Which E-Lifestyle Avoids Internet Advertising More?

Which E-Lifestyle Avoids Internet Advertising More?

Amir Abedini Koshksaray (Department of Business Management, School of Management, Islamic Azad University, Tehran, Iran) and Kambiz Heidarzadeh Hanzaee (Department of Business Management, School of Management and Economics, Islamic Azad University, Tehran, Iran)
Copyright: © 2014 |Pages: 15
DOI: 10.4018/ijide.2014100102

Abstract

This study aimed at finding out which e-lifestyles avoid internet advertising more. To this aim, a survey was conducted on 412 students working with internet. Structural Equation Modeling approach was used for estimating the validity of research constructs and multiple regression was utilized for hypothesis testing. According to the findings, individuals with interest-driven e-lifestyle avoid from internet advertising more than others. Novelty-driven, importance-driven, sociability-driven, need-driven, entertainment-driven, and uninterested or concern-driven e-lifestyles avoid from internet advertising, respectively. This study has considered e-lifestyle's avoidance from internet advertising for the first time. It is the first attempt to investigate which e-lifestyle avoids internet advertising more. Also, it is the first study modifying research data according to the significant effect of “the average hours of using internet” and controlling and analyzing the effect of this variable.
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Introduction

Understanding individual differences with respect to their reactions and behaviors affects the decisions related to developing marketing and advertising strategies. By identifying psychological factors of their target consumers, marketers try to promote their business activities and please their customers. However, consumers’ lifestyles are important factors in understanding and predicting behaviors of a group of individuals. Individual difference variables explain the difference of individuals from each other in distinct behavioral patterns. These variables have three managerial applications; first, a group of individuals with similar personality, self-concept, and psychographic characteristics, might be so large in a section to be the target of the company. Second, by expanding the understanding from personality, self-concept, and psychographic characteristics of target market, companies can create advertising messages which optimally benefit from the needs and wants of the target group. Third, the mental position of brands can be determined based on one of the common features of target market individual differences (Moven and Minor, 1998). According to Michman et al. (2003, p. 67), “behaviors related to changing the good or brand by the customer not only result from the fact that they are unsatisfied with that brand, but are caused by the change in consumer lifestyle, as well”. Additionally, Kucukemiroglu (1999) suggest that lifestyles describe individual’s behavior and interactive groups of people. According to Plummer (1974), the more you know and understand your customers, the more effective communications and transactions you can have with them. Hence, studying individual values and lifestyles is considered as a standard tool for both social sciences and world marketers. Bellman, et al. (1999) emphasize that the basic information for predicting shopping behaviors (whether online or offline) is the lifestyle of consumers rather than demographical factors. In other words, to effectively manage a shopping website, online retailers must be familiar with characteristics and lifestyles of consumers (Chu and Lee, 2007). Thus, due to the importance of individuals’ lifestyles, the necessity of investigating it from different aspects of marketing science is clearly understandable. In addition, the increasing growth internet has created a new space of transactions for both consumers and sellers. Based on the studies conducted, iab.net (2011) announced that the income of internet advertising has reached 2.6 billion dollars in the second quarter of 2010 showing 4.1 percent increase in comparison to the first, and 13.9 percent increase compared to the second quarter of 2009. Despite the apparent benefits of internet advertising, statistics reveal continuous decrease in the click rate by the users. According to the institute of Nielsen (2000), click rate in 1995 was about 2% which decreased to 0.3 in 2008 (MediaPost, 2008), and this descending trend continues. Getting used to the novelty of this medium and excessive publication of ads in web pages have created a kind of avoidance from internet advertising (Cho and Cheon, 2004). Avoidance refers to a state where the consumers consciously and deliberately try to avoid from a stimulus (Tellis, 1997). Advertisement avoidance refers to all activities of internet users which distinctly prevent them from being exposed to advertisement (Speck and Elliott, 1997). Advertisement avoidance involves all activities of internet users and prevents their exposure to ads in different ways (Speck and Elliott, 1997). Advertisers need to completely understand the reasons underlying advertisement avoidance to be able to develop strategies for conveying their messages to the target market effectively and efficiently. According to Cho and Cheon (2004), advertisement avoidance can be investigated in three types of cognitive, affective, and behavioral avoidance. One factor which appears to affect the formation of advertisement avoidance is users’ e-lifestyle. Many studies have revealed that lifestyle is an important variable which affects users’ use of internet in different activities (Schiffman et al., 2003; Kim et al., 2001). The features of lifestyle provide marketers and advertisers with accurate and practical information about consumers. This enables them to meet the needs of consumers in complex and competitive markets (Kamakura and Wedel, 1995). This issue gains more importance since internet is increasingly penetrating different layers of society and is facing a variety of lifestyles (Schiffman et al., 2003; Weiss, 2001). Lifestyle segmentation identifies the important and useful segments so that the advertisers can target appropriate consumers and provide more efficient internet ads. Yu (2011) introduced and tested seven types of e-lifestyles. These seven e-lifestyles are need-driven, interest-driven, entertainment-driven, sociability-driven, importance-driven, uninterested or concern-driven, and novelty-driven. Every individual behaves in internet with specific lifestyle. Whether individuals of an e-lifestyle pay attention to an internet advertisement or click on a certain ad depends upon the features of that lifestyle. Therefore, this study seeks to find out which e-lifestyle avoids more than other from internet advertisement.

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