technology adoption amongst educated non tech- savvy users...

Steyn J, Kirlidog M. (eds). 2012. Alleviating Digital Poverty with ICT innovation in emerging economies. Will ICT Rights make a difference? IDIA2012 Conference Proceedings Beykent University, Istanbul, Turkey

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Technology Adoption amongst educated non tech-savvy users in India:

Motivations, Hurdles & Behavioural Patterns

Singh, Deepak [email protected] Mehta, Dhaumya [email protected] Tanwar, Sachin [email protected] Joshi, Anirudha [email protected] Anuj, Dev [email protected] Indian Institute of Technology Bombay, Mumbai, India

ABSTRACT

In the context of India’s technological landscape, we see people now suddenly accepting several technologies for information sharing across personal and community channels. We conducted a naturalistic study with 18 users along with 4 usage partners (people who were either dependent on the respondent; or on whom the respondent relied upon while doing unfamiliar tasks) encompassing diverse demographic backgrounds in order to understand what were the dimensions related to users that played key role in technology acceptance. We also attempted to use a qualitative study based approach to find emergent usage patterns and relate them to the individual user dimensions. By concentrating on the emerging patterns and insights from our findings, we propose a framework that would be helpful in identifying the triggers and the barriers that mediate the technology adoption process. The framework is aimed at helping designers, entrepreneurs, and technologists in determining if users see value in new technologies; and their motivations for doing so.

Keywords

Technology Adoption Model, Information and Communication Technology,


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Technology Usage

INTRODUCTION

Technology is embedded into its social, political and cultural context. Therefore, its acceptance by people is a complex phenomenon. It has many dimensions that are less understood. This becomes important when we look at how fast mobile phone has penetrated. The rate of mobile penetration in India had reached 74.8% as of January 2012 (TRAI Press Release No. 60/2012, 6 March 2012), which would mean that almost 3 out of every 4 individuals either own a mobile phone or have access to it. For many of these users, the mobile phone is the first interactive digital device they have owned and/or operated. This deep penetration of mobile phone combined with the widening coverage of mobile service providers has, for the first time, brought information and communication technologies to the doorsteps of users who were earlier too far out to be reached by the conventional media; or, for whom internet-access arrangements were either too complex or tedious to manage. The current and prospective role of Information and Communication Technology (ICT) as a means of development has also been a strong theme of deliberation. However, the rate of internet penetration remained at only 10% in 2011(The Economic Times), in spite of the immense boost that mobile phone availability gives to internet access capacity. Most of these users are “dual users” who use the mobile phone as an additional terminal for internet access apart from conventional methods. A large portion of the discussion about Information and Communication Technology for Development (ICT4D) is centred on the top-down ‘push’ from institutions (e.g. Hilbert, 2011). It, however, becomes important to investigate the factors that affect ‘pull’ from the beneficiaries. This knowledge could help the policy level decision makers. It will also be of interest to designers of ICT4D systems because although there is a growing body of work exploring design solutions to overcome resistance to technology permeation, users themselves are known to gradually adopt technology and adapt it to suit their needs. There have been some studies that aim at understanding how people with less technology related abilities do these adoptions and adaptations, their motivations and resistances, the triggers that get them started with a new ICT4D system, the hurdles they face while using and learning to use them, and the workarounds they develop. To start with, a set of factors such as Attitudes (Gressard & Loyd, 1986), Motivation (Malone, 1981) and Self-Efficacy (Bandura, 1977), are decisive in determining whether a user engages with an ICT4D system or not. These factors, in turn, depend both on internal factors like cognitive abilities (which, as indicated in the next few lines, might be affected by levels of literacy); and on external factors like previous exposure to technology–whether in form of self-exposure or vicarious experience (these themselves may be affected by social and economic barriers against access of technology). Illiteracy needs a special mention here as it works as a prime detrimental factor to any form of communication, which relies on the text as a medium (Medhi, Sagar, Toyama 2007b). There are several facets to the impact of illiteracy on technology adoption. For instance, it has been shown that literacy has a positive effect on the way cognitive structures are formed (Katre, 2006). This affects the ability to form


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abstractions. As technologies, especially digital ones, involve structuring and abstraction of information, this directly affects their usage. In another study (Van Linden & Cremers, 2008), it was found that illiterate persons, in comparison to the literate people, fared poorly in terms of cognitive skills, like cognitive processing speed; visual memory and visual organization. In another study (Ardilla, Roselli & Rosas, 1989), while identifying the role of external variables, such as education, on neuropsychological abilities, it was noted that lack of education had negative effects on cognitive abilities. It should be worthwhile, in context of our discussion, to take note of the fact (as appropriately pointed out by the researchers) that the cognitive abilities measured in this particular study were “not “natural” abilities as we usually tend to think. On the contrary, they represent highly trained skills resulting from many years of learning” (p. 164).

In order to continue our discussion on technology adoption, we can ask— ‘what are these specific skills that help a person to thrive in a digital world?’ Some of these are (Eshet-Alkalai, 2004): photo visual skills, branching literacy (instead of linearity), reproduction literacy (recycling existing material), information literacy (ability to process information) and socio-emotional literacy. Literacy seems to have direct bearing upon most of these skills. As many of the cognitive abilities needed to operate digital technology artifacts (reading, abstraction, structuring) are highly practiced during the years of formal literacy, the literacy levels seem to play a strong role in deciding how well a new technology would be learnt. In light of these limitations, it would be interesting to see how people with low literacy cope up with new technologies and also investigate if there are other factors (like community support) that can offset the barriers posed by (limitations such as illiteracy).

The problem at hand, therefore, is to arrive at an integrated framework that would be able to predict the usage behaviour given a set of conditions defining a user and his environment.

One of the earlier attempts at defining users’ capacity to use Information Technology (IT) was in terms of what was termed as Fluency in Information Technology (FIT) (Lin, 2000). It had the following components in its definition: Skill involved in using an Information Technology artefact; An understanding of underlying concepts; and, Ability to creatively put the artefacts for attaining goals. The premise for going for such a definition was the following. IT was attaining more and more importance in our lives. Therefore, a better readiness for participating in such a scenario was needed.

In this context, it must be said, that in case of countries like India, the problem is not simply lack of an adequate understanding about IT. Rather, it is the fact that for majority of people such technologies remain inaccessible. Secondly, the abilities to use such technologies vary due to long history of socio-economic depravity. Thirdly, the cultural context of India is vastly different than that of the west and it must be examined what are the motivational factors in adoption of technologies. An early effort at forming a framework for technology adoption was Technology Acceptance Model (TAM) (Davis, 1989). It has its basis in Theory of Reasoned Action (TRA) (Fishbein & Ajzen, 1975). According to TRA, behavioural intention depended on two factors. The first was a person’s attitude towards that behaviour. Attitude was


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defined to depend upon perceived consequences of a particular behaviour along with the evaluation of those consequences. The second factor was Social Norm that was defined as a person’s perception of whether most of the people important to him/her approved or disapproved of a given behaviour. The concept of perceived behavioural control was added to TRA later (Ajzen, 1991) and gave rise to Theory of Planned Behaviour (TBP). This construct was added because it was noticed that “people’s behaviour is strongly influenced by their confidence in their ability to perform it” (p. 184). In this regard, the aspect of perceived behavioural control comes very near to the concept of Self-Efficacy (Bandura, 1977). TAM proposed that actual system use is dependent on user’s motivation to use the system, which in turn was dependent on the characteristics of the system itself. It was further proposed that user’s attitude towards using a system would be a prime factor for intention to use it. The attitude itself would be influenced by two major beliefs: Perceived Usefulness and Perceived Ease of Use. Moreover, Perceived Ease of Use had an influence on Perceived Usefulness too. As the model evolved, it was found that both Perceived Ease of Use and Perceived Usefulness had direct effect over Intentions, resulting in dropping of Attitude. Also, there was consideration of other variables that would affect a person’s beliefs towards a system. TAM2 (Venkatesh & Davis) was an effort to explain why somebody would find a system useful. It was done by adding additional variables as input to the same (person’s beliefs towards a system). By the time of TAM3 (Venkatesh & Bala), many external variables were defined that fed into Perceived Ease of Use (computer self efficacy, perceived enjoyment, computer playfulness, computer anxiety, perceptions of external control); and Perceived Usefulness (social norms, image, job relevance, output quality, experience, result demonstrability, voluntariness). In between, other studies, which did not derive from TRA, for finding important factors that define Information System (IS) success were also attempted, for example DeLeone & McLean’s (D & M) IS success model (DeLeone & McLean, 1992) is an important one. A review of research between 1989-1991 resulted in the following interdependent factors: System Quality (qualities like reliability, accuracy, response time, usability of system); Information Quality (quality of output); Use (volume and frequency of use); User Satisfaction; Individual Impact (confidence, quality of decision, time expended; and, Organizational Impact (overall performance). IS success model was later studied by Seddon & Kiew (1996). In their evaluation, they modified the model in following ways—firstly, they proposed to replace the construct of Use to Usefulness. The rationale behind it was that non-use did not imply non-success because a person might have had other pressing things to do. Even if a person did not use a system, it still could be perceived as useful. Conversely, a high use did not imply success because the usage might have been compelled on the user. A direct outcome of this alteration was that while in the earlier model, Use and User Satisfaction had two-way relationship, in the newer one it was proposed that usefulness would guide User Satisfaction, not the other way round. In addition, a new construct System Importance was added. This construct tried to relate the importance of a system in light of the importance of the task it was supposed to perform. In other words, “task performed by the system was important would also perceive the system that performed it to be useful”. (p. 97). As indicated earlier, technology acceptance is a complex affair, especially in


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countries like India owing to complexities in various dimensions. It would be worthwhile to explore what factors might be playing role in technology acceptance in case of the developing countries. We propose to attempt this study in a qualitative manner and arrive at a framework. Focus of this paper revolves around a group of users who are literate and educated, and yet are not totally familiar with ICTs. In this paper, we present findings from a study with 18 such users along with 4 usage partners—people who were either dependent on the respondent; or, on whom the respondent relied upon when it came to doing unfamiliar tasks. Based on our analysis, we identify dimensions that characterise technology adoption and adaptation among these users, and identify set of user profiles that get generated along these dimensions. We present our analysis with respect to some of these user profiles. The next section describes our method and the users we talked to. The third section describes the user profiles. It is succeeded by a description of the user dimensions, that we believe help characterise technology adoption among people with low levels of technology familiarity. The fourth section organises the users whom we spoke to among 7 specific categories that we found to be relevant and that fit specific points in the dimensions that we identified. The fifth section describes our findings related to technology adoption among these categories of users and identifies usage dimensions related to technology adoption (the output dimensions). The sixth section proposes a preliminary technology adoption framework based on these categories. The seventh section presents some discussions, conclusions and identifies opportunities for future research.

METHODOLOGY

The study comprised of detailed conversational interviews with 18 users and 4 usage partners in their natural environments. Unlike formal interviews where all respondents face an identical pre-structured set of questions, we adopted more naturalistic research methods of Contextual Inquiry (Bayer & Holtzblatt, 1997) combined with mute observations and probing wherever required (Corbin & Strauss, 1990). There were two reasons why we preferred this approach. Firstly, there were great disparities in the backgrounds of the respondents; and their perceptions and opinions changed on the basis of the prevalent local beliefs and cultural habits. For example, we found that in small towns, for banking operations, people strongly believed that online process was unsafe and messy. Statements like “online is for big cities, in small city everything is nearby” were encountered. Secondly, users’ responses were often related strongly to their situational contexts. For example, while doing the study we found that one of the users initially told that he often checked his emails on his own. During the course of study we went to his home and requested him to check the mail. However, his answer was different from what was reported earlier. Thus, being in context not only allowed us to mould the flow of our study better, but it also enabled us to cross-examine and probe the statements given by our subjects in minute detail in order to create a holistic view around the issue. Talking to the usage partners was an important means to gauge the influence which other individuals had on the usage patterns of our respondents and the supporting role they would play in helping them grasp newer concepts. This also gave rise to


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social dynamics centred on trust and faith, especially with reference to instances where financial matters were a part of the human equation. Out of the 4 usage partners, 2 were from urban areas and were owners of cyber café, and thus were adept users. The remaining 2 from rural area, a personal banker and a postman, did not know to use any technology. Further, we explored what all potential outcomes would mean to the design of technological artefacts and how the framework could help evolve designs which could motivate users to learn new technologies on their own.

USERS’ PROFILES

We did the study in various places in India ranging from large cities to small towns where we were familiar with the local languages and places. We interviewed wide spectrum of people belonging to different cultural backgrounds, ethnicity and beliefs. The study encompassed 22 (18 users and 4 usage partners) such users whose profiles varied substantially across the following parameters. People were selected using convenience sampling.

1. Geography:

a. Metro Cities–Mumbai, New Delhi

b. Urban Tier II Cities—Ahmedabad, Vadodara, Jaipur, Lucknow

c. Semi-Urban—Lakhimpur Kheri (in State of Uttar Pradesh)

d. Rural—Padri Village in Unnao District, Laharpur Village in Sitapur District (all in State of Uttar Pradesh)

2. Age Groups: Between 18-70 years

3. Profession: A variety of income bands (including users who are socially or financially dependent)

4. Language Proficiency: Adept at conversations in their own mother tongues with varying ability of reading / writing in their own language. Different abilities in understanding and using English.

5. Access to Communication Technology: From cyber-café users, with a single borrowed mobile phone to users who owned multiple laptops, tablets and smart phones in their household.

We spent roughly 3-4 hours with every respondent with approximately half the time being used for active dialogue or question and answer. With the exception of 3 respondents, all the others were conducted by a team of at least two interviewers, one mainly involved in conversation and the other in charge of documenting the discussions and observations. Photographs and live notes were taken down during the course of the dialogs as they happened. The direction of the interviews was guided by a loose agenda, and respondents were prompted with pinpointed questions on the basis of which they could narrate their relevant inputs. We also looked at tasks which could be accomplished in several ways in addition to being done through the use of technology, and the differences in the notion of ‘convenience’ amongst these different users with reference to every task. These


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included booking railway tickets, movie tickets, sending pictures, making bill payments and conducting third-party money transfers. Our study aims to provide an important framework for designers, entrepreneurs, and technologists for designing online applications and services for these populations. More importantly, it is proposed to serve as a window to understand users’ perceptions of Information and Communication Technology (ICT) and help determine whether or not users would see greater value in using ICT.

User Dimensions

Based on our data and analysis, we propose 3 user input dimensions: Willingness to use Technology, Ability and Access to technology. We identified ability into 4 categories (to use on one's own, to use with help, to use by delegation and to not use at all). For access we identified 3 categories (high, medium and low) and 4 categories for willingness (prefers / enjoys, is neutral about, uses reluctantly and is unwilling to use).

Figure 1, 2: Analysis and affinity mapping of data

We then mapped the statements, observations and findings from Contextual Inquiry on to a matrix formed by these three user input dimensions (Appendix). There were some combinations that seemed impossible. For example, there could not be a category where a user had a high access and preferred using a technology but did not use it at all. Hence, such categories could easily be ruled out, while there were some for which we lacked the user data which we would like to consider in the future. Although the nature of issues which the respondents narrated was diverse, we often found commonalities in the root causes behind these during analysis; which we used, in turn, for finding emergent patterns in the matrix. The following are the patterns that emerged: Resource Deficient Person: Not having sufficient basic resources & infrastructure needed to access the technology. Completely Dependent User: Relies on others for either know how, infrastructure, or both in order to get tasks done. Non-using Owner: Has access to the technology but never uses it or needs it Capable but Reluctant User: Has sufficient domain knowledge about the technology and the intended use but is not enough confident to operate the technology.


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Communication-centric User: Uses the technology for all purposes except financial transactions and security / confidentiality related matters Self-sufficient User: Uses the technology and is willing to take chance in delicate situations. Compelled User: Situations force technology use, directly or indirectly. A detailed analysis of these patterns is provided in next section.

Technology Adoption Patterns

Noteworthy details of the data we gathered according to each group are as follows: Resource Deficient: The respondents acknowledged the existence of the technology but the absence of real experience gave way to several hypothetical beliefs and inflated expectations (especially from the Web). They gathered a broad image of the technology through stories learnt through newspapers or word of mouth conversations. Accessing technology was considered well outside their notion of “convenience”, meaning that they preferred to do things on paper even if it meant spending more time in the act simply because it was easier to do. Since resource deficiency overlapped with other limitations related to educational backgrounds, network coverage and financial status, respondents expressed the following concerns: 1. Unavailability / unaffordability of hardware 2. Discomfort in using English rather than their vernacular language 3. Notion that Internet can be used only upon completion of a formal course or training

4. Assuring themselves that they were well-equipped in case technology and digital media suddenly died out some day.

5. Belief that the problem of hardware unavailability was the only one that needed to be addressed and that all other issues would sort themselves out eventually.

Completely Dependent: We found this category to relate strongly to age, gender and family structure. Respondents who considered themselves either too old to operate devices or who were considered too young to use devices independently were commonly found to depend on others— either within the family or people in close proximity. From the 6 users in this segment, all the female respondents considered the Internet as a secondary channel of information which they would not access unless absolutely essential. In one instance, email was used only as a form of exchanging family photos. Upon being sent an email, the recipient was asked to check her mailbox through a phone call. Among the elderly, most respondents, with the exception of one, considered the Internet to be a tool meant only for young people and that they were too old to learn using the Internet. Such respondents expressed no motivation to use the Internet as younger members of the family would always be around and would be more than keen to carry out tasks as directed. Even in cases where the younger generations of the family had moved out for work or education, such directions would be mediated via convenient means such as letters, telephone or an intermediate person. Apart from knowledge-based dependence, we also found that there were


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dependencies related to resources and time availability. A family, which would otherwise qualify as resource deficient, depended on their son who could access the Internet through his office in order to book railway tickets. A senior citizen couple relied completely on a particular trusted bank representative who would deliver the services at their doorstep. Non-using Owners: Users who had access to the Internet either through their individual ownership or through a shared connection but still did not use the Internet were found to be limited primarily by their surrounding environment. Such respondents expressed full awareness pertaining to the end utility of web-based activity and agreed that internet-based operations had many advantages. However, most were not sure of what the intermediate steps in carrying out a specific task on the Internet would be. The cognitive load of learning to use the Internet outweighed its latent advantages as these users preferred to do tasks manually on their own even if it meant spending more time. However, in the presence of available assistance, they would prefer to get the tasks done through the Web. One respondent, a government official, expressed complete dependence on his secretary in executing official communication – as per his explanation, he knew the end objectives of the task and it was up to his secretary to figure out the method to fulfil them. His explanation for himself not learning how to use the Internet was that he would need training and training would need time, which was largely unavailable. Capable but Reluctant: We found a definite category of respondents which had sufficient know-how and the required domain knowledge but not enough confidence to initiate regular usage. They demonstrated higher anxiety towards executing sensitive tasks such as conducting financial transactions or confidential usage. These respondents preferred to give up if they would find no easy alternative methods and would seek the help of someone who they know had done the task before. The competencies of these respondents were found to be extremely artefact dependent, meaning that any hardware changes from their familiar configurations would cause confusion or distress. 3 respondents expressed the habit of using only one particular ATM from the many available citing their familiarity with fine properties of that terminal, such as the display text appearing in large fonts, perceived security of the physical location of the machine, and the interface being touch screen as against button-operated. Communication-centric User: A part of the younger respondents were found to be comfortable with internet use only for email and other forms of online communication such as instant messaging and social network services. This group overlapped with several others, with two out of four users accessing the Internet mainly through cyber cafés. These users demonstrated a fair idea of the uses of the Internet but refrained from attempting more complex tasks such as internet payment, banking or file transfer. Such tasks were done manually through familiar means or through an intermediate operator. High dependence on search engines to use the Internet was common. Self-sufficient User: These users were a step ahead of the communication centric users as they had enough skill to take chances while figuring out the means to confront unfamiliar tasks. These users learned from the errors they made and


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preferred not to rely on external help to carry out desired tasks. The eagerness to explore newer content online was high. Their assistance in doing tasks was sought by other users. Compelled User: Several respondents attributed their ability to use the Internet as an outcome of work pressure or situations where the Internet-operating acquaintance moved out of the house. These users were compelled to learn how to use the Internet on their own by receiving some initial priming and instructions on how to perform some specific tasks. Given a choice, these respondents expressed their preference for manual methods but were faced by situations where using the Internet became the only viable option. These users still consulted experts for troubleshooting but also picked up internet usage skills gradually over time. The commonest example of such users was parents who were forced to learn how to use video chat due to their children moving out for higher studies or employment.

INSIGHTS

We also performed a detailed analysis of the statements given by the respondents of the aforementioned categories, and corroborated with our on-field observations. The statements were clustered on the basis of the specific issues and then categorized to the context to which they were related. The insights gained were common to both the rural and urban areas. (In cases where there was something unique about rural areas, we have mentioned it categorically.) The main insights we gathered have been populated below: Linguistic limitations Owing to a variety of languages in India, several users, who had qualifications even up to masters degrees, faced difficulty in understanding and operating interfaces due to the fact that the language of operation and terminology was different from their mother tongue. Even where an option to use the technology in their mother tongue existed, there was a marked difference between the words and meanings used by people as a part of their daily spoken language and the words used in the pure & ideal form of the same language. Several different degrees of amalgamation between languages, such as the rise of different levels of a Hindi-English mixture in day-to-day conversations deepened the issue further. Perceived importance of formal training for using technology Non-users who either had relatively lower exposure to technology or who had crossed their middle-age often felt that it was impossible to learn using the technology on the basis of pure experimentation or even through informal training. These respondents, in their conversations, often quantified the ability to access the Internet as an attribute akin to a skill which merited a special qualification and intensive formal training. Assistance needed due to unfamiliarity with peripheral tasks While most respondents expressed the need to undergo mental preparation and goal-setting before using web-based technologies, seemingly trivial but unexpected


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complications were the cause of immense cognitive anxiety, thus causing the user to stumble even in the execution of his main agenda. In many instances, this lead people to resort to manual and more time-consuming ways of work to avoid this anxiety unless an informed and capable person was willing to assist him in the process. Availability of resources In spite of being aware of the perks of the technology, several users were unable to gather sufficient resources to use it. Such users typically had a “magic box” image of the technology and often held unrealistic expectations from it. However, they considered themselves as too unqualified to be able to use the technology even in the future. Age leads to dependence We found that as age progresses, thanks to the fact that elders live with their children’s families, users choose to rely on a younger and more tech-savvy member of the family to take care of their needs. However, this extinguishes their motivation to learn how to use the technology on their own as help is readily available, and their tasks are being taken care of without having to toil to learn the technology. There are also additional physical limitations related to aging such as delay in motor responses, memory recall, etc. which de-motivate these individuals. Influence of the context and lifestyle on the notion of convenience There was a marked difference in the approach of rural and urban users in performing tasks. For the urban, the tasks to be done invariably exceeded the available time, whereas the situation was exactly the opposite in rural areas, where every task needed to take up a certain amount of time in the day. This lead to significant differences between the attitude of users towards doing things using technology – while the urban person would find it more suited to bank online, his rural counterpart would consider walking to the bank as an easier task than having to face the cognitive pressure of navigating though an unfamiliar technology. Influence of community Usage amongst peers acted as a strong motivation to experiment and use online applications. Typical hubs for such interactions were office environments, where users developed competency only in the area of their work. Seeing peers use other applications of the Internet worked to instigate curiosity and experimentation to do the same on their own. Memorisation of usage patterns People were comfortable in interacting through repetition of patterns before concept formation. Constant repetition of actions and steps resulted in subconscious memorization. Unlike the process of forming detailed mental constructs, this approach was easier, quicker, to-the-point and could be transferred from one person to another. Anxiety related to online financial transactions We found out that dealing with currency in an abstract form leads to uncertainty/anxiety at the intermediate stages where it is not being quantified


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onscreen. This adds to the already existing hesitance of use due to fear of causing irreversible damage to the settings or the monetary balance.

Adoption Framework

Based on the insights gathered through our study, we derived a macro-level framework to explain the stages of technology adoption and possible journeys for educated non tech-savvy users. The framework we propose imbibes the learning gathered through such approaches into a one-to-one user centric framework which serves as a reference for understanding an individual’s stage-wise process of adopting technology.

Figure 3: The User-Centric Adoption Cycle

Options: At this stage, all means to accomplish a goal are considered to be open, including manual methods, and processes which can be done through indirect use (bypassing direct technological interaction by asking an assistant to do the task). The goal itself is not rigid. That means that alternate schemes that eliminate the need for the particular goal itself are also considered as a possibility. There exists a default bias in favour of familiar methods which the user has either tried herself or is aware of as a successful method. In context of the users’ interviewed here, parameters like unavailability of technology coupled with corresponding lack of acquaintance with the interface eliminate the option of accomplishment of the task through direct interaction with technology. Opportunity: Through triggers like word-of-mouth suggestion from a peer ahead in the cycle or due to the methods of manual effort mismatching with the user’s initial assumptions, the user is prompted to contemplate about alternatives to the means which have been familiar to her till now. The real scope for moving onto use of the concerned technology germinates here, as the user compares the attributes of the till-now-familiar means against available or prospective access to technology. If the newer proposition is found to be compelling enough as compared to the older means, the adoption process goes ahead. Convenience: In the situation where sufficient access to the technology is available and where there is some form of assurance of success of the technology in question, it outweighs the past means of accomplishing the task. Consideration on factors related to convenience, such as the availability of time and other pending tasks at hand, work out to form a proposition which is compelling enough for the user to


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convince herself to undergo the learning curve. As possible risks are evaluated and solutions are sought, intangible aspects like trust and faith come into play – this is when the user considers herself, instead of a consulting mediator, as the primary executor of the task. Solution to Obstacle: By now, no other alternative method is deemed to be equally effective, and the user is compelled to take the plunge. Situations or contexts which are time, location, or space sensitive accelerate the phase, as the user attempts to overcome the overwhelming cognitive anxiety by either generating a hypothetical process flow in his mind or is supplied by stepwise instructions by an expert user. As these instructions are put into implementation, the two obvious possibilities arise: Task is accomplished – The user has successfully confronted the task as well as the requirements for using a new technology. Post the afterglow, the user is now assured of the value of the newly learnt path and it takes the highest place in the list of preferred options. Thus, any incremental updates to his learning are picked up rapidly as long as they remain convenient in the flow of the original process. Smaller affordances are also gradually explored, and this mini-cycle of incremental gain in knowledge is repeated several times. Over the time, the usage gathers enough momentum to let the user depend on the means as the primary method of accomplishing the task and builds reliance and trust on it. Good long-term experiences with the technology opens up the user to use similar means even for other tasks, and they will thus undergo the cycle again with reference to another task. Task fails – In case the efforts of the user in coping with the requirements of usage bears no fruit, the user experiences disappointment (or frustration in extreme cases) and the proposition gets thrown back into the pool of options. The perception becomes—‘this method has failed in accomplishing the task.’ It now carries even lesser priority against the other non-tried options. After this stage, it becomes harder for the same option to make its way up the subsequent stages unless it is promptly analysed and troubleshooted by an expert or another person familiar with the method. As compared to linear technology adoption models, the cyclic nature of the framework finds application at multiple levels. In a direct sense, it refers to the user’s sequence of learning newer features and attributes of a technology. This contributes to the formation of a higher level view relating to the user’s needs, motivations and abilities in view of adoption of a new technology. That also explains the psychological milestones a person meets during the process. Further, it covers the entire span of relationships shared with the new technology – from being oblivious, to consideration, to persuasion onwards to a level where the user starts relying on it. In certain situations, the cycle needs to repeat itself over and over again in order to gather enough momentum to move over to the next stage. Finally, the cycle also acknowledges the occurrence and role of failure in shaping the user’s perceptions towards a new technology.

Discussions and Conclusion

The aim of our study was to explore user dimensions that affect adoption of technology and relate them to emergent usage patterns from the qualitative analysis


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of the field data. Our study of 18 educated non tech-savvy users and 4 usage partners enabled us to derive insights into identifying triggers, catalysts and impedances related to technology use and adoption. By concentrating on the patterns emerging from our findings, we proposed a framework for technology adoption. The patterns also helped us define broad categories of users’ characteristics. This helps us to identify broadly what effects different (input) dimensions of users have on how users behave with respect to technology adoption. Since our study takes into account user insights from across several technologies, we believe that this cross-technology applicability also percolates into the framework. Further, since we adopt a user-centric standpoint in place of a predominantly technological perspective, the framework applies even to adoption of emergent technologies. The framework is envisaged to be helpful in identifying the triggers and barriers that mediate the technology adoption process. It has an undercurrent that considers usage of technology as a tool (to accomplish tasks) rather than an aim. Most past work in this field provides insights assuming that newer technology is automatically used by users. However, several times during our research, we were able to find instances where users preferred to hang on to older means and methods (which lie beyond the definition of technology). The explanation for this is that people would not go for a new technology if it does not offer efficiency in terms of efforts over the non-technological methods. This seems to be a probable reason why several newer technological developments were introduced and died out even without being considered for use amongst large populations. Our framework is envisaged to push coherent but non-technological alternatives into the field of view while designing applications and services for people with low levels of technology familiarity. Our immediate plan of action includes probing the role of assistantship or guidance in the process of technology adoption. Further to the current study, we would also like to develop our framework along both macro and micro levels. On the former, we would like to determine the effect of finer variables like context-specific triggers, effect-oriented segmentation of usage environments, and the common patterns in jumping across technologies. On the macro level, we would like to see if similar frameworks emerge out of trends in technology adoption and usage in non-literate or barely literate users and how these two segments of users influence each other’s technology adoption cycles. Amongst other things, the framework also aims to lead to a tool that can help in determining if users see value in changing technologies and their motivations for doing so. Therefore, it remains in the scope of future work to develop the framework into a model.


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