Behavioral Modeling of the Individual’s Acceptance and use of Internet in Bangladesh: An Analysis Using an Integrated Approach

This study attempts to examine individuals’ behavior in the adoption and usage of the Internet for accomplishing various transactions and communication in Bangladesh. A descriptive research design is administered to ascertain the joint impact of the study constructs. A combination of AMOS 18 and PLS graph has been used for structural equation modeling with a cross-sectional dataset of 239 individuals in Bangladesh collected through a questionnaire survey. The proposed model was assessed with two step procedure after scrutiny and correction for non response and subjective response bias. The psychometric properties of the model, convergent and discriminant validity were assessed through confirmatory factor analysis, construct reliability and the constructs correlation. The structural model estimation results reveal a significant association of image with perceived ease of use, perceived usefulness and intention while indirect correlation with actual usage through intention. On the other hand, perceived usefulness has direct effects on intention while perceived ease of use is found to be indirectly associated through perceived usefulness. The path analysis furthered the significant effects of intention on actual usage behavior. The study also reports that analysis of the entire dataset with two different a roaches of structural equation modeling produces a consistent result which ensures robustness in the analysis. The study concludes with implications. INTRODUCTION In past few years the seemingly increasing rate of usage of Information and Communication Technologies (ICTs) has reshaped the global socio-economic and business environment and made changes in the pattern of personal, social and business communication. The world’s shift towards the digital culture, from the traditional way of transaction and communication, creates enormous research opportunities in the IS domain and also in the multidisciplinary fields of studies to look at the adoption and diffusion of Information and Communication Technologies (ICTs). ICT, particularly the Internet, underpins almost every single activity undertaken in the modern world, and affects everyone on the planet — even those who do not themselves have first-hand access to ICTs (ITU 2010). Good examples include food distribution, power networks, water supplies or mass transportation, all of which are controlled and managed today by ICT networks and applications. Journal of International Technology and Information Management Volume 22, Number 1 2013 © International Information Management Association, Inc. 2013 124 ISSN: 1543-5962-Printed Copy ISSN: 1941-6679-On-line Copy According to the World Telecommunication Report 2010, released to review the mid-term status and achievement in-between the World Summit on the Information Society (WSIS) 2005 and the Millennium Development Goals (MDG) 2015, tremendous progress has been made over the past decade, with almost two billion people throughout the world now having access to the Internet. Although significant progress has been evident in the world’s Internet population, household Internet penetration levels vary substantially between countries and regions. At the end of 2008, one out of four households in the world had access to the Internet but only one out of eight households in the developing countries was connected, compared to three out of five in the developed countries. While by the end of 2008, 58.1 per cent of households in Europe had Internet access, only 16.8 per cent of the household in Asia and Pacific countries were connected to the Internet. The Internet population of Asia-Pacific countries remains at a lower level in comparison to Europe, America, CIS and the Arab States. The Internet penetration of Bangladesh is significantly lower, below 1 percent, than that of other Asia-Pacific countries, such as Japan, Malaysia, Korea, Singapore and Australia. Despite its poor internet penetration the present government of Bangladesh has given the highest priority to ICT and initiated diverse policies and programs to achieve the digital goal provisioned in the national election 2009 and post-election agenda. The country’s national budget for 2010-2011 allocates a substantial amount of resources for ICT development and reiterates expanding the ICT networks to the rural communities to achieve government, citizen and business interactions and exchanges through the Internet (GOB 2010). The government also initiated some modifications to the country’s national ICT policy in 2009 which reiterates the necessity of establishing e-government, e-services and ecommerce environments in order to gain economic potential. It also emphasizes formulating appropriate policies and strategies for facilitating Internet related communication, e-commerce operation and e-governance. In order to achieve ICT potentials the government is dedicated to utilizing the Internet in the education and service sector ( Azam & Quaddus, 2009a; Azam & Quaddus, 2009b; Azam & Quaddus, 2009c). Although countable policy initiatives have been adopted to utilize the potential of ICT in the economic development of the country, the success of digitization or computerization is still doubtful. Although Bangladesh has already initiated appropriate steps to fight against the hurdles and hindrances of ICT adoption, such as, limited accessibility to the internet, poor teledensity, poor electricity network, limited affordability of computer and limited knowledge, inadequate legal and regulatory support, inefficient and traditional systems of banking operation, poor financial support and traditional payment mechanism, lack of human resource, high Internet usage cost as well as security concerns (Azam & Quaddus, 2009; Azam, 2005; Azam & Lubna, 2008; Azam, 2006; Hossain, 2000; ITRC, 2000; Rahman, 2002), poor Internet penetration is still considered as the main issue for establishing an ebased transparent society. According to the World Bank (World Bank 2010) the Internet penetrations in various countries are estimated as USA 75.9%, UK 76%, Australia 70.8%, Singapore 69.6%, Malaysia, 55.8%, while Bangladesh’s internet penetration is only 0.347% in 2008. While many developed and developing countries achieved significant advantages through computerization of government departments, business firms and educational institutes, the digital initiatives of Bangladesh remain at risk due to the Behavioral Modeling of Individual’s Acceptance M. S. Azam, M. Quaddus & N. Lubna © International Information Management Association, Inc. 2013 125 ISSN: 1543-5962-Printed Copy ISSN: 1941-6679-On-line Copy poor digital participation of the citizenry. In this context a study looking at individuals’ Internet acceptance behavior in Bangladesh has great significance. Bangladesh is basically an agro-based country. It’s recently developed industrial base, particularly the RMG industry has been emerged as the main vehicle for the country’s economic development. The overall culture of the country is characterized by high population, low income and quite a big number of unemployed people where labor is cheap and available. Like many other Asian states; Bangladesh’s culture has also been characterized by high power distance, collectivism and low uncertainty avoidance (House, et al. 2004). The power is concentrated at the top of the society. There also remain discriminatory rights, privileges, resources, status, and prestige among the individuals in different classes across the social system. The individuals of the upper class in the social hierarchy enjoy more power, prestige and image than others in the lower class. Social class can contribute significantly in forming individual or group behavior with the internal variables such as subjective perceptions and innovations characteristics (Blackwell et al, 2006). With occupation, education, friendship, way of speaking and position, perceived variables that define social classes include power and prestige (Rossides, 1990) which is a relatively under researched issue in the Information Systems (IS) literature in both developed and developing country context. Most of the previous studies examined ICT adoption behavior in Bangladesh through utilization of the Rogers Innovation Diffusion Theory, Theory of Planned Behavior and Theory of Reasoned Action, while a few empirical studies include individuals’ beliefs and perceptions as well as some cultural aspects (Azam, 2006; Azam, 2007; Azam & Quaddus, 2009a; Azam, 2005; Azam & Lubna, 2008; Hossain, 2000; ITRC, 2000; Rahman, 2002). The Technology acceptance model (TAM) although believed to be a robust and parsimonious model for ICT adoption and which is also widely used in different places around the world (Davis, 1989; Davis, Bagozzi, & Warshaw, 1989; Igbaria, Guimaraes, & Davis, 1995; Mathieson, 1991), it’s a location in Bangladesh is not well documented. This paper thus looked at the role of Image (Image is conceptualized as the degree to which use of innovation is perceived to enhance one’s image or status in one’s social system, Moore & Benbasat, 1991) in intention to use Internet in communication and transaction as well as actual behavior in modeling with the two fundamental users’ beliefs in TAM, perceived usefulness and ease of use. THEORETICAL FRAMEWORK AND HYPOTHESES Numerous theories and models have been used to investigate technology acceptance phenomena in the past couple of decades, most of them are adapted from Rogers Innovation Diffusion Theory (Rogers, 1985), Theory of Reasoned Action (Ajzen & Fishbein, 1980; Fishbein & Ajzen, 1975), Theory of Planed Behaviour (Ajzen, 1985; Ajzen, 1981) or Technology Acceptance Model (Davis, 1989; Davis, Bagozzi, & Warshaw, 1989). TAM is the most recent one among these four theories developed to study the innovation adoption and diffusion phenomena. Analyzing the scope and structure of the models and their applicability in different environments, some uniqueness and also som

[1]  James C. Anderson,et al.  STRUCTURAL EQUATION MODELING IN PRACTICE: A REVIEW AND RECOMMENDED TWO-STEP APPROACH , 1988 .

[2]  K. Bollen A New Incremental Fit Index for General Structural Equation Models , 1989 .

[3]  Girish H. Subramanian,et al.  A Replication of Perceived Usefulness and Perceived Ease of Use Measurement , 1994 .

[4]  Fred D. Davis,et al.  User Acceptance of Computer Technology: A Comparison of Two Theoretical Models , 1989 .

[5]  Peter A. Todd,et al.  Perceived Usefulness, Ease of Use, and Usage of Information Technology: A Replication , 1992, MIS Q..

[6]  Olivia R. Liu Sheng,et al.  Examining the Technology Acceptance Model Using Physician Acceptance of Telemedicine Technology , 1999, J. Manag. Inf. Syst..

[7]  G. Lantos,et al.  Resolving the Capability–Rigidity Paradox in New Product Innovation , 2006 .

[8]  M. Chang Predicting Unethical Behavior: A Comparison of the Theory of Reasoned Action and the Theory of Planned Behavior , 1998 .

[9]  Detmar W. Straub,et al.  Information Technology Adoption Across Time: A Cross-Sectional Comparison of Pre-Adoption and Post-Adoption Beliefs , 1999, MIS Q..

[10]  P. Dorfman,et al.  Leadership and Organizations: The GLOBE Study of 62 Societies , 2004 .

[11]  Kar Yan Tam,et al.  Determinants of User Acceptance of Digital Libraries: An Empirical Examination of Individual Differences and System Characteristics , 2002, J. Manag. Inf. Syst..

[12]  J. Wolfowitz,et al.  Introduction to the Theory of Statistics. , 1951 .

[13]  Kenneth L. Kraemer,et al.  Post-Adoption Variations in Usage and Value of E-Business by Organizations: Cross-Country Evidence from the Retail Industry , 2005, Inf. Syst. Res..

[14]  John Hulland,et al.  Use of partial least squares (PLS) in strategic management research: a review of four recent studies , 1999 .

[15]  I. Ajzen The theory of planned behavior , 1991 .

[16]  S. Azam,et al.  Internet Adoption and Usage in Bangladesh , 2007 .

[17]  S. G. Mazman,et al.  The Usage of Social Networks in Educational Context , 2009 .

[18]  I. Ajzen,et al.  Belief, Attitude, Intention, and Behavior: An Introduction to Theory and Research , 1977 .

[19]  E. McKinney,et al.  Extending the Technology Acceptance Model Extending the Technology Acceptance Model and the Task and the Task-Technology Fit Model to Technology Fit Model to Consumer E Consumer E- -Commerce Commerce , 2004 .

[20]  Fred D. Davis,et al.  A Model of the Antecedents of Perceived Ease of Use: Development and Test† , 1996 .

[21]  E. McKinney,et al.  Extending the Technology Acceptance Model and the Task-Technology Fit Model to Consumer E-Commerce , 2004 .

[22]  Izak Benbasat,et al.  Development of an Instrument to Measure the Perceptions of Adopting an Information Technology Innovation , 1991, Inf. Syst. Res..

[23]  P. Bentler,et al.  Significance Tests and Goodness of Fit in the Analysis of Covariance Structures , 1980 .

[24]  Masud Al Noor,et al.  Adoption of B2B e-commerce by the SMEs in Bangladesh , 2011 .

[25]  Wynne W. Chin,et al.  PARTIAL LEAST SQUARES IS TO LISREL AS PRINCIPAL COMPONENTS ANALYSIS IS TO COMMON FACTOR ANALYSIS , 1999 .

[26]  Peter A. Todd,et al.  Understanding Information Technology Usage: A Test of Competing Models , 1995, Inf. Syst. Res..

[27]  Rex B. Kline,et al.  Principles and Practice of Structural Equation Modeling , 1998 .

[28]  Fred D. Davis,et al.  A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies , 2000, Management Science.

[29]  R. Reeve,et al.  The Diffusion of E-Learning Innovations in an Australian Secondary College: Strategies and Tactics for Educational Leaders , 2003 .

[30]  Charles D. Barrett Understanding Attitudes and Predicting Social Behavior , 1980 .

[31]  Fred D. Davis User Acceptance of Information Technology: System Characteristics, User Perceptions and Behavioral Impacts , 1993, Int. J. Man Mach. Stud..

[32]  Hung-Pin Shih,et al.  Extended technology acceptance model of Internet utilization behavior , 2004, Inf. Manag..

[33]  C. Fornell,et al.  Evaluating structural equation models with unobservable variables and measurement error. , 1981 .

[34]  E. Rogers,et al.  Diffusion of innovations , 1964, Encyclopedia of Sport Management.

[35]  Patrick Y. K. Chau,et al.  Reexamining a Model for Evaluating Information Center Success Using a Structural Equation Modeling Approach , 1997 .

[36]  Bernadette Szajna,et al.  Empirical evaluation of the revised technology acceptance model , 1996 .

[37]  L. Tucker,et al.  A reliability coefficient for maximum likelihood factor analysis , 1973 .

[38]  Magid Igbaria,et al.  Personal Computing Acceptance Factors in Small Firms: A Structural Equation Model , 1997, MIS Q..

[39]  Gordon B. Davis,et al.  User Acceptance of Information Technology: Toward a Unified View , 2003, MIS Q..

[40]  John Hulland,et al.  Use of causal models in marketing research: A review , 1996 .

[41]  Viswanath Venkatesh,et al.  Determinants of Perceived Ease of Use: Integrating Control, Intrinsic Motivation, and Emotion into the Technology Acceptance Model , 2000, Inf. Syst. Res..

[42]  Kieran Mathieson,et al.  Predicting User Intentions: Comparing the Technology Acceptance Model with the Theory of Planned Behavior , 1991, Inf. Syst. Res..

[43]  Ritu Agarwal,et al.  Are Individual Differences Germane to the Acceptance of New Information Technologies , 1999 .

[44]  M. Quaddus,et al.  How Organisational Characteristics Explain the Adoption of e-Commerce by the SMEs in Bangladesh? , 2009 .

[45]  Paul Jen-Hwa Hu,et al.  Investigating healthcare professionals' decisions to accept telemedicine technology: an empirical test of competing theories , 2002, Inf. Manag..

[46]  Chang Liu,et al.  Technology acceptance model for wireless Internet , 2003, Internet Res..

[47]  H. Zandhessami,et al.  Determinants of user acceptance of internet banking: An empirical study , 2014 .

[48]  Jayson W. Richardson,et al.  Diffusion of technology adoption in Cambodia: The test of a theory , 2009 .

[49]  R. Frank Falk,et al.  A Primer for Soft Modeling , 1992 .

[50]  E. Rogers Diffusion of Innovations , 1962 .

[51]  Gordon B. Davis,et al.  Testing the Determinants of Microcomputer Usage via a Structural Equation Model , 1995, J. Manag. Inf. Syst..

[52]  Paulus Insap Santosa,et al.  User involvement and user satisfaction with information-seeking activity , 2005, Eur. J. Inf. Syst..

[53]  Viswanath Venkatesh,et al.  Why Don't Men Ever Stop to Ask for Directions? Gender, Social Influence, and Their Role in Technology Acceptance and Usage Behavior , 2000, MIS Q..

[54]  Fred D. Davis Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology , 1989, MIS Q..

[55]  J. Hair Multivariate data analysis , 1972 .

[56]  M. Rahman,et al.  E-Commerce in Bangladesh: status, potential and constraints , 2007 .

[57]  Peter A. Todd,et al.  Assessing IT usage: the role of prior experience , 1995 .

[58]  Shah Azam,et al.  Internet usage behaviour in Bangladesh: A test of theory of planned behaviour through structural equation modeling , 2009 .

[59]  Icek Ajzen,et al.  From Intentions to Actions: A Theory of Planned Behavior , 1985 .

[60]  Patrick Y. K. Chau,et al.  An Empirical Assessment of a Modified Technology Acceptance Model , 1996, J. Manag. Inf. Syst..