Report

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Social Networks and the Buying Behavior of the Consumer

Introduction

An innovation is a new or novel idea for a product, service, or process, or an

enhancement to those offerings (Hivner, Hopkins, & Hopkins, 2003). Diffusion is

the process by which an innovation is communicated through specific channels

over time among members of a social system that are linked via networks

(Rogers, 1995). Thus, innovation diffusion involves the capacity to spread the

production and the use of an innovation in practice through the social network

structure of a group of stakeholders (Muzzi & Kautz, 2004; Dosi, 1988; Enos,

1962). Innovation diffusion is a central issue in high technology sectors of the

economy, such as information technology and telecommunications, which

continue to experience rapid technological changes and continuous innovation.

With network innovations, institutional networks have to be established to

ensure that innovations are diffused successfully in the community of the

adopters. Successful diffusion may require specific institutional actors, such as

opinion leaders and change agents, to initiate and carry out interdisciplinary

undertakings involving different stakeholder communities.

Structural network theorists argue that there are two aspects that determine the

behavior and the propensity of a stakeholder toward adopting technological

innovations: network density and centrality (Rowley, 1997; Nambisan & Agarwal,

1998). Network density characterizes the network as a whole. It measures its

interconnectedness in terms of "the relative number of ties in the network that

link actors together" (Rowley, 1997). The rationale of technologies is to provide

social benefits that can be derived from positive network externalities associated

with mass adoption (Papazafeiropoulou, 2004; Markus, 1990; Markus, 1990).

Such technologies constitute "network innovations" that diffuse through social

networks linking individuals and organizations (King, et al., 1994). The diffusion

of network innovations, at the environmental level, which includes institutional

and regulatory entities, is highly complex and has been relatively neglected in the

literature. Therefore, this paper aims, through a general overview of the

literature on the subject, to understand how the spread of social networks

influence the economy of enterprise. In other words, the research question,

which, the paper tries to answer, is, Can firms' use of social networks influence

the purchasing behavior of consumers, and if so, how?

Learning Resource

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In the first section, we study the main factors, according to academic literature,

that can influence the purchasing behavior of consumers. Then, we proceed to a

general overview of how and with whom social networks have spread, trying to

figure out if and how they can influence the management of firms and

organizations. Next, we investigate demand output and, in particular, the

purchasing behavior of the consumer, trying to study if and how the use of social

networks can influence the purchasing decisions of consumers. The fourth

section describes the methodology that is based on the literature review of the

topics covered by this work. Finally, we present the discussions and conclusions

of the paper.

The Purchasing Behavior of Consumers

Consumers' buying behavior has always been a popular marketing topic,

extensively studied and debated over the last decades, and no contemporary

marketing textbook is complete without a chapter dedicated to this subject. The

predominant approach describes the consumer buying process as learning,

information-processing, and decision-making activities divided into four steps:

1. problem identification

2. information search

3. purchasing decision

4. post-purchase behavior

According to much of the academic literature, demographic, social, economic,

cultural, psychological and other personal factors, largely beyond the control and

influence of marketing, have a major impact on consumer behavior and

purchasing decisions.

Therefore, purchasing decisions are influenced by a complex combination of

internal and external influences. Among these, Kotler and Armstrong (2010)

identify group membership and social networks.

In recent years, online social networking has emerged as a strong component of

social interaction. Social networking includes sites like blogs, networking

websites such as YouTube, and entire virtual worlds like Facebook. The new

social networking technologies offer a genuine communication channel that is

much more credible than any advertising company (Anya, 2006).

Furthermore, the use of social networks increases the word-of-mouth effect. For

this reason, marketers often try to identify or even create their own opinion

leaders for their products, who address their marketing activities. Companies like

Sony, Microsoft, McDonald's, and Procter & Gamble create their own leader of

opinions to facilitate the interactions between consumers (Voight, 2007).

Pellinen, Torma, Uusitalo, & Raijas (2010) indicate that financial skills and

competence are based on financial knowledge and understanding, and are

influenced by personal attitudes in spending and saving. For example, some

consumers are reluctant to make most of their purchases with credit cards

because of the fear that they may not be able to make full payment when their

credit bills are due (Chakravorti, 2003). Some researchers have posited that age,

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income level, occupation, and marital status influence credit card holders'

spending behavior (Erdem, 2008; Ming-Yen, Chong, & Mid Yong, 2013). A

number of interesting findings have been documented concerning age of credit

card holders. Devlin, Worthington, and Gerrard (2007) found that the older the

respondent, the more likely they are to possess one or more credit card.

However, college students and young credit card holders, albeit possessing fewer

credit cards, have been increasingly identified as contributors to credit card debt,

compared to more senior card holders.

In the same way, several studies have looked at the impact of income level on

credit card ownership and use. The findings are, however, not without varying

conclusions. Devlin, Worthington, and Gerrard (2007) found that households

with higher incomes tend to hold more credit cards. Nevertheless, due to their

high income, they are more likely to pay off their credit card debts (Balasundram

& Ronald, 2006). Slocum and Matthews (1970) argue that those from the lowest

category of income always think wisely before making any kind of money-related

decision.

Other studies also show that employment plays an important role in consumers'

purchasing decisions. In fact, Joo and Pauwels (2003) assert that occupation

could influence a person's consumption behavior. They found in their study that

managers and those in the self-employed category are most likely to be heavy

users of credit cards. On the other hand, students are often categorized as

having an occupation, and it has been recognized that many students are living

on the verge of financial crisis (Joo, Grable, & Bagwell, 2003; Manning, 2000). It

is for this reason that usage of credit cards by college students has received

increased visibility throughout the media.

Kinsey (1981) and Steidle (1994) also demonstrate that marital status and length

of marriage affect spending behavior. Devlin et al. (2007) discovered that

married respondents who participated in their research had more departmental

store credit cards than those who are single, separated, or divorced. This is not

difficult to understand, as married consumers are likely to have higher

expenditures than nonmarried consumers.

Bank policies and attitude toward money also play a role in spending behavior.

Many issuing banks and nonbanks offer incentives to entice consumers to apply

for credit cards (Chakravorti, 2003). These incentives include no annual fees

(which have been packaged as an annual fees waiver), cash rebates, point

rewards, airline miles, installment payment plan, and discounts for identified

purchases. Several researchers have argued that green consumer behavior is

determined by a multitude of factors depending on type of behavior and

involvement with the product and behavior. Stern (2000) presents four

categories of determinants of green consumer behaviors:

contextual forces

attitudinal factors

habits or routines

personal capabilities

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Contextual forces affect behavior indirectly through attitudinal factors.

Consumption attitudes are context-specific dispositions that connect personal,

stable values to actual consumption-level attitudes and behaviors (Cleveland,

Kalamas, & Laroche, 2005; Pickett-Baker & Ozaki, 2008). Using this notion, the

value-belief-norm theory has been developed and found valid in a wide variety

of green consumer (curtailment) behavior contexts, such as household energy

use, conservation behavior, and car use reduction (Stern, 2000; Poortinga, Steg,

& Vlek, 2004; Kaiser, Hubner, & Bogner, 2005; Eriksson, Garvill, & Nordlund,

2006; Nordlund & Garvill, 2003).

VBN theory postulates that the factors that influence the relationship between

values and actual behavior are personal moral norms that guide the actions of an

individual. Personal norms, experienced as feelings of moral obligation to act, are

postulated to create a willingness to act pro-environmentally. Personal norms are

in this respect assumed to be formed by incorporating social norms into a

consistent personal value system. The analysis of the literature has identified a

number of factors that, in some way, affect the actions of consumers on the

market.

Social Network and Management

Knowledge is one of the most decisive factors in achieving competitive

advantages for supply chain partners. However, economic systems based on

small and medium-sized enterprises (SMEs) are an important barrier for

transitions from traditional economies to knowledge-based ones. Malhotra,

Gosain, and El Sawy (2001) maintain that supply chain partners engage in

interlinked processes that enable rich information sharing and building

information technology infrastructures to process the information obtained from

partners, a scenario that creates new knowledge. There are different ways of

understanding and classifying knowledge, and most focus on knowledge types:

tacit, explicit, individual, organizational, etc.

Nonetheless, there are many other factors to consider, among which the

interdependence between knowledge and the organizational context stands out

(Zheng, Yang, & McLean, 2010). The literature on innovation has been extremely

broad incorporating perspectives as diverse as traditional structuralist

approaches through to more process-oriented approaches. From the structuralist

perspective, innovation is seen as a thing or entity with fixed parameters (e.g., a

new technology or management practice), which is developed externally,

packaged ("black boxed") by suppliers, and then transferred to potential users

where it can be seen to offer them competitive advantage (Wolfe, 1994).

Structuralist perspectives have been criticized for underemphasizing the

dependency of innovation on the social and organizational context (Scarbrough

& Corbett, 1992). In contrast, process perspectives argue that innovation should

be seen, not simply as a thing to be transferred from place to place, but as a

complex, time-phased, politically-charged design and decision process often

involving multiple social groups within organizations. According to this approach,

innovation may be defined as the development and implementation of new ideas

by people who over time engage in transactions with others in an institutional

context (Van de Ven, 1986). Networking as a social communication process that

encourages the sharing of knowledge among communities is center stage in

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process perspectives, which is reflected in this definition. Therefore, the need

and the possibility for the management company to have new knowledge,

creates the conditions for the creation of a lasting competitive advantage. The

company management can effectively manage the resources at its disposal only

if it has adequate information and if there is a regular flow of information

between the different sectors.

One of the first things to be said about knowledge management (KM) and

innovation is that definitions abound. A broad definition encompasses any

processes and practices concerned with the creation, acquisition, capture,

sharing and use of knowledge, skills, and expertise—whether or not these

practices are explicitly labeled KM. There are also clearly organizational trends

aligned to this focus on KM in innovation. In organizational terms, the new era is

typified by flatter structures, debureaucratization, decentralization, and

coordination through increasing use of information and communication

technologies (ICT).

There have been several theoretical studies and research efforts to explain how

societies can affect actors' behaviors, decisions, and strategies. Granovetter's

(1985) impressive article claims that economic action is socially constructed and

is determined by the ongoing relationships between economic actors. The social-

embeddedness approach emerged as a critique to the "rational actor"

assumption of classical and neoclassical economic models. According to many

researchers, the social capital of individuals helps them find better jobs and

affects occupational success. Organizations and individuals that have numerous

network ties can use these connections to transfer knowledge, reach resources,

and influence others in their environment (Gargiulo & Benassi, 2000).

The measurement of social capital in organizations and individuals is a central

issue in social network research. The high frequency of interactions between two

actors can create acquaintanceship, according to some authors. Tsai and Ghoshal

(1998) state that the increasing interactions between actors in the course of time

can lead to perceptions of mutual trust, and parties start identifying each other's

personal characteristics. Tymon and Stumpf (2003) similarly define social capital

of actors as being developed by the transformation of arms-length ties into

social relations in a period. Individuals who occupy central organizational

positions usually have a high frequency of interactions, which may be sufficient

to strengthen arms-length ties. Hence, the increasing number of reports woven

into business practices enhances confidence of the different actors involved in

the process of value creation. In this way, an engaging process guarantees the

spread of awareness about new technologies and allows actors to create a

climate of social cohesion and develop suitable processes of value creation for all

stakeholders.

In fact, the leveraging of interfirm networks is increasingly considered a strategic

resource that can be shaped by managerial action. Interfirm networks in this

context are defined as consisting of the interactions and relationships

organizations use to access knowledge. These may be in the form of alliances

concerning formalized collaboration and joint ventures that allow access to the

knowledge held by other actors as a means of facilitating innovation. Some

studies introduce the concept of "network resources" to understand the

advantages bestowed by such networks in allowing firms to leverage valuable

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information and resources possessed by their interfirm network partners. Gulati

(2007) defines network resources as an umbrella concept to describe and

understand the resources or capital generated by interfirm networks. The

academic literature highlights the importance of the spread of social networks

and how they can help improve relations within companies and organizations. On

this track it becomes interesting to study whether and how the use of social

networks can influence the purchasing behavior of consumers.

Social media has aroused a lot of interest among researchers and academics. As

use of social media has increased at an amazing rate, companies have allocated

an increasing budget to social media to communicate and reach customers. It is

difficult to measure a real return on investment, though many studies have

sought to quantify this sum.

How the Use of Social Networks Influences Buying Behavior

There is a strong consensus among scholars and practitioners that developments

in information technology (IT) affect several aspects of marketing in significant

ways. In particular, the role of information technology in influencing buying

behavior has been well recognized. A central concern in marketing,

organizational buying behavior has been an important domain of scholarly

investigation for a long time [78 (https://www.omicsonline.org/open-

access/social-networks-and-the-buying-behavior-of-the-consumer-2375-4389-

1000163.php?aid=64942#78)-82 (https://www.omicsonline.org/open-

access/social-networks-and-the-buying-behavior-of-the-consumer-2375-4389-

1000163.php?aid=64942#82)]. The use of new information and communications

technology allows for a better flow of information and thus a greater connection

between the different actors.

Social networking websites act as a platform for bringing together people with

similar interests, beliefs, and ideas. Users of social networking websites connect

to each other with the purpose of finding and exchanging content. Social

networking can also be used are for self-disclosure and self-representation and

thus create and manage a social or even a professional identity (Haythornthwaite

& Wellman, 1998). Social media, especially social network sites, might be an

important agent of consumer socialization because it provides a virtual space for

people to communicate through the use of internet.

Social media provides three conditions that encourage consumer socialization

among peers online. First, blogs and social networking sites all provide

communication tools that make the socialization process easy and convenient

(Muratore, 2008). For example, in virtual communities Ahuja and Galvin (2003)

find that new members can be socialized easily into virtual groups and quickly

learn task-related knowledge and skills through their interactions with other

members. Second, increasing numbers of consumers visit social media websites

to find information to help them make various buying decisions (Lueg & Finney,

2007). Third, social media provides vast product information and evaluations,

acting as a socialization agent between friend and peer by facilitating education

and information (Gershoff & Gita, 2006; Taylor, Lewin, & Strutton, 2011).

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In line with this opinion Taylor, Lewin, and Strutton (2011) find that online

consumers' attitudes toward social network advertising depend on socialization

factors (i.e., peers). According Wang, Yu and Wei (2012), online consumer

socialization through peer communication also affects purchasing decisions in

two way: directly (conformity with peers) and indirectly by reinforcing product

involvement. Lueg and Finney (2007) further suggest retailers should encourage

such communication by setting up tell-a-friend functions on websites because

they find that peer communications online can influence consumers so strongly

that they convert others into internet shoppers. The rapid growth of social media

has revolutionized methods of communication and sharing information and

interests, redefining the priorities of businesses and marketers and creating a

new place of interaction and communication among people (Yogesh & Yesha,

2014).

A key business component of social media is that the tool allows consumers to

evaluate products, make recommendations to contacts, and link current

purchases to future purchases through status updates and Twitter feeds. In

addition, the use of social media presents a valuable tool for firms in which a

satisfied user of a product can recommend that product (good or service) to

other potential users. Forbes and Vespoli (2013) investigate consumers who

made a purchase of an item based on the recommendation of a peer or contact

via social media. Their results indicate that consumers are basing their buying

decisions on recommendations from people they would not consider "opinion

influencers or leaders." Sharma and Rehman (2012) find that positive or negative

information about a product on social media has a significant overall influence on

consumer purchase behavior. Thus, companies could influence opinions through

the word-of-mouth effect among consumers by encouraging them to

recommend their products through social. Online word-of-mouth communication

allows consumers to share and obtain information from a variety of groups of

people—not only from people they know—and it has a greater impact than

traditional marketing tools marketing (Ratchford, Talukdar, & Lee, 2001; Lee,

Cheung, Lim, & Sia, 2006; Katz & Lazarsfeld, 1955). In fact before making any

purchasing decision, especially when buying something new, many consumers

check other consumers' recommendations (Kim & Srivastava, 2007).

Consumers researching on the online community had a sufficient amount of

inquiries to make their decision. According to Li, Bernoff, Pflaum, & Glass (2007),

50 percent of adult users of online social networks recommend products that

they like. One of the main advantages of online social networking is the ability to

create and manage a diffuse network of weak ties. Information exchange on

social networking websites happens between a larger and broader group of

actors, compared to offline exchanges, and encourages the amassing of as many

contacts as possible without deepening connections between the actors in order

to gain business advantages. These benefits are transferred to consumer

behavior.

In fact, the network effect is the extra utility that a consumer derives from the

consumption of a good or the service when there is an increase in the network

size of that good or service. The literature has identified two types of network

effects (Katz & Shapiro, 1985). Growth in the size of the network increases the

value of the network to all users. Facebook is a leading social network, and

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several authors have conducted studies on its use and how it can influence the

purchasing behavior of consumers. Pietro and Pantano (2012) find that

enjoyment is a key determinant of social networks usage as tool for supporting

purchasing decisions. They also suggest a casual positive relationship between

the attitude of customers toward social media and behavioral intention.

Leerapong and Mardjo (2013) focus on the online purchase decision and through

the study of Facebook, examine the factors that influence their decision. In this

study, customers ranked in order of importance relative advantage, trust,

perceived risk, and compatibility as the factors that encouraged or discouraged

them from purchasing product through Facebook. The academic literature on the

subject shows that the spread of social networks and their use may affect the

behavior of social actors.

Methodology

This study presents the results of the review of 111 academic papers selected

from a large pool. Direct network effects have been defined as those generated

through a direct physical effect of the number of purchasers on the value of a

product (e.g., fax machines). Indirect network effects are seen in the market for

systems, where the consumer's utility function does not directly depend on the

adoption decision of other consumers.

Selected papers demonstrated a focus on studying the effects of controllable

factors that influence consumer behavior. The papers selected for the review

were published after 1955. Out of the 111 papers, 64 were published between

the years 2000 and 2014 and 47 between 1955 and 1999. The majority of

papers were drawn from the Journal of Electronic Commerce Research, the

Journal of Consumer Marketing, the Journal of Information Management, and

the Journal of Internet Research. The elements identified in the literature as

influencing online buying behavior were grouped into three main categories and

five subcategories, each one including several of these elements. The selection

of papers and the review and allocation of the web experience elements to one

of the above categories and subcategories was done by the author, in order to

ensure the conformity of the selection criteria. A minimum of one literature

reference was necessary for including a given component in the classification.

Discussions and Conclusions

Analysis of the literature has shown that social networks can bring about a

certain degree of influence on the choices of consumers changing their buying

behavior. In fact, the use of new information and communications technology

allows a better flow of information and thus a greater connection between the

different actors.

The use of social networks is a valuable tool that helps businesses increase the

chances of survival through a the word-of-mouth effect among members of the

virtual community. That finding is confirmed by the arguments of many

researchers, but needs a further study to examine the reasons that are the basis

of this influence.

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