Why Technologists Resist Negative Change: The Resistance to Innovation and Consuming Products against their Better Judgment

This paper is a critical and non-empirical review of innovation resistance and anti-consumption: the concepts, concerns, conflicts, and convergence. Both resistances to innovation and anti-consumptions converge to one another which influence the opinions (i.e., market mavens) of the market segment or non-adopters (voluntary simplifiers). Voluntary simplifiers or non-adopters represent over fifty percent (50%) of the market segment. This paper focuses on the embedded (hidden) assumptions of the resistance to innovation and anti-consumption and describes how the two concepts are different. When both converge, the exact reasons in favor of action will occur. The paper concludes that the technologist can adapt to negative change if they better understand why non-adopters resist innovation and consume products against their better judgment. DOI: 10.4018/jissc.2012100106 International Journal of Information Systems and Social Change, 3(4), 84-96, October-December 2012 85 Copyright © 2012, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited. of an innovation has an individual perspective of the newness of a change agenda while the upper management has their perspectives, individually and collectively, of the reasons for the change. Positive change or negative change is always done for a reason. The reasons for the action (that is, for the change agenda) have two sides, akin to two sides of a coin. The coin has the “exciting” reasons and the “justifying” reasons (Hutcheson, 1897, p. 404), The former presupposes instincts and affections and the latter, a moral sense. The former composes of the reason for action (Dancy, 2000) and the latter, the reason in favor of action (Frankena, 1973). The former represents the true reason for the act is done and the latter consists of the good reason for the action. The former is about the instinctive motive (Dancy, 2000; Hutcheson, 1897) and the latter is about moral reason (Frankena, 1973) or “sensible or right or whatever” (Dancy, 2000, p. 2). Hutcheson (1897) warns, any attempt to tear the two sides of the intentional action apart will render the intentional action intelligible. Both must be kept together. Both must be shewn by truths. Both sides require explanation. Both reasons belong to normative reasons. Historically, human interactions, Tarde (1903, p. 140) asked why, “given one hundred different innovations conceived at the same time—innovations in the form of words, mythological ideas, industrial processes, etc—ten will spread abroad (emphasis added) while ninety will be forgotten.” The positive bias (the pro innovation bias as opposed to innovation resistance), embedded in the Diffusion of Innovations (DOI) theory (Rogers, 2003) as early as the beginning of the twentieth century, assumes that the new idea, product, or service, is favorable and would be “intentionally, deliberately, [and] purposely” adopted with reasons (Dancy, 2000, p. 1). Tarde’s theory has this storyline: (a) A stranger (the innovator) introduces an “invention” (the innovation) to early adopters; (b) people follow the early adopters; (c) the innovator and the early adopters become critical to the success of the adoption; (d) the “selling” (diffusion) of the innovation includes elements of space and time; and (e) if it finds momentum, the rate of adoption follows an S-shaped curve (Kinnunen, 1996). The main actors in Tarde’s diffusion theory are (a) the innovators and (b) the early adopters are sources of reasons for and in favor of the change (the innovation). Ryan and Gross (1943) identified two other adopter categories who take part and form the positively biased S-shaped curve (Bass, 1969; Mahajan & Peterson, 1985): (c) the early majorities and (d) the late majorities. They had a fifth category called (e) the laggards. In the concept of S-shaped curve in the DOI theory, the innovator accounts for two and a half (2.5%) percent. The early adopters represent about thirteen and a half (13.5%) percent. These first two categories (totaling sixteen (16%) percent of the population) are market maven (Clark & Goldsmith, 2005), a slang use for opinion leadership (see Appendices A and B). The subsequent thirty four (34%) percent belonging to the early majority, another thirty four (34%) percent under the late majority, and a last sixteen (16%) percent under laggards bring about a normal distribution. The weakness of the S-shaped curve is the percentage (the statistics) in the normal distribution, which could be misinterpreted (Wheeler, 1976). The terms early majorities and late majorities of Ryan and Gross (1943) misled people that these two groups, amounting to sixty-eight (68%) percent, are potential adopters with positive biases in favor of the innovation. But, based on the research of Brown and Venkatesh (2003), only the first group, the sixteen (16%) percent of the population, has positive bias (that is, to have favorable attitudes) towards the change and innovation. The second group, the remaining eighty four (84%) percent, is negatively biased. Brown and Venkatesh (2003) further argue that about forty (40%) percent of the second group (that is, about thirty four (34%) percent of the population) could be convinced to diminish their negative bias against the innovation. Any decrease of (negative) bias against the change likely increases the (positive) bias in favor of the innovation. Ryan and Gross (1943) referred 11 more pages are available in the full version of this document, which may be purchased using the "Add to Cart" button on the product's webpage: www.igi-global.com/article/technologists-resist-negativechange/72335?camid=4v1 This title is available in InfoSci-Journals, InfoSci-Journal Disciplines Communications and Social Science. Recommend this product to your librarian: www.igi-global.com/e-resources/libraryrecommendation/?id=2