Understanding Diffusion Of Innovation - The Indian Context
Posted in Operations & IT Articles, Total Reads: 2853
, Published on 04 December 2013
Everett Rogers (2003) provides a Diffusion of Innovation theory as the process by which innovation is communicated through specific channels over a period of time among a certain members of the society. The theory identifies four main elements that influence the spread of an idea. The first element is the innovation. Rogers (2003) defines innovation as an idea which is perceived as new by the society. It can be an object or even a practice. The second is the communication channel, the medium of transfer of information where manifestation of awareness and interest takes place with time. Time, the third element, is the length of time required to pass through the diffusion process and lastly, social system is the set of individual and other units of adoption that form a society.
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Diffusion of Innovation theory presents five main intrinsic characteristics of innovations that play major role in an individual’s decision of accepting or rejecting the innovation. Relative Advantage is the first, which, primarily, is the measure of the superiority of the innovation over its previous generation. Second, Compatibility is the level to which the innovation has to be conformed to the life of the individual. The third characteristic is Complexity. This is in inverse proportion with the likelihood of adoption and diffusion. Trialability, the fourth characteristic, measures the ease with which an innovation can be tested and experimented. If the test results are favorable, consumer is more likely to adopt. And the fifth intrinsic characteristic is Observability, a measure of visibility. An innovation, which is more visible to others, enhances the chance of having a continuous flow of information among opinion leaders and other unit of adoption about its positive and negative features.
There is a theory given by Rogers and Shoemaker (1971) which defines the rate of diffusion as the relative speed with which an innovation is spread among the certain percentage of the members of the system. In such uncertain environment, the prime concern of any firm is the number of failures in the marketplace. One possible reason, as explained by Hassan, Mourad and Tolba (2010), could be the inappropriate application of the diffusion models. Another possible reason could be the factors that affect the rate of diffusion. However, it is quite a task to evaluate and develop a better understanding of the factors that influence the accelerating rate of diffusion. Across the world, this has emerged as the top priority among the researchers and managers, mainly those in tech firms.
The factors that affect acceptance and diffusion of innovation can, primarily, be classified as individual factor and cultural factor. Individual factors are represented by the role of opinion leaders or innovators, while cultural factors include Hofstede's cultural dimensions theory, mainly uncertainty avoidance and individualism. Rogers and Shoemaker (1971) state that the adoption and diffusion process follow a Hierarchy of Effects model, as given by Robert J Lavidge and Gary A Steiner (1961).
Since “Awareness” leads to “Knowledge” and hence “Liking”, it is imperative that communication of information is effective enough to create positive perception of the functional benefits and form a favorable attitude toward the emotional benefits of the product. The role of opinion leaders is to develop the “Preference” for the product. The main characteristics of the opinion leaders are knowledge, social influence, innovativeness and interpersonal factors. They are the ones who enjoy higher socio-economic status and have the urge to adopt an innovative product before the society. A positive word of mouth influences the consumer’s decision-making process and at times, the opinion leaders, even, act as the role model for few. Furthermore, cultural characteristics also influence innovation diffusion. Geert Hofstede’s cultural dimension theory identifies five dimensions which describe the effect of culture on the behavior. Ahmed H. Tolba (2001) identifies Individualism and Collectivism as one of the most critical factor that influences rate of diffusion of innovation in a culture. The study states that in an individualistic society, out-groups affect the decision and hence work as an influential factor in innovation diffusion. However, in collectivist society, in-groups foster the early stages of innovation adoption. The other dimension is the Uncertainty Avoidance, which means the measure of tolerance to risk. Ahmed H. Tolba (2001) states that a society with high Uncertainty Avoidance form rigid rules within, which in turn hinder the acceptance and diffusion of innovation.
According to Rogers (2003) a successful innovation diffuses in the same way as that an epidemic. And it is the communication among the potential adopters which determine the rate at which the innovation diffuses or new product is adopted. According to a Technical Assistance Research Program, the negative word of mouth about a new innovation spreads faster than the positive word of mouth. According to John A, it is observed that early adopters have a greater part to play in the opinion leadership than the later adopters. The figure is as shown below. It clearly shows the importance of inter-firm contact in the diffusion of innovation. Dorothy Leonard – Barton suggested that very late adopters were more likely to discontinue the use of a product than the early adopters.
Tata Chemicals Ltd. (TCL), in the year 2009, introduced the “Tata Swach”, which was coined as the world’s cheapest water purifier for household purpose. This was the dissemination of innovation carried out by Tata Motors, another Tata Group Company, when it launched the world’s cheapest car, Tata Nano in the same year. TCL followed on the heels and after investing in R&D for multiple years, it, eventually, launched itself into the industry, which termed it as disruptive innovation. TCL Annual Report (2010) identified the objective as a water purifier which would cut down the occurrence of water borne diseases by purifying drinking water and making it accessible to all. According to the report, the term “Swach” is a variant of “Swachchh”, which is a Hindi word and means “clean”. The TCL report has recognized its Innovation Centre for this innovation which is based on the cutting edge nanotechnology and utilizes natural materials. TCL (2010) claims that the purifier, which uses locally sourced materials with nano-silver particles as the filtering agent, eliminates around 90% of the germs and removes most of the virulent pathogens that, according to Ahlstrom (2010), cause diseases like cholera, diarrhea or typhoid.
Lamont (2010) draws the conclusion that Innovation in India has become more focused towards targeting high demand. It mentions to TCL’s Sawch, in the same context, and identifies its target group as the households, primarily poor and located in semi-urban and rural areas with limited access to running water and electricity. The prime objective, as said by the Tata Group Chairman Ratan Tata, was to reach to the people who do not have pure drinking water. Priced at half the price of its closest competition, Hindustan Lever’s “Pureit”, Swach, according to Lamont (2010), has made the competition irrelevant. Kinetz (2009) explains about the Reverse Osmosis technology that “Pureit” uses and quotes its price as Rs. 2200 (approx. $44), while Swach, the world’s “lowest cost” purifier, is priced at Rs. 999 (approx. $21). Explaining the features of the product, Kinetz (2009) mentions the purifying capacity as 9 liters and a running period as 3000 liters before the bulb needs to be replaced. It, further, says that the replacement of bulb can be done at a cost of Rs. 349 (approx. $7).
In the first year of its launch, TCL expected a volume sale of one million units. TCL (2010) confirms the acceptability of the product among the consumers and acknowledges Swach for creating a new market. TCL (2011), further, affirms the sale of Swach in more than 12 states of India, 9 more than the previous year. TCL (2011) proclaims that the product has been received well by the system and termed the situation as encouraging and in line with the expectations. The success of the Swach can be measured from the fact that the Haldia plant’s capacity of 1 million units has been ramped up to 1.8 million units, as per TCL (2011).
Nancy E. spears and Richard Germain (1995), as studied earlier, state that there is a positive correlation between the DOI theory as given by Rogers (2003) and the concept of PLC. The sales figure, as per TCL (2011), suggests that Swach is in the Growth stage of its PLC. The market size, as estimated by TCL (2011) is 894 million household and it has to achieve a sales volume of 200 million by 2015, which is around 22.37 %. Since, this figure of 22.37% is to be achieved by 2015; the depiction on PLC has been done at the Growth Stage. Having said that, Rogers (2003) has first 16% as Innovators and Early Adopters and in the year 2012, Swach has been marginally below 16% and hence the depiction on the DOI theory curve is approaching the beginning of Early Majority curve.