Theories on consumer attitude towards self service technology
Disclaimer: This work has been submitted by a student. This is not an example of the work written by our professional academic writers. You can view samples of our professional work here.
Any opinions, findings, conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of UK Essays.
Published: Mon, 5 Dec 2016
The attitude defined by Fishbein and Ajzen (1975) was the positive or negative feelings or affect owned by a person when he/she was engaged in a specific action. The consumers attitude toward the self-service technologies is defined as customers affect toward the self-service technologies.
Many researchers have found different variables and factors which effects on the consumers attitude towards self services. Some of variables are related to the IVR and some are related with the consumers.
The Technology acceptance model (TAM) perceived usefulness (PU) and perceived ease of use (PEOU) influences consumers attitude toward system usage (Davis, 1989; Davis et al., 1989; Mathieson, 1991). Even though these two beliefs determine consumers intention to use technology, the TAM does not include social norms (SN) as a determinant of behavioral intention. TAM also may easily lead to a misunderstanding of the actual processes involved in continued use (Kim and Malhotra, 2005). Bagozzi (2007) and noted that no research has deepened TAM in the sense of explaining PU and PEOU, re-conceptualizing existing variables in the model, or introducing new variables explaining how the existing variables produce the effects they do .
The Model 1, Technology acceptance model (TAM) is the clear extension of theory of reason action (TRA) but model 2 tried to integrate the various attitudinal theories such as theory of reason action, theory of planned behavior, theory of trying. A clear strength of Model 2 is that it combines well-grounded theory with practical, problem-relevant interventions. As an example this combination of theories has enabled the model to be used to study the behaviors of IVR consumer¿½s attitudes to understand the intention for future use, considering multiple factors which model 1 could unable do.
In comparison of TRA from model1 and the theory of planned behavior (TOPB), which is part of model 2, in the context of self service technology utilization, Taylor and Todd (1995) found that the TOPB showed an improvement over TAM in explaining behavioral intention and concluded that the TOPB provided a more complete understanding of intention than did TAM.
Technology acceptance model (TAM) or the theory of reasoned action (TRA) could not be used to predict behavioral situations, as the consumption or usage takes place over an extended time period. The theory of trying, also a part of the model 2, explores consumption behaviors. Also as found by Meuter et al., (2005), it is empowered with the intention to try, frequency of trying, social norms toward trying, attitude toward trying, attitude toward success together with the expectations of success, attitude toward failure together with the expectation of failure, attitude toward the process, attitude toward consumption, beliefs about consequences, evaluation of consequences, frequency of past trying, resistance of past trying.
TAM was also criticized by the number of researchers, as it was not found to be technology use is compulsory. It ignored external and situational influence particular to a given circumstance or culture (Al-Sukkar and Hasan, 2005; McCoy, Galletta and King, 2007). But at the same time model 2 in-depth analyzes the external factors such as, perceived risks associated with the IVR based self service, factors associated with the IVR based product categories.
As discussed in the above paragraph, model 1 – Technology Acceptance Model (TAM) has various limitations compared against the model 2- An integration of attitudinal theories to understand and predict use of technology-based self service. In summary, limitations of the model one against the second model can be highlighted as,
1 Unavailability of social norms
2 Low explanatory power
3 Limitations in explaining behavioral intention
4 Limitations in predicting behaviors in situations in which consumption takes place over an extended period of time,
5 Limitations in executing perceived behavioral controls
6 Limitations in exploring the perspective of customer¿½s intention to try to understand the major obstacles for innovation adoptions.
7 Ignorance of external and situational influence factors which are moderating variables in self service technologies such as IVR.
Bobbitt and Dabholkar¿½s (2001) model (figure 2.2) focus on the relationship between attitude, intention and behaviors. There are five main direct theories / factors which influence on attitudes towards using technology-based self services and its experience or favorable/unfavorable outcomes will affect attitude and it is a cyclic process.
1 Category based affect
2 Theory of reasoned action
3 Theory of Planned Behavior
4 Theory of trying
5 External influences
Consumers in general make judgments about new situations, products, or services based on related past attitudes and experiences. Fiske (1982) and Sujan (1985) suggest that past behaviors are associated with category-based affect, i.e. an effective association related to the category of behaviors. They further propose that when a stimulus matches expectations, it triggers this stored category-based affect. Such a generalized attitude has been supported empirically in terms of its influence on situations that are new to consumers, yet similar to their prior experiences (Dabholkar, 1996, 1992; Ledingham, 1984; Dickerson and Gentry, 1983).
In addition various demographic, psychographic, and socioeconomic factors that might affect consumer attitudes toward technology and their adoption to use the technology (Igbaria and Parasuraman, 1989; McMellon et al., 1997). As an example, considering the gender as a demographic category, various researches has come out with different outcomes. Previous research done by Pope and Davis (1991) in experimental findings related to gender based computer attitude, found that there are no significant gender differences in college students¿½ attitude toward the computer. But on the other hand, research did by Ray and Sormunen (2000) related to Men¿½s and Women¿½s attitudes toward computer technology found that Females held more positive attitudes than males regarding the value of computers to make users more productive. But the situation could be varied with Srilanka. As an example, research done by the Department of Census and Statistics in Srilanka (2009) found that computer literacy levels of males in Srilanka are 22.00% but females with lesser percentage of 18.70%. Therefore, if there is a relationship between usage and the attitude, males should have a higher level of attitude towards technology than females. Considering the geographical location as a demographic factor, the same researchers found that the literacy level of consumer¿½s from western province in Srilanka were 27.70% and the 2nd highest province which is southern province only 19.80%. The difference is nearly 8%. Therefore demographic factors should play a major role in point of attitude towards technology.
Also previous research done in related to IVR, a study of public attitudes about IVR as well as telephone answering machines indicates that attitudes varied strongly by age (Kaatz, Aspden, and Reich, 1977). But more importantly, they found that “information rich” persons were not any more positively inclined to IVR than the “information poor.” The most significant predictor of IVR acceptance was the quality of one’s most recent experience with the technology. This conclusion implies that good IVR design begets positive acceptance.
Attitudes towards using technological products in general may provide insight as to why some consumer¿½s do (and others do not). If consumers do not have favorable attitudes toward using technology in general, they will be less likely to have favorable attitudes toward IVR based technology. Therefore consumers might more prefer to contact human agent or will request others help to get the expected service.
The self service trend began with the introduction of the automated teller machine several decades ago, and it continues today with online IVR self services, online banking, online purchase of goods from a retailer¿½s website, self-service checkout at grocery stores and pay at the pump gasoline sales. The broad term of self-service technology has been applied to technological interfaces that enable customers to produce a service independent of direct service employee involvement (Meuter et al., 2000). The growth of IVR as a self service technology has built upon a number of advantages it offers compared to traditional human agent call centers. These include: 24/7 availability, better capability to handle large call volumes at peak hours, and much lower cost. Indeed, a Yankee Group white paper estimates the cost of an IVR self-service call at $0.45 versus $5.50 for a real-time, employee-serviced call (Schoeller, 2006).
On the other hand past research offers somewhat contradictory insights. Anton (2000) found that customers generally seek more human interaction the more complex the reason for the service encounter (Anton, 2000). Yet, for simple service transactions, Dabholkar (1992) found that the need for interaction with a service employee in order to resolve problems with the self service technology causes negative customer attitudes and dissatisfaction. Also Dabholkar (1996) found that the need for interaction with a service employee varies greatly among consumer¿½s. Similarly, Forman and Ven (1991) found that contact with a retail employee is very important to some consumer¿½s. For example, Many IVR systems do not provide callers a choice of selecting human operator, it has left many callers to feel ¿½trapped¿½ inside the system and stranded among an overly complex series of menus when they really just want to talk to a human being. A survey of 2000 panel respondents by Detica Research found that a massive 86 percent want to be given a choice of using IVR or speaking to a live operator (Marketing Week, 2002).This suggests that part of the consumer frustration with IVR may simply be forced use, irrespective of any other perceived advantages or disadvantages of the system.
Walker and Johnston (2006) found that willingness to use technology-enabled service is influenced by an individual¿½s sense of personal capacity or capacity to engage with the specific service systems that the consumer might be required to use, as well as the perceived risks and relative advantages that might result from that particular use. This underscores the need for a better understanding of the roles of technology and the human touch in customer service provision. It was proved by Dabholkar, (1990); Kelley et al. (1990) confirming that consumer¿½s who prefer self-service also perceive greater control and higher service quality. Also Langeard et al. (1981) and Bateson (1985) has surveyed the self-service consumer and have found that consumer¿½s viewed such options as efficient and offering control. They also found that consumer¿½s who avoided self-service saw it as involving too much effort, time, and/or risk. Also the previous research done by Mehta and Sivadas (1995) related to internet shopping has found that consumer¿½s with positive attitudes toward direct marketing are more likely to look favorably on direct marketing on the Internet. Applying this logic to IVR, it should be consumer¿½s with positive attitude towards self service options should have looked more favorable through IVR self services.
Also previous researches has found that consumer¿½s are much more likely to use new technology if they have used similar technologies in the past (Dickerson and Gentry, 1983; Korgaonkar and Moschis, 1987) and have formed favorable attitudes toward using these similar technologies (Dabholkar, 1996, 1992).
Fishbein and Ajzen (1975) define the theory of reasoned action as the links between beliefs, attitudes, norms, intentions, and behaviors of individuals. The concept of behavior intention states that an individual¿½s motivation to engage in behavior is defined by the attitudes that influence the behavior (Fishbein and Ajzen, 1975). Also the theory of reasoned action makes it clear that any attempt to influence the action of an individual, whether the goal is to change an attitude, norm, intention or behavior, must be directed at one of the individual¿½s beliefs. Therefore to change a person¿½s attitude it is necessary to know the primary beliefs on which the attitude is based. Therefore, studying the primary beliefs of consumer¿½s is very important to change their attitude towards using IVR for self services.
Also, one of the primary focuses in using the theory of reasoned action is to identify the link between attitudes and intentions to use the product. In the IVR scenario effort should be given to identify the attitude towards IVR and the intension to use the IVR self service options. As an example what do callers want by using IVR? In a study of 84 personality traits, more than 50% of the 50 subjects wanted the following (Chin, 1996): Practical (78% of subjects) , Intelligent (76%) ,Courteous (72%) , Efficient (68%) ,Straightforward (60%) ,Methodical (54%) ,Sophisticated (50%) . All these mentioned came along with a well developed IVR self service flow. That means if the consumer¿½s succeeded their expectations by using IVR self service options their attitude towards IVR will increase and as a result they will attempt to use more self service options offered by the IVR.
Situational influences can affect consumer¿½s perceived behavioral control. Therefore, they are highly relevant in a model examining the underlying motivation for technology-based self-service and Interactive Voice Response (IVR) in particular. Belk (1974, p. 157) defines situational influences as “all of those factors particular to a time and place which do not follow from knowledge of personal and stimulus attributes and which have a systematic effect on current behavior’. Lutz and Kakkar (1975) expanded on Belk’s (1974) definition to include the effects of situation on an individual’s psychological processes and overt behavior. A further distinction of situational variables can be made according to the type of the situation being either purchase situation, communication situation, or usage situation.
Similarly, if the consumer is using IVR and unable to get the relevant information, As an example, survey done by The Journal of Electronic Commerce (2002) found that consumer¿½s are unable to get the required information when menus that were too lengthy for easy comprehension, unclear vocabulary terms, inconsistent terminology organization of the menus, unclear categories, too many steps (menus too deep). The result might be that consumer may not be able to retrieve the information as quickly as desired and next time might attempt to contact human agent.
Marcoulides (1998) defines deductive approach as an approach of testing of theories. Using this concept, researcher continues with a set of identified theories and theoretical precepts. Accordingly develop the research hypotheses. Based on that, hypotheses will be tested. This research has similar behaviors with the Deductive approach. The research has compared set of theories and models and then identified the most suited theory and model which is Bobbitt and Dabholkar (2001) ¿½An integration of attitudinal theories to understand and predict use of technology-based self service¿½. Then researcher has developed the relevant hypothesis and tested with the research feedbacks. Therefore this research has more similar behaviors towards deductive approach.
Cite This Work
To export a reference to this article please select a referencing stye below: