulus (directed

towards object) (Batra and Ray 1986), we consider two types of affective responses: emotions

(induced by stimuli) and evaluations of affective quality of stimuli. For example, “I feel excited

(by playing the new computer game),” “I am anxious (about computers),” and “I am bored (by

this application),” are emotions within the ICT context because these are directed towards the

person’s feelings. “This interface is pleasing” and “playing this game can be exciting” are

evaluations of affective qualities of the game because these are directed toward the stimulus’s

affective properties.

Affective evaluation is a general term for a set of concepts whose focus is on evaluating or

appraising the affective quality of a stimulus. Its meaning resides between a person and a

stimulus with the meanings towards the stimulus (“I think the object is pleasing”), not toward the


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person (“I am pleased by the object”). The person will determine the specific value of an

affective evaluation based on his or her appraisal of the stimulus’ affective quality. Affective

evaluations can be primitive (such as perceived affective quality), cognitively latent (such as

perceived enjoyment of using an application), or experientially heavy (such as satisfaction with a

decision support system). Affective evaluations happen all the time (with or without

accompanying emotions) because stimuli enter our consciousness affectively interpreted

(Russell, 2003).

Affective response, also known as affective reaction (AR), is a broader term to include both a

person’s emotions induced by a stimulus and affective evaluations of the stimulus. In other

words, affective response/reaction can be both emotion and affective evaluations.

Affective responses are of particular interest to ICT researchers due to their focus on the

interaction and intersection between humans and ICTs. Among affective responses, affective

evaluations need even more attention. There has been much confusion in the literature regarding

affective concepts in this category, prompting the need to clarify. As such, affective evaluation

concepts will be heavily attended to by the taxonomy.

The Temporal Dimension

The affective concepts that reside within a person or between a person and a stimulus can be

examined by whether their values are constrained by time.

There are several studies in the ICT literature examining the trait vs. state nature of certain

affective concepts. For example, a recurring question in the study of “computer anxiety” is

whether it is a relatively stable personality trait or a mutable temporary state (Beckers et al.

2007). Interestingly, this question regarding temporal nature can be applied to a number of

affective concepts. Specifically, an affective concept might refer to a stable value that can be


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applied in similar situations consistently, or it might refer to a temporary value that is gone once

conditions or the environment change. For example, “cognitive absorption” is studied as a state

of deep involvement with IT (Agarwal and Karahanna 2000). It emphasizes how participants feel

at a given moment when they encounter an IT. Thus, it is a state variable. In one study,

“perceived playfulness” is regarded as an individual’s state, because an individual can feel more

or less playful at various points during his/her visit to a web portal (Lin et al. 2005). In another

study, “playfulness” is the pleasure and inherent satisfaction derived from a specific activity and

is regarded as a personality trait (Venkatesh 1999). Yet in another study, “computer playfulness”

refers to an individual’s tendency to interact spontaneously with a computer and is considered a

system specific trait from using the specific system over time (Hackbarth et al. 2003); therefore it

is not a state in particular, not a personality either. Such inconsistencies in the literature lead to

the need to examine the temporal aspect of these and all affective concepts.

Categorizing Affective Concepts along the Temporal Dimension

Attributions for affect can be constrained by the duration of affective conditions. The

temporal/duration constraint (Clore and Schnall 2005; Clore et al. 2001) has been used to help

understand the connections and differences among several important affective concepts such as

mood, emotion and attitude. Clore and Schnall (2005) explain that: “moods and emotions are

ephemeral and cannot be stored [in memory]. Whatever evaluative information they carry is

temporally constrained, existing only as long as the supporting cognitions, perceptions, or other

elicitors are active, and vanishing as soon as one is no longer in that state. The same is not true

for attitudes, because attitudes are not evaluative states, but evaluative tendencies, that do not

necessarily vanish when one stops thinking about the attitude object” (Clore and Schnall 2005,

pp. 438). Regarding moods and temperaments, “the evaluative inclinations of moods are


20

momentary or constrained by time. In contrast, evaluation inclinations based in temperament are

neither object-specific nor temporally-specific. Thus one can be said to have a cheerful

temperament, even if one is momentarily cheerless” (Clore and Schnall 2005, pp. 438).

Affective evaluations are about something specific and the values of the evaluations do not

disappear when one stops thinking about the specific object. In this regard, affective evaluations

are very similar to attitudes in Clore et al.’s discussion. As we have discussed, attitude can be

considered a type of affective evaluation if the focus is on its affective component.

Table 3 applies the temporal dimension to categorize the concepts that reside within a

person or between a person and a stimulus (affective cue and affective quality reside within a

stimulus thus are not included). In our scenario, “Alex does not like playing computer games in

general” and “Alex tends to like colorful things” are not temporally constrained, they are

dispositions or tendencies, and both have to do with some stimulus (computer games, or colorful

things). “Alex felt engaged, stimulated, playful, and overall was having a lot of fun” is

temporally constrained; the state would be true for that moment but would disappear once Alex

stopped playing and walked away from the store. Yet, “Playing this game was really engaging

and enjoyable” as an affective evaluation does not disappear when Alex stopped playing the

game. He would remember this and be able to recall it later without experiencing the specific

emotions he had during play. Thus this affective evaluation is not temporally constrained.

**** Insert Table 3 about here ****

Two Dimensions for Stimulus Specificity: Object vs. Behavior, Particular vs. General

The stimulus, especially if ICT-related, can be further examined from two aspects: object vs.

behavior, and particular vs. general.


21

Computer anxiety is defined as the degree of apprehension, or even fear, when an individual

is faced with the possibility of using computers (Venkatesh and Bala 2008). Thus, the stimulus

should be “using computers,” which is a behavior on objects. Computer anxiety has been

measured by: (1) Computers do not scare me at all; (2) Working with a computer makes me

nervous; (3) Computers make me feel uncomfortable; and (4) Computers make me feel uneasy

(Venkatesh and Bala 2008, p313). A careful examination of these items shows that only the

second item explicitly has to do with using computers, while the other three all have to do with

computers themselves. One could argue that “computers make me feel uncomfortable” might

have a high correlation with “using computers makes me feel comfortable.” It should be noted,

however, that “computers” and “using computers” are two different kinds of stimuli. It is

possible for one to state that “I am not scared of computers but I am scared of using computers.”

The literature shows that some affective concepts tend to be associated with an object, while

others tend to be associated with behaviors. For example, “first impression of a website”

(Schenkman and Jonsson 2000), “identification quality of images” (Hassenzahl 2004), and

“perceived affective quality of a website” (Zhang and Li 2004), are about ICTs (objects); while

“(perceived) enjoyment of using a computer” (Chin and Gopal 1995; Yi and Hwang 2003) and

“(perceived) playfulness of using a computer” (Igbaria et al. 1996; Venkatesh 1999) are about

behaviors with ICTs. The confusion between object-based and behavior-based evaluations, and

the importance of differentiating such evaluations, are articulated in both social psychology

(Ajzen and Fishbein 2005) and the ICT (Zhang et al. 2008; Zhang and Sun 2009) literature.

Intuitively, it seems that studying ICT use as a stimulus is more relevant than studying ICTs

themselves as a stimulus. Yet, given that ICTs compete for users’ attentions, many of them will

not even get a chance to be acted upon if they do not pass the object-based level of pure exposure.


22

Hence we argue that object-based evaluations are an important part of ICT research.

A person’s affective responses to a particular stimulus may be different from the person’s

affective responses to a general stimulus. For example, “I enjoy using this decision support tool”

(using a particular ICT) is different from “I enjoy using decision support tools” (using a general

ICT, or a type of ICT). “Using mobile internet services is enjoyable” (Thong et al. 2006) is about

a general stimulus, whereas “using (this) website is enjoyable” (Heijden 2004) is about a

particular stimulus. Therefore, confusion and/or less consistent results may occur when

researchers treat these two affective responses equally or make inference about one based on the

other.

Categorizing Affective Concepts along the Two Stimulus Specificity Dimensions

Recent developments in attitude theories assert that Attitude Toward Object (ATO) is

defined as a psychological tendency expressed by evaluating a particular entity with some degree

of favor or disfavor (Eagly and Chaiken 1998), or as a combination of evaluative judgments

about an object (Crites et al. 1994). Attitude Toward Behavior (ATB) is defined as an

individual’s positive or negative feelings (evaluative affect) about performing the target behavior

(Fishbein and Ajzen 1975). The same distinction can be applied to affective evaluations. For

example, one can say “this website looks attractive” (toward object) or “using this application is

enjoyable” (toward behavior).

The argument for distinguishing the general vs. particular stimuli is in line with social

judgment research. Attitude studies, for instance, have established that an attitude toward a

particular object may not always be the same as the attitude toward a class of similar objects

(Ajzen and Fishbein 2005; Reeve 2005). For example, one may have a negative attitude toward

certain groups of people (either classified by geographical locations, ethnicities, or political


23

views), while this same person may have a positive attitude toward a particular individual from

that group. “I like hard working people” does not translate into “I like John who is hard

working.” Similarly, “I like John who is hard working” does not necessarily imply, “I like hard

working people.” In fact, stereotypes (a general attitude that may be formed with a bias) may be

corrected or adjusted by one’s encounters with particular individuals who challenge the accuracy

of those stereotypes. Thus, it is necessary to explicitly state whether an affective concept is about

a general stimulus or a particular one. In the ICT context, a statement such as “Apple products

look attractive” refers to a person’s affective responses to a group of objects (such as iPods,

iPads, iPhones, or other Apple products). This is about the same as saying, “Apple products in

general look attractive.” It should be noted that this person may have a different and specific

affective evaluation of a particular new Apple product, such as an Apple laptop. When a study is

concerned with a particular ICT as an object, the affective responses should be related to that

particular ICT. Likewise, if the focus of the study is on a type of ICTs, then the affective

responses should be about that type of ICTs (Zhang et al. 2008; Zhang and Sun 2009).

The differences between object and behavior, and between general and specific can be

illustrated with the scenario. “Alex does not like playing computer games in general” is an

affective evaluation about behaviors (playing) toward a general type of objects (computer

games); while “Alex likes colorful things” is an affective evaluation of a general type of objects

(colorful things). “This is a really cool game that is well designed” is an affective evaluation of a

specific object (cool game).

The Process vs. Outcome Dimension

Several studies in the ICT context reveal the need to distinguish process-based affective

evaluations from outcome-based ones. For example, the “first impression,” “visual appeal” or


24

“immediate aesthetic perception” a person gets from an initial encounter with an ICT can be as

short as a fraction of a second (Lindgaard et al. 2006; Tractinsky et al. 2006). “Perceived

enjoyment,” the extent to which the activity of using the computer is perceived to be enjoyable in

its own right, apart from any performance consequences that may be anticipated (Davis et al.

1992, p. 1113), seems to focus on the duration of the interaction. “Affective award,” the sense of

emotional gratification often expressed by participants after a successful meeting (Reinig et al.

1996), indicates that it is about a conclusion or summary of the session. Hassenzahl (2004)

separates perceptions of a product’s attributes from their evaluations, positing that “perceptions

of hedonic or pragmatic attributes can potentially lead to a positive evaluation but they must not

necessarily do so (pp. 322-323).” In this case, “perceptions of hedonic or pragmatic attributes”

would be process-based, and “positive evaluation” would be outcome-based. In addition,

Hassenzahl makes a distinction between “substantive” (relating to the essence or substance) and

“verdictive” (relating to a final judgment or decision that is a high-level evaluation). Such

distinctions imply that there may be different levels of processing involving different information

sources and different information processing intensities. This leads to the need to examine the

process vs. outcome dimension.

Categorizing Affective Concepts along the Process vs. Outcome Dimension

Action identification theory posits that any action or behavior can be identified in many

ways, ranging from low-level identities that specify how the action is performed to high-level

identities that signify why or with what effect the action is performed (Vallacher and Webner

1987). The theory has been used in the ICT literature with illustrative examples: low-level

identity could be striking keys; higher-level identity could be writing a report, and highest-level

could be achieving one’s annual sales goal (Davis and Venkatesh 2004). Along with the different


25

levels of identities of actions, there are cognitive perceptions and evaluations such as perceived

ease of use (low-level or process-based focusing on means and tactics that relate to concrete

behavioral actions such as hands-on system usage) and perceived usefulness (high-level or

outcome-based relating more closely to goals, plans and consequences on jobs) (Davis et al.

1989; Davis and Venkatesh 2004). It is thus reasonable to say that just as with cognitive

evaluations, affective evaluations could occur at both the low and high levels.

Specifically, we posit that affective evaluations can occur at two levels of identity: at the

level of interaction process (which itself can have different levels such as exposure or the in-

depth exploration/action levels) and at the level of interaction outcome (with a focus on goals,

relevance, consequences or overall take-away messages).

When one is merely exposed to a particular, relatively new ICT (that is, the individual

receives information presented to him/her but has not acted upon the ICT), the amount of

obtained information is limited. Therefore, the information processing is shallow, and one does

not know much beyond what is presented except some references from the memory (further

discussion on this appears in the next section). The formation of affective evaluations at this

stage can be immediate, preliminary, and toward the ICT as an object. In our scenario, “wow,

that is cool!” represents Alex’s first affective evaluation of the computer game upon immediate

exposure. This shallow information-processing stage is part of the interaction process where

affective evaluations are formed. In other words, these are process-based affective evaluations.

Theoretical reasoning and empirical evidence in psychology and social sciences also support this

notion of quick formation of affective evaluations. One example is the concept of perceived

affective quality in that growing empirical evidence shows that an initial perception of affective

quality takes place automatically within 25 ms of encountering the stimulus (Russell, 2003).


26

When the individual is actively involved in experiential interaction with the ICT, such as

exploring, playing, and using it, information about the ICT is accumulated. At this stage, the

individual can evaluate the ICT based on his or her direct interaction with it. That is, one forms

his/her affective evaluations upon the behavioral actions s/he has with the ICT. In our scenario,

“playing this game was really engaging and enjoyable” is an example of this type of affective

evaluation. It is based on the specific interaction with the object during the process, and thus is

another kind of process-based affective evaluations.

More in-depth information processing occurs when one forms overall affective evaluations

as a conclusion of one’s direct ICT interaction experience. These are higher level information

processing results that include reflections, deliberations, conclusions and summaries about the

object itself or behaviors with the object. For example, “this is a really cool game that is well

designed” and “I liked playing it” are both summation-based affective evaluations. Hassenzahl’s

“verdictive” notion (2004), an expression of authoritative judgments that represent a “take-away”

message, is a good representation of the outcome-based affective evaluations. Attitude, with the

adopted definition in this paper, is thus an outcome-based affective evaluation.

It is worth noting that not all affective evaluations formed at the concluding moment are

outcome-based. If the content and/or depth of such evaluations are about the process per se, then

they are process-based evaluations, even if they are formed after the process is over.

Summary of the Taxonomy

The five dimensions discussed so far can be put together into the outline in Table 4 to form

super-categories and categories of all affective concepts.

**** Insert Tables 4 about here ****

The first level of organization is the residing dimension. As discussed earlier, affective


27

responses include those affective concepts whose meanings reside between a person and a

stimulus. Then, those concepts whose meanings reside either within a person or between a

person and a stimulus are divided by the temporal dimension. In Table 4, the first four categories

contain some of the specific affective concepts we have introduced so far: mood, temperament,

affective quality and affective cue, and emotion. In fact, they are considered specific examples of

four categories of affective concepts respectively: mood belongs to Free-floating Affective State

(Category 1), temperament belongs to Affectivity (Category 2), affective quality and affective cue

belong to Affective Characteristics (Category 3), and emotion belongs to Induced Affective State

(Category 4).

Induced affective state is between a person and a stimulus, thus it is one type of affective

responses, and is different from residing within a person and different from residing within a

stimulus. Induced affective state is temporally constrained, thus it is different from affective

evaluation/disposition.

Affective evaluations are those affective concepts that reside between a person and a

stimulus and are temporally unconstrained. There can be many types of affective evaluations.

Here we provide names for the super-categories and categories for easy reference during the rest

of the paper. Particular Affective Evaluations are evaluations of a particular ICT object and

behaviors. There are four categories of them: Process-based Affective Evaluations toward a

Particular Object (Category 5.1), Outcome-based Affective Evaluations toward a Particular

Object (Category 5.2), Process-based Affective Evaluations toward Behaviors on a Particular

Object (Category 6.1), and Outcome-based Affective Evaluations toward Behaviors on a

Particular Object (Category 6.2). Both induced affective state and particular affective evaluation

are about a particular interaction episode and concern both the person and the stimulus in the


28

episode. The main difference is that induced affective state focuses on the person feelings, while

particular affective evaluation focuses on the person’s appraisal of the stimulus’ affective

quality.

Learned Affective Evaluations are evaluations about a type of ICT stimuli, are the results of

higher-level reflections, and are normally stored in memory for future use. There are two types:

Learned Affective Evaluations toward a Type of Objects (Category 7), and Learned Affective

Evaluations toward Behaviors on a Type of Objects (Category 8). It is worth noting that the

notion of learned affective evaluations is broader than just being evaluative. The essence of this

super-category is disposition, tendency, being conditioned, or “learned.” There can be three

facets of the learnedness: learned thinking, learned being, and learned action. Learned Thinking

focuses on affective appraisal and can be illustrated by the example of attitude toward general

stimuli, which influences future formation of attitude toward a new but similar stimulus. Learned

Being focuses on affective states and indicates that if the same or similar condition that caused

certain emotion is given again, the same or similar emotion may occur. This can be through auto-

association without cognitive appraisal or evaluation, or through repeated experiences, or

through other knowledge. For example, while “CMC anxiety” (Brown et al. 2004) is an emotion

(Category 4) induced by using a CMC technology, “computer anxiety” is the tendency of

individuals to be uneasy, apprehensive, or fearful about current or future use of computers

(Brown et al. 2004), thus it is a Learned Being toward a behavior (Category 8). Learned Action

focuses on emotion-driven behaviors and functions in a similar way as learned being: the person

can be action ready if the same condition that caused certain emotion-driven action in the past is

present again. For the purposes of parsimony, we put these three types of learnedness into one

super category and only differentiate them by object and behavior, to be consistent with the


29

Particular Affective Evaluations. Thus to reflect the true nature of the learnedness, Categories 7

and 8 should be named as Learned Affective Evaluations/Dispositions. It is worth noting that for

generic affectivity or tendencies that have little to do with ICTs, they belong to Category 2. For

ICT related tendencies, dispositions, or predispositions, they belong to Categories 7 and 8 as

being learned. For example, playfulness as a generic, non-ICT related human trait (Venkatesh

1999) is Category 2, while computer playfulness (Agarwal and Karahanna 2000; Venkatesh

2000; Webster and Martocchio 1992) is a learned disposition related to ICT, thus Category 8.

Table 5 recaptures the names, definitions and characteristics of various super categories and

categories of affective concepts newly introduced in ARM.

**** Insert Tables 5 about here ****

To illustrate the ARM taxonomy, the following is a complete analysis of the affective

concepts in the scenario, with the ARM taxonomy categories denoted. All ARM categories

appear in the scenario.

Imagine a person named Alex. Alex usually does not get easily over excited about novel

things in his surroundings (Category 2: Affectivity - Temperament). He does not like

playing computer games in general (8: Learned Affective Evaluation/Disposition toward

Behaviors on a Type of Objects – Attitude toward Behavior), yet tends to like colorful

things (7: Learned Affective Evaluation/Disposition toward a Type of Objects – Attitude

toward Object). One day, while passing by an electronics store in a calm mood (1: Free-

floating State - Mood), Alex was attracted to a set of colorful and dynamic screen

displays of a game (3: Affective Characteristics - Affective Quality and Affective Cues).

He said to himself, “Wow, that is cool!” (5.1: Process-based Affective Evaluation toward

a Particular Object) He stepped in and started exploring the game. Soon, he felt engaged,

stimulated, playful, and overall was having a lot of fun (4: Induced Affective States -

Emotions). Alex were really enjoying himself (4: Emotions) without realizing the passing

of time. Once he finished exploration, he was thinking: “Playing this game was really

engaging and enjoyable.” (6.1: Process-based Affective Evaluation toward Behaviors on


30

a Particular Object) As a result of this experience, Alex concluded that “This is a really

cool game that is well designed (5.2: Outcome-based Affective Evaluation toward a

Particular Object), and I liked playing it (6.2: Outcome-based Affective Evaluation

toward Behaviors on a Particular Object).” Then, he wondered that maybe “playing

computer games is not such a bad idea (8: Learned Affective Evaluation/Disposition

toward Behaviors on a Type of Objects).”

Appendix A lists the ICT-related affective concepts/constructs in their original terms/labels,

their formal definitions or measurements if definitions are unclear or missing, and their

classifications with ARM taxonomy. Within the same category, concepts are listed by the

chronological order of the publications. The appendix shows that all ARM categories are studied

to some extent in the ICT literature, although they are not equally attended to. Appendix A also

illustrates the gaps in the literature as mentioned earlier: identical terms or labels are

conceptualized or operationalized differently, and identical concepts are labeled with different

names.

It is worth noting that the characteristics of a stimulus can be applicable to induced states

just as they are to affective evaluations. For example, one’s outcome-based emotions can occur

after careful reflections and deeper processing; emotions can be caused by objects or behaviors,

and objects can be general or particular. Few studies in the ICT literature cover more than

affective feelings, which is just one of the four facets of emotions. Regardless what may cause

emotions (an object, an event, a person, a behavior, etc.), the concept of emotion is still the same.

It emphasizes the person’s feelings (along with biological reactions, etc.) induced by the

stimulus. For this reason, we do not plan to examine emotions further.


31

A Nomological Network and Relationship Propositions Besides synthesizing various affective concepts in the ICT context, we are also interested in

the relationships among them. As mentioned earlier and demonstrated in Appendix B, there is

only a very small number of studies that provided very limited examinations of the relationships

among the affective concepts in the ICT context. Such limited coverage does not provide us with

an understanding of the nature or the underlying processes of the relationships among affective

concepts. In theorizing the possible relationships with ARM, we depict the psychological

processes that underline the formation and influence of various affective concepts during an ICT

interaction episode. Such processes are both event-driven and appraisal-driven, as indicated by

the scenario. Consistent with the scope of this paper, we focus only on affective concepts,

although we acknowledge the involvement other factors in affective reaction formations and

changes.

Our analysis of the relationships among various affective concepts in the ICT context is

influenced by two perspectives in psychology and the social sciences on affect, emotion, and

attitude: the evolutionary (e.g. the notion of hard-wired set-up for human survival) and the

cognitive (e.g. affect appraisal theories, affect infusion theory, dual-process theories on attitude

formation and change). It is also heavily influenced by several specific models of emotional

episodes. It is worth noting that these perspectives and theories are not considered to be in

conflict but more complementary with each other. They all have supporting empirical evidence

and are various ways of understanding the complex affect phenomenon. Since a unified theory of

affect does not exist, it is worth trying to integrate various theories to understand various facets

of the affect phenomenon in the ICT context. Next, we overview emotional episode models that

provide the basis for the ARM nomological net.


32

Emotional Episode and an Overview of the ARM Nomological Net

According to the Component Process Model (CPM) (Scherer 2005, p700-701), emotion as

an episode has several characteristics: (1) it is event driven in that something happens to the

person that stimulates or triggers a response after having been evaluated for its significance; (2)

it is appraisal driven in that the eliciting event and its consequences must be relevant to major

concerns of the person because we do not generally get emotional about things or people we do

not care about; (3) the relevance of an event is determined by a rather complex yet very rapidly

occurring evaluation process that can occur on several levels of processing ranging from

automatic to implicit to conscious conceptual or propositional evaluations; and (4) different

emotions are produced by a sequence of cumulative stimulus evaluation or appraisal checks with

emotion-specific outcome profiles. Scherer also distinguishes intrinsic and extrinsic appraisals:

intrinsic appraisal evaluates the feature of a stimulus independently of the current needs and

goals of the person based on generic (e.g. sweet taste) or learned (e.g. bittersweet food)

preferences. Extrinsic or transactional appraisal evaluates events and their consequences with

respect to their conduciveness for salient needs, desires, or goals of the person.

Russell (2003) depicts a prototypical emotional episode model (PEEM) that consists the

following elements that are ongoing and often temporally overlap: (1) an obvious external

antecedent event (2) is perceived in terms of its affective quality, (3) and dramatically alters core

affect which continues to change as the episode unfolds; (4) the current core affect is attributed

to the antecedent, which becomes the Object thus the person has this salient experience: the

Object is making me feel the way I feel now; (5) the perceptual-cognitive processing of the

Object continues, assessing such qualities as its future prospects, its relevance to one’s goals, its

causal antecedents, and so on (appraisal); (6) (instrumental) action is directed at the Object; (7)


33

facial, vocal, and autonomic changes (physiological and expressive changes) occur and are

accounted for (a) by core affect and (b) as part of, preparation for, or recovery from instrumental

action; (8) in addition, there is a flood of metacognitive judgments being accompanied by core

affect (subjective conscious experiences); (9) there is an additional and separate subjective

conscious experience (emotional meta-experience): the person experiences a specific emotion;

(10) finally, one helps place one’s current state and situation within a broader body of

knowledge, including social norms and roles (emotion regulation).

Addressing affective experiences at work place, the Affect Event Theory (AET) (Weiss and

Cropanzano 1996) considers work environment features, work events, dispositions, affective

responses, work attitudes, judgment driven behaviors and affect driven behaviors. Event driven

and appraisal driven are key ideas of AET, along with the roles of dispositions that can (1)

influence affective reactions directly and (2) moderate the effects of the event on affective

reactions (Weiss and Cropanzano 1996).

The ARM nomological net is a direct application of the emotional episode models that

focuses primarily on the affective aspect, omitting the cognitive and behavioral aspects.

Specifically, an ICT stimulus is encountered by a person (an event) who appraises the ICT for its

relevance and responds affectively during the episode. In Figure 2, we depict the main

relationships among the categories of affective concepts that come into play when one is in an

episode of interacting with a particular ICT. Affective antecedents that trigger and influence the

episode are a person’s free-floating affective state such as mood, affectivity such as

temperament, and the ICT stimulus’ affective characteristics such as affective cues and quality.

In the episode, there are three types of affective responses: induced affective states, particular

affective evaluations, and learned affective evaluations/dispositions. These can influence each


34

other and be influenced by the antecedents. Figure 3 provides a more detailed view of the model

to indicate how affect is manifested and eventually turned into learned affective

evaluations/dispositions. Directional lines indicate causal relationships; double arrowed lines

indicate correlations or mutual influence. Particular affective evaluations are positioned along the

stages of process and outcome. Induced states can happen during the process. Induced states may

influence affective evaluations, both learned and particular. Learned affective

evaluations/dispositions have an impact on induced states and contribute to the formation of

particular affective evaluations. Upon higher level reflections, learned affective

evaluations/dispositions might be updated by particular affective evaluations to reflect new

information gained during the episode.

**** Insert Figures 2 and 3 about here ****

To make the relationships parsimonious and less graphically overwhelming, we focus on

super categories as dashed boxes in Figure 3, and at times may provide discussions at the super

category level. In other words, some propositions (such as P1-P7) reflect such groupings and can

be detailed into sub-propositions. For example, induced states can influence all four categories of

particular affective evaluations, thus P3 can have four sub-propositions.

There are other factors that can influence affective responses in an ICT interaction episode.

These can include particular goals or needs of ICT interaction (Briggs et al. 2008), and social,

situational and cognitive factors that influence the formation of the affective reactions, according

to well-established theories and empirical evidence (see Sun and Zhang 2006b for a meta-

analysis of moderating factors). To be parsimonious, we acknowledge the effects these factors

have but omit discussing them in this paper. Thus, ARM is not intended to depict the full scope

of person-ICT interaction but rather to emphasize only the affective aspect.


35

It is worth noting that some induced states and immediate affective evaluations may not be

influenced by learned affective evaluations, but rather are solely caused by stimuli. This is

known as the affective primacy hypothesis (Zajonc 1980; Zajonc 1984) that is favored by the

evolutionary perspective of affect. There is plenty of empirical evidence, including some from

recent neurophysicological studies, to show that affective responses can occur without any

cognitive processing or deliberation. Emotions can be triggered far more quickly than rational

responses (Ekman 1992), and some believe that such affective responses are “hard-wired”

(Barnard and Teasdale 1991), requiring no learning on the part of the individual as they are

purely human survival instincts. On the other hand, the affect appraisal theories posit that

cognitive processes should be involved when emotions or particular affective evaluations are

influenced by learned affective evaluations/dispositions.

Next in this section, we develop propositions in ARM based on emotional episode models

and other related theoretical work. Along the way, we highlight the ICT literature on

relationships among affective concepts. Appendix B provides a detailed summary of the

empirical evidence of the relationships among affective concepts in the ICT literature, their

theoretical justifications or implications, and the corresponding ARM propositions. A

relationship is considered in Appendix B if the involved affective concepts are about the same

ICT related stimulus. For example, McCoy et al. (McCoy et al. 2008) find that irritation by

advertisement (on a website) leads to negative attitude toward the website. The two concepts

have different stimuli thus such relationship is outside our scope for discussion.

ARM Proposition Development

Propositions are grouped by the categories of concepts they connect.


36

Between Affective Antecedents and Affective Reactions (P0)

Moods are transient states that wax and wane, fluctuating and lasting longer than emotions,

not as intensive as emotions, yet often providing a background to influence consciousness,

including a threshold-like influence on emotion elicitation (Rosenberg 1998). For example, the

affect infusing model (AIM) suggests that being in a good mood (regardless of its sources or

causes) should lead to a host of processing on the stimulus in terms of attending to its

information, selectively retrieving information from the memory, selectively coding its

significance, and making associations and interpretations (Forgas 1995). This means that to some

extent, the particular mood a person has at the time of an ICT interaction episode should

influence other affective components and processes.

P0a. The person’s mood influences his/her affective reactions during an interaction

episode with a particular ICT.

By definition, temperaments and affective traits influence affective reactions in the ICT

context, just as in any other contexts being studied in psychology and the social sciences. This is

not to dismiss or underplay the event or contextual influences, nor the influences from some

more stimulus specific dispositions (such as learned affective evaluations/dispositions related to

the ICT stimulus). Nevertheless, scholars have noticed the dispositional influences on affect

across a diverse contexts and disciplines (Rosenberg 1998). For example, in AET, dispositions

have a direct impact on affective responses (Weiss and Cropanzano 1996).

P0b. The person’s temperament influences his/her affective reactions during an

interaction episode with a particular ICT.

The stimulus-organism-response (S-O-R) paradigm posits that environmental cues act as

stimuli that influence an individual’s cognitive and affective reactions, which in turn influence


37

behavior (Mehrabian and Russell 1974). Affect appraisal theories directly posit that people

appraise a stimulus during an emotional episode where the affective cues trigger people to react

affectively in the form of induced states and affective evaluations. It has been well established

that affect (attitude) may be activated automatically from memory on the mere exposure of an

affect-loaded stimulus (Fazio et al. 1986) and such automatic activation effect is a pervasive and

relatively unconditional phenomenon (Bargh et al. 1992; Hermans et al. 1994). All these

theoretical bases point out that in an interaction episode with an ICT, the ICT’s affective cues

and quality would trigger the corresponding affective states and affective evaluations.

P0c. The ICT’s affective cues and quality influence the person’s affective reactions

during an interaction episode with a particular ICT.

As indicated in Appendix B, the ICT literature supports both P0b and P0c. For P0b,

Negative Affectivity and Trait Anxiety (both Category 2) are theorized to influence Computer

Anxiety (8), although only Trait Anxiety’s effect is found in the empirical data (Thatcher and

Perrewe 2002). The latter relationship is also found by Igbaria and Parasuraman (1989). The

theoretical justification is that dynamic, IT specific individual differences (i.e., computer

anxiety) are a function of stable situation-specific (i.e., personal innovativeness in IT) and broad

(i.e., negative affectivity and trait anxiety) traits. Studies are also found to support P0c. Visual

characteristics of web pages (3) have been found to be highly correlated with immediate

impressions of the web pages (5.1) (Lindgaard et al. 2006). The authors justify the findings

according to the mere exposure effect (Zajonc 1980), in that one can quickly form immediate

visual appeal impressions even given an extremely short period of exposure time that does not

permit cognitive processing. They conclude that feelings happen to us whether we like it or not,

and they can happen in a matter of a few milliseconds. Using the stimulus-organism-response (S-


38

O-R) paradigm (Mehrabian and Russell 1974), Mood Relevant Cues (3) are found to influence

Perceived Enjoyment (6.1) (Parboteeah et al. 2009). Although there is no empirical evidence

found to support P0a (mood influences affective reactions), the scenario can provide some

examples: while passing by an electronics store in a calm mood, Alex was attracted by the

displays and eventually had fun exploring and concluded the experience as positive. A different

mood at the time may yield different affective reactions.

To avoid repeating information, from now on for the rest of this section, we will only briefly

summarize the findings on relationships in the ICT context, and leave the specific theoretical

justifications and implications in Appendix B.

Between Induced States and Learned Affective Evaluations/Dispositions (P1 and P2)

Stimulus based affective tendencies or dispositions (i.e., learned affective evaluations/

dispositions) are more enduring than states (i.e., emotions), but may remain latent and

unexpressed and can be activated by an attitude-relevant stimulus (Clore et al. 2001), which then

influences congruently the induced states during the episode. Thus learned evaluations/

dispositions influence induced states.

P1. Learned affective evaluations influence induced affective states during a person’s

interaction with a particular ICT.

The affect-as-information theory posits a direct link between an affective state and

evaluative judgments in that a person may ask oneself: “How do I feel about this?” and in doing

so the person considers the feeling as an evaluation or judgment of the target (Schwarz 2001;

Schwarz and Clore 1983). This means that the feelings one has toward a stimulus can carry over

to the evaluation of the stimulus. Such evaluations can be both particular affective evaluations

(thus supporting P3) and learned affective evaluations/dispositions, thus supporting P2.


39

P2. Induced affective states influence learned affective evaluations/dispositions.

There is empirical evidence in the ICT literature to support P1. Flow as a state (4) is an

outcome of the individual characteristics of cognitive playfulness of microcomputers (8)

(Webster and Martocchio 1995). Individual dispositions such as computer playfulness (8) are

likely to have an effect on experiential states such as cognitive absorption (4) (Agarwal and

Karahanna 2000). More general anxieties such as computer anxiety (8) are found to influence

more specific ones such as CMC anxiety (4) (Brown et al. 2004). No studies are found to focus

on P2. Using the scenario as an example, Alex being engaged, stimulated, playful, and overall

having a lot of fun (induced affective state) may directly enforce his liking colorful things (7:

learned evaluation/disposition toward things), and directly influence or challenge his not liking

to play computer games (8: learned evaluations/dispositions toward behaviors on games). It is

worth noting that such influences may also be indirect through particular affective evaluations.

Between Induced States and Particular Affective Evaluations (P3 and P4)

When affective evaluations are formed, emotions as induced states may or may not co-occur

(Russell 2003). When emotions do occur, they should be congruent with the corresponding

affective evaluations.

The flow theory (Csikszentmihalyi 1975; Csikszentmihalyi 1990) depicts a direct

relationship between an affective state and affective evaluations of the activity. Flow represents a

state of consciousness where one is so absorbed in an activity that s/he excels in performance

without consciously being aware of his or her every movement or time spent on it. A strong

indication of flow is that one experiences heightened enjoyment (a positive state). Flow

represents an optimal experience during interaction with an ICT (Finneran and Zhang 2005). Due

to the desirability of reaching flow again, one forms process-based affective evaluations toward


40

the behavior that causes flow. The impact of such evaluations, along with the state felt during the

action, should be significant for outcome-based affective evaluations when one concludes the

interaction, leading to future decisions and behaviors in respect to the action. This is to say that

the affective states felt during the interaction can influence particular affective evaluations, both

process-based and outcome-based. Therefore, we have P3.

P3. Induced states influence particular affective evaluations during a person’s


Russell’s Prototypical Emotional Episode Model (PEEM) (Russell 2003) depicts a directed

relationship between immediate affective evaluation and a specific emotion/state. PEEM

illustrates the causal connection and temporal process of a stimulus first being received by an

individual from an immediate affective evaluation, to cognitive deliberation, to specific feelings,

to final behavior response and emotion regulation. In other words, the immediate affective

evaluation (one type of particular affective evaluations) leads to certain feelings (affective states)

that are congruent with the affective evaluations.

Similarly, the component process model of emotional episodes states that different emotions

are produced by a sequence of cumulative stimulus evaluations or appraisal checks with

emotion-specific outcome profiles (Scherer 2005). Therefore both episode models lead to P4.

P4. Particular affective evaluations influence induced states during a person’s


The ICT literature supports P3. Flow as an induced state (4) is found to influence attitudes

toward CMC technologies (5.2) (Trevino and Webster 1992). Mood as an induced state (4) is

found to influence intrinsic motivation (or perceived enjoyment) (6.1) over both the short and

long term (Venkatesh 1999). Individuals experiencing high CMC anxiety (4) are found to have


41

less favorable attitudes toward using the CMC (6.2) (Brown et al. 2004). Perceived playfulness

that is treated as an induced state (4) is found to influence satisfaction with a web portal (6.2)

(Lin et al. 2005). Feelings (4), including both pleasure and arousal, are found to influence

attitude toward mobile Internet services (6.2) (Kim et al. 2003). No studies are found to focus on

P4.

Between Learned and Particular Affective Evaluations (P5 and P6)

The affect priming principle posits that affective states can indirectly inform judgments by

facilitating access to the memory and associated cognitive processes (Bower 1981). This means

that when constructing particular affective evaluations (either as process-based or outcome-

based), one is primed by the currently experienced affective state to access memory on

previously established situations when such a state is experienced (thus the learned affective

evaluations/dispositions). This supports P5.

Attitude theories posit that one may have a particular attitude toward a certain type of object

but a different attitude toward a particular object (Ajzen and Fishbein 2005). This occurs when

other factors may be involved, such as more information being available regarding the particular

individual object, or when situational factors come into play. Due to their nature, general

attitudes have the function of “guiding” the formation of a new attitude toward a particular

stimulus. That is, when all other things being equal, attitude toward a particular stimulus is about

the same as the attitude toward a class of similar stimuli. This further supports P5.

P5. Learned affective evaluations/dispositions influence particular affective

evaluations during a person’s interaction with a particular ICT.

Attitude change theories such as cognitive dissonance theory (Festinger 1957) assert that

existing attitudes have to be changed if a newly formed attitude differs so that the person reduces


42

dissonance. Applying this position to affective evaluations, we anticipate that learned affective

evaluations/dispositions will change if particular affective evaluations differ. This means the two

types should influence each other, although at different stages of human-ICT interaction.

Learned affective evaluations/dispositions can influence particular affective evaluations during

the interaction. On the other hand, learned affective evaluations/dispositions can be influenced

by particular affective evaluations at the conclusion of the interaction.

P6. Particular affective evaluations influence learned affective evaluations/dispositions

after a person’s interaction with a particular ICT.

In the ICT literature, no studies are found to focus on P5, and one is on P6. Satisfaction with

a website (6.2) is found to influence attitude toward commercial websites (7) (Teo et al. 2003).

Among Particular Affective Evaluations (P7, P8 and P9)

It has been established that most stimuli, after being automatically appraised for being

positive or negative (that is, the formation of process-based affective evaluations), are further

appraised (Reeve 2005, p338). Russell’s PEEM suggests in this further processing that early

immediate evaluations have an influence on the later more reflective evaluations. This means

that process-based affective evaluations influence outcome-based affective evaluations.

According to dual-process theories of attitudes, via the central route or deliberative fashion,

one can carefully consider available information in forming evaluations. Such information can be

the emotions the person feels at the time, the cognitive reasoning on the importance related to an

ICT or ICT use, and/or other affective evaluations that have occurred so far. Effortful evaluations

should occur during the process and during the conclusion stages of the interaction when such

types of information are available. Thus, dual-process theories provide additional support to the

following: the formation of some process-based affective evaluations is based on information


43

from other process-based affective evaluations, and the formation of outcome-based affective

evaluations is based on information from process-based affective evaluations. Positive emotions

and evaluations in early stages induce more positive evaluations in later stages than neutral

emotions and neutral evaluations (Cacioppo et al. 1999; Wegener 2001).

According to action identification theory (Vallacher and Webner 1987) and its application in

the ICT context (such as TAM studies), process-based affective evaluations should have a

positive effect on outcome-based affective evaluations.

P7. Process-based affective evaluations influence outcome-based affective evaluations.

Research in attitude theories makes a distinction between attitudes toward an object and

attitudes toward a behavior (Ajzen and Fishbein 1980; Ajzen and Fishbein 2005; Eagly and

Chaiken 1998; Forgas 2000; Wixom and Todd 2005; Zhang et al. 2008; Zhang and Sun 2009),

and theoretically justifies and empirically validates that object-based attitudes have an impact on

behavioral-based attitudes regarding a particular object (Ajzen and Fishbein 1980; Ajzen and

Fishbein 2005). We extend this relationship to particular affective evaluations toward objects and

toward behaviors to yield the following propositions.

P8. Process-based affective evaluations toward a particular ICT influence process-

based affective evaluations toward behaviors on the ICT.

P9. Outcome-based affective evaluations toward a particular ICT influence outcome-

based affective evaluations toward behaviors on the ICT.

P7 is supported by a good number of studies in the ICT literature. First impressions of a set

of web pages (measured by beauty, illustration/text, overview) (5.1) relate with webpage

preferences (5.2) (Schenkman and Jonsson 2000) while hedonic attributes (5.1) relate to the

beauty (5.2) of a MP-3 player with various skins (Hassenzahl 2004). Both perceived


44

entertainment and perceived irritation are Category 5.1 and are found to influence attitudes

toward a website (5.2) (Gao and Koufaris 2006). Perceived playfulness as a playful experience

(6.1) influences attitudinal outcomes such as attitude toward use (6.2) (Moon and Kim 2001).

Similarly, shopping enjoyment (6.1) is found to influence attitudes toward shopping at the

website (6.2) (Jiang and Benbasat 2007).

No study is found to focus on P8. One study supports P9 in that satisfaction as an object-

based attitude (5.2) influences behavior-based attitude such as attitude toward behavior (6.2)

(Wixom and Todd 2005).

Among Learned Evaluations/Dispositions toward Objects and Behaviors (P10)

Although learned affective evaluations can also be about objects and behaviors, we posit

that they have a slightly different relationship with each other than with, for example, 5.1 and

6.1, and 5.2 and 6.2. Since learned affective evaluations are generalized and stored in memory,

they do not have causal relationships but should be congruent with each other.

P10. Outcome-based affective evaluations/dispositions toward a type of ICTs correlate

with outcome-based affective evaluations/dispositions toward behaviors on this

type of ICTs.

In the ICT literature, computer anxiety (8) is found to influence attitude toward computers

(7) (Igbaria and Parasuraman 1989).

Among Affective Responses of the Same Category (P11)

One proposition that is not shown graphically in Figures 2 and 3 concerns the relationships

among affective responses that belong to the same category. We posit that affective responses of

the same category should correlate with each other if these responses are about the same

stimulus. This is because these responses have the same specificity by sharing the same stimulus,


45

the same information process level (and thus the similar amount and intensity), and the same

person/evaluator.

P11. Affective responses toward the same stimulus correlate with each other if these

affective responses belong to the same category.

In the ICT literature, flow as a state (4) with two dimensions (concentration and enjoyment)

is found to influence positive affect, another state variable (Zaman et al. 2010).

Summary of the Relationships in ARM

It has been realized that an emotional episode can be very complex with many processes

occurring and overlapping, leading to constantly changing/evolving feelings and evaluations

(Russell 2009; Scherer 2005). Thus it should be noted that the relationships in Figures 2 and 3

should be true in general, yet any particular relationship may not hold true at any given moment

in an episode. In addition, it might be easier to focus on an association between two affective

concepts rather than a causal relationship, which is what some of the empirical studies did.

Nevertheless, we attempt to crystallize the psychological underpinning that depicts which

specific types of affective concepts are influenced by other affective concepts. Such

underpinning further illustrates the connections and differences among the various types of

affective concepts.

In the ICT literature, the coverage on relationships is spotty, although the findings are

largely consistent with the ARM propositions. Some relationships are relatively heavily attended

to, such as five times on P3 (induced affective states influence particular affective evaluations)

and P7 (process-based affective evaluations influence outcome-based affective evaluations)

respectively, four times on P0 (affective cues/qualities or moods/temperament influence induced

states and evaluations), and three times on P1 (induced states influence learned


46

evaluations/dispositions). Some are barely addressed: once for P6, P9, and P10 respectively, and

some are never attended (P2, 4, 5, 8). The lack of empirical studies on the propositions indicates

the gap in the literature, which can be a natural result of a lack of comprehensive and systematic

examination of the relationships. This is where ARM can contribute, and lead to future research

efforts on empirical studies.

Discussion Affect has become an increasingly important research area in several social sciences

disciplines, including ICT related disciplines. Affect represents a complex set of affective

concepts, which are not all the same, nor all unrelated. In this paper, we proposed the Affective

Response Model (ARM) as a means to address the questions of “What are pertinent affective

concepts in the ICT context?” “In what ways are these affective concepts similar to or different

from each other?” And “how do these affective concepts related to each other?”

ARM considers several dimensions that are theoretically validated to provide conceptual

clarity. Therefore, ARM is a theoretically-bound framework that can provide a systematic and

holistic reference map for any ICT study that considers affect. The proposed taxonomy and the

resulting nomological network offer a detailed and coherent understanding of the complex

phenomenon related to affect in the ICT context. Using ARM, the relatively discrete findings

from the ICT literature can be better connected, compared, analyzed, and synthesized, as we

have demonstrated in Appendices A and B. As a result, research gaps, opportunities, and

directions can be identified and pursued.

Boundaries and Limitations

Although investigating the causes of affective responses that lead to onset, magnitude, and


47

direction can enhance the understanding of affective concepts themselves, we decided to be more

focused and exclude some salient factors, especially non-affective factors, as causes or

moderators. For example, we did not include goals and needs, although it is quite likely that they

are causal factors for affective responses (Briggs et al. 2008). We excluded cognitive

deliberations, which can be important in reaching affective responses. In addition, the context of

interaction is likely to play an important role in affective responses (van Schaik and Ling 2009)

and their relationships with each other. ARM does not prescribe the consequences of the

affective constructs on other factors either. For example, affect has been found to influence

cognitions, intentions, and behaviors in the ICT context, which are excluded from ARM.

Understanding the causes and consequences of affective responses, as well as the interplay

between affect and cognition, is clearly important, and hence deserves scholarly attention. While

some early efforts have started to show promise (see Sun and Zhang 2006a), much more

attention is needed in this area for affective concepts to be better understood.

Explanations of Inconsistencies

One use of ARM is to understand the relatively discrete ICT literature on affect. Here we

demonstrate ARM’s explanatory power with one example. Attitude is studied extensively in the

ICT context, especially in user technology acceptance, adoption and use, and IS success research

(Davis et al. 1989; Goodhue 1988; Zhang et al. 2008; Zhang and Sun 2009). Yet, attitude has

been defined in multiple ways, such as an individual’s positive or negative feelings (evaluative

affect) about performing a target behavior (Davis et al. 1989), a person’s affective evaluation of

a specific object (Brown et al. 2004), an overall evaluation of a shopping experience at a

particular website (Jiang and Benbasat 2007), a positive affective variable (Gao and Koufaris

2006), a learned implicit response that refers to an individual’s evaluation of a concept (Agarwal


48

and Prasad 1999), personal affect toward IT usage (Bhattacherjee and Premkumar 2004),

predispositions to respond in a particular way towards a specified class of objects (Teo 2003),

and satisfaction with process and outcomes (Taylor and Todd 1995). Based on a survey of the

literature showing its inconclusive roles, attitude toward using technology is claimed not to be a

direct determinant of intention, and thus is excluded from the Unified Theory of Acceptance and

Use of Technology (Venkatesh et al. 2003). There are four specific treatments of attitude in the

ICT literature (summarized in Appendix A): a learned affective evaluation/disposition toward (i)

a type of ICTs (thus Category 7), or (ii) behaviors on a type of ICTs (8), or an outcome-based

affective evaluation toward (iii) a particular ICT (5.2) or (vi) behaviors on the ICT (6.2). Case

(ii) can be demonstrated by “affect” (Compeau and Higgins 1995; Compeau et al. 1999), which

is often considered as attitude as well). ARM is able to unearth the sources of inconsistencies in

attitude studies, thus providing directions to correct them in future research efforts.

Theoretical Implications

ARM is a theoretical framework to conceptualize and abstract various affective concepts

along a set of dimensions that specify the target stimulus a person reacts to in the human-ICT

interaction context. ARM has the power for explaining and predicting (Gregor 2006). ARM

describes the affective phenomenon in the ICT interaction context. It analyzes what types of

affective concepts exist and what kinds of relationships these concepts have. Its power is

demonstrated by its ability to classify all the affective constructs and relationships reported in the

ICT literature (as shown in Appendices A & B), and its ability to identify and explain the

discrepancies in the literature, and synthesize consistent findings even if different names are used

in different studies. With the ability to explain and predict, ARM can identify gaps and

opportunities, and new affective concepts or relationships to inspire future research investigation.


49

For example, there might be more Category 2 concepts that have not been studied in the ICT

context. There should be many more affective cues to be studied, especially from guiding ICT

design perspective. And there are several propositions that are never covered in the ICT literature

and yet they can be tested and validated.

ARM goes beyond being just affective. There is abundant empirical evidence, in IS and

other disciplines, to show that affective concepts can have significant interplay with other

fundamental aspects of human beings, such as cognition, motivation, and behavior (for a review,

see Sun and Zhang 2006a). In fact, as we developed ARM in this paper, we pointed out the

interplay between affect, cognition and behavior when necessary. Some affective concepts (such

as affective evaluations) can be cognitively latent, meaning that they are the result of cognitive

processing (but the content being processed is affective). This is to say that one should not over-

simplify the relationships that affect may have with other aspects. As a first step in better

understanding various affective concepts, and the extent to which they are cognitively latent,

ARM provides insight that helps one to make sense of empirical findings about the interplay

between affect, cognition, and potentially other factors.

ARM can be used to study in depth a specific affective concept, emotion, in the ICT context,

which is timely due to the heightened interests in studying emotions in the ICT context. One way

of studying emotions is to examine the characteristics of the target stimulus. The multi-

dimensional structure of stimuli can be a great starting point for such an investigation.

ARM (and logic behind it) may be used to study affect related issues in other aspects of ICT.

For example, research on affective responses to ICT services can be guided by ARM in at least

the following ways: whether the involved affective concepts should be moods, emotions, or

affective evaluations; what/who would be the stimuli (the service websites, the people


50

responsible for the websites, or the customers who deal with either the websites or the

personnel); and which stages of interaction the researchers should focus on.

Finally, ARM may be extended to non-ICT contexts and disciplines. The key is to identify

the stimuli of interest.

Practical Implications

This paper has strong practical implications for ICT design, evaluation, use, training,

management, and improvement in a variety of settings. ARM distinguishes affective concepts

whose meanings reside in an ICT (affective cues and affective quality) or between a person and

an ICT (emotions and affective evaluations). From the design and improvement perspective,

distinguishing and understanding the roles of affective concepts allows designers to focus on

areas that can be most effective in receiving desired user affective reactions. For example, one

challenge that designers face is to identify and construct effective affective cues that can induce

strong desired affective responses. Understanding the importance of process-based affective

evaluations, especially those based on mere exposure, is helpful as it can guide designers toward

interfaces that draw users into the interaction, rather than turning them away to competitors.

Trainers, managers, and evaluators of ICTs can use ARM to better understand the reasons

for, and sources of certain affective responses. As such, they can apply corresponding strategies

and tactics to reach their desired goals. For companies that serve customers with ICTs, there are

many types of affective responses worth paying attention to. The stimuli that may cause various

affective reactions can also be varied and represent different things. For instance, a customer

may have strong affective evaluations or emotions toward the sold products, the provided

service, the staff who handle the service or transactions, the communication channel, the website

of the company, or the company itself. A consumer’s attitude toward the company may be a


51

summary of all affective responses toward these different stimuli, and that attitude can become a

key factor to build customer loyalty. How could a company build positive customer attitude?

ARM points out the potential affective contributors (such as affective antecedents, particular

affective evaluations, induced states, and learned affective evaluations/dispositions) that may

influence the attitudes.

Future Research Directions

There are a number of future directions that we wish to prescribe. The first is toward

development of validated instruments for various affective concepts. This can be both interesting

and challenging in light of the many different types of affective concepts.

The second is about empirically validating the propositions in ARM. The current literature

shows a scattered coverage of the propositions, demonstrating a lack of systematic effort to

investigate the relationships, and leaving an open landscape for future research. All propositions

are important in providing a holistic understanding of the affective concepts in the ICT context.

Yet, specific studies may focus on any subset of the entire net due to its complexity. Testing the

model can be conducted with a variety of ICT artifacts, at various stages of adoption/use, and

within various use contexts to reveal whether the relationships are supported in general, and

whether they are restricted to specific contextual factors.

Third, researchers should be able to reexamine empirical findings regarding the causes and

consequences of affect in the ICT context in order to have a clearer and more holistic

understanding of the various affective concepts as explained by ARM.

Fourth, for scholars interested in a systematic examination of emotions, it is worth

considering the nature of the stimuli that cause the emotions. Many of the dimensions in ARM

for affective evaluations may apply to studying emotions.


52

Fifth, along with efforts similar to ARM to better define affective concepts and clarify

inconsistencies of affect’s causes and effects, scholars can conduct more research to examine

both affective and cognitive factors, as well as other factors such as behavioral, motivational,

social, contextual, cultural, and economical, in human interaction with ICTs. Such investigations

should strive to provide insight and guidelines for designing new ICTs that are effective,

efficient, pleasant, encouraging, and interesting to use for various purposes.

Finally, continued ICT-use research is considered one of the most welcome developments in

recent IS scholarship (Ortiz de Guinea and Markus 2009). In particular, affective or emotional

responses are speculated to contribute to continued ICT-use intention, and may influence

continued ICT-use behaviors directly (Ortiz de Guinea and Markus 2009). This presents

intriguing and potentially ground-breaking opportunities for ICT scholars and practitioners. It

should be interesting to find out how various affective responses occur and interact in continued

ICT-use situations, and in what ways these affective responses can be managed and taken into

account when considering ICT management issues such as training and support.

Acknowledgments I thank the SE Lynne Markus for her encouragement and insightful suggestions. I appreciate

the constructive reviews by the AE and three anonymous reviewers. The early ideas were

presented at the 2006 JAIS theory development workshop and research seminars in City

University of Hong Kong, Renmin University, and Australia National University. I am grateful

for the following individuals who shared their insights during the development of the article:

Kevin Crowston, Robert Heckman, Dov Te’eni, Shirley Gregor, and my former and current

students Na Li, Heshan Sun, Nathan Prestopnik and Michael Scialdone.


53

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About the Author Ping Zhang is a professor in the School of Information Studies at Syracuse University, and

holds multi-year guest professor positions with the Inner Mongolia University, Renmin

University, and Xi’An Jiao Tong University in China. Her research interests include the

intellectual development of information related fields; human-centeredness in ICT development,

evaluation and use; affective, cognitive, motivational and behavioral aspects of individual

reactions towards ICT; and the impact of ICT design and use on individuals, organizations,

societies and cultures. She has published in information systems, human-computer interaction

and information science journals and conference proceedings. She is co-editor (with Dennis

Galletta) of two edited books on HCI and MIS of the Advances in MIS series (by M.E. Sharpe,

2006), and is co-author (with Dov Te’eni and Jane Carey) of the first HCI textbook for non-CS

students (by John Wiley, 2007). She and Dennis Galletta are founding Editors-in-Chief for AIS

Transactions on Human-Computer Interaction since 2008. In addition, she is a former Senior

Editor for the Journal of Associations for Information Systems, guest Senior Editor for MIS

Quarterly, former Associate Editor for the International Journal of Human-Computer Studies

and Communications of Association for Information Systems, on the editorial board of Journal of

Management Information Systems, and a guest Senior Editor of eight special issues.


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Table 1. Fundamental and Basic Concepts

Concept Definition and Characteristics

Core affect

An intrinsic aspect of consciousness (Barrett et al. 2007) that is mental but not cognitive or reflective (Zajonc 2000). A neurophysiologic state consciously accessible as a simple, non-reflective feeling inside oneself. The specific feeling itself may change from time to time, but a person will always have some feeling (core affect) at any moment. Core affect may have no known causes (mood) or be linked to stimuli (such as perceptions of affective quality and emotions). It is a primitive concept and fundamental for all affective events (Barrett and Russell 1999; Russell 1980; Russell 2003; Russell 2009).

Stimulus That which a person responds to. It is a psychological representation, thus can be real, imagined, fictions, remembered, anticipated, and in forms of virtual reality. Also called “the Object” (Russell 2003).

Perceived Affective Quality

One’s estimation of a stimulus’ ability to change his or her core affect. It begins with a specific stimulus and stays with the stimulus to emphasize on the stimulus’ affective properties rather than on a person’s feelings. Different people may perceive the same stimulus to have different affective qualities (Russell 2003).

Affective Quality A stimulus’ capacity to cause a change in a person’s core affect. It is independent of the perceivers because it is the stimulus’ attributes or properties (Mehrabian and Russell 1974; Russell 2003).

Affective Cue Specific features or characteristics of a stimulus that can manifest the affective quality of the stimulus. Also regarded as environmental cues or signals with affective information (Soldat et al. 1997).

Mood Prolonged core affect with no stimulus (simple mood) or with quasi-stimulus. It is often regarded as an affective state without a specific stimulus (Lazarus 1991; Moore and Isen 1990; Watson and Clark 1994).

Temperament A characteristic, habitual inclination, or mode of emotional response (Watson and Clark 1994).

Emotion

An affective state induced by or attributed to a specific stimulus. Emotions typically arise as reactions to situational events and objects in one’s environment that are relevant to the needs, goals, or concerns of an individual. Emotion emphasizes a person’s subjective feeling. The feeling is short-lived, existing only as long as the supporting cognitions, perceptions, or other elicitors are active, and vanishing as soon as one is no longer in that state. An emotional episode depicts the complex process of the emotion in responding to a stimulus (Russell 2003; Scherer 2005).

Attitude

A summary evaluation of a stimulus that may help guide behavior regarding that stimulus; can be considered as either a multidimensional construct comprised of cognitive, affective, and behavioral components, or a two dimensional construct with instrumental (mostly cognitive) and experiential aspects (mostly affective) (Ajzen and Fishbein 2005).

Table 2. Affective Concepts in Relation to the Person and/or Stimulus

Reside within a person Reside within a stimulus Reside between a person and a stimulus Mood Temperament

Affective Cue Affective Quality

Emotion Perceived Affective Quality Attitude Affective Evaluation Affective Reaction/Response

Note: Core affect is a fundamental concept that is the basis to all other affective concepts making them affective in nature. Therefore, core affect is not treated in parallel with other affective concepts, thus not listed here.


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Table 3. Affective Concepts by Temporal and Stimulus Conditions (Adapted from Clore and Schnall 2005; Clore et al. 2001)

Temporally Constrained (State)

Temporally Unconstrained (Disposition)

No Stimulus (Reside within a person)

Mood Temperament

Stimulus (reside between a person and a stimulus)

Emotion Perceived affective quality Attitude Affective evaluation

Affective Reaction/Response

Table 4. Taxonomy of Affective Concepts: Super Categories and Categories

Residing within a person Residing within a

stimulus

Residing between a person and a stimulus (Affective Responses)

Temporally Constrained

(State)

Temporally Unconstrained (Disposition)

Temporally Constrained

(State)

Temporally Unconstrained

(Evaluation/Disposition)

(1) Free-floating Affective State (e.g. Mood)

(2) Affectivity (e.g. Temperament)

(3) Affective Characteristics (e.g. Affective Quality, Affective Cue)

(4) Induced Affective State (e.g. Emotion)

Particular Stimulus

General Stimulus

Process-Based Outcome-Based O

bjec

t St

imul

us (5.1)

Process-based Affective Evaluation Toward a Particular Object

(5.2) Outcome-based Affective Evaluation Toward Behaviors on a Particular Object

(7) Learned Affective Evaluation/ Disposition Toward a Type of Objects

Beh

avio

r St

imul

us (6.1)

Process-based Affective Evaluation Toward Behaviors on a Particular Object

(6.2) Outcome-based Affective Evaluation Toward Behaviors on a Particular Object

(8) Learned Affective Evaluation/ Disposition Toward Behaviors on a Type of Objects


62

Table 5. Definitions and Characteristics of Super Categories and Categories in ARM

Super Category/Category Name ID Definitions and Characteristics

Free-floating Affective State 1 Affective state with unclear contributing stimulus. Affectivity 2 Habitual inclinations, dispositions, tendencies, personality traits.

Affective Characteristics 3 A stimulus’ features, properties, or natures that contain affective information independent of the perceivers.

Affective Response, Affective Reaction

4,5,6,7,8

A general term to represent affective concepts whose meanings reside between a person and a stimulus. Two broad types are induced affective states and affective evaluations.

Induced Affective State 4 Affective state with a clear contributing stimulus. Emphasize on the feelings the perceiver has, rather than the ability or affective characteristics of the stimulus.

Affective Evaluation 5,6,7,8

A general term to represent a set of affective concepts that represent the person’s appraisals of the stimulus’ affective quality. The meanings of affective evaluations are between a person and a stimulus, and an affective evaluation’ values are temporally unconstrained.

Particular Affective Evaluation 5,6 A general term for affective evaluations of a particular ICT object and

behaviors.

Process-based Affective Evaluation toward a particular object

5.1

Appraisals during an episode from exposure to (either immediate or long duration) in-depth interaction with a particular ICT. It is a particular ICT object. Can be automatic, spontaneous, quick, and immediate. Can be long-lasting or short-lived, and is easily modified.

Outcome-based Affective Evaluation toward a particular object

5.2 Summative, concluding the direct experience. Toward a particular object. A higher or global level evaluation beyond the interaction process.

Process-based Affective Evaluation toward behaviors on a particular object

6.1 Appraisals during direct experience/interaction with a particular ICT. Toward behaviors on the particular ICT. Experiential in nature. Focus on the process. Can be long lasting, or short lived, and is easily modified.

Outcome-based Affective Evaluation toward behaviors on a particular object

6.2 Summative, concluding the direct experience. Toward behaviors on the particular object. Focus on the outcome. A higher or global-level evaluation beyond the interaction process.

Learned Affective Evaluation/Disposition 7,8

A general term for affective evaluations of general types of ICT. Dispositions, inclinations, or predispositions toward stimuli. These can be results of higher-level reflections stored in memory. These can be toward future thinking, being, or action readiness.

Learned Affective Evaluation/Disposition toward a type of objects

7 A tendency to form certain affective evaluations based on prior experience or knowledge. Toward a general type of ICT objects. Long-lasting, learned over time, stored in memory, and not so easy to change.

Learned Affective Evaluation/Disposition toward behaviors with a type of objects

8

A tendency to form certain affective evaluations based on prior experience or knowledge. Toward behaviors with a general type of objects. Long-lasting, learned over time, stored in memory, and not so easy to change.


63

Figure 1. The Structure of Affect: the Circumplex Model (Russell 2003)

Figure 2. A Generic Nomological Net for Causal Relationships

P4 P6

4: Induced Affective States(e.g. Emotions)

5, 6: ParticularAffective Evaluations

Affective Responses in an ICT Interaction Episode

7, 8: Learned Affective Evaluations/Dispositions

P1

P0

P2

P3 P5ICT Stimulus

3: Affective Characteristics(Affective Cue

Affective Quality)

Human1: Free-floating State

(Mood)2: Affectivity

(Temperament)

AffectiveAntecedences


64

Figure 3. A Detailed Nomological Net for Causal Relationships

P4

P6

Affective Responses in an ICT Interaction Episode

P1

P0

P2

P3

P5

Outcome-basedAffective Evaluations

5.2: Toward Object

6.2: Toward Behavior

P9

Process-basedAffective Evaluations

5.1: Toward Object

6.1: Toward Behavior

P8

LearnedAffective Evaluations/Dispositions

7: Toward Object

8: Toward Behavior

P10

Particular Affective Evaluations

P7

4: Induced Affective States(e.g. Emotions)

ICT Stimulus3: Affective Characteristics

(Affective CueAffective Quality)

Human1: Free-floating State

(Mood)2: Affectivity

(Temperament)

AffectiveAntecedences


65

Appendix A. Summary of Affective Concepts/Constructs in the ICT Literature ARM ID Original Construct Article Operational Definition

1 Perceived mood (Ang et al. 1993) (no definition) Measured by: The feedback giver Looked as if he had had a bad day; Seemed to be in a good mood today; Looked as if he did not want to be disturbed

1 Mood (Loiacono and Djamasbi 2010)

An individual’s mild, enduring, and objectless affective state (Fredrickson, 2003; Isen et al., 2003; Lazarus, 1991). One’s global feeling state at a given time. Moods are not necessarily a product of reflection or cognitive analysis, but simply describe how people feel at a moment.

2 Trait anxiety (Igbaria and Parasuraman 1989)

Reflects a chronic and generalized predisposition to be anxious and nervous.

2 Playfulness as Trait (Venkatesh 1999) The pleasure and inherent satisfaction derived from a specific activity. 2 Negative Affectivity (Thatcher and Perrewe 2002) The general experience of negative emotions such as guilt or shame regardless of the situation 2 Trait anxiety (Thatcher and Perrewe 2002) The general feeling of anxiety when confronted with problems or challenges. 3 Design factors (Kim et al. 2003) Of background: shape, texture, color. Of relation: match 9title, menu, images) 3 Visual Characters of

WebPages (Lindgaard et al. 2006) (no definition) Measured by interesting-boring, good design-bad design, good colour-bad colour, good

layout-bad layout, imaginative-unimaginative, simple-complex, clear-confusing 3 Webpage Aesthetics (Robins and Holmes 2008) A low aesthetic treatment (LAT) is one in which content is simply placed on a web site without

professional graphic design. A high aesthetic treatment (HAT) presents a professional look and feel appropriate to the organization it represents.

3 Mood relevant cues (Parboteeah et al. 2009) The characteristics, such as visual appeal, that affect the degree to which a user enjoys browsing a website but that do not directly support a particular shopping goal.

4 Flow (Ghani et al. 1991) Holistic sensations that people feel when they act with total involvement 4 Flow (Trevino and Webster 1992) Characterizes the perceived interaction with CMC technologies as more or less playful and

exploratory. Has 4 dimensions: control, focused attention, aroused curiosity, intrinsically interested. 4 Positive Mood (Webster and Martocchio

1992) No specific definition provided. Just implied it is a “demonstrated subjective experiences resulting from higher playfulness”.

4 Flow (Webster and Martocchio 1995)

Is characterized by arousal of curiosity and by the extent to which the user finds the interaction intrinsically interesting

4 Mood (Venkatesh and Speier 1999) A state variable, refers to how people feel when they are engaged in any number of activities (George & Jones, 1996)

4 Cognitive Absorption (Agarwal and Karahanna 2000)

Cognitive absorption is a state of deep involvement with IT. It has five components including curiosity, control, temporal dissociation focused immersion, heightened enjoyment.

4 Satisfaction (Bhattacherjee 2001; Bhattacherjee and Premkumar 2004)

A psychological or affective state related to and resulting from a cognitive appraisal of the expectation-performance discrepancy.

4 Concentration (Koufaris 2002) The holistic sensation that people feel when they act with total involvement. 4 Secondary Emotion (Kim et al. 2003) A non-basic, individual-dependent, and domain specific emotions derived from the primary emotions

(Averill, 1994). A concept that is closely related to the secondary emotion is aesthetic responses or affects. The secondary emotion is usually elicited by external stimuli.

4 Anxiety (Venkatesh et al. 2003) Evoking anxious or emotional reactions when it comes to performing a behavior (e.g., using a computer). Measured by: I feel apprehensive about using the system; It scares me to think that I could lose a lot of information using the system by hitting the wrong key; I hesitate to use the system for fear of making mistakes I


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ARM ID Original Construct Article Operational Definition cannot correct; The system is somewhat intimating to me.

4 Computer/system anxiety (Hackbarth et al. 2003; Hwang and Kim 2007)

The apprehension or fear that results when an individual is faced with the possibility of using an IS.

4 CMC anxiety as application specific anxiety

(Brown et al. 2004) An individual’s level of fear or apprehension associated with actual or anticipated use of IT to communicate with others. Measured by: Using email makes me nervous; using email makes me uneasy; I feel comfortable using email (R); I would be comfortable sending email messages that I know a lot of people will read (R); while composing an email message to someone I don't know, I feel tense; I would be fearful of sending email to someone I don't know.

4 Flow (Hsu and Lu 2004) An extremely enjoyable experience, where an individual engages in an online game activity with total involvement, enjoyment, control, concentration, and intrinsic interest

4 Positive emotion, negative emotion

(Cenfetelli 2004) (no definition) Measured by Diener et al. 95 (negative = shame, embarrassment, loneliness, fear, depression, sadness, rage, nervousness, disgust, regret, worry, anger, unhappiness, anxiety, irritation. Positive = happiness, contentment, love, affection, caring, pride, fondness, joy)

4 Customer Satisfaction (Kim et al. 2004) Is an affective state that is the emotional reaction to a transaction experience (Spreng et al., 1996). Measured by: I am satisfied with the transaction with this store; I am pleased ...; I am contented ...; I am delighted …

4 Perceived Playfulness (Lin et al. 2005) Is regarded as an individual state because an individual can feel more or less playful at various points during his/her visit to a web portal.

4 Feeling (pleasure, arousal) (Kim et al. 2007) Feelings and emotions are treated synonymously. Has pleasure and arousal as main components of feelings: pleasure – the degree to which a user feels good or happy with the target object; arousal – refers to the degree to which a user feels excited, stimulated, or active.

4 Concentration Transcendence of self Transformation of time Perceived control Mergence of action and awareness Autotelic experience

(Guo and Poole 2009) All based on Csikszentmihalyi’s flow theory.

4 Joy & Fear (Li et al. 2008) Emotional responses to interacting with a vendor’s website: joy is positive affective state, fear is negative affective state.

4 Irritation (McCoy et al. 2008) Irritation by ads is a feeling of annoyance as the advertisement has interrupted the user so much that she is unable to continue her task.

4 Emotion (excitement, happiness, anger, anxiety)

(Beaudry and Pinsonneault 2010)

Emotions are defined as a mental state of readiness for action that arises from the appraisal of an IT event (in this study, the IT event is the announcement of the imminent deployment of a new system)

4 Positive Affect (Zaman et al. 2010) Co-occurrence of positive emotional states, such as joy, interest, excitement and confidence 4 Flow (Zaman et al. 2010) Two dimensions: concentration and enjoyment. (no definition for neither) 4 Affective involvement (Jiang et al. 2010) Refers to the heightened emotional feelings associated with a website and is made up of feeling states. 4 Negative reaction to

scanning (Suh et al. 2011) (no definition) Measured by:

Describe the extent to which the following wards describe your typical feelings when being scanned (Diener et al., 1995): Shame, sadness, anger

5.1 First Impression (Schenkman and Jonsson 2000)

The first visual impression that a person gets of a webpage.


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ARM ID Original Construct Article Operational Definition 5.1 Aesthetics (of the

WebPages)

(Hall and Hanna 2004) To the extent a webpage is pleasing and stimulating to the eye.

5.1 Hedonic Attributes (Hassenzahl 2004) One of the two groups of a product's perceived characters: the one that are primarily related to the users' self. Contains two aspects: stimulation (being challenging and novel; a prerequisite of personal development, i.e. the proliferation of knowledge and development of skills) and identification (the human need to express one’s self through objects).

5.1 Perceived affective quality (Benlian et al. 2010; Zhang and Li 2004; Zhang and Li 2005; Zhang et al. 2006)

An individual’s perception of the ability of a stimulus such as IT to change his or her core affect

5.1 Immediate Impression of Visual Appeal

(Lindgaard et al. 2006) A physiological, hard-wired reaction to objects in one’s environment that requires no learning.

5.1 Immediate Aesthetic Perception

(Tractinsky et al. 2006) Visually pleasing

5.1 Classic and Expressive Aesthetic Perceptions

(Tractinsky et al. 2006) Classic: orderliness or clarity of the design. Expressive: the creativity and the richness of the design

5.1 Beauty (Tractinsky et al. 2006) Perception of aesthetics of ATM layouts 5.1 Perceived Entertainment (Gao and Koufaris 2006) Reflects a website’s ability to enhance the experience of visitors to the site. 5.1 Perceived Irritation (Gao and Koufaris 2006) Can manifest itself in the form of visitor feelings of confusion, distraction, messiness, the structure,

navigation, function or design elements of a site. 5.1 Perception of an IT’s

capability to induce positive affect and negative affect

(Zhang and Li 2007) Perception of an IT’s Capability to induce Positive Affect (PC-PA) is an individual’s perception or evaluation that an IT has the capability to induce positive affect in him or her; and Perception of an IT’s Capability to induce Negative Affect (PC-NA) is the person’s perception that an IT has the capability to induce negative affect in him or her.

5.1 Aesthetic Perception (van Schaik and Ling 2009) Perceived attractiveness 5.2 Attitude (Trevino and Webster 1992) Attitude toward particular CMC technology email and voice mail. Measured by:

Dreary/fun, unpleasant/enjoyable, cold/warm, mundane/challenging, humanizing/dehumanizing 5.2 WebPage preference (Schenkman and Jonsson

2000) (no definition) Single item measure: preferred completely

5.2 Beauty (Hassenzahl 2004) A high level evaluative construct that is an expression of authoritative judgment of being ugly or beautiful (vs. substantive or low level determinants such as elegance)

5.2 Attitude (Brown et al. 2004) Is a person’s affective evaluation of a specific object 5.2 Attitude (Galletta et al. 2004) Is defined as the satisfaction with the site. 5.2 Satisfaction (attitude

toward an object) (Wixom and Todd 2005) A person's feelings or attitudes toward a variety of factors affecting that situation.

5.2 Satisfaction with Decision Aid

(Hess et al. 2006) Attitudes toward this task or object

5.2 Attitude toward a site (Gao and Koufaris 2006) A positive affective variable. 5.2 Affective Commitment (Li et al. 2006) A situation in which an end user demonstrates an affective and emotional attachment to the

relationship with an e-vendor 5.2 Attitude (McCoy et al. 2008) Overall reactions to the website 5.2 Emotional attachment (Suh et al. 2011) An emotion-laden, target-specific bond between a person and a 67pecific object (Thomson et al. 2005,

p77). A personal’s affection for a specific object connected with him or her such as pets, gifts, or a


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ARM ID Original Construct Article Operational Definition brand.

6.1 Perceived Enjoyment (Chin and Gopal 1995; Chin et al. 2003; Davis et al. 1992; Hong and Tam 2006; Hwang and Kim 2007; Igbaria et al. 1996; Lin et al. 2005; Parboteeah et al. 2009; Thong et al. 2006; van der Heijden 2004; Venkatesh 2000; Venkatesh and Bala 2008; Yi and Hwang 2003)

The extent to which the activity of using the computer is perceived to be enjoyable in its own right, apart from any performance consequences that may be anticipated (Davis et al. 1992, p. 1113)

6.1 Intrinsic Motivation (operationalized as perceived enjoyment)

(Venkatesh 1999; Venkatesh et al. 2003; Venkatesh and Speier 1999; Venkatesh et al. 2002)

The extent to which the activity of using the computer is perceived to be enjoyable in its own right, apart from any performance consequences that may be anticipated (Davis et al. 1992, p. 1113)

6.1 Emotion (Agarwal and Venkatesh 2002; Venkatesh and Agarwal 2006; Venkatesh and Ramesh 2006)

The extent to which a website evokes emotional reactions from you (a user).

6.1 Perceived Playfulness (Chung and Tan 2003; Moon and Kim 2001)

The strength of one’s belief that interacting with the WWW will fulfill the user’s intrinsic motives. Has three aspects: attention is focused, curious during interaction, interaction enjoyable/interesting.

6.1 Shopping Enjoyment (Jiang and Benbasat 2007; Koufaris 2002)

An affective or emotional response as part of experience in shopping online. Measured by: I found my visit interesting, enjoyable, exciting, fun.

6.1 Perceived Playfulness (Fang et al. 2006) The extent to which the activity of using a specific system is perceived to be enjoyable in its own right, aside from any performance consequences resulting from system us.

6.2 Attitude (Chau and Hu 2001; Davis 1989; Davis et al. 1989; Venkatesh et al. 2003)

An individual’s positive or negative feelings (evaluative affect) about performing the target behavior

6.2 Affect (Thompson et al. 1991) Affect toward PC use: the feelings of joy, elation, or pleasure, or depression, disgust, displeasure, or hate associated by an individual with a particular act. Affect is the affective component of attitude. Measured by: PCs made work more interesting; working with PCs was fun, PCs were all right for some jobs but not the kind of job wanted.

6.2 Affect (Thompson and Higgins 1994)

Feeling toward using a personal computer

6.2 Attitude (Karahanna et al. 1999) The individual’s positive and negative evaluations of performing the behavior 6.2 Affect (= attitude) (Limayem and Hirt 2003) Emotional response to the thought of the behavior 6.2 Attitude (Mathieson 1991) The user’s evaluation of the desirability of his or her using the system 6.2 Attitude (Bhattacherjee and Sanford

2006; Moon and Kim 2001; Taylor and Todd 1995)

Satisfaction with process and outcomes; The strength of one’s willingness to use an ICT. Measurement adopted from Taylor & Todd 95: Using (XYZ) in my job is a (bad … good) idea; (foolish … wise) idea; (unpleasant … pleasant) idea; overall, I (dislike … like) the idea of using (XYZ) in my job.

6.2 Affective Reward (Reinig et al. 1996) Sense of emotional gratification often expressed by participants after a successful meeting, or the positive emotional response sometimes associated with goal attainment. Measured by:


69

ARM ID Original Construct Article Operational Definition This process was stimulating, fulfilling, arousing; today’s meeting was satisfying, dissatisfying; this session was dull, boring, interesting; I felt motivated to generate a large number of ideas; solving the problem was gratifying; I did not enjoy myself; it felt like we won; we really accomplished something here today; I’d like to participate in another scenario.

6.2 Attitude (Jackson et al. 1997) An individual’s positive or negative feelings (evaluative effect) about performing the target behavior (from Fishbein and Ajzen, 1975)

6.2 Satisfaction (Devaraj et al. 2002) An ex post evaluation of consumers' experience with the service and is captured as a positive feeling, indifference, or a negative feeling.

6.2 Satisfaction (Teo et al. 2003) Satisfaction towards commercial website measures the affective appeal of commercial Web sites through a sense of involvement, control and affective feelings.

6.2 Attitude (Bhattacherjee and Premkumar 2004)

Personal affect toward IT usage. Measured by: All things considered, using ~ will be a: 1. Bad idea/good idea; 2. Foolish move/wise move; 3. Negative step/positive step. 4. Ineffective idea/effective idea.

6.2 Attitude (Hong et al. 2004; Hong et al. 2005; Malhotra and Galletta 2005; Wixom and Todd 2005)

An individual’s positive or negative feelings about performing a behavior (Ajzen & Fishbein 80)

6.2 Satisfaction (Lin et al. 2005) Satisfaction in using web portal. Measurement adapted from Spreng & and Olshavsky 93: Using the web portal makes me feel very satisfied; very pleased; very contented; very delighted

6.2 Attitude (Lim et al. 2006) The belief that purchasing from iBook should, with good probability, result in either an overall positive or an overall negative outcome.

6.2 Attitude (Kim et al. 2007) A summary evaluation of a psychological object (by Ajzen 2001) captured in both the functional and hedonic dimensions. Attitude highlights summary evaluation.

6.2 Attitude (Jiang and Benbasat 2007) Attitude toward shopping at a website refers to their overall evaluations of a shopping experience at a particular website. Measured by: I like shopping on this website; shopping on this website is a good idea; shopping on this website is appealing.

6.2 Enjoyment (Nah et al. 2011) The hedonic outcome that can result from the experience. Measured by: I found my virtual tour of <xxx> enjoyable, boring, interesting, fun.

7 Attitude (Igbaria and Parasuraman 1989)

Attitudes toward microcomputers are conceptualized as having three components: cognitive (knowledge or perception of the object), affective (feelings or emotional reactions) and behavioral (predisposition to act in a certain way toward the object).

7 Attitude (Agarwal and Prasad 1999) The mediating affective response between beliefs and usage intentions. A learned implicit response that refers to an individual’s evaluation of a concept.

7 Attitude (Teo et al. 2003) Predispositions to respond in a particular way towards a specified class of objects (Rosenberg, 1960). Affective component refers to the feelings formed without conscious thoughts and they can be expressed in verbal statements of affect. Cognitive component consists of the ideas and beliefs formed through conscious thoughts and they can be expressed in verbal statements of beliefs and values.

8 Computer anxiety (Igbaria and Parasuraman 1989)

The tendency of a person to be uneasy, apprehensive, or fearful about the current or future use of computers in general.

8 Microcomputer Playfulness/computer playfulness

(Agarwal and Karahanna 2000; Agarwal and Prasad 1998; Hess et al. 2006;

The degree of cognitive spontaneity in microcomputer interactions (Webster & Martocchio 92), an individual difference variable


70

ARM ID Original Construct Article Operational Definition Venkatesh 2000; Venkatesh and Bala 2008; Webster and Martocchio 1992)

8 Cognitive playfulness of microcomputers

(Webster and Martocchio 1995)

A situation-specific individual characteristic that represents a type of intellectual playfulness. The degree of cognitive spontaneity in microcomputer interactions.

8 Affect (Compeau and Higgins 1995; Compeau et al. 1999)

Liking of particular behavior. Measurement drawn from Computer Attitudes Scale (Loyd and Gressard, 84): I like working with computers; I look forward to those aspects of my job that require me to use a computer; Once I start working on the Computer, I find it hard to stop; Using a computer is frustrating for me; I get bored quickly when working on a computer

8 Computer Anxiety (Brown et al. 2004; Compeau and Higgins 1995; Compeau et al. 1999; Harrison and Rainer Jr 1992; Venkatesh 2000; Venkatesh and Bala 2008; Webster and Martocchio 1992)

The tendency of individuals to be uneasy, apprehensive, or fearful about current or future use of computers.

8 Computer Anxiety (Thatcher and Perrewe 2002) About the implications of computer use such as the loss of important data or fear of other possible mistakes.

8 Computer Playfulness (Hackbarth et al. 2003) Refers to an individual’s tendency to interact spontaneously with a computer (Webster 89). It is defined as being a system specific trait that can change because the experience in using a specific technology increases over time.


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Appendix B. Summary of Relationships Among Affective Concepts in the ICT Literature (See Appendix A for definitions of the involved affective concepts)

Article Empirical Relationship Theoretical Justification/Implication Corresponding ARM Proposition

(Igbaria and Parasuraman 1989)

Trait anxiety -> Computer anxiety More general anxieties are determinants of more specific ones. 2 -> 8 P0b Computer anxiety -> attitudes toward computers

Computer anxiety operates an intervening variable between individual differences and attitudes toward computers. A reduction in computer anxiety will improve attitudes toward computers.

8 -> 7 P10

(Trevino and Webster 1992)

Flow -> attitudes toward CMC technologies

Previous studies show that positive affect, pleasure, and satisfaction result from the flow experience; IS that provides more perceived control (a flow dimension) results in more positive user attitudes and satisfaction.

4 -> 5.2 P3

(Webster and Martocchio 1995)

Cognitive playfulness of microcomputer -> flow Flow is an outcome of the individual characteristics of playfulness. 8 -> 4 P1

(Venkatesh and Speier 1999)

Mood -> Intrinsic motivation (perceived enjoyment)

Based on both the associative network model and the resource allocation model. Positive moods result in more favorable assessments of one’s abilities thus potentially increasing perceptions of enjoyment and thereby intrinsic motivation. Additionally, individuals in positive moods tend to use heuristic (as opposed to analytical) processing, resulting in increased creativity and playfulness, leading to greater task enjoyment and thus greater intrinsic motivation. Negative moods result in more pessimistic assessments regarding oneself and the adequacy of existing knowledge, which in turn generates uncertainty and/or lack of confidence in one’s ability and can result in a negative judgment towards a given situation.

4 -> 6.1 P3

(Agarwal and Karahanna 2000)

Computer playfulness -> cognitive absorption Individual traits are likely to have an effect on experiential states. 8 -> 4 P1

(Schenkman and Jonsson 2000)

First impression <-> Webpage preference

In the framework of evolutionary psychology, the appreciation of beauty is seen as hard-wired into our genetic set-up and the aesthetic feeling fulfills an adaptive, biological function.

5.1 -> 5.2 P7

(Moon and Kim 2001) Perceived playfulness -> attitude toward use

Attitudinal outcomes, such as positive affect, pleasure, and satisfaction, result from the playful experience. 6.1 -> 6.2 P7

(Thatcher and Perrewe 2002)

Trait affectivity -> Computer anxiety

Dynamic, IT specific individual differences (i.e., computer anxiety) are a function of stable situation-specific (i.e., personal innovativeness in IT) and broad (i.e., negative affectivity and trait anxiety) traits.

2 -> 8 P0b

(Teo et al. 2003) Satisfaction with a website -> attitude towards websites

Attitude is shaped through the internalization of value formed through affective and cognitive evaluations. 6.2 -> 7 P6

(Brown et al. 2004) Computer Anxiety -> CMC anxiety as application specific anxiety More general anxieties are determinants of more specific ones. 8 -> 4 P1

CMC anxiety as application specific anxiety -> Attitude toward use

Individuals high in computer anxiety will have negative attitudes toward using a computer. Due to its application-specific focus, CMC anxiety is a more proximal predictor of attitude toward a CMC application than either computer anxiety or communication apprehension. Thus, it should exhibit a significant effect on attitudes regarding the CMC application, such that individuals with high CMC anxiety would have less favorable attitudes toward using the CMC.

4 -> 6.2 P3


72

Article Empirical Relationship Theoretical Justification/Implication Corresponding ARM Proposition

(Hassenzahl 2004) Hedonic attributes <-> beauty Beauty is rather related to self-oriented, hedonic attributes of a product than to its goal-oriented, pragmatic attributes. 5.1 <-> 5.2 P7

(Lin et al. 2005) Perceived playfulness -> Satisfaction in using web portal

Previous research has shown that higher degrees of pleasure and involvement during computer interactions lead to concurrent subjective perceptions of positive affects and satisfaction. Attitudinal outcomes, such as positive affect, pleasure, and satisfaction, resulted from playful experiences.

4 -> 6.2 P3

(Wixom and Todd 2005)

Satisfaction (attitude toward an object) -> cognitive perceptions -> attitude toward behavior

Object-based attitudes influence behavior-based attitudes via cognitive perceptions. 5.2 -> 6.2 P9

(Lindgaard et al. 2006) Visual characters of webpages <-> immediate impression of visual appeal

According to the mere exposure effect (Zajonc 1980), one can quickly form immediate visual appeal impression even given an extremely short period of exposure time that does not permit cognitive processing. Feelings happen to us whether we like it or not, and they can happen in a matter of a few milliseconds.

3 -> 5.1 P0

(Gao and Koufaris 2006)

Perceived entertainment -> attitude toward the website Perceived irritation -> attitude toward the website

Uses and gratifications research indicates that the entertainment value of a commercial exchange lies in its ability to fulfill the audience's needs for escapism, diversion, aesthetic enjoyment, or emotional release. Research in traditional advertising identified irritation as a significant factor that influences consumer attitude.

5.1 -> 5.2 P7

(Jiang and Benbasat 2007)

Shopping enjoyment -> Attitude toward shopping at a website

The degree to which a website is visually attractive, fun, and interesting is perceived as part of the website’s system quality, which directly affects consumer satisfaction. Similarly, entertainment features that enhance shopping enjoyment improve consumers’ attitudes toward shopping at a website. Therefore, the more enjoyment consumers derive from a shopping experience, the more likely that customers would prefer their online shopping experience.

6.1 -> 6.2 P7

(Kim et al. 2007) Feeling (pleasure, arousal) -> attitude toward using mobile internet services

Users may feel pleasure as well as arousal from the services. These feelings could influence attitude according to the Elaboration Likelihood Model, where feelings operate through peripheral route processing by means of classical conditioning. Previous research has also shown that affect can influence the formation of attitude in the absence of product beliefs. Therefore, attitude formation can be done via direct affect transfer.

4 -> 6.2 P3

(Parboteeah et al. 2009) Mood relevant cues -> perceived enjoyment

The stimulus-organism-response (S-O-R) paradigm posits that environmental cues act as stimuli that influence an individual’s cognitive and affective reactions, which in turn affect behaviors (Mehrabian and Russell 1974)

3 -> 6.1 P0c

(Zaman et al. 2010) Flow -> positive affect Even though flow is a positive emotional state, Csikszentmihalyi (1996) argued that positive affect and flow are two distinct constructs. He explained that, while experiencing flow, a person does not realize the joy. A person feels ‘‘only what is relevant to the activity” (p.123), and anything else would be a distraction. It is shortly after experiencing flow that they have a positive affect towards the activity.

4 ->4 P11


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References for the Appendices Agarwal, R., and Karahanna, E. 2000. "Time Flies When You're Having Fun: Cognitive Absorption and

Beliefs About Information Technology Usage," MIS Quarterly (24:4), pp. 665-694. Agarwal, R., and Prasad, J. 1998. "A Conceptual and Operational Definition of Personal Innovativeness

in the Domain of Information Technology," Information Systems Research (9:2), pp. 204-215. Agarwal, R., and Prasad, J. 1999. "Are Individual Differences Germane to the Acceptance of New

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