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Fazal-E-Hasan, Syed, Ahmadi, Hormoz, Kelly, Louise, & Lings, Ian(2019)The role of brand innovativeness and customer hope in developing onlinerepurchase intentions.Journal of Brand Management, 26(2), pp. 85-98.

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https://doi.org/10.1057/s41262-018-0122-4

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The Role of Brand Innovativeness and Customer Hope in Developing Online

Repurchase Intentions

ABSTRACT: This study considers the role of customer hope in the online purchasing

environment. It presents a model which positions customer-perceived brand innovativeness

as an antecedent to customer hope, and customer brand satisfaction as a consequence of

customer hope and as a predictor of repeat purchase intentions. The model was tested using

survey data from 418 Australian respondents. The results suggest a potential moderating

effect of product knowledge on the relationship between perceived brand innovativeness and

customer hope. For marketing theorists, specifically those interested in online marketing, the

study advances knowledge of how customers’ perceptions of brand innovativeness are

contingent on their emotions (hope), attitudes (brand satisfaction) and behaviours (brand

repurchase intentions). For managers, our study provides useful insights for investing in

innovative brands to stimulate repeat purchase intentions in an online setting.

On behalf of all authors, the corresponding author states that there is no conflict of interest.

Keywords: Brand innovativeness; customer hope; brand satisfaction; repurchase intentions;

product knowledge

INTRODUCTION

In recent years online purchasing has grown significantly, and advances in technology have

made purchasing online considerably quicker and easier (Rosqvist and Hiselius, 2016). This

online revolution has changed the way that brands engage and interact with their customers,

and increasing competition has seen the need for marketers to better understand the importance

of customer perceptions and emotional responses when purchasing online (Rosqvist and

Hiselius, 2016; Colton, 2012). Now more than ever, customers are empowered to search and

2  

analyse information related to a brand (Boyd et al, 2014), and when purchasing online they

draw upon their perceptions of and emotional responses to the brand. These emotional

responses influence brand satisfaction, which drives purchase behaviour. For most firms the

shift towards selling branded products online is inevitable. By 2021 retail e-commerce sales

are predicted to comprise 10.1 per cent of all retail sales globally, representing US$4.479

trillion (Disrupt-africa, 2017). With retail business models becoming more dependent upon

online sales, marketers need to understand the consumer determinants of online purchasing and

repurchase intention. As technology becomes ubiquitous and customers’ online experiences

become less differentiated, the capacity for brands to innovate by offering unique features and

value becomes crucial to their ongoing success (Nedergaard and Gyrd-Jones, 2013). It is also

evident that, given the rapid global expansion of e-commerce technologies, customers are more

knowledgeable and more demanding of their online retailers. A customer’s emotional response

to a brand takes on heightened significance in their decision making, given that the customer

is unable to touch, feel and physically assess the product (Liu et al, 2017).  

Advances in technology and online retailing mean that brands need to be perceived by

their customers as innovative to be competitive (Colton, 2012). Customer-perceived brand

innovativeness is defined as customers’ perceptions of unique brand features of value

(Alexander and Van Knippenberg, 2014; Shams et al, 2015). Studies on brand innovativeness

highlight its importance in the customer–brand relationship (Jensen and Beckmann, 2009)

through its influence on attitudes, emotions and behavioural intentions (Fournier and Alvarez,

2013). At the firm level, customers’ perceptions of brand innovativeness are shown to

increase brand performance, maintain brand strength (Nedergaard and Gyrd-Jones, 2013) and

provide competitive advantage (Sujchaphong et al, 2015). In this study we examine how

consumers’ perceptions of brand impact on their emotional connection to the brand, namely

customer hope. The concepts of ‘hope’ and ‘expectations’ have often been mentioned in the

3  

psychology literature and, while they may be interrelated, they are considered as distinct

constructs. Hope is defined as the emotional response to derive pathways to desired goals,

and motivate oneself via agency thinking to use those pathways (Snyder, 2000). Expectation

is defined as a desire that can be fulfilled without setting any definitive purchase-related goal

and without any related action tendency (Stajkovic, 2006). Hope implies that customers know

about their goals, feel motivated to purchase (agency) a product/service and identify the ways

to make their purchase a positive experience, resulting in satisfaction (Locke and Latham,

2002). On the other hand, expectations refers to customers’ probability-driven assessment of

the likelihood that certain outcomes will result from the purchase (Dowling and Rickwood,

2016). Therefore, expectation is similar to the agency component of hope, but does not

consider the pathways by which desired outcomes may be achieved (Snyder, 2000).

When making a purchase customers often seek cues related to brand features, such as

brand name, price, variety, style, country of origin, recommendations, delivery time,

supplementary services, ease of use and usefulness (Batt and Dean, 2000). Notwithstanding

this information seeking and evaluation, the emotional mechanisms through which customers

feel satisfied with their purchase experience and become willing to repurchase the brand

online have received little attention. While the model developed and tested in this study could

potentially be useful for offline settings, the online setting has unique characteristics that

make the role of hope more prescient. In particular, in the online setting customers are unable

to touch, feel and physically assess the product, so they may rely on hope for a successful

outcome more than in a traditional bricks-and-mortar setting. For this reason, we develop and

test the model specifically for the online context.

This paper extends Snyder et al’s (2002) work by incorporating the concept of hope into a

model of online consumption. As such, it contributes to the digital marketing and consumer

4  

behaviour literature regarding brand satisfaction and repurchase intentions. The work also

contributes to practice by providing insights into consumer behaviour involving the sale of

innovative brands in the online context.

This study investigates the role of customer hope, its relationship with perceptions of

innovativeness and its impact on customer brand satisfaction. While studies have focused the

customer’s emotional connection and passion towards a brand or trade name (Roy et al, 2013;

Carroll and Ahuvia, 2006), and the impact of brand attachment (Batra et al, 2012), the role of

customer hope in the purchase process remains poorly understood. When a customer makes an

online purchase their hope for a positive outcome is an important determinant of their

behaviour. In comparison to in-store purchasing, where products can more easily be evaluated

physically, online purchasing requires a higher level of hope that the purchasing process will

bring a positive outcome such as brand satisfaction for the customers. Furthermore, online

purchasing is inherently riskier and requires energy and techniques to overcome these risks.

Hope may allow customers to approach purchasing problems with a mindset and strategy-set

suitable to success, thereby increasing the chances they will be satisfied with their purchase.

Some previous studies have highlighted the role of hope in customer choices (Poels and

Dewitte, 2008; Kim et al, 2012), enhancing self-regulatory outcomes and ceasing maladaptive

consumption practices (MacInnis and De Mello, 2005). Hope has been shown to be related to

advertising and product evaluation, choice of medicines, cosmetics, pharmaceuticals,

healthcare and magazine brands (Poels and Dewitte, 2008; MacInnis and De Mello, 2005).

Despite this work, the role of hope in explaining the effects of the more general construct of

customer-perceived brand innovativeness (where the consumer perceives unique

characteristics of value in a product) in purchase experiences, such as brand satisfaction and

repurchase intentions, has not been addressed. While studies show that customers will purchase

innovative brands to attain functional and social value (Sweeney and Soutar, 2001), our

5  

understanding of which mechanism will lead to the belief that the brand has provided functional

and social value remains limited. Two psychological mechanisms – hope and satisfaction –

may provide insight that is useful to understand when and how investments in brand innovation

are effective.

In an online setting consumers’ experience of hope about brand satisfaction is likely to

depend on their product knowledge. Product knowledge is defined as the sum of product class

information (attributes, functions and features) and rules stored in an individual's (customer’s)

memory (Philippe and Ngobo, 1999). Previous research highlights the moderating role of

knowledge of a product that customers purchase online on the relationship between a firm’s

strategies and customer consumption experiences (Nepomuceno et al, 2014). Customers with

high product knowledge are more confident of the brand and its value in comparison to other

competing alternatives. On the other hand, customers with low product knowledge purchase

the brand with higher risk and uncertainty, which may hinder the confidence that the perceived

value will be actualised. Consequently, this study focuses on the positive moderating role of

product knowledge on the relationship between customer-perceived brand innovativeness and

hope.

This research examines customer hope in the context of online innovative brand

consumption. Specifically, this study develops and tests a model to shed light on the

psychological mechanisms that influence the experience of consuming innovative brands.

Although prior research has been undertaken on brand innovativeness (O’Cass and Carlson,

2012), customer hope (Snyder, 2000) and brand satisfaction (De Wulf et al, 2001) separately,

this is one of the first studies to test the inter-relationships of the constructs mentioned above

using theories from brand innovation and positive emotion literature. The next section reviews

the literature that guides the conceptual model.

 

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THEORETICAL BACKGROUND AND HYPOTHESES DEVELOPMENT

The internet has changed the way marketers reach customers and how customers purchase

products and services. Customers now have access to vast amounts of brand information,

enhancing their ability to research brands and make informed purchasing decisions (Denegri‐

Knott, 2006). All purchases aim to achieve certain outcomes (i.e., satisfaction) and have the

potential for positive or negative outcomes depending on the interaction with the firm and

experience of the brand.

Consumers’ goal-directed energy and their plans to attain these goals – known as hope –

motivate them to think about the future purchase (Snyder et al, 1991; Bowman, 2013;

Youssef and Luthans, 2007). Snyder et al (1991) state that the agency component of hope

provides the ‘willpower’ to achieve goals, whereas the pathways component promotes ‘way

power’, which is necessary for producing alternative paths. The emotional status of hope is

deemed appropriate for this study given that we are interested in customers’ levels of hope

for satisfactory performance of an innovative brand (Snyder, 2000). In the online context, the

consumer cannot physically evaluate the product, neither do they have extensive tangible

cues to signal the quality of the retailer. This, in conjunction with the nature of innovative

products where unique attributes are linked to unique value, means that consumers are not in

a position to develop solid expectations as they have limited information on which to form

such views. They can, however, hold views about the desired outcome and how to achieve it,

and this desire is represented by hope.

Psychology literature differentiates hope and expectation in the following manner.

Expectation refers to a desire which can be fulfilled without setting any definitive goal and

without any related action tendency (Stajkovic, 2006). Some studies (Youssef and Luthans,

2007) have labelled expectation as passive hope, as opposed to active hope, which is

consistent with the view that has been promoted by Snyder and his colleagues (2002) as well

7  

as by this current study. Therefore, hope implies that a person knows about their goal (the

desired outcome), agency (level of motivation to achieve the desired outcome) and pathways

(different ways to achieve the desired outcome) (Locke and Latham, 2002).

For instance, following the examples presented earlier, a customer may be deeply

motivated (has high agency) to attain social status (goal) by purchasing an innovative brand,

and they may be aware of several different ways to purchase the innovative brand (i.e.

pathways to buy that innovative brand). Examples of pathways could include lay-by options,

instalment plans or quick-delivery options. In this case, the customer is likely to experience

high levels of hope for ultimately achieving their goal (social status). In contrast, if a

customer is less motivated (has low agency) to attain social status they are unlikely to pursue

different options to buy a brand; that is, they will have low pathways thinking. Likewise, if a

highly motivated customer (high agency) cannot think of different ways to achieve their goal

(i.e., has low pathways thinking) they may have little hope of achieving the desired outcome

(in this example social status); such consumers want to achieve the outcome but cannot see

how and so have less hope.

Antecedents to hope

Customers’ perceptions of brand innovativeness

Innovation has been highlighted as a critical foundation for sustainable business growth and

market-based advantages (Vincent et al, 2004). While innovation is a broad topic and has been

conceptualised differently across the marketing, management and entrepreneurship disciplines

this research focuses on customer-perceived brand innovativeness, which is defined as

customers’ perceptions of a brand with unique features of value (Alexander and Knippenberg,

2014; Shams et al, 2015).  

8  

Given the growing global online marketplace (Rosqvist and Hiselius, 2016) and the

existence of conversant online customers, progressive firms invest an enormous amount of

resources to develop customers’ perceptions of their brands as innovative (Colton, 2012).

Previous research shows that customers often purchase innovative brands to establish social

identity, showing off their status and attaining other social goals (Perry-Smith and Mannucci,

2017). Brand innovativeness represents the unique characteristics of a product or service that

are of value to the customer. From an online purchaser’s perspective these novel attributes

denote the likelihood of attaining goal-congruent outcomes. Hence, online marketing

strategies that infer the possibility of goal-congruent innovations in an online brand may

stimulate consumer hope for attaining a goal, such as positioning oneself as a technology-

savvy person. Highlighting the positivity of the customer–brand relationship, Fournier and

Alvarez (2013) draw upon the appraisal theory of emotions (Roseman et al, 1990). Appraisal

theory of emotions posits that customers’ perceptions of self-caused positive experiences

stimulate positive emotional responses such as pride and confidence. On the other hand,

other-caused positive experiences are likely to lead to positive emotional responses such as

gratitude and hope (Roseman et al, 1990). In the context of a firm’s relationship with an

online market, customers’ perceptions of the innovativeness of a firm’s brand are likely to

influence their goal-directed energy, requiring customers to develop pathways to achieve the

satisfactory purchase. If the online purchaser finds the innovative brand novel and unique and

able to satisfy their goal-oriented outcomes they are likely to experience hope for attaining

their goals. Thus, we hypothesise that:

H1: Customer-perceived brand innovativeness has a positive impact on customer hope in

online purchases.

Moderating effect of product knowledge

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While research has increasingly focused on the relationship between perceived brand

innovativeness and brand-related purchase outcomes (Boisvert and Ashill, 2011), there is a

need for further investigation to identify the factors that foster the impact of perceived brand

innovativeness on customers’ positive emotions, such as hope, in an online context. Previous

research demonstrates that moderating factors such as product knowledge may enhance the

explanatory power of the empirical models (Dabholkar and Bagozzi, 2002; Carlson et al, 2007).

Brands – especially in online environments – often have to deal with customer heterogeneity.

One of the main differences amongst online customers is their higher or lower level of

knowledge about the product sold online (Liao et al, 2012). Primarily this is because customers

cannot physically evaluate online products.

Studies show that the level of customers’ product knowledge plays a vital role in forming

their expectations of product performance and their loyalty towards a brand (Bennett et al,

2005). Customers’ existing knowledge of a product or service may be denoted by the level of

‘familiarity’, ‘experience’ or ‘expertise’ about a value offering. Online customers with high

product knowledge (perhaps through previous experience with a prior iteration of the product

or competing product) are expected to be more capable of analysing and processing the

information about an innovative online brand and its unique features and so have a better

understanding of the brand’s level of innovativeness (Eisingerich and Bell, 2008), resulting in

a higher level of confidence with the innovative brand. Therefore, it is also likely that customers

with high a priori knowledge experience higher levels of hope, because they feel more

motivated to use the innovative brand to achieve their goals and believe that by doing so they

will satisfy their goals. Customers with lower a priori levels of product knowledge feel less

confident about a brand’s innovativeness (unique features of value), resulting in a lower

motivation to use the innovative brand to achieve their goals and less certainty that by doing

so they will satisfy their goals. Customers with little or no a priori product knowledge may

10  

assume that the innovative brand is not much different from other brands and online options

and may not recognise unique features of value and, consequently, have little motivation to use

the innovative brand to achieve their goals and low certainty that by doing so they will satisfy

their goals. Hence, we hypothesise that:

H2: Product knowledge positively moderates the relationship between perceived brand

innovativeness and hope in online purchases.

Consequences of customer hope

In all purchases, the customer’s primary goal is to be satisfied with the brand that they

purchase (Thirumalai and Sinha, 2009). Overall brand satisfaction is based on consumers’

experiences with the purchasing process and refers to their level of cognitive response to the

process (Oliver, 1993). It has been suggested that customers may feel satisfied when the

brand’s perceived benefits increase in comparison with the perceived associated efforts; when

expectations or benefits are met or exceeded consumers will be satisfied (Agnihotri et al,

2016). Factors that determine the level of anticipated benefits in the online purchasing

context include product information, convenience, perceived risk and positive emotions (such

as hope). Equity theory (Hatfield et al, 1979) goes some way towards explaining the role that

customer hope has in satisfaction. Customers’ anticipated gains and costs in the online

exchange are important. Simultaneously a customer needs some motivation and an action

plan for experiential value to ensure they experience brand satisfaction. This argument

therefore leads to the following hypothesis:

H3: Customer hope has a positive impact on customers’ brand satisfaction in online

purchases.

The consequence of customer brand satisfaction

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Customer repurchase intentions

Customers’ repurchase intentions are defined as customers’ desire to buy a brand again in

anticipation that they will gain the same or better value from the purchase of an online brand

(Louro et al, 2005). The valence approach of satisfaction (Bagozzi et al, 2000; Lerner and

Keltner, 2000) suggests that customers’ behaviour can be determined by their positive or

negative valence. Customer satisfaction is a gain that is positively valenced and encourages

customers to purchase the brand again if the need arises to maximise the gain. Furthermore,

repurchase intentions from perceptions of being satisfied with the brand may result in

peripheral information processing. Thus, brand satisfaction enables customers to infer a

positive outcome from further interactions with the firm in the online environment, and

therefore they may purchase the brand again for their future use. Previous studies have

investigated the link between customer satisfaction and brand repurchase (Anderson and

Sullivan, 1993; Huang et al, 2014; Napitupulu and Aditomo, 2015); however, it is important

to consider the impact that hope has on the online purchasing process. Customer satisfaction

is impacted by not only the level of satisfaction with the product but also with the purchase

and consumption processes (Heitmann et al, 2007).

The elaboration likelihood model of persuasion (Petty and Cacioppo, 1986) suggests that

changes in cognition-focused attitudes and intentions, such as repurchase intentions, occur

due to either evaluative judgments or simple inferences about personal outcomes. Customer

brand satisfaction as a consequence of a positive emotional response of hope develops a sense

of advantage and benefit within a customer. Customers may perceive that switching over to

another online brand may deprive them of future benefits and cause them to incur higher

switching costs than benefits. These perceptions of anticipated loss stop them from buying

alternative online brands. Consequently, customers intend to maintain their inertia for staying

12  

in the gain domain and are more likely to repurchase the same brand in online settings.

Therefore, we hypothesise that:

H4: Customer brand satisfaction has a positive impact on repurchase intentions of a

brand in online purchases.

A model is developed by bringing these hypotheses together (see Figure 1). The model

describes the impact of customer-perceived brand innovativeness on customer hope, which

leads to customer brand satisfaction. The model further illustrates the effects of customers’

brand satisfaction on their brand repurchase intentions. A customer’s product knowledge is

posited as having moderating effects on the relationship between a customer’s perception of

brand innovativeness and customer hope.

<INSERT FIGURE 1 ABOUT HERE>

METHODOLOGY

The data were collected from participants who were screened to ensure they were online

shoppers. The data were not gathered for a specific brand, as the aim of the research was to

develop a framework to examine the role of psychological mechanisms that help customers

attain positive consumption experiences through the purchase of brands from online retailers.

A survey-based method was deemed appropriate to examine the relationships between the

variables in the model. A professional market research firm was recruited to collect data from

its panel. The data were obtained via an online survey, administered to 418 Australian

customers who were above 18 years old and who had purchased a brand online within the last

30 days. Two screening questions were used, asking respondents to consider their choices of

13  

brands and their emotional responses to those online brands, rather than their perceptions of

general products:

1) Have you purchased a branded product online in last 30 days?

2) Which category type does that last brand that you purchased online fall under?

An email invitation was sent to respondents explaining the nature of the study and the

ethical considerations, together with a link to the online survey. To reflect the context of the

research (online shopping), respondents were asked to answer questions relating to their

shopping experience with online retailers.

Participants were asked to ‘recall their last online purchase of a brand’ and then responded

to a series of multi-item Likert measures on a seven-point scale, ranging from strongly disagree

(1) to strongly agree (7), to capture the constructs studied: customer-perceived brand

innovativeness, customer hope, customer brand satisfaction, customer repurchase intentions

and product knowledge. Two variables, internet consumption and purchase frequency, were

also taken as control variables to avoid high and low consumption variance (bias). The scales

for all constructs were adapted from instruments developed by other researchers. All the

measurements for the major constructs in the research were reflective.

The study sample comprised 51.2 per cent females and 48.8 per cent males. They were

divided into five age categories: 18–25 (14.8%), 26–35 (18.7%), 36–50 (28.5%), 51–65 (22%)

and above 65 (16%). The majority of respondents held undergraduate or higher qualifications

(57.9%). They reported their internet usage on a weekly basis: less than 5 hours (6.5%), from

5 to 15 hours (41.1%) and more than 15 hours (52.4%). When completing the survey

respondents were instructed to recall the last brand they purchased online. Scale items were

both positively and negatively worded in order to minimise acquiescence bias. Further, similar

items were dispersed throughout the questionnaire, and temporal separation between the

measurement of the predictors and criterion variables was managed (Podsakoff et al, 2012).

14  

Perceived brand innovativeness was measured using seven items from O’Cass and Carlson

(2012). Product knowledge was measured by adapting five items from Carlson et al (2017).

For customer hope, we adapted three items from Snyder (1995). Brand satisfaction was

measured using four items from De Wulf et al’s (2001) scale. To measure brand repurchase

intentions we adapted three items from Eggert and Helm (2003).

Post-hoc, Harman’s one-factor test was conducted to ascertain the absence of common

method bias. The results revealed that the variance explained by a single factor was 46.6 per

cent, lower than a threshold of 50 per cent, suggesting that common method variance was not

an issue. Mattila and Enz (2002) suggest that the techniques employed to minimise

acquiescence bias (i.e., wording questions positively and negatively), and Harman’s one-factor

test provide support for the absence of these general method biases in the findings.

ANALYSIS

Analyses were conducted with structural equation modelling (SEM) using AMOS 24.

Following a two-step analytical procedure (Hair et al, 2006), the measurement model was

first evaluated and the structural model was then assessed. The rationale for this two-step

approach was to ensure conclusions emanating from structural relationships were drawn from

a set of measurement instruments with desirable psychometric properties (Hair et al, 2006).

This approach provides a solid foundation for making meaningful inferences about the

constructs in the research models and the relationships between them (Gerbing and Anderson,

1988).

Measurement validation

Confirmatory Factor Analysis (CFA)

15  

Psychometric properties of the constructs were evaluated by conducting a CFA using AMOS

24 on the dataset. The fit of the CFA for Australian data is acceptable, with χ2=490.748 df=

199, χ2/df = 2.466, (p < .01), comparative fit index (CFI) = 0.949, standard root mean square

residual (SRMR) = 0.044, Incremental fit index (IFI) = 0.949 and root mean square error of

approximation (RMSEA) = 0.059. Considering all these goodness of fit measures, the models

adequately fit to the data from the sample. Table 1 shows that the values of Inter-Item

Consistency (α) and Composite Reliability scores of all constructs were above the

recommended cut-off (i.e. 0.70), demonstrating good reliability (Nunnally and Bernstein,

1994).

Table 1 demonstrates that all item loadings are significant (p < .01), in support of

convergent validity (Gerbing and Anderson, 1988). On the other hand, the AVE of all

constructs is greater than the threshold score (i.e. 0.50), except customer hope (0.49). Both

tests ensure convergent validity.

<INSERT TABLE 1 ABOUT HERE>

Inspection of the inter-factor correlation matrix further revealed (see Table 2) low

correlations between the constructs. With the exception of brand innovativeness with brand

satisfaction, brand satisfaction with brand repurchase intention, customer hope with brand

satisfaction and brand repurchase intention further support for the constructs’ discriminant

validity.

<INSERT TABLE 2 ABOUT HERE>

The AVE for product knowledge was greater than its shared variance with any other

construct, suggesting discriminant validity (Fornell and Larcker, 1981). However, the square

16  

root of AVE for brand innovativeness with brand satisfaction, brand satisfaction with brand

repurchase intention, customer hope with brand satisfaction, and brand repurchase were

lower than their shared variance with any other construct. As a further check, the chi-square

difference test suggested by Bagozzi et al (1991) was undertaken to examine the discriminant

validity of moderately high correlations between brand innovativeness with brand satisfaction

and brand satisfaction with brand repurchase intention. The non-significant values were

returned by the chi-square difference test between brand innovativeness and brand

satisfaction (Δχ²= 102.37/43 – 105.527/44 = 3.157, df =1; p> .05). However, the significant

values returned by the chi-square difference test between brand satisfaction and brand

repurchase intention (Δχ²= 102.37/43 – 105.527/44 = 3.157, df =1; p< .05), customer hope

and brand satisfaction (Δχ²= 101.91/20 – 121.927/21 = 20.236, df =1; p< .05), and customer

hope and brand repurchase intention (Δχ²= 126.815/14 – 145.152/15 = 18.337, df =1; p< .05)

extend support to discriminant validity between the respective pair of constructs.

Path Analysis

We tested the effects of predictors brand innovativeness on customer hope, product

knowledge (moderator) on customer hope, first mediating variable (customer hope) on brand

satisfaction and second mediating variable (brand satisfaction) on brand repurchase intention.

The relationships were modelled and tested using AMOS 24. The adequacy of this structural

model was evaluated by fit indices, which suggested that the structural model displayed good

model fit, with χ2 = 472.331, df = 176, χ2/df = 2.684 (p<.01), CFI = 0.936, IFI = 0.937,

SRMR = .047, and RMSEA = 0.064. Path analysis revealed (see Table 3 and Figure 2) that

brand innovativeness has a significant positive impact on customer hope (β = .650, p < .00).

Customer hope has a significant positive impact on brand satisfaction (β = .948, p < .01) and

brand satisfaction significantly increases brand repurchase intention (β = .923, p <.01).

17  

Product knowledge significantly moderates the impact of brand innovativeness on customer

hope (β = .070, p <.01). Internet usage and purchase frequency are the control variables, and

results of these variables are non-significant.

<INSERT TABLE 3 ABOUT HERE>

<INSERT FIGURE 2 ABOUT HERE>

Indirect effects

Following an approach employed by Zhao et al (2010), bootstrapping procedures in AMOS 24

were used to test the significance of the indirect effects of customer hope and brand satisfaction.

In both data sets, 2000 bootstrapping samples were generated from the original dataset (N =

418) by random sampling. According to the results: 1) brand innovativeness significantly

impacted brand satisfaction through customer hope, and 2) customer hope significantly

impacted brand repurchase intention through brand satisfaction. The mediating effects of the

mediators and the associated 95 per cent confidence intervals are displayed in Table 4.

<INSERT TABLE 4 ABOUT HERE>

Moderation (slope) analysis

While AMOS 24 was employed to assess the moderation of product knowledge on the

relationship between customers’ perceived brand innovativeness and customer hope,

estimates were used to perform slope analysis. This test was performed to evaluate the visual

inspection of interaction and ascertain the moderation effect of product knowledge on the

relationship between the independent variable (i.e. customer-perceived innovativeness) and

dependent variable (i.e. customer hope). Results demonstrate that the moderator (CPI*PK)

18  

strengthens the positive relationship between customer-perceived innovativeness and

customer hope (see Figure 3).

<INSERT FIGURE 3 ABOUT HERE>

Path invariance

The sample was collected from customers who had bought convenience (e.g. a pen with laser

pointer) or luxurious, innovative (e.g. a tablet with an embedded mini projector) brands.

As the data were collected based on product type, model path invariance across two product

types (convenience and luxurious innovative) was tested. The sample sizes for respondents

who consumed convenience and luxurious innovative products were 134 and 284

respectively. The structural invariance was used to test for the equality of structural

covariances and factor variances. The results demonstrated that the difference in chi-square

was non-significant between the constrained and unconstrained models for the structural

models (Δχ2/df = (563.056/232) – (551.013/232) = 12.043/16; p = 0.741> .05), thus

indicating that the structural model was invariant across two product categories. A constraint

was applied to each path to get a new chi-square. Any chi-square (after constraining a

relationship between the constructs) that is more than the calculated threshold (554.85 for

95% confidence interval) constitutes variance in the path-by-path analysis. Results indicate

that using the 95 per cent confidence product type moderates the path from brand

innovativeness to customer hope (χ2 (234) = 609.701 > 554.85) and brand satisfaction to

brand repurchase intention (χ2 (234) = 555.655 > 554.85); thus, these two relationships are

different based on two product types (e.g. convenience and shopping). However, product type

does not moderate the path from customer hope to brand satisfaction (χ2 (234) = 551.851 <

554.85) for convenience and shopping product samples because the chi-square (after

19  

constraining a relationship between the constructs) is less than the calculated threshold. The

results demonstrate that the level of customer hope and brand repurchase intentions will be

significantly different when customers buy luxurious products as compared to convenience

goods.

DISCUSSION

This research extends the scholarship on digital/online marketing, customer behaviour and

customer–organisation relationship-building strategies by considering a psychological

construct, namely hope, and developing and testing a conceptual model that is different from

general extrinsic or intrinsic motivation, or desire-based, goal-directed behavioural models for

purchase. This study advances the scope of customer hope and research in the online marketing

literature through scrutinising its antecedents and outcomes in the online setting. Our findings

provide a more holistic perspective on how customer-perceived brand innovativeness could

contribute to the generation of positive emotions at the customers’ end, leading to positive

consumption experiences for both customers (i.e. satisfaction) and firms (repurchase

intentions). Further, our findings extend Snyder et al’s (2002) models of the antecedents and

consequences of hope in the context of online shopping. Our results show that, in an online

setting, customer evaluation of the novelty in features, attributes and functions performs an

important role in causing hope in relation to the brand and achieving customer satisfaction.

While hedonic brands (i.e., brands for which fun and pleasure are the main values) tend to

generate strong emotional responses (Chandon et al, 2000), highly innovative brands (such as

technology-based products) can be the key predictor of customer hope in the context of online

purchases.

Our findings indicate that a customer’s perceptions of brand innovativeness can better

explain customer hope if the customer is highly knowledgeable about that product. Hence,

20  

perceptions about innovativeness, in conjunction with the ability to evaluate and analyse

information about the brand, can generate positive emotions such as customer hope. The

highly knowledgeable customer may engage in cognitive decision making, which may

encourage cognition-focused emotion such as hope.

In a benign organisational environment, goal congruence could be attributed to the

occurrence of favourable outcomes, such as a customer’s hope that they can attain their goals

(e.g. purchase of iPad results in building social identity, eliminating the fear of being

excluded from social circles). In this situation, customers can hope that their purchase of an

online innovative brand will positively affect their personal and social positioning. These

positive outcomes are possible because their perceived benefit of purchasing an online

innovative brand outweighs the costs associated with maintaining the status-quo. Customers

always hope to achieve favourable results and avoid adverse outcomes. The results of the

indirect effects further show that hope remains significant in explaining the relationship

between customer-perceived brand innovativeness and customer brand satisfaction. Results

further highlight the effect of customer hope on customers’ repurchase intentions for the

brand through brand satisfaction. These findings are notable because studies on customers’

purchases of innovative brands online have focused on their positive impact on repurchase

intentions and largely ignored the role of positive emotions such as hope and satisfaction that

customers aim to achieve. We further show that hopeful customers are better able to attain

satisfaction and intend to make a repeat purchase of the same online brand.

Our findings reveal differences in the hypothesised path from customers’ brand

satisfaction to repurchase intentions for convenience and luxury innovative brands in an

online setting. This result highlights the implicit link between innovative brands and attaining

satisfaction associated with luxury brands, as opposed to convenience brands that do not

require any involvement and attention. Our findings further reveal that firms should help their

21  

online customers to experience hope, which may assist customers in the process of attaining

satisfaction. Managers can achieve this by formulating and implementing online marketing

strategies that help customers set and reach collaborative goals; for example, co-creation of

value and customisation. Put simply, the more hope a customer has that the brand will

provide value, the more satisfied they will be with the brand and the firm. Accordingly, brand

managers of multi-channel retailers and service firms should implement strategies to cultivate

consumer hope. For instance, in a retail context, temporary pop-up shops or kiosks would

facilitate consumer experience touchpoints, where customers could touch, feel, taste and

physically experience the product prior to purchasing online (Stein and Ramaseshan, 2016).

Such interactive experiences with brands/products mitigate risk and improve feelings of hope

that the brand will resemble the displayed product. Likewise, ‘Click and Collect’ facilities,

where customers can inspect brands purchased online and engage with the multi-channel

retailer (or even service firms) prior to consumption, would also improve customers’ feelings

of hope (Vyt et al, 2017). Further, a customer will invest time and energy in searching,

evaluating and comparing brands online and seek product knowledge to attain satisfaction

(Chiu et al, 2014). These pathways may include looking for multi-channel retailers or service

firms to provide online transactional facilities, like payment plans, price guarantees or easy

return methods (Jeng, 2017). Such mechanisms will improve the customer’s satisfaction and

win their hearts for repeat purchases and this, in turn, will improve the online purchase

outcomes resulting from the overall experience with the brand and its retailer or service firm.

As such, multi-channel retailers or service firms should implement such online transactional

devices.

Customers want to see how their purchases contribute to their personal well-being and

social fit, and setting the right goals makes this connection explicit for them. Some firms

neglect to think about what a customer is personally trying to accomplish (e.g., pleasant

22  

online shopping experience and satisfaction) in the context of social exchange (online

transaction). To help align customers’ perceptions of brand innovativeness and a firm’s

innovation objectives and strategies, firms may need to incorporate customers’ personal

interests into their marketing mix and online marketing strategies to increase their brand

satisfaction, which will ultimately develop grounds for their customers’ repurchase

intentions.

Clearly, customers with such characteristics of hope and satisfaction would be valuable to

any firm. Firms should also strive to examine the level of hope during the early stages of their

online interaction with customers. Employees who provide online support, if properly trained

and equipped, can assess customers’ purchase intentions by examining their levels of

satisfaction and hope. In short, managers should give their employees discretion to help

customers in this way, especially with the immediacy of social media in an online purchasing

environment. Luthans and Jensen (2002) have already emphasised the need to examine the

role of hope in positive organisational behaviours and human resource management strategies

and practices by shedding light on how hope can be instrumental in human resource

development practices.

Future research and limitations

As with any study, this research contains several limitations that suggest potential avenues for

future research. The cross-sectional nature and one-level data collection from customers place

limitations on the generalisability of this research. Longitudinal, multilevel (on business-to-

customer, business-to-business and even customer-to-customer) research to ascertain

differences in the levels of customers’ responses to innovative online brands, hope and the

satisfaction attainment process will develop insights into customers’ stimulation process of

23  

hope. Also, this study has not considered the temporal effects of hope on customer choices

and preferences.

An area for future research on customer hope may be an exploration of multilevel

differences and their impact on personal and group (bulk-buying) performance outcomes.

Further research needs to measure group preferences objectively. Another avenue for future

research is the relationship between risk perceptions and appraisals about conceptualisation

and operationalisation of hope in an online shopping context. In certain industries, such as

health, pharmacy, law and financial investments, customers find themselves in a situation

where their purchase decisions entail a higher amount of risk, and they perform risky

activities when purchasing an innovative brand. Customers’ perceptions of risk associated

with an initiative as having uncertain, highly personal and severe consequences, and the

moderating role of risk on the hope and choice alternatives, could be an interesting area for

researchers focusing on the online purchasing environment. Further, beyond risk perceptions,

hope may moderate the relationship between the risk-reward trade-off. Employing appraisal

theory, Bowen et al (2003) have shown that medical risk is underestimated by customers

when they experience positive emotions and, conversely, they overestimate the medical risk

when their emotions are negative. As a further extension of this theory, Fredrickson (2004)

states that positive emotions broaden an individual's momentary thought-action repertoire and

promote discovery of innovative and creative actions, ideas and social bonds. Because hope

is a positive emotion, future research may explore the potential link between higher levels of

hope and customers’ personal and social resources in an online shopping environment, which

may help them perceive a purchase as being less risky, easy, enjoyable and one which helps

them achieve satisfaction.

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Table 1: CFA Estimates, Z values, Inter-Item Consistency (α), Composite Reliability and

Average Variance Extracted

Construct Source Items Item loadings

Z-score

Cronbach alpha

CR AVE

BI1 (O'Cass and Carlson, 2012)

The brand I purchased online offered unique features for customers that are different from other existing online brands.

0.804 0.920 0.920 0.623

BI2 The brand I purchased online is highly innovative.

0.809 18.789

BI3 The brand I purchased online has innovative features.

0.840 19.813

BI4 High quality innovations were introduced along with the brand I purchased online.

0.792 18.246

BI5 Compared to similar products or services developed by other brands, the brand I purchased online offered unique features/attributes/benefits to the customers

0.812 18.996

BI6 The brand I purchased online introduced many completely new features to this class of products or services.

0.766 17.450

BI7 Compared to similar brands developed by the same organisation, the brand I purchased online offered unique features/attributes/benefits.

0.696 15.420

PK1 (Carlson et al, 2007)

I had previous knowledge of the brand that I purchased online.

0.861 11.174 0.867 0.874 0.587

PK2 I already knew about the brand that I purchased online.

0.812 10.891

PK3 I had familiarity with the brand I purchased online.

0.848 11.103

33  

PK4 I had experience with the type of brand I purchased online

0.733 10.366

PK5 I regularly have used brands equivalent to the one I purchased online.

0.525

CH1(Snyder,1995) I hope I can achieve my goals in relation to the brand I purchased online.

0.731 12.002 0.738 0.741 0.490

CH2 I hope that the brand I purchased online would benefit me.

0.698 11.611

CH3 When purchasing a brand online, I am always hopeful that I shall achieve what I aim for.

0.666

BS1 (De Wulf et al, 2001)

It is a pleasure to have a purchasing relationship with the brand that I purchased online.

0.0.713 15.532 0.843 0.850 0.586

BS2 I have found the ideal brand that I purchased online.

0.784 17.457

BS3 This brand always returns best value.

0.779 17.324

BS4 I am very satisfied with my online purchase of this brand.

0.783

BRI1 (Eggert and Helm, 2003)

Next time I would buy this brand online again.

0.762 15.306 0.792 0.795 0.565

BRI2 In the future, buying this brand online will fulfil my shopping requirements.

0.740 14.856

BRI3 In the foreseeable future I will consider this brand as an option when purchasing a product or service online.

0.753

(N=418), All values are significant at P<.01, where BI = Brand innovativeness; PK = Product knowledge; CH = Customer hope; BS = Brand satisfaction; BRI = Brand repurchase intention

34  

Table 2: Mean, standard deviation and inter-factor correlation

Construct Mean SD BI PK CH BS BRIBI 4.86 1.20 (0.790) PK 5.24 1.20 0.551 (0.766) CH 5.24 1.11 0.808 0.484 (0.669)BS 5.23 1.20 0.825 0.746 0.808 (0.765) BRI 5.40 1.05 0.660 0.705 0.742 0.948 (0.752)

(N=418), All values are significant at P<.01, Square root of AVE is shown in parentheses, where SD = Standard deviation, BI = Brand innovativeness; PK = Product knowledge; CH = Customer hope; BS = Brand satisfaction; BRI = Brand repurchase intention

35  

Table 3: Path analysis

Hypothesis Estimates Z-value Accepted/Rejected BI CH 0.650** 9.918 AcceptedINTBIPK CH 0.070* 2.082 Accepted CH BS 0.948** 11.444 AcceptedBS BRI 0.923** 14.859 Accepted Internet usage (Control) BRI

0.034 (ns) 0.970 Non-significant

Online Purchase frequency (Control) BRI

0.026 (ns) 0.719 Non-significant

(N=418), **p< .01, *p< .05, where BI = Brand innovativeness; PK = Product knowledge; CH = Customer hope; BS = Brand satisfaction; BRI = Brand repurchase intention and ns = Non-significant

36  

Table 4: Bootstrapping indirect effects and 95% confidence intervals (CI) for the meditational model.

Mediation Independent variable (IV)

Dependent variable (DV)

Point estimates

(95% CI) Bootstrapping (Lower bound–Upper bound)

Brand innovativeness Customer hope Brand satisfaction

Brand innovativeness

Brand satisfaction

.617** (.521)-(.704)

Customer hope Brand satisfaction Brand repurchase intention

Customer hope Brand repurchase intention

.875** (.779)-(.950)

(N=418), ** values are significant at p<.01

37  

Figure 1: The model.

38  

Figure 3: Moderation effect of product knowledge on the relationship between customer-perceived innovativeness and customer hope

1

1.5

2

2.5

3

3.5

4

4.5

5

Low BI High BI

CUSTOMER

 HOPE

Moderator

Low PK

High PK

39  

Figure 2: Path analysis of customer hope model