INFORMATION TECHNOLOGY ACCEPTANCE BY UNIVERSITY LECTURES: CASE STUDY AT APPLIED SCIENCE PRIVATE UNIVERSITY

Similar documents
User Acceptance of Desktop Based Computer Software Using UTAUT Model and addition of New Moderators

An Integrated Expert User with End User in Technology Acceptance Model for Actual Evaluation

RCAPS Working Paper Series

The Influence of Perceived Usefulness, Perceived Ease of Use, and Subjective Norm on the Use of Computed Radiography Systems: A Pilot Study

The use of generalized audit software by Egyptian external auditors: the effect of audit software features

Factors Influencing Professionals Decision for Cloud Computing Adoption

The Acceptance Design Model for Evaluating the Adoption of Folksonomies in UUM Library WEB OPAC

Tahereh Oloumi Department of Library and Information Sciences, Tehran University, Tehran, Iran

JOURNAL OF BUSINESS AND MANAGEMENT Vol. 5, No. 2, 2016:

Understanding the evolution of Technology acceptance model

SME Adoption of Wireless LAN Technology: Applying the UTAUT Model

E-commerce Technology Acceptance (ECTA) Framework for SMEs in the Middle East countries with reference to Jordan

Older adults attitudes toward assistive technology. The effects of device visibility and social influence. Chaiwoo Lee. ESD. 87 December 1, 2010

An Examination of Smart Card Technology Acceptance Using Adoption Model

System Characteristic Facilitates the Acceptance of Information Technology in Middle East culture

This paper utilizes the technology acceptance model (TAM) to uncover the moderating roles of

Issues in Information Systems Volume 19, Issue 3, pp , 2018

Determinants of E-commerce Adoption. among Malaysian SMEs

What Factors Affect General Aviation Pilot Adoption of Electronic Flight Bags?

Intention to Use Digital Library based on Modified UTAUT Model: Perspectives of Malaysian Postgraduate Students

A Questionnaire Approach Based on the Technology Acceptance Model for Mobile Tracking on Patient Progress Applications

The Adoption of Variable-Rate Application of Fertilizers Technologies: The Case of Iran

CORRELATES OF INFORMATION AND COMMUNICATION TECHNOLOGY (ICT) UTILIZATION IN COLLEGES OF EDUCATION IN KANO STATE

Employee Technology Readiness and Adoption of Wireless Technology and Services

Broadband Adoption: A UK Residential Consumers Perspective

Dr hab. Michał Polasik. Poznań 2016

Innovation Diffusion of Wearable Mobile Computing: Pervasive Computing Perspective

ICT acceptance among Malaysian urbanites: A study of additional variables in user acceptance of the new media

A STUDY OF UNDERGRADUATE USE OF CLOUD COMPUTING APPLICATIONS: SPECIAL REFERENCE TO GOOGLE DOCS.

University of Wollongong. Research Online

Internet usage behavior of Agricultural faculties in Ethiopian Universities: the case of Haramaya University Milkyas Hailu Tesfaye 1 Yared Mammo 2

THE ATTITUDES OF ENTREPRENEURS AND MANAGERS REGARDING THE INFORMATION TECHNOLOGY IN ALBANIAN TOURISM ENTERPRISES ABSTRACT

Diffusion of Virtual Innovation

Life Science Journal 2014;11(5s)

Predicting the Adoption of an Android-Based Class Record Using the Unified Theory of Acceptance and Use of Technology Model

Chaloemphon Meechai 1 1

Assessing Use of Information Communication Technologies among Agricultural Extension Workers in Kenya Using Modified UTAUT Model

Technology Initiative Assessment through Acceptance and Satisfaction: A Case Study

Adoption and diffusion of cloud computing in the public sector A case study of Zambia. Shuller Habeenzu ITMC/RIA Focal Point-Lusaka

Procedia - Social and Behavioral Sciences 147 ( 2014 ) IC-ININFO

REVIEW OF TECHNOLOGY ACCEPTANCE AND USE BEHAVIOR

Profiles of Internet Use in Adult Literacy and Basic Education Classrooms

Available online at ScienceDirect. Procedia Computer Science 65 (2015 )

Online Public Services Access and the Elderly: Assessing Determinants of Behaviour in the UK and Japan

Beyond Innovation Characteristics: Effects of Adopter Categories on the Acceptance Outcomes of Online Shopping

Incorporating Technology Readiness (TR) Into TAM: Are Individual Traits Important to Understand Technology Acceptance?

The drivers to adopt renewable energy among residential users.

Malaysian Users Perception towards Facebook as a Social Networking Site

Gamification and user types: Reasons why people use gamified services

Chapter 4. Research Objectives and Hypothesis Formulation

Factors Influencing Adoption of Biometrics by Employees in Egyptian Five Star Hotels

Introducing Agent Based Implementation of the Theory of Reasoned Action: A Case Study in User Acceptance of Computer Technology

Assessing the Impact of Concern for Privacy and Innovation Characteristics in the Adoption of Biometric Technologies

Technology Adoption: an Interaction Perspective

Exploring Factors Affecting the User Adoption of Call-taxi App

Sierra Leone - Multiple Indicator Cluster Survey 2017

Factors Motivating Broadband Adoption in Thailand

Predicting Collaboration Technology Use: Integrating Technology Adoption and Collaboration Research

A Test of the Technology Acceptance Model in Electoral Activities: The Nigerian Experience

The Reality of Software Reverse Engineering Education in the Jordanian Universities and How to improve it

The Usage of Social Networks in Educational Context

JITTA JOURNAL OF INFORMATION TECHNOLOGY THEORY AND APPLICATION

Procedia - Social and Behavioral Sciences 210 ( 2015 ) 43 51

Digitisation A Quantitative and Qualitative Market Research Elicitation

ESS Round 8 Question Design Template New Core Items

IDENTIFYING THE DETERMINANTS OF CLOUD COMPUTING ADOPTION IN A GOVERNMENT SECTOR A CASE STUDY OF SAUDI ORGANISATION

BEHAVIOURAL ANALYSES OF INFORMATION TECHNOLOGY ACCEPTANCE (Case Study: SME s Trade Industrial Sector in Jabodetabek)

Introduction. Data Source

User Acceptance Factors for Anonymous Credentials: An Empirical Investigation

An Evaluative Study of the United States Cooperative Extension Service s Role In Bridging The Digital Divide

ASSESSING USER PERCEIVED SERVICE QUALITY OF DIGITAL LIBRARY

Comment on Providing Information Promotes Greater Public Support for Potable

The Danish 3R Survey Knowledge, attitudes and experiences with the 3Rs among researchers involved in animal experiments in Denmark

Mindfulness, non-attachment, and emotional well-being in Korean adults

From Information Technology to Mobile Information Technology: Applications in Hospitality and Tourism

Washington s Lottery: Daily Race Game Evaluation Study TOPLINE RESULTS. November 2009

Inside or Outside the IP System? Business Creation in Academia. Scott Shane (CWRU)

Web Personalization in Consumer Acceptance of E-Government Services

Exploring the Adoption and Use of the Smartphone Technology in Emerging Regions: A Literature Review and Hypotheses Development

Technological and Institutional Perspectives of Women s IT Entrepreneurial Intention in Saudi Arabia

Perceptions of Sunk Cost and Habitual IS Use

The Acceptance Model for Adoption of Information and Communication Technology in Thai Public Organizations

Modeling the Determinants Influencing the Diffusion of Mobile Internet

2nd World Conference on Technology, Innovation and Entrepreneurship May 12-14, 2017, Istanbul, Turkey. Edited by Sefer Şener

Accepted Manuscript. Title: Factors influencing teachers intention to use technology: Model development and test. Authors: Timothy Teo

Impact of Perceived Desirability, Perceived Feasibility and Performance Expectancy on Use of IT Innovation

The Centrality of Awareness in the Formation of User Behavioral Intention Toward Preventive Technologies in the Context of Voluntary Use

Measuring acceptance of an assistive social robot: a suggested toolkit

ATTITUDES OF LIBRARY STAFF TO THE USE OF ICT: THE CASE OF KENNETH DIKE LIBRARY, UNIVERSITY OF IBADAN, NIGERIA.

An Empirical Investigation of Cloud Computing for Personal Use

APPLYING A QUALITATIVE FRAMEWORK OF ACCEPTANCE OF PERSONAL ROBOTS

TECHNOLOGY READINESS FOR NEW TECHNOLOGIES: AN EMPIRICAL STUDY Hülya BAKIRTAŞ Cemil AKKAŞ**

Research on the Influencing Factors of the. Adoption of BIM Technology

Socio-economics Factors and Information Technology Adoption in Rural Area

The Impact of Privacy Concerns and Perceived Vulnerability to Risks on Users Privacy Protection Behaviors on SNS: A Structural Equation Model

ON THE MULTI-DIMENSIONAL NATURE OF COMPATIBILITY BELIEFS IN TECHNOLOGY ACCEPTANCE

Critical Issues and Problems in Technology Education

Use of ICT Technologies and its Dependency Level among P.G. Students and Faculty Members of G.B. Pant University of Agriculture and Technology

UTILIZING TECHNOLOGY EDUCATION GRADUATES IN SUSTAINING TECHNOLOGICAL GROWTH AND DEVELOPMENT IN 21 ST CENTURY NIGERIA. Olisa, James

How Many Imputations are Really Needed? Some Practical Clarifications of Multiple Imputation Theory

Transcription:

INFORMATION TECHNOLOGY ACCEPTANCE BY UNIVERSITY LECTURES: CASE STUDY AT APPLIED SCIENCE PRIVATE UNIVERSITY Hanadi M.R Al-Zegaier Assistant Professor, Business Administration Department, Applied Science University Amman, Jordan Samer M. Barakat Assistant Professor, Management Information Systems Department, Applied Science University Amman, Jordan Hasan Ali Al-Zu bi Professor, Business Administration Department, Applied Science University Amman, Jordan Abstract Purpose The purpose of this paper is to explore the Information Technology Acceptance by University Lectures within the applied science private university. Design/methodology/approach A purposive sampling technique was Lectures to recruit 156 Lectures representing the desired range of demographic characteristics (e.g. gender, age, Educational Level, and Experience Years). Findings This paper showed that there is not influence perceived usefulness on the acceptance on information technology usage, but there is influence perceived (ease of use, complexity, 35

Computing support, and Management support) on the acceptance on information technology usage. Originality/value The paper contributes to previous research by adding to existing knowledge regarding what constitutes Information Technology Acceptance. The paper makes key recommendations towards enhancing skills of teaching staff members at the fields of educational materials design and development for the use by modern IT methods. Keywords: Information Technology, Applied Science University, Lectures, Jordan. 1. Introduction Information technology acceptance has been studies ever since the existence of the term. It is a fast growing research field and many models has been developed to study the user acceptance and adoption of the new technology. TAM is one of the leading technology acceptance models. A user attitude towards the acceptance of new information technology plays an important role on information technology adoption and use (Davis & Venkatesh, 2004). TAM has been extended over time to include other determinant factors that contributes to the adoption of new technology. This research aims at exploring the factors that influence Information Technology acceptance by professors at Applied Science University. We shall explore to what level professors are using and adopting information technology products in and out of the classroom. A modified version of the Technology Acceptance Model was introduces and shaped to achieve this objective and a new research model was depicted. The research findings shall contribute to the information technology field in general and to the technology acceptance in specific. Universities and higher education institutions shall formulate a clear view of how professors use information technology and to what extent information technology plays an important role in a professor s daily activities in research and academia. 2. Historical Review The Technology Acceptance Model (TAM) is one of the leading models applied in research related to the acceptance of Information Technology use and implementation whether it was software or hardware. TAM was originally introduced by Davis in 1989 (Davis, 1989). It 36

was intended to show what are the true drivers of user acceptance of information technology products. Ajzen and Fishbein s theory of Reason Action inspired Davis to come out with TAM (Ajzen & Fishbein, 1980). According to the model perceived ease of use and perceived usefulness influence the user s intention to use the new technology. The model clearly identifies perceived ease of use as "the degree to which a person believes that using a particular system would be free from effort" and identifies perceived usefulness as "the degree to which a person believes that using a particular system would enhance his or her job performance"(davis, 1989). 3. Previous Studies 3.1. Perceived complexity Complexity is one of the major factors affecting the use of new technology. IT is measured by the level of which new technology is perceived as not easy to use and learn. Rogers associate s users refrain from using new technology due to its higher level of difficulty (Rogers & Shoemaker, 1997). The higher the level of Technology difficulty the lower the level of usage of technology which affects the user adoption of the new Technology (Chau & Hu, 2001). 3.2. Computing support Computing support is divided into tow streams Internal and External (Selamat & Jaffar, 2011) Internal personal computing support is very important in playing a major role in adopting and using of new technology. It is the technical support provided by people working within the company which leads to use of new technology with ease and this shall affect adoption of technology (Viswanath & Davis,2000) and (Selamat & Jaffar, 2011). On the other hand External support is also extremely important and it is provided by technology vendors, support groups and consultants (Selamat & Jaffar, 2011). Support provided by experts and consultants who possess high knowledge of the technology help uses use the technology and in relation drives users to adopt new technology (Gable, 1991). 3.3. Management Support IT has been perceived by Igbaria that management support and perceived usefulness are interrelated (Igbaria, et al., 1995). IT is the perceived degree of supp ort provided by top management for the use of new technology (Viswanath & Davis, 2000). It is well understood 37

that mgmt support influence humans behavior for the adoption of new technology. Change agents within an organization contribute to the organization use and acceptance of new technology. 3.4. Perceived usefulness This was defined by Fred Davis as "the degree to which a person believes that using a particular system would enhance his or her job performance". (Davis,1989) 3.5. Perceived ease-of-use Davis defined this as "the degree to which a person believes that using a particular system would be free from effort" (Davis 1989). 4. Problem Definition The study was conducted to address certain key issues abut information technology acceptance in the applied science private university. It would be worth examining the normal influence of factors (Perceived usefulness, Perceived ease of use, Perceived Complexity, Computing support, and Management support) on the information technology acceptance. Other questions include the following: 1. To what extent is the level of information technology acceptance in applied science private university? 2. Is there any influence for factors (Perceived usefulness, Perceived ease of use, Perceived Complexity, Computing support, and Management support) on the information technology acceptance? 5. Research model and hypotheses Based on the theoretical background and the literature review the researchers have developed a conceptual model to integrate the primary components of TAM (perceived usefulness and perceived ease of use) with other components to predict applied science university lectures attitude toward information technology such as perceived complexity, internal and external personal computing support and management support to the TAM. 38

Perceived usefulness Perceived ease of use Perceived complexity Information Technology acceptance Computing support Management support Figure (1) depicts the research model. 6. Hypotheses of the Study To answer the questions posed by the authors, and based on the literature reviewed, the researchers proposed five main hypotheses as follows: H1: perceived usefulness has influence on information technology acceptance. H2: perceived ease of use has influence on information technology acceptance. H3: perceived complexity has influence on information technology acceptance. H4: Computing support has influence on information technology acceptance. H5: management support has influence on information technology acceptance. 7. Methodology: 7.1. Data and Sample To gather data for this study, a random sample of (164) lectures was selected from the population of Applied Science Privet University, the number of lecturers in this university in 2011 is (285) lecturers. Of the (159) questionnaires returned, (3) wer e rejected due to incomplete responses and (156) responses (92 percent response rate) were used for data analyses. It should be noted that every questionnaire was personally handed and instructions were given to each lecturer before completing the questionnaire. In terms of demographic findings, (74.4%) of respondents were males, and the remaining (25.6%) were females. In terms of the age group of respondents, it is interesting to note that (16%) fell into the (25-30) age group, whereas (24.4%) 39

fell into the (31-35), whereas (16%) fell into the (36-40) age group, whereas (26.3%) fell into the (41-45), only (17.3%) are above this group. As for the educational levels of these lectures, the master degree (25.6%), and the PhD degree (21%). In terms of the Experi ence years of respondents, (60.9%) of them have less than (6) years, whereas (3.2%) have (6-10) Experience years, whereas (18.6%) have (11-15) years of experience, only (17.3%) have more. See table (1). Table 1. Characteristics of the Sample (N=156) Items frequency Percent Gender: Male Female 116 40 74.4 25.6 Age: Less than 25 year 25 30 Years 31 35 Years 36 40 years 41 45 Years 46 Years and more 0 25 38 25 41 27 0 16.0 24.4 16.0 26.3 17.3 Educational Level: Master PhD 40 116 25.6 74.4 Experience Years: 1 5 Years 6 10 Years 11 15 Years 16 Years and more 95 5 29 27 60.9 3.2 18.6 17.3 40

7.2. Research instrument: The questionnaire was designed and developed using the results of the literature review. The draft questionnaire was tested by scholars and experts, which led to minor modifications in the wording of some survey items. The final questionnaire comprises two parts. The first part is demographics of the sample such as gender, age, educational level, experience years, information technology usage and frequency of use. The second part contains a series of questions about the factors affecting the acceptance of IT which is (perceive usefulness, perceived ease. perceived complexity, computing support, and management support) Research constructs were operationalized by means of related studies and a pilot test. A five-point Likert-type scale, ranging from 1 (strongly disagree) to 5 (strongly agree), was used to measure the research variables. 8. Results and Discussion Table (2) displays the regression analyses was performed to test the influence of independents variables on information technology acceptance usage. H1: perceived usefulness has influence on information technology acceptance. The result shows that there a significant influence for the perceived usefulness on the acceptance information technology usage. The value of R was (0.730) and R 2 (0.532) and the regression coefficient (beta) for perceived usefulness is ( -0.047) (p=0.613). The result indicated that the null hypothesis can be accepted. This study finds that there is not influence perceived usefulness on the acceptance on information technology usage. This result is inconsistent with the finding of the study to Selamat and Jaffar (2011), Igbaria et al. (1995), and Ndubisi and jantan (2003). H2: perceived ease of use has influence on information technology acceptance. The result shows that there a significant influence for the perceived ease of use on the acceptance information technology usage. The value of R was (0.730) and R 2 (0.532) and the regression coefficient (beta) for perceived ease of use is (-0.711) (p=0.000). The result indicated that the null hypothesis can be rejected. Therefore, the alternative hypothesis stands. This study finds that there is influence perceived ease of use on the acceptance information technology usage. 41

This result is inconsistent with the finding of the study to Selamat and Jaffar (2011), but this result is consistent with the finding of the study to Igbaria et al. (1995), and Ndubisi & jantan (2003). H3: perceived complexity has influence on information technology acceptance. The result shows that there a significant influence for the perceived complexity on the acceptance information technology usage. The value of R was (0.730) and R 2 (0.532) and the regression coefficient (beta) for perceived complexity is (0.237) (p=0.000). The result indicated that the null hypothesis can be rejected. Therefore, the alternative hypothesis stands. This study finds that there is influence perceived complexity on the acceptance information technology usage. This result is inconsistent with the finding of the study to Selamat and Jaffar (2011), and Al-Gahtani (2003). H4: computing support has influence on information technology acceptance. The result shows that there a significant influence for the perceived computing support on the acceptance information technology usage. The value of R was (0.730) and R 2 (0.532) and the regression coefficient (beta) for perceive d computing support is (0.278) (p=0.001). The result indicated that the null hypothesis can be rejected. Therefore, the alternative hypothesis stands. This study finds that there is influence perceived computing support on the acceptance information technology usage. This result is consistent with the finding of the study to Selamat and Jaffar (2011). H5: management support has influence on information technology acceptance. The result shows that there a significant influence for the perceived management support on the acceptance information technology usage. The value of R was (0.730) and R 2 (0.532) and the regression coefficient (beta) for perceived management support is ( -0.362) (p=0.000). The result indicated that the null hypothesis can be rejected. Therefore, the alternative hypothesis stands. This study finds that there is influence perceived management support on the acceptance information technology usage. This result is consistent with the finding of the study to Selamat and Jaffar (2011). 42

Table 2. Regression results Usage R R 2 Standard Standard Sig. Error coefficient Beta 0.730 0.532 (Constant) 0.059 0.000 Perceived usefulness 0.021-0.047 0.613 Perceived ease of use 0.024-0.711 0.000 Perceived complexity 0.015 0.237 0.000 Computing support 0.014 0.278 0.001 Management support 0.014-0.362 0.000 9. Limitation: Some of the information in this research reflect the judgment of applied science private university lectures whom provide the information used, so may be some personal bias happened, also part of sample were very conservative in providing information. 10. Recommendation: Based on the results concluded, the researchers recommended the following: 1. Facilitate the acceptance of information technology by teaching lectures the benefits of such acceptance. 2. Enhance skills of teaching staff members at the fields of educational materials design and development for the use by modern IT methods. 3. Activate the use of IT at Jordanian universities in education to ensure its quality and increase its effectiveness. 4. provide the necessary technical and material potentials by the university departments to activate the acceptance of information technology 43

References: Ajzen, Icek & Martin, Fishbein, (1980), Understanding attitudes and predicting social behavior, EngleCliffs-Wood: NJ: Prentice Hall. Al-Gahtani, Said S. (2003). Computer Technology Adoption in Saudi Arabia: Correlates of Perceived Innovation Attributes. Information Technology for Development, 10, 57-69. Chau, P. Y. K., & Hu, P. J. H. (2001). Information technology acceptance by individual professionals: A model comparison approach. Decision Sciences, 32(4), 699 719. Fred Davis (1989), Perceived usefulness, perceived ease of use, and user acceptance of information technology, MIS Quarterly, 13, 319-339. Fred Davis, Viswanath Venkatesh (2004), Toward preprototype user acceptance testing of new information systems: implications for software project management, IEEE Transactions on Engineering Management, 51 (1), 31-46. Gable, G.G. (1991). Consultant Engagement for Computer System Selection: A Pro -Active Client Role in Small Businesses. Information and Management, 20, 83-93. Igbaria, M, Guimaraes, T., & Davis, G.B. (1995). Testing the Determinants of Mi crocomputer Usage via a Structural Equation Model. Journal of Management Information Systems, 11(4), 87-114. Ndubisi, N. O. and Jantan, M. (2003). Evaluating IS usage in Malaysian small and medium-sized firms using the technology acceptance model. Logistics information Management, 16 (6), 440-450. Rogers, E.M., and Shoemaker, F.F. (1997). Communication of Innovation: A Cross Culture Approach, New York, Free Press Venkatesh, Viswanath & Fred D. Davis. (2000). a Theoretical Extension of Technology Acceptance Model: Four Longitudinal Studies. Management Science, 46 (2), 186-204. Zarehan Selamat, Nahariah Jaffar, (2011). Information Technology Acceptance: From Perspective of Malaysian Bankers, International Journal of Business and Management, 6 (1), 207-217. 44