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Running head: MEDIATING ROLE OF PUBLIC ENGAGEMENT

Toward a Model of Engaged Publics: Trust, Satisfaction, and the Mediating Role of Public

Engagement for Supportive Behaviors

(Abridged Version of Doctoral Dissertation)

Minjeong Kang, Ph. D.

Syracuse University

March 1, 2012

Mediating Role of Public Engagement, 2

Abstract

The quality of relationships between an organization and its public is a good indicator of the

public’s general attitude toward the organization. However, gaps exist between organization-

public relationship quality and public’s actual supportive behaviors. To fill a critical missing link

between organization-public relationships and publics’ supportive behaviors, this study

investigates if public engagement, defined as a motivated affective state of individual members

of publics that drives their voluntary extra-role behaviors, connects evaluation of organization-

public relationships to actual supportive behavioral outcomes. By focusing on the concept of

engagement, the purpose of the current study is to empirically test a theoretical model of public

engagement with two key antecedents, (i.e., relational trust and satisfaction) and its mediating

role between such antecedents and positive behavioral outcomes.


Toward a Model of Engaged Publics: Trust, Satisfaction, and the Mediating Role of Public

Engagement for Supportive Behavioral Outcomes

For nearly three decades of public relations scholarship, key goals of communication

management have been the strategic management of quality relationships between an

organization and its key publics (e.g., L. Grunig, J. Grunig, & Dozier, 2002; Ledingham &

Bruning, 2000). Since Ferguson (1984, August) called for research on organization-public

relationships (hereafter called OPR) in 1984, Ki and Shin (2006) noted in their systematic

review of past public relations research that the concept and theories of OPR have dominated

public relations research. More specifically, relationships between an organization and its publics

have been examined in terms of four key relational outcomes of trust, satisfaction, commitment,

and control mutuality and their subsequent effects (e.g., Hon & J. Grunig, 1999; Kang & Yang,

2010; Ki & Shin, 2006; Yang & J. Grunig, 2005; Yang, 2007). Previous research examined key

outcomes of OPR in relation to (a) favorable corporate/organizational reputation (e.g., Yang,

2007; Yang & J. Grunig, 2005); and (b) publics’ attitudes toward organizations and behavioral

supports (e.g., Bruning, 2000; Hong & Yang, 2009; Ki & Hon, 2007a; Kang & Yang, 2010).

As many corporate communication campaigns focus on achieving desirable effects on

publics such as increased awareness, knowledge, positive opinions, attitudes, and behaviors

(Dozier & Ehling, 1992), scholars (e.g., Hong & Yang, 2009) have argued that in order for such

communication campaigns to bring out intended effects, factors that provoke publics to engage

in communication with organizations need to be considered. In such an effort, Hong and Yang

(2009) examined the effects of satisfaction and reputation on organizational stakeholders’

communication behaviors and found the mediating role of company-customer identification on

the word-of-mouth intentions.


Filling this gap between conceptual relationship assessments and tangible behavioral

indicators of public support, the concept of public engagement has emerged in the contemporary

public relations practices (e.g., Breakenridge, 2008; Solis, 2010). With the emergence of social

media, publics have increasingly utilized this new form of active communication as a critical tool

of public engagement with organizations (e.g., Breakenridge, 2008; Scott, 2007; Weil, 2006).

Individual stakeholders are increasingly demanding to be active partners in many corporate

activities such as corporate social responsibility campaigns, because they are willing to

“contribute to society’s sustainability and well-being in partnership with business, government

and non-governmental organizations” (Edelman, 2009, March 5, par. 1). As organizations begin

to acknowledge the value of empowered individuals, who are willing to collaborate with

organizations as a critical partner for mutual success, the needs to engage publics as the integral

part of organizational operations and success have exponentially increased. Hence, the success of

organizations in this new public and media environment can be largely dependent on

organizations’ abilities to find ways to effectively and positively engage their stakeholders for

meaningful partnerships.

The concept of engagement is nothing new. In business and organizational context,

engagement has become a popular concept to develop efficient organizational communications

for employee motivation and leadership development. Also, in marketing communication,

customer engagement has been explored for product development and consumer relationships.

As the relationship perspective has become a dominating paradigm in marketing research,

concepts such as customer satisfaction, customer-brand commitment, identification, and

customer/brand engagement have become popular concepts in exploring the value of customer-

brand relationships and the subsequent effects of nurtured relationships with customers on


supportive intentions or behaviors. Moving away from linear persuasion model of marketing

communication (Plummer, 2008), marketers and communication professionals alike have put

forth much effort to understand the changing world of customers and their expectations by

shifting the marketing emphasis to the “co-creation” of customer/public experiences (e.g.,

Rowley, Kupiec-Teahan, & Leeming, 2007). Common to these various understandings of

engagement is that engagement is a desirable condition that brings positive organizational or

marketing outcomes such as increased employee voluntary behaviors, consumer advocacy, and

customer loyalty.

Although public engagement has emerged as an important concept in contemporary

corporate and strategic communication context, the concept of engagement has suffered from the

lack of a clear theoretical definition. Without proper definition of the concept, professionals and

scholars alike have been jumping on the bandwagon to find ways to connect engagement with

more tangible customer outcomes such as return-on-investment (ROI), word-of-mouth (WOM)

behavior, purchase, or loyalty without much success. Our understanding of engagement so far

lacks serious theoretical deliberations as well as empirical support.

With the emergence of new tools such as web analytics that enable for marketers to

monitor and measure people’s activities online, engagement has emerged as a term that describes

the level and degree of activity people have with a brand or company. Common approaches

social media consultants or marketers suggest are equating engagement with the number of

clicks, mentions in the media, “linking, bookmarking, blogging, referring, clicking, friending,

connecting, subscribing, submitting inquiry forms and buying are all engagement measures at

various points in the customer relationship” (Odden, L. cited in Falls, J. “What is Engagement

and How do We Measure it? ” January 4, 2010). Despite the usefulness of such information to


some marketers, what these numbers represent are behaviors that are fragments of behavioral

outcomes of engagement but not engagement itself. Some PR professionals (e.g., KD Paine)

have proposed different levels of engagement measures to differentiate relationship-based

engagement from matrix-based engagement (“Measuring Engagement is Just Another Term for

Measuring Relationships,” January 4, 2010). The best way for the concept of engagement to

have conceptual and behavioral utility is to be conceptualized in a model that embraces both the

psychological and the behavioral components it implies (Macey & Schneider, 2008).

The current study reviews existing organizational and marketing literature on engagement

and adopts pertinent views into public relations research context by theoretically defining the

concept of public engagement; devising a methodologically sound measure for engagement; and

empirically examining the relationships between public engagement and other important

concepts in public relations research.

Literature Review

According to the Merriam-Webster Dictionary Online (2012), the intransitive verb “to

engage” means to pledge oneself; to begin and carry on an activity; to participate or to induce to

participate; or to give attention to something. As such, it carries meanings of both cognitive and

behavioral dimensions such as getting involved or participating in activities such as

conversation, discussion, or making a pledge to do some action. The concept of engagement has

been studied in various contexts such as organizational psychology, education, and consumer

psychology. Macey and Schneider (2008) defined engagement as having three components: trait

engagement, state engagement, and behavioral engagement. In their conceptual model of

engagement, Macey and Schneider suggested that trait engagement, a personality disposition of

individuals (i.e., positive outlooks of life and work in general), provides a perspective for


understanding the world. And, this trait engagement gets to be reflected in psychological state

engagement, and finally this psychological state engagement leads to behavioral engagement.

Similarly, Kahn (1990) also noted that personal engagement refers to “harnessing of organization

members’ selves to their work roles; in engagement, people employ and express themselves

physically, cognitively, and emotionally during role performance” (p. 694).

On the basis of Macey and Schneider’s (2008) and Kahn’s (1990) frameworks of

engagement, the current study discusses the concept of engagement in cognitive, affective, and

behavioral frameworks in relations with key antecedents and outcomes. More specifically, this

study proposes that public engagement is discriminant from OPR, which has been primarily

viewed as a cognitive concept (J. Grunig & Hung, 2002; Kang & Yang, 2010), and is

predominantly an affective concept. More importantly, focusing on trust and satisfaction as key

antecedents of engagement, the concept of public engagement is proposed as a crucial mediator

connecting key relational outcomes—trust and satisfaction– with a public’s supportive and loyal

behaviors.

Definitional and Measurement Issues

Although the concept of engagement has become a popular term both in practice and the

academic world, there are various conceptual and methodological concerns that hinder further

development of theories and practices on engagement. For instance, in March 2006, the

Advertising Research Foundation (ARF) defined customer/brand engagement as “turning on a

prospect to a brand idea enhanced by the surrounding context” (Plummer, 2008, p. 15).

Similarly, Brian Haven (Forrester, Marketing’s New Key Metric: Engagement, 2007 August 8)

has defined engagement as “the level of involvement, interaction, intimacy, and influence an

individual has with a brand over time (p. 5) ” from “a person’s participation with a brand,


regardless of channel, where they call the shots” (p. 5). As such, the working definitions of

engagement widely adopted by professionals lack conceptual clarity and utility at best.

Confusion also exists in academic literature. For instance, problems in the discussion of

engagement are often associated with vague definitions as discussed in Robinson and Perryman,

and Hayday (2004). Colbert and colleagues (2004) defined engagement in terms of heightened

motivational states of employees (Colbert, Mount, Harter, Witt, & Barrick, 2004, p. 603).

Similarly, Wellins and Conselman (2005) also defined engagement as an “illusive force that

motivates employees to higher levels of performance” (p. 1).

Closely connected to the definitional problems, there also exist issues with the measures

of engagement (Robinson et al., 2004). Contemporary measures of employee engagement are

often similar to already existing concepts such as commitment (e.g., Baumruk, 2004; Richman,

2006), satisfaction (e.g., Harter, Schmidt, & Hayes, 2002), organizational citizenship behaviors

(Robinson et al., 2004), or a compilation of four different categories: satisfaction, commitment,

psychological empowerment, and task involvement (Macey & Schneider, 2008). However,

scholars have pointed out such measures as problematic in that factors such as satisfaction, work

involvement, or commitment tap not a whole, but only some aspects of engagement (Macey &

Schneider, 2008). For instance, noting earlier works by Mathieu and Zajac (1990), Brown (1996)

concluded that task involvement is more like an antecedent of commitment rather than a

characteristic or consequence of organizational commitment.

Such definitional ambiguities of engagement and the operational overlaps with similar

concepts are especially problematic in their exclusion of engagement as a state that connotes

passion, commitment, or involvement (Macey & Schneider, 2008). Macey and Schneider argued

that a more precise definition of engagement should include absorption, passion, and affect but


not satisfaction, job involvement, and commitment as its central characteristics (p. 7). This

contention is echoed in Erickson’s (2005) view of engagement. Erickson (2005) noted

engagement is more than simple satisfaction or basic loyalty and argued that it is “about passion

and commitment-the willingness to invest oneself and expend one’s discretionary effort (p. 14)”

beyond what is required. Engagement is relatively persistent or stable (Schaufeli, Salanova,

Gonzalez-Roma, & Bakker, 2002; Macey & Schneider, 2008) with elevated emotional tone of

the state (Schaufeli et al., 2002) that involves two critical factors: attention (i.e., “how much

effort and time are spent”) and absorption (i.e., “how intense is the focus”) (Rothbard, 2001).

The current study adopts this prominent view of engagement with the affective aspects at

the core of its definition and suggests (a) positive affectivity, (b) affective commitment and (c)

empowerment as three key dimensions of public engagement. Therefore, public engagement in

this study refers to a psychologically motivated affective state of individual members of publics

that drives their voluntary extra-role behaviors. Public Engagement is characterized by affective

commitment, positive affectivity and empowerment that individual public experiences in

interactions with an organization over time that result in supportive behavioral outcomes.


Defining Engagement

Engagement as affective commitment. Affective commitment “reflects an emotional

attachment to, identification with and involvement in an organization” (Meyer & Smith, 2000, p.

320). Having received substantive attention in organizational research, affective commitment has

been identified as one of the important determinants of employee dedication and loyalty

(Rhoades, Eisenberger, & Armeli, 2001). Unlike continuance and normative commitment that

connote some degree of reluctance to commitment based on calculation and circumstantial

conditions, affective commitment implies voluntary desires to commit (Bansal, Irving, & Taylor,

2004) and has been closely linked to the concept of engagement (e.g., Meyer & Allen, 1991;

Allen & Meyer, 1996).

Some scholars and practitioners have defined engagement in terms of organizational

commitment (e.g., Wellins & Conselman, 2005) as “to be engaged is to be actively committed,

as to a cause (p. 1).” And, affectively committed individuals tend to possess a sense of

“belonging and identification that increases their involvement in the organization’s activities,

their willingness to pursue the organization’s goals, and their desire to remain with the

organization” (Rhoades, Eisenberger, & Armeli, 2001, p. 825). This emotional and affective

connection may result from “a psychological link” (Allen & Meyer, 1996, p. 252) or “a

psychological bond” (Gruen, Summers, & Acito, 2000, p. 320) between relationship partners,

which makes voluntary defection or disconnection less likely (Gilliland & Bello, 2002; Meyer &

Allen, 1997). The current study postulates affective commitment is a facet of engagement

characterized by emotional bonding and pride that brings additional efforts to sustain that

relationship.


Engagement as positive affectivity. Positive affectivity is largely considered as having

temperamental characteristics that are conducive to feeling joy, excitement, and other positive

feelings (Costa & McCrae, 1980) with links to outcome measures such as job satisfaction (e.g.,

Staw, Bell & Clausen, 1986; Staw & Ross, 1985). Characterized by “activated pleasant affect”

(Larsen & Diener, 1992, p. 31), positive affectivity and its definition are consistent with how

Schaufeli, Bakker, Hoogduin, Schaap, Kladler (2001) defined engagement in terms of positive

affective-motivational state of fulfillment that is typically noted by vigor, dedication, and

absorption. Similarly, Macey and Schneider (2008) suggested that positive affectivity connoting

“feelings of persistence, vigor, energy, dedication, absorption, enthusiasm, alertness, and pride”

(p. 12) is a central facet in the conceptualization and operationalization of engagement.

Similar understanding of positive affectivity to the concept of engagement can be found

in how some scholars refer to positive affectivity as passion, excitement, (Wellins & Concelman,

2005) or emotional engagement (Fleming, Coffman, & Harter, 2005). Shirom’s (2007) notion of

vigor is also similarly positioned to engagement as a persistent positive-affective state with the

feeling of cognitive liveliness as well as enhanced physical and emotional energy. As central as

it is to the understanding of engagement, definitions and measures of engagement without

tapping into the affective energetic state are not properly understanding and measuring the

concept of engagement in whole (Macey & Schneider, 2008). The current study postulates

positive affectivity is a facet of engagement that is characterized by six positive markers

(PANAS) (Watson, Clark, & Tellegen, 1988).

Engagement as empowerment. Closely linked with the concept of power, empowerment

has been largely considered equal to delegation or decentralization of decision-making power

(Burke, 1986; Kanter, 1983). Consequently, empowerment has been used interchangeably with


employee or public participation. Based on the theory of intrinsic task motivation, Thomas and

Velthouse (1990) argued that to empower is equal to “give power to” (p. 667) and suggested that

empowerment entails a sense of authorization, capacity, and energy, concluding that empowering

as “to energize” (p. 667) best captures the term as defined as motivational state.

Viewing empowerment as a motivational concept, Conger and Kanungo, (1988) proposed

enabling (empowering) individuals through enhancing self-efficacy. Bandura (1982) argued that

the self-perceptions of efficacy are central to human agency, impacting actions, cognitive

patterns, and emotional arousal. In other words, individual’s perception of self-efficacy or

efficacy judgment will affect how much effort and persistence is necessary for one to exert in a

given task and environment.

Empowerment is associated with many positive outcomes. For example, empowered

individuals tend to display high efficiency in their achievements, high level of energy and effort

in learning (Bandura, 1977); initiative and innovative behaviors (Block, 1987; Sprietzer, 1995);

and managerial effectiveness (Thomas & Velthouse, 1990; Sprietzer, 1995). Rothbard’s (2001)

view of engagement as psychological presence reflects close relations between efficacy and

engagement. This study adopts the view of empowerment as a motivational state that is internal

to individuals (Conger & Kanungo, 1988) and proposes empowerment represents a motivated

facet of engagement, both conceptually and operationally.

Antecedents of Public Engagement

Since the emergence of organization-public relationships (OPR) as the dominant

paradigm of public relations research, Hon and J. Grunig’s (1999) measures of OPR have been

adopted as the most prominent tool of measuring relationship quality between organizations and

publics, as Ki and Shin (2006) noted from past OPR research. Conceptualized as the outcomes of


a relationship formed between an organization and its publics (J. Grunig & Huang, 2000), Huang

(1997) initially defined OPR as in terms of four key outcomes: trust, satisfaction, commitment,

and control mutuality. Later, Hon and J. Grunig (1999) developed the widely used measurement

index of OPR with four relationship indicators and two relational types (i.e., communal and

exchange relationships).

However, there exist conflicting views on considering these four elements as equal

dimensions of OPR. For example, some researchers (e.g., Morgan & Hunt, 1994; Nooteboom,

Berger, & Noorderhaven, 1997; Garbarino & Johnson, 1999; Tax, Brown, & Chandrashekaran,

1998; Ki & Hon, 2007b) have viewed commitment as a key outcome of trust or satisfaction. This

is similarly echoed in relational commitment defined as “an enduring desire to maintain a

valued relationship” (Moorman, Zaltman, & Deshpande, 1992, p. 23). This view is consistent

with engagement literature that view affective commitment as a facet of engagement. Similarly,

control mutuality, defined as the extent of the reciprocity by which publics’ opinions are shared

with an organization (J. Grunig & Huang, 2000), is viewed interchangeable with the notion of

empowerment of publics in managing an organization (Moore, 1986). Considering

empowerment is viewed as a facet of engagement, this study focuses on two key cognitive

OPR variables—i.e., trust and satisfaction—as the key antecedents of engagement.

Relational trust and engagement. Since the paradigm shift in marketing research to

relationship marketing, trust has been identified as the most important influencer in fostering

strong relationships between customers and organizations (Berry, 1995; Sirdeshmukh, Singh, &

Sabol, 2002). Dubbed as the “cornerstone” (Spekman, 1988, p. 79) of long-term relationships,

trust has been extensively studied across the disciplines including interpersonal relationships

(e.g., Canary & Cupach, 1988; Larzelere & Huston, 1980); relationship marketing (e.g., Berry,


1995; Moorman, Zaltman, & Deshpande, 1992; Morgan & Hunt, 1994; Smith, 1998); political

communication (e.g., Putnam, 1993, 1995); and organizational communication management

(e.g., Becerra, 1998; Bruning & Ledingham, 1999; Huang, 1997, 2001; Jo & Kim, 2003; Ki &

Hon, 2007a; Yang & J. Grunig, 2005; Yang, 2007).

Naturally, both conceptual and empirical studies found evidence to support the pivotal

role of trust as a key determinant of relational commitment (e.g., Nooteboom, Berger, &

Noorderhaven, 1997; Garbarino & Johnson, 1999; Tax, Brown, & Chandrashekaran, 1998),

loyalty (Gassenheimer, Houston, & Davis, 1998; Reichheld & Schefter, 2000; Sirdeshmukh et

al., 2002), and an essential element for strong relationships and sustainable market share (Urban,

Sultan, & Qualls, 2000).

Applying the concept of trust in public-organization contexts therefore calls for caution in

conceptualization and translating the construct, in any particular research setting. Trust, like

other theoretical concepts, has been diversely interpreted and defined. Some scholars have

broadly defined trust as one’s beliefs and expectations about a trustee’s desirable action (e.g.,

Sitkin & Roth, 1993) and others have defined trust more narrowly in terms of one’s cognitive

evaluation of others’ goodwill and reliability (e.g., Cummings & Bromiley, 1996; Ring & Van de

Ven, 1992). For example, Morgan and Hunt (1994) and Doney and Cannon (1997) emphasize a

cognitive and evaluative interpretation of trust that views trust evaluation and resulting behaviors

as subject to the influence of other situational factors. As the primary literature of OPR research,

Hon and J. Grunig (1999) viewed trust as one of the key components of quality relationships

between an organization and its publics, defining trust in terms of three dimensions: (a) integrity,

(b) dependability, and (c) competence.


Trust and engagement have been linked in extant literature. For instance, trust has been

identified as the most important factor that drives civic engagement. Fukuyama (1995) argued

that trust engenders spontaneous sociability, which means “the myriad forms of cooperative,

altruistic, and extra-role behavior in which members of a social community engage” (Kramer,

1999, p. 583). In Bowling Alone, Putnam also puts emphasis on trust as the determining factor

that has reduced civic engagement in American society since the 1960s (Putnam, 2000; Uslaner,

2000). According to Putnam (2000), trust and engagement are highly correlated across time and

individuals as two important facts of social capital. Based on Putnam’s proposition, trust and

civic engagement that manifest in the form of voluntary associations with membership

organizations are interrelated concepts. In organizational studies, trust in terms of perceived

organizational support has been closely linked to higher employee engagement (e.g., Saks,

2006). Therefore, based on the theoretical linkage predicted in the literature, the current study

proposes the following relationship between trust and engagement:

H1: Trust leads to enhanced public engagement with organizations.

Prior research in consumer trust shows that relational trust between consumers and

companies, customer loyalty, and positive word-of-mouth are positively associated (e.g.,

Zeithaml, Berry, & Parasuraman, 1996). Therefore, the current study proposes that trust is a key

antecedent of public-organization engagement and that trust leads to supportive behavioral

outcomes such as WOM or loyalty intentions.

H2: Trust leads to positive behavioral outcomes that publics have toward organizations.

Relational satisfaction and engagement. Satisfaction has been extensively studied in

customer and organizational management literature as the key to both short- and long-term

organizational success (Henning-Thurau, & Klee, 1997) in terms of customer retention and


communicative behaviors (positive and negative WOM) and as one of the key outcomes of

relationships for decades (Garbarino & Johnson, 1999).

According to Anderson and Sullivan (1993), satisfaction is best understood as “a function

of perceived quality and disconfirmation – the extent to which perceived quality fails to match

pre-purchase expectations” (p. 126), and is best characterized as a post-evaluative judgment

based on the customer’s product or service experiences (Kotler, 1991). From the communication

management perspective, satisfaction is referred to as the belief about “the extent to which each

party feels favorably toward the other because positive expectations about the relationship are

reinforced” (Hon & J. Grunig, 1999, p. 3).

Satisfaction and engagement have been closely linked in literature. Some scholars (e.g.,

Harter et al., 2002) have conceptualized engagement and satisfaction as directly linked, if not

isophoric (Macey & Schneider, 2008). Engagement and satisfaction are not the same concept or

concepts in the same level (Macey & Schneider, 2008). Erikson (2005) pointed out there exist

essential differences between engagement and satisfaction because engagement implies

activation, but satisfaction implies satiation. This is also well noted in Kahn’s (1990)

engagement model with three psychological conditions that are necessary for engagement:

meaningfulness, safety, and availability. Kahn (1990) proposed psychological meaningfulness as

a required condition for engagement to occur. Defining psychological meaningfulness as “a

feeling that one is receiving a return on investments of one’s self in a currency of physical,

cognitive, or emotional energy” (p. 704-5), Kahn’s definition of meaningfulness is similar to

how satisfaction has been defined, in that it involves a perception or evaluation of experience in

terms of investment and returns. Macey and Schneider (2008) asserted that satisfied individuals

tend to display a higher level of engagement, characterized by feelings of energy and absorption,


indicating a causal direction from satisfaction to engagement. This study postulates satisfaction

is a key antecedent to engagement in that individuals need to have a satisfying relationship with

an organization before they become engaged with the organization.

H3: Satisfaction leads to enhanced public engagement with organizations.

The relationship between satisfaction and supportive behavioral outcomes, such as

loyalty (e.g., Schaufeli & Bakker, 2004) and WOM, (e.g., Anderson, 1998) are quite extensive in

literature. For instance, Kotler (1994) sums up the satisfaction-loyalty literature by noting that

customer satisfaction is the key to customer retention (p. 20). Similarly, Ravald and Gronroos

(1996) noted that customer satisfaction is one of the leading indicators of customer loyalty and

overall customer satisfaction is a better predictor of intentions to repurchase than overall or

inferred service quality. Therefore, the following hypothesis is proposed.

H4: Satisfaction leads to positive behavioral outcomes that publics have toward

organizations.


Positive Behavioral Outcomes

Positive word-of-mouth (WOM) support. Defined as “information communication

directed at other consumers about the ownership, usage, or characteristics of particular goods and

services and/or their sellers” (Westbrook, 1987, p. 261), word-of-mouth communication

(hereafter called “WOM”), has recently received renowned interests from scholars and

professionals. Some scholars have suggested that WOM is “a dominant force in marketplace”

(Mangold, Miller, and Brockway, 1999, p. 73) and the “ultimate test of the customer’s

relationship” (Bendapudi & Berry, 1997, p. 30). This trend is particularly interesting with

increasing use of social media by organizations to bring about the positive WOM behaviors

among customers. Positive WOM communication has been perceived as a valuable tool for

promoting purposes of a company’s products or services (Gremler, Gwinner, & Brown. 2001) as

people tend to view WOM communication more positively than promotional communication

efforts that are initiated by a firm (Herr, Kardes, & Kim, 1991).

Since Anderson’s (1998) call for more research on antecedents of WOM communication,

there have been many efforts by scholars to understand what may lead to increased customer

WOM behaviors. Gremler, Gwinner, & Brown (2001) examined the effects of customer-

employee relationships on positive WOM and found that the interpersonal relationship between

customers and a service provider that are marked by trust resulted in greater positive WOM

behavior by customers. Brown, Barry, Dacin, and Gunst (2005) also proposed a comprehensive

model of the antecedents of positive WOM. In their study, Brown et al. (2005) found that

customer satisfaction and consumer identification led to positive WOM intentions and behaviors

and these links were both mediated and moderated by consumer commitment. Hong and Yang


(2009) reported positive corporate reputation along with customer satisfaction led to increased

WOM intentions among the customers.

Loyalty. The concept of customer loyalty has received extensive interests in marketing

history (Knox & Walker, 2001). For several decades, a primary objective of many marketing

strategies was to generate loyal customers; the level of customer loyalty to a brand has been used

as a whole or partial indicator of success for marketing campaigns, and of brand equity (Aaker,

1991; Knox & Walker, 2001). As the relationship marketing perspective dominates, the concept

of customer loyalty also has become paramount (Fournier & Yao, 1997) to effective relationship

management efforts. That is, first and foremost in relationship marketing is to create customer

loyalty; as a result, a stable, mutually profitable and long-term relationship is enhanced (Annika

& Gronroos, 1996). Echoing Fournier et al.’s (1997) argument that the loyalty concept needs to

reflect and “dimensionalize the types of sources of affect that may comprise and distinguish

loyalty responses (p. 452),” the current study attempts to explore the essentiality of an affective

notion of engagement on the formation of loyalty behaviors among the customers. For this study,

loyalty is delimited to supportive behavioral intention on the basis of perceived service quality

(Zeithaml, Berry, & Parasuraman, 1996). Zeithaml et al. found customers’ evaluation of service

quality lead to supportive behavioral intention as loyalty, which leads to customer retention and

competitive advantage.

The relationship between loyalty and engagement is evident in organizational research.

Salanova, Agut, and Peiro (2005), for example, reported that supportive organizational climate,

which is affected by organizational support and employee work engagement, led to better

employee performance and customer loyalty. Therefore, the following hypothesis is proposed to

test:


H5: Public engagement leads to positive behavioral outcomes such as positive WOM and

customer loyalty that publics have toward organizations.

Mediating Role of Public Engagement

Regardless of a strong connection between key relational variables (e.g., satisfaction and

trust) and customer supportive behaviors (e.g., loyalty), current literature do not strongly support

the direct linkage between satisfaction/trust and positive outcomes such as loyalty (Agho,

Mueller, & Price1992; Fournier, Dobscha, & Mick, 1998; Yim, Tse, & Chan, 2008). Fournier et

al. (1998) questioned the effectiveness of customer relationship programs by arguing that loyalty

in services is hard to achieve and predict (Agustin & Singh, 2005). Consequently, scholars (e.g.,

Fournier et al., 1998; McEwen, 2005; Yim et al., 2008) have suggested the importance of

building strong affective connections or bonds with the customers in order for firms to build

strong customer loyalty. For instance, Yim et al. (2008) applied the Sternberg’s (1986) triangular

theory of love (i.e., intimacy, passion, and commitment) as three components of love, and

suggested customer-firm affection as a mediating variable among trust, satisfaction, and loyalty.

Many (OPR) research examined the direct link between OPR quality and various outcomes such

as positive attitudes and positive reputations (e.g., Bruning, 2000; Hong & Yang, 2009; Ki &

Hon, 2007a; Kang & Yang, 2010). Surprisingly lacking is the affective component such as liking

or affection that may be the most important aspect of a good relationship. The study

conceptualizes public engagement as an affective concept and examines that the effects of two

important indicators of quality OPRs (i.e., trust and satisfaction) on supportive behavioral

outcomes are to be mediated by public engagement.

Research Question: To what extent does public engagement mediate effects of trust and

satisfaction on positive behavioral outcomes that publics have toward organizations?


Hypothesized Conceptual Model

This study proposes a theoretical causal model in which the quality of relational trust and

satisfaction influences publics’ positive behavioral outcomes to support organizations (i.e., H2

and H4 respectively). Also, as a critical missing linkage, public engagement is suggested as the

mediator between key relational outcomes (i.e., relational trust and satisfaction) and publics’

positive behavioral outcomes (i.e., H1, H3 and H5 respectively). This mediating model is tested

overall in terms of public engagement’s mediation effects (i.e., RQ1).

Method

Sample and Data Collection Process

The link to the online survey was emailed to 4,425 randomly selected current patrons of a

professional theatre organization in the United States. The sample included all donors, long-term

subscribers, and single-ticket buyers during the 2006 to 2010 seasons. The survey was conducted

for a week during the summer of 2010 and generated a random sample of 1084 complete cases

(n=1084) with response rate of 24.50 percent.1 As an incentive to participate in the survey, 10

randomly selected respondents were awarded monetary support (cash value of $200) that may be

used toward their yearly subscription for the next season.

To ensure ethical treatment of study participants, the study obtained approval through

Internal Review Board (IRB)’s review process. Each participant was fully informed of the

following information in the cover letter of the questionnaire: (a) the name of the investigators

and the organization carrying out the research; (b) the sponsorship or any conflict of interest; (c)

an accurate, though brief, description of the purposes of the research; (d) an accurate statement

of the extent to which answers will be protected with respect to anonymity; (e) assurance that

cooperation is voluntary; and (f) assurance that respondents can skip any questions they do not


want to answer. Further, participants’ responses were kept completely anonymous. The

questionnaire did not ask for any specific identifying information about the participants, except

for basic demographic information.

Among 976 research participants who answered the gender question, 721 participants

(73.90 percent) were female. The mode of the participants’ age was the age range from 46 to 55

(n=308; 31.50 percent). Frequency for other age ranges includes: 25 and Under (n=20; 2

percent); 26 to 35 (n=102; 10.40 percent); 36 to 45 (n=158; 16.20 percent); 56 and 64 (n=256;

26.20 percent); and 65 and Over (n=134; 13.70 percent). With regard to race/ethnicity, most of

the research participants reported they are Caucasian (n=920; 96.40 percent). Frequency for other

race/ethnicity categories includes: African American (n=19; 2 percent); Asian (n=10; 1 percent);

Hispanic/Latino (n=4; .40 percent); Native American (n=1; .10 percent); and Other (n=18; 1.80

percent).

Regarding the duration of research participants’ relationships as donors or patrons, the

mode was “Five Years or Longer” (n=560; 61.50 percent), suggesting many of the research

participants had substantial relationships with the organization studied. Previous public relations

research (e.g., Ki & Hon, 2007a) suggested research participants’ having substantial

relationships is critical to measure organization-public relationships. According Ki and Hon,

with minimal interactions and hence only second-hand relationships, individual variance on the

quality of organization-public relationships is difficult to observe. Frequency for other duration

categories includes: “Four Years” (n=64; 7 percent); “Three Years” (n=99; 10.90 percent); “Two

Years” (n=103; 11.30 percent); and “One Year” (n=85; 9.30 percent).

In terms of the type of research participants’ relationships with the organizations studied,

the mode was Current Single-time patron (other than donor) (n=596; 55 percent). Frequency for


other related categories include : Current donor (n=138; 12.70 percent); Current long-term patron

(other than donor) (n=277; 25.50 percent); Past donor (n=79; 7.30 percent); and Past patron

(other than donor) (n=259; 23.90 percent).

Measurement Instrumentation

In the hypothesized model, the researcher aimed to investigate relations between (a)

public engagement, a latent variable with three indicators (i.e., affective commitment, positive

affectivity and empowerment); (b) trust, a latent variable with two indicators (i.e., integrity and

competency); (c) satisfaction, a measured variable; and (d) positive behavioral outcomes, a latent

variable with two indicators (i.e., loyalty and positive word-of-mouth intentions). The

measurement level used for the close-end questions was Likert-type scales with seven-categories

ranging from “strongly agree” to “strongly disagree.”

Public engagement. This study defines the concept of public engagement in three

dimensions: affective commitment, positive affectivity and empowerment.

Affective commitment, conceptualized as emotional bonding and pride that brings

additional efforts to sustain organization-public relationships, was measured with three items

from Allen and Meyer (1996) and Bansal et al. (2004): “feel emotionally attached” (M=4.63;

SD=1.29); “feel like a part of family” (M=3.87; SD=1.27); and “feel a strong sense of

belonging” (M=4.01; SD=1.27). These three items loaded on one factor, which explained about

82.69 percent of shared variance. The resulting scale led to a Cronbach’s alpha of .89 (see Table

1 for descriptive statistics for all variables).

[Insert Table 1 here]

Positive affectivity, conceptualized as elevated emotional tone of the engagement state

(i.e., attention and energy), was measured with five items (Watson et al., 1988): “interested”


(M=5.48; SD=1.04); “attentive” (M=5.16; SD=1.14); “excited” (M=5.31; SD=1.14);

“enthusiastic” (M=5.39; SD=1.14)2; and “proud” (M=5.56; SD=1.17). The five items loaded on

one factor, which explained about 70.43 percent of shared variance. The resulting scale led to a

Cronbach’s alpha of .89 (See Table 1).

Finally, empowerment, conceptualized as self-efficacy and impact, was measured with

the modified five-item scale from Spreizer’s (1995) empowerment scale and Bandura (1977) and

Gist’s (1987) self-efficacy: “can make differences” (M=3.37; SD=1.25); “determined to develop

the org” (M=3.28; SD=1.27); “have a control over the org decision-making” (M=2.46; SD=1.23);

“confident about ability to improve the org” (M=3.00; SD=1.30); and “collaborate with the org”

(M=3.26; SD=1.37). These five items loaded on one factor, which explained about 69.65 percent

of shared variance. The resulting scale led to a Cronbach’s alpha of .89 (See Table 1).

The proposed thirteen-item scale of public engagement turned out to perform well with a

Cronbach’s alpha of .91. The proposed thirteen-item scale of public engagement retained three

theoretical dimensions clearly in exploratory factor analysis as shown in Table 2. The minimum

standardized factor loading was .66 in the item of “feel emotionally attached,” while

standardized factor loadings range from .66 to .87. (See Table 2 for the complete report). In

terms of validity, approximately 73 percent of total variance was extracted by the proposed

measurement system, suggesting this scale has sound explanatory power in explicating public

engagement.


Positive behavioral outcomes. The researcher defined the concept of positive behavioral

outcomes in two dimensions: loyalty and positive word-of-mouth intentions.


Loyalty, defined as supportive behavioral intention on the basis of perceived service

quality, was measured with the following four items modified from Zeithaml et al.’s (1996)

measure of supportive behavioral intentions: “my first choice to attend performances” (M=5.53;

SD=1.34); “attend more performances in the next few years (M=5.59; SD=1.16); “will continue

to attend performances if its prices increase somewhat” (M=5.46; SD=1.26); and “will continue

to attend performances even if experiencing a few problems” (M=5.30; SD=1.26). These four

items loaded on one factor, which explained about 59.51 percent of shared variance. The

resulting scale led to a Cronbach’s alpha of .77.

Positive word-of-mouth, defined as information communication directed at other

consumers about the organization and its service, was measured with the following four items

adopted from Brown et al.’s (2005) word-of-mouth (WOM) intentions: “encourage friends to

attend performances” (M=6.47; SD=.77); “encourage family members to attend performances”

(M=6.42; SD=.82); “recommend the org to someone who asks my advice” (M=6.42; SD=.81);

and “say positive things about the org and its performances to other people” (M=6.46; SD=.78).

These four items loaded on one factor, which explained about 87.48 percent of shared variance.

The resulting scale led to a Cronbach’s alpha of .89.

The proposed eight-item scale of positive behavioral outcomes turned out to perform well

in a Cronbach’s alpha of .88. Furthermore, the proposed eight-item scale of positive behavioral

outcomes retained two theoretical dimensions clearly in exploratory factor analysis. The

minimum standardized factor loading was .51 in the item of “my first choice to attend

performances,” while standardized factor loadings range from .51 to .92 (i.e., “encourage friends

to attend performances”).


Trust. Using existing measurement systems for trust from Morgan and Hunt (1994),

Ganesan (1994), and Hon and J. Grunig (1999), the researcher defined the concept of trust into

two dimensions: integrity and competency. Both dimensions have four measurement items.

Overall, research participants reported they have a higher level of competence (four-item

composite M=5.61; SD=.90) than integrity (four-item composite M=5.41; SD=.96).

To measure integrity, defined as the fairness and justice of the organization’s

management, the following four items were used: “treats patrons fairly” (M=5.85; SD=1.05);

“concerned about patrons” (M=5.10; SD=1.16); “sound principles guide management of the org”

(M=5.24; SD=1.10); and “does not mislead patrons” (M=5.46; SD=1.09). These four items

loaded on one factor, which explained about 75.33 percent of shared variance. The resulting

scale led to a Cronbach’s alpha of .89.

Additionally, to measure competence, defined as the extent to which individual patrons

believe the organization’s ability to achieve what is promised, the following four items were

used: “confident about service quality” (M=5.62; SD=1.00); “the org has ability to accomplish

what it says it will do” (M=5.50; SD=1.04); “the org is known to be successful” (M=5.65;

SD=1.01); and “competent in fulfilling patrons’ expectations” (M=5.67; SD=1.01). These four

items loaded on one factor, which explained about 79.05 percent of shared variance. The

resulting scale led to a Cronbach’s alpha of .91.

In terms of measurement reliability, the proposed eight-item scale of relational trust

turned out to perform well in a Cronbach’s alpha of .94. In exploratory factor analysis, the

minimum standardized factor loading was .74 in the item of “treats patrons fairly,” while

standardized factor loadings range from .74 to .86.


Satisfaction. Modifying Oliver’s (1980) measure of overall satisfaction and Hon and J.

Grunig’s (1999) measure of relational satisfaction, the researcher measured relational satisfaction

as a single dimension using three items. To measure relational satisfaction, defined as the overall

evaluation based on consumption experience with service over time, the following three items

were used: “generally speaking, pleased with the relationship with the org” (M=5.64; SD=1.01);

“satisfied with the org” (M=5.85; SD=1.08); and “delighted with the org” (M=5.51; SD=1.20).

These four items loaded on one factor, which explained about 85.01 percent of shared variance.

The resulting scale led to a Cronbach’s alpha of .91.

Statistical Procedures for Data Analysis

To analyze the data using structural equation modeling, a two-step process of latent path

modeling (Byrne, 2006; Hancock & Mueller, 2004)3 was conducted. The bootstrap procedure4

(1,000 samples) was used to generate a 95% confidence interval in testing the mediation effect of

public engagement for effects of trust and satisfaction on positive behavioral outcomes.

Statistical results were evaluated according to multiple data-model fit indexes5.

Data reduction. Before data analysis in SEM for hypotheses testing, the data was

reduced to composite variables using mean scores. For the merit of retaining the original

measurement units, mean composite scores were selected instead of factor scores. As shown in

Table 2, the variable of positive word-of-mouth support has the highest mean (M=6.44; SD=.74),

while the variable of empowerment has the lowest mean (M=3.08; SD=1.07). Correlations

among all nine tested variables are statistically significant at p < .001, ranging from r=.24

(Competence, Empowerment) to r=.81 (Integrity, Competence) (See Table 3).


Results


Confirmatory Factor Analysis (CFA)

To analyze the data using structural equation modeling, a two-step process of latent path

modeling (Byrne, 2006; Hancock & Mueller, 2004) was conducted. First, in the measurement

phase, the researcher conducted initial confirmatory factor analysis (CFA) by imposing a model

where all factors are allowed to covary. Then, as Figure 1 shows, the researcher modified the

initial CFA model by covarying error variance between affective commitment and empowerment

(r=.33; p < .001).

Data-model fits in the initial CFA model and the final CFA model are as follows:

1. Initial CFA model: Chi-square (15, n=1084)=168.20, p < .001, χ2/df=11.21,

SRMR=.04, TLI (NNFI)=.92, RMSEA=.10 (90% Confidence Interval: .08, .11),

and CFI=.97.

2. Final CFA model: Chi-square (14, n=1084)=95.46, p < .001, χ2/df=6.82,

SRMR=.02, TLI (NNFI)=.95, RMSEA=.07 (90% Confidence Interval: .06, .09),

and CFI=.98 (see Figure 4-1).

3. Nested model comparison: Δ χ2=72.74, Δ df=1, p < .01.

By this modification, data-model fits were substantially improved (Δ χ2=72.74, Δ df=1, p

< .01). Based on the Hu and Bentler’s (1999) joint-cutoff criteria6, the final CFA model can be

retained as a valid model: CFI is larger than .96; SRMR is smaller than 1.0. Factor loadings in

the final CFA model range from .42 (from public engagement to empowerment) to .93 (from

relational trust to competence). Average variance extracted (AVE) has the largest value in

relational trust (AVE=.82; alpha=.94), while public engagement has the lowest value (AVE=.46;

alpha=.91). All factor loadings were statistically significant at p < .001.

[Insert Figure 1 here]


In terms of factor correlations, the range of the correlations expanded from .69

(Relational Trust, Public Engagement) to .83 (Relational Satisfaction, Relational Trust). All

factor correlations are statistically significant at p < .001 (See Table 4). As previously noted,

there was one covaried set of error variances between affective commitment and empowerment

(r=.33, p < .001).


Structural Model Analysis: Testing Hypotheses

Hypothesis 1: Effect of trust on public engagement. H1 posited relational trust between

individual patrons and the organization would lead to enhanced public engagement with the

organization. This hypothesis was supported: B=.48, S.E.=.06, β=.50, p < .001. This path turned

out to have the largest effect size among all relations of variables imposed in this study (see

Table 5).


Hypothesis 2: Effect of trust on positive behavioral outcomes. H2 posited relational trust

between individual patrons and the organization would lead to publics’ positive behavioral

outcomes to support the organization studied. The result partially supported this hypothesis. As

shown in previous Table 3, in the baseline model (with mediation of public engagement), effect

of trust on publics’ positive behavioral outcomes was statistically significant: B=.22, S.E.=.05,

β=.24, p < .001. However, as the researchers posited in RQ1 (i.e., mediation effect of public

engagement), due to a strong full mediation of public engagement, this effect became

insignificant—to almost null/independent—in the mediated model: B=.04, S.E.=.06, β=.04, ns.

Thus, it is noteworthy that public engagement strongly mediated the effect of relational trust on

publics’ positive behavioral outcomes to support the organization studied.


Hypothesis 3: Effect of satisfaction on public engagement. H3 posited relational

satisfaction between individual patrons and the organizations studied would increase public

engagement with the organization. This hypothesis was supported: B=.19, S.E.=.05, β=.23, p

< .001.

Hypothesis 4: Effect of satisfaction on positive behavioral outcomes. In addition to H3,

H4 posited relational satisfaction between individual patrons and the organizations studied would

lead to publics’ positive behavioral outcomes to support the organization studied. This

hypothesis was supported: B=.38, S.E.=.04, β=.50, p < .001. As in the path from relational trust

to public engagement, this path turned out to have a strong effect size. In both the baseline model

and mediated model, the effect of relational satisfaction on positive behavioral outcomes

remained statistically significant: β=.59 in the baseline model (p < .001); β=.50 in the mediated

model (p < .001).

Hypothesis 5: Effect of public engagement on positive behavioral outcomes. H5 posited

public engagement with the organizations studied would lead to positive behavioral outcomes to

support the organization. This hypothesis was supported: B=.37, S.E.=.05, β=.39, p < .001.

Testing RQ1 (Mediation Analysis of Public Engagement)

To the question of a mediation of public engagement, two structural models were

compared in a hierarchical/nested relation in terms of the χ2-df test: a model with structural paths

from public engagement and another model (i.e., the baseline model) without such paths, to

examine if the mediation model is statistically better than the baseline model.

The mediation model turned out to perform substantially better than the baseline.

According to Hu and Bentler’s (1999) joint-cutoff criteria, the baseline model is not acceptable:

χ2 (18, n=1084)=611.78, p < .001, χ2/df=33.99, SRMR=.25, TLI (NNFI)=.73, RMSEA=.18 (90%


Confidence Interval: .25, .18), and CFI=.86. Across all data-model fit criteria, it is clear that the

baseline model without mediating paths via public engagement is not tenable as a valid model.

However, when mediating paths via public engagement were added into the baseline model, its

performance was significantly improved so as to be retained as a valid model: χ2 (14,

n=1084)=95.46, p < .001, χ2/df=6.82, SRMR=.02, TLI (NNFI)=.95, RMSEA=.07 (90%

Confidence Interval: .06, .09), and CFI=.98. Thus, although the baseline model is more

parsimonious by 4 df (Δ df=4), the mediation model should be selected as a better model: 2change

(4, n=1084)=516.32, p < .001.

Also, the bootstrap procedure (1,000 samples) was used to generate a 95% confidence

interval, testing the mediation effect of public engagement for effects of trust and satisfaction on

positive behavioral outcomes. As previously noted, this study found a strong mediation of public

engagement between relational trust and positive behavioral outcomes: β=.20 (95%

interval: .13, .25), p < .01. The results suggest that the direct link between trust and positive

behavioral outcomes (β=.24, p < 001) were fully mediated by public engagement (β=.04, ns).

Even though the effect was not as much strong, the study also found a mediation of public

engagement between relational satisfaction and positive behavioral outcomes: β=.09 (95%

interval: .09, .04), p < .01.

Discussion

Contemporary public relations practice has increasingly emphasized the notion of public

engagement due to the changing nature of publics’ active communication behaviors and higher

expectations to collaborate with organizations. The discussion of engaged publics and their

potential influence on organizational success is especially pertinent in the era of social media.


With the emergence of social media, publics have increasingly utilized this new form of active

communication as a critical tool of engagement with organizations (e.g., Breakenridge, 2008;

Scott, 2007; Weil, 2006). Public relations research can benefit by being more reflective of

changes in the nature of publics who expect and demand organizations’ efforts to acknowledge

the essentiality of publics’ collaborations for the success of organizations. In this new public and

media environment, the success of organizations is largely affected by systematic, strategic

organizational efforts to engage publics as the integral part of organizational operations.

Publics are no longer content to be onlookers in public discourses. Rather, they actively

seek ways to be legitimate participants and to exert an influence. This entails both potential

benefits and problems to organizations, depending on how they manage their public relations

efforts with their key publics. In current public relations practice, the notion of engagement has

received a great deal of attention as the ultimate way to connect with publics. This study

introduced the concept of public engagement as the focal concept that connects the voids in

previous organization-public relationship research.

The goal of this dissertation was to (a) propose the concept of public engagement as an

essential component of public relations management that connects organization-public

relationships and public’s supportive behaviors. To that end, I conceptualized public engagement

in the context of public relations and measured public engagement using three indicators:

positive affectivity, affective commitment, and empowerment. More specifically, this study

defined the concept of public engagement as an affective connector that bridges two key

relational concepts (i.e., satisfaction and trust) and the subsequent publics’ supportive behaviors.

The introduction of public engagement as a predominantly affective concept that connects the

cognitive experiences to the more affective concept of loyalty and positive referral


communication behaviors demonstrates the importance of fostering intimate relationships with

the publics that are not just characterized by cognitive beliefs and assessments of relationship

quality. Identifying engagement with three core dimensions of affective commitment, positive

affectivity, and empowerment, the current study suggested reliable ways to measure public

engagement with 13 items. The proposed 13-item scale of public engagement had sound

reliability and validity and retained three theoretical dimensions clearly in exploratory factor

analysis.

This study also found significant mediation effects of public engagement between two

key relationship variables (i.e., relational trust and satisfaction) and positive behavioral outcomes

(i.e., loyalty and positive WOM support). The baseline model without public engagement turned

out to perform poorly with acceptable data-model fits. When public engagement was added into

the baseline model, this mediation model became tenable as a valid model across multiple data-

model fit indexes. The mediation analysis revealed that public engagement performed strong—

almost full mediation—mediation in effects of relational trust on publics’ positive behavioral

outcomes with significant mediation effect size.

This finding supports public engagement as being critical for linking public’s positive

evaluation of relationships with an organization to their actual supportive behaviors. The current

OPR literature is lacking in this regard. The main focus of relationship research has been limited

to examining the direct relationships between relationship indicators (namely, satisfaction, trust,

commitment, or/and control mutuality) and positive attitudes or supportive behaviors. This study

supports that publics’ cognitive evaluations of relationship quality (high level of satisfaction and

trust) are necessary conditions for publics to act out their beliefs on organizations to support the

organizations. However, the results support the introduction of public engagement in the model


is an important affective connector bridging the cognitive evaluations to publics’ supportive

actions. These findings indicate that publics’ supportive behaviors can be much more likely to be

created and further enhanced when they were affectively engaged with organizations.

Implications

Findings of the current study can offer insights on explication and operationalization of

engagement, which can be incorporated into different practice contexts. Public relations

professionals can utilize the three dimensions of public engagement to test which area of

engagement is lacking in their current efforts to be connected with their key publics. More

importantly, the results of this study indicate that organizational efforts can be most valuable

when they are focused on increasing public engagement by fostering positive feelings, affective

commitment, and a sense of empowerment. That is, getting satisfactory and reliable services or

goods is not sufficient for publics to become loyal with or an advocate for organizations. When

trust and satisfaction are present in the interactions between organizations and publics,

organizations have to work to develop a sense of a community that is centered on feelings such

as affection, pride, or empowerment. When publics become highly engaged with an organization,

their loyalty and supportive behaviors are likely to remain strong unless fundamental issues arise

with the organization that seriously undermine people’ level of trust and satisfaction.

Limitations and Future Research

Even though there are sound fits between data and the hypothesized structural model in

this study, it is still possible that the proposed model might have been misspecified to some

degree. Since a researcher cannot account for all potential causal elements in a hypothesized

model, the scope of this research had to be delimited into relational trust and satisfaction. This


study is only “exploratory” or “suggestive” in this regard; future studies can search for other

relevant precursors of public engagement than those used in this study.

There is also the issue of peculiarity of the organization studied. The organization in this

study has mixed characteristics of nonprofit and profit organizations and relies on financial

support from donors and loyalty from its patrons for its operation. To examine public

engagement in a valid, reliable manner, studying an organization with loyal/long-term donors

and patrons was essential. Nonetheless, the unique nature of the organization studied and the

sample might have influenced the results of this study and limit its general application across

different organizational contexts and stakeholders.

The scope of the current study was limited to the effects of trust and satisfaction on

loyalty and positive WOM that are mediated by engagement. However, it is important to note

that public engagement is not inherently a positive affect. In this study, consistent with how

engagement is conceptualized in organizational studies, engagement was viewed as the opposite

force of disengagement or burnout. For future study, the concept of public engagement can be

expanded to include negative aspects of engagement in its definition and measurement.

A future study can also include identification as an important factor in the overall

mediation model. Brand community literature supports individual customers’ degree of

identification with other members in the community might be an important factor that can affect

the effects of trust and satisfaction on the level of engagement. By examining social influence of

European car clubs, Algesheimer, Dholakia, and Herrmann (2005), for instance, noted that

individuals’ level of identification with the brand community brought out positive outcomes such

as increased engagement in brand community. Future research can further examine public-


organization identification in terms of its measurement or different model specification such as

effects of distrust or dissatisfaction on negative word-of-mouth behaviors.


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Table 1. Descriptive Statistics for Measurement Items on Public Engagement

Dimension Item (n) M SD α Variance

Extracted

Affective

Commitment

Feel emotionally attached (n=1011) 4.63 1.2

9

.89 82.69%

Feel like a part of family (n=1011) 3.87 1.2

7

Feel a strong sense of belonging (n=1002) 4.01 1.2

7

Positive Affectivity Interested (n=1008) 5.48 1.0

4

.89 70.43%

Attentive (n=1006) 5.16 1.1

4

Excited (n=1013) 5.31 1.1

4

Enthusiastic (n=1007) 5.39 1.1

4

Proud (n=994) 5.56 1.1

7

Empowerment Can make differences (n=1002) 3.37 1.2

5

.89 69.65%

Determined to develop the org (n=999) 3.28 1.2

7


Have a control over the org decision-

making (n=1002)

2.46 1.2

3

Confident about ability to improve the org

(n=997)

3.00 1.3

0

Collaborate with the org (n=992) 3.26 1.3

7


Table 2. Exploratory Factor Analysis for Measurement Items on Public Engagement

Factor Loading

Item EMa PA AC % α

1. Feel emotionally attached .66 19.11% .89

2. Feel like a part of family .87

3. Feel a sense of belongings .86

4. Interested .82 26.64% .89

5. Attentive .77

6. Excited .85

7. Enthusiastic .85

8. Proud .72

9. Can make differences .76 26.81% .89

10. Determined to develop the org .79

11. Have a control over the org decision-making .76

12. Confident about ability to improve the org .87

13. Collaborate with org .82

Total Variance Explained with overall α 72.56% .91

Note. Extraction method was Principal Component Analysis with Varimax rotation.

aEM=Empowerment; PA=Positive affectivity; AC=Affective commitment; %=Variance

extracted.


Table 3. Correlation Matrix of Measured Variables with Descriptive Statistics

Measured Variable M (SD) 1 2 3 4 5 6 7 8

1. Affective Commitment 4.17 (1.14) 1

2. Positive Affectivity 5.38 (0.94) .59 1

3. Empowerment 3.08 (1.07) .50 .36 1

4. Loyalty 5.55 (0.97) .44 .47 .27 1

5. Positive WOM support 6.44 (0.74) .34 .51 .14 .60 1

6. Integrity 5.41 (0.96) .49 .48 .27 .54 .45 1

7. Competence 5.61 (0.90) .45 .52 .24 .53 .50 .81 1

8. Satisfaction 5.67 (1.02) .47 .53 .26 .61 .61 .73 .77 1

Note. Correlations for all variables are significant at p < .001.

Table 4. Correlations between Factors and Error Variances in the Final Confirmatory Factor Analysis (CFA) Model (n=1084)

Correlated Factor/Error Variance r

Relational Trust Public Engagement .69

Positive Behavioral Outcomes Relational Trust .73

Positive Behavioral Outcomes Public Engagement .75

Relational Satisfaction Relational Trust .83

Relational Satisfaction Public Engagement .65

Relational Satisfaction Positive Behavioral Outcomes .79

Error Variance of Affective Commitment Error Variance of Empowerment .33

Note. All standardized coefficients are significant at p < .001.


Table 5. Standardized Coefficient of Direct Effects in the Hypothesized SEM Model (n=1084)

Independent Factor Dependent Factor H B S.E. β C.R.

(Z)

Baseline Model

Relational Trust → Positive Behavioral Outcomes .22 .05 .24***

Relational Satisfaction → Positive Behavioral Outcomes .44 .04 .59***

Mediated Model

Relational Trust → Public Engagement H

1

.48 .06 .50*** .72

Relational Trust → Positive Behavioral Outcomes H

2

.04 .06 .04

Relational Satisfaction → Public Engagement H

3

.19 .05 .23*** .47

Relational Satisfaction → Positive Behavioral Outcomes H

4

.38 .04 .50***

Public Engagement → Positive Behavioral Outcomes H

5

.37 .05 .39***

Note. *p < .05, **p < .01, ***p < .001.


Figure 1. The results of the final measurement model with standardized path coefficients.

Note: χ2(14, n=1084)=95.46, p<.001, SRMR=.02, TLI (NNFI)=.95, RMSEA=.07 (90%

Confidence Interval: .06, .09), and CFI=.98. All paths are significant at ***p < .001.


Endnote

1The researcher conducted a full-scale pretest before the survey in this study. The researcher administered a pretest of the proposed survey questionnaire to check the validity and reliability of survey measurement instruments to 594 individual members of a nonprofit organization (n=594) in the United States. This pretest clearly demonstrated sound levels of measurement reliability and validity for all key variables and found supports for all hypotheses. Therefore, no measurement instrument was modified for the actual data collection.2Since there were approximately three times more female research participants (n=721, 73.90 percent) than male participants, the researcher tested possible gender differences in the measurement items of public engagement, using Independent-Samples T test. The results indicate that female participants in general reported higher levels of positive affectivity and empowerment than male participants. In case of affective commitment, male participants reported higher level of engagement than female participants. However, such gender differences were found to be statistically insignificant except only in the item of “enthusiastic” in positive affectivity, t(962) = -2.26, p < .05.3First, in the measurement phase, the researcher conducted initial confirmatory factor analysis (CFA) by imposing a model where all factors are allowed to covary. Because the data-model fit for the initial measurement model was satisfactory, the researcher went to the structural phase. Second, in the structural phase, the researcher compared the CFA model with the proposed structural model in terms of data-model fits.4The bootstrapping method allows to correct non-normality/bias of the data, using repeated random sampling observations with replacement from the data set and computing the statistic of interest in each resample. In this case, using the original data set as a population reservoir, a pseudo (bootstrap) sample of N = 1,000 persons was created by random sampling observations with replacement from the data set. Then, on the replaced pseudo (bootstrap) sample (N = 1,000), an empirical approximation of the sampling distribution of the statistic was generated and used for hypothesis testing. This bootstrapping method will give the researcher the significance level of each mediation effect, along with the 95% bias-corrected confidence interval.5According to Byrne (2006), Hu and Bentler (1999), and Kline (2004), a structural equation model can be valid when (1) the value of χ2/df is less than 3; (2) the value of CFI (Comparative Fit Index) is equal to or greater than .95; and (3) the value of RMSEA (Root Mean Square Error of Approximation) is less than .08.6Hu and Bentler (1999) developed joint-cutoff criteria for fit indexes in a structural equation model (SEM), which can be useful to test a tenable data-model fit. According to them, a SEM model with CFI (i.e., Comparative Fit Index) ≥ .96 and SRMR (i.e., Standardized Root Mean Square Residual) ≤ 1.0 or RMSEA (i.e., Root Mean Square Error of Approximation) ≤ .06 and SRMR ≤ .10 can suggest that the fit between the data and the proposed model is tenable.

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