Abstract
One way to assess the IS and establish a foundation for improvement decisions is to evaluate its maturity using a maturity model (MM) tailored to the organization's type and the goals of these activities. The outcome is the determination of the assessed organization's maturity level, enabling the initiation of improvement activities and comparisons with similar organizations. Many such initiatives have been inspired by well-established maturity models, such as the capability maturity model (CMM). An organization with a higher level of maturity is considered more reliable and customer-friendly. This chapter delves into the issues of IS maturity, providing definitions of maturity, maturity models (with examples), models for implementing MM (change management), highlighting the distinctions and similarities between maturity, diffusion (acceptance), and innovation of information systems, as well as the relationships between methods for assessing IS maturity and the information/data literacy of its users.
TopIntroduction
The creators and employees of libraries and other information systems (IS) have increasingly focused on assessing the success of their activities, particularly the services provided to clients/users. The need for special attention to monitoring IS work results from at least two factors. Firstly, rapid technological changes result in much easier and universal access to information through global networks. However, these changes also entail significant expenses for hardware, software, and employee training. Secondly, we observe changes in the information needs and behavior of users, which arise from their access to an increasingly competitive information market. In this market, traditional organizations such as libraries have to compete for users' attention with numerous commercial enterprises, including Internet search engines, as the most obvious example. The process of building a collection of digital resources, as well as organizing and sharing them, also presents challenges.
Many libraries have adopted tools such as balanced scorecards, value scorecards, performance indicator frameworks, benchmarking, and typologies to demonstrate their value and impact (Dash & Padhi, 2010). Libraries also cooperate in this area (Chadwell, 2011). The success of information activities can be understood through the six dimensions proposed by Petter, DeLone, and McLean (2008), which have been widely used by IS researchers to comprehend and measure these dimensions in functioning IS. Furthermore, each of the variables describing the success of the IS aligns with one or more of the six main dimensions of the model created by the cited authors (Petter, DeLone & McLean, 2008, p. 238). The following dimensions of success have been distinguished:
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System quality: desirable characteristics of the information system. They can be: ease of use, system flexibility, reliability, ease of learning, as well as features of intuitiveness, sophistication, flexibility and responsiveness;
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Information quality: desirable features of system outputs, e.g. reports, data displayed. Indicators such as relevance, understandability, timeliness, and usability can be distinguished;
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Service quality: the quality of the support that users can receive from the IS and its staff. E.g. responsiveness, accuracy, reliability, technical competence, as well as employee empathy. In this area, tools such as SERVQUAL, created in the area of marketing, and LibQUAL, adapted to the measurement of library services, are used. This tool is used to assess IS user satisfaction by measuring the differences (gaps) between three levels of maturity: minimal, actual and optimal (desired) of information services (Kamath et al., 2022);
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System use: the degree and manner in which employees and users/customers use IS capabilities. The measures here may be: level of use, frequency of use, manner of use, suitability of use, extent of use, purpose of use;
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User satisfaction: the level of user satisfaction with IS services, determining its acceptability;
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Net benefits: the degree of IS participation in the success of individuals, groups, organizations, industries and nations. E.g.: improving decision-making, improving productivity, increasing library loans, reducing costs, increasing income, market efficiency, customer/user satisfaction, economic development.
Key Terms in this Chapter
Benchmarking: The process of measuring products, services, and processes against those of organizations known to be leaders in one or more aspects of their operations.
Maturity: A state where the knowledge about and services in a specific area has reached a fully or complete level of development.
IT Acceptance: The perception of an IS after use, leading to a positive decision to use an innovation.
Information Literacy: A set of integrated abilities encompassing the reflective discovery of information, the understanding of how information is produced and valued, and the use of information in creating new knowledge and participating ethically in communities of learning to achieve personal, social, occupational, and educational goals.
Information System: An integrated set of components for collecting, storing, and processing data and for providing information that contributes to knowledge and information products, whether analog or digital, that facilitate decision making.
Innovation Diffusion: The way (pattern, speed etc.) new technologies and other advancements (ideas, goods, products, services, or behaviors) spread throughout societies and cultures, from their introduction to widespread adoption.
Maturity Model: A framework (simplified representation) for measuring an organization’s mature state: its ability to continuously improve in a specific discipline and its success in evolving from a particular criterion.
Research Data Management (RDM): A set of practices covering the entire lifecycle of data, including planning, storage, access, and preservation of data produced from a given investigation.
SWOT Analysis: A framework used to evaluate an organization’s competitive position and to develop strategic planning, facilitating a realistic, fact-based, data-driven examination of the strengths, weaknesses, opportunities, and threads of an organization, its initiatives, or within its industry, leading to fact-based analysis, fresh perspectives, and new ideas.
Research Data Service (RDS): Services aiming at providing information on how to organize, describe, preserve, and share research data (elements of RDM), intended to support researchers in working with data.