A framework to acquire explicit knowledge stored on different versions of software
Introduction
Systems related to information have an accelerated growth as knowledge goes hand in hand with the technological development that is constantly evolving [1]. When a product hits the market, there is already another in line that will replace it, always responding to the rapid changes and the pressure of global competition [2]. This pressure works as a catalyst in advancing technological developments in fast and unimaginable ways [3]. Within organizations, it is common to adopt new technological elements that entail several challenges. One is the risk of loss of explicit knowledge within key systems of organizations, due to incompatibility between the key enterprise software and the hardware where it is contained. This happens because the software that the company has does not have the necessary support for its implementation or they simply cannot be operated under different environments to which they were originally programmed.
In SME's [4], implementation of new technology is considered a cost rather than a benefit, great care has to be taken when the strategic technological tools of the organization have their operation changed. Instead of buying new systems, the company chooses to maintain compatibility between the existent systems [5]. That is, to continue with the same software and hardware as long as possible, mainly because of the cost that the acquisition of a brand new system represents.
SME's have certain characteristics that could be considered as justifications as to why they choose to continue with the same hardware and software for several years, such as:
- •
The software development is based on lightweight processes aimed to be used by staff.
- •
They usually have dynamic and flexible structures with a non-traditional and, sometimes free flow administration.
- •
Typically their management processes are carried out through informal mechanisms based on face-to-face relationships.
- •
They do not have sufficient staff to perform specialized functions.
- •
They have little or no budget for buying expertise.
- •
They are financially vulnerable companies with limited financial resources [6].
In today's technological era, organizations should have updated systems to meet the needs of business changes [7], that is, there will come a point in which they should upgrade their systems. It will be then when the following questions will arise: what is going to happen with older systems? And what about the information stored in previous hardware?
Organizations should make decisions that affect their future work, such as:
- •
Continue with no hardware changes to access old systems.
- •
Perform hardware changes and adaptations for the use of old systems.
- •
Change hardware for new systems and keep old equipment for consultations.
- •
Change hardware and data migration to new software.
In either case, the cost involved about having stored data and information should be taken into account, especially when these have been given a real value and are a liability for the company if they are lost or misplaced.
Section snippets
Background
Knowledge can be seen as a collection of objects, rules and best practices [8]. It is the state of awareness, understanding and amassed thoughts gained through experience and education. It is present in the form of ideas, judgments, intuitions, competencies and skills of the individual [9]. It has become a key factor [10] in the current environment of change, complexity, uncertainty and rapid economic growth, and with the rapid advances in technology and increased competitiveness [9]. Its
Previous or related studies
KM provides methods and techniques that help organizations process and reuse their knowledge. Technology initiatives may not be the main objectives of KM but they are important enablers [31], that is the reason why a review of previous studies can be helpful. As a result studies that could be applied to re-acquire explicit knowledge as well as some methodologies where found, however, most of them focus on tacit knowledge; the distinction between these two types of knowledge has been widely
Proposed framework
This research focuses on the acquisition of explicit knowledge corresponding to Fig. 1 Section C, this knowledge can be found in different forms such as spreadsheets, text documents, unstructured repositories [21], [32] as the knowledge is already encode the misconception that its already available arises [33] however there are some things to take into consideration like, unstructured files, isolated networks, turnover [23] or withdrawal of personnel [8] this situation leads to explicit
Framework application
The proposed framework was applied on a SME company of pharmaceutical type its main activity is the marketing of homeopathic medicine; the problem that arises in the company is that they have a lot of explicit knowledge, some of it, contained in a system that is already in the process of obsolescence, however the migration of all information to a new system would take a long time, so the proposal was to take initial data and start from there with the use of a new software; that may be a good
Discussion
It was possible to apply the framework. During the execution of each of the steps, limitations such as time to perform the targeted interviews or staff turnover where faced, both as a result of changes in the company where the study took place causing an increase of workload.
In what concerns the first point, related to identification, the limitations are mainly external; one of them was a disposition problem to support the studies by a little number of the selected staff, one particular case
Conclusions
In the SME where the framework was tested, good results were obtained, especially in the area of commercialization. After the implementation, users that have access to the system can access knowledge almost immediately, avoiding the need to contact a third party to get the knowledge that they require.
Deliverables in each stage would lead to greater benefits. In this study, data retrieved by intermediate systems was used for the development of a more functional system that could load text files
References (40)
- et al.
A fuzzy AHP-TOPSIS framework for ranking the solutions of knowledge management adoption in supply chain to overcome its barriers
Expert Syst. Appl.
(2014) New media and the changing face of information technology use: the importance of task pursuit, social influence, and experience
Comput. Hum. Behav.
(2014)- et al.
The journal of systems and software using scrum to guide the execution of software process improvement in small organizations
J. Syst. Softw.
(2010) - et al.
Adaptive agent model: software adaptivity using an agent-oriented model-driven architecture
Inf. Softw. Technol.
(2009) - et al.
Social network, social trust and shared goals in organizational knowledge sharing
Inf. Technol. Manag.
(2008) - et al.
Role of explicit and tacit knowledge in six sigma projects: an empirical examination of differential project success
J. Oper. Manag.
(2010) - et al.
Tacit knowledge contained in construction enterprise documents
Procedia Eng.
(2014) - et al.
Organisational knowledge creation strategies: a conceptual framework
Int. J. Inf. Manag.
(2010) - et al.
Suitability assessment framework of agent-based software architectures
Inf. Softw. Technol.
(2013) - et al.
Knowledge sharing: a review and directions for future research
Hum. Resour. Manag. Rev.
(2010)
A semantic framework to support corporate memory management in building construction
Autom. Constr.
Software evolution – background, theory, practice
Inf. Process. Lett.
Software as a service value and firm performance – a literature review synthesis in small and medium enterprises
Procedia Technol.
Has open source software been institutionalized in organizations or not?
Inf. Softw. Technol.
A framework to analyze information systems as knowledge flow facilitators
Inf. Softw. Technol.
A conceptual framework for managing tacit knowledge through ICT perspective
Procedia Technol.
Modeling of tacit knowledge in industry: simulations on the variables of industrial processes
Expert Syst. Appl.
Applying tacit knowledge management techniques for performance assessment
Comput. Educ.
Acquiring and sharing tacit knowledge in software development teams: an empirical study
Inf. Softw. Technol.
A conceptual framework to study the role of communication through social software for coordination in globally-distributed software teams
Inf. Softw. Technol.
Cited by (11)
A methodology for selecting optimal knowledge acquisition through analytic hierarchy process and environment parameters impact
2023, Journal of Applied Research and TechnologyDecision-making desktop software and mobile app for wastewater treatment: selection of experimental parameters to estimate hydrogen peroxide production
2022, Environment Systems and DecisionsRecurrence quantification analysis of Q&A behavior from the perspective of explicit and tacit knowledge – an empirical study based on Zhihu's hashtags
2022, Aslib Journal of Information ManagementWhat determines firm’s innovation? The case of catching-up cee countries
2021, Quality Innovation ProsperityThe role of product innovation and customer centricity in transforming tacit and explicit knowledge into profitability
2020, Journal of Knowledge Management