Antecedents and Consequences of the Risk Taking Behavior of Mobile Commerce Adoption in Lebanon

Antecedents and Consequences of the Risk Taking Behavior of Mobile Commerce Adoption in Lebanon

Rima Charbaji (American University of Beirut, Lebanon), Karim Rebeiz (American University of Beirut, Lebanon) and Yusuf Sidani (American University of Beirut, Lebanon)
DOI: 10.4018/978-1-60566-671-6.ch018
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This study was conducted to explore the attitude towards adopting m-commerce in Lebanon. The sample of respondents were asked twenty Likert’s type questions that taped five different areas: (1) Motives based on Psychographics: Life Style and Hobbies, (2) Perceived Ease of using M-commerce, (3) Adopting M-Commerce, (4) Perceived Credibility, and (5) Experience. Two statistical analysis, Chi-Square and path analysis, were used. Factor analysis and reliability tests were used to establish the validity and reliability of the measuring instrument (questionnaire). Path analysis was used in this study to decompose the relationships between the dependent variable “Respondents Attitude towards Adopting M-Commerce” and the independent variables “Motive,” “Experience,” and “Perceived Ease of Use.” The results of this study suggest that the relationship between the independent variables and the dependent variable to be further studied in further research using a larger sample. Having larger sample seems to be crucial in conducting similar studies.
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Commerce is any kind or type of exchange of goods, productions, or property, or the rights to property offered for a consideration to the general public at large1. It is the exchange of something of value between two entities2. However, with the advent of the Internet and the World Wide Web, commerce can be performed electronically, and the process is termed as e-commerce. Thus, e-commerce means conducting business on the Internet. It is mostly referred to buying and selling items on line3. Furthermore, due to the technology revolutions, and wide spread use of the mobile phones across the continents and the countries, entrepreneurs are utilizing the most benefit out of the use of the cell phones. They are using the cellular phones not only for communication purpose (i.e., for information sharing), but also for making commercial use of them.

Economy of the current world, especially infotainment has clearly been inclined towards transactions made by the cellular phones. In addition to these, mobile phones are being used to buy and sell commodities. As the following definition reveals, mobile commerce is the buying and selling of goods and services through wireless handheld devices such as cellular telephones and personal digital assistants4. Wikipedia, also termed mobile commerce (also known as M-Commerce, mCommerce or U-Commerce, owing to the ubiquitous nature of its services) as the ability of one to conduct commerce, using a mobile device e.g. a mobile phone (cell phone), a PDA, a smartphone and other emerging mobile equipment such as dashtop mobile devices5. In this context, Tiwari & Buse (2007:33) has defined m-commerce as: “Mobile Commerce is any transaction, involving the transfer of ownership or rights to use goods and services, which is initiated and/or completed by using mobile access to computer-mediated networks with the help of an electronic device.”

Development in the number of Internet and telecommunications users since the late 1990s has provided firms with new ways to conduct business and exchange information through the development of the e-commerce market. But due to the differences of m-commerce from the other forms of commerce, recent years have witnesses an increasing discussion of the factors affecting customer satisfaction with m-commerce and how m-commerce differ from e-commerce. Based on review of literature, one may conclude that m-satisfaction is a recent phenomena. Most of previous research on m-commerce was about technology acceptance models. Antecedents and consequences of m-commerce has rarely been studied because of its short history. It is really hard to find causal models explaining and predicting m-satisfaction and or m- motivation. End users differ in their m-Commerce knowledge, awareness, perception, feelings and in their intention to accept to use m-commerce. There are different motives that motivate end users to use m-commerce. Different models such as AIDA (Customers’ Attention, Interest and Desire and Action) are used by industry in making promotion decisions. The days are gone when emphasis was placed on super salesperson that could sell any thing. Understanding consumers’ needs lead to customer satisfaction and loyalty. People have private reasons as well as public reasons for using m-commerce. Motives for using m-commerce may represent different levels of Maslow’s hierarchy of needs and an imperative need exists for future research that deals with what motivates end users to use m-commerce.

This chapter is a case study that was conducted to explore the attitude of Lebanese stakeholders adopting the m-commerce. In doing so, this study looks into issues related to the definition of m-commerce, provide general overview of m-commerce, tries to differentiate between e-commerce and m-commerce, provides a thorough literature review on antecedents and consequences of the risk taking behavior of mobile

commerce, draws recommendations based on the literature review relating to the risk taking behavior of mobile commerce adoption in Lebanon, analysis was performed through a survey questionnaire responses to study the relationships between different variables including the socio-economic patterns of the stakeholders, provided a few future research implications and a few recommendations before concluding.

Key Terms in this Chapter

An Exogenous Variable: Is a variable whose variability is explained by causes outside the causal model.

An Endogenous Variable: Is a variable whose variability is explained by causes (endogenous or exogenous variables) in the causal model. The endogenous variable is treated as a dependent variable in one equation and as independent variable in a different equation.

Path Diagram: Is a useful device for displaying graphically the pattern of causal relations among exogenous and endogenous variables.

Path Analysis: Is a unidirectional simultaneous equations model used for studying the direct and indirect effects of variables taken as causes of variables taken as effects. It is important to note that path analysis is not a method used for discovering causes, but a method used to decompose simple relations into direct and indirect effects in causal models formulated by the researcher on the basis of theoretical and logical basis.

Path Coefficient: Is the symbol p with two subscripts, the first indicating the effect (dependent variable) and the second indicates the cause (independent variable). Accordingly, P43 is the direct effect of variable 3 on variable 4.

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