Journal of Theoretical and Applied Information Technology

Journal of Theoretical and Applied Information Technology

© 2005 – 2016 JATIT & LLS. All rights reserved.

ISSN: 1992-8645 www.jatit.org E-ISSN: 1817-3195

77

SOCIAL LEARNING APPROACH IN DESIGNING

PERSUASIVE E-COMMERCE RECOMMENDER SYSTEM

MODEL

1 NUR SYADHILA CHE LAH,

2 AB RAZAK CHE HUSSIN,

3 NOR ZAIRAH AB RAHIM,

4 ABDELSALAM H.BUSALIM

1,4 PhD Student, Department of Information System, Universiti Teknologi Malaysia, Johor, Malaysia

2,3 Dr., Department of Information System, Universiti Teknologi Malaysia, Johor, Malaysia

E-mail: 1 Sya_ila87@yahoo.com.my,

2 abrazak@utm.my,

3 nzairah@utm.my,

4 abusalim.86@gmail.com,

ABSTRACT

Intention to purchase in existing online business practice is learned through observation of

information display by online seller. The emergent growth of persuasive technologies currently holds a

great potential in driving a positive influence towards consumer purchase behavior. But to date, there is still

limited research on implementing persuasion concept into the recommender system context. Drawing upon

the principle design of persuasive system, the main purpose of this study is to explore social learning

advantages in creating persuasive features for E-Commerce recommender system. Based on Social

Cognitive Theory, the influence of personal and environmental factors will be examined in measuring

consumer purchase intention. In addition, dimensions of social learning environment are represented by

observational learning theory and cognitive learning theory. From those reviews, this study assumed that

social learning environment can be created based on attentiveness, retentiveness, motivational, knowledge

awareness and interest evaluation cues of consumer learning factors. Furthermore, the persuasive

environment of recommender system is assumed to have positive influence towards individual

characteristics such as self-efficacy behavior, perceived task complexity and confused by over choice.

Findings from those reviews have contributed to the development of a research model in visualizing social

learning environment that can be used to develop a persuasive recommender system in E-Commerce and

hence measures the impact towards consumer purchase intention.

Keywords: Recommender Systems, E-Commerce, Social Cognitive Theory, Social Learning, Persuasive

Systems, Purchase Intention.

1. INTRODUCTION

The design of a website is not only for fulfilling

customer’s needs and interest but is expected to

assist customers through the steps of buying

process. Thus, instead of simply seen as a brochure

for online products, E-Commerce should therefore

be a vital instrument of customer service and

persuasion [1]. Currently, most outstanding E-

Commerce do not just display the products which

may influence user’s needs, but the website actively

recommends items that potentially interest users

based on purchase history or similar user’s

preferences [2]. Amazon is a typical example of E-

Commerce website which implements

recommendation services that intelligently suggest

items to that an active user may like. A survey

shows that at least 20 percent of sales in Amazon

come from the work of the recommender system

[3]. In situations where there is an information

overload, providing personalized recommendations

has been proven to be a major source for enhanced

functionality, user satisfaction, and revenue

improvements [5].

According to [6] and [7], area of research in

recommender system is being focused on the

algorithm aspect or system-centered, which

specifically looks on development and evaluation

of the algorithm to generate the most accurate

recommendations. But recently, the emerging

research in recommender system is starting to be

based more on user-centric characteristics. These

include researches that focus on recommendation’s

presentation [8], system transparency which

explains how the system work to the end user [7],

Journal of Theoretical and Applied Information Technology 31

st August 2016. Vol.90. No.2

© 2005 – 2016 JATIT & LLS. All rights reserved.

ISSN: 1992-8645 www.jatit.org E-ISSN: 1817-3195

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and recommendation’s novelty and persuasion [9].

Scholar [10] stated that recommender system also

can act as computer-human persuasion which may

utilize some patterns of interaction that seem

similar to social communication. Persuasion

concept in E-Commerce recommender system is

rarely explored. The opportunities to improve the

quality of recommender system can be achieved

through exploring the benefits of social influence in

designing persuasive features. Thus, this study

mainly aims to examine the persuasiveness of

recommender system represented by consumer

purchase intention and persuasive social features.

For the purpose of creating a persuasive

technology, [11] argued that computers can be

more effective persuaders since they have capacity

to adjust influence tactics based on developed

situations and have a high level of interactivity

compared to human ability. Moreover, user

behavior plays an important role in determining the

system works as it should in order to create the

persuasive experiences via technology [12]. This

includes either people are using the system in the

intended way or even in an unintended way, it may

provide learning opportunities that may further be

integrated in future iterations of the system.

Theories of persuasion typically aim at studying

influences or changes in behaviors and attitudes of

people [13]. Scholar [14] suggested that socio-

technical system can be designed by building upon

user motivations and goals which then can

influence their behaviors and attitudes. The

understanding of fundamental aspects of human

behavior is important as a requirement in applying

social support features effectively for persuasive

systems. In addition, the medium for channeling

this understanding via persuasive systems needs to

be devised to enhance positive user experiences and

social interaction [16]. The evolution of user’s

participation is facilitated by social web through

technological environment that engages diverse

audiences, enhances creativity and fosters user

collaboration, which then turns into active

contributors [17]. Socially active people nowadays

are surrounded with technological advancements

including online purchasing from E-Commerce.

Marketing competitiveness has resulted in

consumers being confused over choices and

information overload. Intention to purchase is

learned trough social engagement and participation

in online communities via numerous social

networks. Learning can occur through the process

of acquiring information from experience and

information storing [18]. Social learning is one of

the persuasive design principles which aim to

motivate users to perform a target behavior by

observing others’ behavior through the systems

[19]. Social cognitive theory by [20] is often

applied in studies on individual behavior to

elucidate the interaction among environmental

factors, personal factors and behavior intention.

Towards achieving the proposed research purpose

as stated, the next section will discuss more on

investigating how to create the persuasive

environment of social features of recommender

system. Review on social cognitive theory and

consumer learning theory will be done. Moreover,

the personal factors also will be examined and will

be further linked with environmental factors and

consumer purchase intention. The research model

will be proposed to visualize the measurement for

each factor discussed.

2. THE CONCEPT OF PERSUASIVE SYSTEMS AND BEHAVIOR CHANGE

Persuasive technology is defined as an

interactive information technology which is

designed for the purpose of changing behavior or

attitude of the users [11]. The emergent growth of

the Internet and other ambient technologies has

opened up the opportunities for persuasion

communication since the user can be reached

easily. Some examples of application areas which

have implemented persuasive technologies are

healthcare, education, sustainability and E-

Commerce. Persuasive systems are defined as

computerized software or information system with

the purpose to reinforce, shape or change the user

attitudes or behaviors or even both [21]. From the

definition above, there are three expected outcomes

of persuasive system, namely voluntary

reinforcement, shaping or change of attitudes and

change or shaping or the behaviors. The concept of

persuasion can be defined as communication

process which includes message passing from

persuaders to the recipient (persuadee) with the

intention to influence recipient’s behavior whilst

leaving the power of making the decision to the

recipient [19]. Moreover, system persuasiveness

can be defined as user perceptions which concern

on the quality of the systems, evaluation of

system’s features whether they meet the user’s

needs and expectation of system excellence [22],

and the integration of system evaluation and its

impact on the individual [23]. According to [11],

the measure of system quality can be represented

by their ease of access, usage easiness, error-

freeness, convenience, system responsiveness,

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st August 2016. Vol.90. No.2

© 2005 – 2016 JATIT & LLS. All rights reserved.

ISSN: 1992-8645 www.jatit.org E-ISSN: 1817-3195

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information quality, system attractiveness, user

loyalty and positive user experience.

The generic steps of persuasive system

development are first starting with the analysis of

persuasion context and selection of persuasive

design principles, followed by requirement

definition for software qualities, software

implementation and behavior change [19]. Design

principles of persuasive system (PSD) consist of

four dimensions, which are primary task support,

dialogue support, system credibility and social

support. All those dimensions are proven to have

significant impact on system persuasiveness and

system qualities evaluation [24]. The primary task

support can be defined as extrinsic IT task support

which involves the usage if information technology

is used as instrument in achieving the user goal.

Besides that, dialogue support is related to system

interactivity and its impact on increasing user

motivation to achieve the target goals. System

credibility is about the support process by making

the system design more reliable and persuasive

while social support is about incorporating a range

of social influence for the purpose of motivating

and persuading to perform a particular action or

behavior. The range of social influence can be

represented by social behavior benefits such as

social learning, social facilitation, social

comparison, normative influence, cooperation,

competition and recognition. However, the design

model does not suggest the implementation of all

possible software features in creating the persuasive

social systems.

Research from human computer interaction

(HCI) perspective specific to E-Commerce context

has mainly focused on designing website interfaces

with the purpose of improving decision-making

effectiveness and efficiency, which can lead a user

towards intention to make a purchase from the

Internet [25]. E-commerce websites are becoming

increasingly functionally persuasive, and are

incorporating increasingly dynamic persuasive

techniques as similar to those applied by face-to-

face sales-persons, to enhance system credibility,

facilitate the process of online buying, and motivate

users to adopt the systems [26]. An example of a

persuasive technique, which is commonly applied

on E-Commerce websites, is customer review

boards, where each product is linked to reviews

from previous consumers, allowing customers to

compare alternatives. People who visit a website

are assumed to have a certain goal; therefore

presenting the appropriate content of the website is

needed to enable them to achieve their goals.

Online seller is responsible in triggering the user

intention to care for information offered on the

website and the same time if they can handle it.

Moreover, responsibilities also go for the obligation

to create the ease in accessing information and as

intuitive to perceive as possible.

2.1 Social Cognitive Perspective\

Social Cognitive Theory is suggested by [27],

which describes learning occurrence within social

context. Moreover, learning can be influenced by

personal factors and environmental events, which

then result in pattern of behavior. All those factors

operate as interacting determinants that influence

each other [28]. Social Cognitive Perspective has

been applied in various domains of human

functioning such as choice of career and physical

health but is very limited in the domain of

persuasive systems. Research by [17] has proposed

social cognitive model in investigating user

engagement in feedback sharing that takes place in

airport service. Social learning, social comparison

and normative influence have been applied as

software features in airport facilities to examine

behavior change of travelers.

According to the above theory, the reciprocal

interactions of personal and environmental events

are assumed to have significant influence towards

one’s behavior. Environmental events can be

represented by various models for the purpose of

information extraction during consumer learning

process. The way information is modeled to create

persuasive environment of recommender system is

the main research aim for this study. Besides that,

consumer’s personal factors such as perceived task

complexity and confused by over choice due to

information overload in online transaction are

assumed to have positive influence towards

persuasive environment. Consumer self-efficacy,

which describes consumers’ belief regarding their

capability to succeed and attain a given level of

performance, is assumed to have positive

interaction with persuasive environment. This

expectation is assumed to shape the process of

consumer decision making, which includes the

selection process of action and behavior taking.

Taking the same concept as social cognitive

perspective, this current study aims to explore the

effect of personal and software features as

environment factors towards the target behavior of

consumer purchase intention in E-Commerce.

Social learning approach will be used as software

features to represent environment factor for this

study. For this reason, the proposed social cognitive

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st August 2016. Vol.90. No.2

© 2005 – 2016 JATIT & LLS. All rights reserved.

ISSN: 1992-8645 www.jatit.org E-ISSN: 1817-3195

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model with specific measurement is designed in the

next section.

2.2 Social Learning Dimensions

Social learning for persuasive system can be

defined as the use of system to observe others’

behavior and being motivated to perform the target

behavior. Based on Social Learning Theory,

concept of observational learning has been

introduced, which stated that people retrieve

behavior knowledge and skills by observing others,

thus having direct influence on their own behavior

[27]. An example of implementation can be seen in

e-health application where a shared fitness journal

in mobile application is provided for encouraging

physical activity [32]. [33] in her work has

proposed the main roles of social learning

environments. These include supporting a learner in

finding the right content, to connect with

appropriate people and being a learner’s motivation

to learn differently but in effective ways.

Experiment using social influence features in

persuasive system has been done and results claim

that it has multiple positive impacts on user

perceptions and behaviors [34], and the presence of

others influence people’s actions [35]. The main

intention in designing software features with social

learning environment is to visualize such a presence

of other people that work toward a similar goal and

interest. In achieving the similar situations or the

same target goals, people are assumed to be able to

be motivated by people that face the same issues

and work towards the same directions. Design of

social learning features should also consider the

applicability of the system that enables the user to

see the progress of their peers and make the others

aware and being observant about their performance.

An online learning environment can greatly benefit

from the integration of recommender system to

personalize the learning process and adapt it to the

user’s existing knowledge, abilities and preferences

[36].

2.3 Observation Learning Theory

Previous studies have confirmed that

consumer’s purchase decision is influenced by

observational learning activities of sales volume

and reference of other’s EWOM [49],[50].

According to [29], observational learning occurred

through the process, which consists of

attentiveness, retentiveness and motivational

factors. Attentiveness is about the way information

is modeled through salience, attractiveness and

functional value activities to raise consumer

attention. Retentiveness is about the way

information is modeled to make it memorable. This

can be achieved through symbolic representation

and application [51]. Motivational factor is about

the way information is modeled as incentive

motivator to raise consumer motivation. This can

be achieved through personalization of standard

similarity and self-approved [52].

2.4 Cognitive Learning Theory

Cognitive learning theory holds the kind of

learning which involves human problem solving

that enables individuals to gain some control over

their environment. This type of learning can occur

through the statement that exhibiting knowledge

and skills related to products [53]. The role of this

learning factor is to show the cognitive information

processing about product characteristics which

disclose learning process and outcome of past

buyers; hence stimulate the critical thinking of

potential online buyers. Research by [54] has

shown that others’ opinions and reasoning may

reduce consumer’s cognitive processing efforts and

energy expenditure and next improve the decision

process of consumer. Model of cognitive learning

stated that consumer learning process can be

triggered through knowledge awareness and interest

evaluation factors. Knowledge awareness can be

created through the length of information, which

consists of argument quality and participative cues.

Meanwhile, interest evaluation can be achieved

through consumer review of information and match

their own knowledge and experiences with

situations described as well as estimate their own

learning curves.

3. STUDY DESIGN AND THE PROPOSED MODEL

Social Cognitive Theory has indicated that

behavior intention may be influenced by

environmental and personal factors. According to

Ajzen, behavior intention is influenced by social

norms through a user’s attitude toward the behavior

[46]. A subjective norm is known as the need for

social pressure to engage or not to engage in a

particular behavior. In this study, social norm will

be represented by the system features of social

learning, which is expected to have significant

influence towards user behavior. The

implementation of social learning environment in

recommender system is also expected to bring

persuasion context for each person’s behavior.

Besides that, the relationship scheme of social

cognitive theory [29] has shown that the observed

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st August 2016. Vol.90. No.2

© 2005 – 2016 JATIT & LLS. All rights reserved.

ISSN: 1992-8645 www.jatit.org E-ISSN: 1817-3195

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behavior may be learned through the influence of

personal factors. Personal factor is determined by

individual perceived self-efficacy towards a

specific behavior. As example, consumers are

getting to believe that their ability in seeking the

right information in online website will result in

completing their decision about purchase intention.

Behavior determinant is the response received by

the user after performing the behavior.

Based on the review of those determinants from

social cognitive theory, this present study aims to

propose a model to investigate the appropriate

factors which represent personal and environmental

factors that will give a significant influence towards

consumer purchase intention for E-Commerce

recommender system. The concept of persuasion is

represented by applying social learning dimension

in environmental factor, which represents software

feature for recommender system. Social learning

dimension represents consumer learning theory of

observational learning and cognitive theory.

Meanwhile, personal factor is represented by

consumer self-efficacy, perceived task complexity

and confused by overchoices. Both personal and

environmental factors for this study are believed to

have a significant influence towards consumer

purchase intention in recommender system that

takes place in E-Commerce setting. The proposed

model with those determinants is shown in Figure

1. The measurement and definition for those

proposed determinants for the research model is

further detail in Table 1.

Table 1: Operational Measurement and Definition

Factor Attributes Definition and

Example

Personal

Factor

Self-

Efficacy

User belief

regarding their

capability to

succeed and attain

a given level of

performance [37]

– Shopping satisfaction

– Frequency of use

– Outcome expectancies

Perceived

Task

Complexity

Task complexity

is about a person-

task interaction

[38].

Task complexity

is related to task

and system’s

motivation. The

value of

completing the

task (task

motivation) is

influenced by

system’s

motivation that

can be achieved

through

considerations of

system’s features

[39]

Confused by

Overchoices

User feels

difficult in

making decision

to choose and

feels overchoice

due to the power

of influence and

stores offered

[40].

Environm

ental

(social

learning

features)

Observation

al Learning

Theory

Observational

learning occurs

when consumers

observe the

actions of others

and make the

same choice that

others have made

[49][50]

Learning occurs

through the

process which

consists of

attentiveness,

retentiveness and

motivational

factors [29]

Cognitive

Learning

Theory

The cognitive

dimension refers

to statements

exhibiting

knowledge and

skills related to

the product [53].

Cognitive cues

such as

knowledge

awareness and

interest

evaluation

embedded in text

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© 2005 – 2016 JATIT & LLS. All rights reserved.

ISSN: 1992-8645 www.jatit.org E-ISSN: 1817-3195

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messages provide

critical

information for

potential buyers

Behavior

Intention

Consumer

Purchase

Intention

In relation to

consumer

perception,

behavior and

attitude [44].

Purchase behavior

acts as an

important key

point for

consumers during

product

evaluation [55].

Purchase behavior

will be driven by

the physiological

motivation which

is related to the

need of retail

store in fulfilling

their need [56].

Decision making

style is related to

mental orientation

in characterizing

consumer

approach in

making choices

[45].

Figure 1: Proposed Research Model for Persuasive

Recommender System

4. DISCUSSION

Even though the research on persuasive

technology has been growing progressively,

investigation in the context of E-Commerce

recommender system still receives little attention.

Besides that, self-learning behavior of consumer

has opened up the opportunity for online sellers to

leverage their consumer experience by designing an

intelligent agent as a tool to persuade and assist

users on the website. Based on the persuasion

context of persuasive technology, social learning

environment can be created to learn about others’

behavior and being motivated to perform the same

[17]. The proposed model in the previous section

describes operational measurement which can be

used to create a persuasive recommender system by

leveraging social learning approach. Review on

persuasive design principles has shown that social

learning support can be used to create a persuasive

environment to trigger user motivation to make

purchase decision by observing their peers’

behavior and history through the system. Consumer

learning perspective of observational learning

theory and cognitive learning theory is found to be

important determinants in creating online learning

environment for persuasive system. The way

information is modeled based on attentiveness,

retentiveness and motivational factors is assumed to

be able to be used as important cues in creating

social learning environment in recommender

system. Besides that, cognitive factor such as

knowledge awareness and interest evaluation is

assumed to be important cues which can be

embedded in information displayed to consumer.

Moreover, user characteristics such as self-

efficacy, task complexity and being confused by

information overload, are also proposed as personal

factors which can influence consumer purchase

intention from persuasive recommender system.

Self-efficacy such as shopping satisfaction and

frequency of use is found to be important

determinants that trigger user motivation in making

decisions about product purchasing. The main

purpose of recommender tools is to assist consumer

decision making by minimizing overload of

information in terms of product choice and

completing their online transaction from task

complexity [5]. Thus, this study aims to investigate

the influence of these personal factors towards

consumer purchase behavior based on persuasive

learning features of recommender system. Based on

those reviews, this study further aims to validate the

proposed personal, environmental and behavioral

Journal of Theoretical and Applied Information Technology 31

st August 2016. Vol.90. No.2

© 2005 – 2016 JATIT & LLS. All rights reserved.

ISSN: 1992-8645 www.jatit.org E-ISSN: 1817-3195

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factors in creating a persuasive recommender

system. Quantitative research method will be used

to conduct the survey among participants who have

experience in online buying. Parallel with that, the

survey instrument will be developed based on each

determinant for validation purpose.

5. CONCLUSION

As conclusion, the quality of recommendation

service can be improved through the evaluation of

user-centric based [9]. Taking the recent

advancement of persuasive technology, this study

aims to enhance research discussion on

recommender system development in triggering

consumer purchase intention. Furthermore, this

study is expected to fill the gap caused by limited

research on implementing persuasion concept into

E-Commerce recommender system. Previous

research [48] has shown that consumer purchase

intention is more influenced by their observation

learning behavior, which proves that such

environment for consumer learning support is

important in present online business practice. Thus,

the proposed research model is hoped to provide a

lens for online seller in maximizing their marketing

strategy in designing the persuasive features of

recommender system to enhance their website

credibility; hence influencing consumer purchase

intention.

Taking social cognitive model as a basis,

personal factor and environmental event is assumed

to influence learning process, which results in

behavior pattern of the consumer. Consumer

purchase intention is measured by the influence of

persuasive learning environment of recommender

system. In addition, this study assumes that

consumer characteristics such as self-efficacy,

perceived task complexity and confused by over

choice are the induced factors for persuasive design

of recommender system. Review on social learning

dimension has disclosed several important factors

which can be used to design persuasive application

features for E-Commerce recommender system.

Practically, those learning features can be used by

online sellers to recommend items which may

enhance consumer motivation during their buying

process. As an example, information about brand

statistics is recommended to consumers, which then

influences self-learning and purchase decision of

the consumer

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