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This research proposes to explain and quantify how individuals perceive the meaning of the word innovation. This research builds upon Zhuang, Williamson, & Carter’s (1999) work as well as a study conducted by Caraballo and McLaughlin in 2012 which defined three unique constructs that describe innovation as either new, improved, or changed. The sample group for the 2012 study included a relatively large and homogenous cultural group (Hispanic IT Professionals pursuing further educational advancement). In that study, there was a definitive difference between generational cohorts (Millenials, Gen X, and Baby Boomers) in how each perceived innovation. This updated study selects a group of culturally diverse MBA students to determine if the differences remain between three generational cohorts.
Innovation is traditionally defined as the process to create a new or novel (distinct) product or service. This general definition is insufficient to describe how people perceive innovation generationally. This study intends to validate that generational differences affect how subjects perceive and define innovation. This paper confirms earlier findings (Caraballo & McLaughlin, 2012) that redefine innovation, as a multi-dimensional construct, in agreement with the Zhuang et al. (1999) research.
The 2019 research validates that Millenials perceive innovation from a new perspective. That is, it must be new to be innovative. Other generations have a broader and more accepting view of what is innovative. The 2019 research demonstrated differences in how innovation is perceived (defined) between those with and without a technical background. The findings further reiterate the need for continued research to market and sell directly to various consumers who perceive innovation differently.
Keywords: Innovation, Generations, Definition, Perception
Innovation is driven initially by need, wants, or desires. Businesses use innovation because it adds value and sustains competitive advantage (Baregheh, Rowley, and Sambrook, 2009, p.1323) and expands the opportunities for growth. A need exists for many organizations to continuously innovate (McLaughlin, McLaughlin & Preziosi, 2004) given their dependence on wealth creation (De Waal, Maritz, & Shieh, 2010). It is essential to involve employees in innovation projects, as they bring both their creativity and inventiveness. The competitive edge that businesses pursue should encompass clear innovative strategies that reflect the cultural values of the organization (Subbotina, 2015). For instance, multinational companies such as Apple, Starbucks, Honda, Toyota, and Procter and Gamble derived profit and growth by integrating innovation into the company’s corporate culture and organizational and operational strategies. Innovation is not confined to just developed nations but is also integral to the progress of emerging economies (Prahalad, 2012). No one country has a “hold” or “lead” in innovation.
Innovation is a concept that derives from ideas/concepts to become products, processes, and services that meet a need. Innovative companies can quickly mitigate market risks, develop sustainable strategies that equip the organization to achieve long term growth, and align the company with the organizational culture (Kumar, 2014). Although often associated only with new technology, innovation begins with a need, want, or desire. The need drives the innovation, which is often individually perceived from a generational perspective.
A Definition of Innovation
Given its critical function and contribution, the concept of innovation should be readily identified and communicated throughout the organization. Flight, Allaway, Kim, and D’Souza (2011) suggest that organizations, marketers, and researchers need the ability to define how individuals perceive innovation generationally based on knowledge and experience. Baregheh et al. (2009) identified numerous and different definitions of innovation based on disciplines such as management, finance/economics, technology (IT, scientific or engineering), and marketing.
Historically, Thompson defined “innovation as the generation, acceptance, and implementation of new ideas, processes, products, and services.” (1965, p. 2). An updated definition by Wang, Guidice, Tansky, & Wang states that “innovation begins with a novel idea and concludes with a market introduction” (2010, p. 767). Therefore, one could say that innovation begins with a new idea and ends with a marketable product or service. According to the Conference Board of Canada, innovation disrupts the status quo by radical change and incremental improvement of products/services and processes (2019). Instead, innovation is more than radical change; it involves new technology, new ways of processing, and a new model of management. According to Baregheh et al. (2009), the method and choice of words to define innovation today contain fundamental concepts that overlap and may be contradictory. The result of these many confusing definitions of innovation is that no standard or authoritative definition of innovation exists (Baregheh et al., 2009, p. 1324). Therefore, to better understand how an individual perceives innovation, a definition must include:
1. How the idea originated;
2. Involve a transformation of some kind; and
3. Meet a need which satisfies.
In general, innovation begins when people use a creative or rational process to meet a particular need; therefore, innovation begins with human ideas and creative possibilities.
In order to clarify how an individual perceives innovation, the authors decided to go beyond the definition and examine the “means of innovation” (Baregheh et al., 2009, p. 1334). The means of innovation explains how the individual perceives the function, essential qualities, or outcome of the innovation. Innovation is now characterized as the process of transforming ideas into “new, improved or changed entities” (Baregheh et al., 2009, p. 1334). Individuals can now perceive how a specific innovation will uniquely add value.
Mangelsdorf (2011) posited that individual demands influence companies to switch, integrate, or form other business relationships that create new products or services. Individuals drive innovation through purchases that meet their need. Finally, a group of innovation experts defines innovation (Figure 1).
Figure 1: Keywords to describe Innovation
The main terms are ideas and value, yet ideas are conceptual and have no physical form. There are more detailed definitions, ones that take into account the user and their perceptions.
A better and more distinctive way of understanding innovation derives from the work of Zhuang (1995) and Zhuang, et al., (1999), whose definition simplifies innovation to be:
- “An invention, i.e., the creation of something entirely new;
- An improvement, i.e., a refinement of what presently exists;
- The diffusion or adoption of innovation developed elsewhere” (i.e., change) (Caraballo and McLaughlin, 2012, p. 554),
Innovation is more method than a single or unique act (Baregheh et al., 2009, p. 1334) involving people, process, and technology. Therefore, an understanding of innovation should be specific as to the need and intent of the desired outcome. Individuals perceive innovation as a multi-dimensional set of characteristics, unique to the product or service. A “one size fits all” approach is insufficient. According to Zhuang (1995), the definition of innovation is outcome dependent. That is, one must consider the need and the desired outcome to generate its definition. The desired outcome, according to Matwiejczuk (2013), is a response factor based on the demands of individuals. Individuals are, therefore, at the epicenter driving the innovation process. Therefore, one must understand the individuals perspective to identify a more unified definition or meaning.
An individual’s ability to innovate is based on their knowledge, skills, and attitude (Caraballo & Mclaughlin, 2012, p. 554). These characteristics to initialize the innovation process. Zhuang (1995) created ten survey statements that measure how individuals perceive innovation. Respondents used a 5-point Likert scale of agreement or disagreement to evaluate each statement. Zhuang’s 1995 study did not show any significant mean differences but did encounter a diversity of responses. Given these results, Zhuang did not pursue any further or more sophisticated analysis.
However, the Caraballo and McLaughlin 2012 study modified Zhuang’s survey slightly (with his permission) and examined a Factor Analysis to determine survey question alignment. Although there were times when the definition was less clear, there was a distinctive “new” “improve,” and “change/replacement” element in all generational groups tested.
Previous research with like cultural groups (US Hispanics IT Professionals, South American IT Professional, Nurse Professionals, Chinese businesspeople) also demonstrate generational differences (Caraballo & McLaughlin, 2014; McLaughlin & Richins, 2015; McLaughlin & Kennedy, 2016). In all groups tested, there was a difference between the three generations, and the results were more similar than different between cultural groups. With this new study, where culture is not a limiting factor, the authors will attempt to answer the following research questions:
1. Does an individual perception of innovation continue to vary between generations?
2. For each generational cohort, is there a difference between individual perceptions of innovation for gender or those employed in a technical role?
McAdam and McClelland (2002) extended the initial research using Zhuang (1995) by using his definition of individual innovation. McAdam and McClelland focused their research on creativity generation at the individual and team levels. They found that three critical elements necessary for innovation: expertise, creative thinking, and task motivation (Caraballo and McLaughlin, 2012). Research on the “source of ideas” (McAdam and McClelland, 2002, p. 95) remains limited. However, when considering the individual as the source of innovation, McAdma and McClelland’s research becomes valuable.
The 2019 results are both replication and expansion of previous (Caraballo & McLaughlin, 2012) research. The authors continue to examine the perceptions of innovation, but this time, the majority of respondents are non-technical MBA students. Two reasons for choosing this group: 1) to examine if a less homogeneous group provides similar answers; 2) to examine if perceptions have changed over the last 5-6 years.
We will begin by exploring a possible understanding of innovation generated from an individual’s perception, given their status as an MBA student, any generational cohort differences or similarities, and whether a technical versus non-technical background similarly perceive innovation for each generational group.
Selection of Sample
The goal of this research was to recruit a heterogeneous group to determine if the perceptions of innovation remain relevant in 2019. MBA students are a favorite sampling group for business research. The sample consists of MBA students enrolled in several different universities. Students were sent an e-mail to encourage them to participate. Participation was voluntary, and the sample considered random. The goal is to determine if there are changes in the perceptions of innovation and the generational difference observed previously. One hundred fifty-one respondents participated in the survey, and one hundred forty-five were useable for analysis.
Innovation Perception Survey Instrument
A slight modification of the Zhuang survey resulted in less need for clarification. There are several independent variables in the 2012 study (generation, technical profession status, gender, location). Generation, gender, and professional status yielded significant differences.
Although Zhuang et al., (1999) research did document both validity and reliability for the instrument, the authors re-ran a Factor Analysis for validity and a Cronbach alpha for reliability. Factor analysis has three critical assumptions: normality of the data, linearity, and conceptual linkages (Hair, Anderson, Tatham, & Black, 1995). The most important assumption is that a conceptual linkage exists which the statistical analysis confirms. 66% of the total variation explained (versus 57% previously) is an improvement from the 2012 Caraballo and McLaughlin study. Cronbach alpha of .75 (versus .675 previously) is an improvement. The survey is useful in capturing perceptions and differentiating these perceptions into the three categories which take on aspects of new, improve, and change.
Analysis – Innovation Assessment Survey
Statistical software consisted of both SPSS 25 and Minitab 18. A significance level of 0.05 determines significant differences. Scores are summed for statistical analysis and identified as the dependent variable. Table 4 lists the ten Innovation Perception Survey statements.
Survey responses use a five-point Likert Agreement scale from Strongly Disagree to Strongly Agree. Table 1 identifies the four independent variables, along with sample sizes and numerical indicators.
Table 1 – Independent Variables
|Generation||Millennials, Generation X, Baby Boomers||85, 38, 22||1||3|
|Technical||Yes, No||20, 124||1||2|
|Gender||Female, Male||80, 64||1||2|
|Education||HS, Some College, Bach, Masters, PhD||5, 29,59,37,21||1||5|
Figure 2 displays a box plot of the summed scores classified by gender, generations, education and those with or without a technical background and how they perceive innovation from a composite standpoint – the higher the score, the more positive the perception. Interestingly, those with a technical background have a lower overall perception of innovation (except Gen X). These results indicate that these individuals deal with innovative products and services on a more frequent basis. Previous research confirms that Millennials behaved similarly in the 2012 research (although Millennials were a much smaller sample in the 2012 Caraballo and McLaughlin research).
For these sums of each of the ten Innovation Perceptions statements, there are no noticeable statistical differences between age, gender, and technical position (Figure 2). The sum of scores test to be normally distributed (Figure 3). There are no apparent significant statistical differences overall (Figure 2). However, the ten statements do factor into three (or occasionally four) distinctive groups or dimensions (sometimes called concepts) (Table 4). Each concept measures a different aspect or meaning of innovation.
Figure 2 – Box-Plots of Generation (in Age), Education (5 levels), technical position (Yes/No) and Gender (F/M)
Figure 3 – Normality Test
Factor Analysis of the Innovation Perceptions Instrument
The initial Factor Analysis (Figure 4) indicated the presence of four distinctive factors or subscales without sorting by dimension, gender, or technical profession. However, further analysis indicated a difference between generational cohorts (Table 5) and professional classification. The analysis describes how the respondents best perceive (understand) innovation as a multi-dimensional construct.
As with the 2012 survey instrument, there are generally three (some with four) observed dimensions, factors, or subscales. The dimension or factor identifies a particular characteristic of innovation (such as new, improved, or changed). The 2019 sample of MBA students will provide for a more homogeneous group but with more non-technical personnel than the 2012 study. Only the analysis will provide an answer as to whether there is commonality or differences between the 2012 and 2019 study.
The results of this research will help in identifying a better, more intricate definition of innovation. With this new sample, there is a more sophisticated understanding of innovation. To better understand these the intricacies of innovation, additional factor analysis will provide the mechanism for examining these sub-scales.
The Instrument was shown to be valid (Table 3) and reliable (Table 2) in tracking perceptions and generally aligning these to the dimensions of New, Improve, and Change (2012). However, more subtle differences and nuances exist with the 2019 data.
Table 2 – Reliability Coefficients
Understanding how a selected group of individuals (MBA students) perceive innovation and how these perceptions relate to generations, gender, and technical position is the main focus of this research. Factor Analysis (using Principal Components Analysis) is a reduction technique which aligns statements with similar responses to form a new variable (or dimension/subscale) which is both descriptive and can act as a wholly new dependent variable.
Figure 4 – Factor Analysis
For the overall analysis, there are four distinguishable factors or dimensions (sub-scales) – Figure 4. The variation explained (Cumulative Variation) by the dependent variables equals 67%, which is acceptable. Table 4 describes the factor loadings (which statements align to each factor). A numerical value in the Component column (Table 3) indicates the strength of the relationship. Large values indicate proper alignment with a rule of thumb suggesting that a value of .5 or higher (or -.5 or lower) indicates statement alignment forming a new dependent variable.
A Factor Analysis examined the independent variable contributions (Table 4). The Variance Explained for each
iteration is all acceptable. The Significance column identifies if Education is a contributing variable (see Figure 6).
Only for Millennials is education important or a contributor (those with the most education being the most precise
with their definition of innovation).
Table 3: Factor Loadings (Rotated)
The Factor Analysis indicates a different pattern of alignment between the technical and non-technical respondents and the three generational cohorts. Male and Female differences are minimal but do indicate a unique set of perceptions regarding innovation. The 2019 findings confirm and expand the 2012 findings. The differences in alignment further reinforce the concept that different generations with and without a technical background view innovation differently. These results continue to confirm the Zhuang (1995;1999) conclusion that innovation is perceived uniquely by individuals.
Table 4 – Factor Analysis of Survey Results
Figure 6: MANOVA Analysis – Millennials
MANOVA Tests for Education
s = 4 m = -0.5 n = 20.0
It is used to test whether the independent variables contribute to the results. Only Education tests for differences.
The diversity of response indicates that innovation is not a simple concept in the respondent’s mind, nor will it be with their purchase behaviors. Table 5 contains a summary of the results.
Technical personnel, as expected, are innovation aware (and have higher scores). The result of this study confirms the need to market (sell) innovation to each generation differently. One size does not fit all! The sample of individuals understands innovation as a multi-dimensional concept. The 2019 data identified three or four distinctive factors of innovation. Disconnects between how a concept is understood and how applied (or defined) continues to cause problems to arise. What one person determines to be new another may understand to be an improvement. The younger the respondent, the more they are attracted to unique and inventive innovations.
Innovation begins at the human level and is critical for success. If everyone in an organization perceives innovation differently, no alignment of perceptions will occur, and innovation efforts will be less successful.
Table 5: Results and Interpretation
The fact that the sample group was diverse may be the reason for some divergence between the original study and this iteration. Most respondents (non-technical personnel) were not expected to have a refined vision of understanding of innovation. Both groups shared much in common. The results are not transferable to all individuals, within a generational cohort, but would be familiar to those who experience, describe, and use innovation on a more frequent basis.
Conclusions and Recommendations
The authors continue to recommend further research on understanding innovation from a more complex perspective. Now it is time to examine how the alignment varies (and agrees at times) between the generational cohorts and technical proficiency. By further refining the definition of innovation for each group, the result would be of interest to marketers, researchers, developers, and designers. It would facilitate a more focused approach and a change from the present process that calls everything innovative. Also, it moves innovation from a disruptive influence to a preferred and supported strategic element that executives can use to become more competitive. Use disruptive innovation only when faced with maximum competitive pressure or survival issues.
The definition of innovation is not only critical to understand how individuals perceive this concept, but how generations recognize its meaning. Although new, or creative products and services offer a great opportunity, improvements are just as innovative (consider the Dyson vacuum and how it changed the home cleaning industry). Change or replacement innovation may also spark new products, new services.
Finally, by understanding innovation, management can effectively communicate strategies and policies to the organization. The tragedy would be to develop a standard (and accepted) definition of innovation and then fail to transfer that information to the organization. Without this understanding; developing a culture of innovation would be next to impossible. Innovation is not just an engineering or research function; it is the responsibility of the organization to meet or exceed customers needs and requirements.
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