Влияние инновационных атрибутов на намерение их принятия сотрудниками университетов на примере EdTech решений

Acceleration of technologies development, along with changing consumers’ behavior and needs, is altering the system of education, which was designed for the needs of industrial society decades ago [Wisbauer, 2017]. Traditional Higher Education institutions are failing to keep up with the times, and as a result they suffer budget deficits and lose the fight for students’ time and money. However, traditional Universities possess various irreplaceable attributes and perks for students, they have to evolve in order to keep the place in the sun. And technologies embracing might be one of the ways, which can level up the service Universities provide and meet the expectations that current students and society have [Navas, 2020].
Fundamental reforms are linked to high risks and uncertainty, and many old-fashioned institutions are too risk averse to start and conduct them. Fortunately, procedural changes may be launched with the help of third parties and services they provide. Therefore, all necessary for Universities’ transformation technologies are out there already, and they are developed by private companies, which provide services to anyone who pays. Consequently, there is no need to run sophisticated software and hardware development programs in-house and allocate formidable portions of budget to them [Williamson, 2021]. Instead, Higher Education Institutions can address the EdTech market and choose solutions, which are designed for their needs. The EdTech market has a lot to offer, and it is estimated to reach 100 billion USD by the end of this year [Grand View Research, 2021].
However, thousands of advanced technological solutions, which aim to solve Universities’ issues, remain unnoticed by the latter ones due to the EdTech companies’ failure to communicate with the target audience adequately and properly. For instant, EdTech startups do not understand what particular attributes are the most crucial for their target audience, when it decides whether to give a product or service a try or not [Lynch, 2017]. By virtue of this situation, Universities do not utilize technological solutions, which have been designed by private out-of-house companies in their interest.
Technology implementation is inseparable from its adoption lifecycle and crossing the chasm in particular. A large gap between early adopters and early majority is what every technological company has to overcome to reach the phase of hyper-growth and success at the market [Schmutzler, Presse, 2021]. It is not a simple endeavor as early adopters’ needs differ a lot from the early majority’s ones. The latter is also more risk-averse, and it demands a proof of how
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the product can help them and a number of success stories par excellence. Unfortunately, existing studies do not cover this topic regarding the University staff’s traits and preferences in technological solutions, though there is a plenty of papers on students as B2C users of EdTech solutions and Universities as B2B clients and partners. Therefore, EdTech startups lack information on what Universities’ employees look at, when they decide to try a product, which may improve job duties execution, or not [Shulman, 2017]. And this thesis is to help them out and pave the way to customers in Universities.
In order to estimate and calculate innovation adoption, which result in University staff’s willingness to use new services and products, influencing parameters or EdTech solutions’ attributes should be identified and measured. Today, many theories dedicated to this topic are designed, which can be grouped in two divisions: the former ones focus on product intrinsic innovative features, while the latter ones are built around environmental conditions, which influence the perception and readiness to utilize innovations [Wisdom, Chor, Hoagwood, Horwitz, 2014]. For the sake of this research, the former approach to calculate innovation adoption is chosen, as it aims at identifying the impact of every innovation feature separately, over which an EdTech startup has a direct control. Therefore, the Everett Rogers’ Innovation-Decision theory altered by Kapoor and other scientists was selected to be a cornerstone of the theoretical framework of the thesis [Rogers, 2003; Kapoor et al, 2014]. It allowed to define the relationship between innovation attributes and their impact on adoption intention by an end-user.
Hence, the research goal of the paper was set to identify relationships between EdTech solutions’ innovation attributes and adoption intention of Universities’ staff. In order to do it, parameters of such relationships had to be identified, and it was done through analysis and merge of theoretical frameworks. However, the Rogers’ Diffusion of Innovations theory was originally developed in 1962 and revised later in 2003, it faces both criticism and alterations from today’s scientists due to its simplification and attributes grouping. Moreover, it may deliver unexpected and biased outcomes, when applied in places with different cultures and levels of development [Chiyangwa & Alexander, 2016; Yang et al, 2016; Hsu et al, 2007]. Therefore, this study covers the gap of University staff’s adoption intention and their evaluation of EdTech solutions’ innovation attributes.
The following two research questions were set to help in reaching the thesis’ goal:
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Q1. Are there relationships between EdTech solutions’ innovation attributes and adoption intention of Universities’ staff?
Q2. What EdTech solutions’ innovation attributes affect Universities’ staff adoption intention?
The research was designed the way, which contribute to both theoretical and managerial fields. First, the evolutionary trajectory of Universities was studied. Within this part of the first chapter, issues and challenges that Higher Education institutions face were identified with the help of the Porter’s Five Forces analysis. Then, the insights on how Information Technology solutions were introduced in Universities were presented and the EdTech startups’ contribution was identified. Second part of the first chapter was dedicated to the Innovation Adoption theories and frameworks, which allow to distinguish particular attributes of innovative solutions and measure them. By the end of the chapter, six hypotheses regarding the relationship between a particular attribute of an EdTech solution and University staff’s adoption intention were formulated. The purpose of the second chapter was to justify research design and methodology for further usage. Thus, a questionnaire with nineteen questions was developed, which covered six hypotheses and respondents’ personal willingness to use innovative solutions. The survey was built on the SoGoSurvey platform with the list of protective tools in order to prevent the sample from manipulated inputs. Next, third chapter is for quantitative analysis, which was conducted in the IBM SPSS Statistics environment. When the reliability test was done, the multiple regression model was built. Finally, conclusions and implications of the studies were discussed in the last chapter.
The thesis is designed to contribute new insights and knowledge to both theoretical and managerial fields of science. For the former one, the research is aimed at checking the applicability of the Rogers’ theory for the EdTech market and its altering, if found necessary. For the latter one, the study is set to deliver recommendations for EdTech startups on which attributes of their innovative solutions to stress on during pitches and advertising campaigns, so the product’s value is delivered and understood by the target audience, and tips on closing the Chasm gap in the field of EdTech University-focused market in general.