 n this interview, in-cites correspondent Gary Taubes talks with Viswanath
Venkatesh, from the University of Arkansas, about his highly cited work in the field of Economics & Business. Dr. Venkatesh's work in this field garnered the highest percent increase in total citations for the bimonthly period of August-October 2003 in the
ISI
Essential
Science Indicators
Web product. Currently, his record in this field includes 10 papers cited a total of 233 times to date. Dr. Venkatesh is Professor and George and Boyce Billingsley Chair in Information Systems in the Information Systems Department at the University of Arkansas' Walton College of Business.
|
Your most-cited paper is from February 2000 entitled "A theoretical extension of the Technology Acceptance Model: four longitudinal field studies,"
(Manage. Sci. 46[2]: 186-204, Feb. 2000). What is the paper about?
It's about trying to understand how people form perceptions about the usefulness of any given technology or software system. Essentially we present two major types of influences. The first set is what we call cognitive instrumental processes, which is to say things that are important from an individual's internal perspective, from an individual's assessment of the
situation—what they consider when they are evaluating the usefulness of a particular technology. For instance, we talk about the quality of output that comes from the particular system, then we talk about the relevance to their job. Sometimes, software can produce high-quality output, but if it's not relevant to an individual's job, it doesn't really matter. The second set of influences is called social influence processes. Until we looked at technology acceptance in this way, typically social influences were taken to be something external to the individual. For instance, somebody tells you to do something at
work—it could be a supervisor or peer or a friend-and you do it just because they told you to do it. We were drawing on previous research about how social influence works, basing it on three mechanisms, known as compliance, identification, and internalization.
|
“TAM suggests that ease-of-use and usefulness perceptions are key drivers of technology use.”
|
|
Compliance, as we define it in the paper, is when an individual simply yields to some other influence. Your boss says do it, and you do it because you have to do it. The second mechanism is identification. You do something because you are trying to gain favors from someone or trying to build a certain image by doing it. That's identification. You do something because it has the potential to give you a certain type of social reward. The third mechanism is internalization: somebody tells you to do something but you do it because you think this person is like you, or you believe he or she thinks like you. This is typical of peer situations. Another professor in your department says you have to use this software because it's great, and so you do. You're not using it because they told you to use it or because you want to gain favors from the person, but because you've internalized the opinion of that person.
So those are the two major sets of determinants that drive people's perception of usefulness. And that is the primary topic of the paper. We do a lot of subtle things within that. We study changes over time; we demonstrate that some of these influences change over time. There is also a companion paper to this one, which appeared in
Information Systems Research, and that actually looks at the determinants of ease of use.
What prompted to you to start this work? What was the context in which it was launched?
It began as part of my dissertation work. I worked with several different companies doing new-technology implementation. This was back in the mid-90s, which already sounds like a long time ago. Everybody was trying to implement a variety of new technologies and facing a lot of difficulties, such as employee resistance, failure of systems, or the new technologies not being used in a manner consistent with their objectives, and so on. My motivation was essentially two-fold: to bring a scientific perspective to the problem about how people form opinions about technology, and to help these organizations implement technology successfully. One thing I tried to do in this work was to study technology implementation longitudinally: how does it change over time? Typically, the duration of my studies varied anywhere from about three months to about two or even three years. This is a general characteristic of my work, or it is if the organizations I'm working with are willing to allow me to participate in their technology implementation and to work with them for extended periods of time.
Does it surprise you how high an impact this work has had?
Not at all. Our work builds on very influential work of Fred Davis, published in 1989 via two
papers—in
Management Science and in MIS Quarterly. Fred Davis is my collaborator on this work. Back in 1989, in those two papers, Fred presented the Technology Acceptance Model, which was abbreviated to TAM. Our model is titled TAM-2. The original model didn't incorporate social influence processes at all. So we brought those in and the dynamics of various types of social influence processes and how they change over time. We also now have presented the determinants of usefulness, one of the critical drivers of technology acceptance per TAM. We were actually adding a significant richness of understanding of individual interaction and acceptance and use of technology.
So you knew while you were doing the work that it would be important?
We felt it was very important. TAM suggests that ease-of-use and usefulness perceptions are key drivers of technology use. It's a very intuitive model. If something is useful and easy to do, then people are more likely to do it. That's basically what it says in the simplest context. That's also primarily a predictive model. If you ask people whether something is easy to use and useful, and they say yes or no, it tells you how people will behave. What it does not do is provide useful guidance to the manager. If I know something will succeed or fail, it tells me if the investment will be successful or not, but it doesn't tell me what I can do to prevent it from failing. So if I know it will fail, what can I do? What my papers have done is to tell researchers and practitioners what it is that goes into the formation of usefulness perceptions and ease-of-use perceptions; that then gives managers important ways of turning the lever, essentially, "What can we do?" It helps them answer the question, "What can we be telling people or what can we be doing so people will have good perceptions of ease of use and usefulness?" So I'm not surprised it's having an impact. I'm glad it's having an impact. It's providing a much greater understanding to managers on how to make technology implementation successful.
How has your work changed since you published that paper?
My current focus is on studying much more complex systems. I used to study very focused systems: for instance, a system for inventory control or customer service. Now a lot of my work is focused on enterprise-wide systems. The other aspect of what I'm doing now is to actually look at the broader impacts of a technology implementation and not just technology use as an end in itself. In other words, I was interested in whether people are using the technology. Now I'm much more interested in job outcomes in the workplace. So there could be a situation where I have a very successful technology implementation, but there are other consequences that have to be taken into account. In other words, people are using this technology, and they've become more efficient, but perhaps at the price of their jobs being de-skilled, routinized, so to speak. In other words, the jobs have been simplified. The technology subsumes the brain of that activity, or has changed the processes in such a way that the employee no longer feels important. That could result in lower job satisfaction and lower organizational commitment. Now people might leave the organization. So there could be other negative consequences that occur that a very techno-centric view does not capture. So my present work focuses on understanding the relationship between technology success variables and broader outcomes in the workplace, such as job satisfaction.
Since the field of information systems has changed dramatically in the past few years, has the research on technology acceptance changed along with it?
A lot of things are evolving very rapidly and this presents a whole new set of challenges. Our questions have to evolve along with technology. It's a little bit of a chicken-and-egg story. We want to be motivated by practical problems, but by the time the science catches up to the problems, they may not be problems any more.
Is this what you would consider the biggest challenge in your research?
Actually to me the biggest challenge is finding questions to work on that are relevant to business practice. That is the philosophical foundation of my research: most, if not virtually all, of my research is field research. I work in organizations. And I study technologies in homes as well. It's also longitudinal because that's how reality is. So I like to be motivated by real business practices and real business problems, and I want to bring to these practices and problems a real scientific frame of reference that can contribute in a meaningful way. That is the biggest challenge: to make sure questions are always relevant to business practice.
Viswanath Venkatesh, Ph.D.
University of Arkansas
Fayetteville, AR, USA
|
cites
