ONLINE SHOPPING BEHAVIORS

The Influence Gender Differences On Online Shopping Behaviors

ABSTRACT

The attitude and gender are vital factors that influence online shopping behavior, toward online shopping attitude residue the poor implicit construct. Moreover, very few studies, if any, have clearly addressed gender differences in online shopping attitude. Using attitude as the multidimensional perception to include cognitive, affective, and behavioral components, current study examines gender differences across three attitudinal components. The results of experimental testing show three distinct components of online shopping attitude and significant gender differences in all three attitudinal components. The results also demonstrate that largest gender difference is in cognitive attitude, representative that females value efficacy of online shopping less than their male equivalents do.

Table of Content

ABSTRACTii

CHAPTER 1: INTRODUCTION1

Outline of Study1

Background of research1

Problem Statement1

Rationale2

Aims and Objectives2

Significance3

Research Question3

Theoretical Frame work3

Limitation of Study4

Assumptions & Limitation5

Reliability5

Validity6

Ethical Concern6

CHAPTER 2: LITERATURE REVIEW8

E-Commerce11

Conceptual foundations12

Product value12

Shopping value15

Critical Differences Between Product Value And Shopping Value18

Relationship Among Different Value Components19

Customer Satisfaction19

Customer Loyalty20

Customer Satisfaction And Loyalty21

CHAPTER 3: METHODOLOGY22

Research Design22

Primary or secondary / Qualitative or Quantitative22

Quantitative Research22

Qualitative Research22

Mixed Method Research23

Experimental Design24

Measures25

Data Collection Method26

CHAPTER 4: RESULTS AND ANALYSIS27

Results27

Discussion29

Appeal Of Website Features: Past Studies32

Website Features: Current Framework33

CHAPTER 5: CONCLUSION35

Future Research36

REFERENCES38

CHAPTER 1: INTRODUCTION

Outline of Study

The number of Internet users is equally divided among genders, more men than women engage in online shopping and make online purchases. This gender gap in online shopping drew attention to role of gender in online shopping and factors that affect men's and women's intention to buy online (Jarveena, 2007:59)

Background of research

While studies of online shopping attitude are widespread in literature, studies of gender differences in online shopping attitude are scarce and reported findings are inconsistent. An extensive review of online shopping literature shows that more men than women buying online in some studies and no significant gender differences in online shopping behavior between genders in other studies. Likewise, the more recent review demonstrates conflicting findings pertaining to impact of gender on online shopping activities. Thus, gender differences in online shopping attitude deserve more attention and better understanding.

Problem Statement

The substantial growth and steady increase of online sales stimulate great interest in understanding what impacts people's decisions to participate in or refrain from shopping online . Among multitude of factors examined in past research as potential determinants of online shopping, attitude toward online shopping demonstrated the significant impact on online shopping behavior Accordingly, better understanding of online shopping attitude is critical for designing and managing effective websites that can help businesses attract and retain online customers.

Rationale

Some studies acknowledge that online shopping attitude is the multifactor construct. In context of using technology acceptance model (TAM) examine acceptance and use of web technologies, distinguish between cognitive and involvement attitudes. They maintain that incorporating the component of attitude in TAM enhances explanatory power of model. (Horrigan2000) A factor analysis data collected from 198 university staff and students about intention to shop online for 17 different products reveals three underlying components of online shopping attitude. They identify these components as convenience, information, and shopping experience and find that three factors explain more variance in predicting online ...