Chapter one: Introduction
This chapter provides general background information regarding online purchasing behavior with an insight into the advantages and disadvantages of e-commerce in general and then specifically in Kuwait. The history of online shopping and internet retailers is presented to better understand e-purchasing behavior alongside a description of general theories of consumer online purchaser behavior and online shopping in Kuwait. The problem definition, research questions and methodology and limitations of the study are then presented, concluding with an outline of the thesis structure.
With advances in technology, specifically in the field of electronics and telecommunications, direct business and commerce with new retail approaches have emerged in recent decades to transform the business world. Due to the increase in the number of internet users and developing network technology, new forms of trade have grown from these advances particularly in Electronic Commerce (EC) a term introduced by Kalakota and Whinston in 1997. Electronic commerce has become one of the primary characteristics of the internet era and a significant method of doing business. According to Jelassi and Enders (2005) EC includes e-trading of digital and physical goods all trading steps: online marketing, online ordering, e-payment and distribution. Kalakota and Whinston (1997) pointed out that EC has two forms: business-to-consumer (B2C) and business-to-business (B2B). According to Molla and Licker (2001) B2C retailers offer their products and services to their customers. In the last decade, Khalifa and Liu (2003) stated that ‘we have witnessed a substantial growth of internet based on services, both from traditional companies and pure internet business that are developing online services’.
Despite apparent growth there are no reliable statistics concerning E-commerce in Kuwait. However there are indications that the volume of e-commerce in Kuwait is growing slowly as discussed by Al-Sabah (2009) Kuwait Financial Forum, the Central Bank Governor stating “We expect growth but so far we have not found a proper to be estimated for 2010, it depends on so many variables”. In research shown in Economist Information in 2006 involving over 100 countries regarding availability of e-commerce, Kuwait came 50th. As the business world recognised the advantages of such socioeconomic changes, Kuwait began to take note of the advantages of electronic trading and commerce including the set up and development of measurements of electronic trading facilities and venues across the country (Al-Shati, 2009). As e-commerce is newly introduced in Kuwait, in order for Kuwaiti firms to reach world standards there needs to be research in different contexts of e-commerce such as online retailing to utilize opportunities and avoid risk.
As observed by Lin (2003) the key to success in e-commerce depends on knowing customers and studying a customer’s viewpoint. The internet has singlehandedly created a concept shift away from more traditional methods of shopping. Studies by Joines et al. (2003) indicate the number of internet users is constantly increasing which signifies online purchasing is also increasing. Oppenheim and Ward (2006) agreed with Joines et al. (2003) explaining rapid increase was due to the growth of use of broadband technology combined with a change in consumer behaviour. Hollensen (2004) added that the internet has developed into a “new” distribution channel and evolution of this channel and e-commerce. Constantinides (2004) pointed out that in the influence of the consumer the first step was to identify certain impact aspects when purchasing online regarded as dimensions.
Numerous and varied studies have been conducted worldwide to identify the advantages and disadvantages of e-shopping. Bridges and Florsheim (2008) argue that online shopping has advantages for both consumers and retailers. From a consumer’s point of view they found e-shopping allows a lower price, different alternatives of products/services, and customized products. Additionally they established retailers benefited from online shopping as it allowed them to reach a maximum number of customers, reduce communication costs and rapid transportation. However, e-shopping has also been criticized as online shopping may be considered non-trust worthy due to concerns of security of privacy (personal and financial information), lack of examination of the products, lack of human interaction and a concern the quality of the products will not reach customer expectation. From a retailer perspective the disadvantages of online shopping are providing high quality and creating special services can be very costly for the firm and may not be a good incentive to make consumers purchase (Kim and Forsythe (2009) and Lee et al. (2006).
Whether it is a traditional market or online market, Hollensen (2004) pointed out that the retailer should understand the online consumer purchasing behaviour and how individuals make decision and buying choices. Therefore, Kotler and Armstrong (2007) stated that the marketers have developed different theories that can explain why consumers interpret information provided by e-retailer in a certain way, and thereby understand certain behaviours. Several authors have set out different definitions of consumer behaviour. According to Dr. Perner “consumer behaviour is study of individuals, groups, or organizations and the processes they use select, secure, use, and dispose of products, services, experiences, or ideas to satisfy needs and the impacts that these processes have on the consumer and society”. Hollensen (2004) and Constantinides (2004) agreed that consumer online purchasing behaviour is a process of various factors and influences experienced by a consumer before finally purchasing products online.
Online consumer behaviour researchers have therefore examined the adoption of technology for e-purchasing in different aspects. There appears to be no constant model of online purchasing adoption and behaviour as it depends on the nature of adoption as influenced by characteristics or social issues; Theory of Diffusion of Innovation (DOI) Roger (1983). In order to investigate consumer online purchasing behaviour, Theory of Reasoned Action (TRA) and Theory of Planned Behaviour (TPB) are considered dominant theories to measure online purchase intention and attitude behaviour, with Decomposed Theory of Planned Behaviour (DTPB) (Taylor and Todd 1995) the extended TPB. On the other hand, one essential model for development technology usage perspective is the Theory of Technology Acceptance Model (TAM) Davis et al. (1989), which developed into the Online Shopping Acceptance Model (OSAM) (Zhou et al. (2007).
E-commerce researchers have measured different approaches for understanding online consumer behavior. Chen and Corkindale (2008) and Hernandez et al. (2009[a]) measured factors that influence consumer’s online purchasing behavior from the perspective of innovation adoption and accepting technology. Moreover, other authors examined trait attributes, situational factors, web site quality, and individual factors and influences on attitude and intention of consumer purchasing online (Monsuwe et al. (2004); Liao and Shi (2009); and Vazquez and Xu (2009)). Chen and Crokindale (2008) agreed attitude and intention have a strong relationship with acceptance of technology and the decision of purchasing online. In addition, innovation characteristics were considered significant factors that influence of technology adoption and purchasing behavior (Rogers, 1983).
Therefore in order to understand online purchasing behavior it is important to measure different factors that may influence e-shoppers and determine online shopping based on insight from technology adoption innovation diffusion literature. This study will therefore present the Liu Model (2004) using it to identify factors that influence Kuwaiti consumer purchasing online. It will also measure the relationship between characteristics of internet retailers/consumers and characteristics of innovation, allowing the research to examine the impacts of these characteristics on consumer decision making and then purchasing behavior.
1.2 Online purchasing
1.2.1 History of Online Shopping
In the 1990s online shopping emerged as a technological breakthrough and novelty in the business arena. Strengthening year on year in 1994 the first of its kind, an online bank was opened and Pizza Hut offered pizza ordering on their web page. Netscape then presented Secure Sockets Layer (SSL) to secure transactions, an essential feature of e-shopping. In 1995 Bezos launched Amazon.com, one of the most successful online businesses worldwide, followed by ‘e-bay’ an online auction site. By 1997 an estimated 41 million people were shopping online. With advances in technology in 1998, electronic postage stamps were introduced, whereby individuals could download and print stamps after paying a fee. In 1999, with the first online shop in the UK, The Virtual Mall was also launched, considered the first UK graphical internet shopping mall. The online shopping market developed rapidly from this point as the consumer gained in confidence and knowledge.
In 1991, Kuwait University connected all university campuses together with the internet using International Business Machine (IBM) then known as BITNET with the help of Ministry of Communication (MOC) university campuses together. This network was limited to e-mail and other minor services. The National Science Foundation (NSF) agreed to expand the internet services to Kuwait in 1992 (Hussain, 2003).
1.2.2 Kuwaiti Consumer Attitudes Towards Online Shopping
Online shopping is a relatively recent phenomenon that has gradually expanded worldwide reaching Kuwait. Compared to traditional stores, e-shopping is far from the target customer in efficacy and provides significant advantages in time saving and low costs. Although developing online shopping in Kuwait advances slowly, it is establishing a solid base as it incorporates a certain lifestyle, is a convenient option and its adventurous nature is attractive to Kuwaiti youths. With these factors increasingly dominant in daily routine, purchasing online has become a natural option in countries such as the USA and economic areas of the EU and the GCC ( Ma’arafy et al. 2007). Common products selling in Kuwait online are from the USA, the UAE and Asia. According to Forrester research (2008), “Global e-commerce spending in 2000 was 132 $ billion, and expected to spend more than 1 trillion by 2012”.
In GCC capitals, the usage of online shopping behavior is different in the USA compared with and European and Asia Pacific cities. In Kuwait the online shopping concept is relatively in its early stages, however the adoption of online purchasing is expected to grow continually in coming years. With a high level of penetration in neighboring countries online such as Saudi Arabia and UAE, Kuwait will not be far from this diffusion of web shopping. Among the GCC, Kuwait lies 3rd with 10.7% in terms of e-commerce penetration, against 25.1% UAE and 14.3% in Saudi Arabia (Field, (2008)).
According to recent worldwide research, as shown in Table 1.1, Kuwait’s internet user growth has jumped from 5.8% of the population in 2000 to over 34% in 2008 and five times more users in the same time period and with further growth expected.
Table1.1: Growth Internet Users in Kuwait
Source: world wide statistics.com
According to Al-Bahar (2009), Kuwait Consumer Adaptors online shopping distinguishes between local and international websites when purchasing online for many reasons. Kuwaiti consumer purchasing online and local websites are still in their infancy and under development. Thus, consumers are oriented to external websites they have established reputations, are trustworthy and provide an assurance of quality of their products. Express delivery firms such as Aramex and DHL compete to provide their services for delivery products in efficacy and effectiveness to encourage customers to e-purchase (Al-Abdullah, 2009).
However, according to Al-Awan, (2008) e-shopping in the Kuwait market is still in its development stage through lack of organization. In order to enlighten and educate consumers, huge effort needs to be made with responsibility on the retailer to reach their maximum number of potential customers in order to realize value. Recently online businesses have started to establish themselves as limited e-firms providing products and services for Kuwaiti customers.
1.3 Problem definition
With the adoption of Kuwaiti consumer online purchasing low, the penetration of e-commerce in Kuwait remains relatively slow with a lack of studies relating to Kuwaiti e-shopping adoption.
Consumer e-purchasing awareness:
Due to a lack of consumer awareness of online shopping it has not been used widely in Kuwait.
As online selling is different to offline selling, it is necessary to fully understand consumer behavior in order to set up business strategies for the long term. In addition the rapid development of technology related to the internet enhances the shopping experience and encourages potential customers to purchase online. It is therefore critical for e-retailers to identify what factors influence the consumer when e-shopping.
1.4 Research objectives
The overall objective of this research is to gain a deeper understanding of online purchasing behavior in Kuwait and factors affecting their buying decision process. This study is therefore focusing on the following objectives:
- To investigate the key factors affecting online purchasing behavior of Kuwaiti consumers.
- To explore the impact of the decision making process on Kuwaiti consumers purchasing behavior.
- To determine the relationship between factors influencing purchasing behavior and the decision making process.
1.5 Research Questions
To fulfill the purpose of this research and reach the stated objectives related to consumer purchase online behavior the following research questions need to be addressed:
- What are the main factors influencing Kuwaiti customers online purchasing?
- How do these factors affect online purchasing behavior?
- What is the impact of the decision making process on consumer online purchasing behavior?
- What is the relationship between factors influencing behavior and the decision making process for e-shopping?
1.6 Research methodology
This study’s approach is deductive, because it measures factors that affect online shopping to explain Kuwaiti consumer online behavior taken from previous studies in different countries. It is mainly explanatory, developing a deeper understanding of the online purchasing behavior of Kuwaiti consumers while investigating varied opinions related to local e-commerce, alongside which factors affect their purchasing behavior. To a certain extent it is exploratory because of a lack of previous research in the online purchase behavior in Kuwait and Gulf region. The study is also mildly descriptive due to previous research of online market phenomena conducted in different countries and extended to Kuwait.
Moreover, this research is quantitative in nature using primary data for the survey questionnaire as the main tool of data collection in order to discuss online Kuwaiti consumer purchase behavior. The questionnaire was randomly distributed either in person or through email. The total sample size 500 was distributed in Kuwaiti firms, ministries, universities and public places with 360 respondents. The data collected from the questionnaire is then used to identify relationships and connections between these variables to achieve the study’s objectives.
In the course of this research a number of limitations were identified as follows:
- As the research examines consumer online shopping behavior without specifying the type of product exchanged whether tangible or intangible, it is limited in its scope.
- This study is limited to selection factors covering aspects of Kuwaiti consumer online purchase behavior disregarding other variables of satisfaction, trust, social aspects and situational factors.
- As with all research using survey data the sample may not be fully representative of the actual behavior in the population, as it is impossible to directly compare our data with data collected on the State of Kuwait level on online purchasing behavior due to time factors.
- Investigation focuses on online consumer behavior mainly from the customer’s perspective rather than the retailer’s perspective.
- This study evaluates only the online adoption purchasing behavior without evaluation of service quality offered by distinct websites.
- With a lack of previous research in this topic in Kuwait and the Gulf region, there is little, if any, comparative literature review or use as a framework.
1.8 Thesis structure
In the first chapter; an overview of the research area is given, introducing e-commerce in general, then in Kuwait. This is followed by a presentation of the country relevance, the problem definition, the research objectives and questions, the research methodology and the limitations of the study. Chapter Two provides a comprehensive review of relevant literature concerning the research to draw an understanding of dominant theories that explain online consumer behavior, followed by factors that influence consumer online purchase with an integrated consumer making decision process. Chapter Three covers the research design and methodology exploring the methodology of the strategy of collecting data and analysis of the survey questionnaire to achieve the objectives. In Chapter Four, data analysis presents the empirical data collected with analysis and a survey discussion of the results. Finally in Chapter Five conclusions drawn from the overall study are summarized with recommendations made for future research in the subject area.
Chapter Two: Literature Review
In this chapter an overview and examination of theories of adoption and online technology acceptance behavior from a global perspective is presented, with a comprehensive review of relevant studies conducted on consumer behavior purchasing online with the decision making process.
Interactivity is considered a primary principle for the World Wide Web (WWW) with Lee et al. (2006) arguing that “interactivity is the extent to which users can participate in modifying the form and content of a mediated environment in real time”. The WWW allows unprecedented access to information and markets which has impacted societies globally with people able to search for information and/or purchase product/service online. Factors influencing consumer online purchasing behavior have been explored between 2004/09. Ha and Stoel (2004), Lee et al. (2006) and Hernandez et al. (2009) [b] analyzed the online behavior from the perspective of innovation adoption and accepting technology by identifying the consumer acceptance of innovativeness and frequency of shopping online. Lin and Wang (2008) focused on the decision making process arguing that consumers depend on their experience with repeat shopping. Broekhuizen and Huizingh (2009) agreed adding experience will lead to a strong relationship between different variables (such as saving time/effort, enjoyment and price attractiveness) and intention to purchase. The research of Monsuwe et al. (2004) and Liao and Shi (2009) explored situational factors, trait attributes, individual factors and website quality and impact on attitude and intention of consumer purchasing online.
This review will therefore cover wide-ranging theories considering the features and benefits of numerous models proposed by such authors studying online consumer behavior.
2.2 Technology readiness and Self-Services Technologies
While customer innovation adoption behavior and diffusion of innovations have been investigated for decades, recent interest has turned toward Self-Service Technologies (SST’s). SST’s involves new service access provided via new channels to meet customer demand in an effective and efficient way. Many technological innovations face resistance from customers, due to a lack of experience and uncertainty. Therefore research involves varied measurements such as: innovation characteristics, service quality, individual differences, ease of use and usefulness. Liljander et al. (2006) agreed personal traits suggest influence on customer adoption of SSTs. A study by Parasurman (2000), presented the attitudinal measurement “Technology Readiness (TR), peoples propensity to embrace and use new technologies for accomplishing goals in home life and at work” stating TR is considered a factor influencing SST’s. The same author explained an individual’s positive or negative feeling toward technology is dominant identifying TR consists of multi-measurements of: Insecurity, Discomfort, Innovativeness and Optimism. The latter, Optimism refers to the positive view of technology and beliefs of control that enable users to increase convenience, efficiency and flexibility, while, Innovativeness is people’s tendency to open up to technology. Discomfort is an individual’s perceived lack of control of technology and has a strong negative influence on SST’s. Insecurity refers to lack of trust in technology and its ability to work effectively. Notably, optimism and innovativeness are considered highly TR individual contributors, with discomfort and flexibility considered to have high level inhibitor attributes decreasing TR. Liljander et al. (2006) proved in their research a positive effect of TR on customer’s attitude towards using SST’s and their website evaluation, finding technology linked with convenience, freedom and control as vital when building positive attitudes towards using SST’s.
2.3 Original theories of consumer online behavior
Having reviewed numerous forms of literature no singular constant model has been identified for innovation diffusion and adoption. Innovation technology depends on the nature of adoption influenced by social theory or characteristics of innovation such as the Technology Acceptance Model (TAM) devised by Davis et al. (1989).Therefore diffusion theory and other factors have been widely used to guide consumer behavior research.
Theory of Reasoned Action (TRA) and Theory of Planned Behavior (TPB) are dominant theories examining consumers online purchase intention and behavior. TAM is considered an initial model for technology usage development, as it is customized to understand the adoption of computer-based technology in the workplace and is used in many studies. Conversely other researchers criticized TAM, because it explores simply the technology side. TRA has evolved from TAM, determining individual attitude toward and behavioral intention to use this new technology. TPB is considered another update from TRA. Theory of Planned Behavior identifies the behavioral intention of purchase online influence with its attitude to technology. Rogers (1983) created a Diffusion of Innovation Theory (DOI) that illustrates adoption of innovation dominant over time in social systems. This theory depends on critical elements, the time of adoption and characteristics of innovation.
2.3.1 Technology acceptance model
By using Theory of Reasoned Action as a theoretical base Davis et al. (1989) created a Technology Acceptance Model. TAM is identified a viable paradigm for examining consumer adoption for the new technology and information technology. The genuine TAM determined the actual use of technology, attitude toward using this technology connected with beliefs to define behavioral intention to use new technology as explained by Liu (2004) and illustrated in 2.1. TAM focused on beliefs about the usefulness and ease of use to be a main role in technology adoption behavior. Perceived Usefulness (PU) refers to the degree of potential individual perception that use of new technology will enhance improving performance Davis et al. (1989). Perceived Ease of Use (PEOU) is identified as an individual perception of using technology not requiring extra effort. Perceived Enjoyment was added later by Davis et al. (1992) and considered “essential motivation in adoption of new technology, the extent to which the activity of using computer is perceived to be enjoyable in its own right, apart from any performance consequences that may be anticipated”. In TAM, behavioral intention to new technology usage was determined by a person’s attitude toward using this technology. In addition TAM evolved with an updated version proposed in 2000 by Venkatesh and Davis called TAM2. This new model was influenced by subjective norms, image and output quality.
Having examined PU, PEOU and enjoyment in different shopping experiences, Lee et al. (2006) and Bridges and Florsheim (2008) found that seeking hedonic benefit depends on perceived enjoyment through online experience. Hedonic elements may encourage internet use, but not necessarily online buying. Furthermore, an individual consumer may be oriented to seek experiential value through enjoyable browsing or shopping online or for their own fun experience. Seeking utilitarian benefits also relies on perceived ease of use and satisfactory outcomes, in addition to influencing the purchase directly. Utilitarian orientation defined by Bellenger and Korgaonker (1980), Babin et al. (1994) and To et al. (2007) observes orientation or motivation seeking instrumental value to minimize time and effort shopping and cost saving or seeking convenience. Acquired benefit depends on whether the mission of shopping is completed or not. The e-retailer’s focus providing utilitarian benefits more than hedonic benefits will increase or be completed efficiently during the process of online buying and future intention.
2.3.2 online shopping acceptance model
Zhou et al. (2007) proposed an extension model of TAM called “Online Shopping Acceptance Model” (OSAM). This model considers a general view of online purchasing acceptance from the consumer’s perspective. These authors also pointed out that in spite of TAM Davis et al. (1989) being broadly used to examine online purchasing environment, it does not analyze specific online shopping characteristics. Therefore OSAM integrated consumer factors in traditional markets and theories may be added to TAM factors to re-examine the issue in the context of online shopping as showed in 2.2. Moreover, OSAM have been developed to predict and explore consumer acceptance e-purchasing by incorporating the beliefs, intention, and attitude behavior relationship into the perspective of perceived usefulness which was replaced by perceived outcomes to cover potential benefits and e-shopping risks. Shopping orientation and motivation have been added from traditional market factors considered antecedents of online purchasing intention and online experience as factors that construct during navigation of e-shopping sites. Also, satisfaction as mediators between behavior and intention has been added. OSAM considers a strong predictor of continue intention to purchasing more than perceived usefulness. Furthermore, this model includes consumer demographics and normative beliefs with their influence on e-purchasing intention. Exploring the development of TAM by introducing OSAM will enhance our understanding of different factors that affect consumer behavior intention.
2.3.3 Theory of reasoned action
Fishbein and Ajzen (1975) formulated a “Theory of Reasoned Action” (TRA), which illustrates behaviors expressed by individual intention to perform a behavior from psychological social factors and aims to examine measurements of that behavior. Based on Marshall et al. (2009) and Lee and Park (2009), they pointed out correlations between beliefs, subjective norms and attitude affects on formation of behavioral individual intention. This intention is influenced by subjective norms referring to the individual’s perception with outside influences to perform (or not) a specific behavior to purchase as illustrated in 2.3. While attitude refers to an individual attitude behavior, negative or positive, toward adoption of innovation and brand overall which creates their beliefs about the consequences of adopting and the brand’s attributes (Jobber, 2004). Beliefs are defined by the person’s subjective probability that performing a particular behavior will produce specific results. Four types of belief attitude towards to e-shopping were identified by Vijayasarathy (2002); shopping experience, product perception, customer services and customer risk. This model therefore suggests that external stimuli influence attitudes by modifying the structure of the person’s beliefs (Ajzan and Fishbein, 1980 and Ajzen, 1991).
Further, TRA provides a strong theoretical basis for studying motivation related decision-making. Using this theory is expected to enhance our understanding toward attitudes and behavioral intention of online shoppers.
2.3.4 Theory of planned behavior
The Theory of Planned Behavior (TPB) can be appraised as an extension of TRA according to Ajzen (1985) used to predict buying behavior based on Bagozzi and Kimmel (1995) and De Cannière et al. (2009). A central element of this theory is the individual intention to perform a given behavior as shown in 2.4. Ajzen (1991) identified intention as ‘how individuals are willing to try and how much effort they are planning to exert, in order to perform the behavior’. The same author and Chen and Corkindale (2008) state this theory includes an additional element which is an individual perceived behavioral control (PBC). Compeau and Higgins (1995) cited by Dennis et al. (2009) defined it as a judgment of one’s ability to use a computer. PBC is compatible with Bandura’s (1977, 1982) concept of “perceived self-efficacy which is concerned with judgments of how well an individual can execute courses of action required to deal with prospective situations”. In PBC attitude and subjective norms factors can predict intention and behavior.
According to TPB, PBC together with intention can be used directly to predict behavioral achievement. This model proposes the intention impact and mediates among these factors: 1) intentions are the immediate antecedent of behavior, 2) fully mediate on impact of attitude towards behavior and 3) intentions partially mediate the impact of perceived behavioral control (Ajzen, 1985, 1991; Fishbein and Ajzen, 1975) as illustrated in 2.4. Furthermore, Ajzen stated that the relative importance of predictors in the TPB would be different among behaviors and situations. On the other hand, TPB components can be used according to De Cannière et al. (2009) to form the experience after purchasing.
2.3.5 Decomposed Theory of planned behavior
In 1995, Taylor and Todd demonstrated that better comprehension of the relationship between beliefs and antecedent of intention need to be combined as attitudinal beliefs as DTPB as shown in 2.5. They argued that DTPB is a strong model, more advanced and purer than the TRA and the TPB model. It was identified that, due to diffusion innovation theory, attitudinal beliefs contained three characteristics of an innovation that affect the adoption: relative advantage, complexity and compatibility (Rogers, 1983). This model contains the main elements of normative beliefs and Perceived Behavioral Control (PBC). PBC reflects behaviors and consists of two main elements: facilitating conditions (Traindis, 1980) and self efficacy (Ajzen, 1991) regards the comfort usage of innovations. As a result we can see DTPB integrated in most theories and models related to consumer behavior.
2.3.6 Triandis Model
Similar to TAM, TRA, and TPB, the Triandis Model (TM) was presented by Triandis in 1980. This author suggested a theoretical network relating to attitude and behavior to many variables such as and will biological and cultural factors. This model proposed the probability of performing behavior is determined by a number of measurements: habits, facilitating conditions, and intention as shown in 2.6. Furthermore, the behavioral intention is function of social factors (including norms, self concept and roles), affect and perceived consequences of acting the behavior, with facilitating conditions determining all necessary resources and sustaining performed a behavior, such as time, money and expertise. Chang et al. (2005) pointed out that due to the construct of the Triandis Model it created a lack of TAM, which believed that usage is preference not prevent an individual from using IS. As TM has been adopted widely in consumer behavior in recent years, it has been applied in technology adoption studies. Cheung et al. (2000) viewed implementing TM to explore the use of internet/WWW and understand user intention using online means for shopping and work.
2.3.7 Criticism of TAM, TRA and TPB theories
In 2009, Kim and Forsythe explained most of these theories tested master models only, which may increase the errors of generalizing results if implemented on different technology. Cheung et al. (2005) and Dennis et al. (2009) claimed TAM, TRA and TPB ignore other factors including: consumer characteristic, environmental influence, medium characteristics, situational factors and consumer traits. A theoretical model that includes TAM and other factors was proposed by Monsuwe et al. (2004) to consider the attitude of online shopping and the behavioral intention trying to implement TAM in the best way. Leder et al. (1999) and Chen and Crokindale (2008) determined that PEOU and PU in the TAM model was not always a significant key role. In addition Lee et al. (2006) explained the Theory of Acceptance Model presented PU and PEOU leading directly to the intention to use the technology without determining the attitude, either negative or positive, of using this system by the individual. In 2009, Taylor and Strutton argued that TAM no longer represents an appropriate study for online purchasing behavior, but PEOU and PU remain main key predictors of behavioral intention. Usage of this theory has decreased as it was not statistically significant in predicting size of the technology acceptance, despite in a relatively short time being widely accepted on the internet as a purchasing and a marketing channel.
2.4 Theory of diffusion innovation
2.4.1 Definition of diffusion innovation
Adoption and diffusion have been widely used in consumer behavior research (Liu, 2004). The innovation diffusion theory provides a set of innovation characteristics that may affect adoption decisions (Rogers, 1995). The difference between adopter and innovator must be determined in order to investigate and understand the Diffusion of Innovation (DOI). Innovators are individuals willing to use the technology without influences. Engell and Blackwell (1982) identified adoption as the “individual process for using technology mentally and behaviorally sequences that lead to acceptance and continue to use”. Early adopters are considered innovators by McDonald and Alpert (2007). These authors pointed out that early buyers for new products or services act under influence of word of mouth and other people's experience or include some adopting independently. Innovativeness arose, was defined and presented in the work of Midgley and Doweling (1978) as “is the degree to which an individual makes innovation decisions independently of the communicated experience of others”. Chen and Crokindale (2008) cited Williams et al. (1994) stating “DOI paradigm brings in a constant demand while innovation direction of how the recently new technology been introduced, communicated, evaluated, adopted or rejected and re-evaluated by consumer”.
Innovation classification investigated by Robertson (1967) was cited by Hand et al. (2009) and Hansen (2005) divided into three types based on consumer behavior toward technology: continues, dynamically continues and discontinues innovation. Hansen regarded discontinues innovation a crucial type, because it not only relates adoption of a new product/service, but also customizes the buyer behavior pattern more over online buying representing this type of innovation. Dynamically continues innovation considers product of new technology will not fundamentally change consumer behavior. Finally continues innovation views minor technology will not change consumer behavior. Lin (2008) agreed that innovation diffusion theory consists of perceived innovation characteristics influencing consumer usage of an innovation. This study also confirmed that direct and positive influence of innovativeness towards consumers' adoption behavior online shopping on future internet shopping intention and retailer should target more innovative users.
2.4.2 Innovation characteristics
According to Rogers (1983) innovation characteristics are considered important measures affecting adoption and consisted of 5 dimensions: 1) Relative Advantage, 2) Compatibility, 3) Complexity, 4) Divisibility or Triability and 5) Communicability.
As well as innovation diffusion integrating with adoption research and connecting with adoption decision and behaviors to a number of innovation characteristics, each type of innovation should be visualized as a foundation based on specific attributes in the adoption context. The innovation characteristics considered a potential influence of consumer adoption have been identified as: ease of use, compatibility, relative advantage, perceived risk and enjoyment.
18.104.22.168 Relevant advantage (RA): Rogers and Shoemaker (1971) and Rogers (2003) view RA as “the degree to which an innovation of technology is perceived as being better than the idea in current methods” compared to existing products affecting the speed of adoption. It also drives more value for consumer online shopping and consists of different elements that make online shopping unique leading eventually to consumers shopping online such as: shopping convenience (saving time), production information (different information for one product in one channel), merchandise (ease customization products, variety of products) and price reduction (Hansen, 2005).
22.214.171.124 Perceived Ease of Use (PEOU): Monsuwe et al. (2004) measure ease of use in the context of the internet as a shopping medium and identify certain elements that affect the consumer such as: experience, control (availability of knowledge and resource), computer playfulness (computer interaction) and computer anxiety. Zeithaml et al. (2006) strengthened these findings adding an additional dimension of the website playing a role in ease of use i.e.: search function, download speed and navigation. Perceived ease of use from the retailer enables consumers to feel comfortable and confident to participate in the shopping process.
126.96.36.199 Compatibility: Tronatzky and Klien (1982) cited by Kleijnen et al. (2009) concluded that compatibility refers in the online shopping context to the degree an individual who receives shopping through the internet is consistent with their current value, habit and past experience, needs and lifestyle. Findings by Jobber (2004) concurred and it is one of few factors of Rogers' theory related to adoption in the context of online shopping. Moreover, when conducting shopping over the internet is compatible with existing processes and systems, then customers employ less effort to deal with incompatibility. Slyke et al. (2007) argued perceived compatibility impacts on beliefs, as beliefs influence attitudes which subsequently impact on intention, therefore compatibility beliefs impact on attitude as well as intention.
188.8.131.52 Perceived Risk (PR): Taylor and Strutton (2009) referring to Bradach and Eccles (1989) identify PR as ‘a consumer's belief about the likelihood of gains and losses being associated with a given consumption decision'. Many consumer scholars including Hansen (2005) identified several types of risks such as social, privacy, performance and product. In the context of shopping online, Chang et al. (2005) analyzed perceived risks of online shopping into two approaches: general risk and specific risk. The general risks covered general risk perception of buying online goods; while specific risks were concerned with system security, privacy infringement, fraudulent merchant behavior product risk and credit card fault. The most common concern of consumer shopping online is perceived risk due to uncertainty of product value (product risk) and/or perceived financial risks (private and credit card information). Such research found that the key reason for consumers not shopping online is fear from invasion of personal information and theft of financial data. Subsequently, perceived financial risks have a significant influence on perception consumer adoption of purchasing online. Monsuwe et al. (2004) commented that “past experience decrease consumer perceived risk level associated with online shopping”. This agreed with the findings of Lee and Turban (2001) that connected perceived risk with trust, because online shopping converts the physical salesperson to buttons and privacy with security has an impact on trust, thus resulting in powerlessness for the consumer through online shopping. Ranganathan and Jha (2007) noted that combined security, privacy and offline delivery and return will influence and enhance consumer trust and increase purchase intention. Finally, Taylor and Strutton (2009) support the negative correlation between privacy concern and behavioral intention.
184.108.40.206 Perceived Enjoyment (PE): The concept of perceived enjoyment to stimulate consumer behavior and acceptance technology has been supported by numerous authors. By comparing and analyzing works of Liu (2004) and Monsuwe et al. (2004), PE has been divided into two approaches. In the “internet adoption” situation, perceived enjoyment is integrated with internet activities such as emails, browsing and downloading. Mounsuwe et al. (2004) forecast the dimension that constructs PE and influences the “consumer behavior” context as escapism, pleasure and arousal. In the same way, positive effects of PE increase the searching information behavior and experimental experience that eventually impacts shopping online behavior for an individual.
In conclusion innovation characteristics have a significant impact of consumer adoption to purchasing online, with RA and compatibility having the greatest influence on online shopping technology innovation and consumer adoption decisions. PEOU, PE and perceived risk are significant factors that influence consumer intention and attitude of purchasing online behavior with accepting the innovation technology. As stated by Liu (2004) the model of consumer online purchasing is integrated with the decision making process in addition to other variables: consumer, e-retailer variables and product moderating as illustrated in 2.7.
2.4.3 Criticism diffusion innovation theory
The Diffusion Innovation Theory (DOI) criticized by Vishwanath and Goldhaber (2003) and Chen and Crokindale (2008), provides inconsistent results and delineates insufficient relationship between the characteristics of innovation and adoption. Moreover, the same authors judged this theory as lacking in the marketplace, because of DOI inefficacious regard to performance prediction and control function. In 2009, Taylor and Strutton approved predicting online consumer behavior by using behavioral models such as TAM and diffusion of innovation theory may no longer adequately capture internet consumer behavior, due to online purchasing behavior and internet usage both reaching the post-adoption stage and peak level adoption.
2.4.4 Innovation decision process
Ha and Stoel (2004) used IDP as a foundation for their studies to evaluate the adoption of innovation for search information or purchase products online. Rogers, (1995) defined the decision process as an individual process to adopt innovation. The same author implemented this process for adopting apparel purchase online connected with characteristics of innovation as illustrated in 2.8. The aim of this process is to collect and seek information in order to obtain relevant information the consumer needs to evaluate attitude toward innovation to reduce their uncertainty of adoption innovation leading to make the eventual decision (purchase online).
2.5 Attitude, intention toward and actual buying behavior
Behavior purchasing online measurements have been conducted by numerous authors. Notable perspectives presented by Limayem et al. 2000 and Cao and Mokhtarian (2005), consider e-shopping intention in some studies dependent variables while other research considers actual online shopping, whereas in other studies, attitude to online purchasing are investigated as dependent variables as shown in Table 2.1. Attitude toward online shopping was identified as a specific action representing individual overall negative or positive beliefs and evaluation of the behavior. Intention to shop online was identified by Pavlou and Chai (2002) as customer intention to exchange, share information online and employ e-transaction. However both acknowledged that the stronger the positive intention behavior, the more likely individuals perform the behavior; highlighting actual online purchasing determinants consist of adoption of online buying, the amount spent online and frequency of using shopping.
Table 2.1: Determinants of Independent Variables of Online Shopping
Measurements of online purchasing intention
Measurements of actual purchasing behavior
Measurements of attitude toward online purchasing
Perceived behavioral control
Ease of use
Perceived behavioral control
Ease of Use
Source: Limayem et al. (2000)
Comparing works between Ha and Stoel (2004) and Kim and Park (2005), purchase behavior was determined by satisfying consumer uncertainty (perceived financial risk) and increasing convenience (price and products variety) factors. George (2004) measured consumer behavior of online purchasing by trust in the internet, attitude toward it and actual purchasing.
Recent contradictory research of Dennis et al. (2009) referred to Fishbein and Ajzen (1975) and Ajzen and Fishbein (1980) stating positive attitude drives online consumer behavioral intention and enhances other perception leading to actual purchase online, as shown in 2.9, which illustrates the difference between theoretical models and empirical studies. Some consumer behavior research explains that attitude and intention to purchase are dramatically changing due to the impact of adoption of the internet on consumer decisions.
2.6 the buyer decision process
2.6.1 General Definition of Consumer Decision Process
Researchers continue to measure consumer behavior purchase online with the assistance of the decision process. Blackwell, Miniard and Engel (2001) defined a series of interlinked multiple stages a consumer may pass through such as information collection, evaluation of alternatives, the purchase itself and post-purchase evaluation. 2.10 shows these stages, which form the consumer decision-making process. Many frameworks propose a consumer decision process in spite of several authors not seeing any fundamental difference between the traditional and the online buying process. Constantinides (2004) argues the process has one additional step which is building trust or confidence, whereas the repetitive loops increase the process of adopting the information which leads to updating the model (Zellwegger, 1997; Butler and Peppard, 1998).
2.6.2 Online consumer decision process
The decision making process can be conducted online and offline. The buying process starts with problem recognition. Jobber (2004) explained the degree to which the consumer intends to resolve the problem depends on two issues: the magnitude of the discrepancy between the desired and present situation and the relative importance of the problem. At this stage, the marketers need to determine the factors and situations that usually trigger consumer need recognition. In the online context, Lin and Wang, (2008) forecast the first step to making a decision is to recognize brand awareness and brand association, factors that help the consumer to identify certain brand products.
The second stage in the consumer decision process starts when problem recognition is sufficiently identified. Information search includes identification of alternative problem solutions. This includes internal search (relevant memory information and reference to personal experience) and external search a personal resource, commercial sources (advertisement) and personal experience. The objective of information search is building up the awareness set. Kulviwat et al. (2004) who referred to Wright (1975) explored motivation factors on searches such as: perceived benefit and cost, ability to search, buying strategies (website satisfaction), situational contingencies (time and pressure) and consumer characteristics (browsing enjoyment). Savolianen and Kari (2006) measured criteria for evaluation searching online either acceptance or rejection of the website or hyperlink as illustrated in 2.11.
The first step in evaluation, consumer use information reduces the awareness set and arrives at final brand choice and series consideration. They have been found to use one or more evaluation procedures that depend on them and their buying decision. Online evaluation is characterized by an evaluation website and services offered as Savolianen and Kari (2006) appraised, and then evaluating the information regarding the product attributes among other competitors, subsequently formulating a convenient feel toward decision purchasing. Further investigation for online consumer evaluation was conducted by Lin and Wang (2008) regarding product consequence, personal value and website trust.
Consumer ranks brands and forms purchase intentions as Kotler et al. (2006) determined, in the evaluation stage. Consumer's purchase decision influenced by two factors shown in 2.12 can come between purchase intention and purchase decision. Attitude from others and unexpected situation factors can influence purchase intention. Moreover, consumer decision is influenced heavily by perceived risks and the amount varies with the amount of purchase uncertainty, money at stake and consumer self-confidence.
After purchasing the products/services, the consumer will be satisfied or dissatisfied and will engage in post purchase behavior. This stage is crucial for the retailer because of the relationship between consumer's expectations and the product's perceived performance. The quality of products/ services is generally a key determinant as Jobber (2004) pointed out, and the role of retailer acting as problem solver can help customer satisfaction, then reduce cognitive dissonance (negative experience from purchase products or services). Also, the purchaser provides retailer's feedback website usage or /and quality of the product based on their experience which will develop in features of the relationship between the buyer and the website. Liu (2004) emphasized at this stage, the consumer experience involves several aspects: ‘decision confirmation, experience evaluation and future response intention'. Chaffey (2007) highlights the relative importance of instruments of the internet in supporting the purchaser through each of the stages of the buying process as shown in Table 2.2. We can see that the process of decision making is supported and connected by different aspects, and identify tools that can enhance achievement in each of the decision steps.
Table 2.2: Tactics to Support Customers through Different Stages of the Buying Process
1- Problem Recognition
Offline advertising and media mentions are important in generating awareness of digital channels as a means by which customers can find, evaluate and purchase products.
2- Information (or supplier) search
Identify different searching behaviors. Surfing website not searching is more important to groups with a high proportion of non-directed information-seekers.
Site content should communicate the features and benefits of the brand in what may be fleeting visits to the site or an in-depth analysis. Also, increase customer buying behaviors according to internet experience.
4- Decision making
Influencing decision making can be used to provide customers incentives to capture an e-mail or postal address and deliver detailed brochure by post, or provide a callback facility so the customer can be contacted to help decision.
Once the decision has been made to purchase, make the purchasing straightforward through the user -centered design.
Use e-mail and the web site to provide customer service and support. E-mail notifications of an order and dispatch can help reduce post purchase dissonance.
Source: Chaffey (2007) and DoubleClick (2003)
2.7 E-Service and adoption
2.7.1 General Definition of Adoption
The diffusion-adoption process determined by Chaffey (2007) and Kotler et al. (2006) referred to Rogers (1983) classifying those trailing new products as innovators, early adopters, early majority, late majority, or laggards. The adoption process is identified by them as ‘the mental process through which an individual passes from first learning about an innovation to final adoption', while adoption is defined as an individual decision to become a regular user of the product. Table 2.3 illustrates the description of each type of process. From definition of type of adopters in Table 2.3, e-retailers must target the innovators and early adopters, playing a key role in the success of innovation and adoption of online purchasing by spreading the word to other consumers who might be interested in the benefits of shopping online.
Table 2.3: Definition of Adoption Process
Type of adopters
Individual who are often adventurers, first who adopt a new idea or innovation and willing to take a chance at some risk.
Individual guided by opinion leaders and adopt new ideas early but carefully.
Individual usually deliberate and cautious in their approach to adopt ideas before the average person.
Individual characterized more cautious and skeptical, adopt innovation only after most people have tried it.
Are tradition-bound people, they are suspicious of changes and adopt the innovation only when it has become something of a tradition itself.
Source: Kotler et al. (2006) and Jobber (2004)
Adoption purchasing online is always integrated with completed steps of the decision making process. The adoption of the internet is classified into two types, full adoption which is a complete decision process and partial adoption that can be identified as the first of three steps of the decision making process (problem recognition, information search and alternatives evaluation).
Table 2.4: The Categories of Adopters of the Internet as a Shopping Medium
Current Adoption Behavior
Future Usage Intention
Will Continue to Visit
A consumer who uses the internet to search for product/service information and evaluate alternatives without intending to purchase through the internet
A consumer who has previously purchased through the internet but has no intention to continue to purchase products/service online
Will Continue to Purchase
A consumer who visits the internet for shopping purposes who has not purchased through the internet yet, but who intends to continue to visits the internet and will purchase products/ services online in the future
A consumer who has previously purchased through the internet and intends to continue to use the internet to purchase products/services online
Source: Liu (2004)
Liu (2004) identified in Table 2.4 four types of adopters in the context of shopping online with respect of the decision making process: steadfast, latent purchaser, dropout purchaser and steadfast purchaser.
By exploring types of adopters with respect of the decision making process in Table 2.3 non-adopters can be identified as shopper to visit website for comparing alternatives or getting information. While online purchaser adopters implement one or more steps of the decision making process.
2.7.2 E-Service Adoption
While internet delivered electronic-service is more and more available for the consumer, there are not sufficient studies to evaluate customer potential adoption (Dehbashi, 2007). It is crucial to differentiate between studying a basic buying transaction and adopting e-services. The e-service adoption decision is basically different from most standard e-commerce transactions. Therefore, the adoption decision is more difficult due to the establishment of the long term relationship between the consumer and e-retailer. According to Featherman and Pavalou (2003) when consumers buy via e-service they receive access to operations provided other than product buyers, where customers receive tangible goods. Furthermore, e-service is influenced by different factors. Despite e-commerce adoption being different to e-service adoption, there are some similar factors influenced such as risks and trust factors.
2.8 Consumer Variables
TAM, TRA and Diffusion Innovation Theory have been criticized because of focusing investigation on consumer behavior from a technological aspect only. Consumer purchases are influenced strongly by culture, social, personal and psychological characteristics. For the most part, marketers cannot control such factors, but they must take them into account. It is considered important to illustrate these characteristics for the case of a hypothetical customer (Kotler et al., 2006). Dennis et al. (2009) demonstrated factors influence consumer behavior in the social aspect including consumer traits. However, innovation characteristics, individual characteristics, demographics, social innovation and psychological variables also influence e-consumers making their individual choices.
2.8.1 Shopping Motivation
An understanding of motivation lies in the relationship between needs, drives and goals. Kotler et al. (2006) outline motive as a need that is sufficiently pressing to direct the person to seek satisfaction. Psychologists have developed theories of human motivation. Abraham Maslow sought to explain why people are driven by particular needs at particular times. In the context of online shopping, motivation according to Vazquez and Xu (2009) pointed to utilitarian motives and hedonic motives having a strong influence on online information search and online purchase intention. This contrasted with other author's buyer behaviors theory and argued that attitude toward online shopping influences on motivation of online shopping motivation.
In 1978, Midgley and Doweling presented innovativeness as the degree to which an individual receives new ideas and makes decisions independently without other experience, with innovativeness a good predictor for new product innovation. Innovativeness and demographics have the advantage of identifying innovators in early stages of adoption steps (Rogers, 1995). McDonald and Alpert (2007) argued that innovative is no longer related to behavior; instead it is defined in terms of time of adoption called “actualized innovativeness”. This is based on Midgley and Doweling (1978, 1993) whereby rather than types of information taken into account influenced by the actions and communications of others, the decision to adopt or not is identified as “ innate innovativeness”.
2.8.3 Internet Self-Efficacy
People's judgment of their capabilities to organize and execute courses of action required to attain designated types of performances' is recognized by (Bandura 1986 cited by Hernandez et al. 2009[b]). Ranganathan and Jha (2007) observed the consumer online orientation for shopping consists of self efficacy. In addition, Hernandez et al. (2009)[b] investigate found an individual is human aspects will influence their accumulate experience of adopting and acceptance of the IT. Self efficacy is therefore considered vital, because an individual should feel comfortable and confident in their capability to use online services for purchasing or browsing from the beginning. Moreover, self efficacy is divided into “computer self-efficacy” and “internet self efficacy”, whereby computer self-efficacy is experience, internet skills and knowledge of computer regarding the individual and technology.
2.9 Retailer variables
E-consumer research explores different aspects studying consumer purchase behavior including the decision process adopting internet, because consumers go through a process of choosing products and then acquiring them from the retailer by selecting alternative sales channels. Subsequently, consumer perceived characteristics of retailer influence online consumer purchasing behavior.
2.9.1 Different Models of Online Service Qualities
Varied research has tried to provide models to encourage e-retailers understanding of different impacts of the website quality on customer buying decisions. Zeithaml et al. (2000) developed a foundation of measuring online service quality known as “E-SERVQUAL”, including the following dimensions: ease of navigation, efficiency, access, reliability, responsiveness, privacy/security, assurance/trust, site aesthetics, and price knowledge. Wolfinbarger and Gilly (2003) presented critical determinants of consumer perception of e-purchasing experience “eTailQ”. Their model was also extended from “E-SERVQUAL” and suggested that the judgment of quality online site strongly related to website design and fulfillment/reliability factors, but privacy and security obtained from website design as shown in 2.14. Another model was presented by Santos (2003) consisting of two main determinants (incubative and active dimensions as illustrated in 2.13. Incubative dimension identifies the proper design of the website implementing new technology for easy access with comprehension interaction with web, while active dimension identifies as “the good, support, fast speed, and attentive maintenance that a website can provide to customers”.
The “e-TransQual” model by Bauer et al. (2006) was developed due to a lack of “eTailQ” and “Santos model” not covering all aspects of consumer's quality evaluation. They applied transactions process-based scale measurements of evaluate service quality. This model identified five quality measurements: enjoyment, process, functionality/design, responsiveness and reliability as shown in 2.14. Their findings led to integrated utilitarian and hedonic e-service quality determinants being in one scale.
2.9.2 Perceived Characteristics of Internet Retailer
Different classification of perceived characteristics retailer such as: website design, shopping incentives and service quality may persuade the consumer to adopt online shopping. In order to evaluate the consumer effectiveness of the e-retailer, several criteria were examined and the most significant relating to websites are: clarity image, quality service, service feature (pre-sales and post-purchase sale). Chaffey (2006) identified a website as “A file of information residing on a server connected by an address to the World Wide Web, and a Web site may include text, photographs, illustrations, music, or other computer programs”. In 2008, Bridges and Florsheim pointed out that providing effective and efficacy characteristics will attract customers more than entertainment characteristics.
220.127.116.11 Site Design
In the same manner of evaluation design and atmosphere in offline shopping, website architecture and design involves marketing and IS disciplines. In addition, website design affects the way visitors perceive retail websites and use. Technical attributes such as user interface, a visual design and navigation continue to influence the e-customers purchase intention (Collin, 2000 and Taylor and Strutton, 2009). Chaffey (2006) measured different elements in website design in order to attract customers including: personalized, highly visual and comprehensive understanding.
18.104.22.168 Shopping Incentives
Collin (2000) highlighted different incentives to attract customers for shopping in a specific website: shopping cart, different type of payment and other services. Money-back guarantee policies can be seen as a process-based trust production mechanism which will then transfer into incentives (Chang et al., 2005).
22.214.171.124 Customer Services
“Customer services aim to assist customers in receiving the ultimate product utility and satisfaction” Chaffey (2006). Site features such as website design and good information play an important role in customer services and influence their intention to shop online Chang et al. (2005) and Gay et al. (2007)). Furthermore, in order to attract visitors, Collin (2000) emphasized the value of adding information such as review products or discussion forums in retailer webs. According to Chaffey (2006) broadening roles in responding to customer needs and introducing a customer tracking system service in the website to increase levels of attention will involve a record of individual purchasing habits or special interests, inventory tracking device and payment preference. Besides offering order sale movements, reporting forms could be considered another type of tracking system.
126.96.36.199 System Usage
Gay et al. (2007) stated that development of search engine technology has been crucial for web-users to access information speedily. Many factors influence the search process such as ease of navigation, website atmosphere, products attributes (price/promotion and quality) (Lin and Wang 2008). Website design and quality associated with purchase intention are important antecedents to online consumer behavior. In 2006, Hawang and Kim agreed websites relate to content, perceived information load, effectiveness of website load and information privacy guarantee positively influence attitude toward using a website. The same authors argue a website should be easily checked for information collected as well as how this information is used in and outside the firm approved by customers.
Everard and Galletta (2005) pointed out the negative influences on consumer online buying intention: errors, poor style and incompleteness of information in the website. In addition, Collin (2000) argued a successful website should provide interesting content such as extra information including a searchable database basic catalogue of products. Other authors viewed service quality from another perspective as Hackman et al. (2006) state that offline market models examine the behavioral intention from variable antecedents and service quality can be applied to the online market environment.
Finally, academic researchers agreed that companies should involve consumers using an e-retailer storefront with numerous incentive motivation techniques (promotion, coupon offering and loyalty points) and provide quality service. Moreover, useful information based on advanced and up-to-date information should be provided. Perceived internet retailers achieving sustainable development e-business encourages individuals to use an e-storefront by providing them with a friendly website and secured e-platforms, alongside providing a facility to develop customer experience.
2.10 Product category as a Moderating Factor
The consumer decision of whether to purchase online or not is influenced by product characteristics considered an essential factor in the online shopping context. To find out what products are more likely to sell online is crucial. Consumer's products examination online are limited, due to a lack of physical contact, the need to feel, touch and try or smell. Products could be categorized into two groups: goods and services (Lui and Wei, 2003). Monsuwe et al. (2004) classified product characteristics in the online context as: products with uncertainty quality (ex. accessories, clothes and furniture), products require personal knowledge (e.g. lotion perfumes and makeup) and products require experience (e.g. computers and cars). There are several schemes to classify products, as a retailer must determine the majority online demand of products to identify the most preferable products to purchase online.
Besides classifying products as convenience shopping and specialty goods, Phau and Poon (2000) categorize products in the online shopping environment based on tangibility (low/high) products. Low tangibility products are considered digital items such as computer software or tickets, whereas high tangibility products are products used on a physical basis. Lui and Wei (2003) argued that in an online environment, products and services considers intangible due to inability of customers to differentiate services from products.
2.11 Relevant studies in online purchasing behavior
2.11.1 Recent Empirical Studies
In 2009, Kim and Guota examined consumer behavior purchasing online and the difference between potential customers and repeat customers based on information processing theory and mental accounting theory. This study conducted in South Korea chose a non-famous online book website and the sample size of study was 1028 responses (218 potential customers and 810 repeat customers). The objective was to help e-retailers develop customized strategies for attracting customers to create initial sales and repeat sales. This study tried to find differences between potential customers and repeat customers in online purchase decision making and consumer purchase behavior. The results of this research were that value perception of the transaction made for purchasing online had an overall judgment in decision making influenced by non-monetary factors (perceived risk) more than monetary factors (perceived price ) for potential customers, while perceived price influenced stronger than perceived risk for repeat customers.
Sicilia and Ruiz (2009) in Spain investigated consumer purchase behavior regarding consumer cognitive responses within a purchasing task. The authors developed a specific website for this experiment based on a real computer website with a sample size of 1179 participants. These cognitive responses were affected by the amount of information found within a website. Their research presented a conceptual integration between the research focusing on persuasion through the website and information overload and agreed on the “inverted U-shape” relating to the content and amount of information on the website. Their research confirmed the findings of other studies that too much information causes more selective and prejudice processing. Also, the type of cognitive responses performed by individuals appears to depend on the amount of information contained in the website. Moreover, this confirmed the findings suggesting that customers need to develop cognitive effort to select the information and to orient themselves within the system.
Ha and Stoel (2009) investigated factors influencing customers acceptance of e-shopping integrated into TAM and confirmed the robustness of this theory. Their study was conducted in the USA at a university (298 respondents) whose students had experience in browsing and/or purchasing products online. Additional factors are enjoyment, trust and e-shopping quality. E-shopping quality measured four dimensions of the website design, privacy/security, customer services and experiential/atmospheric. The structure model reveals that e-shopping quality, perception of enjoyment, trust and usefulness, which influence customers adoption (or predictive) attitude toward online-shopping support the previous result. On the other hand, perceived ease of use does not influence customers e-shopping.
Soopramanien and Robertson (2007), conducted a study in the UK to measure social-demographic variables, beliefs and attitudes toward internet shopping affecting both adoption decision and usage of online shopping channel. Their result differentiated between usage and adoption of internet shopping in accordance with three fundamental consumers' behaviors: purchaser online or buyers, browsers, and non-adopting online or non-internet shoppers with sample size 894 (730 buyers, 46 browsers, and non-internet purchasers). Different groups of consumers exhibited a significantly different attitude towards the internet as a shopping channel. These differences in attitude explained consumers' perception of the risks and benefits of shopping online. Browsers are behaviorally different from buyers in perceiving online retailing environment and its operation, while a consumer chooses different courses of action based on the perceived beliefs of using online.
2.11.2 Online Shopping Trends in Kuwait
According to the latest global online survey on internet shopping habits, conducted by research specialists ACNielsen, more than 875 million consumers worldwide have shopped online in the past two years. This is an increase of around 40% in the online shopping market and more than 50% of internet users worldwide have made a minimum of one purchase in the past month (Jaques, 2007).
The survey was conducted in Europe, North America, Asia Pacific, Latin America and South Africa and asked internet users about their online shopping experience including what products were last purchased as illustrated in 2.15.
On a global level the most popular products purchased via the internet are books by 34%, as shown in 2.16, followed by games/DVDs/videos (22%), reservations/airline tickets (21%), and clothing/ accessories (20%).
At the beginning of the millennium, the internet penetration in Arab countries was low and the general economic outlook not attractive. According to Economist Intelligence Units, in 2005 - 2007 among Arab Countries, Kuwait is placed in 5th stage in electronic readiness. As Kuwait's economy became more robust and internet penetration grew the support of the Kuwaiti government towards IT plans has continued with constructive steps taken in the same domain. E-government provides special opportunities and incentives for the e-retailer to encourage SMEs to grow with the ease of the convenient K-net payment method. The purpose of this service is to maximize the accuracy and efficiency of the financial transactions of customers and optimize the operational cost. Al-Hashmi, (2008) highlighted with easy accessibility and transport there are of low costs due to low petrol prices, meaning delivery of products becomes more cost effective. Another payment method introduced for customers is buying cash on delivery (COD) or using credit cards through authorization. A successful rate of delivery services in different business fields in Kuwait has attracted many SMEs, particularly in restaurants. Successful e-commerce models have also emerged, maachla.com and 6alabat.com illustrating many SMEs are a good indicator of consumers' increasing awareness of e-commerce. In Kuwait there are numerous digital pioneers armed with cutting edge and interactive online stores (Alshahed newspaper 2009). Due to the relative small size of the Kuwaiti market, firms need to be highly competitive to remain in business. Different people have established businesses and operated well, however other individuals who also took the initiative have not survived. Only firms with a bright future could afford to stay in the market for 2-3 years regardless of the type of products selling online (flowers, PC's real estate services and cars).
A successful example of online business in Kuwait is maachla.com. This is an online and tele-business grocery delivery service for residential markets using marketing channels for co-ops' products. Launched in May, 2007 the unique nature of this business is it is run by 5 team members with different backgrounds. Maachla.com differentiates from others by not having any inventories. They buy the requested items from the coop and then deliver it directly to the customer without the need for any storage and hence, avoid unnecessary inventory costs (Khazaal 2009). In a similar way, 6alabat.com, Kuwait's first website delivery service acts as a mediator between customer and many restaurants chains in Kuwait such as: LOFAT, Pizza Hut, KFC and Japanese or Chinese food: Wasabi, Maki and Osaka.
In 2000, q8car.com was launched in Kuwait. The website faced strong competition with firms in the same business at time when Kuwait's economy was not attractive. After more than 8 years, it managed to build a name, trust and cover expenses. According to Al-Abdullah, car dealer (2009) this site helps customers selling and buying while understand market prices.
In the field of telecommunications, kw.zain.com is considered of significant importance in Kuwait. Zain online provides mobile online services besides offline stores. The online services started within the last 10 years. Among various services, the customer can view and settle bills, recharge prepaid lines, view MMS messages, create and edit new line subscriptions without going to branches. Zain online target different layers of society and provide different services that suit their needs such as businessmen and youths (Zain.com 2009). In the business field the stock market in Kuwait has evolved with online brokerage expanding among stockers. Brokerage online is considered significant offering numerous services. Kuwait Stock Exchange website is one of the most important websites in Kuwait that enables brokers in searching for information about companies and current market stock. Numerous companies with their websites according to Al-Dar (2009) support the e-exchange stock by encouraging Kuwaiti Consumers selling and buying electronically through mediator webs such as tadwel.com. NBK.com provides e-services for customers internally and externally, by offering different services for both customers and business. In the tourism field, AL-Jazeera.com, a Kuwaiti low cost airline, supports e-servicing by providing an e-ticketing service. This service encourages customers to use their website for reservation purchasing in the same time.
Globally, Amazon.com is one of the largest websites Kuwaiti consumers can trust, due to their global reputation. This website hosts online stores and auctions notably books and video entertainment. E-bay is another renowned online auction site where consumers can find products from pens to garden tools and even cars and real estate. Gap.com offers clothing for all the family, whereby customers from around the world can order clothing delivered within weeks.
It is important to note the success of Kuwaiti online business depends on the majority of Kuwaiti citizens being young using the internet and being more familiar with such services. The expats rate in Kuwait is also increasing annually and there is potential to attract this particular segment with businesses already providing for them in their own countries and becoming part of their core shopping. Improved educational levels of Kuwaiti citizens and more disposable income/funds means citizens may increase their online purchasing.
Chapter three: Research design and methodology
This chapter explains the overall research design and research methods used in the course of this study. Beginning with an outline and detail of the research design, this chapter then moves on to explore the research objectives, the research questions, the hypotheses and the research strategy. Notably this involves detailing analysis of the data collection (questionnaires) and data analysis techniques used which help to explain consumer purchase behavior in Kuwait.
3.2 Research Design
3.2.1 Research Theoretical Purpose
Research categorizing based on purpose, according to Saunders et al. (2007) and McDaniel and Gates (2006), are classified into three types: Exploratory, Explanatory and Descriptive, and can be implemented in any research with more than one strategy and more than one purpose.
These authors explained exploratory research as comprehending the problem or the principle by understanding the nature of the problem with no clear definition of what characteristics or relations are important. In addition ambiguous research questions with unclear guide theory are available. The objective of exploratory research is to explore the information required for future research which according to Robson (2002) enhances the research design with data collection methods and selection. Saunders et al. (2007) identified three main standards for exploratory research which are: searching of the literature, talking to experts in the field, and conducting focus group interviews.
Explanatory research is beneficial in confirming studies examining a specific situation, problem, or phenomena by exploring a relationship between variables in order to examine and construct theories. Furthermore, it aims to explain the data collected with analysis, more than experiment predicting explanation according to Saunders et al. (2007).
Finally, descriptive research provides a description of situations involving patterns suspected in the exploratory research. It is designed to measure the characteristics described in the research questions. Saunders et al. (2007) explained conducting this type of research, it is crucial to have a clear understanding of the prior phenomena to the collection of data. Descriptive research however is limited by the potential inability to establish relationships among variables.
Having looked at each of these categories the objective of this research is considered mainly descriptive, explanatory, and into some extent exploratory. It is considered descriptive because of the extent of previous research on this phenomenon on consumer online purchase behavior and from collecting data from the distributed questionnaire. It is explanatory research due to the explanation of the relationship between the decision making process and factors that affect shopping online (perception of the innovation characteristics, perception of internet retailer characteristics, consumers' variables and the product categories) that influence on e-purchasing. Finally, this study is regarded as exploratory research to some extent, because it explores the relationship dimension of shopping online and other variables based on previous theories.
3.2.2 Research Methodology
Generally, researchers set many questions before beginning the actual research. These questions are considered an essential part of any research. Yin (2003) pointed out how different approaches to research methodology depend upon the research problem defined and the nature of the information gathered. Saunders et al. (2007) agreed the selection of methodology research can be either qualitative, quantitative or a combination of both.
Quantitative research approach is identified by Fielden (2008) as the “extent to which data are tightly aligned with theoretical arguments”. The objective of the quantitative approach is the measurement in quantity information related to the phenomena, then statistically analyzed to reach a conclusion. This may be referred to as mathematical testing -hypothesis through identifying certain hypothesis resulting from a theory.
Qualitative research according to DeRosia and Christensen (2009) citing DeRuyter and Scholl (1998)
“…is often used to study phenomena about which relatively little is known. In this context, the purpose of [qualitative] research is to formulate theories and/or hypotheses” by providing comprehensive detail of this theory through examination and demonstrating concepts about certain complex situations or problems.
This qualitative method depends on collecting, analyzing and explaining the data through observation. It also focuses on words, historical research, case studies, observations and other descriptions rather than numbers. Saunders et al. (2007) pointed out that in any research, researchers can use a combination of quantitative and qualitative methods especially in research that requires decision quantification.
Based on our research purpose and questionnaire, this research will use a quantitative research approach. As this research relies on scientific knowledge through theory examination, it will be able to enhance the understanding of Kuwaiti consumer purchasing online behavior. This quantitative approach can be achieved by understanding the specific dimensions influencing consumers purchasing online perceptions.
3.2.3 Research Theoretical Approach
Choosing appropriate strategy research is considered crucial, because it plays a major role as a foundation of the research questions. Three main elements should be clearly defined: research approach, objective and source of data.
With general research approaches classified into inductive and deductive, Saunders et al. (2007) identified inductive as the development of a theory as a result of observation of empirical data, whereas deductive approach is viewed as a “research approach involving the testing of a theoretical proposition by the employment of a research strategy specifically designed for the purpose of its testing”.
The inductive approach according to Malhorta and Birks (2006) is considered “a classical research which can be used in social science”, with several steps beginning with collecting data after complete comprehension of research facts, then identifying research hypotheses, selecting samples and analyzing these samples to measure the final result. Thus, fundamentally it considers a cause-effect relationship be made between variables.
In addition Malhorta and Birks (2006) described the deductive approach as a survey strategy that can be used in business and management research. This approach begins by building hypotheses and principles through formulating relationships between variables. This is pursued testing and examining results, to delineate a conclusion by either confirming the theory or modifying for a new outcome. According to Remenyi et al. (2002) there are two significant principles of deductive approaches: reductionism and generalization. The idea of reductionism is to enhance problem understanding by reducing to the simplest possible element, whereas generalization is identified assuming causality where independent causes lead to the observed outcomes.
As the goal of this research is to measure online consumer purchase behavior in Kuwait based on data collection from a specific survey questionnaire from data collection, this survey considers a deductive research approach appropriate because of the logical selection of the survey strategy. In addition, it does not require control over the behavioral circumstances or events versus the influence of the adoption of online shopping. Finally, a conclusion is drawn of specific cases of consumer e-shopping in Kuwait.
3.2.4 Research Time Horizon
Saunders et al. (2007) emphasized time horizon research as an independent research design and play role research strategy. This time horizon method according to Yin (2003) and Malhorta and Birks (2006) can be selected ranging from “snapshot” to “specific period” depending on the research questions and study needs.
Cross-sectional research - snapshot - is observed by Saunders et al. (2007) as “concerned of studying particular phenomena in a particular time or to compare factors in different firms”. Moreover, cross-sectional is considered a descriptive study with objective finding relationships and influence among different variables in a specific time, also involving perception of a group of the population at the same time.
Saunders et al. (2007) also identified longitudinal research as the capability of observing the change and development of the same phenomena over a long period that may last for an extensive time frame. This type of research permits the measurement of control factors being studied and sustains methods that cross-sectional approaches cannot support. In addition the longitudinal approach is a source of gaining valuable data which leads to powerful knowledge in the development of personnel management and industrial relations over times of change.
Like most business research conducted studies in consumer purchasing online behavior are cross-sectional. This study of consumer e-shopping behavior covers a certain current period of time.
Subsequently, this research is considered a combination of deductive, quantitative, descriptive, explanatory, and somewhat exploratory.
3.3 Research objectives
While the primary objective of this study is to gain comprehensive knowledge of consumer's online shopping behavior in Kuwait and factors affecting their buying decision process it also aims to achieve the following:
- To investigate the key factors affecting online purchasing behavior of Kuwaiti consumers.
- To explore the impact of the decision making process on Kuwaiti consumers purchasing behavior.
- To determine the relationship between factors influencing purchasing behavior and the decision making process.
3.4 Research Questions
To fulfill the purpose of the research, reach the stated objectives and gain relevant knowledge and information directly related to the Kuwaiti consumer's online purchase behavior, the following questions need to be addressed:
- What are the main factors influencing Kuwaiti customers online purchasing?
- How do these factors affect online purchasing behavior?
- What is the impact of the decision making process on consumer online purchasing behavior?
- What is the relationship between factors influencing behavior and the decision making process for e-shopping?
In order to reach the objectives and answer questions in this research, a series of hypotheses have been developed to test this research, as illustrated in 3.1 and summarized below:
H1. Consumer adoption of online purchasing will be positively impacted by their perceptions of: (a) relative advantages, (b) ease of use, (c) compatibility, (d) enjoyment, (e) and negatively impact risk.
H2. Consumers' perceptions of internet retailers' characteristics will positively influence their adoption for purchasing online.
H3. Consumers' variables (internet-self efficacy, shopping motivation, and innovativeness) will positively impact their e-shopping.
H4. Consumers' perception of internet retailers' characteristics (Site design, system usage, shopping incentives and customer services) will positively impact their perception of: (a) perceived risk, (b) enjoyment, (c) compatibility, (d) ease of use, and (e) relative advantages.
H5. Consumer variables (internet-self efficacy, shopping motivation, and innovativeness) will be positively impacted by their perceptions of: (a) relative advantages, (b) ease of use, (c) compatibility, (d) enjoyment, (e) and negatively impact risk.
H6. Product category has a moderating influence on consumers' adoption for purchasing online.
H7. Product category has a moderating influence on: (a) consumer variables, (b) perceived Retailer website characteristics.
H8. Perceived Internet retailer website characteristics impact on consumer variables.
H9. Dimension of Perceived Innovation characteristics influence on each other.
H10. Perception of innovation characteristics of online shopping, perception of internet retailers' characteristics and consumer variables are different for adopter groups: regular visitors, latent purchaser, steadfast purchaser and, dropout purchaser.
As the aim of this research is to determine the factors affecting Kuwaiti online consumer purchasing behavior the following assumptions are made:
- The respondents will provide different information about different products/services they are purchasing frequently.
- As these variables are taken from different studies, we assume implementation, but some of these factors will be less relevant than others.
- E-retailer website and characteristics of consumers have a strong impact on adoption of online purchasing.
Experienced online purchaser responses will be different to browsing purchasers.
The present research seeks to explore the factors and characteristics that influence Kuwaiti consumer online purchase behavior and the relationships between these factors and the decision making process. Online consumer purchasing behavior factors have been examined by numerous authors in research investigating these variables in empirical studies therefore in this study we aim to examine these variables relating to Kuwait using a specifically designed questionnaire.
In order to achieve these objectives, this questionnaire (Appendix 1) was constructed as the primary instrument of data collection and is divided into three main sections:
Section 1: Demographics (9 Questions)
This section presents general information about participant internet users and their history of internet usage and covers age, gender, education level, duration average time spend on internet, the main purpose of using the internet, and the annual purchase online.
Section 2: Group Characteristics (48 Statements)
According to the literature review, it was found that innovation characteristics, consumer variables and website design were the most predetermining criteria in relation to the decision making process for shopping online behavior. While sections were adopted from varied authors as detailed in Table 3.1, the overall connection between these questions was adapted from Liu (2004). Thus, the second part of the questionnaire examined factors and variables that influence consumer purchase online behaviors and is split into the following five subsections:
Perceived Innovation Characteristics:
In this section 19 items are constructed to assist the consumer and their perception to adopt online shopping. The 19 items followed the basic five measurements of purchasing online behaviors and include: Relative advantage (4 items), Compatibility (4 items), Ease of Use (4 items), Enjoyment (3 items), and Perceived Risk (3 items).
In this part consumers examine their ability and stimulation for internet usage and drive them to purchase online. In order to provide the respondents with better orientation to respond to the questions, 3 dimensions including 9 items were used to determine consumers variables in shopping online which include: Internet-self efficacy (3 items), Shopping motivation (3 items), and Innovativeness (3 items).
Perceived characteristics internet retailers:
In order to evaluate factors that affect consumer decision purchasing online, e-retailer websites are considered a primary factor that influence consumer perception and enhance making decisions. Therefore four dimensions including 14 items were used to measure websites which include: Site Design (3 items), System Usage (4 items), Shopping Incentives (3 items), and Customers Services (4 items).
Product classification further influences the decision of consumer purchasing online. This part includes 3 dimensions that may affect consumers.
Decision making process:
Finally, in order to identify the consumer purchasing online behavior, the decision making process and their influence must be considered as an important measurement. This part includes 5 measurements.
The measurement scale in Section Two is a 5-point Likert type scale, used to evaluate the statements, ranging from strongly disagree (1) to strongly agree (5).
Table 3.2: Research Questionnaires Constructs.
Perceived Innovation Characteristics
Lancaster & Taylor (1988); Bradach & Eccles (1989); Kwon & Zumd (1987); Davis (1989); Davis et al. (1992); Herbig & Day (1992); Rogers (1995, 2003); Jobber (2004) and Monsuwe et al. (2004).
Davis (1989); Davis et al. (1992); Childers et al. (2001); Lee & Turban (2001); Lui (2004); Hansen (2005); Chang et al. (2005); Slyke et al. (2007); Ranganathan & Jha (2007); Taylor & Strutton (2009) and Kleijnen et al. (2009).
Bandura's (1977, 1982, 1986); Mildgey & Doweling (1978, 1993); Rogers (1995) and Kotler et al. (2006).
Lui (2004); Chang et al. (2005); McDonald & Alpert (2007); Ranganathan & Jha (2007); Vazquez & Xu (2009) and Hernandez et al. (2009).
Perceived characteristics internet retailers
Collin 2000; Chaffey (2006) and Gay et al. (2007).
Lui (2004); Chang et al. (2005); Hackman et al. (2006); Lin & Wang (2008) and Taylor & Strutton (2009).
Phau & Poon (2000) and Monsuwe et al. (2004).
Lui & Wei (2003); Lui (2004); Chang et al. (2005).
Decision making process
Wright (1975); Butler & Peppard (1998); Blackwell et al. (2001); Jobber (2004); Kotler et al. (2006) and Chaffey (2007).
Kulviwat et al. (2004); Lui (2004); Savolianen & Kari (2006); Lin & Wang (2008).
Source: Based on research
Section 3: Type of products frequently purchased online
The last part of the questionnaire examines the products respondents purchase online.
To achieve clarity the questions were distributed carefully to maintain understanding and simplify the respondents' choices. Also, to ensure the validity and reliability of the questionnaire, the construct was then pre-tested using a pilot version with 20 online shoppers before the final questionnaire was distributed to the respective respondents. The questionnaire has two versions: Arabic and English (Appendix 1 and 2).
3.8 Research strategy
According to Saunders et al. (2007), research strategy is a general plan explaining how researchers answer research questions. This requires identifying the objective of study questions, determining sources of data to be collected, and taking into consideration the constraints of accessibility of time, location, data, money, and ethical issues. In 2003, Yin identified five major strategies in social sciences which are: experiments, surveys, archival analysis, histories and case studies with each one of these types having advantages and disadvantages. Furthermore, the selection of these strategies depends on: 1) form of research question, 2) extent of control over actual behavioral events, and 3) focus on contemporary events as illustrated in Table 3.2.
There are many research strategies used in different scenarios. It is important to choose the most appropriate strategy which can be answer study questions and objectives. According to Saunders et al. (2003) Experiment is considered a classical form of research which refers to the natural sciences, and is highly used in social science research, particularly psychology. In this type of research, small populations are targeted with controlled variables and different experiential conditions.
Table 3.2: Relevant Situations for Different Research Strategies.
Form of Research Questions
Requires Control Over Behavioral Events
Focuses On Contemporary Events
Who, What, Where, How many, How much?
Who, What, Where, How many, How much?
Source: Yin (2003)
Survey strategy on the other hand is mostly used in business and management research. This type of strategy is usually associated with the deductive approach collecting large data from a specific target population. Such data is mostly obtained by a questionnaire and is considered standardized allowing easy comparison. Although this strategy gives more control over the study process, it is time consuming with effort required in designing and bound by a limited number of questions. In addition to the length of questionnaires, language is critical in order to get an appropriate response. The survey strategy in addition to a questionnaire is structured interviews and observation.
Case study as pointed out by Robson (2002) is “a strategy for doing research which involves an empirical investigation of a particular contemporary phenomenon within its real life context using multiple sources of evidence”. This type of research is useful for gaining knowledge of the research context and the process being used. Furthermore, it can generate answers to the “why”, “what” and “how” questions. Case study includes questionnaires, interviews, observations, and documentary analysis. It examines and challenges existing theory and provides a source of new hypotheses. Case study can be either multiple or single-case study. According to Yin (2003) in a single-case study an in-depth investigation for a single entity has been made. However, multiple-case study is considered more powerful due to analytic conclusions from two or more entities.
Archival analysis is used when there is no control over behavioral events. This type of strategy is usefully applied when the research aim is to describe the incidence or prevalence of a phenomenon or to predict certain outcomes.
Therefore having examined the various options this research is considered a combination of deductive and quantitative in nature, and tries to measure the different factors that influence consumers and their relationship with the decision making process, in addition to overall online consumer purchasing behavior. The aim of this research was to collect the answers on a large scale of purchasers online and formulate the main factors that affect the intention to adopt online purchasing behavior. The survey strategy is found to be the most appropriate research method in order to gain better knowledge of the research area.
3.9 sampling and data collection procesedures
When the strategy research had been chosen, it is crucial to decide which available data will be collected and analyzed. However, for many studies objectives and questions it will be impossible to collect and analyze all the data available due to time limits and often access. The sampling technique provides different types of methods that enable researchers to reduce the amount of data to be collected (Saunders et al. 2007). The same author divided these sample techniques into: non-probability and probability sampling, with these types of sampling most commonly used with survey based research. Probability allows the researcher to interface about the target population from which the sample is drawn. Non-Probability sampling depends on the researcher's judgment of the research rather than selecting sample elements. This type may yield a good prediction of the population characteristics, however as this research is about online purchasing behavior and the target segment is Kuwaiti internet users, the appropriate sampling technique is probability.
500 questionnaires were randomly distributed in universities, ministries, Kuwaiti firms, public places (shopping malls, coffee shops, and health center etc). There were no target groups as this research examined the Kuwaiti consumer e-purchasing behavior in general. Thus, the survey of this study was scattered to reach different layers of society; customers, employees (private and government sectors), universities students, household and SME owners. Of the sampling size 500 were distributed in different places with 360 respondents. Of these, 20 were eliminated due to incomplete responses. This resulted a validity sample are 340 responses.
3.10 data analysis
The research and statistical instruments used in this study are: Factor Load Analysis, Reliability Analysis, AMOS, Stepwise Regression analysis, Descriptive analysis, Correlation Analysis, ANOVA, and Cross tabulation. All of these techniques were employed by using SPSS (Statistical Package for Social Science) Version 15.
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