User Perceptions and Online News

User Perceptions and Online News Sources:

An Empirical Analysis of the Lazy User Model in Information Technology in Explaining User Preferences for Selecting Online News Sources in Hong Kong

Information Technology and the Internet

Technology Acceptance Models

Lazy User Model

Theory of Reasoned Action

Technology Acceptance Model

Unified Theory of Acceptance and Use of Technology

Cognitive Fit Theory

Technology Task Fit Model

Diffusion of Innovation

Evolution of Online Media

The Digital Marketplace in Hong Kong

Methodology and the Lazy User Model Survey

Rationale of using a Survey Questionnaire

The Survey Questionnaire

Data Design Analysis

Final Results

Suggestions for Future Research

Introduction

Online news media is a relatively recent phenomenon in the history of print media, encompassing and embracing the advance of the internet, and the ability of the average person to not only have access to technology, but also to contribute to it. It stands to reason that in the development of technology that must take into account the needs of the user, various schools of thought have emerged to examine and explain the "why" of why people do what they do. In short, how do people make decisions? What factors influence their set of choices? In and of itself, the study of decision-making is broad and widely documented in diverse scholarly fields.

In the field of information technology, different models have been proposed to explain why and how people come to choose incorporating technology into their lives. It is not a question that the average person lends much thought to, rather, most decisions at the personal level are done with a great deal of subjectivity. However, the field does remain open to scholarly question, and hence a field of models falling under the rubric of "technology access models" exists from which to test relevant hypotheses on various aspects of technology.

The "internet" and "online media" incorporate many facets of information technology. At its core, the issue of information technology as regards online content in any form involves an exchange of ideas in a very new marketplace. As such, not only do we need to identify specifics of the 'marketplace', but we also must define the user.

In this paper, the topic of online news media is examined through applying a technology access model known as the "Lazy User Model" to explain why people choose online news media as their desired venue of news sources over traditional print media.

1.1 Research Question and Hypotheses

The aim of this research study is to determine whether the Lazy User Model of technology acceptance is a suitable evaluation tool to determine the popularity of online news sources in Hong Kong. This paper asks "what are the factors that contribute to making online news media sources popular in Hong Kong?"

To answer these questions, three hypotheses will be tested which employ the Lazy User Model:

H1: The user's needs determine whether they will choose online over paper version.

H2: The users' state determines whether they will choose online over paper version.

H3: The solution (online vs. paper) requiring the least effort by the user will be the one chosen.

In order to test these hypotheses, this paper will first present the background of the LUM (Lazy User Model), offer a research methodology to employ in gathering necessary data through the auspices of a survey questionnaire tool, discuss how the results of the survey should be evaluated, and offer recommendations on the outcomes.

1.2 Definitions and Concepts

Information Technology is defined as 'the industry or discipline involving the collection, dissemination, and management of data, typically through the use of computers' (Network, 2010). Quite likely, the meaning of it twenty years ago in a tangible, applicable sense, was different than it currently is today. Information technology has enjoyed a progressive and rapid growth, both in terms of what it means/is and what it can do/accomplish. Looked at from two perspectives, it means different things to different users, especially from the viewpoint of business and the viewpoint of the end user, or the business target.

IT has changed the way we communicate, with examples ranging from cell phones and other mobile devices, geographic information systems that are geared for personal use (like in-car navigation systems), online chat rooms and social networking sites, as well as how information is conveyed to the end user. Indeed, information technology has made it not only easier, but faster, to both convey and disseminate information (Johnson, 1997). This includes, among other things, online media sources.

Online Media refers to digital media working in digital codes (as opposed to analog codes). Digital Media Alliance Florida defines digital media as "the creative convergence of digital arts, science, technology and business for human expression, communication, social interaction and education" (Digital Media Alliance of Florida, 2010). Therefore, the it branch of online digital media encompasses online news sources. People have been relaying information to each other about current happenings for thousands of years, in the best it available in their day, whether it be writing on stone tablets or establishing a new blog. One way or another, information gets passed along in the easiest and fastest manner possible. Throw in another variable, profit-driven business and the equation changes to answer questions of why people would choose one form of media over another, given the best it of their day. For purposes of delimiting the scope of this research project, the focus will remain on online news sources, specifically in the Hong Kong region.

Hong Kong is an international financial commerce leader, and a potential gateway to leading innovations in information technology, including online media news sources. With a tech-savvy population, the potential for Hong Kong to be a world model in online information dissemination is high (Leung, Chen, & Chan, 2003).

The progressive and rapid growth of the internet is constantly redefining the media landscape, effectively making it a moving target, subject to business and user needs in the face of current technology. Different communication theories attempt to explain why people choose one form of communication over another, with accompanying psychological and behavioral issues that will not be discussed in this paper. Two areas of inquiry are relevant for purposes of this research project in mentioning communication theories. These are the "internationalization" of mass communication flow and "the technological change and convergence," as the boundaries separating mass communication from other forms for communication becomes less clear (Chyi & Lasorsa, 1999). The development of online newspapers is the most pronounced example of this second major area.

The user is defined as the consumer of the product. Here, it is the reader of the news source. The news source in question is online news media in Hong Kong. Hence, the user is the Hong Kong news reader using a computer to access online news sources in Hong Kong. Various problematic issues arise that should be noted. Geographic issues may limit one's access to online news sources. Computers and/or internet access may be limited or restricted, either through geographic restrictions, or other restrictions such as finances, knowledge of how to use a computer, or other restrictions that perhaps flow from government-controlled media content. (Muellr & Kamerer, 1995).

Media in Hong Kong refers specifically to online news media that is based in Hong Kong. This includes local online newspapers, local news blogs, and does not include international news web sites or anything of an international nature based outside of Hong Kong.

Technology Acceptance is an information systems model that attempts to explain how a user accepts and uses technology. There are several competing theories, with the field constantly being under review. The technology acceptance model (TAM) helps to identify the causal relationships between a systems design features, perceived usefulness, perceived ease of use, attitude toward using, and actual usage behavior in determining what factors should be examined in either the study of the history of technology use or the prediction for future technology use (Davis, 1993).

1.3 Delimitations

For purposes of this research project, delimitations refer to those concepts that limit the scope of the inquiry. Specifically, since we are trying to apply a model of technology acceptance called the lazy user model in explaining why people choose to use online newspapers as their primary news source in Hong Kong, some issues are in fact delimiting. What will not be covered in this research papers are:

International news sites.

Comparison of alternative technology acceptance models other than descriptive explanations.

Social networking sites as sources of 'news'.

Psychological models of behavior.

Alternative methodologies that could gather the necessary data outside of a survey questionnaire design tool.

The delimitations of the research project are not comprehensive in scope. However, the preceding delimitations are not covered in this report, and therefore should not be mistaken to be omitted by error of ignorance.

1.4 Overview of the Research Project

This research study continues with an in-depth literature review of information technology and the internet, technology acceptance models, online media, and the digital Hong Kong marketplace. Following the literature review is a presentation of the methodology to study the hypotheses presented. A survey questionnaire design is employed to gather data to be used in the lazy user model test, with details on the sample population in which the questionnaire is to be administered. An innovative method to increase response rate is offered, followed by a data analysis plan. Finally, a conclusion and recommendation will complete this research project.

2. Literature Review

2.1 Information Technology and the Internet

The Information Age has changed our world in many different areas, from mankind's first steps into the space frontier, to the development of consumer items of convenience. Computers where once virtually inaccessible to the average person, and at that time were used only for information processing and logical calculations on a grand scale for large corporations and military endeavors. Indeed, only in the military did the information age really begin to develop, with the need for advanced military operations driving the information technology race.

As a result of the technology race, a rapid growth of online applications has emerged with the advent of the internet. Knowledge related to the Internet and World Wide Web are becoming crucial in delineating the parameters related to various applications; these include more advanced technologies such as Web interface, script languages, and Internet protocols. Web developers and it professionals may find it challenging to meet the demands of the rapidly evolving state of these technologies (Chau, Wong, Zhou, Qin, & Chen, 2009).

Many companies use information technology and the internet to help streamline the organizational workings and enhance revenues (Ozcelik, 2010). However there remain challenges in even bringing some groups of people and business up to speed. Business' and people who have no access to computers and related technologies, will not be able to meet the growing demands on the global business end, but also will not be able to meet personal user needs of information technology and internet related products and services. Many countries in the developing world struggle to provide adequate basic technology in certain areas, including phone lines to say nothing of satellite service or cell phone towers. Companies in such communities may be unable to compete effectively in the marketplace a lack of information technology infrastructure because of geographic or other limitations. This not only has a negative effect but also hinders a company's future growth; thereby reducing chances of employment opportunities for others as well as being a major inhibitor of progress in the information age of technological advancement (Choudrie, Grey, & Tsitsianis, 2010).

The Internet is a "network of networks," linking millions of computers and hence millions of users together from around the globe. This technological 'power' allows data to be transferred from one side of the world to the other in a literal matter of milliseconds, including E-mails, instant messaging, files sharing and web browsing and other forms of information sharing and dissemination, including the distribution of news both local and global (Vangorp & Middleton, 2009).

Before the internet, networked communications between computers was very limited; two computers could share small amounts of data via a central mainframe. As previously discussed, through massive government funding and through the irrepressible drive of corporate profit-making and international commerce, the need for information technology, better and faster computers, a language and venue to transfer and store information, has all led to an incredibly complex yet user-friendly simplistic applications that belie the truth of the new universe of technology that created it (Leiner, et al., 2009).

Information technology and the rise of the internet has been a convergence of online capability due to the advances in computer technology and networking, and technological opportunism driven by market forces and user demands (Bellaaj, 2010).

Accordingly, businesses seek to maximize organizational effectiveness through use of information technology, and users seek to maximize what users are always seeking to maximize: their own needs. Many models have arisen that attempt to address both ends of the spectrum, business needs and user needs. This report will not focus on addressing the business side of the equation. Rather, this project will look at the perspective of user needs through applying a model of technology acceptance: the lazy user model.

2.2 Technology Acceptance Models

2.2.1 the Lazy User Model

The lazy user model was presented by Collan in 2007 and was further developed by Collan and Tetard in 2007 (Collan & Tetard, 2007). This model was created to focus on the user, as the main arbiter of technology acceptance. Most of the existing dominant theories in acceptance research centered on the concept of technology. The lazy user model, on the other hand, places focus on the needs and characteristics of the user in the process of solution selection. Furthermore, the theory focuses on the effort demanded by the user (user effort), when electing a solution to a problem from a set of possible solutions. According to the lazy user model, a user is likely to choose the solution that demands the least effort (Collan and Tetard 2007; Collan and Tetard 2009). The lazy user model tells us that whether or not people accept a technology depends upon the principle of least effort. Otherwise known as the path of least resistance, we see this idea inherent in everyday physical phenomena like water running down a hill. The principle of least effort finds support also in results from medical research, which has found evidence for the human brain applying the law of least effort when solving a problem (Reichle, Carpenter, & Just, 2000). The tradeoff between one solution and another is known as 'switching cost', which tells us that the user examines this cost in terms of time, energy and money when considering how to use a new solution. The Lazy User Model is thus diagramed. (Collan & Tetard, 2009).

2.2.2 Theory of Reasoned Action

The theory of reasoned actions (TRA) was presented by Fishbein and Ajzen in 1975. The origins of the theory stem from the study of social psychology. This field attempts to explain why attitude may affect behavior. TRA seeks to explain and even forecast behavior based on the beliefs, attitudes and intentions of people. An individual's behavior is a result of these three factors, according to the theory of reasoned actions model. According to Fishbein and Ajzen (1975), behavior is driven by behavioral intention. A person's intentions stem from the attitude toward the behavior. Moreover, the behavior in addition to the subjective norms, are also affected. During one's lifetime, various beliefs can impact attitudes. Descriptive beliefs can be formed by personal experience, or gained by obtaining outside information. More generally, the more 'likable' an object/concept is, the better the feeling regarding it, and the more unlikeable an object is, the more negative the feeling is regarding it. As a consequence, an individual makes an assessment about the outcomes of various behaviors. Indeed, the person will evaluate the desirability of these outcomes and associate either a positive or negative association with it.

The TRA model. This model reports behavior as a consequence of intention to behave, which is prompted by the attitude toward the subjective norm. (Adapted from Ajzen and Fishbein, 1975).

2.2.3 Technology Acceptance Model

The technology acceptance model (TAM) is an adaptation of the theory of reasoned action, and it was developed to fit the field of information systems (Davis 1986). TAM substitutes attitude toward the behavior and subjective norm of the TRA with two technology acceptance measures; the perceived ease of use and the perceived usefulness. TAM focus on how perceived ease of use and perceived usefulness affect the intention to use and actual use of technology (Davis, Bagozzi and Warshaw 1989, p. 985). Perceived ease of use is described as "the degree to which an individual believes that using a particular system would be free of physical and mental effort" (Davis, 1986, p. 26).

Perceived ease of use has a causal and significant effect on the perceived usefulness, which is defined as "the degree to which an individual believes that using a particular?

system would enhance his or her job performance" (Davis, 1986, p. 26). This model presumes that a person will be free to act when they have formed the intention to actually act. However,

several factors, such as social or environmental limitations, may affect whether or not the individual will act (Bagozzi 2007).

TAM Model. (Davis et al., pg. 985) (TAM).

2.2.4 Unified Theory of Acceptance and Use of Technology

The unified theory of acceptance and use of technology (UTAUT) was presented by Venkatesh et al. In 2003. The model seeks to explain the user intention to use an information system, as well as the accompanying behavior of users. Various competing theories have been combined in an attempt to produce a more expert model of user behavior (Venkatesh et al. 2003).

The UTAUT theory maintains that four constructs play a significant role as direct determinants of user acceptance and user behavior. These constructs are performance expectancy, effort expectancy, social influence and facilitating conditions. The first three constructs create a behavioral intent to act and, thus, conjointly affect use behavior. The fourth construct, facilitating conditions, does not impact user intentions, rather it straightaway influences use behavior. In addition to the four constructs that directly impact use behavior, there are four moderators that indirectly impact behavioral intention and use behavior. The four moderators are gender, age, experience and voluntariness of use. Each moderator impacts one or more of the four constructs (Venkatesh et al. 2003). The UTAUT model. Factors affecting behavioral intention and use behavior (Venkatesh et al. 2003, p. 447).

UTAUT interprets facets of the user's characteristics, as well as some conditions at the time of the possible action to use a certain system or function. Moreover, it studies the degree of willingness of the user, a point that is not mentioned in other theories. The focus of UTAUT is on using one applied science or technology (Venkatesh et al. 2003).

2.2.5 Cognitive Fit Theory

Cognitive fit theory (CFT) was developed by Iris Vessey. This stems from a general theory of problem solving (Vessey 1991, p. 220). Cognitive fit posits that problem solving is "an outcome of the relationship between problem representation and problem-solving task" (Vessey 1991, p. 220). According to CFT, the resolution to a problem is deduced from the mental internal representation, which is formulated from the problem representation and the problem solving task, and the interaction between the two (Vessey 1991, p. 221).

It is suggested that when similar types of data are offered by both task and representation, these processes create a like mental representation. Accordingly, this mental representation likewise employs corresponding processes to create a problem solution. Thus, the process used to act on the representation and facilitating the task match will be superior to any task that is not facilitated.

2.2.5 Cognitive Fit Model.

The problem-solver cannot use like processes for acting on a problem representation and solving the problem when the problem representation and the task do not match. When that happens, the problem-solver is not guided to problem solving alternatives; rather they are forced to them. Per Vessy, such a case results in a performance that is worse in cases where the problem solver is given the representation focusing on what type of information to use for a unique case.

Cognitive fit theory focuses mainly on how to create a fit between task and problem representation in order to better performance. It enables the possibility of testing distinct technologies to improve the solution. Notwithstanding, the theory does not regard characteristics or the experience of the user, it does not study the circumstances bordering the task, nor does the willingness of use become clear.

2.2.6 Technology Task Fit Model

The task technology fit (TTF) theory extracts from two complementary studies of research; user attitudes as predictors of utilization and task-technology fit as a predictor of performance. The theory puts forward that for technology to have a positive impact on individual performance, the technology must fit the tasks that the user must perform, and that the technology must be utilized (Goodhue and Thompson 1995).

Four factors affecting performance were identified in order to measure the task technology fit model: Task characteristics (nonroutineness, interdependence and job title), Technology characteristics (measured focusing on the information system used, as well as the department in which they are used), Utilization (the proportion of times users choose to utilize systems, or the perceived dependence on a system), and performance impact (the perceived impact on effectiveness, productivity and performance).

The TTF model. According to TTF, a fit between task and technology characteristics leads to improved performance.

The fit can be tested by measuring eight significant factors identified by Goodhue and Thompson. The eight important factors for measuring task technology fit are "data quality, locatability of data, authorization to access data, data compatibility (between systems), training and ease of use, production timeliness, systems reliability, and relationship with users, all of which are measured using two to ten questions" (Goodhue and Thompson 1995, p. 221).

Compatibility of the components can be established by measuring these eight factors, thereby showing possible weaknesses in the fit. A better fit is expected to create improved performance impacts, and a worse fit leads to poorer performance. TTF centers on the fit between performance, task and technology characteristics (Goodhue and Thompson 1995).

2.2.7 Diffusion of Innovation

The Diffusion of Innovations theory was presented by Rogers in 1962. It was designed to apply to most innovations, across industries and technologies. Per Rogers, there are "four crucial elements in the analysis of the diffusion of innovations; the innovation (something that is new to the individual), its communication from one individual to another in a social system (a population of individuals and engaged in collective behavior) over time. In this setting, communication is synonymous with diffusion, the operation by which an innovation broadcasts from its source to the final users. Time of the adoption process includes the user stages awareness, interest, evaluation, trial and adoption.

The diffusion of an innovation is affected by the type of person encountering the innovation, in addition to the five factors affecting the user's conception of the innovation. An individual's willingness to adopt an innovation is chiefly influenced by their characteristics. This places the person/user in one of five categories of individual innovativeness - innovators, early adopters, early majority, late majority or laggards - depending on their willingness to adopt innovations.

Moreover, the rate of adoption is influenced by how the innovation is perceived. This perception is found in terms of relative advantage - the degree to which an innovation is superior to ideas it supersedes, compatibility - the degree to which an innovation is consistent with existing values and past experiences, complexity - the degree to which an innovation is relatively difficult to understand and use, divisibility - later trialability; the degree to which an innovation may be tried on a limited basis and communicability - later observability; the degree to which the results of an innovation may be diffused or communicated to others of the innovation (Rogers 1962, pp. 124-132). Additionally, the rate of adoption is affected by the initial innovation growth as well as the rate of later growth.

Other researchers found that DOI was lacking in descriptive scope, and added more factors. Consequentially, DOI in information systems uses eight factors affecting the adoption of innovations: trialability, relative advantage, compatibility, voluntariness (the degree to which use of the innovation is perceived as being voluntary), image (the degree to which use of an innovation is perceived to enhance one's image or status in one's social system), ease of use, result demonstrability (the more the innovation is demonstrated and the more visible the advantages are, the more likely it is to be adopted) and visibility (the actual visibility of the innovation) (Moore and Benbasat 1991, p. 195).

The DOI in IS model. Implementation of IS mainly dependent on technical compatibility, technical complexity and relative advantage. In DOI, the focus is on one technology and how the use of the specific technology spreads to other users.

2.3 Evolution of Online Media

Online media is a convergence of the rapid growth of technology, and the changing face of the media frontier. David Shedden, Library Director of the Poynter Institute has constructed a timeline which for purposes of this report, is offered in a factual timeline manner, and will be condensed as follows (Shedden, 2010):

1969:

ARPANET is commissioned by the U.S. Government, which is based on a Department of Defense military project known as DARPA. ARPANET is an experimental network of four computers housed at four different universities across the United States. They go "live" in December of 1969. ARPANET evolves during the 1970's into what is commonly known as the "internet." The British Broadcasting System launches an interactive application of graphics and text. In 1969, Honeywell offers a $10,000 "kitchen computer." Compuserve establishes a computer time-sharing service which plays a major role in online communication development. The New York Times establishes 'Infobank', an electronic database of NYT stories.

1970: Alohanet, the first wireless computer networking system, is developed by Norm Abramson at the University of Hawaii. Alohanet is a packet radio network system. News copy is sent from a computer terminal in South Carolina, to a computer terminal in Atlanta, Georgia.

1975: The Altair 8800 is offered; it is the first personal computer for public consumption, offered at $495. The Compuserve dial-up company becomes an independent, publicly held company. French television begins testing a teletext service.

1980: Novell announces that local area network software will be developed. IBM continues to develop the first successful personal computer. Bill Gates and Microsoft hold the licensing rights to the newly developed MS-DOS system. The Compuserve dial-up service begins working with 11 Associated Press member newspapers. Teletext trials continue to develop popularity among news agencies.

1985: In March of 1985, the first .com internet name is registered. The Windows Operating System is released by Microsoft. Intel produces a 32-bit microprocessor chip, the precursor to increased speed by next generation processors. Quantum Computer Service establishes an online service for Commodore 64 and 128 computers. Quantum would later become America Online. The PressLink service is founded by Knight Ridder.

1990: The World Wide Web prototype is created at the European Laboratory for Particle Physics. The Windows 3.0 OS is released by Microsoft. Approximately 165 newspapers have electronic versions available for public consumption.

1995: The NSFNET computer network is transitioned to new network architecture, heralding a major step in the rise of the commercial internet. Amazon.com launches its platform. Many newspapers offer online stories. Windows 95 is released by Microsoft, including a platform for internet Explorer.

2000: Computer virus', web sales, and internet use is normal language in current events discourse. E-commerce and 'cybernews' develops rapidly.

2005: User-generated online news services are available. YouTube launches. Google Earth launches. MySpace is popular. Newsblogs by popular news sources are common. "Look into cyberspace and the picture for journalism seems fractured. There is real hope in the numbers of people who seek news online, particularly the young, a group that shows scant interest in traditional media. The capability of people to get what they want when they want it, and to manipulate it, edit it and seek more depth, could bring a needed revival to journalism. The economic numbers are also growing - and dramatically - each year." (Source: "The State of the News Media: Online Section." Project for Excellence in Journalism, 2005.)

2010: From CNN's Ed Payne: "These days, when everyone seems to have a Facebook friend, is LinkedIn or can Google themselves, it's hard to remember the old days, before the dot-com revolution. It was 25 years ago -- March 15, 1985 -- that the first dot-com domain name -- Symbolics.com -- appeared on the Internet, ushering in the commercial age of the World Wide Web." (Related stories from the San Francisco Chronicle, Wired, BBC, Fortune, a Facebookpage, and the site celebrating the 25th anniversary of .com.).